Evidence Report/Technology Assessment 

Number 193 

Preventing Alzheimer’s Disease and Cognitive Decline 

Prepared for: 

Agency for Healthcare Research and Quality 

U.S. Department of Health and Human Services 

540 Gaither Road 

Rockville, MD 20850 

www.ahrq.gov 

Contract No. HHSA 290-2007-10066-I 

Prepared by: 

Duke Evidence-based Practice Center 

Durham, North Carolina 

Authors: 

John W. Williams, M.D., M.P.H. 

Brenda L. Plassman, Ph.D. 

James Burke, M.D, Ph.D. 

Tracey Holsinger, M.D. 

Sophiya Benjamin, M.D. 

AHRQ Publication No. 10-E005 

April 2010
This report is based on research conducted by the Duke Evidence-based Practice Center (EPC) 

under contract to the Agency for Healthcare Research and Quality (AHRQ), Rockville, MD 

(Contract No. HHSA 290-2007-10066-I). The findings and conclusions in this document are 

those of the author(s), who are responsible for its contents, and do not necessarily represent the 

views of AHRQ. No statement in this report should be construed as an official position of AHRQ 

or of the U.S. Department of Health and Human Services. 

The information in this report is intended to help clinicians, employers, policymakers, and others 

make informed decisions about the provision of health care services. This report is intended as a 

reference and not as a substitute for clinical judgment. 

This report may be used, in whole or in part, as the basis for development of clinical practice 

guidelines and other quality enhancement tools, or as a basis for reimbursement and coverage 

policies. AHRQ or U.S. Department of Health and Human Services endorsement of such 

derivative products may not be stated or implied. 
This document is in the public domain and may be used and reprinted without permission except 

those copyrighted materials noted for which further reproduction is prohibited without the 

specific permission of copyright holders. 

Suggested Citation: 

Williams JW, Plassman BL, Burke J, Holsinger T, Benjamin S. Preventing Alzheimer’s Disease 

and Cognitive Decline. Evidence Report/Technology Assessment No. 193. (Prepared by the 

Duke Evidence-based Practice Center under Contract No. HHSA 290-2007-10066-I.) AHRQ 

Publication No. 10-E005. Rockville, MD: Agency for Healthcare Research and Quality. April 

2010. 

No investigators have any affiliations or financial involvement (e.g., employment, 

consultancies, honoraria, stock options, expert testimony, grants or patents received or 

pending, or royalties) that conflict with material presented in this report. 

ii
Preface 

 The Agency for Healthcare Research and Quality (AHRQ), through its Evidence-Based 

Practice Centers (EPCs), sponsors the development of evidence reports and technology 

assessments to assist public- and private-sector organizations in their efforts to improve the 

quality of health care in the United States. The National Institutes of Health (NIH) Office of 

Medical Applications of Research (OMAR) requested and provided funding for this report. The 

reports and assessments provide organizations with comprehensive, science-based information 

on common, costly medical conditions and new health care technologies. The EPCs 

systematically review the relevant scientific literature on topics assigned to them by AHRQ and 

conduct additional analyses when appropriate prior to developing their reports and assessments. 

 To bring the broadest range of experts into the development of evidence reports and health 

technology assessments, AHRQ encourages the EPCs to form partnerships and enter into 

collaborations with other medical and research organizations. The EPCs work with these partner 

organizations to ensure that the evidence reports and technology assessments they produce will 

become building blocks for health care quality improvement projects throughout the Nation. The 

reports undergo peer review prior to their release. 

 AHRQ expects that the EPC evidence reports and technology assessments will inform 

individual health plans, providers, and purchasers as well as the health care system as a whole by 

providing important information to help improve health care quality. 

 We welcome comments on this evidence report. They may be sent by mail to the Task Order 

Officer named below at: Agency for Healthcare Research and Quality, 540 Gaither Road, 

Rockville, MD 20850, or by e-mail to epc@ahrq.gov. 

iii

Carolyn M. Clancy, M.D. 

Director 

Agency for Healthcare Research and Quality 

Jennifer Crossman, M.D. 

Acting Director 

National Institutes of Health (NIH) 

Office of Medical Applications of Research 

(OMAR) 

Steven Fox, M.D, S.M., M.P.H 

 EPC Program Task Order Officer 

 Agency for Healthcare Research and Quality 

Jean Slutsky, P.A., M.S.P.H. 

Director, Center for Outcomes and Evidence 

Agency for Healthcare Research and Quality 

Beth A. Collins Sharp, Ph.D., R.N. 

Director, EPC Program 

Agency for Healthcare Research and Quality 
iv
Acknowledgments 

The authors thank the following individuals: for help with literature search and retrieval, 

Connie Schardt; for statistical support, Victor Hasselblad, Ph.D.; for assistance in the preparation 

of evidence tables, Remy Coeytaux, M.D., Ph.D.; Jennifer McDuffie, Ph.D.; Ravi Dhurjati, 

D.Phil.; Carolina Aponte Urdaneta, M.D.; and Katie Dore, P.A-C.; for project management, 

Julian Irvine, M.C.M.; for editorial assistance, Rebecca Gray, D.Phil.; and for research 

assistance, Alice Thacher and Vincent Miller. 

v

vii

Structured Abstract 

Objectives: To assess whether previous research on purported risk or protective factors for 

Alzheimer’s disease (AD) and cognitive decline is of sufficient strength to warrant specific 

recommendations for behavioral, lifestyle, or pharmaceutical interventions/modifications 

targeted to these endpoints. 

Data Sources: MEDLINE® and the Cochrane Database of Systematic Reviews. Additional 

studies were identified from reference lists and technical experts. 

Review Methods: A group of experts in the field developed the list of factors to be evaluated in 

preparation for an upcoming National Institutes of Health (NIH) Office of Medical Applications 

of Research (OMAR) State-of-the-Science Conference addressing the prevention of AD and 

cognitive decline. We grouped the factors into the following categories: nutritional factors, 

medical conditions and prescription and non-prescription medications, 

social/economic/behavioral factors, toxic environmental factors, and genetics. Outcomes of 

interest were the development of AD or cognitive decline. Both observational and intervention 

studies were evaluated. Studies were evaluated for eligibility and quality, and data were 

abstracted on study design, demographics, intervention or predictor factor, and cognitive 

outcomes. 

Results: A total of 25 systematic reviews and 250 primary research studies were included. Only 

a few factors showed a consistent association with AD or cognitive decline across multiple 

studies, including both observational studies and randomized controlled trials (when available). 

Such factors associated with increased risk of AD and cognitive decline were: diabetes, epsilon 

4 allele of the apolipoprotein E gene (APOE e4), smoking, and depression. Factors showing a 

fairly consistent association with decreased risk of AD and cognitive decline were: cognitive 

engagement and physical activities. A consistent association does not imply that findings were 

robust, as the data were often limited, and the quality of evidence was typically low. In addition, 

the modification of risk for reported associations was typically small to moderate for AD, and 

small for cognitive decline. Some of the factors that did not show an association with AD or 

cognitive decline in this review may still play an influential role in late-life cognition, but there 

was not sufficient evidence to draw this conclusion. Many of the factors evaluated are not 

amenable to randomization, so rigorous observational studies are required to assess their effect 

on AD and cognitive decline. 

Conclusions: The current research on the list of putative risk or protective factors is largely 

inadequate to confidently assess their association with AD or cognitive decline. Further research 

that addresses the limitations of existing studies is needed prior to be able to make 

recommendations on interventions. 

Contents

Executive Summary............................................................................................................... 1 

Evidence Report................................................................................................................... 11 

Chapter 1. Introduction .......................................................................................................... 13 

 Scope of the Problem....................................................................................................... 13 

 Risk Factors for Alzheimer’s Disease and Cognitive Decline......................................... 14 

 Purpose of this Evidence Report...................................................................................... 15 

 Role of the Technical Expert Panel ................................................................................. 15 

 Organization of this Report.............................................................................................. 16 

 

Chapter 2. Methods................................................................................................................ 17 

 Introduction...................................................................................................................... 17 

 Key Questions.................................................................................................................. 17 

 Analytic Framework ........................................................................................................ 19 

 Literature Review Methods.............................................................................................. 19 

 Peer Review Process........................................................................................................ 23 

 

Chapter 3. Results .................................................................................................................. 25 

 Literature Search Results ................................................................................................. 25 

 Measurement of Cognitive Outcomes ............................................................................. 29 

 Key Question 1 – Factors Associated with Reduction of Risk of 

 Alzheimer’s Disease ...................................................................................................... 30 

 Key Question 2 – Factors Associated with Reduction of Risk of 

 Cognitive Decline ..........................................................................................................141 

 Key Question 3 – Interventions to Delay the Onset of Alzheimer’s Disease..................261 

 Key Question 4 – Interventions to Improve or Maintain Cognitive 

 Ability or Function.........................................................................................................267 

 Key Question 5 – Relationships Between Factors Affecting Alzheimer’s Disease 

 and Cognitive Decline....................................................................................................284 

 Key Question 6 – Future Research Needs .......................................................................295 

Chapter 4. Discussion ............................................................................................................303 

Chapter 5. Conclusions ..........................................................................................................307 

 

References Cited in the Evidence Report ..............................................................................311 

Acronyms and Abbreviations ................................................................................................325 

ix
Figures 

Figure 1. Analytic framework................................................................................................ 19 

Figure 2. Literature flow diagram.......................................................................................... 26

Figure 3. Meta-analysis of three cohort studies on homocysteine 

 and risk of developing AD...................................................................................... 75 

Figure 4. Meta-analysis of six cohort studies on statins and risk of developing AD. ........... 88 

Figure 5. Funnel plot of standard error by log hazard ratio for statins 

 and risk of developing AD...................................................................................... 89 

Figure 6. Meta-analysis of eight cohort studies on NSAIDs and risk of developing AD...... 98 

Figure 7. Meta-analysis of nine cohort studies on physical activity 

 and risk of developing AD......................................................................................119 

Tables 

Table 1. Exposures/interventions evaluated in this report..................................................... 18 

Table 2. Inclusion and exclusion criteria ............................................................................... 20 

Table 3. Included systematic reviews .................................................................................... 27 

Table 4. B vitamins and folate and risk of developing AD ................................................... 32 

Table 5. Antioxidant and multivitamin use and risk of developing AD................................ 37 

Table 6. Omega-3 fatty acids and risk of developing AD – study characteristics and 

 results from studies reviewed by Fotuhi et al., 2009 .............................................. 44 

Table 7. Omega-3 fatty acids and risk of developing AD – recent cohort studies ................ 47 

Table 8. Intake of various types of fat and risk of developing AD........................................ 49 

Table 9. Mediterranean diet and risk of developing AD ....................................................... 51 

Table 10. Intake of fruit and vegetables and risk of developing AD..................................... 54 

Table 11. Total intake of calories, carbohydrates, fats, and protein 

 and risk of developing AD..................................................................................... 56 

Table 12. Diabetes mellitus and risk of developing AD........................................................ 60 

Table 13. Metabolic syndrome and risk of developing AD................................................... 64 

Table 14. Hypertension and risk of developing AD .............................................................. 67 

Table 15. Homocysteine and risk of developing AD............................................................. 73 

Table 16. Obesity and risk of developing AD ....................................................................... 77 

Table 17. Traumatic brain injury and risk of developing AD – results from 

 case-control studies reviewed by Fleminger et al., 2003....................................... 78 

Table 18. Traumatic brain injury and risk of developing AD – cohort studies ..................... 81 

Table 19. Depression and risk of AD – results from stratified analyses by 

 Ownby et al., 2006................................................................................................. 82 

Table 20. Depression and risk of developing AD – recent cohort studies............................. 84 

Table 21. Statins and risk of developing AD......................................................................... 86 

Table 22. Antihypertensives and risk of developing AD....................................................... 91 

Table 23. NSAIDs and risk of developing AD...................................................................... 96 

Table 24. Gonadal steroids and risk of developing AD – results from stratified 

 analyses by LeBlanc et al., 2001............................................................................ 99 

Table 25. Childhood socioeconomic status and risk of developing AD................................101 

x
Table 26. Education and risk of developing AD – results from studies reviewed by 

 Caamano-Isorna et al., 2006 ..................................................................................103 

Table 27. Years of education and risk of developing AD......................................................105 

Table 28. Occupation and risk of developing AD .................................................................107 

Table 29. Social engagement and risk of developing AD .....................................................111 

Table 30. Cognitive activities and risk of developing AD.....................................................116 

Table 31. Physical activity and risk of developing AD ........................................................121 

Table 32. Leisure activities and risk of developing AD ........................................................130 

Table 33. Smoking and risk of developing AD – results from studies reviewed by 

 Anstey et al., 2007 .................................................................................................133 

Table 34. Tobacco use and risk of developing AD – recent cohort studies...........................134 

Table 35. Alcohol use and risk of developing AD – results from studies reviewed by 

 Anstey et al., 2009 .................................................................................................136 

Table 36. Toxic environmental factors and risk of developing AD – characteristics 

 of studies reviewed by Santibanez et al., 2007 ......................................................137 

Table 37. B vitamins and folate and risk of cognitive decline...............................................143 

Table 38. Other vitamins and risk of cognitive decline.........................................................147 

Table 39. Omega-3 fatty acids and risk of cognitive decline – study characteristics and 

 results from studies reviewed by Fotuhi et al., 2009 .............................................148 

Table 40. Omega-3 fatty acids and risk of cognitive decline – recent cohort studies ...........150 

Table 41. Intake of various types of fat and risk of cognitive decline...................................152 

Table 42. Plasma selenium levels and risk of cognitive decline............................................154 

Table 43. Intake of copper, zinc, and iron and risk of cognitive decline...............................156 

Table 44. Mediterranean diet and risk of cognitive decline...................................................158 

Table 45. Intake of fruit and vegetables and risk of cognitive decline..................................160 

Table 46. Diabetes mellitus and risk of cognitive decline.....................................................164 

Table 47. Metabolic syndrome and risk of cognitive decline................................................168 

Table 48. Hypertension and risk of cognitive decline ...........................................................172 

Table 49. Total cholesterol and risk of cognitive decline......................................................181 

Table 50. Homocysteine and risk of cognitive decline..........................................................183 

Table 51. Obesity and risk of cognitive decline ....................................................................186 

Table 52. Depression and risk of cognitive decline...............................................................188 

Table 53. Statins and risk of cognitive decline......................................................................193 

Table 54. Antihypertensives and risk of cognitive decline....................................................195 

Table 55. NSAIDs and risk of cognitive decline ...................................................................198 

Table 56. Gonadal steroids and risk of cognitive decline......................................................202 

Table 57. Childhood factors and risk of cognitive decline ....................................................204 

Table 58. Years of education and risk of cognitive decline...................................................208 

Table 59. Occupation and risk of cognitive decline ..............................................................215 

Table 60. Social engagement and risk of cognitive decline...................................................220 

Table 61. Cognitive activities and risk of cognitive decline..................................................227 

Table 62. Physical activity and risk of cognitive decline ......................................................231 

Table 63. Leisure activities and risk of cognitive decline .....................................................238 

Table 64. Smoking and risk of cognitive decline – results from studies reviewed by 

 Anstey et al., 2007 .................................................................................................241 

xi
xii

Table 65. Tobacco use and risk of cognitive decline – recent cohort studies........................243 

Table 66. Alcohol use and risk of cognitive decline – results from studies reviewed 

 by Anstey et al., 2009 ............................................................................................246 

Table 67. Alcohol and risk of cognitive decline – recent cohort studies...............................249 

Table 68. APOE genotype and risk of cognitive decline.......................................................255 

Table 69. Therapeutic effects of gonadal steroids on development of AD ...........................265 

Table 70. Summary of evidence for association between nutritional factors 

 and AD or cognitive decline ..................................................................................286 

Table 71. Summary of evidence for association between medical factors 

 and AD or cognitive decline ..................................................................................288 

Table 72. Summary of evidence for association between medications 

 and AD or cognitive decline ..................................................................................290 

Table 73. Summary of evidence for association between social/economic/behavioral 

 factors and AD or cognitive decline ......................................................................293 

Table 74. Summary of findings on potential risk factors and interventions for AD .............308 

Table 75. Summary of findings on potential risk factors and interventions 

 for cognitive decline ..............................................................................................309 

Appendixes 

Appendix A: Exact Search Strings 

Appendix B: Evidence Tables 

Appendix C: Quality Assessment – Systematic Reviews 

Appendix D: Quality Assessment – Randomized Controlled Trials 

Appendix E: Quality Assessment – Observational Studies 

Appendix F: Peer Reviewers 

Appendix G: List of Excluded Studies 

Appendixes (including evidence tables) for this report are provided electronically at 

http://www.ahrq.gov/downloads/pub/evidence/pdf/alzheimers/alzcog.pdf. 

1

Executive Summary 

Introduction 

Dementia is a loss of cognitive abilities in multiple domains that results in impairment in 

normal activities of daily living and loss of independence. Alzheimer’s disease (AD) is the most 

common cause of dementia, responsible for 60 to 80 percent of all dementia. AD causes severe 

suffering for patients, including progressive functional impairment, loss of independence, 

emotional distress, and behavioral symptoms. Families and caregivers often experience 

emotional and financial stress. 

The major risk factor for AD is age, with the prevalence doubling every 5 years after the age 

of 65. Most estimates of the prevalence of AD in the United States are about 2.3 million for 

individuals over age 70, but some estimates are as high as 5.3 million individuals over the age of 

65. The number of individuals with mild cognitive impairment exceeds the number with AD. 

These individuals have mild impairment in cognition or daily functions that does not meet the 

threshold for a diagnosis of dementia, but they are at increased risk for development of AD, 

which makes them a prime target for intervention protocols. 

Studies of selected risk or protective factors for cognitive decline and AD have been 

published, but it is not clear whether the results of these previous studies are of sufficient 

strength to warrant specific recommendations for behavioral, lifestyle, or pharmaceutical 

interventions/modifications targeted to these endpoints. 

As background for an upcoming State-of-the-Science Conference in April 2010, the National 

Institutes of Health (NIH) Office of Medical Applications of Research (OMAR) commissioned 

this evidence report on “Preventing Alzheimer’s Disease and Cognitive Decline” through the 

Agency for Healthcare Research and Quality (AHRQ). The aim is to summarize the available 

literature, frame the discussion regarding potential risk factors, and highlight the limitations of 

the evidence base. 

We synthesized the existing literature on the following key questions: 

Key Question 1: What factors are associated with the reduction of risk of 

Alzheimer’s disease? 

Key Question 2: What factors are associated with the reduction of risk of 

cognitive decline in older adults? 

Key Question 3: What are the therapeutic and adverse effects of interventions to 

delay the onset of Alzheimer’s disease? Are there differences in outcomes among 

identifiable subgroups? 

Key Question 4: What are the therapeutic and adverse effects of interventions to 

improve or maintain cognitive ability or function? Are there differences in 

outcomes among identifiable subgroups? 

Key Question 5: What are the relationships between the factors that affect 

Alzheimer’s disease and the factors that affect cognitive decline? 
2

Key Question 6: If recommendations for interventions cannot be made currently, 

what studies need to be done that could provide the quality and strength of 

evidence necessary to make such recommendations to individuals? 

Methods 

We searched MEDLINE® using Medical Subject Heading (MeSH) search terms, 

supplemented by keyword searches. In addition to MEDLINE®, we manually searched reference 

lists and searched the Cochrane Database of Systematic Reviews to identify relevant systematic 

reviews. For topics with a recent good-quality systematic review, we updated the search by 

identifying relevant primary literature published from 1 year prior to the search date of the 

review through October 27, 2009. When we did not identify a relevant good-quality review, we 

searched the primary literature for studies from 1984 through October 27, 2009. Because of the 

large volume of literature and the availability of specialized registries for genetic studies, we 

developed a separate search strategy for this topic and limited our review to select genes of 

special interest. 

We restricted our review to human studies conducted in economically developed countries 

and published in English. We considered studies with participants ≥ 50 years old, of both sexes, 

all racial and ethnic populations, and drawn from general populations. We limited the sample 

size to ≥ 50 for randomized controlled trials (RCTs) and ≥ 300 for observational studies. We 

required at least 1 year between exposure and outcomes assessment for studies of cognitive 

decline, and 2 years for studies of AD. For Key Questions 1 and 2, we evaluated studies using 

observational designs; for Key Questions 3 and 4, we evaluated RCTs. Two reviewers 

independently assessed study eligibility and study quality and abstracted data. For Key Questions 

1 through 5, we considered factors identified by the OMAR planning committee in five major 

categories: (1) nutritional factors; (2) medical factors (including medical conditions and 

prescription and non-prescription medications); (3) social/economic/behavioral factors; (4) toxic 

and environmental factors; and (5) genetics. Data were synthesized qualitatively and, when 

appropriate, using quantitative methods. We rated the overall level of evidence for each factor as 

high, moderate, or low using principles developed by the Grading of Recommendations 

Assessment, Development and Evaluation (GRADE) working group. The level of evidence is 

considered “high” when further research is very unlikely to change our confidence in the 

estimate of effect, and “low” when further research is very likely to have an important impact on 

our confidence in the estimate of effect and is likely to change the estimate. 

Results 

A total of 25 systematic reviews and 250 primary studies met our inclusion criteria. The 

number of included studies differed markedly across the factors considered. Results are 

summarized immediately below by key question. We focus in this summary on the factors that 

showed an association with AD or cognitive decline. Those factors that did not show a consistent 

association with cognitive outcomes are described in more detail in the full report; this highlights 
3

the point that among the many factors investigated, only a few have sufficient evidence to 

indicate a potential association with late-life cognitive outcomes. 

Finally, at the conclusion of this section, we present two summary tables that show the 

direction of association (if any) and the level of evidence for all factors considered in the report. 

Key Question 1 – Factors Associated with Risk of Developing AD 

The results reported here are based on observational studies of AD, but to fully understand 

the associations between factors and cognitive outcomes, it is important to consider the results 

from both observational studies and RCTs when the latter are available. 

In the nutrition category, both higher levels of folic acid and higher adherence to a 

Mediterranean diet were associated with a small to moderate decrease in risk of AD. The level of 

evidence was low for both of these factors. 

For medical conditions, diabetes (summary odds ratio [OR] 1.39; 95 percent confidence 

interval [CI] 1.17 to 1.66), hyperlipidemia in mid-life, depression (summary OR 1.90; 1.55 to 

2.33), and traumatic brain injury in males (summary OR 2.29; 1.47 to 3.58) were all associated 

with increased risk of AD. The level of evidence was low for each of these factors. No other 

factors showed a consistent relation to AD. 

In the medication category, use of statins (summary hazard ratio [HR] 0.73; 95 percent CI 

0.57 to 0.94) showed an association with decreased risk of AD. The observational studies for 

estrogen (summary relative risk [RR] 0.50; 95 percent CI 0.30 to 0.80) and antihypertensives 

showed a likely protective association with AD. The level of the evidence was low for these 

factors. 

In the social, economic, and behavioral category, current smoking (summary RR 1.79; 95 

percent CI 1.43 to 2.23) was associated with increased risk of AD. Moderate use of alcohol 

(summary RR 0.72; 0.61 to 0.86), more years of education, and higher levels of cognitive 

engagement showed an association with a moderately decreased risk of AD. Participation in 

physical leisure activity (summary HR 0.72; 95 percent CI 0.53 to 0.98) was generally associated 

with decreased risk of AD. Limited data on marriage and social support suggest that never being 

married and having less social support are associated with a moderately increased risk of AD. 

The level of evidence for all of these factors was low. 

For the environmental exposure category, case-control studies were included for the 

subtopics reviewed (solvents, pesticides, lead, and aluminum) because there were few cohort 

studies that met inclusion criteria. Only pesticides showed a consistent and large association with 

higher risk of AD, but the level of the evidence was low. 

For the review of genes, we identified 10 genes with the strongest and best quality evidence 

of an association with AD based on a systematic review and quality ratings conducted by 

ALZGene, an online database of genetic association studies performed on AD phenotypes. Based 

on the selection criteria, it is not surprising that all genes showed a significant association with 

AD. It is noteworthy that the epsilon 4 allele of the apolipoprotein E gene (APOE e4) allele 

showed the highest and most consistent risk for AD (summary OR 3.68; 95 percent CI 3.3 to 

4.1). The level of evidence was moderate for the APOE e4 allele. 
4

Key Question 2 – Factors Associated with Risk of Cognitive Decline 

The results reported for this question are based on observational studies for cognitive decline. 

Effect sizes in all cases were small to moderate. In the nutrition category, low plasma 

selenium showed an association with higher risk of cognitive decline. Higher amounts of 

vegetable intake, adherence to a Mediterranean diet, and higher levels of omega-3 fatty acids 

showed a likely association with decreased risk of cognitive decline, but evidence was limited 

for some of these factors. The level of evidence was low for all of these factors. 

For the medical category, diabetes, metabolic syndrome, and depression showed fairly 

consistent associations with a small increased risk of cognitive decline. There were no studies 

that met inclusion criteria on cognitive decline and traumatic brain injury, sleep apnea, 

resiliency, or anxiety. 

For the medication category, two types of medication (non-steroidal anti-inflammatory drugs 

[NSAIDs] and estrogen) showed possibly decreased risk for cognitive decline in select 

subgroups, but the other medications evaluated (statins, antihypertensives, and cholinesterase 

inhibitors) showed no association or no consistent association with cognitive decline. 

Among the social, economic, and behavioral factors, smoking showed an increased risk of 

cognitive decline. Participation in non-physical/non-cognitive leisure activities, cognitive 

engagement, and physical activity all showed a fairly consistent protective association against 

cognitive decline. For observational studies, the level of evidence was low for these factors. 

There were no eligible studies identified for the environmental exposure category.

In the genetic category, only APOE has been assessed in relation to cognitive decline. The 

studies fairly consistently report that APOE e4 is associated with greater cognitive decline on 

selected cognitive measures that were not consistent across studies. The level of evidence was 

rated as low for this factor. 

Key Question 3 – Interventions to Delay the Onset of AD 

There were relatively few RCTs assessing the association between the factors examined and 

AD. This is at least partially attributable to the fact that many of the factors are not amenable to 

testing in an RCT. There were also sparse, if any, data on differences in outcomes among 

subgroups because the few RCTs conducted have generally not been designed to assess such 

differences. 

For the nutrition category, there was one RCT on vitamin E and one on gingko biloba that 

showed no association with AD. There were no other RCTs for nutritional factors, including 

folic acid and Mediterranean diet, factors suggested to decrease risk by observational studies. 

The factors in the medical conditions category are not appropriate for randomization. 

For the medications category, the three RCTs using antihypertensive medication showed no 

association with AD, but findings were limited by low power to detect a clinically important 

effect and assessment for all-cause dementia rather than AD. The eight RCTs using 

cholinesterase inhibitors showed no association with AD (moderate level of evidence). The two 

RCTs assessing NSAIDs showed increased risk of AD with rofecoxib, a medication that was 

subsequently withdrawn from the market for safety reasons, and increased risk for non-specific 

dementia with naproxen (HR 3.57; 95 percent CI 1.09 to 11.7) but the study was stopped early 

and findings were based on few cases. In intervention trials, estrogen alone showed no 

association, but estrogen combined with progesterone showed an increased risk of AD (HR 2.05; 
5

95 percent CI 1.21 to 3.48). The level of evidence was rated as moderate for estrogen combined 

with progesterone and low for NSAIDs. 

For the social, economic, and behavioral factors, there were no intervention trials for any 

factors, including physical activity and cognitive engagement, interventions suggested to be 

beneficial by observational studies. 

Key Question 4 – Interventions to Improve or Maintain Cognitive 

Ability or Function 

There were few RCTs assessing the effect of the various factors on cognitive decline. 

Additionally there was no information on differential outcomes by subgroups. 

For the nutrition category, intervention trials of vitamin B6 and B12, vitamin E, and folic 

acid showed either no effect on cognitive decline or no consistent effect across trials. The level 

of evidence was judged to be high for vitamin E and moderate for the other supplements. We did 

not identify any trials that evaluated the Mediterranean diet or diets high in vegetables, practices 

that have been associated with lower risk of cognitive decline in observational studies. 

The medical conditions were not appropriate for RCTs. 

For the medication category, there was no effect of statins (level of evidence = high), 

antihypertensive medications (low), cholinesterase inhibitors (moderate), or estrogen (high). 

Some of the types of NSAIDs showed no effect, but one (naproxen) showed increased risk of 

cognitive decline. The level of evidence for NSAIDs was rated as low. Observational studies had 

suggested lower risk for both NSAIDs and estrogen. 

For the social, economic, and behavioral categories, physical activity and cognitive training 

interventions showed a small protective association against cognitive decline. The level of the 

evidence for cognitive training was rated high, but that for physical activity was rated low. 

Key Question 5 – Relationships Between Factors Affecting AD and 

Cognitive Decline 

To address this question, we used the results from Key Questions 1 through 4 to compare the 

evidence for the effects of each exposure on risk of AD and cognitive decline. For factors with 

both RCT and observational evidence, we first compared the consistency of findings across study 

designs for each outcome. RCTs were preferred when of high quality. When studies showed a 

consistent effect on risk that was in the same direction for both AD and cognitive decline, we 

judged the results concordant. For many factors, the available data are quite limited, and 

concordant evidence across outcomes should not necessarily be interpreted as a robust finding. 

For other factors, not only were data limited but there was also marked heterogeneity in exposure 

or outcome measures across studies, so it was not possible to draw a conclusion about 

concordance. It is important to note that risk modification was generally small to moderate when 

factors were associated with AD (i.e., odds ratios and relative risk ratios were often substantially 

< 2.0). For cognitive decline, it is more difficult to determine the threshold for a meaningful 

change due to the numerous cognitive measures used to assess cognitive decline. But generally 

the differences in annual rate of decline between the exposed and unexposed groups were quite 

small. 
6

To summarize results for Key Question 5, factors showing an association for both AD and 

cognitive decline were: 

Increased risk: Diabetes 

 APOE e4 

 Smoking 

 Depression 

Decreased risk: Mediterranean diet (limited data) 

 Cognitive engagement 

 Physical activities 

Key Question 6 – Future Research Needs 

The current evidence is insufficient to recommend interventions. Weaknesses in the research 

methodology used in many of the studies reviewed have led to gaps in our knowledge. Critical 

improvements that are needed are: more precise, better validated, and more standard exposure 

measures; more standardized cognitive assessment measures across studies that are appropriate 

for the functional level of the sample (e.g. cognitively normal, mild cognitive impairment 

[MCI]); studies of longer duration; and better documentation and reporting of methods and 

results. Studies should also take into account the intensity, duration, and timing of the exposure, 

as exposures may be more influential and interventions more effective during critical or sensitive 

windows of time throughout life. Given the long sub-clinical, prodromal period of AD, RCTs 

need to continue for extended periods of time, and/or better methods need to be devised to 

evaluate potential interventions more rigorously in long-term observational studies. Although 

long-term RCTs are the ideal approach, in many cases the barriers to implementing such studies 

may make them unrealistic. For this reason, RCTs might aim to identify individuals at high risk 

of cognitive decline to make trials more efficient and economical. In addition, alternative 

research designs and analytical approaches should be considered. The development of research 

consortia might be considered to address the problems of inconsistent measurement of exposures 

and small sample sizes commonly found in previous research. Factors that may now be ready to 

be assessed further in RCTs are physical exercise and cognitive engagement. Although a few 

intervention trials have been done on some aspects of these factors, there is a need for trials that 

consider multiple components of the same general factor and multiple factors simultaneously. 

Summary Tables 

Tables ES1 and ES2 provide an overall summary of the direction of association (if any) and 

the level of evidence for all factors considered in the report for AD and cognitive decline, 

respectively. 
7

Table ES1. Summary of findings on potential risk factors and interventions for AD 

Direction of association Factors Level of evidence‡ 

• APOE e4 genotype 

• Conjugated equine estrogen with methyl 

progesterone* 

Moderate 

Increased risk 

• Some non-steroidal anti-inflammatory drugs* 

• Depressive disorder 

• Diabetes mellitus 

• Hyperlipidemia in mid-life 

• Traumatic brain injury in males 

• Pesticide exposure 

• Never married, less social support 

• Current tobacco use 

Low 

Decreased risk 

• Mediterranean diet 

• Folic acid 

• HMG-CoA reductase inhibitors (statins) 

• Higher levels of education 

• Light to moderate alcohol intake 

• Cognitively engaging activities 

• Physical activity, particularly high levels 

Low 

• Ginkgo biloba* High 

• Vitamin E* 

• Cholinesterase inhibitors* Moderate 

No association 

• Anti-hypertensive medication* 

• Conjugated equine estrogen 

• Omega-3 fatty acids* 

• Vitamins B12, C, beta-carotene 

• Homocysteine 

• Hypertension 

• Obesity 

• Metabolic syndrome 

• Early childhood factors 

• Occupational level 

• Lead 

Low 

Inadequate evidence to 

assess association 

• Saturated fat intake 

• Fruit and vegetable intake 

• Trace metals 

• High caloric intake 

• Memantine 

• Sleep apnea 

• Anxiety disorders 

• Resiliency 

• Non-cognitive, non-physical leisure activities 

• Agent Orange, Gulf War Syndrome 

• Solvents, aluminum 

• Genetic factors other than APOE 

(Not applicable) 

* Data from observational studies and RCTs. 

Abbreviations: APOE = apolipoprotein E gene; APOE e4 = epsilon 4 allele of the apolipoprotein E gene; HMG-CoA = 3-

hydroxy-3-methylglutaryl-coenzyme A; RCTs = randomized controlled trials 

‡GRADE criteria (see Methods section)
8

Table ES2. Summary of findings on potential risk factors and interventions for cognitive decline 

Direction of association Factors Level of evidence‡ 

Increased risk 

• APOE e4 genotype 

• Low plasma selenium 

• Depressive disorder 

• Diabetes mellitus 

• Metabolic syndrome 

• Current tobacco use 

Low 

• Cognitive training* High 

Decreased risk 

• Vegetable intake 

• Mediterranean diet 

• Omega-3 fatty acids* 

• Physical activity* 

• Non-cognitive, non-physical leisure activities 

Low 

• Vitamin C, Vitamin E, beta-carotene 

supplements* 

• Conjugated equine estrogen* 

• HMG-CoA reductase inhibitors (statins)* 

High 

• Aspirin* 

• Dehydroepiandosterone* 

• Cholinesterase inhibitors* 

• Multivitamin supplement* 

• Vitamins B6, B12 and folic acid supplements* 

Moderate 

No association • Alcohol intake 

• Non-steroidal anti-inflammatory drugs*†

• Anti-hypertensive medication* 

• Homocysteine 

• Hyperlipidemia 

• Anxiety disorders 

• Hypertension 

• Obesity 

• Early childhood factors 

• Higher levels of education 

• Social network, social supports 

Low 

Inadequate evidence to 

assess association 

• Trace metals 

• Fat intake 

• High caloric intake 

• Gingko biloba* 

• Memantine 

• Sleep apnea 

• Resiliency 

• Occupational level 

• Traumatic brain injury 

• Toxic environmental exposures 

• Agent Orange, Gulf War Syndrome 

• Genetic factors other than APOE 

(Not applicable) 

*Data from observational studies and RCTs. 

†

 Not associated with decreased risk but may be associated with increased risk. 

Abbreviations: APOE = apolipoprotein E gene; APOE e4 = epsilon 4 allele of the apolipoprotein E gene; HMG-CoA = 3-

hydroxy-3-methylglutaryl-coenzyme A; RCTs = randomized controlled trials 

‡GRADE criteria (see Methods section)

 
9

Discussion and Conclusions 

Many putative risk or protective factors for AD and cognitive decline have been proposed, 

but for few of them can any firm conclusions be drawn about their association with cognition in 

late life. It is important to note that some factors considered in this report that lack even moderate 

supporting evidence may, in fact, be associated with cognitive decline and AD; there simply was 

not sufficient evidence to draw such a conclusion. The main issues that preclude drawing 

conclusions are: few studies and thus limited evidence on any given factor; heterogeneity and 

imprecision in exposure and outcome measures, prohibiting thorough synthesis of the literature; 

inconsistent results among observational studies and between observational studies and RCTs; 

inconsistent results across the two outcomes of AD and cognitive decline; and when associations 

were found, the effect sizes were generally modest. Rigorous research methods addressing these 

issues will need to be developed to identify risk or protective factors with confidence, 

particularly with regard to the value of potential interventions. 

A few of the factors on the list are ready for further investigation using RCTs. But although 

RCTs are the preferred source for investigating the effect of exposures, many of the factors on 

the list are not appropriate for intervention trials. This means that obtaining evidence on these 

factors is dependent on conducting well-designed observational studies. Adding further 

complexity to the issue, many of the exposures reviewed in this report likely do not work in 

isolation in their effect on risk of AD or cognitive decline; instead, they probably work in 

combination with other factors. Thus, for future research the ideal interventions should be multidimensional, combining interventions for multiple risk factors and controlling for many other 

factors. 
Evidence Report 

Chapter 1. Introduction 

Scope of the Problem 

Dementia is a loss of cognitive abilities in multiple domains that results in impairment in 

normal activities of daily living and loss of independence. There are a number of diseases that 

cause dementia, but the most common is Alzheimer’s disease (AD), which is responsible for 60 

to 80 percent of all dementia.1 AD is a neurodegenerative disorder that begins in the mesial 

temporal lobe causing memory loss, but pathology soon spreads into other brain regions causing 

dementia. AD is defined pathologically by the presence of cerebral atrophy, extracellular 

amyloid plaques, and intraneuronal neurofibrillary tangles. 

The major risk factor for AD is age, with the prevalence doubling every 5 years after the age 

of 65.2 The prevalence of AD in 2002 was estimated to be 2.3 million individuals over age 70, 

based on a national population-based sample.3

 Another group estimated the prevalence of AD in 

2000 at 4.5 million individuals aged 65 and older, based on a U.S. regional sample.4 This latter 

figure was updated to an estimated 5.3 million individuals with AD in 2008.1

 This translates into 

about one in 8 to 10 persons over the age of 65 suffering from AD. The worldwide prevalence of 

dementia is estimated to be 35.6 million in 2010, with the number exceeding 65 million in 2030 

and 115 million in 2050, making it a pressing global health concern.5 

The diagnosis of AD is challenging both clinically and pathologically. There are multiple sets 

of well-established criteria for the clinical diagnosis of AD.6-9 There is some variation among the 

sets of criteria, but each requires evidence of cognitive and functional decline that impacts the 

individual’s ability to carry out routine daily activities. Even though significant progress has 

been made in identifying imaging, cerebrospinal fluid, and blood markers of disease, the 

diagnosis of AD during life currently is based primarily on the phenotypic presentation of 

cognitive and functional decline. However, the diagnosis of “definite AD” requires 

neuropathologic confirmation, which is complicated by the fact that AD-specific pathology 

infrequently occurs in isolation. Typically other pathology such as various types of vascular 

lesions or Lewy bodies are present, and these may increase with advancing age.10 The presence 

of these multiple pathologies suggest that dementia is often due to multiple causes and not solely 

AD or any other single etiology. The correlation between AD pathology and cognitive symptoms 

is limited, providing further support for the idea that the other pathologies present also contribute 

to the cognitive presentation. 

The term cognitive decline covers a continuum of cognitive changes, some of which are 

considered to be within the spectrum of normal aging and others that exceed expected decline for 

normal aging and are categorized as mild impairment. Typically performance in one or more 

cognitive domains such as memory, orientation, language, executive function, and praxis are 

assessed to determine decline. The diagnostic threshold between normal and pathological 

cognitive changes is imprecise. Pathological cognitive decline is often referred to as mild 

cognitive impairment (MCI) or cognitive impairment not demented (CIND); each term has 

multiple subtypes reflecting the construct of multiple etiologies. The diagnostic criteria for MCI 

and CIND are still evolving, but guidelines generally include greater than expected cognitive 

decline for the individual’s age and education level, and no more than mild functional 

impairment insufficient to meet the threshold for a diagnosis of dementia. 

13
The number of individuals with MCI or CIND exceeds that of AD. The prevalence of CIND 

in 2002 was estimated to be 5.33 million individuals over age 70 (22 percent), based on a 

nationally representative sample.11 These individuals are at increased risk for development of 

AD, which makes them a prime target for intervention protocols. Longitudinal followup has 

shown that these individuals progress to dementia at a rate of 12 to 15 percent per year compared 

to 1 to 2 percent among cognitively healthy older adults.11,12 

AD has a wide-ranging impact on individuals, families, and healthcare systems. It causes 

severe suffering for patients, including progressive functional impairment, loss of independence, 

emotional distress, and behavioral symptoms. Dementia is associated with a greater burden of 

co-existing medical illness,13 nursing home placement,14 and increased mortality.15,16 Families 

and caregivers often experience emotional and financial stress. Up to 50 percent of caregivers 

suffer from significant psychological distress17 and incur > $18,000 annually in unreimbursed 

caregiving expenses (in 1998 dollars).18 In 2005, the direct cost to Medicare and Medicaid for 

care of people with AD and other dementias was $111 billion, and indirect costs to business for 

employees who were caregivers for individuals with AD and other dementia was estimated at 

$36.5 billion.1 According to the World Alzheimer Report 2009,5 AD accounts for 4.1 percent of 

all disability-adjusted life years (DALY) among those over 60, and cognitive impairment is the 

health condition that is most strongly associated with institutionalization. 

AD is progressive, and it is the sixth leading cause of death for people of all ages in the 

United States.19 Current therapies provide only modest symptomatic benefit, so methods to delay 

onset and/or modify progression are crucially needed. 

Risk Factors for Alzheimer’s Disease 

and Cognitive Decline 

Findings from numerous epidemiological and clinical studies suggest that multiple 

biological, behavioral, social, and environmental factors may contribute to the delay or 

prevention of cognitive decline and AD. Studies of selected risk or protective factors for 

cognitive decline and AD have been published, but few systematic reviews have examined the 

quality of these studies and the conclusions that can be drawn from the data. It is not clear 

whether the results of these previous studies are of sufficient strength to warrant specific 

recommendations for behavioral, lifestyle, or pharmaceutical interventions/modifications 

targeted to these endpoints. 

Researchers face several challenges in accurately identifying factors that alter the risk of 

cognitive decline and AD. The pathological changes for AD begin years prior to the overt 

clinical symptoms currently recognized as the hallmark of the disease,20,21 suggesting that the 

relevant exposures may cover much of the lifespan. Some exposures may alter risk of later 

cognitive disease only at certain time points in life. For these factors, there may be a limited 

window of time when interventions will be effective. The quality of the measurement of 

exposures varies considerably across studies, and the effect of this is magnified when one 

considers the potential inter-relationship between many of the factors. The criterion standard 

procedures and criteria for the cognitive outcomes differ across studies. In addition, the domains 

assessed and the specific cognitive measures used differ across studies, making it difficult to 

synthesize findings from multiple sources. There is evidence that the effect of some putative risk 

factors (e.g., diabetes and psychological stress) may vary by subgroups such as race and/or 

14
sex,22,23 necessitating careful consideration of sample characteristics in the search for 

interventions. Finally, not all exposures under consideration are readily modified. Identifying the 

association between cognitive outcomes and all of the factors investigated in this report is the 

goal, but an added benefit would be realized by identifying those factors that can realistically be 

modified. 

Purpose of this Evidence Report 

The National Institutes of Health (NIH) Office of Medical Applications of Research 

(OMAR) reviews and evaluates clinically relevant NIH research program information and 

promotes the effective transfer of this information to the health care community. OMAR 

accomplishes this objective through its Consensus Development Program. This includes major 

Consensus Development Conferences and State-of-the-Science Conferences when less definitive 

evidence is available. 

As background for a State-of-the-Science Conference scheduled for April 2010, OMAR and 

the National Institute on Aging commissioned this evidence report on “Preventing Alzheimer’s 

Disease and Cognitive Decline” through the Agency for Healthcare Research and Quality 

(AHRQ). The key research questions were developed by a planning committee. The aim of the 

report is to summarize the available literature, frame the discussions regarding potential risk 

factors, highlight the limitations of the evidence base, and identify areas for future research. 

Through this report, OMAR seeks to increase the scientific rigor of its State-of-the-Science 

Conference. The focus of the this conference will be on evaluating existing data to determine 

whether there is sufficient quality of evidence to warrant any specific recommendations at this 

time for behavioral, lifestyle, or pharmaceutical interventions/modifications targeted at AD and 

cognitive decline in later life, and to identify needs for additional research. 

The findings of our review clarify what is known about factors that modify the risk of AD or 

cognitive decline as a means of providing authoritative background information for participants 

at the State-of-the-Science Conference. More broadly, we expect that our findings will be useful 

to major stakeholders in this arena, including policymakers, advocacy groups, community 

organizations, health care providers, and mid- to late-life adults. We also identify future research 

priorities, which may be useful to government agencies and private sector funding organizations. 

Role of the Technical Expert Panel 

We identified experts in the field of Alzheimer’s disease and cognitive decline to serve as 

members of the project’s Technical Expert Panel (TEP). The TEP contributes to AHRQ’s 

broader goals of (1) creating and maintaining science partnerships and public-private 

partnerships; and (2) meeting the needs of an array of potential customers and users of this 

product. To ensure accountability and scientifically relevant work, we asked the TEP for advice 

at key stages of the project. More specifically, TEP members participated in conference calls and 

email exchanges to refine the analytic framework and key questions at the beginning of the 

project, refine the scope of the project, discuss inclusion and exclusion criteria, and provide 

expert advice on methodology. 

15
16

Members of the TEP were: 

• Jesse A. Berlin, Sc.D. – Research & Development at Johnson & Johnson Pharmaceuticals 

• Ornit Chiba-Falek, Ph.D. – Duke University 

• John Ioannidis, M.D. – University of Ioannina, Greece 

• Dan Kaufer, M.D. – University of North Carolina, Chapel Hill 

• Michael Marsiske, Ph.D. – University of Florida 

These individuals represent a broad range of specialties relevant to our topic (including 

neurology, psychology, statistics, and genetics). Because of their extensive knowledge of the 

literature on these topics, TEP members were also invited to participate in the peer review of this 

draft report. 

Organization of this Report 

Chapter 2 describes the methods used to produce this report, including the key questions 

addressed, the analytic framework, our search strategies, and inclusion/exclusion criteria. In 

Chapter 3, we report on the numbers of publications reviewed and present the results of our 

literature search and synthesis on the six key questions that OMAR posed for this review. 

Chapter 4 discusses these findings further, highlights methodological shortcomings of the extant 

research, and offers recommendations for future research. Chapter 5 summarizes the major 

conclusions. 
Chapter 2. Methods 

Introduction 

In this chapter, we document the procedures used by the Duke Evidence-based Practice 

Center (EPC) to develop this comprehensive evidence report on the factors associated with 

Alzheimer’s disease (AD) and cognitive decline. To provide a context for the review, we first 

present the key questions and analytic framework. Next we describe the methods used to identify 

articles relevant to our key questions, our inclusion/exclusion criteria, and the process we used to 

abstract relevant information from eligible articles and generate our evidence tables. We discuss 

our criteria for evaluating the quality of individual articles and synthesizing the evidence. 

Finally, we describe the peer review process. 

Key Questions 

This report addresses risk factors and potential therapeutic interventions that may modify the 

risk of AD or cognitive decline. A National Institutes of Health (NIH) Office of Medical 

Applications of Research (OMAR) State-of-the Science Conference planning committee 

developed the key questions and specified the populations and factors to be evaluated. The 

specific factors and interventions to be reviewed were refined with input from members of the 

project’s technical expert panel (TEP), representatives of NIH-OMAR, and staff at the Agency 

for Healthcare Research and Quality (AHRQ). Although a large number of factors are 

considered, the report is not inclusive of all factors that have been associated with AD or 

cognitive decline. 

The key questions considered are: 

Key Question 1: What factors are associated with the reduction of risk of 

Alzheimer’s disease? 

Key Question 2: What factors are associated with the reduction of risk of 

cognitive decline in older adults? 

Key Question 3: What are the therapeutic and adverse effects of interventions to 

delay the onset of Alzheimer’s disease? Are there differences in outcomes among 

identifiable subgroups? 

Key Question 4: What are the therapeutic and adverse effects of interventions to 

improve or maintain cognitive ability or function? Are there differences in 

outcomes among identifiable subgroups? 

Key Question 5: What are the relationships between the factors that affect 

Alzheimer’s disease and the factors that affect cognitive decline? 

17
Key Question 6: If recommendations for interventions cannot be made currently, 

what studies need to be done that could provide the quality and strength of 

evidence necessary to make such recommendations to individuals? 

For all questions, we were interested in adults age 50 or older drawn from general 

populations. For Key Questions 1 and 2, we examine all the risk factors from an epidemiologic 

standpoint, limiting our review to observational studies and focusing on factors that are not 

amenable to randomization (e.g., hypertension). For Key Questions 3 and 4, we prioritized 

randomized controlled trials (RCTs), but because the evidence was often sparse or limited to 

select samples, we supplemented trial data with evidence from observational studies, where 

necessary. For Key Question 5, we were interested in the consistency of findings for each 

exposure/intervention on risk of AD and cognitive decline. 

The exposures/interventions evaluated are listed in Table 1. 

Table 1. Exposures/interventions evaluated in this report 

Factors examined for Key Questions 1, 2, and 5 

Medical: 

A. Vascular factors: 

Diabetes mellitus 

Metabolic syndrome 

Hypertension 

Hyperlipidemia 

Homocysteine 

B. Other medical factors 

Sleep apnea 

Obesity 

Traumatic brain injury 

C. Psychological and emotional health 

Depression 

Anxiety 

Resiliency 

Social/economic/behavioral: 

A. Early childhood factors (e.g., early life 

environment, rural/urban upbringing) 

B. Education/occupation/IQ/intelligence 

C. Tobacco/nicotine use 

D. Alcohol use 

Toxic environmental exposures, including 

pesticides, pollution, Gulf War Syndrome, and Agent 

Orange exposure 

Genetics 

Factors and interventions examined for Key 

Questions 1, 2, 3, 4, and 5 

Nutritional and dietary factors: 

A. B vitamins and folate 

B. Other vitamins 

C. Gingko biloba 

D. Omega-3 fatty acids 

E. Other fats 

F. Trace metals 

G. Mediterranean diet 

H. Fruit and vegetable intake 

I. Total intake of calories, carbohydrates, fats, and 

proteins 

Prescription and nonprescription drugs: 

A. Statins 

B. Antihypertensives 

C. Anti-inflammatories 

D. Gonadal steroids 

E. Cholinesterase inhibitors 

F. Memantine 

Social/economic/behavioral factors: 

A. Social engagement (social network size, social 

support, and marital status) 

B. Cognitive engagement (including games, 

puzzles, and cognitive training) 

C. Physical activities 

D. Other (non-cognitive, non-physical) leisure 

activities 

18
Analytic Framework 

Our analytic framework (Figure 1) describes the progression from normal cognition to the 

initiation of subclinical pathophysiological processes to cognitive decline that is beyond what is 

expected for normal aging and to AD. Although there is a potential for primary prevention prior 

to the initiation of pathophysiological processes leading to cognitive decline, there are currently 

not well-validated methods to measure these processes in the absence of cognitive decline. 

Therefore, we did not consider effects of the candidate factors on changes in pathophysiological 

processes. The figure shows the potential for treatment interventions to effect cognitive decline 

and the risk for AD. 

General Adult 

Population

(without CI) 

Therapeutic Intervention (KQ3, KQ4)

{Nutritional, Medications, Social/Economic/Behavioral}

Risk Factors (KQ1, KQ2)

{Medical, Toxic Environmental Exposures, Genetics, 

Social/Economic/Behavioral}

Pathological 

Processes Cognitive 

Decline

Alzheimer's 

Disease

(KQ5)

(KQ5)

Adverse 

Experiences

Figure 1. Analytic framework 

Literature Review Methods 

Inclusion/Exclusion Criteria 

After discussion with the TEP, we generated a list of article inclusion and exclusion criteria 

(Table 2) for the Key Questions. Because of the large number of factors and interventions to 

review, we searched initially for good quality systematic reviews. We included primary literature 

to update eligible reviews or when good quality reviews were unavailable. We limited the 

primary literature to comparative studies published in English that enrolled adults age 50 years or 

older at the time of final cognitive assessment, drawn from general populations in economically 

developed countries. We defined general populations as those drawn primarily from noninstitutionalized community settings or general medical populations. With three exceptions, we 

19
limited observational studies to longitudinal designs where the risk factor or intervention was 

measured prior to the outcome. We made exceptions for traumatic brain injury and 

toxic/environmental exposures because of the difficulties studying these factors longitudinally, 

and for sleep apnea, because of the absence of cohort studies. Because AD is a relatively 

uncommon event, we required a sample size greater than 300 to focus on studies with higher 

statistical power. For similar reasons, we required at least 1 year between exposure and outcomes 

assessment for studies of cognitive decline, and at least 2 years for studies of AD. 

Table 2. Inclusion and exclusion criteria 

Category Criteria 

Study population Humans, all races, ethnicities, and cultural groups 

KQ 1-6: Adults age ≥ 50 years old; drawn from a general population or general 

medical setting, with normal cognition or mild cognitive impairment 

Study geography Developed countries: United States, Canada, United Kingdom, Western Europe, 

Australia, New Zealand, Hong Kong, Japan, Republic of China (Taiwan), 

Singapore, South Korea, Israel 

Factors/interventions See Table 1, above 

Study outcomes KQ1 & 3: Diagnosis of Alzheimer’s disease using an acceptable standard (e.g., 

National Institute of Neurological and Communicative Disorders and Stroke and 

the Alzheimer’s Disease and Related Disorders Criteria) 

KQ2 & 4: Diagnosis of mild cognitive impairment using an acceptable standard 

(e.g., Petersen’s criteria) or change in cognition using at least two measurements 

on an acceptable measure 

Outcome timing KQ1 & 3: At least 1 year after the exposure or intervention 

KQ2 & 4: At least 2 years after the exposure or intervention 

Time period 1984 to October 27, 2009 

Publication languages English only 

Admissible evidence 

(study design and other 

criteria) 

Good quality systematic reviews that addressed a question of interest and used 

eligibility criteria consistent with our inclusion/exclusion criteria 

Original research studies that provide sufficient detail regarding methods and 

results to enable use of the data and results; relevant outcomes must be able to be 

abstracted from data presented in the papers. If risk for non-specific dementia only 

were reported, we required ≥ 60% of the outcomes to be AD. 

Eligible original research designs include: 

KQ 3 & 4: Randomized controlled trials (RCTs); 

KQ 1-4: Observational studies: longitudinal designs comparing exposed to 

unexposed. For TBI, sleep apnea, and toxic environmental, case-control studies 

were also eligible. 

Sample sizes must be appropriate for the study question: RCTs ≥ 50; longitudinal 

observational ≥ 300 

Abbreviations: AD = Alzheimer’s disease; KQ = key question; RCT = randomized controlled trial; TBI = traumatic brain injury 

Literature Search Strategies 

Based on the above-described inclusion/exclusion criteria, we generated a list of Medical 

Subject Heading (MeSH) search terms, supplemented by keyword searches, to search 

MEDLINE®. Search terms and strategies were developed in consultation with a medical 

20
librarian. The exact search strategies used are given in Appendix A. ∗

 In addition to 

MEDLINE®, we searched the Cochrane Database of Systematic Reviews to identify releva

systematic reviews. For topics with a recent good quality systematic review (see “Asse

Methodological Quality,” below), we updated the search by identifying relevant primary 

literature published from 1 year prior to the search date through October 27, 2009. The 1-year 

overlap is necessary because of delays between publication in journals and availability for 

searching in MEDLINE®. Relevant older literature missed or excluded in prior reviews that was 

relevant and met eligibility criteria was included. 

nt 

ssment of 

 

When we did not identify a relevant good quality review, we searched the primary literature 

to include studies from 1984 through October 27, 2009. Electronic searching was supplemented 

by examining the bibliographies of reviews and primary studies. Because of the large volume of 

literature and availability of specialized registries for genetic studies, we developed a separate 

search strategy for this literature. We examined the HUGE and ALZGene databases to identify 

relevant systematic reviews for genes identified as being of special interest in consultation with 

the TEP. 

Using the pre-specified inclusion/exclusion criteria, titles/abstracts were examined 

independently by two reviewers for potential relevance to the key questions. Articles included by 

either reviewer underwent full-text screening. At the full-text screening stage, two independent 

reviewers read each article to determine if it met eligibility criteria. Disagreements were resolved 

by consensus. At the full-text review stage, simple agreement was 84 percent, and median 

chance corrected agreement was kappa = 0.63 (range 0.40 to 1.0). Articles meeting our eligibility 

criteria were included for data abstraction. 

Data Abstraction and Data Management 

Data from published reports were abstracted into evidence tables by one reviewer and overread by a second reviewer. Data elements abstracted included descriptors to assess applicability, 

quality elements, intervention/exposure details, and outcomes. Disagreements were resolved by 

consensus or by obtaining a third reviewer’s opinion when consensus could not be reached. The 

final evidence tables are intended to provide sufficient information so that readers can 

understand the study and determine its quality. Evidence tables for all included studies are 

presented in Appendix B. Because some studies address more than one exposure or question, the 

evidence tables are organized alphabetically by author. 

Assessment of Methodological Quality 

We developed separate criteria for assessing the methodological quality of included 

systematic reviews, RCTs, and observational studies. These criteria are given in Appendices C, 

D, and E, respectively. Briefly, for systematic reviews we assessed the comprehensiveness of the 

search strategy, the description and appropriateness of inclusion criteria, whether primary studies 

were assessed for quality and the adequacy of the quality measure, the reproducibility of 

methods to assess studies, whether the results of relevant studies were combined appropriately, 

∗ Appendixes (including Evidence Tables) for this report are provided electronically at 

http://www.ahrq.gov/downloads/pub/evidence/pdf/alzheimers/alzcog.pdf.

21
whether heterogeneity and publication bias were assessed, and whether the conclusions were 

supported by the data presented. 

For RCTs, we used the key criteria described in the AHRQ methods manual for Comparative 

Effectiveness Reviews,24 adapted to this specific topic. These criteria are: adequacy of 

randomization and allocation concealment; the comparability of groups at baseline; blinding; the 

completeness of followup and differential loss to followup; whether incomplete data were 

addressed appropriately; the validity of outcome measures; and conflict of interest. 

To assess individual observational studies, we adapted a basic set of quality criteria used in 

previous AHRQ evidence reports.25,26 These criteria concern the methods used to select the 

cohort, the adequacy of the sample size, the methods used to ascertain exposure status and 

outcomes, the adequacy and completeness of followup, and the appropriateness of the analytic 

methods used. Abstractors assigned a rating of “yes,” “partially,” “no,” or “can’t tell” to each 

item and provided a brief rationale for their decisions. We did not attempt to assign a summary 

quality score (“A, B, C” or “Good, Fair, Poor”) to individual RCTs or observational studies 

because there is no evidence that the use of any particular quality scoring system has a 

substantial impact on the results of systematic reviews.27 In addition, our experience has been 

that it is more helpful to identify consistent and specific quality issues that affect the majority of 

the included studies (concerning, e.g., sample size, analytic methods, or ascertainment bias) in 

order to guide future research, rather than relying on a global quality score. 

We used principles from the Grading of Recommendations Assessment, Development and 

Evaluation (GRADE) working group (www.gradeworkinggroup.org) to summarize the level of 

evidence for each factor as low, moderate, or high. The GRADE approach was developed to 

evaluate the overall level of evidence for interventions, but we have extended the approach to 

factors (e.g., medical illness) that would not be considered as interventions. The approach 

considers the body of evidence for each outcome, assigning an initial rating of low quality to 

observational studies and high quality to RCTs. These initial ratings may be modified by the 

following factors: detailed study design, consistency, strength of association, dose-response 

effect, directness, precision, and if all plausible confounding would reduce a demonstrated effect. 

The resulting judgments about the level of evidence are presented separately in summary tables 

for AD and cognitive decline in Chapter 5. Judgments about the strength of evidence were made 

by at least two investigators; final ratings were reached by consensus. 

Data Synthesis 

When good quality systematic reviews were identified, we summarize the findings in 

narrative form in Chapter 3 (“Results”). Any new studies identified since the systematic review 

was published are summarized descriptively in a table that includes the study sample, exposure 

classification, duration of followup, adjustment for confounding, and primary outcomes. We 

evaluated whether the new evidence was likely to change estimates from the prior review by 

considering the precision and stability of estimates from the original review, the number and size 

of the new studies relative to studies in the original review, the quality of the new studies, and 

the consistency in estimates and conclusions between the new evidence and the original review. 

After considering these issues, we updated prior meta-analyses when substantial new evidence 

was available and a new summary estimate was likely to lead to different conclusions. We 

performed primary meta-analysis when studies were conceptually homogeneous and the needed 

data were available for the summary estimate. Since meta-analysis of observational studies may 

22
23

give spurious precision,28 we applied meta-analysis to observational data only when studies were 

high quality and conceptually homogeneous (similar subjects, exposure, outcomes). 

Synthesizing studies that evaluated cognitive decline was particularly challenging. Cognitive 

decline can be classified categorically by meeting proposed criteria such as those for mild 

cognitive impairment (MCI), or by exceeding a threshold on a global cognitive measure such as 

the Mini-Mental State Examination (MMSE). These categorical outcomes are often more 

clinically meaningful and therefore were prioritized in this review. Cognitive decline may also be 

examined using continuous measures of global, isolated, domain-specific measures (e.g., 

memory, processing speed), or composites of multiple measures for a domain. Many of these 

measures have not been demonstrated to be responsive to change, and any changes observed may 

be of uncertain clinical significance. Because of the heterogeneity of the continuous measures 

reported and the large scope of the present review, we evaluated the relevance of studies 

reporting continuous measures for each exposure. When there were adequate numbers of studies 

using categorical outcomes to address the question, we did not provide detailed summaries of the 

studies reporting continuous outcomes. 

Peer Review Process 

Among the more important activities involved in producing a credible evidence report is 

conducting an unbiased and broadly based peer review of the draft report. External reviewers for 

this report included clinicians and representatives of professional societies, as well as members 

of the TEP. The list of nominees was forwarded to AHRQ for vetting and approval. A list of peer 

reviewers submitting comments on this draft is included in Appendix F. 
Chapter 3. Results 

Literature Search Results 

Figure 2 summarizes the results of our literature search and screening process. We identified 

a total of 6713 citations from the electronic search and an additional 194 citations from other 

sources. After applying inclusion/exclusion criteria at the title-and-abstract level, 1626 full-text 

articles were retrieved and screened. Of these, we excluded 1035 that did not meet our inclusion 

criteria. Appendix G∗

 provides a complete listing of articles excluded at the full-text stage, with 

reasons for exclusion. 

After applying quality assessment criteria to the systematic reviews captured in our search, 

we identified 25 good quality reviews (Table 3), which are summarized in the relevant sections 

below. Publications that were included in one of these 25 reviews are not generally counted in 

our tally of original research studies. However, some original research publications may have 

addressed more than one factor, and may be included in both an existing systematic review for 

one factor, and as an original research study for another factor. In the end, we included 250 

original research studies, along with the 25 systematic reviews. 

 

∗ Appendixes (including Evidence Tables) for this report are provided electronically at 

http://www.ahrq.gov/downloads/pub/evidence/pdf/alzheimers/alzcog.pdf.

25
Figure 2. Literature flow diagram 

Citations identified in

Medline and

Cochrane Database

(n = 6713)

Articles included in

existing systematic reviews

(n = 162)

Duplicate publications

or methods

(n = 154)

Articles & reviews failed to

meet inclusion criteria

(n = 1035)

Eligible primary studies

and reviews

(n = 591)

Primary studies and reviews

retrieved for full text screen

(n = 1626)

Abstracts failed to

meet criteria

(n = 5281)

Citations identified

from bibliographies,

Background, and other

(n = 194)

Primary studies reviewed

(n = 250)

Systematic reviews included

(n = 25)

26
Table 3. Included systematic reviews 

OUTCOMES 

Author, Year Exposure 

Alzheimer’s Disease 

Cognitive Decline Types of Studies Reviewed 

I) Nutrition/Dietary Fotuhi et al., 200929 Omega 3 Yes Yes RCTs and observational (cohort) Issa et al., 200630 Omega 3 Yes Yes Observational (cohort) Lim et al., 200631 Omega 3 Yes No RCTs Balk et al., 200632 Vitamin B and berries Yes Yes RCTs and observational (cohort) in II) Medical McGuiness et al., 200933 Statins No Yes RCTs McGuiness et al., 200634 Antihypertensives Yes Yes RCTs Szekely et al., 200435 Anti-inflammatory Yes No Observational Grimley Evans et al., 200636 Gonadal steroids No Yes RCTs Lethaby et al., 200837 Gonadal steroids No Yes RCTs LeBlanc et al., 200138 Gonadal steroids Yes Yes Observational (case-controlled and Nickelsen et al., 199939 Gonadal steroids No Yes RCTs Anstey et al., 200840 Hypercholesterolemia Yes Yes Observational (prospective cohort) Biessels et al., 200641 Diabetes mellitus Yes No Observational Lu et al., 200942 Diabetes mellitus Yes Yes Observational Cukierman et al., 200543 Diabetes mellitus No Yes Observational Raschetti et al., 200744 Cholinesterase Yes Yes RCTs Ownby et al., 200645 Depression Yes No Observational (cohort) Fleminger et al., 200346 Traumatic brain injury Yes No Observational (case-controlled) Beydoun et al., 200847 Obesity Yes No Observational (cohort) III) Social/Economic/Behavioral Angevaren et al., 200848 Physical activity No Yes RCTs 

27
28

OUTCOMES 

Author, Year Exposure 

Alzheimer’s Disease 

Cognitive Decline Types of Studies Reviewed 

Caamano-Isoma et al., 200649 Education Yes No Observational Anstey et al., 200750 Tobacco Yes Yes Observational (prospective cohort) Anstey et al., 200951 Alcohol Yes Yes Observational IV) Environmental Santibanez et al., 200752 Toxic exposures Yes No Observational (case-controlled & cV) Genetics Bertram et al., 200753 Genetic factors Yes No Gene association 

Abbreviations: RCTs = randomized controlled trials 
Measurement of Cognitive Outcomes 

Alzheimer’s Disease and Dementia 

The assessment for dementia was similar across most of the major cohort studies we 

identified. Typically the cognitive batteries used included measures of global cognitive function; 

language (naming and verbal fluency); verbal memory (word list and/or paragraph immediate 

and delayed recall); visual memory; executive function and processing speed; attention; and an 

estimate of baseline intelligence or reading ability. The specific tests used differed across the 

studies, but the cognitive domains assessed were generally similar. The studies differed in their 

use of information from a proxy informant in the diagnostic process; that is, some studies used 

information from informants, while others did not. 

Cognitive Decline 

Cognitive decline was measured in a number of different ways in the included studies. Some 

studies used a diagnosis of incident mild cognitive decline (MCI) or cognitive impairment not 

demented (CIND) as the definition for cognitive decline. The criteria used for these diagnostic 

categories varied across studies, but typically included a psychometrically determined mild 

impairment on memory tests and/or other cognitive domains, with at most mild functional 

impairment in daily activities. 

Other studies defined cognitive decline based on longitudinal change on one or more 

cognitive measures. Some studies determined decline on the test(s) based on continuous change 

in the test score over time, while other studies defined decline in categorical (often dichotomous) 

terms based on a predetermined threshold of change in performance over two or more time 

points. 

Review of the studies included in this systematic review found that about 40 percent 

reporting on cognitive decline based their findings on performance on a single cognitive 

measure, typically a general measure of cognitive function. The most common measures used 

were the Mini-Mental State Examination (MMSE) or an abbreviated form of the MMSE, the 

Modified Min-Mental State Examination (3MS), and some form of the Telephone Interview for 

Cognitive Status (TICS). Approximately half of the studies using these measures defined 

cognitive change as a continuous outcome, while the other half defined cognitive change in 

categorical terms. Some studies reported results for only a single measure, such as a verbal 

memory task, from the battery of tests that were administered. 

Another 40 percent of the included studies assessed cognitive decline using multiple 

neuropsychological measures. The majority of these studies measured decline as a continuous 

outcome. Some of these studies reported results for both the individual cognitive measures and a 

global composite measure combining all tests. The specific cognitive tests used varied across 

studies but typically included tests in a number of the following domains: global cognitive 

function (MMSE, 3MS, TICS); verbal memory (word list or paragraph immediate and delayed 

recall); visual memory; verbal fluency; naming; speed of processing; attention; executive 

function; working memory; and reasoning. 

29
Finally, about 10 percent of included studies defined cognitive decline based on a composite 

global index of performance on all tests combined. Some of these studies presented the results as 

a continuous outcome, while others reported them as a categorical outcome. 

Key Question 1 – Factors Associated with Reduction of 

Risk of Alzheimer’s Disease 

Key Question 1 is: What factors are associated with the reduction of risk of Alzheimer’s 

disease? 

Nutritional and Dietary Factors 

B vitamins and folate. We identified one good quality systematic review that examined the 

association between B vitamins or berries and development of Alzheimer’s disease (AD).32

However, we decided not to provide a detailed summary of this review here because the majority 

of the studies identified in the review did not meet our eligibility criteria, and the review authors 

did not conduct any meta-analysis combining the studies, thus providing limited benefit for our 

purpose. Instead, we here review the studies identified by the review that met our eligibility 

criteria, along with additional studies identified in our literature search. We identified a total of 

five eligible cohort studies in this way.54-58 These studies are summarized in Table 4; detailed 

evidence tables are provided in Appendix B. Three studies used samples from U.S. 

communities,54-56 and two from communities in Europe.57,58 Length of followup across the 

studies ranged from an average of approximately 3.0 to 6.1 years. In all five studies, participants 

were non-demented at baseline. Two of the studies used blood serum levels of various B 

vitamins and folate.57,58 The other three54-56 estimated levels of B vitamins and folate based on 

self-reported responses on nutrition questionnaires. The studies that used blood serum levels to 

characterize exposure used standard methods to determine the levels of folate and B vitamins. 

Another research group that reported on two different samples55,56 has published the results of 

analyses assessing the reliability and validity of the food frequency questionnaires used in their 

studies.59 They reported that the Spearman correlations for 1-year reproducibility of responses to 

the questionnaire were 0.70 for total folate, 0.50 for total vitamin B-12, and 0.58 for vitamin B-6. 

The Pearson correlations for validity were 0.50 for total folate, 0.38 for total vitamin B-12, and 

0.51 for total vitamin B-6. The authors also reported that the performance characteristics did not 

differ significantly by cognitive ability. 

All of the studies used sample selection methods to minimize selection bias. Four studies 

compared some baseline characteristics by exposure level.55-58 All studies used standard criteria 

for the diagnosis of AD, but only two used an informant report as part of the diagnostic 

process.57,58 Only some of the studies reported results for AD cases only, but the studies that 

reported results for dementia as a whole included enough AD cases to meet our eligibility 

criteria. Two studies explicitly stated that the dementia diagnosis was assigned blind to the 

exposure level of B vitamins and folate;55,56 however, it is unlikely that details of B vitamin and 

folate exposure were discussed during the diagnostic process in any of the studies. Analyses 

were appropriate and generally controlled for relevant potential confounders. 

Results from the two studies57,58 that measured folate serum levels showed that low baseline 

folate levels were consistently associated with increased risk of AD (or dementia). In 

30
31

comparison, B12 levels were typically not associated with risk of AD. The three studies that used 

estimated dietary intake of folate and B vitamins based on self-reported information reported 

conflicting results. One reported an association between higher intake of folate and reduced risk 

of AD,54 while another did not find a significant reduction in AD risk associated with folate 

intake.55 Neither study found an association between vitamins B6 or B12 and risk of AD. Direct 

comparisons of the two studies to identify reasons for these inconsistent results are difficult, but 

based on the information provided in the studies, the average rate of folate intake may differ 

between the two studies, with the study by Morris and colleagues55 reporting a lower rate of 

folate intake. Only one study examined niacin (B3) intake and found a lower risk for AD 

associated with higher intake of niacin.56

In conclusion, based on folate levels measured in serum, there is preliminary evidence from 

two studies that low folate levels are associated with increased risk of AD. The two studies 

estimating folate level from self-report dietary information did not find a consistent association 

with risk of AD. The evidence does not suggest an association between B12 and risk of AD. The 

one study assessing estimated niacin intake showed an association between higher niacin intake 

and lower risk of AD; confirmation of this is required prior to drawing conclusions. Further 

confirmation is also needed of the putative association between folate serum levels and risk of 

AD.
Table 4. B vitamins and folate and risk of developing AD 

Study Sample (n) Followup/ 

Events 

Exposure Case definition Confounding 

adjustment 

Results 

Ravaglia et al., 200557 Community cohort 

(720) 

3.8 years (SD 0.8) 

Serum levels of vitamin B12 and folate Plasma levels of homocysteine 

NINCDS-ADRDA Age 

Sex Education APOE Stroke Creatinine Smoking Diabetes Hypertension Cardiovascular disease BMI Other markers (folate, vitamin B12, and homocysteine) 

After adjustment for covariates, low folate nmol/L) were indepe(1.98; 95% CI 1.15 tCompared with the tadjusted HRs for AD P = 0.045) for the bo(0.62 to 2.72; P = 0.4and 0.66 (0.29, 1.54for trend = 0.015). By contrast, adjusted B12 concentrations t(0.66; 0.40 to 1.09; P statistically significan

Wang et al., 200158 Community cohort 

(370) 

3 years 60 AD cases 

Serum B12 and folate levels 

DSM Age 

Sex Education level Baseline cognitive score Hemoglobin levels Alcohol consumption Cardiovascular disease 

HRs for risk of incidefollowup after adjusteducation: B12 ≤ 150 vs. ≥ 150 

to 2.8) Folate ≤ 10 vs. ≥ 10 Both low B12 and loWhen low levels werpmol/L and folate ≤ 

RR for AD was 7.0 (subjects with MMSE (5 0.7 to 2.7) in subj

26. Low levels of vitamin controlling for age, sbaseline cognitive fu0.8 to 2.4) 

32
Study Sample (n) Followup/ 

Events 

Exposure Case definition Confounding 

adjustment 

Results 

Luchsinger et al., 200754

Community cohort (965) 

6.1 (SD 3.3) years 192 AD cases 

Daily dietary, supplement and total intake of folate and vitamins B6 and B12 estimated from self-reported responses semiquantitative food frequency questionnaire 

NINCDS-ADRDA DSM 

Age Race Sex Educational level APOE DM HTN Smoking Heart disease Stroke 

The risk of AD decrequartile of total folate association was stattrend = 0.02) after advitamins B6 and B12highest quartile (≥ 48folate intake comparwas 0.5 (95% CI 0.3 between dietary folastatistically significanfourth quartile of diet(0.5 to 1.2; P = 0.25 vitamin B6 and B12 of AD in any of the m

Morris et al., 200655 Community cohort 

(1041) 

3.9 years 162 AD cases 

Estimates of total intake of folate and vitamins B6 and B12 during the previous year were calculated from self-report responses on a modified Harvard food frequency questionnaire 

NINCDS-ADRDA Age 

Race Sex Educational level Period of observation APOE Vitamin E Niacin 

Using nutrient-adjushighest quintile to lowNeither total folate (Oor folate from food (1associated with risk Neither total vitamin vitamin B12 from fooassociated with risk Neither total vitamin vitamin B6 from food associated with risk Results for intake of B12 from food only wrisk of AD either. 

Morris et al., 200456 Community cohort 

(815) 

3.9 years 131 AD cases 

Estimates of total intake of niacin (B3) during the previous year were calculated from self-report responses on a modified Harvard food frequency questionnaire 

NINCDS-ADRDA Age 

Race Sex Educational level APOE Time interval between assessments Sample weights Vitamin E 

Reduction in AD risk for highest quintile cquintile: Total niacin: OR 0.2 trend = 0.04) Niacin from food: Otrend = 0.006) Tryptophan (niacin d(0.1 to 0.8; p for trenNiacin equivalents: O

33
34

Study Sample (n) Followup/ 

Events 

Exposure Case definition Confounding 

adjustment 

Results 

Vitamin C 

Beta-carotene Multiple vitamin use DM HTN Smoking Alcohol use Stroke Heart disease Folate 

trend = 0.01) 

Abbreviations: AD = Alzheimer’s disease; APOE = apolipoprotein E gene; CI = confidence interval; DM = diabetes mellitus; DSM = Diagnostic and 

Disorders; HR = hazard ratio; HTN = hypertension; NINCDS-ADRDA = National Institute of Neurological and Communicative Diseases and Stroke-

Related Disorders Association; OR = odds ratio; SD = standard deviation
Other vitamins. We identified 12 eligible cohort studies that examined risk of AD in 

association with use of antioxidant and multivitamins.60-71 These studies are summarized in 

Table 5; detailed evidence tables are provided in Appendix B. Eight studies used samples from 

U.S. communities,62,64-66,68-71one used a sample from a medical cooperative organization in the 

United States;63 two from communities in Europe,60,61 and one from Canada.67 Length of 

followup across the studies ranged from approximately 2 to 33 years. In all studies, participants 

were non-demented at baseline. Studies using food intake of E and C vitamins, beta carotene, or 

flavonoids as the predictor variables estimated intake from self-reported responses on nutrition 

questionnaires. Studies using intake of E and C vitamin supplements as the predictor variables 

estimated intake from self-reported use; some studies confirmed use of supplements by 

examination of medication containers. One study used medical records to obtain information on 

use of supplements for institutionalized participants.67 Two studies reported on the same cohort, 

the Honolulu-Asia Aging Study,64,66 but appeared to use different sources for their exposure data. 

Another two studies reported on the same sample but defined the predictor variable somewhat 

differently.69,70 Yet another study used two distinctly different food frequency questionnaires for 

different subgroups of the sample and then developed a method to combine the information from 

both questionnaires into a single dataset.61 In general, little validation has been done on the 

accuracy of the nutrition questionnaires in these studies, but one research group that reported on 

two different samples68-70 has published some analyses showing that the food frequency 

questionnaires used in their studies were reasonably reliable and valid,59 and that the 

performance characteristics did not vary significantly by cognitive ability. Correlations between 

responses on a food frequency questionnaire and a 24-hour dietary recall typically ranged from 

0.39 to 0.67 for vitamins C and E, and were higher when vitamin supplements were considered.59

Eleven of the studies used sample selection methods to minimize selection bias. One study67

used a subsample from a larger cohort study, of which a disproportionate segment of the sample 

was at relatively high risk of cognitive impairment; part of this study sample was drawn from 

institutionalized participants and part from community participants. The sources of exposure 

information differed for these two subgroups, introducing additional potential sources of bias. 

Eight studies compared some baseline characteristics by exposure level.60,63,65,67-71 All studies 

used standard criteria for the diagnosis of AD, but only five used an informant report as part of 

the diagnostic process.60,62,64,66,71 All but one study61 reported results for AD cases only, but the 

study that reported results for dementia as a whole included enough AD cases to meet our 

eligibility criteria. Few of the studies explicitly stated that the dementia diagnosis was assigned 

blind to the exposure level of the nutrients of interest; however, it is unlikely that details of these 

types of exposure were discussed during the diagnostic process in any of the studies. Analyses 

were appropriate and generally controlled for relevant potential confounders. 

Results from the studies combined are inconclusive. The preponderance of evidence suggests 

that there is no association between the amount taken in of vitamins E or C, flavonoids, or beta 

carotene and risk of AD. However, selected studies have reported associations between AD and 

vitamin C,60,68 vitamin E,64,69 or the combination of the two vitamins.71 When significant 

associations were reported, higher intake of the vitamin was associated with lower risk of AD 

(see Table 5). However, within studies these findings were often not consistent. For example, 

sometimes the significant association was limited to food intake only and not supplemental 

vitamins,69 and in other studies the association between vitamin intake and AD was limited to 

alternating quintiles of vitamin level.64 This raises some questions about the robustness of the 

35
36

findings and leads to the conclusion that there is little evidence supporting a beneficial effect of 

antioxidant vitamins on reducing risk of AD.
Table 5. Antioxidant and multivitamin use and risk of developing AD 

Study Sample (n) Followup/ 

Events 

Exposure Case definition Confounding 

adjustment 

Resu

Engelhart et al., 200260

Community cohort (5395) 

6 years 146 AD cases 

Dietary intake assessed with 2-stage protocol. First, self-report checklist of foods and drinks consumed at least twice a month during the preceding year. The checklist included questions on dietary habits, use of supplements, and prescribed diets. Based on checklist responses, participant interviewed by dietitian, using an extensive, validated semiquantitative food-frequency questionnaire (SFFQ). Estimated intake of vitamins C and E, beta carotene, and flavonoids from SFFQ. 

NINCDS-ADRDA DSM 

Age Sex Educational level Baseline cognitive status Alcohol use Smoking BMI Total energy intake Presence of carotid plaques Supplemental antioxidant use 

AdjuAD fdietaVitamVitamBeta 1.09 Flav

Fillenbaum et al., 200562

Community cohort (616) 

3 to 10 years 93 AD cases 

Information obtained on supplemental use of C, E and multi-vitamins in previous 2 weeks based on review of medication bottles. Use of C or E in multivitamin categorized as low dose, and C or E not as part of a multivitamin as high dose 

NINCDS-ADRDA DSM 

Age Educational level Marital status Income Functional status Health services use Number of prescription drugs Time frame of exposure to vitamins 

Vitamor at diagincid

Gray et al., 200863

Clinical cohort – Group Health Cooperative (2969) 

Mean 5.5 (SD, 2.7) years 289 AD cases 

Self-report at baseline and each biennial followup interview whether they had taken vitamin C,vitamin E, or multivitamins for at least 1 week during the previous month. Categorized as vitamin E user if reported taking vitamin E supplements 

NINCDS-ADRDA DSM 

Age Sex Educational level Exercise Smoking status Self-reported health 

Adjuor prNo v(refeAny to 1.Any 

37
Study Sample (n) Followup/ 

Events 

Exposure Case definition Confounding 

adjustment 

Resu

(excluding multivitamins). Categorized as vitamin C users if they reported taking vitamin C supplements (excluding multivitamins). 

Coronary heart disease (0.72 

Any (0.72 Comchan

Commenges et al., 200061

Community cohort (1367 analytical sample) 

2 to 5 years 66 dementia cases, of which 46 were AD cases 

At one study site, the participant was given a detailed questionnaire on which to record all food consumption over 3 days. Three days later, a dietitian conducted a historical inquiry about food consumption to assess frequencies and then completed the quantitative questionnaire. At the other site, a coarse questionnaire inquiring about intake of 20 categories of foods was administered. Frequency of consumption was assessed qualitatively. A selfreported quantitative interview of wine consumption was administered to all participants. The authors developed a method to combine the data from the two sources and estimate percent of flavonoid intake 

DSM Age 

Sex Educational level Weight Vitamin C 

Flavtertilassodemtertil0.26 If the comshowbetwdemto 0.Wine with 

Laurin et al., 200464 Community cohort 

(2459) 

Range: 25.7 to 33.0 years 102 cases AD 

Vitamin C, E, and beta carotene intake was extracted from selfreported 24-hour dietary recall during 1965–1968. Dietitians trained in standardized procedures used appropriate food models and serving utensils to establish food consumption. Participants were asked whether the 24-hour recall was fairly typical or unusual. In addition, questions 

NINCDS-ADRDA DSM 

Age Educational level Smoking Alcohol use BMI Physical activity Blood pressure Year of birth Total energy intake 

Betarisk oassointakVitamAD aassointakVitam

only AD a

38
Study Sample (n) Followup/ 

Events 

Exposure Case definition Confounding 

adjustment 

Resu

related to the frequencies of consumption of 26 selected food and drink items characteristic of Western or traditional Japanese diets, including tea, were asked in 1965 to 1968 and 1971 to 1974. 

Cholesterol History of cardiovascular disease APOE Supplemental vitamins 

the 3

2nd q

3.183rd q

2.314th q

Flavof AD quarNo squaroxidaHighantioincremixecomgrouAuthdietanot a

Luchsinger et al., 200365

Community cohort (980) 

4 (SD 1.5) years 242 AD cases 

Daily dietary, supplement and total intake of carotenes, and vitamins C and E estimated from self-reported responses on semi-quantitative food frequency questionnaire 

NINCDS-ADRDA DSM 

Age Sex Educational level APOE Smoking 

ComquarsuppCaroassointakVitamwith quarVitamwith quarComquarand Vitamwith 

39
Study Sample (n) Followup/ 

Events 

Exposure Case definition Confounding 

adjustment 

Resu

quarVitamwith quar

Masaki et al., 200066 Community cohort (but 

also some nursing home residents) (3385) 

3 to 5 years for main analyses (subgroup of long term users 11 to 13 years) 47 AD cases 

Self-reported responses to a mailed survey asking whether they had taken multivitamins or additional vitamin A, C, or E pills in the prior year. Details on number of pills taken each week were collected. Categorized as C and E supplement users when the number of pills taken each week was greater than zero. 

NINCDS-ADRDA DSM 

Age Educational level Childhood years spent in Japan APOE History of stroke 

Comnot tof AD who E (Onor fwithonor v0.91 

Maxwell et al., 200567 Community cohort (but 

also some nursing home residents) (894) 

Approximately 5 years 107 AD cases 

For non-institutionalized individuals, self-reported information on supplemental vitamin E and C use. Sometimes confirmed by review of medication bottle. For institutionalized individuals, information on supplemental vitamin E and C use from medical record. 

NINCDS-ADRDA DSM 

Age Sex Educational level Blood pressure Baseline cognitive status Institutional residence 

Comwas (adjuto1.8Use asso

Morris et al., 199868 Community cohort 

(633) 

4.3 years 91 AD cases 

Supplemental vitamin E and C use from self-reported information on medications taken in the previous 2 weeks. Confirmed by visual examination of medication bottles. 

NINCDS-ADRDA Age 

Sex Educational level Time to followup Sample weight 

FewcaseNo dincidamo

Morris et al., 200269 Community cohort 

(815) 

3.9 years 131 AD cases 

Estimates of total intake of vitamins E and C during the previous year were calculated from self-report responses on a modified Harvard food frequency questionnaire 

NINCDS-ADRDA Age 

Race Sex Educational level APOE 

For vonly the hintakrisk oto 0.0.05

40
Study Sample (n) Followup/ 

Events 

Exposure Case definition Confounding 

adjustment 

Resu

Time interval to followup Vitam

suppwith Vitamonly assotrend signiasso(RR Vitamsuppwith For bof fosupprisk oAmovitamassoof AD (quinto 0.vitamagai

Morris et al., 200570 Community cohort 

(1041) 

2.7 years 162 AD cases 

Estimates of total food intake for all eight forms of vitamin E from food during the previous year were calculated from self-report responses on a modified Harvard food frequency questionnaire 

NINCDS-ADRDA Age 

Race Sex Educational level APOE Cognitive activities Observation interval Saturated fat Trans unsaturated fat DHA Vitamin C 

Lowehigh Vitamto 0.Gam0.41 Deltato 0.Alph0.56

41
42

Study Sample (n) Followup/ 

Events 

Exposure Case definition Confounding 

adjustment 

Resu

Zandi et al., 200471 Community cohort 

(3227) 

3 years 104 AD cases 

Self-reported use of supplemental vitamin E and C during the preceding 2 weeks. Confirmed by review of medication containers. Vitamin E users defined as those taking a multivitamin or vitamin E supplemental containing more than 400 IU. Vitamin C users defined as taking vitamin C supplements or multivitamin preparations containing at least 500 mg of ascorbic acid. Multivitamin users defined as use of a multivitamin preparation containing lower doses of vitamin E or C. 

NINCDS-ADRDA DSM 

Age Sex Educational level APOE General health status 

ReduassoE an0.09 No sincidvitamB-cocomvitam

Abbreviations: AD = Alzheimer’s disease; APOE = apolipoprotein E gene; APOE e4 = e4 allele of the apolipoprotein E gene; BMI = body mass inde

DHA = docosahexaenoic acid; DSM = Diagnostic and Statistical Manual of Mental Disorders; HR = hazard ratio; NINCDS-ADRDA = National Instit

Communicative Diseases and Stroke-Alzheimer's Disease and Related Disorders Association; OR = odds ratio; RR = relative risk; SD = standard devi
Gingko biloba. We did not identify any eligible studies examining risk of AD in relation to 

use of gingko biloba supplements. 

Omega-3 fatty acids. We identified two good quality systematic reviews evaluating the 

association between omega-3 fatty acids and risk of Alzheimer’s disease.29,30 We focus the 

discussion on the more recent (2009) review by Fotuhi et al.29 The review included seven 

prospective cohort studies described in nine publications dating from 1997 to 2008.60,72-79 The 

seven studies included a total of 18,922 subjects; three were conducted in the United States, three 

in European countries, and one in Canada (Table 6). Prospective observational studies or trials 

were selected that addressed the specific association between any form of omega-3 fatty acids 

and dementia in participants age 65 or older, and that used standard diagnosis of dementia. The 

number of individuals with AD versus other dementias was available, and all studies met our 

eligibility threshold of at least 60 percent with AD. There was not a structured quality assessment 

of studies reported in this systematic review; however study characteristics for key design 

variables were reported, and study selection criteria focused the review on higher quality studies. 

Length of followup ranged from 3.9 to 7 years. No information was given on followup rates. 

Covariate adjustment included age, sex, and education, and many studies included additional 

covariates such as the apolipoprotein E gene (APOE), other nutritional factors, and income. 

Covariate adjustment for education and income may be particularly important as several studies 

reported an association between fish consumption and higher incomes and education. Both 

unadjusted and adjusted results were reported. Omega-3 fatty acid intake was estimated by 

dietary histories in six studies; one74 measured serum polyunsaturated fatty acids (PUFAs) and 

one reported plasma PUFAs in a subsample.79 Most studies focused on fish consumption to 

estimate omega-3 fatty acids without considering other dietary sources or fish oil supplements. 

Exposure classification varied substantially ranging from a simple count of the frequency of fish 

servings per week to estimates of the number of grams consumed per day. Because of significant 

study heterogeneity in study design, results were synthesized qualitatively. 

Study characteristics and results are summarized in Table 6. There was no consistent 

association between omega-3 fatty acid intake and incident AD. Three of the seven cohort 

studies showed that fish consumption was associated with a statistically significant reduced risk 

of AD;73,75,78 three did not show a statistically significant association,72,76,77 although the point 

estimate favored a lower risk in two studies; and one small study74 showed higher serum PUFAs 

in subjects who developed dementia. Two studies examined the interaction between fish intake 

and APOE, one showing no interaction,78 and one showing an interaction where increased fish 

consumption decreased risk of AD only in those who were non-carriers of the epsilon 4 allele of 

the apolipoprotein E gene (APOE-e4).76 There was substantial heterogeneity in how omega-3 

consumption was assessed, including differences in the types of fish (e.g., fatty versus non-fatty), 

dosage, and duration of use. Most studies focused only on long-chain omega-3 fatty acids and 

not on specific fatty acids (e.g., docosahexaenoic acid [DHA]) or the ratio of omega-3 to omega6 fatty acids, a ratio that has been linked to some cardiovascular outcomes. The variability in 

exposure intake may be an important contributor to inconsistent study findings. The authors 

concluded that the existing data do not favor a role for long-chain omega-3 fatty acids in 

preventing dementia, including AD. 

43
Table 6. Omega-3 fatty acids and risk of developing AD – study characteristics and results from studies reviewed by Fotuhi et a

Study Sample size (n) Followup/ 

Events 

Exposure Case definition Confounding adjustment Results 

Kalmijn et al., 199772

and Englehart et al., 200260

Community cohort (5386) 

2.1 years 58 dementia (42 AD) 

Fat intake by history at baseline (n-3 PUFAs estimated by fish intake; n-6 PUFA estimated by linoleic acid intake) 

DSM NINCDS-ADRDA 72% of dementia cases classified as AD 

Age Sex Education Total energy intake 

Higher flower risg/day: R3 to 18.0.4 to 1g/day). Higher lassocia15.0 g/dto 1.2), 95% CI 9.5 g/da

BarbergerGateau et al., 200273

Community cohort (1416) 

7 years 170 (130 AD) 

Fish intake by dietary history 

DSM Age 

Sex Education 

RR for A1.01) 

Laurin et al., 200374 Community cohort 

(79) 

5 years 11 dementia 

Total serum PUFAs and omega-3 PUFAs 

DSM NINCDS-ADRDA 

Age Sex Education APOE Smoking Alcohol use Cardiovascular disease BMI 

ParticipdementconcentPUFAs total PU

Morris et al., 200375 Community cohort 

(815) 

3.9 years 131 AD 

Fish, total n-3 fatty acids, EPA, linolenic acid by dietary history 

NINCDS-ADRDA Age 

Race Sex Education APOE Time to followup 

Higher fof AD: ≥ 2 time0.2 to 0Once w1 to 3 ti1.3 comHigher t

44
45

Study Sample size (n) Followup/ 

Events 

Exposure Case definition Confounding adjustment Results 

higher Dlinolenic decreas

Huang et al., 200576 Community cohort 

(2233) 

9 years 190 AD 

Fried fish and Fatty fish intake by dietary history (servings/week) 

NINCDS-ADRDA Age 

Race Sex Education Income APOE Total energy intake BMI Study site 

Fried fis0.25 to (95% C≥ 2 servto 1.52) Tuna or with AD0.25 to (0.54 to 2-4 servto 1.17)0.69 (0.

Schaefer et al., 200677 Community cohort 

(899) 

9.1 years 99 dementia (71 AD) 

DHA by dietary history and plasma levels (quartiles); fish intake by dietary history 

DSM NINCDS-ADRDA 

Age Sex Education APOE Homocysteine 

Highest levels (R1.18), d0.62, 0.twice we1.33) coquartiles reduced 

BarbergerGateau, et al., 200778

and Samieri et al., 200879

Community cohort (8085; 1214 in substudy) 

3.48 years 281 dementia (183 AD) 

Fish and other dietary sources of omega-3 by dietary history; Plasma PUFAs in subsample 

DSM NINCDS-ADRDA 

Age Sex APOE e4 Education Income Marital status BMI Diabetes 

Fish onCI 0.46 Plasma inverseldement2-3 timeto 0.94) ≥ 4 timeto 1.34) 

Abbreviations: AD = Alzheimer’s disease; APOE = apolipoprotein E gene; APOE e4 = e4 allele of the apolipoprotein E gene; BMI = body mass inde

DHA = docosahexaenoic acid; DSM = Diagnostic and Statistical Manual of Mental Disorders; EPA = eicosapentaenoic acid; HR = hazard ratio; NINC

Institute of Neurological and Communicative Diseases and Stroke-Alzheimer's Disease and Related Disorders Association; PUFA(s) = polyunsaturate

risk; SD = standard deviation 
46

We identified two additional eligible studies published after the above-described review 

appeared (Table 7). Devore and colleagues80 prospectively followed 5396 subjects from 

Rotterdam for a mean of 9.6 years. Fish and other dietary sources of omega-3 were assessed at 

baseline using a dietary history. Kroger and colleagues81 used a nested case-control design to 

evaluate the association between blood and erythrocyte membrane PUFAs and AD in a 

community sample from Canada. This represents an updated analysis of the study by Laurin et 

al.,74 which was included in the 2009 systematic review described above.29 Only 15 percent of 

the overall sample provided blood samples, potentially introducing selection bias. Both studies 

established AD using the National Institute of Neurological and Communicative Diseases and 

Stroke-Alzheimer’s Disease and Related Disorders Association (NINCDS-ADRDA) criteria and 

controlled for multiple potential confounders including age, educational level, and vascular risk 

factors. Neither study found an association between fish intake, total PUFAs, DHA, or 

eicosapentaenoic acid (EPA). 

In summary, a previous systematic review of seven prospective studies concluded that there 

was no consistent association between PUFAs, usually estimate by dietary histories of fish 

consumption, and incident AD. Results from a relatively large observational study with longerterm followup published since the 2009 systematic review, and from a reanalysis of a previously 

published study, are consistent with this conclusion. 
Table 7. Omega-3 fatty acids and risk of developing AD – recent cohort studies 

Study Sample size (n) Followup/ 

Events 

Exposure Case definition Confounding adjustment Results 

Devore et al., 200980 Community cohort 

(5395) 

Mean 9.6 years 365 AD of total 465 incident dementia 

Total and fatty fish intake at baseline PUFAs at baseline by food frequency questionnaire 

NINCDS-ADRDA Age 

Sex Education Total energy intake Alcohol BMI Total cholesterol Dietary vitamin E Supplement use Vascular risk factors 

AD risk HR 0.99 No assoomega-

Kroger et al., 200981 Community cohort 

(663) 

Median 4.9 years 105 AD of total 149 incident dementia 

Blood total and erythrocyte membrane PUFAs at baseline 

NINCDS-ADRDA Age 

Sex Education Alcohol BMI Vascular risk factors 

No assoAD with AD risk PUFA: 1.98) 

History of depression Family history of dementia 

Abbreviations: AD = Alzheimer’s disease; BMI = body mass index; CI = confidence interval; DHA = docosahexaenoic acid; EPA = eicosapentaenoic NINCDS-ADRDA = National Institute of Neurological and Communicative Diseases and Stroke-Alzheimer's Disease and Related Disorders Associat

polyunsaturated fatty acid(s); RR = relative risk 

47
Other fats. We identified two eligible cohort studies examining risk of AD in relation to 

intake of various types of fat.82,83 These studies are summarized in Table 8; detailed evidence 

tables are provided in Appendix B. One study used a community sample in the United States,82

and the other used a community sample in Europe.83 Length of followup ranged from 3.9 to 21 

years. In one study, 82 exposure was determined based on self-reported information from a semiquantitative food frequency questionnaire in late-life. Based on a validation substudy, the authors 

reported the Pearson correlations for comparative validity with 24-hour dietary recalls were 0.40 

for monounsaturated fat, 0.47 for saturated fat, 0.36 for polyunsaturated fat, and 0.39 for 

cholesterol. In the other study,83 exposure was determined based on a self-reported, 20-question, 

multiple-choice questionnaire completed in mid-life.83 This study estimated the total fat intake 

from milk products and dairy product spreads based on questionnaire responses. Both studies 

used sample selection methods to minimize selection bias, but only one compared baseline 

characteristics by exposure level.82 Investigators used standard criteria for the diagnosis of AD, 

but they did not use an informant report as part of the diagnostic process. One study stated that 

dementia diagnosis was assigned blind to the exposure level;82 it is assumed here that this was 

also the case in the other study.83 Analyses were appropriate and controlled for relevant potential 

confounders in one study,82 and partially controlled for potential confounders in the other 

study.83 

The study assessing mid-life dietary fat intake83 did not find a significant association between 

risk of AD and intake of total fat, polyunsaturated fats, or monounsaturated fats. Investigators 

did report significant increased risk of AD associated with the 2nd quartile of saturated fat intake 

compared with the 1st quartile; however, this increased risk did not hold up across the top two 

quartiles, raising questions about the robustness of the result. The study assessing later life 

dietary fat intake82 reported increased risk of AD associated with increased intake of saturated 

fats and trans-unsaturated fats, and a decreased risk of incident AD associated with higher intake 

of w-6 polyunsaturated fats. Differences between the studies in how the level of exposure was 

determined and the time when the exposure occurred may explain the discrepant results, but such 

fundamental differences also make it difficult to draw conclusions from these two studies. The 

study by Morris and colleagues82 used the most detailed dietary intake data. Giving weight to this 

study based on the data quality, there are preliminary data that saturated fats and transunsaturated fats may contribute to an increased risk of AD. Confirmation of these findings is 

needed. 

48
Table 8. Intake of various types of fat and risk of developing AD 

Study Sample (n) Followup/ 

Events 

Exposure Case definition Confounding 

adjustment 

Results 

Morris et al., 200382 Community cohort 

(815) 

Mean 3.9 years 131 AD cases 

Self-reported responses on a revised Harvard self administered food-frequency questionnaire 

NINCDS-ADRDA Age 

Race Sex Educational level APOE 

Saturated fat: Highest qincreased risk of AD: RTrans-unsaturated fat: of AD, but only quintiles (2.9; 1.2 to 7.2) significaw-6 polyunsaturated fatof AD (0.3; 0.1 to 0.8) Monounsaturated fat, tocholesterol not associatAnimal fat and vegetablAD in multivariable modfat controlled for other dlinear trend (p = 0.002) (although the RR for indsignificant). The p value for trend waother type of fat. 

Laitinen et al., 200683 Community cohort 

(1449) 

Mean 21 years 48 AD cases 

Self-reported responses on 20 multiple choice questions about dietary habits 

NINCDS-ADRDA DSM 

Age (midlife) Sex Educational level Followup time Milk fat and other types of fats from spreads 

Total fat: 2nd, 3rd and 4t

intake was not associateAD (compared to 1st qua

PUFA: 2nd, 3rd and 4th qfrom spreads not associn fully adjusted models MUFA: 2nd, 3rd and 4th q

from spreads was not arisk of AD (compared to 

Midlife vascular risk factors SFA: 2nd quartile of SFA 

associated with increase1st quartile) OR 3.82 (95and 4th quartiles not ass

risk 

APOE History of vascular disorders collected at followup 

Abbreviations: AD = Alzheimer’s disease; APOE = apolipoprotein E gene; CI = confidence interval; MUFA = monounsaturated fatty acid; NINCDS-

of Neurological and Communicative Diseases and Stroke-Alzheimer's Disease and Related Disorders Association; PUFA = polyunsaturated fatty acid

saturated fatty acid 

49
Trace metals. We identified no systematic reviews or studies evaluating a potential 

association between trace metals and reduction of risk of Alzheimer’s disease. 

Mediterranean diet. We identified four eligible cohort studies examining risk of AD and the 

Mediterranean diet.84-87 The Mediterranean diet is characterized by high intake of vegetables, 

legumes, fruits, and cereals; high intake of unsaturated fatty acids (mostly in the form of olive 

oil), but low intake of saturated fatty acids; a moderately high intake of fish; a low-to-moderate 

intake of dairy products (mostly cheese or yogurt); a low intake of meat and poultry; and a 

regular but moderate amount of alcohol, primarily in the form of wine and generally during 

meals. The included studies are summarized in Table 9; detailed evidence tables are provided in 

Appendix B. One study87 used a community sample in Europe. The three other studies84-86 were 

based on the same community sample in the United States, but they address slightly different 

outcomes or exposures. One study assessed the association between AD and the Mediterranean 

diet,84 one assessed the association between progression from MCI to AD and the Mediterranean 

diet,86 and one assessed the association between AD and the Mediterranean diet and physical 

activity combined.85 For all of the studies, participants were non-demented at baseline, but for 

one86 some of the participants were retrospectively assigned a diagnosis of MCI at baseline. 

Length of followup ranged from an average of 4 to 7 years. Exposure was determined based on 

self-reported information from a semi-quantitative food frequency questionnaire. Both studies 

used similar methods to calculate a Mediterranean diet score based on the responses on this 

questionnaire. Investigators in all studies noted that they had previously reported that this 

questionnaire has adequate validity and reliability based on substudies of segments of the 

questionnaire. All of the studies used sample selection methods to minimize selection bias and 

compared baseline characteristics by exposure level. Investigators used standard criteria for the 

diagnosis of AD, but did not use an informant report as part of the diagnostic process. One study 

applied diagnostic criteria for MCI retrospectively.86 It is assumed here that the dementia and 

MCI diagnoses were assigned blind to the exposure level, but this information was not provided 

in some of the publications. Analyses were appropriate and controlled for relevant potential 

confounders. 

The three publications based on the single cohort84-86 reported fairly consistent results 

regarding the association between higher compliance with a Mediterranean diet and a 

significantly lower risk of incident AD. The studies reported significant trend effects, suggesting 

a dose-response pattern. The study on this cohort examining the progression of MCI to dementia 

found that higher adherence to a Mediterranean diet was associated with a lower risk of 

progressing from MCI to AD.86 Another study on this cohort examined the combination of 

physical activity and diet; the authors reported that a lower risk of AD was associated with those 

who both highly adhered to a Mediterranean diet and participated in much physical activity. Low 

adherence to a Mediterranean diet combined with high levels of physical activity, or vice versa, 

did not provide a protective association for AD. The one study on a separate sample87 reported a 

hazard ratio in the direction indicating that high adherence to a Mediterranean diet was 

associated with lower risk of AD, but the hazard ratio did not meet standard significance levels. 

The authors of this manuscript noted that the sample had limited power to detect an association, 

and this may explain their null finding. 

In conclusion, multiple studies on one cohort reported that high adherence to a Mediterranean 

diet is associated with lower risk of AD; one study on a separate sample did not replicate this 

finding, but this may be due to lack of statistical power. Confirmation of the reported protective 

association of a Mediterranean diet is needed using an independent sample. 

50
Table 9. Mediterranean diet and risk of developing AD 

Study Sample (n) Followup/ 

Events 

Exposure Case definition Confounding adjustment Results 

Scarmeas et al., 200684

Community cohort (2258) 

Mean 4.0 (3.0) years 262 AD cases 

Self-reported responses on a food frequency questionnaire 

NINCDS-ADRDA DSM 

Age Race Sex Educational level Sample cohort APOE Caloric intake Smoking Medical comorbidity index BMI

Higher adherediet was assocof AD: Continuous mediet: HR 0.91 Categorical meHigh tertile (HR 0.007 for trend 

Scarmeas, et al., 200985

Community cohort (1880) 

Mean 5.4 (3.3) years 282 AD cases 

Self-reported responses on a food frequency questionnaire and selfreported responses on a leisure time exercise questionnaire 

NINCDS-ADRDA DSM 

Race Sex Educational level BMI Smoking Depression Leisure activities Comorbid medical conditions Baseline CDR score APOE Interval between 1st dietary 

and 1st physical activity 

measure Caloric intake

Higher adhereMediterranean associated with Considered simscore (compar0.60 (95% CI, And much phywith no physicaCI, 0.47 to 0.95Absolute risk fowith both low dactivity, compaof 12% for indiscore and high (95% CI, 0.44 

Scarmeas, et al., 200986

Community cohort (1875) 

Mean 4.5 (2.7) years 275 incident MCI cases 107 incident 

Self-reported responses on a food frequency questionnaire 

NINCDS-ADRDA DSM MCI criteria applied currently accepted diagnostic criteria to previously collected data 

Age Race Sex Education APOE BMI 

Compared to lofor progression middle tertile d0.34 to 0.90) ascore = 0.52 (9

51
52

Study Sample (n) Followup/ 

Events 

Exposure Case definition Confounding adjustment Results 

AD cases Interval between dietary 

assessment and cognitive assessment

Feart et al. 200987 Community cohort 

(1410) 

7 years 66 AD cases 

Self-reported responses on a food frequency questionnaire 

DSM Age 

Sex Education Marital Status Energy Intake Physical Activity Depressive symptomatology Taking 5 medications or more APOE Cardiovascular risk factors Stroke

High MediterraHR 0.86 (95% middle scores to1.94), compawere not assocAD 

Abbreviations: AD = Alzheimer’s disease; APOE = apolipoprotein E gene; BMI = body mass index; CI = confidence interval; DSM = Diagnostic and 

Disorders; HR = hazard ratio; NINCDS-ADRDA = National Institute of Neurological and Communicative Diseases and Stroke-Alzheimer's Disease a

Association 
Fruit and vegetable intake. We identified two eligible cohort studies examining risk of AD 

in relation to intake of fruit and vegetables88or intake of fruit and vegetable juices containing a 

high concentration of polyphenols.89 These studies are summarized in Table 10; detailed 

evidence tables are provided in Appendix B. One study89 used a community sample in the United 

States, and the other used a twin registry in Europe.88 Length of followup ranged from an 

average of 6.3 to 31.5 years. In one study,88 exposure was determined based on self-reported 

responses to one question on fruit and vegetable consumption; in the other study,89 exposure was 

determined by self-reported information from a semi-quantitative food frequency questionnaire. 

The investigators conducted a validation study of the questionnaire and found low to moderate 

correlations (0.42 to 0.77) between food records and responses on the food frequency 

questionnaire for major nutrient groups for the ethnic groups included in the study. Both studies 

used sample selection methods to minimize selection bias, and one89 compared baseline 

characteristics by exposure level. Investigators used standard criteria for the diagnosis of AD, but 

only one of the studies89 used an informant report as part of the diagnostic process. Only one 

study88 reported that the dementia diagnosis was assigned blind to the exposure level, but since 

this type of exposure is not typically discussed as part of the dementia assessment and diagnosis 

process, it is assumed here that the diagnosis was assigned blind to exposure in both studies. 

Analyses were appropriate and controlled for relevant potential confounders. 

One of the studies reported that medium to great fruit and vegetable intake in mid-life was 

associated in lower risk of AD in late life.88 This association was present in women, but not in 

men. It was also present in individuals with angina, but not in those without angina. This study 

used a crude measure (one self-report question) to determine exposure. The other study showed 

that intake of fruit or vegetable juice at least three times per week in later life, compared to less 

than once per week, was associated with reduced risk of incident AD.89 A significant trend was 

noted, suggesting a dose-response pattern. 

In conclusion, these two studies offer preliminary evidence that higher intake of fruit and 

vegetable juices throughout adult life may provide benefits for preventing AD, but the findings 

need to be confirmed.

53
Table 10. Intake of fruit and vegetables and risk of developing AD 

Study Sample (n) Followup/ 

Events 

Exposure Case definition Confounding adjustment Results 

Dai et al., 200689 Community cohort 

(1589)

Mean 6.3 years (SD 2.6) 63 AD cases 

Fruit and vegetable juice intake estimated from self-reported, self-administered semi-quantitative food frequency questionnaire 

NINCDS-ADRDA DSM 

Age Sex Educational level Baseline cognitive status Physical activity BMI Olfaction diagnostic group Total energy intake Intake of types of fat APOE Smoking Alcohol use Vitamin C, E, and multivitamin supplement use 

Individuals who juice at least olikely to get AD HR for 1 to 2/w2.29) HR for ≥ 3/wee

Hughes et al., 200988

Other – Twin Registry cohort (3779) 

Mean 31.5 years (SD 0.91) 

Self report response on one question about fruit and vegetable consumption 

NINCDS-ADRDA DSM 

Age Sex Educational level Smoking Alcohol use Exercise BMI Angina Marital status Total food intake 

Medium or greintake in mid-lirisk of AD (OR 

Medium or greintake in mid-lirisk of AD in w0.73) but not m(0.21 to 0.98). Medium or greintake in mid-lirisk of AD in th0.16 to 0.65), bangina. Interac0.95). 

Abbreviations: AD = Alzheimer’s disease; APOE = Apolipoprotein E gene; BMI = body mass index; CI = confidence interval; DSM = Diagnostic an

Mental Disorders; HR = hazard ratio; NINCDS-ADRDA = National Institute of Neurological and Communicative Diseases and Stroke-Alzheimer's D

Association; OR = odds ratio; SD = standard deviation

54
Total intake of calories, carbohydrates, fats, and proteins. We identified one eligible 

cohort study examining risk of AD and total intake of calories, carbohydrates, fats, and protein.90

This study is summarized in Table 11; a detailed evidence table is provided in Appendix B. The 

study used a community sample in the United States. Length of followup averaged 4 years. 

Participants were non-demented at baseline. Exposure was determined based on self-reported 

information from a semi-quantitative food frequency questionnaire. The validity of the 

questionnaire used in this study was assessed previously in a subsample of individuals using two 

7-day food records as the criterion. The intra-class correlations for energy-adjusted nutrients 

were 0.30 for total calories, 0.28 for carbohydrates, 0.41 for fats, and 0.33 for protein, based on 

energy-adjusted nutrient intakes. The study used sample selection methods to minimize selection 

bias and it compared baseline characteristics by exposure level. Investigators used standard 

criteria for the diagnosis of AD, but did not use an informant report as part of the diagnostic 

process. It was not reported whether the dementia diagnosis was assigned blind to the exposure 

level, but it is unlikely that this type of information would have been discussed during the 

diagnostic process. Analyses were appropriate and controlled for relevant potential confounders. 

This study reported that higher caloric intake was associated with higher risk of incident AD. 

There was no association between AD risk and intake amounts of carbohydrates, fats, or protein. 

In analyses stratified by APOE e4 allele status, both total calorie intake and fat intake were 

associated with high risk of AD. 

In conclusion, the findings from this single study are somewhat difficult to interpret given the 

hazard ratio (HR) < 2, which may suggest that residual confounding explains the association and 

the relatively low correlations reported in the study’s validation of the instrument used to collect 

exposure. In addition, these findings may be inconsistent with other studies reporting that weight 

loss may be an antecedent of AD. However, the findings do suggest that high caloric intake may 

be an aspect of diet that should be investigated further in regards to its association with risk of 

AD. 

55
Table 11. Total intake of calories, carbohydrates, fats, and protein and risk of developing AD 

Study Sample (n) Followup/ 

Events 

Exposure Case definition Confounding 

adjustment 

Results 

Luchsinger et al., 200290

Community cohort (980) 

Mean 4 (SD 1.5) years 242 AD cases 

Self-reported responses on a food frequency questionnaire 

NINCDS-ADRDA DSM 

Age Total daily calories: 

increased risk of AD 2.19) 

Race Sex 

Carbohydrates: No 

Educational level 

Fats: No association 

APOE 

Protein: No associaOnly APOE e4 positAD for: Total calories: Quar4.68); p value for treFats: Quartile 4 HR value for trend = 0.0

Abbreviations: AD = Alzheimer’s disease; APOE = apolipoprotein E gene; APOE e4 = e 4 allele of the apolipoprotein E gene; CI = confidence interv

Statistical Manual of Mental Disorders; HR = hazard ratio; NINCDS-ADRDA = National Institute of Neurological and Communicative Diseases and 

and Related Disorders Association; SD = standard deviation 

56
Medical Factors 

Vascular factors. Factors considered under this heading include diabetes mellitus, metabolic 

syndrome, hypertension, hyperlipidemia, and homocysteine. 

Diabetes mellitus. We identified two good quality systematic reviews that examined the 

association between diabetes mellitus and the development of AD.41,42 The review by Biessels 

and colleagues41 included 11 cohort studies (101,972 subjects); five were from the United States, 

four from Western Europe, one from Canada, and one from Japan. Publication dates ranged 

between 1989 and 2005. Studies were selected that were longitudinal, had subjects recruited at 

the population level, and where the incidence of dementia could be compared between subjects 

with and without diabetes mellitus. Studies that included people with cognitive impairments but 

not dementia were excluded, as were studies of the prevalence of diabetes in patients with 

dementia. Data were presented for the effect of diabetes on any dementia, vascular dementia, and 

Alzheimer’s disease, but the focus here is on Alzheimer’s disease. 

The review authors reported that the quality for cohort designs was fair to good, with 9 of 11 

studies receiving a score of at least 6 points out of 10 using a scale that judged population 

selection and recruitment, participation at followup, dementia assessment and diagnosis, and data 

analysis. Length of study followup ranged from 2.1 to 35 years, with the age of recruited subjects 

ranging from 45 to 84 years. Diagnosis of diabetes varied. Six studies relied on medical history 

or medication use and did not assess blood glucose concentration in all participants. The 

prevalence of diabetes ranged from 8.8 percent to 35 percent of the study population. Six studies 

also assessed diabetes only at baseline, making it likely that a number of subjects who developed 

incident diabetes were assigned to the non-diabetic group. Studies did not distinguish between 

type 1 and 2 diabetes, but since all participants were middle-aged or older adults and type 2 

diabetes predominates in this age group, almost all were likely to have type 2 diabetes. Data for 

diabetes duration, hemoglobin A1c, and microvascular complications were not regularly reported. 

Most studies used the Diagnostic and Statistical Manual of Mental Disorders (DSM) III or IV 

criteria for the diagnosis of dementia and NINCDS-ADRDA criteria for AD. Six studies relied 

on a consensus committee to establish a diagnosis of dementia. 

Biessels et al. did not combine data because of variability of study design, and assessment of 

heterogeneity was not reported.41 The possibility of publication bias was considered, but a funnel 

plot was not performed. Covariates commonly considered included age, sex, education, and, in 

some studies, baseline cognitive performance and cardiovascular risk factors. Nine of 10 studies 

reported that participants with diabetes had an increased risk of developing Alzheimer’s disease, 

with relative risk, odds ratios, or hazard ratios greater than 1 (range 1.2 to 2.4), and with 95 

percent confidence intervals > 1.0 in five studies. Adjustment for vascular risk factors was 

examined in five studies; four of the five reported a relative risk or hazard ratio greater than 1 

(range in all studies 0.8 to 2.0), but for only two of these did the adjusted HR exclude no effect. 

Two studies examined the risk of developing Alzheimer’s disease in individuals who had midlife 

assessment of diabetes status. Yamada et al.91 reported an odds ratio (OR) of 4.4 (p < 0.01), and 

Curb et al.92 reported a relative risk (RR) of 1.0 (95 percent confidence interval [CI] 0.5 to 2.0) 

for individuals with diabetes mellitus developing Alzheimer’s disease. 

Longitudinal studies in which diabetes and dementia were assessed in late life demonstrated 

fairly consistent results. Seven of 11 studies reported a 50 to 100 percent increase in the 

incidence of AD. Two studies examined the effect of APOE genotype and found that the 

presence of an e4 allele doubled the relative risk of dementia in diabetics compared to 

57
participants with either of these risk factors alone. The authors concluded the literature suggests 

that the risk of AD is increased in patients with diabetes mellitus.41

A subsequent systematic review and meta-analysis by Lu and colleagues identified reports 

from two additional cohort studies examining the association between diabetes mellitus and the 

incidence of AD.42 Akomolafe et al. reported results from 2210 participants in the Framingham 

study and found that diabetics had a non-statistically significant increase in risk compared to 

non-diabetics (RR 1.15; 95 percent CI 0.65 to 2.05).93 Similar results were found in the Cache 

County Study of Memory, Health and Aging, where the RR for AD in diabetics was reported to 

be 1.33 (95 percent CI 0.66 to 2.46).94 In their systematic review, Lu and colleagues,42 in contrast 

to Biessels and colleagues,41 judged that studies examining the effect of diabetes on dementia 

risk were sufficiently homogeneous, based on similar criteria for diagnosis and dementia, that 

meta-analysis was appropriate. They performed a meta-analysis on the adjusted relative risk of 

diabetics developing Alzheimer’s disease using data from eight longitudinal, prospective cohort 

studies. The combined RR, using a fixed-effect model, was 1.39 (95 percent CI 1.17 to 1.66). A 

test for heterogeneity did not reveal significant heterogeneity between studies (χ-squared Q-test 

statistic 3.269, df = 5; p = 0.659), and visual inspection of funnel plots and Egger’s test did not 

suggest publication bias. Lu and colleagues concluded, therefore, that diabetes mellitus was 

associated with an increased incidence of AD.42

We identified two additional studies on diabetes mellitus and the risk of developing AD that 

were published after the above-described systematic reviews (Table 12). Irie et al. examined the 

role of diabetes mellitus and APOE genotype on incidence of dementia in over 2000 participants 

in the Cardiovascular Health Study.95 They found that diabetes or inheritance of APOE e4 alone 

each increased the risk of developing AD (OR 1.62; 95 percent CI 0.98 to 2.67; and OR 2.50; 95 

percent CI 1.84 to 3.40, respectively) compared to individuals without diabetes or an APOE e4 

allele. The OR for subjects with both diabetes mellitus and an APOE e4 allele was 4.99 (95 

percent CI 2.70 to 9.20), which the author’s suggested was evidence for an interaction between 

the risk factors. Xu et al. prospectively followed 1248 subjects from the Kungsholmen Project 

for an average of 5.1 years.96 The average age of participants was approximately 82 years, and 

75 percent were women. In a fully adjusted model the hazard ratio of incident AD for individuals 

with borderline diabetes was 1.87 (95 percent CI 1.11 to 3.14), and for undiagnosed diabetes the 

HR was 3.29 (95 percent CI 1.20 to 9.01), indicating an increased risk of AD. The risk for 

subjects with diagnosed diabetes was not statistically different from the risk for non-diabetics. 

No analysis of dementia risk as a function of hemoglobin A1c level was reported. Xu and 

colleagues96 suggested several possible explanations for their findings that borderline and 

undiagnosed diabetes place subjects at greater risk for AD than those with diagnosed diabetes: 

The number of subjects with diagnosed diabetes and dementia was relatively small, limiting the 

statistical power to identify a significant association; diabetics – because they were aware of their 

condition – may have altered their lifestyle, while subjects with borderline or undiagnosed 

diabetes would not be aware of their condition and, therefore, would not have modified their 

lifestyle; and the degree of hyperinsulinemia and insulin resistance might be different in 

borderline and undiagnosed diabetics than in known diabetics. Hyperinsulinemia and insulin 

resistance have been implicated in AD pathogenesis. 

In summary, individual prospective, longitudinal cohort studies, two systematic reviews, and 

a meta-analysis all report an association between diabetes mellitus and incident Alzheimer’s 

disease, but results in individual studies vary. Studies also suggest that inheriting an APOE e4 

allele further increases the risk of AD in diabetics. Limitations of the included studies include 

58
59

variable criteria for diagnosis of diabetes, failure to consider duration of diabetes, and degree of 

glycemic control. Additional research examining the age of diabetes onset (mid-life versus latelife onset), comorbid conditions (such as vascular risk factors), type of treatment (diet versus oral 

versus insulin), and the role of hyperinsulinemia on dementia risk is needed. 
Table 12. Diabetes mellitus and risk of developing AD 

Study Sample (n) Followup/ 

Events 

Exposure Case definition Confounding 

adjustment 

Results 

Irie et al., 200895 Community cohort 

(2547 – 602 with APOE e4; 320 with DM) Random selection Medicare recipients aged > 65 in 4 counties 

Mean 5.4 years; range up to 10 years 

APOE genotype Diabetes mellitus 

NINDS/ADRDA Model 1: 

Age Race Educational level Model 2: Age Race Education HTN Total cholesterol Smoking Alcohol use BMI Depression status Ankle-brachial index Stroke 

HR (95% CI) for inciModel 1: DM only: 1.45 (0.89 APOE e4 only: 2.61 Both: 4.53 (2.47 to 8Model 2: DM only: 1.62 (0.98 APOE e4 only: 2.50 Both: 4.99 (2.70 to 9

Xu et al., 200996

Community cohort (1248) Registered inhabitants of Kungsholmen district, Stockholm, Sweden ≥75 years 

Mean 5.1 years. Maximum 10.5 years 

Diabetes mellitus NINDS/ADRDA Model 2: 

Age Sex Education Baseline MMSE score APOE genotype Survival BMI BP 

Risk of AD (HR [95% Non-diabetic: 1 (refeBorderline DM: 1.87 Diabetics with rando< 7.8 mmol/L: 0.34 7.7-11 mmol/L: 1.26 ≥ 11 mmol/L: 1.08 (Undiagnosed DM: 3Risk of AD with strokNon-diabetic: 1 (refeBorderline DM: 1.93 Undiagnosed DM: 3

60
61

Study Sample (n) Followup/ 

Events 

Exposure Case definition Confounding 

adjustment 

Results Risk of AD without v[95% CI): Non-diabetic: 1 (refeBorderline DM: 2.85 Undiagnosed DM: 4

Abbreviations: AD = Alzheimer’s disease; APOE = apolipoprotein E gene; APOE e4 = epsilon 4 allele of the apolipoprotein E gene; BMI = body ma

pressure; CI = confidence interval; DM = diabetes mellitus; HR = hazard ratio; HTN = hypertension 
Metabolic syndrome. We identified two longitudinal, prospective studies that examined the 

association between metabolic syndrome and incident AD (Table 13).97,98 Both studies were 

conducted in the United States and together they involved a total of 5603 subjects. Both studies 

recruited older adults from the community and used NINCDS-ADRDA criteria to establish a 

diagnosis of AD. Time between screening and followup ranged from 4.4 to 28 years, and the age 

range for the studies was comparable (mean 76 versus 78 years). Muller et al.,98 in the Northern 

Manhattan study, defined the metabolic syndrome according to National Cholesterol Education 

Program 3rd Adult Treatment Panel Guideline (NCEP-ATPIII), and Kalmijn et al.,97 in the 

Honolulu-Asia Aging Study (HAAS), used a novel definition (described below). The NCEPATPIII criteria require at least three of the following for a diagnosis of metabolic syndrome: 

1) Waist measurement > 88 cm for women or > 102 cm for men. 

2) Hypertriglyceridemia (≥ 150 mg/dL [≥ 1.69 mmol/L]). 

3) Low high density lipoprotein (HDL; men < 40 mg/dL [< 1.03 mmol/L]); women < 50 

mg/dL [< 1.29 mmol/L]). 

4) High blood pressure (systolic blood pressure [SBP] ≥ 130 mmHg; diastolic blood 

pressure [DBP] ≥ 85 mmHg) or currently using an antihypertensive medication. 

5) High fasting glucose (≥ 110 mg/dL [≥ 6.10 mmol/L]) or currently using anti-diabetic 

medication (insulin or oral agents). 

In contrast, HAAS defined metabolic syndrome as the sum of seven factors – increased body 

mass index (BMI), elevated total cholesterol, elevated triglycerides, elevated DBP and SBP, 

elevated random post-load glucose, and increased subscapular skinfold thickness – expressed as 

the individual’s z score for that risk factor (calculated as the value compared to the total 

population, assuming a normal distribution [-4 SD to +4 SD]; scores ranged between -12.8 to 

13.4, with higher scores indicative of the presence of more risk factors).97

The variation in definition of metabolic syndrome makes it difficult to compare results 

between studies. Comparisons are further limited because of sex and ethnic differences between 

the two studies. The Northern Manhattan population98 was predominantly female (67 percent), 

39 percent Caribbean Hispanic, 31 percent African-American, and 30 percent white, while 

HAAS97 was restricted to Japanese-American men. Fifty-five percent of the participants in the 

Northern Manhattan study had metabolic syndrome, and 29 percent of the HAAS participants 

had more than two elevated risk factors of the seven examined. Both studies adjusted for 

important confounders, such as age, sex, education, and baseline cognitive performance. Muller 

et al.98 reported baseline differences between participants with and without metabolic syndrome; 

subjects with metabolic syndrome were more likely to be female, Hispanic, smokers, and less 

educated. There was, however, no difference in the risk of developing AD (RR 0.9; 95 percent 

CI 0.6 to 1.3). Analysis of the components of metabolic syndrome revealed that only diabetes 

was associated with a statistically significant increase in total dementia (HR 1.6; 95 percent CI 

1.2 to 2.2), but the risk for AD did not reach statistical significance (HR 1.4; 95 percent CI 1.0 to 

2.1). The RR for AD per 1 unit increase in z-score sum of metabolic risk factors in HAAS was 

1.0 (95 percent CI 0.94 to 1.06), and for AD with cerebrovascular disease 1.04 (0.95 to 1.15).97

Investigators also divided z-scores into quartiles and found that there was a trend toward 

increased risk of dementia (all subtypes) in subjects assigned to quartiles 2, 3 and 4, but data 

were not presented for AD. 

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In summary, metabolic syndrome, using two different diagnostic criteria, is not associated 

with a higher risk of AD. These conclusions are limited by the small number of published 

studies, differences in the study populations, and the lack of uniform criteria used to diagnose 

metabolic syndrome. Additional analysis of subsets of risk factors included in metabolic 

syndrome may provide better insight into the validity of metabolic syndrome as a clinically valid 

construct for predicting dementia risk. 
Table 13. Metabolic syndrome and risk of developing AD 

Study Sample (n) Followup/ 

Events 

Exposure Case definition Confounding adjustment Results 

Kalmijn et al., 200097 Community cohort 

(3770) 

28 years 82 AD 

Metabolic syndrome, defined by the sum of Z scores (-4 to +4 SD, with mean 0) for each of 7 factors (see text, above, for details) 

NINCDS-ADRDA Age 

Sex Education Additional adjustment for occupation, alcohol consumption, smoking, BP medication, and years of childhood in Japan did not appreciably alter estimates of risk 

OR 1.0 (95unit increaz score 

Muller et al., 200798 Community NINCDS-ADRDA Age cohort 5.9 (1.6) years Metabolic syndrome 

according to National Cholesterol Education Program 3rd Adult 

Treatment Panel Guideline (NCEPATPIII; (see text, above, for details) 

Sex 

(1833) Race 

147 AD Education 

Ethnic group APOE allele Smoking 

HR 0.9 (95

Abbreviations: AD = Alzheimer’s disease; APOE = apolipoprotein E gene; BP = blood pressure; CI = confidence interval; HR = hazard ratio; NINCDInstitute of Neurological and Communicative Diseases and Stroke-Alzheimer's Disease and Related Disorders Association; OR = odds ratio; SD = stan

64
Hypertension. We did not identify any good quality systematic reviews evaluating 

hypertension and risk of developing AD. Our independent search identified 11 eligible 

publications,99-109 describing 10 different cohort studies that examined the association between 

hypertension and incident AD. These studies are summarized in Table 14; detailed evidence 

tables are provided in Appendix B. Seven studies were derived from community cohorts in the 

United States, of which two dealt specifically with subjects of Japanese descent.99,102 Subjects 

from the remaining three cohorts were from Finland, Sweden, and Canada. More than 18,700 

subjects were included, with 1511 incident cases of AD. Followup ranged from 5 to 27 years. All 

studies reported good procedures for determination of AD outcome. Only four studies102,106-108

reported results adjusted for antihypertensive use. Two other studies103,109 did check for 

interactions between antihypertensive medications and hypertension and stated that the change to 

reported results was minimal. 

Definitions of hypertension varied. Two of the studies used self-reported hypertension to 

establish exposure.104,105 Bias could be introduced by the subjects who are unaware of their 

hypertension, decreasing the likelihood of detecting an association. Neither study found an 

association between reported hypertension and incident AD. 

When SBP > 140 mmHg was used as a definition,99,101,106,107 the results were not statistically 

significant except for a single study101 that reported an adjusted OR of 1.97 (95 percent CI 1.03 

to 3.77) from a Scandinavian cohort (FINMONICA). An analysis of the HAAS cohort (discussed 

below) did find an association between never-treated hypertension, defined at 140 mmHg and 

compared to SBP < 120 mmHg, with non-specific dementia. When hypertension was defined as 

a SBP > 160 mmHg,100,102,103,107 only one of four studies100 found a significant result, again in an 

analysis of the FINMONICA cohort. The FINMONICA cohort measured blood pressure in midlife, 15 years prior to cognitive testing. 

The Religious Orders Study108 followed a cohort of retired catholic clergy and used blood 

pressure as a continuous variable. There was no relationship between SBP or DBP and incident 

AD. Results from this highly educated cohort may not be generalizable to others, as the mean 

SBP was 134 (64 percent had SBP < 140 mmHg), and the mean DBP was 75 (93 percent had 

DBP < 90 mmHg). 

It is possible that all the cohorts formed later in life99,103-108 had a selection bias in that if 

hypertension predisposes to AD and to death, those subjects with hypertension would have 

selectively died prior to cohort formation. By contrast, the FINMONICA cohort100,101 was 

followed for 21 years, and the HAAS cohort102 for 27 years. 

Measures of DBP also did not show robust associations with incident AD. Low DBP (< 70 

mmHg) was examined in the Kungsholmen cohort and was significantly associated with incident 

AD (RR 1.9; 95 percent CI 1.2 to 3.0).107 High DBP was examined as a risk factor in six studies 

(seven papers)100-103,107-109 and was not found to have a significant association with incident AD 

with the exception of subgroups of the HAAS cohort. The HAAS cohort102 was formed from the 

Honolulu Heart Program (1965 to 1971), when many hypertensive patients were not treated. 

Investigators found significantly elevated odds ratios for AD in those with untreated high DBP 

(OR 4.47; 95 percent CI 1.53 to 13.09), but not untreated high SBP (OR 1.22; 95 percent CI 0.37 

to 4.04). The HAAS cohort is distinguished by having the longest followup of these studies, with 

a mean of 27 years. In other analyses of the HAAS cohort,110 non-specific dementia was 

associated with never-treated hypertension, as defined by SBP > 140 mmHg (and compared to 

SBP < 120 mmHg), with a HR or 2.66 (95 percent CI 1.51 to 4.68). 

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66

In summary, in the cohorts described here, the association between blood pressure and 

incident AD was significant in only one cohort (the FINMONICA cohort100,101), with untreated 

diastolic hypertension significantly associated with incident AD in one other population (the 

HAAS cohort102). These two populations, however, were followed for a considerably longer 

period of time than the other cohorts. 
Table 14. Hypertension and risk of developing AD 

Study Sample (n) Followup/ 

Events 

Exposure Case definition Confounding 

adjustment 

Results 

Borenstein et al., 200599

Kame 

Community cohort (1859) 

6.0 years (2.7) 90 cases probable AD 

Directly measured and self-reported HTN Analysis seems to be based on measured BP, but also ran selfreported history of HTN as a categorical variable 

NINCDS-ADRDA DSM 

Age Race Sex APOE e4 Educational level Baseline cognitive status Developmental risk factors Vascular risk factors 

For subset with 

mmHg, HR for in0.82 to 3.8) 

Kivipelto et al., 2001100and Kivipelto et al., 2005101FINMONICA and others 

Community cohort (1449) 

Mean 21 years (4.9) Range 11 to 26 years 48 AD 

2001 study: Direct measure of BP (and cholesterol) SBP definitions (mmHg): Normal < 140 Borderline 140 to 159 High > 159 DBP definitions (mmHg): Normal < 90 Borderline 91 to 94 High > 94 2005 reanalysis: SBP > 140 used to define HTN 

NINCDS-ADRDA DSM 

2001 study: Age BMI Education History of MI History of cardiovascular symptoms Smoking Alcohol use 2005 reanalysis: Apparently no adjustment 

2001 study: OR (95% CI): Mid-life borderlinMid-life high SBMid-life borderlinMid-life high DB2005 reanalysisIndependent OR mmHg: 1.97 (1.

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Study Sample (n) Followup/ 

Events 

Exposure Case definition Confounding 

adjustment 

Results 

Launer et al., 2000102Honolulu Heart Program (HAAS) 

Community cohort (analytic sample of 3703) 

Mean 27 years 118 AD (197 demented, 79 vascular dementia) 

Direct measurement of BP and self-report of antihypertensives SBP ≥ 160 mmHg 

on at least two exam dates to meet criteria for HTN; otherwise, was considered mixed Same for DBP ≥

95 

NINCDS-ADRDA DSM 

Age (at the fourth exam) Education APOE Smoking (through exam 3) Alcohol use (at exam 3) CVA CHD Subclinical atherosclerosis Antihypertensive use 

High SBP (19651.22 (95% CI 0.3High SBP (19650.56 (95% CI 0.2Among untreate95% CI 1.53 to 1(3.49; 1.28 to 9.5(1.33; 0.54 to 3.2Among treated, DBP and AD: HCI 0.02 to 1.17), 0.17 to 3.00); m3.69) For dementia ovDBP (high and bdementia in untrgroup For dementia ovhigh SBP, but noassociated with not treated grou

Li et al., 2007103Adult changes in thought 

Community cohort  (2356) 

Up to 10 years 204 cases probable AD 

Direct measurement of BP at baseline 1994-96 SBP ≥ 160 mmHg 

NINCDS-ADRDA DSM 

Race (white/nonwhite) Sex Education Presence of at least one APOE e4 allele 

For SBP ≥ 160 m

AD: Age 65-74: 1.38 Age 75-84: 0.94 Age ≥ 85: 0.70 HR (95% CI) for 

compared to DBAge 65-74: 0.82 Age 75-84: 0.73 Age 85+: No caHR (95% CI) for mmHg compareAge 65-74: 1.71 

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Study Sample (n) Followup/ 

Events 

Exposure Case definition Confounding 

adjustment 

Results 

Age 75-84: 0.96 Age 85+: 1.58 (Not significant in 

Lindsay et al., 2002104CSHA 

Community cohort (4615) 

5 years 194 AD 

Not completely clear, but apparently history of HTN came from self-administered questionnaire completed by cognitively normal subjects 

NINCDS-ADRDA Age 

Sex Education 

OR 0.88 (95% C

Luchsinger et al., 2005105

Northern Manhattan 

Community cohort (1138) 

5.5 years (3.2) 246 probable or possible AD 

Self-reported HTN NINCDS-ADRDA Age 

Race Sex Educational level Baseline cognitive status Vascular disease Lipid values BMI 

RR for probable 2.6) RR for both prob1.5 (0.9 to 2.4) 

Posner et al., 2002106Washington Heights – Inwood Columbia Aging Project 

Community cohort (1249) 

Up to 7 years 157 AD 

Direct measurement and self-report SBP > 140 mmHg 

NINCDS-ADRDA Age 

Race Sex Educational level DM Heart disease (MI, CHF, angina) Antihypertensive use 

AD with a history 0.6 to 1.1) Treatment of HTestimates for ADNo treatment: RTreatment: RR 

Qiu et al., 2003107Kungsholmen 

Community cohort (966) 

Mean 5.7 years Range 0.1 to 8.2 years 

Direct measurement of BP and self-report of medications 

DSM Age 

Race Sex Educational level Baseline MMSE 

RR (95% CI): SBP 140-159: 1SBP ≥ 160: 1.4 DBP ≥ 90: 1.0 (DBP < 70: 1.9 (

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Study Sample (n) Followup/ 

Events 

Exposure Case definition Confounding 

adjustment 

Results 

204 AD SBP ≥ 140 mmHg Vascular disease 

(heart disease, CVD, DM) APOE genotype SBP DBP Antihypertensive use 

Antihypertensive Authors state: “no use of antihyAPOE e4 and syadjusted relative to 6.4) for subjecpressure > 140 b1.5 (0.7 to 3.2) fsystolic pressure 

Shah et al., 2006108Religious Orders Study 

Community cohort – sample of retired clergy (824) 

Mean of 6.5 annual exams 151 AD 

Direct measurement of BP BP used as a continuous variable 

NINCDS-ADRDA Age 

Sex Education APOE e4 Antihypertensive use 

In a fully adjusteAPOE e4, use oa “null relationshwere not shownand education, tincrease in SBP 1.00) and for DBFurther analysesquadratic terms categories of HTshowed no asso

Morris et al., 2001109Boston EPESE 

Community cohort (634) 

2 to 13 years 99 AD 

Direct measurement of blood pressure Analysis with blood pressure as a continuous and as a categorical variable 

NINCDS-ADRDA Age 

Sex Education APOE Clinical stroke Heart disease History of HTN DM BMI 

OR (95% CI) for years prior to diaSBP 140-149: 0SBP ≥ 160: 0.22 DBP ≥ 90: 0.79 OR (95% CI) for years before diaSBP ≥ 160: 1.13 DBP ≥ 90: 1.56 

Abbreviations: AD = Alzheimer’s disease; APOE = apolipoprotein E gene; APOE e4 = e 4 allele of the apolipoprotein E gene; BMI = body mass indeCHD = coronary heart disease; CHF = congestive heart failure; CI = confidence interval; CVA = cerebrovascular accident; CVD = cardiovascular disepressure; DM = diabetes mellitus; DSM = Diagnostic and Statistical Manual of Mental Disorders; HR = hazard ratio; HTN = hypertension; JNC VII = Joint National Committee on Prevention, Detection, Evaluation, and Treatment of High Blood Pressure; MI = myocardial infarction; MMSE = Mini-MNINCDS-ADRDA = National Institute of Neurological and Communicative Diseases and Stroke-Alzheimer's Disease and Related Disorders Associatrelative risk; SBP = systolic BP
Hyperlipidemia. We identified one good quality systematic review examining total 

cholesterol as a possible risk factor for AD.40 Eight included cohort studies, involving 14,331 

subjects, examined the association between incident AD and total cholesterol. Three of the 

studies used cholesterol measured in mid-life, one used the average of multiple cholesterol 

measurements over 30 years, and four used cholesterol measured in later life; for this reason, the 

studies were considered too heterogeneous to combine in a single analysis. Followup ranged 

from 4.8 to 29 years, with a mean of approximately 13 years. 

Four studies examined cholesterol as measured in mid-life as it relates to incident AD. One 

looked at the Framingham cohort.111 Cholesterol levels were averaged over the time of the study. 

No association was found between cholesterol measured in this way and incident AD. Another 

study112 found that a decreasing cholesterol level from mid- to late life was associated with 

increased risk of AD (β = -0.33; p = 0.03). Two studies found that high cholesterol in mid-life 

was associated with an increased risk of AD. Kivipelto et al.113 found that, in the FINMONICA 

(Finnish Multinational Monitoring of Trends and Determinants in Cardiovascular Disease) and 

North Karelia Project cohort, followed for a mean of 21 years (range 11 to 26 years), cholesterol 

≥ 6.5 mmol/L (251 mg/dL) in mid-life was associated with an OR of 2.8 (95 percent CI 1.2 to 

6.7) for incident AD in late life. Notkola et al.114 followed up 444 survivors from a cohort formed 

in 1959, checked after 5 to 30 years, and found an OR of 3.1 (1.2 to 8.5) for an average 

cholesterol ≥ 6.5 mmol/L for measured cholesterol in 1959, 1964, 1969, and 1974, when the 

cohort was mid-life. 

Four studies looked at late-life cholesterol and AD. Three studies were considered similar 

enough for fixed-effect meta-analysis.115-117 Combined sample size for these three was 10,195 

controls and 599 cases of incident AD. No difference was found between the lowest quartile of 

total cholesterol and any of the other quartiles in the incidence of AD. The relative risk (RR) 

between first and fourth quartile was 0.85 (95 percent CI 0.65 to 1.12; z = 1.17; n = 5526; p = 

0.24). Yoshitake et al.118 included both prevalent and incident cases of AD in their analysis and 

found that for each increase of one standard deviation in total cholesterol the relative risk for AD 

was 1.1 (0.80 to1.51). 

In summary, based on this systematic review, there is evidence to suggest that 

hypercholesterolemia in mid-life is associated with increased risk of AD later. There is no 

evidence in these studies to suggest that late-life cholesterol levels are related to incident AD. If 

mid-life but not late-life cholesterol is related to increased risk, then averaging cholesterol over 

decades of life, as was done with the Framingham cohort, would not be expected to show a 

relationship. 

Our search did not reveal any other prospective cohort studies meeting our inclusion criteria 

and addressing the relationship between hyperlipidemia and incident AD. 

Homocysteine. Our search identified four cohort studies, involving 2662 subjects, evaluating 

the association between homocysteine and incident AD (Table 15). Two cohorts were from U.S. 

communities,119,120 and two were from Western Europe;57,121 all studies recruited community 

samples. Three of the four cohorts analyzed frozen plasma from fasting subjects, which may give 

a better estimate of bioavailable folate than non-fasting samples. The fourth study121 did not 

specify whether subjects were fasting. The studies defined increased plasma homocysteine levels 

differently. Two studies57,120 compared the highest quartiles of homocysteine in their samples to 

the lowest quartile, one examined log-transformed homocysteine,119 and one compared those 

subjects whose homocysteine doubled over 2.5 years to all others.121 The duration of followup 

ranged from 1 to 13 years. Alzheimer’s disease was diagnosed using NINCDS-ADRDA criteria; 

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72

however, one study57 relied on telephone or informant interviews, medical records, or death 

certificates for 15 percent of the sample. All studies adjusted for potential confounders, but 

two57,119 had a large number of model variables compared to the number of incident cases of AD, 

which may decrease the replicability of their results. 

Three studies reported adjusted results for baseline homocysteine using approximately the 

same threshold (> 14 or >15 μmol/L).57,119,120 We combined these studies using a random-effects 

model (Figure 3). A test for heterogeneity suggested significant variability among studies (Q 

statistic = 6.378, p = 0.04, I2

 = 68.6 percent). We examined design features qualitatively and 

could not explain the variability. Elevated homocysteine levels were not associated with incident 

AD, but the confidence interval was wide (RR 1.53; 95 percent CI 0.94 to 2.49). 

Other classifications of elevated homocysteine found variable associations. For the highest 

homocysteine quartile (mean homocysteine 27.44 μmol/L), Luchsinger et al.120 found an 

increased risk for AD (HR 2.0; 95 percent CI 1.2 to 3.5). However, this association was no 

longer statistically significant after adjusting for age, sex, education, APOE e4 status, and history 

of stroke (HR 1.3; 95 percent CI 0.8 to 2.3). Blasko et al.121 evaluated the association between 

change in homocysteine and incident AD. For subjects whose homocysteine level doubled over 

2.5 years, the risk of AD was increased (OR 4.2; 95 percent CI 1.6 to 11). It is not clear how 

frequently homocysteine levels doubled over the 2.5-year duration of the study, but the wide 

confidence interval may indicate that a relatively low number were in this group. 

In summary, adjusted models in three of the four included cohort studies found an 

association between increased baseline homocysteine and the development of incident AD. Point 

estimates for the relative risk varied substantially across studies, from modest (1.3) to large (4.2). 

However a pooled estimate using a common classification of elevated homocysteine did not 

reach statistical significance. Homocysteine levels rise with age, renal insufficiency, use of 

coffee, tobacco, and the sequelae from heavy alcohol use. Differences in the cohorts studied with 

regard to these factors may have contributed to variable findings, but there were not adequate 

numbers of studies to evaluate this possibility formally. 
Table 15. Homocysteine and risk of developing AD

Study Sample (n) Followup/ 

Events 

Exposure Case definition Confounding 

adjustment 

Results 

Blasko et al., 2008121 Community cohort 

(487) 

2.5 years 90 AD 

Fasting plasma homocysteine measure at 2 time points 

NINCDS-ADRDA DSM 

Age Sex Educational level At least one APOE e4 

Homocysteine doubthose who converted 1.6 to 11.0) 

Luchsinger et al., 2004120

Community cohort (679) 

4.7 years 109 AD 

Fasting plasma homocysteine 

NINCDS-ADRDA DSM 

Age Sex Education APOE e4 Stroke 

Highest quartile of hcompared to the lowhad increased risk (uCI 1.2 to 3.5). Adjusthighest vs. lowest quacross quartiles. Homocysteine thres1.0 (0.7 to 1.5) Including B6, B12, anot affect results 

Ravaglia et al., 200557 Community cohort 

(816) 

3.8 (0.8) years 112 dementia (70 AD) 

Fasting plasma homocysteine 

NINCDS-ADRDA Age 

Sex Education APOE e4 Stroke Creatinine Folate Vitamin B12 Smoking status Diabetes mellitus Hypertension Cardiovascular disease BMI 

Homocysteine > 15 AD: 2.08 (95% CI 1Sensitivity analysis eneuroimaging showinot affect results 

Seshadri et al., 2002119 Community cohort 

(680) 

Median 8 years (range 1 

Plasma homocysteine 

NINCDS-ADRDA Age DSM Sex 

For each 1 SD increhomocysteine, adjusCI 1.3 to 2.5) 

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74

Study Sample (n) Followup/ 

Events 

Exposure Case definition Confounding 

adjustment 

Results 

to 13) 

Vitamins B12 and B6 Diabetes mellitus Smoking status Alcohol use Creatinine Education APOE e4 Stroke Folate 

44 AD 

Systolic blood pressure BMI 

For homocysteine > 1.9 (1.2 to 3.0) 

Abbreviations: AD = Alzheimer’s disease; APOE e4 = epsilon 4 allele of the apolipoprotein E gene; BMI = body mass index; CI = confidence interva

Statistical Manual of Mental Disorders; HR = hazard ratio; NINCDS-ADRDA = National Institute of Neurological and Communicative Diseases and 

and Related Disorders Association; OR = odds ratio; RR = relative risk; SD = standard deviation 
Figure 3. Meta-analysis of three cohort studies on homocysteine and risk of developing AD. Combined 

estimate is given in bottom row. 

Other medical factors. Factors considered under this heading include sleep apnea, obesity, 

and traumatic brain injury (TBI). 

Sleep apnea. We did not identify any good quality systematic reviews or primary studies that 

evaluated the association between sleep apnea and risk of developing AD. 

Obesity. We identified one good quality systematic review that examined the association 

between various measures of obesity and the development of AD.47 The review included 10 

prospective cohort studies published between January 1995 and June 2007, of which four were 

conducted in the United States, two among Japanese men (one of which was in Honolulu), two in 

Sweden, and one each in Finland and France. Prospective cohort studies were selected if the 

sample size was > 100; followup was ≥ 2 years; exposure was recorded as BMI, 

obesity/overweight, a measure of central obesity, or a combination; outcomes reported were AD 

or vascular dementia (VAD), or a combination; and if the outcomes were reported as odds ratio, 

relative risk, or hazard ratio, or as data from which these measures could be calculated. 

Of the 10 eligible studies included in the review, 4 studies involving 15,688 subjects 

examined the relationship between AD and obesity and were combined in a metaanalysis.94,101,122,123 The results from the other studies included dementia as a whole or vascular 

dementia separately, but did not report associations with AD. All participants were ≥ 65 years of 

age at the time of cognitive testing; however, age at baseline ranged from 40 to 45 years old to 

more than 77 in some studies. Length of followup ranged from 3.2 to 36 years. All studies 

measured BMI, and one study also measured change in BMI.122 Level of covariate adjustment 

was reported at the individual study level. Although the review included both AD and VAD, 

both combined and individual analyses were done for the two outcomes, and the RR for AD was 

reported separately. Study quality for the primary studies was not assessed in this review. 

Studies were combined for meta-analysis using a fixed-effect model, as the heterogeneity 

among the four studies was not statistically significant. A funnel plot that included all studies did 

not reveal significant publication bias. This was confirmed by two other numerical tests (Egger’s 

regression asymmetry test: - 0.14 ± 0.54, P = 0.791; and Begg-adjusted rank correlation test: z = 

0.62; P = 0.533). For the four cohort studies, compared with normal-weight subjects, those who 

were obese had a higher risk of developing AD (RR 1.80; 95 percent CI 1.00 to 3.29). Analysis 

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76

was done to estimate the RR of dementia based on weight status; however, this analysis 

combined AD and VAD as outcomes. 

We identified three additional prospective cohort studies published after the beginning of 

2008 which examined the association between obesity and Alzheimer’s disease.124-126 These 

studies are summarized in Table 16; detailed evidence tables are provided in Appendix B. The 

first study was conducted in a community in Sweden where 1255 participants who were enrolled 

in the Kungsholmen Project were followed for 9 years.124 The two other studies were conducted 

in the United States, but the population in one of these studies was restricted to those of Japanese 

ethnicity.125 The average followup periods in the U.S. studies were 5.9 years126 and 7 to 9 

years.125 In all three studies, selection bias was minimized by recruiting participants from the 

community and by excluding those who had dementia at baseline. Two of the three studies 

compared baseline characteristics by weight,125,126 while one examined baseline characteristic 

only by sex.124 All three studies directly measured weight for the calculation of BMI; one study 

also considered midlife weight by self-report as an additional risk factor.126 BMI was categorized 

into four groups in each study; however, the cut-offs used were slightly different in the studies, 

as follows: in Fizpatrick et al., underweight (BMI < 20), normal weight (20-25), overweight (25-

30), and obese (> 30);126 in Hughes et al., obese (BMI ≥ 25.0), overweight (23.0-24.9), normal 

(18.5-22.9), and underweight (< 18.5);125 and in Atti et al., obese (BMI ≥ 30), overweight (25-

29.9), normal weight (20-24.9, reference category) and underweight (< 20).124 Although all 

studies assessed both AD and other types of dementia , the investigators conducted a separate 

analysis for those with AD only as the outcome. 

Atti et al.124 concluded that higher BMI was associated with a lower risk of developing AD; 

that is, overweight subjects had a lower risk of developing dementia over 9 years (HR 0.66; 95 

percent CI 0.50 to 0.88). The other conclusion was that loss of weight is a marker of incipient 

dementia. Hughes et al. concluded that after controlling for covariates except APOE, higher 

baseline BMI was associated with a decreased risk of AD (HR 0.56; 95 percent CI 0.33 to 0.97); 

however, this model was no longer significant after controlling for APOE (HR 0.68; 95 percent 

CI 0.31 to 1.51). Also, lower decline in BMI was associated with a decrease in risk of incident 

AD (HR 0.21; 95 percent CI 0.06 to 0.80).125 Fitzpatrick et al. also concluded that underweight 

persons (BMI < 20) had an increased risk of dementia (HR 1.62; 1.02 to 2.64), whereas being 

overweight (BMI_25-30) was not associated (HR 0.92; 0.72 to 1.18), and being obese reduced 

the risk of dementia (HR 0.63; 0.44 to 0.91) compared with those with normal BMI. In the same 

study, when the association between midlife BMI and dementia was examined, there was a 

reversal in the direction of risk, as an increased risk of dementia was found for the obese (BMI 

> 30) versus those of normal weight (BMI 20-25), adjusted for demographics (HR 1.39; 1.03 to 

1.87) and for cardiovascular risk factors (HR 1.36; 0.94 to 1.95).126

 In conclusion, the meta-analysis published as part of a systematic review found that obesity 

was associated with an increased risk of AD, while all three prospective cohort studies published 

after the meta-analysis found that that a higher BMI was associated with a lower risk of 

developing AD. These conflicting results could be explained by the differences in age in the 

different study populations. The reversal of the direction of risk found by Fitzpatrick et al.126 is 

interesting, as it implies that BMI does not consistently predict dementia risk across the lifespan, 

and that this risk might change based on the age of exposure to obesity. Also, decreasing BMI 

might be a sign of early dementia, as one cannot attribute a causal relationship between decrease 

in weight and dementia yet. 
Table 16. Obesity and risk of developing AD 

Study Sample (n) Followup/ 

Events 

Exposure Case definition Confounding adjustment Results 

Atti et al., 2008124 Community cohort 

(1255 total; 646 analyzed) 

9 years BMI DSM III 

Clinical evaluation by two doctors 

MMSE Depression Impaired ADLs Chronic disease before baseline 

Overweight subjedeveloping deme0.66 (95% CI 0.5

Hughes et al., 2009125 Community cohort 

(1836 total; 1478 analyzed) 

7 to 9 years BMI NINCDS-ADRDA 

DSM IV 

Age Race Sex Educational level Alcohol Smoking Hypertension Hypercholesterolemia Diabetes Angina pectoris Stroke 

Lower decrease with decreased rCI 0.06 to 0.80) Higher baseline Bassociated with a 0.56 (0.33 to 0.97statistically signifAPOE: HR 0.68 

TIA Physical activity APOE genotype 

Fitzpatrick et al., 2009126

Community cohort 

5.4 years BMI NINCDS-ADRDA Age For late life BMI, 

< 20) had an incr(HR 1.62; 95% Cbeing overweight associated (0.92obese reduced th0.63; 0.44 to 0.91with normal BMI. was associated wdementia (HR 1.3

Race 

(2798) Sex 

Educational level Baseline cognitive status Cardiovascular and dementia risk 

Abbreviations: ADLs = activities of daily living; APOE = apolipoprotein E gene; BMI = body mass index; CI = confidence interval; DSM = Diagnos

Mental Disorders; HR = hazard ratio; MMSE = Mini-Mental State Examination; SDMT = Symbol Digit Modalities Test; TIA = transient ischemic att

77
Traumatic brain injury (TBI). We identified one good quality systematic review that 

examined the association between traumatic brain injury (TBI) and the development of AD in 

case-control studies.46 We did not generally consider case-control studies for this report due to 

the numerous limitations of such studies compared to cohort studies. However, in the case of 

TBI, there were few prospective cohort studies that met our eligibility criteria, but meta-analyses 

have been done using case-control studies. In the general population, TBI is a relatively low 

prevalence event, meaning that large sample sizes are necessary to have sufficient power to 

detect an association in general community samples. In addition, TBI is not an exposure that 

lends itself to RCTs. For these reasons, we decided to include the meta-analyses described here 

in our review. The review included 15 case-control studies.127-141 There were a total of 2653 

subjects in the combined sample, of which 164 had exposure to TBI and 2489 did not have a 

reported history of TBI. As expected in case-control studies, the cases were demented at baseline 

and the controls were not demented. Six of the studies were conducted in the United States, six 

in European countries, and one each in Canada, Australia, and China. Studies were included if 

their definition of TBI required loss of consciousness; they used either individual or group 

matching of cases and controls; they used NINCDS-ADRDA or DSM diagnostic criteria; they 

used predefined inclusion criteria for controls to rule out the possibility of dementia; data on TBI 

were collected from informants for both cases and controls (symmetrical data collection); and the 

TBI occurred prior to onset of AD. The authors did not conduct a structured quality assessment 

of the studies reported in this systematic review; however the inclusion/exclusion criteria 

provided a limited indirect assessment of quality. The review did not provide information on the 

length of followup, followup rates, or the analytical covariates used in the studies. Exposure to 

TBI with loss of consciousness was determined by proxy-report for both cases and controls. All 

studies used the DSM and/or NINDS/ADRDA diagnostic criteria. Standard χ

2

 tests using a pvalue of 5 percent were used to examine heterogeneity; results of these analyses showed no 

significant heterogeneity was present (actual p values were p ≥ 0.58). Studies were combined 

using fixed-effect meta-analyses since there was no evidence of heterogeneity. The results from 

these analyses are shown in Table 17. 

Table 17. Traumatic brain injury and risk of developing AD – results from case-control studies reviewed by 

Fleminger et al., 200346

Studies analyzed Odds Ratio (95% CI) 

All studies (n = 15 studies) 1.58 (1.21 to 2.06) 

Females (n = 7 studies) 0.91 (0.56 to 1.47) 

Males (n = 5 studies) 2.29 (1.47 to 3.58) 

Studies with information on time interval from TBI to AD onset 

(n = 10 studies) 1.56 (1.12 to 2.18) 

Abbreviations: AD = Alzheimer’s disease; CI = confidence interval; TBI = traumatic brain injury 

The authors had planned to assess the association between TBI and APOE genotype as risk 

factors for AD, but they were unable to do so because only two of the included studies reported 

APOE genotype. Publication bias was not assessed formally, but the authors did attempt to 

assess for recall bias, a potential major weakness of case-control studies on individuals with 

dementia. When limiting the analyses to those cases and controls for whom the informant type 

was the same (e.g., informants were spouses in both groups), the association weakened slightly 

78
and became statistically insignificant (OR 1.42; 95 percent CI 0.75 to 2.67). This finding 

suggests that differential quality of informants for cases and controls in some studies may have 

resulted in a slight overestimate of the association between TBI and AD in the analyses 

combining all studies. Quality ratings of the studies were not provided, but the selection criteria 

may have increased the likelihood that higher quality studies were included in the review. 

However, it is noted that some studies had small sample sizes, and one study limited the cases of 

AD to those with onset prior to age 65,134 potentially limiting the generalizability of the results. 

The authors concluded that TBI may confer an increased risk of AD in males only. They also 

advised that future studies should use medical records to document head injury and should use 

population-based cohort designs to avoid the limitations associated with case-control studies. 

Due to the limitations inherent in case-control studies, we supplemented the above-described 

systematic review46 with a search for cohort studies. This search identified two eligible 

prospective cohort studies104,142 and one retrospective cohort study.143 These studies are 

summarized in Table 18; detailed evidence tables are provided in Appendix B. Two of the 

studies drew samples from the community,104,142 and one drew its sample from military 

hospitalization records in the early 1940s;143 this latter study included both community residents 

and institutionalized individuals. One study was conducted in the United States,143 one in 

Canada,104 and the third in Europe.142 Length of followup ranged from 2 to approximately 55 

years. Two studies used self-report history of TBI, and one study used military medical records 

at baseline to characterize exposure. For two of the studies,142,143 the definition of TBI required 

loss of consciousness or post-traumatic amnesia associated with the injury, but the third study104

did not include this requirement. For all three studies, individuals were non-demented at 

baseline. Two of the studies used sample selection methods to minimize selection bias;104,142 due 

to the retrospective nature of the third study,143 it only partially met criteria for sample selection 

methods that minimize selection bias. Only one of the studies143 compared baseline 

characteristics to assess differences between exposed and unexposed. All three studies used 

standard criteria for the diagnosis of AD. Only one study143 reported that the cognitive diagnoses 

were assigned blind to exposure status; the other two did not report this information. Analyses 

were appropriate and controlled for relevant potential confounders, but none of the studies 

reported a priori sample size calculations. 

Two of the studies found that risk of AD did not increase in relation to a history of TBI.104,142

The third study reported that TBI was associated with increased risk of AD, and that there was a 

dose-response effect, with the risk being due to those with moderate and severe injuries.143 This 

latter study used an all-male sample. One of the other studies investigated potential differences 

by sex and found no differences in the association between TBI and AD for males and 

females.142 The inconsistency in results across studies may be due to the differences in the 

method of exposure ascertainment (i.e., self-report of lifetime history of exposure versus 

abstracted information from medical records) and to differences in the severity of traumatic brain 

injuries based on the sample characteristics (i.e., sample made up entirely of WWII veterans 

versus samples with limited number of war veterans). Two of the studies investigated the 

interaction between TBI and the APOE e4 allele on risk of AD. One study found no interaction 

effect.142 The other reported progressively larger hazard ratios with increasing numbers of e4 

alleles, but the results did not reach statistical significance, possibly due to the relatively small 

sample size.143 

As noted above, the methodological differences in the studies provide plausible reasons for 

the differing results. The systematic review of case-control studies found an association between 

79
80

TBI and AD in males only, with the OR for males exceeding 2.0 providing some support for the 

robustness of the result. The one cohort study with an all-male sample also reported that TBI 

increased risk of AD.143 The latter study used medical records from the 1940s to document 

exposure, thus avoiding reliance on self-report of lifetime history of injury. This study also 

reported a concordance rate of about 65 to 69 percent between documented TBI in military 

medical records and subsequent self- or proxy report of a history of TBI, suggesting that reliance 

on self- or proxy report may result in marked exposure misclassification. None of the studies 

could adequately assess whether there is a synergistic effect between the APOE e4 allele and 

TBI in altering risk of AD. 

In summary, there is some evidence that TBI, even in early adulthood, may increase risk of 

AD years later. For those studies that reported an association between TBI and increased risk of 

AD, one study had an all-male sample, and the other found the association only in males. This 

potential gender-specific effect may be attributed to males being exposed to more severe TBIs 

given the dose-response association reported by one study.143 Further confirmation of this 

finding is needed using sources such as medical records to document exposure to TBI. 
Table 18. Traumatic brain injury and risk of developing AD – cohort studies 

Study Sample (n) Followup/ 

Events 

Exposure Case definition Confounding 

adjustment 

Results 

Mehta et al., 1999142 Community cohort 

(6645) 

Mean 2.1 (0.8) years 91 AD cases 

Self-report TBI history 

NINCDS-ADRDA DSM 

Age Sex Education 

Relative risk for AD in th0.4 to 1.9) 

Lindsay et al. , 2002104 Community cohort 

(3745 analytical sample) 

5 years 179 AD cases 

Self-report TBI history 

NINCDS-ADRDA DSM 

Age Sex Educational level 

Odds ratio for AD in tho0.56 to 1.36) 

Plassman et al., 2000143

Clinical cohort (retrospective) 

 ~ 55 years TBI history from 

military medical records and selfreport 

NINCDS-ADRDA 

(1776) 

35 AD cases 

DSM 

Age Educational level APOE 

Risk for AD in those witto 3.91) Risk (95% CI) for AD inchead injury: Mild TBI: 0.76 (0.18 to Moderate TBI: 2.32 (1.0Severe TBI: 4.51 (1.77 

Abbreviations: AD = Alzheimer’s disease; APOE = apolipoprotein E gene; DSM = Diagnostic and Statistical Manual of Mental Disorders; NINCDS-

of Neurological and Communicative Diseases and Stroke-Alzheimer's Disease and Related Disorders Association; TBI = traumatic brain injury 

81
Psychological and emotional health. Factors considered under this heading include 

depression, anxiety, and resiliency. 

Depression. We identified one good quality systematic review that examined the association 

between depression and the development of AD.45 The review included 11 cohort studies 

(95,104 subjects) and 9 case-control studies; 6 were from the United States, 5 from European 

countries, and 1 from Canada. Studies were selected that had sufficient data to calculate an odds 

ratio (OR) for risk of AD or AD-like dementia, had a control group for comparison, and made a 

clinical diagnosis of depression and AD. Study quality for cohort designs was fair; 4 of 11 had 

limitations in assessment of exposure,104,144-146 and 5 of 11 had important limitations in 

assessment of AD.144-148 Length of followup and level of covariate adjustment were not reported 

at the individual study level. Studies were classified as those using specific depression criteria 

(e.g., ICD or DSM) to ascertain exposure and studies using symptoms consistent with major 

depressive disorder but without specific criteria. Several studies used hospitalization for 

depression as an indicator of clinical depression, and these studies may not be applicable to 

individuals with milder depression. Studies were further classified into those assessing AD and 

AD-like dementia outcomes with structured criteria such as NINCDS-ADRDA and those using a 

description of diagnostic criteria for AD or AD-like dementia but without structured criteria. 

Included studies were combined using a random-effects model. A test for heterogeneity 

suggested significant variability between studies that persisted when the analysis was limited to 

studies using a cohort design (p = 0.02). An I2 was not reported. A funnel plot suggested possible 

publication bias. For the 11 cohort studies, depression was associated with a statistically 

significant increased risk of AD (OR 1.90; 95 percent CI 1.55 to 2.33). An influence analysis that 

recalculated the summary OR iteratively, removing one study with each iteration, yielded ORs 

ranging from 1.81 (95 percent CI 1.45 to 2.24) to 2.03 (1.71 to 2.41), suggesting that no single 

study had a large effect on the estimate of association. A meta-regression analysis showed a 

positive association between the interval between depression diagnosis and risk of AD, 

suggesting that depression is a risk factor for AD, rather than a prodrome of the disease. 

The authors conducted stratified analyses for prospective versus retrospective study designs 

and specific or non-specific exposure and outcome assessments (Table 19). These analyses 

showed a statistically significant association for all subgroups. In the four studies using the most 

rigorous criteria for depression and AD diagnosis, the pooled OR was 2.23 (95 percent CI 1.71 to 

3.09). 

Table 19. Depression and risk of AD – results from stratified analyses by Ownby et al., 200645

Stratification of analysis Odds ratio (95% CI) 

Cohort studies (n = 11) 

Case-control studies (n = 9) 

1.90 (1.55 to 2.33) 

2.03 (1.73 to 2.38) 

Prospective cohort studies (n = 4) 

Retrospective cohort studies (n = 7) 

1.78 (1.16 to 2.73) 

2.11 (1.82 to 2.45) 

Specific depression criteria 

No specific depression criteria 

2.23 (2.00 to 2.48) 

1.85 (1.58 to 2.17) 

Structured AD criteria 

No structured AD criteria 

1.91 (1.62 to 2.26) 

2.22 (1.98 to 2.49) 

Abbreviations: AD = Alzheimer’s disease; CI = confidence interval; n = number of subjects 

82
83

The authors concluded that depression may confer an increased risk for developing AD later 

in life. 

We identified five additional eligible studies involving 4961 subjects published since the 

beginning of 2005 (Table 20). Two studies were conducted in the United States, one in Canada, 

one in the United States and Canada, and one in Europe. Four prospective cohort studies 

recruited older adults without dementia from the community and used NINCDS-ADRDA criteria 

to establish AD over 5 to 6 years of followup. One study evaluated the association between 

depressive symptoms and incident AD in subjects with amnestic MCI recruited for a 3-year trial 

of vitamin E or donepezil.149 All studies assessed current depressive symptoms at baseline using 

a validated instrument. The significance of such a single assessment for depressive symptoms is 

uncertain. Two studies150,151 went further and established a clinical history of depression 

requiring medical attention. All studies adjusted for some important confounders, but other 

potentially important confounders, such as comorbid psychiatric conditions, were not evaluated. 

Geerlings et al.151 found an association between depression requiring medical attention if onset 

was before age 60 (HR 3.7; 95 percent CI 1.43 to 9.58), but not for late-onset depression (HR 

1.71; 95 percent CI 0.62 to 4.74). The study reporting a “history of depression” did not find an 

association with AD at 5 years (OR 1.5; 95 percent CI 0.49 to 4.63), but the precision of the 

estimate was poor due to few incident cases.150 One study22 found an interaction between APOE 

e4 and depressive symptoms, but the only other study evaluating this interaction found no 

significant effect.149 All studies found an association between significant depressive symptoms at 

baseline and incident AD. 

In summary, a previous systematic review found an association between clinical depression 

and incident AD that was robust to subgroup analyses by study design features. Despite 

variability in depression assessment, ranging from a self-reported history to hospitalization, the 

association with incident AD was reasonably consistent. However, publication bias may have 

inflated the summary estimate of effect. Since publication of the systematic review, five 

additional studies found an association between current depressive symptoms and incident AD; 

one of the four additional studies found an association for early onset clinical depression. 

Collectively, these observational studies suggest an association between a history of depression 

and incident AD. 
Table 20. Depression and risk of developing AD – recent cohort studies 

Study Sample (n) Followup/ 

Events 

Exposure Case definition Confounding 

adjustment 

Results 

Gatz et al., 2005150 Community cohort 

(766) 

5 years 36 AD 

CES-D ≥ 16; history 

of depression 

NINCDS-ADRDA Age 

Sex Education 

OR 2.75 

Geerlings et al., 2008151

Community cohort (563) 

5.9 (1.6) years 33 AD 

CES-D ≥ 16; history 

of depression requiring medical attention 

NINCDS-ADRDA Age 

Sex Education Baseline cognition Memory complaints 

HR 2.46 

Irie et al., 200822 Community cohort 

(2350) 

6 years Number of AD cases NR 

11-item CES-D ≥ 9 NINCDS-ADRDA Age 

Education Smoking DM BMI ABI Cholesterol Memory complaints 

HR 2.9 (9HR 13 (9CES-D ≥ 

Lu et al., 2009149

Cohort derived from RCT of donepezil/ vitamin E in those with MCI (756) 

3 years BDI NINCDS-ADRDA 34 AD at 1.7 years 

Age 

Baseline cognition Treatment group APOE 

HR 1.03 

Luchsinger e al., 2008152

Community cohort 

5.1 (3.3) years HDRS NINCDS-ADRDA Age 

Sex Race Educational level APOE e4 Vascular risk factors 

HDRS 1 HDRS > 

Abbreviations: ABI = ankle-brachial index; AD = Alzheimer’s disease; APOE = apolipoprotein E gene; APOE e4 = epsilon 4 allele of the apolipopro

Depression Inventory; BMI = body mass index; CES-D = Center for Epidemiologic Studies Depression Scale (range 0-60; 11-item version scored 0-3

DM = diabetes mellitus; HDRS = Hamilton Depression Rating Scale (range 0 to 51; 17-item version); HR = hazard ratio; NINCDS-ADRDA = Nationand Communicative Diseases and Stroke-Alzheimer's Disease and Related Disorders Association; NR = not reported; OR = odds ratio 

84
Anxiety. We did not identify any systematic reviews or primary studies that evaluated the 

association between anxiety disorders and incident AD. 

Resiliency. We did not identify any systematic reviews or primary studies that evaluated the 

association between psychological resiliency and incident AD. 

Medications. Prescription and non-prescription drugs considered under this heading include 

statins, antihypertensives, anti-inflammatories, gonadal steroids, cholinesterase inhibitors, and 

memantine. 

Statins. Our search identified six eligible studies examining the association between 3-

hydroxy-3-methylglutaryl-coenzyme A (HMG-CoA) reductase inhibitors (statins) and incidence 

of AD. Five were cohort studies (17,840 subjects; described in six publications),153-158 and one 

was a secondary analysis of data from an RCT (2223 subjects).159 No recent good quality 

systematic reviews were identified. All studies drew samples from the community, five in the 

United States and one in The Netherlands, and then followed patients from 3 to 17 years. All but 

one study153 selected samples using methods to minimize selection bias and baseline differences 

between exposed and unexposed groups. Statin use was determined only at baseline – a crude 

measure of exposure – in two studies.153,158 AD outcomes were assessed using structured criteria, 

but only two studies reported assessments that were blind to exposure status.154,158 Analyses were 

appropriate and controlled for confounding, but only one study conducted an a priori sample size 

calculation.155 Study characteristics are summarized in Table 21. 

85
Table 21. Statins and risk of developing AD 

Study Sample (n) Followup/ 

Events 

Exposure Case definition Confounding adjustment Result

Arvanitakis et al., 2008153

Community cohort (929) 

1-12 years 191 AD 

Statin use at baseline; bottles inspected 

“CERAD approach” Age 

Sex Education 

Adjuste(0.54 to 

Haag et al., 2009154 Community cohort 

(6992) 

Mean 9.2 years 464 AD 

Any statin during study; pharmacy records 

NINCDS-ADRDA Age 

Sex Education Smoking BMI Cholesterol DM SBP Cardiovascular disease Cerebrovascular disease Other lipid-lowering agents 

Adjuste(0.37 to 

Li et al., 2004155and Li et al., 2007156

Community cohort (2581) 

17 years 261 AD 

At least 2 consecutive fills during 6 months; pharmacy records 

NINCDS-ADRDA Age 

Education APOE Other lipid-lowering agents 

Adjuste(0.46 to 

Rea et al., 2005157 Community cohort 

(2798) 

Mean 6 years 396 AD 

< 1 year, 1-3 years, > 3 years; bottles inspected annually 

NINCDS-ADRDA Age 

Sex Education Alcohol use CHD status Stroke status Baseline MMSE 

Adjuste(0.44 to 

Sparks et al., 2008159 Community – secondary 

analysis of RCT 

4 years Statin at all visits, > 2 but 

less than all, or < 33% of visits; self-report 

NINCDS-ADRDA Age 

Sex 

24 AD Education 

APOE (2223) 

Adjuste(0.11 to 

86
87

Study Sample (n) Followup/ 

Events 

Exposure Case definition Confounding adjustment Result

Zandi et al., 2005158 Community cohort 

(4540) 

3 years 102 AD 

Any use at baseline; selfreport NINCDS-ADRDA Age Sex 

Education HTN DM APOE 

Adjuste(0.35 to 

Abbreviations: AD = Alzheimer’s disease; APOE = apolipoprotein E gene; BMI = body mass index; CERAD = Consortium to Establish a Registry fo

= coronary heart disease; CI = confidence interval; DM = diabetes mellitus; HR = hazard ratio; HTN = hypertension; MMSE = Mini-Mental State Exasubjects; NINCDS-ADRDA = National Institute of Neurological and Communicative Diseases and Stroke-Alzheimer's Disease and Related Disorders randomized controlled trial; SBP = systolic BP 
Two studies154,159 showed a statistically significant association between statin use and a 

reduced risk of AD (Figure 4). Some studies reported stratified analyses. There was no 

significant difference in the strength of association for lipophilic and hydrophilic statins,154,157

duration of statin exposure,154-157 or presence of APOE.154 We used a random-effects model to 

compute a summary estimate of effect, which showed a significant association between statin use 

and decreased incidence of AD (HR 0.73; 95 percent CI 0.569 to 0.944). The forest plot, chisquare test (Q = 5.132, df = 5, p = 0.40), and I2

 = 2.58 did not suggest significant statistical 

heterogeneity. 

Study name Hazard ratio 

and 95% CI Hazard Lower Upper 

ratio limit limit

Arvanitakis 2008 0.910 0.542 1.527

Haag 2009 0.570 0.365 0.889

Li 2004 0.820 0.460 1.461

Rea 2005 0.870 0.440 1.720

Sparks 2008 0.330 0.111 0.985

Zandi 2005 1.190 0.411 3.447

0.733 0.569 0.944

0.10.2 0.5 1 2 5 10 Favours Statins Favours No Statin

Meta Analysis

Figure 4. Meta-analysis of six cohort studies on statins and risk of developing AD. Combined estimate is 

given in bottom row. 

Subgroup analyses grouping studies by baseline versus ongoing assessment of exposure 

showed no association for the two studies assessing exposure at baseline only (HR 0.958; 95 

percent CI 0.602 to 1.526) and a significantly reduced risk of AD for those with a more robust 

assessment of exposure (HR 0.655; 95 percent CI 0.485 to 0.986). Subgroup analysis by length 

of followup (< 5 years versus ≥ 5 years) did not show important differences in summary effect. 

A funnel plot (Figure 5) did not suggest significant publication bias. 

88
Standard error

Log hazard ratio

0.6

0.5

0.4

0.3

0.2

0.1

0.0

-2.0 -1.5 -1.0 -0.5 0.0 0.5 1.0 1.5 2.0

Figure 5. Funnel plot of standard error by log hazard ratio for statins and risk of developing AD

In summary, six observational studies with 4 to 17 years followup showed a moderate 

reduction in risk of AD with statin use. 

Antihypertensives. We identified eight eligible cohort studies, described in ten 

publications,99,104,107,109,160-165 that examined the use of antihypertensives and risk of incident AD 

(Table 22). More than 20,000 subjects and 1300 cases of incident AD were included. Five 

studies recruited community samples from the United States.99,109,162-164 Two of these focus on 

Americans of Japanese descent.99,163 The other studies were from Canada (Canadian Study of 

Health and Aging, or CSHA), the Netherlands (Rotterdam),161,165 and Sweden 

(Kungsholmen).107,160 Outcomes were measured well, although one study107 provided few details 

on dementia diagnoses. Exposure information came from self-report and/or inspection of pill 

bottles, except in the study by Haag et al.,165 which used pharmacy data. It is not known if as 

much detail was provided when a questionnaire with multiple risk factors was used, as in 

Lindsay et al.104 Followup rates were between 72 and 94 percent, with the exceptions of Yasar et 

al.,164 which did not report followup rates, and Peila et al.,163 where it appears that 73 percent of 

normotensive subjects had missing or abnormal blood pressures and were not included in the 

analysis. 

Four of the eight cohort studies found a decreased risk for AD with antihypertensive 

medications. Significant impact of antihypertensive use in the risk of incident AD was found in 

the Kungsholmen cohort after 3-year160 and 6-year followup.107 In subjects with SBP ≥ 140 

mmHg, the RR for AD with antihypertensives was decreased (0.6; 95 percent CI 0.4 to 0.8). 

When both APOE e4 allele and high SBP were present, the RR for AD was 2.4 (1.4 to 4.2). This 

89
90

elevated risk was mitigated when antihypertensives were used (RR 1.0; 95 percent CI 0.6 to 1.6). 

The Kungsholmen cohort had a mean age of 81 years at baseline, so it would be expected to have 

a high incidence of dementia and prevalence of hypertension (HTN). It is possible that many 

APOE e4 subjects would have had prevalent AD and not be eligible for inclusion in the cohort, 

thus selecting for individuals less susceptible to AD. 

The Cache County cohort study also found an association between antihypertensive use and 

the development of AD.162 When patients taking antihypertensives at baseline were followed for 

3 years, the hazard ratio (HR) for incident AD was 0.64 (95 percent CI 0.41 to 0.98). This cohort 

was younger at inception (mean age 74.1) and was followed for a shorter time. When different 

classes of antihypertensives were analyzed, the result was significant only for diuretics, with an 

adjusted HR of 0.61 (0.37 to 0.98). When controlled for current blood pressure, statistical 

significance was lost, although a significant result remained when the analysis was restricted to a 

cohort who self-reported hypertension. 

The HAAS cohort163 was formed in mid-life and followed into later life. Compared to nevertreated hypertensive subjects, antihypertensive use for > 12 years was associated with a 

significantly lower risk for incident AD (HR 0.35; 95 percent CI 0.16 to 0.78). Antihypertensive 

use for 0 to 5 years and 5 to 12 years was associated with a non-statistically significant reduced 

risk. There was no statistically significant difference in incident non-specific dementia between 

normotensive subjects (not on antihypertensives) and any hypertensive subjects treated with 

antihypertensives for > 12 years (HR 0.82; 95 percent CI 0.28 to 2.38). However, the confidence 

interval was wide and does not exclude a clinically significant difference. 

Haag et al.165 report data from the Rotterdam cohort after a mean followup of 8 years (up to 

13.3 years); pharmacy records were used to determine exposure. The HR for AD per year of 

antihypertensive use (compared to no use) was 0.94 (95 percent CI 0.90 to 0.99). Subjects 75 

years of age and younger had a statistically significant lower risk of AD when antihypertensives 

had been used, but subjects over 75 years did not. Use of antihypertensives for ranges of duration 

was significant only for use between 1.6 to5.3 years. 

No association between antihypertensive use and incident AD was found in the other cohorts. 

The Kame99 and CSHA cohorts104 were followed for a mean of 6 and 5 years, respectively, at the 

time of these analyses. The Kame cohort99 had a mean age at baseline of 72.6. In the CSHA 

cohort, the mean age at baseline was 81 for those who developed incident AD at wave 2, and 

72.9 for controls. Morris et al.109 followed a subset of the Boston EPESE study for up to 13 

years. There was no clear association between HTN or use of antihypertensives and incident AD. 

Yasar et al.164 used the Baltimore Longitudinal Study on Aging (BLSA) to specifically examine 

the impact of calcium channel blockers (CCB), both dihydropyridine (DHP), and non-DHP; 

neither non-specific nor specific classes of CCBs were significantly associated with incident AD 

over the average 13 years of followup. 

In summary, data from eight cohort studies do not show a consistent association between 

antihypertensive use and risk of developing AD. However, most studies found a decreased risk – 

albeit a statistically non-significant decreased risk – with use of antihypertensive medication, 

suggesting a possible reduction in risk. Age of cohort group studied, length of time followed, and 

prevalence of HTN do not consistently explain the variability in outcomes across studies. 
Table 22. Antihypertensives and risk of developing AD 

Study Sample (n) Followup/ 

Events 

Exposure Case definition Confounding 

adjustment 

Results 

Borenstein, 200599

Kame Project 

Community cohort (1859) 

6.0 (2.7) years 90 cases AD 

Self-report of antihypertensives 

NINCDS-ADRDA DSM 

Antihypertensive results unadjusted 

34.5% of cases repoversus 33.5% non-ca

Guo et al., 2001160AND Qiu et al., 2003107Kungsholmen Project 

Community cohort (1310) 

5.7 years (0.1 to 8.2) 204 cases AD 

Self-report and inspection of pill bottles for 2 weeks preceding baseline evaluations 

DSM Age 

Race Sex Educational level Baseline MMSE Vascular disease (heart disease, cardiovascular disease and diabetes mellitus ) APOE genotype SBP DBP 

Antihypertensive druSBP ≥ 140 mmHg: DBP ≥ 70 mmHg: RInvestigators stated with no use of antihyAPOE e4 and SBP < risks of AD were 3.2 e4 and SBP > 140 b1.5 (0.7-3.2) for persand use of drugs” Use of antihypertensincreased risk of the 

Haag et al., 2009165Rotterdam Study 

Community cohort 

8 years (up to 13.3) 432 cases AD 

Pharmacy data NINCDS-ADRDA 

DSM 

Age Sex DBP SBP Diabetes mellitus CVA BMI Education Smoking Total serum cholesterol Cardiovascular disease Cerebrovascular 

HR (95% CI) for any Per year of treatmenAll subjects: 0.94 (0Subjects ≤ 75: 0.92 Subjects > 75: 0.96 

(6249) 

Duration of treatmen< 1.6 years: 0.91 (01.6 to 5.3 years: 0.7> 5.3 years: 0.69 (0

91
Study Sample (n) Followup/ 

Events 

Exposure Case definition Confounding 

adjustment 

Results 

disease 

Khachaturian et al., 2006162Cache Study 

Community cohort (3227) 

3 years 104 cases AD 

Antihypertensives, inspection of pill bottles, “current use” 

NINCDS-ADRDA Age 

Race Sex Number of APOE e4s History of CVA Hyperlipidemia Diabetes mellitus MI Educational level 

Antihypertensive use 0.64 (95% CI 0.41 to When restricted to sHTN: HR 0.64 (0.42 When controlled for HR 0.65 (0.29 to 1.4

Lindsay et al., 2002104

Canadian Study of Health and Aging (CSHA) 

Community cohort (casecontrol analysis) (4088) 

5 years 194 cases AD 

Risk factor questionnaire (self-report) 

NINCDS-ADRDA Age 

Sex Education 

OR for AD on antihy(0.64 to 1.30) Comparison of odds normotensive subjec

Peila et al., 2006163Honolulu Asia Aging Study (HAAS) 

Community cohort (1251) 

4 to > 12 years 65 cases AD 

Self-report first three exams Pill bottle check fourth exam 

NINCDS-ADRDA DSM 

Age Mid-life BMI Smoking CAD CVA Atherosclerosis APOE e4 Education 

Incident dementia = 19) Duration of treatmen0-5 years: 0.62 (0.25-12 years: 0.54 (0.> 12 years: 0.325 (0to never-treated hypUntreated normotenTreatment > 12 yearnormotensives: 0.82 specifically AD 

Morris et Community 2-13 years Pill bottle 

inspection of all 

NINCDS-ADRDA Age OR (95% CI) for inci

92
93

Study Sample (n) Followup/ 

Events 

Exposure Case definition Confounding 

adjustment 

Results 

al., 2001109

Boston EPESE 

cohort (634) 99 cases AD 

meds taken in past 2 weeks 

Sex 

Education 

antihypertensives: 0“No evidence of intemedications with BP 

Yasar et al., 2005164

Baltimore Longitudinal Study of Aging (BLSA) 

Community cohort (1092) 

Average 13 years (up to 19) 115 cases AD 

Self-report 1980-1990; inspection of pill bottles after 1990 

NINCDS-ADRDA DSM 

Sex Education Smoking BP History of heart problems 

RR (95% CI) for AD blocker (CCB): 0.63 lag For DHP-CCB users to 1.25) for 2-year laNon-DHP-CCB user(0.37 to 1.83) for a 2Odds for users vs. nHTN status 

Abbreviations: AD = Alzheimer’s disease; APOE = apolipoprotein E gene; APOE e4; epsilon 4 allele of the apolipoprotein E gene; BMI = body masCI = confidence interval; CVA = cerebrovascular accident; DBP = diastolic blood pressure; DHP-CCB = dihydropyridine-calcium channel blockers; DStatistical Manual of Mental Disorders; HR = hazard ratio; HTN = hypertension; MI = myocardial infarction; MMSE = Mini-Mental State ExaminatioNational Institute of Neurological and Communicative Diseases and Stroke-Alzheimer’s Disease and Related Disorders Association; OR = odds ratio; 

systolic blood pressure; VAD = vascular Alzheimer’s disease 
Anti-inflammatories. Our search identified one good quality systematic review examining the 

impact of NSAIDs on risk of developing AD.35 This review included studies only if AD was 

diagnosed by validated criteria. Studies examining prevalent and incident AD and case-control 

studies were all included. Data on non-aspirin NSAIDs were summarized quantitatively. For our 

purposes, only the four cohort studies that evaluated incident AD were useful.104,166-168 

Two studies analyzed the use of NSAIDs in community populations in the United States 

(Baltimore Longitudinal Study on Aging168 and Cache County study166). Lindsay and 

colleagues104 examined NSAID use and incident AD in the Canadian Study of Health and Aging, 

and In’t Veld and colleagues167 used the Rotterdam cohort. Two studies104,168 relied on selfreport of subjects regarding use of NSAIDs. Zandi and colleagues166 used direct examination of 

pill bottles in addition to self-report, and In’t Veld and colleagues167 used automated pharmacy 

data. The latter study ran through the end of 1998 (NSAIDs were available by prescription only 

until 1995 in the Netherlands). 

Stewart and colleagues found an RR of 0.40 (95 percent CI 0.19 to 0.84) when NSAIDs were 

used for more than 2 years. The Dutch study167 reported that NSAID use at any time had an RR 

for incident AD of 0.86 (0.66 to 1.09), but when NSAIDs were used for more than 2 years, the 

RR was statistically significant at 0.20 (0.05 to 0.83). Lindsay and colleagues found a milder 

reduced risk with any NSAID use, reporting an OR of 0.65 (0.44 to 0.95). Finally, Zandi and 

colleagues reported a HR of 0.45 (0.17 to 0.97), but followup was short, only 3 years as 

compared to 5 to 15 years for the other studies. 

The cohorts in the In’t Veld and Stewart papers167,168 were relatively young: in both cases, 

78 percent of subjects were under 75 years of age at baseline. In the cohort studied by Zandi et 

al.,166 the mean age was approximately 74 years, while in Lindsay et al.104 controls had a mean 

age of 73 years, and subjects with incident dementia had a mean age of 81 years. The authors of 

this latter study also noted that 18.2 percent of their subjects died between waves of the study. In 

a sensitivity analysis that included decedents and estimated the probability of incident dementia 

in this group, there was no association between NSAID use and AD (OR 0.97; 95 percent CI 

0.77 to 1.20). 

These four prospective studies examining incident AD104,166-168 included 15,990 subjects with 

672 cases of incident AD. The meta-analysis of the four prospective cohort studies using a fixedeffect model showed a RR of 0.74 (95 percent CI 0.62 to 0.89). A chi-square test suggested no 

significant heterogeneity; Q3 = 1.16; p = 0.56. Three of the four studies166-168 evaluated NSAID 

exposure of more than 2 years. The combined RR for those three studies was 0.42 (95 percent CI 

0.26 to 0.66; Q2 = 1.16). An I2

 test for heterogeneity was not reported. 

Our own search of the literature identified four eligible cohort studies published after the 

systematic review described above.169-172 These studies are summarized in Table 23; detailed 

evidence tables are provided in Appendix B. All four studies had community-based populations, 

with a total of more than 8200 subjects. Three studies used U.S. populations and one a Swedish 

population. Subjects were followed for 1 to 12 years. Exposure to NSAIDs was determined by 

self-report and inspection of pill bottles except in the study by Breitner et al.,172 which used a 

pharmacy record and self-report. Two of the papers reported that examining duration of use or a 

lagging time (to account both for difficulty by cognitively impaired subjects in accurately 

reporting exposure and for the possible lagging effects of exposure on risk) did not change the 

results, but the actual hazard ratios for these calculations were not included. Breitner and 

colleagues172 ignored the year preceding dementia onset to avoid some of the influence of 

94
95

cognitive impairment on reported NSAID use. All papers used populations with mean baseline 

ages in the mid 70s. 

One study171 found a reduction in risk for AD with NSAID use that was statistically 

significant. The same study found an association between NSAID use and reduced risk of AD in 

the presence of the APOE e4 allele. In their analysis, benefit was apparent only in those with at 

least one e4 allele. For subjects 75 or younger, the HR for AD with a history of NSAID use was 

0.22 (95 percent CI 0.06 to 0.73), and for those older than 75 years, the HR was 0.45 (0.20 to 

0.97). There were only three incident cases of AD in the younger group and eight in the older 

group. Two other studies169,170 found no associations between NSAID use and the risk of 

developing AD. Breitner and colleagues172 found an increased risk of AD in heavy users of 

NSAIDs, but no statistically significant effect for moderate users, using both pharmacy data and 

pharmacy data integrated with self-report. Analyses were adjusted for APOE status.
Table 23. NSAIDs and risk of developing AD 

Study Sample (n) Followup/ 

Events 

Exposure Case definition Confounding 

adjustment 

Results 

Arvanitakis et al., 2008169Religious Orders study 

Community cohort (1019) 

1 to 13 years 209 incident AD 

Pill bottles baseline and annually 

NINCDS using CERAD 

Age Sex Education Vascular risk factors APOE e4 Average of z scores 

HR (95% CI) for usinbaseline: NSAIDs (not ASA): ASA: 0.84 (0.63 to 1Authors reported thacumulative use, but 

Cornelius et al., 2004170Kungsholmen 

Community cohort (1301) 

3 to 6 years 164 AD 

Self-report and bottles (script) at baseline (1987) and first followup (1991-93), not at second followup (1994-96) 

DSM IIIR Age 

Sex Underlying disease Educational level 

RR (95% CI): NSAID only: 0.61 (0ASA only: 1.34 (0.9Either: 1.11(0.81 to

Szekely et al., 2008171

Cardiovascular Health Study 

Community cohort (3229) 

Up to 10 years 231 AD 

Self-report, pill bottles, annually Analyzed as cumulative and more than or equal to 2 years or less 

NINCDS Age 

Sex Education APOE e4 Baseline 3MS 

HR (95% CI): NSAIDs: 0.65 (0.41 ASA: 0.87 (0.65 to 1This apparent benefdepend strongly on Aevident only in peopallele. According to results: consistent evidence of AD with lagging oduration of use, or hbut no quantitative d

Community cohort 

Up to 12 years (3-12) 

Pharmacy data and an integration of pharmacy data and self report 

Breitner et NINCDS Age al., 2009172

Adult changes in Thought (ACT) 

(2736) 

356 AD 

DSM IV Cohort 

Race Sex Education APOE HTN 

HR (95% CI) for AD use of NSAIDs: Pharmacy data alonModerate use: 1.26 Heavy use: 1.57 (1.Pharmacy + self rep

96
97

Study Sample (n) Followup/ 

Events 

Exposure Case definition Confounding 

adjustment 

Results 

Diabetes mellitus BMI Osteoarthritis Regular exercise 

Moderate use: 1.15 Heavy use: 1.55 (1.

Abbreviations: 3MS = Modified Mini-Mental State Examination; AD = Alzheimer’s disease; APOE = apolipoprotein E gene; APOE e4; epsilon 4 all

gene; ASA = acetylsalicylate (aspirin); BMI = body mass index; CERAD = Consortium to Establish a Registry for Alzheimer’s Disease; CI = confideDiagnostic and Statistical Manual of Mental Disorders; HR = hazard ratio; HTN = hypertension;; NINCDS-ADRDA = National Institute of NeurologiDiseases and Stroke-Alzheimer’s Disease and Related Disorders Association; NSAID(s) = non-steroidal anti-inflammatory drug(s); RR = relative risk 
Explanations for the disparate findings in the studies are unclear. It has been suggested that 

longer duration of NSAID use might be necessary to convey benefit, and that there may be a 

window of opportunity prior to onset of disease when NSAIDs are helpful. As noted above, it 

has also been suggested that the benefit from NSAIDs may be more pronounced or only present 

when there is an APOE e4 allele. 

It is possible that studies that failed to find an association did so for different reasons. For 

example, it is possible the duration of followup was too brief in Cornelius et al.,170 and that the 

populations in Arvanitakis et al.169 and Breitner et al.172 were too old. Breitner’s report on the 

ACT cohort differs in that it uses pharmacy exposure information as well as self-report. It is not 

clear how much NSAID use is over-the-counter and not captured by pharmacy data. The 

secondary analysis by Breitner et al. included a combination of pharmacy and self-report data, 

but the proportions of various user groups (low, moderate, heavy) from self-report data are not 

reported. If APOE e4 causes an earlier onset of illness, and benefit from NSAIDs is most 

apparent in those with APOE e4, it would be most beneficial to follow a younger cohort to 

capture this effect. Additionally, those subjects with earlier onset of AD (e.g., those with APOE 

e4) would not have been eligible for dementia-free inception cohorts forming later in life. The 

most strikingly positive findings involved longer duration of use in relatively younger 

cohorts.167,168

A random-effects meta-analysis combining the cohort studies in the systematic review by 

Szekely et al.35 and the more recent studies summarized above is shown in Figure 6. Studies 

were significantly heterogeneous (Q = 40.84, df = 7, p < 0.001, I2

 = 83 percent). Any use of 

NSAIDs was not associated with the risk of AD (RR 0.83; 95 percent CI 0.63 to 1.09). Analyses 

examining the effect of duration and level of exposure did not explain the heterogeneity. A 

sensitivity analysis removing one study at a time found that when the study by Breitner et al. was 

removed, the summary estimate shows an association between NSAID use and lowered risk for 

incident AD (HR 0.79; 95 percent CI 0.69 to 0.91). It is unclear why this study is an outlier. 

Study name Subgroup within study Hazard ratio and 95% CI

Hazard Lower Upper 

ratio limit limit

Arvanitakis 2008 Any 1.190 0.872 1.624

Breitner 2009 Any 1.402 1.205 1.632

Cornelius 2004 Any 0.610 0.322 1.156

In't Veld 2001 Any 0.860 0.669 1.105

Lindsay 2002 Any 0.650 0.442 0.955

Stewart 1997 Any 0.670 0.406 1.106

Szekely 2008 Any 0.630 0.451 0.881

Zandi 2002 Any 0.670 0.412 1.090

0.826 0.625 1.093

0.01 0.1 1 10 100

Favours Any NSAID Favours No NSAID

Meta Analysis

Figure 6. Meta-analysis of eight cohort studies on NSAIDs and risk of developing AD. Combined estimate is 

given in bottom row. 

98
In summary, these prospective cohort studies do not provide clear consensus on the impact of 

NSAIDs in the reduction of risk for AD. Any use is associated with a moderate statistically 

significant decreased risk, but studies are heterogeneous. Variability may be explained by 

interactions with genetic predispositions, duration of use of NSAIDs, and possibly even a 

therapeutic window of benefit. 

Gonadal steroids. We identified one good quality systematic review that examined the 

association between gonadal steroids and the development of AD.38 Cohort studies were 

reviewed for the effects of hormone replacement therapy (HRT) on cognitive decline and 

dementia risk. Selected studies had sufficient data to calculate an odds ratio for risk of AD or 

AD-like dementia, had a control group for comparison, and made a clinical diagnosis of AD. The 

review included 2 cohort studies (1596 subjects) and 10 case-control studies; 10 were from the 

United States, 1 from European countries, and 1 from Australia. Subjects in the two cohort 

studies had had an average age of 61.5 years in one study and 74.2 years in the other. Study 

quality for cohort designs was fair; one study had limitations because it did not maintain 

comparable groups and did not report loss to followup. The other cohort study was limited 

because it did not assemble comparable groups at baseline. Length of followup and level of 

covariate adjustment ranged from 1 to 16 years, and results were adjusted for education, age, and 

ethnicity. The formulation of estrogen varied, with most participants using oral conjugated 

equine estrogen (CEE), though some subjects used other oral estrogens or estrogen delivered 

using a transdermal delivery system. The duration of estrogen use was not stated in one cohort 

study and ranged in duration from 2 months to 49 years (average 6.8 years) in the other. The 

cohort studies diagnosed AD using structured criteria such as NINCDS-ADRDA. 

Studies were combined using a random-effects model. A test for heterogeneity suggested that 

the studies were not heterogeneous (p > 0.1). No I2 was reported. A funnel plot that included all 

12 studies suggested possible publication bias. In the two cohort studies, estrogen use was 

associated with a statistically significant decreased risk of AD (RR 0.50; 95 percent CI 0.30 to 

0.80). 

The review authors conducted stratified analyses for cohort versus case-control study 

designs; results are summarized in Table 24. 

 Table 24. Gonadal steroids and risk of developing AD – results from stratified analyses by LeBlanc et al., 

200138

Studies analyzed RR (95% CI) 

Cohort studies (n = 2) 

Case-control studies (n = 10) 

0.50 (0.30 to 0.80) 

0.71 (0.56 to 0.91) 

Results from 2 cohort studies and 2 case control studies (excluding 8 poor 

quality case-control studies) 

0.64 (0.32 to 1.06) 

Results excluding 3 case-control studies with proxy bias 0.72 (0.55 to 0.96) 

Abbreviations: CI= confidence interval; RR = relative risk 

Summary RRs were similar for studies with NINDS-ADRDA diagnosed AD and those using 

other, less strict AD diagnostic criteria. Exclusion of a study with uncertain confidence intervals 

and a study with low SE (high weight) did not significantly change the risk assessment. 

The authors of the meta-analysis concluded that hormone replacement therapy decreased risk 

of dementia, but most studies had important methodological limitations. The effect of hormones 

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100

on dementia may be over-estimated if participants with memory problems or proxy respondents 

for women with dementia did not remember or were not aware of HRT exposure. Further 

limitations included a wide range of different estrogens, presence or absence of progestins, 

timing of estrogen treatment (perimenopausal versus early or late post-menopausal), and duration 

of use. 

Our search did not identify any new observational studies published since 2001. See the 

section on “Gonadal Steroids” under Question 3 for results of RCTs examining the therapeutic 

and adverse effects of gonadal steroids used to delay the onset of AD. 

Cholinesterase inhibitors. We did not identify any systematic reviews or primary studies in 

cognitively normal samples that evaluated the association between cholinesterase inhibitors and 

incident AD. 

Memantine. We did not identify any systematic reviews or primary studies that evaluated the 

association between memantine and incident AD. 

Social, Economic, and Behavioral Factors 

Early childhood factors. We did not identify any systematic reviews that examined the 

association between childhood exposures and development of AD. We identified one eligible 

cohort study.173 The study is summarized in Table 25; a detailed evidence table is provided in 

Appendix B. The study was drawn from U.S. communities, but some of the participants lived in 

religious order facilities. The length of followup averaged 5.6 years. At baseline, participants 

were not demented. Self-reported information on variables related to childhood socioeconomic 

status was collected when the participants were an average of 75 years old. This information was 

then used to derive indices of socioeconomic status. There was no objective validation of the 

derived indices. The sample selection method only partially minimized selection bias because as 

part of the enrollment criteria participants were required to agree to post-mortem autopsy, which 

may have resulted in some selection bias. The study did not report comparison of baseline 

characteristics between those exposed and unexposed. Standard criteria were used for the 

diagnosis of AD, but the study did not use an informant report as part of the diagnostic process. 

The authors did not report whether the diagnosis was blind to exposure status; however, it is 

unlikely that details like those used as part of this childhood socioeconomic index would be 

discussed during the diagnostic process. Analyses were appropriate and controlled for relevant 

potential confounders. This study showed that neither early-life household nor community 

socioeconomic factors influenced risk of incident AD in later life. In conclusion, there is no 

evidence supporting an association between these early childhood factors and AD, but there is 

also not sufficient evidence to rule out a possible association. 
Table 25. Childhood socioeconomic status and risk of developing AD 

Study Sample (n) Followup/ 

Events 

Exposure Case definition Confounding 

adjustment 

Results

Wilson et al., 2005173 Community cohort (some 

lived in religious order facilities) (859) 

5.6 years (mean) 154 AD cases 

Self-report and county public records Information collected by selfreport: (1) parental education, (2) paternal occupation, (3) number of children in the family, and (4) participant’s education level. 

NINCDS-ADRDA Age For a 1-

Sex socioec

Childhosocioec(95% C

Education Socioeconomic status indicators

CommuHR 1.35 

Information collected from public records for the participant’s county of birth: (1) literacy rate, (2) percent of children in county attending school, and (3) the Duncan socioeconomic index for head of households for the county. 

Abbreviations: AD = Alzheimer’s disease; CI = confidence interval; HR = hazard ratio; NINCDS-ADRDA = National Institute of Neurological and C

Stroke-Alzheimer's Disease and Related Disorders Association 

101
Education/occupation. Because of their close association, education and occupation are 

considered together here. 

Education. Our review of studies examining the association between years of education and 

AD focused on those studies in which assessing this association was the main aim of the study. 

Reviewing all studies, such as those primarily focused on estimating incidence rates of AD and 

assessing numerous factors that predict AD, was beyond the scope of this review. 

We identified one good quality systematic review that examined the association between 

years of education and development of AD.49 The review included nine prospective cohort 

studies.118,174-181 It also included six case-control studies; however, given the numerous 

weaknesses of case-control studies in assessing risk factors, the current summary describes only 

the cohort studies. The nine cohorts included 22,726 subjects; four studies were from the United 

States, four from European countries, and one from Japan. Studies were selected that used clear 

diagnostic criteria for dementia and AD, provided information about years or level of education 

of participants, controlled for potential confounders, and provided odds ratios or relative risks or 

sufficient data to calculate these figures. 

There was not a structured quality assessment of the studies reported in this systematic 

review; however the strict inclusion/exclusion criteria provided an indirect assessment of quality, 

and the study characteristics for key design variables were reported. Length of followup was not 

reported. However, all studies included in the review reported on incident AD, and education is 

typically completed in early adulthood, meaning that exposure most likely occurred years prior 

to participation in the study. There was no information provided on the followup rates in the 

studies. The covariate adjustment for most studies included at least age and sex; some studies 

included additional covariates such as occupation, APOE, ethnic group, leisure activities, and 

health conditions. Exposure was determined by self-report and categorized as high, medium, or 

low levels of education. The definition of these three levels of education appeared to differ 

across studies. All studies used DSM and NINDS-ADRDA criteria for diagnosis of AD and 

dementia. 

Studies were combined using both fixed-effect and random-effects models to calculate 

pooled relative risks. When results from the two approaches differed, only the random-effects 

models were reported, as they represent more conservative estimates. Heterogeneity was tested 

by using the Cochrane Q statistic, and the Ri statistic. Publication bias was assessed graphically 

using a funnel plot. To assess the potential effect of publication bias on the pooled relative risk, 

the authors conducted sensitivity analysis using three assumptions: (1) published studies 

included only half of all studies conducted; (2) the unpublished studies found null associations; 

and (3) the unpublished studies included as many cases and controls as the average of the 

published studies. 

To briefly summarize the main findings, fewer years of education were associated with a 

greater risk of AD compared to individuals with the highest level of education (Table 26). 

Analyses were not conducted to allow for assessment of a dose-response association. However, 

when the lowest and medium level education groups were combined, the relative risk decreased 

compared to the findings from the analysis using just the lowest level education group. This 

might be interpreted as an indirect measure of a dose-response effect. Both the funnel plot and 

the sensitivity analyses assessing extreme assumptions concerning unpublished studies showed 

that the findings were robust and that no publication bias was evident. The authors concluded 

that having fewer years of education is associated with greater risk of AD. 

102
Table 26. Education and risk of developing AD – results from studies reviewed by Caamano-Isorna et al., 

200649 

Comparison RR (95% CI) Ri* (p value)+

Lowest education level versus highest 

AD (n = 9 studies) 1.59 (1.35 to 1.86) 0.33 ( 0.157) 

Any education level other than highest 

versus highest 

AD (n =5 studies) 1.32 (1.09 to 1.59) 0.61 (0.055) 

* Ri – proportion of the total variance due to between-study variance. Large values (> 0.75) indicate large heterogeneity between 

studies; small values (< 0.4) indicate lack of heterogeneity. +

 Cochrane Q statistic. 

Abbreviations: AD = Alzheimer’s disease; CI = confidence interval; RR = relative risk 

We identified two additional eligible cohort studies published since 2004 examining risk of 

AD in relation to years of education completed.182,183 These two studies are summarized in Table 

27; detailed evidence tables are provided in Appendix B. One study used a community sample,182

and one used a religious order sample in the United States.183 In the study by Ngandu and 

colleagues,182 participants were non-demented at baseline. In the study by Tyas and 

colleagues,183 participants were either cognitively normal or had MCI at baseline. Length of 

followup ranged from 1 to 21 years. Exposure was determined based on self-reported 

information about years of education completed; this is a standard and well-accepted method of 

data collection for this information. The studies used sample selection methods to minimize 

selection bias; however, one study required that participants agree to brain donation at the time 

of death, and this may have introduced some selectivity into the sample.183 One study 

specifically stated that they used standard criteria for the diagnosis of AD;182 the other study did 

not.183 Neither study used an informant report as part of the diagnostic process. The study that 

did not state specific standard criteria did describe criteria that appeared to be in keeping with 

DSM criteria.183 However, while this approach may provide a diagnosis of dementia, it is not 

clear that it would provide a reliable differential diagnosis of AD. It was not reported whether the 

dementia diagnosis was assigned blind to the exposure level, but it seems likely that those 

assigning the diagnosis were aware of the participant’s level of education. However, because the 

association between education and AD was not the primary outcome for these studies, this 

knowledge may not have biased the results. Analyses were appropriate and controlled for 

relevant potential confounders. 

Both studies reported an inverse association between years of education and risk of AD 

(Table 27). In conclusion, the preponderance of evidence indicates that more years of education 

may provide protection from AD. It is not clear whether education is a surrogate for other factors 

such as occupation, baseline intelligence, or socioeconomic status. It is also not clear whether 

more years of education actually prevents AD, delays onset of the disease, or just delays the 

detection of the cognitive decline. Two of the cohort studies included in the systematic review 

discussed above address some of these points. Karp and colleagues174 reported that both low 

education and low socioeconomic status increase risk of AD, but only low education remains a 

significant predictor when both factors are simultaneously included in the model. Stern and 

colleagues176 found that either low education or a low-level occupation increased risk of AD, but 

those with both low education and low occupation had the greatest risk. Combined, these 

103
104

findings suggest that education contributes to risk of AD independently of occupation and other 

socioeconomic factors. 
Table 27. Years of education and risk of developing AD 

Study Sample (n) Followup/ 

Events 

Exposure Case definition Confounding 

adjustment 

Results 

Ngandu, et al., 2007182 Community cohort 

(2000) 

Mean 21 years (4.9) Number or AD cases NR 

Self-reported education 

NINCDS-ADRDA DSM 

Age Education associate

dose-dependent maUnadjusted ORs (95Education ≤ 5 years 

6 to 8 years of educa1.00) ≥9 years of educatio

Sex Followup time Community of residence SES variables Vascular and lifestyle characteristics APOE Late-life diseases and depressive symptoms 

None of the covariatmodels, so the effecbe independent pred

Tyas et al., 2007183 Community cohort 

(members of a religious order) 

1 to 11 years Number or AD cases NR 

Self-reported education 

Not specifically stated, but appears to basically be consistent with DSM 

Age APOE Prior cognitive state 

OR (95% CI) with agthe model and gradureference: Transition from intac≤ High school: 41.48 Undergraduate degrTransition from MCI ≤ High school: 1.11 Undergraduate degr

Abbreviations: AD = Alzheimer’s disease; APOE = apolipoprotein E gene; CI = confidence interval; DSM = Diagnostic and Statistical Manual of MeADRDA = National Institute of Neurological and Communicative Diseases and Stroke-Alzheimer's Disease and Related Disorders Association; NR = 

ratio; RR = relative risk; SES = socioeconomic status

105
Occupation. We identified five eligible cohort studies examining risk of AD in relation to 

occupation.174,176,184-186 The studies are summarized in Table 28; detailed evidence tables are 

provided in Appendix B. Two of the studies used community samples in the United States,176,184

and three used community samples in Europe.174,185,186 Two of these studies were based on the 

same sample,174,186 but they used different lengths of followup and different, but related, 

predictor variables. Length of followup ranged from 1 to 6.4 years. Exposure was determined 

based on self-reported information about occupation. The studies used sample selection methods 

to minimize selection bias. All studies stated that they used standard criteria for the diagnosis of 

AD, but only one of the studies used an informant report as part of the diagnostic process.185 It 

was not reported whether the dementia diagnosis was assigned blind to the exposure level, but it 

seems likely that those assigning the diagnosis were aware of the participant’s occupation. 

However, because the association between occupation and AD was not the primary outcome for 

the parent studies of these substudies, this knowledge may not have biased the results. Analyses 

were appropriate and controlled for relevant potential confounders. The studies used different 

scales to categorize occupational characteristics, making it difficult to make direct comparisons. 

Overall, the findings suggest that typically the relatively modest associations between 

occupation and incident AD become statistically non-significant once years of education are 

included in the model. However, one study did report that low occupation level combined with 

low education further increased the risk of AD, in addition to the effect noted for low education 

alone.176 These results point to the complex inter-relationships among education, occupation, and 

other markers of socioeconomic status. 

In conclusion, the studies to date do not support an association between occupational level 

and risk of AD that is independent of the influence of education level. 

106
Table 28. Occupation and risk of developing AD 

Study Sample (n) Followup/ 

Events 

Exposure Case definition Confounding 

adjustment 

Results 

Evans, et al., 1997184 Community cohort 

(642 analytical sample) 

4.3 years 95 AD cases 

Self-reported occupation coded according to level of prestige. Self-reported income and education 

NINDCS-ADRDA Age 

Sex Followup interval 

OR (95% CI): Lower occupation prbut not lower income associated with increindividually assessed When education (0.8occupational prestigincome (0.92; 0.69 to simultaneously enteeducation remained 

Karp, et al., 2004174 Community cohort 

(931) 

3 years 76 AD 

Self-reported occupation and education. Lifetime SES estimated based on occupation. Socioeconomic mobility based on occupation changes 

NINCDS-ADRDA DSM 

Age Sex Vascular disease Alcohol use 

RR (95% CI): Lifetime low SES alo2.5 Combined model: Low education: 3.3; Low SES: 1.0; 0.6 to Main finding: Low eindividually associateAD, but only low edufactor when both facsimultaneously. 

Stern, et al., 1994176 Community cohort 

(593) 

1 to 4 years 106 dementia cases, of which 97 were AD 

Self-reported education and occupation Occupation dichotomized as: High (manager/ business/ government, professional /technical) 

NINCDS-ADRDA DSM 

Age Sex 

RR (95% CI) for dem≥ 8 years of educatio< 8 years of educatioHigh occupation = reLow occupation: 2.2High education and reference 

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108

Study Sample (n) Followup/ 

Events 

Exposure Case definition Confounding 

adjustment 

Results 

versus Low (unskilled/ semi-skilled, skilled trade or craft, clerical/office worker 

Low education and lto 3.84) 

Helmer, et al., 2001185 Community cohort 

(2950) 

Mean 6.4 years 251 AD cases 

Self-reported occupation Occupation categorized as: professional/ managerial (reference), housewives/ inactive, farmers, domestic service employees, blue collar workers, craftsmen/ shopkeepers 

NINCDS-ADRDA DSM 

Age Sex Educational level Tobacco use Alcohol use Vascular factors Income 

Overall, there was noccupation and incidRisk of AD seemed toccupation differentlcraftsman and shopkwith a protective risk 95% CI: 0.23 to 0.87increased among me

Qiu, et al., 2003186 Community cohort 

(913) 

6 years 197 AD 

Self-reported occupation Categorized as: 1) Manual a) Skilled vs. unskilled b) Service production vs. goods production 2) Non-manual 

DSM Sex 

Educational level (< 8 years vs. ≥ 8 years) Baseline cognitive status Vascular disease (heart disease, CVD, DM) 

Compared with non-work was not significincreased risk of AD1.7) Compared with non-work involving goods adjusted RR of 1.6 ( 0.046) for AD 

Abbreviations: AD = Alzheimer’s disease; CI = confidence interval; CVD = cardiovascular disease; DM = diabetes mellitus; DSM = Diagnostic and 

Disorders; NINCDS-ADRDA = National Institute of Neurological and Communicative Diseases and Stroke-Alzheimer's Disease and Related Disorde

ratio; RR = relative risk; SES = socioeconomic status 
Social engagement. We did not identify any good quality systematic reviews that examined 

the association between social engagement and development of AD. We identified five relevant 

and eligible cohort studies.187-191 These studies are summarized in Table 29; detailed evidence 

tables are provided in Appendix B. 

Social engagement as a risk factor was defined by different exposures in the studies, 

including objective measures such as marital status, living situation, number of people in social 

network, as well as subjective measures such as feelings of loneliness and perceptions of social 

support. Although five social engagement studies were identified, the measurement of exposure 

and reporting of outcomes varied among the studies. Hence, results were not combined to 

provide a single summary statistic; rather, qualitative descriptions of the studies are provided in 

what follows. 

Two of the studies drew their sample from the United States;188,191 the other three were from 

Europe.187,189,190 All studies chose community samples and enrolled non-demented participants. 

The length of followup ranged from 3.3 to 21 years. Wilson et al.188 considered loneliness as a 

risk factor and measured this using a modified version of the de Jong Gierveld Scale with a 5-

point scoring system. It included statements such as “I miss having people around” and “I often 

feel abandoned.” In the same study, social isolation was inferred from two indicators of social 

functioning, social network size and frequency of participating in social activity. Fratiglioni et al. 

measured social network, taking into account martial status, whether subjects lived alone or not, 

and contact with friends and family, including satisfaction with social contact.189 In the study by 

Saczynski et al., social engagement consisted of marital status; living arrangement; participation 

in social, political, or community groups; participation in social events with coworkers; and the 

existence of a confidant relationship.191 The other two studies187,190 defined social engagement 

based on marital status. 

None of the studies had objective validation of exposure. Two studies used informant 

interviews, one of them to confirm exposure data,191 and the other only when the participant was 

unable to answer questions.189 Only two studies examined baseline characteristics by 

exposure.190,191 No information on blinding of the diagnostic assessment to exposure status was 

provided in any of the studies. Although information about social activities is not a routine part 

of dementia assessment, marital status is commonly asked about in many assessments. 

Of the studies that examined marital status and AD, one study found that those who were never 

married had a higher risk of AD (RR 2.31; 95 percent CI 1.14 to 4.68).187 In this study, being 

widowed or divorced was not associated with AD. Fratiglioni et al. found that being single and 

living alone was associated with an increased risk of AD (RR 1.9; 95 percent CI 1.2 to 3.1), but 

being widowed, divorced, or married but living alone did not significantly increase risk of AD.189

Hakansson et al. also found that those who were without a partner after midlife had an increased 

risk of AD (OR 5.0; 95 percent CI 1.4 to 17.5). The association between being without a partner 

at midlife and risk of AD was not statistically significant. (OR 2.06; 95 percent CI 0.9 to 4.7).190

Wilson and colleagues found that a person with a high degree of loneliness (score 3.2, 90th

percentile) was about 2.1 times more likely to develop dementia during followup when compared 

with a person with a low degree of loneliness (score 1.4, 10th percentile).188 In the same study, 

the risk of AD associated with loneliness decreased (RR 1.41; 95 percent CI 0.97 to2.06) after 

adjusting for a 9-item CES-D score (after removing one item about loneliness), whereas the risk 

of AD associated with the CES-D score was decreased by half after controlling for loneliness. In 

the studies that looked at social network and engagement, poor or limited social networks were 

associated with a higher risk of incident dementia (RR 1.87; 95 percent CI 1.12 to 2.1), and 

109
110

participants who were not satisfied with social contact with children were also at a higher risk 

(RR 2.0; 95 percent CI 1.2 to 3.4).189 Though social engagement at midlife was not significantly 

associated with AD, a decline in social engagement from mid- to late life was associated with an 

increased risk of AD (HR 1.87; 95 percent CI 1.12 to 3.13).191

In conclusion, across three studies187,189,190 there was a consistent association between an 

increased risk of AD and being single and not cohabiting with a partner in later life. Generally, 

this association was not present for individuals who were divorced or widowed. But one 

exception to this is a reported association for increased risk of AD among individuals who were 

widowed both at midlife and later life (OR 7.67; 95 percent CI 1.67 to 40.0) compared to those 

who were cohabiting at both time points.190 Further analyses of subgroups based on APOE 

genotype showed that this association was due primarily to those with at least one APOE e4 

allele (OR 25.55; 95 percent CI 5.7 to114.5; P < 0.001) when compared to APOE e4 non-carriers 

who were cohabiting at both time points.190 Some caution in drawing conclusions from these 

results is warranted given the wide confidence intervals. Further studies are needed to confirm 

these findings regarding cohabitation, marriage and AD. 

There is also preliminary evidence that a higher degree of loneliness, dissatisfaction with 

social contacts, and decreased social networks might also be risk factors for AD. As a change 

from high to low social engagement from mid- to late life was associated with a higher risk of 

AD compared to consistently low or consistently high social engagement, it is possible that the 

decrease in social engagement may be associated with changes due to early AD. Further studies 

are needed to clarify the direction of the relationship between social engagement and AD.
Table 29. Social engagement and risk of developing AD 

Study Sample (n) Followup/ 

Events 

Exposure Case definition Confounding 

adjustment 

Results 

Helmer et al., 1999187

PAQUID 

Community cohort (5554 in cohort; 3777 [68%] agreed to participate) 

4.3 years (SD 1.4) 190 incident cases of dementia, 140 of which were AD and 50 “other” 

Marital status assessed by selfreport: 1) Married or 

cohabitant (n = 2106) 

2) Never married (n 

= 179) 

3) Widowed (n = 

1287) 

4) Divorced or 

separated (n = 103) 

215 initially married but widowed during followup considered married until the death of spouse, then considered widowed 

NINCDSADRDA Number of people in the social network 

Satisfaction with work Living alone Number of leisure activities Baseline CES-D Education Wine consumption Sex Age 

RR (with 95% CI): Married (referenceWidowed (n = 74)p = 0.487 Never married (n = 4.68); p = 0.02 Divorced (n = 4); R0.917 

Wilson et al., 2007188

Rush Memory Aging Project 

Community cohort (1023; 857 after exclusions) 

Mean 3.3 years Range 2 to 5 years 76 AD cases 

1) Loneliness: Selfreport 

(questionnaire) 

2) Social isolation: 

Self-report 

NINCDSADRDA Age Sex 

Level of educational achievement Social network Social activity 

Risk of clinical AD approximately 51% loneliness scale (R2.14) Relation of lonelincontrolling for sociactivity in the abovCI 1.01 to 2.09 

Saczynski et al., 2006191

Community cohort (3508) 

Mean 27.5 years for midlife social measures and 4.6 years for late life 

Social engagement – assessed using a composite score of the following: 1) Marital status; 2) Living 

NINCDSADRDA DSM 

Age Education Cognitive Abilities Screening Instrument score, 

Midlife social engawith incident demeCompared to highlate life, lowest sohigher risk of deve

111
Study Sample (n) Followup/ 

Events 

Exposure Case definition Confounding 

adjustment 

Results 

arrangement; 

3) Participation in 

social, political, or community groups; 

4) Participation in 5) social events with 

coworkers; 

6) Existence of a 

confidant relationship 

APOE e4 allele status History of stroke, coronary heart disease, depression, or disability 

95% CI 1.18 to 4.6Compared to consengagement in miwhose social engamid- to late life hadementia (HR 1.87

Fratiglioni et al., 2000189

Community cohort (1473) 

3 years Social network 

1) Marital status; 2) Living 

arrangement; 

3) Contact with 

children; 

4) Satisfaction with 

contacts; 

5) Close social ties 

DSM Age 

Sex Educational level 

Compared to extenetwork, those witnetwork were at indementia (RR 1.6

Baseline cognitive status 

Compared to daily children and satisfwho were not satisof developing dem

Physical function (ADLs) Depression Vascular disease 

Relative risk of decompared with masomeone (RR [95Single and living aMarried and living 

Hakansson et al., 2009190

Community cohort (1449) 

Average 21 years 

Marital status (married/co-habiting, single or divorced) 

MMSE and NINCDS-ARDA 

Age Sex Educational level Baseline cognitive status BMI APOE Systolic BP 

Risk of AD (44/12By status at midlife Without partner: 2Widowed: 2.52 (0Single/divorced: 1By status in late-lif

112
113

Study Sample (n) Followup/ 

Events 

Exposure Case definition Confounding 

adjustment 

Results 

Region of residence Smoking Occupation Physical activity at work Depression at midlife 

Widowed or divorcto 17.5) 

Abbreviations: AD = Alzheimer’s disease; CES-D = Center for Epidemiologic Studies Depression Scale; CI = confidence interval; NINCDS-ADRDA Neurological and Communicative Diseases and Stroke-Alzheimer's Disease and Related Disorders Association; RR = relative risk; SD = standard dev
Cognitive engagement. For the purposes of this review, we have categorized leisure 

activities into three categories: (1) cognitively engaging activities (e.g., puzzles, reading, and 

board or card games); (2) physical activities; and (3) other leisure activities that do not fall into 

the first two categories (e.g., membership in organizations such as clubs). The first group 

(cognitively engaging activities) also includes cognitive training RCTs. We have attempted to 

group the results from studies into these three categories, however, in cases in which studies 

grouped activities together from more than one category, we have assigned the studies to one of 

these categories based on the characteristics of the majority of items in the grouping. We begin 

with cognitively engaging activities, then proceed to physical activities and other leisure 

activities. 

We did not identify any good quality systematic reviews that examined the association 

between cognitive engagement and development of AD. We identified four eligible cohort 

studies.192-195 These are summarized in Table 30; detailed evidence tables are provided in 

Appendix B. Three studies drew samples from U.S. communities;192-194 and one study used a 

community sample in Europe.195 In all four studies, participants were non-demented at baseline. 

Length of followup across the studies was approximately 3.0 to 5.0 years (mean, median, or time 

span for mean number of annual assessments). All four studies used self-report of the frequency 

of involvement in specific activities, but three of the studies asked exclusively about current 

involvement in activities,192,194,195 while the fourth inquired about involvement in activities 

across the lifespan.193 There was no objective validation of this method, but one of the studies194

did ask an informant to confirm the participant’s report of involvement in activities. One study 

used sample selection methods that minimized selection bias,195 while the other three studies 

used methods that partially minimized selection bias. One study compared baseline 

characteristics by exposure status.195 All four studies used standard criteria for the diagnosis of 

AD, but only one used an informant report as part of the diagnostic process.194 None of the 

studies noted whether the diagnosis was blind to exposure status; however, it is unlikely that 

details of involvement in these types of activities would be discussed during the diagnostic 

process. Analyses were generally appropriate and controlled for relevant potential confounders. 

All four studies showed a decreased risk of AD associated with more frequent involvement in 

activities considered to be cognitively engaging. One study assessed the influence of APOE on 

the association between current cognitive activity and AD and reported that APOE e4 status did 

not change the risk estimate, and that there was no interaction between cognitive activity and the 

APOE e4 allele.192 Another study193 reported that the frequency of past cognitive activity also 

was associated with risk of AD (RR 0.56; 95 percent CI 0.36 to 0.88). However, when current 

and past activity were assessed in the same model, the effect of past activity was eliminated (HR 

0.80; 95 percent CI 0.49 to 1.30), but the effect of current activity remained substantially 

unchanged (HR 0.47; 95 percent CI 0.34 to 0.66). Cognitive, physical, and social activity levels 

are often correlated. One study conducted analyses using physical and social activity levels as 

covariates to assess their influence on the association between cognitive activity and incident AD 

and found that the results remained unchanged.193 A reduction in cognitive activities may occur 

in the context of mild cognitive impairment as one of the early symptoms of prodromal AD. One 

study conducted sensitivity analyses, successively excluding individuals with low baseline 

MMSE, incident dementia within first 2 years of followup, and then prevalent MCI, to assess 

whether the association between increased cognitive activity and incident AD may be attributed 

solely to individuals with potential prodromal AD.195 The hazard ratios for these analyses 

114
115

remained similar to those for the full sample, but some of the confidence intervals included 1.0 

which may reflect the reduced sample size. 

In conclusion, the available evidence supports an association between increased involvement 

in cognitive activities and decreased risk of AD. The one study that assessed past and current 

participation in cognitive activities found that current activities explained the protective 

association. Further work is needed to confirm the finding195 that the reduced involvement in 

cognitively stimulating activities among those who develop AD does not reflect early symptoms 

of the disease given the long sub-clinical prodromal period for AD. Validation of both the type 

and level of exposure is needed. 
Table 30. Cognitive activities and risk of developing AD 

Study Sample (n) Followup/ 

Events 

Exposure Case definition Confounding 

adjustment 

Results 

Wilson et al., 2002192 Community cohort 

(some lived in religious order facilities) (733) 

4.5 years (mean) (AD cases developed dementia after a mean followup of 3.0 years) 111 AD cases 

Self-report of frequency of current involvement in the following activities: viewing television; listening to radio; reading newspapers; reading magazines; reading books; playing games such as cards, checkers, crosswords, or other puzzles; and going to museums 

NINCDS-ADRDA Age 

Sex Education APOE Depression Medical conditions 

Adjusteon a 5-scale sto 0.92

Verghese et al., 2003194 Community cohort 

(469) 

Median 5.1 years 61 AD cases 124 dementia cases 

Self-report of frequency of current involvement in the following activities: reading books or newspapers, writing for pleasure, doing crossword puzzles, playing board games or cards, participating in organized group discussions, and playing musical instruments 

NINCDS-ADRDA DSM 

Age Sex Educational level Medical illness Baseline Blessed test score Participation in other leisure activities 

Adjusteactivity IndividuassociadementReadinPlaying (0.17 to Playing HR 0.3

Wilson et al., 2007193 Community cohort 

(residents of continuous care retirement communities and subsidized housing facilities) (829) 

Mean of 3.2 annual followup assessments 

Self-report of frequency of cognitive activities across the lifespan. Activities included activities such as reading a newspaper, playing games like chess or checkers, visiting a library, or attending a play 

NINCDS-ADRDA Age Adjuste

cognitivto 0.77

Sex Educational level 

90 AD cases 

116
117

Study Sample (n) Followup/ 

Events 

Exposure Case definition Confounding 

adjustment 

Results 

Akbaraly et al., 2009195 Community cohort 

(5692) 

4 years 105 AD cases 

Self-report of monthly frequency of doing crosswords, playing cards, attending organizations, going to cinema/theater, and practicing an artistic activity 

NINCDS-ADRDA DSM 

Age Sex Study center (Dijon or Montpelier) Marital status Educational level Occupational grade Vascular risk factors: - Diabetes - HTN - High cholesterol - History of vascular disease Depressive symptoms (CES-D > 16) Physical function (instrumental ADL score > 0) Cognitive impairment (MMSE score < 24) APOE genotype 

HR (95leisure lowest High: 0Mild: 0In a senthose wthen th

followubaselinleisure AD remfrom enthe con1.0. 

Abbreviations: AD = Alzheimer’s disease; ADL = activities of daily living; APOE = apolipoprotein E gene; CI = confidence interval; CES-D = Cente

Depression scale; DSM = Diagnostic and Statistical Manual of Mental Disorders; HR = hazard ratio; HTN = hypertension; MCI = mild cognitive imp

Mental State Examination; NINCDS-ADRDA = National Institute of Neurological and Communicative Diseases and Stroke-Alzheimer's Disease and 

Association 
Physical activities. We did not identify any good quality systematic reviews that examined 

the association between physical activity and development of AD. We identified 12 eligible 

cohort studies.85,118,194-202,203 These studies are summarized in Table 31; detailed evidence tables 

are provided in Appendix B. Five studies used samples from U.S. communities,85,194,197,198,202

five from communities in Europe,195,196,200,201,203one from Canada,199 and one from Japan.118 Of 

these, one study used a sample from a health maintenance organization,198 one used a sample of 

twins,196 one used a community sample but also included institutionalized individuals,203 and the 

remainder of the studies used community samples. Two of the studies used a sample from the 

same parent study where one of the reports focused on leisure time physical activities and the 

other reported on work-related physical activities.200,201 At baseline, participants were cognitively 

normal in three studies,196,199,203 non-demented in seven studies,85,118,194,195,197,198,202 and are 

assumed here to have been non-demented in the other two studies based on the mean baseline 

age of the sample.200,201 Length of followup across the studies was approximately 3.9 to 31 years. 

All studies used self-reported information on involvement in physical activities; some asked 

about specific activities, and others asked more general questions about any physical activities 

(information collected in each study is detailed in Table 31). There was a fair degree of overlap 

among the activities across those studies that asked about specific activities and provided this 

detailed information in the article. Most studies asked about current physical activities (at the 

time of the interview), but one study asked about activities during the previous 25 years (from 

age 25-50).196 The span of years for followup reflects that some studies collected information 

about mid-adult life physical activities, while others collected information about later life 

physical activities. One study averaged the reported physical activity level in mid- and latelife.202 In general, there was no objective validation of the accuracy of this self-reported exposure 

to physical activity. However, one study examined construct validity by comparing the combined 

physical activity score with reported markers of health hypothesized to be related to exercise and 

self-rated health.197 Ten of the studies used sample selection methods to minimize selection bias, 

one partially used such methods,194 and for one study it was not possible to determine whether 

the sample selection methods minimized selection bias.118 Eight studies compared some baseline 

characteristics by level of physical activity.85,195-198,200-202 The other studies did not compare 

baseline characteristics between those exposed and unexposed. All studies used standard criteria 

for the diagnosis of AD, but only three of the studies used an informant report as part of the 

diagnostic process.196,197,203 None of the studies noted whether the diagnosis was blind to 

exposure status; however, it is unlikely that details of involvement in these types of activities 

would be discussed during the diagnostic process. Analyses were appropriate and generally 

controlled for relevant potential confounders. 

Quantitative risk estimates from the eight studies are reported in Table 31. Eight of the 11 

studies (excluding the study that used the duplicate sample but focused only on work-related 

physical activity201) reported risk estimates consistent with moderate or high levels of physical 

activity and suggesting a protective benefit from AD. The risk estimates did not always reach 

statistical significance once appropriate covariates were added or across both moderate and high 

levels of activity. This may point to insufficient sample size to detect a significant difference or 

confounding due to un-identified factors. Two studies reported results from analyses examining 

the interaction between physical activity and APOE genotype. These studies reported 

inconsistent results, with one reporting physical activity was most protective among carriers of 

the APOE e4 allele,200 and the other study reporting the opposite result.202 Similarly, results on 

whether there was a differential effect of physical activity on AD for males and females were not 

118
consistent.199,200 One study assessed the association between risk of AD and the combination of 

physical exercise and the Mediterranean diet.85 Compared with individuals neither adhering to 

the diet nor participating in physical activity (low diet score and no physical activity; absolute 

AD risk of 19 percent), those both adhering to the diet and participating in physical activity (high 

diet score and high physical activity) had a lower risk of AD (absolute risk, 12 percent; HR 0.65 

[95 percent CI 0.44 to 0.96]; P = 0.03 for trend). 

A random-effects meta-analysis combining nine cohort studies is shown in Figure 7. Studies 

were significantly heterogeneous (Q = 23.25, df = 8, p = 0.003, I2 = 66 percent). Higher levels of 

physical activity were associated with lower relative risk for incident AD (HR 0.72; 95 percent 

CI 0.53 to 0.98). An influence analysis that recalculated the summary HR iteratively, removing 

one study with each iteration, yielded summary HRs from 0.66 (95 percent CI 0.48 to 0.91) to 

0.75 (0.54 to 1.05), suggesting that no single study had a large effect on the estimate of 

association. 

Study name Hazard ratio and 95% CI

Hazard Lower Upper 

ratio limit limit

Abbott 2004 0.450 0.218 0.930

Larson 2006 0.640 0.428 0.956

Podewils 2005 0.550 0.342 0.885

Rovio 2005 0.456 0.223 0.930

Vergheses 2003 1.270 0.781 2.064

Yoshitake 1995 0.200 0.059 0.673

Akbaraly 2009 1.290 0.798 2.085

Scarmeas 2009 0.670 0.471 0.953

Ravaglia 2008 1.420 0.679 2.968

0.718 0.525 0.982

0.1 0.2 0.5 1 2 5 10 Favours Physical Activity Favours No Activity

Meta Analysis

Figure 7. Meta-analysis of nine cohort studies on physical activity and risk of developing AD. Combined 

estimate is given in bottom row. 

In conclusion, the results from the meta-analysis and the majority of studies reviewed here 

suggest that physical activity, particularly at high levels, is associated with lower risk of incident 

AD. However, there was substantial heterogeneity among the studies. The risk estimates from 

individual studies were not all statistically significant, and in some studies the risk estimate was 

in the direction indicating increased risk of AD. Differences among the studies in samples, 

119
120

methodologies, and measures of exposure do not provide an obvious explanation for the 

inconsistent results. One point to consider when interpreting these results is that physical activity 

may be a marker for a generally healthier lifestyle and that these other healthy lifestyle factors 

may contribute to preserving cognition in later life. One of the studies described here addressed 

this point by examining the combination of physical activity and a Mediterranean diet on risk of 

AD.85 Future work should consider this multi-factorial approach. 
Table 31. Physical activity and risk of developing AD 

Study Sample (n) Followup/ 

Events 

Exposure Case definition Confounding 

adjustment 

Results 

Andel et al., 2008196 Community cohort 

(twins) (3134) 

31 years (mean) 197 AD 

Time of exposure: Mid-life Self-report responses to the question: “How much exercise have you had from age 25 to 50?’’ Responses were coded: 0 (hardly any exercise), 1 (light exercise such as walking or light gardening), 2 (regular exercise involving sports), or 3 (hard physical training) 

NINCDS-ADRDA DSM 

Age Sex Educational level Diet BMI Alcohol use Smoking Angina 

Adjusted OR (95% compared with haLight exercise: 0Regular (moderat0.86) Hard training: 0.6

Abbott et al., 2004197 Community cohort 

(2257 ) 

7 years 101 AD 

Time of exposure: Late-life Self-report responses to questions about the average amount of distance walked per day. 

NINCDS-ADRDA DSM 

Age APOE Baseline CASI Declines in activity since mid adulthood Physical performance score Education BMI Childhood years spent living in Japan Occupation Health conditions 

Adjusted HR (95% individuals who wThose who walke2.21 (1.06 to 4.57Those who walke1.86 (0.91-3.79) Those who walke1.88 (0.87-4.04) 

Laurin et al., 2001Laurin, 

Community cohort (4615) 

5 years 194 AD 

Time of exposure: Late life 

NINCDS-ADRDA DSM 

Sex Educational level Family history of 

Adjusted OR (95% physical activity cactivity (adjusted 

121
Study Sample (n) Followup/ 

Events 

Exposure Case definition Confounding 

adjustment 

Results 

2001199 Self-report responses 

to two questions about frequency and intensity of exercise for individuals who reported physical activity. Composite physical activity score categorized: 1) “Low” = less than weekly 2) “Moderate” = weekly 3) “High“= ≥ 3 times 

weekly 

dementia Tobacco use Alcohol use NSAID use Daily living activities Clinical variables 

education): Low activity: 0.67 Moderate activityHigh activity: 0.5ORs increased sofemales were exawhen additional cthe model, with thdecreased (even with high levels o

Larson et al. 2006198

Clinical cohort (Group Health Cooperative, HMO) (1740) 

Mean 6.2 years (SD, 2.0) 107 AD 

Time of exposure: Late-life Self-report responses for the number of days per week during the past year the individual did the following activities for at least 15 minutes at a time: Walking, hiking, bicycling, aerobics or calisthenics Swimming, water aerobics, weight training Stretching, or other exercise. Responses dichotomized as “exercised regularly,” defined as self-report of exercise ≥ 3 

NINCDS-ADRDA DSM 

Age Ethnicity Sex Educational level Baseline cognitive function Physical function Depression Health conditions Lifestyle characteristics Supplements APOE 

Risk of AD for thoregularly compareexercise regularlyAge- and sex-adj0.43 to 0.96, p = 0HR adjusted for a0.69 (95% CI 0.45 Risk reduction aswas greater in thoperformance leveinteraction of exebased physical fu

122
Study Sample (n) Followup/ 

Events 

Exposure Case definition Confounding 

adjustment 

Results 

times/week, vs. “did not exercise regularly.” 

Rovio et al. 2005200 Community cohort 

(1449) 

Mean 21 years (SD 4.9) 76 AD 

Time of exposure: Mid-life Self-report responses to: “How often do you participate in leisuretime physical activity that lasts at least 20-30 minutes and causes breathlessness and sweating?” Responses dichotomized: “Active” = active ≥ 2 times/week “Sedentary” = < 2 times/week 

NINCDS-ADRDA DSM 

Age Sex Educational level Followup time Locomotor disorders APOE Clinical variables Smoking status Alcohol use 

Risk of AD for “acAdjusted OR: 0.3Physical activity hsexes APOE appears to among APOE carassociation betweAD, but not amoninteraction RERI 

Rovio et al. 2007201 Community cohort 

(1449) 

Mean 20.9 years (SD 4.9) 48 AD 

Time of exposure: Mid-life Self-report responses to the questions: “How physically heavy is your work?” Responses dichotomized as sedentary vs. active groups. “How many minutes do you walk, bicycle, or have some other physical activity when you are going to and from work?” Categorized as: 

NINCDS-ADRDA DSM 

Race Educational level Followup time Locomotor symptoms Occupation Income at midlife Leisure physical activity APOE Vascular disorder Smoking status 

Adjusted OR (95% associated with hphysical work actAdjusted OR (95% associated with pcommuting: No physical activiactivity: 0.36 (0.1High physical act0.48 (0.09 to 2.58No interactions w

123
Study Sample (n) Followup/ 

Events 

Exposure Case definition Confounding 

adjustment 

Results 

1) not at all 2) ≤ 59 minutes 

3) ≥ 60 minutes 

Verghese et al., 2003194

Community cohort (469) 

Median 5.1 years 124 dementia, of which 86 were AD or mixed dementia 

Time of exposure: Late-life Self-report of frequency of involvement in the following 11 physical activities: Playing tennis or golf, swimming, bicycling, dancing, participating in group exercises, playing team games such as bowling, walking for exercise, climbing more than two flights of stairs, doing housework, and babysitting Frequency of participation reported as “daily,” “several days per week,” “once weekly,” “monthly,” “occasionally,” or “never.” Responses used to create index: 7 points for daily participation; 4 points for participating several days per week; 1point for participating once weekly; and 0 points for participating monthly, occasionally, or never. Summed the activity-days for each 

NINCDS-ADRDA DSM 

Age Sex Educational level Medical illness Baseline Blessed test score Participation in other leisure activities 

Adjusted HR for ddancing (frequent (95% CI 0.06 to 0No other physical significant associAdjusted HR (95% point increment in scale: 1.00 (0.98 Adjusted HR (95% 9 points on physiccomparison: 9 to 16 points: 1.> 16 points: 1.27 

124
Study Sample (n) Followup/ 

Events 

Exposure Case definition Confounding 

adjustment 

Results 

activity to generate a physical-activity score, ranging from 0 to 77. Responses dichotomized as “rare participation” (once a week or less) versus “frequent participation” (several days a week or more). 

Podewils et al., 2005202 Community cohort 

(3041) 

5.4 years 245 AD cases 

Time of exposure: Late-life Self-reported information about frequency and duration during the previous 2 weeks of the following activities: Walking, household chores, mowing, raking, gardening, hiking, jogging, biking, exercise cycling, dancing, aerobics, bowling, golfing, general exercise, and swimming. Activities converted to number of kilocalories (kcal) expended per week and number of activities per week 

NINCDS-ADRDA Age 

Race Sex Educational level Baseline cognitive status 

Adjusted HR (95% activities in previoactivity: 2 activities: 0.73 3 activities: 0.85 ≥ 4 activities: 0.5Adjusted HR (95% with number of kiweek compared t248 to 742 kcal/w743 to 1657 kcal/> 1657 kcal/weekP for trend = 0.08 Association only scarriers. P trend ftrend for number 

Yoshitake et al., 1995118

Community cohort (577 at followup) 

7 years 42 AD 

Time of exposure: Late-life Self reported information about 

NINCDS-ADRDA DSM 

Age Sex Baseline cognitive status 

Adjusted HR (95% active group vers(0.06 to 0.68) 

125
Study Sample (n) Followup/ 

Events 

Exposure Case definition Confounding 

adjustment 

Results 

physical activity (four categories each for leisure and for work). Defined the physically active group as those including daily exercise during the leisure period or moderate to severe physical activity at work. 

Akbaraly et al., 2009195 Community cohort 

(5692) 

4 years 105 AD cases 

Time of exposure: Late-life Self-report of daily frequency physical activities that included doing odd jobs, gardening, and going for a walk 

NINCDS-ADRDA DSM 

Age Sex Study center (Dijon or Montpelier) Marital status Educational level Occupational grade Vascular risk factors: - Diabetes - HTN - High cholesterol - History of vascular disease Depressive symptoms (CES-D > 16) Physical function (instrumental ADL score > 0) Cognitive impairment (MMSE score < 24) APOE genotype 

HR for AD compaphysical leisure aHigh tertile: 1.29 Mild tertile: 0.87 

Scarmeas et al., 

Community cohort 

5.4 years Time of exposure: 

Late-life 

NINCDS-ADRDA Age Considered simul

adherence to a M

126
Study Sample (n) Followup/ 

Events 

Exposure Case definition Confounding 

adjustment 

Results 

200985 (1880) 

282 AD cases 

Self-reported responses about number of times participating and number of minutes per time participating in 3 different categories of activities: vigorous (aerobic dancing, jogging, playing handball), moderate (bicycling, swimming, hiking, playing tennis), and light (walking, dancing, calisthenics, golfing, bowling, gardening, horseback riding). Estimation of adherence to a Mediterranean diet based on self-reported responses on a semiquantitative food frequency questionnaire 

DSM Race 

Sex 

high physical actiwith lower risk of Compared to low Middle diet score1.33) High diet score: 0.87); P = 0.008 fCompared to no p

Educational level BMI Smoking Depression Leisure activities Comorbid medical conditions Baseline CDR score 

Some physical ac0.54 to 1.04) APOE 

Interval between 1st

dietary and 1st

physical activity measure Caloric intake 

Much physical ac0.95); P = 0.03 fo

Ravaglia, et al., 2008203 Community cohort (also 

included institutionalized individuals) (749) 

3.9 years 54 AD cases 

Time of exposure: Late-life Self reported physical activity: (a) number of city blocks walked daily; (b) number of flights of stairs climbed daily; (c) frequency and duration of weekly participation during past year in 

NINCDS-ADRDA DSM 

Age Sex Educational level APOE Cardiovascular disease Hypertension Hyperhomocysteinemia Cerebrovascular 

Physical activities dichotomous varior the number of the activity. None physical activity wassociated with inwere above 1.0 a1.0. 

127
128

Study Sample (n) Followup/ 

Events 

Exposure Case definition Confounding 

adjustment 

Results 

occupational, recreational and sport activity 

disease Diabetes COPD Cancer ADL motor impairment 

Abbreviations: AD = Alzheimer’s disease; ADL = activities of daily living; APOE = apolipoprotein E gene; BMI = body mass index; CASI = Cognit

Instrument; CDR = Clinical Dementia Rating scale; CES-D = Center for Epidemiologic Studies Depression scale; CI = confidence interval; COPD = cpulmonary disease; CVD = cardiovascular disease; DSM = Diagnostic and Statistical Manual of Mental Disorders; HMO = health maintenance organi

HTN = hypertension; MCI = mild cognitive impairment; MMSE = Mini-Mental State Examination; NINCDS-ADRDA = National Institute of NeurolDiseases and Stroke-Alzheimer's Disease and Related Disorders Association; NSAID = non-steroidal anti-inflammatory drug; OR = odds ratio; RERI 

interaction; SD = standard deviation 
Other leisure activities. We did not identify any systematic reviews that examined the 

association between non-physical leisure activities and development of AD. We identified one 

eligible cohort study that assessed participation in a range of leisure activities, including those 

considered to be cognitive, social, or physical,179 and one eligible cohort study that assessed 

activities that the authors of the study categorized as either social leisure or passive leisure 

activities.195 The leisure activities assessed for each study are listed in Table 32. Some of the 

leisure activities in these studies overlapped with activities considered to be “cognitively 

engaging” in other studies,192-194 so the results described here should be interpreted in 

conjunction with the findings for Question 1 for the “Cognitive Engagement” factor. The current 

two studies are summarized in Table 32; detailed evidence tables are provided in Appendix B. 

One of the studies used a sample drawn from a U.S. community,179 and the other used a 

community sample from Europe.195 Mean length of followup ranged from 2.9 to 4 years. 

Exposure status was based on self-report of current involvement in specific activities on either a 

daily or monthly basis. There was no objective validation of this method. Both studies used 

sample selection methods to minimize selection bias, but only one reported comparisons of 

baseline characteristics between those exposed and unexposed.195 Investigators used standard 

criteria for the diagnosis of dementia and AD. They did not report whether the diagnosis was 

blind to exposure status; however, it is unlikely that details of involvement in these types of 

activities would be discussed during the diagnostic process. Analyses were generally appropriate 

and controlled for relevant potential confounders. One study reported results for overall dementia 

(not for AD),179 while the other reported results specifically for AD.195 

Akbaraly and colleagues195 reported that more frequent participation in social leisure or 

passive leisure activities was not associated with reduced incidence of AD; the hazard ratios for 

the highest level of exposure for both social and passive leisure activities were in the direction of 

a lower risk of AD, but they were not statistically significant. In contrast, Scarmeas and 

colleagues179 found that participation in more leisure activities was associated with a decreased 

risk of incident dementia. Grouping the leisure activities into categories showed that intellectual 

activities (RR 0.76; 95 percent CI 0.61 to 0.94), physical activities (RR 0.80; 95 percent CI 0.66 

to 0.97), and social activities (RR 0.85; 95 percent CI 0.77 to 0.94) were all associated with 

reduced risk of incident dementia.179 These results suggest that any leisure activity, regardless of 

whether it is cognitive, physical, or social in nature, may provide some protection against 

dementia. In addition, participation in a greater number of these activities may be key to their 

protective benefits. 

These two studies differed in the types of leisure activities assessed, the number of AD or 

dementia cases, and also in how they characterized the exposure. One study used the frequency 

or time involved in each activity, which also indirectly reflected involvement in multiple 

activities,195 while the other used just the number of activities in which the participant was 

involved.179 Any of these differences may explain the discrepant findings between the two 

studies. 

In conclusion, there is no consistent evidence indicating that involvement in leisure activities 

that are not solely cognitive or physical in nature is associated with lower risk of incident AD or 

dementia. 

129
Table 32. Leisure activities and risk of developing AD 

Study Sample (n) Followup/ 

Events 

Exposure Case definition Confounding 

adjustment 

Res

Scarmeas et al., 2001179

Community cohort (1772) 

Mean 2.9 years (range 0 to 7.2) 207 dementia (153 AD) 

Self-reported participation in the following 13 activities: - Knitting or music or other hobby - Walking for pleasure or excursion - Visiting friends or relatives - Being visited by relatives or friends - Physical conditioning - Going to movies or restaurants or sporting events - Reading magazines or newspapers or books - Watching television or listening to the radio - Doing unpaid community volunteer work - Playing cards or games or bingo - Going to a club or center - Going to classes - Going to church or synagogue or temple 

NINCDS-ADRDA Ethnicity 

DSM Sex 

Educational level Occupation Medical conditions 

One point given for participation in each of the above activities 

Numa coagehighwith dem0.84 

130
131

Study Sample (n) Followup/ 

Events 

Exposure Case definition Confounding 

adjustment 

Res

Akbaraly et al., 2009195 Community cohort 

(5692) 

4 years 105 AD cases 

Passive leisure activities: Selfreport of frequency daily of watching television, listening to the radio, listening to music, and knitting/sewing Social leisure activities: Selfreport of frequency monthly visiting or inviting friends or relatives 

NINCDS-ADRDA DSM 

Age Sex Study center (Dijon or Montpelier) Marital status Educational level Occupational grade Vascular risk factors: - Diabetes - HTN - High cholesterol - History of vascular disease Depressive symptoms (CES-D > 16) Physical function (IADL score > 0) Cognitive impairment (MMSE score < 24) APOE genotype 

HR leisuloweMildHighFor MildHigh

Abbreviations: AD = Alzheimer’s disease; APOE = apolipoprotein E gene; CES-D = Center for Epidemiologic Studies Depression scale; CI = confid

Diagnostic and Statistical Manual of Mental Disorders; HR = hazard ratio; HTN = hypertension; IADL = instrumental activities of daily living; MMS

Examination; NINCDS-ADRDA = National Institute of Neurological and Communicative Diseases and Stroke-Alzheimer's Disease and Related Diso

relative risk
Tobacco use. We identified two good quality systematic reviews, published in 2007 and 

2008, that examined the association between tobacco use and the development of AD.50,204 We 

decided to use only the systematic review by Anstey and colleagues50 because compared to the 

other review204 it used broader search terms and stricter inclusion criteria more consistent with 

those used by the present authors, reported detailed results from multiple exposure levels, and 

clearly identified the studies used in each analyses. The review included 10 prospective cohort 

studies published between 1995 and 2005.64,104,105,118,205-210 The 10 studies included a total of 

13,786 subjects; four were conducted in the United States, two in European countries, and one 

each in Canada, Australia, Japan, and China. Studies were selected that had at least two 

occasions of measurement, had AD as an outcome, had at least a 12-month followup period, and 

measured exposure to smoking at baseline. The number of individuals with AD versus other 

dementias was available for the majority of the studies. There was not a structured quality 

assessment of the studies reported in this systematic review; however, the strict 

inclusion/exclusion criteria provided an indirect assessment of quality, and the study 

characteristics for key design variables were reported. Length of followup ranged from 2 to 30 

years. No information was provided on the followup rates in the studies. The covariate 

adjustment for most studies included at least age and education; many studies included additional 

covariates such as sex, APOE, biological measures, and health conditions. Selection of models to 

report from individual studies was determined first by the model with the smallest standard error 

and then on the model with the largest number of covariates. Exposure was determined by selfreport, and smoking was classified as ever, current, former, or never smokers. All studies with 

AD as an outcome used DSM and/or NINDS-ADRDA diagnostic criteria. 

Studies were combined using fixed-effect meta-analyses if there was no evidence of 

heterogeneity. If heterogeneity was present, random-effects models were used. Standard χ

2

 tests 

using a p-value of 10 percent were used to examine heterogeneity. The small number of studies 

within each group of studies with compatible measures precluded investigation of heterogeneity, 

using meta-regression, subgroup analyses, or assessment of publication bias. 

The results for the various exposure definitions and the outcome of AD are reported in Table 

33. The studies that provided data for three smoking statuses (current, former, and never) 

provided data only for current-versus-never and former-versus-never comparisons. The authors 

of the review mathematically derived conservative estimates of the current-versus-former 

comparison from the current-versus-never and former-versus-never. To briefly summarize the 

main findings, current smokers were at greater risk of AD compared to either never smokers or 

former smokers. The results in Table 33 suggest a crude dose-response association, with the risk 

of AD progressively increasing from never smokers to former smokers to current smokers. Some 

caution is urged in interpreting the pattern of results in this way because different studies 

contribute to the relative risks for each of the comparisons. In addition, the mathematically 

derived relative risk for current versus former smokers is almost equal that of the comparison of 

current versus never smokers, a result that would not be expected if there were a dose-response 

effect. 

132
133

Table 33. Smoking and risk of developing AD – results from studies reviewed by Anstey et al., 200750 

 

Comparison Relative Risk (95% CI) 

Current smokers versus never smokers (n = 4 studies) 1.79 (1.43 to 2.23) 

Ever smokers versus never smokers (n = 3 studies) 1.21 (0.66 to 2.22) 

Former smokers versus never smokers (n = 5 studies) 1.01 (0.83 to 1.23) 

Current smokers versus former smokers (n = 4 studies) 1.70 (1.25 to 2.31) 

Current smokers versus former and never smokers (n = 2 studies) 1.25 (0.49 to 3.17) 

Abbreviation: CI = confidence interval. 

The authors noted that one limitation of the study was that the former smokers group 

included a broad range of exposure periods. Unfortunately, there were not a sufficient number of 

studies with data on the number of smoking pack-years to use this as the exposure variable. 

Although publication bias was not assessed formally, the authors noted that 2 of the 10 studies 

did not focus on smoking, but rather the results on smoking were incidental to the aim of the 

study and additional data were obtained from the authors of the source studies. For this reason, 

one might conclude that the potential for publication bias was reduced. Quality ratings of the 

studies were not provided, but strict selection criteria may have increased the likelihood that only 

high quality studies were included in the review. The authors of the systematic review concluded 

that current smokers are at increased risk of AD. 

We identified two additional eligible cohort studies published since the beginning of 

2005.211,212 These studies are summarized in Table 34; detailed evidence tables are provided in 

Appendix B. Both studies drew samples from the community, and one of them also included 

institutionalized individuals; one study was based on a U.S. sample and the other was conducted 

in Europe. At baseline, participants in both studies were non-demented. Length of followup 

ranged from a mean of 4 to 7 years. Both studies used self-report history of smoking obtained at 

baseline to characterize exposure. The studies used sample selection methods to minimize 

selection bias; however, neither study compared baseline characteristics to assess differences 

between exposed and unexposed. Both studies reportedly used standard criteria for the diagnosis 

of AD, but one of the studies did not use an informant report as part of the diagnostic process. 

Neither study noted whether the cognitive diagnoses were assigned blind to exposure status; 

however, the smoking analyses were not the primary outcome, so knowledge of exposure status 

may have had little effect on the outcome. Analyses were appropriate and controlled for relevant 

potential confounders, but neither study conducted a priori sample size calculations. 

Both studies showed an increased risk of AD associated with current smoking compared to 

individuals who never smoked. They also showed that current smokers without an APOE e4 

allele had an increased risk of AD, but there was no increased risk of AD associated with 

smoking for individuals with one or more e4 alleles. 
Table 34. Tobacco use and risk of developing AD – recent cohort studies 

Study Design Sample 

(n) 

Followup/ Events 

Exposure Case definition Confounding 

adjustment 

Results* 

Aggarwal et al., 2006211

Cohort Community, 

including institutionalized individuals (1064 in present analysis) 

0.4 to 6.9 years (mean 4.1; SD 0.92) 

Self-report smoking history 

NINCDS-ADRDA Age 

Sex 

170 AD cases 

Educational level Race Frequency of participation in cognitive activities APOE Time from baseline cognition 

Adjusted Current sFormer sAmong inmore APCurrent s3.12) Former sAmong ine4 allele: Current s14.65) Former s

Reitz et al., 2007212

Cohort Community 

(6868) 

Mean 7.3 years (SD 4.3) 

Self-report smoking history 

NINCDS-ADRDA Age Current sDSM Sex 2.08) 

Educational level Former sAlcohol use (0.90 to 1

555 AD cases APOE Among in

more APCurrent sFormer sAmong ine4 allele: Current s2.95) Former s

* Reference group is never smokers. Abbreviations: AD = Alzheimer’s disease; APOE = apolipoprotein E gene; APOE e4 = e 4 allele of the apolipoprotein E gene; CI = confidence interv

Statistical Manual of Mental Disorders; HR = hazard ratio; n = number of subjects; NINCDS-ADRDA = National Institute of Neurological and Comm

Stroke-Alzheimer's Disease and Related Disorders Association; OR = odds ratio; SD = standard deviation

134
In conclusion, the studies examining current smokers versus never smokers and/or former 

smokers consistently show an increased risk of AD associated with current smokers (although 

not all studies show a statistically significantly increased risk). However, former smokers do not 

appear to be at increased risk of AD. The authors of the review50 noted that there were 

insufficient data to evaluate the duration of smoking among the current and former smokers or 

the duration of abstinence from smoking among former smokers. Thus, questions about the 

amount of time it takes a former smoker to return to the level of risk of a never smoker could not 

be addressed. 

The evidence provided above refers only to smoking; the effects of nicotine itself may be 

different, as nicotine may aid specific cognitive functions such as attention, reaction time, and 

learning and memory tasks. We searched for systematic reviews and studies examining the 

association between nicotine and cognition, but (as described under Questions 3 and 4) we did 

not identify any eligible publications. 

Alcohol use. We identified a single, good quality systematic review, published in 2009, that 

examined the association between alcohol use and the development of AD.51 The review 

included nine prospective community cohort studies published between 2002 and 2006.104,118,213-

219 The nine studies included a total of 17,835 subjects; two were conducted in the United States, 

three in European countries, one in Canada, one in Japan, one in Korea, and one in China. 

Studies were selected that screened for dementia at baseline or adjusted for cognitive function at 

baseline, had at least a 12-month followup period, had AD as an outcome, and measured 

exposure to alcohol at baseline or during the followup period prior to the final followup 

examination. Study participants were non-demented at baseline. The number of individuals with 

AD versus other dementias was available for the majority of the studies. The meta-analysis 

reported was based on current use of alcohol, although some of the included studies also 

collected data on those who formerly used alcohol versus those who never used alcohol. There 

was not a structured quality assessment of the studies reported in this systematic review; 

however the strict inclusion/exclusion criteria provided an indirect assessment of quality, and the 

study characteristics for key design variables were reported. Length of followup ranged from 2 to 

7 years. No information was provided on the followup rates in the studies. The covariate 

adjustment for most studies included at least age, sex, and education; many studies included 

additional covariates such as APOE, health behaviors, biological measures, and health 

conditions. The authors of the review noted that models with the largest number of covariates 

were given priority when determining the selection for inclusion in the report. Exposure was 

determined by self-report in all studies, but the categorization of extent of current and past 

alcohol use differed across the studies. For the meta-analyses, comparisons were made between 

drinkers versus non-drinkers, light to moderate drinkers versus non-drinkers, and heavy drinkers 

versus non-drinkers. All studies with AD as an outcome used DSM and/or NINDS-ADRDA 

diagnostic criteria. 

Studies were combined using fixed-effect meta-analyses if there was no evidence of 

heterogeneity. If heterogeneity was present, random-effects models were used. Standard χ

2

 tests 

using a P value of 10 percent were used to examine heterogeneity. The test for heterogeneity was 

significant for AD for light to moderate drinkers versus nondrinkers χ

2

[5] = 11.43, P = 0.04). The 

test for heterogeneity for heavy drinkers versus nondrinkers was not significant. Publication bias 

was not formally assessed. 

The results for the various exposure definitions and the outcome of AD are reported in Table 

35. The definition for light to moderate drinker varied across the studies and ranged from 1 to 2 

135
drinks per week as a minimum to 13 to 28 drinks per week as a maximum. To summarize the 

main findings, all drinkers combined had a lower risk of AD compared to non-drinkers. Light to 

moderate drinkers also had a lower risk of AD compared to non-drinkers. Three studies provided 

results by sex and reported that light to moderate alcohol use was protective for AD in both 

males and females. However, heavy/excessive drinkers showed no difference in risk compared to 

non-drinkers. 

Table 35. Alcohol use and risk of developing AD – results from studies reviewed by Anstey et al., 200951 

 

Comparison Relative Risk (95% CI) 

Light to moderate drinkers versus non-drinkers (n = 6 studies) 0.72 (0.61 to 0.86) 

Heavy/excessive drinkers versus non-drinkers (n = 4 studies) 0.92 (0.59 to 1.45) 

Drinkers versus non-drinkers (n = 2 studies) 0.66 (0.47 to 0.94) 

Male light to moderate drinkers versus male nondrinkers (n = 3 

studies) 

0.58 (0.45 to 0.75) 

Female light to moderate drinkers versus female nondrinkers (n = 3 

studies) 

0.83 (0.81 to 0.85) 

Abbreviation: CI = confidence interval 

The authors noted that the study of alcohol use as a risk factor for late-life health outcomes is 

complicated by variation in the type of beverage used and the criteria for measuring and 

categorizing quantity. In addition, the present meta-analyses (and many other studies) are limited 

to current use of alcohol only, but alcohol patterns may change over a lifetime, and former 

drinkers may differ from lifetime abstainers. Five of the studies included in the systematic 

review either for AD or for cognitive decline collected data on former drinkers compared to 

lifetime abstainers.217-221 The cognitive outcomes for these studies were varied and included AD, 

dementia, and cognitive decline. Three of the studies218,219,221 showed no difference in the 

associations between cognitive outcome and former drinkers compared to lifetime abstainers. 

But the results from two other studies217,220 indicated that former drinkers account for much of 

the risk of cognitive impairment among non-drinkers; this suggests many former drinkers may 

have stopped drinking for reasons that also predispose to cognitive impairment, such as health 

problems. Although publication bias was not assessed formally, the systematic review authors 

noted that they included studies from article reference lists and articles that did not focus on 

alcohol use, but in which alcohol use was a covariate. For this reason, one might conclude that 

the potential for publication bias was reduced. Quality ratings of the studies were not provided, 

but strict selection criteria may have increased the likelihood that only high-quality studies were 

included in the review. 

The systematic review authors concluded that light to moderate alcohol use in late life was 

associated with an attenuated risk of AD. They further concluded that it was not clear whether 

these results reflect selection effects in cohort studies that begin in later life, a protective effect of 

alcohol consumption throughout adulthood, or a specific benefit of alcohol in late life. The 

review did not find an increased risk of AD among individuals who drank heavily, but the 

authors speculated that this may be due to selection bias given the age of the samples. 

We did not identify any additional eligible cohort studies published since June 2006. 

In conclusion, individuals who drink light to moderate amounts of alcohol in late life appear 

to be at reduced risk of AD; however further research is needed to determine whether this 

136
association is due to confounding factors. For example, there is some evidence to suggest that 

those who continue to use alcohol in late life are healthier in general which may itself lead to a 

lower risk of dementia. 

Toxic Environmental Exposures 

We identified one good quality systematic review of occupational risk factors for 

Alzheimer’s disease, focusing on the associations between AD and pesticides, solvents, 

electromagnetic fields, lead, and aluminum in the workplace.52 The review included 21 casecontrol studies and three cohort studies published between 1984 and 2003. Although case-control 

studies are a weaker design than cohort studies for establishing causality, we included casecontrol studies for this factor because of the paucity of data from cohort studies. Further, 

exposures to specific toxic substances are relatively uncommon and would require very large 

sample sizes to have sufficient power to detect an effect in general community samples. The 

number of studies and subjects for each risk factor is summarized in Table 36. Three of the 

publications reported on different exposures from the same study population. Studies were 

included if it was possible to calculate a relative risk for AD; if the exposure occurred in the 

workplace; and if the clinical diagnosis of AD was based on NINCDS-ADRDA, DSM, or ICD 

criteria. Two epidemiologists completed data abstraction and quality assessments independently; 

disagreements were resolved by consensus. Study quality was assessed using a 39-item 

assessment tool for case-control studies and a 30-item measure for cohort studies. A global 

quality index was calculated for each study and scored as the percentage of the maximum 

possible value achieved. Results were described qualitatively. 

Table 36. Toxic environmental factors and risk of developing AD – characteristics of studies reviewed by 

Santibanez et al., 200752

Risk Factor Studies* Subjects* Countries 

Solvents 10 case-control 3748 N. America (6), Western Europe (2), Asia (2) 

1 cohort 694 Canada 

Electromagnetic fields 6 case-control 6205 U.S.A. (4), Western Europe (2) 

1 cohort 20,068 U.S.A. 

Pesticides 4 case-control 

2 cohort 

1471 

2201 

Canada (2), U.S.A. (1), Australia (1) 

Canada (1), France (1) 

Lead 6 case-control 2182 U.S.A. (4), U.K. (1), Australia (1) 

Aluminum 3 case-control 1056 U.S.A. (1), U.K. (1), Australia (1) 

* Some studies examined multiple factors, and number of studies and subject counts are included for each exposure. Therefore, 

the study count in this table exceeds the 22 studies identified.

For the 24 studies, the median global quality index was 36.6 percent. The most common 

quality problems were: misclassification of the exposure (18/24), surrogate informants (12/17), 

misclassification of the disease (11/24), and selection bias in 10 studies. Study quality was 

judged to be higher for pesticide exposures. Two cohort studies reported higher adjusted relative 

risks for AD with exposure to defoliants and fumigants (RR 4.35; 95 percent CI 1.05 to 17.90)222

137
and pesticides in men (RR 2.39, 1.02 to 5.63).223 Two higher quality case-control studies137,224

found small, non-statistically significant associations between pesticides and AD. 

Other exposures were reported to show less consistent associations. Of the 11 studies 

evaluating solvents, two found a statistically significant association with AD. However, these 

two studies were from the same population base. The single cohort study evaluating solvent 

exposure222 did not find an association with AD (RR 0.88; 95 percent CI 0.31 to 2.50). Studies of 

lead exposure were all case-control design and assessed as low quality; none showed a 

statistically significant association with AD. One study of aluminum exposure was a higher 

quality case-control study and found no association with AD (RR 0.95; 95 percent CI 0.5 to 

1.9).225 Similarly, the two lower quality case-controls studies226,227 did not find any association 

between aluminum and AD. 

Our search identified two additional studies on the exposures of interest, one evaluating 

aluminum exposure and one evaluating blood mercury levels. Rondeau et al.228 followed a 

community sample of 1925 non-demented adults, age 65 and older, for a mean of 11.3 years. 

Aluminum exposure was estimated using a food frequency questionnaire that assessed tap water 

consumption, coupled with chemical analysis of aluminum levels in drinking water. The estimate 

of aluminum intake is not well validated, and followup rates were not given. The risk of AD was 

increased for aluminum intake ≥ 0.1 mg/day (RR 1.34; 95 percent CI 1.09 to 1.65); no doseresponse relationship was observed. This observation of elevated risk differs from the finding of 

no association in three previous case-control studies. Using a subgroup from the Canadian Study 

of Health and Aging (15 percent of the cohort), Kroger et al.81 used a nested case-control design 

to evaluate the association between blood mercury levels and AD. After a median of 4.9 years, 

individuals in the 3rd (OR 0.41; 95 percent CI 0.23 to 0.74) and 4th quartiles of exposure (OR 

0.56, 0.32 to0.99) were at lower risk for AD. However, the relatively low participation rate may 

have introduced significant selection bias. We did not identify any studies on Agent Orange or 

gulf war syndrome. 

In summary, few cohort studies have examined the association between toxic-environmental 

exposures and risk of AD. Most case-control studies have important methodological limitations 

that may bias the results. Among the exposures considered, only pesticides showed a consistent 

association with AD. 

Genetic Factors 

After age, family history is the strongest risk factor for the development of Alzheimer’s 

disease. As early as the 1920s, there were reports of a few families with many individuals with 

AD across more than one generation, suggesting a genetic contribution to the disease (for a 

review, see Kennedy et al., 1994229). Twin studies provided further support for the role of genes 

in the etiology of AD. Heritability is defined as the proportion of disease liability attributable to 

genes, and it can be estimated from the difference in disease concordance rates for monozygotic 

twin pairs compared to dizygotic pairs. Estimates of heritability of AD from twins studies have 

ranged from 0.33 to 0.74,230-232 indicating a moderate genetic contribution. The genetics of AD, 

however, are complex, with fully penetrant autosomal dominant mutations responsible for earlyonset disease (onset prior to 60 years of age) and other genetic susceptibility factors responsible 

for the much more common late-onset disease (> 95 percent of cases). Mutations in three 

different genes have been identified that cause early-onset AD, but these account for a small 

minority of individuals with AD. Disease-causing mutations in these genes, amyloid precursor 

138
protein (APP) gene and presenilin 1 and 2, are completely penetrant, and most individuals who 

inherit these mutations become symptomatic in their thirties or forties. These three genes also 

play a role in amyloid formation, strengthening the argument that amyloid deposition is a key 

factor in disease pathogenesis. Individuals who inherit a disease-causing mutation in one of these 

genes will develop AD unless they die prematurely from other causes. Genetic testing is 

commercially available for each of these early-onset disease genes. In contrast to early-onset 

AD, no classically Mendelian genetic influences have been found for the much more common 

late-onset AD. 

The literature on genetic influences on late-onset AD is extensive. AlzGene, a regularly 

updated genetic database that compiles association studies on AD (http://www.alzgene.org/), 

reports data from 1355 studies examining 660 genes (Website updated January 29, 2010; 

accessed January 31, 2010).53 AlzGene includes only studies published in peer-reviewed journals 

and performs meta-analyses on genetic polymorphisms that have been examined in at least four 

case-control samples. Meta-analyses are updated as more data are published, but family-based 

studies are not included in meta-analyses. Odds ratios and 95 percent confidence intervals are 

calculated for all polymorphisms with minor allele frequencies greater than one percent in 

healthy controls using a random-effects model with weights that incorporate within- and 

between-study variance. Data are presented for all studies and then separately after excluding 

studies in which in which the Hardy-Weinberg equilibrium criteria have not been met. To avoid 

including overlapping data, usually only the largest sample is included for analysis. 

The meta-analyses performed in AlzGene are graded based on the amount of data available 

for a polymorphism, consistency of replication, and an assessment of bias. The data are graded 

from “A” to “C” based on the number of minor alleles in the case and control population. A 

grade of A requires > 1000 minor alleles, B between 100 and 1000, and C < 100. Consistency of 

replication is determined by I2 point estimates: A = < 25 percent; B = 25 to 50 percent; and C = 

> 50 percent. Sources of bias that are considered include errors in phenotyping, genotyping, and 

population sources, as well as publication bias. Publication bias is assessed with a Beggmodified funnel plot depicting allele-specific ORs for each study versus its standard error on a 

semi-logarithmic scale. Summary ORs from meta-analyses are also graded based on their 

deviation from 1.0. Studies with summary ORs < 1.15 or ORs > 1.15 with evidence of 

publication bias receive a grade of C, acknowledging that occult biases and selective reporting 

may invalidate the proposed association. Studies that lose statistical significance after exclusion 

of the original publication or studies violating Hardy-Weinberg equilibrium are also given a 

grade of C. An overall assessment of association credibility is based on the overall score. 

Credibility is “strong” if a gene received three A grades; “moderate” if it receive at least one B 

grade and no C grades; and “weak” if it receives any C grades. 

Apoliprotein E (APOE = gene; ApoE = protein) is the single most-validated genetic 

susceptibility factor in AD (overall AlzGene grade A). APOE has three common polymorphisms 

(e2, e3 and e4) that introduce an amino acid change in APOE. Inheriting one or two copies of 

APOE e4 increases the risk of developing AD in a dose-dependent fashion, while inheriting an 

e2 allele reduces risk. Case-control studies examining the association of APOE and AD are 

reported for Caucasian (28 studies), Asian (5 studies), African-descent (2 studies), Hispanic (1 

study), and other or mixed origin populations (1 study). All studies reported increased risk of AD 

in subjects with APOEe4. A meta-analysis of 38 studies by AlzGene produced a summary OR of 

3.68 (95 percent CI 3.30 to 4.11) for the e4 versus e3 alleles. The lower limit confidence interval 

excluded 1.0 in 36 of the 38 studies included in the analysis. A meta-analysis of 37 studies 

139
examining the association of APOE e2 on the development of AD demonstrated a protective role 

for this allele (summary OR 0.621; 95 percent CI 0.456 to 0.85 ). The studies used for the 

AlzGene meta-analysis were originally compiled and analyzed by Farrer et al.,233 with some data 

removed because they were derived from family studies, not published in English, or concerned 

unpublished genotype data. The results reported by Farrer and colleagues were qualitatively 

identical to the subsequent AlzGene analysis. They also provided summary ORs for the risk of 

developing AD for each genotype compared to the reference genotype APOE e3/e3; these were 

(OR; 95 percent CI): e2/e4, 2.6 (1.6 to 4.0); e3/e4, 3.2 (2.8 to 3.8); e4/e4, 14.9 (10.8 to 20.60); 

e2/e2, 0.6 (0.2 to 2.0); and e2/e3, 0.6 (0.5 to 0.8). No other susceptibility gene in AD approaches 

the statistical level of APOE. The literature suggests that there are racial and ethnic differences in 

the strength of the association between APOE genotype and AD. The APOE e4 association with 

AD is stronger in people of Japanese ancestry and weaker among African-Americans and 

Hispanics than among Caucasians, but there was significant heterogeneity in the ORs in studies 

of African-Americans (p < 0.03). APOEe2 also appears to be associated with protection from 

AD in Asians (OR for e2 vs. e3 0.548; 95 percent CI 0.277 to 1.08). Additional studies in 

African-Americans, Asians, and Hispanics are needed to establish a definitive risk estimate. The 

APOE e4 effect is age-dependent, with a major contribution to risk in people between the ages of 

40 and 90 years, but the effect diminishes after the age of 70. 

Nine other gene polymorphisms received a grade of A using AlzGene criteria. Clusterin 

(CLU), also called apolipoprotein J, located on chromosome 8, has been linked to AD in nine 

case-control samples. The OR for all samples was less than 1, with a summary OR for all studies 

of 0.86 (95 percent CI 0.82 to 0.89). A publication of these findings by two groups in separate 

GWAS studies involving approximately 30,000 subjects identified CLU rs11136000 as the 

single nucleotide polymorphism (SNP) with the greatest OR, other than APOE (P = 1.4 x 10-9

and P = 7.5 x 10-9 in the two studies.234,235 By comparison, the P value for the most significant 

SNP in the APOE locus in one of the studies was 1.8 x 10-157.

234 CLU expression is increased in 

a number of pathologic conditions involving brain injury or inflammation and binds soluble 

amyloid beta peptide, which may be relevant to AD pathogenesis. Phosphatidylinositol binding 

clathrin assembly protein (PICALM; also known as clathrin assembly lymphoid-myeloid 

leukemia gene [CALM]), located on chromosome 11, was also identified in a GWAS analysis of 

more than 16,000 individuals and received an A grade in AlzGene.234 The OR for PICALM was 

less than 1.0 in 6 of 6 case-control samples examined, and in 5 of 6 samples the 95 percent CI 

excluded 1.0. The AlzGene summary OR for association of PICALM with AD was 0.87 (95 

percent CI 0.83 to 0.91). PICALM is located on chromosome 11, is involved in clathrinmediated endocytosis, and may play a role in synaptic vesicle fusion. Synaptic density is 

correlated with cognitive decline in AD, suggesting that this may be relevant to pathogenesis. 

Sortilin-related receptor (SORL1) is a low-density lipoprotein receptor relative located on 

chromosome 11 that has been associated with risk of AD. An AlzGene meta-analysis of 21 

studies reported an OR of 1.10 (95 percent CI 1.03 to 1.71), with I2

 = 33. A locus on 

chromosome 14 called GWA 14q32.13 was identified as associated with AD in five studies. The 

meta-analysis OR for GWA 14q32.13 was 0.84 (95 percent CI 0.77 to 0.93). No associated gene 

has been identified with this polymorphism. Tyrosine kinase, non-receptor 1 (TNK1) has been 

examined in five case-control populations involving 10,920 people. Three samples showed a 

positive association of TNK1 with AD with 95 percent CIs excluding unity, two showed a trend, 

and one had an OR > 1. A meta-analysis of five datasets of TNK1 by AlzGene produced a 

summary OR of 0.84 (0.76 to 0.93). Angiotensin 1 converting enzyme (ACE) has been examined 

140
in 57 case-control studies, with 20 studies showing positive results, 6 trending positive, and 22 

showing negative results. Separate analysis was not available for six studies. A meta-analysis of 

ACE polymorphism rs1800764 in five datasets found a summary OR of 0.83 (95 percent CI 0.72 

to 0.95), suggesting a protective effect for genetic variants in this gene. Two other singlenucleotide polymorphisms (SNPs) within this gene also produced significant results in metaanalysis. 

Inflammation has been implicated in the pathogenesis of AD, and interleukin 8 (IL8) has 

been examined as a candidate gene in four case-control studies. A meta-analysis of these four 

studies reported an OR of 1.27 (95 percent CI 1.08 to 1.50; I2

 = 0), suggesting that different 

genotypes of IL8 modify an individual’s risk of developing AD. The low-density lipoprotein 

receptor (LDLR), located on chromosome 19, has also been identified as a genetic modifier of 

AD. An AlzGene meta-analysis of four studies found an OR of 0.85 (95 percent CI 0.72 to 0.99). 

A caveat about the validity of ORs determined by meta-analysis is necessary here. The final gene 

with an AlzGene grade of A is Cystatin C. Cystatin C is a member of the cystatin gene family 

that contains proteins with cysteine protease activity; it has been examined in 19 case-control 

studies. Six studies reported an association, and 10 studies were negative. A meta-analysis of 

four datasets found a summary OR of 1.28 (95 percent CI 1.04 to 1.56) for the association of 

cystatin C with AD. It should be noted that meta-analysis ORs can be skewed by publication 

bias, producing inflated estimates if negative studies are less likely to be published. 

A number of genome-wide association studies (GWAS) involving thousands of patients and 

hundreds of thousands of polymorphisms have been performed in AD, but apart from the studies 

identifying CLU and PICALM noted above, most have identified genetic variants of marginal 

statistical significance. Almost all AD GWAS have confirmed the association between the region 

containing APOE and AD, but detection of other polymorphisms has varied between studies 

despite regular use of validation sets to confirm results. Variability in results between studies 

could be the result of differences in populations or could be caused by spurious associations as 

the result of multiple hypothesis testing. At present, most GWAS results are best viewed as 

suggestive, with need for independent confirmation and demonstration of biological relevance to 

disease pathogenesis. 

In summary, autosomal-dominant, early-onset AD is associated with mutations in three 

genes. APOE is the only well-validated susceptibility gene for late-onset AD, but a number of 

promising candidates have been identified, including those listed above. Additional data are 

necessary to confirm the relationship of these genes with AD and to demonstrate their biologic 

relevance to pathogenesis. 

Key Question 2 – Factors Associated with Reduction of 

Risk of Cognitive Decline 

Key Question 2 is: What factors are associated with the reduction of risk of cognitive decline 

in older adults? 

Nutritional and Dietary Factors 

B vitamins and folate. We identified five eligible cohort studies that examined the 

association between folate and B vitamins and cognitive decline.56,236-239 These studies are 

141
142

summarized in Table 37; detailed evidence tables are in Appendix B. All five studies reported 

either continuous variable outcomes or multiple levels of categorical outcome (e.g. quintiles). 

Three of the studies used community samples in the U.S.,56,236,238 one used a community sample 

in Europe,239and the fifth used a clinical sample in Europe.237 Two studies were based on the 

same sample, but one used niacin56 and the other used folate and B12 levels236 to predict 

cognitive decline. For all studies, participants were non-demented at baseline. The length of 

followup ranged from 5.5 to 10 years. All studies used sample selection methods to minimize 

selection bias. Three of the studies used plasma/serum levels of B vitamins and folate.237-239 The 

other two studies estimated dietary and supplement intake of B vitamins and folate based on selfreported information collected using modified Harvard food frequency questionnaire. This group 

has previously reported results from a study that aimed to validate food frequency 

questionnaires. Three studies compared baseline characteristics between those exposed and 

unexposed.56,236,239 The case definitions and measures of cognitive change for the studies are 

described in Table 37. The analyses appear generally appropriate, and most controlled for 

relevant potential confounders, including homocysteine and the other predictor variables (i.e., 

folate, B vitamins). None of the studies conducted a priori sample size calculations. 

One study examined the association between niacin (B3) and cognitive change over time.56

Investigators reported that higher dietary intake of niacin was generally associated with a modest 

protective effect on cognition; however, the results were only significant in subgroups of 

individuals without stroke or myocardial infarction or individuals with baseline cognitive scores 

in the upper 85 percent of the sample. When total niacin intake, including supplements, was 

evaluated there was no significant association between niacin intake and cognitive decline. The 

findings on folate were in opposite directions, with one study that used self-reported intake of 

nutrients reporting that higher levels of folate were associated with higher rates of cognitive 

decline,236 and another study that used plasma levels of folate reporting that low levels of folate 

were associated with greater cognitive decline.238 A third study that used serum levels of folate 

did not show any association between folate levels and cognitive change.237 In general, the 

studies did not show any association between either B12 or B6 and cognitive decline, except in 

select subsamples.236 In addition, there were inconsistent findings for the association between 

cognitive decline and holotranscobalamin and methylmalonic, markers that are related to B12 

levels and function. One study showed no association between these markers and cognitive 

change,239 while another237 reported that doubling holotranscobalamin levels resulted in a slower 

rate of decline on the MMSE, and a doubling of methylmalonic acid levels resulted in a more 

rapid rate of decline. An explanation for the discrepancy in findings using plasma markers for 

B12 is not obvious, as the measures of central tendency for the baseline levels of the markers 

were not markedly different between the studies. The studies did differ in the source of the 

sample, with one being a community sample and the other being a clinical registry. In addition, 

the cognitive measures used to measure change differed between the studies; inconsistent results 

have frequently been reported both within and between studies on many exposures for different 

cognitive measures. 

In conclusion, there is no consistent evidence to support an association between cognitive 

decline and exposure to niacin, folate, B12, or markers for B12 based on estimated intake or 

plasma levels of these factors. The preponderance of the limited studies on these exposures 

reports no association between these factors and cognitive change over time. Inconsistencies in 

the findings reported here may be due to a number of factors, including differences in both the 

types and quality of the exposure, the outcome measures, and sample characteristics. 
Table 37. B vitamins and folate and risk of cognitive decline 

Study Sample (n) Followup Exposure Case definition Confounding 

adjustment 

Results 

Morris et al., 200456

(Same sample as Morris et al., 2005236) 

Community cohort (3718) 

5.5 years (median) 

Estimates of total intake of niacin (B3) during the previous year were calculated from selfreport responses on a modified Harvard food frequency questionnaire 

Global composite index of scores on the MMSE, the immediate and delayed recall of the East Boston Story, and the oral version of the Symbol Digit Modalities Test 

Age Race Sex Educational level APOE Time between assessments Sample weights Vitamin E Vitamin C Beta-carotene Multiple vitamin use DM HTN Smoking Alcohol use Stroke Heart disease Folate 

Food intakprotective decline, budid not rea(beta-coefp = 0.12). MI (beta-c0.010; p = scores (be= 0.011; p the results significanc(including significant change ov

Morris, et al., 2005236

(Same sample as Morris et al., 200456) 

Community cohort (3718) 

5.5 years (median) 

Estimates of total intake of folate and vitamin B12 during the previous year were calculated from self-report responses on a modified Harvard food frequency questionnaire 

Global composite index of scores on the MMSE, the immediate and delayed recall of the East Boston Story, and the oral version of the Symbol Digit Modalities Test 

Age Race Sex Educational level Time between assessments Vitamin E Vitamin C Multivitamin 

Total intakquintiles dlowest quiquintile = 0Folate intaquintiles gfaster than for 5th quin

Intake of vvitamin susignificantcognitive c

143
Study Sample (n) Followup Exposure Case definition Confounding 

adjustment 

Results significant intake of Binteraction rate of decyear-old wsupplemevitamin B1the rate of consumed allowance 

Clarke et al., 2007237

Clinical cohort –from general medicine clinical registry (691 analytical sample) 

10 years Serum levels of B-12, 

folate, holotranscobalamin (the biologically active fraction of vitamin B-12) and methylmalonic acid (an indicator of vitamin B-12 function) were used as markers of vitamin B-12 status 

Change in MMSE over time 

Age Sex Smoking Vascular disease Systolic BP Education APOE Levels of other vitamins being assessed 

Only holotmethylmalsignificant change ovholotranscin an addit0.59 (0.30 methylmalan additio0.65 (-0.98 folate did associatio

Kado et al., 2005238 Community cohort 

(499 analytical sample) 

7 years Plasma levels of folate, 

B6 and B12 

Summary cognitive score of measures assessing confrontational naming, delayed recall of items named, spatial recognition memory, concept similarities, and constructional praxis copying 

Age Sex Education Baseline physical function Smoking Plasma levels of other predictors (B6, B12, folate, homocysteine) 

In multivarhomocystetogether in folate levedecline (risto 2.31; P B12 levels cognitive c

De Lau, et al., 2009239 Community cohort 

(1019) 

7 years Plasma B12 and 

transport (metabolites transcobolamin and holotrans-coboloamin, methylmalonic acid) 

Longitudinal decline on an abbreviated Stroop test, verbal fluency test, Letter-Digit Substitution Task, 

Age Sex Education Creatinine Homocysteine 

No associbetween a(including quintiles) adecline duresults not 

144
145

Study Sample (n) Followup Exposure Case definition Confounding 

adjustment 

Results 

Memory Scanning Test, 15-word memory test Combined tests created summary scores for psychomotor speed, memory, and global cognition 

Folate DM BP Alcohol use Smoking Vitamin supplements Depression Carotid intima-media thickness 

Abbreviations: APOE = Apolipoprotein E gene; BP = blood pressure; CI = confidence interval; DM = diabetes mellitus; HTN = hypertension; MI = m= Mini-Mental State Examination; SE = standard error
Other vitamins. We identified eight eligible cohort studies that examined the association 

between cognitive decline and vitamins C or E, beta carotene or flavonoids.67,70,240-245 This 

summary will focus on the two studies with categorical outcomes.67,244 A brief overview of the 

other studies using continuous outcomes of decline will be given, but a detailed review of these 

studies will not be provided because they do not change the conclusion from the two studies with 

categorical outcomes. The two studies reporting categorical variable outcomes are summarized 

in Table 38; detailed evidence tables for all of the studies are in Appendix B. One of the studies 

used a community sample in Europe,244 and the other used a Canadian sample comprised of both 

community and institutionalized individuals.67 One study stated that participants were nondemented at baseline,67 and it is assumed here (although not explicitly stated by study 

investigators) that the participants were non-demented at baseline in the other study.244 The 

length of followup ranged from 3 to 5 years. One study used sample selection methods to 

minimize selection bias.244 The other study67 used selection methods that partially addressed 

selection bias because they used a subsample from a larger cohort study, of which a 

disproportionate segment of the sample was at relatively high risk of cognitive impairment; part 

of this study sample was drawn from institutionalized participants (20 percent), and part from 

community participants. One study244 used self-reported information to estimate food and 

supplement intake of vitamins C and E, beta carotene, and flavonoids. The other study used selfreported vitamin supplement use confirmed by inspection of medication container for the 

community residents and medical records for the institutionalized participants.67 

One study compared baseline characteristics between those exposed and unexposed.67 The 

case definitions for the studies are described in Table 38. The analyses appear generally 

appropriate and were controlled for relevant potential confounders. Neither study conducted a 

priori sample size calculations. One study reported no association between cognitive decline and 

vitamins E or C, beta carotene, or flavonoids.244 The other study reported no association between 

cognitive decline and vitamins E or C separately, but did show a protective association for any 

vitamin use and combinations of multivitamins and vitamins C and E.67

To briefly summarize the studies reporting continuous outcomes of cognitive decline, we 

note that two studies were based on the same sample, with one reporting the association between 

cognitive decline and vitamins C and E,242 and the other adding NSAIDs to the list of 

predictors.240 Another two studies were based on the same sample with some differences in how 

vitamin E intake was estimated.70,241 Two studies defined exposure levels using blood 

samples,243,245 and the others based exposure levels on self-reported information. Four of the 

studies stated that participants were non-demented at baseline,70,240-242 and it is assumed here that 

the vast majority of subjects in the other two studies243,245 were non-demented at baseline based 

on the relatively young mean baseline age. Of the six studies defining cognitive decline as a 

continuous measure, only two studies that were based on the same sample reported a protective 

effect of vitamin E (but not vitamin C) on cognition.70,241 However, for one of these studies,241

the risk estimates for vitamin E and cognitive decline were not consistently in the same direction 

for all quintile levels of vitamin E. 

In conclusion, the findings on vitamins E and C, beta carotene, and flavonoids provide no 

consistent support for a protective association between these nutrients and cognitive decline. 

146
Table 38. Other vitamins and risk of cognitive decline 

Study Sample (n) Followup Exposure Case definition Confounding 

adjustment 

Results 

Kalmijn et al., 1997244 Community cohort 

(342) 

3 years Estimates of intake of beta 

carotene, vitamins C and E, and flavonoids were calculated based on selfreported responses provided on a cross-check dietary history interview administered by a dietician. This information was based on food consumption pattern during the preceding 2 to 4 weeks Information combined for interviews 5 years preceding baseline and baseline 

Cognitive decline defined as > 2-point decline 

Age Educational level Smoking Alcohol use Energy intake Baseline cognitive status 

No assodecline and C, flavonoranged 

Maxwell et al., 200567 Community cohort (but 

also some nursing home residents) (894) 

5 years For non-institutionalized 

individuals, self-reported information on supplemental vitamin E and C use. Sometimes confirmed by review of medication bottle. For institutionalized individuals information on supplemental vitamin E and C use from medical record 

Cognitive decline defined as a decrease ≥ 10 points 

on the 3MS from Time 1 to Time 2 

Age Sex Educational level Blood pressure Baseline cognitive status Institutional residence 

CognitivVitamin multivitalower ris0.51, 95Any vitalower ris(OR: 0.5Vitamin associa(OR 0.6Vitamin associa(OR 0.8

Abbreviations: 3MS = Modified Mini-Mental State Examination; CI = confidence interval; OR = odds ratio 

147
Gingko biloba. We identified no systematic reviews or studies evaluating the use of gingko 

biloba and risk of cognitive decline. 

Omega-3 fatty acids. We identified two good quality systematic reviews evaluating the 

association between omega-3 fatty acids and risk of cognitive decline.29,30 We discuss the more 

recent (2009) review by Fotuhi et al.29 The review included three cohort studies published 

between 2003 and 2007. The three studies included a total of 4174 subjects; one each was 

conducted in the United States, France, and The Netherlands. Prospective observational studies 

were selected that addressed the specific association between any form of omega-3 fatty acids 

and cognitive change in participants age 65 or older. There was not a structured quality 

assessment of studies reported in this systematic review; however, study characteristics for key 

design variables were reported, and study selection criteria focused the review on higher quality 

studies. In two studies, cognitive testing at baseline excluded participants with dementia, and the 

third study recruited normal volunteers. Length of followup ranged from 4 to 6 years. No 

information was given on followup rates. Covariate adjustment included age, sex, education, and 

baseline cognitive function. Omega-3 fatty acid intake was estimated by dietary histories in two 

studies;246,247 the third248 measured erythrocyte membrane fatty acid content. Dietary histories 

were used in one study to classify exposure as the number of fish-containing meals per week and 

in the other study to estimate the levels of DHA and EPA from fish and other sources. Because 

of significant heterogeneity in study design, results were synthesized qualitatively. Adjusted 

results were reported and are summarized in Table 39. Each of the three studies showed an 

association between greater exposure and less cognitive decline. 

The authors of the systematic review concluded that the existing evidence favors a role for 

long chain omega-3 fatty acids in slowing cognitive decline in older adults. 

Table 39. Omega-3 fatty acids and risk of cognitive decline – study characteristics and results from studies 

reviewed by Fotuhi et al., 200929

Study Subjects Exposure Outcome Results 

Heude 

et al., 

2003248

245 men Erythrocyte 

membrane lipid 

composition (total 

omega-3 PUFA, 

omega-3: omega-6 

fatty acid ratio and 

DHA:AA ratio 

Cognitive decline 

measured as ≥ 2-

point drop in 

MMSE scores 

Higher proportions of omega-3 fatty acid levels 

in blood were associated with less cognitive 

decline. 

Total omega-3 PUFA: OR 0.59 (95% CI 0.38 

to 0.93); 

Omega-3:omega-6 fatty acid ratio: OR 0.55 

(0.33 to 0.91) 

DHA:AA ratio: OR 0.57 (0.35 to 0.92) 

Morris 

et al., 

2005246

3718 

participants 

Fish meals per 

week (0, 1, 2) 

Change in global 

cognitive decline 

estimated from 

mixed models 

Rate of annual decline decreased by 10 to 

13% among individuals who consumed one or 

more fish meals weekly 

Van 

Gelder 

et al., 

2007247

210 men Fish consumption; 

DHA and EPA 

estimated from fish 

and other foods 

Cognitive decline 

by MMSE 

A linear trend was seen between high intake of 

EPA plus DHA and reduced 5-year cognitive 

decline (p = 0.01) 

Abbreviations: AA=arachidonic acid; CI = confidence interval; DHA= docosahexanenoic acid; EPA = eicosapentaenoic acid; 

MMSE = Mini-Mental State Examination; OR = odds ratio; PUFA = polyunsaturated fatty acid 

148
149

Our search identified two additional studies (described in three publications) examining the 

relationship between omega-3 fatty acids and cognitive decline.249-251 The study characteristics 

are summarized in Table 40. Both studies enrolled participants with a mean age < 65 and thus 

were not included in the review by Fotuhi et al.29 Beydoun et al. reported results from dietary 

assessment250 and plasma omega-3 fatty acids249 separately. Participants drawn from four U.S. 

communities (n = 7814) were followed for 6 years; outcomes were reported as reliable change 

index for three tests. Adjusted analyses showed that higher long chain omega-3 fatty acid intake 

was associated with less risk of decline as assessed by the delayed word recall and verbal fluency 

(controlled oral word association) tests, but not as assessed by the digit symbol substitution test 

or global cognition. An analysis of the 2251 participants with plasma omega-3 fatty acid 

measurements showed that higher total n-6 PUFAs decreased the risk of global cognitive decline. 

Total omega-3 PUFAs (OR 0.84; 95 percent CI 0.66 to 1.05), EPA, and DHA were not 

associated with risk of global cognitive decline. Consistent with the analysis by dietary history, 

higher levels of DHA and EPA were associated with less decline in verbal fluency. 

The second study251 was a secondary analysis from a 3-year RCT of folic acid in 404 subjects 

with elevated homocysteine levels. Total omega-3 fatty acid was measured at baseline. Cognitive 

change was measured with five tests evaluating memory, processing speed, word fluency, 

sensorimotor speed, and complex speed. Higher plasma omega-3 PUFAs were associated with 

less decline in sensorimotor speed (p = 0.02) and complex speed (p < 0.01), but not memory, 

information processing speed, or word fluency. 
Table 40. Omega-3 fatty acids and risk of cognitive decline – recent cohort studies 

Study Sample (n) Followup Exposure Case definition Confounding adjustment Results Beydoun et al., 2007249

(subsample from Beydoun et al., 2008250) 

Community (2251) 

6 years Total plasma n-3 

fatty acids; EPA; DHA 

Reliable change index for 3 tests: COWA, DSST and delayed word recall tests 

Age Sex Education 

Mean age 56 to 57 

Smoking Alcohol use Caffeine use Physical activity index BMI Dietary factors Baseline cognition 

Higher total n-6 0.37 to 0.81) decognitive declinNeither total n-3 0.66 to 1.05), nodecreased risk oGreater DHA anwith less decline 

Beydoun et al., 2008250 Community (7814) 

Mean age 57 

6 years Dietary 

assessment of n3 fatty acid intake; analyzed as percentage of energy intake and ratios of fatty acids 

Reliable change index for 3 tests: COWA, DSST and delayed word recall tests 

Age Race Sex Education Baseline cognition APOE Behavioral factors Nutritional factors HTN 

Higher long-chaassociated with DWR (OR 0.90, COWA (OR 0.8DSST or global association afteexposure meas

Dullemeijer et al., 2007251

Cohort drawn from RCT of folic acid 

3 years Total plasma n-3 

fatty acids 

Change on 5 cognitive tests evaluating: memory, processing speed, word fluency, sensorimotor speed and complex speed 

Age Sex Education Baseline cognition Erythrocyte folate 

(404) 

Alcohol use Mean age 

60 

Higher plasma nless decline in s0.02) and compnot memory, infspeed or word f

Abbreviations: APOE = apolipoprotein E gene; BMI = body mass index; CI = confidence interval; COWA = Controlled Oral Word Association; DHA 

DSST = Digit Symbol Substitution Test; DWR = delayed word recall test; EPA = eicosapentaenoic acid; HR = hazard ratio; HTN = hypertension; OR 

polyunsaturated fatty acid(s); RCT = randomized controlled trial; RR = relative risk; SD = standard deviation 

150
In summary, the effects of n-3 fatty acids on cognitive decline have been evaluated in five 

prospective longitudinal studies. Studies vary substantially in measurement of n-3 fatty acids, 

participant characteristics and outcome measures. Each study reports a positive association 

between at least one measure of PUFAs and a measure of cognition. However, some results are 

conflicting. Heude et al.248 found that higher total omega-3 PUFA and higher omega-3:omega-6 

fatty acid ratios were associated with less risk of cognitive decline, while Beydoun et al.249 found 

that higher n-6 PUFAs but not total plasma n-3 PUFAS reduced cognitive decline. Another 

analysis by Beydoun et al.250 found that higher plasma DHA and EPA were associated with less 

decline in verbal fluency, but had no effect on global cognition, while Dullemeijer et al.251 found 

no association between plasma n-3 PUFAs and verbal fluency but positive effects on 

sensorimotor and complex speed. Some studies compared multiple measures of exposure with 

multiple measures of cognition, increasing the risk for detecting spurious associations. The 

positive results could be explained by residual confounding. Eating fish might be a proxy for 

individuals with healthier lifestyles than those who do not eat fish and effects on cognitive 

decline might have little to do with fish consumption. Despite these cautions, these studies 

support the possible association between higher consumption of PUFAs and less cognitive 

decline. 

Other fats. We identified one eligible cohort study that examined the association between 

cognitive decline and fat intake.252 The study is summarized in Table 41; a detailed evidence 

table is provided in Appendix B. The study used a community sample in the United States. 

Participants were non-demented at baseline. The median length of followup was 5.6 years. The 

study used sample selection methods to minimize selection bias. It used self-reported 

information to estimate fat intake. Based on a validation substudy, the authors reported the 

Pearson correlations for comparative validity with 24-hour dietary recalls were 0.40 for 

monounsaturated fat, 0.47 for saturated fat, 0.36 for polyunsaturated fat, and 0.39 for cholesterol. 

The study compared baseline characteristics between those exposed and unexposed. The case 

definitions for the studies are described in Table 41. The analyses appear appropriate and were 

controlled for relevant potential confounders. The study did not conduct a priori sample size 

calculations. 

The study showed that higher intake of saturated fats and trans-unsaturated fats were linearly 

associated with greater cognitive decline. But total fat, vegetable and animal fat, and cholesterol 

were not associated with cognitive change over time. In another study on this same sample,253

the authors noted an interaction between copper intake and fat intake in that higher copper intake 

was associated with greater cognitive decline in subjects with high saturated and trans fats 

intake. 

In conclusion, there is a single study each addressing risk of AD and risk of cognitive decline 

associated with dietary fat intake. The two studies provide preliminary evidence for a deleterious 

association between increased saturated fat and trans fat intake and risk of AD or cognitive 

decline. Further research is needed both to validate self-report exposure measures of dietary 

intake and also to confirm the findings in the present study. 

151
Table 41. Intake of various types of fat and risk of cognitive decline 

Study Sample (n) Followup Exposure Case definition Confounding 

adjustment 

Results 

Morris et al., 2004252 Community cohort 

(2560) 

5.6 years Estimates of total 

intake of various types of fat during the previous year were calculated from self-report responses on a modified Harvard food frequency questionnaire 

Cognitive decline on standardized composite measure from all tests 

Age Race Sex Educational level Total energy from calories Smoking Alcohol use Time between assessments HTN Vitamin C Vitamin E

Higher intake o0.04) and trans= 0.07) were ligreater decline years. When echanged patteyears and/or th15%, effect beTotal fat, vegecholesterol not change 

Abbreviation: HTN = hypertension

152
Trace metals. We did not identify any systematic reviews evaluating the association 

between trace metals and cognitive decline. Our search identified three primary research 

publications245,253,254 from two cohort studies. 

Selenium. Selenium is an antioxidant and constituent of brain selenoproteins that may be 

important for the maintenance of brain functions. The association between plasma selenium and 

cognitive change was described in two publications from the same community-based cohort 

conducted in older adults with normal cognition from the Nantes district of France.245,254 These 

publications are summarized in Table 42; detailed evidence tables are provided in Appendix B. 

Subjects were recruited in part from advertisement campaigns that may introduce selection bias. 

It is assumed here that the majority of participants were non-demented at baseline based on the 

relatively young age at baseline for both studies and the lengthy followup period in one of the 

studies.254 Followup rates were 84 percent at 4 years and 54 percent at 9 years. Analyses were 

adjusted for multiple potential confounding variables. Berr et al.245 described the relationship 

between baseline selenium levels and at least a 3-point decline on the MMSE at 4 years. 

Selenium levels below the 25th percentile increased the risk for cognitive decline (OR 1.58; 95 

percent CI 1.08 to 2.31). Akbaraly et al.254 reported the association between change in plasma 

selenium levels and declines on four cognitive measures. Analyses were conducted to examine 

the 2- and 9-year change in selenium with the four cognitive measures, evaluating change in 

cognition as both a continuous measure and as a dichotomous variable using two separate 

thresholds. Analyses were not adjusted for multiple comparisons. Two-year change in plasma 

selenium was not associated with change in cognition. When change in cognition was analyzed 

as a continuous variable, the 9-year change in selenium was associated only with the MMSE. 

When cognition was analyzed as a dichotomous variable (10th or 25th percentile of decline), 

change in plasma selenium was associated with declines in the finger tapping test. Associations 

with other cognitive measures were inconsistent depending on the threshold for cognitive 

decline. 

In summary, the results of one of these studies provide limited support for a possible 

association between baseline selenium and cognitive decline. However, a number of issues raise 

concerns about the robustness of this finding, namely: the potential selectivity of the sample, the 

lack of an association with change in selenium level and cognitive change, and the modest effect 

size that may indicate confounding due to other factors. 

153
Table 42. Plasma selenium levels and risk of cognitive decline* 

Study Sample (n) Followup Exposure Case definition Confounding 

adjustment 

Results 

Berr et al., 2000245 Community cohort 

(1389) 

4 years Plasma selenium MMSE decline of 

≥ 3 points 

Age Sex Educational level Baseline cognitive status Depressive symptoms Alcohol and tobacco use 

Low selenium (<25

of cognitive decline 2.31); no dose-resp

BMI Cholesterol/ triglycerides 

Akbaraly et al., 2007254 Community cohort 9 years Long-term (9- year) and shortterm (2-year) 

change in plasma selenium 

Decline on the MMSE, Trails B, DSST, and FTT using two thresholds: 10th and 25th

percentiles of change 

Sex Educational level Time period of observation Baseline plasma selenium 

(1228) 

Diabetes Hypertension Hyperlipidemia History of cardiovascular disease 

Short-term selenium associated with cog9 years Long-term selenium with MMSE decline 95% CI 0.14 to 0.62measures 

* The two publications summarized here are based on the same patient cohort. Abbreviations: DSST = Digit Symbol Substitution Test; FTT = Finger Tapping Test; MMSE = Mini-Mental State Examination; Trails B = Trail Mak

154
Copper, zinc, and iron. A single cohort study involving 3718 older adults from a community 

sample in Chicago, Illinois, evaluated the relationship between dietary copper, zinc, and iron and 

cognitive decline.253 This study is summarized in Table 43; a detailed evidence table is provided 

in Appendix B. Subjects were non-demented at baseline, and were followed for a median of 5.5 

years; 88 percent of survivors completed followup. Copper, zinc, and iron intake was estimated 

based on the modified Harvard Food Frequency Questionnaire. Based on a validation analyses in 

a subsample, the authors reported that Pearson correlations between total intake levels on the 

questionnaire and multiple 24-hour dietary recalls were 0.46 for copper, 0.50 for zinc, and 0.43 

for iron. Cognitive decline was measured as the standardized composite of four tests. Analysis 

adjusted for multiple potential confounding variables including other nutritional factors (vitamins 

C and E, niacin, folate) showed no association between copper, zinc, or iron and cognitive 

decline. A power calculation was not reported. However, higher copper intake was associated 

with greater cognitive decline in subjects with high saturated and trans fats (difference in 

cognitive decline for highest versus lowest copper quintile was -0.61 standardized units/year, 

p < 0.01). This interaction between copper intake and saturated fat intake was specified a priori, 

supported by an animal study showing that neurodegenerative changes may be exacerbated by 

consumption of trace amounts of copper in drinking water. These results provide preliminary 

evidence that high copper intake may be associated with more rapid cognitive decline in 

individuals who consume a diet high in saturated and trans fats. 

155
Table 43. Intake of copper, zinc, and iron and risk of cognitive decline 

Study Sample (n) Followup Exposure Case definition Confounding adjustment Results Morris et al., 2006253 Community cohort 

(3718) 

Median 5.5 years 

Copper, zinc, iron intake estimated from HFFQ 

Standardized composite of 4 tests: East Boston immediate and delayed recall tests, MMSE, Symbol Digit Modalities Test 

Age Race Sex Educational level Cognitive activities Physical activities Alcohol use Stroke Heart disease HTN DM Vitamins C and E, niacin, and folate 

No assozinc or In subgand tranwas asscognitiv

Abbreviations: DM = diabetes mellitus; HFFQ = Harvard Food Frequency Questionnaire; HTN = hypertension; MMSE = Mini-Mental State Examin

156
Mediterranean diet. We identified two eligible cohort studies that examined the association 

between cognitive decline and the Mediterranean diet.86,87 The Mediterranean diet is 

characterized by high intake of vegetables, legumes, fruits, and cereals; high intake of 

unsaturated fatty acids (mostly in the form of olive oil), but low intake of saturated fatty acids; a 

moderately high intake of fish; a low-to-moderate intake of dairy products (mostly cheese or 

yogurt); a low intake of meat and poultry; and a regular but moderate amount of alcohol, 

primarily in the form of wine and generally during meals. The included studies are summarized 

in Table 44; detailed evidence tables are provided in Appendix B. One study87 used a community 

sample in Europe, and the other study86 used a community sample in the United States. 

Participants were cognitively normal at baseline in one study86 and non-demented in the other 

study.87 The outcome for one study was progression to MCI; the diagnosis for MCI was 

retrospectively assigned.86 In the other study, the outcome was longitudinal change on multiple 

cognitive tests. Length of followup ranged from an average of 4.5 to 7 years. Exposure was 

determined based on self-reported information from a semi-quantitative food frequency 

questionnaire. Both studies used similar methods to calculate a Mediterranean diet score based 

on the responses on this questionnaire. The investigators of both studies noted that they had 

previously reported that this questionnaire has adequate validity and reliability based on 

substudies of segments of the questionnaire. Both studies used sample selection methods to 

minimize selection bias and compared baseline characteristics by exposure level. One study 

stated that the outcome diagnosis was assigned blind to the exposure level;86 it is assumed here 

that in the other study that the cognitive measures were administered blind to exposure level.87

Analyses were appropriate and controlled for relevant potential confounders. Neither study 

conducted a priori sample size calculations. 

Scarmeas and colleagues86 reported that compared to those with the lowest tertile 

Mediterranean diet score, those in the middle tertile were not at significantly lower risk of 

developing MCI (HR 0.83; 95 percent CI 0.62 to 1.12), but being in the the highest tertile was 

associated with lower risk of MCI (HR 0.72; 95 percent CI 0.52 to 1.00). The hazard ratio for the 

trend was also significant (HR 0.85; 95 percent CI, 0.72 to 1.00; P for trend = 0.05). Feart and 

colleagues87 found a significant association between a higher Mediterranean diet score and fewer 

MMSE errors (β = -0.006; 95 percent CI, -0.01 to -0.0003; P = 0.04 for 1 point of the 

Mediterranean diet score), indicating less decline on the MMSE over 5 years. Longitudinal 

performance on other cognitive tests did not show this association, except when participants with 

incident dementia were excluded. In this latter analysis, the memory test showed slightly less 

decline associated with a higher Mediterranean diet score (β = 0.05; 95 percent CI 0.005 to 

0.010; P = 0.03 for 1 point of the Mediterranean diet score). 

In summary, there is preliminary evidence that greater adherence to a Mediterranean diet 

may be associated with less cognitive decline in later life. Some caution is warranted in drawing 

conclusions from these findings due to the small effect sizes, minimally significant results, and 

the fact that the association is limited to few of the multiple cognitive measures. Confirmation of 

the findings is needed. 

157
Table 44. Mediterranean diet and risk of cognitive decline 

Study Sample (n) Followup Exposure Case definition Confounding 

adjustment 

Results 

Scarmeas, et al., 200986

Community cohort (1875) 

Mean 4.5 (2.7) years 275 incident MCI cases 

Self-reported responses on a food frequency questionnaire 

NINCDS-ADRDA DSM MCI criteria applied currently accepted diagnostic criteria to previously collected data 

Age Race Sex Education APOE BMI Interval between dietary assessment and cognitive assessment

Higher adherence to associated with lowecognitively normal to Using lowest tertile oMiddle tertile: HR 0.Highest tertile: HR 0Trend: HR 0.85 (0.7

0.05) 

Feart et al., 200987 Community cohort 

(1410) 

7 years Self-reported 

responses on a food frequency questionnaire 

Longitudinal change on the four cognitive tests: MMSE, Isaacs Set Test , Benton Visual Retention Test , and Free and Cued Selective Reminding Test 

Age Sex Education Marital Status Energy Intake Physical Activity Depression symptoms Taking 5 medications or more APOE Cardiovascular risk factors Stroke 

Higher Mediterraneawith fewer MMSE er0.01 to -0.0003; P = Mediterranean diet sslower MMSE cognitperformance on otheshow this associatioAmong the subgroup dementia, higher Meassociated with fewe-0.006; 95% CI -0.015 years for 1 point of score) and less decl= 0.05; 95% CI 0.00

Abbreviations: APOE = apolipoprotein E gene; BMI = body mass index; CI = confidence interval; DSM = Diagnostic and Statistical Manual of Ment

ratio; MCI = mild cognitive impairment; MMSE = Mini-Mental State Examination; NINCDS-ADRDA = National Institute of Neurological and Comm

Stroke-Alzheimer’s Disease and Related Disorders Association 

158
Intake of fruit and vegetables. We identified two eligible cohort studies that examined the 

association between cognitive decline and intake of fruits and vegetables.255,256 The outcomes of 

both studies were continuous variables. The two studies are summarized in Table 45; detailed 

evidence tables for the studies are in Appendix B. Both studies used community samples in the 

United States. One study stated the participants were non-demented at baseline;256 the other 

study255 did not provide information about baseline cognitive level, but it is assumed here that 

most of the participants were non-demented at baseline. The length of followup ranged from 2 to 

5.5 years. Both studies used sample selection methods to minimize selection bias. Both studies 

used self-reported information to estimate fruit and vegetable intake, and both reported 

additional substudies aimed at validating the food frequency questionnaires. For the foods of 

interest in these analyses, the correlations tended to be in the moderate range for responses on the 

food frequency questionnaires and more detailed nutrition data. Both studies compared baseline 

characteristics between those exposed and unexposed. The case definitions for the studies are 

described in Table 45. The analyses appear generally appropriate and were controlled for 

relevant potential confounders. Neither study conducted a priori sample size calculations. 

Both studies reported a significant protective association between higher amounts of 

vegetables and lower rates of cognitive decline, with the association being the strongest for green 

leafy vegetables. There were no significant associations between amount of fruit intake and 

cognitive decline. The results from these two studies are consistent in suggesting a protective 

effect on cognition associated with eating vegetables, but the actual difference in mean scores 

between the groups is quite small. Additional studies confirming these findings would be useful 

to rule out the possibility of residual confounding explaining the results and to determine 

whether these small differences have clinical significance. 

159
Table 45. Intake of fruit and vegetables and risk of cognitive decline 

Study Sample (n) Followup Exposure Case definition Confounding 

adjustment 

Results 

Kang et al., 2005255 Community cohort 2 years Fruit and vegetable intake estimated from 

self-reported responses on food frequency questionnaire administered every 2 years for up to 5 time points 

Decline on cognitive measures 

Age Education High blood pressure High cholesterol 

(13,338) 

Diabetes Coronary heart disease Hormone therapy Age at menopause, BMI Smoking Antidepressant use NSAID use Alcohol intake Physical activity Total energy intake Mental health and vitality indices Vitamin supplementation 

On global Highest qushowed lequintile (mtrend < 0.0Highest quvegetables lowest qui0.05; p treHighest quless declin(mean diffNo differenassociated Results fomemory tesimilar to tcognitive s

Morris et al., 2006256 Community cohort 

(3718) 

Median 5.5 years 

Estimates of total intake of fruits and vegetables during the previous year were calculated from self-report responses on a modified Harvard food frequency questionnaire. Categorized by quintiles, range 0.8 to 4.1 servings per day of vegetables and 0.6 to 3.9 servings per /day of fruits. 

Cognitive decline on standardized composite measure from all tests 

Age Race Sex Educational level Cognitive activities Physical activities Alcohol use 

Higher intaassociated decline (trHigher intawith rate o= 0.55) High intakvegetables associatiocognitive d

Abbreviations: BMI = body mass index; NSAID = non-steroidal anti-inflammatory drug; TICS = Telephone Interview for Cognitive Status 

160
Total intake of calories, carbohydrates, fats, and proteins. We identified no systematic 

reviews or studies evaluating total intake of calories, carbohydrates, fats, and protein and risk of 

cognitive decline. 

Medical Factors 

Vascular factors. Factors considered under this heading include diabetes mellitus, metabolic 

syndrome, hypertension, hyperlipidemia, and homocysteine. 

Diabetes mellitus. We identified two systematic reviews that examined the relationship 

between diabetes mellitus and risk of cognitive decline.42,43 Lu et al.42 identified seven 

prospective, longitudinal cohort studies published between 1999 and November 2007 involving 

38,573 subjects. Five studies were conducted in the United States and two in Western Europe. 

Ascertainment of diabetes varied among studies, with the diagnosis of diabetes based on history, 

medical records, fasting glucose, or oral glucose tolerance test. Heterogeneity between studies 

was assessed using the chi-square test, and publication bias was examined using visual 

inspection of funnel plots and Egger’s test. No heterogeneity or publication bias was found. 

Global measures of cognitive function included the MMSE, the 3MS, and the TICS. Several 

studies also examined executive function using Trail Making Test Part B (Trails B), verbal 

fluency, and Digit Symbol Substitution Test (DSST). Individuals with diabetes mellitus were 

found to have faster decline in global cognitive function as measured by change in MMSE, 3MS, 

or TICS score after 2 to 7 years of followup. Similarly, baseline diabetes mellitus was also 

associated with a faster decline in measures of executive function. 

An earlier systematic review by Cukierman et al.43 reported that the annual rate of change in 

MMSE or 3MS scores in three studies was 1.2 to 1.5 times faster in diabetic subjects than in nondiabetics. This review also examined studies that assessed global cognitive change as a 

categorical variable. Cognitive decline was defined as either a percent reduction from baseline 

scores, or reduction below a particular threshold (for example, a score less than 80 percent of the 

population). Diabetics were more likely than non-diabetic subjects to experience a decline in 

MMSE or 3MS score of ≥ 6.6 to 11.5 percent from their baseline score (ORs ranged from 0.7 to 

1.7 in four studies), or to score in the bottom 15 or 20 percentile of the population (ORs ranged 

from 1.0 to 1.2 in two studies), but only one of these six studies had a lower 95 percent CI that 

exceeded 1.0. A meta-analysis of the results from six studies that performed the MMSE at 

baseline and followup found that the OR for cognitive decline for diabetics as measured by the 

MMSE was 1.2 (95 percent CI 1.05 to1.4). There was no statistical evidence of heterogeneity 

(chi squared = 6.73, df = 5 (p = 0.24); I2 = 25.7 percent). A similar analysis for the DSST (two 

studies) found that diabetics were more likely to decline by at least 7.3 percent from their 

baseline score (OR 1.6; 95 percent CI 1.2 to 2.2), or to score in the bottom 15 percentile of the 

population than were non-diabetics (OR 2.3; 95 percent CI 1.2 to 4.3). A meta-analysis of the 

two studies that performed the DSST found that diabetic subjects were at increased risk of a 

decline in performance compared to non-diabetics (OR 1.7; 95 percent CI 1.3 to 2.3). Six studies 

used a composite of other measures of cognitive performance to detect cognitive decline. Five of 

these found that subjects with diabetes had a higher risk of cognitive decline than non-diabetics. 

In three of the studies that demonstrated decline, the lower limit of the 95 percent CI exceeded 

1.0. Cukierman et al.43 concluded that people with diabetes have a greater risk and rate of 

cognitive decline than people without diabetes. 

161
162

We identified five additional studies on the association between diabetes mellitus and 

cognitive decline.257-261 These studies are summarized in Table 46; detailed evidence tables are 

provided in Appendix B. One study was from Australia,257 one from Europe,259 and three from 

the United States.258,260,261 The total number of subjects enrolled was 9056; 58.2 percent were 

women. Only two studies had a significant number of African-American subjects. The mean age 

of subjects ranged from 59 to 74 years, and the duration of studies was 4 to 14 years. One study 

examined conversion to a diagnosis of MCI or any form of MCI (Age Associated Memory 

Impairment, Age Associated Cognitive Decline; Mild Neurocognitive Disorder, CDR = 0.5 and 

Other Cogntive Disorder) and found no association between diabetes and cognitive 

impairment.257 Yaffe et al. did not use a categorical diagnosis, but divided subjects ranging in 

age from 70 to 79 years into three groups based on performance on the 100-point Modified MiniMental State Examination (3MS).258 Subjects whose 3MS scores were stable at baseline, 3, 5, 

and 8 years (slope of scores ≥ 0) were called cognitive maintainers, those with slopes between 0 

and > 1 SD below mean were called minor decliners, and those with slope that declined by more 

than 1 SD were major decliners. Thirty percent of the population maintained cognitive function 

over 8 years, 53 percent demonstrated minor decline, and 16 percent had major cognitive 

decline. The investigators reported that in multivariate analysis, diabetes mellitus was not 

significantly associated with being either a minor or major decliner in cognitive function.258

Comijs et al. used the 30-point MMSE as a measure of general cognitive function in a 6-year 

study of 1358 subjects ranging in age from 62 to 85 years.259 Using a Generalized Estimated 

Equation (GEE) model, investigators found that subjects with diabetes had a significantly lower 

baseline MMSE score, but cognitive change over time was not significantly different from nondiabetics. Diabetes was also associated with lower baseline scores on Raven’s Colored 

Progressive Matrices, the Alphabet Coding Task-15, and the Dutch version of the Auditory 

Verbal Learning Test (AVLT), but cognitive decline over time was only significant for delayed 

recall on the AVLT (p < 0.01). Knopman et al. examined the association of diabetes mellitus 

with cognitive decline over 14 years using three neurocognitive tests (Digit Symbol Substitution 

[DSST], Delayed Word Recall [DWR] and Word Fluency [WF]).260 Although there was a 

decline in all three measures in subjects with diabetes, it was significant in multivariate analysis 

only for WF (P = 0.021). In univariate analysis adjusted for race, age, sex, and education, 

subjects with diabetes had a greater average annual decline on DSST (P = 0.002) and WF (P = 

0.003), but not DWR. Investigators found no interaction between risk factors. Carmelli et al 

examined the effect of APOE e4 genotype on 10-year cognitive decline in 410 subjects with 

midlife hyperglycemia.262 Investigators found that APOE e4 carriers with midlife hyperglycemia 

experienced greater decline than APOE e4 carriers without hyperglycemia and hyperglycemic 

subjects who did not carry and e4 allele. 

In summary, the data linking diabetes mellitus with a rapid rate of cognitive decline are 

mixed, with most studies showing a modest association. A number of studies have identified 

declines in selective cognitive function (e.g., DSST, WF and delayed recall on AVLT) in 

diabetics, but the specific domain affected has varied across studies. Possible explanations for 

variation in results include use of different criteria to diagnose diabetes mellitus, and failure to 

consider the effect of duration and severity of diabetes on cognitive outcome. More data are 

needed on the effect of various forms of diabetes treatment (insulin versus oral agents versus 

diet) and the role of comorbid vascular factors and hyperinsulinemia on cognitive decline. 
Table 46. Diabetes mellitus and risk of cognitive decline 

Study Sample (n) Followup Exposure Case definition Confounding 

adjustment 

Results 

Cherbuin et al., 2009257 Community cohort 

(2082) Baseline Age 60-64 

4 years 18 cases MCI at 4 years; 64 cases any mild cognitive disorder 

Diabetes mellitus (self-report and diabetic medications recorded) 

Incident MCI or any mild cognitive disorder (ageassociated memory impairment, ageassociated cognitive decline, mild neurocognitive disorder) 

Age Race Education 

OR (95% CI): Diabetes convert5.52); p = 0.756 Diabetes convertdisorder: 2.06 (0

Yaffe et al., 2009258 Community cohort 

(2509) Baseline Age 70-79 

8 years 30% maintainers 53% minor decline 16% major decline 

Diabetes mellitus (self-report, direct measurement glucose [fasting > 126 mg/dL or 2-hour challenge > 200 mg/dL], and use of diabetic medications) 

Comparison of scores on 3MS at baseline, 3, 5, and 8 years. Slope of scores < 0 = maintainers; slope between 0 and > 1 SD below mean = minor decliners; and slope > 1 SD below mean = major decliners 

Age Race Education APOE genotype 

OR (95% CI) for Maintainer vs. mi1.30) Minor vs. major d2.00) 

Comijs et al., 2009259 Community cohort 

(1358 with complete data) 

6 years Diabetes mellitus 

(self-report) 

General cognitive function (MMSE) Fluid intelligence (Raven’s Colored Progressive Matrices) Processing speed (Alphabet Coding Task) Auditory Verbal Learning Test 

Age Sex Educational level Presence of comorbid disease outside of the 7 of interest Smoking Alcohol use Antidepressant Benzodiazepines Depressive symptoms (CES-D) Impaired vision, hearing or mobility (6 typical ADLs assessed) 

GEE model (coefGeneral cognitive Negatively affect

0.11) Fluid intelligence affected by DM (-Information proceNegatively affect0.00) Memory performadelayed recall) ovImmediate: Nega(-0.44; -0.83 to -0Delayed: Negati(-0.65; -0.95 to -0

Knopman Community 14 years Diabetes mellitus DSST Age Difference in ave

163
164

Study Sample (n) Followup Exposure Case definition Confounding 

adjustment 

Results 

et al., 2009260

cohort (1130) 

(fasting glucose > 126 mg/dL, nonfasting glucose > 200 dL, selfreported history of diabetes, or treatment for diabetes in previous 2 weeks) 

DWR WF 

Race Sex Educational level Vascular factors Time Risk factor x time interaction 

test scores (P vaDiabetes

DSST: 0.25 (0.8DWR: -0.19 (0.1WF: 0.60 (0.597

Carmelli et al., 1998262 Community cohort 

(NHLBI WWII twin substudy) (410) 

10 to 25 years 

Midlife hyperglycemia (1- hour post-prandial glucose > 200 mg/dL or use of hypoglycemic agent or insulin) APOE genotype 

Change in test scores: MMSE, DSST, BVRT 

Age Race Sex Baseline score Incident cardiovascular disease 

Mean change (SAPOE e4+ and hMMSE: 1.66 (.39DSST: 7.84 (1.0BVRT: 1.05 (0.2APOEe4+ and hyMMSE: 0.73 (.28DSST: 4.47 (.76BVRT: 0.53 (0.1APOE e4- and hyMMSE: 0.47 (0.2DSST: 4.14 (0.5BVRT: 0.84 (0.1APOEe4- and hyMMSE: 0.47 (0.1DSST: 3.34 (0.4BVRT: 0.37 (0.1All scores are sigand statistically s

Abbreviations: 3MS = Modified Mini-Mental State Examination; ADLs = activities of daily living; APOE = apolipoprotein E gene; APOE e4 = epsilapolipoprotein E gene; BVRT = Benton Visual Retention Test; CES-D = Venter for Epidemiologic Studies Depression scale; CI = confidence intervalDSST = Digit Symbol Substitution Test; DWR = delayed word recall; GEE = generalized estimated equations; MCI = mild cognitive impairment; MMExamination; OR = odds ratio; SD = standard deviation; WF = Word Fluency Test
Metabolic syndrome. We identified four prospective, longitudinal cohort studies, involving 

5713 subjects, that evaluated the association between metabolic syndrome and cognitive 

impairment.260,263-265 These studies are summarized in Table 47; detailed evidence tables are 

provided in Appendix B. One study was conducted in the Netherlands, one in Singapore, and two 

in the United States; all were community samples. Metabolic syndrome was identified in three 

studies using National Cholesterol Education Program 3rd Adult Treatment Panel Guidelines 

(NCEP-ATPIII),260,263,264 and in the other using International Diabetic Federation criteria.265 The 

NCEP-ATPIII criteria require at least three of the following for a diagnosis of metabolic 

syndrome: 

1) Waist measurement > 88 cm for women or > 102 cm for men. 

2) Hypertriglyceridemia (≥ 150 mg/dL [≥ 1.69 mmol/L]). 

3) Low HDL (men < 40 mg/dL [< 1.03 mmol/L]); women < 50 mg/dL [< 1.29 mmol/L]). 

4) High blood pressure (systolic ≥ 130 mmHg; diastolic ≥ 85 mmHg) or currently using an 

antihypertensive medication. 

5) High fasting glucose (≥ 110 mg/dL [≥ 6.10 mmol/L]) or currently using anti-diabetic 

medication (insulin or oral agents). 

The International Diabetes Federation criteria are similar, but require a waist circumference 

greater than 90 cm for men (> 80 cm for women) plus at least two of the following: elevated 

blood pressure or use of antihypertensive medication; elevated fasting glucose (≥ 5.6 mmol/L) or 

use of antidiabetic drugs; elevated triglycerides (1.7 mmol/L) or use of lipid-lowering agents; or 

low HDL cholesterol (< 0.9mmol/L in men and < 1.1mmol/L in women) or use of lipid-lowering 

agents. 

The definition of cognitive change also differed among the studies. Yaffe et al.263 described 

cognitive change as a decline of 5 or more points in the 100-point Modified Mental Status (3MS) 

examination at either the 3- or 5-year evaluation, while Ho et al.265 defined change as a 2-point 

decline on the 30-point MMSE over 1 to 2 years. Van den Berg et al.264 and Knopman et al.260

examined the effect of metabolic syndrome on the rate of change in a battery of tests over 5 years 

of followup. Van den Berg et al. used the MMSE, Stroop, Letter digit coding, and word list 

immediate learning or delayed recall, and Knopman et al. used Digit Symbol Substitution, 

Delayed Word Recall and Word Fluency. There were also several differences among the study 

populations. Van den Berg et al.264 examined residents of Leiden, The Netherlands, who were 85 

or older, and 17 percent of the participants had MMSE scores ≤ 18 at baseline. Ho et al.265

studied people from Singapore with a mean age of approximately 65, and all participants had 

MMSE scores ≥ 24. Yaffe et al.263 studied black and white elders from Memphis, Tennessee, and 

Pittsburgh, Pennsylvania, who ranged in age between 70 and 79 years of age, with a mean 

baseline 3MS score of 90. This latter study did not describe the number of subjects with low 

3MS scores, but required a self-report of normal functioning on activities of daily living and the 

absence of a diagnosis of dementia to participate. The subjects in the Knopman et al. study260

were a subset of participants in the Atherosclerosis Risk in Communities (ARIC) study. In all 

studies, participants with metabolic syndrome were more likely to be women, and in two studies 

they had lower levels of education; both female sex and low education are associated with an 

increased risk of AD, so baseline differences in the population may confound interpretation of 

results. All studies adjusted for important confounders, such as sex and educational level. 

Yaffe,263 Ho,265 and Knopman and colleagues260 adjusted for age, but van den Berg and 

165
colleagues264 did not, possibly because of the limited age difference in the latter’s study 

participants. Van den Berg et al. and Knopman et al. also did not stratify results based on 

baseline cognitive testing. There were also differences in followup: in the study by van den Berg 

and colleagues, 51 percent of subjects died before repeat cognitive assessment,264 while followup 

rates for Ho, Yaffe, and Knopman and colleagues were 64 percent, 89 percent, and 59 percent, 

respectively,260,263,265 Mortality in the study by van den Berg et al. was not associated with 

metabolic syndrome (HR 0.9; 95 percent CI 0.7 to 1.2). 

Two studies found that metabolic syndrome was modestly associated with cognitive decline. 

Yaffe and colleagues reported that 26 percent of participants with metabolic syndrome had a 

decline of at least 5 points on the 3MS, compared to 21 percent of subjects without metabolic 

syndrome (adjusted RR 1.20; 95 percent CI 1.02 to 1.41).263 They further analyzed their data 

based on whether participants had evidence of increased inflammation as measured by the serum 

markers C-reactive protein (CRP) and interleukin 6. Subjects with metabolic syndrome and 

increased inflammatory markers were at greater risk of cognitive decline (adjusted RR 1.66; 95 

percent CI 1.19 to 2.32) compared to those with metabolic syndrome and normal levels of 

inflammatory markers (adjusted RR 1.08; 95 percent CI 0.89 to 1.30), suggesting that 

inflammation is a mechanistically important mediator of cognitive change in metabolic 

syndrome. Ho and colleagues reported that subjects with metabolic syndrome were more likely 

to experience a 2-point decline on the MMSE than subjects without metabolic syndrome: among 

subjects with metabolic syndrome, 19.9 percent had a 2-point decline, compared to 14 percent of 

subjects without the syndrome (OR 1.42; 95 percent CI 1.10 to 1.98).265 Knopman et al. 

prospectively followed 1130 individuals with a mean age at baseline of 59 years for 14 years.260

Forty-six percent of the cohort met criteria for metabolic syndrome, and 52 percent were 

African-American. Investigators reported that subjects with metabolic syndrome had a 

statistically significant greater annual decline on word fluency than other subjects in univariate 

testing that controlled for race, age, sex, and education (P < 0.001). Metabolic syndrome was not 

associated with a significant decline on Digit Symbol Substitution or Delayed Word Recall 

Tests. The authors also reported that there was no evidence of differential effects of risk factors 

on cognitive decline by race or sex. Van den Berg et al. found that metabolic syndrome was not 

associated with lower cognitive performance in their study of people over the age of 85 years.264

In contrast, the Leiden 85-Plus study data showed that subjects with metabolic syndrome had a 

slower rate of cognitive decline on the MMSE, Stroop, and Letter Digit Coding tests than 

subjects without metabolic syndrome. The authors suggested that the difference in age between 

Leiden 85-Plus study participants and participants in the other studies may explain the disparate 

findings. There is some literature to suggest that weight loss, low blood pressure, and low 

cholesterol values are associated with an increased risk of dementia and higher mortality in the 

old-old, which could explain the protective effect of metabolic syndrome in the older group. 

There may also be a survivor effect, such that individuals who reach 85 despite having metabolic 

syndrome may be less susceptible to the adverse effects of these risk factors. 

In summary, metabolic syndrome is associated with a modestly increased risk of cognitive 

decline in studies involving subjects under the age of 80. The relationship between metabolic 

syndrome and risk of cognitive decline may not be valid in persons over the age of 85 years. 

There is limited evidence that inflammation may mediate some of the risk of metabolic disease 

in elders under the age of 80, and measures of inflammation should be included in future studies. 

Future studies should also include various definitions of metabolic syndrome and subjects with 

166
167

onset of metabolic syndrome in midlife, as syndrome duration may be relevant to late-life 

cognitive decline and dementia.
Table 47. Metabolic syndrome and risk of cognitive decline 

Study Sample (n) Followup Exposure Case definition Confounding adjustment Results Yaffe et al., 2004263 Community cohort 

(2632) 

3 to 5 years Metabolic 

syndrome using NCEP-ATPIII criteria (see text, above, for details) 

5-point decline in 3MS at 4-year followup 

Age Sex Education Race Baseline cognition Smoking 

Unadjusted R1.43) 

Van den Berg et al., 2007264

Community cohort 

1 to 5 years Metabolic 

syndrome using NCEP-ATPIII criteria (see text, above, for details) 

Rate of decline in battery of tests 

Sex Additional annLevel of education MMSE: 0.18 

(497) Stroop: -1.49 

Letter digit cod0.005 

Ho et al., 2008265 Community cohort 

(1352) 

1 to 2 years Metabolic 

syndrome using International Diabetic Federation Guidelines (see text, above, for details) 

≥ 2-point decline on MMSE 

Age Sex Education Baseline cognitive status Smoking Alcohol use Depression APOE genotype Length of followup 

Metabolic syn2-point decline 19.9%; p < 0.0OR for metaboCI 1.10 to 1.98

Knopman et al. 2009260

Community cohort (1130) 

Median followup 14 years 

Metabolic syndrome using NCEP-ATPIII criteria (see text, above, for details) 

DSST DWR WF 

Age Race Sex Educational level Vascular factors Time Risk factor x time interaction 

Difference in ametabolic synDSST: -0.05 DWR: 0 WF: -0.12 (p 

Abbreviations: 3MS = Modified Mini-Mental State Examination; APOE = apolipoprotein E gene; CI = confidence interval; DSST = Digit Symbol Sudelayed word recall; MMSE = Mini-Mental State Examination; NCEP-ATPIII = National Cholesterol Education Program 3rd Adult Treatment Panel G

= National Institute of Neurological and Communicative Diseases and Stroke-Alzheimer's Disease and Related Disorders Association; NS = not statist

ratio; RR = relative risk; SD = standard deviation; WF = Word Fluency Test

168
Hypertension. We did not identify any good quality systematic reviews evaluating 

hypertension and risk of cognitive decline. Our own search identified 16 unique cohorts 

described in 19 publications that examined the association between hypertension and cognitive 

decline.108,163,258,260,262,266-280 These studies are summarized in Table 48; detailed evidence tables 

are provided in Appendix B. The included studies involved more than 43,000 subjects. Studies 

were widely heterogeneous. Three studies266-268 assigned diagnoses of incident MCI using 

different modifications of Petersen’s criteria. The other studies looked at changes in cognitive 

test scores over time. Twelve studies108,163,258,260,262,271,272,274-276,279,280 used community cohorts 

from the United States, and one used a community cohort from France.278 More narrowly defined 

community-based cohorts included those made up of WWII twin pairs,262,272 retired Catholic 

clergy,108 and a cohort drawn from the participants in the Study of Osteoporotic Fractures.271

Two publications described observational analyses based on RCTs. One cohort273 was formed by 

the subjects (aged ≥ 60 years) from the Systolic Hypertension in the Elderly Program (SHEP) 

trial, a study of anti-hypertension treatment in which all subjects had a SBP > 160 and a DBP < 

90 and lacked “clinically obvious dementia” at baseline. Another cohort277 used subjects from 

the Advanced Cognitive Training for Independent and Vital Elderly (ACTIVE) trial, a test of 

cognitive training. Subjects (mean age ~ 74 at baseline) in ACTIVE had MMSE scores > 22 and 

were not functionally impaired. Subjects with controlled hypertension would have been 

classified as normotensive, and analyses were not adjusted for antihypertensive medication use. 

The studies also used varying definitions of hypertension, as noted in Table 48. Some studies 

treated blood pressure as a continuous variable.108,275,279 Others used self-reported hypertension 

as one component of designating a subject as hypertensive or as the sole means of determining 

the presence of hypertension.163,258,271,276 In the cohort from the SHEP trial,277 all participants had 

isolated systolic hypertension. Definitions of hypertension were set a priori in some 

cases,258,260,266,273,276,277 and were clearly based on the data in another.274 In the remainder of the 

studies, hypertension was self-reported, treated as a continuous variable, or not clearly defined a 

priori. 

There were 2990 subjects in the studies that diagnosed MCI. Rates of incident MCI varied. 

Solfrizzi and colleagues266 describe 113 cases of incident MCI in a population of 1524 over 3.5 

years. Tervo et al.267 found 65 cases of incident MCI in a study sample of 548 over 3.26 years. 

Reitz and colleagues268 found 334 cases of incident MCI in a study sample of 918 over 4.7 years. 

No significant association between hypertension and MCI was found in any of these studies. 

Studies from community samples that evaluated the effects of hypertension on various 

cognitive tests108,163,258,260,262,271,272,274-276,278-280 had mixed results. For various cognitive domains, 

associations between hypertension and cognitive decline were inconsistent: processing speed 

(two of three studies positive), executive functioning (one of two studies positive) and global 

cognition (five of nine studies found a statistically significant association between hypertension 

and greater cognitive decline). The detailed results are discussed in the following paragraphs. 

Two studies275,276 found no significant association between either SBP or DBP and cognitive 

decline over 6 to 7 years. Cognitive outcomes were measured with the MMSE275,276 and other 

memory tests.275 

In a substudy of the ARIC cohort, Knopman et al. found a worsened performance on verbal 

fluency associated with hypertension but no association with delayed recall or processing 

speed.260 Alves de Moraes and colleagues, in an earlier analysis of the full ARIC cohort269

compared five different categories of hypertension with each of three cognitive tests and found 

that only subjects with uncontrolled hypertension (high SBP or high DBP on both followup 

169
visits) and DSST subtest scores were significantly related. Peila and colleagues163 found that 

never-treated hypertensives declined faster on a measure of general cognition, the Cognitive 

Abilities Screening Instrument (CASI; 1.46 points decline/year; range 0 to 100) than did 

hypertensives treated for 5 to 12 years (1.14 points of decline/year). However, differences 

between untreated hypertensives and those treated for 0 to 5 years and those treated > 12 years 

were not statistically significant, making importance of the finding unclear. Barnes and 

colleagues271 gave subjects a shortened version of the MMSE several times over a study duration 

of 6 to 15 years (median 10 years). The study population was divided into tertiles defined by the 

slopes of the lines representing this change over time. Optimal cognitive functioning was defined 

by a slope of 0. Lack of hypertension was predictive of optimal cognitive functioning, with an 

OR of 1.22 (95 percent CI, 1.03 to 1.44). Tzourio et al.278 found the strongest association 

between hypertension and cognitive decline, defined as a 4-point decline in MMSE scores over 

the 4-year followup of the study. When hypertension was defined as SBP ≥ 160 mmHg or DBP ≥

95 mmHg, the OR for cognitive decline was 2.8 (95 percent CI 1.6 to 5.0). When hypertension 

was defined as SBP ≥ 140 mmHg or DBP ≥ 90 mmHg, the OR decreased to 1.8 (1.2 to 2.9). The 

study population was younger than in other cohorts (mean age 65 years), and an MMSE decline 

of 4 points would represent a fairly severe decline. Waldstein and colleagues279 reported a 

nonlinear relation of SBP with cognitive change as measured by tests of non-verbal memory and 

confrontational naming. Younger subjects with higher SBP made more baseline errors on the 

BVRT but improved over time, while older individuals with high SBP made more errors and got 

worse over time. Haan and colleagues274 found that SBP that was a standard deviation above the 

mean was associated with a faster decline on the 3MS and the DSST. Glynn et al.280 looked at 

the Boston EPESE cohort, a subset of which had blood pressure readings from 9 years prior to 

first brief cognitive tests followed by further cognitive tests 3 and 6 years later. No association 

was identified between various blood pressure levels and errors on a brief memory test or the 

short portable mental status questionnaire (SPMSQ) except for a single category of hypertension 

(SBP>160) and a greater increase in SPMSQ errors over time. 

Other populations were less generalizable. Two studies262,272 reported on the association in 

white male twin pairs from WWII. Hypertensives had a greater decline on the DSST, which was 

statistically significant using a one-sided p test,262 but not on the MMSE or BVRT.272 The same 

subjects with high blood pressure in mid-life showed greater decline in MMSE scores over 10 

years when compared to those with low SBP (< 120 mmHg). 

Kuo and colleagues277 looked at subjects in the ACTIVE trial, which tested different 

cognitive training techniques. Subjects were followed over 2 years. Hypertensive subjects 

(defined by direct measurement but not use of antihypertensives) had faster decline in reasoning 

tests, while memory, speed of processing, and global cognition composite scores were not 

significantly affected. The authors found no meaningful (or statistically significant) interactions 

between the cognitive training intervention and the effect of hypertension on cognitive decline. 

If there is a pattern to these isolated positive results, it is that they tended to be in tests 

associated with frontal lobe functioning (reasoning, working memory, etc). This is an area of the 

brain thought to be vulnerable to vascular insults, which could be expected to be more likely in 

hypertensive subjects. 

One study was formed by the subjects in the SHEP trial (subjects were volunteers for blood 

pressure screening and had SBP 160 to 239 and DBP < 100, with randomization to 

antihypertensive or placebo).273 The SHEP trials compared the effects of antihypertensive drugs 

versus placebo on cardiovascular outcomes; cognitive change was a tertiary outcome measured 

170
171

by the Trails A and DSST. Duration of this substudy was only 1 year, and all subjects were 

hypertensive at trial initiation. Neither the antihypertension intervention nor the change in SBP 

was associated with changes in cognition over this brief period. 

The Religious Orders cohort of retired clergy108 had an older mean age of 75. The cohort was 

highly educated (mean of 18 years of education). Baseline blood pressures were low. No 

relationship was noted between blood pressure analyzed as a continuous variable and cognitive 

decline, defined by a global score from combining multiple tests, over 6 to 15 years. It is possible 

that individuals with hypertension selectively died prior to inclusion in this cohort, or that the 

limited variability of blood pressure levels prevented detection of any association. 

In summary, while multiple cohorts have been examined for an association between 

hypertension and cognitive decline using various tests, the samples are as heterogeneous as are 

the outcomes, definitions of hypertension, and results. The strongest results were associated with 

subjects whose hypertension was untreated and whose cognitive decline was relatively severe. 

Some studies found results when multiple tests were compared individually with hypertension at 

baseline, raising the possibility that a positive result could arise by chance. 
Table 48. Hypertension and risk of cognitive decline 

Study Sample (n) Followup Exposure Case definition Confounding adjustment ResulSolfrizzi et al., 2004266

ILSA 

Community cohort (1524) 

3.5 years 113 incident MCI 

Self-report or treatment or measured ≥ 90 or ≥ 140 in last two 

of three 

Petersen’s without requirement for subjective memory disorders and allowance for non-cognitive disability MMSE BSRT DCT 

Age Educational level Total cholesterol HTN Coronary artery disease 

RR foto 1.89

Tervo et al., 2004267Kuopio community 

Community cohort (548) 

3.26 years (0.7) 65 incident MCI 

≥ 160 or ≥ 95 or 

antihypertensive use 

Petersen’s criteria but no informant Visual Reproductive Test from the WMS Logical Memory Test (immediate and delayed) from the WMS-R Word List Recall (immediate and delayed) from CERAD Delayed Recall of the Constructional Praxis from CERAD NYU Paragraph Recall (immediate and delayed) Boston Naming Test (BNT) Trails A and B Block Design from WAISR MMSE 

Age APOE Cardiovascular disease Cerebrovascular disease Sex Educational level DM Medicated HTN 

OR foCI 0.4

Reitz et al., 2007268Northern Manhattan 

Community cohort (918) 

Mean 4.7 years 334 incident MCI 

> 140/90 and selfreport Petersen’s criteria but no informant 

7 subtests of the Selective Reminding Test 

Age Race Sex Educational level APOE e4 

HR foCI 0.8 

172
Study Sample (n) Followup Exposure Case definition Confounding adjustment Resul

Rosen Drawing Test Matching and recognition from Benton Visual Retention Test and identities and oddities subtests of the Mattis Dementia Rating Scale BNT COWA Wechsler similarities 

Stroke DM Heart disease LDL level 

Alves de Moraes et al., 2002269

(also published in Knopman et al., 2001270) 

14-year data published by Knopman et al., 2009260ARIC 

Community cohort (8058) 

6 years Self-report, use of 

antihypertensive meds, or SBP ≥

140 or DBP ≥ 90 Four categories: Normal BP Incident HTN Partially controlled HTN (one or other visits had normal BP) Uncontrolled HTN 

Delayed word recall test Digit symbol subtest Word fluency test 

Age Race Sex Educational level DM 

In comcategonormoof the differeunconnormoscoreslimited mediayears) consid

Knopman et al., 2009260Same cohort as Alves de Moraes et 

Community cohort (1130) 

14 years SBP > 140 

DBP > 90 Use of antihypertensives in previous 2 weeks 

Delayed word recall test DSST subtest WF 

Age Race Sex Educational level Vascular factors Time Risk factor x time interaction 

HTN anon-siDSSTDiffereWF (p hypert

173
Study Sample (n) Followup Exposure Case definition Confounding adjustment Resul

al., 2002269

and Knopman et al., 2001270) 

ARIC Barnes et al., 2007271

Cohort formed from SOF study (9704) 

Median 10 years; range, 6 to 15 years 

Self-reported history of HTN 

MMSE over time, modified to a 26-point scale Subjects divided into maintainers, minor decline, and major decline defined by slopes of lines divided into tertiles 

Age Educational level Baseline cognitive status Study site 

Lack omaintafunctioof 1.22 

Carmelli et al., 1998262 Community cohort 

(WWII twins) (410) 

Cognitive change over approximately 10 years, BP measured over 25 years 

Mean BP > 140/90 or use of antihypertensive medication 

MMSE DSST BVRT 

Age Race Sex Baseline cognitive scores Incident CVD 

Hypergreatenot MMRelativMMSEDSST0.05) 

(Subjects from same cohort as Swan et al., 1998272) 

BVRT

Swan et al., 1998272(Subjects from same cohort as Carmelli et al., 1998262) 

Community cohort (WWII twins) (317) 

Cognitive change over approximately 10 years, BP measured over 25 years 

Directly measured BPs averaged over first three waves, approx 15 years 

MMSE DSST BVRT 

Age History of stroke Educational level 

Subjeexperithan th10-yeaLow SHigh SDSSTLow S

174
Study Sample (n) Followup Exposure Case definition Confounding adjustment Resul

High S

Gurland et al., 1988273

SHEP 

Cohort formed from an RCT (481) 

1 year BP directly 

measured 

SHORT - CARE DSST Trails A 

Age Race Sex Educational level, Baseline cognitive status Annual SBP Baseline SBP Baseline disability Drug status 

Drug uchangwith cAccordsignifibetweand baquanti

Haan et al., 1999274CHS 

Community cohort (between 4700 and 5000 [unclear]) 

5 to 7 years (unclear) 

Direct measure Calculations done for SBP > 158 (a SD over mean) 

3MS DSST 

Age Sex Race Incident stroke Education 

Increamean assoc0.96 pand 0years 

Hebert et al., 2004275 Community cohort 

(4284) 

Baseline, 3 years, 6 years; 64% had all three visits, 36% had two 

Self-report of antihypertensives at baseline and pill bottles maybe examined 

Four tests combined using z scores based on the population mean at baseline. Tests were: Immediate and delayed story recall MMSE Symbol Digit Modalities Test 

Age Race Sex Educational level SBP or DBP (whichever was not examined) 

Outcochangover a mmHg SBP ncognitSBP: 0.0000DBP: 0.0003DBP eterm is curvilimmHg 

BP checked twice and averaged each visit 

Insel et al., 2005276Hispanic 

Community cohort (1460) 

7 years Self reported 

hypertension or SBP ≥ 140 

MMSE Sex 

Age Education 

Neithebaselideclin

175
Study Sample (n) Followup Exposure Case definition Confounding adjustment Resul

EPESE DM 

Income Heart disease Stroke HTN 

This pin BP over tifor the increapredic

Kuo et al., 2005277ACTIVE 

Cohort formed from an RCT (2802) 

2 years BP directly 

measured Subjects divided into: Normal Pre-HTN HTN 1 (140-159/90-99) HTN 2(> 160/100) 

MMSE, Hopkin Verbal Learning Test Related Word Lists Rey Auditory-Verbal Learning Test Unrelated Word Lists Rivermead Behavioral Memory Test Paragraph Recall task 

Age Race Sex Educational level Baseline cognitive status Study site Intervention group Cardiovascular risk factors Tobacco use BMI 

Subjea fastecompoSubjefaster normo

Peila et al., 2006163HAAS 

Community cohort (1294) 

Variable 4 to > 12 years 

Direct measure or self-reported HTN or self-report of antihypertensive medication 

CASI Age 

Mid-life BMI Smoking CAD CVA Atherosclerosis APOE e4 Education 

Annuawas ghypertto trea1.14) 1.01), signifiyears years 

Shah et al., 2006108Religious Orders Study 

Community cohort (retired clergy) (824) 

Mean of 6.5 annual evaluations 

Direct measurement and self-reports of HTN 

Global score based on all tests: Word List Memory Word List Recall Word List Recognition Immediate and delayed recall of Story A from WMS-R East Boston Story (immediate and delayed) Verbal Fluency 

Age Sex Education APOE e4 Use of antihypertensive medications 

Investadjustrelatioresults evaluaage, shad es0.00 ahad es0.001 Time i

176
Study Sample (n) Followup Exposure Case definition Confounding adjustment Resul

BNT Extended Range Vocabulary Test National Adult Reading Test Digits Forward and Backward from WMS-R Digit Ordering Alpha Span SDMT Number Comparison Judgment of Line Orientation Standard Progressive Matrices 

0.036 score. 

Tzourio et al., 1999278

EVA 

Community cohort (1172) 

~4 years Direct 

measurement (SBP ≥ 160 or DBP ≥ 95) 

Those taking antihypertensives also considered to have HTN Chronicity defined as HTN at baseline and 2-year assessment 

MMSE Cognitive decline defined as a 4-point drop over 4 years of study 

Age Sex Education Income Depressive symptoms Alcohol APOE Baseline MMSE 

OR fo95% CHTN: SBP > (1.1 to Antihy1.3 (0Not ta(2.4 to 

Waldstein et al., 2005279BLSA 

Community cohort (847) 

Visits every 2.32 (0.8) years, mean 2.7 (1.5) visits 

Direct measurement once in each arm approximately 90 minutes postbreakfast, averaged 

Digits Forward and Backward 

Age Education 

California Verbal Learning Test 

Alcohol use Smoking Benton Visual Retention 

Test Use of antihypertensives Trails A and B Letter and Category 

Depression 

“Nonlilongitunon veconfro

177
Study Sample (n) Followup Exposure Case definition Confounding adjustment Resul

Fluency BNT 

Yaffe et al., 2009258Health ABC 

Community cohort 

Visits years 1, 3, 5, and 8 

Self-report or use of antihypertensive or SBP > 140 or DBP > 90 

3MS change ‘Maintainer’-slope of 0 or greater ‘Minor decliner’ slope > 0 but < 1 SD of mean of slopes ‘Major decliner’ slope > 1 SD 

Age Race Education Reading level Work/volunteer status Caregiver Social support Living situation Self-rated health Alcohol Exercise 

(2509) 

Smoking Depression BMI DM History of stroke APOE status CRP IL-6 Triglycerides Fasting glucose 

OR (9minor to 1.28For mdeclin

Glynn et al., 1999280

Boston EPESE 

Community cohort (3657) 

BP 9 years pre-baseline then at 3 and 6 years 

Direct measure 9-item SPMSQ 

6-item East Boston Memory Test 

Age Sex Educational level Time in study 

BP at was nchangwith Sbaseliin SPM

Abbreviations: 3MS = Modified Mini-Mental State Examination; APOE = apolipoprotein E gene; APOE e4 = e 4 allele of the apolipoprotein E gene; BNT = Boston Naming Test; BP = blood pressure; BSRT = Babcock Story Recall Test; BVRT = Benton Visual Retention Test; CAD = coronary arterAbilities Screening Instrument; CERAD = Consortium to Establish a Registry for Alzheimer’s Disease; CI = confidence interval; COWA = Controlled CRP = C-reactive protein; CVA = cerebrovascular accident; CVD = cardiovascular disease; DBP = diastolic blood pressure; DM = diabetes mellitus; 

178
179

Substitution Test; DWR = delayed word recall; IL-6 = Interleukin-6; HR = hazard ratio; HTN = hypertension; LDL = low density lipoprotein; MCI = MMSE = Mini-Mental State Examination; NYU = New York University; OR = odds ratio; RCT = randomized controlled trial; RR = relative risk; SBP SD = standard deviation; SDMT = Symbol Digit Modalities Test; SE = standard error; SPMSQ = Short Portable Mental Status Questionnaire; Trails A 

Trails B = Trail Making Test Part B; WAIS-R = Wechsler Adult Intelligence Scale-Revised; WF = Word Fluency Test; WMS = Wechsler Memory ScMemory Scale-Revised 
Hyperlipidemia. We identified one good quality systematic review that examined the 

relationship between total cholesterol and cognitive impairment and cognitive decline.40 No 

formal quality assessment of included papers was done. Two studies examined the relationship 

between a mild cognitive impairment diagnosis and total cholesterol. One266 examined 

cholesterol in late life and found a lower risk with higher cholesterol, but the confidence interval 

included 1 (RR 0.67; 95 percent CI 0.45 to 1.00). Another study281 found total cholesterol in 

midlife of ≥ 6.5 mmol/L (251 mg/dL) to be related to incident MCI, with an OR of 1.9 (95 

percent CI 1.2 to 3.0). It is possible that the method of screening for MCI in this latter study was 

insensitive to some cases, and this may have skewed the results. 

Of the studies examining cognitive decline included in the systematic review, only two 

would have met our inclusion criteria. Kalmijn and colleagues282 found no association between 

late-life cholesterol and cognitive decline (OR 1.38; 95 percent CI 0.75 to 2.55). Reitz et al.283

also found no relationship (after Bonferroni correction) between cholesterol and cognitive 

decline. 

Our own independent search identified two additional papers (Table 49; detailed evidence 

tables are provided in Appendix B). Knopman et al.270 found no association between 

hyperlipidemia and declines on any test in a population initially aged 45 to 64 and followed a 

mean of 6 years. Word fluency, DSST, and DWR were the tests used. Packard et al.284 identified 

no significant associations between LDL or HDL levels and performance in any tests in a cohort 

formed from subjects from a statin treatment trial and adjusted for treatment allocation who were 

followed a mean of 3.2 years with an initial age between 70 and 82 years. Tests given were 

MMSE, picture word recall test (involving immediate recall and recall after 20 minutes), Stroop 

Color and Word Test, and letter digit coding test. 

As in the data concerning incident AD and total cholesterol levels suggest, lipid levels are not 

convincingly related to cognitive impairment by this available data. There was a trend toward a 

lower risk of cognitive decline with higher late-life cholesterol in one study,266 but a lack of 

association in four others.270,282-284

180
Table 49. Total cholesterol and risk of cognitive decline 

Study Sample Followup Exposure Case definition Confounding 

adjustment 

Results 

Knopman et al., 2001270

ARIC 

Community cohort (10,610) 

6.0 years (0.3) 

Hypercholesterolemia, directly measured as LDL ≥ 140 or use of lipid 

lowering agent; fasting status not specified 

Word fluency DSST DWR 

Age Race Sex Educational level Site CNS-relevant medications 

Hyperlipidemdeclines on a

Packard et al., 2007284

PROSPER 

Cohort formed from an RCT (5804) 

Mean 3.2 years; range, 0.7 to 4.2 

Directly measured twice at baseline 

MMSE Picture-word learning test Stroop Color and Word Test Letter digit coding test 

Age Sex Country Education History of vascular disease, MI, stroke, TIA, smoking, antihypertensive medication, BP, BMI, or DM Triglycerides Treatment allocation APOE e4 Baseline cognitive test scores 

Differences and the secomeasures. Dscores reportertile). No significancognitive meActivities of dindependent No significanHDL-C tertile 

Abbreviations: APOE e4 = e 4 allele of the apolipoprotein E gene; ARIC = Atherosclerosis Risk in Communities; BP = blood pressure; BMI = body mnervous system; DM = diabetes mellitus; DSST = Digit Symbol Substitution Test; DWR = Delayed Word Recall; HDL = high density lipoprotein; HDlipoprotein cholesterol; LDL = low density lipoprotein; LDL-C = low density lipoprotein cholesterol; MCI = mild cognitive impairment; MI = myocar

Mini-Mental State Examination; PROSPER = Prospective Study of Pravastatin in the Elderly at Risk; SD = standard deviation; TIA = transient ischemrandomized controlled trial 

181
Homocysteine. We identified four cohort studies120,238,285,286 and a nested case-control 

study237 involving 3409 subjects that examined the association between homocysteine and risk of 

cognitive decline (Table 50). Among the five studies, three were conducted in European 

communities,237,285,286 and two in U.S. communities.120,238 One study selected a sample of highly 

functioning elderly;238 the other studies selected samples from general community populations. 

Three studies237,238,286 used non-fasting homocysteine samples that may not measure bioavailable 

folate as well as fasting samples. Rather than specifying abnormal homocysteine levels a priori, 

all studies set thresholds based on population levels. Thresholds varied across studies. In the 

cohort studies, followup rates exceeded 80 percent. In the nested case-control study, 51 percent 

of survivors agreed to participate when approached at 10-year followup, and of these, only 68 

percent provided blood for analysis. The duration of followup was relatively short in two studies 

(2 to 2.7 years),285,286 and 4.7 to 10 years in the other studies. Three studies237,285,286 used declines 

in the Mini-Mental State Examination (MMSE) to determine cognitive decline. Decline was 

evaluated as a continuous measure or using different thresholds for decline. The other two 

studies used multiple cognitive tests to compute a single summary score238 or summary scores 

for several domains of cognitive function.120 All studies adjusted results for multiple potential 

confounding variables. 

Using a MMSE decline of greater than 1 point per year, Kalmijn et al.286 found no significant 

association with tertiles of homocysteine. Dufouil et al.285 evaluated the association using 

quartiles of homocysteine. The highest quartile (≥ 15 μmol/L) was associated with an increased 

risk for a ≥ 3-point decline in the MMSE over 2 years (OR 2.8; 95 percent CI 1.2 to 6.2). This 1- 

to 1.5-point average annual decrease in MMSE would represent a fairly rapid decline in 

cognition. Clarke et al.237 evaluated the association between the 8-year change in homocysteine 

values and 10-year change in MMSE. Doubling of homocysteine was associated with more rapid 

decline on the MMSE, but when analyses were adjusted for other vitamin markers (B12, folate, 

methylmalonic acid), the association was no longer statistically significant. 

Analyses of other cognitive outcomes showed inconsistent associations with baseline 

homocysteine values. Kado et al.238 used a summary cognitive score and found no significant 

association with homocysteine, categorized by quartiles, and cognitive decline over 7 years in a 

population selected to be in the top third of cognitive and physical functioning (RR for highest 

versus lowest quartile 1.11; 95 percent CI 0.65 to 1.76). Luchsinger et al.120 created summary 

scores for memory, language, and visuospatial domains. Comparing homocysteine values greater 

than the median (15.6 μmol/L) to values below the median, homocysteine was not associated not 

associated with a greater decline in any domain. Subjects were followed for a mean of 4.7 years. 

Dufouil et al.285 found that homocysteine values greater than 15μmol/L were associated with 

greater decline on the DSST, finger tapping, and Trails B test. 

The variability in subjects studied, classification of exposure, outcomes measured, and 

duration of followup may explain the variability in observed associations. However, given the 

small number of studies and the variability across multiple dimensions, no clear pattern can be 

determined. 

In summary, we identified five studies that examined the relationship between baseline 

homocysteine and cognitive decline. Four of the five studies did not find an association between 

cognitive decline and homocysteine levels, and two studies found associations using differing 

definitions of exposure. There is no consistent association between homocysteine levels and 

cognitive decline. 

182
Table 50. Homocysteine and risk of cognitive decline 

Study Sample (n) Followup Exposure Case definition Confounding adjustment Results Kado et al., 2005238 Community (449) 7 years Non-fasting plasma homocysteine Summary cognitive score including naming, 

delayed recall, spatial memory recall, similarities 

Age Sex Education Baseline physical function Smoking Second model added vitamins B6, B12, and folate 

7-year cvs. loweshomocys0.91 to 2Adjusted 7-year co(0.65 to 

Dufouil et al., 2003285 Community (1107) 2 years Fasting plasma homocysteine MMSE decline of ≥ 3 points over 2 

years Other tests also done 

Age Sex Education Baseline cognition BMI Alcohol Smoking Hypertension Hypercholesterolemia Glycemic status Vascular disease Folate Vitamin B12 

2-year chomocysμmol/L) vOR 2.8 (Homocyassociat0.26 poinsubsequOther tesμmol/L adecline otapping t

Kalmijn et al., 1999286 Community (702) 2.7 (0.5) years Non-fasting plasma homocysteine MMSE decline of > 1 point annually Age Sex Educational level 

Baseline MMSE 

1-year cvs. lowesOR 0.91 middle teOR 1.14 

Luchsinger et al., 2004120

Community (679) 

4.7 years Fasting plasma 

homocysteine 

Standardized test scores averaged to evaluated three domains: memory language, and visuospatial 

Age Sex Education APOE Stroke Creatinine Folate 

Homocyμmol /L) coefficiegreater dscore, p High homassociatvisuospa

183
184

Study Sample (n) Followup Exposure Case definition Confounding adjustment Results 

Vitamin B12 Smoking status Diabetes mellitus Hypertension Cardiovascular disease BMI 

Clarke et al., 2007237 Community (472) 10 Non-fasting homocysteine (measured at 

year 2) 

MMSE Age 

Education Smoking Vascular disease Systolic BP APOE Methylmalonic acid Vitamin B12 Folate Holotranscobalamin 

Doubling over 8 yeμmol/L), greater abeta coe(0.029) p

Abbreviations: APOE = apolipoprotein E gene; BMI = body mass index; BP = blood pressure; CI = confidence interval; DSST = Digit Symbol Subst

Mental State Examination; OR = odds ratio; RR = relative risk; SE = standard error 
Other medical factors. Factors considered under this heading include sleep apnea, obesity, 

and traumatic brain injury (TBI). 

Sleep apnea. We did not identify any good quality systematic reviews or primary studies that 

evaluated the association between sleep apnea and risk of cognitive decline. 

Obesity. We did not identify any good quality systematic reviews that examined the 

relationship between weight and cognitive decline. We identified three prospective cohort studies 

that examined the effects of obesity on cognitive decline.257,258,287 These studies are summarized 

in Table 51; detailed evidence tables are provided in Appendix B. Two of these were conducted 

in the United States,258,287 while the other was conducted in Australia.257 All three studies 

recruited participants from the community thereby decreasing bias in selection of the cohort; 

however, only two studies excluded participants with impaired cognition.257,258 Most participants 

were over age 70 at the time of cognitive testing except in one study where the mean age was 

62.5.257 Two of the studies ascertained BMI by direct measurement of height and weight;258,287

the remaining study calculated BMI from self-reported height and weight.257 Cognitive decline 

was considered as a continuous variable in one study.287 The other two studies categorized the 

variable as MCI257 and as major and minor decliners, defined by the slope of cognitive decline 

being ≥ 1 SD below the mean and 0 < but no more than 1 SD below the mean, respectively.258

The period of followup ranged from 4 to 8 years. Only one study compared the sample at 

baseline by exposure and found that persons with the highest BMI tended to be younger, female, 

and black,287 while the others compared samples at baseline based on their outcome. There was 

no a priori calculation of the sample size in any of the studies, but all did control for potential 

confounders in the analysis. 

Sturman et al.287 included people with all levels of baseline cognitive function and showed 

that a higher BMI was associated with less cognitive decline over 6 years in both black (β = 

0.0013, p = 0.009) and non-black subjects (β = 0.0021, p = 0.006). In a separate analysis limited 

to those who had MMSE scores greater than 24 (1010 participants), there was no relationship 

between obesity and cognitive decline over time in black (β = 0.0003, p = 0.415) or non-black 

subjects (β = 0.0008, p = 0.086). This latter analysis is of greatest relevance to our study 

question; however, it is important to bear in mind that this is a secondary analysis. Yaffe et al.258

found that cognitive decline was associated with a higher BMI; however, this association was not 

statistically significant when investigators compared maintainers and minor decliners. They did 

find a statistically significant relationship between minor and major decliners where major 

decline was associated with higher BMI (OR 0.97; 95 percent CI 0.94 to 1.00). Cherbuin et al.257

found that there was no statistically significant association between BMI and MCI (OR 1.01; 95 

percent CI 0.93 to 1.10), but there was a significant association between BMI and any major 

cognitive decline (OR 1.05; 95 percent CI 1.05 to 1.09). 

In conclusion, all three prospective cohort studies that have examined the association 

between weight and cognition are inconclusive. A possible explanation for this could be that the 

effect of weight on cognitive decline is small. It could also be the case that the extremes of 

weight have an adverse outcome which might be masked by considering weight to be single 

continuous variable. It is also notable that the studies did not measure lifetime or midlife BMI, as 

studies on BMI and AD show that the time of exposure to obesity is important. Also, change in 

weight, which has been shown to be a predictor for AD in some studies, was not considered. 

Future studies are needed to clarify the relationship between weight and cognitive decline and 

these studies need to consider age at exposure as well as change in weight. 

185
Table 51. Obesity and risk of cognitive decline 

Study Sample (n) Followup Exposure Case definition Confounding adjustment ResulSturman et al., 2008287 Community cohort 

(3885) 

6.4 years BMI MMSE 

East Boston tests of Immediate Memory and Recall SDMT Combined Z score 

Age Sex Education Time in study Stroke Diabetes Hypertension Heart disease 

BMI dwith coin blacBlack: 0.415 White: 0.086 

Yaffe et al., 2009258 Community cohort 

(2509) 

8 years BMI 3 MS 

Participants with predicted slopes of the 3MS scores of ≤ 0 were considered maintainers; 0 < but no more than 1 SD below the mean were considered minor decliners; ≥ 1 SD below the mean were considered major decliners 

Age Race Educational level APOE genotype 

Cognitassochowevnot staMaintaOR 0.9Major 0.97 (0

Cherbuin et al., 2009257 Community cohort 

(2551; 2081 analytical sample) 

4 years BMI DSM 

Published criteria for MCI AAMI, AACD , MNC, other cognitive decline and impairment on the CDR were grouped together as any MCD 

Age Sex Educational level 

AssocOR 1.0AssocMCD: 1.09) 

Abbreviations: 3MS = Modified Mini-Mental State Examination; AACD = aging-associated cognitive decline; AAMI = age-associated memory impa

apolipoprotein E gene; BMI = body mass index; CDR = Clinical Dementia Rating scale; CI = confidence interval; DSM = Diagnostic and Statistical M

MCD = mild cognitive disorder; MCI = mild cognitive impairment; MMSE = Mini-Mental State Examination; MNC = mild neurocognitive disorder; standard deviation; SDMT = Symbol Digit Modalities Test 

186
Traumatic brain injury (TBI). We did not identify any good quality systematic reviews or 

primary studies that evaluated the association between TBI and risk of cognitive decline. 

Psychological and emotional health. Factors considered under this heading include 

depression, anxiety, and resiliency. 

Depression. We identified 13 cohort studies, involving 32,969 subjects, evaluating the 

association between depression and categorical outcomes for cognitive impairment.257,271,288-298

All studies excluded subjects with dementia, but most did not specifically exclude individuals 

with cognitive impairment that did not meet the threshold for dementia. An additional nine 

studies evaluated the association between depressive symptoms and changes on 26 different 

measures of cognition analyzed as a continuous measure. Because of the heterogeneity of 

continuous outcome measures and the similar results to studies using categorical outcomes, these 

studies will not be discussed in detail.299-307

Among the 13 cohort studies of interest, 6 studies each were conducted in Western Europe 

and the United States, all but one291 in community samples. Almost all studies evaluated adults 

older than age 65. All studies assessed current depressive symptoms using a validated severity 

measure; two257,296 also assessed antidepressant use at baseline. Seven studies reported incidence 

of MCI using similar definitions that required abnormal neuropsychiatric testing, change from 

prior cognitive status, absence of functional impairment, and not meeting criteria for dementia. 

The other six studies defined cognitive decline as a change in MMSE meeting or exceeding a 

specified threshold (1, 3, or 5 points) or in the lowest tertile. The average followup ranged from 

1.5 to 6 years; the mean duration was at least 3 years for all but one study.293 Most studies used 

methods to minimize selection bias and used generally appropriate analysis methods, including 

adjustments for confounding. However, only one study reported an a priori sample size 

calculation,294 few controlled for psychotropic medication use, and followup rates were low or 

not reported in over half the studies. 

Because of the variability in how studies categorized significant depressive symptoms, we 

did not compute a summary estimate of effect. Instead we summarized results qualitatively 

(Table 52). For the seven studies evaluating incident MCI, five showed an elevated risk for 

subjects with significant depressive symptoms. One study that found no association with 

depressive symptoms296 found that antidepressant use increased risk. The study by Christensen et 

al.289 had few incident cases of MCI and was likely underpowered. In contrast, the studies 

examining risk for decline on the MMSE were mixed. Three of the six studies showed an 

elevated risk for cognitive decline among those with depressive symptoms at baseline, one 

showed an elevated risk only for those with persistent depressive symptoms, and two showed no 

association. The variability in findings is not explained by differences in study population, 

exposure measurement, or study design. When all the studies using MCI and decline in MMSE 

are considered, the evidence suggests an association between depressive symptoms and cognitive 

decline.

187
Table 52. Depression and risk of cognitive decline 

Study Sample (n) Followup Exposure Case definition Confounding 

adjustment 

Results 

Barnes et al., 2006288 Community cohort 

(2220) 

6 years 296 cognitive decline 

CES-D-10 = 3-7; CES-D ≥ 8 at 

baseline 

MCI Age 

Sex Education Race Baseline cognition Vascular disease 

CES-D 3-7: OR 1CES-D ≥ 8: OR 2

Cherbuin et al., 2009257 Community cohort 4 years 

18 MCI 64 MCD 

18-item Goldberg Depression & Anxiety Scale Antidepressant medication 

MCI Any mild cognitive disorder (MCD) 

Age Sex Education 

For MCI, depressnot specified): O2.22) (2082) Antidepressant m20.57) 

Christensen et al., 1997289

Community cohort 

Mean 3.6 years 26 cognitive decline 

18-item Goldberg Depression & Anxiety Scale 

MCI Age 

Education 

No association, O

Geda et al., 2006291

Clinical cohort (840) 

Mean 3.5 years 50 cognitive decline 

GDS-15 ≥ 6 prior 

to MCI 

MCI Age 

Sex Education 

HR 2.2 (95% CI 1

Ravaglia et al., 2008296 Community cohort 

(864) 

Mean 3.9 years 155 cognitive decline 

GDS-30 ≥ 10 at 

baseline; antidepressant use 

MCI Age 

Sex Education APOE e4 Stroke risk score HTN Hyperhomocysteninemia 

GDS: OR 1.1 (95Antidepressant us

188
Study Sample (n) Followup Exposure Case definition Confounding 

adjustment 

Results 

Wilson et al., 2007297 Community cohort 

(1256) 

1 to 12 years 482 cognitive decline 

CES-D-10 symptom count at baseline 

MCI Age 

Sex Education 

RR 1.06 (95% CI symptom 

Barnes et al., 2007271 Community cohort 

(9704) 

Median 10 years 3202 cognitive decline 

GDS-15 ≥ 6 MMSE decline in 

lowest tertile 

Age Education Baseline cognition Study site 

Elevated GDS asnot reported 

Dufouil et al., 1996290 Community cohort 

(2726) 

3 years 48 cognitive decline 

CES-D ≥ 17 (men) 

& ≥ 23 (women) at 

baseline 

MMSE decline ≥ 5 

points 

Age Sex Education Marital status IADL Baseline cognition 

OR 0.8 (95% CI 0

Geerlings et al., 2000292

Community cohort (2399) 

Mean 3.1 years 251 cognitive decline 

CES-D ≥ 16 at 

baseline 

MMSE decline ≥ 3 

points 

Age Sex 

OR 1.07 (95% CI 

Education Memory complaints Baseline cognition 

Community cohort 

Ng et al., 2009293 and 

Niti et al., 2009308

Mean 1.5 years 

Chinese GDS ≥ 5 at baseline 

MMSE decline ≥ 1 

point 

Age Sex 

(1487) Educational level 

Baseline MMSE APOE Vascular risk factors 

OR 2.29 (95% CI Men: OR 4.74 (1Women: OR 1.29 

Panza et al., 2008294 Community cohort 

(1524) 

Mean 3.5 years 113 cognitive decline 

GDS ≥ 10 at 

baseline 

MCI Age 

Sex Educational level Vascular risk factors 

RR 1.25 (95% CI 

189
190

Study Sample (n) Followup Exposure Case definition Confounding 

adjustment 

Results 

Paterniti et al., 2002295 Community cohort 

(1189) 

4 years 161 cognitive decline 

CES-D ≥ 17 (men) 

& ≥ 23 (women) at 

one time point (intermittent) or > 1 time point (persistent) 

MMSE decline ≥ 3 

points 

Age Sex Education Alcohol use Tobacco use Psychotropic drugs Six chronic medical conditions Baseline cognition 

OR 1.55 (95% CI Episodic OR 1.22 Persistent OR 2.1 

Yaffe et al., 1999298 Community cohort 

(5781) 

4 years 653 cognitive decline 

GDS-15 ≥ 6; 3 to 

5; vs. ≤ 2 

MMSE decline ≥ 3 

points 

Age Education Baseline cognition Health status Exercise Alcohol use Functional status Clinic site 

GDS ≥ 6: OR 2.1 

GDS 3 to 5: OR 

Abbreviations: APOE = apolipoprotein E gene; APOE-e4 = e 4 allele of the apolipoprotein E gene; CES-D = Center for Epidemiologic Studies Depreitem version scored 0-30); CI = confidence interval; GDS= Geriatric Depression Scale; HR = hazard ratio; HTN = hypertension; IADL = Instrumental MCD = mild cognitive disorder; MCI = mild cognitive impairment; MMSE = Mini-Mental State Examination; NR = not reported; OR = odds ratio; R
Anxiety. We identified four prospective cohort studies, involving 6297 mid- to late-life 

adults, examining the association between anxiety and cognitive decline.257,309-311 All studies 

were conducted in community-based samples in Western Europe or Australia and followed 

subjects for up to 17 years. 

The study by Wetherell et al.311 followed 704 same-sex twins; the overall followup rate was 

75.5 percent. Subjects with dementia at baseline or either of the two followup assessments were 

excluded from analyses. A baseline measure of neuroticism was used as a proxy for anxiety, and 

cognitive outcomes were assessed using 11 different measures. Analyses were adjusted for age, 

sex, and education level, but not for other psychiatric symptoms. There was no association 

between the 9-item neuroticism measure and change in cognition for any of the 11 different 

measures. 

The study by Bierman et al.309 followed 2351 adults aged 55 to 85. The followup rate at year 

nine was 62.5 percent, and dropout was associated with higher anxiety scores and lower 

cognitive performance, which may have biased the estimate of association. Anxiety was 

measured at multiple time points using the Hospital Anxiety and Depression Scale (HADS), and 

cognitive outcomes included a general measure of cognitive functioning (MMSE) and measures 

of fluid intelligence, processing speed, and episodic memory. Analyses were adjusted for age, 

sex, education, chronic disease count, depressive symptoms, alcohol consumption, and 

benzodiazepine use. There was no association between anxiety symptoms and cognitive decline 

for any of the cognitive measures. 

The study by Gallacher et al.310 followed 2358 non-demented men aged 48 to 67 for a mean 

of 17.3 years. Only those with baseline anxiety scores and followup (n = 1160, 48 percent) were 

included in the analyses. There were multiple baseline demographic and clinical differences 

between those with and without followup, potentially biasing the estimate of association. 

Anxiety was measured with the State Trait Anxiety Inventory (STAI) and dichotomized as high 

using the 31st percentile. Analyses were adjusted for age, education, marital status, cognitive 

function, and vascular risk factors. During followup, there were 174 cases of incident CIND and 

69 cases of incident dementia. Elevated anxiety scores were associated with increased risk of 

CIND (OR 2.31; 95 percent CI 1.20 to4.44) and risk of the combined outcome of CIND or 

dementia (OR 2.19; 95 percent CI 1.24 to 3.88). A sensitivity analysis excluding those with 

cognitive impairment at baseline showed a stronger association. 

Cherbuin and colleagues257 followed 2082 cognitively normal adults for 4 years; followup 

exceeded 80 percent. Anxiety was measured using the Goldberg Anxiety/Depression Scale but a 

threshold for an abnormal result was not specified. Anxiety medication was assessed at baseline. 

During followup there were 18 incident cases of MCI and, using broader criteria, 64 cases of 

mild cognitive disorder (MCD). Anxiety symptoms and anxiety medications were not associated 

with MCI or MCD. A sample size or power calculation was not reported, but the study likely had 

low powered to exclude a clinically significant association. 

In summary, four prospective cohort studies failed to find a consistent association between 

anxiety symptoms and cognitive decline. One study309 was strengthened by a validated scale for 

anxiety, measured at multiple time points, but no study used a clinical or criterion-based 

diagnosis of anxiety disorders. Questionnaires, such as the HADS, correlate only moderately 

with clinical diagnosis; a criterion-based diagnosis may be a more clinically relevant measure of 

exposure. 

Resiliency. We did not identify any good quality systematic reviews or primary studies that 

evaluated the association between psychological resiliency and risk of cognitive decline.

191
192

Medications. Prescription and non-prescription drugs considered under this heading include 

statins, antihypertensives, anti-inflammatories, gonadal steroids, cholinesterase inhibitors, and 

memantine. 

Statins. Our search identified four cohort studies examining the relationship between statin 

use and cognitive decline.153,312-314 A total of 6827 older adults (mean age > 70 years in all 

studies) were involved. All studies were conducted in the United States; three drew samples from 

the community. Followup ranged from 1 to 12 years. Three of the four studies reported measures 

of global cognition, while the fourth312 reported executive function. Three studies screened for 

and excluded subjects with dementia. The fourth study312 recruited a consecutive sample of 

veterans from primary care settings, with a mean age of 75 years old, but did not screen for 

dementia. Only one study selected subjects in a manner that minimized selection bias and 

baseline inequalities between exposed and unexposed groups.313 Two of the four studies 

classified statin use only at baseline.312,314 Data were analyzed appropriately and controlled for 

confounders. 

Due to incomplete reporting and heterogeneity in study designs, a summary estimate of effect 

was not calculated. As summarized in Table 53, results were mixed. The study by Bernick et 

al.313 was the largest, assessed statin use annually, used multiple control groups, and evaluated 

annual change for a mean of 5.1 years using a well-validated global measure of cognitive 

change. In an analysis adjusted for age, sex, education, race, APOE e4, and baseline cholesterol, 

the difference in mean rate of change in the Modified Mini-Mental State Examination (3MS) 

between continuous statin users compared to subjects for whom treatment was recommended but 

not taken did not differ significantly (0.40 annually; 95 percent CI -0.03 to 0.87). For continuous 

statin users compared with subjects in whom lipid lowering treatment was not recommended, the 

difference in mean rate of 3MS change favored statin use (0.49; 95 percent CI 0.04 to 0.95). In 

summary, a limited number of observational studies, some with important methodological 

limitations, do now show a consistent association between statin use and cognitive decline in 

older adults. 
Table 53. Statins and risk of cognitive decline 

Study Sample (n) Followup Exposure Case definition Confounding adjustment Results Agostini et al., 2007312

Clinical cohort (756) 

1 year Any use at 

baseline ; medication bottles, medical record 

Trails B Age 

Race Education Alcohol use Tobacco use Charlson comorbidity Dementia Medication count Primary care visits IADL Cholesterol History of MI or PVD Liver disease Baseline Trails B 

No significant d

Arvanitakis et al., 2008153

Community cohort (929) 

1 to 12 years 

Any statin during study; pharmacy records 

Battery of test summarized into: global cognition, memory, perceptual speed, visuospatial ability 

Age Sex Education 

No significant memory, percevisuospatial m

Bernick et al., 2005313 Community cohort 

(3334) 

5.1 years None, 

intermittent, continuous; medication bottles 

3MS Age 

Sex Race APOE e4 Cholesterol 

Mixed results: compared to thtreatment, but compared to thlowering treatmtaken 

Community cohort 

Szwast et al., 2007314 3 years Any statin use; medication 

bottles at baseline 

CSI-D Age 

Sex 

(1808) Education 

APOE e4 

Less decline in 

Abbreviations: 3MS = Modified Mini-Mental State Examination; APOE e4 = epsilon 4 allele of the apolipoprotein E gene; CSI-D = Community Scre

Dementia; IADL = Instrumental Activities of Daily Living; MI = myocardial infarction; PVD = peripheral vascular disease; Trails B = Trail Making T

193
In summary, data from observational studies were limited and did not show a consistent 

association between statin use and cognitive change. Two large RCTs, discussed under Question 

4, also did do not show an association between statin use and cognitive change. 

Antihypertensives. Two studies were identified examining the impact of antihypertensives on 

cognitive decline (Table 54).267,278 Tervo et al.267 looked at risk factors for incident MCI 

diagnosed using very modified Petersen’s criteria in a sample from Kuopio, Finland. Self-report 

of antihypertensive use was elicited during a structured interview. It is not clear that the 

indication for the antihypertensive was elicited, but 44 percent of the overall sample had directly 

measured HTN (≥ 160/95). Diagnosis of MCI was based primarily on a test of delayed recall. 

Over a 3.26 year followup, there was no statistically significant impact of antihypertensive use 

on incident MCI; adjusted OR 1.61 (95 percent CI 0.87 to 2.99). 

In the Tzouri study278 of the Epidemiology of Vascular Aging (EVA) cohort from Nantes, 

France, cognitive decline was defined as a 4-point decrease in the Mini-Mental State 

Examination (MMSE) over 4 years. A 4-point decline in the MMSE would represent a 

significant decline in cognitive function, and was found in 8.5 percent of the sample. Again, the 

use of antihypertensives was not found to be protective against cognitive decline in the overall 

sample (as compared to those with normal measured BP and not on antihypertensives; adjusted 

OR 1.1; 95 percent CI 0.7 to 1.7). However, among subjects with HTN, the risk of cognitive 

decline was decreased in those taking antihypertensive medication at baseline and followup 

compared to those not taking antihypertensives at either time. 

Both studies evaluated relatively young populations. The mean age in Tervo267 was 67.7 

years and in Tzourio278 65 years. Both studies were of relatively brief duration. Cognitive decline 

would be expected to be fairly uncommon under these circumstances and definitions of decline. 

In summary, the limited evidence from observational studies does not support an association 

between antihypertensive use and lower risk for cognitive decline. 

194
Table 54. Antihypertensives and risk of cognitive decline 

Study Sample (n) Followup Exposure Case definition Confounding 

adjustment 

Results 

Tervo et al., 2004267Inhabitants of Kuopio community (Finland) 

Community cohort (806) 

3.26 years Cases of MCI: 65 

Self-report of antihypertensives 

Modification of Petersen criteria (no requirement for subjective complaint, no ADL requirement, and no informant): Scoring 1.5 SDs below average in delayed recall in logical memory or visual reproduction memory, with a CDR score of 0.5 and no dementia were called MCI 

Age Sex Education APOE e4 Cardiovascular disease Cerebrovascular disease DM HTN 

OR (95% CI) for cmedicated HTN in 1.61 (0.87 to 2.99

Tzourio, et al., 1999278

Nantes, France 

Community cohort (1052) 

4 years Cases of cognitive decline at 4 years: 98 

Self-report and medication bottle review 

Decline of 4 points, or more, on MMSE (over 4 yrs) 

Age Sex Education Income Depressive symptoms APOE e4 Baseline MMSE 

Overall OR (95% with antihypertencompared to thosantihypertensive For hypertensive antihypertensives OR (95% CI) for cto 4.9) If not taking antihOR (95% CI) for cto 15.0) 

Abbreviations: ADL = activities of daily living; APOE e4 = epsilon 4 allele of the apolipoprotein E gene; BP = blood pressure; CDR = Clinical Deme

confidence interval; DM = diabetes mellitus; HTN = hypertension; MCI = mild cognitive impairment; MMSE = Mini-Mental State Examination; OR deviation 

195
Anti-inflammatories. Our search identified six cohort studies examining NSAID use and risk 

of cognitive decline.240,270,315-318 These studies are summarized in Table 55; detailed evidence 

tables are provided in Appendix B. The classification of NSAID exposure was variable ranging 

from any use, to use before a certain age, to use for a variable duration of time. All of the studies 

evaluated decline over time in cognitive testing. All used memory tests. Other tests, as listed in 

Table 55, were added to individual studies. Studies by Hee Kang et al.318 and Grodstein et al.317

used a global test score formed from the combination of the tests given. Cognitive decline in the 

Cache County cohort240,315 was defined by change in the 3MS, a measure of general cogniton 

measure using memory, orientation, and similarities among other items. 

Five studies used community cohorts from the United States and one used a cohort from 

Amsterdam.316 Two of the studies examined the same Cache County cohort, one evaluating 

NSAIDs alone,315 the other evaluating the combination of NSAIDs with vitamins C and E.240 In 

total, approximately 32,600 subjects were included from the five unique cohorts. Followup 

ranged from 2 to 9 years. Three studies restricted analysis to subjects without cognitive 

impairment at baseline.240,315,318 Three studies did not eliminate cognitively impaired subjects 

when forming the cohorts, but one316 had a mean baseline MMSE of 27.5, suggesting few 

subjects had significant cognitive impairment, and another270 formed the cohort in middle age 

(47 to 70 years old) when prevalent impairment would be expected to be low. The CHAP 

cohort317did not limit inclusion to cognitively intact subjects and enrolled subjects with a mean 

baseline age of 79.9, suggesting that there may be a significant level of cognitive impairment in 

the sample. Cognitive impairment among participants could differentially bias the recollection of 

exposure. 

Fohuti et al.240 found that subjects using vitamin C, vitamin E, and NSAIDs who had at least 

one APOE e4 maintained cognitive functioning as opposed to declines in every other group. 

Hayden and colleagues,315 examining the same Cache County cohort, found a protective effect of 

NSAIDs that was most beneficial when NSAIDs were started before age 65 and when at least 

one e4 allele was present. Mean age at baseline for the Cache County study was approximately 

74 years. Recall of NSAID use decades earlier are of unclear accuracy. Grodstein317 found 

slower rates of decline with longer NSAID use (5+ years) as compared to no use. Information on 

duration of NSAID use was collected 3 years after baseline (length of followup 3 to 9 years). It is 

possible that information on duration of use is more likely to be biased than the data on any 

NSAID use collected at baseline in those subjects developing cognitive deficits. However, a 

sensitivity analysis eliminating subjects with baseline cognitive scores in the bottom 10 percent 

was performed and did not show substantially different results. Grodstein et al.317 found more 

protective effect in this relatively more intact group, especially those on NSAIDs longer. Jonker 

and colleagues found lowered odds ratio for decline on tests of delayed recall but confidence 

intervals were wide and included no effect.316 An analysis of the large Nurses Health Cohort did 

not show an association between global cognitive decline and aspirin use or NSAID use of at 

least 8 years (RR for substantial decline 0.77; 95 percent CI 0.57 to 1.05).318 Finally, another 

large cohort study found no association between NSAID use and cognitive decline on any of 

three measures.270

In summary, results from five cohort studies are inconsistent regarding the association 

between NSAIDs and cognitive decline. Several studies find no association between NSAID use 

and cognitive decline and no studies find an association of sufficient magnitude that the impact 

of unaccounted confounders can be dismissed. The Cache County cohort found protective effects 

in some subgroups only. Results from the CHAP cohort may be biased given the unknown 

196
197

cognitive status of the cohort at baseline and the collection of duration of use data a few years 

into the study. There is limited support, based on a subgroup analysis, for a greater effect of 

NSAIDs when used at younger ages, for a longer duration, along with vitamin supplements and 

in those with at least one e4 allele. 
Table 55. NSAIDs and risk of cognitive decline 

Study Sample (n) Followup Exposure Case definition Confounding 

adjustment 

Results 

Fotuhi et al., 2008240

Cache 

Community cohort (3376) 

Up to 8 years (0, 3, 8 years) 

Self-report, pill bottles, probe questions At baseline asked about preceding 2 weeks 

3MS Age 

Sex Educational level DM Cerebrovascular accident APOE status 

Study looked at VitaOnly among those usignificant findings: was maintenance (0to 1.89). Non users w4.53 to -3.01) over thFor NSAIDs alone, epoints (95% CI -4.17 with NSAIDs alone d3.83 to -2.43).over th

Hayden et al., 2007315

Cache (same cohort as above) 

Community cohort (3383 at start; 3294 after 3 years; 2235 after 8 years) 

3 and 8 years 

Self-report, pill bottles, probe questions At baseline asked about preceding 2 weeks 

3MS Age 

Sex Education APOE DM Cerebrovascular accident Followup time Quadratic term for time 

Difference per year: NSAID use before aNo APOE e4: 0.10 pto 0.25; p = 0.19), so compared to non-usWith an APOE e4: 00.18 to 0.63; p = 0.0association with maisubset NSAID use after age 

No APOE e4: -0.16 to -0.03; p = 0.002), decline in non-e4 caas compared to non-With an APOE e4: 0-0.15 to 0.27; p = 0.5association with mai

Jonker et al., 2003316

LASA 

Community cohort – groups of interest selected retro3 years Prescription meds queried and prescription pill bottles examined at baseline and MMSE AVLT Coding task Age Sex Educational level Baseline MMSE score ORs for cognitive de

NSAID (including asaspirin, and aspirin atests (immediate reccoding). Choosing d

198
Study Sample (n) Followup Exposure Case definition Confounding 

adjustment 

Results 

spectively 

(612 chosen from community sample) 475 who did not use NSAIDs 137 who did use prescription NSAIDs at both visits 

followup visit Vascular disease 

DM Rheumatoid arthritis 

CI]): NSAIDs (including aNSAIDs (excluding a2.39) Aspirin only: 0.55 (0There was a protect(low-dose predomina> 75 years of age 

Grodstein et al., 2008317

Community cohort 

Up to 9 years 

Pill bottles, self -report 

East Boston Tests of Immediate Memory and Delayed recall MMSE SDMT 

Age Race Sex Educational level Interaction of time with each 

(4409) 

Baseline and cycle 2 (after 3 years) 

CHAP (Chicago) 

In the analysis of the 10% removed, the abut are stated to be the analysis of the wno difference in the ydecline. Comparing participa10%) with short histoyears) to no NSAIDsdecline of 0.009 SD longer duration of us0.013 (p = 0.012); daStandard units per th

Hee Kang et al., 2003318Nurses Health cohort 

Community cohort (13,255) 

2 years Self-report (by 

nurses) in 1980 and every 2 years until 1998 NSAIDs as never, past, current, infrequent, and 

TICS Delayed recall of a 10 word list East Boston memory test (immediate and delayed) 

Age Baseline scores Perceived change in memory Cigarettes 

Using global score, lhad no difference in 0.70 to 1.19) 

Education 

For other NSAIDs, lohad lower risk of “su0.77 (95% CI 0.57 to 

199
200

Study Sample (n) Followup Exposure Case definition Confounding 

adjustment 

Results 

current regular by 

numbers of years 

Verbal fluency Digit span backwards Calculation of a global score Substantial decline defined as decline of ≥ 3 on 

TICS and worst 10% of distribution of decline for the global score 

Alcohol BMI Physical activity HRT DM HTN Hypercholesterolemia Depression Cardiovascular disease 

RR also given for ind

Knopman, 2001270 Community cohort 

(10,963) 

6 years Self-report, pill 

bottles Subjects asked at 3 years (visit 2) about previous 2 weeks 

DWR DSST WF 

Age Race Sex Educational level Site CNS-relevant meds (antipsychotics, antidepressants, anxiolytics, opiates, anticonvulsants, antineoplastic agents) 

Adjusted mean chanrisk factor reported “NSAID use (and seassociated with declcognitive tests” 

Abbreviations: 3MS = Modified Mini-Mental State Examination; APOE = apolipoprotein E gene; APOE e4 = epsilon 4 allele of the apolipoprotein E Verbal Learning Test; BMI = body mass index; CI = confidence interval; CNS = central nervous system; DM = diabetes mellitus; DSST = Digit Symb

delayed word recall; HRT = hormone replacement therapy; HTN = hypertension; MMSE = Mini-Mental State Examination; NSAID(s) = non-steroidaOR = odds ratio; RR = relative risk; SD = standard deviation; SDMT = Symbol Digit Modalities Test; TICS = Telephone Interview for Cognitive Stat
Gonadal steroids. We identified a single good quality systematic review that examined the 

association between hormone replacement therapy and cognitive decline.38 The review identified 

nine RCTs and eight cohort studies. Ten studies were from the United States, four from 

European countries, and three from Canada. The nine RCTs are discussed separately under 

Question 4, below. Of the eight cohort studies, six were rated as having fair quality and two as 

poor. The cohort studies included 15,298 subjects ranging in age from 59 to 77 years, with 

duration of followup ranging from 1.5 to 15 years. The formulation of estrogen varied in 

composition, dose, and method of administration. Most subjects received an estrogen 

formulation that did not include a progestin. 

Studies were not combined because more than 40 different tests were used to assess cognitive 

function. Thirty of these tests were used in a single study, and seven tests were used in more than 

two studies, but test administration was not always uniform. Verbal memory using the immediate 

verbal recall test was examined in four studies and showed a benefit of estrogen treatment in one 

study. Delayed verbal recall was improved by estrogen treatment in two of three studies, while 

visual memory improved in one of two studies. Attention tasks were divided into complex 

attention (0 of 3 positive studies) and mental tracking (0 of 3 positive studies). Most of the 

studies reporting benefit noted an effect of estrogen on attention tasks and involved women with 

menopausal symptoms. Abstract reasoning was shown to be improved by estrogen treatment in 

one of two studies, and mental status, as measured by an improved score in a dementia screening 

examination, was improved in two of five studies. Verbal fluency was reported to be improved in 

one of four studies, with users of estrogen more fluent in naming than non-users. The review 

authors concluded that estrogen does not consistently enhance asymptomatic women’s cognitive 

performance on formal testing. 

Our search identified one new observational study published since 2001 (Table 56; a detailed 

evidence table is provided in Appendix B). Ryan et al. examined the association of self-reported, 

life-time estrogen exposure to late-life cognition in a prospective cohort study involving 996 

French women aged 65 or older.319 A battery of tests – including the MMSE, the 5-word Test of 

Dubois; Isaacs Set Test; semantic fluency; BVRT; MMSE; and Trails A and B – was performed 

at baseline, 2, and 4 years. In the fully adjusted model which accounted for age, education, and 

baseline test performance, the authors found no association of estrogen use with cognitive 

change. 

In summary, there may be a slight benefit for symptomatic postmenopausal women in tests 

of verbal memory, vigilance, reasoning, and motor speed, which could be mediated by symptom 

relief. Available data does not support a consistent benefit of estrogen use in modifying cognitive 

decline. There is insufficient evidence to determine the optimal formulation of estrogen; the 

dose, duration, and onset of treatment; or if progestins attenuate the effect of estrogen. 

201
Table 56. Gonadal steroids and risk of cognitive decline 

Study Sample (n) Followup Exposure Case definition Confounding adjustment ReRyan et al., 2009319ESPRIT study 

Community cohort (996) 

4 years (testing at 2 and 4 years) 

Lifetime estrogen exposure Self-report of reproductive factors associated with estrogen exposure and use of exogenous hormone treatment 

Substantial decline on cognitive tests defined as lowest quintile of the difference between baseline score and score at either of the followup visits Tests used: 5-word Test of Dubois; Isaacs Set Test; semantic fluency; BVRT; MMSE; Trails A and B 

Age Educational level Marital status Depressive symptoms Caffeine intake Physical impairment Medical conditions Baseline cognitive status 

In asesof co

Abbreviations: BVRT = Benton Visual Retention Test; MMSE = Mini-Mental State Examination; Trails A = Trail Making Test Part A; Trails B = Tr

202
Cholinesterase inhibitors. We did not identify any systematic reviews or primary studies that 

evaluated the association between cholinesterase inhibitors and risk of cognitive decline. 

Memantine. We did not identify any systematic reviews or primary studies that evaluated the 

association between memantine and risk of cognitive decline. 

Social, Economic, and Behavioral Factors 

Early childhood factors. We identified three eligible cohort studies that examined the 

association between childhood factors and cognitive decline in later life.173,320,321 These studies 

are summarized in Table 57; detailed evidence tables are in Appendix B. One of the studies 

reported a categorical outcome;321 the other two reported continuous outcomes of cognitive 

decline.173,320 Given the small number of eligible studies, the studies reporting continuous 

outcomes are included in the current discussion. All three of the studies used community samples 

in the United States, and one of the studies included individuals residing in religious order 

facilities.173 The length of followup ranged from 2 to 5.6 years. The cognitive status of 

participants differed across the studies. One study320 included all participants who completed 

cognitive testing at a minimum of two time points, so some individuals may have had dementia 

at baseline. The other two studies173,321 included only individuals who were non-demented at 

baseline. All of the studies at least partially used sample selection methods to minimize selection 

bias. All of the studies collected exposure data using self-report of a range of childhood factors; 

one study also used public records.173 There was no objective validation of the indices derived to 

represent childhood socioeconomic status or childhood cognitive milieu. 

The studies did not compare baseline characteristics between those exposed and unexposed, 

but one compared baseline differences by outcome groups (i.e., those who had cognitive decline 

versus those who did not).321 The case definitions and cognitive outcomes for the studies are 

described in Table 57. The analyses appear generally appropriate and controlled for relevant 

potential confounders, but none of the studies conducted a priori sample size calculations. Two 

studies found no association between early life socioeconomic status or childhood cognitive 

milieu and cognitive decline in later life.173,320 The third study used a Japanese-American cohort 

and found that numerous factors associated with stronger affiliation with Japan or the Japanese 

culture were associated with protection against cognitive decline in later life.321 For select 

variables that allowed graded responses, the study found a dose-response effect where the greater 

the exposure to Japanese culture the less likelihood of cognitive decline. The differences in the 

sample characteristics and the childhood factors examined among these three studies make 

drawing conclusions difficult. The authors of the Japanese-American cohort study point to a 

number of differences between the Japanese and American cultures that may explain their 

findings. Based on the two studies using predominantly individuals born and raised in the United 

States, there does not appear to be a strong influence of childhood socioeconomic status or 

childhood cognitive milieu on cognitive decline in later life.

203
Table 57. Childhood factors and risk of cognitive decline 

Study Sample (n) Followup Exposure Case definition Confounding 

adjustment 

Results 

EversonRose et al., 2003320

Community cohort (4398) 

5.3 years (mean) 

Childhood socioeconomic position index derived from selfreport of: (1) parental educational attainment, (2) parental occupational prestige, (3) family financial status as a child Childhood cognitive milieu index derived from self report of: (1) frequency of someone in household having been read to, (2) told stories to, or (3) played games with as a child. 

Global composite index of scores on the MMSE, the immediate and delayed recall of the East Boston Story, and the oral version of the Symbol Digit Modalities Test 

Age Race Sex Educational level 

Rate of cognitive declinchildhood socioeconom

0.003 (95% CI -0.009 tRate of cognitive declinchildhood cognitive mil

(95% CI -0.004 to 0.00associated with less co

Wilson et al., 2005173 Community cohort 

(some lived in religious order facilities) (859) 

5.6 years Self-report and county 

public records Information collected by self-report: (1) parental education, (2) paternal occupation, (3) number of children in the family, and (4) participant’s education level. Information collected from public records for the participant’s county of birth: (1) literacy rate, (2) percent of children in county attending school, and (3) the Duncan socioeconomic index for head of households for the county. 

Global composite index of scores on the MMSE, the immediate and delayed recall of the East Boston Story, and the oral version of the Symbol Digit Modalities Test 

Age Sex Education 

Rate of cognitive declinchildhood household s(SE) = -0.01 (0.01); p = Rate of cognitive declinchildhood county socio0.01 (0.01); p = 0.10 Results were generally cognitive domains 

Graves et al., 1999321 Community cohort 2 years Self-report of the following information: (1) 

migration history, (2) 

Dichotomous outcome of “decliners” vs. 

Age Sex 

Factors associated lesJapanese is only/most

204
205

Confounding 

adjustment 

Study Sample (n) Followup Exposure Case definition Results 

(1604) 144 

decliners 1455 nondecliners 

education, (3) number of years lived in Japan before age 18 yr, (4) age at which English became main language spoken at home, (5) language usually spoken at home currently, (6) current facility with reading and writing Japanese, (7) friends growing up being mainly Japanese vs. non-Japanese, or even number of both, (8) current friends Japanese, non-Japanese or even number of both, (9) current religion, (10) diet consistent of mainly Asian food, Asian and western food equally or mainly western food. 

“non-decliners.” Decliners defined as individuals who declined 5.15 points (equal to -1.0 SD) on the Cognitive Abilities Screening Instrument (CASI). 

Educational level Baseline cognitive status Followup time 

0.45 (95% CI 0.23 to 0English was the home OR 0.42 (0.21 to 0.81; Baseline interview in Jto 0.69; p < 0.01) Generation Issei (born to 0.58; p < 0.01) or KiJapanese education): 0.05) compared to U.SAny education in Japa< 0.01) Lived in Japan from 1 tto 0.91; p < 0.05) or lived in Japan from 8 to to 0.78; p < 0.01) or livyears: OR 0.32 (0.15 tcompared to 0 years Reads/write Japanese (0.23 to 0.77; p < 0.01) difficulty: OR 0.96 (0.6does not read/write JapCurrent friends mostly to 0.93; p < 0.01) Past friends mostly Jap1.33) Eastern religion (Budd(0.87 to 2.07) Eat only Asian foods: O

Abbreviations: CASI = Cognitive Abilities Screening Instrument; CI = confidence interval; MMSE = Mini-Mental State Examination; OR = odds rat

SE = standard error
Education/occupation. As described above (under Key Question 1), we consider 

educational and occupational factors as subcategories under a single heading. 

Education. We identified eight eligible cohort studies that had a categorical 

outcome.183,258,267,322-326 We also review an additional six studies that had a continuous outcome 

because they provide information on population subgroups of interest, such as different ethnic 

groups327-329 or different APOE genotypes.330-332 In the majority of these studies, the focus was 

on investigating the risk of cognitive decline and years of education completed, but in a few 

studies, education was only one of several risk factors examined in relation to cognitive decline. 

The studies are summarized in Table 58; detailed evidence tables are provided in Appendix B. 

Seven of the studies used community samples in the United States,258,323-325,327-329 one used a 

health maintenance organization sample in the United States,330 three used community samples 

in Europe,322,326,332 one used a sample in Europe that included participants from both the 

community and institutions,267 one used a community sample in Australia,331 and one used a 

religious order sample in the United States.183 At baseline, participants were non-demented in 

some studies322-324,330,332 and cognitively normal in some others.183,267,327 In other studies, those 

with mild cognitive impairment and dementia were not specifically excluded;325,326,328,329,331

however, given the length of the followup period328,329 or the baseline age of the sample,331 it is 

likely that the majority of the participants were non-demented at baseline in most of these 

studies. The final study258 included only individuals with a baseline 3MS score > 80 in an 

attempt to exclude those with dementia. Length of followup ranged from 1 to 11 years. Exposure 

was determined based on self-reported information about years of education completed; this is a 

standard and well-accepted method of data collection for this information. One study examined 

the association between literacy level as measured by a standard neuropsychological test and 

cognitive decline.327 Most of the studies used sample selection methods to minimize selection 

bias; however, one study required that participants agree to brain donation at the time of death, 

and this may have introduced some selectivity into the sample.183 One other study only partially 

used sample selection methods to minimize selection bias.322 Definitions of cognitive decline 

varied among the studies and are described in Table 58. In all but one study331 analyses were 

appropriate and controlled for relevant potential confounders. 

Among the eight studies that had categorical outcomes, four reported that having fewer years 

of education was associated with an increased risk of cognitive decline on at least some of the 

cognitive measures used,258,323-325 and the odds ratio for the fifth study326 was in the same 

direction but did not reach statistical significance. An additional two studies reported that having 

fewer years of education was associated with an increased risk of incident MCI.183,267 In general, 

the association was strongest at the extremes of high and low education, thus suggesting a doseresponse pattern even when the association was not significant at all intermediary education 

levels. In the one study that did not find a significant association between education level and 

cognitive decline, the education level for the sample was quite low.322 

In contrast to the studies that used categorical outcomes, the studies that used non-categorical 

outcomes typically did not find an association between years of education and cognitive decline. 

Four studies reported no association between years of education and rate of cognitive decline in 

their total samples.329-332 A fifth study328 found only a non-linear association such that the rate of 

cognitive decline at average or high levels of education was slightly increased during earlier 

years of followup, but slightly decreased in later years in comparison to low levels of education. 

The sixth study327 reported that after controlling for education, participants with lower literacy 

were more likely to have faster decline in cognition.

206
207

These six studies using continuous variables also examined the association between years of 

education and longitudinal cognitive performance in selected subgroups of the samples. The 

three studies that reported results comparing ethnic subgroups showed few differences across the 

subgroups. The study by Wilson and colleagues328 showed no differences between whites and 

African-Americans for the association between level of education and cognitive decline. Manly 

and colleagues327 reported no significant differences between whites, Hispanic and AfricanAmericans regarding the association between literacy level and rate of cognitive decline. The 

study by Karlamangla and colleagues329 reported only one difference among multiple ethnic 

groups. They found that among non-Mexican Hispanic Americans, a greater number of years of 

education was associated with less cognitive decline over time. 

Four studies (three using continuous outcomes and one using a categorical outcome) assessed 

potential interactions between APOE genotype and education, and each study reported different 

results. Winnock and colleagues332 found no interaction between APOE genotype and education 

in their association with cognitive decline. Kalmijn and colleagues326 reported that APOE e4 

non-carriers with less education tended to show greater decline than APOE e4 carriers with low 

education, but the risk estimate was not statistically significant. Shadlen and colleagues330 found 

that lower education was associated with greater cognitive decline among APOE e4 

homozygotes but not among heterozygotes. Christensen and colleagues331 found that among 

individuals with < 16 years education, those with at least one APOE e4 allele had greater 

cognitive decline on selected cognitive measures. This latter study did not control for baseline 

cognitive performance or age; it also reported many statistical comparisons without adjustment 

for multiple comparisons. The widely discrepant findings from these studies make it difficult to 

draw any conclusions about the interaction between education and APOE genotype in their 

association with cognitive decline. 

The generally inconsistent findings reported by studies using categorical outcomes compared 

to those using continuous outcomes raises fundamental questions about the best methodological 

approach for examining this issue. The studies using categorical outcomes often categorize 

“cognitive decliners” as those who show the most pronounced decline. This may identify 

individuals who are in the prodromal stages of a progressive dementing disorder such as AD. In 

this case, it is possible that the association between years of education and cognitive decline 

reflects an underlying association between years of education and AD. Some additional 

methodological points might be considered. In the United States and some other developed 

countries, years of education may be a poor reflection of inherent ability for ethnic minorities 

and other groups for whom educational opportunities were not accessible. In the first half of the 

20th century, when the participants in these studies were attending school, the quality of 

education in the United States differed across regions of the country and also across racial and 

ethnic groups. For these reasons, it has been suggested that reading skills, not years of education, 

may be a better marker of ability in these groups.327 

In conclusion, the evidence is inconsistent regarding the putative association between years 

of education or its underlying construct and risk of cognitive decline. Further research is needed 

in this area that directly compares the association between years of education and cognitive 

decline using both categorical and non-categorical outcomes in the same sample. 
Table 58. Years of education and risk of cognitive decline 

Study Sample (n) Followup Exposure Case definition Confounding 

adjustment 

Results 

Alvardo, et al, 2002322 Community cohort 

(557) 

4 years Self-reported 

information about education in the following categories: 1) Illiterate 2) Literate (no formal education, can read and write) 3) 1 to 3 years of formal education 4) 4 or more years of formal education Then reclassified into 2 categories: 1) Incomplete primary school 2) Complete primary school 

Change scores on a cognitive scale (0 to 32 points) Cognitive scale made up of simple tests of orientation, verbal memory, naming Categorized as: “Mild decline” = -2 to -7 “Severe decline” = -8 to -23 “Normal” = -1 to 12 

Age Sex Educational level Baseline cognitive status Occupation 

Less than complete pdecline: O2.43) 

Koster, et al., 2005323 Community cohort 

(2088) 

4 years Self-reported education Cognitive decline 

defined as ≥ 5-point 

decline on the 3MS from baseline to followup 

Age Race Sex Educational level Baseline cognitive status Study site Household income Biomedical factors 

Adjusted OHigher risk associated > 12 years 12 years eto 1.83) < 12 years (1.59 to 2.

Lee, et al., 2006324 Community cohort 

(7118) 

2 years Self-reported education Substantial cognitive 

decline defined as the worst 10% of the distribution of change on: 

Age Clinical variables Smoking Physical activity 

No differendecline on or verbal meducated substantia

208
Study Sample (n) Followup Exposure Case definition Confounding 

adjustment 

Results 

1) TICS 2) Verbal fluency test 3) Verbal memory test 4) A composite score of all cognitive tests 

Alcohol use (p value tr

fluency (p generally, least educeffects. Intlevels did difference

Lee, et al., 2003325 Community cohort 

(13,429) 

2 years Self-reported education Substantial cognitive 

decline defined as the worst 10% of the distribution of change on: 1)TICS 2) Immediate or delayed recall of the TICS word list 3) Verbal fluency test 4) Verbal memory test 5) Digit span backwards 6) Composite score for all cognitive tests 

Baseline test scores Age Clinical variables Medications Smoking Alcohol use BMI SF-36 vitality and mental health scores 

Significant of cognitivlevel of edvalue for tto 0.03) On the comcompared diploma, lodecline asGraduate 0.50 to 0.8BS degree 0.94) 

Tyas, et al., 2007183 Community cohort 

(members of religious order) (470) 

1 to 11 years 

Self-reported education Change from cognitively 

intact to MCI 

Age Education APOE Prior cognitive state 

Higher edulower risk Graduate ≤ high sch(95% CI 1Undergrad(1.17 to 2.

Karlamangla et al., 2009329

Community cohort (2353) 

9 years Self-reported education Cognitive change on an 

abbreviated version of the TICS-m and on the word list memory subitem 

Baseline low performance Length of participation Imputed scores Age Sex Ethnicity 

Education baseline lenot associdecline on score or thThese findregardless associatiocognitive csimultaneo

209
Study Sample (n) Followup Exposure Case definition Confounding 

adjustment 

Results 

Marital status Change in marital status Survivorship 

variables ovariables. Among noAmericansschooling 0.35-point (95% CI 0recall scor

Yaffe et al., 2009258 Community cohort 

(2509) 

8 years Self-reported education Longitudinal 

performance on the 3MS Maintainers: Predicted slopes of 0 or greater (indicating no change or improvement in cognitive scores over time) Minor decliners: Predicted slopes less than 0 decline in cognitive score over time) but no more than one SD below the mean of the slopes Major decliners: Predicted slopes more than 1 SD below the mean 

Age Race APOE genotype 

When confactors assmaintainer cognitive mdecliner fohigh schoo(95% CI 1Risk of beminor dec0.37 to 0.7Risk of bevs. a minowith at lea

OR 4.85 (9Risk of beminor decto 0.98) 

Wilson et al., 2009328 Community cohort 

(6533) 

6.5 (SD 3.6) years 

Self-reported education Composite measure of 

longitudinal change on the immediate and delayed recall of the East Boston Story, SDMT, and MMSE 

Age Race Sex Five chronic medical conditions obtained from self-report of heart attack or MI, HTN, stroke, DM, and cancer 

No linear aeducation cognitive fModels thain educatiocognitive deducation change in over time 0.001; p = 

210
Study Sample (n) Followup Exposure Case definition Confounding 

adjustment 

Results 

cognitive dlevels of eincreased followup blater years levels of eFindings wand white 

Tervo, et al., 2004267 Community cohort 

(includes residents of nursing facilities) 

3.26 (SD 0.7) years 66 MCI cases 

Self-reported education NINCDS-ADRDA 

DSM MCI criteria: CDR = 0.5 and performance on one memory test at least 0.5 SD below average 

Age Race Sex Educational level Baseline cognitive status 

Risk of incnumber of 0.80 (95% 

Christensen et al, 2008331

Community cohort 

4 years Self-reported education Longitudinal change on 

word list memory task, MMSE, SDMT, Digit Span Backwards, reaction time task 

Educational level Head Injury 

(2551) Premorbid intelligence 

After contreducation change sccognitive tSignificant APOE genimmediate word list reamong indeducationAPOE e4 decline. 

Shadlen et al., 2005330

Clinical cohort – HMO (2140) 

3.29 (SD 1.36) years 

Self-reported education Longitudinal change in 

CASI score 

Age Race Sex Years of followup Depression Diabetes HTN 

Education was not asdecline Lower eduwith greateAPOE e4 heterozygOne e4 x e0.002 (95% 

211
Study Sample (n) Followup Exposure Case definition Confounding 

adjustment 

Results 

Cerebrovascular disease 

0.976) Two e4 x e(0.12 to 0.

Manly et al., 2005327 Community cohort 

(1362) 

4.5 years Self-reported education Change on cognitive 

factors of memory, language and executive function Factor scores derived from multiple tests 

Age Race Sex Educational level 

After contrand educalower literahave fasteMemory: Executive 0.002 Language

Kalmijn et al., 1997326 Community cohort 

(718) 

3 years Self-reported education Longitudinal change on 

the MMSE. Decline of at least 2 points categorized as cognitive decline. 

Age Baseline cognitive function History of cardiovascular disease 

Risk of coto individueducation≤ 6 years: 4.9) Compared educationAPOE e4 ≤ 6 years: 8.8) APOE e4 ≤ 6 years: 3.8) P = 0.10 

Winnock et al., 2002332 Community cohort 

(626) 

Range 1-8 years 

Self-reported education Longitudinal change on 

MMSE 

Age Sex Education Time Age by time APOE 

Decline on associated 0.14) There was decline for non-carrie

Abbreviations: 3MS = Modified Mini-Mental State Examination; APOE = apolipoprotein E gene; APOE e4 = epsilon 4 allele of the apolipoprotein E 

index; BS = Bachelor of Science degree; CASI = Cognitive Abilities Screening Instrument; CDR = Clinical Dementia Rating scale; CI = confidence in

212
213

mellitus; DSM = Diagnostic and Statistical Manual of Mental Disorders; HMO = Health maintenance organization; HTN = hypertension; MCI = mild myocardial infarction; MMSE = Mini-Mental State Examination; NINCDS-ADRDA = National Institute of Neurological and Communicative Disease

Disease and Related Disorders Association; OR = odds ratio; RN = registered nurse; RR = relative risk; SD = standard deviation; SDMT = Symbol Distandard error; SES = socioeconomic status; SF-36 = Medical Outcomes Study 36-Item Short Form Health Survey; TICS = Telephone Interview for CTelephone Interview for Cognitive Status (modified version) 
Occupation. We identified four eligible cohort studies in which the focus of the study was 

investigating the risk of cognitive decline and occupational history.322,333-335 All of these studies 

had a continuous outcome; there were no eligible studies with categorical outcomes. The studies 

are summarized in Table 59; detailed evidence tables are provided in Appendix B. One of the 

studies used a community twin sample in the United States,333 one used an HMO sample in the 

United States,335 and two used community samples in Europe.322,334 Length of followup ranged 

from 4 to 14 years. Exposure was determined based on self-reported information about 

occupation or job characteristics. Two studies used sample selection methods to minimize 

selection bias,333,334 while the other two studies partially used such methods.322,335 Definitions of 

cognitive decline varied among the studies and are described in Table 59. Analyses were 

appropriate and controlled for relevant potential confounders. 

The four studies examined different aspects of jobs, making it difficult to compare results. 

One study examined the association between the number of hours worked each week and 

cognitive change over time;334 another examined the association between job characteristics, 

such as general intellectual demand and physical exertion, and longitudinal cognitive 

performance;333 the third study dichotomized occupation by farmers versus non-farmers to 

investigate the relation between jobs and cognitive decline;322 and the fourth study assessed the 

association between three aspects of self-directed work (perceived autonomy, work control, and 

innovation) and cognitive decline.335 The results from Alvarado and colleagues,322 Potter and 

colleagues,333 and Yu and colleagues335 are broadly consistent. One showed a trend toward 

greater cognitive decline for farmers;322 one reported that individuals who worked in jobs with 

high levels of physical exertion showed greater decline;333 and the third reported that greater 

control over one’s work is associated with better maintenance of cognition.335 In all three studies, 

other factors, such as fewer years of education, actually accounted for more of the cognitive 

decline than did occupational characteristics. The study by Virtanen and colleagues334 found that 

working longer hours, a characteristic of jobs associated with higher levels of education, was 

linked to greater decline on a test of reasoning. This finding makes the point that the impact of 

jobs may be multi-faceted, and further work needs to be done to examine the relation between 

different aspects of jobs and cognitive outcomes. 

In conclusion, the data available currently suggest that the reported association between 

occupation and cognitive decline is largely attributable to level of education. In addition, further 

research is needed to decompose the various components of occupation and their role on late life 

cognition. 

214
Table 59. Occupation and risk of cognitive decline 

Study Sample (n) Followup Exposure Case definition Confounding 

adjustment 

Results 

Potter et al., 2006333 Community cohort (twin 

registry) (3880) 

7 years Self-reported 

occupation. Job characteristics coded based on Dictionary of Occupational Titles 

Cognitive change on TICS-m from baseline to followup 

Age Educational level Baseline cognitive status Twin pairing Medical conditions 

Within twin pageneral intelleassociated wicognitive funcfollowup (p = Within twin paphysical exertvisual attentioassociated widecline. Within twin pafactors contribchange compcognitive scoreducational le

Alvarado et al., 2002322 Community cohort 

(557) 

4 years Self-reported 

occupational history. Lifelong occupation coded according to the Spanish National Classification of Occupations 5 categories: 1) White collar and skilled workers 2) Semi-skilled 3) Unskilled 4) Housewives 5) Farm workers 

Change scores on a cognitive scale (0 to 32 points). Cognitive scale made up of simple tests of orientation, verbal memory, and naming. 

Age Sex Educational level Baseline cognitive status Occupation 

Risk of cognitworkers versu1.79 (95% CI Less than primversus complworker: OR 2

Categorized as: 1) “Mild decline” = -2 to -7 2) “Severe decline” = -8 to -23 3) “Normal” = -1 to 12 

Less than primversus complworker: OR 1

215
Study Sample (n) Followup Exposure Case definition Confounding 

adjustment 

Results 

Reclassified to: 1) Farm workers 2) Others 

Virtanen et al., 2009334 Community cohort 

(2214) 

5 years Self-reported 

responses to: “How many hours do you work per week in your main job including work brought home?” “How many hours do you work in an average week in your additional employment?” 

Decline from baseline to followup on tests of memory, reasoning, vocabulary, phonemic verbal fluency, and semantic verbal fluency 

Age Sex Educational level Marital status Followup employment status Occupational grade Income Physical health indicators Psychological stress Anxiety Sleep problems Health risk behaviors Social support Family stress Job strain 

Compared to 

hours/week, t41 to 55 hourreasoning tesSE = 0.37; p = > 55 hours/wereasoning tesSE = 0.49; p = Test for linear 

Yu et al., 2009335

Clinical cohort – HMO 

14 years Self-reported 

information on selfdirected work. Included three components and was operationalized in three ways as perceived autonomy, work control, and innovation as measured by a scale of the Work Environment Inventory 

Longitudinal performance on: Measures of verbal memory: (a) Word fluency (b) Immediate recall (c) Delayed recall Measures of inductive reasoning: (a) PMA reasoning measure 

Age Sex Educational level Income 

Jobs with high were associatmaintenance Every increascontrol was aincrease in ve

(626) 

Every increaswas associateincrease in in0.05 

216
217

Study Sample (n) Followup Exposure Case definition Confounding 

adjustment 

Results 

(b) ADEPT Letter Series test (c) Word series and (d) Educational Testing Service number series 

Abbreviations: ADEPT = Adult Development and Enrichment Project; CI = confidence interval; HMO = health maintenance organization; OR = oddMental Abilities; RR = relative risk; SD = standard deviation; SE = standard error; TICS-m = Telephone Interview for Cognitive Status (modified ver
Social engagement. We identified 15 cohort studies that examined the association between 

social engagement and the development of MCI or cognitive decline.188,190,258,271,321,329,336-344

These studies are summarized in Table 60; detailed evidence tables are presented in Appendix B. 

Social engagement as a risk factor was described by different exposures in the studies, including 

objective measures such as marital status, living situation, number of people in social network, as 

well as subjective measures such as feelings of loneliness and perceptions of social support. 

Engaging in social activities (which may or may not involve social engagement) is mostly 

covered in the sections on cognitive engagement and leisure activities, although some overlap is 

unavoidable given that the boundaries are sometimes nebulous. Although 15 social engagement 

studies were identified, the measurement of exposure and reporting of outcomes varied among 

the studies. Hence, they were not combined to provide a single summary statistic; rather, 

qualitative descriptions of the studies are provided in this discussion. 

Qualitatively, the measurement of exposures in the studies fall under three main categories: 

social network size, social support, and marital status. Ten of the 15 studies were conducted in 

various regions of the United States,188,190,258,271,321,329,336-339 four in Europe,340,341,343,344 and one 

in Hong Kong.342 Ten studies reported continuous outcomes of cognitive decline.188,271,329,336-

341,344 The other five reported decline as a categorical outcome, although the definition varied 

from study to study.190,258,321,342,343 All studies used community samples and attempted to 

decrease selection bias. Some studies did not exclude individuals who were cognitively impaired 

at baseline336,338,340 and therefore could have included some demented individuals, except Green 

et al.,338 where the mean age at baseline was 47.3. Though all other studies attempted to exclude 

those who were cognitively impaired at baseline, the criteria and methods of screening were 

heterogenous and included: 3MS > 80;258 MMSE > 24;341 MMSE > 28;337 and participants 

scoring in the top third of the screening test.339 The other studies had a broad inclusion criteria of 

simply non demented. Some studies had a significant amount of loss to followup (> 50 

percent).337,338,344 One study338 was a continuation of another.337 The average length of followup 

ranged from 2 to 21 years. Measurement of social engagement was done through self-report in 

all the studies. There was no objective validation of the measure for ascertaining exposure in any 

of the studies. Five studies compared baseline characteristics between the exposed and 

unexposed groups.190,258,321,340,341 Some studies compared the baseline characteristics of the 

participants who were followed up compared to those who were lost to followup and found 

statistically significant differences between the two groups; for example, participants who were 

followed up were younger and more educated than those who were not.337,338 One study used 

informant interviews;339 however, this was mainly to collect proxy information for missing data. 

The methods used to define cases and cognitive decline are described in Table 60. None of the 

studies reported a priori power calculations. The analyses were largely appropriate with adequate 

adjustment for confounders. 

Of the 15 studies, five examined the relationship between social network and cognitive 

decline. Two studies concluded that a larger social network decreased cognitive decline.336,337

However, continued followup of one of these cohorts337 found discrepant results in that there was 

no association between social network size or support and cognitive decline.338 However, of the 

2607 participants in the original study, only 874 were in the followup study, and they differed in 

demographic characteristics from the original cohort. This may explain the difference in findings 

between the two studies. In another study, there was no association between the size of the social 

network and cognitive decline; however, decreased social engagement as measured by group 

memberships was associated with an increased risk of cognitive decline (OR 2.92; 95 percent CI 

218
219

1.35 to 6.36).343 In a study examining characteristics of a social network, men of Japanese 

descent living in the United States and having current friends who were Japanese were at lower 

risk of cognitive decline (OR 0.64; 95% CI 0.44 to 0.93).321 

Four studies examined the relationship between social support and cognitive decline. One 

found that lack of social support increased the risk of cognitive decline (OR 1.2; 95 percent CI 

1.01 to 1.43),271 while another found an increased risk in men but not women in a preliminary 

model, which then became non-significant in an adjusted model.342 In the third study, lack of 

social support was measured as loneliness, which was found to be associated with more rapid 

decline in global cognition, semantic memory, perceptual speed, and visuospatial ability.188 In 

another study, participants who reported having enough social support had a lower risk of 

becoming a major cognitive decliner.258 Perception of social support in a high functioning group 

was examined only in one study and was not found to be significantly associated with cognitive 

decline in a fully adjusted model.339

Six studies examined the relationship between marital status and cognitive decline.190,329,340-

342,344 Loss of spouse was a significant risk factor for cognitive decline in three studies.190,329,340

Of these, only one defined MCI as a categorical diagnosis using published criteria; investigators 

found that being widowed (OR 3.30; 95 percent CI 1.6 to 6.9) and being without a partner (OR 

2.14; 1.2 to 3.8) at midlife were both associated with increased risk of MCI.190 However, two 

other studies did not report a significant association between cognitive decline and marital 

status341,344 or living situation.341 The final study342 reported that greater cognitive decline was 

associated with being divorced in males, but the association was not found in single or widowed 

males or in females. Given the latter findings, and the extremely broad confidence intervals for 

the association between divorced males and cognitive decline, the robustness of the finding that 

greater cognitive decline in males is associated with being divorced is questionable. The 

association between living with someone and cognitive decline was inconsistent across studies. 

One study showed no significant association,258 while two other studies found that those who 

lived alone at baseline and followup had an increased risk of cognitive decline.190,341

In conclusion, although comparison across studies is difficult given the different measures of 

exposure, it is evident that results are inconsistent among the studies on social network size and 

social support. In addition, those studies reporting a beneficial association between measures of 

social engagement and maintenance of cognition generally report relatively small effect sizes, 

suggesting that residual confounding may explain the association. Thus, there is currently not 

sufficient evidence supporting a protective effect of social engagement. However, there appears 

to be a more robust association between the loss of a spouse and cognitive decline as evidenced 

by the findings from three studies. The findings are inconsistent regarding living alone or being 

without a partner for any reason. We suggest that some of the heterogeneity in the findings may 

be attributed to the shorter followup time in some studies in which the majority of the data was 

collected in late life; as the two studies with over 15 years of follow up showed that those who 

were single at baseline and followup were at increased risk of cognitive decline. 
Table 60. Social engagement and risk of cognitive decline 

Study Sample (n) Followup Exposure Case definition Confounding adjustment Results Barnes et al., 2004336 Community cohort 

(6158) 

6 years (mean) 

Social network Social engagement (scale 0 to 8 points) 

Episodic memory: Immediate and delayed recall of 12 ideas contained in the East Boston Story Perceptual speed: SDMT Global cognition: MMSE 

Age Race Sex Marital status Educational level Income 

0.002 undecline network 0.009 undecline social e(p < 0.0

Holtzman et al., 2004337

Community cohort (881; 354 included in the longitudinal analysis) 

12.4 years (mean) 

Social network Emotional support 

MMSE Change in physical disability 

Change in dysphoria MMSE at baseline Lifetime presence of alcohol disorder Cerebrovascular disease status Age Sex Race Education level 

Linear eMMSE: SE = 0.0Effect si

Green et al., 2008338 Community cohort 

(2607) 

10.9 years (mean) 

Network size Frequency of interaction 

MMSE Age 

Race Sex Educational level Past year household income Depressive symptomatology Lifetime alcohol use disorder Ability to perform ADLs Cerebrovascular disease Baseline cognitive status 

Change significaNetwork 

0.093); Frequen

0.073 to Emotion

(-0.047 Compos

0.005 (-

Barnes et al., 2007271 Community cohort 10 years (median) Social support Modified MMSE Age Education Adjusted 

support: 

220
Study Sample (n) Followup Exposure Case definition Confounding adjustment Results 

(9704) Baseline cognitive function 

Study site 

1.43) 

Seeman et al., 2001339 Community cohort 

(1189) 

7.4 years (mean) 

Perception of social support network 

Language :18 item Boston Naming test Abstraction: 4 items from the Wechsler’s Adult intelligence scale Spatial ability: Copying image Incidental recall of confrontation naming Delayed recall of a story 

Race Sex Educational level Income Number of reported chronic illnesses Pulmonary function Amount of strenuous leisure activity Amount of strenuous yard/house maintenance Depressive symptoms Self-efficacy beliefs 

After cogreater was a pfunction beta = 1When thexcludinstatus asocioderelationsbeta = 1

Wilson et al., 2007188 Community cohort 

(1023; 857 after exclusions) 

Mean 3.3 years Range 2 to 5 years 76 AD cases 

Loneliness by self-report (questionnaire) 

MMSE 7 measures of episodic memory: Immediate and delayed recall of Logical Memory Story and of the East Boston Story, plus Word List Memory, Word List Recall, and Word List Recognition 

Rush Memory Aging Project 

3 tests of semantic Memory: Verbal Fluency Test and short forms of the Boston Naming Test and the National Adult reading Test 3 working memory tests including Digit Span 

Age Sex Level of educational achievement 

Global ctime: Be(0.01); p Episodic time: Be(0.01); p Semanttime: Be

(0.01); p Working time: Be(0.01); p Percepttime: Be(0.01); p Visuosptime: Be(0.01); p 

221
Study Sample (n) Followup Exposure Case definition Confounding adjustment Results 

Forward and Backward plus Digit Ordering 4 measures of perceptual speed including Number Comparison, Symbol Digit Modalities Test (oral version), and 2 indexes from a modified Stroop Neuropsychological Screening Test 2 visuospatial tests including a 15-item version of Judgment of Line Orientation and a 17-item version of Standard Progressive Matrices 

Aartsen et al., 2005340 Community cohort 

(1144) 

6 years Loss of spouse Recall of 15 words from 

the Auditory Verbal Learning Test 

Age Sex Educational level Physical health at baseline Mental health at baseline 

Statisticbetween widowed 

but not f

0.13. 

Van Gelder et al., 2006341

Community cohort (2285; 1734 alive at first followup) 

15 years Marital status 

Living situation 

MMSE Age 

Education Country Smoking Alcohol consumption Prevalence of MI, stroke, diabetes, and cancer Living situation Baseline cognitive functioning For analysis of living situation, 

No signcognitive followup defined 1) Marriof 1.1 po2) Marriin 1990 1.0 poin3) Unmahad an apoints (0

222
Study Sample (n) Followup Exposure Case definition Confounding adjustment Results 

marital status was included as a covariate No sign

decline for the tliving sit1) Lived 1990 ha1.1 poin2) Lived alone in decline 3) Alone addition2.7 poin

Ho et al., 2001342 Community cohort 

(1200) 

3 years Social support 

score 

Information and orientation part of Clifton Assessment procedure for the elderly 

Age Education 

Initial mdivorced OR for m134.8) OR for wSocial sOR for m6.7) OR for w

MunizTerrera et al., 2009344

Community cohort (2053) 

9 years Marital status MMSE Age 

Sex Educational level Profession Marital status Baseline MMSE 

Rate of married (SE = 0

Karlamangla et al., 2009329

Community cohort (6476) 

9 years Marital status TICS for participants 

aged ≤ 79 years, and inperson interviews for 

participants older than 79 years 

Cognition at baseline Length of participation Age Gender Ethnicity 

AssociacognitioMarried Widow/w-0.08) Separat

223
Study Sample (n) Followup Exposure Case definition Confounding adjustment Results 

Education Wealth and income at baseline 

to 2.00) Never m0.81) Associa(per decMarried Widow/w0.13) Separatto 1.56) Never m0.27) 

Hakansson et al., 2009190

Community cohort 

Average 21 years. 

Marital status (married/ cohabiting, single, or divorced) 

MMSE and NINCDSARDA Age Sex 

Educational level Baseline cognitive status BMI APOE Systolic BP 

(1449) 

Region of residence Smoking Occupation Physical activity at work Depression at mid-life 

Risk of MStatus aWithout WidoweSingle/d

Graves et al., 1999321 Community cohort 

(1836; 1604 analyzed) 

2 years (exposure lifelong) 

Past and current friends 

Cognitive decline defined as mean change of -1 SD, i.e., > 5.15 points loss in 2 years 

Age Sex Educational level Baseline cognitive status Followup time 

Having cassociatdecline. Current OR 0.640.01 Past frieOR 0.91

224
225

Study Sample (n) Followup Exposure Case definition Confounding adjustment Results Zunzunegui et al., 2003343

Community cohort (964; 557 analyzed) 

4 years Social network 

Social integration Social engagement 

Cognitive decline on composite measure of cognitive tests. Severe decline defined as greater than 1 SD below the mean change. Mild decline defined as a change within 1 SD of the mean change. 

Age Educational level Sex Baseline cognitive status Depression BP Functional limitations 

OR for s(95% CINo grou2.92 (1.3Social ein men: Less sofriends i1.00) 

Yaffe et al., 2009258 Community cohort 

(2509) 

8 years Social support 

Living with someone 

3 MS Participants with predicted slopes of the 3MS scores of ≤ 0 were 

considered maintainers; > 0 but no more than 1 SD below the mean were considered minor decliners; ≥ 1 SD below the mean were considered major decliners. 

Age Race Educational level APOE genotype 

Those wsupport decline Maintain0.94 (0.7Major vs(0.51 to Living wsignificacognitive Maintain1.24 (0.9Major vs(0.75 to 

Abbreviations: 3MS = Modified Mini-Mental State Examination; AD = Alzheimer’s disease; ADLs = activities of daily living; APOE = apolipoprote

interval; MI = myocardial infarction; MMSE = Mini-Mental State Examination; NINCDS-ADRDA = National Institute of Neurological and Commun

Alzheimer’s Disease and Related Disorders Association; OR = odds ratio; SDMT = Symbol Digit Modalities Test; SD = standard deviation; SE = stan

Telephone Interview for Cognitive Status 
Cognitive engagement. We identified four eligible cohort studies that examined the 

association between cognitive engagement and development of MCI or cognitive decline.335,345-

347 These studies are summarized in Table 61; detailed evidence tables are in Appendix B. One 

of the studies reported a categorical outcome,345 and the other three reported continuous 

outcomes of cognitive decline.335,346,347 Given the small number of eligible studies, the studies 

reporting continuous outcomes are included in this discussion. Two of the studies used 

community samples in the United States,345,346 one used a sample from a health maintenance 

organization (HMO) in the United States,335 and the fourth used a clinical sample in Europe.347

The length of followup averaged 3 to 14 years. Two of the studies used sample selection 

methods to minimize selection bias,346,347 while the remaining studies partially used such 

methods.335,345 In two of the studies, the participants were non-demented at baseline;345,347 the 

other two studies appeared to include all participants at baseline regardless of cognitive status, 

but given the length of the followup periods, it is assumed here that few participants were 

demented at baseline.335,346 All of the studies used self-report of the frequency of current 

involvement in specific activities. There was no objective validation of the method for measuring 

exposure, but one study194 did ask an informant to confirm the participant’s report of 

involvement in activities. The studies did not compare baseline characteristics between those 

exposed and unexposed, but one study compared baseline differences between individuals who 

developed amnestic MCI and those who did not.345 The case definitions and cognitive outcomes 

used are described in Table 61. The analyses appear generally appropriate and controlled for 

relevant potential confounders, but none of the studies conducted a priori sample size 

calculations. 

One study345 reported an attenuation of risk of amnestic MCI with increasing frequency of 

cognitive activities; another study346 reported a reduction in a global measure of cognitive 

decline with increasing levels of cognitive activity; and the third study347 reported that 

cognitively engaging activity was associated with less cognitive decline on selected cognitive 

measures. In contrast to these findings, Yu and colleagues reported no association between 

cognitive decline and involvement in cognitive leisure activities.335 Their study report did not 

detail the activities included in the cognitive activity group, nor did it provide any specific results 

on the cognitive activity analyses. This limits our ability to identify differences among the 

studies that may contribute to the discrepant results. 

In conclusion, there is limited but inconsistent evidence suggesting that increased 

involvement in cognitive activities in later life is associated with less cognitive decline and lower 

risk of incident amnestic MCI. In addition to the limited information reported in one study and 

noted above, there are some other challenges to interpreting these results. First, the effect sizes 

are relatively small and limited to selective measures in some studies. It is possible that residual 

confounding may contribute to some of the findings. Second, given the long subclinical 

prodromal phase of AD, it is not possible to determine whether less involvement in cognitive 

activities in some individuals is an early symptom of AD. Third, validation of the type and extent 

of exposure is needed.

226
Table 61. Cognitive activities and risk of cognitive decline 

Study Sample (n) Followup Exposure Case definition Confounding 

adjustment 

Results 

Community cohort (437) 

5.6 years 

(4.1) (mean [SD]) 

Self-report of frequency of current involvement in the following activities: reading books or newspapers, writing for pleasure, doing crossword puzzles, playing board games or cards, participating in organized group discussions, and playing musical instruments 

Criteria for amnestic MCI: 1) Does not meet criteria for dementia; 2) Objective memory impairment based on cognitive testing; 3) Subjective report of memory symptoms; 4) Normal general cognitive functioning; 5) Generally preserved activities of daily living.

Age Sex Educational level Chronic illnesses Participation in other leisure activities 

Risk of de1-point inscale) in tscore: H0.99) None of tactivities in other aindependlower risk adjusted 

Verghese et al., 2006345

Wilson et al., 2003346 Community cohort 

(4392) 

5.3 years Self-report of current 

involvement in the following activities: viewing television; listening to radio; reading newspapers; reading magazines; reading books; playing games like cards, checkers, crosswords, or other puzzles; and going to a museum 

Global composite index of scores on the MMSE, the immediate and delayed recall of the East Boston Story, and the oral version of the Symbol Digit Modalities Test 

Age Race Sex Educational level 

Frequencassociate0.012 (SE decline (p equivalendecline focognitive 

Bosma et al., 2002347

Clinical cohort – family practice clinics (830) 

3 years Self report of activities 

described as “mentally active sports (e.g., chess, puzzles)”

Longitudinal performance on the following cognitive measures: Stroop Color-Word Test , word list memory test, a letter-digit substitution test, semantic verbal fluency test, and the MMSE

Age Sex Educational level Baseline cognitive status Length of followup interval 

At least 1 active spoless cogn(β coefficdigit subs

0.01). No performaother test

227
228

Sample (n) Followup Exposure Case definition Confounding 

adjustment 

Study Results 

Yu et al., 2009335

Clinical cohort – HMO (626) 

14 years Self-report on the 

socializing, educational, and cultural items on the Life Complexity Inventory Proportion of time spent weekly in cognitive activities divided by time spent in all leisure activities 

Longitudinal performance on: Measures of verbal memory: (a) Word fluency (b) Immediate recall (c) Delayed recall Measures of inductive reasoning: (a) PMA reasoning measure (b) ADEPT Letter Series test (c) Word series and (d) Educational Testing Service number series 

Age Sex Educational level Income 

Involvemactivities longitudinthe memotasks. Spprovided 

Abbreviations: ADEPT = Adult Development and Enrichment Project; aMCI = amnestic mild cognitive impairment; CI = confidence interval; HMO organization; HR = hazard ratio; MCI = mild cognitive impairment; MMSE = Mini-Mental State Examination; PMA = Primary Mental Abilities; SD = standard error 
Physical activities. We identified eight eligible cohort studies that examined the association 

between physical activity and development of MCI or cognitive decline.199,258,261,342,345,348-350

These studies are summarized in Table 62; detailed evidence tables are in Appendix B. Seven 

studies had a categorical outcome; the eighth had a continuous outcome, but we have included it 

here because it focused on a select subgroup of individuals (women with diabetes) relevant to 

one of the key questions of this systematic review.261 These eight studies are the focus of 

attention in what follows. There were an additional three studies with continuous outcomes of 

cognitive decline335,347,351 which are not reviewed in detail, but for which we report general 

conclusions. Five of the studies used community samples in the United States,258,261,345,348,350 and 

one study each used community samples in Canada,199 Europe,349 and Hong Kong.342 The length 

of followup ranged from 2 to 8 years. The cognitive status of participants at baseline differed 

among the studies. Two studies348,349 may have included some individuals with dementia at 

baseline, as they did not appear to apply exclusionary criteria regarding impaired cognitive 

function. Other studies258,350 attempted to exclude those with dementia by only including 

individuals who scored above 80 points on the 3MS or at least 23 out of 26 points on an 

abbreviated MMSE test. One study342 excluded participants categorized at baseline as having 

cognitive impairment based on performance on 12 items of an orientation and information test. 

For the remaining three studies,199,261,345 participants were non-demented at baseline, with a 

subset of the individuals specifically having MCI in one study,345 and a subset of individuals 

being cognitively normal in some studies.199,345 Seven studies used sample selection methods to 

minimize selection bias,199,258,261,342,348-350 and the other partially used such methods.345 All 

studies used self-reported information on involvement in physical activities at baseline; some 

asked about specific activities, but the majority asked more general questions about any physical 

activities. Since a number of the studies used open-ended questions to obtain information about 

engagement in physical activities, it was difficult to assess the degree of overlap among the 

activities across studies. Only one study provided some information on the reliability and validity 

of the physical activity questions.349 Five studies compared baseline characteristics between 

those exposed and unexposed.258,261,348-350 The case definitions for the studies are described in 

Table 62. The analyses appear generally appropriate and most controlled for relevant potential 

confounders. However, one study342 defined a case by a threshold score on the cognitive 

measure, but in the analysis did not control for performance on the cognitive measure at baseline. 

This may have markedly influenced their results since a large proportion of the females, 

compared to the males, scored just above this threshold at baseline. None of the studies reported 

a priori sample size calculations. 

For all studies, the risk estimates were typically in the hypothesized direction, and there was 

often a dose-response pattern for the association between more physical activity and the various 

case definitions of cognitive decline. However, when statistical significance was considered, the 

results were inconsistent. Five studies reported that more physical activity was associated with a 

lower risk of CIND, cognitive impairment, or cognitive decline,199,258,342,348,350 but in two of these 

studies the benefit was attributed entirely to a significant effect among females,199,342 and in one 

the entire sample was female.350 Devore and colleagues261found that among women with 

diabetes those in the highest tertile level of physical activity showed less cognitive decline 

compared to those in the lowest tertile level of physical activity. The difference in longitudinal 

change between the two groups was small, and when the model included adjustment for physical 

disability the results were no longer statistically significant. The last two studies345,349 found no 

significant association between levels of physical activity and risk of either amnestic MCI or 

229
230

cognitive decline. These two studies had the smallest sample sizes, which suggests that lack of 

statistical power may have been an issue. One of these studies349 found that among carriers of the 

APOE e4 allele, physical activity showed significant protective benefit against cognitive decline. 

The three studies that had continuous outcome variables also reported inconsistent results. 

Weuve and colleagues351 showed that increased levels of physical activity were associated with 

better long-term performance on multiple cognitive tests, but Bosma and colleagues347 showed 

that physical activity was associated with less decline on only one of a number of cognitive tests. 

In contrast, Yu and colleagues335 showed no association between physical activity and cognitive 

decline. 

The inconsistent findings may be due to a number of factors, including small number of cases 

and heterogeneity in both the types and quality of the exposure and outcome measures. 

In conclusion, the data currently available provide preliminary evidence for a beneficial 

effect of physical activity deterring cognitive decline, but overall the results are not robust. 

Further work using standardized methods to assess exposure is needed to confirm these findings 

and draw firmer conclusions. 
Table 62. Physical activity and risk of cognitive decline 

Study Sample (n) Followup Exposure Case definition Confounding 

adjustment 

Results 

Ho et al., 2001342 Community cohort 

(988) 

3 years 139 incident cognitive impairment 

Self-report of whether individual exercised (no other details) 

Incident cognitive impairment defined as a score over < 8 points on the Clifton Assessment Procedure for the Elderly 

Age Sex* Educational level *Final model adjusted only for sex

Adjusted OR cognitive impaversus “yes”: Entire group: Females: 2.2 Results not sispecific result

Laurin et al., 2001199 Community cohort 

(4615) 

5 years 436 incident CIND; 882 incident cognitive loss 

Self-report responses to two questions about frequency and intensity of exercise for individuals who reported physical activity Composite physical activity score categorized: 1) “Low” = less than weekly 2) “Moderate” = weekly 3) “High“= ≥ 3 

times/week 

Incident CIND as defined by the Canadian Study of Health and Aging or cognitive loss defined as > 4 point decline on the 3MS at followup 

Sex Educational level Family history of dementia Tobacco use Alcohol use NSAID use Daily living activities Clinical variables 

Adjusted OR compared to For men: Low activity: 0Moderate actHigh activity: p = 0.24 For women: Low activity: Moderate actHigh activity: p =0.003 Adjusted OR education, witloss compareFor men: Low activity: Moderate: 0.High: 0.98 (0For women: 

231
Study Sample (n) Followup Exposure Case definition Confounding 

adjustment 

Results Low: 1.06 (0.Moderate: 0.High: 0.58 (0

Lytle et al., 2004348MoVIES study

Community cohort (929) 

2 years 110 incident cognitive decline 

Self-report responses to question about whether individual engaged in an exercise program, and, if so, what type of exercise, exercise equipment used, and frequency and duration of exercise Categorized exercise as aerobic versus nonaerobic, then categorized by frequency, as follows: High activity = aerobic activity ≥ 30 minutes at 

least 3 days/week. For some analyses high activity defined as ≥ 30 

minutes at least 5 days/week Low activity = all other exercise 

Cognitive decline defined as ≥ 3-point 

decline on the MMSE 

Age Sex Educational level Baseline cognitive score Self-rating of health 

Adjusted OR decline compHigh activity (to 0.78) Low activity: When high acdays/week, it the low activitusing this thre

Schuit et al., 2001349 Community cohort 

(primarily community but only 88% lived independently at home) (347) 

3 years Self-report responses 

to questions about the frequency and duration of walking and bicycling in the previous week, the average amount of time spent weekly on hobbies and gardening in both summer and winter; and the average amount of 

Cognitive decline defined as a decrease of > points on the MMSE 

Age Sex Educational level Smoking Alcohol Baseline cognitive function Clinical variables Disabilities in ADL Health status 

Adjusted OR decline, with > reference: < 30 min/day: 31 to 60 min/dThere was an activity and A

232
Study Sample (n) Followup Exposure Case definition Confounding 

adjustment 

Results 

time spent monthly on odd jobs and sportSummed score for total weekly activity categorized: 1) ≤ 30 min/day 

2) 31 to 60 min/day 3) > 60 min/day 

The OR of coinactive carrie95% CI 1.1 to the OR of act

Verghese et al., 2006345

Community cohort 

Mean 5.6 years (SD 4.1) 

Self-report of frequency of involvement in the following 11 physical activities: Playing tennis or golf, swimming, bicycling, dancing, participating in group exercises, playing team games such as bowling, walking for exercise, climbing more than two flights of stairs, and babysitting 

(488) 

58 amnestic MCI 

Frequency of participation reported as “daily,” “several days per week,” “once weekly,” “monthly,” “occasionally,” or “never.” Responses used to create index: 7 points for daily participation; 4 points for participating several days per week; 1 point for participating once weekly; and 0 points for participating monthly, occasionally, or never. Summed the 

Criteria for amnestic mild cognitive impairment (aMCI): 1) No dementia 2) Memory impairment 3) Memory symptoms 4) Normal cognitive function (verbal IQ >84 and score of less than 8 on the Blessed test) 5) Generally preserved activities of daily living 

Age Sex Educational level Chronic illnesses Participation in other leisure activities 

A 1-point incrscore was noincreased risk 0.970) Compared to adjusted HR f8 to 14 pointsFor > 14 poin

233
Study Sample (n) Followup Exposure Case definition Confounding 

adjustment 

Results 

activity-days for each activity to generate a physical-activity score, ranging from 0 to 70.Responses dichotomized as “rare participation” (once a week or less) versus “frequent participation” (several days a week or more). 

Community cohort (5925) 

Mean 7.5 years 

Self-reported physical activity determined by the number of city blocks individual walked daily for exercise or as part of normal routine, the number of flights of stairs climbed daily, and responses on the modified Paffenbarger Scale. Activities classified as low (walking or gardening), medium (dancing or tennis), or high (jogging or skiing) intensity. Total kilocalories expended calculated 

Cognitive decline defined as a change of ≥ 3 points on an 

abbreviated MMSE over period of followup 

Age Educational level Health status Functional limitation Depression score Stroke Diabetes Hypertension Myocardial infarction Smoking Estrogen use 

Yaffe et al., 2001350 Risk of cognit

lowest quartile week as referSecond quartThird quartileHighest quartRisk of cognitlowest quartile week as referSecond quartThird quartileHighest quart

234
Study Sample (n) Followup Exposure Case definition Confounding 

adjustment 

Results 

Yaffe et al., 2009258 Community cohort 

(2509) 

8 years Self-reported 

information on weekly moderate/vigorous exercise, defined as engagement in moderate to vigorous exercise and activity (e.g., aerobics, weight training, or brisk walking) at least once a week 

Longitudinal performance on the 3MS Maintainers: Predicted slopes of 0 or greater (indicating no change or improvement in cognitive scores over time) Minor decliners: Predicted slopes less than 0 decline in cognitive score over time) but no more than one SD below the mean of the slopes Major decliners: Predicted slopes more than 1 SD below the mean 

Age Race Educational level APOE genotype 

When controlfactors assocmaintainer or cognitive maidecliner for: Weekly modeOR 1.31(95% Risk of being minor declineto 1.28) 

Devore et al., 2009261 Community cohort 4 years Self-reports of average amount of time per 

week spent in the following activities during the past year: Running (< 10 minutes/mile); jogging (> 10 minutes/mile); walking or hiking outdoors; racquet sports; lap swimming; bicycling; aerobic dancing or use of exercise machines; other vigorous activities (e.g., lawn mowing); and lowintensity exercise (e.g., 

Longitudinal performance on six cognitive tests used to create general cognition index and memory index. Tests were: TICS, East Boston Memory Test, Category Fluency, word list memory, and Digit Span backward. 

Age Education, Baseline cognitive status Disability indicators (osteoarthritis, chronic bronchitis, fatigue, balance problems, moderateto-severe body pain, and limitations in walking) 

Among womelevels of long-were associatcognitive meain models adjeducation. Mescore betweeactivity was 00.02 to 0.16; 

(1550) All had diabetes 

Adjustment fothe magnitude measures and significant. Mean differencomparing the lowest was 0.0.03 to 0.12; 

235
236

Study Sample (n) Followup Exposure Case definition Confounding 

adjustment 

Results 

yoga, stretching, toning) Increased lev

associated wicomparing exscore, mean d0.09 to 0.06; 

Abbreviations: 3MS = Modified Mini-Mental State Examination; ADL = activities of daily living; aMCI = amnestic mild cognitive impairment; APO

CI = confidence interval; CIND = cognitive impairment not demented; HR = hazard ratio; IQ = intelligence quotient; MCI = mild cognitive impairmenState Examination; NSAID = non-steroidal anti-inflammatory drug; OR = odds ratio; SD = standard deviation; TICS = Telephone Interview for Cogni
Other leisure activities. We identified two eligible cohort studies that examined the 

association between non-physical leisure activities and cognitive decline.336,347 Both studies 

defined the activities as “social” activities. We also identified one cohort study that examined the 

association between a range of leisure activities – including those considered to be social, 

productive, and physical – and cognitive decline.352 Two of the studies included “leisure 

employment, or part- or full-time work” in the list of leisure activities. Although work is not 

typically considered a leisure activity, these studies best fit in the present section. The leisure 

activities assessed for each study are listed in Table 63. Some of the leisure activities in these 

studies overlapped with some of the activities considered to be “cognitively engaging” in other 

studies, so the results described here should be interpreted in conjunction with the findings for 

Question 2 for the “Cognitive Engagement” factor. One of the studies reported a categorical 

outcome,352 and the other two reported continuous outcomes of cognitive decline.336,347 Given 

that there were only three eligible studies for this factor for Question 2, we include all studies in 

the current discussion. The three studies are summarized in Table 63; detailed evidence tables 

are provided in Appendix B. One study used a community sample in the United States,336 one 

used a community sample in Singapore,352and the third study used a clinical sample in Europe.347

The length of followup ranged from 1.5 to 6 years. Two studies used sample selection methods 

that minimized selection bias,336,352 and the third study partially used such methods.347 Both used 

self-report of current involvement and/or frequency of involvement in specific activities, a 

method of measuring exposure that has not been validated. Only one of the studies reported 

comparisons of baseline characteristics between those exposed and unexposed.352 The cognitive 

outcomes for the study are described in Table 63. The analyses appear generally appropriate and 

controlled for relevant potential confounders, but the studies did not report a priori sample size 

calculations. 

One study347 reported that involvement in social activities was associated with less decline on 

the immediate and delayed recall trials of a verbal memory task (0.01< p < 0.05). It is 

noteworthy that no adjustment was made for multiple statistical comparisons, and the three other 

cognitive measures did not show significant differences in rate of cognitive decline based on 

participation in social activities. Another study336 found that higher levels of involvement in 

social activities were associated with slightly less decline on a global cognitive measure. The 

third study examined a wide range of leisure activities and found that individuals in the medium 

and high tertile levels of leisure activity were less likely to exhibit decline on the MMSE.352 In 

addition, individuals who participated in at least one activity considered to be a “productive 

leisure activity” were less likely to decline on the MMSE, while those who participated in at 

least one social or physical leisure activity did not show such a benefit. Among APOE e4 

carriers, those who participated in at least one physical leisure activity or one social leisure 

activity were significantly less likely to decline on the MMSE; this same association was not 

observed among APOE e4 non-carriers. 

In conclusion, these studies provide preliminary evidence that a range of leisure activities 

may be associated with preservation of cognitive function. The findings are not entirely 

consistent, as two of the three studies reported an association between greater involvement in 

social activities and less cognitive decline, while one did not find such an association. In 

addition, the differences in how exposure was defined, the limited number of statistically 

significant associations among the multiple comparisons, and the relatively small effect sizes 

limit the conclusions that can be drawn. Further research is needed in this area. 

237
Table 63. Leisure activities and risk of cognitive decline 

Study Sample (n) Followup Exposure Case definition Confounding 

adjustment 

Results 

Bosma et al., 2002347

Clinical cohort – family practice clinics (830) 

3 years Self-report of activities 

described as “social activities” such as organizational memberships (e.g., clubs)

Longitudinal performance on the following cognitive measures: Stroop Color-Word Test , word list memory test, a letter-digit substitution test, semantic verbal fluency test, and the MMSE

Age At least 

leisure awith lesimmedialist mem

0.94; p recall of (β = 0.3

Sex Educational level Baseline cognitive status Length of followup interval

Barnes et al., 2004336 Community cohort 

(6158) 

6 years (mean) 

Social activities scale (0 to 8 points) constructed from responses to following items: 1) Attending religious services 2) Going to a museum 3) Participation in activities or groups outside the home 4) A part-time or full-time job 

Global composite index of scores on the MMSE, the immediate and delayed recall of the East Boston Story, and the oral version of the Symbol Digit Modalities Test 

Age Race Sex Martial status Educational level Income 

0.009 udecline index scsocial e0.001). 

Niti et al. 2008352 Community cohort 

(2611) 

1.5 years (median) 

Self-report of “social activities,” including religious services, movies, going to restaurants or sports events, day or excursion trips, playing cards or other games, senior citizen club activities, and group recreational activities such as karaoke and dancing Self-report of “productive activities,” including 

Cognitive decline on the MMSE defined as a decrease of 1 or more points at followup assessments 

Age Sex Educational level Baseline cognitive status APOE Functional status Number of co morbidities Vascular risk factor/events Depression 

Compaleisure acognitivwith higwas 0.6among leisure a(0.45 to Compaengage those wproductof cogn

238
239

Study Sample (n) Followup Exposure Case definition Confounding 

adjustment 

Results 

reading, music, media programs, computing, painting, gardening, preparing meals, shopping, unpaid and paid community work, and other leisure paid employment or business. Self-report of “physical activities,” including walking, active sports or swimming, and tai chi 

Smoking Alcohol 

(95% CIn the toat least activity cognitivHowevethose wone phy95% CI one soc0.16 to decline 

Abbreviations: APOE = apolipoprotein E gene; CI = confidence interval; MMSE = Mini-Mental State Examination; OR = odds ratio
Tobacco use. We identified one good quality systematic review, published in 2007, that 

examined the association between tobacco use and cognitive decline, cognitive impairment or 

cognitive performance change.50 The review included three prospective cohort studies for 

cognitive performance change published between 1996 and 2004.353-355 The three studies 

included a total of 7872 subjects; one was conducted in the United States, and the other two in 

European countries. The review also included three prospective cohort studies reporting a 

dichotomous measure of cognitive decline (776 subjects; two from the United States and 1 from 

Europe),356-358 and three prospective cohort studies reporting cognitive impairment (8385 

subjects; one each from the United States, Canada, and Australia).74,359,360 Studies were selected 

that had at least two occasions of measurement, used cognitive measures compatible with those 

used by other studies, included at least a 12-month followup period, and measured exposure to 

smoking at baseline. The MMSE was the only cognitive measure common to enough studies to 

analyze cognitive performance change. Cognitive performance change was defined as a 

continuous measure of yearly change on the MMSE. The definitions for cognitive decline and 

cognitive impairment differed across studies, but in general terms cognitive decline was defined 

as a dichotomous variable based on cognitive measures that included more than just the MMSE. 

Cognitive impairment was a decline on cognitive measures sufficient to represent a pre-set 

definition of impairment. Study quality was not reported in this systematic review. Length of 

followup ranged from 2 to 7 years. The covariate adjustment for most studies included at least 

age and education; many studies included additional covariates such as sex, APOE, biological 

measures, and health conditions. The results with the most covariates were given preference 

when reporting the data from the individual studies. Exposure was determined by self-report, and 

smoking was classified as ever, current, former, or never smokers. 

Studies were combined using fixed-effect meta-analyses if there was no evidence of 

heterogeneity. If heterogeneity was present, random-effects models were used. Standard χ

2

 tests 

using a p-value of 10 percent were used to examine heterogeneity. The small number of studies 

within each group of studies with compatible measures precluded investigation of heterogeneity, 

using meta-regression, subgroup analyses, or assessment of publication bias. The results for the 

various exposure definitions and the outcomes measures are reported in Table 64. To briefly 

summarize the main findings, current smokers were more likely to show a greater decline on the 

MMSE than either former or never smokers. Current smokers were also more likely to be 

categorized as “cognitive decliners” compared to individuals who were former smokers and 

those who never smoked. Finally, former smokers showed greater yearly decline on the MMSE 

compared to those who never smoked. 

240
Table 64. Smoking and risk of cognitive decline – results from studies reviewed by Anstey et al., 200750

 

Comparison/Outcome assessed Relative risk (95% CI) Cognitive change* 

Current smokers versus never smokers 

Yearly performance change on MMSE (n = 3 studies) - -0.13 (-0.18 to -0.08) 

Ever smokers versus never smokers 

Cognitive impairment (decline on cognitive measure 

into preset impaired level) (n = 3 studies) 

0.85 

(0.35 to 2.09) - 

Former smokers versus never smokers 

Yearly performance change on MMSE (n = 3 studies) - -0.07 (-0.11 to -0.03) 

Current smokers versus former smokers 

Yearly performance change on MMSE (n = 3 studies) - -0.07 (-0.13 to -0.02) 

Current smokers versus former and never smokers 

Cognitive decline (dichotomous outcome, decliners 

versus non-decliners) (n = 3 studies) 

1.41 

( 1.16 to 1.71) - 

*Linear regression coefficient (β) and 95% CI. 

Abbreviations: CI = confidence interval; MMSE = Mini-Mental State Exam. 

The authors noted that one limitation of the review was that the former smokers group 

includes a broad range of exposure periods. Unfortunately, there were not a sufficient number of 

studies with data on the number of smoking pack-years to use this as the exposure variable. 

Publication bias was not assessed formally. Quality ratings of the studies were not provided, but 

strict selection criteria may have increased the likelihood that only high quality studies were 

included in the review. The authors concluded that current smokers are at increased risk of 

cognitive decline compared to those who never smoked. 

We identified five additional eligible cohort studies examining the association between 

smoking and cognitive decline.257,258,266,271,361 These studies are summarized in the Table 65; 

detailed evidence tables are in Appendix B. Four of the five studies used a categorical 

outcome;257,258,266,271 the fifth361 assessed cognitive decline as a continuous variable. This latter 

study is included in the current discussion because it is the only one of the five studies that 

assessed the association of smoking and cognitive decline based on APOE e4 allele status. All 

five studies used samples drawn from the community; one also studied nursing home 

residents.266 Three studies used U.S. samples,258,271,361, one used an Australian sample,257 and the 

other used a European sample.266 In three of the studies, participants were cognitively normal at 

baseline.257,266,361 In the other two studies, it is likely the vast majority of the participants were 

non-demented since one study258 included only individuals with 3MS scores > 80 in an attempt 

to exclude individuals with cognitive impairment, and the other study had a 6-year period 

between the two cognitive assessments.271 Length of followup ranged from 3.5 to 10 years (mean 

or median). All three studies used self-report history of smoking obtained at baseline to 

characterize exposure. The studies used sample selection methods to minimize selection bias; 

however, only three of the studies compared baseline characteristics to assess differences 

between exposed and unexposed.258,271,361 The case definitions and cognitive outcomes used in 

the studies are described in Table 65. The analyses appear generally appropriate and controlled 

for relevant potential confounders, but none of the studies conducted a priori sample size 

calculations. 

241
242

The results were inconsistent across studies, with two studies258,271 reporting that those who 

did not smoke had greater likelihood of maintaining optimal cognitive function versus exhibiting 

minor cognitive decline. In one study, past smoking was associated with increased risk of MCI 

compared to never smoking,257 but another study did not find a significant association between 

number of pack years of smoking and risk of incident MCI.266 The fifth study361 did not find a 

significant association between current smoking and cognitive decline on abstract reasoningvisuospatial tasks in either the group that was ≤ 75 years old or > 75 years old. However on 

memory tasks, current smokers over age 75 showed greater cognitive decline than individuals 

who did not currently smoke; there was no comparable difference among the group that was ≤ 75 

years old. Three of the studies examined current smoking,258,271,361 but only one of them271 used 

the MMSE as the main cognitive measure, making it relatively comparable to the measures of 

exposure and outcome in the systematic review by Anstey et al.50 In general terms, the findings 

from this study were consistent with those from the review, that is, current smoking was related 

to cognitive decline. 

One study examined the association between current smoking and cognitive decline by 

APOE e4 allele status.361 This study found that its reported association between current smoking 

and decline on memory tasks was limited to the group over age 75 years with no APOE e4 allele. 

This finding is generally consistent with those reported for current smoking and AD, that is, the 

statistically significant association found in the entire group was due to the association in the 

subgroup with no APOE e4 allele and not to the subgroup with at least one APOE e4 alleles. 

In conclusion, these studies provide fairly consistent evidence for an association between 

current smoking and increased risk of cognitive decline. The evidence on past smoking is less 

consistent. 
Table 65. Tobacco use and risk of cognitive decline – recent cohort studies 

Study Sample (n) Followup Exposure Case definition Confounding 

adjustment 

Results 

Barnes et al., 2007271 Community cohort 

(9704) 

6 to 15 years (median, 10) 

Self-report smoking history 

Cognitive decline on a 26-point version of MMSE 

Age Risk of maintaining optimal 

minor cognitive decline relaOR 1.73 (95% CI 1.30 to 2.

Educational level Baseline 

Grouped as cognitive status “maintain cognition,” “minor decline,” or “major decline” 

Study site 

Reitz et al., 2005361 Community cohort 

(791) 

5-year interval 

Self-report smoking history 

Decline on cognitive tests 

Age Estimated beta coefficient (

Educational level Abstract/visuospatial 

≤ 75 years: No significant icurrent smoking (beta = 0.1> 75 years: No significant icurrent smoking (beta = -0.Memory 

Race Sex HTN Heart disease DM APOE 

≤ 75 years: No significant dcurrent smoking (beta = -1.> 75 years: Significant intecurrent smoking (beta = -4.APOE -/-

Memory ≤ 75 years: Time x current [1.9]; p = 0.5) > 75 years: Time x current [2.3]; p = 0.016) Abstract/visuospatial ≤ 75 years: Time x current p = 0.5) > 75 years: Time x current p = 0.7) 

243
Study Sample (n) Followup Exposure Case definition Confounding 

adjustment 

Results 

Among individuals with one 

Memory ≤ 75 years: Time x current p = 0.9) > 75 years: Time x current [2.8]; p = 0.7) Abstract/visuospatial ≤ 75 years: Time x current [1.0]; p = 0.5) > 75 years: Time x current [1.2]; p = 0.7) 

Solfrizzi et al., 2004266 Community cohort, 

including institutionalized subjects (1566) 

3.5 years Self-report 

smoking history 

Variation of Petersen MCI criteria 

Age Educational level Total cholesterol HTN Coronary artery disease 

RR Pack years: 0.94 (95% CI 

Yaffe et al., 2009258 Community cohort 

(2509) 

8 years Self-reported 

information on current smoking 

Longitudinal performance on the 3MS. Maintainers: Predicted slopes of 0 or greater (indicating no change or improvement in cognitive scores over time) Minor decliners: Predicted slopes less than 0 decline in cognitive score over time) but no more than one SD below the 

Age Race Educational level APOE genotype 

When controlling for about associated with being a mabeing a cognitive maintaineindividuals who did not currsmokers: OR 1.84 (95% CRisk of being a major declinOR 1.15 (95% CI 0.72 to 1.

244
245

Study Sample (n) Followup Exposure Case definition Confounding 

adjustment 

Results 

mean of the slopes Major decliners: Predicted slopes more than 1 SD below the mean 

Cherbuin et al., 2009257 Community cohort 

(2082) 

4 years Self-report 

information about current and past smoking 

Published criteria for MCI, AAMI, AACD and other cognitive disorder 

Age Sex Educational level 

Incident MCI: Past smokinhigher risk of MCI compare3.22; 95% CI 1.05 to 9.87, Incident any MCD: Past smwith higher risk of MCD com(OR 1.97; 95% CI 1.12 to 3

Abbreviations: 3MS = Modified Mini-Mental State Examination; AACD = aging-associated cognitive decline; AAMI = age-associated memory impa

apolipoprotein E gene; APOE e4 = e 4 allele of the apolipoprotein E gene; CI = confidence interval; HTN = hypertension; DM = diabetes mellitus; MCMCI = mild cognitive impairment; MMSE = Mini-Mental State Examination; NS = not statistically significant; OR = odds ratio; RR = relative risk; Sstandard error
Alcohol use. We identified a single, good quality systematic review, published in 2009, that 

examined the association between alcohol use and cognitive decline.51 The review included two 

prospective cohort studies for cognitive decline published in 2000 and 2005.220,362 The two 

studies were community samples and included a total of 2192 subjects; one was conducted in the 

United States, and the other in a European country. Studies were selected that had measured 

cognition at both baseline and followup periods and either implemented a dementia assessment 

at baseline, which excluded those participants with cognitive impairment or dementia, or 

adjusted for incident dementia and/or baseline cognition performance in analyses. Included 

studies also had at least a 12-month followup period, had cognitive decline as an outcome, and 

measured exposure to alcohol at baseline or during the followup period prior to the final 

followup examination. Study participants were non-demented at baseline. The meta-analysis was 

based on current alcohol use, but one of the studies220 also collected data on former alcohol users 

versus lifetime abstainers. 

The cognitive outcome was defined as longitudinal change on the MMSE for one study.362

and change on a composite score of multiple cognitive measures for the other study.220 There 

was not a structured quality assessment of the studies reported in this systematic review; 

however the strict inclusion/exclusion criteria provided an indirect assessment of quality, and the 

study characteristics for key design variables were reported. Length of followup ranged from 4 

years in one study362 to an average of 7.3 years in the other study.220 No information was 

provided on the followup rates in the studies. The covariate adjustment for the two studies 

included at least age, sex, education, baseline cognitive score, and depressive symptoms; each 

study had additional covariates such as health behaviors and conditions. The results with the 

most covariates were given preference when reporting the data from the individual studies. 

Exposure was determined by self-report and alcohol use was classified as drinkers versus 

nondrinkers. 

Studies were combined using fixed-effect meta-analyses if there was no evidence of 

heterogeneity. If heterogeneity was present, random-effects models were used. Standard χ

2

 tests 

using a P value of 10 percent were used to examine heterogeneity. Publication bias was not 

formally assessed. 

The results for cognitive decline in drinkers versus non-drinkers are reported in Table 66. 

The test for heterogeneity was significant (χ

2

[1] = 11.80, P = 0.00006), suggesting that the pooled 

results from only two studies may not be reliable. To summarize the main findings, the direction 

of the relative risk suggested that drinkers may have a lower risk of cognitive decline, but the 

result did not approach standard statistical significance levels. 

Table 66. Alcohol use and risk of cognitive decline – results from studies reviewed by Anstey et al., 200951 

Comparison/Outcome assessed Relative risk (95% CI) 

Drinkers versus nondrinkers (n = 2 studies) 0.28 (0.03 to 2.83) 

Abbreviation: CI = confidence interval 

As discussed above under Question 1, the authors of the systematic review noted a number of 

complicating factors in the study of alcohol use as a risk factor for late-life cognitive outcomes. 

These factors make interpretation of the meaning of both significant and null results challenging. 

Publication bias was not assessed formally in this systematic review, but the authors suggested 

that the potential for such bias was likely reduced because of the inclusion of studies from article 

246
reference lists and articles that did not focus on alcohol use, but in which alcohol use was a 

covariate. Quality ratings of the studies were not provided, but strict selection criteria may have 

increased the likelihood that only high-quality studies were included in the review. The authors 

concluded that the pooled analysis showed no significant association between alcohol use and 

cognitive decline, but the measure of heterogeneity indicated that the results from the two studies 

combined may not be reliable. 

We identified five additional eligible cohort studies examining the association between 

alcohol use and cognitive decline published since June 2006.257,258,363-365 These studies are 

summarized in Table 67; detailed evidence tables are in Appendix B. In two of the studies257,365

participants were cognitively normal at baseline, and in two other studies the vast majority of 

participants are assumed here to have been non-demented based on either minimum cognitive 

scores required for inclusion in the study364 or mean age and mean cognitive score for the 

group.363 The fifth study258 included individuals who scored 80 or higher on the 3MS; thus it 

may have included some individuals with cognitive impairment and dementia. Two of these 

studies used the categorical outcome of incident mild cognitive impairment (MCI),257,365 and one 

used a categorical outcome indicating maintenance of cognition or minor or major decline. The 

other two studies363,364 assessed cognitive decline as a continuous variable. All five studies used 

samples drawn from the community; one of them also studied nursing home residents.365 Two 

studies used a U.S. sample,258,363 two used European samples,364,365 and one used an Australian 

sample.257 The average length of followup ranged from 2.2 to 8 years. The studies used selfreport history of current alcohol use obtained at baseline to characterize exposure during late life. 

Four of the studies used sample selection methods to minimize selection bias; 257,258,363,365 the 

inclusion criteria for the fifth study364 required that participants have vascular risk factors or 

vascular disease, which may have confounded the association between alcohol and cognitive 

change. Three studies compared baseline characteristics to assess differences between exposed 

and unexposed.258,363,364 The case definitions and cognitive outcomes for the studies are 

described in Table 67. The analyses appear generally appropriate and controlled for relevant 

potential confounders, but none of the studies conducted a priori sample size calculations. 

The results on incident MCI were inconsistent between the two studies evaluating this 

outcome, with one reporting no association between use of alcohol and risk of incident MCI,365

and the other showing that drinkers overall had a lower risk of incident MCI compared to nondrinkers.257 This latter study also showed a U-shaped quadratic relationship with very low and 

very high alcohol intake being associated with higher risk of MCI compared to moderate alcohol 

intake. The third study using a categorical outcome for cognitive decline found no significant 

association between alcohol intake and cognition, but the odds ratios were in the direction of 

more than one drink per day being protective for cognition.258 This study simultaneously 

examined the association between about 20 factors and cognitive decline; alcohol was not the 

focus of the study. The two studies assessing rate of cognitive decline as a continuous measure 

were consistent regarding the use of any alcohol providing greater preservation of cognition over 

time. One study364 reported a significant association (but negligible effect size) between alcohol 

use and maintenance of performance on the MMSE. However, this study did not find an 

association between alcohol intake and longitudinal performance on measures assessing other 

areas of cognition, such as memory and executive function, which are domains that typically 

show decline in the early stages of AD. The other study363 showed a dose-response effect in 

which greater amounts of alcohol per week were associated with less decline on the modified 

Telephone Interview for Cognitive Status (TICS), a measure of cognitive status similar to the 

247
248

MMSE. This dose-response association was not modified by the presence of an APOE e4 allele. 

Interestingly, this study did not find that an excessive amount of alcohol (i.e., more than two 

drinks per day) had a detrimental effect on cognition. 

In conclusion, the results are inconsistent regarding the association between cognitive decline 

and alcohol use in any amount. Obvious differences between the studies do not point to a clear 

explanation for these inconsistencies. 
Table 67. Alcohol and risk of cognitive decline – recent cohort studies 

Study Sample (n) Followup Exposure Case definition Confounding 

adjustment 

Results 

Wright et al., 2006363 Community cohort 

(1428) 

0.5 to 4.4 years (mean, 2.2) 

Self-report alcohol history 

Cognitive decline on a 51-point version of the TICS-m 

Age Race Sex Educational level Baseline cognitive status Interval between cognitive testing Health insurance status HDL-C level BMI HTN DM Cardiac disease 

Drinking less tha0.09), between otwo drinks daily (two drinks daily (associated with lethe TICS-m comp

Stott et al., 2008364 Community cohort 3.2 years (mean) Self-report alcohol history Decline on cognitive tests Age Rate of cognitive 

drinkers and nondomains, except declined significadrinkers compare(attenuated rate ounits per annum, 

Country 

(5804) Educational level 

Baseline cognitive status Smoking status BMI Weight Incident stroke History of vascular disease Test version 

Solfrizzi et al., 2007365 Community cohort, 

including institutionalized subjects (1566) 

3.5 years Self-report alcohol 

history 

Variation of Petersen MCI criteria 

Age Sex Educational level Smoking CAD Diabetes Hypertension 

No significant asslevels of drinking in non-cognitively abstainers 

249
Study Sample (n) Followup Exposure Case definition Confounding 

adjustment 

Results 

Stroke Cholesterol 

Cherbuin et al., 2009257 Community cohort 

(2082) 

4 years Self-report alcohol 

history 

Published criteria for MCI, AAMI, AACD, and other cognitive disorder 

Age Sex Educational level 

Incident MCI: Alcohol intake asMCI compared to 95% CI 0.37 to 0Quadratic modelshowing higher rdrinking groups (2.11; p = 0.002) Incident any mild Alcohol intake ascompared to abs0.57 to 1.00; p = Quadratic modelshowing non-signrisk for low and h1.17; 95% CI 0.9

Yaffe et al., 2009258 Community cohort 

(2509) 

8 years Self-report alcohol 

history 

Change on the 3MS Maintainers- 0 or greater predicted slope over time based on linear mixed model analyses Minor decline -predicted slope less than 0, but no more than one SD below the mean of the slopes Major decline - 

Age Race Educational level APOE genotype Reading ability Volunteer work Caregiver status Social support Living situation Self-rated health Physical exercise Smoking Depression BMI Hypertension 

Maintainers vs. m> 1 drink alcohol 0.91 to 1.93) Major declines vs(reference): > 1 drink alcohol 0.36 to 127) 

250
251

Study Sample (n) Followup Exposure Case definition Confounding 

adjustment 

Results 

predicted slope more than 1 SD below the mean 

Diabetes Stroke C-reactive protein IL-6 Triglycerides Fasting glucose 

Abbreviations: 3MS = Modified Mini-Mental State Examination; AACD = aging-associated cognitive decline; AAMI = age-associated memory impa

apolipoprotein E gene; BMI = body mass index; CAD = coronary artery disease; CI = confidence interval; DM = diabetes mellitus; HDL-C = high den

HTN = hypertension; IL-6 = interleukin-6; MCD = mild cognitive disorder; MCI = mild cognitive impairment; MMSE = Mini-Mental State Examinat

standard deviation; TICS-m = Telephone Interview for Cognitive Status (modified version)
Toxic Environmental Exposures 

We identified no systematic reviews or primary studies that examined toxic environmental 

exposures and the risk of cognitive decline. 

Genetic Factors 

Although there is an extensive literature examining genetic factors associated with AD, the 

literature linking genes and cognitive decline is more limited. The relation between genetic 

polymorphisms and cognitive change has been studied for the apolipoprotein E gene (APOE). 

APOE has three common alleles (e2, e3, and e4) that act as susceptibility factors for late-onset 

(age ≥ 65 years) AD. APOE e4 increases the risk of AD in a dose-dependent fashion, and e2 

reduces the risk. 

We identified 15 cohort studies involving 8509 subjects that examined the association 

between APOE and the risk of cognitive decline.183,258,260,262,267,274,284,330,331,366-371 These studies 

are summarized in Table 68; detailed evidence tables are in Appendix B. Four of the studies 

reported a categorical outcome,183,258,267,367 and the other 11 reported continuous 

outcomes.260,262,274,284,330,331,366,368-371 Fourteen were community samples, and one sample came 

from a clinical trial.284 One sample was from Australia,331 four from Europe,267,284,369,371 and 10 

from the United States.183,258,260,262,274,330,366-368,370 The length of followup ranged from 1 to 14 

years, and approximately 60 percent of subjects were women. All of the studies used sample 

selection methods to minimize selection bias and reported comparisons of baseline 

characteristics between those exposed and unexposed. The case definitions and cognitive 

outcomes for the studies are described in Table 68. None of the studies reported a priori sample 

size calculations. The analyses appear generally appropriate, with all of the studies using 

education as a covariate, and all but one adjusting for age and sex. The one study that did not 

adjust for age or sex had a sample with a narrow age range (ages 65 to 69).331 The studies used 

different baseline cognitive criteria for inclusion and some may have included individuals with 

mild cognitive impairment. One study included some individuals with dementia at baseline,331

but we report here only the analyses that excluded those individuals. The followup rates for four 

of the studies were fairly high, but one study had a followup rate of about 50 percent when 

combining non-participation due to both attrition and exclusion criteria.368 

Generally, various studies reported that APOE e4 was associated with greater decline on 

some, but not all, cognitive measures. Five studies reported a categorical outcome, and all found 

that APOE e4 allele increased the risk of cognitive decline.183,258,267,330,367 Tervo et al.267 reported 

that subjects with an APOE e4 were more likely to receive a diagnosis of MCI than those 

without an APOEe4 (OR 2.23; 95 percent CI 1.23 to 4.05). Bretsky et al.367 assessed global 

cognitive function using the SPMSQ and found that subjects with an APOEe4 allele were at 

increased risk for decline (OR 2.3; 95 percent CI 1.5 to 3.4). Yaffe et al.258 divided subjects into 

cognitive maintainers, minor decliners, and major decliners based on their performance on the 

modified MMS test (3MS). Investigators reported that major decliners were more likely to 

inherit an APOE e4 than minor decliners (OR 2.31; 95 percent CI 1.75 to 3.05). Presence of an 

APOEe4 allele was not, however, significantly different in those who maintained cognitive 

performance compared to those with minor declines. Shadlen et al.330 used the cognitive abilities 

screening instrument (CASI) to assess performance at baseline and after 6 years. At followup 6 

percent of the 2168 subjects had a decline of ≥ 1.5 SD on the CASI. Individuals who were 

252
homozygous for APOE e4 were at increased risk for decline compared to non-e4 subjects, but e4 

heterozygotes were not. Tyas et al.183 reported on data from 470 subjects in the Religious Orders 

Study followed for 1 to 12 years and found that subjects with an APOE e4 allele had an 

increased risk of transition from normal cognition to mild cognitive impairment compared to 

subjects without an APOE e4 allele (OR 1.87; 95 percent CI 1.27 to 2.73). 

Several studies used a battery of tests to assess longitudinal cognitive function. Comparison 

across studies is difficult because of the wide variety of non-overlapping tests used. Blair et al.368

studied subjects from the Atherosclerosis Risk in Communities (ARIC) project over a 6-year 

period. Investigators found a racial difference in APOE genotype effect. In Caucasians, decline 

on the Digit Symbol Substitution Test (DSST) and the Delayed Word Recall (DWR) test was 

correlated with APOE genotype, with the e2 group showing less decline than the e3 group, 

which in turn showed less decline than the e4 group. Among African-Americans, an APOE 

correlation similar to that observed in Caucasians was shown for DSST, but not DWR. Word 

fluency was not correlated with APOE genotype in either group. Knopman et al.260 extended the 

findings with the ARIC population reported by Blair et al.368 After 14 years of followup, APOE 

e4 genotype was still associated with a more rapid decline in DSST and DWR, but not WF, but 

the differential race effect was no longer significant.260 Christensen and colleagues performed the 

MMSE, symbol digit modality, reaction time, California Verbal Learning test, and digits 

backward, and found that APOE e4 was associated with greater decline on the MMSE, but not 

any of the other cognitive measures.331 Interpretation of the results for these multivariate 

analyses is problematic because of the large number of analyses performed without correction 

for multiple comparisons. Haan et al.274 reported that APOE e4 was associated with a higher 

annual rate of decline on the DSST, but not on the 3MS. Staehelin et al.369 examined free recall, 

reaction time, and the WAIS-R vocabulary test and found that baseline scores were lowest in 

subjects who were hetero- or homozygous for APOEe4, but after 2 years there was no APOE 

genotype-related change in performance on any measure. Yaffe et al.370 followed a cohort of 

Caucasian women recruited for an osteoporotic fracture study and found that after an average 

followup of 6.4 years, women with an APOE e4 allele had a greater decline on all tests (modified 

MMSE, 26 points, P = 0.01; DSST, P = 0.05; Trails B, P = .0 503). A similar association 

between decline on DSST in individuals and APOE e4 was also reported by Blair and 

Knopman.260,368 Packard and colleagues284 analyzed the association between APOE genotype 

and cognitive decline in 5804 subjects from the PROSPER trial of pravastatin in 

hypercholesterolemia. Subjects were between the age of 70 and 82 and were followed for an 

average of 3.2 years. Investigators reported that subjects with an APOE e4 allele had poorer 

baseline performance on immediate and delayed memory scores, and slower information 

processing. Subjects with APOE e4 also showed a greater decline in immediate and delayed 

recall, but not significant change in speed of information processing, as measured by the Stroop 

test.284

Three studies reported an interaction effect for APOE e4 and diabetes or 

hypercholesterolemia, such that the presence of at least one e4 allele was associated with greater 

decline among individuals with any of these medical conditions.262,274,368 However, one of these 

studies reported that this interaction was evident only on the 3MS,274 and another reported it for 

the DSST.368 Carmelli and colleagues found a significant difference in MMSE, DSST, and 

BVRT.262 Shadlen et al. reported that lower education was associated with steeper 4-year 

declines on CASI in APOE e4 homozygotes, but not in heterozygotes, suggesting that modifiable 

factors, such as education, could mitigate the association of this genetic risk factor on cognitive 

253
254

decline.330 Dik et al. examined the association between APOE genotype in cognitively normal 

subjects (MMSE > 26) and subjects with mild cognitive impairment (MMSE 21 to 26).371

Investigators reported that APOE e4 is a risk factor for memory decline, but only in cognitively 

impaired individuals (MMSE 21 to 26). No association between decline and APOE e4 was found 

in subjects with baseline MMSE > 26. 

Two studies also found that the APOE e2 allele may provide some protection against 

cognitive decline compared to both APOE e3 and e4.366,368 Wilson and colleagues reported that 

inheriting an APOE e2 allele was associated with a reduced rate of decline in episodic memory, 

while inheriting an APOEe4 allele was associated with an increased rate of decline in semantic 

memory, episodic memory, and perceptual speed.366 Blair et al. found that APOE e2 was 

associated with a slower rate of decline in DSST and DWR, but not WF, compared to non-APOE 

e2 genotypes in Caucasians, but not in DWR for African-Americans.368

In summary, the majority of studies suggest that APOE e4 is associated with an increased 

rate of cognitive decline in elderly individuals, especially on some memory tasks (DWR) and 

tasks of perceptual speed (e.g., the DSST). Not all cognitive domains appear to be affected by 

APOE genotype, and there is variability between studies. There is some evidence that APOE e2 

protects against memory decline, which is consistent with its proposed protective role against 

AD, but more data are needed. The effect of APOE on cognitive decline in African-Americans 

remains uncertain and will require studies with larger numbers of participants. There is modest 

evidence about interactions between APOE genotype and other risk factors, such as diabetes, 

hypercholesterolemia and education, but no firm conclusions can be drawn. Data examining the 

role of other genetic factors linked to AD, such as PICALM and CLU in the rate of cognitive 

decline are lacking. 
Table 68. APOE genotype and risk of cognitive decline 

Study Sample (n) Followup Exposure Case definition Confounding 

adjustment 

Results 

Wilson et al., 2002366 Community cohort 

(669) 

2 to 8 years APOE genotype Change on index of 

combined cognitive tests in separate cognitive domains Tests listed in table legends 

Age Sex Education 

e2 semantic mthan e3/3 e4 decline > eand perceptuamemory or vis

Bretsky et al., 2003367 Community cohort 

(965) 

7 years APOE genotype Decline of ≥ 1 SD on 

individual tests and summary scores as listed in table legend 

Age Sex Race Education 

Risk of declincognitive scor3.6) 

Blair et al., 2005368 Community cohort 

(1693 AfricanAmericans and 6202 Caucasians used in analysis) 

6 years APOE genotype Decline on DWR, 

DSST, and COWA, categorized by quintiles 

Age Sex Education Baseline cognition Cigarette smoking NSAIDs DM HTN Hypercholesterolemia 

Comparing quto all other quAA, e4/4 comDWR OR 1.72 DSST OR 1.8Risk for declinCompared to e2 group DWto 0.98); e4 group (e3/(1.01 to 1.41) e4/4 DWR ORDSST: e4/4 c2.02 (1.31 to 

Christensen et al., 2008331

Community cohort (2021) 

4 years APOE genotype Decline on: 

MMSE SDMT Reaction time CVLT Digits backwards 

Educational level Premorbid intelligence History of stroke Current HTN 

APOE e4 assdecline on MM0.029), but no 

255
Study Sample (n) Followup Exposure Case definition Confounding 

adjustment 

Results 

Haan et al., 1999274 Community cohort 

(3622) 

7 years APOE genotype 

HTN DM 

Annual rate of change on 3MS and DSST 

Age Race Sex Education Incident stroke 

Higher annuain APOE e4 pindividuals (p No difference Interaction bediabetes (p < APOE e4+ anAPOE e4+ anAPOE e4- anAPOE e4- an

Knopman et al., 2009260

Community cohort 

Median 14 years 

APOE genotype DSST 

DWR WF 

Age Race Sex Educational level Vascular factors Time Risk factor x time interaction 

Difference in test scores (P 

(1130) DSST: 1.06 (

DWR: 0.17 (0WF: 0.59 (0.4Difference in value) – APODSST: -0.10 DWR: -0.03 (WF: -0.04 (N

Tervo et al., 2004267 Community cohort 

(747) 

3.26 ± 0.7 years 

APOE genotype Clinical Dementia 

Rating (CDR): MCI diagnosed if score of 0.5 and if subject scored 1.5 SD below average on at least one memory test 

Age Race Sex Educational level Baseline cognitive status 

66 subjects (8MCI. The globwas 25.94/1,0with higher agto 1.16), APO2.04, 95% CI with medicate95% CI 1.05 tconvert to MClower age and allele or medi

256
Study Sample (n) Followup Exposure Case definition Confounding 

adjustment 

Results 

Staehelin et al., 1999369 Community cohort 

(332) 

2 years APOE genotype Computerized test for 

free recall and information processing speed Reaction time WAIS-R vocabulary subtest – define 32 words 

Age Sex Educational level Lipids Smoking 

At baseline: Adjusting for ae4/4 and e3/4 recall, reactiovocabulary sucarriers of one recall P = 0.0WAIS-R vocaNo significant measure (free WAIS-R vocayears in any A

Shadlen et al., 2005330 Community cohort 

(HMO members) (2140) 

3.29 years APOE genotype Change in CASI score Age 

Race Sex Years of followup Depression Diabetes Hypertension Cerebrovascular disease 

GEE analysisRisk factors aglobal cognitivNo e4 – refereOne e4 alleleCI -2.5 to 2.05Two e4 allele(95% CI-16.2

Yaffe et al., 1997370

Clinical cohort - subjects in the multicenter Study of Osteoporotic Fractures (1248) 

6 years APOE genotype Modified MMSE (max 

score 26) Trails B DSST Cognitive decline was defined on each or any test if a woman had the largest 10th percentile 

reduction in performance from initial score to repeat testing 

Age Educational level Baseline cognitive status Depression Presence of severe tremor 

Presence of asignificantly aon all cognitivcompared to MMSE P = 0.B P = 0.003) Incidence of ctimes higher iand ranged frTrails B to 2.4 MMSE. Homotwice as fast atests except T

257
Study Sample (n) Followup Exposure Case definition Confounding 

adjustment 

Results 

Reduction on 0% for no e4; for 2 e4s (P < Reduction on e4; 9% for 1 e= 0.04) Reduction on e4; 25% for 1 = 0.002) 

Yaffe et al., 2009258 Community cohort 

(2509) 

8 years APOE genotype Slopes of 3MS scores 

were estimated by best linear unbiased predictions using a linear mixed model with random intercepts and slopes. Slopes of 0 or greater were classified as maintainers. Those with predicted slopes less than 0, but not more than one SD below the mean of the slopes were classified as minor decliners. Those with predicted slopes more than 1 SD below the mean were classified as major decliners. 

Age Race Educational level APOE genotype 

Minor vs. majAPOE e4: OR to3.05) APOE e4 was a maintainer v0.8 (95% CI 0

Carmelli et al., 1998262 Community cohort 

(NHLBI WWII twin substudy) (410) 

10 to 25 years 

Mid-life hyperglycemia (1-hour postprandial glucose > 200 or use of hypoglycemic agent or insulin) 

Change in test scores: MMSE, DSST, BVRT 

Age Mean change Race APOEe4+ and Sex MMSE: 1.66 Baseline scores DSST: 7.84 (Incident cardiovascular disease 

BVRT: 1.05 (APOEe4+ and 

APOE genotype MMSE: 0.73 

DSST: 4.47 (

258
Study Sample (n) Followup Exposure Case definition Confounding 

adjustment 

Results 

BVRT: 0.53 (APOEe4- and MMSE: 0.47 DSST: 4.14 (BVRT: 0.84 (APOEe4- and MMSE: 0.47 DSST: 3.34 (BVRT: 0.37 (All scores are 0 and statistic

Dik et al., 2000371 Community cohort 3.1 years APOE genotype MMSE; AVLT (3 trials); memory decline was 

defined as ≥1 SD mean 

change score on immediate recall, delayed recall, and retention based on AVLT 

Age Sex 

(1243) Educational level 

APOE e4 carriers APOE e4 non-carriers MMSE 27-30 (normal cognition) MMSE 21-26 (impaired cognition) 

In subjects wiAPOE e4 (adjeducation and Decline on im(95% CI 1.4 to Decline on deto 7.0) Decline on re10.1) No associationormal subjec

Clinical cohort (PROSPER trial) 

Packard et al., 2007284 3.2 years APOE genotype MMSE, picture-word learning test, Stroop 

color word test, letter digit coding test 

Age Sex Country Education (5804) History of vascular disease MI Stroke 

At baseline, se4versus thosmemory perfodifference -0.2for immediate 0.16] for delayinformation prStroop, 2.79 s4.28]; Letter-D0.05]). Subjec

259
260

Study Sample (n) Followup Exposure Case definition Confounding 

adjustment 

Results 

TIA Smoking Antihypertensive medication BP BMI DM Triglyceride Treatment allocation APOE e4 Baseline cognitive test scores 

a greater dec95% CI -0.33 0.30, -0.46 to no significant information pr0.17; Letter-DMemory scorebaseline in thheterozygotes and P = 0.03 and 8.9% to 1(P = 0.04 for ifor delayed, ve4 was associn instrumenta(P < 0.001). 

Tyas et al., 2007183 Community cohort 

(470) Religious Orders Study 

1-11 years APOE genotype Subjects performed 

four CERAD tests, MMSE and an ADL screen. Subjects with mild cognitive impairments had at least one specific area of impaired cognitive function, such as memory or naming, but had intact global cognitive ability and ADL. 

Age Education APOE Prior cognitive state 

Transition fropresent: OR Transition froimpairment – 3.02 (1.87 to 4

Abbreviations: 3MS = Modified Mini-Mental State Examination; ADL = activities of daily living; APOE = apolipoprotein E gene; APOE e2/e3/e4 = 

apolipoprotein E gene; AVLT = Auditory Verbal Learning Test; BVRT = Benton Visual Retention Test; CASI = Cognitive Abilities Screening InstrumDementia Rating; CERAD = Consortium to Establish a Registry for Alzheimer’s Disease; CI = confidence interval; COWA = Controlled Oral Word A

California Verbal Learning Test; DM = diabetes mellitus; DSST = Digit Symbol Substitution Test; DWR = Delayed Word Recall; GEE = Generalized hypertension; MCI = mild cognitive impairment; MI = myocardial infarction; MMSE = Mini-Mental State Examination; NS = not statistically significanti-inflammatory drugs; OR = odds ratio; SD = standard deviation; SDMT = Symbol Digit Modalities Test; TIA = transient ischemic attack; Trails B 

WAIS-R = Wechsler Adult Intelligence Scale-Revised; WF = Word Fluency Test 
Key Question 3 – Interventions to Delay the Onset 

of Alzheimer’s Disease 

Key Question 3 is: What are the therapeutic and adverse effects of interventions to delay the 

onset of Alzheimer’s disease? Are there differences in outcomes among identifiable subgroups? 

Nutritional and Dietary Factors 

B vitamins and folate. There were no studies identified that used B vitamins or folate in 

RCTs to examine prevention of AD. 

Other vitamins. We identified one RCT that examined the effect of supplemental vitamin E 

on progression of amnestic MCI to AD.372 Participants were recruited from 69 Alzheimer’s 

Disease Cooperative Study (ADCS) sites throughout the United States and Canada. Inclusion 

criteria were: a diagnosis of amnestic MCI; impaired memory; a Logical Memory delayed-recall 

score approximately 1.5 to 2 SD below an education-adjusted norm; a Clinical Dementia Rating 

Scale Score (CDR) of 0.5; a score of 24 to 30 on MMSE; and age between 55 to 90 years. There 

were three treatment arms: (1) 2000 IU of vitamin E, placebo donepezil, and multivitamin daily; 

(2) 10 mg of donepezil, placebo vitamin E, and a multivitamin daily; and (3) placebo vitamin E, 

placebo donepezil, and a multivitamin daily (placebo group). The trial lasted for 3 years, during 

which participants were assessed every 6 months. A total of 769 participants were randomized, 

of which 230 discontinued due to death, adverse events, or withdrawal of consent. Followup 

rates did not differ by treatment or placebo groups. The primary outcome was incident AD 

determined by standard assessment procedures and diagnostic criteria. Compared to the placebo 

group, the group treated with vitamin E did not show a difference in their rate of progression 

from amnestic MCI to AD (HR 1.02; 95 percent CI 0.74 to 1.41; P = 0.91). 

Gingko biloba. We identified one RCT that examined the effectiveness of gingko biloba 

versus placebo in reducing the incidence of AD in older individuals with normal cognition and 

those with mild cognitive impairment.373 Volunteers aged 75 years or older were recruited using 

voter registration and other purchased mailing lists from four U.S. communities with academic 

medical centers. To enroll in the study, individuals needed to have a proxy informant who was 

willing to be interviewed every 6 months. Individuals with prevalent dementia were excluded. 

There were additional exclusion criteria primarily related to medication use that are outlined the 

in evidence table in Appendix B. The treatment group took two daily doses of 120 mg gingko 

biloba extract; the placebo group took placebo pills on the same schedule. At the end of the trial, 

60 percent of the active participants were taking their assigned study medication, and compliance 

did not differ between the two groups. A total of 3069 individuals were enrolled and randomized, 

of which 482 had a diagnosis of MCI at enrollment and the remainder were considered 

cognitively normal. Primary outcomes were known on 93 percent of the participants at the end of 

the study. The primary outcome was a diagnosis of dementia. Secondary outcomes were to 

evaluate the effect of gingko biloba on the following end points: overall cognitive decline, 

functional disability, total mortality, and incidence of cardiovascular disease. Only results on the 

primary outcome were presented in this article. The trial results showed that the HR for the entire 

sample for AD for the treatment versus the placebo groups was 1.16 (95 percent CI 0.97 to 1.39; 

P = 0.11); the HR > 1.0 suggests increased risk of AD for gingko biloba users. Gingko biloba 

also had no effect on the rate of progression to AD in participants with MCI (HR 1.10; 95 

261
percent CI 0.83 to 1.47; P = 0.51). The investigators concluded that gingko was not effective in 

preventing incident AD. 

In conclusion, there is little evidence to support the use of gingko biloba to delay the onset of 

Alzheimer’s disease. 

Omega-3 fatty acids. We identified two good quality systematic reviews evaluating the 

association between omega-3 fatty acids and risk of Alzheimer’s disease29,31 The Cochrane 

review by Lim et al.31 searched multiple databases for randomized, double-blinded, placebocontrolled trials lasting at least 6 months in persons aged 60 or above without pre-existing 

dementia. Through October 2005, no eligible studies were identified. Fotuhi et al.29 searched for 

trials that addressed the specific association between any form of omega-3 fatty acids in 

participants age 65 or older and used standard diagnosis of dementia. No trials were identified. 

Our independent search also failed to identify any relevant studies. 

Other fats. We identified no RCTs of other fats used to delay the onset of AD. 

Trace metals. We identified no RCTs evaluating the use of trace metals to delay the onset of 

AD. 

Mediterranean diet. We identified no RCTs evaluating the use of a Mediterranean diet to 

delay the onset of AD. 

Intake of fruits and vegetables. We identified no RCTs assessing the relationship between 

fruit and vegetable intake and onset of AD. 

Total intake of calories, carbohydrates, fats, and proteins. We identified no RCTs 

evaluating the relationship between total intake of calories, carbohydrates, fats, and protein and 

onset of AD. 

Medical Factors 

Medications. Prescription and non-prescription drugs considered under this heading include 

statins, antihypertensives, anti-inflammatories, gonadal steroids, cholinesterase inhibitors, and 

memantine. 

Statins. No systematic reviews or RCTs were identified evaluating the effects of statins on 

the incidence of AD. 

Antihypertensives. We identified one good quality systematic review evaluating the 

association between antihypertensive medications and the prevention of dementia.34 Our own 

independent search did not identify any additional studies. Included in the systematic review 

were randomized, double blind, placebo-controlled trials whose subjects had a diagnosis of 

hypertension without clinical evidence of cerebrovascular disease. Three trials, SCOPE, Syst-Eur 

and SHEP were included.374-376 SCOPE randomized participants (who had an entry SBP of 160 

to 179 mmHg or a DBP 90 to 99 mmHg or both) in a 1:1 ratio to placebo or candesartan. There 

was a stepwise progression of medication changes based on blood pressure. SHEP included 

subjects with isolated systolic hypertension (SBP 160 to 219 mmHg, DBP < 90 mmHg). 

Participants were randomized to placebo or chlorthalidone, with atenolol or reserpine added if 

necessary. Syst-Eur also enrolled subjects with isolated systolic hypertension. SBP was 160 to 

219 mmHg at entry, with DBP < 95 mmHg. Subjects were randomized to placebo with 

medications added if SBP remained high versus nitrendipine with addition of enalapril and/or 

hydrochlorothiazide. All studies reported rates of incident dementia, but only one376 reported the 

proportion of patients with AD, and only a total of 23 cases were observed. In all studies, 

cognitive outcomes were a secondary outcome and investigators did not report a priori sample 

262
size calculation specific to this outcome. Given the low rate of incident dementia, these studies 

may have been underpowered to detect clinically important differences between interventions. 

All studies had a significant number of control-assigned subjects on active medication (84 

percent in SCOPE, 27 percent in Syst-Eur during study, and 44 percent in SHEP). This treatment 

contamination would decrease differences between groups. Also, in each study, a minority of 

subjects was taking initially assigned medications (25 percent in SCOPE, 30 percent in Syst-Eur, 

30 percent in SHEP). All studies did achieve a differential BP response, with lower pressures in 

subjects assigned to active treatment (differences for SBP/DBP were SCOPE 3.2/1.6 mmHg, 

SHEP 11.1/3.4 mmHg, and Syst-Eur 10.1/4.5 mmHg). In a meta-analysis, treatment with 

antihypertensives did not decrease the risk for general dementia (OR 0.89; 95 percent CI 0.69 to 

1.16). 

Forette and colleagues376,377 followed the Syst-Eur subjects for an additional 2 years after the 

end of the study. All control subjects who wished to continue were changed to active medication 

at that time. Throughout the followup, blood pressure remained lower in the group initially 

assigned to active treatment by 7.0 mmHg/3.2 mmHg. In spite of the majority of subjects being 

on active treatment, the rates of dementia were lower in the active treatment group. The reasons 

for the decrease in incidence of dementia are not known. Nitrendipine, a calcium channel 

blocker, was the first study drug started and showed a HR of 0.38 (95 percent CI 0.23 to 0.64). It 

may be that the subjects opting not to continue in the trial had a higher rate of cognitive decline, 

biasing results away from a null effect. It is noted that there was a protective effect in the SystEur study during the duration of the trial also (incidence decreased by 50 percent from 7.7 to 3.8 

cases per 1000 patient-years).34,376,377

In summary, a combination of three large, multi-site RCTs did not suggest a protective effect 

of antihypertensive treatment in incident dementia. The proportion of subjects with incident AD 

was not consistently reported, so the applicability of these data to our study question is uncertain. 

The trials are difficult to evaluate, as many patients were lost to followup and many subjects 

assigned to the control group received medications when their blood pressure remained elevated. 

Bias could be introduced via both mechanisms. It also is noted that durations of studies were 

fairly brief (5 years), and that all studies looked at non-specific dementia rather than AD. The 

brief followup study to Syst-Eur did suggest a benefit to antihypertensives, but in this open-label 

continuation study all subjects were receiving active treatment. Details of dementia diagnosis are 

limited, and it is possible that subjects with cognitive impairment would be less likely to 

participate in the followup study. 

Anti-inflammatories. Our search identified two RCTs using NSAIDs and reporting AD as an 

outcome. Both studies invoked early stopping rules. Thal et al.378 evaluated subjects who had 

MCI at baseline. A total of 1457 subjects with a MMSE ≥ 24 were randomized to rofecoxib 25 

mg daily, a drug that subsequently was withdrawn from the market due to safety concerns, or 

placebo. The study was powered based on the projection of 220 incident cases of AD. The 

original 2-year study duration was lengthened to 4 years because of lower than expected 

conversion rates, and was then shortened to approximately 3 years, as reaching the goal was 

determined to be futile. Over the course of the study 189 subjects developed AD by the study 

definition, primarily a Clinical Dementia Rating Scale (CDR) score ≥ 1, which triggered further 

evaluation. A minority of subjects actually completed the study on drug (40 percent of the 

rofecoxib group and 41 percent of the placebo group). The most common reasons for 

discontinuation were withdrawal of consent, followed by adverse events, and then subjects who 

were lost to followup, uncooperative, or moved. A “completers” analysis evaluating those 

263
subjects who finished the study on drug showed an increased risk of AD with NSAIDs (HR 1.49; 

95 percent CI 1.08 to 2.05), as did the intention-to-treat analysis (HR 1.46; 1.09 to 1.94). 

The second trial, by the Adapt Research Group,379 randomized 2528 subjects who were firstdegree relatives of AD patients to using celecoxib, naproxen, or placebo. Subjects received 

cognitive testing at baseline, and those scoring low enough were referred for a more 

comprehensive dementia evaluation. The cut-points used to trigger a full evaluation were not 

reported. This study was closed early because of concerns over the safety of COX-2 inhibitors as 

a class. Poor adherence to study medications was common: 83 to 85 percent of subjects had 

sufficient data to be included in analysis, but almost half of subjects had terminated use of the 

study drug. According to subject reports, the active medications were taken on medians of 546 

and 561 days out of a possible 733 days. Seven demented subjects were inadvertently enrolled. 

When the data from these subjects were excluded, there were 5 subjects who developed AD in 

the placebo group, 11 in the celecoxib group, and 9 in the naproxen group. Reflecting the small 

number of cases, the confidence intervals were large: the HR for celecoxib versus placebo was 

4.11 (95 percent CI 1.30 to 13.0), and the HR for naproxen versus placebo was 3.57 (1.09 to 

11.7). 

In summary, both RCTs suggest that NSAIDs increase the risk of incident AD. Explanations 

are not clear, but it is possible that NSAIDs adversely affect cognition. Alternatively, initiation 

of an anti-inflammatory after MCI has manifested itself may be too late in the course of illness 

for benefit. Studies that have attempted to treat AD with NSAIDs have also had negative 

findings, and MCI may well represent a prodrome in many patients. The trial conducted by the 

Adapt Research Group379 attempted to begin with unimpaired subjects. The randomization of a 

small number who had actual dementia casts some doubt on the sensitivity of the screening 

process. The frequent termination of study drugs may also have introduced some bias, depending 

on the cause of termination. It has been suggested that cognitively impaired subjects may be 

more likely to terminate participation in a trial. By subject report, it also appears that those 

remaining on medication had a cumulative time on NSAIDs of approximately 18 months, less 

than has been suggested necessary by observational studies. 

Gonadal steroids. No good quality systematic review was identified that specifically 

addressed the therapeutic and adverse effects of gonadal steroids on development of AD. We 

identified two RCTs involving 7479 women that examined the effect of estrogen with or without 

progestins on the development of Alzheimer’s disease.380,381 Both studies were conducted in the 

United States and used a staged diagnosis based on DSM-IV criteria for AD, with data from 

cognitively impaired individuals referred to a central adjudication committee. Participants were 

community-dwelling, non-demented, postmenopausal women between the ages of 65 and 79 

years recruited from 39 of the 40 Women’s Health Initiative Centers. Treatment consisted of 

conjugated equine estrogen (CEE 0.625 mg) or CEE plus 2.5 mg medroxyprogesterone acetate 

(MPA) versus placebo. Both studies assessed cognitive function at baseline using the Modified 

Mini-Mental State Examination (3MS); duration of followup was 4 (CEE plus MPA) or 5 (CEE) 

years. 

The primary outcome in both studies was probable dementia, but a diagnosis of AD was 

made in half the patients with dementia (54 of 108 cases). An additional 16 percent of cases with 

dementia (17 of 108) were attributed to a mixture of cerebrovascular and AD (mixed dementia). 

Results are summarized in Table 69. Treatment with CEE alone did not reduce the risk of 

probable dementia, but appeared rather to increase it (HR 1.76; 95 percent CI 1.19 to 2.60; P = 

0.005). After excluding participants with baseline 3MS scores at or below the screening cut 

264
point, the association of increased risk of dementia with CEE alone was no longer statistically 

significant (HR 1.77; 95 percent CI 0.74 to 4.23; P = 0.20), suggesting that these subjects may 

have been cognitively impaired at the time of enrollment in the study. Treatment with CEE plus 

MPA significantly increased the risk of developing dementia (HR 2.05; 95 percent CI 1.21to 

3.48; P = 0.01). No statistics were provided for AD as a separate endpoint in either the CEE or 

CEE plus MPA treatment arms. 

Table 69. Therapeutic effects of gonadal steroids on development of AD 

Treatment HR (95% CI) for probable dementia 

CEE 1.76 (1.19 to 2.60); P = 0.005 

Exclusion participants with low baseline 3MS 1.77 (0.74 to 4.23); P = 0.20 

CEE plus MPA 2.05 (1.21to 3.48) P = 0.01 

Abbreviations: 3MS = Modified Mini-Mental State Examination; AD = Alzheimer’s disease; CEE = conjugated equine estrogen; 

CI = confidence interval; HR = hazard ratio; MPA = medroxyprogesterone acetate 

The findings from these studies demonstrate that hormone therapy with estrogen with or 

without progestin does not reduce the risk of dementia in postmenopausal women. Regular use 

of CEE plus MPA by postmenopausal women slightly increases the risk of dementia. 

Our own independent search did not identify any additional studies. 

Cholinesterase inhibitors. We identified one good quality systematic review that examined 

the effects of cholinesterase inhibitors on the progression to dementia or AD.44 The review 

included eight RCTs (4127 subjects). Four were multi-site studies in North America or the 

United States; one was a multi-site study in North America and Western Europe; one was a 

small, single-site U.S. study; and two did not report location. RCTs were selected that compared 

a cholinesterase inhibitor (donezpezil, galantamine, rivastigmine) to placebo control in 

participants with abnormal memory function and/or who met diagnostic criteria for mild 

cognitive impairment (MCI); individuals with dementia were excluded. Only English-language 

studies and studies presenting original data were included. Study quality was assessed using the 

Jadad criteria and was judged to be low to medium. Only one trial adequately described the 

randomization process; four followed an intention-to-treat principle for analysis; loss to followup 

was substantial and greater for intervention than control subjects; and in all but one study, 

multiple secondary outcome measures were evaluated without correction for multiple 

comparisons. Formal tests for publication bias (e.g., funnel plot) were not performed, but three 

completed studies382-384 identified at ClinicalTrials.gov have not reported results, suggesting 

possible publication bias. One was a 16-week industry-sponsored study of rivastigmine that was 

terminated early in 2004.384 The second was a 1-year National Institute of Mental Healthsponsored study of donepezil and gingko biloba extract completed in 2004.383 The third was a 1-

year, industry-sponsored study of donepezil in subjects with MCI completed in March 2007.382

From the available records, it is unclear if conversion to AD was an outcome measure in these 

trials. 

Of the eight identified trials, four (described in three publications385-387) reported rates of 

conversion to dementia/AD. Cholinesterase inhibitors evaluated were donepezil 10 mg daily, 

rivastigmine 3 to 12 mg daily, and galantamine 16 or 24 mg daily (two studies). The number of 

subjects ranged from 769 to 1062. Participants were age ≥ 50 years; race was reported in only 

one publication, describing two studies,386 and over 90 percent of subjects were white. One 

265
study387 recruited subjects with amnestic MCI, while the other studies used more inclusive 

criteria for MCI. Two studies specifically reported conversion to AD at 3 to 4 years using 

NINCDS-ADRDA criteria,385,387 while the other two reported conversion to dementia at 2 years 

based on an increase in the CDR from 0.5 to 1.0.386 The authors of the systematic review did not 

compute a summary estimate of effect due to important heterogeneity in the definition for MCI. 

Conversion to dementia or AD for subjects treated with a cholinesterase inhibitor ranged 

from 13 percent (at 2 years) to 25 percent (at 3 years). In comparison, control subjects converted 

at a rate of 18 percent (at 2 years) to 28 percent (3 years). Hazard ratios for conversion to AD 

were reported in two studies and did not show a statistically significant reduction in risk: HRs 

were 0.85 (95 percent CI 0.64 to 1.12)385 and 0.80 (0.57 to 1.13).387 Treatment discontinuation 

due to adverse events was significantly higher for intervention subjects, ranging from 21 to 24 

percent compared to 7 to 13 percent in control subjects. Effects on mortality were not adequately 

reported. The authors concluded that the use of cholinesterase inhibitors in MCI was not 

associated with any delay in the onset of AD or dementia, and that the safety profile showed that 

risks associated with cholinesterase inhibitors are not negligible. A fair quality systematic 

review388 evaluated the same four trials and computed a summary estimate showing a decreased 

risk of conversion to AD or dementia (RR 0.75; 95 percent CI 0.66 to 0.87) and a higher allcause dropout risk (RR 1.36; 95 percent CI 1.24 to 1.49). We judged these summary estimates to 

be suspect due to significant variability in the definition of MCI, variability in outcomes (AD 

versus any dementia), and probable publication bias. 

We did not identify any additional trials that evaluated cholinesterase inhibitors and reported 

conversion to AD or dementia, but we identified a subgroup analysis from the Petersen trial 

comparing donepezil to placebo in 769 subjects with amnestic MCI and Hamilton Depression 

Rating Scale (HDRS) scores < 12 (consistent with no current mild to moderate major depressive 

disorder [MDD]). The primary outcomes publication conducted subgroup analyses in APOE e4 

carriers, showing a reduced risk for conversion to AD in patients treated with donepezil (HR 

0.66; 95 percent CI 0.44 to 0.98). Benefit in APOE e4 carriers was not demonstrated in subgroup 

analyses from the study by Feldman et al.385 The subgroup analysis42 evaluated the effects of 

donepezil in subjects with Beck Depression Inventory (21-item) scores ≥ 10, consistent with 

significant depressive symptoms despite the absence of MDD. In the subgroup with significant 

depressive symptoms (n = 208), donepezil treatment was associated with a lower conversion to 

AD at 1.7 years (11 percent versus 25 percent) and 2.2 years (14 percent versus 29 percent), but 

not at 2.7 years (18 percent versus 32 percent, p = 0.07). 

In summary, a systematic review found four low to medium quality trials reporting the 

effects of cholinesterase inhibitors on conversion to dementia/AD in subjects with MCI. Study 

heterogeneity precluded a valid summary estimate of effect, but conversion rates were similar in 

intervention and control subjects. Differential effects in subgroups, including those at higher risk 

for progression to AD (e.g., amnestic MCI, depressive symptoms, APOE e4) are inconsistent. 

Memantine. We did not identify any systematic reviews or primary studies that evaluated the 

effects of memantine on incident AD in subjects who were cognitively normal or had mild 

cognitive impairment. 

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Social, Economic, and Behavioral Factors 

We did not identify any good quality systematic reviews or RCTs that evaluated the effects 

of the following types of interventions for delaying the onset of AD: 

• Social engagement; 

• Cognitive engagement; 

• Physical activities; 

• Other leisure activities; 

• Nicotine. 

Key Question 4 – Interventions to Improve or Maintain 

Cognitive Ability or Function 

Key Question 4 is: What are the therapeutic and adverse effects of interventions to improve 

or maintain cognitive ability or function? Are there differences in outcomes among identifiable 

subgroups? 

Nutritional and Dietary Factors 

B vitamins and folate. We identified two RCTs that examined the effect of B vitamins on 

maintenance of cognitive function.389,390 The first389 was a substudy of a larger ongoing RCT 

examining the effect of antioxidants and folic acid on reduction of cardiovascular disease in 

female health professionals throughout the United States. Those included in the parent study 

were at least 40 years of age, had at least three coronary disease risk factors, completed the runin-phase of the RCT adequately, were willing to forgo use of other vitamin supplements during 

the course of the study, and had no history of cancer, active liver disease, chronic kidney failure, 

or use of anticoagulants. The cognitive substudy was limited to participants in the parent RCT 

who were aged 65 years and older. No details were provided regarding the baseline cognitive 

status of participants, but since these individuals were part of an ongoing RCT for cardiovascular 

disease, one would predict that the vast majority were non-demented at baseline. This substudy 

included participants assigned to one of the treatment arms and a placebo group of the parent 

study. The intervention was a daily combined vitamin of 2.5 mg folic acid, 50 mg vitamin B6, 

and 1 mg vitamin B12. The time from randomization to the intervention and end of the trial was 

6.6 years. The initial cognitive assessment was about 1 year after the start of the intervention, 

and assessments were then repeated about every 2 years for a total of four assessments. 

Cognitive function was measured using a telephone assessment protocol that included the 

Telephone Interview for Cognitive Status (TICS), an immediate and delayed verbal memory 

task, and a semantic fluency task. The primary outcome measures were: longitudinal change on 

a global composite score that was derived by combining scores from all cognitive tests; and 

longitudinal change on a memory composite score that was derived by combining the memory 

measures. 

Of the 2164 individuals meeting inclusion criteria for the substudy, 93 percent (2009) 

completed the first cognitive assessment. Ninety-four percent completed at least one followup 

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assessment, and 83 percent completed at least three cognitive assessments. Cumulatively, 

however, just over 50 percent of the sample completed the final followup assessment (4th

assessment) due primarily to the short interval of time between the third cognitive assessment 

and the RCT end date. Participation rates did not differ by treatment group. Compliance with 

treatment was 83 percent for both the intervention and placebo groups. The main independent 

variable was the treatment arm (intervention versus placebo). There was no difference in 

cognitive decline over time between the intervention and placebo groups. The mean difference in 

cognitive decline over time between the treatment and placebo groups was 0.03 standard units 

per year (95 percent CI -0.03 to 0.08; p = 0.30) for the global score and 0.03 (95 percent CI -0.03 

to 0.09; p = 0.36) for the verbal memory score. However, in subgroup analyses the investigators 

examined whether other possible risk factors for cognitive decline modified the effect of the 

treatment and placebo groups on rates of cognitive change. One of the potential effect modifiers 

was dietary intake of vitamin B6 and B12 and folate based on self-reported responses to a semiquantitative food-frequency questionnaire administered at baseline. The results of these subgroup 

analyses showed that there was no difference in rate of cognitive change for the global cognitive 

score or the global memory score when stratified by estimated levels of dietary intake of B 

vitamins or folate. However, the analyses provided some support for the idea that supplemental 

B vitamins and folate may be advantageous in maintaining cognitive performance on the TICS 

for those with low dietary intake of B vitamins and folate. 

In summary, this cognitive substudy of a larger RCT found no association between 

supplemental B vitamins and folate and rate of cognitive change over a period of about 6 years. 

The substudy used assignment to the treatment or placebo group as the predictor variable and did 

not use serum levels of the B vitamins or folate. 

The second RCT390 investigated the effect of combined folate, B6, and B12 supplementation 

on cognition (primary outcome) and homocysteine levels (secondary outcome) among 

individuals with elevated baseline homocysteine levels. The study was conducted in New 

Zealand. Participants were recruited from service clubs. Inclusion criteria included age 65 and 

older, a fasting homocysteine > 13 μmol/L, and a normal creatinine level. Exclusion criteria were 

suspected dementia; taking medications known to interfere with folate metabolism (e.g., oral 

hypoglycemic agents or antiepileptic agents); taking vitamin supplements containing folic acid, 

vitamin B12, or vitamin B6; being treated for depression; diabetes; or a history of stroke or 

transient ischemic attacks. The participants were randomized to either the treatment arm (one 

capsule per day that contained 1000 μg of folate, 500 μg of vitamin B12, and 10 mg of vitamin 

B6) or the placebo group (one placebo capsule per day). The trial lasted for 24 months and had 

three time points of cognitive testing (baseline, 1 year, and 2 years). Of the 276 individuals 

randomized in the trial, 253 (92 percent) completed the study and were included in the analyses. 

This included 15 individuals who discontinued taking the supplement, but completed all 

cognitive testing. Compliance rate was adequate, as 85 percent of participants took 95 percent of 

the supplements. The cognitive battery included a number of standard neuropsychological 

measures for the assessment of cognitive decline in later life and assessed a range of cognitive 

domains including memory, verbal fluency, executive function, reasoning, and orientation. 

Scores were reported for individual tests and also for a standardized combined score for all tests. 

Change in performance on the cognitive measures over time was calculated controlling for age, 

sex, and baseline cognitive score. 

We note that the study authors interpreted the results as showing overall no significant 

differences in cognitive performance for the treatment and placebo groups. However, the results 

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showed a modest but statistically significant difference (p = 0.05) in the summary cognitive 

score, with the treatment group scoring 0.11 standard deviations lower than the placebo group. 

Analysis of change in individual test scores revealed a statistically significant worsening of 

scores on Trails B in the treatment group as compared to the placebo group (the exponent of the 

difference between the log-transformed values is the ratio of the result in the vitamin group 

compared to the placebo group = 1.08; 95 percent CI 1.02 to 1.14). The treatment group tended 

to show greater decline on most of the cognitive measures, but these differences did not meet 

standard statistical significance levels. 

The secondary outcome of homocysteine levels showed that the vitamin group had 

homocysteine levels that were, on average, 4.36 μmol/L (p < 0.001) lower than the placebo 

group. 

In summary, the two RCTs that have examined the effect of supplemental folate and vitamins 

B6 and B12 on maintenance of cognition in later life have not shown a beneficial effect. 

Other vitamins. We identified five RCTs that examined the effect of supplemental vitamin 

E, vitamin C, or a multivitamin on maintenance of cognitive function.372,391-394 The studies are 

summarized here, and further details are provided in evidence tables in Appendix B. The first 

trial392 was a substudy of the Women’s Health Study that examined the effect of vitamin E and 

low-dose aspirin on the prevention of cardiovascular disease and cancer. Inclusion criteria for the 

parent study were women at least 45 years old; no history of coronary heart disease, 

cerebrovascular disease, cancer (except for non-melanoma skin cancer), or other major chronic 

illnesses; not actively using any of the study medications; and no history of adverse effects from 

any study medications. The cognitive substudy was limited to women age 65 and older and 

began about 5.6 years after randomization for the parent study. A detailed description of the 

participants’ baseline cognitive status was not provided, but based on the mean baseline scores 

on the TICS, the majority of participants were likely non-demented at baseline. The intervention 

group took vitamin E (600 IU) and low-dose aspirin (100 mg) every other day; the placebo group 

took a placebo pill on the same schedule. Of the 7175 eligible for the study, 6377 (89 percent) 

completed the baseline cognitive assessment, and 5073 completed all three cognitive 

assessments. Followup rates did not differ for the treatment and placebo groups. Compliance was 

similar for the two groups, as 75.4 percent of the vitamin E group and 76.9 percent of the 

placebo group reported taking at least two-thirds of the assigned pills. The cognitive substudy 

lasted for 4 years, which included three telephone cognitive assessments at 2-year intervals. The 

assessment included five tests measuring general cognition, verbal memory, and category 

fluency. The primary outcome was longitudinal change on a global composite score derived by 

averaging standardized scores across all five tests. 

The findings showed that there was essentially no difference in rates of cognitive decline 

between the two groups. Mean cognitive change over time was similar in the vitamin E group 

compared with the placebo group for the global score (mean difference in change = 0.00; 95 

percent CI -0.04 to 0.04). The relative risk of substantial decline in the global score in the 

vitamin E group compared with the placebo group was 0.92 (95 percent CI 0.77 to 1.10). 

(Relative risk < 1.0 means vitamin E was associated with lower risk of substantial decline). 

There were no statistically significant differences in cognitive change between the treatment and 

placebo group for the secondary outcomes of longitudinal performance on the individual 

cognitive tests. 

The second RCT391 examined the effect of micronutrient supplementation on maintenance of 

cognition. This was a secondary outcome of the MAVIS (Mineral And Vitamin Intervention 

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Study) trial, which was a large RCT of multivitamin and multimineral supplementation designed 

to assess possible effects on infection in men and women aged 65 years or over using a 

supplement containing 11 vitamins and 5 minerals. Participants were recruited from six primary 

care clinics in northeast Scotland. Participants had to have not taken vitamin, mineral, or fish oil 

supplements within 3 months of recruitment (1 month for supplements of water soluble vitamins 

other than vitamin B12). The cognitively impaired were not overtly excluded, although the 

authors noted that individuals with dementia were unlikely to volunteer to participate or would 

have been excluded by their physician. A total of 910 individuals enrolled in the study and were 

randomized. Over the 12-month study, the dropout rates were 12.7 percent for the treatment 

group and 17.6 percent for the placebo group. The treatment group daily took a multivitamin 

composed of 16 vitamins and minerals at one to two times the recommended daily allowance. 

The placebo group took a placebo pill on the same schedule. Compliance with taking the tablets 

was over 78 percent in both supplemented and placebo groups. The cognitive assessment 

included the Digit Span forward test and a phonemic verbal fluency measure. The tests were 

administered in person at the beginning of the study and then by telephone at the end of the 

study. 

The results of the study showed no differences in cognitive change between the treatment and 

the placebo groups, either in the groups as a whole or in analyses of the over age 75 subgroup or 

the subgroup at risk for micronutrient deficiency (as defined by self-report responses to a food 

frequency questionnaire). The different modes of test administration at baseline (in person) and 

the end of the study (telephone) may have increased the variability in performances over time, 

but this was unlikely to differ between treatment and placebo groups. 

The third RCT372 examined the association between vitamin E supplementation and decline 

on cognitive tests and other cognitive/functional outcomes over a 3-year period among 

individuals with amnestic MCI. These were secondary outcomes to the RCT described under 

Question 3; details of the study are described in that section. Every 6 months during the 3-year 

trial, a range of standard cognitive tests were completed in addition to the Clinical Dementia 

Rating scale, the Activities of Daily Living Scale, and the Global Deterioration Scale. Among 

the numerous outcomes assessed, there were few significant differences between the treatment 

and placebo groups. The significant differences were less decline in the vitamin E treatment 

group on measures of executive function (p < 0.05) and overall cognitive score at the 6-month 

assessment, and on language measures (p < 0.5) up through the 18-month assessment. No 

significant differences remained after 18 months. 

The fourth RCT393 examined the association between an antioxidant vitamin and cognitive 

decline over a 1-year period. Participants were recruited using advertisements in the United 

Kingdom. Inclusion criteria were age between 60 and 80 years; within two standard deviations of 

the normal weight for height, age and sex; no history of significant disease or mental illness; able 

to give informed consent; and capable of taking 80 ± 120 percent of the prescribed number of 

capsules during the run-in period. Exclusion criteria were: current medication likely to influence 

the outcome measures; use of vitamin supplements in the preceding 3 months; history of drug 

abuse, including alcohol; significant cardiovascular, respiratory, hepatic, renal, gastrointestinal, 

endocrine, neurological disease or abnormality; malabsorption syndrome; psychiatric disorder; 

subjects unable to give informed consent; disorders which would interfere with the 

understanding or compliance with the study, hypersensitivity to any of constituents in the active 

treatment; MMSE score < 18; participation in another drug clinical trial within the previous 6 

months; and subjects from whom blood samples could not be obtained. The exclusion criteria 

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would have excluded individuals with dementia of moderate or greater severity; however, it is 

possible that some individuals with mild dementia were included. There was a treatment and a 

placebo group. The treatment group took a vitamin containing 2 mg beta carotene, 400 mg alphatocopherol, and 500 mg ascorbic acid daily. No information was provided on whether the 

outcome assessors or the participants were blind to group assignment. A total of 205 subjects 

were randomized; 185 appeared to have completed all assessments, but few details were 

provided. Participants were assessed at baseline and at 4, 8, and 12 months thereafter. The 

cognitive assessment included measures of verbal memory, logical reasoning, attention, and 

reaction time. The analyses for the study did not adjust for baseline cognitive performance. The 

authors reported the number of significant findings on all cognitive measures did not exceed the 

number one would expect to find by chance (4/117 significant). The actual significance levels 

were not reported for any of the measures. 

The fifth and final RCT394 was a substudy of a larger ongoing RCT examining the effect of 

antioxidants and beta carotene on reduction of cardiovascular disease in female health 

professionals throughout the United States. Those included in the parent study were at least 40 

years of age, had at least three coronary disease risk factors, completed the run-in phase of the 

RCT adequately, were willing to forgo use of other vitamin supplements during the course of the 

study, and had no history of cancer, active liver disease, chronic kidney failure, or use of 

anticoagulants. The cognitive substudy was limited to participants in the parent RCT who were 

aged 65 years and older. No details were provided regarding the baseline cognitive status of 

participants, but since these individuals were part of an ongoing RCT for cardiovascular disease, 

one would predict that the vast majority were non-demented at baseline. This substudy included 

participants assigned to one of the treatment arms and a placebo group of the parent study. The 

intervention was three antioxidants: 420 mg vitamin E every other day, 500 mg vitamin C daily, 

and 50 mg beta carotene every other day. There were eight intervention groups that ranged from 

zero to three active vitamins. The time from randomization to the intervention and end of the 

trial was 8.9 years. The initial cognitive assessment was about 3.5 years after the start of the 

intervention, and assessments were then repeated about every 2 years for a total of four 

assessments. Cognitive function was measured using a telephone assessment protocol that 

included the TICS, an immediate and delayed verbal memory task, and a semantic fluency task. 

The primary outcome measures were: longitudinal change on a global composite score that was 

derived by combining scores from all cognitive tests; and longitudinal change on a memory 

composite score that was derived by combining the memory measures. 

Of the 3170 individuals meeting inclusion criteria for the substudy, 89 percent (2824) 

completed the first cognitive assessment. Ninety-one percent completed at least one followup 

assessment, and 81 percent completed at least three cognitive assessments. The number of 

participants who completed the 4th assessment was not given, but the study authors stated that 24 

percent of the sample was not contacted for the final followup assessment due to the short 

interval of time between the third cognitive assessment and the RCT end date. Participation rates 

did not differ by treatment group. Compliance with the treatment, defined as taking at least two 

thirds of the study pills, ranged from 64 to 68 percent and was comparable across all groups. The 

main independent variables were the various treatment arms (intervention versus placebo). The 

primary outcome was a global composite score averaging all scores; repeated-measures analyses 

were used to examine cognitive change over time. 

Results showed that vitamin E supplementation and beta carotene supplementation were not 

associated with slower rates of cognitive change (mean difference in change for vitamin E versus 

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placebo -0.01 standard unit; 95 percent CI -0.05 to 0.04; P = 0.78; for beta carotene, 0.03; -0.02 

to 0.07; P = 0.28). Although vitamin C supplementation was associated with better performance 

at the last assessment (mean difference 0.13; 95 percent CI 0.06 to 0.20; P=0.0005), it was not 

associated with cognitive change over time (mean difference in change 0.02; 95 percent CI -0.03 

to 0.07; P = 0.39). In secondary analyses, those taking at least one of the three antioxidant 

supplements (n = 2471) did not differ in cognitive change from baseline compared with those 

assigned to all placebos (n = 353); mean difference in cognitive change over time was 0.02 

standard units (95 percent CI -0.04 to 0.09; P = 0.64). A number of other secondary analyses 

were done to examine whether the results differed by various subgroups. One result from these 

secondary analyses was the finding that vitamin C supplementation was associated with better 

performance over time among those who developed cardiovascular events during followup 

(difference in change from baseline in global score for vitamin C group versus placebo 0.15; 95 

percent CI 0.04 to 0.26) compared to those who did not experience new cardiovascular events 

(difference in change 0.00; 95 percent CI, -0.05 to 0.05; P for interaction = 0.009). The authors 

of the study concluded that vitamin E, vitamin C, or beta carotene supplementation was not 

associated with less cognitive decline in women with cardiovascular disease or risk factors. 

In conclusion, the five included RCTs do not provide support for a beneficial effect of 

supplemental vitamin E, vitamin C, or a multivitamin on maintenance of cognitive function. 

Gingko biloba. We identified one RCT that examined the effect of gingko biloba on 

maintenance of cognitive function.395 Participants were recruited through mass mailings to 

individuals on public registry lists in Oregon. Inclusion criteria were: over 84 years of age; no 

subjective complaint of memory impairment compared to others of similar age; has not sought 

assessment for memory or cognitive dysfunction; normal memory based on performance on 

specific cognitive tests; functionally independent; not depressed; adequate vision and hearing to 

complete all testing; adequate English language skills to complete all testing; general health 

status that will not interfere with ability to complete longitudinal study; and informant available 

with frequent contact with subject to verify functional status. Exclusion criteria were: diseases 

associated with dementia or significant cognitive impairments, current alcohol or substance 

abuse, B12 deficiency, thyroid disease, or urinary tract infection. The trial lasted for 42 months. 

The treatment group took 80 mg of gingko biloba three times per day, and the placebo group 

took a placebo pill on the same schedule. All subjects also took a daily multivitamin with 40 IU 

of vitamin E. Two outcomes that were examined were incident mild cognitive decline, defined as 

progression from Clinical Dementia Rating Scale Score (CDR) = 0 to CDR = 0.5, and decline in 

memory function over time measured by performance on a verbal recall delayed memory task. 

A total of 134 participants were enrolled and randomized in the trial, of which 118 (88 

percent) met completion criteria and were included in the analyses. The dropout rate did not 

differ between the treatment and the placebo groups. The assessment included an in-person 

interview and cognitive status screening every 6 months and more comprehensive 

neuropsychological testing annually. The maximum number of assessments was seven. Overall, 

68.6 percent of participants met the definition of medication compliance, and the gingko biloba 

group (65.0 percent) did not differ from the placebo group (72.4 percent). 

The results showed that in the intention-to-treat analysis there was no reduced risk of 

progression to a CDR score of 0.5 (HR 0.43; 95 percent CI 0.17 to 1.08) in the gingko biloba 

group. There was also no less of a decline in memory function in the treatment group (coefficient 

[SE] 0.111 [0.057]; p = 0.055). In the secondary analysis that controlled for the medication 

adherence level, the gingko biloba group had a lower risk of progression from a CDR score of 0 

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to 0.5 (HR 0.33; 95 percent CI 0.12 to 0.89) and a smaller decline in memory scores (coefficient 

[SE] = 0.115 [0.057]; p = 0.047). The study authors noted that a larger RCT was needed to 

clarify whether gingko biloba was advantageous in deterring cognitive decline, especially among 

those compliant with the medication use. 

In conclusion, there is little evidence to support the use of gingko biloba to improve or 

maintain cognitive ability or function. 

Omega-3 fatty acids. We identified a single good quality systematic review evaluating the 

use of omega-3 fatty acids to improve or maintain cognitive ability or function.29 The authors 

searched for trials that addressed the specific association between any form of omega-3 fatty 

acids and cognitive decline in participants age 65 or older. Four trials were identified, but three 

were conducted in subjects with dementia or organic brain lesions. A single 26-week trial 

compared DHA-EPA 400 mg or 1800 mg versus placebo in adults age ≥ 65 with MMSE score 

> 21 at baseline.396 There was no statistically significant effect for any of the four cognitive 

domains evaluated. Four ongoing RCTs397-400 were identified evaluating the effects of omega-3 

fatty acids in mid-life to older adults without dementia. Study recruitment has been completed in 

three of the four studies, but results had not been published at the time of our search. 

Other fats. We identified no RCTs of other fats used to improve or maintain cognitive 

ability or function. 

Trace metals. We identified no RCTs assessing the relationship between trace metals and 

cognitive decline. We did identify one RCT391 that assessed the association between 

multivitamins (which included trace metals) and cognitive function; this study is described 

above, under “Other vitamins.” 

Mediterranean diet. We identified no RCTs of the Mediterranean diet used to improve or 

maintain cognitive ability or function. 

Intake of fruits and vegetables. We identified no RCTs assessing the relationship between 

fruit and vegetable intake and improvement or maintenance of cognitive ability or function. 

Total intake of calories, carbohydrates, fats, and proteins. We identified no RCTs 

evaluating the relationship between total intake of calories, carbohydrates, fats, and protein and 

improvement or maintenance of cognitive ability or function. 

Medical Factors 

Medications. Prescription and non-prescription drugs considered under this heading include 

statins, antihypertensives, anti-inflammatories, gonadal steroids, cholinesterase inhibitors, and 

memantine. 

Statins. A good quality systematic review examined the effects of two HMG-CoA reductase 

inhibitors (statins) on cognitive decline33 The review included two trials that randomized 

participants to a statin or placebo for the primary purpose of examining effects on cardiovascular 

events.401,402 Change in cognitive status and adverse events were secondary outcomes. The two 

trials randomized 26,340 adults from Western Europe, aged 40 to 82 years old, at elevated risk 

for vascular events. A summary estimate of effect was not computed because the cognitive 

outcomes and duration of followup varied significantly. Both studies were assessed overall as 

good quality. 

The Heart Protection Study401 (n = 20,536) excluded individuals with a history of dementia 

but did not assess cognition at baseline; a modified Telephone Interview for Cognitive Status 

(TICS-m) score below 22 of 39 was pre-specified as indicating cognitive impairment. 

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Participants were randomized to simvastatin (40 mg daily), a lipophilic statin, or matching 

placebo. Adherence was reported as 85 percent; 17 percent of the placebo group used a nonstudy statin. Mean duration of followup was 5 years, and the followup rate was high. The 

proportion of subjects with cognitive impairment at final followup did not differ between 

treatment (23.7 percent) and placebo groups (24.2 percent, p = not significant). The unadjusted 

difference in mean TICS-m scores did not differ significantly (24.08 simvastatin versus 24.06 

placebo; difference = 0.02 [SE 0.07]). Discontinuations due to adverse events were similar (4.8 

percent simvastatin versus 5.1 percent placebo). Key methodological limitations are the limited 

cognitive outcomes and the lack of a baseline cognitive assessment. 

The PROSPER study402 (n = 5806) excluded individuals with a MMSE < 24; changes in 

scores on four cognitive tests were reported. Participants were randomized to pravastatin (40 mg 

daily), a hydrophilic statin, or matching placebo. Adherence was reported as 94 percent; 10 

percent of the placebo group used a non-study statin. Mean duration of followup was 3.2 years; 

approximately 25 percent of participants in each group withdrew. Cognitive status – including 

global cognition, cognitive speed, and cognitive inhibition – was measured by MMSE, pictureword learning test, Stroop Color-Word Test, and a letter digit coding test. Changes in cognition 

adjusted for age, SBP, body mass index, alcohol use, concomitant drugs, Barthel Index score, 

Instrumental Activities of Daily Living (IADL) score, sex, smoking diabetes mellitus, vascular 

disease, country, and test version (if applicable) did not differ significantly for any of the 

cognitive assessments. Discontinuations due to adverse events were similar (3.7 percent 

pravastatin versus 3.98 percent placebo). However, new cancer diagnoses were higher for the 

pravastatin-treated group (HR 1.25; 95 percent CI 1.04 to 1.51). The study authors completed a 

meta-analysis of eight randomized placebo-controlled trials lasting at least 3 years which did not 

show an association between statin use and cancer (HR 1.02; 0.96 to 1.09). 

Our search did not identify any additional trials. In summary, two large RCTs conducted in 

mid- to late-life adults at high risk for vascular disease did not show an effect on cognitive 

function of statins taken for 3 to 5 years. 

Antihypertensives. A good quality Cochrane systematic review34 evaluated the effects of 

antihypertensive medications on cognitive impairment (CI) and dementia. In addition to the 

systematic review, we identified five additional manuscripts discussing several secondary 

analyses related to the trials in the included review, and two additional trial excluded from the 

review.273,374,375,403-406 

Included and discussed in the McGuiness review34 were three randomized, double blind, 

placebo-controlled trials whose subjects had a diagnosis of hypertension without clinical 

evidence of cerebrovascular disease: SCOPE,374 SHEP,375 and Syst-Eur.376 SCOPE randomized 

participants (who had an entry SBP of 160 to 179 mmHg or a DBP 90 to 99 mmHg or both) in a 

1:1 ratio to placebo or candesartan. There was a stepwise progression of medication changes 

based on blood pressure. SHEP included subjects with isolated systolic hypertension (SBP 160 to 

219 mmHg, DBP < 90 mmHg). Participants were randomized to placebo or chlorthalidone, with 

atenolol or reserpine added if necessary. Syst-Eur also enrolled subjects with isolated systolic 

hypertension. SBP was 160 to 219 mmHg at entry, with DBP <95 mmHg. Subjects were 

randomized to placebo, with medications added if SBP remained high, versus nitrendipine with 

addition of enalapril and/or hydrochlorothiazide. 

All studies in the systematic review had a significant number of control subjects taking active 

medication (84 percent in SCOPE, 27 percent in Syst-Eur during study, and 44 percent in 

SHEP). This treatment contamination would decrease differences between groups. Also in each 

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study, a minority of subjects was taking initially assigned medications (25 percent in SCOPE, 30 

percent in Syst-Eur, 30 percent in SHEP). All studies achieved a differential BP response, with 

lowered pressures in subjects assigned to active treatment (differences were SCOPE 3.2/1.6 

mmHg, SHEP 11.1/3.4 mmHg, and Syst-Eur 10.1/4.5 mmHg). Cognitive outcomes were 

secondary analyses in all three studies. Sample size calculations for cognitive decline were 

reported for SHEP but not SCOPE. Sample size calculations reported for Syst-Eur were for 

nonspecific dementia only. 

In the discussion that follows, we review the secondary analyses identified in our search. In 

SCOPE, for ethical reasons 84 percent of placebo patients received antihypertensive 

medications. One publication407 examined only those subjects without add-on therapy, a 

comparison that would be expected to amplify any observed treatment benefit. Change in MMSE 

scores did not differ between placebo and candesartan groups. 

Saxby et al.403 analyzed information from one site of the SCOPE study using a computerized 

test set to define cognitive decline. As in other sites and trials, there was considerable 

contamination of allocated groups. At this site, 81 percent of control subjects were on active 

antihypertensive by study’s end, while 68 percent of treatment group was off of assigned 

medications at study’s end. At the study’s close the average difference in BP was 8 mmHg/3 

mmHg. Small beneficial effects associated with antihypertensive use were seen on episodic 

memory and attention, but not on speed of cognition, working memory, or executive function. 

In SHEP, which included only patients with isolated systolic hypertension, use of add-on 

medications was common. Add-on medication was triggered by high blood pressure and was 

more common in the placebo than treatment groups, possibly biasing the results towards a null 

effect. There was no apparent protective effect of antihypertensives. Di Bari and colleagues408

also suggest that differential dropouts may have hidden a protective effect of antihypertensives. 

The Medical Research Council’s (MRC) trial405 was not included in the systematic review 

but met our eligibility criteria. This study randomized older adults in a 2:1:1 ratio to placebo, 

atenolol 50 mg, or hydrochlorothiazide 25 mg. Patients had SBP 160 to 209 mmHg and mean 

DBP < 115 mmHg during 8 weeks preceding randomization. The mean fall in SBP was 16.4 

mmHg in the placebo group, 30.9 mmHg in the atenolol group, and 33.5 mmHg in the 

hydrochlorothiazide group. A variable proportion of subjects in all treatment arms received 

additional medications: 20 percent of the hydrochlorothiazide group, 27 percent of the atenolol 

group, and 1.3 percent of the placebo group. Non-adherence to study medications was 

substantial; 43 percent of the hydrochlorothiazide group, 52 percent of the atenolol group, and 51 

percent of the placebo group were off of allocated treatment for at least part of the 54-month 

long trial. Cognitive outcomes were assessed using the paired associate learning test and the 

Trails Making Test, Part A (Trails A). There was no difference in cognitive outcomes based on 

group assignment. 

The PROGRESS study406 was excluded from the McGuinness systematic review34 because 

all subjects had a history of stroke or transient ischemic attack. There were no blood pressure 

requirements for inclusion. Subjects were randomly assigned to either active treatment with 

perindopril (plus indapamide if there was neither an indication for nor a contraindication to a 

diuretic) or a placebo. During the study, 22 percent of subjects discontinued study medication. 

Cognitive decline was defined by change in MMSE over a mean of 3.9 years of followup. Active 

treatment was associated with decreased risk for cognitive decline when decline was defined as a 

drop of ≥ 3 points on the MMSE (RR 0.81; 95 percent CI 0.68 to 0.96). Sensitivity analysis 

defining cognitive decline as ≥ 2 or ≥ 4 points did not “materially alter” the results. The mean 

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difference between randomized groups in decline in MMSE score (placebo minus active) was 

0.19 (0.07 SE), with less decline for active treatment (p = 0.01). 

In summary, participants in these trials had mean ages ranging from 70 to 77 years, except 

for the PROGRESS trial, where mean age at baseline was 64 years. For individuals with 

hypertension, antihypertensives were not demonstrably protective against cognitive decline over 

4.5 to 5 years. However, all studies had large amounts of treatment contamination and subjects 

lost to followup. A single trial in subjects with known vascular disease suggests possible benefit 

with antihypertensive treatment. 

Anti-inflammatories. We identified three randomized, placebo-controlled trials evaluating the 

effects of NSAIDs on cognitive decline. Two studies409,410 randomized 6244 subjects to 100 mg 

acetylsalicylic acid (ASA) daily or on alternate days versus placebo for 5 to 6 years. From the 

trial by Price et al.,409 only the cognitive change subset, which included 399 subjects, met our 

inclusion criteria. Within this subset, 24.8 percent of the aspirin group (n = 63) and 16.8 percent 

of the placebo group (n = 42) were lost to followup. Cognitive outcomes were assessed using a 

summary score from multiple measures of cognition. Over the 5-year followup, there was no 

statistically significant difference in cognition (adjusted mean difference 0.01; 95 percent CI -

0.07 to 0.09). 

The Women’s Health Study410 involved 5845 subjects who had completed at least two 

cognitive assessments. The authors analyzed this study as a cohort study within the context of an 

RCT. The trial was originally formed to examine the impact of aspirin on cardiovascular disease 

and cancer. In the aspirin and placebo groups, 79 and 80 percent of subjects, respectively, 

completed all three assessments. The cognitive cohort was started at a mean of 5.6 years after 

randomization, and only women 65 years of age and older were included. 

This study found a slower decline in verbal fluency in the aspirin group, but not an effect on 

the global summary score. Category fluency (number of animals named in a minute) had a mean 

of 17.76 (SE 0.10) for the aspirin group at third assessment, and a mean of 17.38 (0.10) for the 

placebo group at the same assessment; the mean difference between the two groups was 0.37 (95 

percent CI 0.10 to 0.65). The mean difference between aspirin and placebo groups for the global 

summary score at the third assessment was 0.00 (95 percent CI -0.04 to 0.04). 

The Alzheimer’s Disease Anti-inflammatory Prevention Trial (ADAPT)411 randomized 2528 

subjects to celecoxib 200 mg two times per day, naproxen 220 mg two times per day, or placebo. 

This 2-year study terminated early and had a high dropout rate and poor medication compliance. 

There was a suggestion of worsening with both active drugs. The global summary score was 

significantly worse only with naproxen. Actual time on drug, as reported by the subjects, 

averaged 1.50 years for celecoxib and 1.42 years for naproxen. 

In summary, there was no effect of low-dose aspirin on cognitive decline in these studies. 

There was worsening over time with naproxen versus placebo, but not celecoxib versus placebo, 

in the one RCT available. This study had a high dropout rate, and the actual time on drug was 

brief. There is no support in these studies for the use of NSAIDs to slow or prevent cognitive 

decline. As with the incident dementia analysis, the ADAPT study411 gives some concern for 

possible worsening of cognitive functioning, but the problems in the trial mitigate this concern. 

Gonadal steroids. We identified a single good quality systematic review that examined the 

effects of gonadal steroids on cognitive function.37 Studies were included if they were doubleblind RCTs that examined the effects of estrogen or estrogen plus progestin on cognitive 

function over a treatment period of at least 2 weeks in postmenopausal women. Twenty-four 

studies were included in the review, but only 16 had analyzable data (10,114 women). Eleven 

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studies were from the United States, seven from Europe, three from Canada, and one from 

Australia. Treatment duration ranged from 2 weeks to 5.4 years, and five studies had duration of 

greater than 1 year. The eight largest studies included postmenopausal women over the age of 65 

years. Eleven studies had comparable age and education status at baseline for the HRT and 

placebo groups, while four studies did not report education. The type of hormone therapy, dose, 

and mode of administration varied greatly across studies. 

The effect of HRT on the development of mild cognitive impairment (MCI) was examined in 

two studies. MCI was defined by a strict protocol with four phases of ascertainment, including 

performance on neuropsychological tests and clinical assessment. Odds ratios (ORs) were 

calculated using fixed-effect models for rates of cognitive impairment, and weighted mean 

differences (WMDs) were calculated for continuous data. Meta-analyses showed no statistically 

significant effect of estrogen or estrogen plus progestin on prevention of MCI (OR for MCI with 

estrogen after 5 years 1.34 [95 percent CI 0.95 to 1.9]; OR for MCI with estrogen plus progestin 

after 4 years 1.05 [95 percent CI 0.72 to 1.54]). Estrogen or estrogen plus progestin treatment did 

not maintain or improve cognitive function (estrogen WMD -0.45 [95 percent CI -0.99 to 0.09]; 

estrogen plus progestin WMD -0.16 [95 percent CI -0.58 to 0.26]). There was no significant 

statistical heterogeneity (I2 < 50 percent) in any of the analyses. No assessment of publication 

bias was performed. 

The effect of HRT on various cognitive domains was also examined. In one study, the 

immediate Paired Associate test, a test of verbal memory, showed a significant beneficial effect 

after 2 to 3 months of estrogen therapy, but other larger studies found that 4 to 5 years of HRT 

was associated with impaired verbal memory using the CVLT (total WMD -0.52 [95 percent CI 

-0.91 to -0.13]; short delay WMD -0.24 [95 percent CI -0.44 to -0.04]; and long delay WMD 

-0.23 [95 percent CI] -0.43 to -0.03). Removal of two studies with inadequate allocation 

concealment also resulted in a loss of statistical significance in the Paired Associate test. In most 

studies, HRT had no effect on visual memory, but women randomized to receive CEE plus MPA 

in a large study showed a small, but statistically significant benefit on the Benton Visual 

Retention Test (BVRT), a test of short-term figural memory and visuo-constructional abilities (a 

difference of -0.27 [95 percent CI -0.49 to -0.05] errors per year). The clinical significance of 

this small change is unknown. There was no evidence for benefit in verbal fluency, word list 

recall, Wechsler Memory scale tests, Boston Naming, or PMA Vocabulary. 

The review authors concluded that estrogen and combined estrogen plus progestin do not 

prevent cognitive decline in older postmenopausal women. Treatment with CEE plus MPA was 

associated with a small decrement in a number of verbal memory tests and a slight increase in 

figural memory. It is unknown whether HRT may benefit specific subgroups, such as younger 

women, women with different types of menopause (natural versus surgical), formulation, dose, 

or method of administration of HRT. 

We identified one RCT examining the effect of raloxifene, a selective estrogen receptor 

modulator (SERM), on cognitive change.39 This U.S.-based, double-blind, randomized, two-site, 

parallel-group, placebo-controlled study compared two doses of raloxifene (60 or 120 mg/day) to 

placebo on a battery of cognitive tests. One hundred and forty-three (143) postmenopausal 

women ranging in age from 45 to 75 years participated. Tests were derived from the Memory 

Assessment Clinics (MAC) computerized psychometric battery and the Walter Reed 

Performance Assessment Battery and were performed at baseline and at 1, 6, and 12 months. 

Study duration was 12 months. There were no differences in any cognitive measure following 1 

year treatment with 60 or 120 mg raloxifene.39

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Tierney et al. performed a 2-year randomized, double-blind, placebo-controlled trial of the 

effect of 1 mg 17-beta-estradiol and 0.35 mg norethindrone in 142 women between the ages of 

61 and 87.412 The primary outcome was short-delay verbal recall on the CVLT, and subjects 

were stratified by baseline performance on short-delay recall trial of the Rey Auditory Verbal 

Learning Test (RVLT). Women who scored at or above average on baseline RVLT showed 

significantly less decline on CVLT at 1 (p = 0.007) and 2 years (p = 0.01) than women who 

received placebo. There was no treatment effect in women who scored below average on RVLT 

at either year, suggesting that any benefit of estrogen on cognitive function may be limited to 

women with average or above average memory at baseline. 

We also identified one good quality systematic review that examined the effect of 

dehydroepiandosterone (DHEA) supplementation on cognitive function.36 Studies were included 

if subjects received DHEA or DHEA sulfate for any duration and were assessed by a valid 

neuropsychometric measure. The review included six studies; three from the United States and 

three from European countries (264 women and 281 men). Four studies included cognitive 

measures, while two had quality-of-life measures without cognitive testing. The age range of 

subjects was 44 to 85 years, and the duration for studies with cognitive measures ranged from 2 

weeks to 1 year. Bias was assessed and described. DHEA 50 mg or placebo was administered 

daily, and outcomes were change in neuropsychometric test results. 

No consistent benefit of DHEA supplementation on cognitive function was identified. The 

authors concluded that although the evidence is limited, controlled trials do not support a 

beneficial effect of DHEA supplementation on cognitive function in non-demented middle-aged 

or elderly people. 

We identified one additional eligible United States-based study of DHEA on cognitive 

function involving administration of 50 mg DHEA to 225 cognitively normal subjects (aged 55 

to 85 years) for 1 year.413 This double-blind RCT measured cognitive function at baseline and 12 

months using a battery of tests including the 3MS, word list memory and recall, Trail Making 

Part B, category fluency, and modified Boston Naming Test. The authors found no benefit in 

cognitive performance from treatment with DHEA. 

The combined data do not support a benefit of 50 mg DHEA on cognition. No data are 

available on whether regular administration of DHEA has an effect on development of AD. 

In summary, as described under Key Questions 1 and 2, respectively, some cohort studies of 

estrogen treatment suggest a decreased incidence of AD and, for symptomatic post-menopausal 

women, decreased cognitive decline. Double-blind, RCTs trials of estrogen, however, have not 

demonstrated a protective effect in preventing dementia or cognitive decline. Use of CEE plus 

MPA may increase the risk of dementia in postmenopausal women. In studies administering a 

battery of cognitive tests there is no consistent evidence for the benefit of routine administration 

of estrogen in any cognitive domain. Limited evidence suggests that there is also no beneficial 

effect of raloxifene, a SERM, or DHEA on cognitive function. There is insufficient evidence to 

determine whether other groups may benefit from estrogen treatment, such as women < 60 years 

of age; when to begin treatment; or whether effects differ in women who have natural versus 

surgical menopause. Other remaining questions about the effect of gonadal steroids on cognitive 

function include the type of estrogen or SERM used, whether it is supplemented with a 

progestin, the duration of therapy, and whether different modes of delivery would alter efficacy. 

Cholinesterase inhibitors. We identified one good quality systematic review that examined 

the effects of cholinesterase inhibitors on the progression to dementia or AD and included as 

secondary outcomes, effects on cognitive testing.44 The review included eight RCTs (4127 

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subjects). Four were multi-site studies in North America or the United States; one was a multisite study in North America and Western Europe; one was a small, single-site U.S. study; and 

two did not report location. RCTs were selected that compared a cholinesterase inhibitor 

(donezpezil, galantamine, rivastigmine) to placebo control in participants with abnormal memory 

function and/or who met diagnostic criteria for mild cognitive impairment (MCI); individuals 

with dementia were excluded. Only English-language studies and studies presenting original data 

were included. Study quality was assessed using the Jadad criteria and was judged to be low to 

medium. Only one trial adequately described the randomization process; four followed an 

intention-to-treat principle for analysis; loss to followup was substantial and greater for 

intervention than control subjects; and in all but one study, multiple secondary outcome 

measures were evaluated without correction for multiple comparisons. Formal tests for 

publication bias (e.g., funnel plot) were not performed, but three completed studies382-384

identified at ClinicalTrials.gov have not reported results, suggesting possible publication bias. 

One was a 16-week industry-sponsored study of rivastigmine that was terminated early in 

2004.384 The second was a 1-year National Institute of Mental Health (NIMH)-sponsored study 

of donepezil and gingko biloba extract completed in 2004.383 Finally, the third was a 1-year, 

industry-sponsored study of donepezil in subjects with MCI completed in March 2007.382 All 

three studies planned assessment of cognitive outcomes. 

Of the eight identified trials, six (described in five publications385-387,414,415) reported effects 

on measures of cognition, activities of daily living, or neuropsychiatric symptoms. 

Cholinesterase inhibitors evaluated were donepezil 10 mg daily (two studies), rivastigmine 3 to 

12 mg daily, and galantamine 16 or 24 mg daily (three studies). The number of subjects ranged 

from 19 to 1062. The two smaller studies followed subjects for ≤ 6 months, while the large 

studies followed subjects for 2 to 4 years. Participants were aged ≥ 50 years; race was reported in 

three studies (described in two publications386,415), and over 90 percent of subjects were white. A 

total of 36 different scales, tests, and neuropsychological batteries and two measures of 

volumetric imaging were used. The authors of the systematic review did not compute a summary 

estimate of effect due to important heterogeneity in the definition of MCI and the variability in 

outcome measures. Point estimates and 95 percent confidence intervals were reported for the 18 

outcomes for which specific results from the original studies were reported. One small study414

was excluded from analyses because results were only reported for 10 subjects and were not 

based on intention-to-treat analyses. 

For the 18 outcomes reported, statistically significant differences favoring treatment were 

seen in individual studies only for the rate of brain volume atrophy by MRI (mean difference 

0.21; 95 percent CI 0.14 to 0.27);386 a measure of global cognition, the CDR-Sum of boxes 

(mean difference 0.2; 95 percent CI 0.0 to 0.4);386 and the cognitive functions evaluated by the 

ADAS-Cog 13 (mean difference 1.9; 95 percent CI 0.5 to 3.3).415 After correcting for multiple 

comparisons with Bonferroni methods, only the difference in rate of brain atrophy remained 

statistically significant. Treatment discontinuation due to adverse events was significantly higher 

for intervention subjects, ranging from 21 to 24 percent, compared to 7 to 13 percent in control 

subjects. 

We identified two additional RCTs comparing 1 year of treatment with donepezil to 

placebo.416,417 Doody and colleagues evaluated donepezil in subjects with amnestic MCI.416

Amnestic MCI is of particular interest because it progresses to AD more commonly then general 

MCI. This U.S.-based, multi-center, industry sponsored study randomized 821 adults aged 45 to 

90 to donepezil 5 mg daily for 6 weeks, then 10 mg daily for 42 weeks or placebo. Participants 

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were mostly male (54 percent), mostly white (87 percent), and had a memory complaint 

corroborated by an informant, along with neuropsychological testing consistent with amnestic 

MCI (see the evidence table in Appendix B for details). Individuals with medical conditions 

(e.g., neurological, psychiatric) that could affect cognition, who had taken a cholinesterase 

inhibitor for > 1 month, or who were taking a concomitant anticonvulsant, anti-Parkinsonian 

drug, stimulant, or drug with anticholinergic or procholinergic effects, were excluded. The 

followup rate (60.8 percent of those randomized) was low, with fewer subjects in the 

intervention group completing 48-week followup. The primary efficacy measures were the 

ADAS-Cog (range 0 to 70), a measure of cognition, and the CDR-SB (range 0 to 18), a measure 

of global function. Investigators pre-specified statistically significant differences on both 

measures to conclude treatment benefit. At 48 weeks, intervention subjects showed greater 

improvement from baseline than did control subjects on the ADAS-Cog (mean difference -0.9; 

SE 0.37; p = 0.01), but no significant difference on the CDR-SB (mean difference not given). Of 

eight secondary measures, donepezil-treated patients showed statistically significant benefit on 

two. More subjects assigned to donepezil (n = 72, 18.4 percent) than placebo (n = 32, 8.3 

percent) discontinued treatment due to adverse effects. 

Yesavage et al.417 compared donepezil 5 mg daily for 6 weeks, and then 10 mg daily for 46 

weeks, to placebo in 168 adults aged 55 to 90. At study weeks 13 and 14, all subjects received 

cognitive training consisting of 10 separate 2-hour sessions that taught visualization and 

mnemonic techniques. Participants were 65 years old on average, male (48 percent), in good 

general health, and had MCI (29 percent) or non-impaired cognitive functioning. Randomization 

and allocation concealment were adequate. Patients, providers, and outcome assessors were blind 

to intervention status, but followup rates were not reported. Analyses were conducted with 

random regression models using the intention-to-treat principle; funding was from the NIMH and 

VA. 

For the primary cognitive outcomes (word list recall, name-face recall), there were no 

significant between-group differences at any of the three followup time points. Similarly, there 

were no significant between-group differences for secondary outcomes: symbol digit, digit span, 

quality of life, and functional status. More subjects treated with donepezil dropped out within the 

first 12 weeks (15 of 83 versus 6 of 85), or experienced muscle cramps (19 versus 1) or insomnia 

(18 versus 8; p < 0.05 for all comparisons). 

In summary, a systematic review found six low- to medium-quality trials reporting the effects 

of cholinesterase inhibitors on cognition in subjects with MCI; three other studies have not 

reported outcomes. We identified two additional donepezil trials that did not show treatment 

benefit on the primary cognitive outcomes at 1 year, but did show greater dropouts with 

treatment. In aggregate, over 5000 subjects have participated in these trials, but no consistent 

positive effects have been demonstrated. Treatment discontinuations due to adverse effects are 

consistently higher in the cholinesterase inhibitor-treated groups. 

Memantine. We did not identify any systematic reviews or primary studies that evaluated the 

effects of memantine on cognitive testing in subjects who were cognitively normal or had mild 

cognitive impairment. 

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Social, Economic, and Behavioral Factors 

Social engagement. No good quality systematic reviews or RCTs were identified that 

evaluated a social engagement intervention to improve or maintain cognitive ability or function. 

Cognitive engagement. Our review identified three reports from the Advanced Cognitive 

Training for Independent and Vital Elderly (ACTIVE) trial that examined the effects of cognitive 

training on improving long-term cognitive performance.418-420 In the ACTIVE trial, participants 

were randomized to one of three cognitive treatment groups (memory training, reasoning 

training, or speed of processing training) or the control group with no contact. Participants in the 

treatment groups attended 10 sessions over a 5- to 6-week period. A randomly selected 

subsample of 60 percent of each treatment group received four sessions (over a 2- to 3-week 

period) of booster training at 11 months and then again at 35 months after the initial training 

sessions. Primary outcomes were performance on cognitive measures and functional 

performance in daily activities. 

Individuals were recruited from senior housing, community centers, hospitals, and medical 

clinics in six cities in the United States. Participants had to be over age 65 years, living 

independently, and able to perform their activities of daily living (ADLs) independently. 

Excluded individuals had an MMSE score < 22 points; reported a diagnosis of AD; reported 

substantial functional decline; reported having a medical condition that could predispose them to 

severe functional decline or death; had severe loss of vision, hearing, or ability to communicate; 

had recently participated in another cognitive training study; or planned to move out of the area 

during the time course of the trial. A total of 2802 individuals were enrolled and appropriately 

randomized. Dependent variables were measured at baseline, immediately post-treatment, and 

then at 1, 2, and 5 years post-treatment. Eighty-nine percent of participants completed at least 

eight training sessions. 

The mean age of the sample was 73.6 (5.9) years. Comparisons of baseline characteristics 

among intervention and control groups were reported. Followup rates were 80 percent at 2 years 

and 63 percent at 5 years. Although participants who did not complete all 5 years of data 

collection were more likely to be older, male, have less education and more health problems, and 

have lower cognitive function on baseline measures, there were no significant interactions 

between treatment group and these variables. 

Each intervention group showed improvement in the targeted cognitive ability compared 

with baseline, and the effect was still evident at 2 years post-intervention (memory: effect size 

0.17; p < 0.001; reasoning: effect size 0.26; p < 0.001; speed of processing: effect size 0.87; p 

< 0.001).420 Booster training increased training gains in speed (p = 0.001) and reasoning (p = 

0.001) interventions at both the 1-year and the 2-year followup. One of the outcome measures 

was an estimate of reliable change. At the 2-year followup, only the speed of processing training 

group showed marked differences in this outcome, with 79 percent of the booster speed 

processing group showing reliable change, compared to 65 percent of the no booster group and 

37 percent of the control group. No training effects were observed on everyday functioning at the 

2-year followup. 

At the 5-year followup,418 each intervention group maintained positive effects on its specific 

targeted cognitive ability (memory: effect size 0.23 [99 percent CI 0.11 to 0.35]; reasoning: 

effect size 0.26 [99 percent CI 0.17 to 0.35]; speed of processing: effect size 0.76 [99 percent CI 

0.62 to 0.90]). Booster training on the targeted ability produced additional improvement for 

reasoning performance (effect size 0.28; 99 percent CI 0.12 to 0.43) and for speed of processing 

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performance (effect size 0.85; 99 percent CI 0.61 to 1.09). The booster training for the speed of 

processing group, but not for the other two groups, showed a significant effect on the 

performance-based functional measure of everyday speed of processing (effect size 0.30; 99 

percent CI 0.08 to0.52). 

A third report on the ACTIVE trial419 assessed whether a subgroup of individuals classified 

as memory impaired showed as much improvement on cognitive measures after training as the 

remainder of the group who were not memory impaired. Individuals scoring ≥ 1.5 standard 

deviations below their expected score on a verbal memory test at baseline were considered to be 

memory impaired (n = 193). Results indicated that memory-impaired participants failed to 

benefit from memory training, but did show normal training gains after reasoning (effect size 

0.28; p < 0.05) and speed training (effect size -0.76; p < 0.001). The study authors concluded that 

memory function mediates the response to some forms of cognitive training. 

Our search did not identify any additional trials. In summary, one large cognitive training 

trial has shown modest long-term benefits from cognitive training over a 5- to 6-week period 

with subsequent periodic booster training. Overall, the smallest effect is shown on the tasks of 

verbal declarative memory. 

Physical activities. We identified one good quality systematic review examining the 

association of physical activity interventions on cognitive change over time.48 This review 

identified 11 eligible RCTs with participants that met the following criteria: aged 55 or older, 

not demented due to any reason, not recovering from surgery, and did not have comorbidities 

that precluded them from participation in physical exercise programs. Acceptable physical 

activity interventions were any form of exercise of any intensity, duration, or frequency that was 

aimed at improving cardiorespiratory fitness. The studies identified in this review had a followup 

period of no greater than 6 months, and the majority lasted 4 months or less. There were no 

studies identified examining the longer term effects of physical activity on cognition. 

The authors of the review reported that 8 of the 11 eligible studies showed an improvement 

in at least one aspect of cognitive function, but the domains of cognitive function that improved 

were not the same in each study, and the majority of comparisons yielded no significant results. 

Thus, the review authors concluded that there were insufficient data to state that aerobic physical 

activity improves cognitive function. 

Our own review identified one eligible RCT that examined the effect of physical activity on 

improving or maintaining long-term cognitive performance.421 Participants were randomized to 

an education and usual care group or to a 24-week home-based program of physical activity. The 

primary outcome was change in the Alzheimer Disease Assessment Scale-Cognitive Subscale 

(ADAS-Cog) scores over 18 months. Individuals were recruited from a number of sources, 

including two memory clinics and the general community, using advertisements in the local 

media in Perth, Australia. Participants had to be over age 50 years and had to have responded 

“yes” to the question, “Do you have any difficulty with your memory?” Individuals excluded had 

scores lower than 19 of 50 on the TICS-m (a score consistent with significant cognitive 

impairment or dementia); had a Geriatric Depression Scale-15 score of 6 or higher; reported 

drinking more than four standard units of alcohol a day; had a chronic mental illness, such as 

schizophrenia; had medical conditions likely to compromise survival, such as metastatic cancer, 

or render them unable to do in physical activity, such as severe cardiac failure; or had severe 

sensory impairment or lack of fluency in written or spoken English. Additional exclusion criteria 

were a diagnosis of dementia, an MMSE score < 24, a Clinical Dementia Rating ≥ 1, and 

inability to walk for 6 minutes without assistance. 

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The aim of the physical activity intervention was to have participants engage in moderate 

intensity physical activity for at least 150 minutes per week, to be completed in three 50-minute 

sessions. Participants recorded the details of their physical activities in a diary. To enhance 

compliance with the program, participants were also given a modified behavioral intervention 

package based on social cognitive theory. Participants in the usual care control group received 

educational material about memory loss, stress management, healthful diet, alcohol consumption, 

and smoking, but not about physical activity. Participants in the physical activity group were also 

offered these educational materials.

A total of 170 individuals were enrolled and appropriately randomized. Outcomes were 

measured at baseline, and then at 6, 12, and 18 months after baseline. A total of 81.2 percent of 

the participants completed the trial. Adherence to the prescribed physical activity for the 24 

weeks was 78.2 percent. The mean age of the sample was 68.6 (8.7) for the exercise group and 

68.7 (8.5) for the control group. Baseline characteristics were reported for the intervention and 

control groups, but statistical comparisons were not reported. The values reported in Table 1 of 

the manuscript suggest that the control group may have had higher frequency of moderately 

intense physical activity at baseline, but without a statistical comparison that cannot be 

confirmed. Women were more likely than men to drop out in both groups, and those who 

dropped out had higher ADAS-Cog scores than those who remained in the trial. 

At the 6-month point, the physical activity group showed a decline of -0.26 (95 percent CI 

-0.89 to 0.54) points on the ADAS-Cog (lower scores indicate better performance), and the 

control group showed an increase of 1.04 (0.32 to 1.82) points on this measure. At the 18-month 

followup, the difference between the two groups had diminished, with the treatment group 

showing a decline on the ADAS-Cog of -0.73 (-1.27 to 0.03) points, and the control group 

showing a decrease of -0.04 (-0.46 to 0.88). The repeated measures ANCOVA across the 6-, 12-, 

and 18-month followups showed statistically significant less decline in the intervention group (p 

= 0.04). Analyses on secondary outcomes showed differences on the delayed word list task, with 

the physical activity group showing an increase of 0.45 (0.03 to 0.87) points compared to the 

control groups increase of 0.38 (-0.01 to 0.77) points at the 6-month followup. This pattern of 

differences continued at the 18-month followup, with the physical activity group showing an 

increase of 0.76 (0.41 to 1.10) points, and the control group showing a decrease of -0.02 (-0.36 to 

0.32) points (p = 0.02 for ANCOVA for repeated measures across the three time points). There 

were no statistically significant differences on the other cognitive measures. Similar differences 

were seen on the ADAS-Cog when the analyses were limited to individuals categorized as 

having mild cognitive impairment. When considering only those individuals who completed all 

assessments, the physical activity group showed more improvement or maintenance of cognition 

on the ADAS-Cog (p = 0.009 for ANCOVA for repeated measures across the three time points), 

the delayed word list (p = 0.01), and the Clinical Dementia Rating scale (CDR) (p = 0.003). 

In summary, this RCT found a modest, but positive effect of physical activity on one 

relatively comprehensive cognitive measure (ADAS-Cog) and also on a delayed recall task over 

an 18-month period, that is, 1 year post-intervention. The participants were individuals who 

confirmed having problems with their memory, and in fact some met criteria for a diagnosis of 

mild cognitive impairment, suggesting that the individuals were likely at increased risk for 

cognitive decline. Thus, relatively greater preservation of cognition associated with physical 

activity in this group may be particularly meaningful. Furthermore, the study authors noted that 

the effect associated with physical activity was comparable to or better than the results from 

some of the medication treatment trials. 

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Other leisure activities. We did not identify any good quality systematic reviews or RCTs 

that assessed the effects of non-cognitive, non-physical leisure activities for preserving cognitive 

ability. 

Nicotine. We did not identify any good quality systematic reviews or RCTs that evaluated 

the effects nicotine for preserving cognitive ability. 

Key Question 5 – Relationships Between Factors Affecting 

Alzheimer’s Disease and Cognitive Decline 

 Key Question 5 is: What are the relationships between the factors that affect Alzheimer’s 

disease and the factors that affect cognitive decline? 

Introduction 

Concordance for factors affecting cognitive decline and Alzheimer’s disease has a number of 

potential implications. A consistent body of evidence increases our confidence in the observed 

association. It is also consistent with the proposed analytic framework that the symptoms of AD 

begin with insidious cognitive decline that progress to more marked cognitive and functional 

impairment. Finding consistent evidence for cognitive decline and AD would reinforce the 

potential effectiveness of early interventions that could diminish both the risk of cognitive 

decline and AD. Discordant findings weaken our confidence in the association, but may simply 

reflect the heterogeneity of the etiology of cognitive decline; that is, cognitive decline may be 

due to normal aging mechanisms or the prodromal stage of other types of dementing disorders 

such as vascular or frontal lobe dementia. To address this question, we used the results from Key 

Questions 1 through 4 to compare the evidence for the effects of each exposure on risk of AD 

and cognitive decline. For factors with both randomized controlled trial (RCT) and observational 

evidence, we first compared the consistency of findings across study designs for each outcome. 

RCTs are a stronger design than observational studies and were prioritized when there were 

high-quality studies that used robust outcome measures. When studies showed a consistent effect 

on risk that was in the same direction for both AD and cognitive decline, we judged the results 

concordant. For many factors, the available data are quite limited, and concordant evidence 

across outcomes should not necessarily be interpreted as a robust finding. 

Nutritional and Dietary Factors 

These factors include vitamins, diet composition, and gingko biloba. In Table 70 we 

summarize the number of studies and subjects and provide a qualitative summary of the 

association. 

Concordant evidence. Concordant evidence for these factors was as follows:

• Increased risk with higher exposure: None. 

• No consistent association with risk: Beta carotene, flavonoids, gingko biloba, 

multivitamins, vitamin B12, vitamin C, and vitamin E. 

• Decreased risk with higher exposure: Mediterranean diet (limited evidence). 

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285

Discordant evidence. In observational studies, folic acid was associated with decreased risk 

for AD, but this association was not consistent for cognitive decline. RCTs did not show a 

protective effect for folic acid. In observational studies, omega-3 fatty acids were associated with 

less risk for cognitive decline but not a decreased risk for AD. No RCTs of at least a year’s 

duration have been conducted for omega-3 fatty acids. 

Concordance not determined. For some factors, concordance was not determined because 

of the lack of evidence for both AD and cognitive decline, namely: diet composition, trace 

metals, vitamin B3 (niacin), and vitamin B6 (pyridoxine). For fruit and vegetable consumption, 

we made the judgment that the exposures were not comparable across outcomes and 

concordance could not be determined. Preliminary evidence suggests that saturated fat intake 

may be associated with AD and cognitive decline, but the evidence was considered too limited to 

judge concordance.
Table 70. Summary of evidence for association between nutritional factors and AD or cognitive decline 

Exposure B vitamins Vitamins C and E, betacarotene Gingko biloba Omega-3 fatty acids 

Design Cohort RCT Cohort RCT Cohort RCT Cohort RCT Studies (subjects) 

5 None 12 1 

(769) 

None 1 

(3069) 

9 (24,980) 

None 

(5927) (19,874) 

Association with AD* 

Folic acid: Decreased risk B12: No consistent association 

- No 

consistent association 

Vitamin E: No association 

- No 

association 

No consistent association 

- 

Studies (subjects) 

5 (5927) 

2 (2440) 

8 (11,033) 

Vitamin E: 4 (10,473) Multivitamin: 1 (910) 

- 1 

(134) 

5 (12,392) 

1 (302) 

Association with cognitive decline* 

Folic acid, B6, B12, niacin: No consistent association 

Folic acid, B6, B12: No consistent association 

No association 

Vitamin E and multivitamin: No association 

- No 

association 

Possibly decreased risk 

No association 

Concordance/ discordance for AD and cognitive decline outcomes 

B12: Concordant for no association Folic acid: Discordant B6 and niacin: Both outcomes not studied 

Concordant for no association, but limited evidence for betacarotene, flavonoids and multivitamins 

Concordant for no association, but limited evidence 

Discordant. Exposure definitions variable; duration of RCT only 6 months 

Abbreviations: AD = Alzheimer’s disease; RCT = randomized controlled trial 

*Direction of risk for higher exposure (intake) and AD or cognitive decline.

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Medical Factors 

Vascular, other medical, and psychological and emotional health. These factors include 

diabetes mellitus, metabolic syndrome, hypertension, hyperlipidemia, homocysteine, sleep 

apnea, obesity, traumatic brain injury, and depressive and anxiety disorders. In Table 71 we 

summarize the number of studies and subjects and provide a qualitative summary of the 

association. 

Concordant evidence. Concordant evidence for these factors was as follows: 

• Increased risk with higher exposure: Diabetes mellitus, depressive disorders (although 

evidence less consistent for cognitive decline). 

• No consistent association with risk: Hypertension, homocysteine, obesity. 

Discordant evidence. In observational studies, metabolic syndrome was associated with 

increased risk for cognitive decline in the young-old, but was not associated with risk for AD. 

Hyperlipidemia was associated with AD in mid- but not late-life and did not show a consistent 

association with cognitive decline. 

Concordance not determined. For some factors, concordance was not determined because of 

the lack of evidence for both AD and cognitive decline, namely: anxiety disorders and traumatic 

brain injury. There were no studies for sleep apnea or resiliency. 

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Table 71. Summary of evidence for association between medical factors and AD or cognitive decline 

Exposure Diabetes 

mellitus 

Metabolic 

syndrome 

Hyperlipidemia Homocysteine Hypertension Obesity 

Studies (subjects) 

13 (> 100,000) 

2 (5603) 

8 (14,331) 

4 (2662) 

11 (18,793) 

7 (21,577) 

Association with AD* 

Increased No Midlife: 

Increased Late-life: No 

No No consistent 

association 

No association 

Studies (subjects) 

12 (47,629) 

4 (5713) 

5 (20,184) 

5 (3409) 

19 (>43,000) 

3 (8475) 

Association with cognitive decline* 

Possibly increased risk 

Increased risk, except for age > 85 years 

No consistent association 

No consistent association 

MCI: No association Global: No association Processing speed: No consistent association 

No consistent association 

Concordance/ discordance for AD and cognitive decline outcomes 

Concordant, increased risk 

Discordant but limited evidence 

Discordant Concordant, but 

heterogeneity in how exposure defined 

Concordant, no association Heterogeneous studies 

Concordant, no association 

Abbreviations: AD = Alzheimer’s disease; MCI = mild cognitive impairment *Direction of risk for higher exposure and AD or cognitive decline. 

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Prescription and non-prescription medications. These factors include HMG-CoA 

reductase inhibitors (statins), antihypertension medications, non-steroidal anti-inflammatory 

medications (NSAIDs), gonadal steroids (estrogens, raloxifene, dehydroepiandosterone), and 

cholinesterase inhibitors. In Table 72 we summarize the number of studies and subjects and a 

qualitative summary of the association. 

Concordant evidence. Concordant evidence for these factors was as follows: 

• Increased risk with higher exposure: None 

• No consistent association with risk or rate of cognitive decline: Cholinesterase inhibitors, 

estrogens 

Discordant evidence. Observational studies suggest that statins decrease risk for AD, but 

observational and trial data do not show a consistent benefit for cognitive decline. Treatment 

with antihypertensive medication may decrease risk for AD, but no protective effect was found 

for cognitive decline. These studies are limited by the absence of trial data for AD, and by data 

from a trial for cognitive decline that used an outcome measure that is relatively insensitive to 

change. In observational studies, exposure to NSAIDs were possibly associated with decreased 

risk for AD and cognitive decline, but RCTs support an increased risk for AD and no consistent 

association for cognitive decline. 

Concordance not determined. For some factors, concordance was not determined because of 

the lack of evidence for both AD and cognitive decline, namely: raloxifene and 

dehydroepiandosterone. There were no studies for memantine.

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Table 72. Summary of evidence for association between medications and AD or cognitive decline 

Exposure HMG-CoA reductase 

inhibitors (statins) 

Anti-hypertensive 

medication 

NSAIDs Gonadal steroids 

Design Cohort RCT Cohort RCT Cohort RCT Cohort RCT Studies (subjects) 

6 (17,840) 

None 8 

(19,7373) 

5 (20,563) 

8 (24,275) 

2 (3985) 

2 (1596) 

2 (7479) 

Association with AD* 

Decreased risk 

Probably 

decreased risk 

No association for dementia (not specifically AD) 

No consistent association 

Increased risk 

Decreased risk 

CEE: No association CEE + MPA: Increased risk 

Studies (subjects) 

4 (6827) 

2 (26,340) 

2 (3599) 

4 (14,107) 

6 (33,600) 

3 (8972) 

9 (16,294) 

CEE: 18 (10,256) Raloxifene: 1 (143) DHEA: 7 (770) 

Association with cognitive decline* 

Inconsistent association 

No association 

No association 

Inconsistent association 

No association; Possibly decreased risk in some subgroups 

Aspirin: No association Naproxen: Increased risk Celecoxib: No association 

No association, except decreased risk in symptomatic postmenopausal women 

CEE: No association Raloxifene: No association DHEA: No association 

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291

Exposure HMG-CoA reductase 

inhibitors (statins) 

Anti-hypertensive 

medication 

NSAIDs Gonadal steroids 

Design Cohort RCT Cohort RCT Cohort RCT Cohort RCT Concordance/ discordance for AD and cognitive decline outcomes 

Discordant Discordant. 

General dementia but not AD evaluated in RCTs 

Concordant 

across outcomes but inconsistent across study designs 

CEE: 

Concordant 

for no 

association 

DHEA, raloxifen, CEE + MPA: Both outcomes not studied 

Abbreviations: AD = Alzheimer’s disease; CEE = conjugated equine estrogen; DHEA = dehydroepiandosterone; HMG-CoA = 3-hydroxy-3-methylgl

medroxyprogesterone; NSAIDs = non-steroidal anti-inflammatory drugs; RCT = randomized controlled trial *Direction of risk for higher exposure (intake) and AD or cognitive decline 
Social, Economic, and Behavioral Factors 

These factors include early childhood factors, education and occupation, social engagement, 

cognitive engagement, physical activities, other leisure activities, smoking, and alcohol use. In 

Table 73 we summarize the number of studies and subjects and a qualitative summary of the 

association. 

Concordant evidence. Concordant evidence for these factors was as follows:

• Increased risk with higher exposure: tobacco. 

• No consistent association with risk of AD or rate of cognitive decline: early childhood 

socioeconomic environment (limited data). 

• Decreased risk with higher exposure: 

o Observational studies show that greater cognitive engagement (imprecise 

measures of exposure) decrease risk of AD and cognitive decline. Observational 

studies are limited by imprecise and variable measures of exposure; the effect of 

cognitive training on cognitive decline has been evaluated in a single RCT. 

o Greater physical activity in late adult life is associated with decreased risk of AD 

and less cognitive decline, but conclusions are limited by imprecise measures of 

exposure, variable measures of cognitive decline, and a single small RCT. 

Discordant evidence. Light to moderate alcohol intake is associated with a decreased risk of 

AD, and lower educational level is associated with an increased risk of AD; neither shows a 

consistent association with cognitive decline. 

Concordance not determined. For some factors, concordance was not determined because 

of the lack of evidence for both AD and cognitive decline, namely: physical activity during midadult life. For marital status, data are insufficient to determine concordance. Occupation 

exposure, social support, and social network were defined too heterogeneously both within and 

between the studies for AD and cognitive decline to determine concordance. Other leisure 

activities are not consistently associated with AD but probably decrease the risk of cognitive 

decline; again, definition of exposure varied substantially between studies, leading us to 

conclude that the evidence is insufficient to determine concordance. 

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Table 73. Summary of evidence for association between social/economic/behavioral factors and AD or cognitive decline 

Exposure Childhood 

exposures 

Education/ 

occupation 

Social 

engagement 

Other 

leisure 

activities 

Alcohol Tobacco Physical activity in late 

adults 

Design Cohort Cohort Cohort Cohort Cohort Cohort Cohort RCT Studies (subjects) 

1 (859) 

Education: 11 (25196) Occupation: 5 (6029) 

Marital status: 3 (6699) Social network: 1 (1473) 

2 6 12 12 None 

(7464) (14,646) (21,718) (25,603) 

Social support: 2 (4365) 

Association with AD* 

No association 

Education: Decreased risk 

Never married: Increased risk 

Inconsistent association 

Decreased risk 

Increased risk 

Probably decreased risk 

- 

Less social network: 

Occupation: Increased risk No Less social 

support: Increased risk 

Studies (subjects) 

3 Education: 

14 (43201) 

Marital status/ cohabitation: 7 (16565) 

3 7 14 8 1 

(6,861) (9599) (15,581) (33685) (17351) (170) 

Occupation: 4 (7277) Social network: 

5 (10926) Social support: 5 (15459) 

Association with cognitive decline* 

No association 

Education: Inconsistent association 

Marital status: Inconsistent association 

Probably decreased risk 

No association 

Increased risk 

Probably decreased risk 

Decreased risk 

Occupation: Possibly 

Social network: Inconsistent 

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294

Exposure Childhood 

exposures 

Education/ 

occupation 

Social 

engagement 

Other 

leisure 

activities 

Alcohol Tobacco Physical activity in late 

adults 

Design Cohort Cohort Cohort Cohort Cohort Cohort Cohort RCT 

decreased risk 

association Social support: Inconsistent association 

Concordance/ discordance for AD and cognitive decline outcomes 

Concordant 

for no 

association 

Exposure 

measure 

variable. 

Education: 

Discordant 

Occupation: 

Evidence 

inadequate 

to determine 

Evidence 

inadequate to 

determine 

Evidence 

inadequate 

to 

determine 

Discordant Concordant 

for 

increased 

risk 

Concordant for 

decreased risk but 

exposure measures 

variable and imprecise; 

little trial data; cognitive 

decline measured 

variably 

Abbreviations: AD = Alzheimer’s disease; RCT = randomized controlled trial 

*Direction of risk for higher exposure (intake) and AD or cognitive decline.
Toxic Environmental Exposures 

For toxic environmental exposures, concordance was not determined because of the lack of 

evidence for both AD and cognitive decline. 

Genetic Factors 

Of the six genes associated with risk for AD and included in this review, only one (APOE 4) 

has been evaluated in cohort studies for risk of cognitive decline. These studies are generally 

concordant. The presence of APOE e4 increases the risk of AD and the risk of cognitive decline, 

especially on some memory tasks and tasks of perceptual speed. 

Key Question 6 – Future Research Needs 

Key Question 6 is: If recommendations for interventions cannot be made currently, what 

studies need to be done that could provide the quality and strength of evidence necessary to make 

such recommendations to individuals? 

Introduction 

To address this question, we first identified the factors included in the present review that are 

potential interventions. Only a subset of the factors considered meets this criterion. Childhood 

exposures, education, genetics, toxic exposures, and the medical conditions considered are not 

potential interventions, but rather potential targets for intervention. Components or intermediary 

measures of some of the risk factors evaluated (e.g., treatment for diabetes mellitus) may be 

appropriate for intervention, but these factors were not on the list of exposures to be considered 

in this review. This discussion focuses primarily on the factors reviewed that are potential 

interventions. 

Based on a review of the quality, strength, consistency, and extent of evidence for each 

factor, for AD, the only risk factors with moderate quality evidence for increased risk of AD 

were the APOE e4 allele, some non-steroidal anti-inflammatory drugs (NSAIDs), and conjugated 

equine estrogen with methyl progesterone. For cognitive decline, there was moderate quality 

evidence for an increased risk with some NSAIDs, and high quality evidence for a decreased risk 

with cognitive training. Chapter 5 describes the other factors that had low quality evidence 

supporting either an increased or decreased risk of AD or cognitive decline. 

Given the number of studies that have investigated one or more of the factors on this lengthy 

list of putative risk or protective exposures for AD and cognitive decline, this much abbreviated 

list of factors with even moderate support may seem discouraging. But it is important to note that 

the factors on the list that lack even moderate supporting evidence may be associated with 

cognitive decline and AD; there just was not sufficient evidence to draw such a conclusion. For 

example, findings from cohort studies showed an association between statins and decreased AD 

risk, but there were no RCTs confirming this finding. The findings on the Mediterranean diet and 

other dietary components, such as folic acid, look intriguing, but the research is limited or too 

heterogeneous to draw firm conclusions. Many of these prior studies, including those reporting 

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on factors with some supporting evidence, should be viewed as exploratory investigations that 

need to be followed up by well-designed hypothesis-testing observational studies or RCTs. The 

current literature does not provide adequate evidence to make recommendations for 

interventions. 

We discuss below the characteristics unique to AD that present particular challenges when 

assessing the effect of given exposures on disease outcome. We also discuss some of the diseaserelated issues and the methodological challenges to assimilating the present studies in this area. 

Protracted Course of Disease without Overt Clinical Symptoms 

Issues. Neuropathological evidence suggests the pathological changes associated with AD 

may begin as early as the 4th decade of life, but overt clinical symptoms do not present until 

years later during the 7h, 8th, and 9th decades of life.20 Subtle cognitive changes may begin prior 

to age 60 among those with an APOE e4 allele,422 but these changes are difficult to detect in 

individuals. The age criteria for the present review was age 50 and older, but the majority of 

studies examined exposures well beyond mid-adult life, meaning that for some individuals (e.g., 

APOE e4 allele positive individuals) or factors the studies may have missed the critical exposure 

time period. The extended sub-clinical prodromal phase of AD also means that exposures 

measured 1 to 2 years prior to onset of symptoms may conflate the risk factor exposure with 

prodromal AD. 

Addressing the gap. Observational studies need to assess exposures initially years prior to 

expected onset of symptoms. The collection of exposure data should continue over an extended 

period of time because it is not known whether exposures with a protective effect or those with a 

detrimental effect may still be influential even after the pathological process has begun. It is also 

important to collect longitudinal exposure data to examine whether the timing of the exposure 

makes a difference, and whether changes in exposure over time alter risk of cognitive decline. 

Prospectively collecting this exposure information for decades prior to onset of clinical disease is 

costly and logistically challenging. Realistically, intermediate or shorter-term outcomes may 

need to be integrated into such a life course approach to make the studies viable. Some of the 

initial work in this area may be able to use established registries. In fact, some research groups 

have already taken advantage of longitudinal registry databases, such as those from the Veteran’s 

Administration and health maintenance organizations, to collect more objective information on 

exposure variables that spans decades. The value of these registries can be optimized by linking 

the exposure data to a prospective and comprehensive evaluation for diagnosis of dementia. 

Multiple registries could contribute data to establish research consortia to conduct planned 

prospective meta-analysis. This would be particularly useful for some of the research questions 

that require very large sample sizes such as assessing interaction effects and differential effects 

in sample subgroups. This approach would have the potential additional benefit of encouraging 

some standardization of data collection methods and instruments across studies. 

The protracted course of the disease also means that early symptoms of AD may be 

mistakenly reported as risk factors for the disease when in fact they are correlates or symptoms 

of disease. An example of this is depression, which is often a symptom of AD, especially in the 

early stages of disease. It is difficult to separate depressive symptoms that are antecedents of AD 

from depression that is an early symptom of the disease. 

The long prodromal phase of AD means that interventions should not only be implemented 

as early as possible, but also that there also may be windows of time during which interventions 

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are most effective, and these time periods may differ for different risk factors and interventions. 

Due to the long prodromal period of AD, RCTs also need to continue for extended periods of 

time. The current review identified few clinical trials that were even 1 year in length. If 

exposures throughout the lifespan are being examined for their role in AD and cognitive decline 

in late life, it is unrealistic to expect interventions of less than 1 year to change the path of the 

disease. However, if unaffected or mildly affected individuals are to be exposed to interventions 

for long periods of time, the interventions need to be low risk. For example, one intervention trial 

of non-steroidal anti-inflammatory (NSAID) medication (the Alzheimer's Disease Antiinflammatory Prevention Trial [ADAPT]) was discontinued due to concerns about serious sideeffects of the medication.379 It is important to note that the interventions do not need to be 

pharmacologic; low-risk interventions could involve lifestyle interventions like exercise and diet, 

or aggressively monitored treatment of existing diseases like diabetes, cholesterol, or 

hypertension. Another approach to limiting the period of exposure to an intervention and to 

optimize outcome would be to enrich the sample with individuals at particularly high risk of 

progressing to AD. This would result in shorter followup time and smaller sample sizes required 

to evaluate the intervention. Some RCTs have already used this approach.372 Another efficient 

way to test interventions for potential risk factors such as diabetes mellitus is to design robust 

measures for cognition as a secondary outcome in trials designed to test multifactorial 

interventions for the disease of interest. The ACCORD (Action to Control Cardiovascular Risk 

in Diabetes) and ACCORD-MIND (Action to Control Cardiovascular Risk in Diabetes – 

Memory in Diabetes) trials are current examples of this strategy.423,424

Although long-term RCTs are the ideal approach, in many cases the barriers to implementing 

such studies may make them unrealistic. In these cases, alternative analytical approaches such as 

structural equation modeling, path analysis, and multi-level modeling applied to life course data 

may help to identify causal relations between exposure and disease.425 In addition, alternative 

designs such as randomized encouragement designs and non-random quantitative assignment of 

treatment designs are options which may be more feasible and still allow one to make causal 

inferences.426 

Long-term studies may not only be unrealistic but they also create their own issues, such as 

attrition due to numerous reasons (e.g., mortality, refusal), which need to be carefully considered 

in the planning stages. Those who continue to participate throughout the course of the study may 

be younger, healthier, and of higher socioeconomic status than those who discontinue 

participation.427 This may create selectivity in the sample over time, another issue that should be 

addressed in the planning stages of the study. Although evidence-based approaches to decrease 

attrition are not well established, a recent systematic review found that studies using multiple 

strategies such as community involvement, frequently updating participant contact information, 

financial incentives, and minimizing participant burden were associated with less attrition.428

Lack of Validation of Exposure Measures 

Issues. There are a number of issues regarding the measurement of exposures. Large cohort 

studies often rely on self-reported information from questionnaires that briefly assess a range of 

exposures. Typically any given exposure is assessed with just a few questions. Often responses 

to questions are then combined post hoc to create exposure variables that were never intended 

when the questionnaire was designed. Often the derived exposure variables have not been 

formally assessed for construct validity; that is, do the variables measure what they say they do? 

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For example, among the studies cited in this review, there was a good deal of overlap among the 

activities categorized as cognitive, physical, and leisure. Validation for the categorization was 

not provided. Another example that raised questions about construct validity was that some 

studies interpreted exposure on a single item to have broader meaning. For example, the variable 

“being married” was used to indicate more social support, even though the benefits of marriage 

are multi-dimensional. Another issue related to construct validity is that exposure variables may 

actually serve as surrogates for other variables. An example of this is that education may be a 

surrogate for premorbid intellect or cumulative advantage throughout life. The association 

between a greater number of years of education and lower risk of AD may also reflect an 

insensitivity of diagnostic methods to identify impairment among those with high education. 

Identifying an association between a surrogate factor and disease outcome is an important first 

step, but prior to implementing RCTs or interventions based on these findings, the underlying 

risk factor needs to be identified. 

Another issue is the imprecision of the measurement of exposure in observational studies. 

One example of this would be the accuracy of self-report information on food intake and the 

conversion of this information to actual nutritional components. In addition, it is unclear whether 

intake of nutrient directly equates to in-vivo level of nutrient. The studies reporting validation 

analyses indicate a limited correlation between responses on the food frequency questionnaire 

and 24-hour records of food intake. Another example of imprecise exposure data is the 

variability in the type, duration, and frequency of exercise. It is difficult to retrospectively assess 

exercise activity over decades of exposure when there may be periods of regular activity 

followed by no activity. 

Yet another issue of measurement is that studies ordinarily investigate a single exposure, but 

many of the exposures of interest are likely inter-related. This is particularly true for nutrition, as 

it is unrealistic to consider single nutrients in isolation. In addition, many of the exposures of 

interest are behaviors that commonly co-occur in individuals aiming to maintain a healthy 

lifestyle; measuring any single exposure among the numerous healthy behaviors would lead to 

inaccurate conclusions. 

 Another issue relates to how exposure is defined. It was often not clear whether exposure 

levels were determined a priori and whether they were linked to biological rationale, clinical 

relevance, or informed by prior studies. For example, definitions of hypertension and nutritional 

intake levels varied across studies or were defined by proportions of the available data. In 

addition, categorizing the exposure based on distributional properties (e.g., quartiles) may 

decrease the power to detect an association. To assist in interpreting the results, the reader will 

need to know whether the analysis was exploratory, with multiple definitions of exposures being 

tested, or whether the analysis addressed a specific hypothesis, with the exposure level being 

predetermined as part of the hypothesis. 

One final issue that is related to both exposure and outcome is that power analyses were 

rarely reported in the included studies. Providing a priori power analyses for planned analyses or 

post hoc calculations for exploratory analyses would allow readers and systematic reviewers to 

better understand if null findings were due to low power. 

Addressing the gap. There are multiple issues related to exposure variables, as noted above. 

A few basic steps would advance the field substantially in addressing these issues, but some of 

these steps are quite challenging. A first step should be developing standard methods to measure 

exposure and provide validation data to show that the measure is reliable and valid. Some areas 

of research have established “measures warehouses” to standardize the measurement with the 

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aim of advancing the research. Similar to the idea of a measures warehouse, sponsors of research 

might establish a web-based resource for dementia studies that inventories exposure measures 

and data about validity. Finally, editors for more journals might require that authors follow 

standard guidelines for reporting observational studies (e.g., the Strengthening the Reporting of 

Observational Studies in Epidemiology [STROBE] guidelines).429

Sensitivity, Validation, and Homogeneity of Outcome Measures 

Issues. For inclusion in this review, we required that studies on AD used standard diagnostic 

criteria. However, there was wide variation in how these diagnostic criteria were operationalized, 

particularly regarding the extent of neuropsychological testing used and whether information was 

collected from both a knowledgeable informant and the study participant to determine the 

diagnosis. In contrast to AD, for mild impairment the diagnostic standards are still evolving, with 

most diagnostic nomenclature suggesting that cognitive decline leading to mild impairment 

appears to have many causes. For example, there are multiple types of mild cognitive impairment 

(MCI) and cognitive impairment not demented (CIND). This heterogeneity in both the cognitive 

profile and most likely the underlying etiology may be part of the reason why only a few 

cognitive measures show significant change associated with a risk factor. This alone makes 

interpretation of the results difficult. But compounding the issue are the facts that different 

cognitive measures are used across studies, and associations between specific exposures and 

specific cognitive tests or tests in the same cognitive domain are not replicated across studies. 

The heterogeneity of cognitive measures has made synthesis of the literature on cognitive decline 

difficult. 

Often studies reported that exposure to a factor was associated with statistically significant, 

but very modest decline on one or two cognitive measures only. It is important to note that 

statistical significance does not equate to clinical significance. 

Addressing the gap. Further work is required to reach a consensus on which cognitive 

measures are the best validated, most responsive to change, and measure the needed domains. If 

the experts could agree on a limited battery of measures, it would make synthesis of the literature 

more straightforward and allow for pre-planned meta-analysis. If the same exposure and 

cognitive assessments were used in different studies, then datasets could be combined and patient 

level meta-analysis could be performed. This is an efficient way to look at subgroups rather than 

powering individual studies for this type of analysis. The National Institutes of Health (NIH) 

Toolbox, part of the NIH Neuroscience Blueprint Initiative, is a brief comprehensive battery of 

assessment tools being developed to measure cognitive, motor, sensory, and emotional function 

over the full range of normal function.430 It is an example of a standardized assessment tool that 

has the potential to improve uniformity of assessment and make synthesis of results from 

multiple studies more meaningful. 

Using a more standard battery of measures, it may be possible to better identify individual 

measures or domains of cognition that predict progression to clinically significant cognitive 

impairment (e.g., MCI or AD). Performance on these measures could be used to identify 

individuals at greater risk of decline in the near term. 

More work is needed to better characterize and validate the various subtypes of CIND and 

MCI to be able to identify specific cognitive measures or domains of cognition that predict 

progression to AD. These findings could be used to enrich intervention samples with individuals 

at highest risk of progressing to dementia. 

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Finally, more research is needed to determine size of effect necessary to be of clinical 

significance, and this information should be used when interpreting results. In addition, 

measurement of meaningful change needs to include assessment of practice effects. 

Identifying Differential Effects of Risk Factors in Subgroups and 

Interactions 

Issues. Due to lack of data, we were not able to address whether there were important 

subgroup differences or interactions in the association between factors and cognitive outcomes. 

Even when studies reported that an interaction effect was not statistically significant, often the 

relevant information to determine if the study had statistical power to detect an interaction effect 

was not provided. Important subgroups where differential risk and differential effect of 

interventions are sometimes observed include sex, ethnic groups, and specific genes. 

Addressing the gap. Observational studies should be powered to look at the differences 

between subgroups and interaction effects. Interactions may be present for specific individual 

characteristics or between exposure factors. The effects of exposures and interventions may 

depend on individual characteristics, so assessing the sample as a whole may hide effects. The 

use of a standard assessment battery (as suggested above) would allow for combining studies so 

that no single study would need to be sufficiently powered to examine differences among 

multiple subgroups. 

Publication Bias 

Issues. Most large epidemiological studies of aging ask questions about many of the same 

exposures. Depression and diabetes are examples of conditions that are not only routinely 

inquired about, but also show the most consistent association with AD and cognitive decline. In 

contrast, it is as striking that many of the large cohort studies have not published reports on the 

topic of the association between depression or diabetes and AD. It is possible that these other 

studies have investigated these exposures in their data and that the lack of publication on the 

finding means that they did not find a significant association. This suggests the potential for 

important publication bias. 

Addressing the gap. One idea for addressing this gap would be to establish a registry of 

cohort studies that includes planned analyses. Although establishing a registry of cohort studies 

would be more challenging than creating the registries of clinical trials, it would allow the 

planned versus published results to be tracked to get a sense of publication bias. This would 

require the cooperation of journal editors and funding agencies to provide incentives to 

researchers to submit their data to the registry. In addition, statistical techniques for identifying 

publication bias in observational studies need to be developed and validated. 

Determining the Cost and Benefit of Intervention 

Issues. There is a lack of information on the overall effectiveness and the cost-effectiveness 

of the interventions. To date, the few RCTs conducted on the factors of interest here have not 

shown a positive effect of the intervention. However, once evidence is available to indicate 

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301

efficacy of an intervention, further research will need to be done to determine the effectiveness 

of the intervention from multiple perspectives. 

Addressing the gap. Demonstrating an association between an intervention and a cognitive 

outcome in an RCT provides an indication of efficacy, but that is just the first step in evaluating 

the benefit of an intervention. From that point, the effectiveness of the intervention on many 

levels will need to be determined. Typically, effectiveness research has focused on the outcomes 

of cognitive decline and decline in performance of daily activities by the patient, but research in 

the area of pharmacoeconomics has shown that other outcomes should also be assessed when 

estimating the cost-benefit values of AD interventions.431 These additional outcomes include not 

only others related to the patient, such as the presence and severity of neuropsychiatric and other 

behavioral symptoms, but may also include factors related to caregiver burden. These factors 

include the extent of care needed, whether providing care has required the caregiver to leave the 

workforce, and the impact on physical and mental health of providing care. 

Some of the interventions suggested by this review (e.g lipid lowering agents) have been 

shown to have net benefit for other outcomes (e.g., cardiovascular). Evidence for a positive 

effect on cognition would simply be one more reason to use the intervention. But the additional 

benefit on cognition would also alter the cost-effectiveness ratio. In these situations, it will also 

be important to assess whether the threshold for effectiveness is the same for both outcomes (i.e., 

the cognitive outcome and the other outcome). It is possible that there may be a threshold effect 

or curvilinear effect for the intervention (e.g., glucose control for DM), and that these may differ 

for the two outcomes, which would influence recommendations for intervention intensity. 
Chapter 4. Discussion 

Alzheimer’s disease (AD) is unique in that it may be the only late-life disease that has a long 

“silent” prodromal phase, no validated biological test for diagnosis, and imprecise measures of 

correlation between progression of phenotype and progression of pathology. Diagnosis during 

life is based on the clinical phenotype of symptom progression, which is heterogeneous between 

individuals. Part of the variation in clinical presentation may be due to the presence of other 

types of neuropathological changes in the brain in addition to those typically considered to be 

AD-related. These characteristics make it difficult not only to accurately diagnose AD but also to 

identify risk or protective factors for the disease; they also make it challenging to implement 

interventions efficiently and economically. The impact of these challenges is made clear by the 

fact that few of the putative risk or protective factors covered in this review had sufficient 

evidence from which to draw firm conclusions about their effect on AD and cognitive decline. 

But these findings need to be interpreted in the context of the effect size of a treatment or 

intervention that would make a noticeable difference in the disease burden. Using analytical 

models, it has been shown that relatively small delays in the onset of AD or the progression of 

the disease would have a large effect on the prevalence of the disease. A 1-year delay in both 

onset of AD and progression of AD would decrease the number of prevalent AD cases in 2050 

by 9.19 million. This reduction in the number of AD cases is almost entirely due to fewer 

individuals with late-stage dementia, the point in the disease course when many individuals with 

AD are institutionalized and when the most care is needed.432

Many of the exposures reviewed in this report likely do not work in isolation in their effect 

on risk of AD or cognitive decline. Instead, they work in combination with other factors. Thus, 

the ideal interventions should be multi-dimensional, combining interventions for multiple risk 

factors and controlling for many other factors. But as noted when discussing the Key Question 6 

in Chapter 3, above, few of the exposures reviewed here are appropriate for randomized 

controlled trials (RCTs). Among those that are not appropriate for intervention trials are 

exposures that one would want to avoid due to their negative impact on outcomes other than 

cognition. For example, smoking, diabetes, hypertension, and few years of education are all 

factors that have deleterious effects on health and lifestyle. Although healthcare interventions 

may be appropriate for some other potential influential factors (e.g., omega-3 fatty acids, statins, 

cognitive engagement), many of the other factors may be most appropriately addressed through 

public policy interventions (e.g., education, designing communities to facilitate physical activity) 

and public health interventions (educational campaigns on diet). Public education campaigns to 

change behavior to incorporate or exclude these factors would have relatively less risk (cost) to 

individuals. 

One of the key limiting factors in synthesizing the current literature is the lack of 

standardization of exposure and outcome measures. Because outcome measures for cognitive 

decline were not standardized across studies, we limited the use of studies with continuous 

outcome measures when the conclusions from these studies were consistent with those from 

studies with categorical outcome measures. This meant that some studies reporting continuous 

measures were not reported in detail in this report, and the results of these studies were not 

synthesized quantitatively, but we do not think that this changed the conclusions for any 

exposure factor. In the future, more standardization at various steps of the research process is 

needed before all available data can be synthesized. We also acknowledge that standardization 

303
can have its weaknesses and can limit innovations that may advance science. The key is to strike 

a balance between enough uniformity to maximize the use of study results and methods that are 

novel enough to advance the field to the next level. 

Issues related to age are central to the interpretation of all of these results. The incidence of 

AD increases markedly with age, doubling in rate approximately every 5 years. Due to this, the 

age distribution of a study sample influences the expected number of AD cases; that is, the older 

the sample, the greater number of cases of AD expected. For this reason, the age distribution also 

influences the statistical power present to detect an association between an exposure and AD. 

Complicating this issue further, the neuropathological evidence available suggests that both 

typical AD pathology and microvascular changes in the brain become more frequent with age, so 

the older the sample, the more likely it is that mixed pathologies are present and contribute to the 

cognitive profile. However, the phenotype of the mixed pathology is often difficult to distinguish 

from that of AD pathology alone, meaning that the clinical AD group may become more 

heterogeneous with advancing age. The increasing incidence of AD with age also can affect the 

interpretation of studies of cognitive decline. The older the sample, the more likely it is that 

cognitive decline represents prodromal AD, and thus any association with a risk exposure may 

reflect an association with AD, not just cognitive decline. 

Age may also be a central issue in regard to the timing of the exposure. There may be a 

window of time during which exposures influence risk of AD. For example, obesity in mid-life 

may be associated with increased risk of AD, while obesity in late life may be associated with 

reduced risk of disease. The latter finding may be explained by the weight loss often associated 

with the disease itself. But the point is clear that different exposures may have effects at different 

times along the life course or the natural history of AD. Ideally the exposure should be measured 

in different age groups within the same study to control for inter-study variability in 

measurement, but this may not be realistic given the long period of followup necessary when 

studying exposures in mid-life. Interventions may also have different effects at different points 

throughout life or the AD process. Although one might assume that interventions or lifestyle 

modification should be undertaken as early as possible, there may be other windows during 

which a given intervention may exert its effect. Careful consideration of the complex relation of 

exposure, age, and disease will likely be key to understanding the factors that alter risk of AD 

and cognitive decline. 

The present review has some limitations. By excluding small to moderate observational 

studies and small RCTs, we may have missed some important evidence, particularly for factors 

with scant data. To evaluate the potential impact of excluding small studies, we coded detailed 

reasons for exclusion in a subset of citations. Of 549 citations, only three observational studies 

and two randomized controlled trials were excluded solely for small sample size. Applying these 

rates to the 6713 citations identified overall from electronic searching, we may have excluded as 

many as 48 articles for small sample size that otherwise would have met our eligibility criteria. 

However, small RCTs and systematic reviews based on small RCTs are more prone to bias, 

including publication bias and failure of randomization. Small observational studies have limited 

power. For factors where we have large studies already, it is very unlikely that the addition of 

small studies would change the estimate of effect or conclusions. 

The exclusion of RCTs lasting less than 1 year may have missed some studies showing 

promising short-term results. These would not have been adequate to conclude that the 

intervention was useful for preventing cognitive decline or AD, but may have provided the 

impetus to conduct longer trials. 

304
305

The extant research for a specific factor generally did not include more than a couple of 

studies using the same cognitive measure for a continuous outcome. Given the variability in 

outcome measures and the limited resources and time to complete the present project, it was not 

possible to perform quantitative meta-analyses on studies with continuous outcomes. We 

acknowledge, however, that quantitative estimates of effect may have been easier to interpret 

than qualitative syntheses. 

The focus of this review was on the association between specific conditions (e.g., diabetes 

mellitus) and AD or cognitive decline. We did not evaluate the association between AD or 

cognitive decline and the treatments or interventions for the conditions. These exposures are of 

potential interest, but were not specified by the planning committee. 

We note that this is a difficult literature to search for several reasons, including the wide 

range of factors assessed, the lack of well-validated search strategies for relevant observational 

studies, variability in categorizing studies by standard search terms, and variability in the terms 

used to categorize cognitive decline. For all these reasons, it is possible that relevant studies were 

overlooked. 

Epidemiological studies of complex diseases using observational data often simultaneously 

evaluate the association between a range of exposures and the outcome of interest, in this case, 

AD or cognitive decline. These studies do not typically design their analyses specific to one or 

two factors of interest. We were not able to assess systematically how this approach may 

influence the association between the factor of interest and the outcome, but we note the issue as 

one to be considered when interpreting the results. 

In summary, previous work on the search for clues to factors that alter the risk of AD and 

cognitive decline has provided a number of potential leads. These leads now need to be pursued 

with potentially novel approaches and increasingly rigorous scientific methods to be able to 

identify a real signal among the numerous factors throughout the life course that may contribute 

to the complex late-life disorders considered in this report. 
Chapter 5. Conclusions 

Among the many factors examined in this review, only some are amenable to being 

evaluated in randomized controlled trials (RCTs), and only a subset of these have actually been 

studied in high-quality RCTs as potential interventions for preventing or delaying the onset of 

Alzheimer’s disease (AD) and cognitive decline. Effects of interventions in important subgroups, 

such as minority populations, were evaluated infrequently. A few of the factors considered in this 

report have shown potential promise in observational studies for both AD and cognitive decline, 

and in RCTs for at least one of the outcomes of interest. Moreover, several of the factors 

reviewed have demonstrated benefits beyond the potential of preserved cognition; that is, they 

promote overall health. Thus, there may be other reasons to recommend an intervention (e.g., 

increased physical activity) while further research is completed on its role in cognition. 

The most general conclusions of this evidence report are summarized in Tables 74 and 75. 

These conclusions are based on a systematic review of the evidence for each factor, and on 

judgments about the quality of that evidence made using principles developed by the GRADE 

working group (www.gradeworkinggroup.org). For each factor examined, we considered the 

entire body of evidence and summarized the quality of that evidence as low, moderate, or high. 

The GRADE approach assigns an initial rating of “low” quality to observational studies and 

“high” quality to RCTs. These initial ratings may be modified by considerations relating to: 

detailed study design, consistency, strength of association, dose-response effect, directness, 

precision, and consideration of all plausible residual confounders that could reduce a 

demonstrated effect. Note that even within a given rating level, the quality of evidence may vary 

substantially; for example, there is considerable variability within the “low” quality level. 

Tables 74 and 75 list, for AD and cognitive decline, respectively, the potential risk factors 

and interventions considered in this report, the associations observed between them and the 

outcome of interest (if any), and the quality of evidence supporting those associations. The tables 

also list factors for which the evidence was insufficient to establish whether or not an association 

exists. It is noteworthy that this last category includes many of the risk factors examined in this 

report. 

In addition to sparse evidence, the extant research literature has other important limitations. 

Needed advances in study design and reporting include validated measures of exposure, prespecified exposure categorizations, longer term trials, reporting of power calculations, and an 

agreed-upon battery of cognitive measures. Improving research design and reporting in these and 

other ways could improve confidence in observed associations and targeting of potential 

interventions. Conducting trials initially in those at high risk (e.g., those with mild cognitive 

impairment) would be an efficient approach. Well-designed, long-term cohort studies with robust 

measures of exposure and cognitive outcomes are needed to address the factors for which there is 

a strong biological mechanism or preliminary clinical evidence to suggest an important 

association. 

307
Table 74. Summary of findings on potential risk factors and interventions for AD 

Direction of association Factors Level of evidence‡ 

• APOE e4 genotype 

• Conjugated equine estrogen with methyl 

progesterone* 

Moderate 

Increased risk 

• Some non-steroidal anti-inflammatory drugs* 

• Depressive disorder 

• Diabetes mellitus 

• Hyperlipidemia in mid-life 

• Traumatic brain injury in males 

• Pesticide exposure 

• Never married, less social support 

• Current tobacco use 

Low 

Decreased risk 

• Mediterranean diet 

• Folic acid 

• HMG-CoA reductase inhibitors (statins) 

• Higher levels of education 

• Light to moderate alcohol intake 

• Cognitively engaging activities 

• Physical activity, particularly high levels 

Low 

• Ginkgo biloba* High 

• Vitamin E* 

• Cholinesterase inhibitors* Moderate 

No association 

• Anti-hypertensive medication* 

• Conjugated equine estrogen 

• Omega-3 fatty acids* 

• Vitamins B12, C, beta-carotene 

• Homocysteine 

• Hypertension 

• Obesity 

• Metabolic syndrome 

• Early childhood factors 

• Occupational level 

• Lead 

Low 

Inadequate evidence to 

assess association 

• Saturated fat intake 

• Fruit and vegetable intake 

• Trace metals 

• High caloric intake 

• Memantine 

• Sleep apnea 

• Anxiety disorders 

• Resiliency 

• Non-cognitive, non-physical leisure activities 

• Agent Orange, Gulf War Syndrome 

• Solvents, aluminum 

• Genetic factors other than APOE 

(Not applicable) 

* Data from observational studies and RCTs. 

Abbreviations: APOE = apolipoprotein E gene; APOE e4 = epsilon 4 allele of the apolipoprotein E gene; HMG-CoA = 3-

hydroxy-3-methylglutaryl-coenzyme A; RCTs = randomized controlled trials

‡GRADE criteria (see text)

308
309

Table 75. Summary of findings on potential risk factors and interventions for cognitive decline 

Direction of association Factors Level of evidence‡ 

Increased risk 

• APOE e4 genotype 

• Low plasma selenium 

• Depressive disorder 

• Diabetes mellitus 

• Metabolic syndrome 

• Current tobacco use 

Low 

• Cognitive training* High 

Decreased risk 

• Vegetable intake 

• Mediterranean diet 

• Omega-3 fatty acids* 

• Physical activity* 

• Non-cognitive, non-physical leisure activities 

Low 

• Vitamin C, Vitamin E, beta-carotene 

supplements* 

• Conjugated equine estrogen* 

• HMG-CoA reductase inhibitors (statins)* 

High 

• Aspirin* 

• Dehydroepiandosterone* 

• Cholinesterase inhibitors* 

• Multivitamin supplement* 

• Vitamins B6, B12 and folic acid supplements* 

Moderate 

No association • Alcohol intake 

• Non-steroidal anti-inflammatory drugs*†

• Anti-hypertensive medication* 

• Homocysteine 

• Hyperlipidemia 

• Anxiety disorders 

• Hypertension 

• Obesity 

• Early childhood factors 

• Higher levels of education 

• Social network, social supports 

Low 

Inadequate evidence to 

assess association 

• Trace metals 

• Fat intake 

• High caloric intake 

• Gingko biloba* 

• Memantine 

• Sleep apnea 

• Resiliency 

• Occupational level 

• Traumatic brain injury 

• Toxic environmental exposures 

• Agent Orange, Gulf War Syndrome 

• Genetic factors other than APOE 

(Not applicable) 

*Data from observational studies and RCTs. 

† Not associated with decreased risk but may be associated with increased risk. 

Abbreviations: APOE = apolipoprotein E gene; APOE e4 = epsilon 4 allele of the apolipoprotein E gene; HMG-CoA = 3-

hydroxy-3-methylglutaryl-coenzyme A; RCTs = randomized controlled trials 

‡GRADE criteria (see text)
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Acronyms and Abbreviations 

3MS Modified Mini-Mental State Examination 

AA Arachidonic acid 

AACD Aging-associated cognitive decline 

AAMI Age-associated memory impairment 

ABI Ankle-brachial index 

ACE Angiotensin 1 converting enzyme 

ACTIVE Advanced Cognitive Training for Independent and Vital Elderly trial 

AD Alzheimer’s disease 

ADAPT Alzheimer’s Disease Anti-inflammatory Prevention Trial 

ADAS-Cog Alzheimer Disease Assessment Scale-Cognitive subscale 

ADEPT Adult Development and Enrichment Project; 

ADL(s) Activities of daily living 

AHRQ Agency for Healthcare Research and Quality 

aMCI Amnestic mild cognitive impairment 

ApoE Apolipoprotein E protein 

APOE Apolipoprotein E gene 

APOE e4 Epsilon 4 allele of the apolipoprotein E gene 

APP Amyloid precursor protein 

ARIC Atherosclerosis Risk in Communities study 

ASA Acetylsalicylate (aspirin) 

AVLT Auditory Verbal Learning Test 

BDI Beck Depression Inventory 

BMI Body mass index 

BNT Boston Naming Test 

BP Blood pressure 

BSRT Babcock Story Recall Test 

BVRT Benton Visual Retention Test 

CAD Coronary artery disease 

CASI Cognitive Abilities Screening Instrument 

CDR Clinical Dementia Rating 

CDR-SB Clinical Dementia Rating-sum of boxes 

CEE Conjugated equine estrogen 

CERAD Consortium to Establish a Registry for Alzheimer’s Disease 

CES-D Center for Epidemiologic Studies Depression scale 

CHD Coronary heart disease 

CHF Congestive heart failure 

CI Confidence interval 

CIND Cognitive impairment not demented 

CNS Central nervous system 

COPD Chronic obstructive pulmonary disease 

COWA Controlled Oral Word Association test 

CRP C-reactive protein 

CSI-D Community Screening Interview for Dementia 

CVA Cerebrovascular accident 

325
CVD Cardiovascular disease 

CVLT California Verbal Learning Test 

DBP Diastolic blood pressure 

DCT Digit Cancellation Test 

DHA Docosahexaenoic acid 

DHEA Dehydroepiandosterone 

DHP-CCB Dihydropyridine-calcium channel blockers; 

DM Diabetes mellitus 

DSM Diagnostic and Statistical Manual of Mental Disorders 

DSST Digit Symbol Substitution Test 

DWR Delayed word recall 

EPA Eicosapentaenoic acid 

EPC Evidence-based Practice Center 

FTT Finger Tapping Test 

GDS Geriatric Depression Scale 

GEE Generalized estimated equations 

GRADE Grading of Recommendations Assessment, Development and Evaluation 

GWAS Genome-wide association studies 

HDL High density lipoprotein 

HDL-C High density lipoprotein cholesterol 

HDRS Hamilton Depression Rating Scale 

HDDS Hasegawa Dementia Screening Scale 

HFFQ Harvard Food Frequency Questionnaire 

HMG-CoA 3-hydroxy-3-methylglutaryl-coenzyme A 

HMO Health maintenance organization 

HR Hazard ratio 

HRT Hormone replacement therapy 

HTN Hypertension 

IADL Instrumental activities of daily living 

IL-1B Interleukin-1beta 

IL-6 Interleukin-6 

IQ Intelligence quotient 

JNC VII Seventh Report of the Joint National Committee on Prevention, Detection, 

Evaluation, and Treatment of High Blood Pressure 

LDL Low density lipoprotein 

MAC Memory assessment clinics 

MCD Mild cognitive disorder 

MCI Mild cognitive impairment 

MDD Major depressive disorder 

MeSH Medical Subject Heading 

MI Myocardial infarction 

MMSE Mini-Mental State Examination 

MNC Mild neurocognitive disorder 

MPA Medroxyprogesterone acetate 

mTICS modified Telephone interview for cognitive status 

MUFA(s) Monounsaturated fatty acid 

326
NCEP-ATPIII National Cholesterol Education Program 3rd Adult Treatment Panel 

Guideline 

NIH National Institutes of Health 

NIMH National Institutes of Mental Health 

NINCDS-ADRDA National Institute of Neurological and Communicative Diseases and 

Stroke-Alzheimer’s Disease and Related Disorders Association 

NS Not statistically significant 

NSAID(s) Non-steroidal anti-inflammatory drug(s) 

NYU New York University 

OMAR Office of Medical Applications of Research 

OR Odds ratio 

PMA Primary Mental Abilities 

PUFA(s) Polyunsaturated fatty acid(s) 

PVD Peripheral vascular disease 

RCT Randomized controlled trial 

RERI Relative excess risk from interaction 

RR Relative risk 

RVLT Rey Auditory Verbal Learning Test 

SBP Systolic blood pressure 

SCOPE Study on Cognition and Prognosis in the Elderly 

SD Standard deviation 

SDMT Symbol Digit Modalities Test 

SE Standard error 

SERM Selective estrogen receptor modulator 

SES Socioeconomic status 

SF-36 Medical Outcomes Study 36-Item Short Form Health Survey 

SFA(s) Saturated fatty acid(s) 

SHEP Systolic Hypertension in the Elderly Program 

SNP Single-nucleotide polymorphism 

SPMSQ Short Portable Mental Status Questionnaire 

STAI State Trait Anxiety Inventory 

Syst-Eur Systolic Hypertension in Europe trial 

TBI Traumatic brain injury 

TEP Technical expert panel 

TFAM Transcription factor A, mitochondrial 

TIA Transient ischemic attack 

TICS Telephone Interview for Cognitive Status 

TICS-m Telephone Interview for Cognitive Status (modified version) 

TNK1 Tyrosine kinase, non-receptor 1 

Trails A/B Trail Making Test Part A/B 

Trails B Trail Making Test Part B 

VA United States Department of Veterans Affairs 

VAD Vascular Alzheimer’s disease 

VRT Visual Reproduction Test (immediate and delayed recall) from the 

Wechsler Memory Scale 

WAIS Wechsler Adult Intelligence Scale 

327
328

WAIS-R Wechsler Adult Intelligence Scale-Revised 

WF Word Fluency Test 

WMD Weighted mean difference 

WMS Wechsler Memory Scale 

WMS-R Wechsler Memory Scale-Revised 
A-1

Appendix A. Exact Search Strings 

Our search strategy to identify systematic reviews combined terms specific to the risk 

factor or intervention, terms for Alzheimer’s disease or cognitive impairment, and the 

PubMed filter for systematic reviews. We used a similar strategy in the Cochrane 

Database of Systematic Reviews. 

1. (Terms for the exposures), AND 

2. (Terms for the outcome of interest (AD or cognitive decline)), AND 

3. Systematic[sb] 

Our search strategy to identify original research combined terms specific to the risk 

factor or intervention, terms for Alzheimer’s disease or cognitive impairment, and terms 

for the relevant study designs. We limited the search to studies in humans, age 45+, 

and published in English. We excluded studies conducted in special populations. 

For KQ 1 and KQ2, we used the following general search strategy, utilizing the specific 

terms that follow: 

1. (Terms for the exposures), AND 

2. (Terms for the outcome of interest (AD or cognitive decline)), AND 

3. (Terms for observational study designs) 

4. NOT (Terms for excluded non general population samples) 

5. NOT (Terms for excluded publication types) 

6. Limits (Human, English, Age 45+) 

For KQ 3 and KQ4, we used the following general search strategy, utilizing the specific 

terms that follow: 

1. (Terms for the exposures), AND 

2. (Terms for the outcome of interest (AD or cognitive decline)), AND 

3. (Terms for randomized controlled trial study designs) 

4. NOT (Terms for excluded non general population samples) 

5. NOT (Terms for excluded publication types) 

6. Limits (Human, English, Age 45+) 

SPECIFIC SEARCH TERMS 

KQ1 and KQ2: Terms for Exposures

Sleep apnea syndromes[Mesh] OR “sleep apnea”[tw] OR (obstructive[all fields] AND 

sleep[all fields] AND apnea[all fields]) 

Obesity[Mesh] OR overweight[mesh] 

Diabetes mellitus[Mesh] 

Intelligence tests[Mesh] or “IQ”[Title/abstract] OR “aptitude tests”[mesh] 
A-2

Metabolic syndrome x[Mesh] OR insulin resistance[Mesh] OR 

Hyperinsulinism/*epidemiology/psychology 

 “TBI”[All fields] OR “traumatic brain injury”[All fields] OR (“traumatic” AND “brain” AND 

“injury”) OR craniocerebral trauma[mesh] 

Hypertension[mesh] 

Educational status[mesh] 

Employment[mesh] OR "occupational status"[Title/abstract] OR retirement[mesh] 

Literacy[tw] OR illiterate*[tw] OR illiteracy[tw] OR reading[mesh] 

"Social Identification"[Mesh] OR "Social Isolation"[Mesh] OR "Social Desirability"[Mesh] 

OR "Social Adjustment"[Mesh] OR "Social Conformity"[Mesh] OR "Social 

Behavior"[Mesh:noexp] OR "Social Environment"[Mesh] OR “Interpersonal 

Relations"[Mesh:noexp] OR family conflict[mesh] OR (social AND (network* OR 

engage* OR participat*)) OR “marital status”[mesh] 

(("Resilience, Psychological"[Mesh]) OR (resilienc*)) OR ((depressive disorder) OR 

(depression[MeSH])) OR (anxiety[MeSH] OR "anxiety disorders"[Mesh]) 

homocysteine[mesh] OR homocysteine[all fields] OR homocyst*[title/abstract] 

smoking[MeSH] OR Nicotine[MeSH] OR (tobacco[All Fields] AND smoking[All Fields]) 

OR (Cigarette[All Fields] AND Smoking[All Fields]) 

Persian Gulf Syndrome[MeSH] OR (Gulf[All Fields] AND War[All Fields] AND 

Syndrome*[All Fields]) OR (Gulf[All Fields] AND War[All Fields] AND Illness*[All Fields]) 

Environmental Pollutants[MeSH] OR (Environmen*[All Fields] AND Pollut*[All Fields]) 

Agent Orange[substance name] OR Agent orange[all fields] OR 

tetrachlorodibenzodioxin[Mesh] OR tetrachlorodibenzodioxin[all fields] OR “2,4-

Dichlorophenoxyacetic Acid”[mesh] OR “2.4,5-Trichlorophenoxyacetic Acid[all fields] 

Pesticides[MeSH] OR Pesticides[All Fields] 

((childhood[tw] OR child[tw] OR children[tw]) AND socioecono*[tw]) OR ((childhood[tw] 

OR child[tw] OR children[tw]) AND exposure*[tw]) OR ((childhood[tw] OR child[tw] OR 

children[tw]) AND “urban population”[Mesh]) OR ((childhood[tw] OR child[tw] OR 

children[tw]) AND “rural population”[Mesh]) 
A-3

KQ 1, KQ2, KQ3, KQ4: Terms for exposures and/or interventions

Dietary supplements[Mesh] OR “ginkgo biloba”[tw] OR “ginkgo biloba”[Mesh] OR 

pregnenolone[mesh] OR pregnenolone[tw] OR huperzine[tw] 

Antioxidants[mesh] OR Antioxidants[pharmacological action] OR resveratrol[all fields] 

OR “ascorbic acid”[mesh] OR “vitamin e”[mesh] OR tocopherols[mesh] 

Vitamins[Mesh] OR [pharmacological action] OR trace elements [pharmacological 

action] 

Gonadal steroid hormones[mesh] OR Dehydroepiandrosterone[mesh] OR 

“DHEA”[title/abstract] OR leuprolide[mesh] OR leuprolide[tw] OR lupron[tw] OR 

“estrogens, conjugated (usp)"[MeSH Terms] OR premarin[tw] OR “conjugated 

estrogens”[all fields] OR gonadotropin*[tw] OR Phytoestrogens [Pharmacological 

Action] 

“Nutritional status”[mesh] OR “nutrition assessment”[mesh] OR “diet therapy”[mesh] OR 

“diet, fat-restricted”[mesh] OR “diet, Mediterranean”[mesh] OR “Mediterranean diet”[all 

fields] OR “diet, vegetarian”[mesh] OR “diet, atherogenic”[mesh] OR “dietary fats”[mesh] 

OR fruit[mesh] OR vegetables[mesh] OR phytoestrogens[pharmacological action] OR 

“fatty acids, omega-3”[mesh] OR “fish oil”[tw] 

Video games[mesh] OR puzzle*[tw] OR “memory training”[tw] OR “cognitive training”[tw] 

OR (“cognitive”[tw] AND “training”[tw]) 

(((((((("Diuretics"[Mesh] OR "Diuretics "[Pharmacological Action])) OR ("Calcium 

Channel Blockers"[Mesh] OR "Calcium Channel Blockers "[Pharmacological Action])) 

OR ("Angiotensin-Converting Enzyme Inhibitors"[Mesh] OR "Angiotensin-Converting 

Enzyme Inhibitors "[Pharmacological Action])) OR ("Adrenergic alphaAntagonists"[Mesh] OR "Adrenergic alpha-Antagonists "[Pharmacological Action])) OR 

("Adrenergic beta-Antagonists"[Mesh] OR "Adrenergic beta-Antagonists 

"[Pharmacological Action])) OR ("Ganglionic Blockers"[Mesh] OR "Ganglionic Blockers 

"[Pharmacological Action])) OR ("Vasodilator Agents"[Mesh] OR "Vasodilator Agents 

"[Pharmacological Action]) AND ("Hypertension"[Mesh])) OR ("Antihypertensive 

Agents"[Mesh] OR "Antihypertensive Agents "[Pharmacological Action]) 

leisure activities[mesh] OR "leisure activity"[title/abstract] OR "leisure 

activities"[title/abstract] OR travel[mesh] OR travel[title/abstract] 

exercise[mesh] OR "physical fitness"[mesh] OR running[mesh] OR swimming[mesh] OR 

walking[mesh] 

(("Anti-Inflammatory Agents"[Mesh] OR "Anti-Inflammatory Agents "[Pharmacological 

Action])) OR ("Anti-Inflammatory Agents, Non-Steroidal"[Mesh] OR "Anti-Inflammatory 

Agents, Non-Steroidal "[Pharmacological Action]) 
A-4

(("Hydroxymethylglutaryl-CoA Reductase Inhibitors"[MeSH Terms]) OR 

("Hydroxymethylglutaryl-coa"[All fields] AND "reductase"[All fields] AND "inhibitors"[All 

fields]) OR "Hydroxymethylglutaryl-CoA Reductase Inhibitors"[All fields] OR "statins"[All 

fields] OR "statin"[All fields] OR "Hydroxymethylglutaryl-CoA Reductase 

Inhibitors"[Pharmacological Action] OR (rosuvastatin) OR (simvastatin) OR (pravastatin) 

OR (atorvastatin) OR (fluvastatin) OR (lovastatin) OR (cerivastatin) OR (compactin) OR 

(meglutol) OR ("red yeast rice" OR ("red" AND "yeast" AND "rice"))) 

(("Thiazolidinediones"[Mesh]) OR ("Metformin"[Mesh]) OR ("insulin-sensitivity"[All 

fields]) OR ("insulin-sensitizing"[All fields]) OR ("insulin"[All fields] AND ("sensitivity"[All 

fields] OR "sensitizing"[All fields]))) OR (metformin[all fields]) OR (Thiazolidinedione*[all 

fields]) 

"cholinergic antagonists"[MeSH Terms] OR "cholinergic antagonists"[Pharmacological 

Action] 

((galantamine) OR (donepezil) OR (rivastigmine) OR (memantine)) 

KQ 1, KQ2, KQ3, KQ4: Terms for Observational study designs 

((Epidemiologic Studies[Mesh:noexp] OR case-control studies[Mesh] OR cohort 

studies[Mesh] OR seroepidemiologic studies[Mesh]) OR cohort OR cohorts OR observ* 

OR case-control OR non-randomized OR nonrandomized OR unrandomized OR 

prospectiv* OR retrospectiv* OR follow* OR longitudinal OR (cases AND controls)) AND 

(odds ratio[Mesh] OR "odds ratio" OR "relative risk" OR risk OR risks OR associat* OR 

causality OR etiology OR epidemiology OR ethnology OR probability OR inciden*) 

 

Because of the high degree of overlap between terms for emotional health factors 

cognitive decline, we limited the terms for observational study designs

((Epidemiologic Studies[Mesh:noexp] OR cohort studies[Mesh] OR follow* OR 

longitudinal) AND (odds ratio[Mesh] OR "odds ratio" OR "relative risk" OR risk OR risks 

OR inciden* OR etiology OR causality)) 

KQ 3, KQ4: Terms for RCTs (sensitive strategy)

((clinical[Title/Abstract] AND trial[Title/Abstract]) OR clinical trials[MeSH Terms] OR 

clinical trial[Publication Type] OR random*[Title/Abstract] OR random allocation[MeSH 

Terms] OR therapeutic use[MeSH Subheading]) 

KQ 1, KQ 3: Terms for Alzheimers disease

Alzheimer* OR alzheimer disease[mesh] 

KQ 2, KQ4: Terms for mild cognitive impairment or cognitive decline

(((cognitiv* OR cognition OR memory) AND (declin* OR impair* OR deteriora* OR 

change* OR deficit* OR complaint*)) OR "Cognition Disorders"[Mesh:noexp]) OR ("preclinical AD" OR "preclinical AD" OR "pre-clinical Alzheimer" OR "preclinical alzheimer") 
A-5

KQ1, KQ2, KQ3, KQ4: Terms to exclude non general population or non-general 

medical samples

schizophrenia[mesh] OR schizophrenia[all fields] OR “down syndrome”[mesh] OR 

“down syndrome”[all fields] OR “psychotic disorders”[mesh] OR “psychosis”[all fields] 

OR "substance-related disorders"[MeSH Terms] OR “substance abuse”[all fields] OR 

epilepsy[mesh] OR epilepsy[all fields] OR “seizure disorder”[all fields] OR “Parkinson 

disease”[mesh] OR “Parkinson disease”[all fields] 

KQ1, KQ2, KQ3, KQ4: Terms to exclude selected Publication types 

review, letter 

KQ1, KQ2, KQ3, KQ4: Terms to Limit to the samples of interest

human, English, age 45+ 
B-1

Appendix B. Evidence Tables Study Study Information Participants Risk Factor and 

Outcome Assessment 

Results Comments

Aartsen, Van Tilburg, Smits, et al., 2005 Longitudinal Aging Study of Amsterdam (LASA) 

Geographical location: Netherlands Setting:Community Study design: Prospective cohort Number of participants enrolled:3105 participants enrolled for T1 of LASA. (Oversampled for men and older participants) 1144 participants enrolled for this analysis. Duration of follow up:6 years. Time from risk factor assessment to final cognitive assessment:6 years. 

Age:Range: 60-85 Sex: [n (%)] 

Female: 474 (41.43) Male: 690 (58.57%) Race/ethnicity: [n (%)] NR Baseline cognitive status:All Inclusion criteria: Age >60 yrs Married at baseline Exclusion criteria:NR 

Risk factor/exposure

1:Loss of spouse during the follow up period (1992-1998) Method of assessing risk factor/exposure 1:Self-report Covariates/potential confounders adjusted for in analyses:Age Sex Educational level Physical health at baseline Mental health at baseline. Method(s) of assessing cognitive status:Other – Recall of 15 words from the Auditory verbal learning test. Informant interview?:No 

1) Follow-up rate: 3805 participants recruited in the first sample which was collected for a different study. Of this, 3107 participated in the T1 phase of the LASA study. Of the 698 who did not participate, 126 (18%) dies, 134 (19%) were too disabled to participate, 394 (56%) refused and 44 (6%) could not be contacted. 2545 (82%) participated in T2 and 2076 (67%) participated in T3. Of the participants in T1, 1144 met the inclusion criteria to be included in this analysis. 2) Important baseline differences: Attrition of the sample was related to lower memory at baseline, being male, having chronic diseases or having lower functional ability. 3) Outcome of interest #1: Memory decline was observed in 33% of the widowed men and 17% of the widowed women while one 17% of the non widowed men and 13% of non widowed women had memory decline. There was a statistically significant difference between widowed and non widowed men: χ2= 6.6; p<0.05 but 

not for women χ2= 2.3; p=0.13. 

CommentsThere were differences who were lincluded in Quality assFor observ1) Unbias

cohort?

2) Selectio

differenfactors

3) Sample 

differen

4) Adequa

cohort?

5) Validat

ascerta

6) Validat

ascertaYes 

7) Outcom

exposu

8) Adequa9) Comple

Can’t T

10) Analys

confou

11) Analyti

Yes. 
B-2

Study Study Information Participants Risk Factor and 

Outcome Assessment 

Results Comments

Abbott, White, Ross, et al., 2004 Honolulu Heart Program, HonoluluAsia Aging Study (HAAS) 

Geographical location: Honolulu, Hawaii Setting:Community Study design: Prospective cohort Number of participants enrolled:Initially 3734; Final sample of 2257. Duration of follow up:Mean “nearly” 7 years Time from risk factor assessment to final cognitive assessment:Mean “nearly” 7 years 

Age:Mean (SD): Miles walked/day: <0.25: 77.4 (4.4) 0.25-1: 77.3 (4.2) <1-2: 76.6 (3.8) >2: 76.0 (3.6) Sex:

Female: 0% Male: 100% Race/ethnicity:Japanese ancestry 

Baseline cognitive status:Non-demented Inclusion criteria:  Survivors of the original Honolulu Heart Program cohort.  Japanese ancestry.  Men physically capable of exercise, as defined by having presented for a baseline clinical exam and reported slight or moderate activities in a 24-hour period. Exclusion criteria:Prevalent dementia.  Poor cognitive function whose dementia status could not be confirmed.  Prevalent 

Risk factor/exposure 1:Physical activity, specifically walking Method of assessing risk factor/exposure 1:Self report. “Participants were asked about the average amount of distance walked per day.” Other--Physical Activity Index (referenced in paper, but not described, other than saying it is a common measure of daily metabolic output). Also assessed physical function at baseline via battery of test, for a “physical performance score.” Covariates/potential confounders adjusted for in analyses:Age; APOE; Baseline CASI; Declines in activity since mid adulthood Method(s) of 

1) Follow-up rate: 2257 out of 3734 (60.4%). Initial Honolulu Heart Program had 8006 men. 3734 of survivors initially potentially eligible for this study. Excluded from f/u: men who died (n=377), prevalent dementia (n=145), poor cognitive function (n=75) whose dementia status couldn’t be confirmed, Parkinsons (n=39), prevalent stroke (n=116), missing data on physical activity (n=194), failed to present for a clinic visit (n=112), no slight or moderate activity (n=76), smokers (n=161), use of walker or cane (n=27). 2) Important baseline differences: NA 3) Outcome of interest #1 Incidence of dementia: 158 (15.6/1000 person-years).  Among these, 101 (10.0/1000 person-yrs) were attributed to AD and 30 (3.0/1000 p-y) attributed to vascular dementia as sole or primary cause.  27 cases (2.7/1000 prs-yrs) with mixed AD and other dementia.  Median time from baseline exam to Dx was 4.7 yrs (range: 2.4-7.4). 4) Outcome of interest #2--Dementia Men who walked the least (<0.25 mile/d) experienced a 1.8 fold excess of total dementia compared to those 

CommentsNone 

Quality assFor observ1) Unbias

cohort?

2) Selectio

differenfactors

3) Sample 

differen

4) Adequa

cohort?

5) Validat

ascerta

6) Validat

ascertaYes 

7) Outcom

exposu

8) Adequa9) Comple

Yes 

10) Analys

confou

11) Analyti

Yes 
B-3

Study Study Information Participants Risk Factor and 

Outcome Assessment 

Results Comments

Parkinson’s disease or stroke.  Subjects with missing data on physical activity.  Continued employment.  Daily activities failed to meet criteria for being slight or moderate.  Smokers.  Use of walker or cane. 

assessing cognitive status: Initial screening with CASI <74.  3 screening phases.  NINCDS-ADRDA  DSM IIIR  Other: Informant Questionnaire on Cognitive Decline in the Elderly Informant interview?:Yes 

who walked the most (> 2 mile/d). Compared with men who walked the most (> 2 mile/d), an excess of dementia was observed in those who walked 0.25 to 1 mile/d (17.6 vs. 10.3/1000 person-yrs; RH, 1.71; 95% CI, 1.02-2.86). (RH = relative hazard) After adjusting for covariates, a 1.9-fold excess risk of total dementia wasfound in me who walked less than 0.25 mile/d compared to those who walked > 2 mile/d (RH, 1.93; 95% CI, 1.11-3.34). Compared with the most active men, those who walked 0.25 to 1 mile/d experienced a 1.7-fold excess in dementia risk (RH, 1.75; 95% CI, 1.03-2.99). 5) Outcome of interest #3—Alzheimer’s Disease There was an 1.8-fold excess of AD in men who walked 2 mile/d or less vs. those who walked more than 2 mile/d. An association between walking and vascular dementia was less apparent. After adjusting for covariates, risk of AD was 2.2-fold higher in men who walked the most (RH, 2.21; 95% CI, 1.06-4.57). 6) Outcome of interest #4—Timed walk “The focus of this report is on day-today activity; however, a faster timed walk at baseline eval was also 
B-4

Study Study Information Participants Risk Factor and 

Outcome Assessment 

Results Comments

associated with a decreased ageadjusted incidence of dementia.” 

ADAPT Research Group, 2007 

Geographical location: Baltimore, MD Boston, MA Rochester, NY Seattle, WA Sun City, AZ Tampa. FL Setting:Community Study design: RCT Test intervention: Celecoxib 200mg BID ORNaproxen Sodium 220mg BID Comparator intervention(s): Placebo Number of participants enrolled:2528 Duration of follow up: ~735 days Time from risk factor assessment to final cognitive assessment:RCT with annual 

Age:Mean (SD): 74 Range: 70-90 Sex: [n (%)] 

Female: 1160 (45.9%)Male: 1368 (54.1%) Race/ethnicity: [n (%)] White, non-Hispanic 2452 (97%) African-American 38 (1.5%) Hispanic 18 (0.7%) Other 20 (0.8%) Baseline cognitive status:Non-demented For MCI analyses baseline status excluded those with prevalent MCI/PrAD But all have first degree relatives with AD Inclusion criteria: ≥ 70 yo; h/o at least 1 first degree relative w/ Alzheimer-like dementia; aspirin use of ≤ 81 mg/day allowedExclusion criteria:Regular use of NSAIDS 

Risk factor/exposure

1:nsaid Method of assessing risk factor/exposure 1:RCT with naproxen, celecoxib, placebo Covariates/potential confounders adjusted for in analyses:Randomization stratified by age group, field site Method(s) of assessing cognitive status:

NINCDS-ADRDA

DSM Informant interview?:Yes 

1) Follow-up rate: 83-5% follow up but nearly half “terminated drug” 2) Important baseline differences: p’s not given, nothing looks obvious 3) Outcome of interest #1: Neither tx associated with a decreased risk of AD. 4) Outcome of interest #2: HR for possible increased risk of AD celecoxib 4.11 (1.3-13), naproxen 3.57 (1.09-11.7) 

CommentsStudy termAlmost half drug Quality assFor RCTs: 1) Baselin2) Valid A

assess

3) Subjec4) Outcom

Partial 

5) Incomp

addres

6) Differen

10%?:Y

7) Overall 8) Conflic

insignif

9) Random10) Allocat

adequa
B-5

Study Study Information Participants Risk Factor and 

Outcome Assessment 

Results Comments

cognitive screeningTime varied because of termination of trial – 75th percentile ~830 days 

Aggarwal, Bienas, Bennett, et al., 2006 CHAP Study 

Geographical location: 3 southside Chicago neighborhoods (Morgan Park, Washington Heights, & Beverly) Setting:Community Study design:

Prospective cohort Number of participants enrolled:

6158 Duration of follow up: mean 4.1 (range 0.4 – 6.9) Time from risk factor assessment to final cognitive assessment:mean 4.1 (range 0.4 – 6.9) 

Age:Mean (SD): 73.1 Range: ≥65 Sex: [n (%)] 

Female: 61.9% Male: 38.1% Race/ethnicity: [n (%)] AA 49.8% Other 50.2% Baseline cognitive status:Non-demented Inclusion criteria: ≥ 65 yo;

institutionalized residents included Exclusion criteria:

NR 

Risk factor/exposure

1:Smoking Method of assessing risk factor/exposure 1:Self-report 

Covariates/potential confounders adjusted for in analyses:Age Race Sex Educational level Freq participation in cog act. APOE Time from baseline to cog eval Method(s) of assessing cognitive status:NINCDS-ADRDA Informant interview?:No 

1) Follow-up rate: 1064/1527 (69.7%)2) Important baseline differences: NR 3) Outcome of interest #1: Current smokers at greater risk of AD than never smokers Former smokers not at greater risk of AD than non-smokers (Ever smoked vs never smoke did not show increased risk of AD for smoking) 4) Outcome of interest #2 Current smokers, no e4 – increased risk of AD Former smoker, e4 – reduced risk of AD 5) Outcome of interest #3 Current smokers, pack yrs did not assoc with risk Former smokers, as pack years increased, AD risk decreased 

CommentsFor Q1 Quality assFor observ1) Unbias

cohort?

2) Selectio

differenfactors?

3) Sample 

differen

4) Adequa

cohort?

5) Validat

ascerta

6) Validat

ascertaPartial 

7) Outcom

exposu

8) Adequa9) Comple

Can’t te

10) Analys

confou

11) Analyti

Yes 
B-6

Study Study Information Participants Risk Factor and 

Outcome Assessment 

Results Comments

Akbaraly, HiningerFavier, Carriere, et al., 2007 EVA Study 

Geographical location: Nantes district, France Setting:Community Study design: Prospective cohort Number of participants enrolled:702 completed 9 waves of data collection (Numbers vary by analyses, but this seems to be the maximum in any analyses). Duration of follow up:9 yrs Time from risk factor assessment to final cognitive assessment:9 yrs from baseline, but risk factor collected each wave also. Analyses looked at parallel change in risk factor level and cognitive performance 

Age:Mean (SD): 65 (3.0) yrs Sex: [n (%)] 

Female: 436 (62.1) Male: 266 (37.9) Race/ethnicity: [n (%)] NR Baseline cognitive status:Non-demented – this is not stated but is assumed. Only those that were followed for 9 yrs were included in the analyses, so it is likely that anyone demented at baseline would have been able to still do the cognitive tests 9 yrs later. Inclusion criteria: Born between 1922-1932 Living in Nantes district of France Recruited from electoral rolls and information campaigns When ind enrolled automatically asked spouse to participate. Exclusion criteria: None 

Risk factor/exposure

1: selenium Method of assessing risk factor/exposure 1:Direct measurement Covariates/potential confounders adjusted for in analyses:Sex Educational level Time period of observation Baseline plasma selenium level Diabetes Hypertension Dyslipidemia Hx of cardiovascular disease 

Method(s) of assessing cognitive status: Other – cognitive decline on multiple measures using both continuous change as outcome and dichotomous outcomes using two cutoffs (25th

and 10th percentiles of change) The analytical approach(mixed models) takes into 

1) Follow-up rate: 702/1288 (denominator excludes those who did not complete fup due to death)2) Important baseline differences: NR reported by exposure group 3) Outcome of interest #1 9-yr change in selenium was associated with 9 yr continuous change in MMSE only (CI=0.12-0.62). It was not significant for other cognitive measures. 4) Outcome of interest #2 Change in selenium during the 1st 2 

years of the study was not associated with cognitive change in years 1-9 of the study 5) Outcome of interest #3 Using the categorical cognitive decline measure, cognitive decline at either the 25th or the 10th percentile 

was significant for MMSE, DSS, TMTB (but not at both cut points). Only FTT was significant at both impairment cut points. 

CommentsQuestion 2 Did not covbecause it with changQuality assFor observ1) Unbias

cohort?electora

2) Selectio

differenfactors

3) Sample 

differen

4) Adequa

cohort?

5) Validat

ascerta

6) Validat

ascertaYes 

7) Outcom

exposuprobab

8) Adequa9) Comple10) Analys

confou

11) Analyti

Yes 
B-7

Study Study Information Participants Risk Factor and 

Outcome Assessment 

Results Comments

 account the baseline 

score Informant interview?:No 

Akbaraly, Portet, Fustinoni, et al., 2009 3 City Study 

Geographical location: Dijon (n=4931) Montpelier (n=2259) France Setting:Community 1999-2001 Study design: Prospective cohort Number of participants enrolled:5692 Duration of follow up:4 yr Time from risk factor assessment to final cognitive assessment:4 yr 

Age:Mean (SD):  73.7(SDNR) Range: ≥65 Sex: [n (%)] 

Female: 3468 (60.9%)Male: 2238 (39.1%) Race/ethnicity: [n (%)] NR Baseline cognitive status:Non-demented Inclusion criteria: ≥ 65 Had both F/U appts leisure activity Ques Complete baseline information Exclusion criteria:dementia 

Risk factor/exposure 1:16 leisure activities at baseline, categorized as stimulating, passive, physical or social and analyzed by tertiles Method of assessing risk factor/exposure 1:2 Self-report Ques. Daily with 3 pt scale Monthly with 4 pt scaleCovariates/potential confounders adjusted for in analyses:Age Sex Study center (Dijon or Montpelier) Marital status Educational level Occupational grade Health status –  Vascular risk factors  Diabetes  HTN  High cholesterol  Hx of CVD  Depressive sx  CES-D > 16 

1) Follow-up rate: 92.3% of cohort had F/U data This was a retrospective analysis of prospectively collected data 2) Important baseline differences: 

Participants varied on numerous socio-demographic and clinical factors across the tertiles of leisure activities 3) Outcome of interest #1 All cause dementia over time (161 new cases over 4 y) Stimulating activities related to reduced risk: HR = 0.46, CI=0.27/0.80; independent of other proxies for CR, vascular disease risk factors, and other leisure activities BUT if control for cognitive impairment at baseline as well as health status, CI includes one and association is now a trend 4) Outcome of interest #2 Alzheimer’s Disease over time (105 new cases over 4 y) Stimulating activities related to reduced risk: HR = 0.50, CI=0.33/0.78; independent of other proxies for Cognitive Reserve, vascular disease risk factors, and other leisure activities 

CommentsQuestion 1 Quality assFor observ1) Unbias

cohort?

2) Selectio

differenfactorsbaselinlast ana

3) Sample 

differen

4) Adequa

cohort?

5) Validat

ascertascales 

6) Validat

ascertaYes 

7) Outcom

exposu

8) Adequa9) Comple

Yes 

10) Analys

confou

11) Analyti

Partial leisure demenby prop
B-8

Study Study Information Participants Risk Factor and 

Outcome Assessment 

Results Comments

 Physical fx  AODL (score > 0)  Cognitive impairment MMSE (score <24)  APOE genotype Method(s) of assessing cognitive status: 3-step process:Neuropsych tests Individual assessment Committee review using NINCDS-ADRDA And DSM-IV criteria Informant interview?:No 

BUT if control for cognitive impairment at baseline as well as health status, CI includes one and association becomes trend 5) Outcome of interest #3 In the most adjusted model, the HR for AD by tertile was: Stimulating leisure activities High: 0.39 (0.21-0.71) Mild: 0.45 (0.26-0.77) Ref Passive leisure activities: High: 0.68 (0.41-1.13) Mild: 1.02 (0.62-1.69) Ref Physical leisure activities: High: 1.29 (0.80-2.09) Mild: 0.87 (0.50-1.51) Ref Social leisure activities: High: 0.70 (0.41-1.21) Mild: 1.06 (0.67-1.68) Ref In a sensitivity analysis excluding those with low MMSE at baseline, then those with incident AD at 1st

follow-up, then those with MCI at baseline, stimulating leisure activities remained associated with a lower risk of AD 

(time scpoint). BUT powas furmaking becauswas nodistribuactivitieWere oexaminwith ancompasame? shown. 
B-9

Study Study Information Participants Risk Factor and 

Outcome Assessment 

Results Comments

Akomolafe, Beiser, Meigs, et al., 2006 Framingham Study 

Geographical location: Framingham, Massachusetts, USA Setting:Community Study design: Prospective cohort Number of participants enrolled:2210 Duration of follow up:12.7 years Time from risk factor assessment to final cognitive assessment:Varies. Diabetes was assessed at each of the biennial exams. 

Age:Mean (SD): 70 years (7.0) Sex: [n (%)] 

Female: 1325 (60%) Male: 885 (40%) Race/ethnicity:NR Baseline cognitive status:Normal Non-demented Inclusion criteria:  Participants in the Framingham study  Not demented Exclusion criteria:MCI or dx as having dementia 

Risk factor/exposure 1:Diabetes mellitus Method of assessing risk factor/exposure 1:Self-report Direct measurement Medical record Covariates/potential confounders adjusted for in analyses:Age Race Sex Educational level Baseline cognitive status Total homocysteine Smoking Alcohol BP Cardiovascular risk factors Stroke Method(s) of assessing cognitive status:NINCDS-ADRDA Informant interview? Can’t tell 

1) Follow-up rate: 2210/2611= 84.6% 2) Important baseline differences: DM>control Male Sex, systolic BP, BMI, stroke, other cardiovascular risk factors Control>DM Education >12 years, <2 alcoholic drinks/day 3) Outcome of interest #1

17 of 202 persons with DM (8.4%) and 220of 2008 persons without DM (11.0%) developed AD RR 1.15 (95% confidence interval, 0.65-2.05).4) Outcome of interest #2 Among subjects without an apolipoprotein E 4 allele or elevated plasma homocysteine levels, 44 of 684 persons (6.4%) developed AD. RR diabetics with nondiabetics 2.98 (95% confidence interval, 1.06-8.39; P=.03).

Age >75 years and DM RR incident AD 4.77 (95% confidence interval, 1.28- 17.72; P=.02).

CommentsResults madifferences could be asQuality assFor observ1) Unbias

cohort?

2) Selectio

differenfactors

3) Sample 

differen

4) Adequa

cohort?

5) Validat

ascerta

6) Validat

ascertaYes 

7) Outcom

exposu

8) Adequa9) Comple

Yes 

10) Analys

confou

11) Analyti

Yes 

Alvarado, Zunzuneg

Geographical location: 

Age:Range:65-89 yrs old 

Risk factor/exposure 1:

1) Follow-up rate:  557/964 = 57.7% 

CommentsNone 
B-10

Study Study Information Participants Risk Factor and 

Outcome Assessment 

Results Comments

ui, Del Ser, et al., 2002 Aging in Leganes Study 

Leganes, Spain Setting:Community Study designProspective cohort Number of participants enrolled:964 enrolled 557 completed follow up Duration of follow up:4 years Time from risk factor assessment to final cognitive assessment:4 years 

Sex:

Female: 294(52.7%) Male: 263(47.3%) Race/ethnicity:NR Baseline cognitive status:Non-demented Inclusion criteria: At least 65 yrs old, living at home, without severe cognitive impairment or visual impairment, low educational level (without primary school completion) Exclusion criteria:Severe cognitive deficit(92 subjects excluded) Visual impairment (unable to see 23-point characters)(102 subjects excluded) 

educational attainment Method of assessing risk factor/exposure 1:Self-report 1) illiterate 2) literate (no formal educ, can read and write) 3) 1-3 yrs of formal education 4) 4 or more years of formal education Then reclassified into 2 categories: 1) incomplete primary school 2) complete primary school Risk factor/exposure 2: occupation Method of assessing risk factor/exposure 2:Self-report Lifelong occupation, according to the Spanish National Classification of Occupations 5 categories: 1) white collar and skilled workers 2) semiskilled 

2) Important baseline differences: NA 3) Outcome of interest #1557 subjects completed follow up. Total 176 subjects combined experienced decline: 61 subjects (11%) experienced severe decline (> 1 SD below mean, -8 to-23/32) 115(20.6%) experienced mild decline.(change within 1SD below mean, -2 to-7/32) Less than primary education vs complete primary risk of cognitive decline: OR 1.49(95%CI:0.92-2.43) Less than primary and farm worker vs complete primary and non-farm worker: OR 2.36(95%CI 1.16-4.81) Less than primary and non-farm worker vs complete primary and nonfarm worker: OR 1.39(95% CI: 0.85-2.29) Farm workers vs non-farm workers: OR 1.79 (95% CI:0.99-3.23) 4) Outcome of interest #2 Authors’ conclusion: “the association of low education level with cognitive decline is supported by our study” among a Spanish population with low levels of formal education 

Quality assFor observ1) Unbias

cohort?

2) Selectio

differenYes 

3) Sample 

differen

4) Adequa

cohort?

5) Validat

ascertaeducatoccupa

6) Validat

ascertaYes (auhas be

7) Outcom

exposu

8) Adequa9) Comple

attrition 

10) Analys

confou

11) Analyti

Yes 
B-11

Study Study Information Participants Risk Factor and 

Outcome Assessment 

Results Comments

3) unskilled 4) housewives 5) farm workers Reclassified to: 1) farm workers 2) others Method of assessing risk factor/exposure 3: Combined education and occupation. 1) primary school and not farm workers 2) no primary school and farm workers 3) no primary school and not farm workers Method(s) of assessing cognitive status:“Cognitive function assessed via items involving orientation and memory that have been validated for people with low levels of education.” Total cumulative score (range 0-32) at baseline and 4-yr f/u. Both continuous and change scores in 3 categories: 1) “mild decline” = -2 to -7 
B-12

Study Study Information Participants Risk Factor and 

Outcome Assessment 

Results Comments

2) “severe decline” -8 to -23 2) “normal” = -1 to 12 Covariates/potential confounders adjusted for in analyses:Age Sex Educational level Baseline cognitive status Occupation Method(s) of assessing cognitive status: Other – Cognitive decline over 4 years. Short Portable Mental Status Questionnaire (SPMSQ) Informant interview?:No 

Alves de Moraes, Szklo, Knopman, et al., 2002 ARIC Study 

Geographical location:  Forsyth County, NC  Jackson, MS  Minneapolis, MN  Washington County, MD Setting:Community Study design: 

Age:Mean (SD): 56.7 (5.6) Sex:

Female: 51.7% Male: 48.3% Race/ethnicity:White 6342 (78.7%) Other: 1716 (21.3%) Baseline cognitive 

Risk factor/exposure

1:htn Method of assessing risk factor/exposure 1: Self-report  Direct measurement htn defined by self report, use of antihypertensive meds, 

1) Follow-up rate: 11320/15782 (72%) had both follow up visits. Final n of 8058 by excluding those with strokes, tias, missing cognitive scores, or cns meds 2) Important baseline differences: I see baseline differences between those who followed up and those who didn’t but not between those with and without htn.

CommentsNone Quality assFor observ1) Unbias

cohort?

2) Selectio

differenfactors

3) Sample 

differen
B-13

Study Study Information Participants Risk Factor and 

Outcome Assessment 

Results Comments

Prospective cohort Number of participants enrolled:8058 Duration of follow up: 6 years Time from risk factor assessment to final cognitive assessment:risk factor assessment done at beginning and end of six year period. Cognitive testing also at both visits. 

status: Subjects don’t appear to have been screened on the basis of cognitive functioning. Inclusion criteria: Participating in ARIC Study (Atherosclerosis Risk in Communities) Exclusion criteria:

 History of stroke or transient ischemic attack in visit 2 and/or visit 4  Taking medications that may affect the central nervous system Missing cognitive test scores in either visit 

or sbp >140 or dbp > 

90. Four categories: nl bp, incident htn, partially controlled htn (one or other visits had nol bps) and uncontrolled htn. Covariates/potential confounders adjusted for in analyses:Age, Race, Sex, Educational level, diabetes Method(s) of assessing cognitive status: change in test scoreInformant interview?:No 

3) Outcome of interest #1 In comparing each category of htn to normotensive subjects, the only significant difference was that between uncontrolled hypertensives and normotensives for the DSS score. In data not shown this is limited to inidividuals over the median age of the cohort (>56 yrs at the first visit considered here). 

4) Adequa

cohort?

5) Validat

ascerta

6) Validat

ascertaYes 

7) Outcom

exposu

8) Adequa9) Comple

Yes 

10) Analys

confou

11) Analyti

Yes 

Andel, Crowe, Pedersen, et al., 2008 The HARMONY Study Swedish Twin Registry 

Geographical location: Sweden Setting:Community Study design: Case-control design and co-twin control design “Prospective casecontrol” (i.e., participants in a casecontrol study in 1967 

Age:Mean (SD): 48.1 (4.9) at baseline and 79.5 (5.0) at f/u. Sex:

Female: 61% Male: 39% Race/ethnicity:NR Baseline cognitive status:Normal Demented 

Risk factor/exposure 1:Light exercise or hard physical training at midlife Method of assessing risk factor/exposure 1:Self-report: “How much exercise have you had from age 25 to 50?” 0=hardly any 1=light exercise 2=regular exercise 3=hard physical 

1) Follow-up rate: 3134/4506 = 70%. 3366 participated in telephone screening and/or clinical w/u for dementia. 1372 drop outs (who were 1.5 yrs older, more women, fewer high education level, less likely to drink alchohol). Some differences in exercise levels also. 2) Important baseline differences: Cases were older than controls, but the groups did not differ in time of 

CommentsMethod of anot reporteQuality assFor observ1) Unbias

cohort?

2) Selectio

differenfactors

3) Sample 

differen

4) Adequa

cohort?

5) Validat
B-14

Study Study Information Participants Risk Factor and 

Outcome Assessment 

Results Comments

follow-up in 1998) Number of participants enrolled:4506 were eligible to be contacted by HARMONY in 1998. 3366 participated in telephone screening and/or w/u for dementia. 3134 in final analysis (includes 655 twin pairs). 70% response rate. Duration of follow up:31 years Time from risk factor assessment to final cognitive assessment:31 years 

Inclusion criteria:  All living twins in the STR cohorts of twin pairs who completed a questionnaire in 1967 or 1970 and who underwent dementia assessment in 1998 or later as part of the HARMONY study.  HARMONY inclusion criteria include all twins in the STR who were living and 65 years or older in 1998.  Controls were selected from the community (including persons in long-term care). Exclusion criteria:

NR 

training Covariates/potential confounders adjusted for in analyses:Age Sex Educational level Other—diet, BMI, alcohol, smoking, angina. Also explored lifestyle as a possible effect modifier Method(s) of assessing cognitive status: Two-stages: screen followed by clinical evaluation. “Telephone screening and/or clinical work-up for dementia.” Informant interview?Yes 

follow-up. 3) Outcome of interest #1Of 3134, 264 had dementia (176 with AD). 4) Outcome of interest #2  Case-control analysis  Crude OR (95% CI), with hardly 

any exercise as the reference: Dementia

light exercise: 0.61 (0.44-.086) regular exercise: 0.21 (0.10-0.45) hard training: 0.78 (0.46-1.30) AD

light exercise: 0.62 (0.41-0.93) regular exercise 0.21 (0.09-0.52) hard training: 0.78 (0.46-1.30) No effect modifiers for lifestyle factors were identified. Adjusted OR (95% CI), with hardly 

any exercise as the reference: Dementia

light exercise: 0.63 (0.43-0.91) regular exercise: 0.34 (0.16-0.72) hard training: 0.70 (0.40-1.24) AD

light exercise: 0.64 (0.41-1.00) regular exercise 0.34 (0.14-0.86) hard training: 0.65 (0.33-1.29) 5) Outcome of interest #3  Co-twin control analysis “There was a statistical trend indicating that twins who exercised 

ascerta

6) Validat

ascertaYes 

7) Outcom

exposu

8) Adequa9) Comple

Partial 

10) Analys

confou

11) Analytic 

Yes 
B-15

Study Study Information Participants Risk Factor and 

Outcome Assessment 

Results Comments

more than their co-twins had reduced odds of dementia in analyses with and without controlling for education.” Adjusted OR for co-twin controls association between exercise and dementia: 0.66 (95% CI: 0.24-1.83) 

Anonymous, 2002 The Heart Protection Study 

Geographical location: 69 UK sites Setting:Clinical – Special, hospital based study clinics Study design: RCT; 2*2 factorial Test intervention: Simvastatin 40mg daily; antioxidant vitamins Comparator intervention(s):Placebo Number of participants enrolled:20,536 (10,269 intervention; 10, 267 placebo) Duration of follow up:Mean= 5 years Time from risk factor 

Age:Range:~40 – 80 years Sex: [n (%)] 

Female: 5082 (24.7%)Male: 15454 (75.3%) Race/ethnicity: [n (%)] NR Baseline cognitive status:Non-demented (no existing diagnosis at baseline; no screening or formal assessment done) Inclusion criteria: Age about 40-80  Total cholesterol >= 135 mg/dl  High risk for death from CHD Exclusion criteria: GP determined statin is clearly indicated  Chronic liver or renal disease  severe CHF 

Risk factor/exposure

1:statin Method of assessing risk factor 1:Direct measurementcalendar packed tablets Method(s) of assessing cognitive status: 1. modified Telephone interview for cognitive status at final follow-up only 2. Dementia – assessment method not specified but appears to be nonstudy clinician diagnosis Informant interview?:No 

1) Follow up rate:>99% m-TICS score <22/39 at final followup:  23.7% simvastatin vs. 24.2% placebo; p=ns Mean m-TICS at final follow-up (unadjusted):  24.08 simvastatin vs. 24.06 placebo; difference between group means = 0.02 [SE 0.07] Incident dementia (dementia/total):  31/10,269 (0.3%) simvastatin vs. 31/ 10267(0.3%) placebo (no p value) 

CommentsPoor meas(TICS may change) Poor assesQuality assFor RCTs:1) Baselin2) Valid A

assessm

3) Subject4) Outcom

for TICS

5) Incomp

address

6) Differen

Yes 

7) Overall 8) Conflict 

insignifi

9) Random10) Allocati

adequa
B-16

Study Study Information Participants Risk Factor and 

Outcome Assessment 

Results Comments

assessment to final cognitive assessment:Mean = 5 years 

 inflammatory muscle disease  conditions limiting adherence (e.g. dementia or psychiatric disorder) 

Applegate, Pressel, Wittes, et al., 1994 SHEP study 

Geographical location:USA, Multicenter Setting:Community Study design: RCT – double-blind, placebo controlled Test intervention: Chlorthalidone 12.5 or 25mg daily, step 1 – atenolol 25 or 50m mg or reserpine 0.05 or 0.10 mg daily Comparator intervention(s): Matching placebo Number of participants enrolled:4736 in sample overall; 1993 had detailed cognitive assessment (987 intervention, 1006 control) Duration of follow up:Mean 5 years 

Age:Mean (SD): 71.6 (6.7) Sex: [n (%)] 

Female: 807 (57%) Male: 566 (43%) Race/ethnicity: [n (%)] White non-Hispanic (79.2%) Black 13.85 Hispanic 1.8% Asian 4.3% Other 0.9% Baseline cognitive status:Non-demented Inclusion criteria: Mean SBP 160-219 and DBP <90 mmHg Exclusion criteria:History or signs of major CV disease likely to require pharmacologic and other treatment; other major diseases (e.g., cancer) with competing risk factors for primary endpoint; h/o 

Covariates/potential confounders adjusted for in analyses:None Method(s) of assessing cognitive status:Other – Short care cognitive assessment; Digit symbol substitution; addition test; findings A’s test; Boston Naming Test; Letter Sets Test; Delayed Recognition Span Test Informant interview?:No 

1) Follow-up rate: 1564/1993 2) Important baseline differences: None 3) Outcome of interest #1 Mean short care cognitive impairment assessment (placebo change minus intervention change) = 0.05 (95% CI -0.0006 – 0.11); intervention declined more but not statistically significant 4) Outcome of interest #2 “There were no significant 

differences in the mean changes between treatment and control groups for any of the cognitive function tests” (data not given) 5) Outcome of interest #3 Dementia: 37/2365 in intervention group; 44/2371 in control group; OR 0.84 (0.54-1.31) Adverse effect leading to drug discontinuation: intervention group 665/2365, control group 493/2371; OR 1.49 (1.30-1.70) 

CommentsNone Quality assFor RCTs: 1) Baselin2) Valid A

assess

3) Subjec4) Outcom5) Incomp

addres

6) Differen

10%?:Y

7) Overall 8) Conflic

insignif

9) Random10) Allocat

adequa
B-17

Study Study Information Participants Risk Factor and 

Outcome Assessment 

Results Comments

Time from risk factor assessment to final cognitive assessment:5 years 

dementia, alcohol abuse 

Arvanitakis, Grodstein, Bienias, et al., 2008 Religious Orders Study 

Geographical location: Numerous US locations Setting:Community –Religious orders Study design: Prospective cohort Number of participants enrolled:1019 Duration of follow up: annual follow up from one to 12 years Time from risk factor assessment to final cognitive assessment:Variable because risk factor info collected at each annual assessment. Time between risk factor and final outcome could be between 1 and 12 years follow-up 

Age:Mean: 75 yo Sex: [n (%)] 

Female: 707 (69.4%) Male: 312 (30.6%) Race/ethnicity: [n (%)] NR Baseline cognitive status:Non-demented Inclusion criteria: Enrolled in Religious Order Study; agree to annual clinical evaluations & brain donation upon death Exclusion criteria:Dementia at baseline 

Risk factor/exposure

1:nsaids/asa Method of assessing risk factor/exposure 1:inspection of pill bottles at each assessment Covariates/potential confounders adjusted for in analyses:Age Sex Education, vasc risk factors, E4 Method(s) of assessing cognitive status:NINCDS-ADRDA Other: cognitive change on multiple tests Informant interview?:No 

1) Follow-up rate: 1019/1102 had at least one annual follow-up assessment 2) Important baseline differences: nsaid users, more women, higher sbp. ASA users: older, to be male, more mi’s, more cva’s 3) Outcome of interest #1 Risk of AD not different according to use of nsaid or asa baseline. 4) Outcome of interest #2 nsaids vs not AD 1.19 (0.87-1.62) 5) Outcome of interest #3 ASA vs not AD 0.84 (0.63-1.11) 6) Outcome of interest #4 Cognitive decline on multiple measures was not associated with use of NSAIDS or ASA (p values ranged from 0.14 to 0.77) 

CommentsHighly educQuality assFor observ1) Unbias

cohort?

2) Selectio

differenfactors

3) Sample 

differen

4) Adequa

cohort?

5) Validat

ascerta

6) Validat

ascertaPartial 

7) Outcom

exposu

8) Adequa9) Comple10) Analys

confou

11) Analyti

Yes 
B-18

Study Study Information Participants Risk Factor and 

Outcome Assessment 

Results Comments

Arvanitakis, Schneider, Wilson, et al., 2008 Religious Orders Study 

Geographical location: Multiple US sites Setting:Community Study design: Prospective cohort Number of participants enrolled:1011 929 with ≥ 1 yr f/u analyzed Duration of follow up:1 – 12 yrs (mean NR) Time from risk factor assessment to final cognitive assessment:1 – 12 yrs 

Age:Mean (SD):  Group A 72.7 (6.1)  Group B 75.2 (7.1) Sex:

Female: 638 (69%) Male: 291 (31%) Race/ethnicity: [n (%)] NR Baseline cognitive status:Normal Non-demented Inclusion criteria: “Older Catholic Clergy”Exclusion criteria:Dementia 

Risk factor/exposure 1:Statin  simvistatin 32  lovastatin 33  atorvastatin 35  pravastatin 12  fluvastatin 5 antidiabetic agents Method of assessing risk factor/exposure 1:Other – medication containers inspected Risk factor/exposure 2:Vascular disease summary score (MI, CHF, claudication, stroke) Vascular risk factor summary score (HTN, diabetes, smoking) Method of assessing risk factor/exposure 2:Self-report Other – clinical exam for stroke Covariates/potential confounders adjusted for in analyses:Age 

1) Follow-up rate: 

929 of 1011 (91.8%) HR for AD = 0.91 (95% CI 0.54 to 1.52), adjusted for age, sex, education, Analysis that added vascular disease score and vascular risk factor score “did not change this finding” Interaction effects were nonsignificant for : statins and vascular diseases or risk factors or ApoE e4 Continuous outcome: Statin use associated with change in cognition adjusted for age, sex and education. Regression coefficient, (Standard error), p value Global cognition: -0.014, (0.012,) p=0.245 Episodic memory: -0.017, (0.016), p=0.290 Semantic memory: -0.008, (0.013), p=0.529 Working memory: -0.009, (0.009), p=0.321 Perceptual speed: -0.006 (0.013), p=0.617 Visuospatial ability: -0.009, (0.010), p=0.329 (unsure when f/u assessment was performed) Continuous outcome [see instructions above] 

CommentsF/U time is in cognition appropriatechange mastatin use eQuality assFor observ1) Unbias

cohort?

2) Selectio

differenfactors

3) Sample 

differen

4) Adequa

cohort?

5) Validat

ascerta

6) Validat

ascertaPartial 

7) Outcom

exposu

8) Adequa9) Comple

Yes 

10) Analys

confou

11) Analyti

Yes 
B-19

Study Study Information Participants Risk Factor and 

Outcome Assessment 

Results Comments

Race Sex Educational level In a separate model, they also added vascular risk factors and stroke as covariates. Method(s) of assessing cognitive status:NINCDS-ADRDA Other – change in performance on cognitive tests over time Informant interview?:No 

Atti, Palmer, Volpato, et al., 2008 Kungsholmen Project 

Geographical location: Kungsholmen area of Stockholm, Sweden Setting:Community Study designProspective cohort Number of participants enrolled:1255 Duration of follow up:9 years Time from risk factor 

Age:Mean (SD): 80.8 (4.5) Sex: [n (%)] 

Female: 925 (73.71%)Male: 330 (26.29) Race/ethnicity: [n (%)] NR Baseline cognitive status:Normal Non-demented Inclusion criteria: All residents of the Kungsholmen area 

Risk factor/exposure 1:Obesity Method of assessing risk factor/exposure 1:Direct measurement Covariates/potential confounders adjusted for in analyses:Age Sex Educational level Baseline cognitive status Depressive symptoms 

1) Follow-up rate:646/1255 *100= 51.47% of those not in the follow-up sample 291 subjects were deceased at follow-up and 189 had incident dementia. Only 170 dropped out and 98 lacked BMI measurement. 2) Important baseline differences: The sample had more women More women were underweight More men had chronic disease at baseline. 3)Outcome of interest #1 Overweight subjects (n575, 22.5%) had a lower risk of developing AD over 9 years of follow-up (HR50.66, 95% CI50.50–0.88), which 

Commentsstudy are oother studiepopulations Though andone, unsudementia wQuality assobservation1) Unbias

cohort?

2) Selectio

differenfactors

3) Sample 

differen

4) Adequa
B-20

Study Study Information Participants Risk Factor and 

Outcome Assessment 

Results Comments

assessment to final cognitive assessment:9 years 

Exclusion criteria:

Diagnosis of dementia;Unknown educational level, Baseline MMSE score less than 20, Very old age (≥95) 

Impairment in ADLs Chronic disease at baseline. Method(s) of assessing cognitive status:DSM III (agreement among 3 physicians. If they disagree, patient examined by third) Informant interview?:No 

was confirmed when only incident cases occurring between 6 and 9 years were considered (n 521, 15.3%; HR50.67, 95% CI50.40–1.15)4) Outcome of interest #2 (The following include all types of dementia) Risk of Developing Dementia at Different Follow-Up Times (Risk Periods) According to Baseline Body Mass Index (BMI) after adjusting for sex, age, education, baseline MiniMental State Examination score, depressive symptoms, chronic disease up to baseline, and impairment in activities of daily living Obesity as a continuous variable: HR 0.96 (0.92-1.01) (incident dementia between years 3 and 9 of follow up)  HR 0.98 (0.94-1.00) (incident dementia between years 1 and 9 of follow up) HR 0.97 (0.91-1.04) (incident dementia between years 6 and 9 of follow up) Categorical, n (%) HR (95% CI) for dementia between years 3 and 9 of follow up In BMI < 20.0 (underweight) 26 (30.9) 0.91 (0.59–1.40) In BMI 20.0–24.9 (normal weight) 115 (31.7) 1 (reference) And in BMI ≥25.0 

cohort?

5) Validat

ascerta

6) Validat

ascertaYes 

7) Outcom

exposu

8) Adequa9) Comple10) Analys

confou

11) Analyti

Yes 
B-21

Study Study Information Participants Risk Factor and 

Outcome Assessment 

Results Comments

(overweight/obese) 55 (23.6) 0.72 (0.52–1.02 
B-21

Study Study Information Participants Risk Factor and 

Outcome Assessment 

Results Comments

Ball, Berch, Helmers, et al., 2002 ACTIVE Trial 

Geographical location: 6 metropolitan areas USA Setting:Community, Clinical – hospital and clinics, Other – senior housing Study design: RCT Test intervention: 3 different groups: -Training memory -Reasoning training -Speed processing training  A subgroup of each had a booster at 11 months Comparator intervention(s): No contact group Number of participants enrolled:2832, of this 2802 analyzed (30 excluded due to inappropriate randomization). Duration of follow up:2 years Time from risk factor 

Age:Mean (SD): 73.6 (5.9) Range: 65-94 Sex: [n (%)] 

Female: 2127 (75.9%)Male: 675 (24.1%) Race/ethnicity: [n (%)] White: 2054 (73.3%)  AA: 729 (26.0%) Other: 19 (0.7%)Baseline cognitive status:Non-demented MMSE above 22. Mean MMSE 27.3 (SD 2.0) (range 23-30) Inclusion criteria: Independent living Older than 65 Able to perform ADLs independently At risk for cognitve decline but without it yet. 

Exclusion criteria: 

-Younger 65y -MMSE lower 22 -Self report AD dx. -Substantial functional decline -Medical condition that could predispose to severe functional decline or death. 

Covariates/potential confounders adjusted for in analyses:Age, Sex, Educational level, Baseline cognitive status (they state this was done with overall pattern of results being similar but data not shown) Method(s) of assessing cognitive status: Other – specific to each of the interventions (see bove for each intervention measurement). Measures completed at: baseline, Immediate post test, first annual and second annual Memory composite: Hopkins verbal learning test, auditory verbal learning verbal test, Rivermead Behavioral Memory test. Reasoning composite:Word series, Letter series, letter sets. 

1) Follow-up rate: 2802 included in analysis. (at 2 year follow up a total of 2244 assessed (80%), drop outs due to death, protocol violations, withdrawal due to scheduling, illness or lack of interest in continuing). 2) Important baseline differences: Randomized group was Slightly younger(mean 74 vs 75), more educated (13.5 vs 12.3 years), higher MMSE scores (27.3 vs 26.8) and fewer non white (27 vs 40%). This is in comparison with non randomized group (refused participation) there is no actual description of baseline characteristics or differences among intervention groups vs. control! 3) Outcome of interest #1

 Every day problem solving at 2 years: Effect size compared to control: Memory training (-0.073), Reasoning training (-0.027), Speed training (0.031); p=ns for all Proportion showing improvement at 2 years (>1 SEM above baseline): Memory training (21%), Reasoning training (25%), Speed training (26%), control (23%) 4) Outcome of interest #2 ADL and IADL functioning. Proportion showing improvement at 2 years (>1 SEM above baseline): Memory training (17%), Reasoning 

CommentsQuestion 5 60% of the where giveand this daseparately. For RCTs: 1) Baselin

Tell 

2) Valid A

assess

3) Subjec4) Outcom5) Incomp

addresdropou

6) Differen

Yes 

7) Overall 

Yes 

8) Conflic

insignifpart owmakes speed o

9) Random10) Allocat

adequa
B-22

Study Study Information Participants Risk Factor and 

Outcome Assessment 

Results Comments

assessment to final cognitive assessment:2 annual post test (2 years) 

- Severe loss of vision (20/70), hearing or communication abilities. - Prior participation in cognitive trials (recent cognitive training). Planning to move out of the area 

Speed of processing

Useful field of view tasks 2-4.. Informant interview?:No 

training (16%), Speed training (17%), control (17%) 5) Outcome of interest #3 Everyday speed post test Proportion showing improvement at 2 years (>1 SEM above baseline): Memory training (33%), Reasoning training (29%), Speed training (30%), control (29%) 6) Outcome of interest #4 Driving habits Proportion showing improvement at 2 years (>1 SEM above baseline): Memory training (16%), Reasoning training (16%), Speed training (16%), control (18%) For the 4 primary outcomes assessed in each of the intervention groups, the effects were generally small (most below 0.10) and did not differe significantly in both assessments at 1 year or 2 years after intervention. Therefore no training effects on everyday function where detected at 2 years. Measurement of proximal outcome composites was performed (this is not their primary outcomes) Here they measured memory, reasoning and speed as outlined in previous column. Each intervention improved the targeted cognitive ability compared with baseline, durable to 2 years (p <.001 for all). Booster sessions enhanced training gains significantly in reasoning and 
B-23

Study Study Information Participants Risk Factor and 

Outcome Assessment 

Results Comments

speed (p.001) but not for memory. 

Barnes, Alexopoulos, Lopez, et al. 2006 Cardiovascular Health Study 

Geographical location: 4 US counties (NC, MD, CA, PA) Setting:Community Study designed: Prospectively Number of participants enrolled:5888 in overall cohort; 2220 in this analysis Duration of follow up:6 years Time from risk factor assessment to final cognitive assessment:6 years from initial assessment. 

Age:Mean: 74 Range: 64-92 Sex: [n (%)] 

Female: 1310 (59%) Male: 910 (41%) Race/ethnicity: [n (%)] African-Amer 200 (9%)Other (predom White) 2020 (91%) Baseline cognitive status:Non-demented (3ms>9=0) Inclusion criteria:  Medicare eligible  Live in 4 selected U.S communities  Age >=65  Able to respond to questions  MRI and 3MS completed Exclusion criteria: Institutionalized  Cancer treatment  Wheelchair bound  No baseline lipid or statin use data  Dementia  3MS < 90 at baseline

Risk factor 1Current DepressionCEDS 10-item (0-30) >=8 at baseline Method of assessing risk factor 1: [ 

Self-report Risk factor 2 Antidepressant medication use at baseline Method of assessing risk factor 2:Direct measurementmedication bottles Covariates/potential confounders adjusted for in analyses:

 Age  Race  Sex  Educational level  Baseline cognitive status  Vascular disease 

Method(s) of assessing cognitive status:Other –Clinical and neuropsych testing. MCI = “poor cognitive function that reflected a 

1) Follow-up rate: CT 2) Important baseline differences:Depressed subjects were more likely to be female and had higher clinical and subclinical vascular disease 3) Out come of interest #1 MCI Incidence (296 cases)  CESD 0-2: Reference  CESD 3-7: OR 1.37 (95% CI 1.00 to 1.88)  CESD >=8: OR 2.09 (1.46 to 2.97)  Stratified analysis by gender, age <=75, race, baseline 3MS, education <12, APOE e4 and antidepressant use did not show significant differences in the odds ratios 4) Outcome of interest #2 Continuous outcome [see instructions above] 

Comment:High cognit(3MS >=90Quality assFor observ1) Unbias

cohort

2) Select

differefactors

3) Sampl

differe

4) Adequ

cohort

5) Validat

ascerta

6) Validat

ascertaYes 

7) Outcom

exposu

8) Adequ

Yes 

9) Compl

Can’t T

10) Analys

confou

11) Analyt

Yes 
B-24

Study Study Information Participants Risk Factor and 

Outcome Assessment 

Results Comments

decline from prior level” but w/o dementia Informant interview?: No

Barnes, Cauley, Lui, et al., 2007 Study of Osteoporotic Fractures (SOF) Study 

Geographical location: Baltimore, MD Minneapolis, MN Portland, OR Monongahela Valley, PA Setting:Community Study design: Prospective cohort Number of participants enrolled:9704 Duration of follow up:Median 10 yrs (range 6-15) Time from risk factor assessment to final cognitive assessment:Median 10 yrs (range 6-15) 

Age:Mean (SD): 71.7 (5.3) Range: 65-99 Sex: [n (%)] 

Female: 9704 (100%) Male: 0 (0%) Race/ethnicity: [n (%)] “primarily white” (>99%) Baseline cognitive status:Non-demented *May have included some demented, but unlikely to be many as 1st follow-up 

assessment was 6 yrs after baseline Inclusion criteria: ≥ 65 yo; participating in the Study of Osteoporotic Fractures Study; Exclusion criteria: NR 

Risk factor/exposure

1:smoking Method of assessing risk factor/exposure 1:Self-report Risk factor/exposure 2:depression and social networking Method of assessing risk factor/exposure 2:gds at year 2 Lubben Social Network Scale at year 2 Covariates/potential confounders adjusted for in analyses:Age Educational level Baseline cognitive status Study site Method(s) of assessing cognitive status: 

1) Follow-up rate: over 15 yrs attrition due to causes other than death 832/9704 (9%) Attrition due to death was 4040/9704 (42%) 2) Important baseline differences: 3 outcome groups differed on almost all baseline characteristics: age, educ, baseline cog score, stroke, DM, HTN, distance walked daily, smoking, ETOH, physical performance, IADL, vision, self-rated health, depressive sxs, social network 3) Outcome of interest #1 Lack of smoking increased likelihood of maintaining cognition 4) Outcome of interest #2  Lack of DM increased likelihood of maintaining cognition 5) Outcome of interest #3 Lack of poor social network increased likelihood of maintaining cognition 

Comments26 pt mmsemmse, lowgroup as a Quality assFor observ1) Unbias

cohort?

2) Selectio

differenfactors

3) Sample 

differen

4) Adequa

cohort?

5) Validat

ascerta

6) Validat

ascertaPartial 

7) Outcom

exposu

8) Adequa9) Comple

Yes 

10) Analys

confou

11) Analyti

Yes 
B-25

Study Study Information Participants Risk Factor and 

Outcome Assessment 

Results Comments

Other – Cognitive decline in a modified version of the MMSE (26 pts). Grouped as maintain cognition, minor decline, major decline Informant interview?:No 

Barnes, Mendes de Leon, Wilson, et al., 2004 Chicago Health and Aging Project 

Geographical location: Chicago USA Setting:Community Study design:

Prospective cohort Number of participants enrolled:

6158 Duration of follow up:mean of 5.3 years Time from risk factor assessment to final cognitive assessment:3-6 years 

Age:Mean (SD): 73.94 (6.46) Sex: [n (%)] 

Female: 3827 (62.2%) Male: 2331 (37.8%) Race/ethnicity: [n (%)] African American:3824 (62.1%) White: 2334 (37.9%) Baseline cognitive status:Normal Non-demented MCI CIND AAMI AACD (they did not exclude cognitively impaired at baseline) Inclusion criteria: Participant in Chicago Health and Aging Project; ≥ 65 yo; 

Risk factor/exposure

1:Social network Method of assessing risk factor/exposure 1:Self-report Risk factor/exposure 2:Social engagement Method of assessing risk factor/exposure 2:Self-report (range 0-8) Covariates/potential confounders adjusted for in analyses:Age Race Sex Educational level Marital status and income 

1) Follow-up rate: Baseline cohort: 6,102 1,241 died before the first follow-up interview 473 persons were lost to follow-up Of the remaining 4,388 people, 3,899(88.9%) completed at least one follow-up interview; 3,899 or 6,102 original cohort (63.9%) 2) Important baseline differences: NR 3) Outcome of interest #1 After controlling for age, sex, race, education, marital status, and income, for each social network there was a 0.002 unit (SE 0.001) reduction in rate of cognitive decline p = 0.001 4) Outcome of interest #2 Frequency of social engagement was strongly related to rate of cognitive decline, with a reduction of 0.009 unit (SE 0.001) for each point on the social engagement scale. 

CommentsThis article who had cobaseline. In same popusample had baseline. Quality assFor observ1) Unbias

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B-26

Study Study Information Participants Risk Factor and 

Outcome Assessment 

Results Comments

completed ≥ 1 followup 

Exclusion criteria:NR 

Method(s) of assessing cognitive status: A composite of the MMSE, Immediate and delayed recall of East Boston Story, and Symbol Digit Modalities Test using the average of z scores Informant interview?:

No 

5) Outcome of interest #3Results were not affected after the analyses was done after dropping the participants lowest 10 percentile of cognition. 

10) Analys

confoucontrol status. 

11) Analyti

Yes. 

Bernick, Katz, Smith, et al., 2005 Cardiovascular Health Study (CHS) 

Geographical location: 4 US Counties (NC, MD, CA, & PA) Setting:Community Study design: Prospective cohort Number of participants enrolled:5880 in overall cohort 3334 for this analysis Duration of follow up:Mean of 5.1 years Time from risk factor assessment to final cognitive assessment:Mean of 5.1 years from initial assessment 

Age:Mean (SD): 72.9 (3.6) to 75.9 (5.8) Sex:

Female: 2014 (60.4%)Male: 1320 (39.6%) Race/ethnicity:Non-black 2776 (83.3%) Black 558 (16.7%) Baseline cognitive status:Non-demented (3MS>80) Inclusion criteria: Medicare eligible; live in 4 selected US communities; ≥ 65 yo; 

able to respond to questions; underwent study MRI 

Risk factor/exposure

1:No statin; Intermittent statin (2-4 yrs continuous Tx or 3-5 yrs nonconsecutive use); Continuous statin (>4 yrs continuous Tx) Method of assessing risk factor/exposure 1:Direct measurement – medicine bottles Risk factor/exposure 2:Age, sex, educational level (self-report), cholesterol, APOE e4 (direct measurement) Method of assessing risk factor/exposure 

1) Follow-up rate: Uncertain Continuous outcome [ 3MS Baseline values, mean (SD) Continuous (n=293): 93.7 (4.5) Intermittent (n=158): 92.9 (4.6) No treatment (n=2,031): 92.9 (4.9) No treatment (diet recommended, n=501): 92.9 (5.1) No treatment (drug recommended, n=351): 93.1 (4.9) 3MS Unadjusted mean change per year* Continuous (n=293): -0.26 (-0.56 to 0.05) Intermittent (n=158): -0.50 (-0.92 to -0.09) No treatment (n=2,031): -0.75 (-0.86 to -0.63) No treatment (diet recommended, n=501): -0.61 (-0.85 to -0.38) No treatment (drug recommended, 

CommentsMany excludid not confactors – buincident TIAassess beccohort, then (legitimatelcould have yrs f/u cogndata). Time assessmenassessmenassessed rQuality assFor observ1) Unbias

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B-27

Study Study Information Participants Risk Factor and 

Outcome Assessment 

Results Comments

Exclusion criteria:

Institutionalized; CA Tx; wheelchair-bound; no baseline lipid or statin use data; 3MS score ≤ 80 or no 

baseline; < 2 yrs cognitive testing; incident TIA or stroke 

2:Self-report Direct measurement Covariates/potential confounders adjusted for in analyses:

age, gender, race APOE e4, cholesterol Method(s) of assessing cognitive status:Other – 3MS Informant interview?:No 

n=351): -0.73 (-1.01 to -0.45) 3MS adjusted mean change per year (age, gender, race APOE e4, cholesterol) Continuous (n=293): -0.27 (-0.61 to 0.06) Intermittent (n=158): -0.45 (-0.89 to -0.01) No treatment (n=2,031): -0.76 (-0.89 to -0.63) No treatment (diet recommended, n=501): -0.61 (-0.87 to -0.36) No treatment (drug recommended, n=351): -0.70 (-1.02 to -0.38) * not specified but should represent f/u – baseline since it is described as a decline 

cohort?

5) Validat

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6) Validat

ascertaYes 

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exposu

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Yes 

Berr, Balansard, Arnaud, et al., 2000 EVA Study 

Geographical location: Nantes district, France Setting:Community Study design: Prospective cohort Number of participants enrolled:1389 Duration of follow up:4 yr Time from risk factor assessment to final cognitive 

Age:Mean 65.0 (3.0): Sex:

Female: 684 (58.7) Male: 482 (41.3) Race/ethnicity:NR Baseline cognitive status:Non-demented (this is assumed based on the age of the sample. Demented not overtly excluded, but assume few demented at baseline) 

Risk factor/exposure

1:Selenium Method of assessing risk factor/exposure 1:Direct measurement Risk factor/exposure 2:carotenoids Method of assessing risk factor/exposure 2:Direct measurement Risk factor/exposure 3:

1) Follow-up rate: 1166/13892) Important baseline differences: Compared based on TBAR level (not sure how to apply to other risk factors) TBAR > 75th%tile had greater ETOH 

use, fewer never smoked individuals, higher cholesterol, lower RBC vit E, higher TBAR level 3) Outcome of interest #1 Selenium -<25th %tile vs >25%tile OR=1.58 (1.08-2.31) for cog decline 4) Outcome of interest #2 Plasma carotenoids -<25th %tile vs 

>25%tile OR=1.17 (0.75-1.81) for cog decline 

CommentsQuestion: Q Quality asFor observ1) Unbias

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B-28

Study Study Information Participants Risk Factor and 

Outcome Assessment 

Results Comments

assessment:4 yr 

Inclusion criteria: Born between 1922-1932 Living in Nantes district of France Enrolled from electoral rolls and, to a lesser extent, ad campaigns. When ind enrolled automatically asked spouse to participate. Exclusion criteria:

None 

RBC vit E Method of assessing risk factor/exposure 3:Direct measurement Covariates/potential confounders adjusted for in analyses:Age Sex Educational level Baseline cognitive status Depressive sxs ETOH and tobacco useBMI Cholesterol triglycerides 

Method(s) of assessing cognitive status: Other – cog decline defined as loss of 3 pts on MMSE –represented worse 15th%tile change Informant interview?:No 

5) Outcome of interest #3 RBC Vit E -<25th %tile vs >25%tile 

OR=1.04 (0.68-1.56) for cog decline 

exposu

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Yes 

Beydoun, Kaufman, Satia, et al., 2007 ARIC 

Geographical location: Four US communities (NC, MS, MN, & MD) Setting:Community 

Age:Mean (SD):  No decline: 56.2 (4.2) Decliners:57.7(4.2) Sex: [n (%)] 

Female: 50.7% 

Risk factor/exposure 1:n-3 fatty acids; mean values compared and OR for 1 SD difference.Method of assessing 

1) Follow-up rate: 2251 with all data available out of 7814 enrolled overall 2) Important baseline differences: Reported differences between decliners and non-decliners at 

CommentsThere are mthis paper wresults and Question: Q
B-29

Study Study Information Participants Risk Factor and 

Outcome Assessment 

Results Comments

Study design: Prospective cohort Number of participants enrolled:7814 2251 with all data used in this analyses Duration of follow up:9 yrs overall 6 yrs for two cognitive assessments used Time from risk factor assessment to final cognitive assessment:9 yrs from blood draw to final cognitive assessment used in analyses cognitive decline was measured over 6 yrs 

Male: 49.3% Race/ethnicity: [n (%)] 

White 100% Baseline cognitive status:Those with impairment are not intentionally excluded – but given the age range of the sample at baseline, suspect most met criteria for normal cognition Inclusion criteria: a) complete plasma fatty acid data, b) survived to visit 4, c) complete cognitive data visits 2 and 4, e) age 50 or older at baseline Exclusion criteria:opposite of the inclusion criteria 

risk factor/exposure 1:Direct measurement Covariates/potential confounders adjusted for in analyses:Age Sex Educational level Smoking, ETOH, caffeine use Physical activity index BMI Dietary factors Baseline cognitive status (essentially did this but in somewhat more elaborate manner) Considered as effect modifiers: APOE Comorbid med cond Method(s) of assessing cognitive status:Other – Cognitive decline using Reliable change index for 3 tests: COWA, DSST, and delayed word recall test Informant interview?:No 

baseline: Non-decliners were younger, more physically active, less depressive sxs, relatively hypocoagulable profile.Decliners had higher baseline cognitive score 3) Outcome of interest #1- 

Numerous results given for comparisons (selected ones given here) a) Total PUFA- no decliners higher mean values than decliners (OR=0.55; 0.37-0.81) b)palmitic acid-no decliners lower than decliners (OR=1.28; 1.07,1.54) c) greater DHA (OR=.0.74; 0.57-0.97) and EPA (OR=0.73; 0.58-0.93) associated with less decline on verbal fluency 

Quality assFor observ1) Unbias

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Yes 

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Partial 
B-30

Study Study Information Participants Risk Factor and 

Outcome Assessment 

Results Comments

Beydoun, Kaufman, Sloane, et al., 2008 Atherosclerosis Risk in Communities (ARIC) 

Geographical location: Four US communities (NC, MS, MN, & MD) Setting:Community Study design: Prospective cohort Number of participants enrolled:7814 Duration of follow up:9 yrs Time from risk factor assessment to final cognitive assessment:9 yrs but need to look at how replicate FFQ info used – cognitive decline was measured over 6 yrs 

Age:Mean (SD): 56.6 (4.31) Median: Range: 50-65 Sex: [n (%)] 

Female: 54.6% Male: 45.4% Race/ethnicity: [n (%)] White 81.5% Baseline cognitive status:Those with impairment are not intentionally excluded – but given the age range of the sample at baseline, suspect most met criteria for normal cognition Inclusion criteria: a) complete dietary intake data at visit 1, b) survived to visit 4, c) complete cognitive data visits 2 and 4, e) age 50 or older at baseline Exclusion criteria:opposite of the inclusion criteria 

Risk factor/exposure 1:Dietary Assessment Method of assessing risk factor/exposure 1:Self-report Food Frequency questionnaire Risk factor/exposure 2: Blood assay of dietary data Method of assessing risk factor/exposure 2:Self-report Direct measurement of blood pressure for all subjects and blood 

samples for subset at visit 1(n=2251) Covariates/potential confounders adjusted for in analyses:Age Race Sex Educational level Baseline cognitive status (essentially did this but in somewhat more elaborate manner) 

1) Follow-up rate: for self-report dietary data – 7814. For blood assay of dietary data – 2251. Only those who had all data were included in analyses. 2) Important baseline differences: N/A 3) Outcome of interest #1- a) adjusted analyses b) decline in word list recall modestly reduced with increase in long-chain n-3 fatty acid intake (3H) as % of total energy intake c) decline in verbal fluency reduced by increase in long-chain and all n-3 fatty acids (3H and 3) as % of total energy intake, by ratio 3H/6H and by 3Hin g day-1

4) Outcome of interest #2 interaction with HTN a) finding 3b above maintained in HTN subgroup b) for DSST, interaction for ratio 3H/6H with HTN - showed less decline for HTN compared to nonHTN c) finding 3c above stronger in HTN with a sig interaction for 3H in gday -1

5) Outcome of interest #3 Subgroup with plasma – a) generally less decline with higher concentration of n-3 fatty acid in their plasma cholesteryl esters and 

CommentsNo results frequency mQuality assFor observ1) Unbias

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B-31

Study Study Information Participants Risk Factor and 

Outcome Assessment 

Results Comments

APOE Behavioral factors Nutritional factors Hypertension Method(s) of assessing cognitive status:Other – Cognitive decline using Reliable change index for 3 tests: COWA, DSST, and delayed word recall test Informant interview?:No 

phospholipids and elevated ratio of n-3/n-6 fatty acids– but generally not significant except for verbal fluency b) for verbal fluency, HTN group showed less decline for 3H and 3H/6H for plasma cholesteryl esters and 3H/6H for plasma phospholipids 

Bierman, Comijs, Rijmen, et al., 2008 LASA Study 

Geographical location: The Netherlands Setting:Community Study design:

Prospective cohort Number of participants enrolled:

2351 Duration of follow up:Up to 9 years Time from risk factor assessment to final cognitive assessment:

Age:at baseline Mean (SD): 69.5 (8.6) Sex: [n (%)] Female: 1097 (46.7%)Male: 1254 (53.3%) Race/ethnicity: [n (%)] NR Baseline cognitive status:Not specified MMSE = 27.31 (2.4) Inclusion criteria: Random sample of 55-85 y.o. from 11 municipalities in the Netherlands 

Risk factor/exposure

1:Anxiety at 4 time pointsMethod of assessing risk factor/exposure 1:Self-report; Hospital Anxiety and Depression Scale – Anxiety subscale: 0-7=normal; 8-10 =mild anxiety, >10 = moderate/severe anxiety Covariates/potential confounders adjusted for in analyses:Age 

1) Follow-up rate: 1469/2351 (62.5%) at year 9 Drop-out was associated with age, gender, education, more anxiety symptoms and lower cognitive performance 2) Important baseline differences: NR 3) Outcome of interest #1No significant association between anxiety symptoms and cognitive decline for any of the cognitive tests (parameter estimates not reported) 

CommentsSubsample those inviteand femalewere less liAnalysis nonormal cogUsed randoQuality assFor observ1) Unbias

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B-32

Study Study Information Participants Risk Factor and 

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Results Comments

Up to 9 years Analyses restricted to 

those age 62 and older with snxiety and cognition measured at baseline Exclusion criteria:

NR 

Sex Educational level Chronic disease count Depressive symptoms Alcohol consumption Benzodiazapine use Method(s) of assessing cognitive status:

Other – measured at 4 timepoints: General cognitive functioning: MMSE (0-30) Fluid intelligence: Ravens coloured progressive matrices (0-24) Processing speed: adjusted version of coding task (2-53) Episodic memory auditory verbal learning test: 3 learning trials (0-45); delayed recall (0-15) Informant interview?:No 

cohort?

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ascerta

6) Validat

ascertaYes 

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exposu

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Yes 

Blair, Folsom, Knopman, et al., 2005 ARIC 

Geographical location: Medicare files Forsyth County,NC; Jackson, MS; suburban Minneapolis, MN; Washington County, MD Setting:

Age:Mean (SD): 55 SD varied by APOE genotype Sex: [n (%)] 

Female: not specifically stated, but APOE genotype, but approximately 60% 

Risk factor/exposure 1:APOE ε4Method of assessing risk factor/exposure 1:Direct measurement Genotyping 

1) Follow-up rate: 7895/15,792= 50% 2) Important baseline differences: Higher cholesterol, LDL and lower HDL in E4 groups; in AAs E4 carriers had increased carotid intima-media thickness; Caucasians homozygous for E4 more likely to have diabetes and less likely to be hypertensive. 

CommentsHigh dropocognitive stExcluded pmedicationQuality assFor observ1) Unbias

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B-33

Study Study Information Participants Risk Factor and 

Outcome Assessment 

Results Comments

Probability sample Community Study design: Prospective cohort Number of participants enrolled:1693 AfricanAmericans and 6202 Caucasians used in analysis Duration of follow up:6 years Time from risk factor assessment to final cognitive assessment:6 years 

female in AA population; 49% women in Caucasians Male: AA ~40% White ~51% Race/ethnicity: [n (%)] 

78.6 % white 21.4 % blackBaseline cognitive status:Non-demented Inclusion criteria: Men and women age 45 to 64 at enrollment. AAs sampled exclusively in Jackson and over-sampled in Forsyth County. Exclusion criteria:Missing cognitive data; did not have apoe genotyping, incident or prevalent stroke, taking antidepressants, anxiolytics, sedatives, anticonvulsants, narcotics, antipsychotics, or chemotherapy. 

Covariates/potential confounders adjusted for in analyses: Age, sex, education, baseline cognitive scores, cigarette smoking, use of NSAIDs, diabetes, hypertension, hypercholesteremia Method(s) of assessing cognitive status: Delayed word recall (DWR); Digit Symbol Substitution (DSS); Word Fluency (aka controlled oral word association test) Informant InterviewNo 

DSS was only cognitive test different among APOE genotypes- lowest in E4/4 caucasians even after adjustment for age, sex and education. Not significant in AAs after adjustment. 3) Outcome of interest #1 AA: (adjusted for age, sex, education, education, baseline score, hypertension, DM) only the DSS showed a dose-response relation between APOE genotype and performance. E4/4 declined by 3.99 symbols, E3/3 declined by 0.98; and E2 group (E2/2 and E2/3) declined by 0.43 symbols (p=0.002) Risk for decline in AA E4/4 

compared to E3/3 DWR OR = 1.72 (95% CI 0.97-3.06) DSS OR= 1.86 (1.06-3.27) Caucasians: (adjusted for age, sex, education, education, baseline score, hypertension, DM) the DWR and DSS showed a dose-response relation between APOE genotype and performance. DSS test: E4/4 declined by 4.54; E4/2 or E4/3 group declined by 3.20 symbols, E3/3 declined by 2.69; and E2 group (E2/2 and E2/3) declined by 2.51 symbols. (p<.0001)DWR scores: E4/4 declined by .31; words; E4/2 or E4/3 group declined by .21 words, E3/3 declined by .13 words; and E2 group (E2/2 and E2/3) declined by .06 words. (p=.02) 

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Partial 

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Yes 
B-34

Study Study Information Participants Risk Factor and 

Outcome Assessment 

Results Comments

Risk for decline in Cauc. Compared to E3/3 genotype E2 group DWR OR = .78 (95% CI .61-.98); E4 group (E3/4 or E2/4) DWR OR 1.19 (1.01-1.41) and E4/4 OR DWR 1.53 (0.95-2.45) DSS OR E4/4 compared to E3/3 = 2.02 (1.31-3.12) Word fluency was not related to APOE genotype in AA or caucasians.4) Outcome of interest #2 Interaction between APOE genotype and other risk factors. Interaction between APOE and hypercholesterolemia (p value for interaction = 0.008) Interaction between APOE genotype and diabetes mellitus (p value for interaction = 0.04) 

Blasko, Jellinger, Kemmler, et al., 2008 VITA 

Geographical location: Vienna, Austria Setting:Community Study design: Prospective cohort Number of participants enrolled:606 Duration of follow up: 30 months 

Age:Mean (SD): 75.8 (0.5) Sex: [n (%)] 

Female: 359 (59.4%) Male: 247 (40.6%) Race/ethnicity: [n (%)] NR Baseline cognitive status:Non-demented Inclusion criteria: Age ≥ 75 

Risk factor/exposure 1:homocysteine ; analyzed as log transformed values Method of assessing risk factor/exposure 1:Direct measurement plasma stored frozen doesn’t say for how long, doesn’t say if fasting or not. Covariates/potential 

1) Follow-up rate: 83.2% of the 119 lost to follow up, 38 died, 1 was dxd schizophrenic, 10 had only telephone interviews and 70 refused. 2) Important baseline differences: Not clearly stated. . No information on the low vs high homocysteine at baseline groups. 3) Outcome of interest #1: The change in homocysteine over 2.5 years for those who converted to AD: OR for AD in those with doubling of homocysteine 4.2 (1.6-11.0) 

CommentsQuestion 1 Quality assFor observ1) Unbias

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Study Study Information Participants Risk Factor and 

Outcome Assessment 

Results Comments

Time from risk factor assessment to final cognitive assessment:Change in homocysteine, so 0-30 months 

Complete baseline data Exclusion criteria:

Dementia Schizophrenia 

confounders adjusted for in analyses:Age, Sex, Educational level, at least one apoE4 Method(s) of assessing cognitive status:NINCDS-ADRDA DSM MCI diagnosed if one of CERAD neuropsychatric test ≥1.5 SD below the meanInformant interview?:No 

4) Outcome of interest #2: For persons who deteriorated to mci OR AD, OR for AD in those with doubling of homocysteine 2.2 (1.2-4.1), for just conversion to mci alone, table notes “no association” but data not given. 

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Yes 

Borenstein, Wu, Mortimer, et al., 2005 Kameproject (whose participants were followed in the Ni-HonSeaProject) 

Geographical location: King County, WA Setting:Community Study design: Prospective cohort Number of participants enrolled:Initial cohort of 3045 eligible participants; 1985 baseline screened; 1859 enrolled. 

Cases (n=90)Age:Mean (SD): 78 yrs Sex:

Female: 61 (68%) Male: 29 (32%) Non Cases (n=1769) Age:Mean (SD): 72 yrs Sex:Female: 978 (55%) Male: 791 (45%) Race/ethnicity:Predominantly 

Risk factor/exposure

1:Diabetes mellitus Method of assessing risk factor/exposure 1:Self-report Risk factor/exposure 2:Is the presence of Apolipoprotein E-(ApoE) a risk factor for AD? Method of assessing risk factor/exposure 2

1) Follow-up rate: Obtained ApoE genotyping on 1111/1859(59%) 2) Important baseline differences: NA 3) Outcome of interest #1Cox proportional hazard models for vascular risk factors, by positive ApoE status demonstrated a HR 0.51 with a 95% CI 0.12-2.26. 4) Outcome of interest #2 The risk for AD was stronger for women who carried ApoE 4 allele than for men. 

CommentsNone Quality assFor observ1) Unbias

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B-36

Study Study Information Participants Risk Factor and 

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Results Comments

Duration of follow up:Cognition was assessed at baseline and at each of four follow up waves. Subjects with a score of >87/100 were followed every 2 yrs. Those with scores of 87 or less at any biennial follow up were then evaluated with a full evaluation. Total follow up: 6 yrs Time from risk factor assessment to final cognitive assessment:6 yrs(SD =2.7) 

Japanese American Baseline cognitive status:Non-demented Inclusion criteria: 65 yrs and older; free of AD at baseline Exclusion criteria:

NR 

Direct measurement Covariates/potential confounders adjusted for in analyses:Age Race Sex Educational level Baseline cognitive status Developmental risk factors Vascular risk factors Method(s) of assessing cognitive status:NINCDS-ADRDA DSM-IV Other – Cognitive Abilities Screening Instrument(CASI) Informant interview?:No 

Women who carried an ApoE 4 allele was also higher ( HR=2.37,95%CI 0.93-6.01,p=0.07) than for those who did not (HR=0.98,95%CI 0.47-2.04) Women who were negative for ApoE 4 allele: HR 0.98, 95%CI 0.47-2.04, p=0.95. 

Yes 

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exposu

8) Adequa9) Comple

Partial; 59% 

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confou

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Yes 

Bosma, van Boxtel, Ponds, et al., 2002 Maastricht Aging Study” (MAAS)

Geographical location:The South of the Netherlands Setting:Clinical –Family practice clinics. Study design: Prospective cohort 

Age:Range: > 50 (49 – 81 at baseline) Since they stratified the sample, it is hard to get a specific age number. Sex:

Both genders included; no specific numbers reported 

Risk factor/exposure 1: Physically active sportsMethod of assessing risk factor/exposure 1:Self-report Risk factor/exposure 2:mentally active sports 

1) Follow-up rate: 1069 participants recruited. 138 refused. 50 died during follow up period and 8 developed dementia. Therefore, only 830 (77.64%) persons were used in the analysis. 2) Important baseline differences: NR 3) Outcome of interest #1: Physical activities were significantly 

CommentsNone Quality assFor observ1) Unbias

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B-37

Study Study Information Participants Risk Factor and 

Outcome Assessment 

Results Comments

Number of participants enrolled: 1823 enrolled of whom, 1069 met inclusion criteria. Duration of follow up:3 years. Time from risk factor assessment to final cognitive assessment:3 years 

Race/ethnicity:

NR Baseline cognitive status:Non-demented Inclusion criteria:  >50 yrs Exclusion criteria: Chronic neurological pathology  Mental retardation  Chronic psychotropic drug use Dementia 

(e.g., chess, puzzles) Method of assessing risk factor/exposure 2:Self-report Risk factor #3: organizational memberships (e.g., clubs) Method of assessing risk factor/exposure 3: Self report. Covariates/potential confounders adjusted for in analyses:Age Sex Educational level Baseline cognitive status Length of follow up interval. Method(s) of assessing cognitive status:Other – Stroop Color – Word Test (interference sub-task) ,  the Verbal Learning Test (immediate and delayed recall subtasks) ,  the Letter Digit 

associated with the letter digit coding. β = 0.82 p <0.05 4) Outcome of interest #2 Mental activities were significantly associated with Letter digit coding β = 0.1.18 p <0.01  and MMSE β = 0.40 p <0.01. 5) Outcome of interest #3 Social activities were significantly associated with total recall β = 0.94 

 p <0.05 and Delayed recall β = 0.30, p <0.05 6) Outcome of interest #4 Number of activities treated as a continuous variable was associated with Letter digit coding β = 0.66, p <0.01, Word fluency β = 0.34, p 

<0.05, Delayed recall β = 0.16, p 

<0.05 and MMSE β = 0.17, p <0.01 

differen

4) Adequa

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ascerta

6) Validat

ascertaYes 

7) Outcom

exposu

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Yes 
B-38

Study Study Information Participants Risk Factor and 

Outcome Assessment 

Results Comments

Coding Test ,  the Word Fluency Test ,and the Mini-Mental State Examination Method of assessing dementia: NRInformant interview?No 

Breitner, Haneuse, Walker, et al., 2009 Adult Changes in Thought (ACT) 

Geographical location: Seattle, WA Setting:Community Study design: Prospective cohort Number of participants enrolled:3392 (1994-2003) 2581 from 1994-6 811 from 2001-3 Duration of follow up:Up to 12 years Original cohort=10-12 Expansion cohort=3-5 Time from risk factor assessment to final cognitive assessment:between 3 and 12 years 

Age:Median: 74.8 Range: ≥ 65 y Sex: [n (%)] 

Female: 1636 (59.8) Male: 1100 (40.2) Race/ethnicity: [n (%)] White : 2473 (90.4) Other: 263 (9.6) Baseline cognitive status:Non-demented Inclusion criteria: ≥ 65 yo Membership in group health plan of ≥10 y 

At least one follow-up visit Exclusion criteria:Presence of dementia or AD 

Risk factor/exposure 1:NSAIDs prescribed and/or used over time Method of assessing risk factor/exposure 1:NSAID use Self-report Medical record classified as heavy use (≥ 500 Standard daily doses within 2 years); moderate 60-499 SDD; light <60 SDD Covariates/potential confounders adjusted for in analyses:(Analysis was stratified by age) Race Sex Educational level Comorbidities plausibly 

1) Follow-up rate: 

For primary analysis: At least one F/U visit= 90% By end of study, 10% withdrew and 24% had died For secondary analysis: Two or more F/U visits = 69% 2) Important baseline differences: None with standard demographics Degree of NSAID exposure  - decreased with (no surprises)  Exercise, smoking, normal wt  - increased with (no surprises)  Limitation in AODL, obesity, total prescriptions, use of H2 blockers or proton pump inhibitors, Dx of osteoarthritis At baseline, 50% were non or light users of NSAIDs, 37% were moderate users, and 13% were heavy users 3) Outcome of interest #1All-cause Dementia using pharmacy 

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B-39

Study Study Information Participants Risk Factor and 

Outcome Assessment 

Results Comments

 assoc’d with NSAIDs 

or dementia APOE status Method(s) of assessing cognitive status:2-stage evaluation with CASI, then diagnostic evaluation for CASI ≤

85; NINCDS-ADRDA DSM-IV Informant interview?:No 

data  476 (17%) In all 3 models, no reduction in risk of dementia among NSAID users; in fact, risk appears to increase c use M1 – low=1.00; mod= 1.13 (0.92-1.38); heavy=1.51 (1.18-1.94) M2– low=1.00; mod= 1.09 (0.88-1.35); heavy=1.48 (1.13-1.93) M3– low=1.00; mod= 1.13 (0.90-1.43); heavy=1.66 (1.24-2.24) This result was robust in 2° analyses 4) Outcome of interest #2 Alzheimer’s Disease 356 of 476 (13%) attributed to AD Dementia using pharmacy data In all 3 models, no reduction in risk of dementia among NSAID users; in fact, risk appears to increase c use M1 – low=1.00; mod= 1.17 (0.92-1.47); heavy=1.40 (1.05-1.87) M2– low=1.00; mod= 1.18 (0.92-1.52); heavy=1.38 (1.01-1.89) M3– low=1.00; mod= 1.26 (0.97-1.65); heavy=1.57 (1.10-2.23) This result was robust in 2° analyses 

8) Adequa9) Comple

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Bretsky, Guralnik, Launer, et al., 2003 MacArthur Successful Aging Study 

Geographical location: Durham, NC, East Boston, MA, New Haven, CT Setting:Community Study design:

Prospective cohort 

Age:Mean (SD): E4+ 73.8 (2.7) E4- 74.1 (3.0) Range: 73-79 Sex: [n (%)] 

Female: 539 (44%) Male: 426 (56%) Race/ethnicity: [n (%)] 

Risk factor/exposure 1:Apolipoprotein E genotype Method of assessing 

risk factor/exposure 1:Direct measurement Covariates/potential 

1) Follow-up rate: 88.8% at 3 years and 67.1% at 7 years 2) Important baseline differences: Distribution of E4 carriers was different by ethnicity 3) Outcome of interest #1Adjusted OR (95% CI) at year 3 in APOE e4 vs non-e4: 

CommentsParticipants top 1/3 of pto general pBaseline coby 9 questiparticipate, score ≥6, wmild demen
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Study Study Information Participants Risk Factor and 

Outcome Assessment 

Results Comments

Number of participants enrolled:965 Duration of follow up:7 years Time from risk factor assessment to final cognitive assessment:Not stated when genotyping was performed 

725 (75%) white 234 (24.4%) black 6 (0.6%) other Baseline cognitive status:Participants who scored in the top third of the cognitive and physical screening tests for their age group Inclusion criteria: Age 70-79 in 3 communities. Aim is to identify those in the top 1/3 of population. No reported disability on 7 item ADL; no more than 1 reported mild disability on 8 items of tapping, gross mobility and ROM; ability to hold a semi-tandem balance for at least 10 seconds; ability to stand from a seated position five times in 20 seconds. Cognitive criteria include scoring 6 or more on SPMSQ; remembering 3 or more of 6 elements on a delayed recall of a short story Exclusion criteria:NR 

confounders adjusted for in analyses:Age Race Sex Educational level Method(s) of assessing cognitive status:

Other – Short Portable Mental Status Questionnaire (SPMSQ); Abstraction (based on four items from similarities test of Wechsler adult intelligence scalerevised (0-16 points); delayed spatial recognition (0-17); language (Boston naming test; 0-18); spatial ability (0-20). Two summary scores were made from the subscores. Total cognition included sum of all subscores (0-89). Total memory score is composed of sum of delayed incidental and spatial recall (0-31). Decline on SPMSQ was defined as a score ≤6. A decline in other domain was defined as ≥1 SD decline from baseline score. 

Only Naming ( OR=2.7; CI = 1.2 -5.9) and Copying figures (OR =1.8; CI = 1.1-3.1) showed significant differences. Adjusted OR (95% CI) Odds of cognitive decline at year 7 In APOE e4 vs non-e4 SPMSQ 2.3 (1.5-3.4) Total cognition 2.0 (1.1-3.6) Memory 1.7 (1.1-2.5) Naming 2.5 (1.5-4.2) Figures 2.1 (1.4-3.3) Similarity 1.8 (1.1-3.1) Not significant difference Story recall 1.4 (0.9-2.1) Spatial recognition 1.3 (.9-2.0) 

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Yes 
B-41

Study Study Information Participants Risk Factor and 

Outcome Assessment 

Results Comments

Informant interview?:No 
B-42

Study Study Information Participants Risk Factor and 

Outcome Assessment 

Results Comments

Carmelli, Swan, Reed, et al., 1998 National Heart Lung and Blood Institute Twin Study (WW II veterans sub-study) 

Geographical location: USA Setting:Community Study design: Prospective cohort Number of participants enrolled: 410 Duration of follow up: 10 years Time from risk factor assessment to final cognitive assessment:10-25 years 

Age:Mean 63.2 (2.9) Range: 73 and up Sex: [n (%)] 

Female: 0 (0%) Male: 410 (100%) Race/ethnicity: [n (%)] White: 410 (100%) Baseline cognitive status:did not eliminate cognitive impaired but mean age was 63.1 (2.9) and mean mmse 27 for overall group. Inclusion criteria:  Participating in National Heart, Lung, and Blood Institute Twin Study  Evaluated for cognitive function at third and fourth cardiovascular exam Exclusion criteria:See NHLBI Twin Study, Reference 16 

Risk factor/exposure 1:htn Method of assessing risk factor/exposure 1:mean bp >140/90 or use of antihypertensive medication at any of the exams on or prior to baseline cognitive assessment (10-25 years before f/u cognitive assessment) Risk factor/exposure 2:dm Method of assessing risk factor/exposure 2:1 hour post prandial glc > 200 or use of hypoglycemic agent or insulin. Covariates/potential confounders adjusted for in analyses:

Age,Race,Sex, baseline score, incident CVD Method(s) of assessing cognitive status:

1) Follow-up rate: 410/589, 69.6% 2) Important baseline differences: baseline difference are given for apoE4 present and absent and the only significant difference was more errors in Benton visual retention test for those without apoE4 3) Outcome of interest #1 hyperglycemics experienced a significantly greater decline on dss, bvrt and mmse. 4) Outcome of interest #2 hypertensives also experienced a greater decline on the dss but not mmse and bvrt. p values (non-exact) are given for one sided significance 5) Outcome of interest #3 Subjects with dm and htn had a greater decline on the dss than those with neither risk factor and more than expected for both combined (but not significant) Mean change (SD) APOEe4 + and Hyperglyc present MMSE 1.66 (.39) DSS 7.84 (1.08) BVRT 1.05 (.26) APOEe4+ and hyperglyc absent MMSE 0.73 (.28) DSS 4.47 (.76) BVRT .53 (.19) 

CommentsNone Quality assFor observ1) Unbias

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Yes 
B-43

Study Study Information Participants Risk Factor and 

Outcome Assessment 

Results Comments

change in test scores Informant interview?:No 

APOEe4 – and hyperglyc present MMSE .47 (.2) DSS 4.14 (.56) BVRT .84 (.14) APOEe4- and hyperglyc absent MMSE .47 (.16) DSS 3.34 (.45) BVRT .37 (.11) All scores are significantly different from 0 and statistically significant at p<.05 

Cherbuin, RegladeMeslin, Kumar, et al., 2009 

Geographical location: Canberra and Queanbeyan, Australia Setting:Community Study design: Prospective cohort Number of participants enrolled:2082 (analytical sample) Duration of follow up:4 yrs Time from risk factor assessment to final cognitive assessment:4 yrs 

Age:Mean (SD): Normal Wv 2: 62.5(1.5)Mild-impaired Wv2: 62.53(1.6) Sex:

Female: 1020 (48.99%) Male: 1062 (51.01%) Race/ethnicity: [n (%)] White: 1910 (91.7%) Other: 172 (8.3%) Baseline cognitive status:Cognitively normal Inclusion criteria: At baseline, age 60-64 and cognitively normal Exclusion criteria:None except as covered by inclusion criteria 

Risk factor/exposure

Alcohol Smoking Anxiety medication Anxiety and depressive symptoms Method of assessing risk factor/exposure 1Self-report for alcohol using the AUDIT interview Self report for smoking Unclear how medication use was obtained Anxiety and depressive symptoms – Goldberg anxiety/depression scales-threshold for significant symptoms not reported Blood pressure measured Covariates/potential confounders adjusted for in 

1) Follow-up rate: 2082/2551 (81.7%) 2) Important baseline differences: Reported differences by outcome not by exposure 3) Outcome of interest #1 Incident MCI (18 incident cases): alcohol intake associated with lower risk of MCI (OR=0.59; 95% CI 0.37-0.92; p=0.021) Quadratic model – U-shaped association showing higher risk for low and high drinking groups (OR=1.58; 1.18-2.11; p=0.002) Past smoking (OR3.22; 1.05-9.87) Anxiety medication (OR 3.58; 0.97-13.22) Goldberg depression scale (OR 1.54; 1.07-2.22) and anxiety scale (OR 0.83; 0.58-1.18), antidepressant medication (OR 2.79; 0.38-20.57), Diabetes (OR 0.53; 0.06-4.6), BMI (OR 1.01; 0.91-1.11) reported in full but not reduced model used for other results. 

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B-44

Study Study Information Participants Risk Factor and 

Outcome Assessment 

Results Comments

analyses:Age Sex Educational level Method(s) of assessing cognitive status:DSM Other – published criteria for MCI, AAMI, AACD and other cognitive disorder Informant interview?:Yes (when available) 

4) Outcome of interest #2 Incident any mild cognitive disorder(MCD, n=64): alcohol intake associated with lower risk (OR=0.75; 0.57-1.00; p=0.046) Diastolic Blood pressure (OR 0.96; 0.92-0.99) Past smoking (OR 1.97; 1.12-3.44) Antidepressant medication (OR 3.25; 1.51-7.00) Anxiety medication (OR 0.67; 0.2-2.28), Goldberg depression scale (OR 1.16; 0.96-1.4) and anxiety scale (OR 0.93;0.79-1.1), diabetes (OR 1.09; 0.48-2.44), BMI (OR 1.03; 0.98-1.07) reported in full but not reduced model used for other results.Quadratic model – U-shaped association showing higher risk for low and high drinking groups (OR=1.17; 0.98-1.40; p = 0.087) 

Partial, candidafor the 

Christensen, Batterham, Mackinnon, et al., 2008 

Geographical location: Canberra and Queanbeyan Australia Setting:Community Study design: Prospective cohort Number of participants enrolled:2551 

Age:Mean (SD): 60-64 Sex: [n (%)] 

Female: 1329 (51.72%) Male: 1232 (48.28%) (This is based on the first wave). Race/ethnicity: [n (%)] All Caucasian Baseline cognitive status:

Risk factor/exposure

1:Genotype Method of assessing risk factor/exposure 1:Direct measurement Cheek swab Risk factor/exposure 2:Education Head Injury Premorbid intelligence 

1)Follow-up rate: 2551 in the first wave and 2222 in the second wave. Of the 770 234 refused or were unable to be interviewed due to medical reasons, 25 could not be located and 70 died . The rest were excluded due to study design reasons. 2) Important baseline differences: None 3) Outcome of interest #1After controlling for Head Injury, education and premorbid 

CommentsThere is no comparisonthey may bHead injury one self repnot be an aexposure. Quality assFor observ1) Unbias

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2) Selectio
B-45

Study Study Information Participants Risk Factor and 

Outcome Assessment 

Results Comments

Duration of follow up:4 years Time from risk factor assessment to final cognitive assessment:4 years 

All Inclusion criteria: 60-64% Alive at the time of second survey Those who were not genotyped Exclusion criteria:

NR 

Method of assessing risk factor/exposure 2:Self-report Direct Measurement Covariates/potential confounders adjusted for in analyses:Educational level Head Injury Premorbid intelligence Method(s) of assessing cognitive status:Other – change on word list memory task, MMSE, SDMT, Digit Span Backwards, Reaction time task Informant interview?:Yes 

intelligence, the APOE genotype was associated with change in Symbol Digit Modalities Test (SDMT) F=3.20 and p= 0.041 and digit span backwards F= 3.14, p = 0.44. 4) Outcome of interest #2 After controlling for cofactors, education was not associated with change scores in any of the cognitive tests. 5) Outcome of interest #3 After controlling for cofactors, head injury was associated with change score in MMSE F = 4.91, p = 0.027 

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Christensen, Henderson, Korten, et al., 1997 

Geographical location: Canberra and Queanbeyan, Australia Setting:Community Study design:

Prospective cohort Number of participants enrolled:

Age:Range: 70 – 97 years Sex: [n (%)] 

Female: NR Male: NR Race/ethnicity: [n (%)] NR Baseline cognitive status: Non demented 

Risk factor/exposure

1: Depression 2: Anxiety Method of assessing risk factor/exposure 18- item interview Goldberg Depression & Anxiety questionnaire; threshold for positive not specified Covariates/potential 

1) Follow-up rate: 612/897=68% of total and 83% of those alive (124 died; 129 lost to f/u; 32 only informant data ) 2) Important baseline differences: NR 3) Outcome of interest #1 Mild Cognitive Impairment (26 cases); multiple logistic regression analysis evaluating: age, education, anxiety, depression, only age was 

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B-46

Study Study Information Participants Risk Factor and 

Outcome Assessment 

Results Comments

897 Duration of follow up:Mean 3.6 years, range 3.3 to 4.2 years Time from risk factor assessment to final cognitive assessment:Mean 3.6 years 

 MCI Inclusion criteria: “sample of 897 elderly persons” Exclusion criteria:

NR 

confounders adjusted for in analyses: Age  Educational level Method(s) of assessing cognitive status:Mild cognitive impairment based on 4 criteria: 1. Report of 

neurological or other physical diseases causing cerebral dysfunction 

2. Decline in 

cognition reported by subject or informant 

3. >1.5 below mean 

on 2 of 12 cognitive tests 

4. Met ICD-10 criteria 

for dementia or probable dementia, DSMIIR delirium or amnestic syndrome. 

Informant interview?:Yes, for some subjects

significantly associated with incident MCI- OR 1.09 per year (CI 1.01 to 1.18).  Parameter estimates not given for other risk factors. 

cohort: 

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Partial 

Clarke, Birks, Nexo, et al., 2007 

Geographical location: Oxford, United Kingdom 

Age:Mean (SD): 71.9 (5.2) for analytical sample Sex: [n (%)] 

Risk factor/exposure

1:B-12, folate, homocysteine, holotranscobalamin, 

1) Follow-up rate: 691/1344 (51%), but not all of those gave blood 2) Important baseline differences: 

CommentsQuestion 2 Quality assFor observ
B-47

Study Study Information Participants Risk Factor and 

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Results Comments

Oxford Healthy Aging Project 

Setting:Clinical – from general medical practice registry Study design: Prospective cohort Number of participants enrolled:691 – analytical sample Duration of follow up:10 years Time from risk factor assessment to final cognitive assessment:8 years 

Female: 60.4 Male: 39.6 Race/ethnicity: [n (%)]  NRBaseline cognitive status:Non-demented Inclusion criteria: Age aged 65 or older at baseline. Randomly selected from general practice registers for people living in Oxford city. Completed blood draw at Year 2 and completed MMSE year 1 and year 10. Exclusion criteria:Participants (n = 9) with extreme elevations of vitamin B-12 (>1000 pmol/L) or holoTC (>400 pmol/L) or who reported use of vitamin B-12 injections or any B-vitamin supplements (n=22) 

methylmalonic acid Method of assessing risk factor/exposure 1:Direct measurement, non-fasting at year 2 Covariates/potential confounders adjusted for in analyses:Age Sex Smoking Vascular disease, Systolic blood pressureEducation APOE Levels of other vitamins being assessed 

Method(s) of assessing cognitive status: Other – change in MMSE Informant interview?:No 

NR 3) Outcome of interest #1Doubling in thcy was associated with a > 50% more rapid cognitive decline4) Outcome of interest #2 Cognitive decline was not associated with serum concentrations of thcy after adj for other markers of vitamin status 

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Comijs, Kriegsman, Dik, et al., 2009 LASA 

Geographical location: 11 municipalities throughout the Netherlands Setting:

Age:Mean (SD): 72.1 (6.5) Range: 62-85 Sex: [n (%)] 

Female: 668 (51.6%) Male: 626 (48.4%) 

Risk factor/exposure 1:presence of chronic disease – a) cardiac disease, b) peripheral artheroschlerosis, 

1) Follow-up rate: At T1 = 95.3% At T2 = 95.4% At T3 = 74.8% Follow-up rate for those eligible at baseline is uncertain 

CommentsSubjects winsufficient were older, limited visiowomen, anbaseline. 
B-48

Study Study Information Participants Risk Factor and 

Outcome Assessment 

Results Comments

Community Study design: Prospective cohort Number of participants enrolled:2429 at baseline 1358 with complete data at 2 time-points were analyzed: T1 = 1294 data points T2 = 1296 data points T3 = 1016 data points Duration of follow up:1993-1999 T1 = 1992/93 T2 = 1995/96 T3 = 1998/99 Time from risk factor assessment to final cognitive assessment:6 yr 

Race/ethnicity: [n (%)] 

NR Baseline cognitive status:NR (Referring to Knipscheer, 1995 – original article given at a congress and published in Dutch) Inclusion criteria: Member of cohort recruited for NESTORLSN study (Knipscheer, 1995) Age 50-85 

Exclusion criteria: 

Born after 1930 Only one measurement time-point 

c)stroke, d) DM, e) COPD, f) arthritis, g) cancer. Method of assessing risk factor/exposure 1:Self-report Covariates/potential confounders adjusted for in analyses:Age, Sex Educational level Presence of comorbid disease outside of the 7 of interest Smoking Alcohol use Antidepressant meds Benzodiazepines Depressive sx (CES-D)Impaired vision Impaired hearing Mobility (6 AODL) 

Method(s) of assessing cognitive status: 

Other – Outcome 1: General Cognition -Mini-Mental State Exam (Folstein, 1975) O. 2: Fluid intelligence -Raven’s Colored Progressive Matrices (Raven, 1995) O.3: Processing speed 

2) Important baseline differences:NR 3) Outcome of interest #1General cognitive function over time:  Negatively affected by DM (-0.49, CI -0.86/-0.11) 4) Outcome of interest #2 Fluid intelligence over time:  Negatively affected by DM (-1.03, CI -1.54/-0.51) & stroke (-073, CI -1.32/-0.14) 5) Outcome of interest #3 Information processing speed over time: negatively affected by PVD (-0.73, CI -1.43/-0.03), stroke (-1.97 CI -2.78/-1.16) and DM (-0.76, CI -1.53/0.00) 6) Outcome of interest #4 Memory performance (immediate and delayed recall) over time: Immediate-  Negatively affected by DM (-0.44, CI -0.83/-0.06); positive association with cardiac disease (0.32, CI 0.11/0.52) Delayed –  Negatively affected by DM (-0.65, CI -0.95/-0.17); positive association with cardiac disease (0.23, CI 0.005/0.45) and cancer (0.32, CI 0.08/0.67) Positive associations were the weakest reported; interactions showed faster rates of decline in immediate recall with PVD, information processing speed and 

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B-49

Study Study Information Participants Risk Factor and 

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Results Comments

- Alphabet Coding Task (Savage, 1984) O.4: Auditory Verbal Learning Test (Rey, 1964) Informant interview?:NR (but the interviews took place in the subject’s home) 

memory with stroke, delayed recall with DM, and immediate recall with cancer. 

Commenges, Scotet, Renaud, et al., 2000 Paquid Study 

Geographical location: Gironde & Dordogne districts of France Setting:Community Study design: Prospective cohort Number of participants enrolled:3777 in overall study but 1367 meet criteria for current analyses Duration of follow up:2-5 yrs Time from risk factor assessment to final cognitive assessment:2 – 5 yrs 

Age:Mean (SD): 76 yr Sex: [n (%)] 

Female: 801 (59%) Male: 566 (41%) Race/ethnicity: [n (%)] NR Baseline cognitive status:Non-demented Inclusion criteria: > 65 yr 

Living at home For current analyseshad to have completed nutrition questionnaire, not be demented at 3-yr fup, and have covariate info available, and were seen at one of the visits after 3-yr fup Exclusion criteria:Opposite of inclusion 

Risk factor/exposure

1:flavonoids Method of assessing risk factor/exposure 1:Self-report (2 different questionnaires for subsets of sample) Covariates/potential confounders adjusted for in analyses:Age Sex Educational level Weight Vitamin C Method(s) of assessing cognitive status: DSM Informant interview?:No 

1) Follow-up rate: 1367 used in analyses. Difficult to assess follow-up rate because this is a subset of larger sample2) Important baseline differences: NR 3) Outcome of interest #1 Flavonoid values in the upper 2 tertile-level were associated with lower rate of dementia (RR=0.49;0.26-0.92) 

CommentsQuestion 1 Flavonoid qfood frequeby imputing “percentile uncertain Quality assFor observ1) Unbias

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Partial 
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Study Study Information Participants Risk Factor and 

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Results Comments

criteria 10) Analys

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Yes 

Cornelius, Fastborn, Winblad, et al., 2004 Kungsholmen Project 

Geographical location: Stockholm, Sweden Setting:] Community Study design:

Prospective cohort Number of participants enrolled:

1301 Duration of follow up: Baseline 10/87 First follow up 91-93 Second f/up 94-96 Time from risk factor assessment to final cognitive assessment:nsaid exposure recorded baseline and first follow up. 2-9 years from time of risk factor assessment at baseline to final cognitive assessment 

Age:Range: 74 – 85+ Sex: [n (%)] 

Female: 976 (75%) Male: 325 (25%) Race/ethnicity: [n (%)] NR Baseline cognitive status:Non-demented Inclusion criteria: All inhabitants of Kungsholman Parrish, Stockholm in Oct 1987 who were born in 1912 or before, including institutionalized residents. Unfortunately, I can’t tell how many were institutionalized. 

Exclusion criteria: it NR

Risk factor/exposure

1:nsaid Method of assessing risk factor/exposure 1:Self-report Inspection of pill bottles. Covariates/potential confounders adjusted for in analyses:Age Sex Underlying disease Educational level Method(s) of assessing cognitive status:

DSM Informant interview?:Yes 

1) Follow-up rate: 50% at six years (approx) but only 3.5% due to drop-out; others demented or deceased so were not followed, 88% at first follow up 2) Important baseline differences: NR 3) Outcome of interest #1 ASA AD 1.34(0.96-1.89) 4) Outcome of interest #2 NSAIDs 0.61 (0.32-1.15) 5) Outcome of interest #3 ASA or NSAIDs 1.11 (0.81-1.52) 6) Outcome of interest #4 RR of AD with asa use if E4 negative: 1.80 (1.14-2.83) 

CommentsQuality assFor observ1) Unbias

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Yes 

Dai, Borenstein, Wu, et al., 

Geographical location: King County, 

Age:Mean (SD): 71.8 

Risk factor/exposure 1:Dietary intake of a 

1) Follow-up rate: Initial cohort of 3045 enumerated in a census, representing 90% of the 

CommentsFruit juice cpriori hypot
B-51

Study Study Information Participants Risk Factor and 

Outcome Assessment 

Results Comments

2006 Kame Project 

Washington Setting:Community Study design: Prospective cohort . Baseline, with 4 f/u waves 2 years apart. Number of participants enrolled:1836 enrolled. Data from 1589 (86.5%) Duration of follow up:6.3 yrs (SD 2.6) Time from risk factor assessment to final cognitive assessment:6.3 yrs (SD 2.6) 

Sex:

Female: 864 (54.4%) Male: 726 (45.6%) Race/ethnicity:Japanese American Baseline cognitive status:Non-demented Inclusion criteria: Japanese Americans (self-identified in the US Census) in King County, WA, aged > 65 

yrs Exclusion criteria:Dementia at baseline. 

variety of foods Method of assessing risk factor/exposure 1:Self-report. Food frequency questionnaire. Each food item has 8 frequency options and 3 usual portion sizes. Intake of nutrients calculated from these data. 3 categories of frequency: 1) Less than weekly (reference) 2) 1-2 times/wk 3) > 3 times/wk 

Risk factor/exposure 2:APOE status Method of assessing risk factor/exposure 2:Direct measurement on 1047 of the 1589 (65.9%) participants with complete food diaries Covariates/potential confounders adjusted for in analyses:Age, 

Japanese American population in King County in 1990. Of these, 1985 (65.2%) participated in the baseline study, of whom 1836 (60.3%) were dementia free and comprise the analytical sample. Of 1836 dementia-free participants, food intake data available from 1589 (86.5%) 2) Important baseline differences: NA 3) Outcome of interest #181 incident cases of probable AD, 63 of which completed the food diary and are included in the analyses. 4) Outcome of interest #2 HR for incident probable AD by frequency of intake Fruit and vegetable juice: 

1) 1-2 x’s/wk: HR 0.84 (95% CI: 0.31-2.29) 2) >3 x’s/wk: HR 0.24 (0.09-0.61) 

Tea drinking: 

1) 1-2 x’s/wk: HR 1.49 (95% CI: 0.43-5.16) 2) >3 x’s/wk: HR 1.70 (0.67-4.33) 

Wine (sake) drinking: 

1) 1-2 x’s/wk: HR 0.49 (95% CI: 0.11-2.10) 5) Outcome of interest #3 Author’s conclusions: “We found that frequent drinking of 

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4) Adequa

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5) Validat

ascertaInstrumsepara

6) Validat

ascertaYes 

7) Outcom

exposu

8) Adequa9) Comple10) Analys

confou

11) Analyti

Yes 
B-52

Study Study Information Participants Risk Factor and 

Outcome Assessment 

Results Comments

Dietary factors, Tobacco and alcohol, education, physical activity, APOE status Method(s) of assessing cognitive status:CASI to assess cognition at baseline and f/u. Further w/u if scored <87. 

Dx by Consortium to Establish a Registry for Alzheimer’s Disease criteria. NINCDS-ADRDA DSM-IV Informant interview?:Yes, using the Clinical Dementia Rating Scale

fruit and vegetable juices was associated with a substantial decrease of AD. This inverse association was stronger after adjustments for potential confounding factors.” 

de Lau, Smith, Refsum, et al., 2009 

Geographical location: Rotterdam, The Netherlands Setting:Community Study design: Prospective cohort Number of participants enrolled:1019 

Age:Mean (SD): 72.2 (7.4) Median: NR Range: 60-90 Sex: [n (%)] 

Female: 530 (52) Male: 489 (48) Race/ethnicity: [n (%)] NR Baseline cognitive status:Non-demented 

Risk factor/exposure 1:Plasma B12 (and transport; metabolites transcobolamin and holotranscoboloamin, methylmalonic acid) Method of assessing risk factor/exposure 1:Microbial assay Covariates/potential confounders 

1) Follow-up rate:832/1019 (81.6%) 2) Important baseline differences: B12 deficiency associated with older age and white matter lesions on MRI 3) Outcome of interest #1Follow-up cognition No association was observed for any of the studied variables (including plasma B12 analyzed by quintiles) with rate of cognitive decline during follow-up...data not shown. 

CommentsQuestion 2 Quality assFor observ1) Unbias

cohort?

2) Selectio

differenfactors

3) Sample 

differen

4) Adequa

cohort?

5) Validat
B-53

Study Study Information Participants Risk Factor and 

Outcome Assessment 

Results Comments

Duration of follow up:7 years 1995-96 assembled 2001-2003 Time from risk factor assessment to final cognitive assessment:7 yr 

Inclusion criteria: Age, 60-90 y Exclusion criteria:

Dementia blindness 

adjusted for in analyses:Age, sex, education,  creat holoTC, homoCys, folate, DM, BP, Alcohol use, smoking, vitamin supplements, depression, intimamedia thickness Method(s) of assessing cognitive status: Neuropsych tests to measure global cognitive function derived by combining z scores for all tests below- (Stroop test, Letter-Digit Substitution, Verbal fluency, Memory Scanning, memory function with 15-word verbal learning task for immediate and delayed recal Informant interview?:No 

ascerta

6) Validat

ascertaYes 

7) Outcom

exposuprobab

8) Adequa9) Comple

Yes 

10) Analys

confou

11) Analyti

Partial, multiple 

DeKosky, Williamson, Fitzpatrick, et al., 2008 

Geographical location: 4 US academic medical centers (MD, PA, CA, & NC) 

Age:Mean (SD): 79.1 (3.3) Sex: [n (%)] 

Female: 46% Male: 54% 

Risk factor/exposure

1:ginkgo biloba Method of assessing risk factor/exposure 

1) Follow-up rate: 379 died – not sure from which groups. States knew cognitive status of 93.6% participants at trial end. 1426/1524 placebo 1448/1545 GB 

CommentsNone Quality assFor RCTs: 1) Baselin
B-54

Study Study Information Participants Risk Factor and 

Outcome Assessment 

Results Comments

Ginkgo Evaluation of Memory Study 

Setting:Community Study design: RCT Test intervention: Twice-daily doses of 120-mg G bilboa extract (EGb 761; Schwabe Pharmaceuticals) Comparator intervention(s): Identically appearing placebo Number of participants enrolled:3069 Duration of follow up:Median 6.1 yrs Time from risk factor assessment to final cognitive assessment:median follow-up was 6.1 yrs (max = 7.3 yrs) 

Race/ethnicity: [n (%)] White 2930 (95%) Nonwhite 139 (5%)

Baseline cognitive status:Normal MCI Inclusion criteria: Aged 75 or older, on voter registration list or purchased mailing list; have willing proxy to be interviewed every 6 mos Exclusion criteria:Prevalent dementia (meeting DSM-IV criteria for dementia or a score >0.5 on the CDR; currently taking warfarin; taking cholinesterase inhibitors for cognitive problems or dementia; unwilling to discontinue taking over-the-counter G bilboa for the duration of study; currently being treated with tricyclic antidepressants, antipsychotics, or other medications with significant psychotropic or central cholinergic effects; daily use of more than 400-IU 

1:Direct measurement Covariates/potential confounders adjusted for in analyses:Age Race Sex MCI APOE Cardiovascular diseaseMethod(s) of assessing cognitive status:NINCDS-ADRDA DSM Informant interview?:Yes 

2) Important baseline differences: none 3) Outcome of interest #1 No difference in rate of AD by intervention for all participants No difference in rate of AD by intervention for baseline normal group No difference in rate of AD by intervention for baseline MCI group 4) Outcome of interest #2 

No interaction by age, sex, or MCI for results in 3) above by 

2) Valid A

assess

3) Subjec4) Outcom5) Incomp

addres

6) Differen

Yes 

7) Overall 8) Conflic

insignif

9) Random10) Allocat

adequa
B-55

Study Study Information Participants Risk Factor and 

Outcome Assessment 

Results Comments

vitamin I or unwillingness to reduce intake to this level; history of bleeding disorders; hospitalization for depression within the last yr or electroconvulsive therapy within last 10 yrs; history of Parkinson disease or taking anti-Parkinson medications; abnormal thyroid tests, serum creatinine level greater than 2.0 mg/dL, or liver function tests more than 2 times the upper limit of normal at baseline; baseline vitamin B12 levels 210 

pg/mL or lower; hematocrit level less than 30%; platelet count lower than 100x103/μL; diseaserelated life expectancy of less than 5 yrs; known allergy to G bilboa 

Devore, Grodstein, van Rooij, et al., 2009 Rotterdam Study 

Geographical location: Ommoord (Rotterdam), Netherlands Setting:Community 

Age:Mean (SD):8.2 Range: 67 – 88.3 Sex: [n (%)] 

Female: 3184, 59% Male:2211, 41% 

Risk factor/exposure 1:Consumption of fish and omega-3 polyunsaturated fatty acids (PUFAs) Method of assessing 

1) Follow-up rate: 

5395/6444=83.7.5% 

- Of the 7963 individuals who agreed to participate, 7046 underwent cognitive screening and were free of dementia. 6444 eligible for dietary history -Final population for analysis = 5395 

CommentsNone Quality assFor observ1) Unbias

cohort?

2) Selectio
B-56

Study Study Information Participants Risk Factor and 

Outcome Assessment 

Results Comments

Dietary consumption of fish and omega-3 PUFA’s in relation to long-term risk of dementia 

Study design: Prospective cohort Number of participants enrolled:5395 Duration of follow up:9.6 years Time from risk factor assessment to final cognitive assessment:14 years 

Race/ethnicity:NR 

Baseline cognitive status:Non-demented Inclusion criteria: Participants in the Rotterdam study, aged≥55 years who were free of dementia and reported dietary information at baseline Exclusion criteria:-Questionable cognitive status (score of <80 on the Cambridge examination of mental disorders of the elderly, Camdex) -living in a nursing home -lack of reliable dietary information 

risk factor/exposure 1:Self-report 2-step protocol consisting of home interview and a validated semiiquantitative foodfrequency questionnaire administered by a trained dietician at the time of clinical examination. Covariates/potential confounders adjusted for in analyses:-Age -Sex -Education -Total energy intake -Alcohol intake -Smoking -Body mass Index (BMI) -High total cholesterol -Hypertension -Dietary intake of Vitamin E -Supplement use (either fish, omega-3, or antioxidant supplements) -History of stroke, myocardial infraction, or type 2 diabetes Method(s) of assessing cognitive 

2) Important baseline differences: -Participants with greater fish intake also tended to consume more alcohol 3) Outcome of interest #1

- Dementia developed in 465 participants (365 with diagnosis of AD) -Total fish and omega-3 PUFA intake unrelated to AD risk. HR for high (>sex-specific median) intake 0.99 (0.76-1.29), low intake HR 1.05 (0.83-1.37) compared to no intake No association between quartiles of long chain omega-3 fatty acid intake (p=0.7 for trend), EPA (p=0.7 for trend) or DHA (p=0.9 for trend). 

differenfactors

3) Sample 

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4) Adequa

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5) Validat

ascerta

6) Validat

ascertaYes 

7) Outcom

exposu

8) Adequa9) Comple10) Analys

confou

11) Analyti

Yes 
B-57

Study Study Information Participants Risk Factor and 

Outcome Assessment 

Results Comments

status: DSM Dementia assessed by 3 step protocol: 1. Combined MiniMental State Examination (MMSE) and Geriatric Mental State Schedule (GMS) 2. Camdex examination for those with MMSE scores<26 or GMS scores>0 3. Evaluation by neurologist and neuropsychologist Final diagnosis made by panel consisting of neurologist, neuropsychologist and research physician according to DSM-IIIR;NINCDS-ADRDA for AD Informant interview?:No 

Devore, Kang, Okereke, et al., 2009 Nurses Health 

Geographical location: USA (participants dispersed across several states in the US) 

Age:Mean (SD):74(2.3) Sex:

Female: 1550 (100%) Male: 0 (0%) 

Risk factor/exposure 1:Physical activity levels Method of assessing risk factor/exposure 1:

1) Follow-up rate: -1550 women analyzed for cognitive decline across 3 interviews over 4 yrs; >90% follow-up. 2) Important baseline differences: 

CommentsNone Quality assFor observ1) Unbias

cohort?
B-58

Study Study Information Participants Risk Factor and 

Outcome Assessment 

Results Comments

Study Participants Physical activity levels and cognition in women with type 2 diabetes 

Setting:Community Study design:

Prospective cohort Number of participants enrolled:

1550 Duration of follow up:4 years Time from risk factor assessment to final cognitive assessment:4 yrs 

Race/ethnicity: [n (%)] NR Baseline cognitive status:Non-Demented Inclusion criteria: Nurses Health Study participants, aged≥70 

with type 2 diabetes. (Nurses health study is a long-running study of registered nurses that started in 1976 with recruitment of 121,700 nurses between ages 30-55yrs) Exclusion criteria:-Women unable to walk -Women diagnosed with Parkinson’s or Alzheimer’s disease prior to initial cognitive assessment -Women who did not report information on specific disability indicators (15%) (osteoarthritis, chronic bronchitis, fatigue, balance problems, moderate-to-severe body pain, and limitations in walking) 

Self-report: Self reports of physical activity converted into metabolical equivalent hours per week (METhr) (e.g. MET for sitting=1, for running =12, for stair climbing=8 and so on)  MET multiplied by hours per activity and summed over all activities gives energy expenditure per week.) based on average of 5 reports over a median of 13.3 years Covariates/potential confounders adjusted for in analyses:  Age, education, baseline cognitive status, disability indicators (osteoarthritis, chronic bronchitis, fatigue, balance problems, moderate-to-severe body pain, and limitations in walking) Method(s) of assessing cognitive status: Battery of 6 cognitive 

tests administered by trained nurses via telephone; starting with telephone interview of 

Differences in self-reported physical disability across increasing tertiles of physical activity 3) Outcome of interest #1Mean difference in change in cognitive function scores by tertile of average physical activity Adjusted for age, education and baseline cognitive status, women with greater levels of long-term physical activity associated with less cognitive decline on TICS, global and verbal cognition; however this finding was not statistically significant when adjusted for disability indicators. 

2) Selectio

differenfactors

3) Sample 

differen

4) Adequa

cohort?

5) Validat

ascerta

6) Validat

ascertaYes 

7) Outcom

exposu

8) Adequa9) Comple10) Analys

confou

11) Analyti

Yes 
B-59

Study Study Information Participants Risk Factor and 

Outcome Assessment 

Results Comments

cognitive status (TICS) and including, East Boston Memory Testimmediate and delayed recall, Category Fluency, delayed recall of 10 word list and digit span backward. Assessment expressed in terms of general cognition and verbal memory; general cognition obtained by averaging all 6 tests; verbal memory score obtained by averaging 4 tests: immediate and delayed recalls of East Boston Memory Test and Telephone interview of Cognitive Status 10-word list. Baseline interview followed by 3 interviews over a 4 year period. Informant interview?:No 

Dik, Jonker, Bouter, et al., 2000 LASA study 

Geographical location: Amsterdam, The Netherlands Setting: LASA: Community 

Age:Mean (SD):  Equal numbers in 5 year intervals from 55 to 85. Only subjects >62 in this study.

Risk factor/exposure 1:APOE E4 genotype Method of assessing risk factor/exposure 1:genotyping 

1) Follow-up rate: 876/1243 = 70.5% Death 13.5%; refusal 11.1%; frailty 4.4%; loss of contact 0.5%. 22 subjects lost data leaving 854 with testing at both time points. Loss to follow-up was associated 

Comments APOE E4 memory deimpaired innot in cogn(MMSE ≤27subjects wiyears of ag
B-60

Study Study Information Participants Risk Factor and 

Outcome Assessment 

Results Comments

Study design:Prospective cohort Number of participants enrolled: LASA: 3107 enrolled. 1551provided blood. 1297 genotypes; Excluded 54 excluded because MMSE <21. Total 1243 participated Duration of follow up: LASA: mean of 3.1 years Time from risk factor assessment to final cognitive assessment:Average 3.1 years (SD 0.2) 

Range: 

≥62 to 85 

Sex: [n (%)] Female: 

Male: Race/ethnicity: [n (%)] NR Baseline cognitive status:Non-demented Inclusion criteria: Age ≥62 MMSE ≥21 Exclusion criteria:

Covariates/potential confounders adjusted for in analyses:Age Sex Educational level E4 carriers E4 noncarriers MMSE 27-30 (normal cognition) MMSE 21-26 (impaired cognition) Method(s) of assessing cognitive status:MMSE; AVLT (3 trials); memory decline was defined as ≥1 SD mean change score on IR, DR and retention based on AVLT. Informant interview?:

No 

with older age, lower education and lower scores on all cognitive measures (p<.001). No association between follow-up and APOE genotype. Important baseline differences: NR Outcome of interest #1APOE E4 is a risk factor for memory decline only in cognitively impaired individuals (MMSE 21-26), not in cognitively normal subjects (MMSE ≤27). In Subjects with MMSE 21-26 And APOE E4 (adjusted for age, sex, education and baseline recall scores)OR decline on IR 3.8 (95% CI 1.4-10) OR decline on DR 2.9 (1.2-7.0) OR decline on retention 3.3 (1.1-10.1). No association of decline in cognitively normal subjects with APOE E4. Outcome of interest #2 Subjects with MMSE 21-26 and age >75 and APOE E4 OR decline on IR 4.5 (1.4-13.8) OR decline on DR 3.6 (1.2-10.8) OR decline on retention 6.6 (1.5-29.7) 

increased rQuality assFor observ1) Unbias

Yes 

2) Selectio

differenYes 

3) Sample 

differen

4) Adequa

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5) Validat

ascerta

6) Validat

ascertaYes 

7) Outcom

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Partial 

10) Analys

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Yes 

Dodge, Zitzelberger, Oken, et al., 2008 

Geographical location: Oregon, US 

Age:Mean (SD): 87.5 yr (2.14-2.22) Range: 85-94.1 yrs 

Risk factor/exposure 1:RCT – Ginkgo biloba extract 

1) Follow-up rate: 79/118 (66.9%) 2) Important baseline differences: 

CommentsUsed propoAppeared tthe point of 
B-61

Study Study Information Participants Risk Factor and 

Outcome Assessment 

Results Comments

Setting: [ Community – mailing to age-eligible in community and research in university aging and AD center Study design: RCT Test intervention: Standardized GBE (80 mg 3x daily) Comparator intervention(s): placebo Number of participants enrolled:118 Duration of follow up:42 mo Time from risk factor assessment to final cognitive assessment: 42 mo was the aim – in reality ave 3.0 (0.98) yr for placebo and 3.3 (0.77) yr for GBE 

Sex: [n (%)] 

Female: 71 (60% Male: 47 (40%) Race/ethnicity: [n (%)] NR Baseline cognitive status:Normal Inclusion criteria: Age > 84 yrs; no subjective complaint of memory impairment compared to others of their own age; has not sought assessment for memory or cognitive dysfunction; normal memory function defined by an education adjusted score on the Logical Memory Subscale of the Wechsler Memory Scale-Revised; Mini0Mental State Examination score >23; Blessed Orientation Memory Concentration Test <12; Functionally independent (ADL=0); Clinical Dementia Rating = 0; Absence of significant depressive symptoms (CES-D-10 score <4); Sufficient vision and hearling to 

Method of assessing risk factor/exposure 1:Direct measurement of number of pills taken Covariates/potential confounders adjusted for in analyses:Covariates used in secondary analyses Age Sex Educational level Baseline MMSE score Adherence to intervention medicationDepression APOE # prescriptions Cumulative illness scale Living arrangement 

Method(s) of assessing cognitive status: Other – change in CDR from 0.0 to 0.5 Some analyses examined decline in delayed recall task – but description of these results are not clear Informant interview?:Yes 

None 3) Outcome of interest #1In unadjusted model, no difference in conversion to CDR = 0.5 for GBE vs placebo group. 4) Outcome of interest #2 When adjust for adherence to intervention, GBE group at lower risk of converting to CDR = 0.5. Effect remains when all other covariates added. 5) Outcome of interest #3 GBE does not have an effect on delayed recall test over time (not sure if this is change in score or what) 

due to strokfor some biattrition? Quality assFor RCTs: 1) Baselin2) Valid A

assess

3) Subjec4) Outcom5) Incomp

addres

6) Differen

10%?:N

7) Overall 

No 30-

8) Conflic

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9) Random

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adequa
B-62

Study Study Information Participants Risk Factor and 

Outcome Assessment 

Results Comments

complete all testing; sufficient English language skills to complete all testing; general health status that will not interfere with ability to complete longitudinal study; informant available with frequent contact with subject to verify functional status Exclusion criteria:Diseases associated with dementia such as AD, ischemic vascular dementia, normal pressure hydrocephalus, or Parkinson disease; significant disease of the CNS such as brain tumor, seizure disorder, subdural hematoma, cranial arteritis; current (within last 2 yrs) alcohol or substance abuse according to DSM-IV criteria; abnormal laboratory values indicating B12 deficiency, thyroid disease, or urinary tract infection (documented chronic bacterial colonization is acceptable); unstable or significantly symptomatic 
B-63

Study Study Information Participants Risk Factor and 

Outcome Assessment 

Results Comments

cardiovascular disease such as CAD with frequent angina, or CHF with shortness of breath at rest; insulin dependent diabetes mellitus; active systemic CA within 5 yrs of study entry (Gleason Grade <3 prostate CA, and nonmetastatic skin CA are acceptable); illness that requires >1 visit per mo to clinician; progressive vision loss; need for oxygen supplementation for adequate function; frequent use of high doses of analgesics; sedative medications except for those used occasionally for sleep; subjects taking CNSactive medications that have not been on stable doses for at least 2 mos including cimetidine, betablockers, and selective serotonin reuptake inhibitors; subjects taking neuroleptics, antiparkinsonian agents, systemic corticosteroids, and narcotic analgesics; Subjects will NOT be excluded if they are taking other over-the-
B-64

Study Study Information Participants Risk Factor and 

Outcome Assessment 

Results Comments

counter supplements, but the dose must not be changed during the course of the trial unless medically indicated; Subjects taking cholinesterase inhibitors; use of investigational drugs within 5 half-lives prior to baseline 

Doody, Ferris, Salloway, et al., 2009 (Aricept)

Geographical location: U.S.A, multicenter Setting:NR Study design: RCT with 3-week placebo run-in phase Test Intervention: Donepezil 5mg daily * 6 weeks, then 10mg daily Comparator:Intervent

ion: Placebo Number of participants enrolled:

821 randomized; 778 analyzed Duration of follow up:years 

Age:Mean (SD):70.2 (9.71), 69.8 (10.32) Sex: [n (%)] 

Female: 354 Male: 424 Race/ethnicity: [n (%)] Caucasian 676 (87%) Baseline cognitive status:Amnestic MCI Inclusion criteria: Age 45-90 Memory complaint corroborated by an informant MCI defined by: CDR 0.5 with memory box score 0.5 or 1.0 and <= 2 other boxes >=1; MMSE 24-28; Logical Memory II delayed Paragraph recall ≤ 8 

Covariates/potential confounders adjusted for in analyses: [delete any from the list below that do not apply and add items as needed] Age Educational level Method(s) of assessing cognitive outcomes: [delete all that do not apply] Primary: Modified ADAS-Cog (0-89 point scale, 13 subtests) and CDR sum of boxes (0-18; 6 subscales each rated 0-3; CDR-SB) Secondary: MMSE Symbol Digit Modalities Test Digit Span Backwards 

1) Follow-up rate: 499/821 randomized = 60.8% 499/778 analyzed = 64.1% Mean exposure rate to treatment Donepezil = 248 (120) days Placebo = 282 (100) days 2) Important baseline differences: No, comparable at baseline 

3) Outcome of interest #1Analyzed by analysis of covariance using last observation carried forward (mean difference = (baseline – follow-up)donepezil – (baseline – follow-up)placebo  ADAS-Cog: mean difference at f/u = -0.90 (SE 0.37), p=0.01 favoring donepezil  CDR-SB, mean difference not given; no statistically significant difference 4) Outcome of interest #2 Mean change from baseline to endpoint on 8 cognitive measures 

CommentsNone Quality assFor RCTs: 1) Baselin2) Valid A

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5) Incomp

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B-65

Study Study Information Participants Risk Factor and 

Outcome Assessment 

Results Comments

48 weeks (education ≥ 16 years), 

≤ 4 (8-15 years educ), ≤ 2(≤ 7 years educ); 

modified Hachinski Ischemia scale score ≤4; an informant; brain imaging w/in 12 months without infarction or focal lesions. Exclusion criteria:Dementia Neurologic or psychiatri disorder Sleep disorder that could affect cognition Alcohol abuse/dependence w/in 5 years Uncontrolled HTN or DM Any other medical condition incompatible with study participationPast treatment with ChEI or memantine for > 1 month or within 3 months of study screening Concomitant anticholinergics, anticonvulsants, antiparkinsonian agents, stimulants, cholinergic agents, antipsychotics or antidepressants or anxiolytics with anticholinergic or procholinergic effects. 

tst Pereived Deficits Questionnaire (PDQ) PDQ for relatives Neuropsychiatric Inventory Patient Global Assessment Clinical Global Impression of ChangeMild Congitive Impariement Informant interview?:No 

Of 8 secondary measures, donepezil treated subjects showed statistically significant benefit on two: Perceived Deficits Questionnaire: -1.8 (0.8)donepezil vs. -0.2 (0.7) placebo Patient Global Assessment: 3.3 (0.1) donepezil vs. 3.5 (0.1) placebo 5) Outcome of interest #3 Discontinuation due to adverse event72 (18.4%) donepezil vs. 32 (8.3%) placebo Any adverse event: 318 (81.3%) donepezil vs. 267 (69.0%) placebo; most common – diarrhea (16.4% vs. 3.4%), muscle spasms (13.3% vs. 1.8%) and nausea (9.7% vs. 4.4%) Serious adverse event: 48 (12.3%) donepezil vs. 41 (10.6%) placbo Deaths: 3 donepezil, (lymphoma, sudden death, lung cancer) 1 placebo (pleural mesothelioma) – all judged to be unrelated to study medication 
B-66

Study Study Information Participants Risk Factor and 

Outcome Assessment 

Results Comments

DuFouil, Alperovitch, Ducros, et al., 2003 EVA 

Geographical location: Nantes, France Setting:Community Study design: Prospective cohort Number of participants enrolled:1241 Duration of follow up: With a population of 1241 at baseline , 1151 followed up for 2 yrs, 986 for 3 years, 782 for four years OR for homocysteine calculated for 2 yr change in mmse Time from risk factor assessment to final cognitive assessment:blood drawn at baseline, cog testing each time subject returned. 

Age:Mean (SD): 67 (3.0) Range: 61-73 Sex: [n (%)] 

Female: 58.6% Male: 41.4% Race/ethnicity: [n (%)] NR Baseline cognitive status:doesn’t look like they eliminated the impaired but mean mmse high at baseline Inclusion criteria: Homocysteine measured at baseline 2 year f/u completed Exclusion criteria:NR 

Risk factor/exposure

1:homocysteine Fasting plasma stored unkn length of time Method of assessing risk factor/exposure 1:Direct measurement Covariates/potential confounders adjusted for in analyses: age, gender, education, baseline cognition, bmi, etoh, smoking, htn, hyperchol, glycemic status, hx of vascular dz, folate, vit B12 concen. Method(s) of assessing cognitive status: change in test scores (MMSE, Trails B, Digit symbol substitution test, Finger tapping)

Informant interview?:No 

1) Follow-up rate: 

With a population of 1241 at baseline , 1151 followed up for 2 yrs, 986 for 3 years, 782 for four years1107/1241 (89%) in cognitive decline analysis 2) Important baseline differences: In the higher class of hcy, subjects were older, more men, more ETOH, and more likely to have htn, dm, and lower folate levels Overall, lower cognitive performance in those with higher homocysteine. 3) Outcome of interest #1 cognitive deterioration defined as mmse decrease of 3 or more pts in two years (118 out of 1107 with 2 year f/u). OR 2.8 (1.2 – 6.2) for highest hcy group (>15 umol/l) vs lowest hcy group (<10 umol/l)  Stratified analysis by HTN, B12, folate, h/o vascular disease, glycemic status, and cholesterol status did not show any interaction between these factors and homocysteine. 4) Outcome of interest #2 Change in cognition evaluated as a continuous measure. Statistically significant greater decline on 3 of 4 outcomes (MMSE, Finger tapping, DSST) for highest homocysteine vs. lowest. Comparison of 2nd and 3rd

CommentsQuestion 2 Population baseline animpaired suwas 27.6 wAppears thcategories based on dtheorecticaQuality assFor observ1) Unbias

cohort?

2) Selectio

differenfactors

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differen

4) Adequa

cohort?

5) Validat

ascerta

6) Validat

ascertaPartial, of unkn

7) Outcom

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8) Adequa9) Comple10) Analys

confou

11) Analyti

Yes 
B-67

Study Study Information Participants Risk Factor and 

Outcome Assessment 

Results Comments

highest homocysteine vs lowest groups did not show a statistically significant difference. 

Dufoil, Fuhrer, Dartigues, et al., 1996 PAQUID Study 

Geographical location: Gironde, France Setting:Community Study design: Prospective cohort Number of participants enrolled:2792 overall; 2726 in this analysis Duration of follow up:3 years Time from risk factor assessment to final cognitive assessment:3 years 

Age:Range: >65 years 

Sex: [n (%)] Female: 1632 (59.9%) Male: 1094 (40.1%) Race/ethnicity: [n (%)] NR Baseline cognitive status:Non-demented Inclusion criteria:  Age >=65  Cognitive assessment at baseline and follow-up Exclusion criteria:Dementia 

Risk factor/exposure

1:Depression (CESD >16 for men and >22 women) Method of assessing risk factor/exposure 1:Self-report at baseline and 3 year f/u Covariates/potential confounders adjusted for in analyses: Age  Sex  Educational level  Marital status  IADL  Baseline cognition Method(s) of assessing cognitive status:MMSE decline >= 5 points Informant interview?:No 

1) Follow-up rate: 1600 of 2726 (59%); 800 refused, 311 died, and 15 lost to follow-up 2) Important baseline differences:  Not given  Logistic Regression Analysis 3) Outcome of interest #1 Incidence of cognitive impairment defined by MMSE decline >=5 points.(48 subjects)  CESD > threshold at baseline; OR 0.8 (95% CI 0.3 to 2.1)  Sensitivity analysis to evaluate the effects of subjects lost to follow-up showed no association between depressive symptom and cognitive impairment until assuming a 10% rate of cognitive impairment in depressive non-respondents (compared to an observed rate of 2.8% in depressed respondents) 4) Outcome of interest #2 Change in MMSE (F/U – Baseline) was associated with change in CESD scores; adjusted estimate Beta=-0.026 (95%CI -0.039 to -0.013) 5) Outcome of interest #3 Mean change +0.3 (2.6) 

CommentsNone Quality assFor observ1) Unbias

Yes 

2) Selectio

differenYes 

3) Sample 

differen

4) Adequa

cohort: 

5) Validat

ascerta

6) Validat

ascertaYes 

7) Outcom

exposu

8) Adequa

Tell 

9) Comple10) Analys

confou

11) Analytic 

Yes 

Dullemeijer, Durga, 

Geographical location: 

Age:Mean (SD): 60 (6.0) 

Risk factor/exposure

1:

1) Follow-up rate: 404/408 (2 that did not return for fup 

CommentsQuestion 2 
B-68

Study Study Information Participants Risk Factor and 

Outcome Assessment 

Results Comments

Brouwer, et al., 2007 FACIT 

Wageningen, Netherlands Setting:NR Study design: Secondary analyses of an RCT arm Number of participants enrolled:404 subjects in this analyses Duration of follow up:3 yrs Time from risk factor assessment to final cognitive assessment:3 yr 

Sex: [n (%)] 

Female: 117 (29) Male: 287 (71) Race/ethnicity: [n (%)] NR Baseline cognitive status:Non-demented (assume because part of RCT and also young age of sample) Inclusion criteria: Participants in FACIT, a randomized placebocontrolled trial of folic acid supplementation on cognitive performance, carotid intima-media thickness, and hearing. Men and postmenopausal women aged 50-70 Plasma total homocysteine concentrations:> 13 

micromol/L and < 26 

micromol/L and serum vitamin B-12 concentrations > 200 

pmol/L. Exclusion criteria:NR 

n-3 fatty acid Method of assessing risk factor/exposure 1:Direct measurement Method of assessing risk factor/exposure 2:Self-report Proxy report Direct measurement Medical record Other Covariates/potential confounders adjusted for in analyses:Age Sex Educational level Baseline cognitive status Erythrocyte folate ETOH use Method(s) of assessing cognitive status: Other – used standardized test scores at baseline and 3 yr follow-up in 5 domains Informant interview?:No 

had died)2) Important baseline differences: NR by exposure group 3) Outcome of interest #1Higher plasma n-3 PUFAs predicted less decline over 3 yr in domains of sensorimotor speed (p = 0.02) and complex speed (<0.01), but domains of memory, information processing speed, and word fluency showed no sig association with n-3 PUFAs 

This paper of other lonassessing nQuality ass

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ascerta

6) Validat

ascertaYes 

7) Outcom

exposu

8) Adequa9) Comple

Yes 

10) Analys

confou

11) Analyti

Yes 
B-69

Study Study Information Participants Risk Factor and 

Outcome Assessment 

Results Comments

Engelhart, Geerlings, Ruitenberg, et al., 2002 Rotterdam Study 

Geographical location: Rotterdam, Netherlands Setting:Community Study design: Prospective cohort Number of participants enrolled:5395 Duration of follow up:Mean 6 yr Time from risk factor assessment to final cognitive assessment: Mean 6 yr 

Age:Mean (SD): 67.7 (7.8) Sex: [n (%)] 

Female: 3183 (59) Male: 2212 (41) Race/ethnicity: [n (%)] NR Baseline cognitive status:Non-demented Inclusion criteria: > 55 yr; resident of 

specific suburb in Rotterdam, had reliable nutritional data, not demented at baseline Exclusion criteria:

Nursing home residents 

Risk factor/exposure

1:anti-oxidant intake Method of assessing risk factor/exposure 1:Self-report Covariates/potential confounders adjusted for in analyses:Age Sex Educational level Baseline cognitive status ETOH use Smoking BMI Total energy intake Presence of carotid plaques Supplemental antioxidant use Method(s) of assessing cognitive status:NINCDS-ADRDA DSM Informant interview?:Yes 

1) Follow-up rate: authors note f/u for dementia was 99.9% - but there were exclusions from analytical sample for other reasons—can not determine overall f/u – but in general appears to be adequate2) Important baseline differences: NR 3) Outcome of interest #1Fully adjusted model, Vit C associated with reduced risk of incident AD (RR-0.82; 0.68-0.99) 4) Outcome of interest #2 Fully adjusted model, Vit E borderline association with reduced risk of incident AD (RR-0.82; 0.66-1.00) 5) Outcome of interest #3 Fully adjusted model, beta carotene (RR-0.87; 0.70-1.09) and flavonoids (RR-0.99; 0.83-1.18) not associated with reduced risk of incident AD 

CommentsQuestion 1 Quality assFor observ1) Unbias

cohort?

2) Selectio

differenfactors

3) Sample 

differen

4) Adequa

cohort?

5) Validat

ascerta

6) Validat

ascertaYes 

7) Outcom

exposu

8) Adequa9) Comple10) Analys

confou

11) Analyti

Yes 

Evans, Hebert, 

Geographical location: 

Age:Mean (SD): NR 

Risk factor/exposure

1:

1) Follow-up rate: Initial prevalence study of 3623 

CommentsNone 
B-70

Study Study Information Participants Risk Factor and 

Outcome Assessment 

Results Comments

Beckett, et al., 1997 NIA EPESE study (Established Populations for Epidemiologic Studies of the Elderly) 

East Boston, MA SettingCommunity Study designProspective cohort Number of participants enrolled:642 enrolled. This number was a stratified random sample drawn from a cohort of Duration of follow up:4.3 years Time from risk factor assessment to final cognitive assessment:4.3 years 

Range:65 -80+ years Sex:

Female:362(56.4%) Male: 280(43.6%) Race/ethnicity:NR Baseline cognitive status:Non-demented Inclusion criteria: 65+ years old, nondemented, community resident. Exclusion criteria:NR 

years of formal schooling Method of assessing risk factor/exposure 1:Self-report Risk factor/exposure 2 Level of occupational status Method of assessing risk factor/exposure 2:

Self-report ”Occupations were coded according to perceived prestige.” 

Covariates/potential confounders adjusted for in analyses Age Sex F/u interval For combined logistic regression model, Occupational prestige score and income were also included. Method(s) of assessing cognitive statusAll participants underwent clinical 

residents. 2313 free of AD. Excluded 177 with poor or intermediate memory performance. Sample = 2136 303 died, 409 did not participate. 

Stratified random sample of 642 of remaining 1601 persons (79.6%) in analytical sample. 2) Important baseline differences: NA 3) Outcome of interest #1—probable AD95 with incident probably AD. Fewer years of education (OR 0.83; 95% CI: 0.75, 0.92), lower occupation prestige (OR 0.96, 95% CI: 0.93,0.99) and lower income are associated with increased risk of probable AD In the logistic regression analysis of risk of incident clinically diagnosed AD, odds ratio compared to the rest of the population was 0.85 (0.75-0.95). 

Quality assFor observ1) Unbias

cohort?

2) Selectio

differenfactors

3) Sample 

differen

4) Adequa

cohort?

5) Validat

ascerta

6) Validat

ascertaYes 

7) Outcom

exposu

8) Adequa9) Comple

Partial 

10) Analys

confou

11) Analyti

Yes 
B-71

Study Study Information Participants Risk Factor and 

Outcome Assessment 

Results Comments

evaluation. NINCDS-ADRDA Informant interview No 

EversonRose, Mendes de Leon, Bienias, et al., 2003 Chicago Health and Aging Project (CHAP) 

Geographical location: Chicago, IL Setting:Community Study design: Prospective cohort Number of participants enrolled:4398 Duration of follow up:Mean: 5.3 yrs Time from risk factor assessment to final cognitive assessment:Mean: 5.3 yrs 

Age:Mean (SD): 73.9 (6.4) Sex:

Female: 2731 (62.1%)Male: 1667 (37.9%) Race/ethnicity:Black: 2713 (61.7%) Non-Black: 1685 (38.3%) Baseline cognitive status:NR. No exclusion for dementia. Inclusion criteria: In CHAP study. Age >65 yrs, living in 

south side of Chicago. Must have had tests of cognitive function from at least 2 of 3 interviews. Exclusion criteria:NR 

Risk factor/exposure 1:Socieconomic position (SEP). Method of assessing risk factor/exposure 1:Self-report. Composite index: parental educational attainment and occupational prestige and self-reported family financial status as a child. Risk factor/exposure 2:Childhood cognitive milieu. Method of assessing risk factor/exposure 2:Self-report. Composite index of 3 questionnaires: frequency of someone in household having been read to, told stories to, or played games with as a child. 

1) Follow-up rate: 6158 in CHAP study. 1175 died before f/u, 149 relocated, 341 refused, 34 could not be contracted, and 61 were missing for other reasons. 4398 in this study (71.4% of eligible) 2) Important baseline differences: NA 3) Outcome of interest #1SEP: Each 1-unit increase in childhood SEP associated with a 0.158-standard unit higher level of cognitive function (95% CI: 0.130, 0.186, p<0.0001). 4) Outcome of interest #2 Cognitive milieu: Each 1-unit increase in childhood SEP associated with a 0.055-standard unit higher level of cognitive function (95% CI: 0.039 ,0.070, p<0.0001). 5) Outcome of interest #3 Neither SEP (β = -0.003, 95% CI: -

0.009, 0.003; p=0.32) nor cognitive milieu (β==-0.001, 95% CI: -0.004, 

0.002, p=0.39) was associated with cognitive change over time. 

CommentsNone. Quality assFor observ1) Unbias

cohort?

2) Selectio

differenfactors

3) Sample 

differen

4) Adequa

cohort?

5) Validat

ascerta

concepcitation 

6) Validat

ascertaYes. 

7) Outcom

exposu

8) Adequa9) Comple

Yes 

10) Analys

confou

11) Analyti

Yes 
B-72

Study Study Information Participants Risk Factor and 

Outcome Assessment 

Results Comments

Covariates/potential confounders adjusted for in analyses:Age Race Sex Educational level Interactions of time with childhood Method(s) of assessing cognitive status:Global cognitive index, derived from measures of memory, perceptual speed. Symbol Digit Modalities Test; recall portions of the East Boston Story; MMSE. Informant interview?:No 

Feart, Samieri, Rondeau, et al., 2009 Three-City (3C) study 

Geographical location: Bordeaux, France Setting:Community Study design: Prospective cohort Number of participants enrolled:1524 enrolled; 

Age:Mean (SD): 75.9 Range:67.7-94.9 Sex: [n (%)] 

Female: 883,62.6% Male: 527,37.4% Race/ethnicity: [n (%)] NR 

Baseline cognitive status:

Risk factor/exposure 1:Mediterranean Diet Method of assessing risk factor/exposure 1:Self-report; Based on food frequency questionnaire administered by a specifically trained 

1) Follow-up rate: 1213/1524= 79.6% 1524 enrolled; 1410 participants without dementia had at least 1 follow-up; 1213 participants examined at the end of the 3rd and final follow-up 

exam. 2) Important baseline differences: Greater Mediterranean diet adherence was associated with male 

CommentsNone Quality assFor observ1) Unbias

cohort?

2) Selectio

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3) Sample 

differendetect 
B-73

Study Study Information Participants Risk Factor and 

Outcome Assessment 

Results Comments

1410 analyzed Duration of follow up:7 years Time from risk factor assessment to final cognitive assessment:7 years 

Non-demented Inclusion criteria: -65 years or older Exclusion criteria:

-Dementia at baseline 

dietician, frequency of consumption of 40 categories of food and beverages for all meals were recorded and food groups considered to be part of Mediterranean diet were identified and adherence to the diet rated on a 0 to 9 scale. Covariates/potential confounders adjusted for in analyses:Age, Sex, Education, Marital Status, Energy Intake, Physical Activity, Depressive symptomatology, Taking 5 medications or more, Apolipoprotein E genotype, Cardiovascular risk factors, Stroke Method(s) of assessing cognitive status: DSM 4 neuropsychological tests administered by trained psychologists: 1. Mini Mental State 

sex and being married but not with education, income or physical activityIndividuals in the middle or high Mediterranean diet score categories had a lower mean BMI and higher mean energy intake than those in the lowest category 3) Outcome of interest #1Main outcome measure was cognitive performance on the 4 neuropsychological tests. Higher Mediterranean diet score associated with fewer MMSE errors (β=-0.006; 95%CI, -0.01 to -0.0003; 

P=0.04 for 1 point of the Mediterranean diet score) and therefore slower MMSE cognitive decline but this was not consistently the case with other cognitive tests. Among the subgroup who did not develop dementia, higher Mediterranean diet score associated with fewer MMSE errors and less decline on the FCSRT 4) Outcome of interest #2 99 incident cases of dementia 66 probable or possible cases of Alzheimer disease High Mediterranean diet score (6-9) HR 1.12 (0.60-2.10) nor middle scores (4-5) HR 1.11 (0.63-1.94) compared to low scores (0-3) were not associated with lower rates of dementia. High Mediterranean diet score (6-9) 

4) Adequa

cohort?

5) Validat

ascerta

6) Validat

ascertaYes 

7) Outcom

exposu

8) Adequa9) Comple

Yes 

10) Analys

confou

11) Analyti

Yes 
B-74

Study Study Information Participants Risk Factor and 

Outcome Assessment 

Results Comments

Examination (MMSE) 2. Isaacs Set Test (IST) 3. Benton Visual Retention Test (BVRT)4. Free and Cued Selective Reminding Test (FCSRT) Diagnosis of dementia based on 2 Stage procedure First stage: Neurological exam by a neurologist Second stage: Review of potential cases of dementia by independent committee of neurologists with in depth assessment of medical history of each participant to obtain consensus on diagnosis and etiology according to criteria of the Diagnostic and Statistical Manual of Mental Disorders. Informant interview?:No 

HR 0.86 (0.39-1.88) nor middle scores (4-5) HR 0.99 (0.51-1.94) compared to low scores (0-3) were not associated with lower rates of AD. 

Fillenbaum, Kuchibhatla, Hanlon, et al., 2005 Subset of 

Geographical location: Durham, Granville, Vance, Warren, & Franklin Counties, NC Setting:

Age:Mean (SD): 73 Range: 65 - 105 Sex: [n (%)] 

Female: 382 (62%) Male: 234 (38%) 

Risk factor/exposure

1:Vitamins C and E Method of assessing risk factor/exposure 1:

1) Follow-up rate: NR 2) Important baseline differences: Differed on age, education, health service use, prescription drugs 

CommentsNone Quality assFor observ1) Unbias

cohort?
B-75

Study Study Information Participants Risk Factor and 

Outcome Assessment 

Results Comments

Duke Established Populations for Epidemiologic Studies of the Elderly (EPESE) Study 

Community Study design: Prospective cohort Number of participants enrolled:616 Duration of follow up:Follow-up ranged from 3 – 10 years for incident dementia Time from risk factor assessment to final cognitive assessment: 3-4 yrs (data used from the wave prior to the diagnosis of dementia – assume meant inperson wave) 

Race/ethnicity: [n (%)] African-American 382 (62%) Other 234 (38%) Baseline cognitive status:Non-demented Inclusion criteria: ≥ 65 yo; participating in the Duke EPESE Study Exclusion criteria:The implication seems to be that the potential subjects were chosen to oversample for blacks and then all selected subjects in the community were taken.

Self-report Proxy report Covariates/potential confounders adjusted for in analyses:Age Educational level Marital status Income Functional status Health services use # prescription drugs time frame of exposure to vitamins Method(s) of assessing cognitive status:NINCDS-ADRDA DSM Informant interview?:

Yes – does not actually say, but the CERAD protocol (which was used) does use an informant 

3) Outcome of interest #1Vitamin E use at baseline or at wave prior to dementia diagnosis not associated with incident AD 4) Outcome of interest #2 Vitamin C use at baseline or at wave prior to dementia diagnosis not associated with incident AD 

2) Selectio

differenfactors

3) Sample 

differen

4) Adequa

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ascerta

6) Valida

ascertaYes 

7) Outcom

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8) Adequa9) Comple

Can’t T

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confou

11) Analyti

Yes 

Fitzpatrick, Kuller, Lopez, et al., 2009 Cardiovascular Health Study 

Geographical location: Forsyth County, NC; Washington County, MD; Sacramento County, CA; Pittsburgh, PA Setting:Community 

Age:Mean (SD): 74.7 Sex: [n (%)] 

Female: 1654 (59.1%) Male: 1144 (40.9%) Race/ethnicity: [n (%)] White 2457 (87.8%) Non-white 341 (12.2%)

Risk factor/exposure 1:BMI at mid and late lifeMethod of assessing risk factor/exposure 1:Self-report at midlife and Direct measurement at 

1) Follow-up rate: Not clearly stated. Subjects with dementia and mild cognitive impairment excluded from population. 2) Important baseline differences: ≤.001 for age, sex, race, education, smoking status, diabetes mellitus, hypertension, ABI, CRP and IL-6 

CommentsQuestion 1 In evaluatioincreased rfor obese (weight(BMfor demogr1.39; 95% [CI], 1.03-1cardiovasc
B-76

Study Study Information Participants Risk Factor and 

Outcome Assessment 

Results Comments

Study design: Prospective cohort Number of participants enrolled:2798 Duration of follow up:5.4 years Time from risk factor assessment to final cognitive assessment:mean 5.4 years 

Baseline cognitive status:Normal Non-demented Inclusion criteria: Medicare recipients ≥65 years of age in target counties. Exclusion criteria:Dementia or mild cognitive impairment 

late life Covariates/potential confounders adjusted for in analyses:Age Race Sex Educational level Baseline cognitive status cardiovascular and dementia risk factors (including history of hypertension, diabetes mellitus status, coronary heart disease, total cholesterol level, ankle-arm index, Creactive protein level, interleukin 6 level, smoking status, kilocalories expended per week, and apolipoprotein E genotype)Method(s) of assessing cognitive status:NINCDS-ADRDA modifiedMMSE,Digit Symbol Substitution Test,BentonVisual Retention Test, TrailsAandB, Center for Epidemiologic Studies Depression Scale, medications 

levels. 3) Outcome of interest #1Classification resulted in 480 persons with incident dementia,245with Alzheimer disease (no vascular dementia), and 213 with vascular dementia (with or without Alzheimer disease).BMI measured at Midlife (age 50) adjusted HR Overall 1.0 (0.95-1.04) Underweight 1.47 (0.7-3.09 Normal- reference Overweight 1.04 (0.74-1.47) Obese 1.25 (0.74-2.11) 4) Outcome of interest #2 BMI measured at late life (age 65 or older ) adjusted HR Overall 0.95 (0.74-0.99) p=.008 

Underweight 1.42 (0.74-2.70) Normal- reference Overweight 0.74 (0.52-1.05) Obese 0.58 (0.31-.96) p=.03 

0.94-1.95).reversed in BMI. Underhad an incr(1.62; 1.02overweight associated being obesdementia (0with those wQuality assFor observ1) Unbias

cohort?

2) Selectio

differenfactors

3) Sample 

differen

4) Adequa

cohort?

5) Validat

ascerta

6) Validat

ascertaYes 

7) Outcom

exposu

8) Adequa9) Comple

Yes 

10) Analys

confou

11) Analyti

Yes 
B-77

Study Study Information Participants Risk Factor and 

Outcome Assessment 

Results Comments

inventory, activities of daily living, instrumental activities of daily living, other physical function measures (gait speed, balance tests, grip strength, etc), and documentation of hospitalized medical eventsInformant interview?:no. except for deceased. 

Fotuhi, Zandi, Hayden, et al., 2008 Subset of Cache County Study 

Geographical location: Cache Country, UT Setting:Community Study design:

Prospective cohort Number of participants enrolled:

3376 Duration of follow up: f/up 3 and 8 years. At least one f/u to get into study Time from risk factor assessment to final cognitive assessment:Ranged generally from 

Age:Mean (SD):  Grp 1 – 74.3 (6.6)  Grp 2 – 73.9 (6.3)  Grp 3 – 73.6 (5.5)  Grp 4 – 73.4 (6.1)  Grp 5 – 72.9 (6.1) Sex: [n (%)] 

Female: 1974 (58.4%)Male: 1402 (41.6%) Race/ethnicity: [n (%)] NR Baseline cognitive status:Non-demented Inclusion criteria: ≥ 65 yo; resident of Cache Country, UT Exclusion criteria:

Risk factor/exposure

1:nsaids Method of assessing risk factor/exposure 1:self report, probe questions, pill bottles Risk factor/exposure 2:vit E, vit C Method of assessing risk factor/exposure 2: :self report, probe questions, pill bottles Covariates/potential confounders adjusted for in analyses:

1) Follow-up rate: three waves, 63% and 37% 2) Important baseline differences: more females using vit E, vit C or nsaids, vit E and C users more likely to have E4 3) Outcome of interest #1 Users of all 3 (nsaids, vit e, vit c) had less decline than nonusers, but only significant in E4 carriers. 4) Outcome of interest #2 Users of vits e and c performed better at baseline as did users of nsaids alone, but only the combined users did better over time. 

CommentsNone Quality assFor observ1) Unbias

cohort?

2) Selectio

differenfactors

3) Sample 

differen

4) Adequa

cohort?

5) Validat

ascerta

6) Validat

ascertaYes 

7) Outcom

exposu

8) Adequa9) Comple10) Analys
B-78

Study Study Information Participants Risk Factor and 

Outcome Assessment 

Results Comments

3 to 8 years Dementia @ baseline; 

only one 3MS evaluation; incomplete info on medication use 

Age Sex Educational level Dm, cva, apoE status Method(s) of assessing cognitive status:change in 3MS score Informant interview?:

No 

confou

11) Analyti

Yes. 

Fratiglioni, Wang, Ericsson, et al., 2000 Kungsholmen Project

Geographical location: 

Kungsholmen district in Stockholm, Sweden

Setting:Community Study design: Prospective cohort Number of participants enrolled:

1473

Duration of follow up:

3 yrs Time from risk factor assessment to final cognitive assessment:3 yrs 

Age:Range: >75 Sex: [n (%)] Female: 338 (35%) Male: 897 (65%) Race/ethnicity: [n (%)] NR Baseline cognitive status:Non-demented Inclusion criteria: Not demented, Lived at home, Good cognition (Mini Mental Status Examination [MMSE]>23) >75 yrs of age Resident of Kungsholmen Exclusion criteria:NR 

Risk factor/exposure 1:social network Method of assessing risk factor/exposure 1:Self-report and Proxy report (nurse interviews) Covariates/potential confounders adjusted for in analyses:Age Sex Educational level Baseline cognitive status Physical function (ADLs) Depression Vascular disease Method(s) of assessing cognitive 

1) Follow-up rate: Of the 1473s, 98 were excluded at baseline due to impaired cognition (MMSE<24) or institutionalization, and 172 refused to participate in the follow-up examination. Analytical sample = 1203. Follow up rate: 87.5% 2) Important baseline differences: In comparison with the participants, the dropouts were younger (odds ratio 0·96, p=0·017). Differences in social network characteristics not reported. 3) Outcome of interest #1 176 incident dementia cases (126 of Alzheimer’s disease and 32 vascular dementia) Adjusted RR compared with those who were married and living with someone RR(95% CI): Single and living alone 1·9 (1·2–3·1) 

CommentsQuestion1 Results for presented tdementia is Quality assFor observ1) Unbias

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ascerta

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ascertaYes 

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B-79

Study Study Information Participants Risk Factor and 

Outcome Assessment 

Results Comments

status:DSM Informant interview?:

Yes, only when participant was unable to answer 

Widowed/divorced and living alone 1·5 (0·9–2·2) Married and living alone 1·5 (0·4–6·4)Single and living with someone 1·4 (0·5–3·9) Widowed/divorced and living with someone 1·4 (0·4–4·7) 4) Outcome of interest #2 Adjusted RR compared to those who had daily to weekly contact with children and were satisfied: Contact less frequent than weekly and satisfying 1·3 (0·7–2·7) Contact less frequent than weekly and not satisfying 0·9 (0·4–2·3) Contact daily to weekly and not satisfying 2·0 (1·2–3·4) No children 1·4 (1·0–1·9) 5) Outcome of interest #3 RR compared to those who had close social ties on a daily to weekly basis with which they were satisfied: Contact less frequent than weekly and satisfying 1·1 (0·7–1·8) Contact less frequent than weekly and not satisfying 1·2 (0·7–2·0) Contact daily to weekly and not satisfying 1·4 (0·8–2·3) No friends or relatives 1·6 (1·0–2·6) All three social network variables were combined to construct a summary score. Compared to those with an extensive or moderate social network, those with a poor or limited social network were more likely to become demented (RR=1.6; 95% 

Yes 

10) Analys

confou

11) Analyti

Yes 
B-80

Study Study Information Participants Risk Factor and 

Outcome Assessment 

Results Comments

CI: 1·2–2·1). 

Freitag, Peila, Masaki, et al., 2006 HonoluluAsia Aging Study (HAAS) 

Geographical location: Oahu, Hawaii, USA Setting:Community Study design: Prospective cohort Number of participants enrolled:2505 Duration of follow up: 5.1 years of cognitive follow up. Time from risk factor assessment to final cognitive assessment:bp’s checked 3 times 1965-1974, cognitive evals done 1991, 1994, 1999 

Age:Mean at first assessment of dementia: 76.9 years Sex:

Female: 0% Male: 100% Race/ethnicity:Japanese-American 100% Baseline cognitive status:Non-demented Inclusion criteria:  Japanese-American  Male  Born between 1900 and 1919  Living on Oahu Exclusion criteria:NR 

Risk factor/exposure

1:bp, (also pulse pressue, map Method of assessing risk factor/exposure 1:Direct measurement 3 times, five minutes apart, left arm while seated. Covariates/potential confounders adjusted for in analyses:age, education, apo E, antihypertensive meds, midlife alcohol, smoking and bmi, abi, hx of cad, cm or stroke at exam 4 (first cog assessment?) Method(s) of assessing cognitive status:NINCDS-ADRDA DSM CASI Informant interview?:Yes 

1) Follow-up rate: 84% and 90% of survivors at two follow up cognitive evaluations 2) Important baseline differences: higher midlife pulse pressures associated with older age, lower education, lower CASI score, higher bmi and higher sbp and dbp 3) Outcome of interest #1 “in the age adjusted model, sbp, dbp and map, and not pulse pressure, were significantly associated with incident dementia” (but not in fully adjusted model) 4) Outcome of interest #2 After admusting for confounders, the association remained significant only for sbp with a HR of 1.77 (1.1-2.84) for sbp >140 compared with sbp < 

120. 5) Outcome of interest #3 Among those never treated for htn: (above is whole sample), all 4 bp components were correlated with incident dementia, an assoc that did not change after adjusting for cardiovasc confounders. HR 2.66 (1.51 – 4.68) for sbp > 140 as 

compared to < 120. Only AD specific analysis reported - when the single bp component analyses were done (with only adj for age) the “results were similar for VaD 

CommentsAnalyses ddementia, tAD. Quality assFor observ1) Unbias

cohort?

2) Selectio

differenfactors

3) Sample 

differen

4) Adequa

cohort?

5) Validat

ascerta

6) Validat

ascertaYes 

7) Outcom

exposu

8) Adequa9) Comple10) Analys

confou

11) Analyti

Yes 
B-81

Study Study Information Participants Risk Factor and 

Outcome Assessment 

Results Comments

and AD cases.” Also of interest: “none of the analyses were significant when we performed them on late-life instead of midlife bp components” 

Gallacher, Bayer, Fish, et al., 2009 Caerphilly Study 

Geographical location: UK Setting:Community Study design:

Prospective cohort Number of participants enrolled:

2398 in parent study; 1160 analyzed and 982 with complete covariate data Duration of follow up:Mean 17.3 (1.3) years Time from risk factor assessment to final cognitive assessment:Mean 17.3 years 

Age:Range: 48-67 at enrollment; Sex: [n (%)] 

Female: 0, 0% Male: 1160, 100% Race/ethnicity: [n (%)] NR Baseline cognitive status:Non-demented Inclusion criteria: Men Exclusion criteria:NR 

Risk factor/exposure 1:Anxiety: 20-item trait scale of the State Trait Anxiety Inventory (STAI); dichotomized at score of 31 (≥ 31st

percentile) Method of assessing risk factor/exposure 1:Self-report Covariates/potential confounders adjusted for in analyses:Age Race Educational level Marital status Alcohol consumption National Adult Reading test for cognitive function Vascular risk factors Method(s) of assessing cognitive status: 2-stage assessment; dementia using DSM, 

1) Follow-up rate: 1160/2358 with baseline anxiety scores (49%) 2) Important baseline differences: Multiple differences for those with low vs. high anxiety: social class, education, current smoker, GHQ30 score Also multiple differences between analytic sample and overall cohort. 3) Outcome of interest #1Of total sample (1160), 69 had incident dementia and 174 CIND. OR for dementia/CIND with STAI in 31st to 95th percentile OR 2.19 (95% CI 1.24-3.88). Sensitivity analysis excluding men with some decline at baseline, OR 3.36 (1.61,7.01) 4) Outcome of interest #2 OR for CIND with STAI in 31st to 95thpercentile OR 2.31 (95% CI 1.20-4.44). Sensitivity analysis excluding men with some decline at baseline, OR 3.32 (1.51,7.31) 

CommentsNone Quality assFor observ1) Unbias

cohort?

2) Selectio

differenfactors

3) Sample 

differen

4) Adequa

cohort?

5) Validat

ascerta

6) Validat

ascertaPartial, incomp

7) Outcom

exposu

8) Adequa9) Comple10) Analys

confou

11) Analyti

Yes 
B-82

Study Study Information Participants Risk Factor and 

Outcome Assessment 

Results Comments

CIND using CAMCOG <83 or CAMCG decline of ≥ 10 points or unable to produce a CAMCOG despite an attempt but without functional impairment or dementiaInformant interview?:No 

Gatz, Tyas, St John, et al., 2005 Manitoba study of health and aging 

Geographical location: Manitoba, Canada Setting:Community Study design: Prospective cohort Number of participants enrolled:766 Duration of follow up:5 years Time from risk factor assessment to final cognitive assessment:5 years 

Age:Mean (SD): 74.5 (6.0) Range: 65 - 96 Sex: (%) 

Female: 473 (61.7%) Male: 293 (38.3%) Race/ethnicity: [n (%)] NR Baseline cognitive status:Non-demented - >77 on 3MS Inclusion criteria: Age >=65 Randomly selected from those living at home in Manitoba Fluent – english or french Exclusion criteria:Life-threatening condition Unable to complete 

Risk factor/exposure

1:Depression – Center for Epidemiological Studies Depression Questionnaire score ≥16 2. Participant reported history and duration of depression Method of assessing risk factor/exposure 1:Self-report Covariates/potential confounders adjusted for in analyses:Age Sex Educational level Method(s) of assessing cognitive status:2 –stage screening 

1) Follow-up rate: NR Around 20% were lost to follow up due to death. 2) Important baseline differences: NR 3) Outcome of interest #1CESD>=16 OR for AD (36 cases) after 5 years f/u = 2.75 (95% CI 1.04 to 7.24) adjusted for age, sex, education Subject reported h/o depression was not associated with AD at 5 years; OR 1.50 (95% CI 0.49 to 4.63) Subject reported duration of depression was not associate with AD at 5 years; OR 1.01 (95% CI 0.88 to 1.15) 

CommentsMean educyears (3.2) Subjects wolder, had fhigher basebias againsAnalysis usQuality assFor observ1) Unbias

Yes 

2) Selectio

differenYes 

3) Sample 

differen

4) Adequa

cohort: 

5) Validat

ascerta

6) Validat

ascertaYes 

7) Outcom

exposu

8) Adequa
B-83

Study Study Information Participants Risk Factor and 

Outcome Assessment 

Results Comments

screen due to illness or sensory deficits 

NINCDS-ADRDA Informant interview?:No 

9) Comple

Can’t T

10) Analys

confou

11) Analytic 

Geda, Knopman, Mrazek, et al., 2006 Mayo Alzheimer Registry 

Geographical location:Olmsted County, Minnesota Setting:Clinical Study design:

Prospective cohort Number of participants enrolled:

840 Duration of follow up: 3.5 years Time from risk factor assessment to final cognitive assessment:NR 

Age:Range: 50-102 Sex: [n (%)] 

Female: 519 (61.8) Male: 321 (38.2) Race/ethnicity: [n (%)] NR Baseline cognitive status:Normal Inclusion criteria: NR Exclusion criteria: Neurologic or psychiatic condition judged to interfere with cognitive assessment (including current depression)  Psychiatric medicines that could compromise cognition 

Risk factor/exposure

1:Depression; GDS (15 items) >= 6 before MCI diagnosis 2:History of depression Method of assessing risk factor/exposure 1:Self-report every 12-18 months 2:Clinical history-not specified Risk factor/exposure 2:.APOE Genotype Method of assessing risk factor/exposure 2: Direct: PCR using standard methods Covariates/potential confounders adjusted for in analyses: Age  Educational level  Sex 

1) Follow-up rate: NR 2) Important baseline differences: Depressed group older (mean of 84 vs. 77) and more female (68.5% vs. 60.4%) 3) Outcome of interest #1 MCI (50 cases)  GDS >=6 (143 subjects)  HR=2.2 (95% CI 1.2 to 4.1)  Interaction between history of depression and GDS>=6 compared to referent group of no history and no current depression showed:  HR = 4.5 (95% CI 1.9 to 10.9) for no h/o depression and GDS >=6  HR = 2.9 (95% CI 1.5 to 5.8) for h/o depression and GDS <6  HR = 2.6 (95% CI 1.1 to 6.3) for h/o depression and GDS >=6  Test for multiplicative interaction, p=0.008, antagonistic; additive interaction, p=0.3 Addtitional analysis showed:  a non-significant increased risk for depressed men vs. women  no “dose response” relationship when analyzing by depression severity (GDS scores) or duration of depressive symptoms  significant interaction between 

Comments Mean durdepressed  Cox PropQuality assFor observ1) Unbias

Yes 

2) Selectio

differenYes 

3) Sample 

differen

4) Adequa

cohort: 

5) Validat

ascerta(h/o de

6) Validat

ascertaYes 

7) Outcom

exposuTell for 

8) Adequa

Partial, may be 

9) Comple

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10) Analys

confou

11) Analytic 

Yes 
B-84

Study Study Information Participants Risk Factor and 

Outcome Assessment 

Results Comments

Method(s) of assessing cognitive status: Clinical assessment, nuropsychological battery, MRI  MCI by Petersen criteria (memory complaint, normal ADLs, normal general cognitive function, abnormal memory for age, not demented) Informant interview?:Yes 

APOE genotype – increasing the HR for MCI 

Geerlings, den Heijer, Koudstaal, et al., 2008 Rotterdam Study 

Geographical location: The Netherlands Setting:Community Study design: Prospective cohort Number of participants enrolled:563 consented 486 analyzed Duration of follow up:5.9 (1.6) years Time from risk factor assessment to final cognitive assessment:

Age:Range: 60 – 90 years Sex: [n (%)] Female: 238 (49%) Male: 248 (51%) Race/ethnicity: [n (%)] NR Baseline cognitive status:Non-demented Inclusion criteria:  Age 60-90  Random selection stratified by age and sex Exclusion criteria: Dementia 

Risk factor/exposure

1:History of Depression requiring the attention of a GP, psychologist or psychiatrist 2. Current depression defined by CES >=16 Method of assessing risk factor/exposure 1:Self-report Covariates/potential confounders adjusted for in analyses: Age  Sex  Educational level  Baseline cognitive 

1) Follow-up rate: 486/563 (86%) 2) Important baseline differences: More women in depressed group 3) Outcome of interest #1 Risk of incident AD (33 cases)  H/O depression, HR 2.46 (95% CI 1.15 to 5.26)  CESD >=16 at baseline, HR1.02 (95% Ci 0.40 to .64) Subgroup Analysis  H/O depression with onset before age 60 vs >=60  Early onset, 7 cases of AD, HR 3.70 (1.43 to 9.58)  Late onset, 5 cases of AD, HR 1.71 (0.62 to 4.74)  No h/o depression, 21 cases of AD, Reference group 

CommentsNone Quality assFor observ1) Unbias

Yes 

2) Selectio

differenYes 

3) Sample 

differen

4) Adequa

cohort: 

5) Validat

ascertabased o

6) Validat

ascertaYes 

7) Outcom

exposu

8) Adequa
B-85

Study Study Information Participants Risk Factor and 

Outcome Assessment 

Results Comments

5.9 (1.6) years Blind 

 Contraindications to MRI 

status  Subjective memory complaint score Method(s) of assessing cognitive status: 2 stage evaluation;  NINCDS-ADRDA Informant interview?:

 No 

 9) Comple

10) Analys

confou

11) Analytic 

Yes 

Glynn, Beckett, Hebert, et al., 1999 

Geographical location: Boston, USA Setting:Community Study design: Prospective cohort Number of participants enrolled:3657 in overall cohort followed for up to 6 years Subsample 2068 age 65-81 with BP 9 years prior to cognitive baseline Duration of follow up:6 years of cognitive assessments Time from risk factor assessment to final cognitive 

Age:Mean (SD): 72.5 to 75.2 across BPgroups Sex: [n (%)] 

Female: 2230 (61%) Male: 1427 (39%) Race/ethnicity: [n (%)] NRBaseline cognitive status:Not specified, but suspect many with cognitive impairment based on a mean of > 2 errors on SPMSQ Inclusion criteria: Resident of East Boston Age ≥ 65 yo 

Non-institutionalized. Exclusion criteria:NR 

Risk factor/exposure 1:BP at baseline; SBP classified into 5 groups (130-139 referent); DBP classified into 4 groups (70-79 referent)Method of assessing risk factor/exposure 1: Direct measurement based on average of 3 measures 30 seconds apart Covariates/potential confounders adjusted for in analyses:Age Sex Educational level Time in study Method(s) of assessing cognitive 

1) Follow-up rate: 3657 at baseline; 2736 (75%) SPMSQ and 2679 (73%) EBMT at 3 years, 524 died in interval; 1994 (54.5%) SPMSQ and 1970 EBMT (53.9%), 631 died in interval 2) Important baseline differences: Significant differences between BP groups on multiple factors: baseline cognition, age, education, vascular risk factors 3) Outcome of interest #1Overall, BP at baseline or 9 years earlier was not associated with 6 year change in cognition. Only those with SBP ≥ 160 9 years prior to 

baseline 1 of the 5 SBP groups) had a greater increase in SPMSQ errors over time 

CommentsNone Quality assFor observ1) Unbias

cohort?

2) Selectio

differenfactors

3) Sample 

differen

4) Adequa

cohort?

5) Validat

ascerta

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ascertaPartial, to chan

7) Outcom

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confou

11) Analyti
B-86

Study Study Information Participants Risk Factor and 

Outcome Assessment 

Results Comments

assessment:6 years 9-15 years in subsample age 65-81 

status:9-item SPMSQ 6-item East Boston Memory Test Stratified analyses by antihypertensive med use and medical comorbidities 

Yes 

Gonzalez, Bowen and Fisher, 2008 Health and Retirement Study—HRS Merged with AHEAD cohort 

Geographical location: United States Setting:Community Study design: Prospective cohort Number of participants enrolled:18,465 Duration of follow up:6 years Time from risk factor assessment to final cognitive assessment:6 years 

Age: 

Range: 51 to 80+ Sex:Female: 10,867 (57.2%) Male: 7,598 (42.8%) Race/ethnicity: [n (%)] White: 15,334 (87.7%) Nonwhite: 3,119 (12.3%) Baseline cognitive status:Nationally representative sample, irrespective of baseline cognitive status Inclusion criteria: Multistage probability sample, reportedly representative of the U.S. population over age 50 in 1998. Exclusion criteria:Institutionalized 

Risk factor/exposure 1:Depressive symptoms Method of assessing risk factor/exposure 1:Self-report. Depressive Sxs in the week prior to interview. CES-D scale. 8-item version. Score range 0-8 Risk factor/exposure 1:Cardiovascular risk factors. Method of assessing risk factor/exposure 1:Self report. Respondents asked if a doctor ever told them they had diabetes, stroke, HTN, or CVD 

1) Follow-up rate: 72.3% combined year response rate. Wave-to-wave re-interview response rates ranged from 92.1% to 87.5%. 2) Important baseline differences: NA 3) Outcome of interest #1Depressive sxs were associated with significantly lower Immediate (-0.05; p<0.001) and Delayed (=-0.06; p<0.001) word list recall scores. 4) Outcome of interest #2 Depressive Sx: Betas and SE: Immediate recall: -0.05 (0.00), p<0.001 Delayed recall: -0.06 (0.00), p<0.001 5) Outcome of interest #3 CVD risk factors Betas and SE: Immediate recall: -0.07 (0.001), p<0.001 Delayed recall: -0.10 (0.00), p value not reported, but > 0.001 

CommentsNone Quality assFor observ1) Unbias

cohort?

2) Selectio

differenfactors

3) Sample 

differen

4) Adequa

cohort?

5) Validat

ascerta

6) Validat

ascertaYes 

7) Outcom

exposu

8) Adequa9) Comple10) Analys

confou

11) Analyti

Yes 
B-87

Study Study Information Participants Risk Factor and 

Outcome Assessment 

Results Comments

Covariates/potential confounders adjusted for in analyses:Age Race Sex Educational level Wordlist exposure frequency Households with more than 1 respondent Method(s) of assessing cognitive status:Verbal learning and memory of a 10-word list learning task Immediate recall: immediately after having been read a list of 10 words. Delayed: after 3 minutes of interference tasks. Informant interview?:No 

Graves, Rajaram, Bowen, et al., 1999KAME Project 

Geographical location: King County, Washington, USA Setting: Community  Clinical – 

Age:Range: 65-95+ Sex: [n (%)] 

Female: 1028(56%) Male: 808 (44%) Race/ethnicity: [n (%)] 

Risk factor/exposure

1:Migration history, education, number of years lived in Japan before age 18 y, age at which English became main language spoken 

1) Follow-up rate: 87% completed 2 year follow up. 77 died 117 refused 2nd testing. 

37 moved or where lost to f/u 2) Important baseline differences: NR. 

CommentsQuestion 2 Quality assFor observ1) Unbias

cohort?

2) Selectio
B-88

Study Study Information Participants Risk Factor and 

Outcome Assessment 

Results Comments

institutionalized and non institutionalized patients in the census Study design: Prospective cohort Number of participants enrolled:1836 at baseline 1604 at 2 yr follow up Duration of follow up:2 years Time from risk factor assessment to final cognitive assessment:Life-long exposure or since childhood. Measurement is 2 years follow up for cognition. 

Japanese origin (96%)  Japanese American (1 parent only Japanese) 4%Baseline cognitive status:Non-demented Inclusion criteria: 65 y or older Living in King County, WA With Japanese Heritage; 1 or 2 parents Japanese. Exclusion criteria:

Dementia Younger than 65 

at home, language usually spoken at home currently, current facility with reading and writing Japanese. Method of assessing risk factor/exposure 1:Self-report With highly structured interview Risk factor/exposure 2:Friends growing up being mainly Japanese vs. non Japanese, or even number of both. Current friends Japanese, non Japanese or even number of both. Current religion. Diet consistent of mainly Asian food, Asiand and western equally or mainly western. Method of assessing risk factor/exposure 2:Self-report with highly structured interview. Covariates/potential confounders adjusted for in analyses:Age Sex 

3) Outcome of interest #1CASI mean change -1 SD of -5.15 points= 144 decliners 1455 non decliners 4) Outcome of interest #2 After adjusting for baseline age, sex, baseline CASI score, education and follow up time the results are as follows: 

- Home language only/mostly Japanese: OR:0.45 CI 0.23-0.86, p<.01  - English Home language after 40 y : OR 0.42, CI 0.21-0.81 p<.01 - Baseline interview taken in Japanese: OR0.38, CI 0.21-0.69 p<.01 - Generation Issei (born in Japan) OR 0.28, CI 0.13-0.58 p<.01; - Kibei (born in US, Japan education) OR 0.58, CI 0.33-1, p<.05, compared to US born and educated - Any education in Japan: OR 0.44, CI: 0.27-0.73, p<.01 - Years lived in Japan1-7 OR 0.46, CI 0.23-0.91, P<.05; - Years lived in Japan 8-15: OR0.38, CI 0.19-0.78, p<.01; - Years lived in Japan 16-18: OR 0.32, CI 0.15-0.69, p<.01, compared to 0 years - Reads/write Japanese with no difficulty: OR 0.42, CI: 0.23-0.77, p<.01; - Reads /write with difficulty OR 0.96, CI 0.62- 1.47; compared to Does not read/write Japanese 

differenfactors

3) Sample 

differen

4) Adequa

cohort?

5) Validat

ascerta

6) Validat

ascertaYes 

7) Outcom

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8) Adequa9) Comple10) Analys

confou

11) Analyti

Yes. 
B-89

Study Study Information Participants Risk Factor and 

Outcome Assessment 

Results Comments

Educational level Baseline cognitive status f/u time Method(s) of assessing cognitive status:Other – CASI (cognitive abilities screening instrument) decline was defined as mean change – 1 SD, ie:>5.15 points loss in 2 yrs. Random measurement error inherent in CASI taken into account. Informant interview?:No 

-Current friends mostly Japanese: OR0.64, CI 0.44-0.93, p<.01; Past friends mostly Japanese OR 0.91, CI 0.63-1.33 5) Outcome of interest #3 - Eastern religion (Buddhist, Shinto) OR 1.34, CI 0.87-2.07 - - Eat only Asian foods OR 0.96, CI 0.62-1.49. 

Gray, Anderson, Crane, et al., 2008 Adult Changes in Thought study (ACT) 

Geographical location: Seattle, WA Setting:Clinical – Group Health Cooperative Study design: Prospective cohort Number of participants enrolled:2969 Duration of follow up:Mean 5.5 (+ 2.7) yrs 

Age:Mean (SD):  Group A 75.4 (6.2)  Group B 76.1 (6.6)  Group C 75.4 (6.2) Sex: [n (%)] Female: 1768 (60%) Male: 1201 (40%) Race/ethnicity: [n (%)] 

Caucasian 2681(90.3%) Other 288 (9.7%)Baseline cognitive status:

Risk factor/exposure

1:Nutritional intake of Vit C, E, or multivitamins (MVI) for at least 1 week during the previous month at baseline. Method of assessing risk factor/exposure 1:Self-report Risk factor/exposure 2:APOE 

1) Follow-up rate: 2969/3392 (87.5%) 2) Important baseline differences: NA 3) Outcome of interest #1 Primary analysis examined whether baseline vitamin E or C use was associated with incident AD, compared with nonuse: no vitamin E, vitamin C, or MVI. Also looked at potential synergistic effect of Vitamin E and C. Results: “No difference was found in 

CommentsNone Quality assFor observ1) Unbias

cohort?

2) Selectio

differenfactors

3) Sample 

differen

4) Adequa

cohort?

5) Validat

ascerta

6) Validat
B-90

Study Study Information Participants Risk Factor and 

Outcome Assessment 

Results Comments

Time from risk factor assessment to final cognitive assessment:Mean 5.5 (+ 2.7) yrs 

Non-demented Inclusion criteria: Participating in Adult Changes in Thought (ACT) study; free of dementia (CASI ≥86, 

or scored <86 but had no evidence of dementia based on additional medical record review and standard clinical and neuropsychological evaluation for dementia) Exclusion criteria:NR 

Method of assessing risk factor/exposure 2:Direct measurement Covariates/potential confounders adjusted for in analyses:Age Sex Educational level Exercise Smoking status Self-reported health Coronary heart diseaseMethod(s) of assessing cognitive status:Screened with CASI every 2 years. If score <86, underwent dementia diagnostic eval. Relevent lab tests and brain CT performed or obtained from records. NINCDS-ADRDA DSM IV Informant interview?:No 

degree of association between supplement use and overall dementia or AD risk when stratified according to age.” 4) Outcome of interest #2—AD Adjusted HR’s (95% CI) for possible or probable AD. 1. No vitamins (n=106): 1.0 (referent)2. Any Vit. E (n=89): 1.04 (.78-1.39) 3. Any Vit. C (n=105): 0.95 (.72-1.25)4. Any MVI (n=134): 0.94 (.72-1.22) 

ascertaYes 

7) Outcom

exposu

8) Adequa9) Comple

Yes 

10) Analys

confou

11) Analyti

Yes 

Green, Rebok and Lyketsos, 2008 

Geographical location: Baltimore, USA 

Age:Mean (SD): 47.3 at enrollment. 

Risk factor/exposure

1:Network size 

1) Follow-up rate: 33.53% 874 out of 2607 

CommentsFollow up rsignificant dgroups that 
B-91

Study Study Information Participants Risk Factor and 

Outcome Assessment 

Results Comments

BLSA 

Setting:Community Study design: Prospective cohort Number of participants enrolled:3481 adults interviewed at wave 1 1920 interviewed at wave 3 and 1071 interviewed at wave 4. 874 included in this analysis. Duration of follow up:10.9 yrs. Time from risk factor assessment to final cognitive assessment:10.9 yrs. 

Sex: [n (%)] 

Female: 550 (62.9%) Male: 324 (37.1) Race/ethnicity: [n (%)] AA 322 (36.8%) White 526 (60.2%) Other 26 (2.97) Baseline cognitive status:Mean MMSE 28.9 but individuals with decreased cognition not specifically excluded Inclusion criteria: Participants having cognitive scores at wave 3 and 4 Exclusion criteria:NR 

Method of assessing risk factor/exposure 1:Self-report Risk factor/exposure 2:Frequency of interaction Method of assessing risk factor/exposure 2:Self-report Risk factor/exposure 3:Emotional support Method of assessing risk factor/exposure 3:Self report. Covariates/potential confounders adjusted for in analyses:Age Race Sex Educational level Past year household income Depressive symptomatology Lifetime alcohol use disorder, Ability to perform ADLsCerebrovascular disease. 

2) Important baseline differences:Assessed participants were younger, had more education, higher income and higher MMSE scores. 3) Outcome of interest #1 After adjustment of covariates, participants 

with more frequent contacts at baseline exhibited greater decline in delayed recall p = 0.042. When this was controlled for health factors, p= 0.057.4) Outcome of interest #2 After adjusting for Age Race Sex Educational level Past year household income Depressive symptomatology Lifetime alcohol use disorder, Ability to perform ADLs Cerebrovascular disease change in MMSE was not significantly affected by network size β= 0.028 (-0.037, 0.093) p= 0.403;  frequency of contact β= 0.002 (-0.073, 0.078) p= 0.950; emotional support β = -0.004 (-0.047, 0.040) p= 0.862; or composite social network β = 0.005 (-0.023, 0.033) p = 0.721 at wave 3. 

who were lQuality assFor observ1) Unbias

cohort?

2) Selectio

differenfactors

3) Sample 

differen

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cohort?

5) Validat

ascerta

6) Validat

ascertaYes 

7) Outcom

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8) Adequa9) Comple10) Analys

confou

11) Analyti

Yes 
B-92

Study Study Information Participants Risk Factor and 

Outcome Assessment 

Results Comments

Baseline cognitive status Method(s) of assessing cognitive status: MMSE Delayed recall Informant interview?:No 

Grodstein, Skarupski, Bienias, et al., 2008 CHAP (Chicago) 

Geographical location: 3 neighborhoods (Morgan Park, Beverly, & Washington Heights) in south Chicago, IL Setting:Community Study design: Prospective cohort Number of participants enrolled:4409 Duration of follow up: From 3 to 9 years Time from risk factor assessment to final cognitive assessment:from 3 to 9 years Details on lifetime use of NSAIDS collected at Cycle 2 – concurrent 

Age:Range: 65+ yo Sex: [n (%)] 

Female: 2722 (61.7%)Male: 1687 (38.3%) Race/ethnicity: [n (%)] White 1699 (38.5%) Black 2710 (61.5%)Baseline cognitive status:did not remove demented folks (or even dx dementia) Inclusion criteria: ≥ 65 yo; completed baseline & at least 1 f/u interview Exclusion criteria: NR 

Risk factor/exposure

1:nsaids Method of assessing risk factor/exposure 1:checked pill bottles, self reported duration of use Covariates/potential confounders adjusted for in analyses:Age Race Sex Educational level Interaction of time with each Cardiovascular factors Method(s) of assessing cognitive status:change in test scores

1) Follow-up rate: 90% did 3 follow ups, 80% did all four 2) Important baseline differences: ASA users higher educ, more whites, more strokes NSAID users-more joint pain Both ASA and NSAID-higher global cognitive score 3) Outcome of interest #1 No relation of current use of ASA or NSAIDS to cog decl. 4) Outcome of interest #2 No relation to longer use of ASA. 5) Outcome of interest #3 For NSAIDS, longer use assoc. with slower cog. decl. For analysis with the lowest 10% of baseline scores out, mean cog decline of 0.009 (p=0.02) with short use; 0.013 (p-0.06) with longer use. (NSAIDS) Data not changed in this analysis with ASA. 

CommentsNone Quality assFor observ1) Unbias

cohort?

2) Selectio

differenfactors

3) Sample 

differen

4) Adequa

cohort?

5) Validat

ascerta

6) Validat

ascertaYes 

7) Outcom

exposu

8) Adequa9) Comple10) Analys

confou

11) Analyti

Yes 
B-93

Study Study Information Participants Risk Factor and 

Outcome Assessment 

Results Comments

with one time point of cognitive change score – also new users of NSAIDS could be identified in Cycle 2 

Informant interview?:No 
B-94

Study Study Information Participants Risk Factor and 

Outcome Assessment 

Results Comments

Haag, Hofman, Koudstaal, et al., 2009a The Rotterdam Study 

Geographical location: Rotterdam, The Netherlands Setting:Community Study design:

Prospective cohort Number of participants enrolled:

6992 Duration of follow up:Mean 9.2 yrs (up to 15.3 yrs) Time from risk factor assessment to final cognitive assessment:Anytime prior to event 

Age:Mean (SD): 69.4 (9.1) Sex: [n (%)] 

Female: 4195 (60%) Male: 2797 (40%) Race/ethnicity: [n (%)] NR Baseline cognitive status:Non-demented Inclusion criteria: Age ≥55; residing in 

Ommoord, NE Exclusion criteria:Dementia; <6 mos medication history 

Risk factor/exposure

1:statins –  Simvastatin (58.7%)  Pravastatin (13.5%)  Atrovastatin (13%)  Fluvastatin (5.7%)  Cerivastatin (0.5%)  Rosuvastatin (0.2%) Non-statin  cholesterol lowering  drugs (8.4%) of Rx Method of assessing risk factor/exposure 1:Direct measurement Other – pharmacy records Risk factor/exposure 2:Age, sex, education level, smoking Method of assessing risk factor/exposure 2:Self-report Covariates/potential confounders adjusted for in analyses:Age, Sex, use of other lipid lowering agents, education, systolic blood pressure, smoking, total serum 

1) Follow-up rate: NR 438 people who were not exposed to statins developed AD. HR = 1.00 (REF) 28 people who were on statins developed dementia. HR= 0.57 (0.37-0.90) 

CommentsVery good pharmacy radherence) Quality assFor observ1) Unbias

cohort? 

2) Selectio

differenYes 

3) Sample 

differen

4) Adequa

cohort? 

5) Validat

ascerta

6) Validat

ascertaYes 

7) Outcom

exposu

8) Adequa9) Comple

Can’t Tmanusccompathis stufollow-u

10) Analys

confou

11) Analytic 

Yes 
B-95

Study Study Information Participants Risk Factor and 

Outcome Assessment 

Results Comments

cholesterol, BMI, DM, cardiovascular illnesses and cerebrovascular illnesses. Method(s) of assessing cognitive status:NINCDS-ADRDA Other – MMSE<26 OR Geriatric Mental State organic level >0 underwent Cambridge examination for mental disorders of the elderly. If dementia suspected, “more extensive neuropsychological testing was performed.” Incident dementia from medical records (GP and Mental Health) Informant interview?:No 

Haag, Hofman, Koudstaal, et al., 2009b Rotterdam study 

Geographical location: Ommoord, a district of Rotterdam, the Netherlands Setting:Community Study design: Prospective cohort 

Age:Mean (SD): 68.4 Sex: [n (%)] 

Female: 3749 (60%) Male: 2500 (40%) Race/ethnicity: [n (%)] Caucasian 6249 (100%)Baseline cognitive 

Risk factor/exposure 

1:antihypertensives Method of assessing risk factor/exposure 1:Other – pharmacy record Covariates/potential confounders 

1) Follow-up rate: 6249/7046= 88.7% 2) Important baseline differences: NR 3) Outcome of interest #1Model II HR for AD (432 cases) Any Anti-hypertensive Never use: 1.0 <1.6 years 0.91 (.71-1.17) 1.6-5.3 years: 0.73 (.55-.96) 

CommentsQuestion 1 Antihypertewith a redu(adjusted H(95% CI 0.9-1%) risk refor persons 

whereas fowas 4% (95Equivalent 
B-96

Study Study Information Participants Risk Factor and 

Outcome Assessment 

Results Comments

Number of participants enrolled:6249 Duration of follow up:Up to 13.3 years Average 8 years Time from risk factor assessment to final cognitive assessment:average 8 years 

status:Non-demented Inclusion criteria: All persons aged _55 years living in Ommoord, a district of Rotterdam, were invited to participate. Of 10,275 eligible persons, 7,983 (78%) signed informed consent. Of these, 7,528 (94%) were screened for dementia and 7,046 were free of dementia at baseline Exclusion criteria:

dementia 

adjusted for in analyses:Age Sex Educational level systolic and diastolic blood pressure, current smoking, total serum cholesterol, body mass index, diabetes mellitus, and cardiovascular and cerebrovascular disease. All analyses were adjusted for age, sex, and systolic and diastolic blood pressure (model I). To adjust for potential confounders (model II) included smoking, total serum cholesterol, education, body mass index, diabetes mellitus, and cardiovascular and cerebrovascular disease .Method(s) of assessing cognitive status:DSM III-R NINCDS-ADRDA Informant interview?:No 

>5.3 years 0.69 (.46-1.05) HR per year treatment: 0.94 (.90-.99)4) Outcome of interest #2 Antihypertensive use by age: Model II HR for AD Age <75 or >75 no significant association between use of antihypertensives and AD 5) Outcome of interest #3 Model II HR for AD No differences were found between classes of antihypertensive medications and AD. 

observed fodifferences different typdrugs. Quality assFor observ1) Unbias

cohort? 

2) Selectio

differenYes 

3) Sample 

differen

4) Adequa

cohort? 

5) Validat

ascerta

6) Validat

ascertaYes 

7) Outcom

exposu

8) Adequa9) Comple10) Analys

confou

11) Analytic 

Yes 
B-97

Study Study Information Participants Risk Factor and 

Outcome Assessment 

Results Comments

Haan, Shemanski, Jagust, et al., 1999 Cardiovascular Health Study (CHS) 

Geographical location: Medicare files: Forsyth County,NC Sacramento County, CA; Washington County, MD; Pittsburgh, PA Setting:Community Other – Medicare files Study design:

Prospective cohort Number of participants enrolled:

Not clear- number of subjects with testing at each year is listed. 3622 subjects had 3MS at 7 year followup (listed as year 9 in Table 1); 3333 had digit symbol substitution test. Duration of follow up:5-7 years Time from risk factor assessment to final cognitive assessment:5 years one cohort; 7 years other cohort 

Age:Range: ≥ 65 years Sex: [n (%)] 

Female: 57% Male: 43% Race/ethnicity: [n (%)] 85% white 5% blackBaseline cognitive status:Non-demented Inclusion criteria: Residence in counties of interest; Age≥65; 

not institutionalized; Able to give informed consent Exclusion criteria:Age<65; not able to give informed consent. 

Risk factor/exposure 1:Hypertension (Systolic Bp>158mm Hg) Method of assessing risk factor/exposure 1:Direct measurement Risk factor/exposure 2:Diabetes- presence also identified at biannual follow-up visit. All diabetes included in analysis. Method of assessing risk factor/exposure 2:Self-report and confirmed by medical record review or physician 

questionnaire. Risk Factor/exposure 3: APOE ε4 Method of assessing risk factor/exposure 3: Genotyping Covariates/potential confounders adjusted for in analyses:Age 

1) Follow-up rate: NR 2) Important baseline differences: NR 3) Outcome of interest #1 7 year change Risk: Systolic BP>158 DSSRisk absent: -.09 Risk present: -.62 P<.0001 3MSE Risk absent: -.16 Risk present: -1.12 Increase in bp of 1 sd over mean (21.84 mmHg) was associated with a decrease of 0.96 pts in 3MS over 7 years and 0.53 points in DSS over 7 years. Legend seems to indicate both were significant at p<0.0001. 4) Outcome of interest #2 7 year change Risk Diabetes mellitus DSSRisk absent: -.23 Risk present: -1.61 P<.0001 3MSE Risk absent: -.10 Risk present: -.71 5) Outcome of interest #3 7 year change Risk APOE ε4 any DSS 

CommentsData reportyears of folrecruited at include this first cohort Diabetes avisits and luQuality assFor observ1) Unbias

cohort? 

2) Selectio

differenYes 

3) Sample 

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ascertaYes 

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8) Adequa9) Comple

Can’t T

10) Analys

confou

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Yes 
B-98

Study Study Information Participants Risk Factor and 

Outcome Assessment 

Results Comments

Race Sex Educational level Incident stroke Method(s) of assessing cognitive status: 3MSE Digit symbol substitution testInformant interview?:No 

Risk absent: -.29 Risk present: -2.00 P<.0001 3MSE Risk Absent: -.42 Risk Present: -2.94 6) Outcome of interest #4 Annual rate of change on 3MSE in subjects with and without APOEε4 AND with or without Diabetes. + APOEε4 and + DM: -.39 

+ APOEε4 and – DM: -.70 

-APOEε4 and +DM: -.46 

- APOEε4 and -DM: -.23 P<.001 for interaction (f/u year x risk factor x APOEε4) Ratio of annual decline with APOEε4

+ APOEε4 and + DM: 1.67 

+ APOEε4 and – DM: 3.01 

-APOEε4 and +DM: 1.99 - APOEε4 and -DM: 1.00 All values adjusted for age, sex, education. 

Hakansson, Rovio, Helkala, et al., 2009 CAIDE study 

Geographical location: Kuopio and Joensuu regions in eastern Finland Setting:Community Study design: [ 

Age:Mean (SD): 50.4 (4.9) Range:65-79 Sex: [n (%)] 

NR Race/ethnicity: [n (%) Caucasian 

Risk factor/exposure 1: marital status (married/cohabiting, single, divorced, or widowed) measured at mid-life and follow-up. Method of assessing risk factor/exposure 

1) Follow-up rate: 1449/2000= 72% 2) Important baseline differences: % participated in follow-up Age, % women, education, occupation physical activity, % smokers midlife, % office workers 3) Outcome of interest #1

CommentsQuestion 1 No cognitivMMSE donQuality assFor observ1) Unbias

cohort? 
B-99

Study Study Information Participants Risk Factor and 

Outcome Assessment 

Results Comments

Prospective cohort Number of participants enrolled:1449 Duration of follow up:Average 21 years Time from risk factor assessment to final cognitive assessment:Average 21 years 

Baseline cognitive status:Non-demented Inclusion criteria: The participants of the CAIDE study comprised a random sample of 2000 survivors from four separate population samples, originally investigated in 1972, 1977, 1982, or 1987. Age at original enrollment 30-59. Exclusion criteria:

NR 

1:Self-report Covariates/potential confounders adjusted for in analyses:Age Sex Educational level Baseline cognitive status BMI APO E Systolic BP Region of residence Smoking Occupation Physical activity at work Depression at mid-life Method(s) of assessing cognitive status:If MMSE score <24 then NINCDS-ADRDA DSM-IV Informant interview?:No 

Risk of AD (44/1216) Status at mid-life Without partner 2.06 (0.9-4.7) Widowed 2.52 (0.8-7.7) Single/divorced 1.78 (0.7-4.9) 4) Outcome of interest #2 Risk of Cognitive Impairment (131/1303) Status at mid-life Without partner 2.09 (1.3-3.4) Widowed 2.76 (1.5-5.2) Single/divorced 1.56 (0.9-2.8) 5) Outcome of interest #3 Risk of MCI (78/1250) Status at mid-life Without partner 2.14 (1.2-3.8) Widowed 3.30 (1.6-6.9) Single/divorced 1.50 (0.7-3.4) With cohabiting apolipoprotein E e4 non-carriers as reference, the odds ratio for apolipoprotein E e4 carriers who had been widowed or divorced both in mid-life and later life was OR 25.55 (5.7 - 114.5, P<0.001)OR for APOE e4 carriers who were widowed or divorced both at baseline and follow-up was considerably lower with mild cognitive impairment as outcome (OR 4.68, 1.65 to 13.3) OR for those who were widowed or divorced after mid-life for mild cognitive impairment (2.66, 1.1 to 6.2) and for Alzheimer’s disease (5.0, 1.4 to 17.5) were generally lower than those widowed 

or divorced at mid-life. 

2) Selectio

differenYes 

3) Sample 

differen

4) Adequa

cohort? 

5) Validat

ascerta

6) Validat

ascertaYes 

7) Outcom

exposu

8) Adequa9) Comple10) Analys

confou

11) Analytic 

Yes 
B-100

Study Study Information Participants Risk Factor and 

Outcome Assessment 

Results Comments

Hayden, Zandi, Khachaturian, et al., 2007 Cache County Study 

Geographical location: Cache County, UT Setting:Community Study design: Prospective cohort Number of participants enrolled:3383 Duration of follow up At least one follow up, baseline 95-96, first f/u 98-99, second 02-03 Ranged from 3 – 8 years Time from risk factor assessment to final cognitive assessment:ranged from 3 to 8 years approximately 

Age:Mean (SD):  NSAID users 73.7 (6.2)  Non-NSAID 74.2 (6.5) Sex: [n (%)] 

Female: 1978 (58.4%)Male: 1405 (41,6%) Race/ethnicity: [n (%)] NR Baseline cognitive status:Non-demented Inclusion criteria: ≥ 65 yo; pts contributed multiple time points for longitudinal analysis Exclusion criteria:Dementia @ baseline; pt provided a 3MS score at only one time point; pt provided incomplete info on NSAID use 

Risk factor/exposure 1:NSAID use Method of assessing risk factor/exposure 1:self report, probe questions, pill bottles Covariates/potential confounders adjusted for in analyses:Age Sex, education, apoE, dm, cva, time followed up, quadratic term for time [I would not consider these to be covariates] okay Method(s) of assessing cognitive status: Change on the 3MS Informant interview?:No 

1) Follow-up rate: 

97.3% first f/u exam 66.0% second f/u exam 2) Important baseline differences: nsaid users more likely female, htn, high chol. sl higher 3ms scores (<half a point) 3) Outcome of interest #1 No real difference with longer term users (started pre 65 yo) who have no E4. 4) Outcome of interest #2 E4 protective with earlier start nsaids. 5) Outcome of interest #3 Later onset of use(after 65 yo), those with E4 had higher scores at baseline but same change over time.6) Outcome of Interest #4 No E4, late start, more decline 

CommentsNone Quality assFor observ1) Unbias

cohort?

2) Selectio

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3) Sample 

differen

4) Adequa

cohort?

5) Validat

ascerta

6) Validat

ascertaYes 

7) Outcom

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8) Adequa9) Comple

Yes 

10) Analys

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11) Analyti

Can’t T

Hebert, Scherr, Bennett, et al., 2004 CHAP 

Geographical location: Chicago, USA Setting:Community 

Age:Mean (SD): 74 (6.4) Sex:

Female: 62% Male: 38% 

Risk factor/exposure

1:htn/bp Method of assessing risk factor/exposure 1:

1) Follow-up rate: 64% had all three visits, 36% had two visits 2) Important baseline differences: cognitive change and bp both treated as continuous variables 

CommentsNone Quality assFor observ1) Unbias

cohort?
B-101

Study Study Information Participants Risk Factor and 

Outcome Assessment 

Results Comments

Study design: Prospective cohort Number of participants enrolled:6158 Duration of follow up: baseline with up to six years follow up Time from risk factor assessment to final cognitive assessment:meds checked at baseline, bp checked every time? Cognition checked every time 

Race/ethnicity:

African American 62% White 38% Baseline cognitive status:can’t tell from here, but this is the Chicago biracial study and I don’t believe they eliminated the cognitively impaired. Baseline mmse 26.3 (4.4) Inclusion criteria:  Age > 65 years 

 Live in a particular geographically defined community Exclusion criteria:NR 

Direct measurement two sitting blood pressures done each visit, mean used. Risk factor/exposure 2:antihypertensives Method of assessing risk factor/exposure 2:Self-report of meds taken within the last two weeks done at baseline visit. Implies that pill bottles were checked also. Covariates/potential confounders adjusted for in analyses:Age, Race, Sex, Educational level, either systolic or diastolic bp (whichever wasn’t examined, I think) Method(s) of assessing cognitive status:change in summary cognitive score

Informant interview?:No 

3) Outcome of interest #1 Outcome was predicted annual change in global outcome score over a 6 year interval for 1 mmHg increase in bp. Neither sbp nor dbp were related to cognitive change. Sbp -0.0001 (-0.0003 to 0.00001) Dbp -0.00002 (-0.00036 to 0.00032) 4) Outcome of interest #2 dbp entered as a quadratic term is said to be significant in a curvilinear fashion such that 75mmHg has a minimum decline. 5) Outcome of interest #3 “None of the indicators for medications (general antihypertensives or type of antihypertensive) substantially altered the result.” 

2) Selectio

differenfactors

3) Sample 

differen

4) Adequa

cohort?

5) Validat

ascerta

6) Validat

ascertaYes 

7) Outcom

exposu

8) Adequa9) Comple

Yes 

10) Analys

confou

11) Analyti

Yes 

Hee Kang, Geographical Age: Risk factor/exposure 1) Follow-up rate: Comments
B-102

Study Study Information Participants Risk Factor and 

Outcome Assessment 

Results Comments

Cook, Manson, et al., 2007 Women’s Health Study 

location: 11 US locations Setting:Community Study design: RCT Test intervention Asa 100mg & vitamin E 600 IU on alternate days Comparator intervention(s) placebo Number of participants enrolled:6377 Duration of follow up: For cognition follow-up was about 4 yrs (3 time pts) 9.6 years Time from risk factor assessment to final cognitive assessment:first cog assessment 5.6 yrs after randomization, then q2yrs. 

Mean (SD): 71.8 -71.9Range: 70 – 81?? Sex: [n (%)] 

Female: 6377 (100%) Male: 0 (0%) Race/ethnicity: [n (%)] White > 6058 (> 95%) Baseline cognitive status:Assumed Normal Inclusion criteria: Participating in the Women’s Health Study; age 65 or older; providing information on NSAID and potential confounders in biennial questionnaires Exclusion criteria:No hx of CHD, CVD, CA, or other major chronic illnesses, no current use of study medications or hx of side effects from study meds 

1:RCT 100 mg asa Method of assessing risk factor/exposure 1: RCT Covariates/potential confounders adjusted for in analyses:Age baseline score, perceived change in memory, cigarettes, education, etoh, bmi, physical activity, hrt, dm, htn, hyperchol, depression, cardiovasc dz. Method(s) of assessing cognitive status:Change over time on various cognitive measures

Informant interview?:No 

79.5% all cognitive assessment, 80% all assessments, 79% placebo 2) Important baseline differences: none 3) Outcome of interest #1 No differences were observed in mean change in cognitive performance by treatment assignment for cognitive outcome. 

None Quality assFor RCTs: 1) Baselin2) Valid A

assess

3) Subjec4) Outcom5) Incomp

addres

6) Differen

Yes 

7) Overall 

Yes 

8) Conflic

insignif

9) Random10) Allocat

adequa

Hee Kang and Grodstein, 2003

Geographical location: 11 US States 

Age:Range: 70 – 81 yo Sex: [n (%)] 

Risk factor/exposure

1:nsaids/asa 

1) Follow-up rate: 93% did baseline. Of those 90% did follow up. 

CommentsFindings stauthors in t
B-103

Study Study Information Participants Risk Factor and 

Outcome Assessment 

Results Comments

Nurses’ Health Cohort 

Setting:Community Study design: Prospective cohort Number of participants enrolled:16,128 Duration of follow up: exposure 1980 and q2yrs until 1998, cognition baseline and 2 years later Time from risk factor assessment to final cognitive assessment:f/up cog testing 2 yrs after baseline which was 1995-2001 

Female: 16,128 (100%) Male: 0 (0%) Race/ethnicity:NR Baseline cognitive status:Used cohort from ongoing study, didn’t give categorical dx Inclusion criteria: Had answered the most recent f/u questionnaire; were free of diagnosed stroke; had complete information on NSAID and aspirin use Exclusion criteria:diagnosed stroke; otherwise it looks like they took everyone over 70 

Method of assessing risk factor/exposure 1:Self-report Covariates/potential confounders adjusted for in analyses:Age Sex Educational level Categorical value for each test, hx dm, hx heart disease, vit E, hrt, menopause age, bmi, cigarettes, alcohol, mental health index, energy fatigue index Method(s) of assessing cognitive status:decline in testing scores

Informant interview?:No 

2) Important baseline differences:asa and nsaid users: sl less educ, poorer health, more htn, dm, cad, more use of other meds incl antidepressants, vit E, hrt nsaid users but not asa users more likely to be obese. 3) Outcome of interest #1 many analyses and done individually for each test but over all: RR of global score decline for use of nsaids 3 years before testing: 0.95 (0.70-1.29) 

Quality assFor observ1) Unbias

cohort?

2) Selectio

differenfactors

3) Sample 

differen

4) Adequa

cohort?

5) Validat

ascertaself-rep

6) Validat

ascertaYes 

7) Outcom

exposu

8) Adequa9) Comple10) Analys

confou

11) Analyti

Yes 

Helmer, Damon, Letenneur, et al., 1999 PAQUID 

Geographical location: Southwestern France Setting:Community Study design: Prospective cohort 

Age:Mean (SD): NR 1822 older than 74 yrs at baseline. Sex:

Female: 2133 (58%) Male: 1541 (42%) Race/ethnicity:

Risk factor/exposure 1:Marital Status Method of assessing 

risk factor/exposure 1:Self-report 1) Married or 

1) Follow-up rate: 3675 nondemented participants: 794 (21.6%) lost to followup (365 died, 12 lost to f/u, 417 refused f/u).b Follow-up rate: 2881/3675 = 78.4% 2) Important baseline differences: NA 

CommentsNone Quality assFor observ1) Unbias

cohort?

2) Selectio

differenfactors
B-104

Study Study Information Participants Risk Factor and 

Outcome Assessment 

Results Comments

Number of participants enrolled:5554 in cohort, 3777 (68%) agreed to participate. Duration of follow up:4.3 yrs (SD 1.4) Time from risk factor assessment to final cognitive assessment:4.3 yrs (SD 1.4) 

NR Baseline cognitive status:Non-demented Inclusion criteria: Living at home in Southwestern France, age 65 yrs or older, Exclusion criteria:

NR 

cohabitant (n=2106) 2) Never married (179)3) Widowed (n=1287) 4) Divorced or separated (n=103) 215 initially married who became widowed during the f/u period were considered married until the death of their spouses, and then considered widowed. Covariates/potential confounders adjusted for in analyses:Number of people in the social network. Satisfaction with work, living alone, number of leisure activities. Baseline CED-D score. Education and wine consumption. Stratified for sex. Cox model with delayed entry taking age at the time scale. Method(s) of assessing cognitive status:Home interviews. First, patients with suspected dementia were diagnosed using DSM IIIR criteria. Then seen by a senior neurologist who 

3) Outcome of interest #1--AD

190 incident cases of dementia, 140 of which were AD and 50 “other.” 4) Outcome of interest #2—Association between marital status and ADA) Reference: Married (n=44) 

B) Widowed (n=74): RR 0.82 

(95%CI: 0.46-1.44), p=0.487 C) Never married (n=18): RR 2.31 (95% CI: 1.14-4.68), p0.02 D) Divorced (n=4); RR 0.93 (95% CI: 

0.26-3.31), p=0.917 5) Outcome of interest #3 Authors’ conclusion: “Our results...confirm that never-married individuals have a significantly higher risk of dementia or AD than married ones—a twofold increase for the risk of AD.” 

3) Sample 

differen

4) Adequa

cohort?

5) Validat

ascerta

6) Validat

ascertaYes 

7) Outcom

exposu

8) Adequa9) Comple

Yes 

10) Analys

confou

11) Analyti

Yes 
B-105

Study Study Information Participants Risk Factor and 

Outcome Assessment 

Results Comments

confirmed the diagnoses and applied NINCDS-ADRDA criteria. Informant interview?:No 

Ho, Niti, Yap, et al., 2008 Singapore Longitudinal Ageing Studies 

Geographical location: South East Singapore Setting:Community Study design: Prospective cohort Number of participants enrolled:1352 Duration of follow up:1-2 yrs (mean 1.4 yrs – 0.5SD) Time from risk factor assessment to final cognitive assessment:1-2 years with mean 1.4 years and median 1.5 years. 

Age:Mean (SD):  Group A = 64.6 (6.9)  Group B = 66.2 (6.9) Sex: [n (%)] 

Female: 896 (66%) Male: 456 (34%) Race/ethnicity: [n (%)] Chinese Baseline cognitive status:Normal Defined by MMSE score ≥24 

Inclusion criteria: Chinese older adults without cognitive impairment (MMSE <24) and without cardio-vascular disease and stroke; not mentally, physically, or functionally incapacitated Exclusion criteria:MMSE score<24 No stroke or 

Risk factor/exposure

1:metabolic syndrome (international diabetic federation criteria) Method of assessing risk factor/exposure 1:Direct measurement Risk factor/exposure 2:metabolic syndrome Method of assessing risk factor/exposure 2:Direct measurement waist circumference >90 cm or 80cm Chinese men, women; plus any 2 of following 1. systolic bp>130, diastolic >85. 2. Elevated fasting glucose >5.6mmol/L or on diabetes drug; 3. Elevated triglycerides >1.7mmol/L or on lipid lowering drug; low HDL <0.9mmol/L in men 

1) Follow-up rate: 2611 at baseline; 1674 reinterviewed (64%); selected 1357 cognitively unimpaired- 1352 with complete baseline and followup data 2) Important baseline differences: Subjects lost to followup more likely men and had lower MMSE scores. Of people included- Metabolic syndrome more likely to be older, female, have less than 6 yrs education, have low leisure activities; and low baseline MMSE 3) Outcome of interest #1 MMSE 2 pt decline Metabolic Syndrome more likely to have 2 pt decline MMSE 14 vs 19.9% p<.008 (OR for Metabolic syndrome 1.42 (1.10-1.98) p<0.008)- adjusted for age, gender, education, smoking, alcohol; depression, apoe4 status, level leisure activities, baseline MMSE and length of f/u 4) Outcome of interest #2 MMSE 2 point decline- adjusted for HTN OR 1.01 (0.7-1.45) 

CommentsDescribed study, but pindividuals baseline an64% of popassessmenQuality assFor observ1) Unbias

cohort?

2) Selectio

differenfactors

3) Sample 

differen

4) Adequa

cohort?

5) Validat

ascerta

6) Validat

ascertaPartial 

7) Outcom

exposu

8) Adequa

Yes 

9) Comple

Partial 

10) Analys

confou
B-106

Study Study Information Participants Risk Factor and 

Outcome Assessment 

Results Comments

cardiovascular disease and <1.1mmol/L 

women or lipid lowering agent. Covariates/potential confounders adjusted for in analyses:Age Sex Educational level (> or <6 years) Baseline cognitive status APOE Depression Current alcohol smoking Leisure activities (physical, social or productive) Method(s) of assessing cognitive status: MMSE ≥24

Informant interview?:No 

11) Analyti

Yes. 

Ho, Woo, Sham, et al., 2001

Geographical location: Hong Kong Setting:Community Study design: Prospective cohort 

Age:Range: 70 to 90+ Sex:

Female: 469 (47.5%) Male: 519 (52.5%) Race/ethnicity:NR 

Risk factor/exposure 1:Sociodemographic and health factors Method of assessing risk factor/exposure 1:Self-report 

1) Follow-up rate: 988 of the1200 (83.2%). 996 were alive at f/u. 2) Important baseline differences: NA 3) Outcome of interest #1—Education No formal education vs. formal 

CommentsFew details assessmenvariables inwere not reQuality assFor observ1) Unbias

cohort?
B-107

Study Study Information Participants Risk Factor and 

Outcome Assessment 

Results Comments

Number of participants enrolled:2032 initial cohort. Of these, 1200 selected by stratified random sampling. Duration of follow up:3 years Time from risk factor assessment to final cognitive assessment:3 years 

Baseline cognitive status:Non-demented No cognitive impairment Inclusion criteria: Elderly subjects >30 yrs identified by stratified (by age) disproportional random sampling among Old Age Allowance Scheme, which covers 90% of the Hong Kong elderly population. Exclusion criteria:Cognitive impairment or dementia at baseline

Multiple risk factors assessed, including: 1) Education (no formal education vs. formal education) 2) Exercise (no vs. yes) Minimal details provided. Covariates/potential confounders adjusted for in analyses:Sex only Method(s) of assessing cognitive status:Orientation part of CAPE as screening test. 12 CAPE questions asked. CI defined as scoring < 

7 points on the CAPE. Informant interview?:No 

education: OR 3.2 (95% CI: 1.8, 5.5) 4) Outcome of interest #2—ExerciseNo vs. yes: OR 2.1 (95% CI: 1.3, 3.3) 

2) Selectio

differenfactors

3) Sample 

differen

4) Adequa

cohort?

5) Validat

ascertaTell 

6) Validat

ascertaYes (C

7) Outcom

exposu

8) Adequa9) Comple

Yes 

10) Analys

confou

11) Analyti

Yes 

Holtzman, Rebok, Saczynski, et al., 2004 Epidemiologic 

Geographical location: Baltimore Setting:Community 

Age:Range: > 50 years 

Sex:Both genders participated; statistics NR 

Risk factor/exposure

1:Social network Method of assessing risk factor/exposure 1:

1) Follow-up rate: 40.18 % 881 eligible, 440 lost to follow up,107 had missing data. 2) Important baseline differences: Those who were in the analysis were 

CommentsThe major article is thdata and loQuality assFor observ
B-108

Study Study Information Participants Risk Factor and 

Outcome Assessment 

Results Comments

Catchment Area (ECA) Survey, Baltimore site 

Study design: Prospective cohort Number of participants enrolled: 4238 enrolled in wave 1, however, only 881 met inclusion criteria for age and MMSE cut off. Duration of follow up:12.4 years. Time from risk factor assessment to final cognitive assessment:12.4 years 

Race/ethnicity:White and non-white; statistics NR Baseline cognitive status:MMSE ≥ 28 Inclusion criteria: Age ≥ 50 MMSE ≥ 28 Exclusion criteria:None 

Self-report Risk factor/exposure 2:Emotional support Method of assessing risk factor/exposure 2:Self-report Covariates/potential confounders adjusted for in analyses:Age Race Sex Educational level Baseline MMSE score Δ physical activity Δ dysphoria Lifetime presence of alcohol disorder CVD status at Wave 3 Method(s) of assessing cognitive status: MMSE Informant interview?:No 

younger, had higher MMSE scores, had more education and more likely to be female that those who were excluded. 3) Outcome of interest #1 After controlling for Δ physical 

disability and Δ dysphoria, 

MMSE at baseline, lifetime presence of alcohol disorder and CVD status as of Wave 3, age, , gender, and race and educationsal level, there was a linear effect of the baseline network size on the change in MMSE scores. B= 0.18 SE= .06 β = .14 p <0.01 

Effect size = 0.06 P= 0.006 The variance explained by network size was very small. For example, age explained 3.2 times the variance as social network. 4) Outcome of interest #2 After controlling for Δ physical disability and Δ dysphoria, MMSE at baseline, lifetime presence of alcohol disorder and CVD status as of Wave 3, age, , gender, and race there was a significant independent effect of education on the maintenance of cognitive function . B= 0.21; SE= .05 ; β =21; p<0.0005 

1) Unbias

cohort?

2) Selectio

differenfactors

3) Sample 

differen

4) Adequa

cohort?

5) Validat

ascerta

6) Validat

ascertaYes- thmade t

7) Outcom

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8) Adequa9) Comple10) Analys

confou

11) Analyti

Yes 

Huang, Zandi, Tucker, et 

Geographical location: 4 US communities 

Age:Mean (SD): est 71.8 

Risk factor/exposure

1:fatty fish 

1) Follow-up rate: difficult to tell –required that had both nutrition data and MRI to be in 

CommentsQuestion 1 
B-109

Study Study Information Participants Risk Factor and 

Outcome Assessment 

Results Comments

al., 2005 Cardiovascular Health Study (CHS) 

Forsyth County, NC Washington, County, MD Sacramento, CA Pittsburgh, PA Setting:Community Study design: Prospective cohort Number of participants enrolled:2233 Duration of follow up:Est 9 yr Time from risk factor assessment to final cognitive assessment:9 yr 

Sex: [n (%)] 

Female: 1306 (58.5%)Male: 927 (41.5%) Race/ethnicity:White: 2166 (96.99%) Other: 67 (3.0%)Baseline cognitive status:Non-demented Inclusion criteria: >65 yr in 1989/90 

Drawn from Medicare eligibility lists in 4 communities Had MRI as part of CHS study Exclusion criteria:NR 

Method of assessing risk factor/exposure 1:Self-report Covariates/potential confounders adjusted for in analyses:Age Race Sex Educational level APOE Total energy BMI Study site income Method(s) of assessing cognitive status:NINCDS-ADRDA DSM Informant interview?:No (informant interview only done for those who refused in-person assessment, were deceased or could not come to clinic for inperson interview) 

analyses 2) Important baseline differences: Individuals who ate more lean, fried fish were more likely to be male, less likely to be white, and more likely to be at NC site. Those who ate more fatty fish were more likely to be male 

and more likely to be at NC site. 3) Outcome of interest #1Intake of fried fish not assoc with risk of AD 0.25-2 serv/wk: HR- 0.97 (0.67-1.4) >2 serv/wk: HR-0.95 (0.60-1.52) 

4) Outcome of interest #2 Intake of tuna and other fish not assoc with risk of AD 0.25-2 serv/wk: HR- 0.85 (0.54-1.33) 2-4 serv/wk: HR-0.72(0.44-1.17) >4 serv/wk: HR – 0.69 (0.91-1.22) 

Quality assFor observ1) Unbias

cohort?

2) Selectio

differenfactors

3) Sample 

differen

4) Adequa

cohort?

5) Validat

ascerta

6) Validat

ascertaPartial 

7) Outcom

exposu

8) Adequa9) Comple

Can’t T

10) Analys

confou

11) Analyti

Yes 

Hughes, Andel, Small, et al., 2009 

Geographical location: locations throughout 

Sweden 

Age:Mean (SD): Baseline: 48.33 (5.14) Follow-up: 79.81 (5.09)

Risk factor/exposure 1:fruit and vegetable consumption (1 question) 

1) Follow-up rate: 3779 of 5588 survivors participated (68%). Of these 3318 of 3779 had 

CommentsNone Quality assFor observ
B-110

Study Study Information Participants Risk Factor and 

Outcome Assessment 

Results Comments

Swedish Twin Study – HARMONY study 

Setting:Other –Twin Registry Study design: Prospective cohort Number of participants enrolled:3779 (in models with covariate adjustment N = 3217) Duration of follow up:31.47 yrs (0.91) Time from risk factor assessment to final cognitive assessment:31.47 yrs (0.91) 

Sex: [n (%)] 

Female: 2346 (62.08)Male: 1433 37.92) Race/ethnicity: [n (%)] NR Baseline cognitive status:Non-demented Inclusion criteria: Members of the Swedish Twin Registry born between 1886 and 1925 who completed questionnaire in 1967. Age > 65 years at time of cognitive evaluation for dementia Exclusion criteria:NR 

Method of assessing risk factor/exposure 1:Self-report Covariates/potential confounders adjusted for in analyses:Age Sex Educational level Smoking Alcohol use Exercise BMI Angina Marital status Total food intake Method(s) of assessing cognitive status:NINCDS-ADRDA DSM Informant interview?:No 

covariates collected. 2) Important baseline differences: NR by exposure status 3) Outcome of interest #1Medium or great fruit and vegetable intake in mid-life associated with reduced risk of AD (OR 0.60; 95% CI: 0.41-0.86) 4) Outcome of interest #2 Medium or great fruit and vegetable intake in mid-life associated with reduced risk of AD in women (OR=0.47; CI: 0.31-0.73) but not men. Interaction significant (OR=0.45; CI: 0.21-0.98) 

5) Outcome of interest #3 Significant interaction (OR=0.44; CI: 0.21-0.95) also identified where those with angina and medium/great fruit and vegetable intake had lower risk of AD (OR=0.32; CI: 0.16-0.65). No significant association observed in those without angina. 

1) Unbias

cohort?

2) Selectio

differenfactors

3) Sample 

differen

4) Adequa

cohort?

5) Validat

ascerta

6) Validat

ascertaYes 

7) Outcom

exposu

8) Adequa9) Comple

Partial 

10) Analys

confou

11) Analyti

Yes 

Hughes, Borenstein, Schofield, et al., 2009 KAME 

Geographical location: King County, WA Setting:Community Study design: Prospective cohort 

Age:Mean (SD): 71.8 Sex: [n (%)] 

Female: 55.3 Male: 44.7 Race/ethnicity: [n (%)] 100% Japanese 

Risk factor/exposure 1:BMI Method of assessing risk factor/exposure 1:Direct measurement Covariates/potential 

1) Follow-up rate: 1478/1836 = 80.5% 2) Important baseline differences: Female sex, alcohol, smoking, hypertension, hypercholesterolemia, diabetes mellitus 3) Outcome of interest #1129 incident dementia cases, 71 

CommentsQuestion 1 Quality assFor observ1) Unbias

cohort?

2) Selectio

differenfactors
B-111

Study Study Information Participants Risk Factor and 

Outcome Assessment 

Results Comments

Number of participants enrolled:1478 Duration of follow up:Mean 7.8 years; SD 0.3 Time from risk factor assessment to final cognitive assessment:7 to 9 years 

Baseline cognitive status:Non-demented Inclusion criteria: a population-based prospective study of community- and institution-dwelling Japanese Americans 65 years and older living in King County, WA. Exclusion criteria:

none 

confounders adjusted for in analyses:Age Race Sex Educational level alcohol, smoking, hypertension, hypercholesterolemia, diabetes, angina pectoris, stroke, TIA, physical activity and APOE genotype. Method(s) of assessing cognitive status:CASI ≤86 triggers evaluation NINCDS-ADRDA DSM IV Informant interview?:Yes 

incident AD cases, and 22 incident VaD cases Baseline BMI Model 4 (fully adjusted) HR 0.68 (0.31-1.51) 43/971 cases BMI Change Model 4 (fully adjusted) HR 0.21 (0.06-0.80) 43/971 4) Outcome of interest #2 Higher baseline BMI was significantly associated with a reduced risk of AD (HR= 0.56, (0.33–0.97)) in the fully adjusted model. 5) Outcome of interest #3 Slower rate of decline in BMI was associated with a reduced risk of dementia (HR 0.37, 0.14–0.98), with the association stronger for those who were overweight or obese (HR 0.18, 0.05–0.58) compared to normal or underweight (HR 1.00, 0.18–5.66) at baseline. 

3) Sample 

differen

4) Adequa

cohort?

5) Validat

ascerta

6) Validat

ascertaYes 

7) Outcom

exposu

8) Adequa9) Comple

Yes 

10) Analys

confou

11) Analyti

Yes 

Insel, Palmer, StroupBenham, et al., 2005 Hispanic Established Population for Epidemiolo

Geographical location: Texas, New Mexico, Colorado, Arizona, California Setting:Community Study design: Prospective cohort 

Normotensives (n=1138) Age:Mean (SD): 73.3 (7.2) Sex:

NR Hypertensives (n=1721) Age:

Risk factor/exposure 1:Blood pressure. Method of assessing risk factor/exposure 1:Direct measurement of SBP and DBP. Baseline HTN status 

1) Follow-up rate: 3050 at baseline, with 2579 (84.6%) or 2859 (inconsistent reporting in the paper) with blood pressure readings at baseline and 1460 (56.6%) BP readings at 7 year f/u. 2) Important baseline differences: NA 3) Outcome of interest #1: 

CommentsOutcome is MMSE oveQuality assFor observ1) Unbias

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B-112

Study Study Information Participants Risk Factor and 

Outcome Assessment 

Results Comments

gic Study of the Elderly Number of 

participants enrolled:3050 at baseline. Duration of follow up:7 years Time from risk factor assessment to final cognitive assessment:7 years 

Mean (SD): 72.8 (6.8) Sex:

NR Race/ethnicity:Mexican American population Baseline cognitive status:No exclusion for cognitive status reported. Inclusion criteria: Area probability sampling design of counties with a high proportion of Mexican Americans in 5 US states. Mexican American, >65 yrs 

Exclusion criteria:NR 

defined as both selfreported HTN and SBP > 140. 

SBP and MMSE data analyzed with a latent growth curve model. The beta parameter indicates the constant rate of change per unit of time. Method of assessing risk factor/exposure: Self report for: Education, selfreported diabetes, HTN, anti-HTN medication, physical activity, tobacco use. Covariates/potential confounders adjusted for in analyses:Age BMI Sex Income Educational level Baseline MMSE score Baseline CESD score Physical activity Lifestyle factors Diabetes Stroke Cardiovascular diseaseMethod(s) of assessing cognitive status:

Numerous RF’s (education, diabetes, stroke, depression, BMI, antihypertensives, smoking, physical activity) parameters reported, stratified by normotensive vs. HTN. Analysis: Regression analysis with latent growth curve models by baseline HTN status: unstandardized regression coefficients reported. Beta coefficients and SE reported below. *=p<.05, **=p<.01, ***=p<.001 Normotensives

Education: .03 (.01)* Diabetes: .24 (.14) Depression: -.02 (.00)** BMI: 0 (.01) Anti-HTN 2: .18 (.41) Anti-HTN 3: .01 (.36) Anti-HTN 4: .81 (.34) Smoking: .02 (.11) Physical activity: .004 (.00)*** Hypertensives

Education: .4 (.01)*** Diabetes: -.48 (.01)*** Depression: .01 (.00)** BMI: .03 (.01)*** Anti-HTN 2: -.38 (.19)* Anti-HTN 3: -.04 (.22) Anti-HTN 4: .46 (.30) Smoking: -.01 (.09) Physical activity: 0 (.00) 4) Outcome of interest #2—SBP Authors’ conclusion: “This investigation found that baseline SBP and MMSE did not predict the rate of 

3) Sample 

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B-113

Study Study Information Participants Risk Factor and 

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Results Comments

MMSE assessed 4 times over 7 years. Used as screen for CI. Informant interview?:No 

change of MMSE over 7 years for either normotensive or hypertensive participants.” 5) Outcome of interest #3—DBP “Because DBP did not vary greatly in either group, this was not modeled and was not included in the analysis.” 

In’t Veld, 

Ruitenberg, Hofman, et al., 2001 Rotterdam Study 

Geographical location: Rotterdam, The Netherlands Setting:Community Study design: 

Prospective cohort Number of participants enrolled:6416 Duration of follow up:Mean =2.2 years Time from risk factor assessment to final cognitive assessment:Mean = 2.2 years 

Age:Range: > 55 years at 

baseline Sex:Both genders included Race/ethnicity:NR Baseline cognitive status:Non-demented Inclusion criteria:  Age >=55 y.o  Living in Ommoord suburb of Rotterdam for >= 1 year Exclusion criteria:Dementia 

Risk factor/exposure 1:Anti-hypertensive medication Method of assessing risk factor/exposure 1: Self-report  Direct measurementmedication bottles 21.1% used 1 anti-HTN medication; 8.5% two and 1.7% three or more medications. b-blocker 14.6%; diuretics 15.3%; ACE inhibitor 5.7%; other 1.9% Covariates/potential confounders adjusted for in analyses:Age Sex Educational level Baseline cognitive 

1) Follow-up rate: 5,571/6416 had f/u (87%) 2) Important baseline differences: Anti-HTN medication users were: older and had higher BMI, and more likely to be female, smoke, have DM, PAD or h/o stroke 3) Outcome of interest #1Incident dementia =118 (70 in untreated and 48 in treated groups); of these, AD=82 Any anti-HTN medication; HR for AD = 0.77 (95% CI 0.49-1.24) HR or all dementias = 0.67 (95% CI 0.45 – 1.00) Sensitivity analyses: 1) Excluding untreated subjects w/ SBP < 160 and DBP < 95; any antiHTN use, HR for AD=0.99 (0.47 – 2.12); HR for total dementia 0.67 (0.35 – 1.32) 2) Gender: any anti-HTN use, HR for total dementia, men HR 0.52 (0.22-1.20); women HR 0.93 (0.59-1.46) 

CommentsAbout 5% ohomes for tQuality assFor observ1) Unbias

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Yes 

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B-114

Study Study Information Participants Risk Factor and 

Outcome Assessment 

Results Comments

status DBP and SBP H/O stroke, DM or PADBMI Tobacco use Independent vs home for the elderly Method(s) of assessing cognitive status:NINCDS-ADRDA DSM 2- stage exam ; secondary evaluation triggered by MMSE < 26 or Geriatric Mental State schedule >0. Of those who were not re-examined or who died, cognitive function assessed by close informants and general practitioners. Informant interview?Yes, for those in second stage of dementia screening, CAMDEX included informant interview. Also of those not directly reexamined (dead or not), some had informants. 

Irie, Fitzpatrick, 

Geographical location: 

Age:Mean (SD): 74 at first 

Risk factor/exposure 1:

1) Follow-up rate: Uncertain as 5888 were recruited but 

CommentsThe autho
B-115

Study Study Information Participants Risk Factor and 

Outcome Assessment 

Results Comments

Lopez, et al., 2008 Cardiovascular Health Study (CHS) 

Pittsburgh, PA, Forsyth County, NC, Washington county, MD, Sacramento county, CA Setting:Community Study design: Prospective cohort Number of participants enrolled:2547 Duration of follow up:Up to 10 years Mean 5.4 years Time from risk factor assessment to final cognitive assessment:Diabetes mellitus assessed annually. 

examination 80.1 (exit) Sex: [n (%)] 

Female: 59% Male: 41% Race/ethnicity: [n (%)] 91.3% white 8.7% AA Baseline cognitive status:Non-demented Inclusion criteria: Random selection from Medicare eligibility lists in 4 counties. Nondemented on MMSE Exclusion criteria:Mild cognitive impairment and dementia 

APOE genotype 602 with APOEε4 Method of assessing risk factor/exposure 1:Direct measurement Risk factor/exposure 2:Diabetes mellitus 320 diabetes (12.6%) Method of assessing risk factor/exposure 2:Direct measurement Medication use. Covariates/potential confounders adjusted for in analyses:Model 1: Age Race Educational level Model 2: age, race, education, HTN, total cholesterol, smoking, alcohol, BMI, depression status, ankle-brachial index, stroke. 

Method(s) of assessing cognitive status:NINCDS-ADRDA 3MSE DSS 

only 2547 included in this analysis. Further details not available. 2) Important baseline differences: Those with DM had higher systolic Bp, total cholesterol, BMI, lower ankle-brachial index 3) Outcome of interest #1Compared to those without DM or APOEε4: Model 1 (see covariates) Incident AD DM only 1.45 (0.89-2.37) APOEε4 only 2.61 (1.93-3.54) Both 4.53 (2.47-8.30) Model 2 (see covariates) DM only 1.62 (0.98-2.67) APOEε4 only 2.50 (1.84-3.40) Both 4.99 (2.70-9.20) 

both DM an

to a greateadditive coQuality assFor observ1) Unbias

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Yes 
B-116

Study Study Information Participants Risk Factor and 

Outcome Assessment 

Results Comments

Informant interview?:Yes 

Irie, Masaki, Petrovitch, et al., 2008 HonoluluAsia Aging Study (HAAS) 

Geographical location: Oahu, Hawaii Setting:Community Study design:

Prospective cohort Number of participants enrolled:

2350 Duration of follow up:Approximately 6 years Time from risk factor assessment to final cognitive assessment:NR 

Age:Range: 71 - 90 Sex:

Male: 100% Race/ethnicity: [n (%)] Japanese-American Baseline cognitive status:Non-demented Inclusion criteria:  Born between 1900 and 1919  Living on Oahu, Hawaii  Complete information on depression symptoms and APOE genotypes Exclusion criteria: Dementia Clinical dementia rating score of>=0.5 or Cognitive abilities sreening instrument score of <82  Died before first f/u exam or did not attend f/u examinations 

Risk factor/exposure

1:Current depressive symptoms using 11-item CESD, (range 0-33), score >=9 Method of assessing risk factor/exposure 1:Self-report Covariates/potential confounders adjusted for in analyses: Age  Educational level 

Awareness of 

memory problem and cardiovascular risk factors (Smoking, DM2, BMI, cholesterol level, ABI), Method(s) of assessing cognitive status: 3-stage screening beginning with CASI  NINCDS-ADRDA Informant interview?:Yes 

1) Follow-up rate:

1932/2350=82% 2) Important baseline differences: More baseline stroke and low ABI in depressed or depressed and APOEe4 positives 3) Outcome of interest #1:  CESD 11>=9; HR for AD = 2.9 (95% CI 1.4 to 5.9)  CESD 11>=9; HR for mixed AD =2.8 (95% CI 1.5 to 5.1) 4) Outcome of interest #2  The interaction term for depression and APOE-e4 was significant in the models above.  Neither Depression or APOE-e4, reference  Only APOE-ef, HR for AD = 1.6 (0.8 to 3.1)  Only CESD 11>=9, HR for AD = 2.2 (0.9 to 5.2)  Both APOE and CESD 11 >=9, HR for AD 13.0 (4.3 to 39.5) 

CommentsDo not adjuQuality assFor observ1) Unbias

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Yes 
B-117

Study Study Information Participants Risk Factor and 

Outcome Assessment 

Results Comments

Jonker, Comijs and Smit, 2003 Longitudinal Aging Study Amsterdam (LASA) 

Geographical location: 3 regions in The Netherlands Setting:Community Study design: Prospective cohort Number of participants enrolled:612 Duration of follow up: 3 yrs Time from risk factor assessment to final cognitive assessment:BL 92/93, f/up 95/96 

Age:Mean (SD):  NSAID- 72.6 (6.7)  NSAID+ 73.1 (6.5) Range: 55 - 85 Sex: [n (%)] 

Female: 328 (53.6%) Male: 284 (46.4%) Race/ethnicity: [n (%)] NR Baseline cognitive status:community dwelling, reasonable mmse scores Inclusion criteria: Born in 1930 or before; participated in the second data collection cycle of LASA; completed all cognitive tests at both times Exclusion criteria:This paper doesn’t really say. It implies that weighted (by expected mortality), random samples in three areas were pulled and didn’t eliminate anyone. Institutionalized subjects are not mentioned. 

Risk factor/exposure 1:prescripton nsaids/asa Method of assessing risk factor/exposure 1:Self-report Covariates/potential confounders adjusted for in analyses:Age Sex Educational level Baseline mmse score, vascular disease, dm, RA Method(s) of assessing cognitive status:change in test score.

Informant interview?:No 

1) Follow-up rate: Group chosen retrospectively from those will all information available. Group using nsaids both times and group not using prescription nsaids. 2) Important baseline differences: nsaid users had more vascular disease 3) Outcome of interest #1 information given for immed recall, delayed recall and coding tasks separately. The one that was “almost significant” showed an OR for NSAIDS for immed recall of 0.49 (0.23-1.05) 

CommentsOnly prescMean mmsQuality assFor observ1) Unbias

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B-118

Study Study Information Participants Risk Factor and 

Outcome Assessment 

Results Comments

Kado, Karlalmangla, Huang, et al., 2005 MacArthur studies of successful aging. 

Geographical location:  Durham, North Carolina  East Boston, Massachusetts  New Haven, Connecticut Setting:Community Study design: Prospective cohort Number of participants enrolled:  1189 participated  499 with baseline data and 370 with longitudinal data analyzed Duration of follow up: 7 yrs Time from risk factor assessment to final cognitive assessment:7 yrs 

Age:Range: mean 74 yrs (SD=2.7 yrs) Sex:

Female: 270 (54%) Male: 229 (46%) Race/ethnicity:NR 

Baseline cognitive status:population selected to be in the top third of physical and cognitive functioning for age group Inclusion criteria:  70 – 79 years old  No disability on the Katz seven-item activities of daily living scale  No more than one disability on eight selfreport items regarding physical functioning  Ability to hold a semitandem balance for >

10 seconds  Ability to stand from a seated position five times within 20 seconds  Score of > 6 on the 9-item Short Portable Mental Status 

Risk factor/exposure

1:hcy stored frozen plasma – nonfastingfor ~8yrs Method of assessing risk factor/exposure 1:Direct measurement Risk factor/exposure 2:B6, B12, and folate Method of assessing risk factor/exposure 2:Direct measurement Covariates/potential confounders adjusted for in analyses: in one model adjusted for age, sex, education, baseline physical fxn, smoking, in second model b 6 &12 and folate also added. Method(s) of assessing cognitive status:Change over time in the summary score from the following measures: Language 18 item 

1) Follow-up rate: 370/499 with 79 dead, 29 with proxy interviews, 14 who refused and 7 did not complete testing 2) Important baseline differences: NR 3) Outcome of interest #1 HCY: with first set of covariates risk ratio of 7 yr cognitive decline 1.44 (0.91-2.09) with addition of B6, B12, and folate as covariates, rr for 7 yr cognitive decline with hcy 1.11 (0.65-1.76) 4) Outcome of interest #2 Folate: with first set of covariates risk ratio for 7 yr cognitive decline was 1.71 (1.13–2.37) With addition of B6, B12, and HCY as covariates, risk ratio for 7 yr decline was 1.60 (1.01–2.31) 5) Outcome of interest #3 Vitamin B6: with first set of covariates risk ratio for 7 yr cognitive decline was 1.20 (0.74–1.81) 

With addition of B12, folate, and HCY as covariates risk ratio for 7 yr cognitive decline was 1.02 (0.59–1.62) 6) Outcome of interest #4 Vitamin B12: with first set of covariates risk ratio for 7 yr decline was 1.42 (0.91–2.06) 

CommentsParticipants top 1/3 of pto general pBaseline coby 9 questisubjects hawould may dementia. Exposure msamples threflect bioahomocysteQuality assFor observ1) Unbias

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B-119

Study Study Information Participants Risk Factor and 

Outcome Assessment 

Results Comments

Questionnaire  Ability to remember at least three of six elements on a delayed recall of a short story Exclusion criteria:NR 

Boston Naming test Abstraction: 4 items from the Similarities subtest of the Wechsler’s Adult intelligence scale Spatial ability: Copying image Incidental recall of confrontation naming Delayed recall of a story Informant interview?:No 

With addition of B6, folate and HCY as covariates risk ratio for 7 yr decline was 1.27 (0.82–1.92) 

11) Analyti

Yes 

Kalmijn, Feskens, Launer, et al., 1997a Zutphen Elderly Study 

Geographical location: Zutphen, Netherlands Setting:Community Study design: Cohort Number of participants enrolled:718 Duration of follow up:3 years Time from risk factor assessment to final cognitive assessment:3 years 

Age:Mean (SD): 74.6 (4.2) years Sex: [n (%)] 

Female: 0 (0%) Male: 718 (100%) Race/ethnicity: [n (%)] NR Baseline cognitive status:Can’t tell Inclusion criteria:  Male  Living in Zutphen Exclusion criteria:NR 

Risk factor/exposure 1:Education Method of assessing risk factor/exposure 1:self report Years of formal education: 1) <6 yrs 

2) >6 yrs (reference) Risk factor/exposure 2:ApoE Method of assessing risk factor/exposure 2:Direct measurement Covariates/potential 

1) Follow-up rate: 560/718 (78%) in 1990, than 390/533) in 1993. Complete information in 356 2) Important baseline differences: NA 3) Outcome of interest #1Association between education and cognitive decline in total group, and ApoE carriers vs. noncarriers. 4) Outcome of interest #2--Education Total population:

<6 yrs: OR 2.1 (95% CI: 0.9, 4.9) 

5) Outcome of interest #3—Education and ApoE interaction ApoE non carrier (n=272) 

<6 yrs: OR 3.1 (95% CI: 1.1, 8.8) 

ApoE carrier (n-84) 

CommentsNone Quality assFor observ1) Unbias

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B-120

Study Study Information Participants Risk Factor and 

Outcome Assessment 

Results Comments

confounders adjusted for in analyses:Age h/o cardiovascular disease Method(s) of assessing cognitive status:MMSE in 1990 and 1990. Cognitive decline defined as a drop of 2 or more points. Informant interview?:No 

<6 yrs: OR 0.9 (95% CI: 0.2, 3.8) 9) Comple

Yes 

10) Analys

confou

11) Analyti

Yes 

Kalmijn, Feskens, Launer, et al., 1997b Zutphen Elderly Study 

Geographical location: Zutphen, Netherlands Setting:Community Study design: Prospective cohort Number of participants enrolled:342 Duration of follow up:3 yr Time from risk factor assessment to final cognitive assessment:

Age:NR Sex: [n (%)] Female: 0 (0%) Male: 342 (100%) Race/ethnicity: [n (%)] NR Baseline cognitive status:Non-demented – most were probably nondemented – but some may have been demented Inclusion criteria: Born between 1900 and 1920 

Risk factor/exposure

1:antioxidant and polyunsaturated fats Method of assessing risk factor/exposure 1:Self-report Covariates/potential confounders adjusted for in analyses:Age Educational level Smoking ETOH use Energy intake Baseline cognitive status 

1) Follow-up rate: 342/476 (but don’t know reason for attrition) 2) Important baseline differences: NR 3) Outcome of interest #1No association between cognitive decline and linoleic acid, n-3 fatty acids, beta carotene, vitamins C and E, flavonoids. P for trends across low, medium and high tertile for each nutrient ranged from 09 – 0.9. 

CommentsQuestion 2 Quality assFor observ1) Unbias

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B-121

Study Study Information Participants Risk Factor and 

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Results Comments

3- 8 yrs (nutrition data used from 1985 and 1990 time point, final cognitive outcome 1993) 

Completed 1990 and 1993 MMSE Exclusion criteria:

NR 

Method(s) of assessing cognitive status: Other – > 2 pt decline on MMSE indicated ‘cognitive decline’ Informant interview?:No 

8) Adequa9) Comple

Partial 

10) Analys

confou

11) Analyti

Yes 

Kalmijn, Launer, Lindemans, et al., 1999 Rotterdam Case control subgroup 

Geographical location: suburban Rotterdam, The Netherlands Setting:Community Study design:

Prospective cohort Number of participants enrolled:

 Baseline enrollment: 7983  Sample size for this study: 702 Duration of follow up: mean 2.7 (0.5) yrs. Time from risk factor assessment to final cognitive assessment: serum collected at baseline and stored for 4+ yrs 

Age:Range: > 55 years 

Sex: [n (%)] Female: 424.08 ( 60.5)Male: 277.92 (39.5) Race/ethnicity:NR Baseline cognitive status: case control, kind of. Random subset of cohort who had mmse done plus a group with mmse decline of <1 point per year. Inclusion criteria: Residents of Rotterdam Age 55 and older Exclusion criteria:Non Rotterdam Residents Age 54 and younger 

Risk factor/exposure 1:hcy Method of assessing risk factor/exposure 1:Direct measurement of a nonfasting serum sample, frozen for 4.1 yrs (no decline) or 4.3 yrs (cog decline grp) Covariates/potential confounders adjusted for in analyses:Age, Sex, Educational level, Baseline mmse Method(s) of assessing cognitive statusNINCDS-ADRDA DSM Informant interview?:No 

1) Follow-up rate: groups chosen that had data available. 2) Important baseline differences: more alcohol use in the random sample as opposed to decliners. 3) Outcome of interest #1 for middle third of hcy (12.9-15.7) as opposed to lowest tertile OR 1.14 (0.67 – 1.93), for highest third as compared to lowest third OR 0.91 (0.52 – 1.58) 

CommentsThey had a follow up arapid cogniselected rameeting a dthose who these two ghad stored Quality assFor observ1) Unbias

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B-122

Study Study Information Participants Risk Factor and 

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Results Comments

 9) Comple

10) Analys

confou

11) Analyti

Yes 

Kalmijn, Launer, Ott, et al., 1997 Rotterdam study 

Geographical location: Rotterdam, Netherlands Setting:Community Study design: Prospective cohort Number of participants enrolled:5386 Duration of follow up:2.1 yr (0.8) Time from risk factor assessment to final cognitive assessment: 2.1 yr (0.8) 

Age:Mean (SD): 67.7 (7.8) Sex: [n (%)] 

Female: 3182 (59%) Male: 2204 (41%) Race/ethnicity: [n (%)] NR Baseline cognitive status:Non-demented Inclusion criteria: > 55 yr; resident of 

specific suburb in Rotterdam, had reliable nutritional data, not demented at baseline Exclusion criteria:

Nursing home residents 

Risk factor/exposure

1:Fat intake Method of assessing risk factor/exposure 1:Self-report Covariates/potential confounders adjusted for in analyses:Age Sex Educational level Total energy intake Method(s) of assessing cognitive status:NINCDS-ADRDA DSM Informant interview?:Yes 

1) Follow-up rate: 5386 had all info – not clear f/u rate2) Important baseline differences: NR 3) Outcome of interest #1Used results for all dementia because mixed dementia (AD +vascular) included in these numbersDementia (particularly that with a vascular component) associated with highest tertile of: Total fat: RR 2.4 (1.1-5.2) Saturated fat: RR 1.9 (0.9-4.0) Cholesterol: RR 1.7 (0.9-3.2) 4) Outcome of interest #2 Fish intake > 18.5 g/day associated with decreased risk of dementia (RR=0.4; 0.2-0.9) Linoleic acid – not associated with dementia (RR=0.6; 0.3-1.2) 

CommentsQuestion 1 Quality assFor observ1) Unbias

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ascerta

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11) Analyti

Yes 

Kang, Ascherio and Grodstein, 

Geographical location: 11 US states 

Age:Mean (SD): 74 yr (but only gives 3 quintiles – so this is an estimate) 

Risk factor/exposure 1:Fruit and vegetable 

1) Follow-up rate: 90% completed 2nd cognitive wave of 

cognitive assessment 

CommentsQuestion 2 Some of thare very sm
B-123

Study Study Information Participants Risk Factor and 

Outcome Assessment 

Results Comments

2005 Nurses Health Study 

Setting:Community Study design: Prospective cohort Number of participants enrolled:13,388 Duration of follow up:2 yrs (cognitive) Time from risk factor assessment to final cognitive assessment:Up to ~19 yrs (averaged diet intake from 1984 – first cognitive data (1995-2001) –and then last cognitive interview from 1997-2003 

Sex:

Female: 13,388 (100%) Male 0 (0%) Race/ethnicity: [n (%)] NR Baseline cognitive status:Non-demented – (assume most were non-demented, but not stated in paper) Inclusion criteria: Parent sample: Nurses aged 30-55 in 1976 in 11 US states Current sample:  > 70 yr 

No hx of CVA Responded to most recent mailed questionnaire Exclusion criteria:NR 

Method of assessing risk factor/exposure 1:Self-report Covariates/potential confounders adjusted for in analyses:

age, education, high blood pressure, high cholesterol, diabetes, coronary heart disease, hormone therapy, age at menopause, body mass index, smoking, antidepressant use, nonsteroidal antiinflammatory drug use, alcohol intake, physical activity, total energy intake, mental health and vitality indices of the 36-question short-form health survey (SF-36), and vitamin supplementation Method(s) of assessing cognitive status: TICS, episodic memory and composite test summary score Informant interview?:No 

2) Important baseline differences:Highest fruit and vegetable consumption group (compared to lower groups) were more educated, less likely to take antidepressants, better health habits, greater use of vitamins and HRT, greater physical activity, less smoking 3) Outcome of interest #1On global cognitive score,  --highest quintile of vegetable intake showed less decline than the lowest quintile (mean difference 0.04 (p trend <0.01) -- highest quintile of green leafy veg showed less decline than lowest quintile (mean diff 0.05; p trend <0.001) --Highest quintile of legumes showed less decline than lowest quintile (mean diff 0.03; p trend 0.02) Highest quintile of cruciferous veg showed less decline (mean diff 0.04; 0.003 -0.07, but no sig trend) 4) Outcome of interest #2 On episodic memory highest quintile of cruciferous veg scored better (mean diff 0.05; p trend =0.02) Highest quintile on green leafy vegetables showed less decline (0.06, p trend <0.001) 5) Outcome of interest #3 On TICS highest quintile on green leafy vegetables showed less decline (0.23, p trend 0.003 

significant bsignificant bsample Quality assFor observ1) Unbias

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6) Validat

ascertaYes 

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exposu

8) Adequa9) Comple

Yes 

10) Analys

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11) Analyti

Yes 
B-124

Study Study Information Participants Risk Factor and 

Outcome Assessment 

Results Comments

Kang, Cook, Manson, et al., 2008 Women’s Antioxidant and Folic Acid Cardiovascular Study 

Geographical location: throughout the US Setting:Community Study design: RCT-add on to RCT Test intervention Vitamin E Vitamin C Beta carotene Vitamin B (Folic acid, Vitamin B-6, Vitamin B12) Comparator intervention(s): placebo Number of participants enrolled:2009 Duration of follow up:6 yr (cognitive) Time from risk factor assessment to final cognitive assessment:6.6 y (range 6.3-6.9) 

Age:Mean (SD): 71.3 (4.2) Sex: [n (%)] 

Female: 2009 (100%) Male: 0 (0%) Race/ethnicity: [n (%)] NR Baseline cognitive status:Normal Non-demented MCI CIND AAMI AACD Inclusion criteria: Female health professionals > 40 yr 

with CVD or > 3 

coronary risk factors. Those who completed the run-in-phase okay and had no history of cancer, active liver disease, chronic kidney failure, or use of anticoagulants, and who were willing to fore-go use of other vitamin supplements – were accepted for randomization Exclusion criteria:

Risk factor/exposure

1:Vitamin B (folic acid, B6, B-12) Method of assessing risk factor/exposure 1:Direct measurement Covariates/potential confounders adjusted for in analyses:None Method(s) of assessing cognitive status: Other – Decline on cognitive measures Informant interview?:No 

1) Follow-up rate: 93% randomized completed 1st

cognitive assessment, 94% completed at least one fup, 83% completed at least 3 assessments. Cumulatively, though, just over 50% of those sample completed Wave 4 (this was partially due to a logistic issue) 2) Important baseline differences: No differences 3) Outcome of interest #1B vitamin group did not differ from the placebo group on extent of cognitive decline on any cognitive measure 

CommentsQuestion: QFor RCTs: 1) Baselin2) Valid A

assess

3) Subjec4) Outcom5) Incomp

addres

6) Differen

Yes 

7) Overall 8) Conflic

insignif

9) Random10) Allocat

adequa
B-125

Study Study Information Participants Risk Factor and 

Outcome Assessment 

Results Comments

NR 

Kang, Cook, Manson, et al., 2006 Women’s Health Study 

Geographical location: US locations Setting:Community Study design:

RCT. 10-year study, but this is a cognitive function substudy initiated 5.6 yrs after randomization. Test intervention Vitamin E (600 IU every other day) ASA 100 mg every other day) Comparator intervention(s) placebo Number of participants enrolled:

6377 Duration of follow up:4.0 yrs (range, 2.6-5.7) Time from risk factor assessment to final cognitive assessment:Time from randomization (beginning of 

Age:Mean (SD):  Vit E 66.2 (4.0)  Placebo 66.3 (4.1) Range:  Vit E 66.1 – 89.9  Placebo 60.4 – 87.1 Sex: [n (%)] 

Female: 6377 (100%) Male: 0 (0%) Race/ethnicity: [n (%)] NR Baseline cognitive status:NR Inclusion criteria: ≥ 45 yo; no history of coronary heart disease, cerebrovascular disease, cancer (except non-melanoma skin cancer), or other major chronic illnesses; did not actively use any of the study medications or have any history of adverse effects from the medications Exclusion criteria:NR 

Risk factor/exposure 1:Vitamin E supplementation, 600 IU every other day, as part of RCT. Subjects also took aspirin 100 mg every other day in a factorial design. Method of assessing risk factor/exposure 1:RCT intervention Covariates/potential confounders adjusted for in analyses:NA (RCT) Method(s) of assessing cognitive status: 

5 tests measuring general cognition, verbal memory, and category fluency. Primary, prespecified outcome was a global composite score averaging performances across all 5 cognitive tests using z scores. Informant interview?:

1) Follow-up rate: 5073/7175 (70.7%) of those initially 

enrolled completed all 3 assessments. 5073/6377 (80.0%) of those who completed initial baseline evaluation.2) Important baseline differences: None 3) Outcome of interest #1No between-group scores on the 5 tests at any of the 3 assessments. Also no between-group differences in mean change in cognitive performance. Mean difference in cognitive change global score at final assessment was

0.00 (−0.04 to 0.04)Compared with the placebo group, the vitamin E group did not have a lower risk of substantial cognitive decline from the first through third assessment and had a relative risk (RR) of substantial decline in global score of 0.92 (95% CI, 0.77 to 1.10). For the verbal memory score, the vitamin E group had a borderline significant 15% lower risk of substantial decline compared with the placebo group (RR, 0.85; 95% CI, 0.71 to 1.02).

Comments10-year stufunction suafter randoQuality assFor RCTs: 1) Baselin2) Valid A

assess

3) Subjec4) Outcom5) Incomp

addres

6) Differen

Yes 

7) Overall 8) Conflic

insignif

9) Random10) Allocat

adequa
B-126

Study Study Information Participants Risk Factor and 

Outcome Assessment 

Results Comments

exposure) to initial cognitive assessment was 5.6 yrs (range: 4.4-6.8 yrs). Time from randomization to final cognitive assessment was approximately 9.6 yrs. 

No 

Kang, Cook, Manson, et al., 2009 Women’s antioxidant cardiovascular study (WACS) 

Geographical location: Various US locations Setting:Other – female nurses with history cardiovascular disease Study design: RCT Test intervention : vitamin E 402mg Beta carotene 50mg Vitamin C 500mg Comparator intervention(s): Matching placebo Number of participants enrolled:1586 Duration of follow up:5.4 years Time from risk factor assessment to final cognitive 

Age:Mean (SD): 69 at randomization Sex: [n (%)] 

Female: 1586 (100%) Male: 0 (0%) Race/ethnicity: [n (%)] 94.0% white, 3.3% black, 0.9% Latino American, 0.7% Asian American, 1.1% other/multiple races 

Baseline cognitive status:Non-demented Inclusion criteria: Women, aged 40 and over, at high risk, with a history of coronary artery disease, carotid endarterectomy, peripheral artery surgery, or three or more coronary heart disease risk factors 

Covariates/potential confounders adjusted for in analyses:Age Race Sex Educational level Baseline cognitive status Method(s) of assessing cognitive status:

Other – The primary outcome was a global composite score averaging all test scores (TICS, 10 word list delayed recall, East Boston Memory immediate and delay, category fluency animals) Informant interview?:No 

1) Follow-up rate: Compliance 64-68% across treatment 2) Important baseline differences: none 3) Outcome of interest #1The primary outcome was a global composite score averaging all scores; repeated-measures analyses were used to examine cognitive change over time. Vitamin E supplementation and beta carotene supplementation were not associated with slower rates of cognitive change (mean difference in change for vitamin E versus placebo, -0.01; -0.05 to 0.04; P=0.78; for 

beta carotene, 0.03; -0.02 to 0.07; P=0.28). Although vitamin C supplementation was associated with better performance at the last assessment (mean difference, 0.13; 0.06 to 0.20; P=0.0005), it was not associated with cognitive change over time (mean difference in change, 0.02; -0.03 to 0.07; P_0.39). 

CommentsQuestion 2 Quality assFor RCTs: 1) Baselin2) Valid A

assess

3) Subjec4) Outcom5) Incomp

addres

6) Differen

Yes 

7) Overall 

Yes 

8) Conflic

insignifstateme

9) Random10) Allocat

adequa
B-127

Study Study Information Participants Risk Factor and 

Outcome Assessment 

Results Comments

assessment:8.9 years (7.8-9.6) 

Exclusion criteria:

Subjects were randomized only if they reported good compliance, willingness to continue in the trial, had no history of cancer, active liver disease, or use of coumadin, and expressed continued willingness to forego the use of betacarotene and vitamin A, C, or E supplements. 

Kang and Grodstein, 2008 Nurses’ Health study subgroup 

Geographical location: 11 US sites Setting:Community Study design:

Prospective cohort Number of participants enrolled:

858 Duration of follow up:4 years for cognitive decline analysis Time from risk factor assessment to final cognitive assessment:Mean of 10 years 

Age:Mean (SD): 65 Sex: [n (%)] 

Female: 858 (100%) Male: 0 (0%) Race/ethnicity: [n (%)] NR Baseline cognitive status:No reported exclusion for dementia. Inclusion criteria: Enrolled in Nurses’ Health Study cognitive study; no history of stroke. Data from patients included in the 

Risk factor/exposure

1:Plasma antioxidant levels Method of assessing risk factor/exposure 1:Direct measurement 1) Total carotenoids 2) Five individual carotenoids Covariates/potential confounders adjusted for in analyses:Age Elapsed time Education Clinical variables Smoking 

1) Follow-up rate: 788/858 = (91.8%) 2) Important baseline differences: NA 3) Outcome of interest #1—Cognitive decline “Higher plasma levels of carotenoids or tocopherols were not associated with slower decline in cognition.” See Table 5 for mean differences in rate of CD over 4 years by quartile of plasma carotenoids and tocopherols.

CommentsNone Quality assFor observ1) Unbias

cohort?

2) Selectio

differenfactors

3) Sample 

differen

4) Adequa

cohort?

5) Validat

ascerta

6) Validat

ascertaYes 

7) Outcom

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8) Adequa9) Comple
B-128

Study Study Information Participants Risk Factor and 

Outcome Assessment 

Results Comments

between blood draw and initial cognitive interview. 

cognitive function subcohort. Exclusion criteria:

Those who did not provide blood samples; those who did not have plasma carotenoids and tocopherols measured; those who were cases of heart disease, breast cancer and colon cancers in nested-case control studies 

Medications Alcohol Physical activity Method(s) of assessing cognitive status:Initially, TICS for screening. Then gradually added 5 other cognitive tests to initial screening. 3 main outcomes: 1) global performance on test battery; 2) verbal memory; 3) TICS Informant interview?: No 

Yes 

10) Analys

confou

11) Analyti

Yes 

Karlamangla, MillerMartinez, Aneshensel, et al., 2009 Assets and Health Dynamics Among the Oldest Old (AHEAD) Study 

Geographical location: USA Setting:Community Study design: Prospective cohort Number of participants enrolled:6476 Duration of follow up:9 years Time from risk factor 

Age:Mean (SD): 77.1 Sex: [n (%)] 

Female: 3970 (61.3%)Male: 2506 (38.7%) Race/ethnicity: [n (%)] -Non-Hispanic white 5712 (88.2%) -Non-Hispanic black 492 (7.6%) -Mexican Hispanic 110(1.7%) -Other Hispanic 91 (1.4%) -Other 71 (1.1%) 

Risk factor/exposure 1:Demographic information (Age, sex, marital status, race/ethnicity) Method of assessing risk factor/exposure 1:Self reported Risk factor/exposure 2: Socio Economic Status (SES) as measured by highest year of school/college completed, household 

1) Follow-up rate: 2353/6476=36.3% at all visits; 81% had at least 1 follow-up 2) Important baseline differences: Did not report comparisons by exposure level 3) Outcome of interest #1Mean decline with aging in total cognition score (range,0-35, SD, 6.00)= =4.1( 0.68 SD) per decade(95%CI,3.8,4.4) Older cohorts, women, widows/widowers, and those never married declined faster and nonHispanic blacks and those in the 

CommentsNone Quality assFor observ1) Unbias

cohort?

2) Selectio

differenfactors

3) Sample 

differen

4) Adequa

cohort?

5) Validat

ascerta

6) Validat

ascerta
B-129

Study Study Information Participants Risk Factor and 

Outcome Assessment 

Results Comments

assessment to final cognitive assessment:9 years 

Baseline cognitive status:Non-demented (some possibly demented) Inclusion criteria: Participants in the AHEAD study born before 1924 Exclusion criteria:

-Institutionalized persons -Proxy cognition testing- Missing more than one cognition subscale

wealth, and annual household income. Method of assessing risk factor/exposure 2:Self-reported Covariates/potential confounders adjusted for in analyses:-Baseline low performance -Length of participation-Imputed scores Age Gender Ethnicity Marital status, Change in marital status Survivorship Method(s) of assessing cognitive status: -an abbreviated version of the Telephone Interview for Cognitive Status for participants aged 79 years or younger and in-person interviews for participants older than 79 years Informant interview?:No 

bottom income quartile declined slower. 4) Outcome of interest #2 Mean decline in total cognition score with race, income and educational level (SES, socioeconomic status) Large SES differences in baseline scores did not translate to differences in rates of cognitive decline 

Yes 

7) Outcom

exposu

8) Adequa9) Comple10) Analys

confou

11) Analyti

Yes. 
B-130

Study Study Information Participants Risk Factor and 

Outcome Assessment 

Results Comments

Khachaturian, Zandi, Lyketsos, et al., 2006 Cache Co. 

Geographical location: Cache County, Utah Setting:Community Study design:

Prospective cohort Number of participants enrolled:

 5092 at baseline;  3297 participating in this substudy Duration of follow up: 3 yrs Time from risk factor assessment to final cognitive assessment:pill bottle checked and cog eval both waves 

Age:Range: > 65 years 

Sex:Female: 59% Male: 41% Race/ethnicity:NR Baseline cognitive status:Non-demented Inclusion criteria: Participating in the Cache County Study Exclusion criteria:NR 

Risk factor/exposure

1:antihypertensives Method of assessing risk factor/exposure 1:inspection of pill bottles for “current” use. Covariates/potential confounders adjusted for in analyses:Age, Race, Sex, number of apo E4s, hx of cva, hyperlpidemia, dm, mi, Educational level Method(s) of assessing cognitive status:NINCDS-ADRDA Informant interview?:not for everybody but IQCODE if unable to participate in screening and DQ if 3ms positive 

1) Follow-up rate: 5092 baseline, 355 demented, 627 died, 802 refused to complete study,2) Important baseline differences: antihtn users older, less educ, fewer women, more strokes, more hyperlipidemia, more dm. more mi, more apoE4 than non antihypertensives3) Outcome of interest #1 antihypertensive use and incident AD HR 0.64 (0.41-0.98) 

CommentsQuestion 1 Quality assFor observ1) Unbias

cohort?

2) Selectio

differenfactors

3) Sample 

differen

4) Adequa

cohort?

5) Validat

ascerta

6) Validat

ascertaYes 

7) Outcom

exposu

8) Adequa9) Comple

Yes 

10) Analys

confou

11) Analyti

Yes 

Kivipelto, Ngandu, Fratiglioni, et al., 2005 AND 

Geographical location: Kuopio & Joensuu, Finland Setting:Community 

Age:Mean (SD): Baseline: 50.6 (6.0) Follow-up: 71.6 (4.1) Sex: [n (%)] 

Female: 900 (62%) Male: 549 (38%) 

Risk factor/exposure

1:htn, BMI Method of assessing risk factor/exposure 1:

1) Follow-up rate: 1449/2000 invited participated (72.5%); f/u rate from original cohort cannot be determined 2) Important baseline differences: 

CommentsNone Quality assFor observ1) Unbias

cohort?
B-131

Study Study Information Participants Risk Factor and 

Outcome Assessment 

Results Comments

Kivipelto, Helkala, Laakso, et al., 2001 CAIDE & North Karelia Project 

Study design: Prospective cohort Number of participants enrolled:1449 Duration of follow up: 21 yrs (4.9) from baseline interview until cog assessment Time from risk factor assessment to final cognitive assessment:21 yrs, range 11-26 yrs 

Race/ethnicity: [n (%)] NR Baseline cognitive status:unclear, but baseline measures were done in mid life when cog impairment would be unlikely Inclusion criteria: Survivors of 4 separate samples of the North Karelia Project and FINMONICA study; lived in two geographically defined areas; permission for BP and blood specimens to be taken Exclusion criteria:NR 

Direct measurement Normal sbp < 140, borderline 140-159, high >159, normal dbp < 90, borderline 91-94. High > 94 Direct measurement; BMI calculated based on weight/height; Categorized as >30; 25-30 and <25 Risk factor/exposure 2:cholesterol; high = >=6.5 mmol/l Method of assessing risk factor/exposure 2:Direct measurement Covariates/potential confounders adjusted for in analyses:Age, sex, education, and follow-up interval, Some analysis adjusted for APOE, hx MI, hx DM, hx stroke, midlife SBP and DBP, cholesterol, smoking, and ETOH use Method(s) of assessing cognitive status:

NINCDS-ADRDA

DSM 

At baseline, higher BMI associated with increased age, shorter follow-up interval, higher SBP and DBP,and lower education 3) Outcome of interest #1. Risk of AD 57 incident dementia (48 AD)  Midlife borderline sbp OR 2.1 (0.8-5.0), high sbp 2.8 (1.1 – 7.2) 4) Outcome of interest #2 Midlife borderline dbp 1.4 (0.6 – 3.5) high dbp 1.7 (0.8 – 3.6) 5) Outcome of interest #3 midlife cholesterol > 6.5 mml/l OR 2.2 (1.0- 4.7) Both high BP (>159) and high cholesterol (>=6.5 mml/l) compared to one risk factor; OR=3.5 (1.6 to 7.9)6) Outcome of interest #4: Obesity and incidence of AD BMI > 30: OR adjusted for covariates listed + APOE = 1.88 (95% CI 0.76  to 4.63) BMI 25-30 not associated with incident AD, OR=0.99 (0.47 to 2.15) 7) Outcome of Interest #5: Number of midlifed vascular risk factors (BMI>30, BP >140, T Chol >252) adjusted for age, sex, education and follow-up time: OR for 1 risk factor = 1.37 (0.44 to 4.27); 2 risk factors OR=3.03 (1.03 to 8.89); 3 risk factors OR=6.21 (1.94 to 19.92) 

2) Selectio

differenfactors

3) Sample 

differen

4) Adequa

cohort?

5) Validat

ascerta

6) Validat

ascertaPartial 

7) Outcom

exposu

8) Adequa9) Comple

Yes 

10) Analys

confou

11) Analyti

Yes 
B-132

Study Study Information Participants Risk Factor and 

Outcome Assessment 

Results Comments

Informant interview?:No 

Knopman, Boland, Mosley, et al., 2001 ARIC 

Geographical location: Forsyth County, NC Jackson, MS Suburban Minneapolis, MN Washington County, MD Setting:Community Study design: Prospective cohort Number of participants enrolled: 10,963 Duration of follow up: mean 6 years (0.3). Time from risk factor assessment to final cognitive assessment:6 years 

Age:Range: 47-70 Sex:

NR Race/ethnicity: 8729 white (79.6%)  2234 black (20.4%) Baseline cognitive status:Population formed 45-64 years of age, no cog requirements. Inclusion criteria: Enrolled in ARIC StudyExclusion criteria:History of stroke or TIA

Risk factor/exposure

1:nsaids Method of assessing risk factor/exposure 1:self report, pill bottles Covariates/potential confounders adjusted for in analyses:Age Race Sex Educational level Site, cns-relevant meds (antipsychotics, antidepressants, anxioulytics, opiates, anticonvulsants, antineoplastic agents). Method(s) of assessing cognitive status:Change in individual thests Informant interview?:no 

1) Follow-up rate: 76% at six years 2) Important baseline differences: not well recorded This paper covers multiple risk factors 3) Outcome of interest #1 nsaid use not associated with declines on any test. 

CommentsASA includChange in change in tQuality assFor observ1) Unbias

cohort?

2) Selectio

differenfactors

3) Sample 

differen

4) Adequa

cohort?

5) Validat

ascerta

6) Validat

ascertaYes 

7) Outcom

exposu

8) Adequa9) Comple10) Analys

confou

11) Analyti

Yes 

Knopman, Mosley, 

Geographical location: 

Age:Mean (SD): 59 (4.3) 

Risk factor/exposure 1:

1) Follow-up rate: 15,792 at visit 1. 12,887 in visit 3; of 

CommentsQuestion 2 
B-133

Study Study Information Participants Risk Factor and 

Outcome Assessment 

Results Comments

Catellier, et al., 2009 ARIC study subset 

4 US communites: Forsyth county, NC; Jackson, MS; Minneapolis, MN; & Washington county, MD Setting:Community Study design:

Prospective cohort Number of participants enrolled:

1130 Duration of follow up:Median of 14 years Time from risk factor assessment to final cognitive assessment:14 years 

Sex: [n (%)] 

Female: 701 (62%) Male: 429 (38%) Race/ethnicity: [n (%)] African/Amer: 588 (52%) Other: 542 (48%) Baseline cognitive status:Normal Inclusion criteria: Subset of the ARIC cohort who participated in two brain MRI studies between 1993-1995 and 2004-2006. Exclusion criteria:Prior surgery for an aneurysm in the brain; metal fragments in the eyes, brain, or spinal cord; valvular prosthesis; cardiac pacemaker; cochlear implant; spinal-cord stimulator, or other internal electrical device; pregnancy; occupations associated with exposure to metal fragments 

APOE genotype Method of assessing risk factor/exposure 1:TaqMan assay Risk factor/exposure 2:Vascular risk factors at baseline Method of assessing risk factor/exposure 2:Diabetes: Fasting glucose >126 mg/dl or nonfasting glucose >200 dl or self-reported h/o diabetes or treatment for diabetes in previous 2 weeks. HTN: SBP >140 mm HG or DBP >90 or any use of antihypertensive medication in previous 2 weeks. Education: self report (<12 yrs), 12-16 yrs, >17 yrs) 

Covariates/potential confounders adjusted for in analyses:Age Race Sex Educational level 

these, 2891 participants aged 55 and older invited for MR imaging. 1945 completed an MR, with 1920 usable scans. 1130 completed visit 4, for a rate of 1130/1920 = 59%. 2) Important baseline differences: N/A 3) Outcome of interest #1Difference in average baseline cognitive test scores (P value): APOE genotype 

DSS: 1.06 (0.03) DWR: 0.17 (0.49) WF: 0.59 (0.405) 4) Outcome of interest #2 Difference in average baseline cognitive test scores (P value): DiabetesDSS: 0.25 (0.803) DWR: -0.19 (0.173) WF: 0.60 (0.597) 5) Outcome of interest #3 Difference in average baseline cognitive test scores (P value): HTN 

DSS: 1.55 (0.016) DWR: 0.15 (0.089) WF: -0.123 (0.088) 6) Outcome of interest #4 Difference in average baseline cognitive test scores (P value): Education level

DSS: 6.87 (<0.001) DWR: 0.33 (<0.001) WF: 7.71 (<0.001) 

Quality assFor observ1) Unbias

cohort?MRI su

2) Selectio

differenfactors

3) Sample 

differen

4) Adequa

cohort?

5) Validat

ascerta

6) Validat

ascertaYes 

7) Outcom

exposu

8) Adequa9) Comple

Yes 

10) Analys

confou

11) Analyti

Yes 
B-134

Study Study Information Participants Risk Factor and 

Outcome Assessment 

Results Comments

Vascular factors Time Risk factor x time interaction Method(s) of assessing cognitive status:Digit Symbol Substitution (DSS); Delayed Word Recall (DWR); Word Fluency (WF) Informant interview?:No 

Koster, Penninx, Bosma, et al., 2005 Health, Aging and Body Composition study (Health ABC) 

Geographical location: Pittsburg, PA Memphis, TN Setting:Community Study designProspective cohort Number of participants enrolled:2574 enrolled subjects out of longitudinal cohort of 3075. Duration of follow up:4 yrs Time from risk factor 

Age:Range: 70-79 yrs old Sex:

both included but numbers NR Race/ethnicity:Black and white but actual numbers NR Baseline cognitive status:Non-demented Inclusion criteria: Well-functioning: no difficulty walking onequarter mile or going up 10 steps without resting. 

Risk factor/exposure

1:Education Categories: <12 yrs education 12 yrs education >12 yrs education Method of assessing risk factor/exposure 1:Self-report Covariates/potential confounders adjusted for in analyses:Age Race Sex 

1) Follow-up rate:  2088 followed up yr 4(81.1%)  486 lost to follow up (18.9%) 2) Outcome of interest #1 Cognitive decline was defined as a decrease of 5 or more points on the 3MS between baseline and 4th yr 

follow up. Adjusted odds ratio were significantly higher in those with low education: >12 yrs education: OR 1.00  12 yrs education: OR 1.42 (1.10- 1.83)  <12 yrs education: OR 2.16 (1.59-2.94 All CI 95% Two models were used for OR assessment based on slightly 

CommentsNone Quality assFor observ1) Unbias

cohort?

2) Selectio

differenfactors

3) Sample 

differen

4) Adequa

cohort?

5) Validat

ascerta

6) Validat

ascertaYes 

7) Outcom

exposu
B-135

Study Study Information Participants Risk Factor and 

Outcome Assessment 

Results Comments

assessment to final cognitive assessment:4 yrs 

Exclusion criteria:

-Active treatment for cancer most recent 3 yrs -Planned move out of study area in next 3yrs -Current participation in randomized trial of lifestyle intervention 

Educational level Baseline cognitive status Study site House hold income Biomedical factors Method(s) of assessing cognitive status: Other – Modified MiniMental State Examination(3MS) Informant interview?:No 

different covariates. Results were very similar. 

8) Adequa9) Comple10) Analys

confou

11) Analyti

Yes 

KritzSilverstein, von Muhlen, Laughlin, et al., 2008 DAWN Trial 

Geographical location: San Diego, CA Setting:Clinical Research Facility Study design: RCT Test intervention: 50 mg oral DHEA daily Comparator intervention(s): placebo Number of participants enrolled:225 Duration of follow up:

Age:Mean (SD): 68 yr (8) Median: Range: 55-85 yrs Sex: [n (%)] 

Female: 115 (51%) Male: 110 (49%) Race/ethnicity: [n (%)] NR Baseline cognitive statusNormal Inclusion criteria: Aged 55-85; nonsmokers; not currently using any hormone therapy Exclusion criteria:

Risk factor/exposure 1: DHEA (dehydro Epiandrosterone) Method of assessing risk factor/exposure 1: RCT Risk factor/exposure 2: RCT Method of assessing risk factor/exposure 2: RCT Covariates/potential confounders adjusted for in analyses RCT Method(s) of assessing cognitive status:

Other – modified 

1) Follow-up rate: compliance with treatment 95% treatment, 94% placebo; 23 DHEA treatment stopped adverse events; 10 placebo stopped. Followup rate for treatment group 79.5%; placebo 91.2%. Follow up rate not reported by sex. 2) Important baseline differences: Possibly relevant- DHEA levels in treated woman higher at baseline than placebo (p<0.003); testosterone higher in treated woman than placebo (p<.01) 3) Outcome of interest #1 Outcome comparisons made using Wilcoxon tests. No differences in treatment and placebo groups in any cognitive measure in either sex. Modified MMSE- no difference dhea 

CommentsNone Quality ass

For RCTs: 1) Baselin2) Valid A

assess

3) Subjec4) Outcom5) Incomp

addres

6) Differen

No. DHplacebo 

7) Overall 

Yes 

8) Conflic

insignif

9) Random10) Allocat

adequa
B-136

Study Study Information Participants Risk Factor and 

Outcome Assessment 

Results Comments

1 yr Time from risk factor assessment to final cognitive assessment:12 mos 

NR MMSE; word list; word 

list recall; verbal fluency; boston naming; trails b Informant interview?:

No 

treated and placebo 4) Outcome of interest #2 Word List- no difference dhea treated and placebo 5) Outcome of interest #3, 4, 5, 6 Word List Recall- no difference dhea treated and placebo Verbal Fluency- no difference dhea treated and placebo Boston Naming- no difference dhea treated and placebo Trails B- no difference dhea treated and placebo 

Kroger, Verreault, Carmichael, et al., 2009 Candadian Study of Health and Aging 

Geographical location: 36 Canadian provinces Setting:Community Other 0 institutionalized individuals Study design: Nested case-control Number of participants enrolled:For 8361 nondemented, 1219 provided blood samples, 663 analytical sample Duration of follow up:Median of 4.9 years (IQ range 4.5-5.2) 

Age:Mean (SD):  80 (6.0) normals;  82.5 (6.6) dementia Sex: [n (%)] 

Female: 401 (61%) Male: 262 (39%) Race/ethnicity: [n (%)] NR Baseline cognitive status:Non-demented Inclusion criteria: Age ≥ 65 yo 

Living in community or in institutions in 1991 Provided blood sampleSelected for full neuropsychiatric examination 

Risk factor/exposure 1:Total n-3 PUFAS and erythrocyte membrane omega-3 PUFAs at baseline analyzed by quartiles, above below median and as continuous variables. Method of assessing risk factor/exposure 1:Direct measurement Risk factor/exposure 2:Blood mercury levels Method of assessing risk factor/exposure 2:Direct measurement 

1) Follow-up rate: 1219 with blood samples; 450 died, 68 lost to follow-up, 31 had blood samples that were missing or could not be analyzed; 663/1219 = 54%2) Important baseline differences: NR by exposure category; this subsample had slightly less education than overall cohort 3) Outcome of interest #1 149 incident cases of dementia (105 AD) HR (95% CI) for quartiles of total n-3 PUFAs and AD Quartile 1: ref Quartile 2: 1.36 (0.79-2.35) 

Quartile 3: 0.97 (0.55-1.71) Quartile 4: 1.12 (0.63-1.98) No association for all cause dementia 

CommentsQuestion 1 This is an u2003; sampQuality assFor observ1) Unbias

cohort? 

2) Selectio

differenYes 

3) Sample 

differen

4) Adequa

cohort? 

5) Validat

ascerta

6) Validat

ascertaYes 

7) Outcom

exposu

8) Adequa
B-137

Study Study Information Participants Risk Factor and 

Outcome Assessment 

Results Comments

Time from risk factor assessment to final cognitive assessment:Median 4.9 years; max 10 years 

Exclusion criteria:

Dementia No viable blood sampleDid not complete ≥ 1 follow-up 

Covariates/potential confounders adjusted for in analyses:Age Sex Educational level APOE e4, BMI, ever smoking, ETOH, diabetes mellitus, HTN, CVD, h/o stroke or MI, depression, family h/o dementia Method(s) of assessing cognitive status:2-stage screening with neuropsychological evaluation for those with abnormal 3MS and random sample of normals. NINCDS-ADRDA: AD DSM-Dementia Informant interview?:Yes 

4) Outcome of interest #2 HR (95% CI) for quartiles of docosahexanoic acid and AD Quartile 1: ref Quartile 2: 0.81 (0.47-1.38) Quartile 3: 0.77 (0.44-1.35) Quartile 4: 0.81 (0.47-1.40) No association for all cause dementia 5) Outcome of interest #3 HR (95% CI) for quartiles of eicosapentaenoic acid and AD Quartile 1: ref Quartile 2: 1.16 (0.68-1.98) Quartile 3: 0.98 (0.56-1.71) Quartile 4: 0.89 (0.49-1.59) No association for all cause dementia 5) Outcome of interest #4 HR (95% CI) for quartiles of blood mercury and AD Quartile 1: ref Quartile 2: 0.76 (0.46-1.26) Quartile 3: 0.41 (0.23-0.74) Quartile 4: 0.56 (0.32-0.99) Higher mercury concentration also associated with lower risk for all cause dementia 

Partial, effects 

9) Comple

Partial 

10) Analys

confou

11) Analytic 

Yes 

Kuo, Jones, Milberg, et al., 2005 

Geographical location: Six field sites in US Setting:

Age:Mean (SD): 73.6+/-5.9 Range: 65-94 yrs old Sex

Risk factor/exposure 1:Blood pressure Method of assessing 

1) Follow-up rate: NR 2) Important baseline differences: NA 

Comments

Patients with excluded

Participant 
B-138

Study Study Information Participants Risk Factor and 

Outcome Assessment 

Results Comments

Advanced Cognitive Training For Independent and Vital Elderly(ACTIVE) 

Community Study design: Observational analysis (cohort) from a RCT Comparator intervention(s) All participants were randomized into three cognitive intervention groups (memory training, reasoning training or speed or processing training) and a no-contact control group. Number of participants enrolled:2802 Duration of follow up:Annually for 2 yrs Time from risk factor assessment to final cognitive assessment:2 yrs 

Female: 2126(75.9%) Male: 676(24.1%) Race/ethnicity:White: 2017(72.0%) African American: 724 (25.8%) Hispanic: 15(0.5%) Other: 46(1.7%) Baseline cognitive status:Non-demented Inclusion criteria: 65 yrs and older, nondemented Exclusion criteria:<65yrs,< 23 on MMSE, known diagnosis of AD, functionally impaired, medically unstable, recent or current participation in other cognitive training, visual, hearing or communicative impairment 

risk factor/exposure 1:Direct measurement: obtained from a trained research assistant Risk factor/exposure 2:Diabetes Mellitus: Method of assessing risk factor/exposure 2:Self-report: obtained by asking direct question to subjects Covariates/potential confounders adjusted for in analyses:Age Race Sex Educational level Baseline cognitive status Study site Intervention group Cardiovascular risk factors Tobacco use BMI Method(s) of assessing cognitive status:Other – MMSE: measured global cognitive function; 

Reasoning domain 

3) Outcome of interest #1—10 mm increase in SBPBeta coefficient (SE), p value MMSE: -0.021 (0.016), p=.19 Memory composite: -0.020 (0.019), p=.30 Reasoning composite: -0.049 (0.019), p=.008 Speed of processing  Digit Symbol Substitution test: -0.020 (0.082), p=.80  Useful Field of View: 3.049 (2.170), p=.16 4) Outcome of interest #2--Diabetes Beta coefficient (SE), p value MMSE: -.0.305 (0.108), p=.005 Memory composite: -.303 (0.130), p=.02 Reasoning composite: -0.108 (0.126), p=.39 Speed of processing  Digit Symbol Substitution test  -2.371 (0.559), p<.001  Useful Field of View: 60.936 (14.647), p<.001 

training Quality assFor observ1) Unbias

cohort? 

2) Selectio

differenYes 

3) Sample 

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5) Validat

ascertaDM basreport 

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7) Outcom

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8) Adequa9) Comple10) Confou11) Analytic 

Yes 
B-139

Study Study Information Participants Risk Factor and 

Outcome Assessment 

Results Comments

used word series, letter series and letter sets. A higher reasoning composite score indicates better performance. Speed of processing assessed using Useful Field of View(UFOV) Informant interview?:No 
B-140

Study Study Information Participants Risk Factor and 

Outcome Assessment 

Results Comments

Laitinen, Ngandu, Rovio, et al., 2006 CAIDE Study 

Geographical location: North Karelia and Kuopio provinces, Finland Setting:Community Study design: Prospective cohort Number of participants enrolled:2000, but 1,449 participated in followup. Included all in analyses Duration of follow up:21 (4.9) yrs (for the 1,449) Time from risk factor assessment to final cognitive assessment:21(4.9) yrs 

Age:(for 1,449) Mean (SD): midlife exam: 50.4 (6.0) yr fup exam: 71.3 (4.0) Sex: [n (%)] 

Female: 900 (62.1%) Male: 549 (37.9%) Race: [n (%)] NR Baseline cognitive status: 

Non-demented Inclusion criteria: Participated in one of two other populationbased studies. Alive, e, aged 65 to 79 at the end of 1997 and living in one of two geographically defined areas in or close to thetowns of Kuopio and Joensuu in Finland.Exclusion criteria:NR 

Risk factor/exposure

1:Fat intake Method of assessing risk factor/exposure 1:Self-report Covariates/potential confounders adjusted for in analyses:Age (midlife) Sex Educational level FUP time Milk fat and other types of fats from spreads Midlife vascular risk factors APOE History of vascular disorders collected at f/u Method(s) of assessing cognitive status:NINCDS-ADRDA DSM Other: ~551 nonparticipants at FUP, dx from medical records, assume still tried to apply above criteria Informant interview?:No (neither this article 

1) Follow-up rate: not relevant because the included non-participants in analyses – 2000 selected from baseline study to be followed ~21 yr later 2) Important baseline differences: At baseline, individuals who became demented older, less educated, had higher BMI, higher, SBP, higher cholesterol than non-demented 3) Outcome of interest #1Total fat: 2nd, 3rd and 4th quartiles of total fat intake was not associated with increased risk of AD (compared to 1st quartile) PUFA: 3rd quartile of PUFA 

associated with lower risk of AD (OR0.36; 0.16-0.82) MUFA: 2nd, 3rd and 4th quartiles of 

MUFA was not associated with increased risk of AD (compared to 1st

quartile) SFA: 2nd quartile of SFA was not 

associated with increased risk of AD(compared to 1st quartile) 

CommentsQuestion: QResults secwere very swere limiteparticipated Quality assFor observ1) Unbias

cohort? 

2) Selectio

differenYes 

3) Sample 

differen

4) Adequa

cohort? non-pa

5) Validat

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6) Validat

ascertaNo 

7) Outcom

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8) Adequa9) Comple

Partial. non-pa

10) Analys

confouhow lawere departicip

11) Analytic 

Yes 
B-141

Study Study Information Participants Risk Factor and 

Outcome Assessment 

Results Comments

nor the methods paper mentions an informant interview) 

Larson, Wang, Bowen, et al., 2006 ACTS (Adult Changes in Thought Study) 

Geographical location: Seattle, WA Setting:Clinical—Group Health Cooperative HMO Study design: Prospective cohort Number of participants enrolled:5422 eligible, 2581 participated (2841 declined) in ACT study. 1740 in final sample, from 1895 persons in the ACT study whose CASI scores were above the 25th

percentile. 155 withdrew after the baseline visit. Duration of follow up:6.2 yrs (SD, 2.0) Time from risk factor assessment to final cognitive assessment:6.2 yrs (SD, 2.0) 

Age:

Mean (SD): Free of dementia: 73.2 

(5.1). With dementia: 78.2 

(5.5) Sex:Female: Free of dementia: 731 

(61.9%) With dementia: 93 

(58.9%) Male: Free of dementia: 454 

(38.1%) With dementia: 65 

(41.1%) Race/ethnicity: Free of dementia: 

White: 1109 (93.7%) 

Black: 20 (1.7%) 

Other: 55 (4.6%) 

Baseline cognitive status:Normal Non-demented Inclusion criteria:  Age > 65 when study 

began in 1994-1996.  Member of Group Health Coop HMO. 

Risk factor/exposure 1:Physical exercise. Method of assessing risk factor/exposure 1:Self-report: # of days per week they did each of list of activities for at least 15 minutes at a time during the past year. Scale dichotomized “exercised regularly” defined as self-report of exercise >3 

times/wk, vs. “did not exercise regularly.” Covariates/potential confounders adjusted for in analyses:Age Ethnicity Sex Educational level Baseline cognitive function Physical function Depression Health conditions Lifestyle characteristicsSupplements 

1) Follow-up rate: 1740/1895 (92%). 155 withdrew after baseline visit.  Random sample of 6782 members of GHC  Excluded: dementia, nursing home, or participating in other studies (1360).  Of 5422 eligible, 2581 participated and 2841 declined (no difference in age, sex, or ethnicity, but older, women, and minority more likely to decline).  Excluded lowest quartile of CASI scores (n=686). 2) Important baseline differences: NA 3) Outcome of interest #1158 incident cases of dementia (107 of which were AD and 33 were vascular dementia and 18 were other). Incidence rate 13.0/1000 person-yrs for dementia. 4) Outcome of interest #2--Dementia Incidence rate 13.0/1000 person-yrs for persons who exercised >3 

times/wk vs. 19.7/1000 person-yrs for persons who exercised <3 times/wk. Age- and sex-adjusted HR was 0.62 

CommentsNone Quality assFor observ1) Unbias

cohort? 

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differenYes 

3) Sample 

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Yes 
B-142

Study Study Information Participants Risk Factor and 

Outcome Assessment 

Results Comments

 Participants in ACT study with CASI scores above the 25th

percentile. Exclusion criteria: Existing diagnosis of dementia  current residents of a nursing home  participation in other studies. 

APOE Method(s) of assessing cognitive status: Screened with CASI.  Screen positives (CASI < 86) had additional medical record review and standardized clinical and neuropsych eval.  “Cognitively intact” if CASI >86. 

 NINCDS-ADRDA  DSM-IV Informant interview?:No 

(95% CI, 0.44-0.86, p=0.004). HR was 0.68 (95% CI, 0.48-0.96) when adjusted for all potential confounders. Kaplan-Meier survival estimates show that exercising >3 times/wk is 

associated with higher probability of being dementia-free. Significant interaction between exercise and performance-based physical function (p=0.013). Risk reduction associated with exercise was greater in those with lower performance levels. 5) Outcome of interest #3--AD  Age- and sex-adjusted HR was 0.64 (95% CI, 0.43-0.96, p=0.031).  HR was 0.69 (95% CI, 0.45-1.05; p=0.081) when adjusted for all potential confounders.  The interaction of exercise with performance-based physical function was significant (p=0.021). 

Launer, Ross, Petrovich, et al., 2000 Honolulu Heart Program 

Geographical location: Honolulu, HI Setting:Community Study design:

Prospective cohort Number of participants enrolled:

8006 in initial cohort; 

Age:Mean (SD): 52.7 (4.7) at baseline exam; 77.9 (4.7) at outcome assessment Range: 71 – 93 yo Sex: [n (%)] 

Female: 0% Male: 100% Race/ethnicity: [n (%)] Japanese-American 

Risk factor/exposure 1:Measured each visit 3 times five min apart, dbp “recorded as the fifth phase” Low sbp <110, normal 110-139, borderline 140-159, high 160+, dpb low <80, nl 80-89, borderline 90-94, high 95+ 

1) Follow-up rate: 80j% of survivors participated in evaluation; non-participants had lower education and moe missing data for one of the mid-life exams 2) Important baseline differences: high midlife sbp ore associated with with more stroke, dementia (not ad), and vascular dementia. High midlife dbp associated with more stroke. Men with low and nl baseline 

CommentsQuestion 1 Dementia eover 85 pluon the casithe threshoNo evaluatphases of sQuality assFor observ
B-143

Study Study Information Participants Risk Factor and 

Outcome Assessment 

Results Comments

3703 in this analysis Duration of follow up:>=23 years Time from risk factor assessment to final cognitive assessment:average of 27 years between first bp measurement and the dementia assessment 

(100%) Baseline cognitive status:no elimination of cognitive impairment but mean age at baseline 52.7+4.7 

Inclusion criteria: Participant in Honolulu Heart Program; Japanese-American males; born between 1900 – 1919; living in Oahu, HI at baseline; military service registered from WWII Exclusion criteria:30 subjects with dementia due to PD, b12 defiiency, subdural hematoma, or supranuclear palsy) 

A fifth category was created for those whose bp did not fall into a category above in 2/3 measurements. Self report of antihypertensives. Method of assessing risk factor/exposure 1:Direct measurement Covariates/potential confounders adjusted for in analyses:Age (at the fourth exam), education, apolipoprotein phenotype, smoking thru exam 3, alcohol at exam 3, cva, cad, subclinical atherosclerosis (abi based) Method(s) of assessing cognitive status:DSMIII-R - dementia NINCDS-ADRDA- AD Informant interview?:Yes – for those who got dementia eval 

pressure 1.5 yrs younger than others. 3) Outcome of interest #1 Analysis stratified by h/o treatment or no treatment with anti-hypertensive medication. Dementia cases = 197; AD=118 Among untreated, high DBP (OR 4.47 (95% CI 1.53 to 13.09), borderline DBP (OR 3.49, 95% CI 1.28 – 9.52) but not mixed DBP (OR 1.33, 95% CI 0.54 to 3.26) associated with AD Among treated, no association between DBP and AD: high DBP (OR 0.14 (95% CI 0.02 to 1.17), borderline DBP (OR 0.71, 95% CI 0.17 – 3.00); mixed DBP (OR 1.35, 

95% CI 0.49 to 3.69) Among untreated, no association between SBP and AD: high SBP (OR 1.22 (95% CI 0.37 to 4.04), borderline SBP (OR 1.23, 95% CI 0.63 – 2.43); mixed DBP (OR 0.25, 95% CI 0.05 to 1.14) Among treated, no association between SBP and AD: high SBP (OR 0.65 (95% CI 0.20 to 2.15), borderline SBP (OR 1.03, 95% CI 0.40 – 2.61); mixed DBP (OR 1.03, 95% CI 0.28 to 3.76) 4) Outcome of interest #2 high sbp (1965) and AD (1991-3) 0.56 (0.20-2.15) treated 

1) Unbias

cohort? 

2) Selectio

differenYes 

3) Sample 

differen

4) Adequa

cohort? 

5) Validat

ascerta

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ascertaYes 

7) Outcom

exposu

8) Adequa9) Comple10) Analys

confou

11) Analytic 

Yes 
B-144

Study Study Information Participants Risk Factor and 

Outcome Assessment 

Results Comments

For dementia overall, DBP (high and borderline) associated with dementia in untreated but not treated group. For dementia overall, high SBP but not borderline or mixed associated with dementia in untreated but not treated group. 

Laurin, Masaki, Foley, et al., 2004 HAAS 

Geographical location: Oahu, Hawaii Setting:Community Study design: Prospective cohort Number of participants enrolled:2459 Duration of follow up:Range: 25.7-33.0 yrs Time from risk factor assessment to final cognitive assessment:Range: 25.7-33.0 yrs 

Age:Mean (SD): At exam 4: Nondemented:76.3 (IQR 74.2-79.3) Demented: 78.9 (IQR 76.1-83.3) Sex: [n (%)] 

Female 0 (0%) Male: 2459 (100%) Race/ethnicity: [n (%)] NR Baseline cognitive status:Non-demented Inclusion criteria: Men of Japanese ancestry born between 1900 and 1919 who resided on the island of Oahu, Hawaii in 1965 and were participants of the Honolulu Heart Program. Exclusion criteria:

Risk factor/exposure

1:beta-carotene, flavonoids, Vit E and CMethod of assessing risk factor/exposure 1:Self-report Covariates/potential confounders adjusted for in analyses:Age Educational level Smoking ETOH use BMI Physical activity Blood pressure Year of birth Total energy intake Cholesterol Hx of cardiovascular disease APOE Supplemental vitamins Method(s) of 

1) Follow-up rate: NR in detail2) Important baseline differences: Individuals who became demented were older at baseline (p<0.001). No other differences 3) Outcome of interest #1Beta-carotene – no difference in risk of AD and mixed AD/vasc associated with higher quartiles of intake Vitamin C - – no difference in risk of AD and mixed AD/vasc associated with higher quartiles of intake Vitamin E – 2nd and 4th quartiles only 

associated with higher risk of AD and mixed AD/vasc (but not the 3rd

quartile) 2nd quartile: RR 1.92 (1.16-3.18) 

4th quartile: RR 1.78 (1.06-2.98) 

Flavonoids- no difference in risk of AD associated with higher quartiles of intake No sig trends across quartiles noted for any of the anti-oxidants 

CommentsQuestion 1 Quality assFor observ1) Unbias

cohort? 

2) Selectio

differenYes 

3) Sample 

differen

4) Adequa

cohort? 

5) Validat

ascerta

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ascertaYes 

7) Outcom

exposu

8) Adequa9) Comple

Partial 

10) Analys

confou

11) Analytic 

Yes 
B-145

Study Study Information Participants Risk Factor and 

Outcome Assessment 

Results Comments

NR assessing cognitive 

status:NINCDS-ADRDA DSM Informant interview?:

Yes 

4) Outcome of interest #2 Highest group of sum of all antioxidants intake associated with increased risk of AD and AD mixed/vasc dementia compared to lowest summed group. RR=1.82 (1.04-3.21) 

Laurin, Verreault, Lindsay, et al., 2001 Canadian Study of Health and Aging 

Geographical location: All 10 Canadian provinces Setting:Community Study design: Prospective cohort AND Nested case-control Number of participants enrolled:4615 Duration of follow up:5 years Time from risk factor assessment to final cognitive assessment:5 years 

Age:Controls:

Age 65-74: 59.5% Age 75-84: 36.6% Age >85: 3.9% 

Dementia:

Age 65-74: 18.6% Age 75-84: 53.7% Age >85: 27.7% 

Sex:Female: Controls:

2351 (60.4%) Dementia:175 (61.8%) Male: Controls:1543 (39.6%) Dementia:109 (38.2%) Race/ethnicity:NR Baseline cognitive status:

Risk factor/exposure 1:Physical activity Method of assessing risk factor/exposure 1: Self-report  Combined 2 questions from the risk factor questionnaire regarding frequency and intensity of exercise for subjects who reported physical activity.  Composite physical activity score categorized:  1) “low” = less than weekly  2) “moderate” = weekly  3) “high“= >3 times/wk  Reference category was no physical activity (subjects who reported no physical activity) Covariates/potential 

1) Follow-up rate:  4615 of 6434 initially eligible (72%). 442 excluded from the initial 9008 sample because they lived in Newfoundland, 826 had CIND or dementia.  Others excluded for death, refusal, lost to follow up. 2) Important baseline differences: NA 3) Outcome of interest #1285 incident cases of dementia, 436 incident cases of cognitive impairment, and 194 incident cases of AD. 4) Outcome of interest #2 High levels of physical activity were associated with reduced risks of cognitive impairment (age-, sex-, and education-adjusted OR, 0.58; 95% CI, 0.41-0.83), AD (OR, 0.50; 95% CI, 0.28-0.90), and dementia of any type (OR, 0.63; 95% CI, 0.40-0.98). 5) Outcome of interest #3  Authors’ comments:  “study showed a significant protective effect of regular physical 

[Comment

None Quality assFor observ1) Unbias

cohort? 

2) Selectio

differenYes 

3) Sample 

differen

4) Adequa

cohort? 

5) Validat

ascerta

6) Validat

ascertaYes 

7) Outcom

exposu

8) Adequa9) Comple10) Analys

confou

11) Analytic 

Yes 
B-146

Study Study Information Participants Risk Factor and 

Outcome Assessment 

Results Comments

Normal Non-demented Inclusion criteria: 65 years or older and living in the community in one of 36 selected urban and surrounding rural areas in Canada. Exclusion criteria: 

 Residents of Newfoundland,  Dx of CIND or dementia at the first evaluation. 

confounders adjusted for in analyses:Age Sex Educational level Family h/o dementia Tobacco use Alcohol use NSAID use Daily living activities Clinical variables Method(s) of assessing cognitive status: Screened with MMSE (screen + if MMSE <77).  NINCDS-ADRDA  DSM-IIIR (baseline)  DSM-IV (follow up) Informant interview?:No 

activity on the risk of CI and dementia, particularly of the AD type” “these associations were mainly in women, with a significant doseresponse relationship with decreasing risk with increasing physical activity.” 

Lautenschlager, Cox, Flicker, et al., 2008 FABS Fitness for the Aging Brain Study. 

Geographical location: Perth Australia. Setting:Other – Multiple sources. Study design: RCT Test intervention: Physical activity (encouragement to 

Age:Mean (SD): 68.6 (8.7) for the exercise group and 68.7 (8.5) for the control group Sex: [n (%)] 

Female: 42 (49.4) in the exercise groups 44 (51.8) in the control group. Male: 0 (0%) 

Risk factor/exposure 1:Physical activity Method of assessing risk factor/exposure 1:Self-report Direct measurement Risk factor/exposure 2:Apoe 

1) Follow-up rate: 138/170 (81.17%) 2) Important baseline differences: None 3) Outcome of interest #1The effect of the intervention on the entire sample (n=170)- P value for repeated measures ANOVA: Mean change of ADAS-COG scores:Between participants: 0.04 Within participants :0.54 

CommentsGood qualiexplicitly exQuality assFor RCTs: 1) Baselin2) Valid A

assess

3) Subjec4) Outcom5) Incomp

addres

6) Differen
B-147

Study Study Information Participants Risk Factor and 

Outcome Assessment 

Results Comments

participate in 150 minutes of moderate intensity activity per week) with behavioral intervention to increase adherence. Comparator intervention(s): Usual care. Number of participants enrolled:311 screened, 170 randomized (141 excluded) Duration of follow up:18 months. Time from risk factor assessment to final cognitive assessment:18 months. 

Race/ethnicity: [n (%)] 

NR Baseline cognitive status:Non-demented MCI Inclusion criteria: Age >50 yrs Answers yes to the following question: “Do you have any difficulty with your memory?” Exclusion criteria: .

1)Scores lower than 19 of 50 on the Telephone Interview for Cognitive Status–Modified 2)Geriatric Depression Scale-15 score of 6 or higher 3)Drinking more than 4 standard units of alcohol a day4)chronic mental illness, such as schizophrenia; 5) medical conditions likely to compromise survival, such as metastatic cancer, or render them unable to engage in physical activity, such as severecardiac failure. 6) severe sensory impairment or lack of fluency in written or 

Method of assessing risk factor/exposure 2:Direct measurement Covariates/potential confounders adjusted for in analyses:Age Sex Educational level Baseline cognitive status (premorbid IQ) Marital Status Adjusted baseline measures of outcome Method(s) of assessing cognitive status:ICD CERAD MMSE Informant interview?:No 

Word List Delayed recall: Between participants: 0.02 Within participants :0.10 No statistically significant difference for the other cognitive, health and quality of life measures. 4) Outcome of interest #2 The effect of the intervention and time on the MCI sample (n=100)- P value for repeated measures ANOVA: Mean change of ADAS-COG scores:Between participants: 0.02 Within participants :0.45 Word List Delayed recall: Between participants: 0.48 Within participants :0.55 No statistically significant difference for the other cognitive, health and quality of life measures. 5) Outcome of interest #3 The effect of the intervention and time on the complete- case analysis sample (n=138)- P value for repeated measures ANOVA: Mean change of ADAS-COG scores:Between participants: 0.0009 Within participants :0.25 Word List Delayed recall: Between participants: 0.01 Within participants :0.45 

Yes 

7) Overall 

Yes 

8) Conflic

insignif

9) Random10) Allocat

adequa
B-148

Study Study Information Participants Risk Factor and 

Outcome Assessment 

Results Comments

spoken English CDR sum of Boxes: 

Between participants: 0.003 Within participants :0.64 No statistically significant difference for the other cognitive, health and quality of life measures. 

Lee, Buring, Cook, et al., 2006 Women’s Health Study (WHS) 

Geographical location: NR Setting:Community Study design: Prospective cohort Number of participants enrolled:7118 Duration of follow up:2 yrs Time from risk factor assessment to final cognitive assessment:2 yrs 

Age:Range: > 66 years 

Sex:Female: 100% Race/ethnicity:NR Baseline cognitive status:Non-demented Inclusion criteria: Women’s Health Study participants 66 yrs or older in 1998. Exclusion criteria:Stroke (n=69) 

Risk factor/exposure 1:Education Method of assessing risk factor/exposure 1:Self-report “What is the highest level of education you have completed?” 1) Licensed practical or vocation nurse; 2) 2-year associates degree; 3) 3-year nurse diploma program (reference category); 4) Bachelors in nursing; 5) Masters degree; 6) Doctoral degree. Covariates/potential confounders adjusted for in analyses:BMI, physical activity, high blood pressure, 

1) Follow-up rate: 7118 eligible. 408 (5.7%) refused, 396 (5.9%) unreachable. Final sample at baseline: 6314 (88.7%) F/u rate: 5907/6314 (93.5%). 181 (3.1%) refused, 132 (2.3%) lost to f/u, 21 (0.4%) died. 2) Important baseline differences: NA 3) Outcome of interest #1—cognitive impairment Refer to Table 3 in article. 4) Outcome of interest #2—cognitive decline Refer to Table 5 in article. Authors conclusion: “In analysis of cognitive decline, findings were generally consistent with those of initial cognitive function; however, results were somewhat weaker, likely due to the short period over which we measured decline.” Odds ratios of cognitive decline according to educational attainment: RN: 1.0 (ref): LPN/LVN: 1.1 (0.8–1.5) 

CommentsNone Quality assFor observ1) Unbias

cohort? 

2) Selectio

differenYes 

3) Sample 

differen

4) Adequa

cohort? 

5) Validat

ascerta

6) Validat

ascertaYes 

7) Outcom

exposu

8) Adequa9) Comple10) Analys

confou

11) Analytic 

Yes 
B-149

Study Study Information Participants Risk Factor and 

Outcome Assessment 

Results Comments

diabetes, postmenopausal hormone use, history of depression, and income Age Smoking Physical activity Alcohol Method(s) of assessing cognitive status:Cognitive function assessed using TICS, a validated telephone battery, plus 4 other cognitive tests: East Boston Memory test (immediate and delayed recalls); Delayed word recall; Category fluency. Summary composite score calculated from all 5 tests. Cognitive impairment and decline defined as 

worst 10% of test distribution. Informant interview?No 

2-yr AD: 0.9 (0.6–1.4) BA or BS: 1.0 (0.8–1.3) Masters: 1.0 (0.8–1.4) Doctoral: 0.7 (0.4–1.2) After controlling for covariates, there was no statistically significant association between level of education and cognitive decline. 

Lee, Geographical Age: Risk factor/exposure 1) Follow-up rate: Comments
B-150

Study Study Information Participants Risk Factor and 

Outcome Assessment 

Results Comments

Kawachi, Berkman, et al., 2003 Nurses Health Study 

location: U.S. Setting:Community Study design: Prospective cohort Number of participants enrolled:22,213 contacted. 19,510 (88%) completed baseline interview. 15,594 Duration of follow up:2 years Time from risk factor assessment to final cognitive assessment:2 yrs 

Mean: 74 yrs. Sex:

Female: 19,319 (100%) Male: 0 Race/ethnicity:NR Baseline cognitive status:No exclusion by cognitive function Inclusion criteria: Nurses’ Health Study participants aged 70 yrs or more who were free of diagnosed stroke and had answered the most recent mailed questionnaire. Exclusion criteria:Less than 15 years of education. 

1:Education Method of assessing risk factor/exposure 1:Self-report 3 categories: 1) 3-year RN diploma (77.9%) 2) Bachelor’s degree (16.4%) 3) Master’s/doctoral degree (5.7%) Covariates/potential confounders adjusted for in analyses:Baseline test scores Age Clinical variables Medications Smoking Alcohol BMI SF-36 vitality and mental health scores Method(s) of assessing cognitive status: Cognitive function assessed using TICS, a validated telephone battery, plus 5 other cognitive tests: East Boston Memory test (immediate and delayed recalls); 

22,213 were contacted at baseline. 19,510 (88%) completed the interview (7% refused, and 5% not reached because of inaccurate contact information). 19,319 completed baseline interview.15,594/19,319 = 80.7% (but f/u was still ongoing at time of this analysis). 13,429 women (69.5%) had complete data for cognitive decline analyses. 2) Important baseline differences: NA 3) Outcome of interest #1—cognitive decline “We found statistically significant trends of decreasing odds of cognitive decline with increasing level of education on all six tests.” Global change score OR (95% CI):

1) RN: 1.0 2) Bachelor’s: 0.80 (0.68,0.94) 3) Master’s/doctorate: 0.65 (0.50, 0.86) 4) Outcome of interest #2—cognitive tests as continuous data“Comparable results; we found statistically significantly less mean decline on five tests for women with advanced graduate degrees, and statistically significant trends of decreasing mean decline with increasing education after multivariate adjustment.” 

None Quality assFor observ1) Unbias

cohort? 

2) Selectio

differenYes 

3) Sample 

differen

4) Adequa

cohort? 

5) Validat

ascerta

6) Validat

ascertaYes 

7) Outcom

exposu

8) Adequa9) Comple10) Analys

confou

11) Analytic 

Yes 
B-151

Study Study Information Participants Risk Factor and 

Outcome Assessment 

Results Comments

Delayed word recall; Verbal fluency; Digit span backwards test. Global score calculated from all 6 tests. Low scorers defined as <31 points on the TICS. For remaining tests, low score defined as worst 10% of test distribution. Change scores calculated for each test, including global score. Cutpoints defined for each test. Informant interview?:No 

Li, Higdon, Kukull, et al., 2004 Adult Changes in Thought (ACT) 

Geographical location: Seattle, WA Setting:Community Study design: Prospective cohort Number of participants enrolled:2581 

Age:Mean (SD): 75.1 (6.1) Sex:

Female: 1409 (59.8%)Male: 947 (40.2%) Race/ethnicity:White 2149 (91.2%) Non-White 206 (8.7%) Missing 1 (0.04%) Baseline cognitive 

Risk factor/exposure

1:Statin 0 one statin equivalent = 10 mg simvastatin, or 20 mg lovastatin or pravastatin, or 5 mg atorvastatin with use defined as at least 2 consecutive fills within a 6-month period Method of assessing 

1) Follow-up rate: 2356 (91.3%) 392 statin users (41 demented; 351 non-demented) 1964 non-statin (271 demented; 1693 non-demented) 168 with AD; 48 possible AD; 96 other dementia (69% AD/possible AD) Unadjusted HR for probable AD (95% CI) 

CommentsNone Quality assFor observ1) Unbias

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differenYes 

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B-152

Study Study Information Participants Risk Factor and 

Outcome Assessment 

Results Comments

Duration of follow up:~ 17 yrs Time from risk factor assessment to final cognitive assessment:Variable 

status:Non-demented Inclusion criteria: Group Health Cooperative HMO member; ≥ 65 yo Exclusion criteria:Cognitive Abilities Screening Instrument (CASI) score < 86 

risk factor/exposure

1:Other – pharmacy record Risk factor/exposure 2:Age, sex, medical history, family history Method of assessing risk factor/exposure 2:Self-report Covariates/potential confounders adjusted for in analyses:status Age at entry Yrs of education APOE e4 status Use of other lipid lowering agents Method(s) of assessing cognitive status:Other – CASI screen and if < 86, clinical exam, lab test, neuroimaging and neuropsychological testing; Dx assigned using NINCDS-ADRDAInformant interview?:No 

No statin 1.0 (ref) Statin 0.90 (0.54 to 1.51) Adjusted HR for probable AD (95% CI) – age, education, APOE-e4 status an use of other lipid lowering agents No statin 1.0 (ref) Statin 0.82 (0.46 to 1.46) No dose response relationship. Adjusted HR analyzed by cumulative equivalent dose (<1,461 s >=1,451 equivalents), duration (< 2 years vs >= 2years) or average daily equivalent dose (<4 vs. >= 4 equivalents/day) showed overlapping confidence intervals. CEQ < 1,461 0.95 (0.46 to 1.97); >= 1,461 (0.73 (0.26 to 2.05) Duration < 2 years 0.91 (0.40 to 2.09); >= 2 years 0.87 (0.31 to 2.47) ADED < 4 0.91 (0.40 to 2.09); >= 4 0.63 (0.21 to 1.91) 

cohort? 

5) Validat

ascerta

6) Validat

ascertaYes 

7) Outcom

exposu

8) Adequa9) Comple10) Analys

confou

11) Analytic 

Yes 
B-153

Study Study Information Participants Risk Factor and 

Outcome Assessment 

Results Comments

Li, Rhew, Shofer, et al., 2007 Adult Changes in Thought (ACT) 

Geographical location:Seattle, WA Setting:Community – cohort from health maintenance organization Study design: Prospective cohort Number of participants enrolled:2581 2356 analyzed Duration of follow up: Baseline (and exposure) 1994-6 then biennially through end of 2004. CASI each follow up; mean f/u duration NR Time from risk factor assessment to final cognitive assessment:up to 10 years 

Age:Range:  Age 65-69 542 (23%)  Age 70-74 730 (31%)  Age 75-79 565 (24%)  Age 80-84 353 (15%)  Age 85+ 166 (7%) Sex: [n (%)] 

Female: 1414 (60%) Male: 942 (40%) Race/ethnicity: [n (%)]  White 2144 (91%)  African-Amer 94 (4%) Other 94 (4%)  Info missing 24 (1%)Baseline cognitive status:Non-demented Inclusion criteria: Member of communitybased, large HMO; age >=65; selected randomly; dementiafree; non-nursing home resident; agree to prticipate (48% of eligibles) and at least one follow-up Exclusion criteria:NR other than above 

Risk factor/exposure

1:htn with sbp high >

160, borderline 140-159, dbp high > 90, borderline 80-89. Enrollment bp considered primary exposure Method of assessing risk factor/exposure 1:Direct measurement Covariates/potential confounders adjusted for in analyses:Race (white/nonwhite), Sex, years education, presence of at least one apoE4, (hx cad, cvc, dm, use of antihypertensives), analyses were done but paratmeter estimates not reported for AD, just nonspecific dementia Separate models for three age strata: 65-74, 75-84, older because of significant interaction term for HTN*age Method(s) of 

1) Follow-up rate: of the 48% of the initial eligible who participated 91% had at least one follow up. 2) Important baseline differences: in hypertensive group, more females, diabetics and use of antihypertensives 3) Outcome of interest #1 Incident dementio =380 (AD = 204) HR for Ad with sbp > 160 compared 

to <140 age 65-74 1.38 (95% CI 0.71-2.70) age 75-84 0.94 (0.62-1.42) >85 0.70(0.25-1.95) 

HR for Ad with sbp 140-159

compared to < 140 age 65-74 1.47 (95% CI 0.80-2.71) age 75-84 0.60 (0.38-0.92) >85 0.48 (0.15-1.57) 

4) Outcome of interest #2 HR for AD with dbp > 90 compared 

to dbp < 80 age 65-74 0.82 (95% CI 0.29-2.35) 75-84 0.73 (0.34-1.59) 85+ no cases HR for AD with dbp 80-89 compared 

to dbp < 80 age 65-74 1.71 (95% CI 0.98-2.97) 75-84 0.96 (0.63-1.47) 85+ 1.58 (0.58 – 4.29) Additional analyses that adjusted for additional covariates (hx cad, cvc, dm, use of antihypertensives), analyses were reported to produce 

CommentsQuestion 1 Dementia escore < 86. Quality assFor observ1) Unbias

cohort? 

2) Selectio

differenYes 

3) Sample 

differen

4) Adequa

cohort? 

5) Validat

ascerta

6) Validat

ascertaYes 

7) Outcom

exposu

8) Adequa9) Comple

Can’t T

10) Analys

confou

11) Analytic 

Yes 
B-154

Study Study Information Participants Risk Factor and 

Outcome Assessment 

Results Comments

assessing cognitive status:NINCDS-ADRDA DSM-IV Informant interview?:No 

little change in the risk estimates 

Lindsay, Laurin, Verreault, et al., 2002 Canadian Study of Health and Aging (CSHA) 

Geographical location: Eighteen field centers across all Canadian provinces. Setting:Community Study design: Prospective cohort Number of participants enrolled:Community sample:9008 Eligible subjects:7273 Enrolled subjects:6434 Final study sample:4615 Duration of follow up:5 yrs Time from risk factor assessment to final cognitive assessment:5 yrs 

Age:Case/Control Mean (SD): 81/72.9 Median::87/78 Range: 69-105 yrs/ 70-100 yrs Sex:

Case/control Female: 131 (67.5%)/ 2239(57.5%) Male: 63(32.5%)/ 1655(42.5%) Race/ethnicity:NR Baseline cognitive status:Non-demented Inclusion criteria: 65 yrs and older Exclusion criteria: NR 

Risk factor/exposure

1:ApoE4 Method of assessing risk factor/exposure 1:Direct measurement Risk factor/exposure 2:High blood pressure Method of assessing risk factor/exposure Self report Direct measurement Risk factor/exposure 3: Depression Method of assessing risk factor/exposure Self report Risk factor/exposure 4: Prior head injury Method of assessing risk factor/exposure

1) Follow-up rate:  4615/6434 (71.7%) participated in follow up study 2) Important baseline differences: NA 3) Outcome of interest #1--APOE Odds ratio(OR) 3.28 (95% CI: 1.98,5.44) 4) Outcome of interest #2—High BP OR 0.88(0.62,1.27) 5) Outcome of interest #3--Depression OR 1.44(0.84,2.48) 6) Outcome of interest#4—Prior head injury OR 0.87 (0.56,1.36) 7) Outcome of interest#5--Diabetes OR 1.03 (0.58,1.84) 8) Outcome of interest #6—Antihypertensive agents OR 0.91 (0.64,1.30) 9) Outcome of interest#7—Any NSAIDs 

CommentsNone Quality assFor observ1) Unbias

cohort? 

2) Selectio

differenYes 

3) Sample 

differen

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5) Validat

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6) Validat

ascertaYes 

7) Outcom

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8) Adequa9) Comple10) Analys

confou

11) Analytic 

Yes 
B-155

Study Study Information Participants Risk Factor and 

Outcome Assessment 

Results Comments

Self report Risk factor/exposure 5: Diabetes Method of assessing risk factor/exposure Self report Risk factor/exposure 6: Antihypertensive agents Method of assessing risk factor/exposureSelf report Risk factor/exposure 7: Any NSAID use Method of assessing risk factor/exposure Self report Risk factor/exposure 8: Estrogen replacement therapy(ERT) Method of assessing risk factor/exposure 8:Self-report Covariates/potential confounders adjusted for in analyses:

OR 0.65 (0.44,0.95) 

10 )Outcome of interest#8—Estrogen replacement therapy 

OR 1.37 (0.48,3.95) 

11) Years of Education (controlled for age and sex) with >13 years as 

reference. 9-12 yrs: OR 1.37 (95% CI: .91,2.06)0-8 yrs: OR 1.90 (95% CI: 1.25,2.90)Analysis included 194 AD cases and 3894 cognitively normal controls. Increased risk of AD was associated with ApoE4 while NSAID use was associated with reduced risk of AD. No statistically significant association was found for history of depression, estrogen replacement therapy, high blood pressure, head trauma, antihypertensive use, diabetes. 
B-156

Study Study Information Participants Risk Factor and 

Outcome Assessment 

Results Comments

Age Race Sex Educational level Baseline cognitive status Wine consumption Coffee consumption Medical conditions( arthritis, cancer, thyroid, PUD) Family history AD Vascular disease Tobacco use Method(s) of assessing cognitive status:NINCDS-ADRDA DSM-4th edition 

Other – NINDS-AIREN Modified Mini- Mental State Exam(3MS)(screening criteria: positive result <78/100) Informant interview?:Yes 

Lu, Edland, Teng, et al., 2009 Alzheimer’s Disease Cooperative Study 

Geographical location: 69 ADCS sites in US & Canada Setting:Clinical – participants in the Alzheimer’s Disease Cooperative 

Age:Mean (SD):  Depressed  73.11 (7.32)  Non-depressed  72.83 (7.31) Range: 55-91 years Sex: [n (%)] 

Risk factor/exposure 1:Depression Method of assessing risk factor/exposure 1:Beck Depression Inventory (BDI) 

1) Follow-up rate: 756/769 (98%)2) Important baseline differences: N/A 3) Outcome of interest #1Impact of risk factor on progression to AD 

CommentsQuestion 4 Note: This analysis of across all t(donepezil with adjustmthe Cox mo
B-157

Study Study Information Participants Risk Factor and 

Outcome Assessment 

Results Comments

drug trial Study drug trial 

Study design: RCT (though analyzed as if it were an uncontrolled observational study) Test intervention Vitamin E (2,000 IU) OR Donepezil (10mg) Comparator intervention(s) Matching placebo Number of participants enrolled:756  208 Depressed  548 Non-depressed Duration of follow up:3 years Time from risk factor assessment to final cognitive assessment:3 years 

Female:  Depressed  104 (50%)  Non-depressed  241 (44%) Male:  Depressed  104 (50%)  Non-depressed  307 (56%) Race/ethnicity: [n (%)] White  Depressed  193 (93%)  Non-depressed  504 (92%) Baseline cognitive status:aMCI Inclusion criteria: Met criteria for aMCI of a presumably degenerative nature (insidious onset, gradual progression), defined as 1) subjective memory complaint corroborated by an informant, 2) insufficient global cognitive and functional impairment to meet National Institute of Neurological and Communicative Disorders and StrokeAlzheimer’s Disease 

Risk factor/exposure 2:APOE genotype Method of assessing risk factor/exposure 2:Direct measurement Covariates/potential confounders adjusted for in analyses:Age Baseline MMSE score APOE genotype Treatment group NYU paragraph delayed recall score Method(s) of assessing cognitive status:NINCDS-ADRDA When the clinical diagnosis of AD was made, all cognitive and functional data were sent to the ADCS Coordinating Center and forwarded to a 5-

member central review committee for a consensual diagnosis. Informant interview?:No 

BDI score: HR 1.03 (95% CI: 1.01, 1.06; p=0.022) APOE carrier: HR 2.03 (95% CI: 1.45, 2.83; p<0.0001) 

Quality assFor observdata are froanalyzed auncontrolle1) Unbias

cohort? 

2) Selectio

differenYes 

3) Sample 

differen

4) Adequa

cohort? 

5) Validat

ascerta

6) Validat

ascertaYes 

7) Outcom

exposu

8) Adequa9) Comple10) Analys

confou

11) Analytic 

Yes 
B-158

Study Study Information Participants Risk Factor and 

Outcome Assessment 

Results Comments

and Related Disorders Association (NINCDSADRDA) criteria for probable AD, 3) Logical Memory (one paragraph) delayed recall score 1.5 SD below educationadjusted normative means, 4) Clinical Dementia Rating (CDR) score of 0.5, and 5) Mini-Mental State Examination (MMSE) score ≥ 24. 

Exclusion criteria:Score of greater than 12 on the Hamilton Depression Rating Scale (HAM-D) or a modified Hachinski score of >4; h/o significant cerebrovascular disease; CNS infarct, infection, or focal lesions of clinical significance on CT or MRI; medical or psychiatric conditions that could interfere with study participation; pregnancy, lactation, or childbearing potential; or taking vitamins or other supplements (may take stable doses at least 1 month prior to screening of antidepressants 
B-159

Study Study Information Participants Risk Factor and 

Outcome Assessment 

Results Comments

lacking significant anticholinergic side effects. 

Luchsinger, Honig, Tang, et al., 2008 WHICAP 

Geographical location: Northern Manhattan, NYC, USA Setting:Community Study design:

Prospective cohort Number of participants enrolled:

1,128 in parent study; 526 in current analysis Duration of follow up:5.1 (3.3) years Time from risk factor assessment to final cognitive assessment:5.1 (3.3) years 

Age:Mean (SD): 75.1 (6.4) Sex: [n (%)] 

Female: 356 (67.7%) Male: 170 (32.3%) Race/ethnicity: [n (%)] AA 31.2% Hispanic 48.3% White 20.5% 

Baseline cognitive status:Non-demented Inclusion criteria:  Medicare recipient selected at random  Age >=65  HAMD at baseline  At least one f/u Exclusion criteria:Dementia 

Risk factor/exposure

1:Depression – Hamilton Depression Rating Scale – 17-item Method of assessing risk factor/exposure 1:Self-report Covariates/potential confounders adjusted for in analyses:Age Race Sex Educational level APOE-e4 DM HTN Heart disease Current smoking Stroke Method(s) of assessing cognitive status:NINCDS-ADRDA Informant interview?:No 

1) Follow-up rate:  50.2% >= 4 f/u visits  9.7% 3 f/u visits  17.5% 2 f/u visits  22.6% 1 f/u visit  Unknown with 0 visits in the overall cohort 2) Important baseline differences: NR 3) Outcome of interest #1 HAMD = 0, 8 AD cases, HR 1.0  HAMD = 1 to 9, 83 cases, HR 2.3 (1.0 to 5.3)  HAMD >9, 23 AD cases, HR 3.0 (1.2 to 7.9) 

CommentsOnly a convoverall cohand they di(younger, mstroke) than HAMD Quality assFor observ1) Unbias

Partial 

2) Selectio

differenYes 

3) Sample 

differen

4) Adequa

cohort: 

5) Validat

ascerta

6) Validat

ascertaYes 

7) Outcom

exposu

8) Adequa9) Comple

Can’t T

10) Analys

confou

11) Analytic 

Yes 

Luchsinge Geographical Age: Risk factor/exposure 1) Follow-up rate: Comments
B-160

Study Study Information Participants Risk Factor and 

Outcome Assessment 

Results Comments

r, Reitz, Honig, et al., 2005 WHICAP 

location: northern Manhatten, NY Setting:] Community Study designProspective cohort Number of participants enrolled:2126 initial screened cohort; 1138 final cohort Duration of follow up:Follow up data were collected ~ every 18 months through ~5 yrs. (6292 person-year follow up) Time from risk factor assessment to final cognitive assessment:Mean 5.5 yrs(SD 3.2 person years) 

Mean (SD): 76.2(5.9) Sex:

Female: 734(69.8%) Male: 404(40.2%) Race/ethnicity:Black: 377(33.1%) Hispanic: 505(44.4%) White: 256(22.5%) Baseline cognitive status:Non-demented Inclusion criteria: 65 yrs and older, nondemented Exclusion criteria:NR 

1:Diabetes Mellitus Method of assessing risk factor/exposure 1:Self-report Other – Use of specific DM medications Risk factor/exposure 2:Hypertension Method of assessing risk factor/exposure 2:Self-report Risk factor/exposure 3: Tobacco use(current vs past)Method of assessing risk factor/exposure 3: Self report Covariates/potential confounders adjusted for in analyses:Age Race Sex Educational level Baseline cognitive status Vascular disease Lipid values 

1012/1138(88.9%) 126 excluded as they were missing 

APOE4 genotyping. 

2) Important baseline differences: NA 3) Outcome of interest #1At risk, n=36; cases n=11(30.6 %) HR 3.8(1.8,8.2) At risk: n=306; cases n=48(15.7%) HR 1.5(0.9,2.4) 4) Outcome of interest #2—Probable and possible AD (n=246), by risk factor Hazard ratio (95% CI) Diabetes: 3.8 (1.8, 8.2) HTN: 1.5 (0.9, 2.4) Tobacco: 2.2 (1.0, 4.9) 5) Outcome of interest #3 At risk: 41; cases n=9(21.9) HR2.2(1.0,4.9) All data utilized model 2 which adjusted for age, sex, ethnic group, education and APOE4.Sample size 1012 due to 126 missing APOE

genotyping All CI :95% Authors’ conclusion: “The risk of AD increased with the number of vascular risk factors, diabetes, HTN, heart disease, and current smoking. We also found that different combinations of risk factors 

None Quality assFor observ1) Unbias

cohort? 

2) Selectio

differenYes 

3) Sample 

differen

4) Adequa

cohort? 

5) Validat

ascerta

6) Validat

ascertaYes 

7) Outcom

exposu

8) Adequa9) Comple10) Analys

confou

11) Analytic 

Yes 
B-161

Study Study Information Participants Risk Factor and 

Outcome Assessment 

Results Comments

BMI Method(s) of assessing cognitive status:NINCDS-ADRDA Other-Clinical Dementia Rating(>0.5) Informant interview?:No 

were associated with a high risk of AD. Diabetes and smoking were the strongest risk factors.” 

Luchsinger, Tang, Miller, et al., 2007 WHICAP 

Geographical location: Northern Manhattan,NY Setting:Community Study design: Prospective cohort Number of participants enrolled:965 Duration of follow up:6.1 (3.3) yr Time from risk factor assessment to final cognitive assessment:6.1 (3.3) yr 

Age:Mean (SD): 75.8 (5.8) Sex: [n (%)] 

Female: 680 (70.5) Male: 285 (29.5) Race/ethnicity: [n (%)] AA 315 (32.6) White 213 (22.1) Hispanic 437 (45.3) Baseline cognitive status:Non-demented Inclusion criteria: Medicare recipients age >65 residing in 

Northern Manhattan Exclusion criteria:None 

Risk factor/exposure 1:Folate, Vit B6 & B12 Method of assessing risk factor/exposure 1:Self-report Covariates/potential confounders adjusted for in analyses:Age Race Sex Educational level APOE DM HTN Smoking Heart disease Stroke Method(s) of assessing cognitive status:NINCDS-ADRDA 

1) Follow-up rate: 965/1375 (denominator excludes those with dementia, but don’t know how much attrition due to death)2) Important baseline differences: Ind who dev AD were older, less educated. A higher proportion of Hispanics and a lower proportion of whites dev AD. A higher proportion w/ DM, HTN, heart disease and stroke dev AD. 3) Outcome of interest #1 Folate: Higher quartiles of intake were not significantly associated with risk of AD B6: Higher quartiles of intake were not significantly associated with risk of AD B12: Higher quartiles of intake were not significantly associated with risk of AD 

CommentsQuestion 1 The associAD became controlled fQuality assFor observ1) Unbias

cohort? 

2) Selectio

differenYes 

3) Sample 

differen

4) Adequa

cohort? 

5) Validat

ascerta

6) Validat

ascertaYes 

7) Outcom

exposu

8) Adequa9) Comple10) Analys
B-162

Study Study Information Participants Risk Factor and 

Outcome Assessment 

Results Comments

DSM Informant interview?:No 

confou

11) Analytic 

Yes 

Luchingser, Tang, Shea, et al., 2002 WHICAP 

Geographical location: Northern Manhattan,NY Setting:Community Study design: Prospective cohort Number of participants enrolled:980 Duration of follow up:4 (1.5) Time from risk factor assessment to final cognitive assessment:4 (1.5) 

Age:Mean (SD): 75.3 (5.8) Sex: [n (%)] 

Female: 657 (67) Male: 323 (33) Race/ethnicity: [n (%)] AA 314 (32) White 245 (25) Hispanic 421 (43) Baseline cognitive status:Non-demented Inclusion criteria: Medicare recipients age >65 residing in 

Northern Manhattan Exclusion criteria:NR 

Risk factor/exposure

1:caloric intake, carbohydrates, fats, protein Method of assessing risk factor/exposure 1:Self-report Covariates/potential confounders adjusted for in analyses:Age Race Sex Educational level APOE Method(s) of assessing cognitive status:NINCDS-ADRDA DSM Informant interview?:No 

1) Follow-up rate: 980/1192 (1192 includes those lost to follow-up only, not those excluded due to dementia) 2) Important baseline differences: Total calories: highest quartiles older and more education Carbohydrates: Highest quartiles older, less likely to be female, Protein: highest quartiles less education 3) Outcome of interest #1Total daily calories: quartile 4 assoc with increased risk of AD (HR: 1.48; 1.00-2.19) Carbohydrates: no assoc with AD Fats: no assoc with AD Protein: no assoc with AD 4) Outcome of interest #2 Only APOE 4 positive associated with risk of AD for: Total calories: quartile 4 (HR 2.27 (1.11-4.68) Fats: quartile 4 (HR: 2.31; 1.09-4.89)

CommentsQuestion 1 Quality assFor observ1) Unbias

cohort? 

2) Selectio

differenYes 

3) Sample 

differen

4) Adequa

cohort? 

5) Validat

ascerta

6) Validat

ascertaYes 

7) Outcom

exposu

8) Adequa9) Comple10) Analys

confou

11) Analytic 

Yes 

Luchsinger, Tang, Shea, et al., 2003 

Geographical location: Northern Manhattan,NY 

Age:Mean (SD): Mean (SD): 75.3 (5.8) 

Risk factor/exposure

1:Vit C & E and carotenoids 

1) Follow-up rate:980/1192 (1192 includes those lost to follow-up only, not those excluded due to dementia) 

CommentsQuestion 1 Quality ass
B-163

Study Study Information Participants Risk Factor and 

Outcome Assessment 

Results Comments

WHICAP Setting:

Community Study design: Prospective cohort Number of participants enrolled:980 Duration of follow up:4 (1.5) Time from risk factor assessment to final cognitive assessment:4 (1.5) 

Sex: [n (%)] 

Female: 657 (67%) Male: 323 (33%) Race/ethnicity: [n (%)] AA 314 (32) White 245 (25) Hispanic 421 (43) Baseline cognitive status:Non-demented Inclusion criteria: Medicare recipients age >65 residing in 

Northern Manhattan Exclusion criteria:NR 

Method of assessing risk factor/exposure 1:Self-report Covariates/potential confounders adjusted for in analyses:Age Sex Educational level APOE Smoking Method(s) of assessing cognitive status:NINCDS-ADRDA DSM Informant interview?:

No 

2) Important baseline differences: Vit C & E users had more education Lower proportion of Hispanics were Vit E users 3) Outcome of interest #1Calorie adjusted intake (nosupplements) Carotenoids: higher intake quartiles no assoc with AD Vit C: higher intake quartiles no assoc with AD Vit E: higher intake quartiles no assoc with AD 4) Outcome of interest #2 Supplemental and dietary intake Vit C: Highest intake quartile no assoc with AD Vit E: Highest intake quartile no assoc with AD 

For observ1) Unbias

cohort? 

2) Selectio

differenYes 

3) Sample 

differen

4) Adequa

cohort? 

5) Validat

ascerta

6) Validat

ascertaYes 

7) Outcom

exposu

8) Adequa9) Comple10) Analys

confou

11) Analytic 

Yes 

Luchsinger, Tang, Shea, et al., 2004 WHICAP 

Geographical location: New York City, NY Setting:Community Study design: Prospective cohort Number of participants enrolled: 2126 original subjects  909 sample for this 

Age:Median: 77 years Sex:

Female: 70% Male: 30% Race/ethnicity:Hispanic 52% African American 30% White 18% Baseline cognitive status:Non-demented 

Risk factor/exposure

1:hcy Method of assessing risk factor/exposure 1:Direct measurement Frozen fasting plasma, doesn’t say how long it was stored. Covariates/potential confounders adjusted for in 

1) Follow-up rate: subset who had a follow up and hcy levels seem to have been chosen. 2) Important baseline differences: Subjects with higher hcy were older, more men, less dm, more stroke, more prevalent dementia, more prevalent AD. 3) Outcome of interest #1 When unadjusted those in the highest quartile of hcy as compared to the lowest quartile had hr for ad of 2.0 (1.2 – 3.5). When adjusted for 

CommentsNone Quality assFor observ1) Unbias

cohort? 

2) Selectio

differenYes 

3) Sample 

differen

4) Adequa

cohort? 

5) Validat
B-164

Study Study Information Participants Risk Factor and 

Outcome Assessment 

Results Comments

study  679 available for longitudinal analysis Duration of follow up: I can’t tell. Plasma reportedly drawn at baseline. Cog testing done every 18 mos. Reportedly 3,206 person years. Can we assume a mean follow up of 4.7 yrs per person? Time from risk factor assessment to final cognitive assessment:hcy at baseline. Follow ups every 18 mos. 

Inclusion criteria:  Medicare recipients  Residents of Washington Heights community in NYC Exclusion criteria:

Dementia 

analyses: 

age, sex, education, apoE4, strokeMethod(s) of assessing cognitive status:NINCDS-ADRDA DSM Informant interview?:No 

age, sex, education, apoE4, stroke hr was 1.3 (0.8 – 2.3) 

ascerta

6) Validat

ascertaYes 

7) Outcom

exposu

8) Adequa

Can’t T

9) Comple

Partial 

10) Analys

confou

11) Analytic 

Yes 

Lytle, Vander Bilt, Pandav, et al., 2004 MoVIES 

Geographical location: Southwestern Pennsylvania, USA Setting:Community Study design: Prospective cohort Number of participants enrolled:1146 Duration of follow up:2 yrs 

Age:Mean (SD): 76.8 (5.3) Sex: [n (%)] 

Female: 722 (63%) Male: 424 (37%) Race/ethnicity:White: 97.7% Non-white: 2.3% Baseline cognitive status:All Inclusion criteria: 65 yrs or older, living in the community, fluent 

Risk factor/exposure 1:Exercise. Method of assessing risk factor/exposure 1:Self-report Subjects were asked whether they engaged in an exercise program, and, if so, in what type of exercise, exercise equipment used, and freq. and duration of exercise. 

1) Follow-up rate: Analytical sample 929 Attrition rate due to death 9 – 14% Attrition due to other causes 2.8% 2) Important baseline differences: There was a statistically significant difference in age and sex among the high, low, and no exercise groups at baseline 3) Outcome of interest #1High exercise level at wave 3 was associated with reduced risk of cognitive decline at wave 4. OR: 0.39, (95%CI 0.19, 0.78) 4) Outcome of interest #2

CommentsNone Analysis inbaseline coQuality assFor observ1) Unbias

cohort? 

2) Selectio

differenYes 

3) Sample 

differen

4) Adequa

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5) Validat
B-165

Study Study Information Participants Risk Factor and 

Outcome Assessment 

Results Comments

Time from risk factor assessment to final cognitive assessment:2 yrs 

in English, and having at least a 6th grade 

education. Exclusion criteria:NR 

Aerobic vs. nonaerobic Covariates/potential confounders adjusted for in analyses:Age Sex Educational level Self rating of health Method(s) of assessing cognitive status:Cognitive battery, including the MMSE and a standardized risk factor and outcome assessment questionnaire. Cognitive decline defined as “being in the 90th percentile of 

decline in this cohort, ie, declining by 3 or more MMSE points during the 2-year interval between assessments.” Informant interview?No 

When high exercise was considered as exercising for more than 5 or more days a week for at least 30 minutes, cognitive decline was negatively associated with high exercise. OR: 0.45, (95%CI 0.22, 0.95) Low exercise also showed a negative association. OR:0.63, (95%CI 0.39, 0.997 Outcome of interest #3Wave 3 mmse was not associated with future exercise level. This analysis was done to examine both directions of the relationship. 

ascerta

6) Validat

ascertaYes 

7) Outcom

exposu

8) Adequa9) Comple10) Analys

confou

11) Analytic 

Yes 
B-166

Study Study Information Participants Risk Factor and 

Outcome Assessment 

Results Comments

Manly, Schupf, Tang, et al., 2005 WHICAP 

Geographical location: Northern Manhattan NY, USA Setting:Community Study design: Prospective cohort Number of participants enrolled:1362 Duration of follow up:Approximately 4.5 years. Not reported specifically. Time from risk factor assessment to final cognitive assessment:Approximately 4.5 years. Not reported specifically. 

Age:

Mean (SD): High education: 75.5 (6.2) Low education: 75.9 (5.9) Sex: [n (%)] High education: Female: 67.1% Male: 32.9% Low education: Female: 69.8% Male: 30.2% Race/ethnicity: [n (%)] 

High education: White 73.6% Low education: White 26.4% Baseline cognitive status:Normal Non-demented Inclusion criteria: English as primary language, self identified as Hispanic, African American or Non-Hispanic White. Exclusion criteria:Stroke, Parkinson’s disease Cognitive or functional impairment at baseline. 

Risk factor/exposure 1:Reading Level Method of assessing risk factor/exposure 1:Self-report Direct measurement - Wide Range Achievement Test Version-3 Risk factor/exposure 2:Literacy, education Method of assessing risk factor/exposure 2:Self-report Covariates/potential confounders adjusted for in analyses:Age Race Sex Educational level Method(s) of assessing cognitive status:CDR DSM IV Informant interview?:No 

1) Follow-up rate: Of 1362 in current study, 80 were dead, 94 refused and 75 moved out of the area. 111 had missing data. 1002/1113= 90.02% 2) Important baseline differences: High education group was more likely to be White, have more years of education, have higher reading level, and follow up longer. 3) Outcome of interest # After controlling for age, gender, race and education, participants with lower literacy were more likely to have faster decline in cognition. Memory: β= 3.2; p= .002 

Executive function: β= 1.0; p= 0.002 Language: β= 0.2; p= .000 

CommentsNone Quality assFor observ1) Unbias

cohort? 

2) Selectio

differenYes 

3) Sample 

differen

4) Adequa

cohort? 

5) Validat

ascertaTell 

6) Validat

ascertaYes 

7) Outcom

exposu

8) Adequa9) Comple10) Analys

confou

11) Analytic 

Yes 
B-167

Study Study Information Participants Risk Factor and 

Outcome Assessment 

Results Comments

Martin, Szekely, Brandt, et al., 2008 ADAPT 

Geographical location:Baltimore, MD Boston, MA Rochester, NY Seattle, WA Sun City, AZ Tampa, FL Setting:Community Study design:

RCT Test intervention Celecoxib 200mg 2x/day OR naproxen sodium 220mg 2x/day Comparator intervention(s) placebo Number of participants enrolled:

2528 Duration of follow up: celecoxib 736 dys, naproxen 737 dys, placebo 736 dys Time from risk factor assessment to final cognitive assessment: Up to 3 yrs of annual cognitive assessments 

Age:Median: 74 Range: 70 - 90 Sex: [n (%)] 

Female: 1160 (45.9%)Male: 1368 (54.1%) Race/ethnicity: [n (%)] White 2452 (97.0%) African American 38 (1.5%) Hispanic 18 (0.7%) Other 20 (0.8%) Baseline cognitive status:Non-demented Inclusion criteria: ≥ 70 yo; have at least 1 first-degree relative with AD-like dementia, score satisfactorily on eligibility test battery for excluding cognitive impairment Exclusion criteria:Regularly use NSAIDS (but aspirin use of 81 mg/day allowed) 

Risk factor/exposure 1:RCT with celecoxib, naproxen, placebo Method of assessing risk factor/exposure 1: This is an rct. The nsaid was given to subjects. Covariates/potential confounders adjusted for in analyses:NR Method(s) of assessing cognitive status:change in test scores over time.

Informant interview?:No 

1) Follow-up rate: see comments 2) Important baseline differences: none are obvious 3) Outcome of interest #1 Whether an ITT analysis or if censored after drug terminated,, scores of 3MS were significantly lower in both treatment groups than in placebo. 4) Outcome of interest #2 use of naproxen or celecoxib did not improve cognitive function. Weak evidence fro detrimental effect of naproxen. 

CommentsTrial termincelecoxib 41% terminfollow up, drug, 20% 38% terminfollow up This group dementia in publicationFor RCTs: 1) Baselin2) Valid A

assess

3) Subjec4) Outcom5) Incomp

addres

6) Differen

Can’t T

7) Overall 8) Conflic

insignif

9) Random10) Allocat

adequa
B-168

Study Study Information Participants Risk Factor and 

Outcome Assessment 

Results Comments

Masaki, Losonczy, Izmirlian, et al., 2000 HAAS 

Geographical location: Oahu, Hawaii Setting:Community (some in nursing homes) Study design: Prospective cohort Number of participants enrolled:3385 Duration of follow up:3-5 yr Time from risk factor assessment to final cognitive assessment:3-5 yr for main analyses (sub-group of long term users 11-13 yr) 

Age:Mean (SD): Non-demented 73.9 Demented 78.6 Sex: [n (%)] 

Female 0 (0%) Male: 3385 (100%) Race/ethnicity: [n (%)] NR Baseline cognitive status:Non-demented Inclusion criteria: Men of Japanese ancestry born between 1900 and 1919 who resided on the island of Oahu, Hawaii in 1965 and were participants of the Honolulu Heart Program. Exclusion criteria:NR 

Risk factor/exposure

1:Vit E and C Method of assessing risk factor/exposure 1:Self-report Covariates/potential confounders adjusted for in analyses:Age Educational level Childhood years spent in Japan APOE Hx of stroke Method(s) of assessing cognitive status:NINCDS-ADRDA DSM CASI Informant interview?:Yes 

1) Follow-up rate: 3385/3682 (denominator excludes those thought to be demented at time of nutrition data collection) 91.93%2) Important baseline differences: Nondemented were younger, more education, less time during childhood in Japan Some differences (age) reported are at the time of the dementia diagnosis (not really baseline) 3) Outcome of interest #1No association between AD and vitamin E or C use C w/o E: OR-1.61 (0.67-3.87) E w/o C: OR 0.84 (0.19-3.77) E and C use: OR – 1.81 (0.91-3.62) 

CommentsQuestion 1 Quality assFor observ1) Unbias

cohort? 

2) Selectio

differenYes 

3) Sample 

differen

4) Adequa

cohort? 

5) Validat

ascerta

6) Validat

ascertaYes 

7) Outcom

exposu

8) Adequa9) Comple10) Analys

confou

11) Analytic 

Yes 

Maxwell, Hicks, Hogan, et al., 2005 CSHA 

Geographical location: British Columbia, Prairie Provinces, Ontario, Quebec, Atlantic Provinces, Canada 

Age:Mean (SD): 78.1 (6.8) Sex: [n (%)] 

Female: 572 (64) Male: 322 (36) 

Risk factor/exposure

1:Vit E and C supplements, including multi-vitamins Method of assessing 

1) Follow-up rate: 94/1084 (denominator excludes 698 not followed due to death)2) Important baseline differences: Vitamin users were older, less likely to have hx of heavy smoking, more 

CommentsQuestion 1 This is on a CSHA samrisk of beinincluding th
B-169

Study Study Information Participants Risk Factor and 

Outcome Assessment 

Results Comments

Setting:Community (included residents of institutions) Study design: Prospective cohort Number of participants enrolled:894 Duration of follow up:Approx 5 yrs Time from risk factor assessment to final cognitive assessment:Approx 5 yrs 

Race/ethnicity: [n (%)] 

NR Baseline cognitive status:Non-demented Inclusion criteria: Representative sample of Canadians > 65 yr 

from the 5 regions noted above For present analyses included only those who completed a clinical exam at baseline and were not demented. Those who completed the clinical exam: < 78 on 3MS, 

random sample of those scoring >78 on 3MS, those who could not be screened and all institutionalized subjects Exclusion criteria:NR 

risk factor/exposure

1:Self-report Medical record – institutionalized subjects Covariates/potential confounders adjusted for in analyses:Age Sex Educational level Blood pressure Baseline cognitive status Institutional residence Method(s) of assessing cognitive status:NINCDS-ADRDA DSM Other – Cog decline= decrease > 10 points 

on 3MS from Time 1 to Time 2 Informant interview?:No 

likely to lower serum albumin levels 3) Outcome of interest #1 Cognitive decline: Vit E and C and/or multivitamin use assoc with lower risk of cognitive decline (OR – 0.51, 0.29-0.-0.90) Any vitamin use assoc with lower risk of cognitive decline (OR – 0.57; 0.34-0.93) Vit E alone was not assoc with cognitive decline (OR-0.64 (0.08-5.41) Vit C alone was not assoc with cognitive decline (OR – 0.83 (0.29-2.39) 4) Outcome of interest #2 Any vitamin use not assoc with risk of AD (OR-1.00 (0.53-1.87) 

Source for different for institutionaQuality assFor observ1) Unbias

cohort? 

2) Selectio

differenNo 

3) Sample 

differen

4) Adequa

cohort? 

5) Validat

ascerta

6) Validat

ascertaYes 

7) Outcom

exposu

8) Adequa9) Comple10) Analys

confou

11) Analytic 

Yes 

McMahon, Green, Skeaff, et al., 2006 (New Zealand Homocystei

Geographical location: Dunedin, New Zealand Setting:Community Study design: 

Age:Median: 73 years Sex:

Female: 65 (52%) in placebo group Female: 47 (37%) in vitamin group 

Risk factor/exposure

1:hcy Method of assessing risk factor/exposure 1:Direct measurement 

1) Follow-up rate:  For purposes of analysis – 91.3% in placebo group, 92.0% in vitamin group.  In placebo group, 12 were lost to follow up, and 7% dc’d intervention but stayed in study.  In vitamin group, 11 were lost to 

CommentsQuestion 5 rct in cogni

Quality asse1) Baselin2) Valid A
B-170

Study Study Information Participants Risk Factor and 

Outcome Assessment 

Results Comments

ne) RCT 

Test intervention:  Folate 1000 micrograms per day  Vitamin B12 500 micrograms per day  Vitamin B6 10 milligrams per day Comparator intervention(s): Placebo Number of participants enrolled:  465 assessed for eligibility  276 randomized  253 analyzed Duration of follow up: follow ups done at 1 and 2 yrs. Time from risk factor assessment to final cognitive assessment:2 yrs 

Male: 61 (48%) in placebo group Male: 80 (63%) in vitamin group Race/ethnicity:NR Baseline cognitive status:  didn’t have “suspected dementia”  all but five had mmse > 26, mean baseline mmse > 29 Inclusion criteria:  > 65 years 

Exclusion criteria: Suspected dementia  Taking meds known to interfere with folate metabolism  Taking vitamin supplements containing folic acid, B12, or B6  Being treated for depression  Diabetic  History of stroke or TIAs 

Fasting plasma, only those >13 μmol/l of hcy were eligible Covariates/potential confounders adjusted for in analyses:Sex, education, baseline cognitive scores. Method(s) of assessing cognitive status:change in test scores

Informant interview?:No 

follow up, and 8 dc’d intervention but stayed in study. 2) Important baseline differences: more women and lower cholesterol in the placebo group. 3) Outcome of interest #1 For the combined testing score, the vitamin group was -0.11 std dev scores WORSE than the placebo group. 4) Outcome of interest #2  1 and 2 yrs change scores were given for each test.  The only significant findings in the fully adjusted models was on Trails B for which the mean time to completion was 8% longer in the treatment group (the exponent of the difference between the logtransformed values =1.08; 95% confidence interval1.02 -1.14) 

assess

3) Subjec4) Outcom5) Incomp

addres

6) Differen

Yes 

7) Overall 8) Conflic

insignif

9) Random10) Allocat

adequa

McNeill, Avenell, Campbell, et al., 2007 MAVIS 

Geographical location:6 centers in Northeast Scotland Setting:

Age:Median:  Suppl 72  Placebo 71 Range:  Suppl 68.0 – 76.0 

Risk factor/exposure 1:Single tablet containing 11 vitamins and 5 minerals taken daily for 12 months. 

1) Follow-up rate: Of the 910 participants, over the course of the 1-year study, 12 died, 77 stopped taking their tablets and 44 were lost to follow-up. 

CommentsNone For RCTs: 1) Baselin2) Valid A
B-171

Study Study Information Participants Risk Factor and 

Outcome Assessment 

Results Comments

Trial Clinical – Primary care 

health centers Study design: RCT Test intervention Supplement containing: 800 μg vitamin A, 60 mg vitamin C, 5 μg vitamin D, 10 mg vitamin E, 1.4 mg thiamin, 1.6 mg riboflavin, 18 mg, niacin, 6 mg pantothenic acid, 2 mg pyridoxine, 1 μg vitamin B12, 200 μg folic acid, 14 mg iron, 150 μg iodine, 0.75 mg copper, 15 mg zinc, and 1 mg manganese Comparator intervention(s) placebo Number of participants enrolled:910 Duration of follow up:1 year Time from risk factor assessment to final cognitive assessment:1 year 

 Placebo 68.0 – 76.0 Sex: [n (%)] 

Female: 431 (47.3%) Male: Race/ethnicity: [n (%)] NR Baseline cognitive status: NR Authors state: “we did not exclude any participation on the basis of impaired cognitive function, though those with dementia were unlikely to volunteer or would have been excluded by their doctor.” Inclusion criteria: ≥ 65 yo; had not taken vitamin, mineral, or fish oil supplements within 3 mos of recruitment (1 mo for supplements of water soluble vitamins other than vitamin B12)Exclusion criteria:Did not exclude any participants on basis of impaired cognitive function, though those with dementia were unlikely to volunteer, or would have been excluded by their doctor. 

Method of assessing risk factor/exposure 1:RCT intervention Covariates/potential confounders adjusted for in analyses:NA (RCT) Method(s) of assessing cognitive status:Digit span forward and verbal fluency tests at start and end of intervention period. Informant interview?:No 

Does not appear to be intent-to-treat analysis. Not clear how many participants were included in the final analysis. 2) Important baseline differences: None 3) Outcome of interest #1—Digit span forward No evidence of an effect of supplements 4) Outcome of interest #2—Verbal fluency “No evidence of a beneficial effect on the whole study population but there was weak evidence for a beneficial effect of supplementation in the 2 pre-specified subgroups: 1) age >75 (n=290), mean difference 

2.8 (95% CI: -0.6, 6.2) 2) increased risk of micronutrient deficiency (n=260), mean difference 2.5 (95% CI: -1.0, 6.1) 

assess

3) Subjec

Subjec

4) Outcom

Tell 

5) Incomp

addresapproa

6) Differen

Can’t T

7) Overall 8) Conflic

insignif

9) Random10) Allocat

adequa
B-172

Study Study Information Participants Risk Factor and 

Outcome Assessment 

Results Comments

Mehta, Ott, Kalmijn, et al., 1999 The Rotterdam Study 

Geographical location: Rotterdam, Netherlands Setting:Community Study design: Prospective cohort Number of participants enrolled:6645 Duration of follow up:Average 2.1 (0.8) years. Time from risk factor assessment to final cognitive assessment:Average 2.1 (0.8) years 

Age:Mean (SD): 68.9 (8.6) Sex: [n (%)] 

Female: 3927 (59.1) Male: 2718 (40.9) Race/ethnicity: [n (%)] NR Baseline cognitive status:Non demented Inclusion criteria: >55 yrs of age Residents of Rotterdam Exclusion criteria:Dementia 

Risk factor/exposure

1:Head Trauma Method of assessing risk factor/exposure 1:Self-report Covariates/potential confounders adjusted for in analyses:Age Sex Education Method(s) of assessing cognitive status:NINCDS-ADRDA and DSM Informant interview?:Yes 

1) Follow-up rate: 6645/7046 94.31% (those not included in analyses were missing TBI info) 2) Important baseline differences: Patient who developed AD were older, less educated and more likely to be women at baseline. 3) Outcome of interest #1 The relative risk of AD for head trauma with loss of consciousness after adjusting for age, sex and education was 0.8; 95% CI 0.4-1.9 4) Outcome of interest #2  RR of AD for number of head traumas:  1 head trauma = 0.8 (0.3- 2.0)  >1 head trauma = 1.0 (0.1-7.6) 5) Outcome of interest #3  RR of AD for period between head trauma and interview: 

≤ 10 years= 1.4 (0.3-6.3) 

 >10 years= 0.7 (0.2-1.8) 6) Outcome of interest #4: After controlling for age sex and education, APOE did not interact with head trauma in incident AD. 

CommentsNone Quality assFor observ1) Unbias

cohort? 

2) Selectio

differenYes 

3) Sample 

differen

4) Adequa

cohort? 

5) Validat

ascerta

6) Validat

ascertaYes 

7) Outcom

exposu

8) Adequa9) Comple10) Analys

confou

11) Analytic 

Yes 

Morris, Beckett, Scherr, et al., 1998 

Geographical location: East Boston, MA Setting:

Age: 

Mean (SD): mean range across exposures: 72 -75 Sex: [n (%)] 

Risk factor/exposure

1:Vit E and C supplement use 

1) Follow-up rate: Notes 80% of survivors in selected sample completed f/u 2) Important baseline differences: 

CommentsQuestion 1 No vitamin those who comparison 
B-173

Study Study Information Participants Risk Factor and 

Outcome Assessment 

Results Comments

East Boston Study

Community Study design: Prospective cohort Number of participants enrolled:633 Duration of follow up:4.3 yrs Time from risk factor assessment to final cognitive assessment:4.3 yrs 

Female: range across exposure groups 342-437 (54-69%) Male: 196-291 (31-46%) Race/ethnicity: [n (%)] NR Baseline cognitive status:Non-demented Inclusion criteria: Stratified sample of residents of East Boston age > 65 yr in 1982-83. In 1985-86 fup, the stratified sample for clinical eval was weighted towards those who were older and had greater cog decline on screening measures Exclusion criteria:NR 

Method of assessing risk factor/exposure 1:Self-report – limited to use in previous 2 wks Covariates/potential confounders adjusted for in analyses:Age Sex Educational level Time to FUP Sample weight Method(s) of assessing cognitive status:NINCDS-ADRDA Informant interview?:No 

Vitamin supplement users were more like to have at least some high school education. Vit E users were slightly younger. Multivitamin users more likely to be female and to have more than a H.S. educ 3) Outcome of interest #1Fewer than expected incident AD cases used Vit C (p=0.04) No difference in expected AD incidence and observed incidence among Vit E users (p=0.23) 

rate of AD Quality assFor observ1) Unbias

cohort? those a

2) Selectio

differenYes 

3) Sample 

differen

4) Adequa

cohort? 

5) Validat

ascerta(vitamin 

6) Validat

ascertaPartial. 

7) Outcom

exposu

8) Adequa9) Comple

Yes. Ofup) 

10) Analys

confou

11) Analyti

Partial of AD robserveexposu

Morris, Evans, Bienias, et al., 2004a CHAP 

Geographical location: Chicago, IL Setting:Community 

Age:For AD sample (815): Mean ranged from 71-73.2 across niacin exposure groups 

Risk factor/exposure

1:Niacin Method of assessing risk factor/exposure 

1) Follow-up rate: Difficult to get appropriate numbers 842/1249 new stratified random sample (authors reported 73.95% of survivors completed fup) 

CommentsReports codecline; alsoutcome buQuality ass
B-174

Study Study Information Participants Risk Factor and 

Outcome Assessment 

Results Comments

Study design: Prospective cohort Number of participants enrolled:3718 for cognitive decline 815 for incident AD Duration of follow up:Mean 3.9 yrs (for AD analyses) Says Median 5.5 yrs in abstract (appears to be cognitive decline analyses) Time from risk factor assessment to final cognitive assessment:1041 - 2.7 yrs 3718 – 4.3 yr (these are estimates based on info in other papers) 

Sex: [n (%)] 

NR in a format that is useful Race/ethnicity: [n (%)] 

NR in a format that is useful

Baseline cognitive status:Non-demented Inclusion criteria: Residents of three geographically contiguous neighborhoods on southside of Chicago. Aged >65 yrs 

Exclusion criteria:NR 

1:Self-report Covariates/potential confounders adjusted for in analyses:Age Race Sex Educational level APOE Time interval between assessments Sample weights Vit E Vit C Beta-carotene Multiple vitamin use DM HTN Smoking ETOH use Stroke Heart disease folate Method(s) of assessing cognitive status:NINCDS-ADRDA Other: Cognitive decline on standardized composite measure from all tests-baseline performance incorporated into composite measure Informant interview?:

4324/6158 completed diet info and 2 cognitive time points (authors reported was 87% of surviving members)- some excluded from group because of invalid diet data 2) Important baseline differences: Lowest quintile of total niacin intake and niacin food intake compared to higher quintiles: higher percent of females, blacks, ind w/ stroke, and ind with low food intake of Vit E Lowest quintile of total niacin intake more likely to have APOE e4 allele Highest quintile of both total and food intake of niacin had higher prevalence of DM 3) Outcome of interest #1 Higher quintiles of total Niacin from supplements (p=0.04), from food (p=0.006), from tryptophan (p=0.03) and from niacin equivalents (p=0.01) associated with reduced risk of AD 4) Outcome of interest #2 Food intake of niacin had a linear effect on cognitive decline, but in fully adjusted model did not reach significance (p=0.12). When those with stroke or MI (p=0.002) or low cognitive scores (p=0.03) were excluded there was an sig linear association. 

For observ1) Unbias

cohort? 

2) Selectio

differenfactors

3) Sample 

differen

4) Adequa

cohort? 

5) Validat

ascerta

6) Validat

ascertaYes 

7) Outcom

exposu

8) Adequa

9) Comple10) Analys

confou

11) Analytic 

Yes 
B-175

Study Study Information Participants Risk Factor and 

Outcome Assessment 

Results Comments

Yes –says informant interviews for the cognitively impaired, but this differs from all other descriptions of this study 

Morris, Evans, Bienias, et al., 2003a CHAP 

Geographical location: Chicago, IL Setting:Community Study design: Prospective cohort Number of participants enrolled:815 Duration of follow up:Mean 3.9 yrs Time from risk factor assessment to final cognitive assessment:Mean 2.3 yr 

Age:Range: 65-94 Sex: [n (%)] 

Female: 497 (61%) Male: 318 (39%) Race/ethnicity: [n (%)] AA: 424 (52%) White and other: 391 (48%)Baseline cognitive status:Non-demented Inclusion criteria: Residents of three geographically contiguous neighborhoods on southside of Chicago. Aged >65 yrs 

Exclusion criteria:NR 

Risk factor/exposure

1:fat intake Method of assessing risk factor/exposure 1:Self-report Covariates/potential confounders adjusted for in analyses:Age Race Sex Educational level APOE Method(s) of assessing cognitive status:NINCDS-ADRDA Informant interview?:Yes –says informant interviews for the cognitively impaired, but this differs from all other descriptions of this study 

1) Follow-up rate: reported that 75.6% of surviving stratified sample participated (n = 842) then 815/842 had complete diet info 2) Important baseline differences: Higher % of women and vit C users in lowest quintile of intake for both saturated and w-6 polyunsaturated fat Black more likely to be in lowest quintile of saturated fat intake and highest quintile of w-6 polyunsaturated fat intake Ind with APOE e4 mose likely to be in the lowest quintile of saturated fat intake 3) Outcome of interest #1 Saturated fat: highest quintile associated w/ increased risk of AD: RR -2.2 (1.1-4.7) Trans-unsaturated fat: Quintiles 2-5 higher risk of AD, but only quintiles 2 (2.4 ;1.1- 5.3) and 3 (2.9; 1.2-7.2) significant w-6 polyunsaturated fat: Quintile 5 had lower risk of AD (0.3; 0.1-0.8) Monounsaturated fat, total fat and 

CommentsQuestion 1 Used multivadjustment Quality assFor observ1) Unbias

cohort? 

2) Selectio

differenYes 

3) Sample 

differen

4) Adequa

cohort? 

5) Validat

ascerta

6) Validat

ascertaYes 

7) Outcom

exposu

8) Adequa9) Comple10) Analys

confou

11) Analytic 

Yes 
B-176

Study Study Information Participants Risk Factor and 

Outcome Assessment 

Results Comments

dietary cholesterol not associated with AD Animal fat and vegetable fat not associated with AD in multivariable models. But when vegetable fat controlled for other dietary fat, there was a linear trend (p = 0.002) for protection against AD (although the RR for ind quintiles was not significant) 

Morris, Evans, Bienias, et al., 2002a CHAP 

Geographical location: Chicago, Illinois Setting:Community Study design: Prospective cohort Number of participants enrolled:815 Duration of follow up:3.9 yrs Time from risk factor assessment to final cognitive assessment:2.3 yrs 

Age:Mean (SD): 73.3 (9.7) Sex: [n (%)] 

Female: 505 (62) Male: 310 (38) Race/ethnicity: [n (%)] AA: 419 (51.4) White and other:396 (48.6) Baseline cognitive status:Non-demented Inclusion criteria: Residents of three geographically contiguous neighborhoods on southside of Chicago. Aged >65 yrs 

Exclusion criteria:None 

Risk factor/exposure

1:Antioxidant-vitamin C, E, beta-carotene Method of assessing risk factor/exposure 1:Self-report Covariates/potential confounders adjusted for in analyses:Age Race Sex Educational level APOE Time interval to fup Method(s) of assessing cognitive status:NINCDS-ADRDA Informant interview?:Yes –says informant 

1) Follow-up rate:reported that 75.6% of surviving stratified sample participated (n = 842) then 815/842 had complete diet info 2) Important baseline differences: For each antioxidant, ind in the upper quintiles to total intake were more likely to be white, had more education, had higherh intake of other antioxidants than ind in lower quintiles Ind with high food intake of Vit E tended to be men and to have a higher intake of fat and beta carotene, and a lower intake of Vit C Ind with high food intake of Vit C tended to be female and to have a lower intake of Vit E and total fat Ind in lowest quintile of beta-carotene intake more likely to be black and have an APOE e4 allele compared to upper quintiles 

CommentsQuestion 1 In descriptinoted that 9collected wassessmenbecame no1.02) Quality assFor observ1) Unbias

cohort? 

2) Selectio

differenYes 

3) Sample 

differen

4) Adequa

cohort? 

5) Validat

ascerta

6) Validat

ascertaYes 

7) Outcom

exposu

8) Adequa
B-177

Study Study Information Participants Risk Factor and 

Outcome Assessment 

Results Comments

interviews for the cognitively impaired, but this differs from all other descriptions of this study 

3) Outcome of interest #1 Vit E: Food intake only (not food and supplement): highest quintile associated with lower risk of AD (RR -0.30;0.10-0.92); trend for all quintiles p = 0.05 Food and supplements – not significant Vit C: Intake of food only – overall not sig assoc with AD. Trends do not approach significance. Quintile 4 only is associated with reduced risk of AD (RR-0.37; 0.17-0.82) Intake of food and supplements not significant Beta-carotene – neither intake of food only or food plus supplements were significantly assoc with AD 4) Outcome of interest #2 Vit E intake from food: APOE e4 negatives had reduced incidence of AD among Quintiles 3, 4, and 5 (Quintile 5 –RR-0.17; 0.06-0.47) In APOE e4 positives, Vit E not protective against AD. 

9) Comple10) Analys

confou

11) Analytic 

Yes 

Morris, Evans, Bienias, et al., 2003b CHAP 

Geographical location: Chicago, Illinois Setting:Community Study design: Prospective cohort 

Age:Range: 65-94 Sex: [n (%)] 

Female: 497(61) Male: 318 (39) Race/ethnicity: [n (%)] AA 505 (62) 

Risk factor/exposure

1:fish and n-3 fatty acids, DHA, EPA, linolenic Method of assessing risk factor/exposure 1:Self-report 

1) Follow-up rate: reported that 75.6% of surviving stratified sample participated (n = 842) then 815/842 had complete diet info 2) Important baseline differences: Compared to lowest quintile of n-3 polyunsaturated fat intake, those in 

CommentsQuestion 1 Quality assFor observ1) Unbias

cohort? 

2) Selectio

differen
B-178

Study Study Information Participants Risk Factor and 

Outcome Assessment 

Results Comments

Number of participants enrolled:815 Duration of follow up:3.9 yrs Time from risk factor assessment to final cognitive assessment:2.3 yrs 

White 310 (38) Baseline cognitive status:Non-demented Inclusion criteria: Residents of three geographically contiguous neighborhoods on southside of Chicago. Aged >65 yrs 

Exclusion criteria:NR 

Covariates/potential confounders adjusted for in analyses:Age Race Sex Educational level APOE Time interval to fup Method(s) of assessing cognitive status:NINCDS-ADRDA Informant interview?:Yes –says informant interviews for the cognitively impaired, but this differs from all other descriptions of this study 

highest quintile group were more likely to be male, to have more education, to have a hx of HTN, and to have lower consumption of Vit E and all types of fat 3) Outcome of interest #1Compared to ind who never ate fish, those who did eat fish had lower risk of AD (RR for > 2/wk fish: 0.4 (0.2-

0.9). Trend p =0.07 4) Outcome of interest #2 N-3 fatty acid: highest quintile associated with reduced risk of AD (RR=0.4;0.1-0.9); trend p = 0.01 DHA: two highest quintiles associated with reduced risk of AD (RR for highest quintile=0.03; 0.1-0.9); trend p = 0.02 EPA intake not associated with AD risk Linolenic intake not associated with AD risk 

Yes 

3) Sample 

differen

4) Adequa

cohort? 

5) Validat

ascerta

6) Validat

ascertaYes 

7) Outcom

exposu

8) Adequa9) Comple10) Analys

confou

11) Analytic 

Yes 

Morris, Evans, Bienias, et al., 2005 CHAP 

Geographical location: Chicago, Illinois Setting:Community Study design: Prospective cohort Number of participants enrolled:

Age:Mean (SD):Mean range across quintiles of folate exp: 74.0-74.9 Sex: [n (%)] 

Female: Mean range of % across quintiles of folate exp: 59-68 Male: Race/ethnicity: [n (%)] 

Risk factor/exposure

1:Folate and B12 Method of assessing risk factor/exposure 1:Self-report Covariates/potential confounders adjusted for in 

1) Follow-up rate:

4390/6158 completed diet info and 2 cognitive time points (authors reported was 89% of surviving members)- excluded 677 from group because of invalid diet data (does not add up to 3718) 2) Important baseline differences: High intake total folate had more years education, higher baseline cognitive scores, greater 

CommentsQuestion 2 Quality assFor observ1) Unbias

cohort? 

2) Selectio

differenYes 

3) Sample 

differen
B-179

Study Study Information Participants Risk Factor and 

Outcome Assessment 

Results Comments

3718 Duration of follow up:3718 ind –median 5.5 yrs 1964 ind – median 6.3 yrs Time from risk factor assessment to final cognitive assessment:3718 ind -4.3 yr 1964 ind – 5.1 yr 

Mean range of % across quintiles of folate exp:43-75 Baseline cognitive status:Non-demented Inclusion criteria: Residents of three geographically contiguous neighborhoods on southside of Chicago. Aged >65 yrs 

Exclusion criteria:None 

analyses:Age Race Sex Educational level Time interval between assessments Vitamin E Vitamin C Multivitamin Method(s) of assessing cognitive status: Other – Cognitive 

decline on standardized composite measure from all tests-baseline performance incorporated into composite measure (this was noted in previous article but not in this article) Informant interview?:No 

consumption of vitamin E and C; less likely to have heart disease or HTN 3) Outcome of interest #1Total intake of folate: upper to quintiles declined slightly faster than lowest quintile (p value for 5th quintile 

=0.002; trend p = <.001) Folate intake from food:higher quintiles generally declined slightly faster than lowest quintiles(p value for 5th quintile = 0.02; trend p = .04) 

4) Adequa

cohort? 

5) Validat

ascerta

6) Validat

ascertaYes 

7) Outcom

exposu

8) Adequa9) Comple10) Analys

confou

11) Analytic 

Yes 

Morris, Evans, Bienias, et al., 2002b CHAP 

Geographical location: Chicago, Illinois Setting:Community Study design: Prospective cohort Number of participants enrolled:

Age:Mean (SD): 73.9 Sex: [n (%)] 

Female: 1791 (62) Male: 1098 (38) Race/ethnicity: [n (%)] AA: 1594 (55%) White: 1295 (45%) Baseline cognitive 

Risk factor/exposure

1:Vitamin E and C Method of assessing risk factor/exposure 1:Self-report Covariates/potential confounders adjusted for in 

1) Follow-up rate: 4376/ 4983 completed cog screen F/U; total of 1486 excluded because no or invalid diet data, or timing of data collection inappropriate 2) Important baseline differences: Vit E supplement users had more education and higher intake of antioxidant nutrients Lowest quintile of Vit E intake from food had higher ETOH use, were 

CommentsQuestion 2 Quality assFor observ1) Unbias

cohort? 

2) Selectio

differenYes 

3) Sample 

differen
B-180

Study Study Information Participants Risk Factor and 

Outcome Assessment 

Results Comments

2889 Duration of follow up:3.2 yrs (range 1.8-5.9 yr) Time from risk factor assessment to final cognitive assessment:1.8 (0.7) yrs 

status:Non-demented Inclusion criteria: Residents of three geographically contiguous neighborhoods on southside of Chicago. Aged >65 yrs 

Exclusion criteria:None 

analyses:Age Race Sex Educational level Total energy from calories Smoking ETOH use Time between assessments Method(s) of assessing cognitive status: Other – Cognitive decline on standardized composite measure from all tests-baseline performance incorporated into composite measure Informant interview?:No 

more likely to be smokers. Black participants had higher intake of Vit E from food, but were less likely to use either Vit E supplements or multi-vitamins 3) Outcome of interest #1Vitamin E total intake:highest quintile showed less decline ( p=0.05) used ‘multivariable alone’ model Vitamin C total intake – not associated with cognitive decline 4) Outcome of interest #2 Vitamin E food intake: Highest two quintiles associated with less decline (p <0.05) Vitamin C food intake: not associated with cognitive decline 

4) Adequa

cohort? 

5) Validat

ascerta

6) Validat

ascertaYes 

7) Outcom

exposu

8) Adequa9) Comple10) Analys

confou

11) Analytic 

Yes 

Morris, Evans, Bienias, et al., 2004b CHAP 

Geographical location: Chicago, Illinois Setting:Community Study design: Prospective cohort Number of participants enrolled:2560 

Age:Mean (SD): Mean range across fat intake quintiles: 73.7-74.3 Sex: [n (%)] 

Female: mean % range across fat intake quintiles 46.4-76.0 Male: Race/ethnicity: [n (%)] AA: 1587 (62) 

Risk factor/exposure

1:fat intake Method of assessing risk factor/exposure 1:Self-report Covariates/potential confounders adjusted for in analyses:

1) Follow-up rate: 4398/4930 completed at least one cognitive follow-up; others excluded due to no diet data, invalid diet data, inappropriate timing of diet data collection, or hx of stroke or MI resulting in change of diet 2) Important baseline differences: Ind in top quintile of both saturated and trans-unsaturated fat intake were more likely to be male, to be white, to have higher intake levels of all other 

CommentsQuestion 2 Quality assFor observ1) Unbias

cohort? 

2) Selectio

differenYes 

3) Sample 

differen

4) Adequa
B-181

Study Study Information Participants Risk Factor and 

Outcome Assessment 

Results Comments

Duration of follow up:Median 5.6 yr for 2560 ind Median 6.3 yr for 1397 ind Time from risk factor assessment to final cognitive assessment:4.6 yr for 2560 ind 

White: 973 (38) Baseline cognitive status:Non-demented Inclusion criteria: Residents of three geographically contiguous neighborhoods on southside of Chicago. Aged >65 yrs 

Exclusion criteria:None 

Age Race Sex Educational level Total energy from calories Smoking ETOH use Time between assessments HTN Vitamin C Vitamin E Method(s) of assessing cognitive status: Other – Cognitive decline on standardized composite measure from all tests-baseline performance incorporated into composite measure Informant interview?:No 

types of fat, and higher prevalence of smoking. Those with high intake of saturated fat were more likely to have higher baseline cognitive score and hx of HTN. Those with high intake of trans-unsaturated fat tended to have low consumption of alcohol. 3) Outcome of interest #1Higher intake of saturated fat (trend p=0.04) and trans-unsaturated fat (trend p = 0.07) were linearly associated with greater decline in cognitive score over 6 yrs. When excluding individuals who changed pattern of fat intake in last 10 years and/or those scoring in lowest 15%, effect became stronger. Total fat, vegetable and animal fat, and cholesterol not associated with cognitive change 

cohort? 

5) Validat

ascerta

6) Validat

ascertaYes 

7) Outcom

exposu

8) Adequa9) Comple10) Analys

confou

11) Analytic 

Yes 

Morris, Evans, Schneider, et al., 2006 CHAP 

Geographical location: Chicago, Illinois Setting:Community Study design: Prospective cohort Number of 

Age:Mean (SD): range of means across folate quintiles: 71.7-73.3 Sex: [n (%)] 

Female: Male: % range across folate quintiles: 34.4-43.1 

Risk factor/exposure

1:Vitamins B6 and B12, folate Method of assessing risk factor/exposure 1:Self-report Covariates/potential 

1) Follow-up rate: Can’t determine from info provided – combined 2 waves of incidence data 2) Important baseline differences: High total intake of Vit B6, B12 and folate were associated with being younger, white, more education, greater participation in cognitive activities, not having an APOE e4 allele, and higher intake of Vit E and 

CommentsQuestion 1 Quality assFor observ1) Unbias

cohort? 

2) Selectio

differenYes 

3) Sample 
B-182

Study Study Information Participants Risk Factor and 

Outcome Assessment 

Results Comments

participants enrolled:1041 Duration of follow up:Median 3.9 yr Time from risk factor assessment to final cognitive assessment:2.7 yr 

Race/ethnicity: [n (%)] 

AA: % range across folate quintiles: 34.6-68.4 Baseline cognitive status:Non-demented Inclusion criteria: Residents of three geographically contiguous neighborhoods on southside of Chicago. Aged >65 yrs 

Exclusion criteria:None 

confounders adjusted for in analyses: [delete any from the list below that do not apply and add items as needed] Age Race Sex Educational level Period of observation APOE Vitamin E Niacin Method(s) of assessing cognitive status:NINCDS-ADRDA Informant interview?:Yes –says informant interviews for the cognitively impaired, but this differs from all other descriptions of this study 

niacin. High intake of B-12 was associated with higher intake of saturated fats. 3) Outcome of interest #1Using nutrient adjusted models comparing highest quintile to lowest quintile: Neither total folate (OR=1.6; 0.5-5.2) or folate from food (1.8; 0.8-4.1) was associated risk of AD. Neither total vitamin B-12 (0.6; 0.2-1.6) or vitamin B-12 from food (1.0; 0.3-2.7) was associated with risk of AD. Neither total vitamin B-6 (0.7; 0.2-2.4) or vitamin B-6 from food (0.7; 0.3-1.4) was associated with risk of AD. 

differen

4) Adequa

cohort? 

5) Validat

ascerta

6) Validat

ascertaYes 

7) Outcom

exposu

8) Adequa9) Comple

Can’t T

10) Analys

confou

11) Analytic 

Yes 

Morris, Evans, Tangney, et al., 2006a CHAP 

Geographical location: Chicago, IL, USA Setting:Community Study design: Prospective cohort Number of participants enrolled:

Age:Mean (SD): Mean range across copper intake quintiles: 74.0-74.8 Sex: [n (%)] 

Female: Mean % range across copper intake quintiles: 57.7 -67.1 Male: 

Risk factor/exposure

1:Copper, zinc, iron, saturated and trans fats Method of assessing risk factor/exposure 1:Self-report Covariates/potential 

1) Follow-up rate: Authors note 88% of survivors participated in data collection; additional subjects were excluded because of invalid dietary data 2) Important baseline differences: Ind with high copper intake were more likely to have healthy lifestyle behaviors and higher baseline cognitive scores 

CommentsQuestion 2 Quality assFor observ1) Unbias

cohort? 

2) Selectio

differenYes 

3) Sample 

differen
B-183

Study Study Information Participants Risk Factor and 

Outcome Assessment 

Results Comments

3718 Duration of follow up:Median 5.5 yrs Time from risk factor assessment to final cognitive assessment:4.3 yr 

Race/ethnicity: [n (%)] 

AA: Mean % range across copper intake quintiles: 48.5-69.5 Baseline cognitive status:Non-demented Inclusion criteria: Residents of three geographically contiguous neighborhoods on southside of Chicago. Aged >65 yrs 

Exclusion criteria:None 

confounders adjusted for in analyses:Age Race Sex Educational level Cognitive activities Physical activities ETOH use Stroke Heart disease HTN DM Vitamin E Vitamin C Niacin Folate Method(s) of assessing cognitive status: Other – Cognitive decline on standardized composite measure from all tests-baseline performance incorporated into composite measure Informant interview?:No 

3) Outcome of interest #1Neither total intake or food intake of copper, zinc or iron were associated with cognitive decline 4) Outcome of interest #2 Total copper intake combined with diet high in saturated and trans fat was associated with faster cognitive decline (p<0.001) 

4) Adequa

cohort? 

5) Validat

ascerta

6) Validat

ascertaYes 

7) Outcom

exposu

8) Adequa9) Comple10) Analys

confou

11) Analytic 

Yes 

Morris, Evans, Tangney, et al., 2006b CHAP 

Geographical location: Chicago, IL, USA Setting:Community 

Age:Mean (SD): 73.6 Range: 65-102 Sex: [n (%)] 

Female: 2305 (62) Male: 1413 (38) 

Risk factor/exposure

1:fruit and vegetable Method of assessing risk factor/exposure 1:

1) Follow-up rate: Authors report 92.2% fup rate at 1st

fup and 89.8% fup rate at 2nd fup. 

Additional ind were excluded because of invalid diet data 2) Important baseline differences: 

CommentsQuestion 2 Quality assFor observ1) Unbias

cohort? 
B-184

Study Study Information Participants Risk Factor and 

Outcome Assessment 

Results Comments

Study design: Prospective cohort Number of participants enrolled:3,718 Duration of follow up:3718 ind –median 5.5 yrs 1964 ind – median 6.3 yrs Time from risk factor assessment to final cognitive assessment:3718 ind -4.3 yr 1964 ind – 5.1 yr 

Race/ethnicity: [n (%)] 

AA: 2246 (60.4) White 1472 (39.6) Baseline cognitive status:Non-demented Inclusion criteria: Residents of three geographically contiguous neighborhoods on southside of Chicago. Aged >65 yrs 

Exclusion criteria:None 

Self-report Covariates/potential confounders adjusted for in analyses:Age Race Sex Educational level Cognitive activities Physical activities ETOH use Method(s) of assessing cognitive status: Other – Cognitive decline on standardized composite measure from all tests-baseline performance incorporated into composite measure Informant interview?:No 

Ind with high intakes of fruits and vegetables were likely to be female, to be white, have more years of education, and higher physical activity level. Ind with high intake of fruit more likely to have a cardiovascular condition. 3) Outcome of interest #1Higher intake of vegetables associated with less cognitive decline (trend p = 0.04). Higher intake of fruit not associated with rate of cognitive decline (trend p = 0.55) 4) Outcome of interest #2 High intake of green leafy vegetables showed strongest association with reduction in cognitive decline (trend p = 0.03) 

2) Selectio

differenYes 

3) Sample 

differen

4) Adequa

cohort? 

5) Validat

ascerta

6) Validat

ascertaYes 

7) Outcom

exposu

8) Adequa9) Comple10) Analys

confou

11) Analytic 

Yes 

Morris, Evans, Tangney, et al., 2005 CHAP 

Geographical location: Chicago,IL, USA Setting:Community Study design: Prospective cohort Number of participants enrolled:

Age:Mean (SD): range across quintiles of alpha-tocopherol: 74.1-74.8 Sex: [n (%)] 

Female: % range across quintiles of alpha-tocopherol: 57.6-68 Male: % range across 

Risk factor/exposure

1:tocopherol forms Method of assessing risk factor/exposure 1:Self-report Covariates/potential confounders adjusted for in 

1) Follow-up rate: NR in format that is useful. Combined incident cases from multiple waves of data collection. 2) Important baseline differences: Ind with high intake of alphatocopherols had more education, higher intake of Vit C and n-3 fatty acid DHA. Ind with high intake of gamma tocopherol had lower intake of Vit C, higher intake of saturated 

CommentsQuestion: QQuality assFor observ1) Unbias

cohort? 

2) Selectio

differenYes 

3) Sample 

differen
B-185

Study Study Information Participants Risk Factor and 

Outcome Assessment 

Results Comments

1041 –AD analyses 3718- cognitive decline analyses Duration of follow up:1041 – median 3.9 yr 3718 – median 5.5 yr (from other study) Time from risk factor assessment to final cognitive assessment:1041 - 2.7 yrs 3718 – 4.3 yr (these are estimates based on info in other papers) 

quintiles of alphatocopherol: 32-42.4 Race/ethnicity: [n (%)] 

AA: % range across 

quintiles of alphatocopherol: 56.6-65.4

Other: % range across quintiles of alphatocopherol: 34.6-43.4 Baseline cognitive status:Non-demented Inclusion criteria: Residents of three geographically contiguous neighborhoods on southside of Chicago. Aged >65 yrs 

Exclusion criteria:None 

analyses:Age Race Sex Educational level APOE Cognitive activities Observation interval Saturated fat Trans unsaturated fat DHA Vitamin C Method(s) of assessing cognitive status:NINCDS-ADRDA Other – Cognitive decline on standardized composite measure from all tests-baseline performance incorporated into composite measure Informant interview?:No (Does not say used informant and based on my knowledge of methods did not use informant. But many other of their articles say used Informant for the cognitively impaired). 

and trans unsaturated fats. 3) Outcome of interest #1Lower AD risk associated with high intake of: Vit E (RR=0.74; 0.62-0.88) Gamma-tocopherol (RR=0.60; 0.41-0.88) Delta-tocopherol (RR=0.75; 0.58-0.96) Alpha-tocopherol equivalents (RR=0.56; 0.32-0.98) 4) Outcome of interest #2 Slower rate of cognitive decline associated with high intake of: Vit E (p=0.0003) Alpha tocopherol (p=0.01) Gamma-tocopherol (p=0.03) Alpha-tocopherol equivalents (p=0.005) 

4) Adequa

cohort? 

5) Validat

ascertaFood fr

6) Validat

ascertaYes 

7) Outcom

exposu

8) Adequa9) Comple10) Analys

confou

11) Analytic 

Yes 

Morris, Scherr, 

Geographical location: 

Age:Mean (SD): 72.2 

Risk factor/exposure

1:

1) Follow-up rate: Of those sampled 97% agreed to 

CommentsCalled non 
B-186

Study Study Information Participants Risk Factor and 

Outcome Assessment 

Results Comments

Hebert, et al., 2001 Boston EPESE 

Boston, MA Setting:Community Study design: Prospective cohort Number of participants enrolled:634 Duration of follow up: bp reported mean of 13.6 years before dx and 4.5 yrs before dx Time from risk factor assessment to final cognitive assessment:NR 

Range: ≥ 65 Sex: [n (%)] 

Female: 402 (63.4%) Male: 232 (36.6%) Race/ethnicity: [n (%)] NR Baseline cognitive status:Non-demented Inclusion criteria: ≥ 65 years Participating in the East Boston EPESE study Free of AD at baseline Exclusion criteria:NR 

htn Method of assessing risk factor/exposure 1:Self-report Direct measurement Risk factor/exposure 2:antihypertensives Method of assessing risk factor/exposure 2:pill bottle inspection Covariates/potential confounders adjusted for in analyses:Age, Sex Educational level Method(s) of assessing cognitive status:NINCDS-ADRDA Informant interview?:No 

participate 426 out of 634 (67%) had blood pressure measurements at the end of 6 years and this was the sample included in the analysis. 2) Important baseline differences: Those with sbp > 160 were older, 

more likely to have cv dz including htn cva, heart dz, dm 3) Outcome of interest #1 no association between sbp measured 13 yrs before dx OR 1.03 /10 mmHg (0.80 – 1.32) 4) Outcome of interest #2 inverse association between sbp measured 4 yrs before dx OR 0.82/10mmHg (0.72 – 0.95) 

memory pesubjects. MQuality assFor observ1) Unbias

cohort? 

2) Selectio

differenYes 

3) Sample 

differen

4) Adequa

cohort? 

5) Validat

ascerta

6) Validat

ascertaYes 

7) Outcom

exposu

8) Adequa9) Comple10) Analys

confou

11) Analytic 

Yes 

Muller, Tang, Schupf, et al., 2007 WHICAP 

Geographical location: Northern Manhattan, NY, USA Setting:Community 

Age:Mean (SD): 76.1 (6.0) Sex: [n (%)] 

Female: 1234 (67.3) Male: 599 (32.7) Race/ethnicity: [n (%)] 

Risk factor/exposure

1:Metabolic syndrome Method of assessing risk factor/exposure 1:Self-report for diabetes 

1) Follow-up rate: 1833/2210 (denominator are those with labs done who were not demented at baseline)2) Important baseline differences: Those with MS were less educated, smoked more, more likely to be 

CommentsQuestion 1 Quality assFor observ1) Unbias

cohort? 

2) Selectio
B-187

Study Study Information Participants Risk Factor and 

Outcome Assessment 

Results Comments

Study design: Prospective cohort Number of participants enrolled:1,833 Duration of follow up:4.4 (2.5) yrs Time from risk factor assessment to final cognitive assessment:4.4 (2.5) yrs 

Hispanic: 720 (39.3) AA: 565 (30.8) White: 548 (29.9) Baseline cognitive status:Non-demented Inclusion criteria: Two related cohorts drawn from probability samples of Medicare recipients, aged > 65 residing in Northern Manhattan. One of the two cohorts excluded individuals who selfreported prevalent dementia. Current analyses limited to subset with assessment of lipid levels. Exclusion criteria:NR 

when insulin level not available (or use of diabetes medication) Direct measurement ( for insulin, only available on 997 subjects) Covariates/potential confounders adjusted for in analyses:Age Race Sex Educational level APOE Smoking Cohort drawn from Method(s) of assessing cognitive status:NINCDS-ADRDA DSM Informant interview?:No 

female, more likely to be Hispanic. (Table 2 says the MS were younger and that female was not significant, but the text states differently). 3) Outcome of interest #1Metabolic syndrome (NCEP-ATPIII criteria) was not associated with increased risk of AD (HR: 0.9; 95% CI: 0.6-1.3) n= 1833 4) Outcome of interest #2 Metabolic syndrome (EGIRI criteria) was not associated with increased risk of AD (HR: 1.2; 95% CI: 0.6-2.5) n= 542 

differenYes 

3) Sample 

differen

4) Adequa

cohort? 

5) Validat

ascerta

6) Validat

ascertaYes 

7) Outcom

exposu

8) Adequa9) Comple10) Analys

confou

11) Analytic 

Yes 

MunizTerrera, Matthews, Dening, et al., 2009 Cambridge City over 75s Cohort Study 

Geographical location: Cambridge, UK Setting:Clinical – Primary Care Practices Study design: Prospective cohort 

Age:Range:  75-84: 1719 (84%)  85+: 334 (16%) Sex: [n (%)] 

Female: 1328 (65%0 Male: 725 (35%) Race/ethnicity:

Risk factor/exposure 1:Education (left school before or after the age of 14) Profession (manual or non-manual) Married vs. not ever 

1) Follow-up rate: 1st f/u: 1161/2053 (57%) 2nd f/u: 647/2053 (32%) 

3rd f/u: 304/2053 (15%) 

2) Important baseline differences: N/A 3) Outcome of interest #1Rate of decline of MMSE score over 

CommentsQuestion 2 Quality assFor observ1) Unbias

cohort? among patients 

2) Selectio
B-188

Study Study Information Participants Risk Factor and 

Outcome Assessment 

Results Comments

Number of participants enrolled:2053 Duration of follow up:Three f/u visits at 2, 7, & 9 yrs after baseline assessment Time from risk factor assessment to final cognitive assessment:Average of 2, 7, & 9 yrs 

NR Baseline cognitive status:Non-demented Inclusion criteria: Age >85 in 1985 and 

registered at one of 6 primary care practices in the Cambridge City area. Exclusion criteria:MMSE <24 on an inhome screening evaluation. 

married Method of assessing risk factor/exposure 1:Self-report Covariates/potential confounders adjusted for in analyses:Age Sex Educational level Profession Marital status Baseline MMSE Method(s) of assessing cognitive status: MMSE as part of a detailed clinical interview. Informant interview?:No 

9 years (SE) Left school prior to age 14: 0.01 (0.05) Non-manual profession: 0.05 (0.06) Married: 0.01 (0.05) (Note: none of the above rates of decline reached statistical significance at the p<0.05 level) 

differenCan’t T

3) Sample 

differen

4) Adequa

cohort? 

5) Validat

ascerta

6) Validat

ascertaYes 

7) Outcom

exposu

8) Adequa9) Comple

(15% reassess

10) Analys

confou

11) Analytic 

No (ratscore ogiven lobe the 
B-189

Study Study Information Participants Risk Factor and 

Outcome Assessment 

Results Comments

Ngandu, von Strauss, Helkala, et al., 2007 CAIDE study North Karelia Project FINMONICA study 

Geographical location: Kuopio & Joensuu, Finland Setting:Community Study design: Prospective cohort Number of participants enrolled:1449 Duration of follow up:Mean 21 yrs (4.9) Time from risk factor assessment to final cognitive assessment:Mean 21 yrs (4.9) 

Age:Midlife evaluation:

Mean (SD): 50.6 (6.0) Late-life evaluation:

Mean (SD): 71.6 (4.1) Sex:Female: 900 (62.1%) Male: 549 (37.9%) Race/ethnicity:NR Baseline cognitive status:NR, but unlikely to be impaired at baseline in midlife Inclusion criteria: Participants of one of 4 separate samples (North Karelia Project and the FINMONICA study). lived in two geographically defined areas. Exclusion criteria:NR 

Risk factor/exposure 1:education Method of assessing risk factor/exposure 1:Self-report at midlife evaluation. 3 categories: 1) low (<5 yrs) 

2) medium (6-8 yrs) 3) >9 yrs 

Risk factor/exposure 2:Method of assessing risk factor/exposure 2:Covariates/potential confounders adjusted for in analyses:Model 1:Age Sex F/u time Community of residence SES variables Living arrangement Midlife vascular conditions Midlife physical activitysmoking APOE 

1) Follow-up rate: 1449/2000 (72.5%) participated in the first phase of re-examination. Exclusions: 40 didn’t come to 2nd

evaluation, 21 had missing data on education, for a total analytical sample of 1388 of 2000 (69.4%) 2) Important baseline differences: Those with fewer years of education were older; were more likely to have lower income, were more likely to have occupation with more physical activity, more likely to have higher blood pressure and higher cholesterol, and more likely to have higher BMI 3) Outcome of interest #161 incident cases of dementia, of which 48 had AD. Total # of dementia cases increased to 117 when patient records of nonparticipants reviewed (# of additional AD cases from record reviews not reported). It appears results reported were based on the 48 AD. 4) Outcome of interest #2 Education associated with risk of dementia in a dose-dependent manner. With < 5 yrs of education as the 

reference, crude OR (95% CI): 

AD:

CommentsNone Quality assFor observ1) Unbias

cohort? 

2) Selectio

differenYes 

3) Sample 

differen

4) Adequa

cohort? 

5) Validat

ascerta

6) Validat

ascertaPartial 

7) Outcom

exposu

8) Adequa9) Comple10) Analys

confou

11) Analytic 

Yes 
B-190

Study Study Information Participants Risk Factor and 

Outcome Assessment 

Results Comments

late-life diseases depressive symptoms. Method(s) of assessing cognitive status:Screening with MMSE  (screen + = MMSE scores < 24) 

NINCDS-ADRDA DSM-IV Informant interview?:No 

1) 6-8 yrs of education: OR=0.49 (0.24, 1.00) 2) > 9 yrs: OR=0.15 (0.05, 0.40) 

Similar adjusted ORs. Authors conclude: none of the covariates were significant in the models, so the effect of education appears to be independent of other risk factors for dementia. 5) Outcome of interest #3—APOE APOE did not modify the association, but the risk of dementia and AD was very low among APOE noncarriers with high education. 

Nickelson, Lufkin, Riggs, et al., 1998 

Geographical location:Rochester, MN & Scottsdale, AZ Setting:Clinical – Mayo Clinics Study design: RCT Test intervention: raloxifene 60 mg or 120 mg Comparator intervention(s): placebo Number of participants enrolled:143 

Age:Mean (SD): 68.4 Range: 51-76 Sex: [n (%)] 

Female: 143 (100%) Male: 0 (0%) Race/ethnicity: [n (%)] NR Baseline cognitive status:Not stated, but baseline testing indicates good fct Inclusion criteria: Good health except for osteoporosis, free of any serious acute or chronic medical 

Risk factor/exposure

1:Raloxifene 60 or 120mg vs placebo Method of assessing risk factor/exposure 1:clinical trial pill count Covariates/potential confounders adjusted for in analyses:Age Baseline cognitive status Method(s) of assessing cognitive status: [

Other – 

1) Follow-up rate: 143 randomized 48 placebo; 48 rlx 60mg and 48 rlx 120mg Followup rate Pl 93.7 vs RLX 60mg 95.8 vs RLX 120mg 93.6 2) Important baseline differences: Mean age was slightly older in the Rlx 60 mg group p 0.028. alcohol consumption 3 drinks/wk was greater in the placebo than 60 or 120 mg rlx (33 vs 15 vs 20%) p .022 3) Outcome of interest #1Memory assessment clinics battery Walter Reed performance assessment battery  At 12 months there were no differences in the MAC or PAB 

CommentsAmong 10 were no difat 12 monthQuality assFor RCTs: 1) Baselin2) Valid A

assess

3) Subjec4) Outcom5) Incomp

addresObservsubopt

6) Differen

No 

7) Overall 8) Conflic

insignif

9) Random
B-191

Study Study Information Participants Risk Factor and 

Outcome Assessment 

Results Comments

Duration of follow up:12 months Time from risk factor assessment to final cognitive assessment:12 months 

condition that might affect bone or calcium metabolism, and fully ambulatory. Postmenopausal status confirmed by serum estradiol ≤ 73 pmol/l 

and follicle stimulating hormone ≥ 30 IU/l in 

age < 60. Osteoporosis documented by Dx of at least one nontraumatic vertebral fracture and a bone mineral density of the lumbar spine or proximal femur of less than the tenth percentile of normal postmenopausal women. Exclusion criteria:

Pts with bone disorders other than osteoporosis, clinically significant menopausal symptoms (hot flashes, sweating, etc.), any history of cancer (except superficial basal or squamous cell carcinoma of the skin) within the previous 5 years, acute or chronic liver disease, history of deep vein thrombosis or cerebral vascular accident, or impaired kidney function were excluded. Also, Tx 

Memory assessment clinics battery Walter Reed performance assessment battery Informant interview?:No 

10) Allocat

adequa
B-192

Study Study Information Participants Risk Factor and 

Outcome Assessment 

Results Comments

with estrogen, progestin, calcitonin, androgen, or systemic corticosteroid more recently than 6 months prior to study were grounds for exclusion. 

Niti, Yap, Kua, et al., 2009 AND Ng, Niti, Zaw, et al., 2009 Singapore Longitudinal Aging Study (SLAS) 

Geographical location: Southeast region of Singapore Setting:Community Study design: Prospective cohort Number of participants enrolled:2808 eligible @ baseline (of which 2611 were eligible for f/u) 1487 analyzed Duration of follow up:Mean 1.46 (0.5) Time from risk factor assessment to final cognitive assessment:Mean 1.5 years 

Age:Mean (SD): 65.4 (7.0) Sex: [n (%)] 

Female: 944 (63.5%) Male: 543 (36.5%) Race/ethnicity: [n (%)] Chinese 1487 (100%) Baseline cognitive status:Non-demented Inclusion criteria: Chinese participants in the SLAS cohort. Exclusion criteria:Baseline MMSE score <23. 

Risk factor/exposure 1:Depressive symptoms.Method of assessing risk factor/exposure 1:Local Chinese version of the 15-item Geriatric Depression Scale (GDS). “Depressed symptoms” defined as GDS >15. 

Risk factor/exposure 2:APOE genotype Method of assessing risk factor/exposure 2:Polymerase chain reaction (PCR) Covariates/potential confounders adjusted for in analyses:Age Sex Educational level Baseline MMSE 

1) Follow-up rate: 1487 of 2611 (57%). 15 unfit to be interviewed, 444 refused, 426 could not be contacted, 53 died. Of the remaining 1673 who completed f/u interviews, 169 were excluded because of cognitive impairment at baseline and 17 excluded because of missing APOE genotype data. 2) Important baseline differences: N/A 3) Outcome of interest #1 Incident cognitive impairment: Overall: n=44/1487 (3.0%) Not depressed: n=35/1329 (2.6%) Depressed: n=9/158 (5.7%) Adjusted odds ratio: 2.29 (95% CI: 1.05, 5.00; p=0.04) 4) Outcome of interest #2 Incident cognitive decline, Adjusted OR (95% CI): GDS >5: 0.95 (0.61,1.48) 

APOE carrier: 1.10 (0.86,1.41) Interaction, GDS >5 x APOE status: 

APOE noncarriers: 0.73 (0.44, 1.21) 

CommentsQuestion 2 Same study articles. Quality assFor observ1) Unbias

cohort? 

2) Selectio

differenYes 

3) Sample 

differen

4) Adequa

cohort? 

5) Validat

ascerta

6) Validat

ascertaYes 

7) Outcom

exposu

8) Adequa9) Comple

Partial 

10) Analys

confou

11) Analytic 

Yes 
B-193

Study Study Information Participants Risk Factor and 

Outcome Assessment 

Results Comments

APOE genotype Length of f/u Vascular risk factors or events Method(s) of assessing cognitive status: MMSE “Cognitive decline” defined as >1 point 

drop in MMSE score from baseline to f/u. Informant interview?:No 

APOE carriers: 2.89 (1.03, 8.12) 

Niti, Yap, Kua, et al., 2008 Singapore Longitudinal Aging Study cohort 

Geographical location: South East region of Singapore Setting:Community Study design: Prospective cohort Number of participants enrolled:2611 Duration of follow up:1-2 years. Median= 1.5 years Time from risk factor assessment to final cognitive 

Age:Mean (SD): 66.0 (7.3) Sex: [n (%)] 

Female: 1063 (65%) Male: 572 (35%) Race/ethnicity: [n (%)] Chinese Baseline cognitive status:NR, but analyses were re-run excluding those with MMSE <24 and reportedly results were the same Inclusion criteria: Residents of South East Singapore who consented to 

Risk factor/exposure 1:Physical, social and productive activity Method of assessing risk factor/exposure 1:Self-report Covariates/potential confounders adjusted for in analyses:Age Sex Educational level Baseline cognitive status APOE Functional status Number of co 

1) Follow-up rate: Of 2611, 45 died before follow up. Of the 2566, 1635 were included in analysis – 63.71% 2) Important baseline differences: Thos who were lost to follow up were more likely to be men, have lower MMSE scores and lower scores on physical, social as well as productive activity. After categorizing baseline level of leisure activities into tertiles, the trend statistic was significant for those with fewer leisure activities to older, have lower MMSE score, less likely to be female, more likely to have < 6 yrs education, have more 

comorbid conditions, have more vascular risk factors/events, more likely to be depressed, and more likely to currently smoke. 

CommentsQuestion 2 Quality assFor observ1) Unbias

cohort? 

2) Selectio

differenYes (Rbased 75%) 

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6) Validat

ascertaYes 

7) Outcom
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Study Study Information Participants Risk Factor and 

Outcome Assessment 

Results Comments

assessment:1-2 years. Median= 1.5 years 

participate in study >55 yrs of age Exclusion criteria:

NR 

morbidities Vascular risk factor/events Depression Smoking Alcohol Method(s) of assessing cognitive status:Other – Longitudinal cognitive change on MMSE Informant interview?:No 

3) Outcome of interest #1Compared to those who had low leisure activity levels the odds of cognitive decline among those with high levels of leisure activity was  OR = 0.62 (0.46-0.84) and those who had medium leisure activity was OR = 0.60 (0.45 – 0.79) 4) Outcome of interest #2 Among those who had MMSE ≥ 24, Compared to those who had low leisure activity levels the odds of cognitive decline for those with high levels of leisure activity was  OR = 0.62 (0.46-0.85) and those who had medium leisure activity was OR = 0.61(0.46 – 0.72) 5) Outcome of interest #3 Compared to those who did not engage in any productive activity, those who engaged in at least one productive activity had lower cognitive decline OR = 0.36 (0.20- 0.65) In the total sample, participation in at least one social or physical activity was not associated with dementia. However, in the APOE carriers, those who participated in at least one physical activity (OR=0.34; 95% CI: 0.17-0.68) or at least one social activity (OR=0.40; CI: 0.16-0.99) were less likely to become demented. 

exposu

8) Adequa9) Comple10) Analys

confou

11) Analytic 

Yes 
B-195

Study Study Information Participants Risk Factor and 

Outcome Assessment 

Results Comments

Okereke, Kang, Cook, et al., 2008 Physician’s Health Study and Women’s Health Study 

Geographical location: Throughout the US Setting:Community Study design: RCTs – this is secondary analyses in two separate RCTs. The one RCT was to examine prevention of CVD, cancer and agerelated eye disease with vitamin supplements. The other RCT was to examine prevention of CVD and cancer using vitamin E. Number of participants enrolled:PHSII- 5209 WHS-5199 Duration of follow up:PHSII-mean 2 yrs WHS- mean 4 yrs Time from risk factor assessment to final cognitive assessment:PHSII-mean 2 yrs WHS- mean 4 yrs 

Age:Mean (SD): PHSII: DM = 74.3, No DM = 74.1 (total crosssectional sample) WHS: DM=71.5, No DM=71.9 (total crosssectional sample) Sex: [n (%)] 

Male and female samples from different source studies, so they were analyzed separately. Percentage of each does not seem relevant here. Race/ethnicity: [n (%)] NR Baseline cognitive status:Non-demented (ind were included as long as they were able to complete the telephone cognitive measures, so may have included some demented) Inclusion criteria: Participants in the PHSII or WHS and >

65 yr old Exclusion criteria:Ind with onset of DM prior to age 25 

Risk factor/exposure 1:Diabetes Method of assessing risk factor/exposure 1:Self-report Covariates/potential confounders adjusted for in analyses:Age Educational level Baseline cognitive status BMI HTN Cholesterol Smoking ETOH use HRT Physical activity Depression history Observation time Method(s) of assessing cognitive status: Other – difference in standardized test scores from baseline to fup Informant interview?:No 

1) Follow-up rate: PHSII-5209/5907; WHS – 5199/63262) Important baseline differences: Men and women with DM were more likely to have HTN, high cholesterol, be overweight or obese, more sedentary, have low ETOH consumption, and lower baseline cognitive scores. Women with DM were less likely to take HRT. 3) Outcome of interest #1Men with DM showed greater cognitive decline than men w/o diabetes on the TICS (-0.37; -0.64--.09), global cognitive score (-0.07; -0.13-0.00, ns) and verbal memory (-0.07 (-.014 to 0.01, ns) 4) Outcome of interest #2 Women with DM showed greater cognitive decline than women w/o diabetes on the TICS (-0.47; -0.71to -0.22), global cognitive score (-0.09; -0.15 to -0.04) and verbal memory (-0.09 (-.015 to -0.02) 5) Outcome of interest #3 There was a dose response effect with duration of diabetes for both men and women for the TICS and global memory score and for the verbal memory score in men 

CommentsQuestion 2 Quality assFor observ1) Unbias

cohort? 

2) Selectio

differenYes 

3) Sample 

differen

4) Adequa

cohort? 

5) Validat

ascerta

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ascertaYes 

7) Outcom

exposu

8) Adequa9) Comple10) Analys

confou

11) Analytic 

Yes 
B-196

Study Study Information Participants Risk Factor and 

Outcome Assessment 

Results Comments

Packard, Westendorp, Stott, et al., 2007 PROSPER study 

Geographical location: Scotland, Ireland, The Netherlands Setting:Clinical – Primary care Study design: Observational analysis from an RCT Test intervention:Pravastatin Comparator intervention(s):Placebo Number of participants enrolled:5804 Duration of follow up:Mean = 3.2 years (range 0.7 to 4.2) Time from risk factor assessment to final cognitive assessment:Mean = 3.2 years 

Age:Mean (SD): 75 Range: 70-82 Sex: [n (%)] 

Female: 3000 (52%) Male: 2804 (48%) Race/ethnicity: [n (%)] NR Baseline cognitive status:Non-demented Inclusion criteria: Age 70-82  High risk for (≈50%) 

or known vascular disease (≈50%)  Total cholesterol 154 to 347 mg/dl and triglyceride < 231 mg/dl Adhere to study drug of >=75% and <=120% during run-in phase Exclusion criteria: MMSE < 24  Various medical criteria related to safety Alcohol or drug abuse  Current lipid-lowering treatment 

Risk factor 1:LDL-C; HDL-C Method of assessing 

risk factor 1:  Directly measured twice at baseline in a central laboratory standardized through CDC Covariates/potential confounders adjusted for in analyses: Age, sex, country, education; history of vascular disease, MI, stroke, TIA, smoking, antihypertensive medication, BP, BMI, DM; triglyceride, treatment allocation, apoe e4,and baseline cognitive test scores 

Method(s) of assessing cognitive status:  Other – MMSE, picture-word learning test, Stroop color word test, letter digit coding test Informant interview?:No 

Follow-up: 86% of potential visits completed; Treatment adherence:94% in intervention and control Cognitive decline: Differences between last ontreatment and the second of two baseline measures. Difference in changes scores reported (by LDL-C and HDL-C tertile)  No significant difference for any cognitive measure: MMSE, Letter digit codes,  Picture word learning testimmediate and delayed recall, Stroop test  Activities of daily living and Independent activities of daily living:  No significant difference by LDL-C or HDL-C tertile for either outcome Continuous outcome [see instructions above] 

CommentsNone Quality assFor observ1) Unbias

cohort? 

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differenYes 

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ascertaYes 

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Yes 
B-197

Study Study Information Participants Risk Factor and 

Outcome Assessment 

Results Comments

Panza, D’Introno, Colacicco, et al., 2008 Italian longitudinal study on aging 

Geographical location: Italy – 8 cities Setting:Community Study design:

Prospective cohort Number of participants enrolled:

5632 overall, 2963 in this analytic sample but only 1524 included for incident MCI Duration of follow up:3.5 years Time from risk factor assessment to final cognitive assessment:3.5 years 

Age:Mean (SD): 71.9 (5.0) Sex: [n (%)] 

Female: 663 (43.5%) Male: 861 (56.5%) Race/ethnicity: [n (%)] NR Baseline cognitive status:Non-demented Inclusion criteria: Age 65-84 Randomly selected Completed baseline neuropsychological testing Exclusion criteria:Dementia 

Risk factor/exposure1:Depression Method of assessing risk factor/exposure 1:Direct measurement – geriatric depression scale (GDS) ≥ 10 at baseline Risk factor/exposure 2:Vascular risk factors: coronary artery disease, HTN, diabetes mellitus, stroke Method of assessing risk factor/exposure 2:Self-report Direct measurement (examination and blood values, EKG) Medical record Covariates/potential confounders adjusted for in analyses:Age Sex Educational level Stroke, HTN, DM, smoking, total cholesterol Method(s) of assessing cognitive 

1) Follow-up rate: Unclear 

2) Important baseline differences: NR 3) Outcome of interest #1113 incident cases of MCI. RR for MCI with depressive symptoms (1.25; 0.85-1.84) 4) Outcome of interest #2 Subgroup analysis showed increased risk for MCI among those with depressive symptoms and without CAD, RR 1.5 (1.0-2.3); among those with CAD, RR 0.5 (0.2-1.3). However, this association was no longer significant after adjusting for age, gender, education, stroke, HTN, smoking, DM and total cholesterol. 

CommentsQuestion 2 65% power Quality assFor observ1) Unbias

cohort? comple

2) Selectio

differenYes 

3) Sample 

differen

4) Adequa

cohort? 

5) Validat

ascerta

6) Validat

ascertaYes 

7) Outcom

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8) Adequa9) Comple

Can’t T

10) Analys

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11) Analytic 

Yes 
B-198

Study Study Information Participants Risk Factor and 

Outcome Assessment 

Results Comments

status:2-stage assessment using modified Petersen’s criteria (subjective memory complaint not required and allowed for noncognitive disabilities) Informant interview?:uncertain 

Paterniti, VerdierTaillefer, Dufouil, et al., 2002 EVA Study 

Geographical location: Nantes, France Setting:Community Study design:

Prospective cohort Number of participants enrolled:

1189 (1003 analyzed) Duration of follow up:4 years Time from risk factor assessment to final cognitive assessment:2-4 years 

Age:Range: 59- 71 years Sex:

Female: 429 (42.8%) Male: 574 (57.2%) Race/ethnicity: [n (%)]NR Baseline cognitive status:Non-demented Mmse>25 Inclusion criteria: 59-71 years old 

Exclusion criteria: 

MMSE<26 

Risk factor/exposure

1: Depression (CESD>16 for men; >22 for women)  Episodic depression = above threshold at one timepoint  Persistent depression = above threshold at >1 timepoint Method of assessing risk factor/exposure 1:Self-report at baseline, 2- and 4-year follow-upCovariates/potential confounders adjusted for in analyses:Age Sex Educational level Alcohol use Tobacco use 

1) Follow-up rate: 1003/1189 = 84% 2) Important baseline differences: More smokers in depressed group 3) Outcome of interest #1 MMSE decline >=3 points at 4 year f/u (161 cases)  CESD> threshold: OR=1.55 (95% CI 0.95 to 2.55)  Not depressed = referent  Episodic depression: OR=1.22 (95% CI 0.68 to 2.18)  Persistent depression: OR=2.10 (95% CI 1.23 to 3.58) 4) Outcome of interest #2  Low cognitive functioning (MMSE< 26 at 2- and 4-year f/u.  CESD > threshold: OR=3.22 (95% CI, 1.23 to 8.42) 5) Outcome of interest #3  Change in MMSE (4 year -baseline)  CESD below threshold (n-881): Mean change=-0.88 (SE 0.06)  CESD above threshold (n=122): 

CommentsMore subjebaseline diQuality assFor observ1) Unbias

Partial 

2) Selectio

differenYes 

3) Sample 

differen

4) Adequa

cohort: 

5) Validat

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6) Validat

ascertaYes 

7) Outcom

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8) Adequa9) Comple10) Analys

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11) Analytic 

Yes 
B-199

Study Study Information Participants Risk Factor and 

Outcome Assessment 

Results Comments

Psychotropic drug use Six chronic medical conditions Baseline MMSE (outcome #3 only) Method(s) of assessing cognitive status:Other – Cognitive decline= Decline in MMSE >=3 points; Low cognitive function = MMSE <25 at 2- and 4-year follow-up Informant interview?:No 

Mean change = -1.42 (SE 0.16) 

Peila, White, Masaki, et al., 2006 HonoluluHeart Program 

Geographical location: Oahu, HI Setting:Community Study design:

Prospective cohort Number of participants enrolled:

3734 in HHP cohort; 1294 in this analysis Duration of follow up: midlife bps from 1965-74, latelife bp from 1991-3 Cognitive baseline 1991 follow up 1994 

Age:Mean (SD):  Hypertensive 77 (0.1)  Normotensive 76.3  (0.2) Sex: [n (%)] 

Female: 0 (0%) Male: 1294 (100%) Race/ethnicity: [n (%)] Japanese-American 1294 (100%) Baseline cognitive status:Non-demented Inclusion criteria: Japanese-American men; born between 

Risk factor/exposure 1:antihypertensives Method of assessing risk factor/exposure 1:Self-report Risk factor/exposure 2:htn Method of assessing risk factor/exposure 2:Direct measurement or self-report of HTN or selsf report of antihypertensive medication 

1) Follow-up rate: analysis of 1294 who were normotensive t/o study or hypertensive t/o study. Looks like 1223 had abnl bp or missing bp, 64 had tx early but not late and 10 had missing tx data Adjusted loss to f/u: 66.8% in treated vs. 57.4% in untreated hypertensives31% seem to have been deaths, refusals, demented but I don’t see a breakdown 2) Important baseline differences: subj with htn were older, had higher bp’s at mid and late life, higher bmi, lower abi, more vasc dz, more apoE43) Outcome of interest #1 Incident dementia = 108 (AD – 65; 

CommentsQuestion 1 Quality assFor observ1) Unbias

cohort? 

2) Selectio

differenPartial 

3) Sample 

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B-200

Study Study Information Participants Risk Factor and 

Outcome Assessment 

Results Comments

Time from risk factor assessment to final cognitive assessment:Variable: 4 to >12 years 

1900 – 1919; living in Oahu, HI Specific criteria for this study sample not well specified Exclusion criteria:

Subjects with missing data on BP Hypertensive treated at mid-life but not late-life Missing data on duration of anti-HTN treatment 

Covariates/potential confounders adjusted for in analyses:Age, midlife bmi, smoking, cad, cva, atherosclerosis (using abi), apoE4, education Method(s) of assessing cognitive status:NINCDS-ADRDA DSM-IIR/IV In those screening positive on Cognitive Abilities Screening Instrument Informant interview?:yes for those who were evaluated by screen positive men 

AD/VaD – 19) 

duration of tx, hr for ad 0-5 yrs 0.62(0.27-1.43) 5-12 yrs 0.54 (0.21-1.36) >12 yrs 0.35 (0.16-0.78) as comopared to never treated hypertensives Untreated normotensives 0.26 (0.10-0.66) 4) Outcome of interest #2 tx > 12 yrs as compared with normotensives 0.82 (0.28-2.38) not specifically ad 5) Outcome of interest #3: Annual decline in CASI score was greater for never treated hypertensives (-1.46) compared to treatment for 5-12 years (-1.14) and normotensives (-1.01) but was not statistically significant compared to 0-5 years treatment (-1.22) or >12 years treatment (-1.08) 

8) Adequa9) Comple10) Analys

confou

11) Analytic 

Yes 

Petersen, Thomas, Grundman, et al., 2005 

Geographical location: multiple sites throughout the US and Canada Setting:Clinical – 69 ADCS in US and Canada Study design: RCT Test intervention: 

Age:Mean (SD): 72.9 (7.3) Sex: [n (%)] 

Female: 352 (46) Male: 417 (54) Race/ethnicity: [n (%)] NR Baseline cognitive status:MCI (amnestic) 

Risk factor/exposure 1:Vitamin E Method of assessing risk factor/exposure 1:Self report – but RCT so some objective evidence Covariates/potential confounders adjusted for in 

1) Follow-up rate: 230 of 769 discontinued during trial – no sig diff between treatment arms 2) Important baseline differences: No significant differences 3) Outcome of interest #1No difference in rate of progression to AD between vitamin E and placebo groups at any point, either among all patients or among apolipoprotein e4 carriers. (HR =1.02; 95% CI, 0.74 to 1.41; P=0.91).

CommentsNone Quality assFor RCTs: 1) Baselin2) Valid A

assess

3) Subjec4) Outcom5) Incomp

addres

6) Differen

Yes 
B-201

Study Study Information Participants Risk Factor and 

Outcome Assessment 

Results Comments

2000 IU of vitamin E and multivitamin daily; OR 10 mg of donepezil, and a multivitamin OR a multivitamin daily. Comparator intervention(s): Other arms (donepezil and multi-vit OR multivit) Number of participants enrolled:769 Duration of follow up:3 years Time from risk factor assessment to final cognitive assessment:3 years 

Inclusion criteria: Had amnestic MCI, impaired memory, a Logical Memory delayed-recall score approximately 1.5 to 2 SD below an education-adjusted norm, a CDR of 0.5, a score of 24 to 30 on MMSE, and between 55 to 90 years old. Exclusion criteria:

NR 

analyses:Age Baseline cognitive status APOE Method(s) of assessing cognitive status:NINCDS-ADRDA Other – Change on cognitive measures, CDR, Activities of Daily Living Scale; the Global Deterioration Scale Informant interview?:Yes 

At 36 months, no differences in secondary outcomes between vitamin E and placebo groups 

7) Overall 8) Conflic

insignif

9) Random10) Allocat

adequa

Plassman, Havlik, Steffens, et al., 2000 (WWII Veterans with head injury) 

Geographical location: All over US Setting:Other –World War II veterans Study design: Retrospective cohort Number of participants enrolled:2361 

Age:Mean (SD): 73.05 in the exposed and 72.78 in the unexposed Sex: [n (%)] 

Female: 0 (0%) Male: 2361 (100%) Race/ethnicity: [n (%)] 95% Caucasian 3.5 % AA 1.5 % Other races

Risk factor/exposure 1:Head injury Method of assessing risk factor/exposure 1:Self-report Medical record Risk factor/exposure 2:APOE 

1) Follow-up rate: Of the 5444 identified to be eligible, 2361 (43.36%) completed the baseline interview. Of this sample, 1776 (75.22%) were included in the analysis. The others were excluded due to medical reasons and other exclusion criteria. 2) Important baseline differences: Among those exposed to head injury, those who agreed to participate had higher cognitive functioning and were more educated than those who 

CommentsObjective egathered frlong period important sa communifeasible to for cohort sQuality assFor observ1) Unbias

cohort? design 
B-202

Study Study Information Participants Risk Factor and 

Outcome Assessment 

Results Comments

Duration of follow up:Approximately 55 years Time from risk factor assessment to final cognitive assessment:Approximately 55 years. 

Baseline cognitive status:No marked cognitive sequelae for 3 months after head trauma. Inclusion criteria: World War II US Navy or Marine male veterans during 1944 to 1945 who had a head injury that was 1) was documented in the military medical records, 2) occurred during military service, 3) produced loss of consciousness, posttraumatic amnesia, or skull fracture, 4) did not penetrate the dura mater, and 5) did not result in marked cognitive impairment or neurologic sequelae more than 3 months post-trauma. 

Exclusion criteria: 

1) the medical record lacked evidence of head injury, loss of consciousness, posttraumatic amnesia, or hospitalization for head trauma; 2) the only reported head injury was before enlistment; 3) the record documented a 

Method of assessing risk factor/exposure 2:Direct measurement Covariates/potential confounders adjusted for in analyses:Age Educational level APOE Method(s) of assessing cognitive status:NINCDS-ADRDA DSM Informant interview?:Yes 

refused to participate. 3) Outcome of interest #1 

History of head injury increased the risk of AD (hazard ratio [HR] = 2.00, 95% CI = 1.03 to 3.90) After controlling for age, HR remained the same for AD (HR = 2.01, 95%CI = 1.03 to 3.91)4) Outcome of interest #2 Risk for AD increased with severity of head injuryCompared with the group with no head injury, there was increased risk of AD for Moderate head injury: (HR = 2.32,95% CI = 1.04 to 5.17) Severe head injury : (HR = 4.51, 95% CI = 1.77 to 11.47) but not for mild head injury (HR = 0.76, 95% CI = 0.18 to 3.29)5) Outcome of interest #3 After controlling for head injury and years of education, the HR for AD associated with homozygous e4 was 13.97 (95% CI = 4.64 to 42.01) and for e4 heterozygotes was 1.03 (95% CI = 0.43 to 2.50) when compared with men with no e4 as a reference group 

2) Selectio

differenYes 

3) Sample 

differen

4) Adequa

cohort? 

5) Validat

ascerta

6) Validat

ascertaYes 

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11) Analytic 

Yes 
B-203

Study Study Information Participants Risk Factor and 

Outcome Assessment 

Results Comments

penetrating head injury, depressed skull fracture, brain surgery, or severe neurologic sequelae; 4) the individual was female or not in the armed services during 1944 to 1945; 5) the individual died during military service . 

Podewils, Guallar, Kuller, et al. 2005 Cardiovascular Health Cognition Study (CHCS – sub-group of CHS) 

Geographical location:

Sacramento Co., CA; Washington Co., MD; Forsyth Co., NC; Pittsburgh, PA Setting:

Community Study design: Prospective cohort Number of participants enrolled:3375 Duration of follow up:5.4 yrs Time from risk factor assessment to final cognitive assessment:5.4 yrs 

Age:Mean (SD): 74.8 (4.9) Sex:

Female: 59.1% Male: 40.9% Race/ethnicity:Caucasian: 85% Non-Caucasian: 15% 

Baseline cognitive status:Non-demented Inclusion criteria:  Residing in areas listed above  Age > 65 years 

 Participated in the Cardiovascular Health Cognition Study in 1992-2000 Exclusion criteria:Dementia at baseline 

Risk factor/exposure 1:Leisure-time energy expenditure and an activity index reflecting # of different physical activities was calculated.” Method of assessing risk factor/exposure 1:Self-report Proxy report Direct measurement Medical record Covariates/potential confounders adjusted for in analyses:Age Race Sex Educational level Baseline cognitive status

apolipoprotein E 

1) Follow-up rate: 3608 included in this study. Outcomes available for 3375. 93%follow up rate. N=3041 for fully adjusted models 2) Important baseline differences: Compared with nonparticipants, CHCS participants were younger, more educated, and less likely to have cardiovascular disease3) Outcome of interest #1--ADTable 5. Multivariate Hazards Ratio (95% CI) 1) 0-1 activities: 1.0 (referent) 2) 2 activities: 0.73 (0.49, 1.08) 3) 3 activities: 0.85 (0.57, 1.29) 4) >4 activities: 0.44 (0.34, 0.88) 

p-trend 0.03 4) Outcome of interest #2 “We identified an inverse association between physical activity and 

CommentsNone Quality assFor observ1) Unbias

cohort? 

2) Selectio

differenYes 

3) Sample 

differen

4) Adequa

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5) Validat

ascerta

6) Validat

ascertaYes 

7) Outcom

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Yes 
B-204

Study Study Information Participants Risk Factor and 

Outcome Assessment 

Results Comments

genotype (APOE) (e4 or non-e4), magnetic resonance imaging white-mattergrade score (<3 or _3), activities of daily living impairment (<1 or _1), instrumental activities of daily living impairment (<1 or _1), Lubben Social Network Score , and social support score Method(s) of assessing cognitive status:NINCDS-ADRDA DSM ICD Informant interview?:No 

dementia (and AD) for APOE noncarriers, but found no association for APOE carriers.” 

Posner, Tang, Luchsinger, et al., 2002 Washington HeightsInwood Columbia Aging Project (WHICAP) 

Geographical location: Northern Manhattan, NY Setting:Community Study design:

Prospective cohort Number of participants enrolled:

1259 

Age:Mean (SD):  Incident AD 79.3 (6.7  Incident VaD 77.9  (6.2)  Free of dementia 75.0  (5.6) Sex: [n (%)] 

Female:  Incident AD 108  (12.4%)  Incident VaD 41  (4.7%)  Dementia-free 721 

Risk factor/exposure

1:htn Method of assessing risk factor/exposure 1:Self-report and Direct measurement measured x 3 with dinamap, last reading used, >140 sbp and > 90 dbp considered htn, not clear how self report counted. 

1) Follow-up rate: 540/1799 (30%) died, refused, or moved; those w/ f/u were younger, more likely to be Hispanic, and less likely to have DM or heart disease 2) Important baseline differences: subj with htn had more heart dz, dm and cva and less smoking 3) Outcome of interest #1 Incident AD=157; Incident VaD=56; risk of AD with a history of htn: HR= 0.8 (95% CI, 0.6-1.1) 

CommentsQuestion 1 Quality assFor observ1) Unbias

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B-205

Study Study Information Participants Risk Factor and 

Outcome Assessment 

Results Comments

Duration of follow up: every 18 mos up to seven years for cog testing Time from risk factor assessment to final cognitive assessment:Variable, up to 7 years. 

 (83.1%) Male:  Incident AD 49  (12.5%)  Incident VaD 15  (3.8%)  Dementia-free 322 (82.4%) Race/ethnicity: [n (%)] 

African-American  Incident AD 62  (15.2%)  Incident VaD 22  (5.4%)  Dementia-free 328  (80.4%) Hispanic  Incident AD 71  (12.7%)  Incident VaD 25  (4.5%) Dementia-free 458  (81.8%) White  Incident AD 23 (8.2%) Incident VaD 9 (3.2%) Dementia-free 249  (88.3%) Other  Incident AD 1 (11.1%) Incident VaD 0 (0%)  Dementia-free 8  (88.9%) Baseline cognitive status:Non-demented Inclusion criteria: Participant in 

Covariates/potential confounders adjusted for in analyses: Age Race, Sex, Educational level, dm, heart disease (mi, chf, angina) Method(s) of assessing cognitive status:NINCDS-ADRDA Informant interview?:No 

4) Outcome of interest #2 Treatment of htn did not affect risk estimates for AD: no tx HR= 0.96 (95% CI 0.6 – 1.5), tx HR 0.86 (95% Ci 0.6 – 1.5) In additional analyses, no additive or synergistic effects were found between HTN and other vascular risk factors and risk of AD. 5) Outcome of interest #3 GEE analysis of composite factors for memory, language, cognition (based on neuropsych testing) showed no association between HTN and cognitive peformance. 

ascerta

6) Validat

ascertaYes 

7) Outcom

exposu

8) Adequa9) Comple

Partial 

10) Analys

confou

11) Analytic 

Yes 
B-206

Study Study Information Participants Risk Factor and 

Outcome Assessment 

Results Comments

Washington HeightsInwood Columbia Aging Project; randomly selected; agreed to participate (1259/2126), no AD @ baseline; Medicare recipient; ≥ 65 yo Exclusion criteria:NR 

Potter, Plassman, Helms, et al., 2006 Duke Twins Study 

Geographical location: throughout the US Setting:Community Other – Twin Registry Study design: Prospective cohort Number of participants enrolled:3880 Duration of follow up:7 years Time from risk factor assessment to final cognitive assessment:7 years 

Age:Mean (SD): 65.83 (2.74) Sex: [n (%)] 

Female: 0% Male: 100% Race/ethnicity: [n (%)] NR Baseline cognitive status:Non-demented Inclusion criteria: Member of the NASNRC Twin Registry of male WWII veterans. Not demented. Both members of twin pair have occupation data and cognitive data. Exclusion criteria:NR 

Covariates/potential confounders adjusted for in analyses:Age Educational level Baseline cognitive status Twin pairing Medical conditions Method(s) of assessing cognitive status: Other – Cognitive decline on TICS-mInformant interview?:No –not for this part of the study 

1) Follow-up rate: NR2) Important baseline differences: NR 3) Outcome of interest #1Within twin pairs, jobs with higher general intellectual demands were associated with more improvement in cognitive function from baseline to follow-up (p = 0.011) Within twin pairs, jobs with higher physical exertion (p = 0.002) and higher visual attention (p = 0.023) was associated with greater cognitive decline. 4) Outcome of interest #2 Within twin pairs, these occupational factors contributed little to cognitive change compared to the baseline cognitive score, the twin pairing, and education. 

Comments

None Quality assFor observ1) Unbias

cohort? 

2) Selectio

differenYes 

3) Sample 

differen

4) Adequa

cohort? 

5) Validat

ascerta

6) Validat

ascertaYes 

7) Outcom

exposuoccupaknown 

8) Adequa9) Comple

Can’t T

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B-207

Study Study Information Participants Risk Factor and 

Outcome Assessment 

Results Comments

11) Analytic 

Yes 

Price, Stewart, Deary, et al., 2008 Aspirin for Asymptomatic Atherosclerosis (AAA) Study 

Geographical location:Edinburgh, Glasgow, & Lanarkshire, in Central Scotland Setting:Clinical – mailing to general medical practices Study design:

RCT Test intervention Daily enteric aspirin 100mg Comparator intervention(s) placebo Number of participants enrolled: 3350 randomized 504 enrolled after cognitive testing 399 in subset at 5 yr f/u Duration of follow up: 5 years Time from risk factor assessment to final cognitive assessment:

Final cognitive 

Age:(at randomization) Mean (SD): 62 (7) Range: 50 - 75 Sex: [n (%)] 

Female: 2396 (71.6%)Male: 954 (28.4%) Race/ethnicity: [n (%)] NR Baseline cognitive status:Normal Inclusion criteria: > 50 yo; participating in Aspirin for Asymptomatic Atherosclerosis Trial Exclusion criteria:History of MI, angina, PAD, or stroke; if taking aspirin or warfarin; ankle brachial index >0.95 in both legs; severe indigestion; chronic liver or kidney disease; chemotherapy; contraindications to Tx w/ aspirin; an abnormally high or low packed cell volume 

Risk factor/exposure 1:RCT asa (100 mg daily) /placebo given Covariates/potential confounders adjusted for in analyses:Age Sex, abi, cholesterol, smoking, Carstairs deprivation category, baseline test results Method(s) of assessing cognitive status: Other – Change in cognitive score over time Informant interview?:No 

1) Follow-up rate: 24.8% of ASA lost, 16.8% of placebo 

lost 2) Important baseline differences: We don’t have good info on cognitive change subset. 3) Outcome of interest #1 No significant differences in the change in cognitive ability over the five years for any of the individual tests or for the general factor between the treatment groups. 

CommentsCan only usubgroup (Quality assFor RCTs: 1) Baselin

Tell 

2) Valid A

assess

3) Subjec4) Outcom5) Incomp

addres

6) Differen

Partial 

7) Overall 8) Conflic

insignif

9) Random10) Allocat

adequa
B-208

Study Study Information Participants Risk Factor and 

Outcome Assessment 

Results Comments

assessment about 5 yrs post enrollment in RCT 

Prince, Cullen, and Mann, 1994 MRC study 

Geographical location: 226 general practices in UK Setting:Community (drawn from general practice lists) Study design: Nested case-control Test intervention: Atenolol 50mg daily (n=640) or hctz 25mg + amiloride 2.5mg daily (n=633) adjusted to BP target range Comparator intervention(s): Placebo (n=1311) Number of participants enrolled:2651 in cognitive substudy; 453 included in this analysis Duration of follow up: 54 months (4.5 years) Time from risk factor assessment to final cognitive 

Age:Range: 65 – 74 years Sex:NR Race/ethnicity:

NR Baseline cognitive status: [delete all that do not apply] Non-demented, but only routine clinical assessment Inclusion criteria:  SBP 160-209 and mean DBP < 115 mmg Hg  Age 65-74 Exclusion criteria: Taking anti-HTN med CHF, angina, DM, asthma or other serious disease  MI or CVA w/in 3 months 

Risk factor/exposure

1: Area of residence from birth to 15 years (rural/urban)  2. Maternal age>34; paternal age >37  3. Paternal social class  4. Education <10 years  5. Current smoking  6. Elevated depression score Method of assessing risk factor/exposure 1:Self-report + Proxy report Risk factor/exposure 2: Cholesterol >7.2mmol  2. BMI  3. SBP >190 at baseline  4. IQ (NART score) Method of assessing risk factor/exposure 2:Direct measurement Covariates/potential 

1) Follow-up rate: 73% during trial; only 67% of the PALT decliners completed further cognitive evaluation 2) Important baseline differences: NR 3) Outcome of interest #1 223 PALT decliners; Within PALT decliners, Incident dementia = 50 (AD=31);  AD  Current rural residence OR 0.28 (0.08-0.94)  Smoking >=10 cigarettes daily: OR 4.38 (1.47-13.1)  Dementia:  Adjusted OR showed no significant association for: area of residence from birth to age 15, season of birth, paternal social class, serum cholesterol BMI, systolic HTN, smoking, ecg arrythmia, extreme fall in SBP or DBP 4) Outcome of interest #2  Risk factors for cognitive decline on the PALT  Moduretic Rx: OR 2.00 (95% CI 1.17-3.45)  Low premobid IQ: OR=2.03 (1.27-3.26)  <10 years education: 2.12 (1.20-3.57); no secondary school OR 2.20 (1.25-3.88); no tertiary education OR 

Comments Multiple cadjustment  Limited pcalculations  Baseline population  Only 63% available foexposures Quality assFor observ1) Unbias

cohort? 

2) Selectio

differenPartial 

3) Sample 

differen

4) Adequa

cohort? 

5) Validat

ascerta

6) Validat

ascerta

Partial 

7) Outcom

exposu

8) Adequa9) Comple

Applica

10) Analys
B-209

Study Study Information Participants Risk Factor and 

Outcome Assessment 

Results Comments

assessment: 4.5 years 

confounders adjusted for in analyses:

Age Sex IQ FH of dementia Area of residence Method(s) of assessing cognitive status: 2-stage screening -  NINCDS-ADRDA  DSM-IIIR  Other – Paired associated learning test (PALT) decliner = >=16 at baseline and <16 at f/u Informant interview?:Yes- for a small subset

2.02 (1.00-4.08)  Advanced paternal age: OR 0.49 (0.27-0.91) 

confou

11) Analytic 

Yes 

Prince, RabeHesketh, and Brennan, 1998 MRC Treatment Trial of Hypertension in Older Adults 

Geographical location: United Kingdom Setting: Clinical – UK general practices Study design: Nested case-control analysis in sample recruited for RCT of anti-hypertensive medication treatment Number of participants enrolled: 

Age:Mean (SD): 70 years Range: 65 – 74 years Sex:

Female: 58% Male: 42% Race/ethnicity: [n (%)] NR Baseline cognitive status: these are trial participants so theoretically could give 

Risk factor/exposure

1:nsaids Method of assessing risk factor/exposure 1:Self-report Covariates/potential confounders adjusted for in analyses:Entry PALT score, entry depression score, NART score 

1) Follow-up rate: 

62% had four data pts, 88% had 3 data pts, 2) Important baseline differences: nsaid users: more female, sl older, higher bmi, more depressive symptoms. More antidepressants, more benzos. Less likely to smoke.3) Outcome of interest #1 They say there is a slight protective effect until age 74, but I am having trouble understanding their data. 

Commentsreanalysis beta blockehypertensivTrial particitesting. MeIt doesn’t sis sufficient Quality assFor observ1) Unbias

cohort? 

2) Selectio
B-210

Study Study Information Participants Risk Factor and 

Outcome Assessment 

Results Comments

2651 Duration of follow up: 8 years for trial,Cognitive substudy:baseline 1983-4, nart at bl, palt and trails A Time from risk factor assessment to final cognitive assessment:baseline, months 1, 9, 21, 54 

consent. No baseline cognitive requirements. Mean age 70. Inclusion criteria:  Participation in the MRC treatment trial of hypertension in older adults Exclusion criteria:

 Serious cardiovascular, cerebrovascular, or other intercurrent illnesses 

Method(s) of assessing cognitive status:change in PALT scores.

Informant interview?:No 

differenNo 

3) Sample 

differen

4) Adequa

cohort? 

5) Validat

ascerta

6) Validat

ascertaNo 

7) Outcom

exposu

8) Adequa9) Comple

Applica

10) Analys

confou

11) Analytic 

Yes 

Prince, Bird, Blizard, et al., 1996 MRC Trial 

Geographical location: 226 UK locations Setting:Clinical – drawn from GP registries Study design: RCT Test intervention: Atenolol 50mg daily (n=640) or hctz 25mg + amiloride 2.5mg daily (n=633) adjusted to BP target range Comparator 

Age:Range: 65 – 74 years Sex:

Female: 58% Male: 42% Race/ethnicity:NR Baseline cognitive status:Normal Non-demented MCI CIND AAMI AACD 

Covariates/potential confounders adjusted for in analyses:Age Sex Baseline cognitive status Method(s) of assessing cognitive status:Other – Paired associate learning test, Trails A,– administered at baseline, 1, 9, 21, and 54 months Informant interview?:

1) Follow-up rate: 88% completed at least 3 of the 5 f/u assessments 2) Important baseline differences: No 3) Outcome of interest #1No signficiant difference in PALT or Trails A between groups Secondary “per-protocol” analysis did not show any significant difference on the PALT or Trails A between groups 

CommentsMean fall in 31.5 for b-bplacebo. Quality assFor RCTs: 1) Baselin2) Valid A

assess

3) Subjec

(subjecblind) 

4) Outcom

Tell 

5) Incomp

addres

6) Differen

Yes 
B-211

Study Study Information Participants Risk Factor and 

Outcome Assessment 

Results Comments

intervention: Placebo (n=1311) Number of participants enrolled:4396 overall 2584 in cognitive substudy Duration of follow up:Mean = 5.8 years Time from risk factor assessment to final cognitive assessment: 5.8 years 

Inclusion criteria: SBP 160-209 and mean DBP < 115 mmg Hg Age 65-74 Exclusion criteria:

Taking anti-HTN med CHF, angina, DM, asthma or other serious disease MI or CVA w/in 3 months 

No 7) Overall 

8) Conflic

insignif

9) Random10) Allocat

adequa

Qiu, Winblad, Fastbom, et al., 2003 AND Guo, Fratiglioni, Viitanen, et al., 2001 Kungsholmen Project 

Geographical location: Stockholm, Sweden Setting:Community Study design: Prospective cohort Number of participants enrolled:1473 in overall cohort; 966 in this analysis Duration of follow up:Median 5.7 years Time from risk factor assessment to final cognitive assessment:

Age:Range: > 75 years 

Sex: [n (%)] Female: 727 (75%) Male: 239 (25%) Race/ethnicity: [n (%)] NR Baseline cognitive status:Non-demented Inclusion criteria:  Age >=75 y.o  Resident of Kungsholmen district  APOE and baseline BP data available Exclusion criteria:

Risk factor/exposure

1:Anti-hypertensive at baseline Method of assessing risk factor/exposure 1:Self-report Direct measurementbottles or prescriptions when available Risk factor/exposure 2:Apo# E4; HTN at baseline Method of assessing risk factor/exposure 2:Direct measurement 

1) Follow-up rate: Drop-out was related to increasing age and decreased baseline MMSE 2) Important baseline differences: Yes by APOE status 3) Outcome of interest #1Incident AD = 204 subjects Relative risk for AD by exposure: Any E4, RR=1.6 (95% CI, 1.2-2.1) SBP <140 (reference) 140-159, RR 1.3 (0.8-2.0) >=160, RR 1.4 (0.9-2.2) DBP <70, RR 1.9 (1.2-3.0) 70-89, Reference >=90, RR 1.0 (0.7-1.4) 

CommentsNone Quality assFor observ1) Unbias

cohort? 

2) Selectio

differenYes 

3) Sample 

differen

4) Adequa

cohort? 

5) Validat

ascerta

6) Validat

ascertaPartial 

7) Outcom

exposu

8) Adequa
B-212

Study Study Information Participants Risk Factor and 

Outcome Assessment 

Results Comments

Median 5.7 years (range 0.1 to 8.2 ) 

Dementia 

Covariates/potential confounders adjusted for in analyses:

Age Sex Educational level Baseline cognitive status Vascular disease SBP, DBP and antihtn drug use Method(s) of assessing cognitive status: 2 physicians independently made a preliminary diagnosis and 3rd opinion used 

for disagreements; for deceased subjects, 2 MDs made diagnosis after reviewing medical records and death certificates  NINCDS-ADRDA like criteria  DSM-IIIR Informant interview?No 

Anti-HTN medication, RR 0.6 (0.5-0.9); risk reduction only noted in those with elevated SBP (>=140; RR 0.6, 95% Ci 0.4 to 0.8) or with elevated DBP (>=70, RR = 0.6, 95% CI 0.5-0.9) 4) Outcome of interest #2 Interaction terms: APOE-e4 allele combined with low DBP increased the risk of AD (RR 4.5, 95% CI 2.6-8.0), independent of anti-HTN drug use. Anti-HTN treatment reduced the risk of AD, regardless of APOE-e4 status

9) Comple

Can’t T

10) Analys

confou

11) Analytic 

Yes 
B-213

Study Study Information Participants Risk Factor and 

Outcome Assessment 

Results Comments

Ravaglia, Forti, Lucicesare, et al., 2008a Conselice Study of Brain Aging (CSBA) 

Geographical location: Conselice municipality, Italy Setting:Community Other – also included institutionalized individuals Study design: Prospective cohort Number of participants enrolled:749 Duration of follow up:Mean 3.9 (sd = 0.7) years Time from risk factor assessment to final cognitive assessment:Mean 3.9 (sd = 0.7) years 

Age:Mean (SD): 73.2 (6.0) Sex: [n (%)] 

Female: 401 (53.5) Male: 348 (46.5) Race/ethnicity: [n (%)] NR Baseline cognitive status:Normal Inclusion criteria: >65 yrs old participant 

in the CSBA study Exclusion criteria: Individuals with baseline diagnosis of MCI, dementia, or unclassified cognitive status. Individuals with sensory/motor deficits precluding outdoor activity, missing APOE genotype or lacked follow-up info to determine cognitive status 

Risk factor/exposure 1:physical activity a) no. of city blocks walked daily, b) no. flights of stairs climbed daily, c) frequency and duration of weekly participation during past year in occupational, recreational and sport activity Method of assessing risk factor/exposure 1:Self-report Covariates/potential confounders adjusted for in analyses:Age Sex Educational level APOE Cardiovascular diseaseHypertension HyperhomocysteinemaCerebrovascular disease Diabetes COPD Cancer ADL motor impairment Method(s) of assessing cognitive status:

1) Follow-up rate: 749/8652) Important baseline differences: NR 3) Outcome of interest #1

54 incident AD cases  86 incident dementia total 4) Outcome of interest #2 None of the categorizations of physical activity was significantly associated with incident AD. Some HRs were above 1.0 and some were less than 1.0 

CommentsQuestion 1 Quality assFor observ1) Unbias

cohort? 

2) Selectio

differenYes 

3) Sample 

differen

4) Adequa

cohort? 

5) Validat

ascerta

6) Validat

ascertaYes 

7) Outcom

exposu

8) Adequa9) Comple10) Analys

confou

11) Analytic 

Yes 
B-214

Study Study Information Participants Risk Factor and 

Outcome Assessment 

Results Comments

NINCDS-ADRDA DSM Other – MCI defined as MMSE <24, not demented, < 1.5 sd 

below age/education adjusted norms on any test, independently perform ADL/IADL Informant interview?:Yes 

Ravaglia, Forti, Lucicesare, et al. 2008b Conselice Study of Brain Aging 

Geographical location: Conselice, Italy Setting:Community Study design: Prospective cohort Number of participants enrolled:864 Duration of follow up:years 3.9 (0.5) Time from risk factor assessment to final cognitive assessment:3.9 (0.5) 

Age:Median: NCI-72.3 (5.6) MCI- 78.1 (8.3)Sex: [n (%)] 

Female:NCI-306 (48.6) MCI- 36 (50) Male: NCI-323 (51.4)  MCI- 36 (50) Race/ethnicity: [n (%)] NR Baseline cognitive status:Non-demented Inclusion criteria: Age >=65 years old Exclusion criteria: Dementia at baseline or during f/u  Major sensory –motor deficits or any psychiatric condition 

Risk factor/exposure

1: Depression by GDS30 >=10 at baseline 2: Antidepressant use at baseline Method of assessing risk factor/exposure 1:Self-report Risk factor/exposure 1:APOE genotyping Method of assessing risk factor/exposure 1:Direct: PCR Covariates/potential confounders adjusted for in analyses:

1) Follow-up rate:  675/864=78%  After excluding incident dementia (n=78)or unclassifiable status (n=3), 595 analyzed 2) Important baseline differences: 3) Outcome of interest #1 Incident MCI (155 subjects)  GDS >=10: 1.1 (0.7 to 1.9)  Antidepressant use at baseline: OR 2.9 (1.3 to 6.6) 4) Outcome of interest #2  Subgroup analyses for MCI with memory impairment (79 subjects)  GDS >=10: 1.1 (0.5 to 2.0)  Antidepressant use at baseline: OR 2.8 (1.0 to 7.7) Subgroup analyses for MCI without memory impairment (76 subjects)  GDS >=10: 1.2 (0.6 to 2.3)  Antidepressant use at baseline: OR 

Comments Very low < 5 years  Logistic rQuality assFor observ1) Unbias

Yes 

2) Selectio

differenYes 

3) Sample 

differen

4) Adequa

cohort: 

5) Validat

ascerta

6) Validat

ascertaYes 

7) Outcom

exposu

8) Adequa9) Comple10) Analys
B-215

Study Study Information Participants Risk Factor and 

Outcome Assessment 

Results Comments

(other than depression) hampering a reliable cognitive assessment. 

Age Sex Educational level APOE genotype Framingham stroke risk score HTN Hyperhomocysteinemia Method(s) of assessing cognitive status: 2-stage evaluation with neuropsychological testing  Other – MCI: a) age and education adjusted score >= 1.5 SD below reference threshold on any neuropsycholgical testing; b) no need for supervision or external help in ADLs or IADLS; c) absence of DSM-IV criteria for dementia ...Subclassified into MCI with objective memory impairment and MCI w/o memory impairment Informant interview?:No 

3.1 (1.2 to 8.2)  A test for interaction between baseline elevated GDS and antidepressant use was significant. Risk of MCI for both compared to no antidepressant/low GDS: OR 12.0 (95% CI 2.8 to 52.1) 

confou

11) Analytic 

Yes 

Ravaglia, Forti, Maioli, et al., 2005 

Geographical location: Conselice, Italy Setting:

Age:Mean (SD): 74.6 (7.1) Range: > 65 years 

Sex: [n (%)] 

Risk factor/exposure

1:hcy Method of assessing 

1) Follow-up rate: 816/937 87%. 2) Important baseline differences: high hcy: older, more women, less 

Comments15.3 % of sreassessed “subjects thgeneral pra
B-216

Study Study Information Participants Risk Factor and 

Outcome Assessment 

Results Comments

AND Ravaglia, Forti, Maioli, et al., 2007 Conselice Study of Brain Aging 

Community Study design: Prospective cohort Number of participants enrolled:937 dementia free at baseline Duration of follow up: 3.8 yrs (0.8) Time from risk factor assessment to final cognitive assessment:3.8 yrs 

Female: 563 (55%) Male: 453 (45%) Race/ethnicity: [n (%)] NR Baseline cognitive status:Non-demented Inclusion criteria:  Resident of Conselice  Age > 65 years as of 

01 JAN 1999 Exclusion criteria:NR 

risk factor/exposure1:Direct measurement Fasting plasma, frozen, doesn’t say how long Covariates/potential confounders adjusted for in analyses:age, sex, education, apoE, stroke, creatinine, folate, vit b12, smoking status, dm, htn, cardiovasc dz, bmi Method(s) of assessing cognitive status:DSM NINCDS-ADRDA Informant interview?: Yes, for those who screened positive for dementia 

APOE e4, less dm, lower vit B, more smokers, more strokes, more cardiovasc dz, 3) Outcome of interest #1 HR for AD 2.08 (1.15 – 3.79) 

certificatesgiven. Quality assFor observ1) Unbias

cohort? 

2) Selectio

differenYes 

3) Sample 

differen

4) Adequa

cohort? 

5) Validat

ascerta

6) Validat

ascertaPartial 

7) Outcom

exposu

8) Adequa9) Comple10) Analys

confou

11) Analytic 

Yes 

Rea, Breitner, Psaty, et al., 2005 The Cardiovascular Health Study (CHS) 

Geographical location: 4 US communities in NC, SA, MD, & PA Setting:Community Study design: Prospective cohort Number of 

Age:NR Mean 71-72 for 5888 participants in the parent study Sex:

Female: NR Male: NR (Reported in person years) 

Risk factor/exposure

1:Statin Method of assessing risk factor/exposure 1:Direct measurement – baseline use from Rx bottles; reassessed annually 

1) Follow-up rate: > 95% HR for AD (95% CI) Adjusted for age, sex, educational level, baseline alcohol consumptin, baseline MMSE, coronary heart disease status, stroke status. Never use (216 events/1,000 person years), HR 1 (ref) Stain ever use (21 events/1,000 

CommentsOverlappinal., 2005, breported Quality assFor observ1) Unbias

cohort? 

2) Selectio

differenYes 
B-217

Study Study Information Participants Risk Factor and 

Outcome Assessment 

Results Comments

participants enrolled:2798 Duration of follow up:Mean = 6 yrs Time from risk factor assessment to final cognitive assessment:Median 5 yrs? 

Race/ethnicity:

NR Baseline cognitive status:Non-demented Inclusion criteria: Living in study community; ≥ 65 yo; 

able to respond to questions Exclusion criteria:Dementia; institutionalized; CA Tx; wheelchair-bound 

Risk factor/exposure

2:Age, sex, education level, baseline alcohol consumption, coronary heart disease, stroke status Method of assessing risk factor/exposure 2:Self-report Covariates/potential confounders adjusted for in analyses: age, sex, educational level, baseline alcohol consumptin, baseline MMSE, coronary heart disease status, stroke status. Method(s) of assessing cognitive status:NINCDS-ADRDA OR DSM-IV Other – Included CESD for depression Informant interview?:Yes 

person years) HR 1.21 (0.76 to 1.91)HR for mixed AD/Vascular Dementia (95% CI) Adjusted for age, sex, educational level, baseline alcohol consumptin, baseline MMSE, coronary heart disease status, stroke status. Never use (137 events/1,000 person years), HR 1 (ref) Stain ever use (9 events/1,000 person years) HR 0.87 (0.44 to 1.72)No dose-response for duration of statin use. HR (95% CI) for AD < 1 year statin: 1.52 (0.78 to 2.98) 1 to 3 years statin: 1.05 (0.49 to 2.24) > 3 years statin: 1.04 (0.42 to 2.56) No relationship with statin lipophilia Lipophilic HR 1.03 (0.57 to 1.86) Less lipophiilic: HR 1.58 (0.80 to 3.11) Sensitivity analysis show no difference when restricted to subjects with clinical CAD or Total cholesterol >/200 mg/dl; No interactin effects between statins and - age >75 vs. younger; sex; race; smoling status, HTN, DM, clinical cerebrovascular disease, APOEe4 genotype, CRP. 

3) Sample 

differen

4) Adequa

cohort? 

5) Validat

ascerta

6) Validat

ascertaYes 

7) Outcom

exposu

8) Adequa9) Comple10) Analys

confou

11) Analytic 

Yes 

Reitz, den Heijer, van Duijn, et al., 2007 

Geographical location: Ommoord District of Rotterdam, The Netherlands 

Age:Mean (SD): 69.5 (9.1) Sex: [n (%)] 

Female: 4221 (59.9%)

Risk factor/exposure 1:smoking Method of assessing 

1) Follow-up rate: reports follow-up rate of 99.9% with respect to dementia 2) Important baseline differences: 

CommentsNone Quality assFor observ
B-218

Study Study Information Participants Risk Factor and 

Outcome Assessment 

Results Comments

Rotterdam Study 

Setting:Community Study design: Prospective cohort Number of participants enrolled:6868 Duration of follow up:Mean follow-up 7.3 +

4.3 yrs Time from risk factor assessment to final cognitive assessment: mean follow-up 7.1 yrs 

Male: 2647 (40.1%) Race/ethnicity: [n (%)] NR Baseline cognitive status:Non-demented Inclusion criteria: Participation in the Rotterdam Study Exclusion criteria:Prevalent dementia; missing information on smoking history 

risk factor/exposure 1:Self-report Covariates/potential confounders adjusted for in analyses:Age Sex Educational level ETOH use apoE Method(s) of assessing cognitive status:NINCDS-ADRDA DSM Informant interview?:Yes (at least for those who refused cognitive eval) or who had CAMDEX as second stage of case identification. 

NR 3) Outcome of interest #1 Current smokers had greater risk of incident AD 4) Outcome of interest #2 Current smokers without an APOE e4 allele had greater risk of incident AD 5) Outcome of interest #3 Current smokers with an APOE e4 allele were not at greater risk of incident AD 

1) Unbias

cohort?

2) Selectio

differenfactors

3) Sample 

differen

4) Adequa

cohort?

5) Validat

ascerta

6) Validat

ascertayes 

7) Outcom

exposu

8) Adequa9) Comple10) Analys

confou

11) Analyti

yes 

Reitz, Luchsinger, Tang, et al., 2005 WHICAP 

Geographical location: Washington Heights, Hamilton Heights, and Inwood, in northern Manhattan, NY Setting:Community Study design:

Prospective cohort 

Age:Mean (SD): 75.6 (5.4) Sex: [n (%)] 

Female: 558 (70.5%0 Male: 233 (29.5%) Race/ethnicity: [n (%)] Hispanic 384 (48.6%) White 152 (19.2%) Black 250 (31.6%) DK 5 (0.6%) 

Risk factor/exposure

1:smoking Method of assessing risk factor/exposure 1:Self-report Covariates/potential confounders adjusted for in 

1) Follow-up rate: only included subjects who have 3 waves of follow-up 791/1613 (not demented at baseline and had smoking data available) 2) Important baseline differences: Current smokers more likely to be male and more likely to be African American 3) Outcome of interest #1 

CommentsQuestion 2 Quality assFor observ1) Unbias

cohort?

2) Selectio

differenfactors

3) Sample 

differen
B-219

Study Study Information Participants Risk Factor and 

Outcome Assessment 

Results Comments

Number of participants enrolled:791 Duration of follow up:About 5 years Time from risk factor assessment to final cognitive assessment:about 5 years 

Baseline cognitive status:Normal Inclusion criteria: Medicare recipients ≥

65 yo; without dementia or cognitive impairment; provided complete smoking information; had at least 3 f/u visits Exclusion criteria:

Dementia or CIND @ baseline; smoking information unavailable; < 3 f/u visits 

analyses:Age Race Sex Educational level HTN, Heart disease DM APOE Method(s) of assessing cognitive status: Other – decline on cognitive tests Informant interview?:No 

Current or past smoking was not associated with more rapid cognitive decline in the whole sample (p = 0.2) 4) Outcome of interest #2 Current smokers > 75 years showed greater decline on memory tasks (p=0.02). There was no significant difference by smoking status for those < 75 years or on any subgroup 

on the abstract/visuospatial tasks. 5) Outcome of interest #3 In those without an APOE e4 allele, the current smoking was associated with increased risk of decline on memory among those > 75 yrs. There was no significant difference for those < 75 years, the 

abstract/visuospatial tasks or individuals with at least one APOE e4 allele. 

4) Adequa

cohort?

5) Validat

ascerta

6) Validat

ascertaYes 

7) Outcom

exposu

8) Adequa9) Comple

Partiall

10) Analys

confou

11) Analyti

Yes 

Reitz, Tang, Manly, et al., 2007 Washington Heights – Inwood Columbia Aging Project (WHICAP) 

Geographical location: Northern Manhattan, NY, USA Setting:Community Study design:

Prospective cohort Number of participants enrolled:

1772 Duration of follow up: baseline (1992-94) 

Age:Mean (SD): 76.3 (6.1) Sex:

Female: 69.4% Male: 30.6% Race/ethnicity:White 22.6% Black 33.6% Hispanic 43.9% “(percentages do not total 100 because of rounding)” Baseline cognitive 

Risk factor/exposure

1:HTN at baseline Method of assessing risk factor/exposure 1:Self-report Direct measurement Covariates/potential confounders adjusted for in analyses:Age, Race, Sex Educational level, apoE4, stroke, dm, 

1) Follow-up rate: “about half” were evaluated at the third follow up for one section (change over time) it says 79% had at least 3 intervals, 59% had 4 or more intervals, but it doesn’t say if this is really the whole sample 2) Important baseline differences: NR 3) Outcome of interest #1 risk of all cause mci with htn 1.2 (0.81 – 1.69) 

CommentsNone Quality assFor observ1) Unbias

cohort? 

2) Selectio

differenYes 

3) Sample 

differen

4) Adequa

cohort? 

5) Validat

ascerta

6) Validat
B-220

Study Study Information Participants Risk Factor and 

Outcome Assessment 

Results Comments

then every 18 mos. for three additional waves; mean of 4.7 years Time from risk factor assessment to final cognitive assessment:Mean of 4.7 years 

status:Non-demented Not mci Inclusion criteria:  No MCI or dementia at baseline  Had at least one follow-up interval  Had complete information to ascertain MCI Exclusion criteria:

 Prevalent dementia  Prevalent MCI  Unavailable for follow-up 

heart disease, LDL level Method(s) of assessing cognitive status:Petersen’s criteria referenced but not really

Informant interview?:Petersen’s criteria referenced but informant missing 

amnestic mci 0.90 (0.54 – 1.47) nonamnestic mci 1.60 (0.93 – 2.85) 

ascertaPartial 

7) Outcom

exposu

8) Adequa9) Comple

Can’t T

10) Analys

confou

11) Analytic 

Yes 

Reitz, Tang, Luchsinger, et al., 2004 Washington Heights – Inwood – Columbia Aging Project (WHICAP) 

Geographical location: Northern Manhattan, NY, USA Setting:Community Study design: Prospective cohort Number of participants enrolled:4316 Duration of follow up:4.8 +/- 2.9 years Time from risk factor assessment to final 

Age:Range: > 65 years 

Sex: [n (%)] NR Race/ethnicity:NR Baseline cognitive status:Non-demented Inclusion criteria:  Medicare recipients  > 65 years of age 

 Residing in northern Manhattan, NY Exclusion criteria: Prevalent dementia 

Risk factor/exposure

1:Plasma lipids Method of assessing risk factor/exposure 1:direct measurement cholesterol and lipid profile measured by fasting blood sample obtained at initial assessment Risk factor/exposure 2:Diabetes mellitus Method of assessing risk factor/exposure 2:self-report 

1) Follow-up rate: 1168/2126 = 54.9% 2) Important baseline differences: NR 3) Outcome of interest #1Total cholesterol: lower cholesterol is associated with lower risk of AD in a model adjusted for BMI, APOE, diabetes, heart disease and hypertension (trend test P=.04), but does not reach significance in a model adjusted for sex, age, education and race (trend test P=.07). No other factors reached significance in either model (NonHDL-C, HDL-C, triglycerides or LDLC) 4) Outcome of interest #2 

CommentsAnalysis fohypertensiopercentage HTN in incigroups repSelf report hypertensioalso asked hypertensioto be underQuality assFor observ1) Unbias

cohort? 

2) Selectio

differenYes 

3) Sample 
B-221

Study Study Information Participants Risk Factor and 

Outcome Assessment 

Results Comments

cognitive assessment:4.8 +/- 2.9 years 

 Race other than those listed above  No blood available 

Risk factor/exposure 3: hypertension Method of assessing 

risk factor/exposure 3:self-report Covariates/potential confounders adjusted for in analyses:Age Race Sex Educational level Additional models adjusted for: BMI, diabetes mellitus, hypertension, heart disease and APOE4 genotype Method(s) of assessing cognitive status: [delete all that do not apply] NINCDS-ADRDA Informant interview?:NR 

 Diabetes- no statistics calculated.  119 cases incident AD 5 untreated diabetics (4.2%); 18 treated diabetics (15.1%)  635 control subjects.  29 untreated diabetics (3.9%)  86 treated diabetics (11.5%) 5) Outcome of interest #3  Hypertension- no statistics calculated.  119 cases incident AD  22 untreated htn (18.5%)  39 treated htn (32.8%)  635 control subjects  125 (16.8%) untreated htn  275 (36.9%) treated htn 

differen

4) Adequa

cohort? 

5) Assess6) Assess

Yes 

7) Outcom

exposu

8) Adequa9) Comple10) Analys

confou

11) Analytic 

Yes 

Rondeau, JacqminGadda, Commenges, et al., 

Geographical location: Gironde and Dordogne, France 

Age:At 10 yr f/u: Mean (SD):  PAQUID sample: 82.5 ALMA sample: 82.3 

Risk factor/exposure 1:exposure to aluminum in drinking water 

1) Follow-up rate: 1925/3970 nondemented at baseline

2) Important baseline differences: Statistical comparisons NR 

CommentsQuestions Quality assFor observ
B-222

Study Study Information Participants Risk Factor and 

Outcome Assessment 

Results Comments

2009 PAQUID 

Setting:Community Study design: Prospective cohort Number of participants enrolled:1925 Duration of follow up:11.3 yrs (mean) Time from risk factor assessment to final cognitive assessment:Uncertain, but estimated range from 0-8 yrs (Not entirely clear that all exposure data collected prior to time point for final cognitive outcome) 

Sex: [n (%)] 

Female: 1,181 (61.4) Male: 744 (38.6) Race/ethnicity: [n (%)] NR Baseline cognitive status:Non-demented Inclusion criteria: Age >65, living at 

home, in specific region of France Exclusion criteria:None except as covered by inclusion criteria 

Method of assessing risk factor/exposure 1:Self-report Other – chemical analyses of drinking water in geographic area Covariates/potential confounders adjusted for in analyses:Age Gender Educational level Wine consumption Place of residence (urban vs rural) Cohort (ALMA or PAQUID) Method(s) of assessing cognitive status:NINCDS-ADRDA DSM Other – change over time on MMSE Informant interview?:No 

3) Outcome of interest #1Greater decline on MMSE for every 0.1 mg/day higher aluminum intake based on daily consumption (p=0.001) or geographic exposure (<0.001). Silica intake was not associated with cognitive decline. Associations no longer significant when the demented were excluded suggesting that aluminum intake only associated with decline as part of the dementing process. 4) Outcome of interest #2 RR = 1.34 (95% CI: 1.09-1.65) –increased risk of AD for ≥0.1mg/day consumption of aluminum. No dose-response relationship 5) Outcome of interest #3 R=0.88 (95% CI: 0.79-0.99) lower risk of AD for each 10 mg/day higher intake of silica Exposure to aluminum or silica based on geographic exposure not associated with AD 

1) Unbias

cohort? 

2) Selectio

differenYes 

3) Sample 

differen

4) Adequa

cohort? 

5) Validat

ascerta

6) Validat

ascertaPartial 

7) Outcom

exposu

8) Adequa9) Comple

Partial 

10) Analys

confou

11) Analytic 

Yes 

Rovio, Kareholt, Helkala, et al., 2005 Cardiovascular risk 

Geographical location: Kuopio & Joensuu, Finland Setting:Community 

Age:At midlife exam:

Mean (SD): 50.6 (6.0) Range: 39-64 At re-examination:

Mean (SD): 71.6 (4.1) 

Risk factor/exposure 1:Leisure-time physical activity at midlife Method of assessing risk factor/exposure 

1) Follow-up rate: 1449 of 2000 randomly selected (72.5%) participated. 434 refused f/u, and 107 refused due to poor health (total refusals = 551). F/U rate not calculable 

CommentsRovio 2007 Quality assFor observ1) Unbias

cohort? 
B-223

Study Study Information Participants Risk Factor and 

Outcome Assessment 

Results Comments

factors, Aging and Incidence of Dementia (CAIDE) study North Karelia Project FINMONICA study 

Study design:

Prospective cohort Sampled once at midlife (1972, 1977, 1982 or 1987) and again in 1998 Number of participants enrolled:

1449 of 2000 randomly selected (72.5%) Duration of follow up:21 yrs (SD 4.9) Time from risk factor assessment to final cognitive assessment:21 yrs (SD 4.9) 

Range: 65-79 Sex:

Female: 900 (62.1%) Male: 549 (37.9%) Race/ethnicity:NR Baseline cognitive status: NR but unlikely had cognitive impairment in midlife at baseline Inclusion criteria: Survivors of 4 separate samples of the North Karelia Project and FINMONICA study, lived in 2 geographically defined areas; complete data on outcome, physical activity, and covariates.Exclusion criteria:NR 

1:Self-report: “How often do you participate in leisuretime physical activity that lasts at least 20-30 minutes and causes breathlessness and sweating?” “active” = active > 2 

times/wk “sedentary” = < 2 times/wk Covariates/potential confounders adjusted for in analyses:Age Sex Educational level f/u time locomotor disorders APOE Clinical variables Smoking status Alcohol use Method(s) of assessing cognitive status:MMSE for screening (<24 MMSE score) NINCDS-ADRDA DSM-IV Informant interview?:No 

2) Important baseline differences:Those who were sedentary were slightly younger at baseline and slightly longer f/u interval. Relatively more women than men were sedentary. 3) Outcome of interest #161 incident cases of dementia (48 had AD) 4) Outcome of interest #2 Dementia (n=1251) Crude OR 0.55 (95% CI, 0.30-1.01) Fully adjusted OR 0.47 (0.25-0.90) 5) Outcome of interest #3 AD (n=1239) Physical activity reduced the risk of AD in all 4 models (crude and 3 adjusted). Active individuals had approximately 60% lower odds of AD than sedentary ones. Crude OR 0.45 (95% CI, 0.22-0.93) Fully adjusted OR 0.35 (0.16-0.80) Physical activity had same effect on both sexes. APOE appears to be an effect modifier: among APOE carriers there is an association between physical activity and AD, but not among noncarriers. 

2) Selectio

differenYes 

3) Sample 

differen

4) Adequa

cohort? 

5) Validat

ascerta(exercis

6) Validat

ascertaPartial. MMSE

7) Outcom

exposu

8) Adequa9) Comple10) Analys

confou

11) Analytic 

Yes 
B-224

Study Study Information Participants Risk Factor and 

Outcome Assessment 

Results Comments

Rovio, Kareholt, Viitanen, et al., 2007 Cardiovascular risk factors, Aging and Incidence of Dementia (CAIDE) study North Karelia Project FINMONICA study 

Geographical location: Kuopio & Joensuu, Finland Setting:Community Study design: Prospective cohort Sampled once at midlife (1972, 1977, 1982 or 1987) and again in 1998 Number of participants enrolled:1449 Duration of follow up:Mean: 20.9 years (SD 4.9) Time from risk factor assessment to final cognitive assessment:21 years (mean) 

Age:At midlife exam:

Mean (SD): 50.4 (6.0) Median: Range: 39-64 At re-examination:

Mean (SD): 71.3 (4.0) Median: Range: 65-79 Sex:Female: 900 (62.1%) Male: 549 (37.9%) Race/ethnicity:NR Baseline cognitive status:NR, but unlikely they were impaired at baseline in midlife Inclusion criteria:  Survivors of 4 separate samples of the North Karelia Project and FINMONICA study; lived in two geographically defined areas; complete data on outcome, physical activity, and covariatesExclusion criteria:NR 

Risk factor/exposure 1:Work-related physical activity Method of assessing risk factor/exposure 1:Self-report Occupational physical 

activity: 

“How physically heavy is your work?” Dichotomized to sedentary vs. active groups. Dichotomization point NR. Total daily commuting 

physical activity: 

“How many minutes do you walk, bicycle, or have some other physical activity when you are going to and from work?” Categorized: 1) not at all 2) < 59 minutes 

3) > 60 minutes Covariates/potential confounders adjusted for in analyses:Age Sex Educational level 

1) Follow-up rate: 1449 of 2000 randomly selected (72.5%). Remaining 27.5% “nonparticipants.” Missing data on independent variables in 291 persons. Analytical sample = 1158 (57.9%) 2) Important baseline differences: NA 3) Outcome of interest #1 44 incident cases of dementia (33 AD). 4) Outcome of interest #2 Neither occupational (OR, 1.90; 95% CI, 0.73-4.95) nor commuting physical activity (OR, 0.48; 95% CI 0.09-2.58) were associated with the risk of AD. 

CommentsNone Quality assFor observ1) Unbias

cohort? 

2) Selectio

differenYes 

3) Sample 

differen

4) Adequa

cohort? 

5) Validat

ascerta

6) Validat

ascertaPartial 

7) Outcom

exposu

8) Adequa9) Comple10) Analys

confou

11) Analytic 

Yes 
B-225

Study Study Information Participants Risk Factor and 

Outcome Assessment 

Results Comments

F/u time Locomotor symptoms Occupation Income at midlife Leisure physical activity APOE Vascular disorder Smoking status Method(s) of assessing cognitive status: MMSE for screening (screen + if score <24)  NINCDS-ADRDA  DSM-IV Informant interview?:No 

Ryan, Carriere, Scali, et al., 2009 ESPRIT substudy 

Geographical location: Montpelier, France Setting:Community Study design: Prospective cohort Number of participants enrolled:996 Duration of follow up:4 yrs Time from risk factor assessment to final 

Age:Mean (SD): 72.8 (5.5) Sex: [n (%)] 

Female: 996 (100%) Male: 0 (0%) Race/ethnicity: [n (%)] NR Baseline cognitive status:Non-demented Inclusion criteria: >65 yrs, noninstitutionalized and 

resided in Montpelier, France 

Risk factor/exposure 1:lifetime estrogen exposure Method of assessing risk factor/exposure 1:Self-report of reproductive factors associated with estrogen exposure and use of exogenous hormone treatment Covariates/potential confounders adjusted for in analyses:

1) Follow-up rate: 996/1277 of non-demented at baseline2) Important baseline differences: NR 3) Outcome of interest #1

In fully adjusted model, no association between lifetime estrogen exposure and risk of substantial decline on any cognitive measures 

CommentsQuestion 2 Quality assFor observ1) Unbias

cohort? 

2) Selectio

differenYes 

3) Sample 

differen

4) Adequa

cohort? 

5) Validat

ascerta

6) Validat

ascertaYes 
B-226

Study Study Information Participants Risk Factor and 

Outcome Assessment 

Results Comments

cognitive assessment:Lifetime 

Exclusion criteria:

None except as covered by exclusion criteria 

Age Educational level Marital status Depressive symptoms Caffeine intake Physical impairment Medical conditions Baseline cognitive status Method(s) of assessing cognitive status:DSM Other – substantial decline on cognitive tests defined as lowest quintile of the difference between baseline score and score at either of the follow-up visits Informant interview?:No 

7) Outcom

exposu

8) Adequa9) Comple10) Analys

confou

11) Analytic 

Yes 
B-227

Study Study Information Participants Risk Factor and 

Outcome Assessment 

Results Comments

Saczynski, Pfeifer, Masaki, et al., 2006 HAAS Honolulu Asia Aging Study 

Geographical location: Honolulu, Hawaii Setting:Community Study design: Prospective cohort Number of participants enrolled:3,508 Duration of follow up:27.5 (mean) yrs for midlife social measures and 4.6 (mean) yrs for late life Time from risk factor assessment to final cognitive assessment:27.5(mean) yrs for midlife social measures and 4.6 (mean) yrs for late life 

Age:Mean (SD): 76.8 years Sex: [n (%)] 

Female: 0 (0%) Male: 2513 (100%) Race/ethnicity: [n (%)] All of Japanese origin. Baseline cognitive status:Non-demented Inclusion criteria: JapaneseAmerican men born between 1900 and 1919 who were living on the island of Oahu, Hawaii, at the time of enrollment in 1965 Exclusion criteria:Those who had dementia at the 1991 exam were excluded from the incident cohort. 

Risk factor/exposure 1:Social engagement Method of assessing risk factor/exposure 1:Self-report marital status; living arrangement; participation in social, political, or community groups; participation in social events with coworkers; and the existence of a confidant relationship(composite score of the above) Covariates/potential confounders adjusted for in analyses:Age Education Cognitive Abilities Screening Instrument score, apolipoprotein E e4 allele status, History of stroke, coronary heart disease, depression, and disability Method(s) of 

assessing cognitive status:NINCDS-ADRDA 

1) Follow-up rate:Of 3,508, 521died before examination 5, 359 did not participate in examination 5, and 115 had missing data Final sample: 2,513 men Excluding those who died, rate of follow up was 84.13% 2) Important baseline differences: Compared with men who died or dropped out of the sample, those who survived were younger and had higher CASI scores, more education, less cerebrovascular disease , less coronary heart disease, and less impairment in activities of daily living.

Those with low mid-life or late-life social engagement scores were older at baseline. 3) Outcome of interest #1222 men diagnosed with incident dementia, 134 (60%) had Alzheimer’s disease, 47 had vascular dementia, and 41 had other types of dementia 4) Outcome of interest #2 Midlife social engagement not associated with incident dementia. Compared to those who had highest social engagement in late life, those who had the lowest social engagement had a higher risk of developing dementia. HR= 2.34 (1.18, 

4.65)

CommentsQuestion 1 Results predementia. NAD though they analyzfound similQuality assFor observ1) Unbias

cohort? 

2) Selectio

differenYes 

3) Sample 

differen

4) Adequa

cohort? 

5) Validat

ascerta

6) Validat

ascertaYes 

7) Outcom

exposu

8) Adequa9) Comple10) Analys

confou

11) Analytic 

Yes 
B-228

Study Study Information Participants Risk Factor and 

Outcome Assessment 

Results Comments

DSM Informant interview?:Yes 

5) Outcome of interest #3Compared to those who had consistently high social engagement in mid and late life, those whose social engagement decreased from mid to late life had a higher risk of incident dementia. HR= 1.87 (1.12, 

3.13)

Saxby, Harrington, Wesnes, et al., 2008 Study on Cognition and Prognosis in the Elderly (SCOPE) 

Geographical location: Tyneside, UK (one site from a multi-center trial) Setting:Clinical Study design:

RCT Test intervention: Candesartan 8-16mg; mean dose = 12 mg Other antihypertensives allowed Comparator intervention(s): Placebo, other antihypertensives allowed Number of participants enrolled:

257; 228 available for analysis Duration of follow up: 

Age:Mean: 76 years Range: 70 – 89 years Sex: [n (%)] 

(of those available for analysis) Female: 107 (47%) Male: 121 (53%) Race/ethnicity: [n (%)] NR Baseline cognitive status: eliminated theoretically those who had mmse < 24 or who had sig decline in cdr and iqcode but no one was actually eliminated using these criteria Inclusion criteria:  Hypertensive  70 – 89 years Exclusion criteria: MMSE score < 24  Reported significant decline in cognitive 

Covariates/potential confounders adjusted for in analyses: age, number of errors on the New Adult Reading Test, baseline cognitive performance Method(s) of assessing cognitive status: change in test score measured every 12 months in 5 domains: Episdoic memory (5 tests); Attention (3 tests); Working memory (2 tests); Speed of cognition (# tests not given); Executive function (4 tests) Informant interview? no 

1) Follow-up rate: 159/228 completed maximum number of assessments – 70%; 228/257 analyzed = 88.7%, average 

proportion of the follow up period spent on active tx was 88% 2) Important baseline differences: “no baseline difference between the candesartan and placebo groups” 3) Outcome of interest #1 change in cognition between the candesartan and placebo groups as measured by coef of decline on five composite factor factor scores significant for attn (candesartan = 0.004 vs. placebo -0.036, effect size = 0.28, p= 0.04) and episodic memory (0.14 vs. -0.22, effect size = 0.28, p=0.04) but not for speed of cognition, working memory or executive functioning. 

Commentssubj 70-89 mmHg, dbp For scope o49% of canof the contrOne site froSkoog, Lith2005); only participants Quality assFor RCTs: 1) Baselin2) Valid A

assess

3) Subjec

Tell (doblind no

4) Outcom5) Incomp

addres

6) Differen

Yes 

7) Overall 8) Conflic

insignifsponsoanalysi
B-229

Study Study Information Participants Risk Factor and 

Outcome Assessment 

Results Comments

mean 44 mos, (12), range 12 – 60 mos Time from risk factor assessment to final cognitive assessment:rct administered meds 

function 9) Random

10) Allocat

adequa

Scarmeas, Levy, Tang, et al., 2001 

Geographical location: Manhattan, NY Setting:Community Study design: Prospective cohort Number of participants enrolled:1772, from 2126 of 3452 initially eligible persons. Duration of follow up:Mean 2.9 yrs (range: 0-7.2) Time from risk factor assessment to final cognitive assessment:Mean 2.9 yrs (range: 0-7.2) 

Age:Incident dementia: 78.2 + 6.5 No incident dementia: 75.3 +6.2 Sex:Females: Incident dementia: 69% No incident dementia: 68% Males: Incident dementia: 31% No incident dementia: 32% Race/ethnicity:NR Baseline cognitive status:Non-demented Inclusion criteria: Cohort identified from a 

Risk factor/exposure 1:Leisure activities Method of assessing risk factor/exposure 1:Self-report. Asked about 13 different activities. When dichotomized, “low”= <6 and “high” = >6 

Covariates/potential confounders adjusted for in analyses:Ethnicity Sex Educational level Occupation Clinical variables Method(s) of assessing cognitive status:NINCDS-ADRDA DSM Other – Care Diagnostic Interview, clinical evaluation, 

1) Follow-up rate: 2126 initially selected. 327 demented at 1st eval and excluded, 

leaving 1799. Leisure activity available for final sample of 1772. 1772/2126 = 83% 2) Important baseline differences: NA 3) Outcome of interest #1207 incident cases of dementia (153 with probable or possible AD) 4) Outcome of interest #2--dementia With activity as a continuous variable in an age-stratified Cox model, higher scores were associated with a reduced risk of dementia (RR, 0.88; 95% CI, 0.83-0.93). Associate remained after adjusting for ethnicity, education, and occupation. There appears to be a synergistic effect of leisure activities and education, and leisure activities and occupation. 5) Outcome of interest #3--AD 

CommentsAll of the rebut the authabout AD. Quality assFor observ1) Unbias

cohort? 

2) Selectio

differenYes 

3) Sample 

differen

4) Adequa

cohort? 

5) Validat

ascerta

6) Validat

ascertaYes 

7) Outcom

exposu

8) Adequa9) Comple10) Analys

confou

11) Analytic 

Yes 
B-230

Study Study Information Participants Risk Factor and 

Outcome Assessment 

Results Comments

probability sample of Medicare beneficiaries residing in northern Manhattan. 65 years or older, nondemented, seen for at least one follow-up evaluation. Exclusion criteria:Recent h/o stroke or Parkinson’s Disease 

neuropsych eval. Informant interview?:No 

No results about AD other than reporting that 153 participants had probable or possible AD at f/u, and that 27 had possible AD with concomitant stroke. 

Scarmeas, Luchsinger, Schupf, et al., 2009 WHICAP 

Geographical location: New York, New York Setting:Community Study design: Prospective cohort Number of participants enrolled:1880 Duration of follow up:Mean (sd): 5.4 (3.3) yrs Time from risk factor assessment to final cognitive assessment:NR 

Age:Mean (SD): 77.2(6.6) Sex: [n (%)] 

Female: 1293 (69) Male: 587 (31) Race/ethnicity: [n (%)] White 531 (28) Black 605 (32) Hispanic 715 (38) Other 29 (2) Baseline cognitive status:Non-demented Inclusion criteria: Cohort identified from a probability sample of Medicare beneficiaries residing in northern Manhattan. 65 years or older, nondemented, seen for at least one follow-up evaluation. 

Risk factor/exposure 1:Physical activity and nutrition Method of assessing risk factor/exposure 1:Self-report Covariates/potential confounders adjusted for in analyses:Age Race Sex Educational level BMI Smoking Depression Leisure activities Comorbid medical conditions Baseline CDR score APOE Interval between 1st

1) Follow-up rate: 1880/2247 with dietary and physical activity data2) Important baseline differences: Less physically active individuals were more likely to be female, older, Hispanic, smokers, depressed, less educated, had a lower total caloric intake, higher BMI, more comorbid illnesses, and adhered less to the diet. 3) Outcome of interest #1

Considered simultaneously, both 

adherence to a Mediterranean-type diet (compared with low diet score) HR for middle diet score was 0.98 [95% CI, 0.72-1.33]; the HR for high diet score was 0.60 [95% CI, 0.42-0.87]; P=.008 for trend) and physical 

activity compared with no physical activity, the HR for some physical activity was 0.75 [95% CI, 0.54-1.04]; the HR for much physical activity was 0.67 [95% CI, 0.47-0.95]; P=.03 for 

trend) were associated with lower AD 

CommentsQuestion 1 Quality assFor observ1) Unbias

cohort? 

2) Selectio

differenYes 

3) Sample 

differen

4) Adequa

cohort? 

5) Validat

ascerta

6) Validat

ascertaYes 

7) Outcom

exposu

8) Adequa9) Comple10) Analys

confou

11) Analytic 

Yes 
B-231

Study Study Information Participants Risk Factor and 

Outcome Assessment 

Results Comments

Exclusion criteria:NR 

dietary and 1st physical 

activity measure Caloric intake Method(s) of assessing cognitive status:NINCDS-ADRDA DSM Informant interview?:No 

risk. 4) Outcome of interest #2 Compared with individuals neither adhering to the diet nor participating in physical activity (low diet score and no physical activity; absolute AD risk of 19%), those both adhering to the diet and participating in physical activity (high diet score and high physical activity) had a lower risk of AD (absolute risk, 12%; HR, 0.65 [95% CI, 0.44-0.96]; P=.03 for trend).

Scarmeas, Stern, Mayeux, et al., 2009 WHICAP subsets 

Geographical location:Northern Manhattan, NY Setting:Community Study design Prospective cohort Number of participants enrolled:1875  1393 cog normal  482 MCI Duration of follow up: 4.5 (2.7) years range 0.9-16.4 yrs Time from risk factor assessment to final cognitive assessment:evaluated every 1.5 yrs 

Age:Mean (SD): 76.9 (6.5)  Cog norm 76.7 (6.5)  MCI 77.5 (6.6) Sex: [n (%)] 

Female: 1272 (68%)  Cog norm 946 (68%) MCI 326 (68%) Male: 603 (32%)  Cog norm 447 (32%) MCI 156 (32%) Race/ethnicity: [n (%)] White 558 (30%)  Cog norm 434 (31%) MCI 124 (26%) Black 623 (33%)  Cog norm 479 (34%) MCI 144 (30%) Hispanic 687 (36%)  Cog norm 473 (34%) MCI 214 (44%) Other 7 (1%)  Cog norm 7 (1%)  MCI 0 (0%) 

Risk factor/exposure 1:Mediterranean diet Method of assessing risk factor/exposure 1:Self-report Covariates/potential confounders adjusted for in analyses: Age, Race, Sex, education, apoE, bmi, time betw dietary assessment and cog assessment, Method(s) of assessing cognitive status:NINCDS-ADRDA DSM Mci dx’d retrospectively

1) Follow-up rate: subject pool selected from larger study cohort on basis on cognitive status and follow up. 2) Important baseline differences: Hispanic subjects adhered more to med. Diet. Black subj adhered less, higher adherence associated with lower caloric intake. 3) Outcome of interest #1 using lowest tertile of adherence as reference, middle tertile had hr 0.83 (0.62 – 1.12), highest tertile hr 0.72 (0.52-1.00) for development of mci 4) Outcome of interest #2 for progression from mci to ad, middle tertile hr 0.55 (0.34 – 0.90), highest tertile hr 0.52 (0.30 – 0.91) 

Comments

Questions Diagnosis oretrospectivQuality assFor observ1) Unbias

cohort? 

2) Selectio

differenYes 

3) Sample 

differen

4) Adequa

cohort? 

5) Validat

ascerta

6) Validat

ascertaNo 

7) Outcom

exposu

8) Adequa9) Comple

Can’t T
B-232

Study Study Information Participants Risk Factor and 

Outcome Assessment 

Results Comments

time between cog assessment and dietary assessment 

Baseline cognitive status:Non-demented Inclusion criteria: Participated in either 1992 or 1999 WHICAP study, Medicare beneficiary, residing in a designated geographic area of northern Manhattan, NY Exclusion criteria:

NR 

Informant interview?:No 

10) Analys

confou

11) Analytic 

Yes 

Scarmeas, Stern, Tang, et al., 2006 WHICAP 

Geographical location: Northern Manhattan, NY, USA Setting:Community Study design: Prospective cohort Number of participants enrolled:2,258 Duration of follow up:Mean= 4.0 (3.0) yrs Range = 0.2-13.9 yrs Time from risk factor assessment to final cognitive 

Age:Mean (SD): 77.2 (6.6) Sex: [n (%)] 

Female: 1514 (68) Male: 720 (32) N slightly different than total N due to non-AD dementia Race/ethnicity: [n (%)] AA 722 (32) White 620 (28) Hispanic 848 (38) Other 36 (2) 

N slightly different 

than total N due to non-AD dementia Baseline cognitive status:Non-demented 

Risk factor/exposure

1:Mediterranean diet Method of assessing risk factor/exposure 1:Self-report Covariates/potential confounders adjusted for in analyses:Age Race Sex Educational level Sample cohort APOE Caloric intake Smoking Medical comorbidity 

1) Follow-up rate: 2258/2784 (denominator excludes those who did not participate in fup due to death) 2) Important baseline differences: Ind who developed dementia were older, less educated, and had higher BMI. Among those who developed dementia, there was a higher proportion of Hispanics and a lower proportion of whites. 3) Outcome of interest #1Higher adherence to a Mediterranean diet was associated with decrease in risk of AD: Continuous measure of Mediteranean diet (HR=0.91; 0.83-0.98) Categorical measure: High tertile (HR=0.60; 0.42-0.87) 

CommentsQuestion 1 Quality assFor observ1) Unbias

cohort? 

2) Selectio

differenYes 

3) Sample 

differen

4) Adequa

cohort? 

5) Validat

ascerta

6) Validat

ascertaYes 

7) Outcom

exposu

8) Adequa
B-233

Study Study Information Participants Risk Factor and 

Outcome Assessment 

Results Comments

assessment:Estimated – 2.5 yrs – risk factor data collected at 1st followup and follow-ups were 

every 1.5 yrs 

Inclusion criteria: Medicare recipients age >65 residing in 

Northern Manhattan. Two separate cohorts were used WHICAP 1992 and WHICAP 1999. Exclusion criteria:None 

index BMI Method(s) of assessing cognitive status:NINCDS-ADRDA DSM Informant interview?:

No 

 9) Comple

10) Analys

confou

11) Analytic 

Yes 

Schaefer, Bongard, Beiser, et al., 2006 Framingham 

Geographical location: Framingham, MA, USA Setting:Community Study design: Prospective cohort Number of participants enrolled:899 Duration of follow up:9.1 yrs Time from risk factor assessment to final cognitive assessment:9.1 yrs 

Age:Mean (SD): 76 (5.0) yrs Sex: [n (%)] 

Female: 571 (63.5) Male: 328 (36.5) Race/ethnicity: [n (%)] NR Baseline cognitive status:Non-demented Inclusion criteria: In 1948, men and women between the ages of 30 and 62 from the town of Framingham, MA followed with biennial exams since Exclusion criteria:none 

Risk factor/exposure

1:DHA Method of assessing risk factor/exposure 1:Direct measurement Self-report Method of assessing risk factor/exposure 2:Self-report Proxy report Direct measurement Medical record Other Covariates/potential confounders adjusted for in analyses:Age Sex Educational level APOE 

1) Follow-up rate: difficult to get meaningful numbers. 899 had plasma measures out of the 1208 that completed the wave of data collection used as the baseline for these analyses. Then subjects followed until point of censoring. 2) Important baseline differences: NR 3) Outcome of interest #1Ind in upper quartile of baseline plasma PC DHA levels, compared to lower 3 quartiles, did not have sig lower risk of AD (RR=0.61; 0.31–1.18). Results for all dementia were significant (RR=0.53; 0.29-0.97) 4) Outcome of interest #2 Ind in upper quartile of dietary intake of DHA, compared to lower 3 quartiles, did not have sig lower risk of AD (RR=0.63; 0.23-1.72) 5) Outcome of interest #3 Ind who consumed fish > twice a 

CommentsQuestion 1 Quality assFor observ1) Unbias

cohort? 

2) Selectio

differenYes 

3) Sample 

differen

4) Adequa

cohort? 

5) Validat

ascerta

6) Validat

ascertaYes 

7) Outcom

exposu

8) Adequa9) Comple10) Analys

confou

11) Analytic 

Yes 
B-234

Study Study Information Participants Risk Factor and 

Outcome Assessment 

Results Comments

Homocysteine Method(s) of assessing cognitive status:NINCDS-ADRDA DSM Informant interview?:Yes 

week compared to those who consumed fish < twice a week did not 

have sig lower risk of AD (RR=0.61; 0.28-1.33) 

Schuit, Feskens, Launer, et al., 2001 Zutphen Elderly Study Seven Countries Study 

Geographical location: Zutphen, Netherlands Setting:NR. 88% lived independently at home. Study design: Prospective cohort Number of participants enrolled:560 – 347 analyzed Duration of follow up:3 years Time from risk factor assessment to final cognitive assessment:3 years 

Age:Mean (SD): 74.6 +4.3 

Sex:Female: 0 Male: 347 (100%) Race/ethnicity:NR Baseline cognitive status:Did not appear to exclude those with cognitive impairment Inclusion criteria:  Participants in the Seven Countries Study aged 65-84 at baseline  living in Zutphen. Exclusion criteria:NR 

Risk factor/exposure 1:Physical activity Method of assessing risk factor/exposure 1:Self-report. Validated questionnaire for measuring physical activity in elderly men. Summed score for total weekly activity. Categorized: 1) <30 min/day 

2) 31-60 min/day 3) > 60 min/day Risk factor/exposure 2:APOE phenotype. Method of assessing risk factor/exposure 2:Direct measurement; Isoelectric focusing followed by immunoblotting. 

1) Follow-up rate: 347 of 560 (62%). No information provided on non-responders. Non-response associated with: lower SES, and health status 2) Important baseline differences: NA 3) Outcome of interest #1—Physical activity and CDAge and education adjusted OR (95% CI) for cognitive decline, with > 60 min/day as the reference: < 30 min/day: OR 2.0 (0.7-5.6) 31- 60 min/day: OR 1.8 (0.6-5.1) 4) Outcome of interest #2—Interaction of physical activity and APOE with CD – subgroup analysis The OR of cognitive decline among inactive (<=1 hr/day) vs active (>1 hr/day) APOE e4 non-carriers: (OR, 0.9; 95%CI, 0.2-3.2) APOE e4 carriers: (OR, 3.7; 95%CI, 

CommentsOR for cognot statisticthat did not effect modiAt baselineMMSE <=2Quality assFor observ1) Unbias

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B-235

Study Study Information Participants Risk Factor and 

Outcome Assessment 

Results Comments

Covariates/potential confounders adjusted for in analyses:Age Sex Educational level Smoking Alcohol Baseline cognitive function Clinical variables Disabilities in ADL Health status Method(s) of assessing cognitive status:Cognitive decline defined as a decrease of >3 points on the MMSE. Informant interview?:No 

1.1-12.6) 6) Validat

ascertaYes 

7) Outcom

exposu

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(f/u rate 

10) Analys

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Yes 

Seeman, Lusignolo, Albert, et al., 2001 McArthur Study of Healthy Aging

Geographical location:Durham NC East Boston MA New Haven CT Setting:Community Study design: Prospective cohort Number of 

Age:Mean (SD): 74 Sex: [n (%)] 

Female: 632 (55.2%) Male: 513 (44.8%) Race/ethnicity: [n (%)] AA 206 (18%) White 940 (82%) Baseline cognitive status:

Risk factor/exposure

1:Respondents’ perception of their social network using the MacArthur battery which had both qualitative and quantitative components. Method of assessing risk factor/exposure 

1) Follow-up rate: Of 1189, 273 (23%) died before follow up. Of the remaining 916, 722 completed face to face interviews, 107 (11.7% had proxy partial interviews) and the rest refused or could not be contacted. 1145 had complete baseline data and were included in the analyses 2) Important baseline differences: At baseline, among other differences noted, men had higher income and 

CommentsThis populathe participone-third of functional abaseline. Apopulation Quality assFor observ1) Unbias

cohort? 

2) Selectio
B-236

Study Study Information Participants Risk Factor and 

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Results Comments

participants enrolled: 1189 participated 1145 analyzed Duration of follow up:7.4 YEARS SD= 4.7 months Time from risk factor assessment to final cognitive assessment:Mean of 7.4 years. 

Participants who scored in the top third of the cognitive and physical screening tests for their age group. Inclusion criteria: Age between 70-79 Physical: 1)No. reported disability on the 7-item activities of living scale. 2))No more than 1 reported mild disability on eight items tapping gross mobility and range of motion 3)Ability to maintain semi tandem balance for at least 10 s 4) Ability to stand from seated position at least 5 times in 20 s. Cognitive: 1) Scoring at least 6 or more on the SPSMQ 2) Remembering three or more of the six elements on a delayed recall of a short story. Exclusion criteria:

NR 

1:Self-report Covariates/potential confounders adjusted for in analyses:Age Race Sex Educational level Income Number of reported chronic illnesses Pulmonary function Amount of strenuous leisure activity. Amount of strenuous yard/house maintenance. Depressive symptoms Self efficacy beliefs. Method(s) of assessing cognitive status: Other – Language 18 item Boston Naming test Abstraction: 4 items from the Similarities subtest of the Wechsler’s Adult intelligence scale Spatial ability: Copying image Incidental recall of confrontation naming Delayed recall of a story 

reported more social ties overall but women reported greater involvement in groups. 3) Outcome of interest #1 After controlling for covariates, greater baseline social support was not associated with greater decline on a cognitive summary score at 7.5 year follow up: b= 1.26 p= .07. When the model was reduced by excluding baseline cognitive status and other sociodemographic factors, 

health status, behavioral and psychological variables, the relationship between baseline emotional support and cognitive decline became significant; b= 1.20, p= 0.05. 4) Outcome of interest #2 Being married (b= - 0.48, p= 0.52); Number of close ties (- 0.02, p=0.75); number of groups(- 0.13, p =0.70) were not significant predictors of cognitive decline over the same time period. 

differenYes 

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cohort? 

5) Validat

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6) Validat

ascertaYes 

7) Outcom

exposu

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confou

11) Analytic 

Yes 
B-237

Study Study Information Participants Risk Factor and 

Outcome Assessment 

Results Comments

Informant interview?:Yes Proxy interviews were conducted for some who had missing data. 

Seshadri, Beiser, Selhub, et al., 2002 Framingham 

Geographical location: Framingham, MA Setting:Community Study design: Prospective cohort Number of participants enrolled:1092 Duration of follow up: median 8 yrs (range 1 to 13) Time from risk factor assessment to final cognitive assessment:8 years on average 

Age:Mean (SD): 76 Sex: [n (%)] 

Female: 667 Male: 425 Race/ethnicity: [n (%)] NRBaseline cognitive status:Non-demented Inclusion criteria: Participation in the Framingham Study Exclusion criteria:Dementia 

Risk factor/exposure

1:hcy Method of assessing risk factor/exposure 1:Direct measurement Plasma, frozen, fasting status not indicated so most likely not. Covariates/potential confounders adjusted for in analyses:age, sex, apoE, folate and vitamins b12 and b6, education, stroke, smoking, alcohol, dm, bmi sbp at baseline Method(s) of assessing cognitive status:NINCDS-ADRDA DSM In subjects with abnormal MMSE screen Informant interview?:Yes 

1) Follow-up rate: 77% of those alive who had been free of dementia participated in this baseline visit 2) Important baseline differences: NR 3) Outcome of interest #1 Dementia n=111 (83 AD) For each 1 SD increase in logtransformed homocysteine, 

RR of AD fully adjusted for total hcy 

1.8(1.3 – 2.5)  For homocysteine>14 umol/l , adjusted HR = 1.9 (95% CI 1.2-3.0) 4) Outcome of interest #2 No association between folate, B12, B6 and incident AD (data not given) 

CommentsNone Quality assFor observ1) Unbias

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3) Sample 

differen

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5) Validat

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confouadjuste54 AD covaria

11) Analytic 

Partial, given n
B-238

Study Study Information Participants Risk Factor and 

Outcome Assessment 

Results Comments

Shadlen, Larson, Wang, et al., 2005 ACT 

Geographical location: Seattle, WA Setting:Other - HMO Study design: Prospective cohort Number of participants enrolled:2581 enrolled from ACT 2410 declared race 2168 had APOE data 2140 were analyzed @ f/u Duration of follow up:3.29 years (1.36)Time from risk factor assessment to final cognitive assessment:3.29 years (1.36)

Age: (from 2410 @ baseline) Mean (SD): 75.4 (6.2) Range: 65 - >85 Sex: [n (%)] (from 

2410 @ baseline) Female: 1431 (59.4%)Male: 979 (40.6%) Race/ethnicity: [n (%)] (from 2410 @ baseline) White 2307 (95.7%) Black 103 (4.3%) Baseline cognitive status:Non-demented Inclusion criteria: Enrolled in ACT study; free of dementia; not institutionalized; age ≥65, member of Group Health Cooperative (HMO) Exclusion criteria:Dementia, living in nursing home 

Risk factor/exposure 1:APOE Method of assessing risk factor/exposure 1:Direct measurement Risk factor/exposure 2:education Method of assessing risk factor/exposure 2:Self-report Risk factor/exposure 3:Depression Method of assessing risk factor/exposure:

CES-D Risk facot/exposure 4:Diabetes mellitus Method of assessing 

risk factor/exposure:Self-report Covariates/potential confounders adjusted for in analyses:Age 

1) Follow-up rate: 2140 with APOE and f/u data. Difficult to extract exact f/u rate. 165 discontinued and 366 died during study = 75.2% f/u rate 2) Important baseline differences: NR 3) Outcome of interest #1Education as a continuous measure was not associated with cognitive decline. 4) Outcome of interest #2 Compared to individuals without an APOE4 allele, individuals with a single APOE4 allele did not have greater CASI decline. But individuals with two APOE4 alleles experienced greater decline in cognitive performance and the magnitude of that decline decreased as years of educational attainment increased. (coefficient =0.51 (95% CI 0.12, 0.91; P = 0.011)). Generalized estimating equation analysis (GEE) Risk factors associated with change in global cognitive performance No E4 reference One E4 allele coef=-0.23 (-2.5, 2.05) P=0.846 Two E4 alleles coef=-10.08 (-16.24, -3.92) P=0.001 

CommentsQ2 – no caDepressive last f/u; thesectional aAt 4-yr f/u, sample had scores by 1points) or gSubjects wdementia dincluded in Author’s CoLower educsteep 4-yr cAPOE4 homAPOE4 hetmodifiable education cassociation and cognitiQuality assFor observ1) Unbias

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5) Validat

ascerta
B-239

Study Study Information Participants Risk Factor and 

Outcome Assessment 

Results Comments

Race Sex Years of followup Depression Diabetes Hypertension Cerebrovascular disease Method(s) of assessing cognitive status:] NINCDS-ADRDA DSM Other – longitudinal change in CASI score Informant interview?:No 

Interaction of APOE4 and education One E4 x education coef .002 (-.15, .16) P=.976 Two E4 x education coef 0.51 (.12, .91) P=.011 Outcome of interest #3Generalized estimating equation Diabetes mellitus No-reference Yes- coef -.59 (-1.14, -.04) P=.001 

6) Validat

ascertaYes 

7) Outcom

exposu

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confou

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Yes 

Shah, Wilson, Bienias, et al., 2006 Religious orders study 

Geographical location: 40 groups across US Setting:Community Study design:

Prospective cohort Number of participants enrolled:

990 in study overall; 824 in this analysis Duration of follow up: mean of 6.5 annual clinical evaluations Time from risk factor 

Age:Mean (SD): 75 (7) Sex: [n (%)] 

Female: 569 (69%) Male: 255 (31%) Race/ethnicity: [n (%)] White 750 (91%) Other 74 (9%) 

Baseline cognitive status:Non-demented Inclusion criteria: Participation in Religious Orders Study; agreement to annual clinical 

Risk factor/exposure

1:htn Method of assessing risk factor/exposure 1:Direct measurement two sitting and one standing bp averaged also figured orthostatics and did self report. Covariates/potential confounders adjusted for in analyses:Age, Sex, education, presence of apoE4, 

1) Follow-up rate: 98% did at least one follow up. 98% of possible clinical evaluations done also. (23 died before first f/u; 47 recent enrollees and not due for annual f/u) 2) Important baseline differences: bp analyzed as a continuous variable so didn’t really compare two groups. 3) Outcome of interest #1151 incident cases of AD In a fully adjusted model (presence of apoE4, use of antihypertensive meds), a “null relationship persisted” but results not shown. In age, sex and education adjusted model, the relative risk of 1 mmHg increase in 

CommentsQuestions Probable smeasured idementia; Iwith longstadied prior to Quality assFor observ1) Unbias

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2) Selectio

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5) Validat
B-240

Study Study Information Participants Risk Factor and 

Outcome Assessment 

Results Comments

assessment to final cognitive assessment:NR, annual assessments 

evaluations; no dementia @ baseline Exclusion criteria:

No f/u evaluation 

use of antihypertensive meds. Method(s) of assessing cognitive status:NINCDS-ADRDA Other: change in performance on cognitive tests over time Informant interview?:No 

sbp was 0.995 (0.986-1.004) and for dbp 1.0 (0.985-1.015) Further analyses, using history of HTN, quadratic terms for SBP and DBP, JNC VII categories of HTN, and sitting BP only, there was no association with incident AD 4) Outcome of interest #2 Again when examining cognitive decline, in a fully adjusted model “the null relationship persisted” but results are not shown. In evaluation using covariates for age, sex, education, sbp x time had estimate of 0.00 with SE 0.00 and p =0.237, dbp x time had estimate 0.000 with SE 0.001 and p = 0.232. time itself had decrease of 0.036 points per year in global score. 

ascerta

6) Validat

ascertaPartial 

7) Outcom

exposu

8) Adequa9) Comple10) Analys

confou

11) Analytic 

Yes 

Shumaker, Legault, Kuller, et al., 2004 Women’s Health Initiative Memory Study (WHIMS) 

Geographical location: North America Setting:Clinical Study design:

RCT Test intervention: CEE (0.625mg) OR CEE + MPA (2mg) 

Age:Range: 65 – 79 years Sex: [n (%)] 

Female: 7479 (100%) Male: 0 (0%) Race/ethnicity: [n (%)] White, non-white; overall statistics not reported Baseline cognitive status:Non-demented 

Risk factor/exposure

1: CEE or matching placebo  Also combined data with CEE + MPA trial Method of assessing risk factor/exposure 1:Other – RCT Risk factor/exposure 2:CEE + MPA or matching placebo 

1) Follow-up rate: At year 6  CEE alone 539 of 1464 (36.8%)  Placebo 518 of 1483 (34.9%)  CEE or CEE+MPA 550 of 3693 (14.9%)  Or total placebo 539 of 3786 (14.2%)  Adherence at year 6 was 42% for HRT and 47.8% for placebo. 2) Important baseline differences:  Higher prevalence of hypertension in CEE group (p=.01)  Comparing CEE alone vs CEE + MPA: women receiving CEE alone were less educated, had lower 

Comments For 13 mcorrection wtype 1 errofor total dem For analymodels a swas used.  Endpoint AD causing dementia. Quality assFor RCTs: 1) Baselin

Some ddifferen
B-241

Study Study Information Participants Risk Factor and 

Outcome Assessment 

Results Comments

Comparator interventions:Matching placebo Number of participants enrolled: 2947 in estrogenalone trial  4532 in estrogen plus progestin trial Duration of follow up:4.05 (1.19) Time from risk factor assessment to final cognitive assessment:4.05 (1.19) 

Inclusion criteria: Participating in WHIMS study Exclusion criteria:

Probable dementia 

Method of assessing risk factor/exposure 2:other – RCT Covariates/potential confounders adjusted for in analyses:Age Race Sex Educational level Smoking Self report cardiovascular dx Hypertension Diabetes Prior HRT or unopposed estrogen therapy Statin use Aspirin use Baseline cognitive status: Method(s) of assessing cognitive status: DSM- IV for dementia.  Plus blinded adjudicators.  Other – MCI operationally defined as 10th percentile or 

lower on 1 or more cerad tests and a report of some fct impairment, but not 

baseline 3MSE scores, more ethnically diverse, more likely to have hx of stroke or coronary heart disease and to have used hrt previously (p<.001 for all) 3) Outcome of interest #1 Classification of alzheimer’s 

disease  By treatment assignment  CEE: 13 of 28 dementias were AD  Placebo: 9 of 19 dementias were AD  CEE+MPA: 20 of 40 dementias dx as AD  Placebo: 12 of 21 dementias dx as AD.  Combined HRT trials  HRT 33 of 68  Placebo 21 of 40 4) Outcome of interest #2  Classification of MCI by treatment  CEE: 76  Placebo: 58  HR 1.34 (95% CI 0.97-1.60)  In combined CEE and CEE + MPA trial the risks were similar HR 1.25 95% CI 0.97-1.60 5) Outcome of interest #3  Total dementia:  CEE HR 1.49 (0.83-2.66) 

 Rate per 10,000 person-years  CEE + MPA HR 2.05 (1.21-3.48)  Rate per 10,000 person-years  Combined 1.76 (1.19-2.60)  Rate per 10,000 person-years 

2) Valid A

assess

3) Subjec4) Outcom5) Incomp

addres

6) Differen

Yes 

7) Overall 8) Conflic

insignif

9) Random10) Allocat

adequa
B-242

Study Study Information Participants Risk Factor and 

Outcome Assessment 

Results Comments

enough to interfere with basic adls (eating dressing grooming) from informant Informant interview?:Yes for individuals with cognitive impairment 

Shumaker,Legault, Rapp, et al., 2003 WHIMS 

Geographical location: 39 WHI Centers in the US Setting:Clinical Study design: RCT Test intervention 1 daily tablet of .625mg of conjugated equine estorogen plus 2.5 mg of medroxyprogesterone acetate Comparator intervention(s) Matching placebo Number of participants enrolled:4532 Duration of follow up:4.05 (1.19) years Time from risk factor 

Age:Range: 65 + Sex: [n (%)] 

Female: 4352 (100%) Male: 0 (0%) Race/ethnicity: [n (%)] NR Baseline cognitive status:Non-demented Inclusion criteria: Post menopausal Free of probable dementia Age 65 or older Exclusion criteria:64 or younger Male Pre-menopausal Probable dementia 

Risk factor/exposure

1:CEE 0.625mg + MPA 2.5 mg vs placebo Method of assessing risk factor/exposure 1:RCT pill count Covariates/potential confounders adjusted for in analyses:not varied for MCI or AD Method(s) of assessing cognitive status:

DSM IV DSM- IV for dementia. Plus blinded adjudicators. MCI operationally defined as 10thpercentile or lower on 1 or more cerad tests and a report of some fct impairment, but not enough to interfere 

1) Follow-up rate: CEE + MPA at 5 years 408/2229= 18.3% Placebo at 5 years 479/2303= 20.8%Adherence rates were lower for each year in CEE+MPA compared to placebo (p<.001) 2) Important baseline differences: Slightly lower prevalence of stroke (p=.01) and higher prevalence of statins (p=.02) in the CEE + MPA group. 3) Outcome of interest #1

CEE+MPA: 20 of 40 dementias dx as AD Placebo: 12 of 21 dementias dx as AD. Reported in shumaker 2004, #2491 and in evidence table for #2491 HR 2.05 (1.21-3.48) for total dementia Rate per 10,000 personyears. 4) Outcome of interest #2 MCI CEE +MPA 56 of 2229 f/u mean 3.99 (SD 1.23) 

CommentsNone Quality assFor RCTs: 1) Baselin

Slight d

2) Valid A

assess

3) Subjec4) Outcom5) Incomp

addres

6) Differen

Yes 

7) Overall 

not at 5 

8) Conflic

insignif

9) Random10) Allocat

adequa
B-243

Study Study Information Participants Risk Factor and 

Outcome Assessment 

Results Comments

assessment to final cognitive assessment: 4.05 (1.19) years 

with basic adls (eating dressing grooming) from informant Informant interview?:Yes 

rate/10000 person years 63 Placebo 55 of 2303 f/u mean 4.04 (SD 1.20) rate/10 000 person years 59 HR 1.07 (0.74-1.55) 

Skoog, Lithell, Hansson, et al., 2005 Study on Cognition and Prognosis in the Elderly (SCOPE) 

Geographical location: Not specified; SCOPE was in 15 countries Setting:Clinical Study design: RCT Test intervention : Candesartan 8-16mg daily; other antihypertensives allowed Comparator intervention(s): Placebo; other antihypertensives allowed Number of participants enrolled:4937 Duration of follow up: 3.7 yrs range 3 – 5 yrs Time from risk factor assessment to final cognitive 

Age:Range: 70 – 89 years Sex: [n (%)] 

NR Race/ethnicity: [n (%)] NR Baseline cognitive status:mmse > 24 

Inclusion criteria:  70 – 89 years  Mild to moderate hypertension  MMSE score > 24 

Exclusion criteria: Secondary hypertension  Stroke  MI within 6 months  Serious concomitant diseases affecting survival  Dementia 

Risk factor/exposure

1:antihypertensive candesarten (ace i) Method of assessing risk factor/exposure 1:Direct measurement Covariates/potential confounders adjusted for in analyses:country and Baseline cognitive status Method(s) of assessing cognitive status:change in mmse as continuous measure and as categorical outcomes (>=4 point decline)

Informant interview?:No 

1) Follow-up rate: can’t tell. 2) Important baseline differences: candesartin vs placebo “similar”, those with “low” mmse had lower education, were older, more women, more hx cva, more dm, 3) Outcome of interest #1 the risk of cognitive decline did not differ between candesartan and placebo (rates not given for participants by intervention). Subgroup analysis: Low cognitive function (baseline MMSE 24-28): candesartan 6.1% vs. placebo 7.0%; p=NS) High cognitive function (baseline MMSE 28-30): candesartan 3.5% vs. placebo 3.7%; p=NS) 4) Outcome of interest #2 In the low mmse group, the mmse score declined less with candesartan than with placebo (mean difference 0.49, (95% CI 0.02 – 0.97) In the high cognitive function group, there was no difference in rate of MMSE decline (-0.8 candesartan vs. 

CommentsWe were ucriteria use“Informatiodeveloped signif cognon a speciaFor scope o49% of canof the contrTarget BP Quality AsFor RCTs: 1) Baselin2) Valid A

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B-244

Study Study Information Participants Risk Factor and 

Outcome Assessment 

Results Comments

assessment:mean=3.7 years 

-0.73 placebo, p>0.20) adequa

Slooter, Cruts, Hofman, et al., 2004 

Geographical location: Rotterdam Setting:Community Study designProspective cohort Number of participants enrolled:6,852 Duration of follow up:4 years Time from risk factor assessment to final cognitive assessment:Not stated when APOE genotyping was done 

Age:Mean (SD): Reported by genotype with means ranging from 67.9 to 72.2 Sex: [n (%)] 

Female: 59.8 Male: 40.2 Race/ethnicity: [n (%)] 100% CaucasianBaseline cognitive status:Dementia present in 351 subjects at baseline= 5.1% population Inclusion criteria: Age >55 living in Rotterdam Exclusion criteria:NR 

Risk factor/exposure 1:APOE genotype Method of assessing risk factor/exposure 1:Direct measurement Covariates/potential confounders adjusted for in analyses:Age Sex Educational level Method(s) of assessing cognitive status:NINCDS-ADRDA DSM III-R Informant interview?:Yes 

1) Follow-up rate: 6852/7983= 85.8% 1131 (14%) of cohort could not be genotyped. 2) Important baseline differences: Increased prevalent dementia (12 vs 3%) and younger age (67.9 (8.0) vs 69.9 (9.4))in 4/4 compared to 3/3 3) Outcome of interest #1Relative Risk of AD by genotype AD n = 256 RR (95% CI) p values compared to E3/3 E2/2 = 1.0 (0.2 to 3.9) E2/3 = 0.5 (0.3 to 0.9) p<.05 E2/4 = 2.4 (1.3 to 4.4) p<.005 E3/3 = 1 (reference) E3/4 = 2.2 (1.6 to 2.9) p<.005 E4/4 = 7.0 (4.1 to 11.9) p<.005 

Comments5.1% of subdementia awith prevalwere excluassociation Quality assFor observ1) Unbias

cohort? 

2) Selectio

differenYes 

3) Sample 

differen

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5) Validat

ascerta

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ascertaYes 

7) Outcom

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confou

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Yes 

Smith, Clark, Nutt, et al., 1999 

Geographical location: United Kingdom 

Age:Mean (SD): Placebo: 66.9 (0.56) Vitamin: 66.8(0.48) 

Risk factor/exposure 1:vitamin 

1) Follow-up rate: Not specifically reported but appears to be 185/205 [JIA SR reported that placebo group 16.% % dropped out 

CommentsNone Quality ass
B-245

Study Study Information Participants Risk Factor and 

Outcome Assessment 

Results Comments

Setting:Community – recruited with advertisements Study design: RCT Test intervention: 2 mg beta carotene, 400 mg alpha - tocopherol and 500 mg/ascorbic acid daily Comparator intervention(s): placebo Number of participants enrolled:205 Duration of follow up:1 year Time from risk factor assessment to final cognitive assessment:1 year 

Sex: [n (%)] 

Female: 110 (54) Male: 95 (46) Race/ethnicity: [n (%)] NRBaseline cognitive status:Non-demented (at least not profoundly demented) Inclusion criteria: The inclusion criteria were: aged between 60 and 80 years and within two standard deviations of the normal weight for height, age and sex; no history or evidence of significant disease or mental illness; able and willing to give informed consent; capable of taking 80±120 per cent of the prescribed number of capsules during the run-in period (subjects were given 70 placebo capsules and told to take two daily for a period of 4 weeks. Compliance was considered acceptable if they took between 45 and 67 capsules). 

Method of assessing risk factor/exposure 1:  Self-report Direct measurement Covariates/potential confounders adjusted for in analyses:Age Race Sex Educational level Vegetable/fruit consumption; alcohol consumption; smoking; somatic symptoms; levels of other antioxidants Method(s) of assessing cognitive status: Other – change on cognitive measures Informant interview?:No 

and vitamin group 2.1 dropped out.] 2) Important baseline differences: No significant differences 3) Outcome of interest #1 Number of significant findings on all cognitive measures did not exceed the number one would expect to find by chance (4/117 significant). Did not give significance level. 

For RCTs: 1) Baselin2) Valid A

assess

3) Subjec

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4) Outcom

Tell 

5) Incomp

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6) Differen

No 

7) Overall 8) Conflic

insignif

9) Random

Tell 

10) Allocat

adequa
B-246

Study Study Information Participants Risk Factor and 

Outcome Assessment 

Results Comments

Exclusion criteria:Exclusion criteria were: current medication likely to influence the outcome measures; use of vitamin supplements in the preceding 3 months; evidence or history of regular or chronic drug abuse including alcohol; significant cardiovascular, respiratory, hepatic, renal, gastrointestinal, endocrine, neurological disease or abnormality; malabsorption syndrome; psychiatric disorder; subjects unable or unwilling to give informed consent; disorders which would interfere with the understanding or compliance with the study, hypersensitivity to any of constituents in the active treatment; MMSE score < 18; participation in another drug clinical trial within the previous 6 months; subjects from whom blood samples could not be obtained. 

Solfrizzi, D’Introno, Colacicco, 

Geographical location: 8 Italian municipalities 

Age:Mean (SD): 73.4 (5.6) 

Risk factor/exposure

1:alcohol 

1) Follow-up rate: 2963/4521 completed baseline (226 demented, 1171 ref cognitive tests, 

CommentsQ2 only 
B-247

Study Study Information Participants Risk Factor and 

Outcome Assessment 

Results Comments

et al., 2007 Italian Longitudinal Study on Aging (ILSA)

Setting:Community-includes residents of institutions Study design: Prospective cohort Number of participants enrolled:1566 analytical sample Duration of follow up:3.5 yr Time from risk factor assessment to final cognitive assessment:3.5 yr 

Sex:

Female: 1374 (43.6%)Male: 1589 (56.4) Race/ethnicity: [n (%)] NR Baseline cognitive status:Non-demented but some had MCI Inclusion criteria: Aged 65 to 84 residing in 8 Italian municipalities Exclusion criteria:Dementia at baseline (excluded from present analyses) 

Method of assessing risk factor/exposure 1:Self-report - amount of beer, wine, ‘shots of spirits’ consumed in previous year. Also asked about life long history of alcohol use. Covariates/potential confounders adjusted for in analyses:Age Sex Educational level Smoking CAD Diabetes Hypertension Stroke cholesterol Method(s) of assessing cognitive status:NINCDS-ADRDA DSM Other – MCI defined by modified Petersen criteria Informant interview?:Yes 

161 education unknown) 1445/2963 with baseline normal cognition completed follow-up 121/139 with MCI completed followup 2) Important baseline differences: Statistical comparisons not reported 3) Outcome of interest #1

No significant associations between any levels of drinking and the incidence of MCI in non–cognitively impaired individuals vs abstainers. 4) Outcome of interest #2 MCI moderate drinkers (<1 drink/day) had a lower rate of progression to dementia than abstainers (hazard ratio [HR] 0.15; 95% CI 0.03 to 0.78) MCI moderate drinkers (<1 drink/day) of wine had a lower rate of progression to dementia than abstainers (HR 0.15; 95% CI 0.03 to 0.77). No significant association between higher levels of drinking (>1 drink/day) and rate of progression to dementia in patients with MCI vs abstainers. 

Quality assFor observ1) Unbias

cohort? 

2) Selectio

differenYes 

3) Sample 

differen

4) Adequa

cohort? 

5) Validat

ascerta

6) Validat

ascertaYes 

7) Outcom

exposu

8) Adequa9) Comple10) Analys

confou

11) Analytic 

Yes 

Solfrizzi, Panza, 

Geographical location:

Age:Range: 65 - 84 

Risk factor/exposure

1:

1) Follow-up rate: 2963/ 4134 (the difference in these 

CommentsNone 
B-248

Study Study Information Participants Risk Factor and 

Outcome Assessment 

Results Comments

Colacicco, et al., 2004 Italian Longitudinal Study on Aging (ILSA) 

8 Italian Municipalities: Genoa, Segrate (Milan), SelvazzanoRubano (Padua), Impruneta (Florence), Fermo (Ascoli-Piceno), Naples, Casamassima (Bari), and Catania Setting:Community (but also includes nursing homes). Study design: Prospective cohort Number of participants enrolled:2963 (they seem to have used different pools of subjects for different risk factors (e.g., some risk factors required laboratory work and thus had a smaller n) Duration of follow up:3.5 yrs Time from risk factor assessment to final cognitive assessment:3.5 yr 

Sex: [n (%)] 

Female: 1373 (46.3%)Male: 1590 (53.7%) Race/ethnicity: [n (%)] NR Baseline cognitive status:Normal MCI Inclusion criteria: Independent or institutionalized; on electoral rolls of stated municipalities; each site was stratified by gender and age Exclusion criteria:Brain tumors, cerebrovascular malformations, psychosis, epilepsy, MS, stage III syphilis, dementia and any active neuropsychiatric condition producing disability, subjects taking neuroleptics 

smoking Method of assessing risk factor/exposure 1:Smoking by self-report Risk factor/exposure 2: Diabetes Method of assessing risk factor/exposure 2: self report or hyperglycemia on blood work and confirmed with medical records and subject’s physician. Risk factor/exposure 3: HTN Method of assessing 

risk factor/exposure 3: self report, direct measurement, medical records Covariates/potential confounders adjusted for in analyses:Age Educational level Total cholesterol HTN Coronary artery 

numbers are those who were excluded from study because they refused cognitive screening test). It is not the best measure of follow-up rate but only one provided.2) Important baseline differences: NR 3) Outcome of interest #1Number of pack-years of smoking not associated with risk of incident MCI in multi-variate models 4) Outcome of interest #2 Ever vs never smoking did not alter risk of progression from MCI to dementia 

Quality assFor observ1) Unbias

cohort? 

2) Selectio

differenYes 

3) Sample 

differen

4) Adequa

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5) Validat

ascerta

6) Validat

ascertaYes 

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exposu

8) Adequa9) Comple

Partial 

10) Analys

confou

11) Analytic 

Partial 
B-249

Study Study Information Participants Risk Factor and 

Outcome Assessment 

Results Comments

disease Method(s) of assessing cognitive status:NINCDS-ADRDA DSM Other – variation of Petersen’s criteria for MCI Informant interview?:Yes 

Staehelin, PerrigChiello, Mitrache, et al., 1999 Basel IDA 

Geographical location: Basel, Switzerland Setting:Community Study design: Prospective cohort Number of participants enrolled:332 Duration of follow up:2 years Time from risk factor assessment to final cognitive assessment:APOE genotype obtained at second assessment 

Age:Mean (SD): young old 71.43 years ( 115 men and 72 women Old-old mean age 82.58 years (112 men and 33 women) Sex: [n (%)] 

Female: 31.6 Male: 68.4 Race/ethnicity: [n (%)] NR Baseline cognitive status:Non-demented Inclusion criteria: A randomly selected subsample of the Basel IDA Exclusion criteria:NR 

Risk factor/exposure 1:APOE Method of assessing risk factor/exposure 1:Direct measurement Covariates/potential confounders adjusted for in analyses:Age Sex Educational level Lipids Smoking Method(s) of assessing cognitive status: Other – computerized test for free recall (FR), and information processing speed. 

1) Follow-up rate: 442 subjects randomly identified. 332 have full data. 110 dropped out due to death, ill health, changed mind about participating. 332/442= 75.1% 2) Important baseline differences: Subjects who completed study are likely to be in better health than those who did not complete study. 3) Outcome of interest #1No significant changes in any outcome measure (FR, RT and WVT) after 2 years. 4) Outcome of interest #2 At baseline: Adjusting for age and education: E4/4 and E3/4 performed lowest in FR, RT and WVT compared to E3/3 or carriers of one or two E2 alleles (FR P=.05; RT P=.009; WVLT P<.05) 

CommentsStudy is limand 2 year Subjects w

more poorly and WVLTany outcomover two yeQuality assFor observ1) Unbias

cohort? 

2) Selectio

differenYes 

3) Sample 

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4) Adequa

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ascerta

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ascertaYes 
B-250

Study Study Information Participants Risk Factor and 

Outcome Assessment 

Results Comments

 Recall consists of 

describing all the elements of a scene that the subject can remember. Reaction time (RT) was assessed by responding to flashing suns on screen. WAIS-R vocabulary test (WVT)- define 32 words Informant interview?:No 

7) Outcom

exposu

8) Adequa9) Comple10) Analys

confou

11) Analytic 

Yes 

Stott, Falconer, Kerr, et al., 2008 PROSPER (Prospective Study of Pravastatin in the Elderly Risk) 

Geographical location: Ireland, the Netherlands, and Scotland Setting:Community-based (2nd-dary analyses of RCT data) Study design: Prospective cohort approach for secondary analyses of RCT Number of participants enrolled:5804 Duration of follow up:Mean = 3.2 yr 

Age:Provided by 3 levels of exposure and gender. Means ranged from 74.7 – 75.8 (sd ranged 3.2-3.4) Sex:

Female: 3000 (51.7%)Male: 2804 (48.3%) Race/ethnicity: [n (%)] NR Baseline cognitive status:Non-demented – (assume most were non-demented because a score of >

24 on the MMSE was required for inclusion) Inclusion criteria: 

Risk factor/exposure

1:Alcohol Method of assessing risk factor/exposure 1:Self-report – usual intake in units per week during previous month Covariates/potential confounders adjusted for in analyses:Age Country Educational level Baseline cognitive status Smoking status BMI Weight 

1) Follow-up rate: NR 2) Important baseline differences: Compared to nondrinkers, drinkers were slightly younger, had more yrs of education, more likely to smoke, less likely to have history of vascular disease or diabetes, were taller, had lower BMI, had higher HDL-C and lower triglycerides. Greater proportion of drinkers in the Netherlands than in Scotland or Ireland. 3) Outcome of interest #1Rate of cognitive decline was similar for drinkers and nondrinkers for all cognitive domains, except the MMSE, which declined significantly less in female drinkers compared to nondrinkers (attenuated rate of decline = 0.05 MMSE units per annum, p=0.001) 

CommentsNone Quality assFor observ1) Unbias

cohort? 

2) Selectio

differenYes 

3) Sample 

differen

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cohort? 

5) Validat

ascerta

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ascertaYes 

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Can’t T
B-251

Study Study Information Participants Risk Factor and 

Outcome Assessment 

Results Comments

Time from risk factor assessment to final cognitive assessment:Mean = 3.2 yr 

Participant in PROSPER RCT, aged 70-82 with vascular risk factors or vascular disease, baseline MMSE >24 points Exclusion criteria:None except as covered by inclusion criteria. 

Incident stroke History of vascular disease Test version Method(s) of assessing cognitive status:Other – longitudinal performance on MMSE, Stroop ColorWord test, Letter-Digit Coding test, PictureWord Recall test. Informant interview?:No 

 10) Analys

confou

11) Analytic 

Yes 

Sturman, de Leon, Bienias, et al., 2008 CHAP 

Geographical location: Chicago (south side), US. Setting: Community Study design: Prospective cohort Number of participants enrolled:3,885 out of 6185 participants who were originally enrolled. Duration of follow up:6 Yrs Time from risk factor assessment to final 

Age:Mean (SD): 73.8 Range: 65- 85+ Sex: [n (%)] 

Female: 2369 (60.97%) Male: 1516 (39.02%) Race/ethnicity: [n (%)] Black : 2371 (61%) Non-Black: 1514 (39%)Baseline cognitive status: Per the methods papers, detailed cognitive testing done on all. However, AD not mentioned as exclusion criteria in this study. In further 

Risk factor/exposure 1:BMI (Body Mass Index)Method of assessing risk factor/exposure 1:Direct measurement Risk factor/exposure 2:Chronic medical conditions including hypertension, heart disease, diabetes and stroke. Method of assessing risk factor/exposure 2:Self-report Direct measurement 

1) Follow-up rate: 63.09% (3885 out of 6158 residents) 569 -missing global cognitive function scores at baseline or had only one global cognitive measurement, 1,139 died before the first follow-up, and 477 had no information on weight or height at baseline 13 participants had Body mass index (BMI kg/m2) outside a range of15 and 50 2) Important baseline differences: Unable to determine specifically. From text: Individuals with high BMIs were more likely to be young, female and black with higher incidences of chronic illnesses. 3) Outcome of interest #1Association of categories of body mass index (BMI) (kg/m2) relative to 

CommentsThe main sparticipants cognitive pmethods paclassified acognitive fu152 patientwere not exmake an efwhose MM

analysis.Quality assFor observ1) Unbias

cohort? 

2) Selectio

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B-252

Study Study Information Participants Risk Factor and 

Outcome Assessment 

Results Comments

cognitive assessment:6 Yrs 

analysis of the initial model, participants whose MMSE was less than 24 were excluded. Inclusion criteria: Resident of three neighborhoods in Chicago: Morgan Park, Beverly, and Washington Heights Exclusion criteria:

Body mass index (BMI kg/m2) outside a range of15 and 50 

Medication records. Covariates/potential confounders adjusted for in analyses:Age Sex Educational level Hypertension Heart disease, Diabetes and Stroke Method(s) of assessing cognitive status:NINCDS-ADRDA DSM ICD Other Informant interview?:No 

normal weight with global cognitive scores over time after adjusting for age (years, centered at 75), sex, education (years, centered at 12 years), and the time on study (years since baseline) Underweight x time for Black participants:  Coefficient 0.0164 p value 0.379 Underweight x time for non black participants: Coefficient 0.0512 p value 0.011 Overweight x time for Black participants:  Coefficient 0.0012 p value 0.849 Overweight x time for Non Black participants:  Coefficient 0.0102 p value 0.191 Obese x time for Black participants: Coefficient 0.0072 p value 0.275 Overweight x time for Non Black participants: Coefficient 0.0119 p value 0.234 [ Note: above sample had participants with all levels of cognitive functioning) 4) Outcome of interest #2 Association of body mass index (BMI) (kg/m2) with global cognitive scores over time among participants with Mini-Mental State Examination (MMSE) score greater than or equal to 24: 

4) Adequa

cohort? 

5) Validat

ascerta

6) Validat

ascertaYes 

7) Outcom

exposu

8) Adequa9) Comple10) Analys

confou

11) Analytic 

Can’t T
B-253

Study Study Information Participants Risk Factor and 

Outcome Assessment 

Results Comments

BMI X time for black participants: Coefficient 0.0003 p value 0.415BMI X time for Non Black participants: Coefficient 0.0008 p value 0.086 

Swan, DeCarli, Miller, et al., 1998 NHLB Institute Twin Study 

Geographical location: USA Setting:Community Study design: Prospective cohort Number of participants enrolled:1028 at baseline for larger study; 392 available for analysis in this sub-study Duration of follow up: baseline 1969-1972, cv followups 79-80 and 85-86 (and first cognitive) and 95-97 Time from risk factor assessment to final cognitive assessment:Bp’s checked waves 1-3, cognitive 85-86 and 95-97 

Age:Range: 68 – 79 years Sex:

Male: 100% Race/ethnicity:White 100% Baseline cognitive status:doesn’t really say, but baseline age was 46-47 Inclusion criteria: Participating in the NHLBI Twin Study Exclusion criteria:Ineligible or unwilling to undergo MR imaging 

Risk factor/exposure

1:htn Method of assessing risk factor/exposure 1:Direct measurement Mean of bps taken lying, sitting, standing then first three waves averaged Covariates/potential confounders adjusted for in analyses:Age, stroke hx, Educational level Method(s) of assessing cognitive status:change in test scores

Informant interview?:No 

1) Follow-up rate: maybe 317/392, 70.9%, not clear 2) Important baseline differences: increasing levels of midlife sbp were associ with age, incid cvd, chd and prevalent pad, antihypertensives associ with sbp 3) Outcome of interest #1 Subjects with high midlife sbp experienced a greater decline than those with low sbp (<120), 10 year change mmse +sem low sbp 0.04 +

0.28, high sbp -0.66 + 0.36 

dss test -1.55 + 0.69 for low sbp, -

5.03 + 0.84 for high sbp 

Commentslargely the Quality assFor observ1) Unbias

cohort? 

2) Selectio

differenYes 

3) Sample 

differen

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Yes 
B-254

Study Study Information Participants Risk Factor and 

Outcome Assessment 

Results Comments

Szekely, Breitner, Fitzpatrick, et al., 2008 Cardiovascular Health Cognition Study (CHCS – sub-group of CHS) 

Geographical location: Sacramento, County, CA Washington County, MD Forsyth County, NC Allegheny County, PA Setting:Community Study design:

Prospective cohort Number of participants enrolled:

3229 Duration of follow up: annually up to 10 years Time from risk factor assessment to final cognitive assessment:both assessment and rf done 1992-4 and annually 

Age:Range: ≤ 75 yo 1631 (51%) > 75 yo 1598 (49%) Sex: [n (%)] 

Female: 1931 (59.8%)Male: 1298 (40.2%) Race/ethnicity: [n (%)] African American 471 (14.6%) White 2743 (84.9%) Other 15 (0.5%) Baseline cognitive status:Not demented Inclusion criteria: Participation in Cardiovascular Health Cognition Study; ≥ 65 yo; free of dementia @ baseline; info available for Rx and OTC medications Exclusion criteria:NR 

Risk factor/exposure 1:nsaids Method of assessing risk factor/exposure 1:examined pill bottles Covariates/potential confounders adjusted for in analyses:Age Sex, Education, E4, baseline 3MS Educational level Baseline cognitive status Method(s) of assessing cognitive status:NINCDS-ADRDA DSM 

Informant interview?:Yes- the majority of the living had an informant; multiple approaches used for living and deceased individuals 

1) Follow-up rate: This includes 3,229 subjects who were not demented in 1992-1994 visit. Not clear how many were followed for how long. 2) Important baseline differences: nsaid users: more women, younger, more arthritis. 3) Outcome of interest #1 HR with nsaids 0.62 (0.44-0.88) 4) Outcome of interest #2 no ‘greater reduction’ (assume means still was a significant reduction) in HR with lagging of exposure, longer use, higher doses – These are the results we need to use, but actual HR not given for these 5) Outcome of interest #3 possibly only reduced if e4 POSITIVE HR 0.34 (0.18-0.65) 

CommentsThe results were limiteleast 1-2 yeQuality assFor observ1) Unbias

cohort? 

2) Selectio

differenYes 

3) Sample 

differen

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ascerta

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ascertaPartial 

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Can’t T

10) Analys

confou

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Partial 

Szwast, Hendrie, Lane, et al., 2007 Indianapolis Ibadan 

Geographical location: Indianapolis, IN Setting:Community 

Age:Mean (SD): 77.3 (5.3) Sex:

Female: 791 (69.3%) Male: 350 (30.7%) 

Risk factor/exposure

1:Statin use (simvastatin, atorvastatin, pravastatin, fluvastatin, cerivastatin, lovastatin), medical 

1) Follow-up rate: 1146 of 1808 with ApoE data (63.1%) 2) Important baseline differences:  The statin and non statin users differed significantly in the following: 

CommentsNone Quality assFor observ1) Unbias

cohort? 
B-255

Study Study Information Participants Risk Factor and 

Outcome Assessment 

Results Comments

Dementia Project 

Study design: Prospective cohort Number of participants enrolled:2519 Duration of follow up:3 yrs Time from risk factor assessment to final cognitive assessment:0 to 3 yrs 

Race/ethnicity:African American 1146 (100%) Baseline cognitive status:Non-demented Inclusion criteria: 1992 sample: African American; ≥ 65 yo 2001 sample: African American; ≥ 70 yo; Medicare beneficiary Exclusion criteria:No ApoE results at baseline; dementia 

history, smoking, alcohol use, social involvement Method of assessing risk factor/exposure 1:Self-report Direct measurement – for statins: medication bottles or printed lists from pt’s Dr at baselineRisk factor/exposure 2:BP, height, weight, ApoE, lipids Method of assessing risk factor/exposure 2:Direct measurement Covariates/potential confounders adjusted for in analyses:Age , sex, years of educations, statin use at baseline, Any Apoe E4 allele Method(s) of assessing cognitive status:Other – Community Screening Interview for Dementia (0-34 with higher scores indicating better cognitive function) 

Age at baseline, BMI at baseline, h/o hypertension, h/o stroke, h/o diabetes, h/o heart disease, cholesterol level >300 mg/dl, LDL-C >130, use of NSAIDS, use of antipatelet medication/ asprin. Baseline: 284 on statin only, 3 on statin + other lipid lowering agent Statin use at baseline 3) Continuous outcome [for each such outcome, please report the following information wherever possible for the exposed/intervention group and the unexposed/control group: - N, mean value and SD at baseline

- N, mean value, and SD at follow 

up, and/or the N and mean change and SD of the change. 

If these values are not given, abstract whatever is reported.] 287 on statins, 854 non-statin 1. Analysis of covariance, adjusting for age, gender, education, ApoE e4 allele. Cognitive decline = CSI-D scores at baseline minus 3-year f/u score standardized to effect sizes. Parameter estimate (Value > 0 indicates cognitive decline), SE, p value Female: 0.02, 0.06, p=0.7489 Education(years): -0.02, 0.01, p=0.1668 ApoEe4: 0.15, 0.06, p=0.0149 Baseline statin: -0.16, 0.07, p=0.0177

2) Selectio

differenPartial 

3) Sample 

differen

4) Adequa

cohort? 

5) Validat

ascerta

6) Validat

ascertaYes 

7) Outcom

exposu

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Can’t T

9) Comple10) Analys

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11) Analytic 

Yes 
B-256

Study Study Information Participants Risk Factor and 

Outcome Assessment 

Results Comments

Informant interview?:Yes- They used the CAMDEX 

Adjustment for baseline cognitive score, statins associated with less cognitive decline (only p value given, p=0.0046) 2. Analysis of covariance, adjusting for age, gender, education, ApoE e4 allele. Cognitive decline = CSI-D scores at baseline minus f/u score standardized to effect sizes. Parameter estimate (Value > 0 indicates cognitive decline), SE, p value Female: 0.03, 0.06, p=0.6076 Education(years): -0.02, 0.01, p=0.1708 ApoEe4: 0.16, 0.06, p=0.0115 Baseline statin only: -0.28, 0.12, p=0.0217 Statin at 3 year f/u only: 0.04, 0.10, p=0.6765 Statin at baseline and f/u: -0.12, 0.08, p=0.1258 
B-257

Study Study Information Participants Risk Factor and 

Outcome Assessment 

Results Comments

Tang, Cross, Andrews, et al., 2001 WHICAP 

Geographical location: Manhattan, NY, USA Setting:Community Study design: Prospective cohort Number of participants enrolled:1788 Duration of follow up:Mean 4.3 yrs SD1.4 (Caribbean Hispanic; 1.5 white and AA) Time from risk factor assessment to final cognitive assessment:Mean 4.3 yrs SD1.4 (Caribbean Hispanic; 1.5 white and AA) 

Age:Mean (SD): AA 75.8 (6.2); Caribbean Hispanic 74.9 (5.8); white 76.9 (7.2) Sex: [n (%)] 

Female: 224 (12.5%) Male: 1564 (87.5%) Race/ethnicity: [n (%)] Caribbean Hispanic: 42.5% AA: 34.1% White: 23.4% Baseline cognitive status:Non-demented Inclusion criteria: Random sample from 3 contiguous zip codes within Washington Heights, NY, aged > 65 

yrs old Current analyses included subset with baseline and longitudinal follow-up Exclusion criteria:Dementia 

Risk factor/exposure

1:Diabetes mellitus Method of assessing risk factor/exposure 1:medical history, medication Risk factor/exposure 2:Stroke, heart disease, hypertension Method of assessing risk factor/exposure 2:Self-report Medical history Other –use of medication Covariates/potential confounders adjusted for in analyses:Age Sex Educational level APOE Diabetes BMI Hypertension Heart disease Stroke Method(s) of assessing cognitive 

1) Follow-up rate: 1788/2126 =84.1%

2) Important baseline differences: Whites were older (p=.001) and had more years of education (p=.001) than AA or Caribbean Hispanics. AA had more education than Caribbean Hispanics (p=.001). AA and Caribbean Hispanics had more diabetes than whites (p=.01). Heart disease was more frequent in Caribbean Hispanics than AAs (p=.001). 3) Outcome of interest #1HR developing possible or probable AD in participants with diabetes 1.6 (95% CI 1.1-2.3) (p ≤ 0.01) 4) Outcome of interest #2 Stroke HR 0.9 (95% CI 0.5-1.6) 5) Outcome of interest #3  Hypertension HR 1.4 (95% CI 0.9-1.9) 

CommentsQuestion 1 Diabetes mwith a signiincident AD this multi-rapopulation. heart diseaassociated probable AQuality assFor observ1) Unbias

cohort? 

2) Selectio

differenYes 

3) Sample 

differen

4) Adequa

cohort? 

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ascerta

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ascertaYes 

7) Outcom

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confou

11) Analytic 

Yes 
B-258

Study Study Information Participants Risk Factor and 

Outcome Assessment 

Results Comments

status:NINCDS-ADRDA DSM Other – cognitive change within cognitive domain. Used analytical method that controls for baseline score (tests combined based on factors analyses) Informant interview?:No 

Tervo, Kivipelto, Hanninen, et al., 2004 

Geographical location: Kuopio, Finland Setting:Community Other-nursing facilities Study design: Prospective cohort Number of participants enrolled:Random sample screened: 1,150; 747 enrolled subjects Duration of follow up:3.26 +/- 0.70 yrs Time from risk factor assessment to final cognitive assessment:3.25 +/- 0.72 yrs 

Age:Range: 60-76 yrs SexFemale: 454 (61%) Male: 293 (39%) Race/ethnicity:NR Baseline cognitive status:Non-demented Inclusion criteria: 60 yrs and older, nondemented; no evidence MCI Exclusion criteria:NR 

Risk factor/exposure

1:Education, years Method of assessing risk factor/exposure 1Self-report Risk factor/exposure 2:ApoE4 allele Method of assessing risk factor/exposure 2Direct measurement Risk factor/exposure 3: Diabetes mellitus (included diet, tablet or insulin-treated) Method of assessing risk factor/exposure 3Self report 

1) Follow-up rate:  Random sample of 1150 subjects. 806 evaluated. 747 eligible. F/u: 550/747(77.7%) 2) Important baseline differences: NA 3) Outcome of interest #1—Education OR (95% CI) 0.80 (0.71-0.90) 4) Outcome of interest #2--APOE OR (95% CI) 2.23(1.23-4.05) 5) Outcome of interest #3--Diabetes OR (95% CI) 1.55(0.58-4.19) 6) Outcome of interest #4—High blood pressure (DBP>95 or 

CommentsNone Quality assFor observ1) Unbias

cohort? 

2) Selectio

differenYes 

3) Sample 

differen

4) Adequa

cohort? 

5) Validat

ascerta

6) Validat

ascertaYes 

7) Outcom

exposu

8) Adequa9) Comple10) Analys

confou
B-259

Study Study Information Participants Risk Factor and 

Outcome Assessment 

Results Comments

Risk factor/exposure 4: Elevated blood pressure: HTN=SBP 160 mm Hg or greater or DBP 95 mm Hg or greater. Method of assessing 

risk factor/exposure 4Direct measurement Risk factor/exposure 5: Medicated hypertension Method of assessing risk factor/exposure 5Self report Covariates/potential confounders adjusted for in analyses Age Race Sex Educational level Baseline cognitive status Method(s) of assessing cognitive status:NINCDS-ADRDA DSM-IV Other –CERAD; Clinical Dementia Rating (CDR):MCI 

SBP>160) 

OR (95% CI) 0.91(0.49-1.69)  7) Outcome of interest #5—Medicated HTN OR (95% CI) 1.61(0.87-2.99) Results: 66 subjects (8.8%) had converted to MCI. The global incidence rate of MCI was 25.94/1,000 person-years. Persons with ApoE4 allele and medicated hypertension were more likely to convert to MCI. High education is a protective factor for MCI 

11) Analytic 

Yes 
B-260

Study Study Information Participants Risk Factor and 

Outcome Assessment 

Results Comments

diagnosed if score of 0.5 and if subject scored 1.5 SD below average on at least one memory test. Informant interview?:No 

Thal, Ferris, Kirby, et al., 2005 

Geographical location: 46 US sites Setting:Other – clinical and community: combination of patients identified by investigators and volunteers responding to an ad about RCT – Study design: RCT Test intervention: Rofecoxib 25 mg Comparator intervention(s): placebo Number of participants enrolled:1457 Duration of follow up: 115 weeks rofecoxib, 130 weeks placebo 

Age:Mean (SD):  Placebo = 74.8 (6.0)  Drug = 75.1 (6.0) Sex: [n (%)] 

Female: 477 (32.7%) Male: 980 (67.3%) Race/ethnicity: [n (%)] NR Baseline cognitive status:MCI Inclusion criteria: ≥ 65 yo; at least 8 grades of education; had a reliable informant who could accompany them to each visit; pt or informant reported memory problem; memory has declined in last yr; MMSE ≥ 24; CDR global score = 0.5 with memory domain score ≥ 0.5; BDRS 

total score ≤ 3.5 with 

Risk factor/exposure

1:nsaid Method of assessing risk factor/exposure: rct rofecoxib and placebo Covariates/potential confounders adjusted for in analyses:treatment region, mmse strata (24-26 or >26) Method(s) of assessing cognitive status:NINCDS-ADRDA Other – Dementia determined by CDR >

1 Informant interview?:Yes 

1) Follow-up rate: placebo 45% dc’d, 41% finished rofecoxib 45% dc’d, 40% finished 2) Important baseline differences: not apparent 3) Outcome of interest #1 increased HR for AD with rofecoxib 1.46 (1.09-1.94) but a minority finished on drug, and secondary measures did not confirm increased risk (ADAS-Cog, SRT, MMSE, BDRS, CDR sum of boxes) 

CommentsMinority finterminated Quality assFor RCTs: 1) Baselin2) Valid A

assess

3) Subjec4) Outcom5) Incomp

addres

6) Differen

Yes 

7) Overall 8) Conflic

insignif

9) Random10) Allocat

adequa
B-261

Study Study Information Participants Risk Factor and 

Outcome Assessment 

Results Comments

Time from risk factor assessment to final cognitive assessment:q4mos:cdr, mmse,srt, q12mos ADAS-Cog Time from 1st to last 

cognitive assessment = 48 mos 

no part 1 item score > 0.5; AVLT total score ≤37 Exclusion criteria:Dementia; inadequate motor or sensory capacities to comply with testing; a modified Hachinski Ischemic Scale score > 4; Hamilton Depression Scale (17-item version) score > 13; history of angina or CHF with symptoms that occurred at rest; uncontrolled HTN; history within past yr of MI; coronary artery bypass, angioplasty, or stent placement; history within past 2 yrs of stroke, multiple lacunar infarcts, or transient ischemic events; history within past 3 months of GI bleeding; and expected therapeutic need for chronic NSAID or estrogen replacement therapy during the study; pts taking NSAIDS on a chronic basis for 2 mos prior to study; estrogen replacement therapy (excluding topical ointments) withint 2 mos of study; 
B-262

Study Study Information Participants Risk Factor and 

Outcome Assessment 

Results Comments

cholinesterase inhibitors within 1 mo of study 

Tierney, Oh, Moineddin, et al., 2009 

Geographical location:Greater Toronto area Setting:Community Study design RCT Test intervention (RCTs only): Per week 1 mg 17-βestradiol for 4 days, then combo with 0.35 norethindrone for 3 days Comparator intervention(s) (RCTs only): placebo Number of participants enrolled:142 Duration of follow up: 2 year trial Time from risk factor assessment to final cognitive assessment:NR 

Age:Mean (SD): 74.8 (6.9) Sex: [n (%)] 

Female: 142 (100%) Male: 0 (0%) Race/ethnicity: [n (%)] White 132 (93.0 %) Black 6 (4.2%) Asian 4 (2.8%) Baseline cognitive status:Non-demented Inclusion criteria: Age ≥ 60 with last 

menstrual cycle ≥ 12 

months before screening; were fluent in English; could read normal print and hear normal speech. Exclusion criteria:Met criteria for dementia, or had a clinical history of a neurological systemic or psychiatric condition that would affect cognition; women with conditions that were considered at the time of enrollment to be 

Risk factor/exposure 1:estrogen/progesterone hormone therapy Method of assessing risk factor/exposure 1:meds administered Covariates/potential confounders adjusted for in analyses:Age, education, apoE, prior hormone use Method(s) of 

assessing cognitive status:NINCDS-ADRDA DSM used to dx dementia per methods but outcome here is cvlt recall Informant interview?:No 

1) Follow-up rate: in active tx group: 70 randomized, 4 dropped out, 1 death, 18 dc’d meds at yr 1, 2 dropped out, 1 died, 8 dc’d meds at yr 2. In the placebo group, 72 randomized, 4 dropped out and 1 died and 12 dc’d tx at yr 1. In yr 2, 1 refused, 1 died, 4 self dc’d 2) Important baseline differences: More apoe4 carriers in placebo group. More prior ht use in tx group. 3) Outcome of interest #1 Group differences on the cvlt short delay verbal recall were not significant at year 1 or 2 4) Outcome of interest #2 For the subgroup scoring average or above at baseline (>7), those on HT had less decline at yr 1 and yr 2 as compared to placebo (p=.007 and p=0.01) 5) Outcome of interest #3 no treatment effect for those scoring below average. 

CommentsQuestion 5 Primary ourecall on CVestimate of is. Quality assFor RCTs: 1) Baselin2) Valid A

assess

3) Subjec4) Outcom5) Incomp

addres

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Yes 

7) Overall 8) Conflic

insignif

9) Random10) Allocat

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Study Study Information Participants Risk Factor and 

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Results Comments

exacerbated by estrogen, including history of breast or endometrial cancer; history of myocardial infarction (MI), coronary artery bypass graft (CABG), angioplasty or unstable angina within the past year; history of congestive heart failure (CHF) (NYHA Class III or IV); or history of thromboembolic event withint the past 6 months; women taking donepezil, galantamine, rivastigmine, hydergine, tamoxifen, or raloxifene, or had used any mode or dose of HT within the past 2 years; women who met neuropsychological criteria for dementia; women who had an identifiable cause of memory disorder (e.g., stroke) or were considered to meet criteria for dementia. 

Tyas, Salazar, Snowdon, et al., 2007 

Geographical location: United States Setting:

Age:Mean (SD): 84.3 (5.0) Sex:

Female: 470 (100%) 

Risk factor/exposure 1:Education 1) < High school 

1) Follow-up rate: 1031 initially eligible. 678 (66%) agreed to participate. Exclusions: missing examinations 

CommentsA variety of decline assQuality ass
B-264

Study Study Information Participants Risk Factor and 

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Results Comments

NUN study Other – Nuns 

Study design: Prospective cohort Number of participants enrolled:1031 initially eligible, 678 agreed to participate, 470 had complete data. Duration of follow up:NR. Annual exams from 1991-2002, so range is probably 1-11 years Time from risk factor assessment to final cognitive assessment:NR. Annual exams from 1991-2002, so range is probably 1-11 years 

Male: 0 (0%) Race/ethnicity:NR Baseline cognitive status:Normal Non-demented MCI CIND AAMI Inclusion criteria: Members of the School Sisters of Notre Dame born before 1917 and living in certain regions of the US. Aged >75 

yrs. Exclusion criteria:NR 

2) Undergrad degree 3) Grad degree (reference) Method of assessing risk factor/exposure 1:Self-report Risk factor/exposure 2:APOE Method of assessing risk factor/exposure 2:Direct measurement Covariates/potential confounders adjusted for in analyses:Age Education APOE Prior cognitive state Method(s) of assessing cognitive status:Cognitive test in the Consortium to Establish a Registry for Alzheimer’s Disease Informant interview?:No 

(n=58), missing APOE data (n=35), dementia at baseline (n=115). Analytic sample: 470/678 (69%) Of the 470, 192 provided data on 6 transitions and all 7 annual exams. 2) Important baseline differences: NA 3) Outcome of interest #1

 Transitions/outcomes: 1) intact cognition 2) MCI 3) global impairment 4) death Total of 1905 transitions. From MCI to global impairment: n=110 (11.6%) From MCI to dementia: n=71 (7.5%) 4) Outcome of interest #2 Age, education, and APOE were all significant predictors of transition from intact cognition to mild cognitive impairment. Similar pattern for transition from intact cognition to global impairment. 5) Outcome of interest #3 Transition from intact to MCI, OR 

(95% CI): 1) Age 1.06 (1.03, 1.09) 2) Education (grad degree as ref.)  --<high school 2.36 (1.26, 4.42) 

 --undergrad 1.53 (1.17, 2.00) 3) APOE present 1.87 (1.27, 2.73) 4) Prior cognitive state (global 

For observ1) Unbias

cohort? 

2) Selectio

differenYes 

3) Sample 

differen

4) Adequa

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5) Validat

ascerta

6) Validat

ascertaCan’t T

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confou

11) Analytic 

Yes 
B-265

Study Study Information Participants Risk Factor and 

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Results Comments

impairment as ref.)  --intact cognition 0.18 (0.09, 0.38)  --MCI 1.82 (0.09, 3.68) Transition from intact to global impairment, OR (95% CI): 

1) Age 1.15 (1.10, 1.20) 2) Education (grad degree as ref.)  --<high school 2.79 (1.32, 5.91) 

 --undergrad 1.62 (1.10, 2.38) 3) APOE present 3.02 (1.87, 4.89) 4) Prior cognitive state (global impairment as ref.)  --intact cognition 0.02 (0.01, 0.03)  --MCI 0.11 (0.06, 0.21) 

Tzourio, Anderson, Chapman, et al., 2003 Perindopril Protection Against Recurrent Stroke Study (PROGRESS) 

Geographical location: 172 centers in 10 countries Setting:Clinical Study design: RCT Test intervention: Perindopril 4mg daily +/- indapamine 2-2.5 mg daily Comparator intervention(s): placebo Number of participants enrolled:6105 

Age:Mean (SD): 64 (10) years Sex:

Female: 30% Male: 70% Race/ethnicity:Asian: 39% Other: 61% Baseline cognitive status: Non-demented and cognitively impaired (15% with MMSE <25)  MCI Inclusion criteria:  H/o TIA or Stroke w/in 5 years  No clear indication for , nor 

Covariates/potential confounders adjusted for in analyses:Age Race Sex Educational level Baseline cognitive status Method(s) of assessing cognitive status: MMSE at baseline, 6-and 12-month visit, then annually  Cognitive decline defined as >=3 point drop Informant interview?:NA 

1) Follow-up rate:  22% discontinued use of all study tablets (active 23%; placebo 21%)  Cognitive decline assessed in 5888 study participants (96.4%) 2) Important baseline differences: No 3) Outcome of interest #1 Cognitive decline = 610 (134 with recurrent stroke, 476 w/o stroke): Active: 276/3051 (9.1%), 23/1000 person years  Control: 334/3054 (11.0%), 28/1000 person years  RR = 0.81 (95% CI 0.68-0.96)  Sensitivity analysis defining cognitive decline as ?=2 or >=4 points did not “materially alter” the results 4) Outcome of interest #2 Change in MMSE (baseline – f/u) 

CommentsNote – no B

had SBP >on antihypebaseline Quality assFor RCTs: 1) Baselin2) Valid A

assess

3) Subjec

Tell, pr

4) Outcom5) Incomp

addres

6) Differen

Yes 

7) Overall 8) Conflic

insignifwith SeCompa

9) Random
B-266

Study Study Information Participants Risk Factor and 

Outcome Assessment 

Results Comments

Duration of follow up:Mean = 3.9 years Time from risk factor assessment to final cognitive assessment:Mean = 3.9 years 

contraindication to treatment with an ACE inhibitor  Tolerated and adhered to perindopril during 4-week run-in phase Exclusion criteria:

NR 

Active: 0.05 (0.05 SE) Placebo: 0.24 (0.05 SE) Difference in change (placebo – active): 0.19 (0.07 SE) less decline for active, p=0.01 5) Outcome of interest #3 Mean difference in BP between active and control = 9/4 mm Hg 

10) Allocat

adequa

Tzourio, Dufouil, Ducimetiere, et al., 1999 EVA 

Geographical location: Nantes, France Setting:Community Study design: Prospective cohort Number of participants enrolled:1,373 Duration of follow up:4 years Time from risk factor assessment to final cognitive assessment:2-4 years 

Age:Mean (SD): 65 (3.0) Sex: [n (%)] 

Female: 807 (58.8%) Male: 566 (41.2%) Race/ethnicity: [n (%)] NR Baseline cognitive status: Uncertain, those with cognitive impairment not specifically excluded. Inclusion criteria: Age 59-71 yo Exclusion criteria:Stroke during f/u 

Risk factor/exposure

1:HTN : SBP ≥ 160 or DBP ≥ 95 (average of 2 measures) or taking anti-hypertensive medication Method of assessing risk factor/exposure 1:Self-report: medication Direct measurement: BP Covariates/potential confounders adjusted for in analyses:Age Sex Educational level Baseline cognitive status ApoeE polymorphism, Depressive symptomatology Method(s) of 

1) Follow-up rate: 1,255/1373 completed 2 yr f/u 1172/1373 completed 4 year f/u Non participants had lower MMSE at baseline (27.1 vs. 28.2) 2) Important baseline differences: HTN associated with: male, heavy drinking, smoking and higher BMI; MMSE scores were similar 3) Outcome of interest #1HTN: OR for cognitive decline = 2.8 (1.6 – 5.0) Sensitivity analysis using SBP ≥ 140 

or DBP ≥90 to define HTN: OR for cognitive decline = 2.8 (1.1 to 2.9) 4) Outcome of interest #2 HTN and antihypertensives High BP with anti-HTN medication: OR=4.3 (2.1-8.8) High BP w/o anti-HTN medication: OR=1.9 (0.8 – 4.4) Normal BP with anti-HTN medication: OR=1.2 (0.6-2.2) Normal BP w/o -HTN medication: OR 

CommentsNone Quality assFor observ1) Unbias

cohort? on sele

2) Selectio

differenYes 

3) Sample 

differen

4) Adequa

cohort? 

5) Validat

ascerta

6) Validat

ascertaYes 

7) Outcom

exposu

8) Adequa9) Comple10) Analys

confou

11) Analytic 

Yes 
B-267

Study Study Information Participants Risk Factor and 

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Results Comments

assessing cognitive status:Other – >=4 point decline on MMSE between baseline and 4 year f/u Informant interview?:No 

1 (reference) 5) Outcome of interest #3 Anti-HTN medication at baseline: OR for cognitive decline = 1.1 (0.7 -1.7) 

Unverzagt, Kasten, Johnson, et al., 2007 Advanced Cognitive training for Independent and Vital Elderly (ACTIVE) 

Geographical location:Birmingham Al; Detroit Mich; Boston Mass; Baltimore Md; Indianapolis In; State College Pa; Setting:Other – Senior Housing Community Centers Hospitals Clinics Study design: RCT Test intervention: Reasoning Training Memory Training Speed Training. Comparator intervention(s): No Training (Control) Number of participants enrolled:2832 

Age:Mean (SD): 73.6 (5.9) Sex: [n (%)] 

Female: 2078 (74.16%) Male: 754 (25.84%) Race/ethnicity: [n (%)] 26% Black Baseline cognitive status:MMSE ≥ 23 No self reported AD Inclusion criteria: NR 

Exclusion criteria: < 65 yrs of age; functional impairment (≥2ADLdisabilities); cognitive decline (MMSE score ≤22); self reported AD/stroke/ uncertain cancer; severe losses in vision, hearing, or communicative ability 

Risk factor/exposure 1:NA Method of assessing risk factor/exposure 1:NA Covariates/potential confounders adjusted for in analyses:Cant tell. From the manuscript, it appears that they did not control for age, sex, or education. Method(s) of assessing cognitive status:MMSE and self report To divide the baseline sample into memory normal and memory impaired they used the AVLT test. Informant interview?:

1) Follow-up rate: 2832 randomized. 2244 analyzed at year 2. Follow up: 79% However, since they did ITT, 2802were included in the analysis. 2) Important baseline differences: The memory impaired group was older and had lower MMSE scores. 3) Outcome of interest #1 At years 1 and 2 the memory normal group (n=2580) who receivedmemory training did better than 

controls on memory tests. Year 1 :Effect size= 0.254, p<0.001 Year 2: Effect size= .214, p<0.001 reasoning training did better than controls on reasoning tests Year 1 Effect size= 0.416, p<0.001 Year 2 Effect size= 0.262, p<0.001 speed training did better on speed processing tests Year 1 effect size= -1.238, p<0.001 Year 2 effect size= -0.886, p<0.001 (negative effect sizes indicate better performance of this groups on the 

CommentsNone Quality assFor RCTs: 1) Baselin

Tell 

2) Valid A

assess

3) Subjec4) Outcom5) Incomp

addres

6) Differen

Yes 

7) Overall 8) Conflic

insignif

9) Random10) Allocat

adequa
B-268

Study Study Information Participants Risk Factor and 

Outcome Assessment 

Results Comments

Duration of follow up:2 years Time from risk factor assessment to final cognitive assessment:2 years 

that would interfere with study participation; recent cognitive training; or unavailable during the study period

No raw scores) 

4) Outcome of interest #2 At years 1 and 2 the memory impaired group (n=193) who receivedmemory training did better no than controls on memory tests. reasoning training did better than controls on reasoning tests in year 2 only Year 1 Effect size= 0.208, p>0.05 Year 2 Effect size= 0.276, p<0.05 speed training did better on speed processing tests Year 1 effect size= -1.100, p<0.001 Year 2 effect size= -0.755, p<0.001 

van Gelder, Tijhuis, Kalmijn, et al., 2006 Finland, Italy, the Netherlands Elderly (FINE) Study

Geographical location: Finland, Italy, the Netherlands Setting:Community Study design:

Prospective cohort Number of participants enrolled:

1383 Duration of follow up:15 years Time from risk factor 

Age:Range: 65 – 84 years Sex:

Female: 0% Male: 100% Race/ethnicity: [n (%)] NR Baseline cognitive status:MMSE >24 Inclusion criteria:  Finnish, Dutch, or Italian survivor of the Seven Countries Study

Risk factor/exposure 1:Marital Status Method of assessing risk factor/exposure 1:Self-report Risk factor/exposure 2:Living situation Method of assessing risk factor/exposure 2:Self-report Covariates/potential 

1) Follow-up rate: 1363 men were recruited in 1985. Information for 1042 men in 1990. Follow up for year 2000 NR. 2) Important baseline differences: Men who were not included in the present study were older (in 1990, mean ageof 79 years vs 76 years, p < .001), had lower education (5 yearsvs 7 years, p < .001), and were more likely to have a history of stroke (13% vs 5%, p < .001) compared to the men who participated. 3) Outcome of interest #1 After adjustment for age, education, country, smoking, alcohol 

CommentsWe do not Quality assFor observ1) Unbias

cohort? 

2) Selectio

differenYes 

3) Sample 

differen

4) Adequa

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5) Validat

ascerta

6) Validat

ascertaYes 
B-269

Study Study Information Participants Risk Factor and 

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Results Comments

assessment to final cognitive assessment:10 years. 

 Male Exclusion criteria:

 Female  Institutionalized  MMSE score < 18 

confounders adjusted for in analyses:Age Country Educational level Smoking status Alcohol Consumption Baseline cognitive status Prevalence of MI Stroke Diabetes Cancer Hypertension Physical activity Depression Functional status For the analysis of marital status, living situation was included as a covariate. Method(s) of assessing cognitive status:Other – MMSE Informant interview?:No 

consumption, prevalence of myocardial infarction, stroke, diabetes and cancer, living situation, and baseline cognitive functioning, men who were married from 1985-90 had a cognitive decline of 1.1 point (95% CI 0.9–1.4) over the 10 year follow up. Men who were married in 1985 but unmarried in 1990 had a cognitive decline of additional decline of 1.0 point(95% CI 0.1–1.9) Men who were unmarried in 1985 and 1990 had an additional decline of 1.3 points (95% CI 0.5–2.1) 4) Outcome of interest #2 After adjustment of after adjustment for age, education, country, smoking,alcohol consumption, prevalence of myocardial infarction, stroke, diabetes and cancer, marital status, and baseline cognition men who lived with others in 1985 and 90 had a cognitive decline of 1.1 points (95% CI 0.8–1.4) Men who lived with others in 1985 but alone in 1990 had an additional decline of 1.1 points (95% CI1⁄40.2–2.0) Men who lived alone in 1985 and 1990 had an additional cognitive decline of 2.7 points (95% CI 1.7–3.7) 

7) Outcom

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8) Adequa9) Comple

Can’t T

10) Analys

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Yes 

Verghese, Geographical Age: Risk factor/exposure 1) Follow-up rate: Comments
B-270

Study Study Information Participants Risk Factor and 

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Results Comments

LeValley, Derby, et al., 2006 Bronx Aging Study 

location: NY, NY Setting:Community Study design: Prospective cohort Number of participants enrolled:488; 437 in relevant subsample Duration of follow up:2713 person-years. Mean: 5.6 yrs +4.1. 21-year study period. Time from risk factor assessment to final cognitive assessment:Mean: 5.6 yrs +4.1. 21-year study period. 

No aMCI: 79.0 +3.1 

Incident aMCI: 78.9 

+2.8 

Sex:Female: No aMCI: 64.7% 

Incident aMCI: 58.6% 

Male: No aMCI: 35.3% 

Incident aMCI: 41.4% 

Race/ethnicity:White: No aMCI: 89.2% 

Incident aMCI: 89.3% 

Baseline cognitive status:Non-demented Inclusion criteria: English speaking, age between 75 and 85 yrs, community dwelling and <= 8 errors on Blessed Information Memory Concentration Test. Exclusion criteria:Prevalent aMCI. Severe visual or hearing impairment, Parkinson’s disease, liver disease, alcoholism, or known terminal illness. 

1:Leisure activities Method of assessing risk factor/exposure 1:Self-report 6 cognitive activities and 10 physical activities Cognitive-activity and physical-activity scales in units of activity-days per week (range: 0-42 for cognitive activity and 0-70 for physical activity). Scale scores not dichotomized. Covariates/potential confounders adjusted for in analyses:Age Sex Educational level Chronic illnesses (Participation in other leisure activities when analyzing individual leisure activities). Method(s) of assessing cognitive status:“Subjects with suspected dementia 

437 of 488 enrolled (89.5%) in Bronx Aging Study. 2) Important baseline differences: NA 3) Outcome of interest #1

58 incident cases of aMCI; 84 incident cases of dementia (43 AD, 15 mixed AD) 26 incident cases of dementia after meeting aMCI criteria (11 AD, 8 mixed AD and vascular dementia, 4 vascular, and 3 other) The 58 incident aMCI patients had lower baseline cognitive ability but not physical activity scale scores. None of the individual cognitive and physical leisure activities showed independent associations wit lower risk of aMCI in the fully adjusted models. 4) Outcome of interest #2 A 1-point increment in cognitive activity score was associated with a reduced risk of aMCI (HR, 0.949; 95% CI, 0.910-0.990), but a 1-pt increment in physical activity score was not (HR=0.970, 95% CI 0.933 to 1.008). A 1-point increment in cognitive activity score was associated with a reduced risk of aMCI or Dementia (HR, 0.946; 95% CI, 0.921-0.972), but a 1-pt increment in physical activity score was not associated 

None Quality ass

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2) Selectio

differenfactors

3) Sample 

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Yes 
B-271

Study Study Information Participants Risk Factor and 

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Results Comments

received further w/u. Triggers for w/u included: new symptoms, staff observations, Blessed test score change of 4 points or more than 8 errors, or worsening neuropsych test scores. NINCDS-ADRDA DSM-IIIR “The concept of aMCI evolved after study was launched; we adapted current aMCI criteria to diagnose cases.” Criteria for aMCI: 1) no dementia 2) memory impairment: >= 3 errors on 5-item Blessed test memory phrase 3) memory symptoms 4) normal cognitive function (verbal IQ >84 and score of less than 8 on the Blessed test) 5) generally preserved activities of daily living Informant interview?:Yes, when available 

(HR=0.985, 95% CI 0.967 to 1.008). 

Verghese, 

Lipton, 

Geographical location: 

Age:No dementia: 78.9 +3.1

Risk factor/exposure 1:

1) Follow-up rate: 469 of 488 enrolled (96.1%). 

CommentsNone 
B-272

Study Study Information Participants Risk Factor and 

Outcome Assessment 

Results Comments

Katz, et al., 2003 Bronx Aging Study 

NY, NY Setting:Community Study design: Prospective cohort Number of participants enrolled:469 Duration of follow up:2702 person-years. Median f/u of 5.1 yrs. Mean f/u for subjects in whom dementia did not develop: 5.6 + 4.1 

. Mean f/u for subjects in whom dementia did develop: 5.9 + 4.1. Time from risk factor assessment to final cognitive assessment:Median 5.1 yrs 

Dementia: 79.7 +3.1 

Sex:Female: No dementia: 63% 

Dementia: 67% 

Male: No dementia: 37% 

Dementia: 33% 

Race/ethnicity:White: No dementia: 92% 

Dementia: 91% 

Other: No dementia: 8% 

Dementia: 9% 

Baseline cognitive status:Non-demented Inclusion criteria: English speaking, age between 75 and 85 yrs, community dwelling. Exclusion criteria:Severe visual or hearing impairment, Parkinson’s disease, liver disease, alcoholism, or known terminal illness. 

Frequency of leisure activities. Method of assessing risk factor/exposure 1:Self-report Cognitive-activity and physical-activity scales in units of activity-days per week. Scales dichotomized to “rare participation” vs. “frequent participation”.6 cognitive activities and 11 physical activities Covariates/potential confounders adjusted for in analyses:Age Sex Educational level Medical illness Baseline Blessed test score Participation in other leisure activities. Method(s) of assessing cognitive status:NINCDS-ADRDA DSM Informant interview?: No

2) Important baseline differences: NA 3) Outcome of interest #1Incident dementia in 124 (61 with AD) 4) Outcome of interest #2 Reading, playing board games, playing musical instruments, and dancing were associated with reduced risk of dementia. A 1-point increment in cognitive activity score was associated with a reduced risk of dementia (HR, 0.93; 95% CI, 0.90-0.97), but a 1-pt increment in physical activity score was not (HR=1.00). Results were similar for AD and vascular dementia. HR reported for all activities in Table 2 in article. 

Quality assFor observ1) Unbias

cohort? 

2) Selectio

differenYes 

3) Sample 

differen

4) Adequa

cohort? 

5) Validat

ascerta

6) Validat

ascertaYes 

7) Outcom

exposu

8) Adequa

Partial 

9) Comple10) Analys

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11) Analytic 

Yes 
B-273

Study Study Information Participants Risk Factor and 

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Results Comments

Virtanen, 

SinghManoux, Ferrie, et al., 2009 Whitehall II study 

Geographical location: London, England Setting:

Community Study design: Prospective cohort Number of participants enrolled:2214 Duration of follow up:5 years Time from risk factor assessment to final cognitive assessment:5 years 

Age:Mean (SD): 52.1 Sex: [n (%)] Female: 23% Male: 77% Race/ethnicity: [n (%)] NR Baseline cognitive status:Non-demented Inclusion criteria: Office staff from 20 London-based Civil Servant depts. Aged 35-55 between 1985 and 1988. Exclusion criteria:None 

Risk factor/exposure

1:“How many hours do you work per week in your main job including work brought home?” “How many ours do you work in an average week in your additional employment?” Method of assessing risk factor/exposure 1:Self-report Covariates/potential confounders adjusted for in analyses:Age Sex Educational level Marital status Follow-up employment status Occupational grade Income Physical health indicators Psychological stress Anxiety Sleep problems Health risk behaviors Social support Family stress Job strain 

Method(s) of assessing cognitive status: 

1) Follow-up rate: 2214/3597 2) Important baseline differences: Differed by # hours worked on: sex, marital status, educational level, income, and psychological distress 3) Outcome of interest #1 Compared to those who worked <

40 hrs/wk, those who worked: 41-55 hrs/wk declined more on reasoning test (mean difference (-2.23; SE = 0.37; p = 0.046) >55 hrs/wk declined more on reasoning test (mean difference -2.9; SE=0.49; p = 0.007) Test for linear trend, p = 0.036 

CommentsNone Quality assFor observ1) Unbias

cohort? 

2) Selectio

differenYes 

3) Sample 

differen

4) Adequa

cohort? 

5) Validat

ascerta

6) Validat

ascertaYes 

7) Outcom

exposu

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10) Analys

confou

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Yes 
B-274

Study Study Information Participants Risk Factor and 

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Results Comments

Other – Decline from baseline to follow-up on tests of memory, reasoning, vocabulary, phonemic verbal fluency, and semantic verbal fluency Informant interview?:No 
B-275

Study Study Information Participants Risk Factor and 

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Results Comments

Waldstein, Giggey, Thayer, et l., 2005 Baltimore Longitudinal Study of Aging (BLSA) 

Geographical location: USA, majority from Baltimore, MD – Washington, D.C. area Setting:Community Study design: Prospective cohort Number of participants enrolled:847 Duration of follow up: visits every 2.32 (0.8) yrs, mean 2.7 (1.5) visits Time from risk factor assessment to final cognitive assessment:Calculated average 6.26 years (mean number of visits multiplied by mean number of years between visits) 

Age:Mean (SD): 70.6 (8.5) Sex:

Female: 344 (41%) Male: 503 (59%) Race/ethnicity:White 84.2% Non-white 15.8% Baseline cognitive status:Non-demented Inclusion criteria: Participating in the BLSA Exclusion criteria: Dementia  Cerebrovascular disease, including stroke  Renal failure 

Risk factor/exposure 1:Hypertension Method of assessing risk factor/exposure 1:Direct measurement once in each arm at least 90 min post breakfast, averaged Covariates/potential confounders adjusted for in analyses:Age, education, alcohol smoking antihypertensives depression Method(s) of assessing cognitive status:change in test score

Informant interview? No 

1) Follow-up rate: Not reported in detail. Participants had different number of follow-up assessments 2) Important baseline differences: NR 3) Outcome of interest #1 Only significant result was a 3-way interaction of baseline age, time interval, and quadratic systolic BP for the BVRT and the Boston Naming Test. For the BVRT, among younger individuals (age 60 at baseline), those with higher systolic BP made more errors on the BVRT than those with normal BP but improved over time (ie, practice effects). In contrast, among older individuals (age 80 at baseline), those with higher systolic BP declined in BVRT performance over time. On the Boston Naming Test, younger individuals (age 60 at baseline) with higher systolic BP performed more poorly than those with lower systolic BP across testing sessions. For older individuals (age 80 at baseline), those with higher systolic BP declined in performance over time. 

CommentsNone Quality assFor observ1) Unbias

cohort? 

2) Selectio

differenYes 

3) Sample 

differen

4) Adequa

cohort? 

5) Validat

ascerta

6) Validat

ascertaYes 

7) Outcom

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8) Adequa9) Comple

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Yes 

Wang, Wahlin, Basun, et al., 2001 Kungsholm

Geographical location: Stockholm Sweden Setting:Community 

Age:Range: 75-101 Sex: [n (%)] 

Female: 298 (80.54%)Male: 72 (19.46%) 

Risk factor/exposure

1:B12 Method of assessing risk factor/exposure 

1) Follow-up rate: 86 out of the 370 subjects died before the follow up period. Information on them was derived from hospital records. 

CommentsNone Quality assFor observ1) Unbias
B-276

Study Study Information Participants Risk Factor and 

Outcome Assessment 

Results Comments

en study subset Study design: 

Prospective cohort Number of participants enrolled:668 selected from initial sample. 443 included as non demented. Duration of follow up:3 years. Time from risk factor assessment to final cognitive assessment:3 years 

Race/ethnicity: [n (%)] NR Baseline cognitive status:Normal Non-demented Inclusion criteria: Born in 1912, Living in Kungsholmen area. Exclusion criteria:Refusing blood test. On folate or B12 replacement therapy. 

1:Direct measurement Blood test with cut off of B12≤ 150 pmol/L 

being low. 2nd cut off: B12≤ 250 

pmol/L being low Risk factor/exposure 2:Folate Method of assessing risk factor/exposure 2:Direct measurement Blood test with cut off of ≤ 10 nmol/L being 

low. 2nd cut off: ≤ 12 nmol/L 

being low. Covariates/potential confounders adjusted for in analyses:Age Sex Educational level Baseline cognitive status Method(s) of assessing cognitive status:DSM III R Informant interview?:Yes 

2) Important baseline differences:Patient with low B12 scores were less educated at baseline. Patient with low Folate scores were lower MMSE scores at baseline. 3) Outcome of interest #1 RR risk of incident AD during the three year follow up after adjusting for ages, sex and education: B12 ≤ 150 VS ≥150 pmol/L = 1.6 , 95% CI 0.9, 2.8 Folate ≤ 10 VS ≥10 nmol/L= 1.7 

95% CI 1.0, 3.4 Both B12 and Folate: 2.1; 95% CI 1.4, 3.8 4) Outcome of interest #2 When low levels were defined as B12 ≤250 pmol/L and folate ≤12 nmol/L, the adjusted RR for AD was 7.0 (95% CI 5 1.6 to 31.6) in subjects with MMSE score > 26 and was 1.4 (95% CI 5 0.7 to 2.7) in subjects with MMSE score ≤26 Low levels of vitamin B12 or folate after controlling for age, sex, education and baseline cognitive functioning: 1.4 (0.8–2.4) 5) Outcome of interest #3 No interaction between B12 and folate. 

cohort? 

2) Selectio

differenYes 

3) Sample 

differen

4) Adequa

cohort? 

5) Validat

ascerta

6) Validat

ascertaYes 

7) Outcom

exposu

8) Adequa9) Comple10) Analys

confou

11) Analytic 

Partial. folate a
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Study Study Information Participants Risk Factor and 

Outcome Assessment 

Results Comments

Wengreen, Munger, Corcoran, et al., 2007 Cache County Study 

Geographical location: Cache County, UT Setting:Community Study design: Prospective cohort Number of participants enrolled:3832 Duration of follow up:average 7.2 yrs Time from risk factor assessment to final cognitive assessment:average 7.2 yrs 

Age:Mean (SD):  Male 74.2 (6.5)  Female 75.0 (6.8) Sex: [n (%)] 

Female: 2066 (53.9%)Male: 1566 (46.1%) Race/ethnicity: [n (%)] NR Baseline cognitive status:Non-demented Inclusion criteria: ≥ 65 yo, residents of Cache County Exclusion criteria:NR 

Risk factor/exposure 1:Intake of antioxidants (vitamins C & E and carotenes) Method of assessing risk factor/exposure 1:Self-report Dietary food frequency questionnaire Covariates/potential confounders adjusted for in analyses:Several different models with different adjustments Method(s) of assessing cognitive status:Modified MMSE (3MS). Conducted in person at baseline and at f/u visits 2 and 3. Informant interview?:No 

1) Follow-up rate: 3632/3832 (94.8%) 2) Important baseline differences: Higher baseline 3MS scores in individuals with increasing quartiles of Vitamin C intake alone and combined with Vitamin E 3) Outcome of interest #1Lower levels of intake of vitamin C, E and carotene had greater acceleration of the rate of 3MS decline over time compared to those with higher levels of intake. Conclusion: “High antioxidant intake from food and supplement sources of vitamin C, vitamin E, and carotene may delay cognitive decline in the elderly.” 

4) Outcome of interest #2 See Table 3 for differences in mean baseline MS3 score across increasing quartile of intake of vitamins. p-trend reported across quartiles of intake. No single measure of association reported. 

CommentsNone Quality assFor observ1) Unbias

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Yes 

Wetherell, Reynolds, Gatz, et al., 2002 Swedish Adoption/T

Geographical location: Sweden Setting:Community 

Age:Mean (SD): 63.7 (8.6) Sex: [n (%)] 

Female: 416 (59.0%) Male: 288 (41.0%) 

Risk factor/exposure

1:Anxiety/neuroticism Method of assessing risk factor/exposure 1:

1) Follow-up rate: 75.5% 2) Important baseline differences: NR 3) Outcome of interest #1

CommentsRandom efQuality assFor observ1) Unbias

cohort? 
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Results Comments

win Study of Aging 

Study design:

Prospective cohort Number of participants enrolled:

704 Duration of follow up:Up to 9 years Time from risk factor assessment to final cognitive assessment:NR 

Race/ethnicity: [n (%)] NR Baseline cognitive status:Non-demented Inclusion criteria: Same sex twins born between 1886 and 1958 reared apart & control group reared together matched on gender, age, county of birth Age >=50 during study Exclusion criteria:Dementia at anypoint in f/u 

Self-report – 9-item short-form of the Eyesenck Personality Inventory Neuroticism Scale Covariates/potential confounders adjusted for in analyses:Age Sex Educational level Method(s) of assessing cognitive status: Other – 11 cognitive measures: Wechsler Adult Intelligence Scale Infomration subtest; Synonymes; Analogies; Figure Logic; Koh’s Block Design; Card Rotations; Figure Identifiiation; Symbol Digit; Digit Span, Names and Faces Pairs; Thurstone’s Picture Memory Informant interview?:No 

No significant association between neuroticism and cognitive change for any of the measures 

2) Selectio

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Yes 

Williamson, Espeland, Kritchevsky, et al., 2009 

Geographical location: Winston Salem, NC and Palo Alto, CA USA 

Age:Mean (SD): 77.4 (4.3) Sex: [n (%)] 

Female: 72 (70.6) 

Risk factor/exposure 1:Physical exercise Method of assessing 

1) Follow-up rate: 93/102 had cognitive testing at final time point2) Important baseline differences: 

CommentsQuestion 2Quality assFor RCTs: 
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Results Comments

Setting:Community Study design: RCT Test intervention: Physical activity: combination of aerobic, strength, balance and flexibility over a period of 12 mos Comparator intervention(s): Successful aging health education Number of participants enrolled:102 Duration of follow up:1 year Time from risk factor assessment to final cognitive assessment:Not applicable 

Male: 30 (29.4) Race/ethnicity: [n (%)] Caucasian: 83 (81.4) African Am: 14 (13.7) Hispanic: 2 (2.0) Other/mixed: 2 (2.0) Baseline cognitive status:Non-demented Inclusion criteria: Age 70-89 years. Sedentary life style (< 20 min/wk in structured physical exercise), able to walk 400 m within 15 minutes without sitting and without using any assistive device, Short Physical Performance Battery Exclusion criteria:NR 

risk factor/exposure 1:Self-report Direct measurement Covariates/potential confounders adjusted for in analyses:Baseline cognitive status Clinical site 

Method(s) of assessing cognitive status: Other – longitudinal change on cognitive tests (DSST, RAVLT, 3MS, modified Stroop) from baseline to 12 mos Informant interview?:No 

No differences on a number of demographic, medical, and function variables 3) Outcome of interest #1Intervention group showed slight improvement on DSST at 12 mos, but difference not significant. Change on the other measures favored the non-intervention group, but differences were not significant. 4) Outcome of interest #2 Outcome that is indirectly related to outcomes of interest: Improvement in DSST was associated with improvement in total Short Physical Performance Battery, chair stand score, and balance score. 

1) Baselin2) Valid A

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Yes 

7) Overall 8) Conflic

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Willis, Tennstedt, Marsiske, et al., 2006 Advanced Cognitive training for Independen

Geographical location: Birmingham Al; Detroit Mich; Boston Mass; Baltimore Md; Indianapolis In; State College Pa; Setting:

Age:Mean (SD): 73.6 Sex: [n (%)] 

Female: 2078 (74.16%) Male: 754 (25.84%) Race/ethnicity: [n (%)] 

Risk factor/exposure 1:Not Applicable – measuring training versus no training Covariates/potential confounders adjusted for in 

1) Follow-up rate: 2832 enrolled 2802 analyzed (ITT) Total attrition at 5 years – 1077 1755/2832= 62% 245 died; 595 withdrew; 214 were excluded by administrative decision and 23 were withdrawn by the family. 

CommentsGood qualisome differparticipants community For RCTs: 1) Baselin2) Valid A
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Results Comments

t and Vital Elderly. (ACTIVE) 

Other – [specify] Senior Housing Community Centers Hospitals Clinics Study design:

RCT Test intervention: Reasoning Training Memory Training Speed Training. Comparator intervention(s): No Training (Control) Number of participants enrolled:

2832 Duration of follow up:5 years Time from risk factor assessment to final cognitive assessment:5 years 

26% Black Baseline cognitive status:MMSE ≥ 23 No self reported AD Inclusion criteria: NR 

Exclusion criteria:  < 65 yrs of age;  functional impairment(≥2ADLdisabilities)  cognitive decline (MMSE score ≤22);  self reported AD;  medical conditions associated with imminent functional decline or death;  severe losses in vision, hearing, or communicative ability that would interfere with study participation;  recent cognitive training;  unavailable during the study period

analyses:Age Baseline cognitive status for those who did booster training since they were younger and had higher mmse scores For non booster analysis independent variables were: ‘Fixed effects for treatment group, time, assignment to booster training, field site. time x training, booster x training’Method(s) of assessing cognitive status: MMSE Other – Self Reported AD Informant interview?:No 

2) Important baseline differences:participants who were randomized to booster training were younger (P=.007) and had higher baseline MMSE scores (P=.008) compared with participants who were eligible and not assigned to booster training3) Outcome of interest #1  Effect of Training on Cognitive Outcomes From Baseline to Year 5 presented as Mean change from baseline to year 5; Effect size (99% CI)  Memory Training (outcome Memory) = −1.0 ; 0.23 (0.11 to 0.35)

 Reasoning Training (outcome reasoning)= 8.1 ; 0.26 (0.17 to 0.35) Speed Training (outcome processing speed) = 241.8; 0.76 (0.62 to 0.90) Speed Training (outcome reasoning) = 119.6; 0.15 (0.01 to 0.29)4) Outcome of interest #2  Effect of Booster Training on Cognitive Outcomes From Baseline to Year 5 after controlling for baseline age and MMSE score presented as Effect size (99% CI)  Reasoning Training (outcome reasoning)= 0.28 (0.12 to 0.43) 

 Speed Training (outcome processing speed) = 0.85 (0.61 to 1.09)5) Outcome of interest #3 None of the effect sizes for effect of training on functional outcomes from baseline to Year 5 reached statistical 

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Results Comments

significance at the 99% confidence interval. 

Wilson, Bennet, Bienias, et al., 2003 Chicago Health Aging Project. 

Geographical location: Chicago, USA Setting:Community Study design: Prospective cohort Number of participants enrolled:6158 enrolled. 1175 dies before first follow up. Of 4983 alive, 4392 completed first follow up (88.1%). This was considered to be the study sample. Duration of follow up:5.3 years Time from risk factor assessment to final cognitive assessment:6 years. Interviews done over 3 yr intervals. Average of 2.6 interviews per person. 

Age:Mean (SD): 73.9 (6.5) Sex: [n (%)] 

Female: 2727 (62%) Male: 1665 (38%) Race/ethnicity: [n (%)] AA: 2710 (61.7%)Other: 1682 (38.3%) Baseline cognitive status:All (none excluded based on cognitive status) Inclusion criteria: Residents of the Chicago area. ≥ 65 yrs of age. Exclusion criteria:NR 

Risk factor/exposure

1:Cognitive activity. Method of assessing risk factor/exposure 1:Self-report of number of activities on a 5 point scale- then converted into a composite score. Risk factor/exposure 2:Depression Method of assessing risk factor/exposure 2:Self-report CESD Covariates/potential confounders adjusted for in analyses: [delete any from the list below that do not apply and add items as needed] Age Race Sex Educational level Method(s) of assessing cognitive status:

1) Follow-up rate: Can’t tell. It appears that 88.1% of those alive at the first follow up completed at least one follow up interview and were included in the analysis. However, the number of participants who completed the second follow up is unknown. 2) Important baseline differences: Can’t tell. 3) Outcome of interest #1 The rate of cognitive decline was 0.064 units per year on the global measure of cognition Frequency of cognitive activity was associated with rate of cognitive decline. For each point on the cognitive activity scale, cognition decreased by 0.012 units, or about 19%. SE= 0.003, P <0.001 Compared to a person with infrequent cognitive activity (score = 2.14,10th percentile), rate of global cognitive decline was reduced by about 35% in a person with frequent cognitive activity (score = 4.00, 90th percentile) 4) Outcome of interest #2 After controlling for disability, number of medical conditions, CES-D score, 

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Study Study Information Participants Risk Factor and 

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Results Comments

Other – [specify] Cognitive change on global index of cognitive function. Informant interview?:No 

age, sex, race, and education, cognitive activity continued to be related to reduced cognitive decline (estimate = 0.010, SE = 0.004, p =0.003). 

Wilson, Bienias, BerryKravis, et al., 2002 Religious Orders Study 

Geographical location: 40 sites across the USA Setting:Community - Religious orders Study design: Prospective cohort Number of participants enrolled:669 Duration of follow up:2-8 years Annual assessment Average 5.9 to 6 Time from risk factor assessment to final cognitive assessment:Up to 8 years 

Age:Means(sd) e2: 75.7 (7.3) yrs e3: 75.7 (6.7) yrs e4 74.8 (6.3) yrs Sex: [n (%)] 

Female: 435 (65%) Male: 234 (35%) Race/ethnicity: [n (%)] 622 (93%) white nonhispanic Baseline cognitive statusNon-demented Inclusion criteria: Religious orders member at 1 of 40 groups. Age at least 65. Not demented Exclusion criteria:Dementia. 

Risk factor/exposure

1:Apolipoprotein E ε4 APOE ε4 Method of assessing risk factor/exposure 1:Direct measurement Covariates/potential confounders adjusted for in analyses:Age Sex Educational level Time since baseline Method(s) of assessing cognitive status:

19 tests 7 assessed episodic memory (world list memory, recall, and recognition; immediate and delayed recall logical memory and East Boston); Semantic memory (verbal fluency); 

1) Follow-up rate: 98% 2) Important baseline differences: NR 3) Outcome of interest #1 Random effects model Rate of episodic memory change ε2/2 or 2/3: +.016 ε3/3: -.022 ε4/4 or 3/4: -.073 ε2 vs ε3/3 p<.05 ε4 vs ε3 p<.001 No difference between ε2 and ε3 in 

other cognitive domains ε4 declined more rapidly than ε3/3 in 

semantic memory and perceptual speed, but not in working memory or visuospatial ability ε2 semantic memory decline is slower than ε3/3, but there is no 

effect in other cognitive domains. 

Comments None Quality assFor observ1) Unbias

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Results Comments

Boston naming; National adult reading test; extended range vocabulary; Working memory (digits forward, digits backward, digit ordering and alpha span); Perceptual speed (symbol digit modalities test and number comparison); visuospatial ability (judgment of line orientation, standard progressive matrices). Other – rate change cognitive test Informant interview?:No 

Wilson, Hebert, Scherr, et al., 2009 Chicago Health and Aging Project

Geographical location: Southside Chicago USA Setting:Community Study design:

Prospective cohort Number of participants enrolled:

6533 Duration of follow up:6.5 (SD = 3.6) years

Age:Mean (SD): 72.2 years (SD = 6.1) Sex: [n (%)] Female: 61% Male: 39% Race/ethnicity: [n (%)] 67% were African American Baseline cognitive status:All Inclusion criteria: Older residents of the 

Risk factor/exposure 1:Educational attainmentMethod of assessing risk factor/exposure 1:Self-report Covariates/potential confounders adjusted for in analyses:Age Race Sex Five chronic medical conditions was 

1) Follow-up rate: 10,068 people interviewed at baseline 1,552 died before the first follow-up interview and 1,580 had not yet reached the date scheduled for the first follow-up. Among the 6,936 eligible for followup, 6,533 (94%) completed at least one follow-up interview.

2) Important baseline differences: Higher education associated with younger age (p < 0.001) and white race (p < 0.001) 3) Outcome of interest #1No linear association between 

CommentsQuestion 2 Quality assFor observ1) Unbias

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Time from risk factor assessment to final cognitive assessment:6.5 (SD = 3.6) years

Chicago Southside area. Completed at least one follow up interview. Exclusion criteria:

NR 

obtained from self report of heart attack or myocardial infarction, hypertension, stroke, diabetes mellitus, and cancer Method(s) of assessing cognitive status:Other – longitudinal change on the immediate and delayed recall of the East Boston Story Oral form of the Symbol Digit Modalities Test Mini-Mental State Examination Informant interview?:No 

education and rate of change in cognitive function. Models that allowed for non-linearity in education and its relation to cognitive decline showed that education was associated with change in cognitive performance over time (coefficient >-0.001; se: <0.001; p = 0.005). The rate of cognitive decline at average or high levels of education was slightly increased during earlier years of follow-up but slightly decreased in later years in comparison to low levels of education. Findings were similar among black and white participants. 4) Outcome of interest #2 Cognitive performance improved with repeated test administration, but there was no evidence that retest effects were related to education or 

attenuated education’s association with cognitive change (Education x retest 4: coefficient <-0.001; se: 0.039; p = 0.990) 

Yes 

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Yes 

Wilson, Krueger, Arnold, et al., 2007 Rush Memory & Aging Project

Geographical location: Chicago, IL Setting:Community Study design: Prospective cohort 

Age:Mean (SD): 80.7 (7.1) Sex: [n (%)] 

Female:  600 (75.8%) Male:  192 (24.2%) Race/ethnicity: [n (%)] 

Risk factor/exposure

1:Loneliness Method of assessing risk factor/exposure 1:Self-report – de Jong Gierveld Loneiness Scale (range 0-

1) Follow-up rate: 92.3% 2) Important baseline differences: NR 3) Outcome of interest #1 After adjusting for age, sex, and level of educational achievement, risk of clinical AD (76 subjects) increased 

CommentsNone Quality assFor observ1) Unbias

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Results Comments

Number of participants enrolled:857; 791 analyzed Duration of follow up:Mean 3.3 years. Range: 2-5 years. Time from risk factor assessment to final cognitive assessment:Mean 3.3 years. Range: 2-5 years. 

 African-American  46 ( (5.8%)  Other  746 (94.2%)Baseline cognitive status:Non-demented Inclusion criteria: Participant in Rush Memory and Aging Project; agreement to annual in-home clinical evaluations; agreement of brain donation upon death; completed at least one follow-up evaluation Exclusion criteria:Dementia Dx @ baseline 

5)(Questionnaire) Risk factor/exposure 2:Social isolation (social network size [#] and participation in social activity (0-5 scale) Method of assessing risk factor/exposure 2:Self-report Covariates/potential confounders adjusted for in analyses:age, sex, and level of educational achievement and for social activity, social network, physical activity, cognitive activity, depressive symptoms, income, race/ethnicity, disability, and vascular risk factors Method(s) of assessing cognitive status:NINCDS-ADRDA Informant interview?:NO 

by approximately 51% for each point on the loneliness scale (relative risk [RR], 1.51; 95% [CI], 1.06-2.14) Social activity (0-5): RR 0.52 (95% CI 0.34 to 0.79) Social network size: RR 1.01 (95% CI 0.97 to 1.05) 4) Outcome of interest #2 Relation of loneliness to AD incidence after controlling for social network and social activity in the above model: RR, 1.45; 95% CI, 1.01-2.09 Additional analyses showed the association between loneliness and AD was unchanged after controlling for income, disability on the Katz scale and vascular risk factors and conditions.

5) Outcome of interest #3 Relation of Loneliness to Change in Cognitive Function after controlling for age, sex, and level of educational achievement in separate mixed effect models: Global cognition: Loneliness x time Estimated SE: -0.01 (0.01) P = .03 Episodic memory: Loneliness x time Estimate (SE) 0.00 (0.01) p = .79Semantic memory: Loneliness x time Estimate (SE) −0.02 (0.01) p = .01 

Working memory: Loneliness x time Estimate (SE) −0.02 (0.01) p = .09 

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Results Comments

Perceptual speed: Loneliness x time Estimate (SE) −0.02 (0.01) p = .03 

Visuospatial ability: Loneliness x time Estimate (SE) −0.03 (0.01) p = .04

Wilson, Mendes De Leon, Barnes, et al., 2002 RELIGIOUS ORDERS STUDY 

Geographical location: U.S. Setting:Community –Religious Orders Study design:

Prospective cohort Number of participants enrolled:

879 screened; 801 eligible Duration of follow up:Mean 4.5 years Time from risk factor assessment to final cognitive assessment:Mean 4.5 years 

Age:Range: Incident AD: 81.1(6.2) No AD: 74.3 (6.3) Sex:

Incident AD (n=111) Female: 74 (66.7%) Male: 37 (33.3%) No AD (n=622) Female: 418 (67.2%) Male: 204 (32.8%) Race/ethnicity:Incident AD White, non-Hispanic = 105 (94.6%) No AD White, non-Hispanic =562 (90.4%) 

Baseline cognitive status: Non-demented Inclusion criteria:  > 65 years at baseline  Consent to annual clinical evaluations  Consent to brain 

Risk factor/exposure 1:Cognitive activity frequency. Method of assessing risk factor/exposure 1:Self-report 7 common activities that involve information processing. Frequency rated on a 5-point scale: 5) 5 points: every day or about every day. 4) 4 points: several times a week. 3) 3 points: several times a month. 2) 2 points: several times a year. 1) once a year or less. Covariates/potential confounders adjusted for in analyses:Age Gender Education Cognitive activity score

1) Follow-up rate: 724/801 (90%) 2) Important baseline differences: NA 3) Outcome of interest #1 Annual Rate of Change in Specific Cognitive Functions: Association with Cognitive Activity Frequency Estimate (SE), p value Working memory: 0.021 (0.008), p=.007 Perceptual speed: 0.026 (0.012), p=0.02 In random-effects models, a 1-point increase in cognitive activity was associated with reduced decline in global cognition (by 47%), working memory (by 60%), and perceptual speed (by 30%). 4) Outcome of interest #2 RR of Incident AD by Cognitive Activity Frequency Score: RR 0.67 (95% CI: 0.49, 0.92) A 1-point increase in cognitive activity score was associated with a 33% RR of AD (hazard ration, 0.67; 

CommentsNone Quality assFor observ1) Unbias

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donation at the time of death Exclusion criteria:Dementia at baseline 

Method(s) of assessing cognitive status: 20 cognitive tests administered in a 45-minute session. MMSE for descriptive purposes. 7 tests of episodic memory; 4 tests of working memory; 2 tests of perceptual speed; and 2 tests of visuospatial ability  Composite measures of global cognition.  AD diagnosed according to NINCDS/ADRDA Informant interview?:No 

95% CI: 0.48, 0.92) 5) Outcome of interest #3 Results were comparable when terms for ApoE were added to the model. 6) Outcome of interest #4 Physical activity was not associated with risk of AD (HR, 1.00; 95% CI, 0.97-1.02). 

Wilson, Scherr, Hoganson, et al., 2005 Religious Order Study 

Geographical location: Multiple US sites Setting:Community - members of Religious Orders Study design: Prospective cohort Number of participants enrolled:859 Duration of follow up:

Age:Mean (SD): 75.0 (7.0) Sex:

Female: 596 (69.4%) Male: 263 (30.6%) Race/ethnicity:African-American: 71 (8.3%) Other: 787 (91.7%) Baseline cognitive status:Non-demented 

Risk factor/exposure 1:Early life socioeconomic status (SES) indicators Method of assessing risk factor/exposure 1:Self-report SES: 1) parental education, 2) paternal occupation, 3) # of children in the family. 

1) Follow-up rate: 859/ 877 – 98% 2) Important baseline differences: NA 3) Outcome of interest #1154 incident cases of AD. 4) Outcome of interest #2 Neither early life household (RR: 1.12, 95% CI: 0.88,1.42) nor community SES (RR: 1.35, 95% CI: 0.93, 1.96) was related to risk of AD. (RR is for a 1-unit increase in each 

CommentsNone Quality assFor observ1) Unbias

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Results Comments

Mean: 5.6 years Time from risk factor assessment to final cognitive assessment:Mean: 5.6 years 

Inclusion criteria: Catholic nuns, priests, and brothers from the Religious Orders StudyExclusion criteria:

Dementia at baseline 

Also, 3 other SES indicators based on county of birth: 4) literacy rate, 5) % of children in county in school, 6) Duncan SES. The 7th SES indicator 

was participant’s own education level attained. Summary measures used for early life household and community SES level. Covariates/potential confounders adjusted for in analyses:Age Sex Educational level SES indicators Method(s) of assessing cognitive status:NINCDS-ADRDA Other: change in performance on cognitive tests over time Informant interview?:No 

SES indicator) No significantly different findings when quadratic terms for SES indicators added. 5) Outcome of interest #3 Higher SES was related to slightly greater decline on semantic memory task. There were no other significant associations between independent variables and cognitive change over time. 

6) Validat

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Yes 

Wilson, Geographical Age: Risk factor/exposure 1) Follow-up rate: Comments
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Results Comments

Scherr, Schneider, et al., 2007 RUSH MEMORY AND AGING PROJECT 

location: Chicago area, USA Setting:Community Study design:

Prospective cohort Number of participants enrolled:

931 with baseline evaluation; 829 eligible at one year follow-up Duration of follow up:Mean of 3.5 (sd = 1.2) annual follow up assessments. Range: 2 – 6 follow-ups Time from risk factor assessment to final cognitive assessment:Mean of 3.5 (sd = 1.2) annual follow up assessments. Range: 2 – 6 follow-ups 

Mean (SD): 80.4 (7.4) Sex:

Female: 581 (75%) Male: 194 (25%) Race/ethnicity:White (non-Hispanic): 705 (91%) Other: 70 (9%) Baseline cognitive status:Non-demented Inclusion criteria:  Participating in the Rush Memory and Aging Project  Agree to annual clinical evaluation  Agree to donate brain at death Exclusion criteria:Dementia at baseline 

1:Cognitive activity participation Method of assessing risk factor/exposure 1:Self-report. Structured questionnaire at baseline. Frequency of participate on a 5-point scale, from 1 = once a year or less, to 5= every day or about every day. Covariates/potential confounders adjusted for in analyses:Age Sex Educational level Method(s) of assessing cognitive status:NINCDS-ADRDA MCI classified as evidence of impairment in at least one cognitive domain in the 

absence of dementia. Other: change in performance on cognitive tests over 

775/829 (93.5%) with f/u data 2) Important baseline differences: NR by cognitive activity level 3) Outcome of interest #1 More frequent current cognitive 

activity was associated with reduced incidence of AD (RR _ 0.58; 95% CI: 0.44, 0.77).More frequent past cognitive activity was also associated with reduced risk of AD (RR _ 0.56; 95% CI: 0.36, 0.88)

4) Outcome of interest #2 

more frequent cognitive activity was associated with reduced incidence of MCI (RR _ 0.71; 95% CI: 0.58, 0.87). 5) Outcome of interest #3More frequent current cognitive activity associated with less decline on global cognitive measure  Estimate = 0.025; se=0.010; p = 0.015

None Quality assFor observ1) Unbias

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Study Study Information Participants Risk Factor and 

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Results Comments

time Informant interview?:No 

Wilson, Schneider, Boyle, et al., 2007 Religious Orders Study & Rush Memory and Aging Project 

Geographical location: Chicago, USA & other USA locations Setting:Community Study design: Prospective cohort Number of participants enrolled:1256 Duration of follow up:RMAP = 3.9 and for the combined group = 6.2 mean annual evaluations Range 1 – 13 yrs Time from risk factor assessment to final cognitive assessment:RMAP = 3.9 and for the combined group = 6.2 mean annual evaluations Range 1 – 13 yrs 

Age:Mean (SD): 76.8(7.7) Sex: [n (%)] 

Female: 888(70.7%) Male: 368 (29.3%) Race/ethnicity: [n (%)] 1143 (91%) White nonHispanic Baseline cognitive status:Non-demented Inclusion criteria: Catholic nuns priests and brothers who agreed to brain donation at death (ROS study) or participant in RMAP At least 1 year f/u Valid score on NEO neuroticism scale Exclusion criteria:Dementia or MCI 

Risk factor/exposure

1:Depression – 10-item CESD 2: Distress proneness – 6 items from the 12-item NEO Five Factor Inventory (score ranges 0- 48) Method of assessing risk factor/exposure 1:Self-report at baseline Covariates/potential confounders adjusted for in analyses:Age Sex Educational level Method(s) of assessing cognitive status:NINCDS-ADRDA for AD MCI – cognitive impairment w/o meeting criteria for dementiaInformant interview?:No 

1) Follow-up rate: 95.2% 2) Important baseline differences: Can’t tell 3) Outcome of interest #1Association with MCI  CESD for each depressive symptom, RR=1.06 (95% CI 1.002 to 1.120) Distress proneness RR for each one point increase = 1.02 (95% CI 1.01 to 1.04) When controlling for CESD score the association between distress proneness and MCI was not substantially changed, RR 1.02, 1.01 to 1.04 When controlling for distress proneness score the association between CESD and MCI was not significant RR=1.02, 0.96 to 1.09 

CommentsUnclear CEassociation increase or Quality assFor observ1) Unbias

Partial. autopsy

2) Selectio

differenYes 

3) Sample 

differen

4) Adequa

cohort: 

5) Validat

ascerta

6) Validat

ascertaPartial 

7) Outcom

exposu

8) Adequa9) Comple10) Analys

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Yes 
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Study Study Information Participants Risk Factor and 

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Results Comments

Winnock, Letenneur, JacqminGadda, et al., 2002 PAQUID 

Geographical location: Gironde, France Setting:Community Study design: Prospective cohort Number of participants enrolled:2792 in PAQUID. Of these, 626 initially eligible by volunteering for APOE testing. Duration of follow up:Mean NR. Range: 1-8 yrs. Time from risk factor assessment to final cognitive assessment:Mean NR. Range: 1-8 yrs. 

Age at baseline:Mean (SEM): 73.7 (0.26) Range: 65-94 Sex:

NR Race/ethnicity:NR Baseline cognitive status:Non-demented Inclusion criteria: > 65 yrs, living in 

southern France. Participants of PAQUID study who volunteered to give a blood sample for APOE phenotyping at the 1sr year f/u interview. Exclusion criteria:Dementia at baseline and at 1st year of f/u. 

Risk factor/exposure 1:Education Method of assessing risk factor/exposure 1:Self-report Risk factor/exposure 2:APOE Method of assessing risk factor/exposure 2:Direct measurement Covariates/potential confounders adjusted for in analyses:Age Sex Education Time Age by time APOE Random effects linear regression model, which takes into account the lack of independence of a subject’s measurements across time. Method(s) of 

1) Follow-up rate: 2792 in PAQUID. 626 in this study because they volunteered for APOE testing. Two analyses: 1) Excluded dementia at baseline or 1st yr f/u (n=26). Sample size: 

600/626 = 96% 2) Excluded dementia at baseline, 1st

year or 3rd year f/u (n=53). Sample 

size: 547/626 = 87% MMSE f/u rates: 1-yr: 574 (95.7%) 3-yr: 508 (84.7%) 5-yr: 457 (76.2%) 8-yr: 364 (60.7%) Four MMSE measurements available in 332 participants (55.3%) 2) Important baseline differences: NA 3) Outcome of interest #1--APOEAPOE was significantly associated with lower cognitive performance at baseline. Course of cognitive performance during the f/u was the same for both APOE carriers and noncarriers. 4) Outcome of interest #2—APOE and education Lower education level was associated with lower cognitive performance at baseline, and the 

CommentsNone Quality assFor observ1) Unbias

cohort? 

2) Selectio

differenYes 

3) Sample 

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ascertaYes 

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Yes 
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Study Study Information Participants Risk Factor and 

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Results Comments

assessing cognitive status: Assessments at 1, 3, 5, 8, & 10 yrs after baseline visit. Cognitive performance evaluated at each visit with a comprehensive battery of tests. DSM-IIIR for dementia, followed by neurologist evaluation to confirm diagnosis of dementia. Main outcome: MMSE scores at multiple timepoints Informant interview?:No 

effect of an APOE allele on cognitive performance disappeared after adjustment for education. APOE carriers show decreased MMSE scores compared with noncarriers, but the effect of APOE on cognition disappears after adjustment for education. Non-demented elderly people maintain a stable cognitive performance regardless of the their APOE phenotype. 5) Outcome of interest #3 Conclusions: 1) Baseline cognition related to APOE phenotype 2) APOE effects disappeared after adjustment for education 3) No global cognitive decline observed over time among nondemented participants 4) Level of global cognitive performance remained stable throughout f/u and was independent of APOE phenotype. 

Wright, Elkind, Luo, et al., 2006 Northern Manhattan Study 

Geographical location: Northern Manhattan, NY, USA Setting:Community 

Age:Mean (SD): 71 yr (9) Sex:

Female: 957 (67%) Male: 471 (33%) Race/ethnicity: [n (%)] 

Risk factor/exposure

1:Alcohol Method of assessing risk factor/exposure 1:Self-report- at cognitive 

1) Follow-up rate: NR (cannot tell how many of those not included in analyses actually dropped out vs were missing alcohol data) 2) Important baseline differences: Trend (p<0.0001) toward those 

CommentsNone Quality assFor observ1) Unbias

cohort? 

2) Selectio
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Results Comments

(NOMAS) Study design: 

Prospective cohort Number of participants enrolled:1428 analytical sample Duration of follow up:Mean 2.2 yrs (range 0.5-4.4) Time from risk factor assessment to final cognitive assessment:Mean 2.2 yrs (range 0.5-4.4) 

NR Baseline cognitive status:NR Inclusion criteria: At least 40 yrs old, no history of stroke, resident of North Manhattan for at least 3 mos, have a phone Exclusion criteria:None except as covered by inclusion criteria. 

baseline asked questions about alcohol intake during past six months; details of quantity of wine, beer, and liquor were collected Covariates/potential confounders adjusted for in analyses:Age Race Sex Educational level Baseline cognitive status Interval between cognitive testing Health insurance status HDL-C level BMI History of hypertensionDiabetes Cardiac disease Smoking Depression Physical activity Method(s) of assessing cognitive status: Other – longitudinal performance on the TICS-m Informant interview?: No 

drinking less or no alcohol being younger, more likely to be female, had less than 8 yrs education, less likely to have insurance, more likely to be Hispanic, more likely to have hypertension, more likely to have diabetes, more likely to smoke, more likely to have a higher BMI, more likely to be depressed, and more likely to be physically active. Individuals who drank 1 drink/month to <1/week or > 2/day had higher homocysteine levels than never drinkers. Individuals who drank 1/week or more had higher baseline TICS-m scores than nondrinkers. 3) Outcome of interest #1Drinking less than one drink a week (P=0.09), between one drink weekly up to two drinks daily (P=0.001), and more than two drinks daily (P=0.003) were associated with less cognitive decline on the modified Telephone 

Interview for Cognitive Status (TICSm) compared to never drinkers.. 4) Outcome of interest #2 This dose-response relationship was not modified by the presence of an APOE-4 allele in a subsample 

differenYes 

3) Sample 

differen

4) Adequa

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5) Validat

ascerta

6) Validat

ascertaYes 

7) Outcom

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8) Adequa9) Comple

Partial 

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Yes 
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Study Study Information Participants Risk Factor and 

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Results Comments

Xu, von Strauss, Qiu, et al., 2009 Kungsholmen 

Geographical location: Kungsholmen district of Stockholm, Sweden.Setting:Community Study design: Prospective cohort Number of participants enrolled:1248 Duration of follow up:9 year; (mean per person=5.1 years; maximum=10.5 years)Time from risk factor assessment to final cognitive assessment:~6 yr 

Age:Mean (SD):  nl 81.4 (4.9)  borderline DM 82.2 (5.2)  DM 81.6 (5.2) Sex: [n (%)] 

Female: 74.7% Male: 25.3% Race/ethnicity: [n (%)] NR Baseline cognitive status:Non-demented Inclusion criteria: all registered inhabitants who were living in the Kungsholmen district of Stockholm, Sweden, and were aged ≥75 

years on 1 October 1987 were initially invited to participate in the project.

Exclusion criteria:dementia 

Risk factor/exposure 1:Diabetes mellitus Method of assessing risk factor/exposure 1:Direct measurement Medical record Other – medication useCovariates/potential confounders adjusted for in analyses:Age, sex, education, baseline MMSE score, BMI, APOE genotype and vascular disorders (i.e. heart disease, stroke, antihypertensive drug use and BP) were considered as potential confounders.

Method(s) of assessing cognitive status:DSMIII-R Informant interview?:No 

1) Follow-up rate: 1248/1475 = 84.6 2) Important baseline differences: MMSE score; presence of heart disease; diastolic BP; use of antihypertensive drugs differ in nondiabetic, borderline and DM groups 3) Outcome of interest #1Fully adjusted model AD with stroke Non-diabetic HR 1 Borderline DM 1.93 (.59-6.28) Undiagnosed DM 3.75 (.48-4.55) AD without vasc comorbidities Non-diabetic 1 Borderline HR 2.85 (1.29-6.3) Undiagnosed DM 4.74 (1.08-18.46) 4) Outcome of interest #2 Normal 1 Borderline HR 1.87 (1.11-3.14) <7.8mmol OR 0.34 (0.05-2.43) 7.7-11mmol 1.26 (0.46-3.62) >11mmol 1.08 (0.4-2.95) Undiagnosed DM 3.29 (1.2-9.01) 

CommentsNone Quality assFor observ1) Unbias

cohort? 

2) Selectio

differenYes 

3) Sample 

differen

4) Adequa

cohort? 

5) Validat

ascerta

6) Validat

ascertaYes 

7) Outcom

exposu

8) Adequa9) Comple10) Analys

confou

11) Analytic 

Yes 

Yaffe, Barnes, 

Geographical location: 

Age:Mean (SD): 70.8 ±4.7 

Risk factor/exposure 1:

1) Follow-up rate: There were 7701 women who had a 

CommentsQuestion 2
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Study Study Information Participants Risk Factor and 

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Results Comments

Nevitt, et al., 2001 Study of Osteoporotic Fxs 

Baltimore, Minneapolis, Monongahela Valley (near Pittsburgh), Portland Oregon Setting:Community Study design:

Prospective cohort Number of participants enrolled:

5925 Duration of follow up:Mean 7.5 yrs range Time from risk factor assessment to final cognitive assessment:Mean 7.5 years. Follow-up at both 6 and 8 years after initial assessment 

Range: ≥65 Sex: [n (%)] 

Female: 100% Race/ethnicity: [n (%)]Black women excluded Baseline cognitive status:shortened mmse >

23/26 Inclusion criteria: Participant in the Study of Osteoporotic Fractures. Exclusion criteria:Shortened mmse < 23/26, women unable to stand up unaided from chair or walk up stairs (self reported), black women, women with missing baseline cognitive score, women with baseline physical limitations, women with missing information on physical limitations, women who did not complete baseline physical activity assessments 

Physical activity Method of assessing risk factor/exposure 1:Self-report Covariates/potential confounders adjusted for in analyses:Age, Educational level Health status, functional limitation, depression score, stroke, dm, htn, mi, smoking, estrogen use Method(s) of assessing cognitive status:change in shortened mmse score. Change of > 3 points over 

period of follow up defined cognitive decline.

Informant interview?:No 

high enough baseline cognitive score and who did not report physical limitations at baseline. Of these, 8% (596) died, 3% were lost (238), 12% (942) did not have follow up cognitive testing, leaving 5925/7701 or 77% 2) Important baseline differences: Physical activity divided into quartiles. Those in higher quartiles were younger, more educated, more likely to drink and take estrogen, less likely to smoke with a lower bmi, lower depression scores, fewer medical comorbidities and less functional limitation. 3) Outcome of interest #1 Using lowest quartile of blocks walked per week as reference: Second had OR 0.87 (0.72 – 1.05) third OR 0.63 (0.52-0.77) highest quartile had OR 0.66 (0.54 – 0.82) Using total kilocalories per week into quartiles with the lowest as the reference: again OR Second 0.90 (0.74-1.09) Third 0.78 (0.64-0.96) Highest 0.74 (0.60-0.90) 4) Outcome of interest #2 Results are presented comparing the second, third and highest quartiles to the lowest with results stratified by age (at 70), by presence or absence of medical comorbidities and by education (at 12 yrs). These results do not appear otherwise adjusted. 

I suspect thin this studyQuality assFor observ1) Unbias

cohort?

2) Selectio

differenfactors

3) Sample 

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5) Validat

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Yes 

10) Analys

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11) Analyti

Yes. 
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Study Study Information Participants Risk Factor and 

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Results Comments

5) Outcome of interest #3The percentage decline in the shortened mmse score was also treated as a continuous variable. The difference between women in the higher quartiles and those in the lower quartiles was significant (p<0.001) 6) Outcome of interest #4 cognitive decline (defined as a three or more point drop in screener score) was present in 17% of those in highest activity quartile, 18% next, 22% next and 24% of those in lowest quartile. It is noted that these women had important baseline differences as above, however (particularly age, vascular disease, smoking). Baseline cognitive scores were also reported difference with p=0.001 but difference was between 25.1 in lowed group and 25.2 in other quartiles . 

Yaffe, Blackwell, Gore, et al., 1999 Study of Osteoporotic Fractures 

Geographical location: Baltimore, MD; Minneapolis, Minn; Monongahela Valley, PA; Portland, OR Setting:Community Study design:

Prospective cohort Number of participants enrolled:

Age:Mean (SD): 72.8 (4.7) to 74.0 (5.2) Sex: [n (%)] 

Female: 7511 (100%) Male: 0 (0%) Race/ethnicity: [n (%)] NR Baseline cognitive status:Non-demented 

Risk factor/exposure

1:Depressive symptoms Method of assessing risk factor/exposure 1:Self-report at baseline using the Geriatric Depression Scale (GDS, range 0-15) Covariates/potential confounders adjusted for in 

1) Follow-up rate: 645 died; 5781/7511 had follow-up (76.9%) Women w/o f/u had lower baseline cognitive and depression scores 2) Important baseline differences: Women with more depressive symptoms were older, reported more functional impairment, were less educated, exercised less, were less likely to report good health status and less likely to be married 3) Outcome of interest #1

CommentsLogistic regdecline in MOnly womeQuality assFor observ1) Unbias

Yes 

2) Selectio

differenYes 

3) Sample 

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Study Study Information Participants Risk Factor and 

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Results Comments

7511 Duration of follow up:4 years Time from risk factor assessment to final cognitive assessment:4 years 

Inclusion criteria: Age >=65 yo Community dwelling Exclusion criteria:

Black race Prior clinical diagnosis of dementia 

analyses:Age Educational level Baseline cognition Health status Exercise Alcohol use Funcational status Clinic site Method(s) of assessing cognitive status:Modified MMSE decline by >=3 points (mMMSE range 0-26) Change in Trails B, Digit symbol and mMMSE Informant interview?:No 

Incident AD >=3 point decline on mMMSE (n=653 cases): OR for >=6 on GDS=2.1 (1.4-3.1); OR for 3-5 on GDS=1.6 (1.2-2.1) compared to 0-2 on GDS 4) Outcome of interest #2  MMSE decline of >=3 points Subgroup analysis educational level showed: <=8 years: OR for MMSE decline = 0.84 (0.49 to 1.43) > 8 years: 1.83 (95% CI 0.93 to 3.6) 5) Outcome of interest #3 Change in cognition Women with more depressive symptoms had a greater decline in cognitive scores for the Trails B (F=3.64, p=0.03), Digit Symbol (F=3.41, p=0.03) and modified MMSE (F=8.44, p<0.001) A sensitivity analysis excluding women with a modified MMSE of < 20 at baseline or who reported a history of physician-diagnosed stroke, dementia, or Parkinson disease at the time of f/u “did not substantially affect the results.” - data not given 

4) Adequa

cohort: 

5) Validat

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6) Validat

ascertaPartial; signific

7) Outcom

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8) Adequa9) Comple

Partial, with co

10) Analys

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11) Analytic 

Yes 

Yaffe, Cauley, Sands, et al., 1997 

Geographical location: Monongahela Valley near Pittsburgh, PA 

Age:Mean (SD): 71 Sex: [n (%)] 

Female: 100% 

Risk factor/exposure 1:APOE genotype Method of assessing 

1) Follow-up rate: 1248/1750= 71.3% Follow-up cognitive testing in 1138 1138/1248 = 91.2% 

CommentsNone Quality assFor observ
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Study Study Information Participants Risk Factor and 

Outcome Assessment 

Results Comments

Setting:Clinical – Monongahela Valley Clinic of the multicenter Study of Osteoporotic Fractures Study design: Prospective cohort Number of participants enrolled:1750 1248 with cognitive testing Duration of follow up:Average 6.4 years Time from risk factor assessment to final cognitive assessment:6 years 

Male: 0% Race/ethnicity: [n (%)] 

100% white except for 3 Asian and 1 other. Baseline cognitive status:Non-demented Inclusion criteria: Women were over the age of 65 and living in the community. They were recruited from 1985 voter registration lists in selected zip codes within approximately 40 km of the clinic. Exclusion criteria:Men and black women because of lower risk of osteoporotic fractures. Dementia, Parkinson’s disease or stroke. 

risk factor/exposure 1:Direct measurement Covariates/potential confounders adjusted for in analyses:Age Educational level Baseline cognitive status Depression Presence of severe tremor Method(s) of assessing cognitive status:Other – Modified MMSE (max score 26 Trails B Digit Symbol Cognitive decline was defined on each or any test if a woman had the largest 10th percentile 

reduction in performance from initial score to repeat testing. Informant interview?:No 

2) Important baseline differences:none 3) Outcome of interest #1Presence of an APOE4 was significantly associated with worsening on all cognitive tests at follow-up compared to no E4 group (modified MMSE P=.01; Digit Symbol P=.05; Trails B P=.003) 4) Outcome of interest #2 Incidence of cognitive decline was 1.6 times higher in the E4 group (P<.03) and ranged from 1.2 times higher for Trails B to 2.4 times higher for modified MMSE. Homozygotes declined almost twice as fast as heterozygotes on all tests except Trails B. 5) Outcome of interest #3 Reduction on the modified MMSE was 0% for no E4; 1.9% for 1 E4; and 3.7% for 2 E4s (P<.001) Reduction on Digit Symbol was 6.2% for no E4; 9% for 1 E4 and 17.5% for 2 E4s. (P=.04) Reduction on Trails B was 5.9% for no E4; 25% for 1 E4 and 10.9% on 2 E4s (P=.002) 

1) Unbias

cohort? 

2) Selectio

differenYes 

3) Sample 

differen

4) Adequa

cohort? 

5) Validat

ascerta

6) Validat

ascertaYes 

7) Outcom

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8) Adequa9) Comple10) Analys

confou

11) Analytic 

Yes 

Yaffe, Fiocco, Lindquist, et al., 2009 

Geographical location:Memphis, TN Pittsburgh, PA 

Age:Mean (SD):  Maintainers 73 (2.6)  Minor decline 73.6 

Risk factor/exposure 1:diabetes 

1) Follow-up rate: 2509/3075 2) Important baseline differences: 

CommentsOver 8 yeamaintained showed mi
B-299

Study Study Information Participants Risk Factor and 

Outcome Assessment 

Results Comments

Health ABC Setting:

Community Study design:

Prospective cohort Number of participants enrolled:

2509 Duration of follow up:8 years Time from risk factor assessment to final cognitive assessment:3, 5 and 7 years 

 (2.9)  Major decline 74.3  (2.6) Range: 70-79 @ baseline Sex: [n (%)] 

Female: 1334 (53.2%) Male: 1175 (46.8%) Race/ethnicity: [n (%)] White 1612 (64.3% ) Black 897 (35.7%) Baseline cognitive status:3MS>80 Inclusion criteria: a random sample of white and all black Medicare-eligible elders, within designated zip code areas, were contacted. To be eligible, participants had to report no difficulty with activities of daily living, walking a quarter of a mile, or climbing 10 steps without resting. They also had to be free of life-threatening cancer diagnoses and have no plans to move out of the study area for at least 3 years. Exclusion criteria:Difficulty with activities 

Method of assessing risk factor/exposure 1:Self-report Direct measurement Medical record Other – use of medication Risk factor/exposure 2:Hypertension Method of assessing risk factor/exposure 2:Self-report Direct measurement Medical record Other – use of medication Risk factor/exposure 3: Depression Method of assessing risk factor/exposure 3: Other- use of CES-D 20 item Risk factor/exposure 4: Physical activity Method of assessing risk factor/exposure 4: Self-report 

‘major decliners’ older, more black, less educated, lower reading level, lower perceived social support, more likely to live with someone, lower self rated health, fewer drinkers, fewer exercisers, more smokers, more depressed, heavier, more HTN, more 

DM, more MIs, more CVAs, more e4s, higher il-6, lower triglycerides, higher fasting glc 3) Outcome of interest #1In the multivariate model, baseline variables significantly associated with being a Maintainer vs a minor declinerwere: age OR = 0.65, (0.55–0.77 per 5 years), white race OR= 1.72, (1.30–2.28), high school education level or greater (OR= 2.75, 95% CI 1.78–4.26), ninth grade literacy level or greater (OR = 4.85, 95% CI 3.00–7.87), weekly moderate/vigorous exercise OR = 1.31, 95% CI 1.06–1.62), and not smoking (OR= 1.84, 95% CI 1.14–2.97). 4) Outcome of interest #2 Minor vs Major Decliner APOE4 OR 2.31 (1.75-3.05) Education ≥12 OR 0.52 (.37-.72) 9th grade literacy or greater OR 0.7 

(0.5-.98) Not statistically significant: Htn, DM, 

drinking 1 alcoholic beverage/day CESD<16, not a current smoker. 5) Outcomes of interest #3There is a table of all factors 

major cognQuality assFor observ1) Unbias

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2) Selectio

differenYes 

3) Sample 

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5) Validat

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Yes 
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Study Study Information Participants Risk Factor and 

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Results Comments

of daily living, be unable to walk a quarter of a mile, or climb 10 steps without resting. Have lifethreatening cancer diagnoses or have plans to move out of the study area for at least 3 years. 

Risk factor/exposure 5: Smoking Method of assessing risk factor/exposure 5: Self-report Risk factor/exposure 6: works or volunteers Method of assessing risk factor/exposure 6: Self-report Covariates/potential confounders adjusted for in analyses:Age Race Educational level APOE genotype Method(s) of assessing cognitive status:3MSThe participant-specific slopes of 3MS scores were estimated by best linear unbiased predictions using a linear mixed model with random intercepts and slopes. Participants with predicted slopes 

adjusted for all others for maintainer vs minor decliner and for major vs minor decliner. For htn OR 1.03 (0.83-1.28) and 1.29(0.97-1.73) Educ (self report) > high school 

2.75 (1.78-4.26) 0.52 (0.37-0.73) works or volunteers (self rpt) 1.24 (0.99-1.54) 0.96 (0.73-1.25) has enough social support 0.94 (0.73-1.21) 0.69 (0.51-0.91) drinks >1 etoh daily 1.33 (0.91-1.93) 0.67(0.36-127) moderate to vigorous exercise (>once a week) 1.31 (1.06-1.62) 0.97 (0.73-1.28) not current smoker 1.84 (1.14-2.97) 1.15 (0.72-1.84) ces-d < 16 1.23 (0.68-2.22) 0.70 (0.38-1.29) dm (self rpt OR use of meds OR fasting glc > 126 OR 2 hour challenge glc > 200) 0.91 (0.64-1.30) 
B-301

Study Study Information Participants Risk Factor and 

Outcome Assessment 

Results Comments

of 0 or greater (indicating no change or improvement in cognitive scores over time) were classified as maintainers. Those with predicted slopes less than 0 (decline in cognitive score over time) but no more than one SD below the mean of the slopes were classified as minor decliners. Those with predicted slopes more than 1 SD below the mean were classified as major decliners. Informant interview?:No 

1.35 (0.92 – 2.00) 

Yaffe, Kanaya, Lindquist, et al., 2004 Health, Aging and Body Composition (ABC) study 

Geographical location: Memphis, TN and Pittsburgh, PA Setting:Community Study design: Prospective cohort Number of participants enrolled:2632 38.6% of participants with metabolic 

Age:Mean (SD): 73.6 (2.9) Sex: [n (%)] 

Female: 52 Male: 48 Race/ethnicity: [n (%)] 60% white 40% black Baseline cognitive status:Non-demented Inclusion criteria: 

Risk factor/exposure 1:Metabolic syndrome defined by National Cholesterol Education Program 3rd Adult 

treatment panel guidelines (NCEPATPIII). At least 3 of the following: 1. Waist measurement (>88cm women; 102cm men). 2. Hypertriglyceridemia (≥150mg/dL ( ≥1.69 

mmmol/L)) 3. Low HDL (men <40mg/dL (<1.03 

1) Follow-up rate: 2632/2949= 89% 164 died, 69 lost to follow-up, 84 no repeat cognitive testing. 2) Important baseline differences: Participants with Metabolic syndrome were more likely to be women, white, smoke, higher depression scores, higher BMI, + hx of MI, use statins and NSAIDs, and to have high markers of inflammation. 3) Outcome of interest #1Cognitive impairment was defined as a change of 5 or more points at 

CommentsFindings sumetabolic scognitive imcontributor due to metato be inflamQuality assFor observ1) Unbias

cohort? 

2) Selectio

differenYes 

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Study Study Information Participants Risk Factor and 

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Results Comments

syndrome. 61.4% without metabolic syndrome. Duration of follow up:5 years Time from risk factor assessment to final cognitive assessment:Metabolic syndrome assessed at baseline. Final assessment at 5 years 

Random sample of 70 -79 year old, Medicare eligible whites and blacks living in designated zip codes. Had to be wellfunctioning (self report of no difficulty in walking 1⁄4 mile or climbing 10 steps without resting.) Exclusion criteria:

Any difficulty with ADLs, clinical dementia (DSM IV dx), inability to communicate with interviewer, intention of moving out of vicinity in next year, active rx for cancer in prior 3 years, participation in a trial involving a lifestyle intervention. Subjects missing data on metabolic, inflammatory markers, or cognitive testing. 

mmol/L)); women (<50mg/dL (<1.29 mmol/L)). 4. High blood pressure (systolic ≥130 mm Hg; diastolic ≥85 

mm Hg). 5. High fasting glucose (≥110 

mg/dL (≥6.10 mmol/L)) 

or currently using antidiabetic medication (insulin or oral agents) Method of assessing risk factor/exposure 1:Self-report Direct measurement Risk factor/exposure 2: inflammatory markers (Interleukin 6 (IL-6) and C-reactive protein (CRP) Method of assessing risk factor/exposure 2:Direct measurement Covariates/potential confounders adjusted for in analyses:Age Race Sex Educational level Smoking (current) Alcohol use (past year)Baseline cognitive status 

either follow-up visit on 3MS.  26% participants with metabolic sx and 21% no metabolic sx. Multivariate adjusted RR 1.66 (95% CI 1.02-1.41) 4) Outcome of interest #2 Individuals with Metabolic sx and high inflammation had increased likelihood of cognitive impairment (RR multivariate adjusted 1.66 (95% CI 1.19-2.32). Individuals with Metabolic syndrome and low inflammation did not have increased 

risk of cognitive impairment (RR multivariate adjusted 1.08 (95% CI 0.89-1.30) 5) Outcome of interest #3 Stratified multivariate random effects models showed that participants with metabolic sx and high inflammation had greater 4-year decline on 3MS compared to no Met sx (P=.04). Those with metabolic sx and low inflammation did not have greater decline (P=.44) 

differen

4) Adequa

cohort? 

5) Validat

ascerta

6) Validat

ascertaYes 

7) Outcom

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8) Adequa9) Comple10) Analys

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11) Analytic 

Yes 
B-303

Study Study Information Participants Risk Factor and 

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Results Comments

Method(s) of assessing cognitive status:3MSEInformant interview?:No 

Yasar, Corrada, Brookmeyer, et al., 2005 BLSA 

Geographical location: USA, majority from Baltimore, MD – Washington, D.C. area Setting:Community Study design: Prospective cohort Number of participants enrolled:1092 Duration of follow up:Mean yrs 11.0 Range 0.3 – 19.6 Time from risk factor assessment to final cognitive assessment: Ongoing assessment of meds throughout study. Some analyses required 2 to 4 year lag time between exposure and final cognitive outcome. 

Age:Mean (SD): at last f/u 78.1 Range: 61.1 – 104.2 Sex:

Female: 407 (37.3%) Male: 685 (62.7%) Race/ethnicity: [n (%)] White (93%) Other (7%) Baseline cognitive status:Non-demented Inclusion criteria: Participant in the Baltimore Longitudinal Study of Aging (BLSA > 60 years Exclusion criteria:NR 

Risk factor/exposure

1:antihypertensives (ca channel blocker) Method of assessing risk factor/exposure 1:1980 -1990 self report for past two years, 1990 on pill bottle check Covariates/potential confounders adjusted for in analyses:Age, Sex Educational level Smoking, bp, hx heart problems Method(s) of assessing cognitive status:NINCDS-ADRDA DSM Informant interview?:Yes 

1) Follow-up rate: 

NR 2) Important baseline differences: baseline differences for ad versus not given, but not calcium channel blockers vs not. 3) Outcome of interest #1 RR for any CCB compared to non users 0.63 (0.31 – 1.28) for 2 yr lag 0.71 (0.33 – 1.51) for 4 yr lag 4) Outcome of interest #2 dhp-ccb user vs non user 0.30 (0.07 – 1.25) for 2 yr 0.45 (0.11 – 1.87) for 4 yr lag 5) Outcome of interest #3 non dhp –ccb user vs non user 0.82 (0.37 – 1.83) for 2 yr lag 0.82 (0.35 – 1.95) for 4 yr lag 

CommentsNone Quality assFor observ1) Unbias

cohort? 

2) Selectio

differenYes 

3) Sample 

differen

4) Adequa

cohort? 

5) Validat

ascerta

6) Validat

ascertaYes 

7) Outcom

exposuappearanalysesignific

8) Adequa9) Comple

Can’t T

10) Analys

confou

11) Analytic 

Yes 
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Study Study Information Participants Risk Factor and 

Outcome Assessment 

Results Comments

Yesavage, Friedman, Ashford, et al., 2008 (Donepezil) 

Geographical location: Palo Alto, USA Setting:Community Study design: RCT Test intervention Donepezil 5mg daily * 6 weeks, then 10mg daily for 46 weeks; dose reduction to 5mg allowed + 2 weeks cognitive training at weeks 13-14

Comparator intervention(s): Placebo + 2 weeks cognitive training at weeks 13-14 Number of participants enrolled:

168 (83 donepezil; 85 placebo) Duration of follow up:1 year 

Age:Mean (SD): 65.0 (7.4) donepezil; 64.3 (8.0) placebo Sex: [n (%)] 

Female: 88 Male: 80 Race/ethnicity: [n (%)] NR Baseline cognitive status:Normal-71% of participants MCI-29% of participants MMSE 28.6 (1.4) donepezil; 28.6 (1.2) placebo Inclusion criteria: Age 55-90 Good general health with normal B12, BP, thyroid, CBC, chemistries MMSE 24-30 Adequate auditory and visual acuity for neuropsych testing Exclusion criteria:Hachinski score >4 Hamilton depression rating scale -17 score >12 Significant neurological 

Risk factor/exposure 1: Cognitive training: Provided to both groups. 2 hours daily * 10 days; visualization techniques and mnemonic training Method(s) of assessing cognitive status:Primary: Word list recall at 5 and 30 minutes Name-face recall Secondary: Logical Memory I scoreLogical Memory II score Symbol digit Digit Span Quality of life (Medical Outcomes Study Functioning and WellBeing Profile) Functional capacity (Everday problems 

test) 

1) Follow-up rate: Not given; random regression analysis used ITT principle Adherence: 89% of participants attended all 10 cognitive training sessions 2) Important baseline differences: More MCI APOE e4 carriers in placebo group (50% vs. 30%) 3) Outcome of interest #1No significant effects at any timepoint (baseline, week 13 pre-cognitive training, week 14 post-cognitive training, or week 52) Mean change (SD) from baseline at week 52 [positive numbers = improvement] Word list recall: Donepezil 4.5 (4.0) Placebo 4.3 (4.2) Name-face: Donepezil 1.2 (2.7) Placebo 1.6 (2.7) 4) Outcome of interest #2 No significant differences in symbol digit or digit span; logical memory scores not reported No significant differences in quality of life measure or functional capacity 5) Outcome of interest #3 

CommentsNo power cNo participdiagram prNo data on given Quality assFor RCTs: 1) Baselin

except placebo 

2) Valid A

assess

3) Subjec4) Outcom5) Incomp

addres

6) Differen

Can’t T

7) Overall 

Can’t T

8) Conflic

insigniffunded 

9) Random10) Allocat

adequa
B-305

Study Study Information Participants Risk Factor and 

Outcome Assessment 

Results Comments

disease (other than suspected incipient AD) MDD, Alcohol or substance dependence in the past 2 years 

Dropouts for any reason in first 12 weeks: 15/83 (18.0%) donepezil vs. 6/85 (7.1%), p<0.05 Most common Adverse events: Donepezil vs. Placebo Muscle cramps: 19 vs. 1 Insomnia: 18 vs. 8 Abnormal dreams: 12 vs. 6 Nausea: 7 vs. 2 Only muscle cramps and insomnia statistically significant 

Yoshitake, Kiyohara, Kato, et al., 1995 The Hisayama Study 

Geographical location: Hisayama Town, Japan Setting:Community Study design: Prospective cohort Number of participants enrolled: 828 Duration of follow up:Seven years Time from risk factor assessment to final cognitive assessment:7 years 

Age:Mean (SD): For men: 73 (5.6) For women: 74 (6.1) Sex: [n (%)] 

Female: 494 (60%) Male: 334 (40%) Race/ethnicity:Japanese: 100% Baseline cognitive status:Non-demented Inclusion criteria:  Resident of Hisayama Town  Age > 65 years 

Exclusion criteria:Demented 

Risk factor/exposure 1:physical activity Method of assessing risk factor/exposure 1:Self-report “we defined the physically active group as those including daily exercise during the leisure period or moderate to severe physical activity at work.” Covariates/potential confounders adjusted for in analyses: [delete any from the list below that do not apply and add items as needed] Age 

1) Follow-up rate: Initially 828. 214 died during f/u. f/u: 577 of 614 survivors (94.0%); 577 or 828 recruited (70%) 2) Important baseline differences: NR 3) Outcome of interest #1--AD

“Age and a low score on Hasegawa’s dementia scale were significant risk factors for AD, and physical activity was a significant preventive factor.” RR (95% CI) Physically active: 0.20 (0.06-0.68) 

CommentsNone Quality assFor observ1) Unbias

cohort? 

2) Selectio

differenYes 

3) Sample 

differen

4) Adequa

cohort? 

5) Validat

ascertameasuvalidati

6) Validat

ascertaCan’t T

7) Outcom

exposu

8) Adequa9) Comple10) Analys
B-306

Study Study Information Participants Risk Factor and 

Outcome Assessment 

Results Comments

Sex Method(s) of assessing cognitive status: [delete all that do not apply] 2-stage assessment; second stage based on clinical evaluation but assessment not well specified NINCDS-ADRDA DSM Informant interview?:No 

confou

11) Analytic 

Yes 

Yu, Ryan, Schaie, et al., 2009 Seattle Longitudinal Study SLS

Geographical location: Pacific Northwest USA Setting:Other – health maintenance organization (HMO) Study design: Prospective cohort Number of participants enrolled:626 Duration of follow up:14 yrs Time from risk factor assessment to final cognitive assessment:

Age:Mean (SD): 53.20 (12.76) Range: 23 – 82 Sex: [n (%)] Female: 351 (56%) Male: 275 (44%) Race/ethnicity: [n (%)] White 601 (96%) Other 25 (4%)Baseline cognitive status:No exclusion based on cognitive status. 429 ofthe 502 participants over 60 years of age were given the neuropsychological battery. Of those, 3.7% were identified as 

Risk factor/exposure 1: leisure-time physical activity, leisure-time cognitive activity

Method of assessing risk factor/exposure 1: Self-report survey: Life Complexity Inventory, LCI Risk factor/exposure 2:self-directed work, (work control, perceived autonomy and innovation) Method of assessing risk factor/exposure 2: 

1) Follow-up rate:703 participants initially, 77 participants had missing data, so final sample of 626 participants, representing 38% of the total SLS sample in1984 (n= 1,647). Average yearly attrition rate for the study sample was 2.71%. 2) Important baseline differences: Compared to the SLS total sample in 1984, the study sample was younger, but otherwise relatively equivalent 2) Outcome of interest #1 Work control was the only significant factor associated with verbal memory (p<0.05) 3) Outcome of interest #2 Work control was the only significant factor associated with inductive 

CommentsThis study participants impaired at study thougcohort was Quality assFor observ1) Unbias

cohort? 

2) Selectio

differenPartial 

3) Sample 

differen

4) Adequa

cohort? 

5) Validat

ascerta

6) Validat

ascertaYes 
B-307

Study Study Information Participants Risk Factor and 

Outcome Assessment 

Results Comments

14 years having probable or 

definite dementia in 1998, representing 2.2% of the sample Inclusion criteria: SLS participants who met two criteria: (a) had completed three waves of data collection (in 1984, 1991, and 1998) (b) had no missing data for the independent variables and covariatesExclusion criteria:NR 

Self-report Work Environment Inventory Risk Factor/Exposure: 3.Hypertension

Method of assessing risk factor/exposure 3: The diagnosis was retrieved from participants’ HMO records Covariates/potential confounders adjusted for in analyses:Age Sex Educational level Income Method(s) of assessing cognitive status:Other – [specify] Verbal memory (a) word fluency  (b) immediate recall (c)delayed recall Inductive reasoning (a) Primary Mental Abilities, PMA, reasoning measure (b) Adult Development and Enrichment Project letter series, 

reasoning.Every increased unit of work control at the third wave was associated with a .14 t-score unit increase in inductive reasoning (p<0.05)

7) Outcom

exposu

8) Adequa9) Comple

Can’t T

10) Analys

confou

11) Analytic 

Yes 
B-308

Study Study Information Participants Risk Factor and 

Outcome Assessment 

Results Comments

ADEPT-letter (c) word series and (d) Educational Testing Service number series Informant interview?:No 

Zandi, Sparks, Khachaturian, et al., 2005 Cache County Study 

Geographical location: Cache County, UT Setting:Community Study design: Prospective cohort Number of participants enrolled:4895 Duration of follow up:3 yrs Time from risk factor assessment to final cognitive assessment:3 yrs 

Age:Mean (SD): 73.0 to 75.7 Sex:

Female: 2797 (57%) Male: 2098 (43%) Race/ethnicity:NR Baseline cognitive status:Non-demented Inclusion criteria: ≥ 65 yo; permanent resident of Cache County, UT Exclusion criteria:Less than 65 years old Resident outside of Cache County, UT Dementia at baseline 

Risk factor/exposure

1:Statin Method of assessing risk factor/exposure 1:Direct measurement – medication bottles Medical record - supplemented Risk factor/exposure 2:education; h/o stroke; HTN or DM; smoking Method of assessing risk factor/exposure 2:Self-report Covariates/potential confounders adjusted for in analyses:Age Sex Educational level Number of ApoE E4 alleles, 

1) Follow-up rate: 3308/4540 (82.8%) 508 died 724 lost to f/u HR (95% CI) for AD – unadjusted Statin used 4AD/630 person years, HR 0.62 (0.19 to 1.48) No statin used 98/9522 person years, HR 1.0 (ref) Statin <= 3 years HR 0.49 (0.08 to 1.54) Statin > 3 years 0.43 (0.03 to 1.96) HR (95% CI) for AD – adjusted for age, sex, education, number o Apoe e4 alleles, age by e4 interaction, h/o HTN, h/o DM Statin used 4AD/630 person years, HR 1.19 (0.35 to 2.96) No statin used 98/9522 person years, HR 1.0 (ref) Statin <= 3 years HR 1.41 (0.23 to 4.70) Statin > 3 years 0.62 (0.03 to 2.92) 

CommentsNone Quality assFor observ1) Unbias

cohort? 

2) Selectio

differenYes 

3) Sample 

differen

4) Adequa

cohort? 

5) Validat

ascerta

6) Validat

ascertaYes 

7) Outcom

exposu

8) Adequa9) Comple10) Analys

confou

11) Analytic 

Yes
B-309

Study Study Information Participants Risk Factor and 

Outcome Assessment 

Results Comments

age X e4 interaction h/o diabetes h/o hypertension Method(s) of assessing cognitive status:Other – Screen with modified 3MS or IQCODE. High risk by screening or clinical characteristics underwent detailed history, examination and neuropsych testing. NINCDS-ADRDA Informant interview?:Yes Text in the article reports that informant interviews were included when participants could not do 3MS.

Zandi, Anthony, Hayden, et al., 2002 Cache 

Geographical location:Cache County Utah. Setting:Community Study design:

Prospective cohort Number of participants enrolled: 3511, 104 AD 

Age:Range: 65 years and up Sex: [n (%)] 

Female: NR Male: NR Race/ethnicity: [n (%)] NR Baseline cognitive status:

Risk factor/exposure

1:nsaids Method of assessing risk factor/exposure 1:Self-report And examination of pill bottles Covariates/potential confounders 

1) Follow-up rate: 83% of those without baseline dementia and still alive. 2) Important baseline differences: non asa nsaid users more likely to be women. 3) Outcome of interest #1 Use of nsaids for > 2 years associated with decreased risk of ad (but not current use unless use extended for 2 years prior to wave 1). 

CommentsQuestion 1 waves 1 anQuality assFor observ1) Unbias

cohort? 

2) Selectio

differenYes 

3) Sample 

differen
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Study Study Information Participants Risk Factor and 

Outcome Assessment 

Results Comments

Duration of follow up: 3 years Time from risk factor assessment to final cognitive assessment:3 years 

Normal Non-demented Inclusion criteria: 

Participating in the 

Cache County Study Exclusion criteria:

Less than 65 years old 

adjusted for in analyses:Age, squared deviation of age,Sex,apoe4, interaction age/apoE4 Educational level Baseline cognitive status Method(s) of assessing cognitive status:

DSM Informant interview?:sometimes 

Hr  0.45 (0.17-0.97) 4) Outcome of interest #2 Any lifetime use of nsaids almost associated with decreased risk of ad with hr 0.67 (o,40-1.06) 

4) Adequa

cohort? 

5) Validat

ascerta

6) Validat

ascertaYes 

7) Outcom

exposu

8) Adequa9) Comple10) Analys

confou

11) Analytic 

Yes 

Zandi, Anthony, Khachaturian, et al., 2004 Cache County Study 

Geographical location: Logan, UT, USA Setting:Community Study design: Prospective cohort Number of participants enrolled:3227 Duration of follow up:Est 3 yr Time from risk factor assessment to final cognitive assessment:Est 3 yr 

Age:Mean (SD): mean range across exposure categories: 74.2-76.6 Sex: [n (%)] 

Female: mean % range across exposure categories: 53.6-64.0 Race/ethnicity: [n (%)] NR Baseline cognitive status:Non-demented Inclusion criteria: Resident of Cache County, UT; age > 65 

yrs Exclusion criteria:

Risk factor/exposure

1:Vitamins E and C, multivitamins, Bcomplex vitamins Method of assessing risk factor/exposure 1:Self-report Covariates/potential confounders adjusted for in analyses:Age Sex Educational level APOE General health status Method(s) of assessing cognitive 

1) Follow-up rate: 3227/ 4110 (denominator excludes those lost to f/u due to death) 2) Important baseline differences: User of Vitamin C or E were more likely to be female, younger, better educated and report better general health 3) Outcome of interest #1Reduced risk of incident AD associated with combined Vitamin E and C use (HR=0.36; 0.09-0.99) No significant association between incident AD and Vitamin E alone, Vitamin C alone, multivitamin, or B-complex vitamins or any combination of these except for Vitamin E and C combined 

CommentsQuestion 1 Quality assFor observ1) Unbias

cohort? 

2) Selectio

differenYes 

3) Sample 

differen

4) Adequa

cohort? 

5) Validat

ascerta

6) Validat

ascertaYes 

7) Outcom

exposu

8) Adequa9) Comple
B-311

Study Study Information Participants Risk Factor and 

Outcome Assessment 

Results Comments

None status:

NINCDS-ADRDA DSM-3 revised Informant interview?:Yes 

10) Analys

confou

11) Analytic 

Yes 

Zunzunegui, Alvarado, Del Ser, et al., 2003 

Geographical location: Leganes, a suburb of Madrid, Spain Setting:Community Study design: Prospective cohort Number of participants enrolled:557 analytical sample Duration of follow up:4 yrs Time from risk factor assessment to final cognitive assessment:4 yrs 

Age:Mean (SD): NR Sex: [n (%)] 

Female: 264 (47.3) Male: 293 (52.7) Race/ethnicity: [n (%)]  NRBaseline cognitive status:Non-demented (excluded individuals thought to be severely impaired based on cognitive screening score) Inclusion criteria: Stratified random sample of commondwelling residents of Leganes, Spain > 65 years Exclusion criteria:Severely cognitively impaired defined as > 5 

errors on the SPMSQ, visually impaired 

Risk factor/exposure 1:Social networks (number of monthly visual and phone contacts with friends and relatives (other than children)), social integration (membership in community associations, monthly attendance of religious services, visits to the community center) and social engagement (how frequently help, are useful, and play important roll in life of children, family and friends) Method of assessing risk factor/exposure 1:Self-report Covariates/potential confounders adjusted for in analyses:Age Educational level 

1) Follow-up rate: 557/964 completed f/u. 152 of the 964 were deceased, so f/u rate 557/812 (69%). 2) Important baseline differences: Men were more likely to be married whereas women were more likely to live alone or with family. Women reported less extensive networks than men. Attendance of religious services occurred more frequently among women than men. Women tended to be less engaged with friends than men. There were more women reporting cardiovascular morbidity (51.0%), high depressive symptomatology (40.5%), and functional limitations (22.7%), than men (36.0%, p < .001; 12.0%, p < .001; 8.0%, p < .001, respectively). There were no significant gender differences with respect to frequency of cognitive decline: 10.5% of women had severe and 24.6% mild decline, whereas 12.9% of men showed severe and 18.5% mild decline. 3) Outcome of interest #1

Increased risk of severe decline was only associated with no group membership in men, less social engagement with children in men, 

CommentsQ2 – yes cQuality assFor observ1) Unbias

cohort? 

2) Selectio

differenYes 

3) Sample 

differen

4) Adequa

cohort? 

5) Validat

ascerta

6) Validat

ascertaYes 

7) Outcom

exposu

8) Adequa9) Comple

Partial 

10) Analys

confou

11) Analytic 

Yes (buhow to interpre
B-312

Study Study Information Participants Risk Factor and 

Outcome Assessment 

Results Comments

Sex Baseline cognitive status Depression Blood pressure Functional limitations Method(s) of assessing cognitive status: Other – decline on composite measure of cognitive tests. Severe decline defined as greater than 1 SD below the mean change. Mild decline defined as a change within 1 SD of the mean change. Informant interview?:No 

and less social engagement with friends in women. 4) Outcome of interest #2 The number of relatives seen at least monthly (p = 0.028) and the social integration index (p = 0.04) are significant predictors of cognitive decline for both sexes. 

Among women, engagement with friends predicts lower probability of cognitive decline. (interaction p= 0.19). Neither engagement with relatives or children was related to decline in this final model. Depression is associated with decline in men but not in women. (interaction p = 0.051). 
B-313 

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Order) 

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Adapt Research Group, Lyketsos CG, Breitner JC, et al. Naproxen and celecoxib do not 

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Aggarwal NT, Bienias JL, Bennett DA, et al. The relation of cigarette smoking to incident 

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5. 

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Arvanitakis Z, Grodstein F, Bienias JL, et al. Relation of NSAIDs to incident AD, change 

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Bernick C, Katz R, Smith N, et al. Statins and cognitive function in the elderly: the 

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Dai Q, Borenstein AR, Wu Y, et al. Fruit and vegetable juices and Alzheimer's disease: 

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17. 

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Appendix C. Quality Assessment – Systematic Reviews∗

For reviews, first determine whether it is a systematic review (SR). To be a systematic 

review, it must include a methods section that describes (1) a search strategy and (2) 

an a priori approach to synthesizing the data. For reviews determined to meet the SR 

criteria, assess methodological quality. 

General instructions: 

Step 1: Grade each of the criteria listed below as “Yes,” “No,” “Partially,” or 

“Can’t tell.” Factors to consider when making an assessment are listed under 

each criterion. Where appropriate (particularly when assigning a “No,” 

“Partially,” or “Can’t tell” score), please provide a brief rationale for your decision 

(in parentheses). 

1. Is a focused clinical question clearly stated? 

a. At a minimum, question should clearly identify population and 

outcomes 

b. Does not have to be in PICO format (Population, Intervention, 

Comparisons, Outcomes) 

 

2. Are the search methods used to identify relevant studies clearly 

described? 

a. Search methods described in enough detail to permit replication 

3. Was the search for evidence reasonably comprehensive? 

a. Search included MEDLINE and other appropriate databases 

 

4. Are the inclusion/exclusion criteria used to screen primary studies 

clearly described? 

a. Inclusion/exclusion criteria described in enough detail to permit 

replication 

5. Were the inclusion/exclusion criteria appropriate (aimed at avoiding 

bias in the included studies)? 

a. Criteria likely to capture all relevant studies (consider especially criteria 

related to study population, risk factor/intervention, outcomes, and 

study design) 

6. Were the primary studies assessed for quality using clearly stated 

criteria? 

a. Quality assessment was done, and criteria used to assess study 

quality were specified in enough detail to permit replication 

 

∗ Adapted from Marinopoulos et al., 20071

 and Moher et al., 1999.2
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7. Was the quality assessment done appropriately? 

a. Quality assessment was performed using a validated instrument (with 

citation), or the authors demonstrated the validity of their methods. 

8. Were the methods used to assess primary studies reproducible? 

a. Did two or more raters make inclusion/exclusion decisions, abstract 

data, and assess study quality – either independently or with one overreading? 

b. Was an appropriate method used to resolve disagreements? 

9. Did the authors discuss whether any variation observed in the results of 

the primary studies might be due to differences in study design or 

population?

a. Text or tables provide comparative information on most of following: 

study design, populations, interventions, and outcome measures 

b. Authors discuss possible sources of heterogeneity 

10. Were the results of the relevant studies combined appropriately? 

a. Some assessment of qualitative or quantitative assessment 

heterogeneity of study results 

b. Accepted qualitative or quantitative method of pooling used (i.e., more 

than simple addition; e.g., random-effects vs. fixed-effect model for 

quantitative data) 

11. Was publication bias assessed? 

a. Publication bias tested for using funnel plots, test statistics, or search 

of trials registry for unpublished studies. 

12. Are the stated conclusions supported by the data presented? 

Step 2: Rate the overall quality of the SR as “Good,” “Fair,” or “Poor” using the 

guidance below. 

Good = After considering items 1-11, item 12 is rated “Yes” with no important 

limitations. This means that few of the items 1-11 are rated “Partially” or “No,” and none 

of the limitations are thought to decrease the validity of the conclusions. 

Fair = After considering items 1-11, item 12 is rated “Yes,” but with at least some 

important limitations. This means that enough of the items 1-11 are rated “Partially” or 

“No” to introduce some uncertainty about the validity of the conclusions. 

Poor = After considering items 1-11, item 12 is rated “No.” This means that several of 

items 1-11 are rated “Partially” or “No,” introducing serious uncertainty about the validity 

of the conclusions. 
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References 

1. Marinopoulos S, Dorman T, Ratanawongsa N, et al. Effectiveness of Continuing 

Medical Education. Evidence Report/Technology Assessment No. 149 (Prepared 

by the Johns Hopkins University Evidence-based Practice Center under Contract 

No. 290-02-0018.) AHRQ Publication No. 07-E006. Rockville, MD:Agency for 

Healthcare Research and Quality. January 2007. Available at 

http://www.ahrq.gov/clinic/tp/cmetp.htm. Accessed on September 29, 2009. 

2. Moher D, Cook DJ, Eastwood S, et al. Improving the quality of reports of metaanalyses of randomised controlled trials: the QUOROM statement. Quality of 

Reporting of Meta-analyses. Lancet 1999;354(9193):1896-900. 
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Appendix D. Quality Assessment – RCTs 

Quality Assessment – RCTs∗

General instructions: Grade each criterion as “Yes,” “No,” “Partially,” or “Can’t tell.” 

Factors to consider when making an assessment are listed under each criterion. Where 

appropriate (particularly when assigning a “No,” “Partially,” or “Can’t tell” score), please 

provide a brief rationale for your decision (in parentheses) in the evidence table. 

1. Were the groups similar at baseline in terms of baseline characteristics 

and prognostic factors? (Consider baseline prognostic characteristics of 

intervention/control groups including age, sex, race, educational level, general 

medical conditions, and performance on a cognitive measure.)

a. No important baseline differences 

b. Important baseline differences 

c. Can’t tell if important baseline differences (not reported or key baseline 

characteristics not reported) 

2. Were AD/cognitive outcomes assessed using a valid methodology and 

criteria? (See details below.)

a. Valid method used (assessment method and definition) 

b. Valid method used only in some of the subjects 

c. Valid method not used 

3. Were subjects and providers blind to the intervention/exposure status 

of participants? 

a. Subjects blind to exposure/intervention 

b. Providers blind to exposure/intervention 

4. Were outcome assessors blind to exposure/intervention status? 

5. Were incomplete outcome data adequately addressed? (See more 

detailed guidance below.)

6. Was the differential loss to follow-up between the compared groups low 

(defined as < 10%)?* 

a. *Note: If event rates (e.g., conversion to AD) are low, then even 

smaller differences in f/u by group could lead to large biases in 

estimate of effect. 

7. Was the overall loss to follow-up low (defined as < 30%)? 

 

∗ Taken from AHRQ et al., 20071

 and Higgins et al., 2008.2
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a. Where different numbers of patients are followed up for different 

outcomes, use the number followed up for the primary outcome for this 

calculation. 

8. Conflict of interest reported and insignificant? 

a. Is the source of funding identified? 

b. Is the funding from a source that does not have a vested interest in the 

study results? 

9. Were the methods used for randomization adequate? 

a. Yes, true random number generator (e.g., computer randomization) 

b. No, not true random number generator (e.g., every other, odd or even 

DOB, patient record number) 

10. Was allocation concealment adequate? (Allocation sequence should be 

described in sufficient detail to determine whether intervention allocations 

could have been foreseen in advance of, or during, enrollment.) 

a. Allocation concealment was adequate (e.g., call central number for 

intervention allocation after eligibility confirmed, sequentially 

numbered sealed opaque envelopes, sequentially numbered drug 

containers of identical appearance) 

b. Allocation concealment inadequate 

******************************************************************************************** 

Detailed guidance for Item 2 – assessment of AD/cognitive outcomes 

Principles for an acceptable criterion standard for diagnosis of AD: 

1. Uses established diagnostic criteria (e.g., DSM-IV, NINCDS-ADRDA, ICD or 

similar). 

2. Uses an acceptable method for obtaining the necessary data to apply the 

diagnostic criteria, defined as an in-person assessment using an assessment 

battery that addresses the key domains in the diagnostic criteria, namely, at least 

memory plus one or more of the following: orientation, agnosia, aphasia, apraxia, 

executive function, or effect on functional status. If the diagnosis is from medical 

records only, need evidence that a formal in-person evaluation was done to 

determine the diagnosis of AD. 

3. Pathological specimens alone are not satisfactory since AD is a clinical 

diagnosis. If AD is diagnosed using an acceptable criterion standard, then 

pathological specimens could provide useful supplementary information. 

Principles for an acceptable criterion standard for diagnosis of cognitive decline: 

1. An agreed upon set of diagnostic criteria for a categorical diagnosis (e.g., MCI, 

CIND, or similar as described in text). The diagnostic criteria will vary across 

studies, but each study should provide details of the criteria used for MCI, CIND, 

or similar diagnostic terms for mild cognitive symptoms. The definition should 
D-3

include mild cognitive impairment reported by the individual or informant that did 

not meet criteria for dementia, or performance on neuropsychological measures 

that was both below expectation and considered to be in the impaired range 

based on normative standards. 

2. An acceptable method for obtaining the necessary data to apply the diagnostic 

criteria, defined as an in-person assessment using an assessment battery that 

addresses the key domains in the diagnostic criteria, namely, at least memory 

plus one or more of the following: orientation, agnosia, aphasia, apraxia, 

executive function, and evidence that cognitive impairment does not significantly 

interfere with functional status. If the diagnosis is from medical records only, 

need evidence that a formal in-person evaluation was done to determine the 

diagnosis of mild impairment. 

3. If cognition is assessed at two or more time points, then change on a validated 

instrument. 

**************************************************************************************************** 

Detailed guidance for Item 5 (“Were incomplete outcome data adequately 

addressed?”) – taken from Cochrane Handbook for Systematic Reviews of 

Interventions2

, Table 8.5.c 

Criteria for a judgment of 

“Yes” (i.e., low risk of bias) 

Any one of the following: 

- No missing outcome data; 

- Reasons for missing outcome data unlikely to be 

related to true outcome (for survival data, censoring 

unlikely to be introducing bias); 

- Missing outcome data balanced in numbers across 

intervention groups, with similar reasons for missing 

data across groups; 

- For dichotomous outcome data, the proportion of 

missing outcomes compared with observed event 

risk not enough to have a clinically relevant impact 

on the intervention effect estimate; *(see example 

below) 

- For continuous outcome data, plausible effect size 

(difference in means or standardized difference in 

means) among missing outcomes not enough to 

have a clinically relevant impact on observed effect 

size; 

- Missing data have been imputed using appropriate 

methods. 

Criteria for the judgment of 

“No” (i.e., high risk of bias) 

Any one of the following: 

- Reason for missing outcome data likely to be 

related to true outcome, with either imbalance in 
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numbers or reasons for missing data across 

intervention groups; 

- For dichotomous outcome data, the proportion of 

missing outcomes compared with observed event 

risk enough to induce clinically relevant bias in 

intervention effect estimate; ; *(see example below) 

- For continuous outcome data, plausible effect size 

(difference in means or standardized difference in 

means) among missing outcomes enough to induce 

clinically relevant bias in observed effect size; 

- “As-treated” analysis done with substantial 

departure of the intervention received from that 

assigned at randomization; 

- Potentially inappropriate application of simple 

imputation. 

Criteria for the judgment of 

“Can’t tell” (uncertain risk 

of bias) 

Any one of the following: 

- Insufficient reporting of attrition/exclusions to permit 

judgment of “Yes” or “No” (e.g., number randomized 

not stated, no reasons for missing data provided); 

- Study did not address/report this outcome. 

*Example for risk of bias due to incomplete follow-up 

Historically, methodologists have sometimes suggested somewhat arbitrary thresholds 

for acceptable loss to follow-up (e.g. less than 20%). The significance of particular rates 

of loss to follow-up, however, varies widely and is dependent on the relation between 

loss to follow-up and number of events. For instance, loss to follow-up of 5% in both 

intervention and control groups provides little threat to bias if event rates were 20% and 

40% in intervention and control groups respectively. If event rates were 2% and 4%, 

however, concern with 5% loss to follow-up is much greater. 

Example where lost to f/u is a relatively low proportion of those with events and little risk 

of bias. RR=0.5 (.21/.42) and if assumed all lost to f/u had events, RR=0.55 (0.25/0.45) 

 Enrolled/FU 

outcomes 

Lost to F/U Event rate Event rate if lost to f/u had 

events 

Intervention 100/95 5 20/95=.21 25/100=.25 

Control 100/95 5 40/95=.42 45/100=.45 

Example where lost to f/u is a relatively higher proportion of those with events and 

significant risk of bias. It only takes a few lost to follow to have had events to change the 

difference in event rates substantially. RR=0.5 (.02/.04) and if assumed all lost to f/u 
D-5

had events, RR=0.78 (0.07/0.09) and may be distorted further if event rates in the lost to 

f/u differed between intervention and control 

 Enrolled/FU 

outcomes 

Lost to F/U Event rate Event rate if lost to f/u had 

events 

Intervention 100/95 5 2/95=.02 7/100=.07 

Control 100/95 5 4/95=.04 9/100=.09 

References 

1. Agency for Healthcare Research and Quality. Methods Reference Guide for 

Effectiveness and Comparative Effectiveness Reviews, Version 1.0 [Draft posted 

Oct. 2007]. Rockville, MD:Agency for Healthcare Research and Quality. Available 

at: http://effectivehealthcare.ahrq.gov/repFiles/2007_10DraftMethodsGuide.pdf. 

Accessed September 3, 2009. 

2. Higgins J, Altman D. Assessing the risk of bias. In: Higgins J, Green S, eds.

Cochrane Handbook for Systematic Reviews of Interventions (version 5.0.1) 

updated September 2008.: The Cochrane Collaboration. 
E-1

Appendix E. Quality Assessment – Observational Studies 

General instructions: Grade each criterion as “Yes,” “No,” “Partially,” or “Can’t tell.” 

Factors to consider when making an assessment are listed under each criterion. Where 

appropriate (particularly when assigning a “No,” “Partially,” or “Can’t tell” score), please 

provide a brief rationale for your decision (in parentheses) in the evidence table. 

Criteria marked italics are considered the most essential quality indicators for our 

purposes. 

1) Unbiased selection of the cohort? 

Factors that help reduce selection bias: 

• Prospective study design and recruitment of subjects 

• Inclusion/exclusion criteria 

o Clearly described (especially re: age and cognitive status) 

o Assessed using valid and reliable measures 

• Recruitment strategy 

o Clearly described 

o Relatively free from bias (selection bias might be introduced, e.g., by 

recruitment via advertisement) 

2) Selection minimizes baseline differences in prognostic factors? 

Factors to consider: 

• Was selection of the comparison group appropriate? 

Note: This may not be an issue in the cohort studies we review. In general, the 

exposed and unexposed groups should be from the same source. However, it is 

possible that for some medical condition exposures the exposed group will be 

patients from a specialty medical clinic and the unexposed comparison group will 

be from another source. Consider whether these two sources are likely to differ 

on factors related to the outcome (besides the exposure factor). 

• In addition to selecting the cohort in an unbiased way, did study investigators do 

other things to ensure that exposed/unexposed groups were comparable, e.g., by 

using stratification, matching, or propensity scores?

3) Sample size calculated/5% difference? 

Factors to consider: 

• Did the authors report conducting a power analysis or describe some other basis 

for determining the adequacy of study group sizes for the primary outcome(s) of 

interest to us? 

• Was the sample size sufficiently large to detect a clinically significant difference 

of 5% in event rates or an OR/RR increase of ≥ 1.5 or decrease of ≥ 0.67 

between groups in at least one primary outcome measure of interest to us? 

4) Adequate description of the cohort? 

Consider whether the cohort is well-characterized in terms of baseline: 

• Age 

• Sex 
E-2

• Race 

• Educational level 

• Cognitive status 

• For genetic association studies, were the diseased and non-diseased 

populations drawn from groups with the same ethnic/racial mix? 

5) Validated method for ascertaining exposure? 

Factors to consider: 

• Was the method used to ascertain exposure clearly described? (Details should 

be sufficient to permit replication in new studies.) 

• Was a valid and reliable measure used to ascertain exposure? (Subjective 

measures based on self-report tend to have lower reliability and validity than 

objective measures such as clinical reports and lab findings.) 

• For gene association studies, is the “call rate” of genotyping (the proportion of 

samples in which the genotyping provides an unambiguous reading) reported? 

Were quality checks implemented or rules established to determine when 

genotyping results would be considered valid? 

To clarify your score, please make a note of the method/measure used to ascertain 

exposure. 

6) Validated method for ascertaining clinical outcomes? 

Factors to consider: 

• Were primary outcomes (AD and/or cognitive decline) assessed using valid and 

reliable measures? (See details below.)

• Were these measures implemented consistently across all study participants? 

7) Outcome assessment blind to exposure? 

• Were the study investigators who assessed outcomes blind to the intervention or 

exposure status of participants? 

8) Adequate follow-up period? 

Factors to consider: 

• Minimum adequate follow-up period is 2 years for AD and 1 year for cognitive 

decline 

• Follow-up period should be the same for all groups 

o In cohort studies, length of follow-up should be the same across all 

groups. 

o In nested case-control studies, period between the intervention/exposure 

and outcome should be the same for cases and controls. 

o OK if differences in follow-up time were adjusted for using statistical 

techniques, e.g., survival analysis. 

9) Completeness of follow-up? 

Factors to consider: 
E-3

• Did attrition from any group exceed 30%? (Attrition is measured in relation to the 

time between baseline/allocation and outcome measurement. Where different 

numbers of patients are followed up for different outcomes, use the number 

followed up for the primary outcome for this calculation.) 

• Did attrition differ between groups by more than 10% percent? 

10) Analysis controls for confounding? 

Factors to consider: 

• Did the analysis control for any baseline differences between groups? 

• Does the study identify and control for important confounding variables and effect 

modifiers? (Confounding variables are risk factors that are correlated with the 

intervention/exposure and outcome and may therefore bias the estimation of the 

effect of intervention/exposure on outcome if unmeasured. Effect modifiers are 

not correlated with the intervention/exposure, but change the effect of the 

intervention/exposure on the outcome. Age, race/ethnicity, education, and 

measures of SES are examples of effect modifiers and confounding variables for 

the exposures and outcomes of interest in this study.) 

11) Analytic methods appropriate? 

Factors to consider: 

• Was the kind of analysis done appropriate for the kind of outcome data? 

o Dichotomous – logistic regression, survival 

o Categorical – mixed model for categorical outcomes 

o Continuous – ANCOVA, mixed model 

• Was the analysis done on an intention-to-treat basis? (That is, was the impact of 

loss to follow-up [or differential loss to followup] assessed, e.g., through 

sensitivity analysis or another intent-to-treat adjustment method? 

• Was the number of variables used in the analysis appropriate for the sample 

size? (The statistical techniques used must be appropriate to the data and take 

into account issues such as controlling for small sample size, clustering, rare 

outcomes, multiple comparison, and number of covariates for a given sample 

size. The multiple comparisons issue may be a problem particularly when 

performance results on numerous cognitive measures are being compared. 

When assessing change on cognitive measure over time, consider whether 

change score should be adjusted for baseline score, and consider distribution of 

baseline scores and change scores.) 

• For gene association studies:

o Did the investigators conduct statistical tests to check whether the 

observed genotype frequencies are consistent with the Hardy-Weinberg 

Equilibrium? 

o Did the investigators adjust for multiple comparisons? 
E-4

******************************************************************************************** 

Detailed guidance for Item 6 – assessment of AD/cognitive outcomes 

Principles for an acceptable criterion standard for diagnosis of AD: 

1. Uses established diagnostic criteria (e.g., DSM-IV, NINCDS-ADRDA, ICD or 

similar). 

2. Uses an acceptable method for obtaining the necessary data to apply the 

diagnostic criteria, defined as an in-person assessment using an assessment 

battery that addresses the key domains in the diagnostic criteria, namely, at least 

memory plus one or more of the following: orientation, agnosia, aphasia, apraxia, 

executive function, or effect on functional status. If the diagnosis is from medical 

records only, need evidence that a formal in-person evaluation was done to 

determine the diagnosis of AD. 

3. Pathological specimens alone are not satisfactory since AD is a clinical 

diagnosis. If AD is diagnosed using an acceptable criterion standard, then 

pathological specimens could provide useful supplementary information. 

Principles for an acceptable criterion standard for diagnosis of cognitive decline: 

1. An agreed upon set of diagnostic criteria for a categorical diagnosis (e.g., MCI, 

CIND, or similar as described in text). The diagnostic criteria will vary across 

studies, but each study should provide details of the criteria used for MCI, CIND, 

or similar diagnostic terms for mild cognitive symptoms. The definition should 

include mild cognitive impairment reported by the individual or informant that did 

not meet criteria for dementia, or performance on neuropsychological measures 

that was both below expectation and considered to be in the impaired range 

based on normative standards. 

2. An acceptable method for obtaining the necessary data to apply the diagnostic 

criteria, defined as an in-person assessment using an assessment battery that 

addresses the key domains in the diagnostic criteria, namely, at least memory 

plus one or more of the following: orientation, agnosia, aphasia, apraxia, 

executive function, and evidence that cognitive impairment does not significantly 

interfere with functional status. If the diagnosis is from medical records only, 

need evidence that a formal in-person evaluation was done to determine the 

diagnosis of mild impairment. 

3. If cognition is assessed at two or more time points, then change on a validated 

instrument. 
F-1

Appendix F. Peer Reviewers 

The Duke Evidence-based Practice Center is grateful to the following peer reviewers who read 

and commented on a draft version of this report: 

Jesse Berlin, ScD; Pharmaceutical Research & Development; Johnson & Johnson 

Pharmaceuticals; Titusville, NJ 

Soo Borson, MD; Department of Psychiatry; University of Washington; Seattle, WA 

Ornit Chiba-Falek, PhD; Institute for Genome Sciences and Policy; Duke University; 

Durham, NC 

Mary Ganguli, MD, MPH; Department of Psychiatry; University of Pittsburgh; Pittsburgh, 

PA 

Tiffany Hughes, PhD, MPH; Department of Psychiatry; University of Pittsburgh; Pittsburgh, 

PA 

Dan Kaufer, MD; Department of Neurology; University of North Carolina; Chapel Hill, NC 

Eric B. Larson, MD, MPH, MACP; Group Health Research Institute; Seattle WA 
G-1

Appendix G. Excluded Studies 

All excluded studies listed below (in alphabetical order) were reviewed in their full-text version. 

Following each reference, in italics, is the reason for exclusion. “Excluded,” in this context, 

means “not included for data abstraction.” Reasons for exclusion signify only the usefulness of 

the articles for this study and are not intended as criticisms of the articles. 

Aartsen MJ, Smits CHM, van Tilburg T, et al. Activity in 

older adults: cause or consequence of cognitive 

functioning? A longitudinal study on everyday activities 

and cognitive performance in older adults. Journals of 

Gerontology Series B-Psychological Sciences & Social 

Sciences 2002;57(2):P153-62. 

Full Text: Exclude - not longitudinal 

Aevarsson O, Skoog I. A longitudinal population study of 

the mini-mental state examination in the very old: relation 

to dementia and education. Dement Geriatr Cogn Disord 

2000;11(3):166-75. 

Full Text: Exclude - not applicable population 

Agostini JV, Tinetti ME, Han L, et al. Effects of statin use 

on muscle strength, cognition, and depressive symptoms in 

older adults. J Am Geriatr Soc 2007;55(3):420-5. 

Full Text: Exclude - dementia @ baseline 

Akbaraly NT, Faure H, Gourlet V, et al. Plasma carotenoid 

levels and cognitive performance in an elderly population: 

results of the EVA Study. J Gerontol A Biol Sci Med Sci 

2007;62(3):308-16. 

Full Text: Exclude - not longitudinal 

Akbaraly TN, Singh-Manoux A, Marmot MG, et al. 

Education attenuates the association between dietary 

patterns and cognition. Dement Geriatr Cogn Disord 

2009;27(2):147-54. 

Full Text: Exclude - not longitudinal 

Akiyama H, Meyer JS, Mortel KF, et al. Normal human 

aging: factors contributing to cerebral atrophy. J Neurol Sci 

1997;152(1):39-49. 

Full Text: Exclude - outcome non-specific AD 

Albert MS, Jones K, Savage CR, et al. Predictors of 

cognitive change in older persons: MacArthur studies of 

successful aging. Psychol Aging 1995;10(4):578-89. 

Full Text: Exclude - unable to extract results 

Aleman A, Muller M, de Haan EH, et al. Vascular risk 

factors and cognitive function in a sample of independently 

living men. Neurobiol Aging 2005;26(4):485-90. 

Full Text: Exclude - not longitudinal 

Alexander CN, Langer EJ, Newman RI, et al. 

Transcendental meditation, mindfulness, and longevity: an 

experimental study with the elderly. J Pers Soc Psychol 

1989;57(6):950-64. 

Full Text: Exclude - dementia @ baseline 

Almeida OP, Norman P, Hankey G, et al. Successful 

mental health aging: results from a longitudinal study of 

older Australian men. Am J Geriatr Psychiatry 

2006;14(1):27-35. 

Full Text: Exclude - not longitudinal 

Ampuero I, Ros R, Royuela A, et al. Risk factors for 

dementia of Alzheimer type and aging-associated cognitive 

decline in a Spanish population based sample, and in brains 

with pathology confirmed Alzheimer's disease. J 

Alzheimers Dis 2008;14(2):179-91. 

Full Text: Exclude - dementia @ baseline 

Ancelin ML, Artero S, Portet F, et al. Non-degenerative 

mild cognitive impairment in elderly people and use of 

anticholinergic drugs: longitudinal cohort study. BMJ 

2006;332(7539):455-9. 

Full Text: Exclude - risk factor out of scope 

Andel R, Crowe M, Pedersen NL, et al. Complexity of 

work and risk of Alzheimer's disease: a population-based 

study of Swedish twins. Journals of Gerontology Series BPsychological Sciences & Social Sciences 

2005;60(5):P251-8. 

Full Text: Exclude - not longitudinal 

Andersen G, Vestergaard K, Riis JO, et al. Dementia of 

depression or depression of dementia in stroke? Acta 

Psychiatr Scand 1996;94(4):272-8. 

Full Text: Exclude - risk factor out of scope 

Andersen K, Launer LJ, Ott A, et al. Do nonsteroidal antiinflammatory drugs decrease the risk for Alzheimer's 

disease? The Rotterdam Study. Neurology 

1995;45(8):1441-5. 

Full Text: Exclude - not longitudinal 

Anderson GL, Limacher M, Assaf AR, et al. Effects of 

conjugated equine estrogen in postmenopausal women with 

hysterectomy: the Women's Health Initiative randomized 

controlled trial.[see comment]. JAMA 2004;291(14):1701-

12. 

Full Text: Exclude - no cognitive endpoints 

Andre-Petersson L, Elmstahl S, Hagberg B, et al. Is blood 

pressure at 68 an independent predictor of cognitive decline 

at 81? Results from follow-up study "Men born in 1914", 

Malmo, Sweden. Aging Ment Health 2003;7(1):61-72. 

Full Text: Exclude - observational N < 300 
G-2

Andrieu S, Gillette S, Amouyal K, et al. Association of 

Alzheimer's disease onset with ginkgo biloba and other 

symptomatic cognitive treatments in a population of 

women aged 75 years and older from the EPIDOS study. J 

Gerontol A Biol Sci Med Sci 2003;58(4):372-7. 

Full Text: Exclude - outcomes inadequately assessed 

Andrieu S, Ousset PJ, Coley N, et al. GuidAge study: a 5-

year double blind, randomised trial of EGb 761 for the 

prevention of Alzheimer's disease in elderly subjects with 

memory complaints. i. rationale, design and baseline data. 

Curr Alzheimer Res 2008;5(4):406-15. 

Full Text: Exclude - insufficient outcomes data 

Annerbo S, Wahlund LO, Lokk J. The significance of 

thyroid-stimulating hormone and homocysteine in the 

development of Alzheimer's disease in mild cognitive 

impairment: a 6-year follow-up study. Am J Alzheimers 

Dis Other Demen 2006;21(3):182-8. 

Full Text: Exclude - observational N<300 

Anonymous. The Atherosclerosis Risk in Communities 

(ARIC) Study: design and objectives. The ARIC 

investigators. Am J Epidemiol 1989;129(4):687-702. 

Full Text: Exclude - Methods paper 

Anonymous. Final report on the aspirin component of the 

ongoing Physicians' Health Study. Steering Committee of 

the Physicians' Health Study Research Group.[see 

comment]. N Engl J Med 1989;321(3):129-35. 

Full Text: Exclude - outcomes not AD/CD 

Anonymous. Prevention of stroke by antihypertensive drug 

treatment in older persons with isolated systolic 

hypertension. Final results of the Systolic Hypertension in 

the Elderly Program (SHEP). SHEP Cooperative Research 

Group.[see comment]. JAMA 1991;265(24):3255-64. 

Full Text: Exclude - outcomes unacceptably assessed 

Anonymous. The Canadian Study of Health and Aging: 

risk factors for Alzheimer's disease in Canada. Neurology 

1994;44(11):2073-80. 

Full Text: Exclude - not longitudinal 

Anonymous. Design of the Women's Health Initiative 

clinical trial and observational study. The Women's Health 

Initiative Study Group. Control Clin Trials 1998;19(1):61-

109. 

Full Text: Exclude - methods paper 

Anonymous. Potassium may help prevent Alzheimer's 

disease. Potassium could be a possible deterrent for 

dementia, three new studies suggest. Health News 

2006;12(6):7-8. 

Full Text: Exclude - dementia @ baseline 

Anthony JC, Breitner JC, Zandi PP, et al. Reduced 

prevalence of AD in users of NSAIDs and H2 receptor 

antagonists: the Cache County study. Neurology 

2000;54(11):2066-71. 

Full Text: Exclude - not longitudinal 

Arauz A, Alonso E, Rodriguez-Saldana J, et al. Cognitive 

impairment and mortality in older healthy Mexican 

subjects: a population-based 10-year follow-up study. 

Neurol Res 2005;27(8):882-6. 

Full Text: Exclude - non-Western country 

Arlt S, Schulze F, Eichenlaub M, et al. Asymmetrical 

dimethylarginine is increased in plasma and decreased in 

cerebrospinal fluid of patients with Alzheimer's disease. 

Dement Geriatr Cogn Disord 2008;26(1):58-64. 

Full Text: Exclude - not longitudinal 

Aronson MK, Ooi WL, Morgenstern H, et al. Women, 

myocardial infarction, and dementia in the very old. 

Neurology 1990;40(7):1102-6. 

Full Text: Exclude - risk factor out of scope 

Arvanitakis Z, Schneider JA, Wilson RS, et al. Diabetes is 

related to cerebral infarction but not to AD pathology in 

older persons. Neurology 2006;67(11):1960-5. 

Full Text: Exclude - outcomes not AD/CD 

Arvanitakis Z, Wilson RS, Li Y, et al. Diabetes and 

function in different cognitive systems in older individuals 

without dementia. Diabetes Care 2006;29(3):560-5. 

Full Text: Exclude - not longitudinal 

Arve S, Tilvis RS, Lehtonen A, et al. Coexistence of 

lowered mood and cognitive impairment of elderly people 

in five birth cohorts. Aging (Milano) 1999;11(2):90-5. 

Full Text: Exclude - not longitudinal 

Ashman TA, Cantor JB, Gordon WA, et al. A comparison 

of cognitive functioning in older adults with and without 

traumatic brain injury. J Head Trauma Rehabil 

2008;23(3):139-48. 

Full Text: Exclude - not longitudinal 

Atiea JA, Moses JL, Sinclair AJ. Neuropsychological 

function in older subjects with non-insulin-dependent 

diabetes mellitus. Diabet Med 1995;12(8):679-85. 

Full Text: Exclude - not longitudinal 

Atkinson HH, Cesari M, Kritchevsky SB, et al. Predictors 

of combined cognitive and physical decline. J Am Geriatr 

Soc 2005;53(7):1197-202. 

Full Text: Exclude - not applicable population 

Bachman DL, Wolf PA, Linn RT, et al. Incidence of 

dementia and probable Alzheimer's disease in a general 

population: the Framingham Study. Neurology 1993;43(3 

Pt 1):515-9. 

Full Text: Exclude - risk factor out of scope 

Baldeiras I, Santana I, Proenca MT, et al. Peripheral 

oxidative damage in mild cognitive impairment and mild 

Alzheimer's disease. J Alzheimers Dis 2008;15(1):117-28. 

Full Text: Exclude - not longitudinal 

Ban TA, Morey L, Aguglia E, et al. Nimodipine in the 

treatment of old age dementias. Prog 

Neuropsychopharmacol Biol Psychiatry 1990;14(4):525-
G-3

51. 

Full Text: Exclude - not longitudinal 

Barnes DE, Covinsky KE, Whitmer RA, et al. Predicting 

risk of dementia in older adults. The late-life dementia risk 

index. Neurology 2009. 

Full Text: Exclude - <60% of dementia is AD 

Barnes DE, Tager IB, Satariano WA, et al. The relationship 

between literacy and cognition in well-educated elders. J 

Gerontol A Biol Sci Med Sci 2004;59(4):390-5. 

Full Text: Exclude - not longitudinal 

Barrett-Connor E, Edelstein SL. A prospective study of 

dehydroepiandrosterone sulfate and cognitive function in 

an older population: the Rancho Bernardo Study. J Am 

Geriatr Soc 1994;42(4):420-3. 

Full Text: Exclude - not longitudinal 

Basaria S, Wisniewski A, Dupree K, et al. Effect of highdose isoflavones on cognition, quality of life, androgens, 

and lipoprotein in post-menopausal women. J Endocrinol 

Invest 2009;32(2):150-5. 

Full Text: Exclude - CD f/u < 1 yr 

Bassuk SS, Berkman LF, Wypij D. Depressive 

symptomatology and incident cognitive decline in an 

elderly community sample. Arch Gen Psychiatry 

1998;55(12):1073-81. 

Full Text: Exclude - SPMSQ single test 

Bassuk SS, Glass TA, Berkman LF. Social disengagement 

and incident cognitive decline in community-dwelling 

elderly persons. Ann Intern Med 1999;131(3):165-73. 

Full Text: Exclude - SPMSQ single test 

Bathum L, von Bornemann Hjelmborg J, Christiansen L, et 

al. Methylenetetrahydrofolate reductase 677C>T and 

methionine synthase 2756A>G mutations: no impact on 

survival, cognitive functioning, or cognitive decline in 

nonagenarians. J Gerontol A Biol Sci Med Sci 

2007;62(2):196-201. 

Full Text: Exclude - dementia @ baseline BPIncl 

Battino M, Bompadre S, Leone L, et al. Coenzyme Q, 

Vitamin E and Apo-E alleles in Alzheimer Disease. 

Biofactors 2003;18(1-4):277-81. 

Full Text: Exclude - dementia @ baseline 

Beard CM, Waring SC, O'Brien PC, et al. Nonsteroidal 

anti-inflammatory drug use and Alzheimer's disease: a 

case-control study in Rochester, Minnesota, 1980 through 

1984. Mayo Clin Proc 1998;73(10):951-5. 

Full Text: Exclude - outcome non-specific AD 

Becker JT, Chang YF, Lopez OL, et al. Depressed mood is 

not a risk factor for incident dementia in a communitybased cohort. Am J Geriatr Psychiatry 2009;17(8):653-63. 

Full Text: Exclude - observational N<300 

Beeri MS, Schmeidler J, Silverman JM, et al. Insulin in 

combination with other diabetes medication is associated 

with less Alzheimer neuropathology. Neurology 

2008;71(10):750-7. 

Full Text: Exclude - selected population 

Beeri MS, Silverman JM, Davis KL, et al. Type 2 diabetes 

is negatively associated with Alzheimer's disease 

neuropathology. J Gerontol A Biol Sci Med Sci 

2005;60(4):471-5. 

Full Text: Exclude - not applicablel population 

Bennett DA, Whitmer RA. NSAID exposure and risk of 

Alzheimer disease: is timing everything? Neurology 

2009;72(22):1884-5. 

Full Text: Exclude - editorial, no primary data 

Bennett DA, Wilson RS, Schneider JA, et al. 

Apolipoprotein E epsilon4 allele, AD pathology, and the 

clinical expression of Alzheimer's disease. Neurology 

2003;60(2):246-52. 

Full Text: Exclude - outcomes non-specific AD 

Bennett DA, Wilson RS, Schneider JA, et al. Education 

modifies the relation of AD pathology to level of cognitive 

function in older persons. Neurology 2003;60(12):1909-15. 

Full Text: Exclude - outcomes non-specific AD 

Benton D, Williams C, Brown A. Impact of consuming a 

milk drink containing a probiotic on mood and cognition. 

Eur J Clin Nutr 2007;61(3):355-61. 

Full Text: Exclude - AD/CD f/u < 1 year 

Bermejo-Pareja F, Benito-Leon J, Vega S, et al. Incidence 

and subtypes of dementia in three elderly populations of 

central Spain. J Neurol Sci 2008;264(1-2):63-72. 

Full Text: Exclude - incidence study (risk factor not focus 

of study) 

Berr C, Coudray C, Bonithon-Kopp C, et al. Demographic 

and cardiovascular risk factors in relation to antioxidant 

status: the EVA Study. Int J Vitam Nutr Res 

1998;68(1):26-35. 

Full Text: Exclude - outcomes not AD/CD 

Berr C, Richard MJ, Gourlet V, et al. Enzymatic 

antioxidant balance and cognitive decline in aging--the 

EVA study. Eur J Epidemiol 2004;19(2):133-8. 

Full Text: Exclude - risk factor out of scope 

Berr C, Richard MJ, Roussel AM, et al. Systemic oxidative 

stress and cognitive performance in the population-based 

EVA study. Etude du Vieillissement Arteriel. Free Radic 

Biol Med 1998;24(7-8):1202-8. 

Full Text: Exclude - not longitudinal 

Bes A, Orgogozo JM, Poncet M, et al. A 24-month, doubleblind, placebo-controlled multicentre pilot study of the 

efficacy and safety of nicergoline 60 mg per day in elderly 

hypertensive patients with leukoaraiosis. Eur J Neurol 

1999;6(3):313-22. 

Full Text: Exclude - risk factor out of scope 

Bicikova M, Ripova D, Hill M, et al. Plasma levels of 7-
G-4

hydroxylated dehydroepiandrosterone (DHEA) metabolites 

and selected amino-thiols as discriminatory tools of 

Alzheimer's disease and vascular dementia. Clin Chem Lab 

Med 2004;42(5):518-24. 

Full Text: Exclude - dementia @ baseline 

Bierman EJ, Comijs HC, Jonker C, et al. Effects of anxiety 

versus depression on cognition in later life. Am J Geriatr 

Psychiatry 2005;13(8):686-93. 

Full Text: Exclude - not longitudinal 

Bird AS, Blizard RA, Mann AH. Treating hypertension in 

the older person: an evaluation of the association of blood 

pressure level and its reduction with cognitive performance. 

J Hypertens 1990;8(2):147-52. 

Full Text: Exclude - AD/CD f/u < 1 yr 

Birns J, Morris R, Jarosz J, et al. The structural and 

functional consequences of diurnal variations in blood 

pressure in treated patients with hypertensive 

cerebrovascular disease. J Hypertens 2009;27(5):1042-8. 

Full Text: Exclude - observational N<300 

Bisol Balardin J, Vedana G, Ludwig A, et al. Contextual 

memory and encoding strategies in young and older adults 

with and without depressive symptoms. Aging Ment Health 

2009;13(3):313-8. 

Full Text: Exclude - observational N<300 

Blasko I, Jungwirth S, Jellinger K, et al. Effects of 

medications on plasma amyloid beta (Abeta) 42: 

longitudinal data from the VITA cohort. J Psychiatr Res 

2008;42(11):946-55. 

Full Text: Exclude - dementia @ baseline 

Blasko I, Kemmler G, Krampla W, et al. Plasma amyloid 

beta protein 42 in non-demented persons aged 75 years: 

effects of concomitant medication and medial temporal 

lobe atrophy. Neurobiol Aging 2005;26(8):1135-43. 

Full Text: Exclude - risk factor out of scope 

Bogner HR, Richie MB, de Vries HF, et al. Depression, 

cognition, apolipoprotein e genotype: latent class approach 

to identifying subtype. Am J Geriatr Psychiatry 

2009;17(4):344-52. 

Full Text: Exclude - not longitudinal 

Bohannon AD, Fillenbaum GG, Pieper CF, et al. 

Relationship of race/ethnicity and blood pressure to change 

in cognitive function. J Am Geriatr Soc 2002;50(3):424-9. 

Full Text: Exclude - SPMSQ single test 

Boita F, Couderc LJ, Crestani B, et al. [Evaluation of 

pulmonary function in the elderly. Intergroupe Pneumo 

Geriatrie SPLF-SFGG]. Rev Mal Respir 2006;23(6):619-

28. 

Full Text: Exclude: non-English 

Boland LL, Shahar E, Iber C, et al. Measures of cognitive 

function in persons with varying degrees of sleepdisordered breathing: the Sleep Heart Health Study. J Sleep 

Res 2002;11(3):265-72. 

Full Text: Exclude - not longitudinal 

Bond GE, Burr RL, McCurry SM, et al. Alcohol and 

cognitive performance: a longitudinal study of older 

Japanese Americans. The Kame Project. Int Psychogeriatr 

2005;17(4):653-68. 

Full Text: Exclude - risk factor out of scope 

Boritz TZ, Angus L, Monette G, et al. An empirical 

analysis of autobiographical memory specificity subtypes 

in brief emotion-focused and client-centered treatments of 

depression. Psychother Res 2008;18(5):584-93. 

Full Text: Exclude - risk factor out of scope 

Boron JB, Turiano NA, Willis SL, et al. Effects of 

cognitive training on change in accuracy in inductive 

reasoning ability. J Gerontol B Psychol Sci Soc Sci 

2007;62(3):P179-86. 

Full Text: Exclude - AD/CD f/u < 1 year 

Boron JB, Willis SL, Schaie KW. Cognitive training gain 

as a predictor of mental status. J Gerontol B Psychol Sci 

Soc Sci 2007;62(1):P45-52. 

Full Text: Exclude - comparator not placebo/control 

Bosch J, Yusuf S, Pogue J, et al. Use of ramipril in 

preventing stroke: double blind randomised trial. BMJ 

2002;324(7339):699-702. 

Full Text: Exclude - outcomes not AD/CD 

Bosch J, Yusuf S, Pogue J, et al. Use of ramipril in 

preventing stroke: double blind randomised trial.[see 

comment][summary for patients in J Fam Pract. 2002 

Jul;51(7):595; PMID: 12160488]. BMJ 

2002;324(7339):699-702. 

Full Text: Exclude - outcomes unacceptably assessed 

Bottiggi KA, Salazar JC, Yu L, et al. Long-term cognitive 

impact of anticholinergic medications in older adults. Am J 

Geriatr Psychiatry 2006;14(11):980-4. 

Full Text: Exclude - risk factor out of scope 

Bouchard M, Mergler D, Baldwin M, et al. 

Neurobehavioral functioning after cessation of manganese 

exposure: a follow-up after 14 years. Am J Ind Med 

2007;50(11):831-40. 

Full Text: Exclude - observational N < 300 

Brady CB, Gaziano JM, Cxypoliski RA, et al. 

Homocysteine lowering and cognition in CKD: the 

Veterans Affairs homocysteine study. Am J Kidney Dis 

2009;54(3):440-9. 

Full Text: Exclude - not applicable population 

Brady CB, Spiro A, 3rd, Gaziano JM. Effects of age and 

hypertension status on cognition: the Veterans Affairs 

Normative Aging Study. Neuropsychology 

2005;19(6):770-7. 

Full Text: Exclude - not longitudinal 

Braszko JJ, Karwowska-Polecka W, Halicka D, et al. 

Captopril and enalapril improve cognition and depressed 
G-5

mood in hypertensive patients. J Basic Clin Physiol 

Pharmacol 2003;14(4):323-43. 

Full Text: Exclude - observational N < 300 

Brayne C, Best N, Muir M, et al. Five-year incidence and 

prediction of dementia and cognitive decline in a 

population sample of women aged 70-79 at baseline. Int J 

Geriatr Psychiatry 1997;12(11):1107-18. 

Full Text: Exclude - observational N<300 

Brayne C, Gao L, Dewey M, et al. Dementia before death 

in ageing societies--the promise of prevention and the 

reality. PLoS Med 2006;3(10):e397. 

Full Text: Exclude - dementia @ baseline 

Brehaut JC, Raina P, Lindsay J. Does cognitive status 

modify the relationship between education and mortality? 

Evidence from the Canadian Study of Health and Aging. 

Int Psychogeriatr 2004;16(1):75-91. 

Full Text: Exclude - dementia @ baseline 

Breitner JC, Welsh KA, Helms MJ, et al. Delayed onset of 

Alzheimer's disease with nonsteroidal anti-inflammatory 

and histamine H2 blocking drugs. Neurobiol Aging 

1995;16(4):523-30. 

Full Text: Exclude - dementia @ baseline 

Broe GA, Creasey H, Jorm AF, et al. Health habits and risk 

of cognitive impairment and dementia in old age: a 

prospective study on the effects of exercise, smoking and 

alcohol consumption. Aust N Z J Public Health 

1998;22(5):621-3. 

Full Text: Exclude - no outcomes data 

Broe GA, Grayson DA, Creasey HM, et al. Antiinflammatory drugs protect against Alzheimer disease at 

low doses. Arch Neurol 2000;57(11):1586-91. 

Full Text: Exclude - not longitudinal 

Brown DR, Wang Y, Ward A, et al. Chronic psychological 

effects of exercise and exercise plus cognitive strategies. 

Med Sci Sports Exerc 1995;27(5):765-75. 

Full Text: Exclude - risk factor out of scope 

Brown ES, Vera E, Frol AB, et al. Effects of chronic 

prednisone therapy on mood and memory. J Affect Disord 

2007;99(1-3):279-83. 

Full Text: Exclude - not applicable population 

Bruce DG, Davis WA, Casey GP, et al. Predictors of 

cognitive decline in older individuals with diabetes. 

Diabetes Care 2008;31(11):2103-7. 

Full Text: Exclude - observational N<300 

Bruce DG, Davis WA, Casey GP, et al. Predictors of 

cognitive impairment and dementia in older people with 

diabetes. Diabetologia 2008;51(2):241-8. 

Full Text: Exclude - <60% of dementia is AD 

Bruehl H, Wolf OT, Sweat V, et al. Modifiers of cognitive 

function and brain structure in middle-aged and elderly 

individuals with type 2 diabetes mellitus. Brain Res 

2009;1280:186-94. 

Full Text: Exclude - observational N<300 

Buchman AS, Wilson RS, Boyle PA, et al. Grip strength 

and the risk of incident Alzheimer's disease. 

Neuroepidemiology 2007;29(1-2):66-73. 

Full Text: Exclude - risk factor out of scope 

Burke V, Beilin LJ, Cutt HE, et al. Moderators and 

mediators of behaviour change in a lifestyle program for 

treated hypertensives: a randomized controlled trial 

(ADAPT). Health Educ Res 2008;23(4):583-91. 

Full Text: Exclude - risk factor out of scope 

Burke V, Mansour J, Mori TA, et al. Changes in cognitive 

measures associated with a lifestyle program for treated 

hypertensives: a randomized controlled trial (ADAPT). 

Health Educ Res 2008;23(2):202-17. 

Full Text: Exclude - risk factor out of scope 

Butler SM, Ashford JW, Snowdon DA. Age, education, 

and changes in the Mini-Mental State Exam scores of older 

women: findings from the Nun Study. J Am Geriatr Soc 

1996;44(6):675-81. 

Full Text: Exclude - likely dementia @ baseline 

Bygren LO, Weissglas G, Wikstrom BM, et al. Cultural 

participation and health: a randomized controlled trial 

among medical care staff. Psychosom Med 

2009;71(4):469-73. 

Full Text: Exclude - <80% >= 50 yr old 

Cancelli I, Gigli GL, Piani A, et al. Drugs with 

anticholinergic properties as a risk factor for cognitive 

impairment in elderly people: a population-based study. J 

Clin Psychopharmacol 2008;28(6):654-9. 

Full Text: Exclude - risk factor out of scope 

Cao YJ, Mager DE, Simonsick EM, et al. Physical and 

cognitive performance and burden of anticholinergics, 

sedatives, and ACE inhibitors in older women. Clin 

Pharmacol Ther 2008;83(3):422-9. 

Full Text: Exclude - risk factor out of scope 

Capurso C, Solfrizzi V, D'Introno A, et al. Short arm of 

chromosome 11 and sporadic Alzheimer's disease: catalase 

and cathepsin D gene polymorphisms. Neurosci Lett 

2008;432(3):237-42. 

Full Text: Exclude - dementia @ baseline 

Carles S, Jr., Curnier D, Pathak A, et al. Effects of shortterm exercise and exercise training on cognitive function 

among patients with cardiac disease. J Cardiopulm Rehabil 

Prev 2007;27(6):395-9. 

Full Text: Exclude - RCT N<50 

Carlson LE, Sherwin BB. Relationships among cortisol 

(CRT), dehydroepiandrosterone-sulfate (DHEAS), and 

memory in a longitudinal study of healthy elderly men and 

women. Neurobiol Aging 1999;20(3):315-24. 

Full Text: Exclude - risk factor out of scope 
G-6

Carlsson C, Gleason C, Hess T, et al. Effects of simvastatin 

on cerebrospinal fluid biomarkers and cognition in middleaged adults at risk for Alzheimer's disease. J Alzheimers 

Dis 2008;13(2):187-97. 

Full Text: Exclude - not longitudinal 

Carlsson CM, Papcke-Benson K, Carnes M, et al. Healthrelated quality of life and long-term therapy with 

pravastatin and tocopherol (vitamin E) in older adults. 

Drugs Aging 2002;19(10):793-805. 

Full Text: Exclude - AD/CD f/u < 1 year 

Carriere I, Fourrier-Reglat A, Dartigues JF, et al. Drugs 

with anticholinergic properties, cognitive decline, and 

dementia in an elderly general population: the 3-city study. 

Arch Intern Med 2009;169(14):1317-24. 

Full Text: Exclude - risk factor out of scope 

Cascalheira JF, Joao SS, Pinhancos SS, et al. Serum 

homocysteine: interplay with other circulating and genetic 

factors in association to Alzheimer's type dementia. Clin 

Biochem 2009;42(9):783-90. 

Full Text: Exclude - observational N<300 

Caselli RJ, Reiman EM, Osborne D, et al. Longitudinal 

changes in cognition and behavior in asymptomatic carriers 

of the APOE e4 allele. Neurology 2004;62(11):1990-5. 

Full Text: Exclude - observational N<300 

Caserta RJ, Young J, Janelle CM. Old dogs, new tricks: 

training the perceptual skills of senior tennis players. J 

Sport Exerc Psychol 2007;29(4):479-97. 

Full Text: Exclude - risk factor out of scope 

Cassidy K, Kotynia-English R, Acres J, et al. Association 

between lifestyle factors and mental health measures 

among community-dwelling older women. Aust N Z J 

Psychiatry 2004;38(11-12):940-7. 

Full Text: Exclude - not longitudinal 

Censori B, Manara O, Agostinis C, et al. Dementia after 

first stroke. Stroke 1996;27(7):1205-10. 

Full Text: Exclude - not applicable population 

Cervilla JA, Prince M, Joels S, et al. Long-term predictors 

of cognitive outcome in a cohort of older people with 

hypertension. Br J Psychiatry 2000;177:66-71. 

Full Text: Exclude - not longitudinal 

Cervilla JA, Prince M, Joels S, et al. Does depression 

predict cognitive outcome 9 to 12 years later? Evidence 

from a prospective study of elderly hypertensives. Psychol 

Med 2000;30(5):1017-23. 

Full Text: Exclude - Inadequate outcomes 

Chaves ML, Camozzato AL, Godinho C, et al. Incidence of 

mild cognitive impairment and Alzheimer disease in 

Southern Brazil. J Geriatr Psychiatry Neurol 

2009;22(3):181-7. 

Full Text: Exclude - non-Western country 

Chen R, Hu Z, Wei L, et al. Is the relationship between 

syndromes of depression and dementia temporal? The 

MRC-ALPHA and Hefei-China studies. Psychol Med 

2009;39(3):425-30. 

Full Text: Exclude - dementia @ baseline 

Cherubini A, Andres-Lacueva C, Martin A, et al. Low 

plasma N-3 fatty acids and dementia in older persons: the 

InCHIANTI study. J Gerontol A Biol Sci Med Sci 

2007;62(10):1120-6. 

Full Text: Exclude - not longitudinal 

Cherubini A, Martin A, Andres-Lacueva C, et al. Vitamin 

E levels, cognitive impairment and dementia in older 

persons: the InCHIANTI study. Neurobiol Aging 

2005;26(7):987-94. 

Full Text: Exclude - not longitudinal 

Chiang CJ, Yip PK, Wu SC, et al. Midlife risk factors for 

subtypes of dementia: a nested case-control study in 

Taiwan. Am J Geriatr Psychiatry 2007;15(9):762-71. 

Full Text: Exclude - inadequate AD assessment 

Chiu CC, Su KP, Cheng TC, et al. The effects of omega-3 

fatty acids monotherapy in Alzheimer's disease and mild 

cognitive impairment: a preliminary randomized doubleblind placebo-controlled study. Prog 

Neuropsychopharmacol Biol Psychiatry 2008;32(6):1538-

44. 

Full Text: Exclude - RCT N<50 

Chodosh J, Kado DM, Seeman TE, et al. Depressive 

symptoms as a predictor of cognitive decline: MacArthur 

Studies of Successful Aging. Am J Geriatr Psychiatry 

2007;15(5):406-15. 

Full Text: Exclude - SPMSQ single test 

Christensen H, Jorm AF, Henderson AS, et al. The 

relationship between health and cognitive functioning in a 

sample of elderly people in the community. Age Ageing 

1994;23(3):204-12. 

Full Text: Exclude - not longitudinal 

Christensen H, Korten A, Jorm AF, et al. Activity levels 

and cognitive functioning in an elderly community sample. 

Age Ageing 1996;25(1):72-80. 

Full Text: Exclude - not longitudinal 

Chui MH, Papanikolaou Y, Fontaine-Bisson B, et al. The 

TNF-alpha-238G > a single-nucleotide polymorphism 

protects against memory decline in older adults with type 2 

diabetes. Behav Neurosci 2007;121(3):619-24. 

Full Text: Exclude - observational N<300 

Churchill JD, Galvez R, Colcombe S, et al. Exercise, 

experience and the aging brain. Neurobiol Aging 

2002;23(5):941-55. 

Full Text: Exclude - observational N<300 

Clark MS, Bond MJ, Hecker JR. Environmental stress, 

psychological stress and allostatic load. Psychol Health 

Med 2007;12(1):18-30. 

Full Text: Exclude - not applicable population 
G-7

Clarke R, Harrison G, Richards S. Effect of vitamins and 

aspirin on markers of platelet activation, oxidative stress 

and homocysteine in people at high risk of dementia. J 

Intern Med 2003;254(1):67-75. 

Full Text: Exclude - not applicable population 

Clarke R, Sherliker P, Hin H, et al. Folate and vitamin B12 

status in relation to cognitive impairment and anaemia in 

the setting of voluntary fortification in the UK. Br J Nutr 

2008;100(5):1054-9. 

Full Text: Exclude - risk factor out of scope 

Clarke R, Smith AD, Jobst KA, et al. Folate, vitamin B12, 

and serum total homocysteine levels in confirmed 

Alzheimer disease. Arch Neurol 1998;55(11):1449-55. 

Full Text: Exclude - dementia @ baseline 

Clarkson-Smith L, Hartley AA. Relationships between 

physical exercise and cognitive abilities in older adults. 

Psychol Aging 1989;4(2):183-9. 

Full Text: Exclude - not longitudinal 

Cohen-Zion M, Stepnowsky C, Marler, et al. Changes in 

cognitive function associated with sleep disordered 

breathing in older people. J Am Geriatr Soc 

2001;49(12):1622-7. 

Full Text: Exclude - observational N < 300 

Colcombe SJ, Kramer AF, Erickson KI, et al. 

Cardiovascular fitness, cortical plasticity, and aging. Proc 

Natl Acad Sci U S A 2004;101(9):3316-21. 

Full Text: Exclude - outcome non-specified AD 

Comijs HC, Dik MG, Deeg DJ, et al. The course of 

cognitive decline in older persons: results from the 

longitudinal aging study amsterdam. Dement Geriatr Cogn 

Disord 2004;17(3):136-42. 

Full Text: Exclude - observational N<300 

Comijs HC, Jonker C, Beekman AT, et al. The association 

between depressive symptoms and cognitive decline in 

community-dwelling elderly persons. Int J Geriatr 

Psychiatry 2001;16(4):361-7. 

Full Text: Exclude - Q2 Continuous data only 

Comijs HC, van Tilburg T, Geerlings SW, et al. Do 

severity and duration of depressive symptoms predict 

cognitive decline in older persons? Results of the 

Longitudinal Aging Study Amsterdam. Aging Clin Exp Res 

2004;16(3):226-32. 

Full Text: Exclude - observational N<300 

Conquer JA, Tierney MC, Zecevic J, et al. Fatty acid 

analysis of blood plasma of patients with Alzheimer's 

disease, other types of dementia, and cognitive impairment. 

Lipids 2000;35(12):1305-12. 

Full Text: Exclude - dementia @ baseline 

Corder EH, Beaumont H. Susceptibility groups for 

Alzheimer's disease (OPTIMA cohort): integration of gene 

variants and biochemical factors. Mech Ageing Dev 

2007;128(1):76-82. 

Full Text: Exclude - not longitudinal 

Cordonnier C, van der Flier WM, Sluimer JD, et al. 

Prevalence and severity of microbleeds in a memory clinic 

setting. Neurology 2006;66(9):1356-60. 

Full Text: Exclude - dementia @ baseline 

Correa Leite ML, Nicolosi A, Cristina S, et al. Nutrition 

and cognitive deficit in the elderly: a population study. Eur 

J Clin Nutr 2001;55(12):1053-8. 

Full Text: Exclude - not longitudinal 

Corsentino EA, Sawyer K, Sachs-Ericsson N, et al. 

Depressive symptoms moderate the influence of the 

apolipoproteine epsilon4 allele on cognitive decline in a 

sample of community dwelling older adults. Am J Geriatr 

Psychiatry 2009;17(2):155-65. 

Full Text: Exclude - SPMSQ single test 

Corzo L, Zas R, Rodriguez S, et al. Decreased levels of 

serum nitric oxide in different forms of dementia. Neurosci 

Lett 2007;420(3):263-7. 

Full Text: Exclude - dementia @ baseline 

Costa MM, Reus VI, Wolkowitz OM, et al. Estrogen 

replacement therapy and cognitive decline in memoryimpaired post-menopausal women. Biol Psychiatry 

1999;46(2):182-8. 

Full Text: Exclude - dementia @ baseline 

Cramer C, Haan M, Galea S, et al. Use of statins and 

incidence of dementia and cognitive impairment without 

dementia in a cohort study. Neurology 2008;71(5):344-50. 

Full Text: Exclude - outcome non-specific AD 

Crooks VC, Lubben J, Petitti DB, et al. Social network, 

cognitive function, and dementia incidence among elderly 

women. Am J Public Health 2008;98(7):1221-7. 

Full Text: Exclude - <60% of dementia is AD 

Crowe M, Andel R, Pedersen NL, et al. Do work-related 

stress and reactivity to stress predict dementia more than 30 

years later? Alzheimer Dis Assoc Disord 2007;21(3):205-9. 

Full Text: Exclude - <60% of dementia is AD 

Csernansky JG, Dong H, Fagan AM, et al. Plasma cortisol 

and progression of dementia in subjects with Alzheimertype dementia. Am J Psychiatry 2006;163(12):2164-9. 

Full Text: Exclude - dementia @ baseline 

Cui X, Lyness JM, Tu X, et al. Does depression precede or 

follow executive dysfunction? Outcomes in older primary 

care patients. Am J Psychiatry 2007;164(8):1221-8. 

Full Text: Exclude - observational N<300 

Cukierman-Yaffe T, Gerstein HC, Anderson C, et al. 

Glucose intolerance and diabetes as risk factors for 

cognitive impairment in people at high cardiovascular risk: 

results from the ONTARGET/TRANSCEND research 

programme. Diabetes Res Clin Pract 2009;83(3):387-93. 

Full Text: Exclude - not longitudinal 
G-8

Cukierman-Yaffe T, Gerstein HC, Williamson JD, et al. 

Relationship between baseline glycemic control and 

cognitive function in individuals with type 2 diabetes and 

other cardiovascular risk factors: the action to control 

cardiovascular risk in diabetes-memory in diabetes 

(ACCORD-MIND) trial. Diabetes Care 2009;32(2):221-6. 

Full Text: Exclude - not longitudinal 

Cummings SR, Black DM, Nevitt MC, et al. Appendicular 

bone density and age predict hip fracture in women. The 

Study of Osteoporotic Fractures Research Group.[see 

comment]. JAMA 1990;263(5):665-8. 

Full Text: Exclude - outcomes not AD/CD 

Cunningham CJ, Sinnott M, Denihan A, et al. Endogenous 

sex hormone levels in postmenopausal women with 

Alzheimer's disease. J Clin Endocrinol Metab 

2001;86(3):1099-103. 

Full Text: Exclude - dementia @ baseline 

Dahle CL, Jacobs BS, Raz N. Aging, vascular risk, and 

cognition: blood glucose, pulse pressure, and cognitive 

performance in healthy adults. Psychol Aging 

2009;24(1):154-62. 

Full Text: Exclude - observational N<300 

Dam H. Depression in stroke patients 7 years following 

stroke. Acta Psychiatr Scand 2001;103(4):287-93. 

Full Text: Exclude - not applicable population 

Dangour AD, Allen E, Elbourne D, et al. Fish consumption 

and cognitive function among older people in the UK: 

baseline data from the OPAL study. J Nutr Health Aging 

2009;13(3):198-202. 

Full Text: Exclude - not longitudinal 

Dargent-Molina P, Favier F, Grandjean H, et al. Fallrelated factors and risk of hip fracture: the EPIDOS 

prospective study.[erratum appears in Lancet 1996 Aug 

10;348(9024):416]. Lancet 1996;348(9021):145-9. 

Full Text: Exclude - outcomes not AD/CD 

Dartigues JF, Carcaillon L, Helmer C, et al. Vasodilators 

and nootropics as predictors of dementia and mortality in 

the PAQUID cohort. J Am Geriatr Soc 2007;55(3):395-9. 

Full Text: Exclude - <60% of dementia is AD 

Dartigues JF, Gagnon M, Barberger-Gateau P, et al. The 

Paquid epidemiological program on brain ageing. 

Neuroepidemiology 1992;11 Suppl 1:14-8. 

Full Text: Exclude - methods paper 

Dassanayake T, Gawarammana IB, Weerasinghe V, et al. 

Auditory event-related potential changes in chronic 

occupational exposure to organophosphate pesticides. Clin 

Neurophysiol 2009;120(9):1693-8. 

Full Text: Exclude - non-Western country 

de Castro MS, Fuchs FD, Santos MC, et al. Pharmaceutical 

care program for patients with uncontrolled hypertension. 

Report of a double-blind clinical trial with ambulatory 

blood pressure monitoring. Am J Hypertens 

2006;19(5):528-33. 

Full Text: Exclude - non-Western country 

De Ronchi D, Fratiglioni L, Rucci P, et al. The effect of 

education on dementia occurrence in an Italian population 

with middle to high socioeconomic status. Neurology 

1998;50(5):1231-8. 

Full Text: Exclude - not longitudinal 

Dealberto MJ, Pajot N, Courbon D, et al. Breathing 

disorders during sleep and cognitive performance in an 

older community sample: the EVA Study. J Am Geriatr 

Soc 1996;44(11):1287-94. 

Full Text: Exclude - not longitudinal 

Dealberto MJ, Sauron B, Derouesne C, et al. Factors 

associated with low cognitive performance in general 

practice. Eur Arch Psychiatry Clin Neurosci 

1994;244(2):53-8. 

Full Text: Exclude - not longitudinal 

Deary IJ, Whalley LJ, Batty GD, et al. Physical fitness and 

lifetime cognitive change. Neurology 2006;67(7):1195-200. 

Full Text: Exclude - not longitudinal 

Deary IJ, Whiteman MC, Pattie A, et al. Apolipoprotein e 

gene variability and cognitive functions at age 79: a followup of the Scottish mental survey of 1932. Psychol Aging 

2004;19(2):367-71. 

Full Text: Exclude - not longitudinal 

Deary IJ, Whiteman MC, Starr JM, et al. The impact of 

childhood intelligence on later life: following up the 

Scottish mental surveys of 1932 and 1947. J Pers Soc 

Psychol 2004;86(1):130-47. 

Full Text: Exclude - methods paper 

Debling D, Amelang M, Hasselbach P, et al. Diabetes and 

cognitive function in a population-based study of elderly 

women and men. J Diabetes Complications 

2006;20(4):238-45. 

Full Text: Exclude - not longitudinal 

DeCarli C, Miller BL, Swan GE, et al. Cerebrovascular and 

brain morphologic correlates of mild cognitive impairment 

in the National Heart, Lung, and Blood Institute Twin 

Study. Arch Neurol 2001;58(4):643-7. 

Full Text: Exclude - outcomes non-specific AD 

DeCarli C, Mungas D, Harvey D, et al. Memory 

impairment, but not cerebrovascular disease, predicts 

progression of MCI to dementia. Neurology 

2004;63(2):220-7. 

Full Text: Exclude - observational N < 300 

Deeg DJH, van Tilburg T, Smit JH, et al. Attrition in the 

Longitudinal Aging Study Amsterdam. The effect of 

differential inclusion in side studies. J Clin Epidemiol 

2002;55(4):319-28. 

Full Text: Exclude - risk factor out of scope 
G-9

den Heijer T, Launer LJ, Prins ND, et al. Association 

between blood pressure, white matter lesions, and atrophy 

of the medial temporal lobe. Neurology 2005;64(2):263-7. 

Full Text: Exclude - outcomes non-specific AD 

Deschamps V, Astier X, Ferry M, et al. Nutritional status of 

healthy elderly persons living in Dordogne, France, and 

relation with mortality and cognitive or functional decline. 

Eur J Clin Nutr 2002;56(4):305-12. 

Full Text: Exclude - observational N < 300 

Desmond DW, Tatemichi TK, Paik M, et al. Risk factors 

for cerebrovascular disease as correlates of cognitive 

function in a stroke-free cohort. Arch Neurol 

1993;50(2):162-6. 

Full Text: Exclude - observational N<300 

desRosiers G, Hodges JR, Berrios G. The 

neuropsychological differentiation of patients with very 

mild Alzheimer's disease and/or major depression. J Am 

Geriatr Soc 1995;43(11):1256-63. 

Full Text: Exclude - dementia @ baseline 

Devi G, Massimi S, Schultz S, et al. A double-blind, 

placebo-controlled trial of donepezil for the treatment of 

menopause-related cognitive loss. Gender Medicine 

2007;4(4):352-8. 

Full Text: Exclude - RCT N<50 

Devore EE, Stampfer MJ, Breteler MM, et al. Dietary fat 

intake and cognitive decline in women with type 2 diabetes. 

Diabetes Care 2009;32(4):635-40. 

Full Text: Exclude - dementia @ baseline 

Di Bari M, Pahor M, Franse LV, et al. Dementia and 

disability outcomes in large hypertension trials: lessons 

learned from the systolic hypertension in the elderly 

program (SHEP) trial. Am J Epidemiol 2001;153(1):72-8. 

Full Text: Exclude - not cognitive outcomes 

Di Bari M, Salti F, Nardi M, et al. Undertreatment of 

hypertension in community-dwelling older adults: a drugutilization study in Dicomano, Italy. J Hypertens 

1999;17(11):1633-40. 

Full Text: Exclude - not longitudinal 

Diener HC, Sacco RL, Yusuf S, et al. Effects of aspirin 

plus extended-release dipyridamole versus clopidogrel and 

telmisartan on disability and cognitive function after 

recurrent stroke in patients with ischaemic stroke in the 

Prevention Regimen for Effectively Avoiding Second 

Strokes (PRoFESS) trial: a double-blind, active and 

placebo-controlled study. Lancet Neurol 2008;7(10):875-

84. 

Full Text: Exclude - risk factor out of scope 

Dik M, Deeg DJ, Visser M, et al. Early life physical 

activity and cognition at old age. J Clin Exp Neuropsychol 

2003;25(5):643-53. 

Full Text: Exclude - not longitudinal 

Dik MG, Jonker C, Comijs HC, et al. Contribution of 

metabolic syndrome components to cognition in older 

individuals. Diabetes Care 2007;30(10):2655-60. 

Full Text: Exclude - not longitudinal 

Dik MG, Jonker C, Hack CE, et al. Serum inflammatory 

proteins and cognitive decline in older persons. Neurology 

2005;64(8):1371-7. 

Full Text: Exclude - risk factor out of scope 

Doll R, Peto R, Boreham J, et al. Smoking and dementia in 

male British doctors: prospective study. BMJ 

2000;320(7242):1097-102. 

Full Text: Exclude - outcomes non-specific AD 

Doraiswamy P, Steffens D, McQuoid D. Statin use and 

hippocampal volumes in elderly subjects at risk for 

Alzheimer's disease: a pilot observational study. Am J 

Alzheimers Dis Other Demen 2004;19(5):275-8. 

Full Text: Exclude - not longitudinal 

Dorner T, Kranz A, Zettl-Wiedner K, et al. The effect of 

structured strength and balance training on cognitive 

function in frail, cognitive impaired elderly long-term care 

residents. Aging Clin Exp Res 2007;19(5):400-5. 

Full Text: Exclude - selected population 

Dotson VM, Resnick SM, Zonderman AB. Differential 

association of concurrent, baseline, and average depressive 

symptoms with cognitive decline in older adults. Am J 

Geriatr Psychiatry 2008;16(4):318-30. 

Full Text: Exclude - Q2 continuous data only 

Downhill JE, Jr., Robinson RG. Longitudinal assessment of 

depression and cognitive impairment following stroke. J 

Nerv Ment Dis 1994;182(8):425-31. 

Full Text: Exclude - not applicable population 

Draper K, Ponsford J. Cognitive functioning ten years 

following traumatic brain injury and rehabilitation. 

Neuropsychology 2008;22(5):618-25. 

Full Text: Exclude - <80% >= 50 yo 

Dufouil C, Alperovitch A, Tzourio C. Influence of 

education on the relationship between white matter lesions 

and cognition. Neurology 2003;60(5):831-6. 

Full Text: Exclude - risk factor out of scope 

Dufouil C, Ducimetiere P, Alperovitch A. Sex differences 

in the association between alcohol consumption and 

cognitive performance. EVA Study Group. Epidemiology 

of Vascular Aging. Am J Epidemiol 1997;146(5):405-12. 

Full Text: Exclude - not longitudinal 

Dufouil C, Richard F, Fievet N, et al. APOE genotype, 

cholesterol level, lipid-lowering treatment, and dementia: 

the Three-City Study. Neurology 2005;64(9):1531-8. 

Full Text: Exclude - dementia @ baseline 

Dunne MP, Macdonald D, Hartley LR. The effects of 

nicotine upon memory and problem solving performance. 

Physiol Behav 1986;37(6):849-54. 

Full Text: Exclude - <80% >= 50 yo 
G-10

Edelstein SL, Kritz-Silverstein D, Barrett-Connor E. 

Prospective association of smoking and alcohol use with 

cognitive function in an elderly cohort. J Womens Health 

1998;7(10):1271-81. 

Full Text: Exclude - outcome non-specific AD 

Elias MF, Elias PK, Sullivan LM, et al. Lower cognitive 

function in the presence of obesity and hypertension: the 

Framingham heart study. Int J Obes Relat Metab Disord 

2003;27(2):260-8. 

Full Text: Exclude - not longitudinal 

Elias MF, Elias PK, Sullivan LM, et al. Obesity, diabetes 

and cognitive deficit: The Framingham Heart Study. 

Neurobiol Aging 2005;26 Suppl 1:11-6. 

Full Text: Exclude - not longitudinal 

Elias MF, Robbins MA, Budge MM, et al. Arterial pulse 

wave velocity and cognition with advancing age. 

Hypertension 2009;53(4):668-73. 

Full Text: Exclude - Risk factor out of scope 

Elias MF, Robbins MA, Elias PK, et al. A longitudinal 

study of blood pressure in relation to performance on the 

Wechsler Adult Intelligence Scale. Health Psychol 

1998;17(6):486-93. 

Full Text: Exclude - observational N<300 

Elias MF, Sullivan LM, D'Agostino RB, et al. Framingham 

stroke risk profile and lowered cognitive performance. 

Stroke 2004;35(2):404-9. 

Full Text: Exclude - risk factor out of scope 

Elias MF, Sullivan LM, D'Agostino RB, et al. 

Homocysteine and cognitive performance in the 

Framingham offspring study: age is important. Am J 

Epidemiol 2005;162(7):644-53. 

Full Text: Exclude - not longitudinal 

Elias MF, Sullivan LM, Elias PK, et al. Left ventricular 

mass, blood pressure, and lowered cognitive performance 

in the Framingham offspring. Hypertension 

2007;49(3):439-45. 

Full Text: Exclude - risk factor out of scope 

Elias MF, Wolf PA, D'Agostino RB, et al. Untreated blood 

pressure level is inversely related to cognitive functioning: 

the Framingham Study. Am J Epidemiol 1993;138(6):353-

64. 

Full Text: Exclude - not longitudinal 

Elias PK, Elias MF, D'Agostino RB, et al. NIDDM and 

blood pressure as risk factors for poor cognitive 

performance. The Framingham Study. Diabetes Care 

1997;20(9):1388-95. 

Full Text: Exclude - not longitudinal 

Elias PK, Elias MF, Robbins MA, et al. Blood pressurerelated cognitive decline: does age make a difference? 

Hypertension 2004;44(5):631-6. 

Full Text: Exclude - risk factor out of scope 

Elkins JS, Johnston SC, Ziv E, et al. 

Methylenetetrahydrofolate reductase C677T polymorphism 

and cognitive function in older women. Am J Epidemiol 

2007;166(6):672-8. 

Full Text: Exclude - risk factor out of scope 

Elkins JS, Yaffe K, Cauley JA, et al. Pre-existing 

hypertension and the impact of stroke on cognitive 

function. Ann Neurol 2005;58(1):68-74. 

Full Text: Exclude - observational N<300 

Emery CF, Shermer RL, Hauck ER, et al. Cognitive and 

psychological outcomes of exercise in a 1-year follow-up 

study of patients with chronic obstructive pulmonary 

disease. Health Psychol 2003;22(6):598-604. 

Full Text: Exclude - RCT N<50 

Engelhart MJ, Ruitenberg A, Meijer J, et al. Plasma levels 

of antioxidants are not associated with Alzheimer's disease 

or cognitive decline. Dement Geriatr Cogn Disord 

2005;19(2-3):134-9. 

Full Text: Exclude - not longitudinal 

Eskelinen MH, Ngandu T, Helkala EL, et al. Fat intake at 

midlife and cognitive impairment later in life: a populationbased CAIDE study. Int J Geriatr Psychiatry 

2008;23(7):741-7. 

Full Text: Exclude - Not adequate reference standard 

Euser SM, Hofman A, Westendorp RG, et al. Serum uric 

acid and cognitive function and dementia. Brain 

2009;132(Pt 2):377-82. 

Full Text: Exclude - risk factor out of scope 

Euser SM, van Bemmel T, Schram MT, et al. The effect of 

age on the association between blood pressure and 

cognitive function later in life. J Am Geriatr Soc 

2009;57(7):1232-7. 

Full Text: Exclude - AD/CD f/u < 1 year 

Eussen SJ, de Groot LC, Joosten LW, et al. Effect of oral 

vitamin B-12 with or without folic acid on cognitive 

function in older people with mild vitamin B-12 deficiency: 

a randomized, placebo-controlled trial. Am J Clin Nutr 

2006;84(2):361-70. 

Full Text: Exclude - not applicable population 

Eussen SJ, Ferry M, Hininger I, et al. Five year changes in 

mental health and associations with vitamin B12/folate 

status of elderly Europeans. J Nutr Health Aging 

2002;6(1):43-50. 

Full Text: Exclude - observational N<300 

Evans MA, Golomb BA. Statin-associated adverse 

cognitive effects: survey results from 171 patients. 

Pharmacotherapy 2009;29(7):800-11. 

Full Text: Exclude - not applicable population 

Fabrigoule C, Letenneur L, Dartigues JF, et al. Social and 

leisure activities and risk of dementia: a prospective 

longitudinal study.[see comment]. J Am Geriatr Soc 
G-11

1995;43(5):485-90. 

Full Text: Exclude - <60% of dementia is AD 

Farmer ME, Kittner SJ, Abbott RD, et al. Longitudinally 

measured blood pressure, antihypertensive medication use, 

and cognitive performance: the Framingham Study. J Clin 

Epidemiol 1990;43(5):475-80. 

Full Text: Exclude - not longitudinal 

Farmer ME, Kittner SJ, Rae DS, et al. Education and 

change in cognitive function. The Epidemiologic 

Catchment Area Study. Ann Epidemiol 1995;5(1):1-7. 

Full Text: Exclude - dementia @ baseline 

Farmer ME, White LR, Kittner SJ, et al. 

Neuropsychological test performance in Framingham: a 

descriptive study. Psychol Rep 1987;60(3 Pt 2):1023-40. 

Full Text: Exclude - not longitudinal 

Faxen-Irving G, Andren-Olsson B, Geijerstam A, et al. 

Nutrition education for care staff and possible effects on 

nutritional status in residents of sheltered accommodation. 

Eur J Clin Nutr 2005;59(8):947-54. 

Full Text: Exclude - selected population 

Fernandes MA, Proenca MT, Nogueira AJ, et al. Influence 

of apolipoprotein E genotype on blood redox status of 

Alzheimer's disease patients. Int J Mol Med 1999;4(2):179-

86. 

Full Text: Exclude - dementia @ baseline 

File SE, Hartley DE, Elsabagh S, et al. Cognitive 

improvement after 6 weeks of soy supplements in 

postmenopausal women is limited to frontal lobe function. 

Menopause 2005;12(2):193-201. 

Full Text: Exclude - AD/CD f/u < 1 yr 

Finkel D, Andel R, Gatz M, et al. The role of occupational 

complexity in trajectories of cognitive aging before and 

after retirement. Psychol Aging 2009;24(3):563-73. 

Full Text: Exclude - risk factor out of scope (occupational 

complexity) 

Finkel D, Reynolds CA, McArdle JJ, et al. The longitudinal 

relationship between processing speed and cognitive 

ability: genetic and environmental influences. Behav Genet 

2005;35(5):535-49. 

Full Text: Exclude - risk factor out of scope 

Fiocco AJ, Poirier J, Joober R, et al. Acute and long-term 

associations between ApoE genetic polymorphism, cortisol 

levels, and declarative memory performance in older 

adults. Psychoneuroendocrinology 2008;33(5):625-33. 

Full Text: Exclude - observational N<300 

Fischer P, Zehetmayer S, Bauer K, et al. Relation between 

vascular risk factors and cognition at age 75. Acta Neurol 

Scand 2006;114(2):84-90. 

Full Text: Exclude - not longitudinal 

Fitzpatrick AL, Buchanan CK, Nahin RL, et al. 

Associations of gait speed and other measures of physical 

function with cognition in a healthy cohort of elderly 

persons. J Gerontol A Biol Sci Med Sci 2007;62(11):1244-

51. 

Full Text: Exclude - risk factor out of scope 

Fleisher AS, Sowell BB, Taylor C, et al. Clinical predictors 

of progression to Alzheimer disease in amnestic mild 

cognitive impairment. Neurology 2007;68(19):1588-95. 

Full Text: Exclude - risk factor out of scope 

Fletcher AE, Battersby C, Adnitt P, et al. Quality of life on 

antihypertensive therapy: a double-blind trial comparing 

quality of life on pinacidil and nifedipine in combination 

with a thiazide diuretic. European Pinacidil Study Group. J 

Cardiovasc Pharmacol 1992;20(1):108-14. 

Full Text: Exclude - risk factor out of scope 

Fluck E, File SE, Rymer J. Cognitive effects of 10 years of 

hormone-replacement therapy with tibolone. J Clin 

Psychopharmacol 2002;22(1):62-7. 

Full Text: Exclude - observational N<300 

Fogari R, Mugellini A, Zoppi A, et al. Influence of losartan 

and atenolol on memory function in very elderly 

hypertensive patients. J Hum Hypertens 2003;17(11):781-

5. 

Full Text: Exclude - AD/CD f/u < 1 yr 

Fogari R, Mugellini A, Zoppi A, et al. Effect of 

telmisartan/hydrochlorothiazide vs 

lisinopril/hydrochlorothiazide combination on ambulatory 

blood pressure and cognitive function in elderly 

hypertensive patients. J Hum Hypertens 2006;20(3):177-

85. 

Full Text: Exclude - AD/CD f/u < 1 yr 

Fogari R, Mugellini A, Zoppi A, et al. Effects of valsartan 

compared with enalapril on blood pressure and cognitive 

function in elderly patients with essential hypertension. Eur 

J Clin Pharmacol 2004;59(12):863-8. 

Full Text: Exclude - AD/CD f/u < 1 yr 

Foley DJ, Masaki K, White L, et al. Sleep-disordered 

breathing and cognitive impairment in elderly JapaneseAmerican men. Sleep 2003;26(5):596-9. 

Full Text: Exclude - AD/CD f/u < 1 yr 

Ford AB, Mefrouche Z, Friedland RP, et al. Smoking and 

cognitive impairment: a population-based study. J Am 

Geriatr Soc 1996;44(8):905-9. 

Full Text: Exclude - SPMSQ single test 

Forti P, Maioli F, Pisacane N, et al. Atrial fibrillation and 

risk of dementia in non-demented elderly subjects with and 

without mild cognitive impairment. Neurol Res 

2006;28(6):625-9. 

Full Text: Exclude - risk factor out of scope 

Forti P, Maioli F, Pisacane N, et al. Atrial fibrillation and 

risk of dementia in non-demented elderly subjects with and 

without mild cognitive impairment (MCI). Arch Gerontol 

Geriatr 2007;44 Suppl 1:155-65. 
G-12

Full Text: Exclude - risk factor out of scope 

Fournier LR, Ryan Borchers TA, Robison LM, et al. The 

effects of soy milk and isoflavone supplements on 

cognitive performance in healthy, postmenopausal women. 

J Nutr Health Aging 2007;11(2):155-64. 

Full Text: Exclude - AD/CD f/u < 1 yr 

Frederiksen H, Gaist D, Bathum L, et al. Angiotensin Iconverting enzyme (ACE) gene polymorphism in relation 

to physical performance, cognition and survival--a followup study of elderly Danish twins. Ann Epidemiol 

2003;13(1):57-65. 

Full Text: Exclude - not longitudinal 

French LR, Schuman LM, Mortimer JA, et al. A casecontrol study of dementia of the Alzheimer type. Am J 

Epidemiol 1985;121(3):414-21. 

Full Text: Exclude - dementia @ baseline 

Friedland RP, Fritsch T, Smyth KA, et al. Patients with 

Alzheimer's disease have reduced activities in midlife 

compared with healthy control-group members. Proc Natl 

Acad Sci U S A 2001;98(6):3440-5. 

Full Text: Exclude - not longitudinal 

Fritsch T, Smyth KA, McClendon MJ, et al. Associations 

between dementia/mild cognitive impairment and cognitive 

performance and activity levels in youth. J Am Geriatr Soc 

2005;53(7):1191-6. 

Full Text: Exclude - <60% of dementia is AD 

Fujishima M, Kiyohara Y. Incidence and risk factors of 

dementia in a defined elderly Japanese population: the 

Hisayama study. Ann N Y Acad Sci 2002;977:1-8. 

Full Text: Exclude - not longitudinal 

Gabryelewicz T, Styczynska M, Luczywek E, et al. The 

rate of conversion of mild cognitive impairment to 

dementia: predictive role of depression. Int J Geriatr 

Psychiatry 2007;22(6):563-7. 

Full Text: Exclude - non-Western country 

Gale CR, Martyn CN, Cooper C. Cognitive impairment and 

mortality in a cohort of elderly people. BMJ 

1996;312(7031):608-11. 

Full Text: Exclude - risk factor out of scope 

Gallacher JE, Pickering J, Elwood PC, et al. 

Glucoregulation has greater impact on cognitive 

performance than macro-vascular disease in men with type 

2 diabetes: data from the Caerphilly study. Eur J Epidemiol 

2005;20(9):761-8. 

Full Text: Exclude - not longitudinal 

Gallo JJ, Rebok GW, Tennsted S, et al. Linking depressive 

symptoms and functional disability in late life. Aging Ment 

Health 2003;7(6):469-80. 

Full Text: Exclude - risk factor out of scope 

Ganguli M, Du Y, Dodge HH, et al. Depressive symptoms 

and cognitive decline in late life: a prospective 

epidemiological study. Arch Gen Psychiatry 

2006;63(2):153-60. 

Full Text: Exclude - Q2 continuous data only 

Ganguli M, Seaberg EC, Ratcliff GG, et al. Cognitive 

stability over 2 years in a rural elderly population: the 

MoVIES project. Neuroepidemiology 1996;15(1):42-50. 

Full Text: Exclude - risk factor out of scope 

Gao L, Matthews FE, Sargeant LA, et al. An investigation 

of the population impact of variation in HbA1c levels in 

older people in England and Wales: from a population 

based multi-centre longitudinal study. BMC Public Health 

2008;8:54. 

Full Text: Exclude - <60% of dementia is AD 

Gao S, Jin Y, Unverzagt FW, et al. Hypertension and 

cognitive decline in rural elderly Chinese. J Am Geriatr Soc 

2009;57(6):1051-7. 

Full Text: Exclude - non-Western country 

Garcia A, Haron Y, Pulman K, et al. Increases in 

homocysteine are related to worsening of stroop scores in 

healthy elderly persons: a prospective follow-up study. J 

Gerontol A Biol Sci Med Sci 2004;59(12):1323-7. 

Full Text: Exclude - observational N<300 

Gatto NM, Henderson VW, St John JA, et al. Metabolic 

syndrome and cognitive function in healthy middle-aged 

and older adults without diabetes. Neuropsychol Dev Cogn 

B Aging Neuropsychol Cogn 2008;15(5):627-41. 

Full Text: Exclude - not longitudinal 

Gatz M, Reynolds CA, Fratiglioni L, et al. Role of genes 

and environments for explaining Alzheimer disease. Arch 

Gen Psychiatry 2006;63(2):168-74. 

Full Text: Exclude - not longitudinal 

Gatz M, Svedberg P, Pedersen NL, et al. Education and the 

risk of Alzheimer's disease: findings from the study of 

dementia in Swedish twins. J Gerontol B Psychol Sci Soc 

Sci 2001;56(5):P292-300. 

Full Text: Exclude - observational N<300 

Gaw A, Murray H, Brown EA. Plasma lipoprotein(a) 

[Lp(a)] concentrations and cardiovascular events in the 

elderly: evidence from the prospective study of pravastatin 

in the elderly at risk (PROSPER). Atherosclerosis 

2005;180(2):381-8. 

Full Text: Exclude - risk factor out of scope 

Geerlings MI, Schmand B, Braam AW, et al. Depressive 

symptoms and risk of Alzheimer's disease in more highly 

educated older people. J Am Geriatr Soc 2000;48(9):1092-

7. 

Full Text: Exclude - risk factor out of scope 

Geerlings MI, Schmand B, Jonker C, et al. Education and 

incident Alzheimer's disease: a biased association due to 

selective attrition and use of a two-step diagnostic 

procedure? Int J Epidemiol 1999;28(3):492-7. 

Full Text: Exclude - methods paper 
G-13

Gengo F, Cwudzinski D, Kinkel P, et al. Effects of 

treatment with lovastatin and pravastatin on daytime 

cognitive performance. Clin Cardiol 1995;18(4):209-14. 

Full Text: Exclude - RCT N<50 

Gerstorf D, Lovden M, Rocke C, et al. Well-being affects 

changes in perceptual speed in advanced old age: 

longitudinal evidence for a dynamic link. Dev Psychol 

2007;43(3):705-18. 

Full Text: Exclude - outcomes unacceptably assessed 

Ghisletta P, Bickel JF, Lovden M. Does activity 

engagement protect against cognitive decline in old age? 

Methodological and analytical considerations. J Gerontol B 

Psychol Sci Soc Sci 2006;61(5):P253-61. 

Full Text: Exclude - outcomes unacceptably assessed 

Gibellato M, Moore J, Selby K, et al. Effects of lovastatin 

and pravastatin on cognitive function in military aircrew. 

Aviat Space Environ Med 2001;72(9):805-12. 

Full Text: Exclude - not applicable population 

Giem P, Beeson WL, Fraser GE. The incidence of dementia 

and intake of animal products: preliminary findings from 

the Adventist Health Study. Neuroepidemiology 

1993;12(1):28-36. 

Full Text: Exclude - risk factor out of scope 

Gill SS, Anderson GM, Fischer HD, et al. Syncope and its 

consequences in patients with dementia receiving 

cholinesterase inhibitors: a population-based cohort study. 

Arch Intern Med 2009;169(9):867-73. 

Full Text: Exclude - dementia @ baseline 

Gillette-Guyonnet S, Andrieu S, Nourhashemi F, et al. 

Cognitive impairment and composition of drinking water in 

women: findings of the EPIDOS Study. Am J Clin Nutr 

2005;81(4):897-902. 

Full Text: Exclude - outcomes inadequately assessed 

Glaso M, Nordbo G, Diep L, et al. Reduced concentrations 

of several vitamins in normal weight patients with lateonset dementia of the Alzheimer type without vascular 

disease. J Nutr Health Aging 2004;8(5):407-13. 

Full Text: Exclude - observational N<300 

Glei DA, Landau DA, Goldman N, et al. Participating in 

social activities helps preserve cognitive function: an 

analysis of a longitudinal, population-based study of the 

elderly. Int J Epidemiol 2005;34(4):864-71. 

Full Text: Exclude - outcomes unacceptably assessed 

Gliebus G, Lippa CF. The influence of beta-blockers on 

delayed memory function in people with cognitive 

impairment. Am J Alzheimers Dis Other Demen 

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Full Text: Exclude - no placebo comparator 

Gluck MA, Myers CE, Nicolle MM, et al. Computational 

models of the hippocampal region: implications for 

prediction of risk for Alzheimer's disease in non-demented 

elderly. Curr Alzheimer Res 2006;3(3):247-57. 

Full Text: Exclude - risk factor out of scope 

Gold DP, Andres D, Etezadi J, et al. Structural equation 

model of intellectual change and continuity and predictors 

of intelligence in older men.[erratum appears in Psychol 

Aging 1998 Sep;13(3):434]. Psychol Aging 

1995;10(2):294-303. 

Full Text: Exclude - not longitudinal 

Goldbourt U, Schnaider-Beeri M, Davidson M. 

Socioeconomic status in relationship to death of vascular 

disease and late-life dementia. J Neurol Sci 2007;257(1-

2):177-81. 

Full Text: Exclude - no AD outcomes 

Goldstein G, Materson BJ, Cushman WC, et al. Treatment 

of hypertension in the elderly: II. Cognitive and behavioral 

function. Results of a Department of Veterans Affairs 

Cooperative Study. Hypertension 1990;15(4):361-9. 

Full Text: Exclude - no placebo comparator 

Golomb BA, Criqui MH, White H, et al. Conceptual 

foundations of the UCSD Statin Study: a randomized 

controlled trial assessing the impact of statins on cognition, 

behavior, and biochemistry. Arch Intern Med 

2004;164(2):153-62. 

Full Text: Exclude - no primary data (methods paper) 

Gomez-Isla T, Blesa R, Boada M, et al. A randomized, 

double-blind, placebo controlled-trial of triflusal in mild 

cognitive impairment: the TRIMCI study. Alzheimer Dis 

Assoc Disord 2008;22(1):21-9. 

Full Text: Exclude - risk factor out of scope 

Goodwin JS, Regan M. Cognitive dysfunction associated 

with naproxen and ibuprofen in the elderly. Arthritis 

Rheum 1982;25(8):1013-5. 

Full Text: Exclude - not applicable population 

Goodwin JS, Sanchez CJ, Thomas P, et al. Alcohol intake 

in a healthy elderly population. Am J Public Health 

1987;77(2):173-7. 

Full Text: Exclude - risk factor out of scope 

Gorelick PB, Brody J, Cohen D, et al. Risk factors for 

dementia associated with multiple cerebral infarcts. A casecontrol analysis in predominantly African-American 

hospital-based patients. Arch Neurol 1993;50(7):714-20. 

Full Text: Exclude - selected population 

Gow AJ, Johnson W, Pattie A, et al. Mental ability in 

childhood and cognitive aging. Gerontology 

2008;54(3):177-86. 

Full Text: Exclude - not longitudinal 

Grassi V, Carminati L, Cossi S, et al. [Chronic obstructive 

lung disease. Systemic manifestations]. Recenti Prog Med 

2003;94(5):217-26. 

Full Text: Exclude - non-English 

Graves AB, Larson EB, Edland SD, et al. Prevalence of 
G-14

dementia and its subtypes in the Japanese American 

population of King County, Washington state. The Kame 

Project. Am J Epidemiol 1996;144(8):760-71. 

Full Text: Exclude - not longitudinal 

Gray SL, Hanlon JT, Landerman LR, et al. Is antioxidant 

use protective of cognitive function in the communitydwelling elderly? Am J Geriatr Pharmacother 2003;1(1):3-

10. 

Full Text: Exclude - SPMSQ single test 

Green HJ, Pakenham KI, Headley BC, et al. Quality of life 

compared during pharmacological treatments and clinical 

monitoring for non-localized prostate cancer: a randomized 

controlled trial. BJU Int 2004;93(7):975-9. 

Full Text: Exclude - not applicable population 

Greendale GA, Kritz-Silverstein D, Seeman T, et al. Higher 

basal cortisol predicts verbal memory loss in 

postmenopausal women: Rancho Bernardo Study. J Am 

Geriatr Soc 2000;48(12):1655-8. 

Full Text: Exclude - risk factor out of scope 

Grodstein F, Chen J, Willett WC. High-dose antioxidant 

supplements and cognitive function in community-dwelling 

elderly women. Am J Clin Nutr 2003;77(4):975-84. 

Full Text: Exclude - not longitudinal 

Grodstein F, Chen J, Wilson RS, et al. Type 2 diabetes and 

cognitive function in community-dwelling elderly women. 

Diabetes Care 2001;24(6):1060-5. 

Full Text: Exclude - not longitudinal 

Grodstein F, Kang JH, Glynn RJ, et al. A randomized trial 

of beta carotene supplementation and cognitive function in 

men: the Physicians' Health Study II. Arch Intern Med 

2007;167(20):2184-90. 

Full Text: Exclude - not longitudinal 

Guo Z, Fratiglioni L, Winblad B, et al. Blood pressure and 

performance on the Mini-Mental State Examination in the 

very old. Cross-sectional and longitudinal data from the 

Kungsholmen Project. Am J Epidemiol 

1997;145(12):1106-13. 

Full Text: Exclude - dementia @ baseline 

Guo Z, Fratiglioni L, Zhu L, et al. Occurrence and 

progression of dementia in a community population aged 

75 years and older: relationship of antihypertensive 

medication use. Arch Neurol 1999;56(8):991-6. 

Full Text: Exclude - <60% of dementia is AD 

Gupta R, Solanki RK, Pathak V. Blood pressure is 

associated with cognitive impairment in young 

hypertensives. World J Biol Psychiatry 2008;9(1):43-50. 

Full Text: Exclude - non-Western country 

Gurland BJ, Teresi J, Smith WM, et al. Effects of treatment 

for isolated systolic hypertension on cognitive status and 

depression in the elderly. J Am Geriatr Soc 

1988;36(11):1015-22. 

Full Text: Exclude - covered in existing systematic review 

Guskiewicz KM, Marshall SW, Bailes J, et al. Association 

between recurrent concussion and late-life cognitive 

impairment in retired professional football players. 

Neurosurgery 2005;57(4):719-26; discussion 719-26. 

Full Text: Exclude - <60% of dementia is AD 

Gussekloo J, Heijmans BT, Slagboom PE, et al. 

Thermolabile methylenetetrahydrofolate reductase gene 

and the risk of cognitive impairment in those over 85. J 

Neurol Neurosurg Psychiatry 1999;67(4):535-8. 

Full Text: Exclude - observational N<300 

Haan MN, Miller JW, Aiello AE, et al. Homocysteine, B 

vitamins, and the incidence of dementia and cognitive 

impairment: results from the Sacramento Area Latino 

Study on Aging. Am J Clin Nutr 2007;85(2):511-7. 

Full Text: Exclude - non-specific dementia in analyses 

Hailpern SM, Melamed ML, Cohen HW, et al. Moderate 

chronic kidney disease and cognitive function in adults 20 

to 59 years of age: Third National Health and Nutrition 

Examination Survey (NHANES III). J Am Soc Nephrol 

2007;18(7):2205-13. 

Full Text: Exclude - risk factor out of scope 

Hajjar I, Catoe H, Sixta S, et al. Cross-sectional and 

longitudinal association between antihypertensive 

medications and cognitive impairment in an elderly 

population. J Gerontol A Biol Sci Med Sci 2005;60(1):67-

73. 

Full Text: Exclude - dementia @ baseline 

Hajjar I, Schumpert J, Hirth V, et al. The impact of the use 

of statins on the prevalence of dementia and the 

progression of cognitive impairment. J Gerontol A Biol Sci 

Med Sci 2002;57(7):M414-8. 

Full Text: Exclude - not longitudinal 

Hall CB, Lipton RB, Sliwinski M, et al. Cognitive activities 

delay onset of memory decline in persons who develop 

dementia. Neurology 2009;73(5):356-61. 

Full Text: Exclude - observational N<300 

Halyburton AK, Brinkworth GD, Wilson CJ, et al. Lowand high-carbohydrate weight-loss diets have similar 

effects on mood but not cognitive performance. Am J Clin 

Nutr 2007;86(3):580-7. 

Full Text: Exclude - AD/CD f/u < 1 yr 

Hamidovic A, Kang UJ, de Wit H. Effects of low to 

moderate acute doses of pramipexole on impulsivity and 

cognition in healthy volunteers. J Clin Psychopharmacol 

2008;28(1):45-51. 

Full Text: Excluded - risk factor out of scope 

Han C, Jo SA, Seo JA, et al. Adiposity parameters and 

cognitive function in the elderly: application of "Jolly Fat" 

hypothesis to cognition. Arch Gerontol Geriatr 

2009;49(2):e133-8. 

Full Text: Exclude - non-Western country 
G-15

Han L, Agostini JV, Allore HG. Cumulative anticholinergic 

exposure is associated with poor memory and executive 

function in older men. J Am Geriatr Soc 2008;56(12):2203-

10. 

Full Text: Exclude - risk factor out of scope 

Hanlon JT, Schmader KE, Landerman LR, et al. Relation 

of prescription nonsteroidal antiinflammatory drug use to 

cognitive function among community-dwelling elderly. 

Ann Epidemiol 1997;7(2):87-94. 

Full Text: Exclude - SPMSQ single test 

Hanon O, Berrou JP, Negre-Pages L, et al. Effects of 

hypertension therapy based on eprosartan on systolic 

arterial blood pressure and cognitive function: primary 

results of the Observational Study on Cognitive function 

And Systolic Blood Pressure Reduction open-label study. J 

Hypertens 2008;26(8):1642-50. 

Full Text: Exclude - not longitudinal 

Hanon O, Pequignot R, Seux ML, et al. Relationship 

between antihypertensive drug therapy and cognitive 

function in elderly hypertensive patients with memory 

complaints. J Hypertens 2006;24(10):2101-7. 

Full Text: Exclude - selected population 

Harris SE, Fox H, Wright AF, et al. The brain-derived 

neurotrophic factor Val66Met polymorphism is associated 

with age-related change in reasoning skills. Mol Psychiatry 

2006;11(5):505-13. 

Full Text: Exclude - not applicable population 

Hartley DE, Elsabagh S, File SE. Gincosan (a combination 

of Ginkgo biloba and Panax ginseng): the effects on mood 

and cognition of 6 and 12 weeks' treatment in postmenopausal women. Nutr Neurosci 2004;7(5-6):325-33. 

Full Text: Exclude - not longitudinal 

Hassing LB, Grant MD, Hofer SM, et al. Type 2 diabetes 

mellitus contributes to cognitive decline in old age: a 

longitudinal population-based study. J Int Neuropsychol 

Soc 2004;10(4):599-607. 

Full Text: Exclude - observational N< 300 

Hassing LB, Hofer SM, Nilsson SE, et al. Comorbid type 2 

diabetes mellitus and hypertension exacerbates cognitive 

decline: evidence from a longitudinal study. Age Ageing 

2004;33(4):355-61. 

Full Text: Exclude - observational N<300 

Hastings EC, West RL. The relative success of a self-help 

and a group-based memory training program for older 

adults. Psychol Aging 2009;24(3):586-94. 

Full Text: Exclude - AD/CD f/u < 1 year 

Hatch SL, Feinstein L, Link BG, et al. The continuing 

benefits of education: adult education and midlife cognitive 

ability in the British 1946 birth cohort. J Gerontol B 

Psychol Sci Soc Sci 2007;62(6):S404-14. 

Full Text: Exclude - not longitudinal 

Hayashi T, Nomura H, Osawa M, et al. Nitric oxide 

metabolites are associated with survival in older patients. J 

Am Geriatr Soc 2007;55(9):1398-403. 

Full Text: Exclude - risk factor out of scope 

Hayward L, Mant A, Eyland A, et al. Sleep disordered 

breathing and cognitive function in a retirement village 

population. Age Ageing 1992;21(2):121-8. 

Full Text: Exclude - observational N<300 

Heckbert SR, Longstreth WT, Jr., Psaty BM, et al. The 

association of antihypertensive agents with MRI white 

matter findings and with Modified Mini-Mental State 

Examination in older adults. J Am Geriatr Soc 

1997;45(12):1423-33. 

Full Text: Exclude - not longitudinal 

Heitner J, Dickson D. Diabetics do not have increased 

Alzheimer-type pathology compared with age-matched 

control subjects. A retrospective postmortem 

immunocytochemical and histofluorescent study. 

Neurology 1997;49(5):1306-11. 

Full Text: Exclude - outcomes unacceptably assessed 

Helbecque N, Codron V, Cottel D, et al. An apolipoprotein 

A-I gene promoter polymorphism associated with cognitive 

decline, but not with Alzheimer's disease. Dement Geriatr 

Cogn Disord 2008;25(2):97-102. 

Full Text: Exclude - not applicable population 

Helmer C, Peuchant E, Letenneur L, et al. Association 

between antioxidant nutritional indicators and the incidence 

of dementia: results from the PAQUID prospective cohort 

study. Eur J Clin Nutr 2003;57(12):1555-61. 

Full Text: Exclude - <60% of dementia is AD 

Henderson AS, Jorm AF, Christensen H, et al. Aspirin, 

anti-inflammatory drugs and risk of dementia. Int J Geriatr 

Psychiatry 1997;12(9):926-30. 

Full Text: Exclude - <60% of dementia is AD 

Henderson AS, Jorm AF, Mackinnon A, et al. A survey of 

dementia in the Canberra population: experience with ICD10 and DSM-III-R criteria. Psychol Med 1994;24(2):473-

82. 

Full Text: Exclude - risk factor out of scope 

Henderson VW, Guthrie JR, Dennerstein L. Serum lipids 

and memory in a population based cohort of middle age 

women. J Neurol Neurosurg Psychiatry 2003;74(11):1530-

5. 

Full Text: Exclude - <60% of dementia is AD 

Henderson VW, Guthrie JR, Dudley EC, et al. Estrogen 

exposures and memory at midlife: a population-based study 

of women. Neurology 2003;60(8):1369-71. 

Full Text: Exclude - <60% of dementia is AD 

Hendrie HC, Hall KS, Ogunniyi A, et al. Alzheimer's 

disease, genes, and environment: the value of international 

studies. Can J Psychiatry 2004;49(2):92-9. 

Full Text: Exclude - not longitudinal 
G-16

Hengstermann S, Laemmler G, Hanemann A, et al. Total 

serum homocysteine levels do not identify cognitive 

dysfunction in multimorbid elderly patients. J Nutr Health 

Aging 2008;12(6):411-6. 

Full Text: Exclude - not longitudinal 

Hengstermann S, Laemmler G, Hanemann A, et al. Total 

serum homocysteine levels do not identify cognitive 

dysfunction in multimorbid elderly patients. J Nutr Health 

Aging 2009;13(2):121-6. 

Full Text: Exclude - not applicable population 

Hertzog C, Schaie KW, Gribbin K. Cardiovascular disease 

and changes in intellectual functioning from middle to old 

age. J Gerontol 1978;33(6):872-83. 

Full Text: Exclude - observational N<300 

Hestad KA, Engedal K. Antihypertensive medication is 

associated with less cognitive impairment in the very old 

with apolipoprotein-E epsilon4 allele. Drugs Aging 

2006;23(9):723-31. 

Full Text: Exclude - not longitudinal 

Heude B, Ducimetiere P, Berr C. Cognitive decline and 

fatty acid composition of erythrocyte membranes--The 

EVA Study. Am J Clin Nutr 2003;77(4):803-8. 

Full Text: Exclude - observational N<300 

Heun R, Kolsch H, Jessen F. Risk factors and early signs of 

Alzheimer's disease in a family study sample. Risk of AD. 

Eur Arch Psychiatry Clin Neurosci 2006;256(1):28-36. 

Full Text: Exclude - not applicable population 

Heyer EJ, Wilson DA, Sahlein DH, et al. APOE-epsilon4 

predisposes to cognitive dysfunction following 

uncomplicated carotid endarterectomy. Neurology 

2005;65(11):1759-63. 

Full Text: Exclude - selected population 

Hillen T, Lun A, Reischies FM, et al. DHEA-S plasma 

levels and incidence of Alzheimer's disease. Biol 

Psychiatry 2000;47(2):161-3. 

Full Text: Exclude - observational N<300 

Himanen L, Portin R, Isoniemi H, et al. Longitudinal 

cognitive changes in traumatic brain injury: a 30-year 

follow-up study. Neurology 2006;66(2):187-92. 

Full Text: Exclude - observational N<300 

Ho SC, Chan AS, Ho YP, et al. Effects of soy isoflavone 

supplementation on cognitive function in Chinese 

postmenopausal women: a double-blind, randomized, 

controlled trial. Menopause 2007;14(3 Pt 1):489-99. 

Full Text: Exclude - AD/CD f/u < 1 yr 

Hofer SM, Christensen H, Mackinnon AJ, et al. Change in 

cognitive functioning associated with apoE genotype in a 

community sample of older adults. Psychol Aging 

2002;17(2):194-208. 

Full Text: Exclude - observational N<300 

Hoffman LB, Schmeidler J, Lesser GT, et al. Less 

Alzheimer disease neuropathology in medicated 

hypertensive than nonhypertensive persons. Neurology 

2009;72(20):1720-6. 

Full Text: Exclude - not applicable population 

Hofman A, Ott A, Breteler MM, et al. Atherosclerosis, 

apolipoprotein E, and prevalence of dementia and 

Alzheimer's disease in the Rotterdam Study.[see comment]. 

Lancet 1997;349(9046):151-4. 

Full Text: Exclude - risk factor out of scope 

Hogervorst E, Sadjimim T, Yesufu A, et al. High tofu 

intake is associated with worse memory in elderly 

Indonesian men and women. Dement Geriatr Cogn Disord 

2008;26(1):50-7. 

Full Text: Exclude - non-Western country 

Hohaus L. Remembering to age successfully: evaluation of 

a successful aging approach to memory enhancement. Int 

Psychogeriatr 2007;19(1):137-50. 

Full Text: Exclude - AD/CD f/u < 1 yr 

Honig LS, Tang MX, Albert S, et al. Stroke and the risk of 

Alzheimer disease. Arch Neurol 2003;60(12):1707-12. 

Full Text: Exclude - risk factor out of scope 

Houlihan LM, Harris SE, Luciano M, et al. Replication 

study of candidate genes for cognitive abilities: the Lothian 

Birth Cohort 1936. Genes Brain Behav 2009;8(2):238-47. 

Full Text: Exclude - not longitudinal 

Howe MN, Price IR. Effects of transdermal nicotine on 

learning, memory, verbal fluency, concentration, and 

general health in a healthy sample at risk for dementia. Int 

Psychogeriatr 2001;13(4):465-75. 

Full Text: Exclude - AD/CD f/u < 1 yr 

Howe MN, Price IR. Effects of transdermal nicotine on 

learning, memory, verbal fluency, concentration, and 

general health in a healthy sample at risk for dementia. Int 

Psychogeriatr 2001;13(4):465-75. 

Full Text: Exclude - AD/CD f/u < 1 yr 

Hsu HC. Does social participation by the elderly reduce 

mortality and cognitive impairment? Aging Ment Health 

2007;11(6):699-707. 

Full Text: Exclude - SPMSQ single test 

Hu L, Yue Y, Zuo PP, et al. Evaluation of neuroprotective 

effects of long-term low dose hormone replacement therapy 

on postmenopausal women brain hippocampus using 

magnetic resonance scanner. Chin Med Sci J 

2006;21(4):214-8. 

Full Text: Exclude - non-Western country 

Huang CQ, Dong BR, Zhang YL, et al. Association of 

cognitive impairment with smoking, alcohol consumption, 

tea consumption, and exercise among Chinese 

nonagenarians/centenarians. Cogn Behav Neurol 

2009;22(3):190-6. 

Full Text: Exclude - non-Western country 
G-17

Hughes TF, Andel R, Small BJ, et al. The association 

between social resources and cognitive change in older 

adults: evidence from the Charlotte County Healthy Aging 

Study. J Gerontol B Psychol Sci Soc Sci 2008;63(4):P241-

P244. 

Full Text: Exclude - observational N<300 

Huijbregts PP, Feskens EJ, Rasanen L, et al. Dietary 

patterns and cognitive function in elderly men in Finland, 

Italy and The Netherlands. Eur J Clin Nutr 

1998;52(11):826-31. 

Full Text: Exclude - not longitudinal 

Hultsch DF, Hammer M, Small BJ. Age differences in 

cognitive performance in later life: relationships to selfreported health and activity life style. J Gerontol 

1993;48(1):P1-11. 

Full Text: Exclude - not longitudinal 

Hultsch DF, Hertzog C, Small BJ, et al. Use it or lose it: 

engaged lifestyle as a buffer of cognitive decline in aging? 

Psychol Aging 1999;14(2):245-63. 

Full Text: Exclude - observational N<300 

Incalzi RA, Corsonello A, Trojano L, et al. Cognitive 

training is ineffective in hypoxemic COPD: a six-month 

randomized controlled trial. Rejuvenation Res 

2008;11(1):239-50. 

Full Text: Exclude - selected population 

Israel L, Melac M, Milinkevitch D, et al. Drug therapy and 

memory training programs: a double-blind randomized trial 

of general practice patients with age-associated memory 

impairment. Int Psychogeriatr 1994;6(2):155-70. 

Full Text: Exclude - AD/CD f/u < 1 yr 

Jack CR, Jr., Petersen RC, Xu YC, et al. Prediction of AD 

with MRI-based hippocampal volume in mild cognitive 

impairment. Neurology 1999;52(7):1397-403. 

Full Text: Exclude - risk factor out of scope 

Jagger C, Matthews R, Matthews F, et al. The burden of 

diseases on disability-free life expectancy in later life. J 

Gerontol A Biol Sci Med Sci 2007;62(4):408-14. 

Full Text: Exclude - dementia @ baseline 

Jama JW, Launer LJ, Witteman JC, et al. Dietary 

antioxidants and cognitive function in a population-based 

sample of older persons. The Rotterdam Study. Am J 

Epidemiol 1996;144(3):275-80. 

Full Text: Exclude - not longitudinal 

Janke MC, Payne LL, Van Puymbroeck M. The role of 

informal and formal leisure activities in the disablement 

process. Int J Aging Hum Dev 2008;67(3):231-57. 

Full Text: Exclude - not relevant outcomes 

Jick H, Zornberg GL, Jick S, et al. Statins and the risk of 

dementia. Lancet 2000;356(9242):1627-31. 

Full Text: Exclude - outcome non-specific AD 

Johnson EJ, McDonald K, Caldarella SM, et al. Cognitive 

findings of an exploratory trial of docosahexaenoic acid 

and lutein supplementation in older women. Nutr Neurosci 

2008;11(2):75-83. 

Full Text: Exclude - AD/CD f/u < 1 yr 

Johnson KC, Margolis KL, Espeland MA, et al. A 

prospective study of the effect of hypertension and baseline 

blood pressure on cognitive decline and dementia in 

postmenopausal women: the Women's Health Initiative 

Memory Study. J Am Geriatr Soc 2008;56(8):1449-58. 

Full Text: Exclude - <60% of dementia is AD 

Jonsson L, Gerth W, Fastbom J. The potential economic 

consequences of cognitive improvement with losartan. 

Blood Press 2002;11(1):46-52. 

Full Text: Exclude - outcomes not AD/CD 

Jorissen BL, Brouns F, Van Boxtel MP, et al. The influence 

of soy-derived phosphatidylserine on cognition in ageassociated memory impairment. Nutr Neurosci 

2001;4(2):121-34. 

Full Text: Exclude - AD/CD f/u < 1 yr 

Kadoi Y, Goto F. Factors associated with postoperative 

cognitive dysfunction in patients undergoing cardiac 

surgery. Surg Today 2006;36(12):1053-7. 

Full Text: Exclude - selected population 

Kagan A, Popper JS, Rhoads GG. Factors related to stroke 

incidence in Hawaii Japanese men. The Honolulu Heart 

Study. Stroke 1980;11(1):14-21. 

Full Text: Exclude - not applicable population 

Kahonen MH, Tilvis RS, Jolkkonen J, et al. Predictors and 

clinical significance of declining plasma 

dehydroepiandrosterone sulfate in old age. Aging (Milano) 

2000;12(4):308-14. 

Full Text: Exclude - observational N<300 

Kahonen-Vare M, Brunni-Hakala S, Lindroos M, et al. Left 

ventricular hypertrophy and blood pressure as predictors of 

cognitive decline in old age. Aging Clin Exp Res 

2004;16(2):147-52. 

Full Text: Exclude - observational N<300 

Kalaydjian A, Zandi PP, Swartz KL, et al. How migraines 

impact cognitive function: findings from the Baltimore 

ECA. Neurology 2007;68(17):1417-24. 

Full Text: Exclude - risk factor out of scope 

Kalmijn S, Feskens EJ, Launer LJ, et al. Glucose 

intolerance, hyperinsulinaemia and cognitive function in a 

general population of elderly men. Diabetologia 

1995;38(9):1096-102. 

Full Text: Exclude - not longitudinal 

Kalmijn S, Foley D, White L, et al. Metabolic 

cardiovascular syndrome and risk of dementia in JapaneseAmerican elderly men. The Honolulu-Asia aging study. 

Arterioscler Thromb Vasc Biol 2000;20(10):2255-60. 

Full Text: Exclude - RF not assessed adequately 
G-18

Kalmijn S, Launer LJ, Stolk RP, et al. A prospective study 

on cortisol, dehydroepiandrosterone sulfate, and cognitive 

function in the elderly. J Clin Endocrinol Metab 

1998;83(10):3487-92. 

Full Text: Exclude - observational N<300 

Kalmijn S, van Boxtel MP, Ocke M, et al. Dietary intake of 

fatty acids and fish in relation to cognitive performance at 

middle age. Neurology 2004;62(2):275-80. 

Full Text: Exclude - not longitudinal 

Kanoni S, Dedoussis GV. Design and descriptive 

characteristics of the GHRAS: the Greek Health 

Randomized Aging Study. Med Sci Monit 

2008;14(4):CR204-12. 

Full Text: Exclude - Outcomes not AD/CD 

Kanowski S, Hoerr R. Ginkgo biloba extract EGb 761 in 

dementia: intent-to-treat analyses of a 24-week, multicenter, double-blind, placebo-controlled, randomized trial. 

Pharmacopsychiatry 2003;36(6):297-303. 

Full Text: Exclude - dementia @ baseline 

Karlamangla AS, Singer BH, Chodosh J, et al. Urinary 

cortisol excretion as a predictor of incident cognitive 

impairment. Neurobiol Aging 2005;26 Suppl 1:80-4. 

Full Text: Exclude - risk factor out of scope 

Karlamangla AS, Singer BH, Reuben DB, et al. Increases 

in serum non-high-density lipoprotein cholesterol may be 

beneficial in some high-functioning older adults: 

MacArthur studies of successful aging. J Am Geriatr Soc 

2004;52(4):487-94. 

Full Text: Exclude - observational N<300 

Katsuya T, Baba S, Ishikawa K, et al. Epsilon 4 allele of 

apolipoprotein E gene associates with lower blood pressure 

in young Japanese subjects: the Suita Study. J Hypertens 

2002;20(10):2017-21. 

Full Text: Exclude - Outcomes not AD/CD 

Kearney-Schwartz A, Rossignol P, Bracard S, et al. 

Vascular structure and function is correlated to cognitive 

performance and white matter hyperintensities in older 

hypertensive patients with subjective memory complaints. 

Stroke 2009;40(4):1229-36. 

Full Text: Exclude - AD/CD f/u < 1 yr 

Keenan PA, Jacobson MW, Soleymani RM, et al. The 

effect on memory of chronic prednisone treatment in 

patients with systemic disease. Neurology 

1996;47(6):1396-402. 

Full Text: Exclude - AD/CD f/u < 1 yr 

Kenny AM, Bellantonio S, Gruman CA, et al. Effects of 

transdermal testosterone on cognitive function and health 

perception in older men with low bioavailable testosterone 

levels. J Gerontol A Biol Sci Med Sci 2002;57(5):M321-5. 

Full Text: Exclude - RCT N<50 

Kharrazi H, Vaisi-Raygani A, Rahimi Z, et al. Association 

between enzymatic and non-enzymatic antioxidant defense 

mechanism with apolipoprotein E genotypes in Alzheimer 

disease. Clin Biochem 2008;41(12):932-6. 

Full Text: Exclude - dementia @ baseline 

Kilander L, Nyman H, Boberg M, et al. Hypertension is 

related to cognitive impairment: a 20-year follow-up of 999 

men. Hypertension 1998;31(3):780-6. 

Full Text: Exclude - not longitudinal 

Kilander L, Nyman H, Boberg M, et al. Cognitive function, 

vascular risk factors and education. A cross-sectional study 

based on a cohort of 70-year-old men. J Intern Med 

1997;242(4):313-21. 

Full Text: Exclude - not longitudinal 

Kim JM, Stewart R, Kim SW, et al. Changes in folate, 

vitamin B12 and homocysteine associated with incident 

dementia. J Neurol Neurosurg Psychiatry 2008;79(8):864-

8. 

Full Text: Exclude - dementia @ baseline 

Kim JM, Stewart R, Prince M, et al. Dental health, 

nutritional status and recent-onset dementia in a Korean 

community population. Int J Geriatr Psychiatry 

2007;22(9):850-5. 

Full Text: Exclude - risk factor out of scope 

King R, Travers C, O'Neill S, et al. The influence of 

postmenopausal hormone replacement therapy on cognitive 

functioning: results from an observational study. J Br 

Menopause Soc 2004;10(3):103-7. 

Full Text: Exclude - not longitudinal 

Kinsella GJ, Mullaly E, Rand E, et al. Early intervention 

for mild cognitive impairment: a randomised controlled 

trial. J Neurol Neurosurg Psychiatry 2009;80(7):730-6. 

Full Text: Exclude - AD/CD f/u < 1 yr 

Kivipelto M, Annerbo S, Hultdin J, et al. Homocysteine 

and holo-transcobalamin and the risk of dementia and 

Alzheimers disease: a prospective study. Eur J Neurol 

2009;16(7):808-13. 

Full Text: Exclude - observational N<300 

Kivipelto M, Helkala EL, Hanninen T, et al. Midlife 

vascular risk factors and late-life mild cognitive 

impairment: A population-based study. Neurology 

2001;56(12):1683-9. 

Full Text: Exclude - outcomes assessed inadequately 

Klonoff H, Clark C, Kavanagh-Gray D, et al. Two-year 

follow-up study of coronary bypass surgery. Psychologic 

status, employment status, and quality of life. J Thorac 

Cardiovasc Surg 1989;97(1):78-85. 

Full Text: Exclude - not applicable population 

Knecht S, Wersching H, Lohmann H, et al. How much does 

hypertension affect cognition?: explained variance in crosssectional analysis of non-demented community-dwelling 

individuals in the SEARCH study. J Neurol Sci 

2009;283(1-2):149-52. 

Full Text: Exclude - not longitudinal 
G-19

Knight RG, McMahon J, Skeaff CM, et al. Reliable Change 

Index scores for persons over the age of 65 tested on 

alternate forms of the Rey AVLT. Arch Clin Neuropsychol 

2007;22(4):513-8. 

Full Text: Exclude - risk factor out of scope 

Knopman DS. Hypertension and late-life dementia: A real 

link? Neurology 2009;72(20):1716-7. 

Full Text: Exclude - no data, editorial 

Komulainen P, Lakka TA, Kivipelto M, et al. Metabolic 

syndrome and cognitive function: a population-based 

follow-up study in elderly women. Dement Geriatr Cogn 

Disord 2007;23(1):29-34. 

Full Text: Exclude - observational N<300 

Koontz J, Baskys A. Effects of galantamine on working 

memory and global functioning in patients with mild 

cognitive impairment: a double-blind placebo-controlled 

study. Am J Alzheimers Dis Other Demen 2005;20(5):295-

302. 

Full Text: Exclude - RCT N<50 

Korf ES, White LR, Scheltens P, et al. Brain aging in very 

old men with type 2 diabetes: the Honolulu-Asia Aging 

Study. Diabetes Care 2006;29(10):2268-74. 

Full Text: Exclude - risk factor out of scope 

Korten AE, Henderson AS, Christensen H, et al. A 

prospective study of cognitive function in the elderly. 

Psychol Med 1997;27(4):919-30. 

Full Text: Exclude - risk factor out of scope 

Kostis JB, Rosen R, Wilson A. Central nervous system 

effects of HMG CoA reductase inhibitors: lovastatin and 

pravastatin on sleep and cognitive performance in patients 

with hypercholesterolemia. J Clin Pharmacol 

1994;34(10):989-96. 

Full Text: Exclude - RCT N<50 

Kotani S, Sakaguchi E, Warashina S, et al. Dietary 

supplementation of arachidonic and docosahexaenoic acids 

improves cognitive dysfunction. Neurosci Res 

2006;56(2):159-64. 

Full Text: Exclude - dementia @ baseline 

Kreijkamp-Kaspers S, Kok L, Grobbee DE, et al. Dietary 

phytoestrogen intake and cognitive function in older 

women. J Gerontol A Biol Sci Med Sci 2007;62(5):556-62. 

Full Text: Exclude - not longitudinal 

Kritz-Silverstein D, Von Muhlen D, Barrett-Connor E, et 

al. Isoflavones and cognitive function in older women: the 

SOy and Postmenopausal Health In Aging (SOPHIA) 

Study. Menopause 2003;10(3):196-202. 

Full Text: Exclude - AD/CD f/u < 1 yr 

Kuningas M, de Rijk RH, Westendorp RG, et al. Mental 

performance in old age dependent on cortisol and genetic 

variance in the mineralocorticoid and glucocorticoid 

receptors. Neuropsychopharmacology 2007;32(6):1295-

301. 

Full Text: Exclude - risk factor out of scope 

Kurinami H, Sato N, Shinohara M, et al. Prevention of 

amyloid beta-induced memory impairment by fluvastatin, 

associated with the decrease in amyloid beta accumulation 

and oxidative stress in amyloid beta injection mouse model. 

Int J Mol Med 2008;21(5):531-7. 

Full Text: Exclude - not applicable population 

Kurt M, Bekci B, Karakas S. Hormone replacement therapy 

and cognitive function in postmenopausal women. 

Maturitas 2006;53(1):39-48. 

Full Text: Exclude - non-Western country 

Kurtz MM, Gerraty RT. A meta-analytic investigation of 

neurocognitive deficits in bipolar illness: profile and effects 

of clinical state. Neuropsychology 2009;23(5):551-62. 

Full Text: Exclude - not applicable population 

Kuusisto J, Koivisto K, Mykkanen L, et al. Association 

between features of the insulin resistance syndrome and 

Alzheimer's disease independently of apolipoprotein E4 

phenotype: cross sectional population based study. BMJ 

1997;315(7115):1045-9. 

Full Text: Exclude - not longitudinal 

La Rue A, Koehler KM, Wayne SJ, et al. Nutritional status 

and cognitive functioning in a normally aging sample: a 6-y 

reassessment. Am J Clin Nutr 1997;65(1):20-9. 

Full Text: Exclude - observational N<300 

Laitala VS, Kaprio J, Koskenvuo M, et al. Coffee drinking 

in middle age is not associated with cognitive performance 

in old age. Am J Clin Nutr 2009;90(3):640-6. 

Full Text: Exclude - outcomes inadequately assessed 

Landi F, Cesari M, Onder G, et al. Non-steroidal antiinflammatory drug (NSAID) use and Alzheimer disease in 

community-dwelling elderly patients. Am J Geriatr 

Psychiatry 2003;11(2):179-85. 

Full Text: Exclude - dementia @ baseline 

Landi F, Russo A, Liperoti R, et al. Anticholinergic drugs 

and physical function among frail elderly population. Clin 

Pharmacol Ther 2007;81(2):235-41. 

Full Text: Exclude - risk factor out of scope 

Lane R, He Y, Morris C, et al. BuChE-K and APOE 

epsilon4 allele frequencies in Lewy body dementias, and 

influence of genotype and hyperhomocysteinemia on 

cognitive decline. Mov Disord 2009;24(3):392-400. 

Full Text: Exclude - selected population 

Lang IA, Llewellyn DJ, Langa KM, et al. Neighborhood 

deprivation, individual socioeconomic status, and cognitive 

function in older people: analyses from the English 

Longitudinal Study of Ageing. J Am Geriatr Soc 

2008;56(2):191-8. 

Full Text: Exclude - not longitudinal 

Langbaum JB, Rebok GW, Bandeen-Roche K, et al. 
G-20

Predicting memory training response patterns: results from 

ACTIVE. J Gerontol B Psychol Sci Soc Sci 2009;64(1):14-

23. 

Full Text: Exclude - secondary analysis of data 

Lasser NL, Nash J, Lasser VI, et al. Effects of 

antihypertensive therapy on blood pressure control, 

cognition, and reactivity. A placebo-controlled comparison 

of prazosin, propranolol, and hydrochlorothiazide. Am J 

Med 1989;86(1B):98-103. 

Full Text: Exclude - AD/CD f/u < 1 yr 

Launer LJ, Dinkgreve MA, Jonker C, et al. Are age and 

education independent correlates of the Mini-Mental State 

Exam performance of community-dwelling elderly? J 

Gerontol 1993;48(6):P271-7. 

Full Text: Exclude - not longitudinal 

Launer LJ, Masaki K, Petrovitch H, et al. The association 

between midlife blood pressure levels and late-life 

cognitive function. The Honolulu-Asia Aging Study. 

JAMA 1995;274(23):1846-51. 

Full Text: Exclude - not longitudinal 

Laurin D, Verreault R, Lindsay J, et al. Omega-3 fatty acids 

and risk of cognitive impairment and dementia. J 

Alzheimers Dis 2003;5(4):315-22. 

Full Text: Exclude - observational N<300 

Lechevallier-Michel N, Molimard M, Dartigues JF, et al. 

Drugs with anticholinergic properties and cognitive 

performance in the elderly: results from the PAQUID 

Study. Br J Clin Pharmacol 2005;59(2):143-51. 

Full Text: Exclude - not longitudinal 

Lee BK, Glass TA, McAtee MJ, et al. Associations of 

salivary cortisol with cognitive function in the Baltimore 

memory study. Arch Gen Psychiatry 2007;64(7):810-8. 

Full Text: Exclude - risk factor out of scope 

Lee H, Wintermark M, Gean AD, et al. Focal lesions in 

acute mild traumatic brain injury and neurocognitive 

outcome: CT versus 3T MRI. J Neurotrauma 

2008;25(9):1049-56. 

Full Text: Exclude - risk factor out of scope 

Lee JY, Chang SM, Jang HS, et al. Illiteracy and the 

incidence of Alzheimer's disease in the Yonchon County 

survey, Korea. Int Psychogeriatr 2008;20(5):976-85. 

Full Text: Exclude - risk factor out of scope 

Lee L, Kang SA, Lee HO, et al. Relationships between 

dietary intake and cognitive function level in Korean 

elderly people. Public Health 2001;115(2):133-8. 

Full Text: Exclude - non-Western country 

Lee LK, Shahar S, Rajab N. Serum folate concentration, 

cognitive impairment, and DNA damage among elderly 

individuals in Malaysia. Nutr Res 2009;29(5):327-34. 

Full Text: Exclude - non-Western country 

Leibovici D, Ritchie K, Ledesert B, et al. The effects of 

wine and tobacco consumption on cognitive performance in 

the elderly: a longitudinal study of relative risk. Int J 

Epidemiol 1999;28(1):77-81. 

Full Text: Exclude - observational N<300 

Leibson CL, Rocca WA, Hanson VA, et al. Risk of 

dementia among persons with diabetes mellitus: a 

population-based cohort study. Am J Epidemiol 

1997;145(4):301-8. 

Full Text: Exclude - outcomes unacceptably assessed 

Lessov-Schlaggar CN, Reed T, Swan GE, et al. Association 

of sex steroid hormones with brain morphology and 

cognition in healthy elderly men. Neurology 

2005;65(10):1591-6. 

Full Text: Exclude - not longitudinal 

Letenneur L, Dartigues JF, Commenges D, et al. Tobacco 

consumption and cognitive impairment in elderly people. A 

population-based study. Ann Epidemiol 1994;4(6):449-54. 

Full Text: Exclude - not longitudinal 

Levine B, Stuss DT, Winocur G, et al. Cognitive 

rehabilitation in the elderly: effects on strategic behavior in 

relation to goal management. J Int Neuropsychol Soc 

2007;13(1):143-52. 

Full Text: Exclude - RCT N<50 

Li G, Cherrier MM, Tsuang DW, et al. Salivary cortisol 

and memory function in human aging. Neurobiol Aging 

2006;27(11):1705-14. 

Full Text: Exclude - risk factor out of scope 

Llewellyn DJ, Lang IA, Langa KM, et al. Exposure to 

secondhand smoke and cognitive impairment in nonsmokers: national cross sectional study with cotinine 

measurement. BMJ 2009;338:b462. 

Full Text: Exclude - risk factor out of scope 

Llewellyn DJ, Lang IA, Xie J, et al. Framingham Stroke 

Risk Profile and poor cognitive function: a populationbased study. BMC Neurol 2008;8:12. 

Full Text: Exclude - not longitudinal 

Louis WJ, Mander AG, Dawson M, et al. Use of 

computerized neuropsychological tests (CANTAB) to 

assess cognitive effects of antihypertensive drugs in the 

elderly. Cambridge Neuropsychological Test Automated 

Battery. J Hypertens 1999;17(12 Pt 2):1813-9. 

Full Text: Exclude - AD/CD f/u < 1 yr 

Luchsinger JA, Tang MX, Mayeux R. Glycemic load and 

risk of Alzheimer's disease. J Nutr Health Aging 

2007;11(3):238-41. 

Full Text: Exclude - risk factor out of scope 

Luchsinger JA, Tang MX, Miller J, et al. Higher folate 

intake is related to lower risk of Alzheimer's disease in the 

elderly. J Nutr Health Aging 2008;12(9):648-50. 

Full Text: Exclude - summary duplicate of study outcomes 

Luchsinger JA, Tang MX, Shea S, et al. Hyperinsulinemia 
G-21

and risk of Alzheimer disease. Neurology 2004;63(7):1187-

92. 

Full Text: Exclude - risk factor out of scope 

Luchsinger JA, Tang MX, Siddiqui M, et al. Alcohol intake 

and risk of dementia. J Am Geriatr Soc 2004;52(4):540-6. 

Full Text: Exclude - risk factor out of acope 

Luciano M, Gow AJ, Harris SE, et al. Cognitive ability at 

age 11 and 70 years, information processing speed, and 

APOE variation: the Lothian Birth Cohort 1936 study. 

Psychol Aging 2009;24(1):129-38. 

Full Text: Exclude - not longitudinal 

Luciano M, Gow AJ, Taylor MD, et al. Apolipoprotein E is 

not related to memory abilities at 70 years of age. Behav 

Genet 2009;39(1):6-14. 

Full Text: Exclude - outcomes unacceptably assessed 

Lupien S, Lecours AR, Lussier I, et al. Basal cortisol levels 

and cognitive deficits in human aging. J Neurosci 

1994;14(5 Pt 1):2893-903. 

Full Text: Exclude - risk factor out of scope 

Lupien SJ, Schwartz G, Ng YK, et al. The Douglas 

Hospital Longitudinal Study of Normal and Pathological 

Aging: summary of findings. J Psychiatry Neurosci 

2005;30(5):328-34. 

Full Text: Exclude - risk factor out of scope 

Luukinen H, Viramo P, Koski K, et al. Head injuries and 

cognitive decline among older adults: a population-based 

study. Neurology 1999;52(3):557-62. 

Full Text: Exclude - not longitudinal 

MacKenzie SM, Dewar D, Stewart W, et al. The 

transcription of steroidogenic genes in the human 

cerebellum and hippocampus: a comparative survey of 

normal and Alzheimer's tissue. J Endocrinol 

2008;196(1):123-30. 

Full Text: Exclude - not applicable population 

MacLullich AM, Deary IJ, Starr JM, et al. Plasma cortisol 

levels, brain volumes and cognition in healthy elderly men. 

Psychoneuroendocrinology 2005;30(5):505-15. 

Full Text: Exclude - risk factor out of scope 

Madden DJ, Blumenthal JA, Allen PA, et al. Improving 

aerobic capacity in healthy older adults does not necessarily 

lead to improved cognitive performance. Psychol Aging 

1989;4(3):307-20. 

Full Text: Exclude - AD/CD f/u < 1 yr 

Mainous AG, 3rd, Eschenbach SL, Wells BJ, et al. 

Cholesterol, transferrin saturation, and the development of 

dementia and Alzheimer's disease: results from an 18-year 

population-based cohort. Fam Med 2005;37(1):36-42. 

Full Text: Exclude - outcomes unacceptably assessed 

Maioli F, Coveri M, Pagni P, et al. Conversion of mild 

cognitive impairment to dementia in elderly subjects: a 

preliminary study in a memory and cognitive disorder unit. 

Arch Gerontol Geriatr 2007;44 Suppl 1:233-41. 

Full Text: Exclude - observational N<300 

Mak Z, Kim JM, Stewart R. Leg length, cognitive 

impairment and cognitive decline in an African-Caribbean 

population. Int J Geriatr Psychiatry 2006;21(3):266-72. 

Full Text: Exclude - observational N<300 

Malaguarnera M, Ferri R, Bella R, et al. Homocysteine, 

vitamin B12 and folate in vascular dementia and in 

Alzheimer disease. Clin Chem Lab Med 2004;42(9):1032-

5. 

Full Text: Exclude - dementia @ baseline 

Mandal B, Roe B. Job loss, retirement and the mental 

health of older Americans. J Ment Health Policy Econ 

2008;11(4):167-76. 

Full Text: Exclude - outcomes not acceptably assessed 

Manly JJ, Bell-McGinty S, Tang MX, et al. Implementing 

diagnostic criteria and estimating frequency of mild 

cognitive impairment in an urban community. Arch Neurol 

2005;62(11):1739-46. 

Full Text: Exclude - risk factor out of scope 

Manly JJ, Touradji P, Tang MX, et al. Literacy and 

memory decline among ethnically diverse elders. J Clin 

Exp Neuropsychol 2003;25(5):680-90. 

Full Text: Exclude - observational N<300 

Manzato E, Roselli della Rovere G, Zambon S, et al. 

Cognitive functions are not affected by dietary fatty acids 

in elderly subjects in the Pro.V.A. study population. Aging 

Clin Exp Res 2003;15(1):83-6. 

Full Text: Exclude - observational N<300 

Marcellini F, Giuli C, Papa R, et al. Zinc status, 

psychological and nutritional assessment in old people 

recruited in five European countries: Zincage study. 

Biogerontology 2006;7(5-6):339-45. 

Full Text: Exclude - not longitudinal 

Marcopulos B, McLain C. Are our norms "normal"? A 4-

year follow-up study of a biracial sample of rural elders 

with low education. Clin Neuropsychol 2003;17(1):19-33. 

Full Text: Exclude - observational N<300 

Marder K. Vitamin E and donepezil for the treatment of 

mild cognitive impairment. Curr Neurol Neurosci Rep 

2005;5(5):337-8. 

Full Text: Exclude - no primary data 

Mariani E, Monastero R, Ercolani S, et al. Vascular risk 

factors in mild cognitive impairment subtypes. Findings 

from the ReGAl project. Dement Geriatr Cogn Disord 

2007;24(6):448-56. 

Full Text: Exclude - observational N<300 

Marin DB, Breuer B, Marin ML, et al. The relationship 

between apolipoprotein E, dementia, and vascular illness. 

Atherosclerosis 1998;140(1):173-80. 

Full Text: Exclude - dementia @ baseline 
G-22

Marklund N, Peltonen M, Nilsson TK, et al. Low and high 

circulating cortisol levels predict mortality and cognitive 

dysfunction early after stroke. J Intern Med 

2004;256(1):15-21. 

Full Text: Exclude - risk factor out of scope 

Martin CK, Anton SD, Han H, et al. Examination of 

cognitive function during six months of calorie restriction: 

results of a randomized controlled trial. Rejuvenation Res 

2007;10(2):179-90. 

Full Text: Exclude - AD/CD f/u < 1 yr 

Maruyama M, Matsui T, Tanji H, et al. Cerebrospinal fluid 

tau protein and periventricular white matter lesions in 

patients with mild cognitive impairment: implications for 2 

major pathways. Arch Neurol 2004;61(5):716-20. 

Full Text: Exclude - risk factor out of scope 

Marx BP, Brailey K, Proctor SP, et al. Association of time 

since deployment, combat intensity, and posttraumatic 

stress symptoms with neuropsychological outcomes 

following Iraq war deployment. Arch Gen Psychiatry 

2009;66(9):996-1004. 

Full Text: Exclude - risk factor out of scope 

Mas E, Dupuy AM, Artero S, et al. Functional Vitamin E 

deficiency in ApoE4 patients with Alzheimer's disease. 

Dement Geriatr Cogn Disord 2006;21(3):198-204. 

Full Text: Exclude - dementia @ baseline 

Masley S, Roetzheim R, Gualtieri T. Aerobic exercise 

enhances cognitive flexibility. J Clin Psychol Med Settings 

2009;16(2):186-93. 

Full Text: Exclude - <80% >= 50 yo 

Mathieu A, Mazza S, Decary A, et al. Effects of obstructive 

sleep apnea on cognitive function: a comparison between 

younger and older OSAS patients. Sleep Med 

2008;9(2):112-20. 

Full Text: Exclude - observational N<300 

Mauri M, Sinforiani E, Bono G, et al. Interaction between 

Apolipoprotein epsilon 4 and traumatic brain injury in 

patients with Alzheimer's disease and Mild Cognitive 

Impairment. Funct Neurol 2006;21(4):223-8. 

Full Text: Exclude - observational N<300 

May FE, Moore MT, Stewart RB, et al. Lack of association 

of nonsteroidal anti-inflammatory drug use and cognitive 

decline in the elderly. Gerontology 1992;38(5):275-9. 

Full Text: Exclude - not longitudinal 

Mazza M, Capuano A, Bria P, et al. Ginkgo biloba and 

donepezil: a comparison in the treatment of Alzheimer's 

dementia in a randomized placebo-controlled double-blind 

study. Eur J Neurol 2006;13(9):981-5. 

Full Text: Exclude - dementia @ baseline 

McCaddon A, Hudson P, Davies G, et al. Homocysteine 

and cognitive decline in healthy elderly. Dement Geriatr 

Cogn Disord 2001;12(5):309-13. 

Full Text: Exclude - observational N<300 

McEntee WJ, Crook TH, Jenkyn LR, et al. Treatment of 

age-associated memory impairment with guanfacine. 

Psychopharmacol Bull 1991;27(1):41-6. 

Full Text: Exclude - AD/CD f/u < 1 yr 

McGeer PL, McGeer EG. The inflammatory response 

system of brain: implications for therapy of Alzheimer and 

other neurodegenerative diseases. Brain Research - Brain 

Research Reviews 1995;21(2):195-218. 

Full Text: Exclude - not longitudinal 

McGue M, Christensen K. Social activity and healthy 

aging: a study of aging Danish twins. Twin Res Hum Genet 

2007;10(2):255-65. 

Full Text: Exclude - dementia @ baseline 

McGuire LC, Ajani UA, Ford ES. Cognitive functioning in 

late life: the impact of moderate alcohol consumption. Ann 

Epidemiol 2007;17(2):93-9. 

Full Text: Exclude - not longitudinal 

McGurn B, Deary IJ, Starr JM. Childhood cognitive ability 

and risk of late-onset Alzheimer and vascular dementia. 

Neurology 2008;71(14):1051-6. 

Full Text: Exclude - not longitudinal 

McIlroy SP, Dynan KB, Lawson JT, et al. Moderately 

elevated plasma homocysteine, methylenetetrahydrofolate 

reductase genotype, and risk for stroke, vascular dementia, 

and Alzheimer disease in Northern Ireland. Stroke 

2002;33(10):2351-6. 

Full Text: Exclude - dementia @ baseline 

McLaurin EY, Holliday SL, Williams P, et al. Predictors of 

cognitive dysfunction in patients with systemic lupus 

erythematosus. Neurology 2005;64(2):297-303. 

Full Text: Exclude - not applicable population 

McLay RN, Maki PM, Lyketsos CG. Nulliparity and late 

menopause are associated with decreased cognitive decline. 

J Neuropsychiatry Clin Neurosci 2003;15(2):161-7. 

Full Text: Exclude - risk factor out of scope 

McMorris T, Mielcarz G, Harris RC, et al. Creatine 

supplementation and cognitive performance in elderly 

individuals. Neuropsychol Dev Cogn B Aging 

Neuropsychol Cogn 2007;14(5):517-28. 

Full Text: Exclude - risk factor out of scope 

Meinert CL, McCaffrey LD, Breitner JC. Alzheimer's 

Disease Anti-inflammatory Prevention Trial: design, 

methods, and baseline results. Alzheimers Dement 

2009;5(2):93-104. 

Full Text: Exclude - risk factor out of scope 

Mendelsohn AB, Belle SH, Stoehr GP, et al. Use of 

antioxidant supplements and its association with cognitive 

function in a rural elderly cohort: the MoVIES Project. 

Monongahela Valley Independent Elders Survey. Am J 

Epidemiol 1998;148(1):38-44. 
G-23

Full Text: Exclude - not longitudinal 

Menec VH. The relation between everyday activities and 

successful aging: a 6-year longitudinal study. Journals of 

Gerontology Series B-Psychological Sciences & Social 

Sciences 2003;58(2):S74-82. 

Full Text: Exclude - outcomes unacceptably assessed 

Meyer JS, Rauch G, Rauch RA, et al. Risk factors for 

cerebral hypoperfusion, mild cognitive impairment, and 

dementia. Neurobiol Aging 2000;21(2):161-9. 

Full Text: Exclude - observational N<300 

Meyer JS, Rauch GM, Crawford K, et al. Risk factors 

accelerating cerebral degenerative changes, cognitive 

decline and dementia. Int J Geriatr Psychiatry 

1999;14(12):1050-61. 

Full Text: Exclude - observational N<300 

Meyer JS, Rauch GM, Rauch RA, et al. Cardiovascular and 

other risk factors for Alzheimer's disease and vascular 

dementia. Ann N Y Acad Sci 2000;903:411-23. 

Full Text: Exclude - observational N<300 

Middleton LE, Kirkland SA, Maxwell CJ, et al. Exercise: a 

potential contributing factor to the relationship between 

folate and dementia. J Am Geriatr Soc 2007;55(7):1095-8. 

Full Text: Exclude - observational N<300 

Mielke MM, Zandi PP, Sjogren M, et al. High total 

cholesterol levels in late life associated with a reduced risk 

of dementia. Neurology 2005;64(10):1689-95. 

Full Text: Exclude - <60% of dementia is AD 

Milders M, Ietswaart M, Crawford JR, et al. Impairments in 

theory of mind shortly after traumatic brain injury and at 1-

year follow-up. Neuropsychology 2006;20(4):400-8. 

Full Text: Exclude - <80% >= 50 yo 

Millar K, Nicoll JA, Thornhill S, et al. Long term 

neuropsychological outcome after head injury: relation to 

APOE genotype. J Neurol Neurosurg Psychiatry 

2003;74(8):1047-52. 

Full Text: Exclude - -<80% >= 50 yo 

Min SK, Moon IW, Ko RW, et al. Effects of transdermal 

nicotine on attention and memory in healthy elderly nonsmokers. Psychopharmacology (Berl) 2001;159(1):83-8. 

Full Text: Exclude - AD/CD f/u < 1 yr 

Mitchell JL, Cruickshanks KJ, Klein BE, et al. 

Postmenopausal hormone therapy and its association with 

cognitive impairment. Arch Intern Med 

2003;163(20):2485-90. 

Full Text: Exclude - outcomes unacceptably assessed 

Mix JA, Crews WD, Jr. A double-blind, placebocontrolled, randomized trial of Ginkgo biloba extract EGb 

761 in a sample of cognitively intact older adults: 

neuropsychological findings. Hum Psychopharmacol 

2002;17(6):267-77. 

Full Text: Exclude - AD/CD f/u < 1 yr 

Miyasaka Y, Barnes ME, Petersen RC, et al. Risk of 

dementia in stroke-free patients diagnosed with atrial 

fibrillation: data from a community-based cohort. Eur Heart 

J 2007;28(16):1962-7. 

Full Text: Exclude - risk factor out of scope 

Mocchegiani E, Giacconi R, Costarelli L, et al. Zinc 

deficiency and IL-6 -174G/C polymorphism in old people 

from different European countries: effect of zinc 

supplementation. ZINCAGE study. Exp Gerontol 

2008;43(5):433-44. 

Full Text: Exclude - AD/CD f/u < 1 yr 

Moceri VM, Kukull WA, Emanuel I, et al. Early-life risk 

factors and the development of Alzheimer's disease. 

Neurology 2000;54(2):415-20. 

Full Text: Exclude - dementia @ baseline 

Moffat SD, Zonderman AB, Harman SM, et al. The 

relationship between longitudinal declines in 

dehydroepiandrosterone sulfate concentrations and 

cognitive performance in older men. Arch Intern Med 

2000;160(14):2193-8. 

Full Text: Exclude - <80% are >= 50 yo 

Moffat SD, Zonderman AB, Metter EJ, et al. Longitudinal 

assessment of serum free testosterone concentration 

predicts memory performance and cognitive status in 

elderly men. J Clin Endocrinol Metab 2002;87(11):5001-7. 

Full Text: Exclude - observational N<300 

Mooijaart SP, Gussekloo J, Frolich M, et al. Homocysteine, 

vitamin B-12, and folic acid and the risk of cognitive 

decline in old age: the Leiden 85-Plus study. Am J Clin 

Nutr 2005;82(4):866-71. 

Full Text: Exclude - dementia @ baseline 

Mori K, Inatomi S, Ouchi K, et al. Improving effects of the 

mushroom Yamabushitake (Hericium erinaceus) on mild 

cognitive impairment: a double-blind placebo-controlled 

clinical trial. Phytother Res 2009;23(3):367-72. 

Full Text: Exclude - AD/CD f/u < 1 yr 

Morris MS, Jacques PF, Rosenberg IH, et al. Folate and 

vitamin B-12 status in relation to anemia, macrocytosis, 

and cognitive impairment in older Americans in the age of 

folic acid fortification. Am J Clin Nutr 2007;85(1):193-

200. 

Full Text: Exclude - not longitudinal 

Morrison MF, Redei E, TenHave T, et al. 

Dehydroepiandrosterone sulfate and psychiatric measures 

in a frail, elderly residential care population. Biol 

Psychiatry 2000;47(2):144-50. 

Full Text: Exclude - selected population 

Mortel KF, Meyer JS, Herod B, et al. Education and 

occupation as risk factors for dementias of the Alzheimer 

and ischemic vascular types. Dementia 1995;6(1):55-62. 

Full Text: Exclude - dementia @ baseline 
G-24

Mortimer JA, Snowdon DA, Markesbery WR. Small head 

circumference is associated with less education in persons 

at risk for Alzheimer disease in later life. Alzheimer Dis 

Assoc Disord 2008;22(3):249-54. 

Full Text: Exclude - risk factor out of scope 

Muldoon MF, Barger SD, Ryan C, et al. Effects of 

lovastatin on cognitive function and psychological wellbeing. Am J Med 2000;108(7):538-46. 

Full Text: Exclude - <80% >= 50 yo 

Muldoon MF, Ryan CM, Sereika SM, et al. Randomized 

trial of the effects of simvastatin on cognitive functioning 

in hypercholesterolemic adults.[see comment]. Am J Med 

2004;117(11):823-9. 

Full Text: Exclude - AD/CD f/u < 1 yr 

Muldoon MF, Waldstein SR, Ryan CM, et al. Effects of six 

anti-hypertensive medications on cognitive performance. J 

Hypertens 2002;20(8):1643-52. 

Full Text: Exclude - <80% >= 50 yo 

Murray MD, Lane KA, Gao S, et al. Preservation of 

cognitive function with antihypertensive medications: a 

longitudinal analysis of a community-based sample of 

African Americans. Arch Intern Med 2002;162(18):2090-6. 

Full Text: Exclude - <60 of dementia is AD 

Natale V, Albertazzi P, Zini M, et al. Exploration of 

cyclical changes in memory and mood in postmenopausal 

women taking sequential combined oestrogen and 

progestogen preparations. BJOG 2001;108(3):286-90. 

Full Text: Exclude - sample not randomly assigned 

National Institute of Mental Health; University of Iowa. 

Cognitive Enhancers Explored with PET Imaging. In: 

ClinicalTrials.gov [Internet]. Bethesda (MD): National 

Library of Medicine (US). 2000- [cited 2009 Jul 09]. 

Available from: 

http://clinicaltrials.gov/ct/show/nct00042172. 2002. 

Full Text: Exclude - no primary data 

Nemetz PN, Leibson C, Naessens JM, et al. Traumatic 

brain injury and time to onset of Alzheimer's disease: a 

population-based study. Am J Epidemiol 1999;149(1):32-

40. 

Full Text: Exclude - outcomes unacceptably assessed 

Newman GC, Bang H, Hussain SI, et al. Association of 

diabetes, homocysteine, and HDL with cognition and 

disability after stroke. Neurology 2007;69(22):2054-62. 

Full Text: Exclude - outcomes unacceptably assessed 

Newman MF, Grocott HP, Mathew JP, et al. Report of the 

substudy assessing the impact of neurocognitive function 

on quality of life 5 years after cardiac surgery. Stroke 

2001;32(12):2874-81. 

Full Text: Exclude - risk factor out of scope 

Nguyen HT, Black SA, Ray LA, et al. Predictors of decline 

in MMSE scores among older Mexican Americans. J 

Gerontol A Biol Sci Med Sci 2002;57(3):M181-5. 

Full Text: Exclude - dementia @ baseline 

Nilson LN, Backman L, Sallsten G, et al. Dose-related 

cognitive deficits among floor layers with previous heavy 

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17. 

Full Text: Exclude - observational N<300 

Nilsson K, Gustafson L, Hultberg B. Relation between 

plasma homocysteine and Alzheimer's disease. Dement 

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Full Text: Exclude - dementia @ baseline 

Nilsson K, Gustafson L, Hultberg B. Plasma homocysteine, 

cobalamin/folate status, and vascular disease in a large 

population of psychogeriatric patients. Dement Geriatr 

Cogn Disord 2006;22(4):358-66. 

Full Text: Exclude - selected population 

Nilsson P, Gullberg G, Ekesbo R, et al. No impaired 

cognitive function in treated patients with mild-moderate 

hypertension compared to normotensive controls. Blood 

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Full Text: Exclude - observational N<300 

Nilsson SE, Johansson B, Takkinen S, et al. Does aspirin 

protect against Alzheimer's dementia? A study in a 

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J Clin Pharmacol 2003;59(4):313-9. 

Full Text: Exclude - outcomes unacceptably assessed 

Nilsson SE, Read S, Berg S, et al. Low systolic blood 

pressure is associated with impaired cognitive function in 

the oldest old: longitudinal observations in a populationbased sample 80 years and older. Aging Clin Exp Res 

2007;19(1):41-7. 

Full Text: Exclude - dementia @ baseline 

Nilsson SE, Takkinen S, Tryding N, et al. Association of 

biochemical values with morbidity in the elderly: a 

population-based Swedish study of persons aged 82 or 

more years. Scand J Clin Lab Invest 2003;63(7-8):457-66. 

Full Text: Exclude - dementia @ baseline 

Nishinaga M, Takata J, Okumiya K, et al. High morning 

home blood pressure is associated with a loss of functional 

independence in the community-dwelling elderly aged 75 

years or older. Hypertens Res 2005;28(8):657-63. 

Full Text: Exclude - not longitudinal 

Nolin P. Executive memory dysfunctions following mild 

traumatic brain injury. J Head Trauma Rehabil 

2006;21(1):68-75. 

Full Text: Exclude - <80% are >= 50 yo 

Nooyens AC, van Gelder BM, Verschuren WM. Smoking 

and cognitive decline among middle-aged men and women: 

the Doetinchem Cohort Study. Am J Public Health 

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Full Text: Exclude - <80% >= 50 yo 

Novartis. Efficacy and safety of Rivastigmine in patients 
G-25

with mild cognitive impairment. In: ClinicalTrials.gov 

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http://clinicaltrials.gov/ct/show/nct00134953. 2005. 

Full Text: Exclude - no primary data 

Nurk E, Refsum H, Tell GS, et al. Plasma total 

homocysteine and memory in the elderly: the Hordaland 

Homocysteine Study. Ann Neurol 2005;58(6):847-57. 

Full Text: Exclude - not longitudinal 

Nybo M, Andersen K, Sorensen GL, et al. Serum surfactant 

protein D is correlated to development of dementia and 

augmented mortality. Clin Immunol 2007;123(3):333-7. 

Full Text: Exclude - risk factor out of scope 

Nys GM, van Zandvoort MJ, de Kort PL, et al. The 

prognostic value of domain-specific cognitive abilities in 

acute first-ever stroke. Neurology 2005;64(5):821-7. 

Full Text: Exclude - AD/CD f/u < 1 yr 

Obidi CS, Pugeda JP, Fan X, et al. Race moderates agerelated cognitive decline in type 2 diabetes. Exp Aging Res 

2008;34(2):114-25. 

Full Text: Exclude - observational N<300 

O'Brien JT, Lloyd A, McKeith I, et al. A longitudinal study 

of hippocampal volume, cortisol levels, and cognition in 

older depressed subjects. Am J Psychiatry 

2004;161(11):2081-90. 

Full Text: Exclude - risk factor out of scope 

O'Brien JT, Wiseman R, Burton EJ, et al. Cognitive 

associations of subcortical white matter lesions in older 

people. Ann N Y Acad Sci 2002;977:436-44. 

Full Text: Exclude - risk factor out of scope 

O'Dwyer ST, Burton NW, Pachana NA, et al. Protocol for 

Fit Bodies, Fine Minds: a randomized controlled trial on 

the affect of exercise and cognitive training on cognitive 

functioning in older adults. BMC Geriatr 2007;7:23. 

Full Text: Exclude - AD/CD f/u < 1 yr 

O'Hara R, Yesavage JA, Kraemer HC, et al. The APOE 

epsilon4 allele is associated with decline on delayed recall 

performance in community-dwelling older adults. J Am 

Geriatr Soc 1998;46(12):1493-8. 

Full Text: Exclude - observational N<300 

Okereke O, Hankinson SE, Hu FB, et al. Plasma C peptide 

level and cognitive function among older women without 

diabetes mellitus. Arch Intern Med 2005;165(14):1651-6. 

Full Text: Exclude - risk factor out of scope 

Okereke OI, Pollak MN, Hu FB, et al. Plasma C-peptide 

levels and rates of cognitive decline in older, communitydwelling women without diabetes. 

Psychoneuroendocrinology 2008;33(4):455-61. 

Full Text: Exclude - risk factor out of scope 

Ortega RM, Requejo AM, Andres P, et al. Dietary intake 

and cognitive function in a group of elderly people. Am J 

Clin Nutr 1997;66(4):803-9. 

Full Text: Exclude - not longitudinal 

Ostrosky-Solis F, Mendoza VU, Ardila A. 

Neuropsychological profile of patients with primary 

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72. 

Full Text: Exclude - observational N<300 

Oswald WD, Rupprecht R, Gunzelmann T, et al. The 

SIMA-project: effects of 1 year cognitive and psychomotor 

training on cognitive abilities of the elderly. Behav Brain 

Res 1996;78(1):67-72. 

Full Text: Exclude - sample not randomly assigned 

Ott A, Breteler MM, de Bruyne MC, et al. Atrial fibrillation 

and dementia in a population-based study. The Rotterdam 

Study. Stroke 1997;28(2):316-21. 

Full Text: Exclude - risk factor out of scope 

Ott A, Stolk RP, Hofman A, et al. Association of diabetes 

mellitus and dementia: the Rotterdam Study. Diabetologia 

1996;39(11):1392-7. 

Full Text: Exclude - dementia @ baseline 

Ousset PJ, Nourhashemi F, Reynish E, et al. Nutritional 

status is associated with disease progression in very mild 

Alzheimer disease. Alzheimer Dis Assoc Disord 

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Full Text: Exclude - dementia @ baseline 

Ownby RL. Donepezil and vitamin E for mild cognitive 

impairment. Curr Psychiatry Rep 2006;8(1):9. 

Full Text: Exclude - no primary data 

Paganini-Hill A, Henderson VW. Estrogen replacement 

therapy and risk of Alzheimer disease. Arch Intern Med 

1996;156(19):2213-7. 

Full Text: Exclude - dementia @ baseline 

Paile-Hyvarinen M, Raikkonen K, Kajantie E, et al. Impact 

of glucose metabolism and birth size on cognitive 

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Full Text: Exclude - not longitudinal 

Paillard-Borg S, Fratiglioni L, Winblad B, et al. Leisure 

activities in late life in relation to dementia risk: principal 

component analysis. Dement Geriatr Cogn Disord 

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Full Text: Exclude - <60% of dementia is AD 

Paleologos M, Cumming RG, Lazarus R. Cohort study of 

vitamin C intake and cognitive impairment. Am J 

Epidemiol 1998;148(1):45-50. 

Full Text: Exclude - observational N<300 

Palmer K, Berger AK, Monastero R, et al. Predictors of 

progression from mild cognitive impairment to Alzheimer 

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Full Text: Exclude - observational N<300 
G-26

Palsson S, Aevarsson O, Skoog I. Depression, cerebral 

atrophy, cognitive performance and incidence of dementia. 

Population study of 85-year-olds. Br J Psychiatry 

1999;174:249-53. 

Full Text: Exclude - observational N<300 

Pan HA, Wang ST, Pai MC, et al. Cognitive function 

variations in postmenopausal women treated with 

continuous, combined HRT or tibolone. A comparison. J 

Reprod Med 2003;48(5):375-80. 

Full Text: Exclude - AD/CD f/u < 1 yr 

Pandav R, Dodge HH, DeKosky ST, et al. Blood pressure 

and cognitive impairment in India and the United States: a 

cross-national epidemiological study. Arch Neurol 

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Full Text: Exclude - not longitudinal 

Panegyres PK, Frencham K. Course and causes of 

suspected dementia in young adults: a longitudinal study. 

Am J Alzheimers Dis Other Demen 2007;22(1):48-56. 

Full Text: Exclude - dementia @ baseline 

Panza F, Capurso C, D'Introno A, et al. Impact of 

depressive symptoms on the rate of progression to dementia 

in patients affected by mild cognitive impairment. The 

Italian Longitudinal Study on Aging. Int J Geriatr 

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Full Text: Exclude - <60% of dementia is AD 

Parale GP, Baheti NN, Kulkarni P, et al. Effects of 

atorvastatin on higher functions. Eur J Clin Pharmacol 

2006;62(4):259-65. 

Full Text: Exclude - non-Western country 

Park H, Hildreth A, Thomson R, et al. Non-valvular atrial 

fibrillation and cognitive decline: a longitudinal cohort 

study. Age Ageing 2007;36(2):157-63. 

Full Text: Exclude - risk factor out of scope 

Parkkinen L, Kauppinen T, Pirttila T, et al. Alphasynuclein pathology does not predict extrapyramidal 

symptoms or dementia. Ann Neurol 2005;57(1):82-91. 

Full Text: Exclude - risk factor out of scope 

Parnetti L, Ciuffetti G, Mercuri M, et al. Haemorheological 

pattern in initial mental deterioration: results of a long-term 

study using piracetam and pentoxifylline. Arch Gerontol 

Geriatr 1985;4(2):141-55. 

Full Text: Exclude - dementia @ baseline 

Parnetti L, Senin U, Carosi M, et al. Mental deterioration in 

old age: results of two multicenter, clinical trials with 

nimodipine. The Nimodipine Study Group. Clin Ther 

1993;15(2):394-406. 

Full Text: Exclude - dementia @ baseline 

Parsons TD, Kratz KM, Thompson E, et al. Dhea 

supplementation and cognition in postmenopausal women. 

Int J Neurosci 2006;116(2):141-55. 

Full Text: Exclude - AD/CD f/u < 1 yr 

Patel M, Coshall C, Rudd AG, et al. Natural history of 

cognitive impairment after stroke and factors associated 

with its recovery. Clin Rehabil 2003;17(2):158-66. 

Full Text: Exclude - observational N<300 

Peacock JM, Folsom AR, Knopman DS, et al. Dietary 

antioxidant intake and cognitive performance in middleaged adults. The Atherosclerosis Risk in Communities 

(ARIC) Study investigators. Public Health Nutr 

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Full Text: Exclude - not longitudinal 

Pefanco MA, Kenny AM, Kaplan RF, et al. The effect of 3-

year treatment with 0.25 mg/day of micronized 17betaestradiol on cognitive function in older postmenopausal 

women. J Am Geriatr Soc 2007;55(3):426-31. 

Full Text: Exclude - does not measure cognitive decline 

Peila R, White LR, Petrovich H, et al. Joint effect of the 

APOE gene and midlife systolic blood pressure on late-life 

cognitive impairment: the Honolulu-Asia aging study. 

Stroke 2001;32(12):2882-9. 

Full Text: Exclude - not longitudinal 

Peretti CS, Gierski F, Harrois S. Cognitive skill learning in 

healthy older adults after 2 months of double-blind 

treatment with piribedil. Psychopharmacology (Berl) 

2004;176(2):175-81. 

Full Text: Exclude - AD/CD f/u < 1 yr 

Perez-Stable EJ, Halliday R, Gardiner PS, et al. The effects 

of propranolol on cognitive function and quality of life: a 

randomized trial among patients with diastolic 

hypertension. Am J Med 2000;108(5):359-65. 

Full Text: Exclude - < 80% >= 50 yo 

Perrig WJ, Perrig P, Stahelin HB. The relation between 

antioxidants and memory performance in the old and very 

old. J Am Geriatr Soc 1997;45(6):718-24. 

Full Text: Exclude - not longitudinal 

Perrig-Chiello P, Perrig WJ, Ehrsam R, et al. The effects of 

resistance training on well-being and memory in elderly 

volunteers. Age Ageing 1998;27(4):469-75. 

Full Text: Exclude - AD/CD f/u < 1 yr 

Peters R, Beckett N, Geneva M, et al. Sociodemographic 

and lifestyle risk factors for incident dementia and 

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Full Text: Exclude - non-Western country 

Peters R, Beckett N, Nunes M, et al. A substudy protocol of 

the hypertension in the Very Elderly Trial assessing 

cognitive decline and dementia incidence (HYVET-COG) : 

An ongoing randomised, double-blind, placebo-controlled 

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Full Text: Exclude - methods paper 

Petersen RC, Smith GE, Ivnik RJ, et al. Apolipoprotein E 

status as a predictor of the development of Alzheimer's 

disease in memory-impaired individuals.[erratum appears 
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in JAMA 1995 Aug 16;274(7):538]. JAMA 

1995;273(16):1274-8. 

Full Text: Exclude - observational N<300 

Peterson SE, Stull MJ, Collins MW, et al. Neurocognitive 

function of emergency department patients with mild 

traumatic brain injury. Ann Emerg Med 2009;53(6):796-

803 e1. 

Full Text: Exclude - <80% >= 50 yo 

Pettersen R, Saxby BK, Wyller TB. Poststroke urinary 

incontinence: one-year outcome and relationships with 

measures of attentiveness. J Am Geriatr Soc 

2007;55(10):1571-7. 

Full Text: Exclude - risk factor out of scope 

Pignatti F, Rozzini R, Trabucchi M, et al. Physical activity 

and cognitive decline in elderly persons.[comment]. Arch 

Intern Med 2002;162(3):361-2. 

Full Text: Exclude - Correspondence, inadequate outcomes 

Piguet O, Cramsie J, Bennett HP, et al. Contributions of 

age and alcohol consumption to cerebellar integrity, gait 

and cognition in non-demented very old individuals. Eur 

Arch Psychiatry Clin Neurosci 2006;256(8):504-11. 

Full Text: Exclude - observational N<300 

Piguet O, Grayson DA, Creasey H, et al. Vascular risk 

factors, cognition and dementia incidence over 6 years in 

the Sydney Older Persons Study. Neuroepidemiology 

2003;22(3):165-71. 

Full Text: Exclude - observational N<300 

Pipingas A, Silberstein RB, Vitetta L, et al. Improved 

cognitive performance after dietary supplementation with a 

Pinus radiata bark extract formulation. Phytother Res 

2008;22(9):1168-74. 

Full Text: Exclude - AD/CD f/u < 1 yr 

Poirier J, Delisle MC, Quirion R, et al. Apolipoprotein E4 

allele as a predictor of cholinergic deficits and treatment 

outcome in Alzheimer disease. Proc Natl Acad Sci U S A 

1995;92(26):12260-4. 

Full Text: Exclude - observational N<300 

Ponholzer A, Madersbacher S, Rauchenwald M, et al. 

Serum androgen levels and their association to depression 

and Alzheimer dementia in a cohort of 75-year-old men 

over 5 years: results of the VITA study. Int J Impot Res 

2009;21(3):187-91. 

Full Text: Exclude - observational N<300 

Potter GG, Helms MJ, Burke JR, et al. Job demands and 

dementia risk among male twin pairs. Alzheimer's & 

Dementia 2007;3:192-199. 

Full Text: Exclude - data collected by proxy 

Potter GG, Helms MJ, Plassman BL. Associations of job 

demands and intelligence with cognitive performance 

among men in late life. Neurology 2008;70(19 Pt 2):1803-

8. 

Full Text: Exclude - not longitudinal 

Pradignac A, Schlienger JL, Velten M, et al. Relationships 

between macronutrient intake, handicaps, and cognitive 

impairments in free living elderly people. Aging (Milano) 

1995;7(1):67-74. 

Full Text: Exclude - not longitudinal 

Presse N, Shatenstein B, Kergoat MJ, et al. Low vitamin K 

intakes in community-dwelling elders at an early stage of 

Alzheimer's disease. J Am Diet Assoc 2008;108(12):2095-

9. 

Full Text: Exclude - observational N<300 

Prohaska TR, Eisenstein AR, Satariano WA, et al. Walking 

and the preservation of cognitive function in older 

populations. Gerontologist 2009;49 Suppl 1:S86-93. 

Full Text: Exclude - not longitudinal 

Psaltopoulou T, Kyrozis A, Stathopoulos P, et al. Diet, 

physical activity and cognitive impairment among elders: 

the EPIC-Greece cohort (European Prospective 

Investigation into Cancer and Nutrition). Public Health 

Nutr 2008;11(10):1054-62. 

Full Text: Exclude - not longitudinal 

Qiu C, Winblad B, Marengoni A, et al. Heart failure and 

risk of dementia and Alzheimer disease: a population-based 

cohort study. Arch Intern Med 2006;166(9):1003-8. 

Full Text: Exclude - risk factor out of scope 

Rabbitt P, Lunn M, Ibrahim S, et al. Unhappiness, health 

and cognitive ability in old age. Psychol Med 

2008;38(2):229-36. 

Full Text: Exclude - Q2 continuous data only 

Rammsayer TH. Effects of pharmacologically induced 

changes in NMDA receptor activity on human timing and 

sensorimotor performance. Brain Res 2006;1073-1074:407-

16. 

Full Text: Exclude - <60% of dementia is AD 

Ramos MI, Allen LH, Mungas DM, et al. Low folate status 

is associated with impaired cognitive function and 

dementia in the Sacramento Area Latino Study on Aging. 

Am J Clin Nutr 2005;82(6):1346-52. 

Full Text: Exclude - not longitudinal 

Rapoport M, Wolf U, Herrmann N, et al. Traumatic brain 

injury, Apolipoprotein E-epsilon4, and cognition in older 

adults: a two-year longitudinal study. J Neuropsychiatry 

Clin Neurosci 2008;20(1):68-73. 

Full Text: Exclude - observational N<300 

Rapoport MJ, Herrmann N, Shammi P, et al. Outcome after 

traumatic brain injury sustained in older adulthood: a oneyear longitudinal study. Am J Geriatr Psychiatry 

2006;14(5):456-65. 

Full Text: Exclude - observational N<300 

Rapp S, Brenes G, Marsh AP. Memory enhancement 

training for older adults with mild cognitive impairment: a 

preliminary study. Aging Ment Health 2002;6(1):5-11. 
G-28

Full Text: Exclude - AD/CD f/u < 1 yr 

Rasmussen LS, O'Brien JT, Silverstein JH, et al. Is perioperative cortisol secretion related to post-operative 

cognitive dysfunction? Acta Anaesthesiol Scand 

2005;49(9):1225-31. 

Full Text: Exclude - risk factor out of scope 

Rastas S, Verkkoniemi A, Polvikoski T, et al. Atrial 

fibrillation, stroke, and cognition: a longitudinal 

population-based study of people aged 85 and older. Stroke 

2007;38(5):1454-60. 

Full Text: Exclude - <60% of dementia is AD 

Ravaglia G, Forti P, Lucicesare A, et al. Plasma 

tocopherols and risk of cognitive impairment in an elderly 

Italian cohort. Am J Clin Nutr 2008;87(5):1306-13. 

Full Text: Exclude - risk factor out of scope 

Ravaglia G, Forti P, Maioli F, et al. Endogenous sex 

hormones as risk factors for dementia in elderly men and 

women. J Gerontol A Biol Sci Med Sci 2007;62(9):1035-

41. 

Full Text: Exclude - risk factor out of scope 

Ravaglia G, Forti P, Maioli F, et al. Blood inflammatory 

markers and risk of dementia: The Conselice Study of 

Brain Aging. Neurobiol Aging 2007;28(12):1810-20. 

Full Text: Exclude - risk factor out of scope 

Ravaglia G, Forti P, Maioli F, et al. Incidence and etiology 

of dementia in a large elderly Italian population. Neurology 

2005;64(9):1525-30. 

Full Text: Exclude - risk factor out of scope 

Ravaglia G, Forti P, Maioli F, et al. Conversion of mild 

cognitive impairment to dementia: predictive role of mild 

cognitive impairment subtypes and vascular risk factors. 

Dement Geriatr Cogn Disord 2006;21(1):51-8. 

Full Text: Exclude - observational N<300 

Ravaglia G, Forti P, Maioli F, et al. Education, occupation, 

and prevalence of dementia: findings from the Conselice 

study. Dement Geriatr Cogn Disord 2002;14(2):90-100. 

Full Text: Exclude - not longitudinal 

Ravaglia G, Forti P, Maioli F, et al. Homocysteine and 

cognitive performance in healthy elderly subjects. Arch 

Gerontol Geriatr Suppl 2004(9):349-57. 

Full Text: Exclude - observational N<300 

Raymont V, Greathouse A, Reding K, et al. Demographic, 

structural and genetic predictors of late cognitive decline 

after penetrating head injury. Brain 2008;131(Pt 2):543-58. 

Full Text: Exclude - risk factor out of scope 

Raynaud-Simon A, Lafont S, Berr C, et al. Plasma insulinlike growth factor I levels in the elderly: relation to plasma 

dehydroepiandrosterone sulfate levels, nutritional status, 

health and mortality. Gerontology 2001;47(4):198-206. 

Full Text: Exclude - risk factor out of scope 

Raz N, Rodrigue KM, Kennedy KM, et al. Vascular health 

and longitudinal changes in brain and cognition in middleaged and older adults. Neuropsychology 2007;21(2):149-

57. 

Full Text: Exclude - observational N<300 

Reinprecht F, Elmstahl S, Janzon L, et al. Hypertension and 

changes of cognitive function in 81-year-old men: a 13-

year follow-up of the population study "Men born in 1914", 

Sweden. J Hypertens 2003;21(1):57-66. 

Full Text: Exclude - observational N<300 

Reischies FM, Neu P. Comorbidity of mild cognitive 

disorder and depression--a neuropsychological analysis. 

Eur Arch Psychiatry Clin Neurosci 2000;250(4):186-93. 

Full Text: Exclude - observational N<300 

Renvall MJ, Spindler AA, Ramsdell JW, et al. Nutritional 

status of free-living Alzheimer's patients. Am J Med Sci 

1989;298(1):20-7. 

Full Text: Exclude - dementia @ baseline 

Resnick SM, Coker LH, Maki PM, et al. The Women's 

Health Initiative Study of Cognitive Aging (WHISCA): a 

randomized clinical trial of the effects of hormone therapy 

on age-associated cognitive decline. Clin Trials 

2004;1(5):440-50. 

Full Text: Exclude - methods paper 

Reynolds CA, Gatz M, Berg S, et al. Genotypeenvironment interactions: cognitive aging and social 

factors. Twin Res Hum Genet 2007;10(2):241-54. 

Full Text: Exclude - observational N<300 

Richard F, Berr C, Amant C, et al. Effect of the angiotensin 

I-converting enzyme I/D polymorphism on cognitive 

decline. The EVA Study Group. Neurobiol Aging 

2000;21(1):75-80. 

Full Text: Exclude - risk factor out of scope 

Richards M, Jarvis MJ, Thompson N, et al. Cigarette 

smoking and cognitive decline in midlife: evidence from a 

prospective birth cohort study. Am J Public Health 

2003;93(6):994-8. 

Full Text: Exclude - <80% >= 50 yo 

Richards M, Meade TW, Peart S, et al. Is there any 

evidence for a protective effect of antithrombotic 

medication on cognitive function in men at risk of 

cardiovascular disease? Some preliminary findings. J 

Neurol Neurosurg Psychiatry 1997;62(3):269-72. 

Full Text: Exclude - risk factor out of scope 

Richards M, Shipley B, Fuhrer R, et al. Cognitive ability in 

childhood and cognitive decline in mid-life: longitudinal 

birth cohort study. BMJ 2004;328(7439):552. 

Full Text: Exclude - <80% >= 50 yo 

Richards M, Wadsworth ME. Long term effects of early 

adversity on cognitive function. Arch Dis Child 

2004;89(10):922-7. 

Full Text: Exclude - not longitudinal 
G-29

Richards SS, Emsley CL, Roberts J, et al. The association 

between vascular risk factor-mediating medications and 

cognition and dementia diagnosis in a community-based 

sample of African-Americans. J Am Geriatr Soc 

2000;48(9):1035-41. 

Full Text: Exclude - not longitudinal 

Riemersma-van der Lek RF, Swaab DF, Twisk J, et al. 

Effect of bright light and melatonin on cognitive and 

noncognitive function in elderly residents of group care 

facilities: a randomized controlled trial. JAMA 

2008;299(22):2642-55. 

Full Text: Exclude - dementia @ baseline 

Robbins MA, Elias MF, Budge MM, et al. Homocysteine, 

type 2 diabetes mellitus, and cognitive performance: The 

Maine-Syracuse Study. Clin Chem Lab Med 

2005;43(10):1101-6. 

Full Text: Exclude - not longitudinal 

Robbins MA, Elias MF, Elias PK, et al. Blood pressure and 

cognitive function in an African-American and a 

Caucasian-American sample: the Maine-Syracuse Study. 

Psychosom Med 2005;67(5):707-14. 

Full Text: Exclude - not longitudinal 

Roberts RO, Geda YE, Knopman DS, et al. Association of 

duration and severity of diabetes mellitus with mild 

cognitive impairment. Arch Neurol 2008;65(8):1066-73. 

Full Text: Exclude - not longitudinal 

Robertson-Tchabo EA, Arenberg D, Tobin JD, et al. A 

longitudinal study of cognitive performance in noninsulin 

dependent (type II) diabetic men. Exp Gerontol 1986;21(4-

5):459-67. 

Full Text: Exclude - observational N<300 

Rockwood K, Ebly E, Hachinski V, et al. Presence and 

treatment of vascular risk factors in patients with vascular 

cognitive impairment. Arch Neurol 1997;54(1):33-9. 

Full Text: Exclude - dementia @ baseline 

Rockwood K, Howlett S, Fisk J, et al. Lipid-lowering 

agents and the risk of cognitive impairment that does not 

meet criteria for dementia, in relation to apolipoprotein E 

status. Neuroepidemiology 2007;29(3-4):201-7. 

Full Text: Exclude - not longitudinal 

Rockwood K, Kirkland S, Hogan D, et al. Use of lipidlowering agents, indication bias, and the risk of dementia in 

community-dwelling elderly people. Arch Neurol 

2002;59(2):223-7. 

Full Text: Exclude - not longitudinal 

Rondanelli M, Trotti R, Opizzi A, et al. Relationship 

among nutritional status, pro/antioxidant balance and 

cognitive performance in a group of free-living healthy 

elderly. Minerva Med 2007;98(6):639-45. 

Full Text: Exclude - observational N<300 

Ronnemaa E, Zethelius B, Sundelof J, et al. Impaired 

insulin secretion increases the risk of Alzheimer disease. 

Neurology 2008;71(14):1065-71. 

Full Text: Exclude - risk factor out of scope 

Ronnlund M, Nyberg L, Backman L, et al. Stability, 

growth, and decline in adult life span development of 

declarative memory: cross-sectional and longitudinal data 

from a population-based study. Psychol Aging 

2005;20(1):3-18. 

Full Text: Exclude - risk factor out of scope 

Roriz-Cruz M, Rosset I, Wada T, et al. Cognitive 

impairment and frontal-subcortical geriatric syndrome are 

associated with metabolic syndrome in a stroke-free 

population. Neurobiol Aging 2007;28(11):1723-36. 

Full Text: Exclude - non-Western country 

Rosenblatt A, Mehta KM, Romanoski A, et al. Major 

depression and cognitive decline after 11.5 years: findings 

from the ECA study. J Nerv Ment Dis 2003;191(12):827-

30. 

Full Text: Exclude - <80% >= 50 yo 

Rotkiewicz-Piorun AM, Al Snih S, Raji MA, et al. 

Cognitive decline in older Mexican Americans with 

diabetes. J Natl Med Assoc 2006;98(11):1840-7. 

Full Text: Exclude - non-Western country 

Rowan E, Morris CM, Stephens S, et al. Impact of 

hypertension and apolipoprotein E4 on poststroke cognition 

in subjects >75 years of age. Stroke 2005;36(9):1864-8. 

Full Text: Exclude - not applicable population 

Rowan EN, Dickinson HO, Stephens S, et al. 

Homocysteine and post-stroke cognitive decline. Age 

Ageing 2007;36(3):339-43. 

Full Text: Exclude - observational N<300 

Rozzini L, Chilovi BV, Bertoletti E, et al. Angiotensin 

converting enzyme (ACE) inhibitors modulate the rate of 

progression of amnestic mild cognitive impairment. Int J 

Geriatr Psychiatry 2006;21(6):550-5. 

Full Text: Exclude - observational N<300 

Rozzini L, Costardi D, Chilovi BV, et al. Efficacy of 

cognitive rehabilitation in patients with mild cognitive 

impairment treated with cholinesterase inhibitors. Int J 

Geriatr Psychiatry 2007;22(4):356-60. 

Full Text: Exclude - sample not randomly assigned 

Rozzini R, Ferrucci L, Losonczy K, et al. Protective effect 

of chronic NSAID use on cognitive decline in older 

persons. J Am Geriatr Soc 1996;44(9):1025-9. 

Full Text: Exclude - SPMSQ single test 

Ryglewicz D, Rodo M, Kunicki PK, et al. Plasma 

antioxidant activity and vascular dementia. J Neurol Sci 

2002;203-204:195-7. 

Full Text: Exclude - dementia @ baseline 

Saag KG, Rubenstein LM, Chrischilles EA, et al. 

Nonsteroidal antiinflammatory drugs and cognitive decline 
G-30

in the elderly. J Rheumatol 1995;22(11):2142-7. 

Full Text: Exclude - dementia @ baseline 

Sabia S, Kivimaki M, Shipley MJ, et al. Body mass index 

over the adult life course and cognition in late midlife: the 

Whitehall II Cohort Study. Am J Clin Nutr 2009;89(2):601-

7. 

Full Text: Exclude - not longitudinal 

Sabia S, Nabi H, Kivimaki M, et al. Health behaviors from 

early to late midlife as predictors of cognitive function: The 

Whitehall II study. Am J Epidemiol 2009;170(4):428-37. 

Full Text: Exclude - not longitudinal 

Sachdev PS, Brodaty H, Valenzuela MJ, et al. Clinical 

determinants of dementia and mild cognitive impairment 

following ischaemic stroke: the Sydney Stroke Study. 

Dement Geriatr Cogn Disord 2006;21(5-6):275-83. 

Full Text: Exclude - <60% of dementia is AD 

Sachs-Ericsson N, Blazer DG. Racial differences in 

cognitive decline in a sample of community-dwelling older 

adults: the mediating role of education and literacy. Am J 

Geriatr Psychiatry 2005;13(11):968-75. 

Full Text: Exclude - SPMSQ single test 

Sachs-Ericsson N, Joiner T, Plant EA, et al. The influence 

of depression on cognitive decline in community-dwelling 

elderly persons. Am J Geriatr Psychiatry 2005;13(5):402-8. 

Full Text: Exclude - SPMSQ single test 

Sacktor N, Gray S, Kawas C, et al. Systolic blood pressure 

within an intermediate range may reduce memory loss in an 

elderly hypertensive cohort. J Geriatr Psychiatry Neurol 

1999;12(1):1-6. 

Full Text: Exclude - observational N<300 

Saczynski JS, Jonsdottir MK, Garcia ME, et al. Cognitive 

impairment: an increasingly important complication of type 

2 diabetes: the age, gene/environment susceptibility--

Reykjavik study. Am J Epidemiol 2008;168(10):1132-9. 

Full Text: Exclude - not longitudinal 

Salloway S, Correia S, Richardson S. Key lessons learned 

from short-term treatment trials of cholinesterase inhibitors 

for amnestic MCI. Int Psychogeriatr 2008;20(1):40-6. 

Full Text: Exclude - no primary data 

Salloway S, Ferris S, Kluger A, et al. Efficacy of donepezil 

in mild cognitive impairment: a randomized placebocontrolled trial. Neurology 2004;63(4):651-7. 

Full Text: Exclude - not longitufinal SB-AD/CD f/u < 1 yr 

Salminen EK, Portin RI, Koskinen AI, et al. Estradiol and 

cognition during androgen deprivation in men with prostate 

carcinoma. Cancer 2005;103(7):1381-7. 

Full Text: Exclude - not applicable population 

Samieri C, Feart C, Letenneur L, et al. Low plasma 

eicosapentaenoic acid and depressive symptomatology are 

independent predictors of dementia risk. Am J Clin Nutr 

2008;88(3):714-21. 

Full Text: Exclude - <60% of dementia is AD 

Santanello NC, Barber B, Applegate W, et al. Effect of 

pharmacologic lipid lowering on health-related quality of 

life in older persons: results from the Cholesterol Reduction 

in Seniors Program (CRISP) Pilot Study. J Am Geriatr Soc 

1997;45(1):8-14. 

Full Text: Exclude - AD/VD f/u < 1 year 

Saxby BK, Harrington F, McKeith IG, et al. Effects of 

hypertension on attention, memory, and executive function 

in older adults. Health Psychol 2003;22(6):587-91. 

Full Text: Exclude - not longitudinal 

Scarmeas N, Albert SM, Manly JJ, et al. Education and 

rates of cognitive decline in incident Alzheimer's disease. J 

Neurol Neurosurg Psychiatry 2006;77(3):308-16. 

Full Text: Exclude - dementia @ baseline 

Scarmeas N, Stern Y, Mayeux R, et al. Mediterranean diet, 

Alzheimer disease, and vascular mediation. Arch Neurol 

2006;63(12):1709-17. 

Full Text: Exclude - not longitudinal 

Schantz SL, Sweeney AM, Gardiner JC, et al. 

Neuropsychological assessment of an aging population of 

Great Lakes fisheaters. Toxicol Ind Health 1996;12(3-

4):403-17. 

Full Text: Exclude - not longitudinal 

Schippling S, Kontush A, Arlt S, et al. Increased 

lipoprotein oxidation in Alzheimer's disease. Free Radic 

Biol Med 2000;28(3):351-60. 

Full Text: Exclude - dementia @ baseline 

Schmand B, Jonker C, Geerlings MI, et al. Subjective 

memory complaints in the elderly: depressive symptoms 

and future dementia. Br J Psychiatry 1997;171:373-6. 

Full Text: Exclude - AD f/u < 2 yr 

Schmand B, Smit J, Lindeboom J, et al. Low education is a 

genuine risk factor for accelerated memory decline and 

dementia. J Clin Epidemiol 1997;50(9):1025-33. 

Full Text: Exclude - <60% of dementia is AD 

Schmand B, Smit JH, Geerlings MI, et al. The effects of 

intelligence and education on the development of dementia. 

A test of the brain reserve hypothesis. Psychol Med 

1997;27(6):1337-44. 

Full Text: Exxclude - <60% of dementia is AD 

Schmidt R, Fazekas F, Koch M, et al. Magnetic resonance 

imaging cerebral abnormalities and neuropsychologic test 

performance in elderly hypertensive subjects. A casecontrol study. Arch Neurol 1995;52(9):905-10. 

Full Text: Exclude - observational N<300 

Schmidt R, Hayn M, Reinhart B, et al. Plasma antioxidants 

and cognitive performance in middle-aged and older adults: 

results of the Austrian Stroke Prevention Study. J Am 

Geriatr Soc 1998;46(11):1407-10. 

Full Text: Exclude - not longitudinal 
G-31

Schoeman R, Carey P, Seedat S. Trauma and posttraumatic 

stress disorder in South African adolescents: a case-control 

study of cognitive deficits. J Nerv Ment Dis 

2009;197(4):244-50. 

Full Text: Exclude - risk factor out of scope 

Scott RD, Kritz-Silverstein D, Barrett-Connor E, et al. The 

association of non-insulin-dependent diabetes mellitus and 

cognitive function in an older cohort. J Am Geriatr Soc 

1998;46(10):1217-22. 

Full Text: Exclude - not longitudinal 

Scuteri A, Coluccia R, Castello L, et al. Left ventricular 

mass increase is associated with cognitive decline and 

dementia in the elderly independently of blood pressure. 

Eur Heart J 2009;30(12):1525-9. 

Full Text: Exclude - not longitudinal 

Scuteri A, Palmieri L, Lo Noce C, et al. Age-related 

changes in cognitive domains. A population-based study. 

Aging Clin Exp Res 2005;17(5):367-73. 

Full Text: Exclude - not longitudinal 

Scuteri A, Tesauro M, Appolloni S, et al. Arterial stiffness 

as an independent predictor of longitudinal changes in 

cognitive function in the older individual. J Hypertens 

2007;25(5):1035-40. 

Full Text: Exclude - dementia @ baseline 

Seeman TE, Huang MH, Bretsky P, et al. Education and 

APOE-e4 in longitudinal cognitive decline: MacArthur 

Studies of Successful Aging. J Gerontol B Psychol Sci Soc 

Sci 2005;60(2):P74-83. 

Full Text: Exclude - SPMSQ single test 

Seeman TE, McEwen BS, Singer BH, et al. Increase in 

urinary cortisol excretion and memory declines: MacArthur 

studies of successful aging. J Clin Endocrinol Metab 

1997;82(8):2458-65. 

Full Text: Exclude - risk factor out of scope 

Seidler A, Bernhardt T, Nienhaus A, et al. Association 

between the psychosocial network and dementia--a casecontrol study. J Psychiatr Res 2003;37(2):89-98. 

Full Text: Exclude - dementia @ baseline 

Selhub J, Morris MS, Jacques PF, et al. Folate-vitamin B12 interaction in relation to cognitive impairment, anemia, 

and biochemical indicators of vitamin B-12 deficiency. Am 

J Clin Nutr 2009;89(2):702S-6S. 

Full Text: Exclude - not longitudinal 

Senanarong V, Jamjumrus P, Harnphadungkit K, et al. Risk 

factors for dementia and impaired cognitive status in Thai 

elderly. J Med Assoc Thai 2001;84(4):468-74. 

Full Text: Exclude - non-Western country 

Sendelbach S, Lindquist R, Watanuki S, et al. Correlates of 

neurocognitive function of patients after off-pump coronary 

artery bypass surgery. Am J Crit Care 2006;15(3):290-8. 

Full Text: Exclude - risk factor out of scope 

Serra JA, Marschoff ER, Dominguez RO, et al. Oxidative 

stress in Alzheimer's and vascular dementias: masking of 

the antioxidant profiles by a concomitant Type II diabetes 

mellitus condition. J Neurol Sci 2004;218(1-2):17-24. 

Full Text: Exclude - dementia @ baseline 

Serrano S, Domingo J, Rodriguez-Garcia E, et al. 

Frequency of cognitive impairment without dementia in 

patients with stroke: a two-year follow-up study. Stroke 

2007;38(1):105-10. 

Full Text: Exclude - not longitudinal 

Seshadri S, Wolf PA, Beiser A, et al. Lifetime risk of 

dementia and Alzheimer's disease. The impact of mortality 

on risk estimates in the Framingham Study. Neurology 

1997;49(6):1498-504. 

Full Text: Exclude - risk factor out of scope 

Shadlen MF, Siscovick D, Fitzpatrick AL, et al. Education, 

cognitive test scores, and black-white differences in 

dementia risk. J Am Geriatr Soc 2006;54(6):898-905. 

Full Text: Exclude - <60% of dementia is AD 

Shahinian VB, Kuo YF, Freeman JL, et al. Risk of the 

"androgen deprivation syndrome" in men receiving 

androgen deprivation for prostate cancer. Arch Intern Med 

2006;166(4):465-71. 

Full Text: Exclude - not applicable population 

Shapiro AP, Nixon P, Miller RE, et al. Behavioural 

consequences of hypertension: effects of age and type of 

antihypertensive agent. J Hum Hypertens 1989;3(6):435-

42. 

Full Text: Exclude - observational N<300 

Shatenstein B, Kergoat MJ, Reid I. Poor nutrient intakes 

during 1-year follow-up with community-dwelling older 

adults with early-stage Alzheimer dementia compared to 

cognitively intact matched controls. J Am Diet Assoc 

2007;107(12):2091-9. 

Full Text: Exclude - dementia @ baseline 

Shepherd CE, Piguet O, Broe GA, et al. Histocompatibility 

antigens, aspirin use and cognitive performance in nondemented elderly subjects. J Neuroimmunol 2004;148(1-

2):178-82. 

Full Text: Exclude - observational N<300 

Shumaker SA, Reboussin BA, Espeland MA, et al. The 

Women's Health Initiative Memory Study (WHIMS): a trial 

of the effect of estrogen therapy in preventing and slowing 

the progression of dementia. Control Clin Trials 

1998;19(6):604-21. 

Full Text: Exclude - methods paper 

Simons LA, Simons J, McCallum J, et al. Lifestyle factors 

and risk of dementia: Dubbo Study of the elderly. Med J 

Aust 2006;184(2):68-70. 

Full Text: Exclude - <60% of dementia is AD 

Singh-Manoux A, Marmot M. High blood pressure was 
G-32

associated with cognitive function in middle-age in the 

Whitehall II study. J Clin Epidemiol 2005;58(12):1308-15. 

Full Text: Exclude - not longitudinal 

Sink KM, Leng X, Williamson J, et al. Angiotensinconverting enzyme inhibitors and cognitive decline in older 

adults with hypertension: results from the Cardiovascular 

Health Study. Arch Intern Med 2009;169(13):1195-202. 

Full Text: Exclude - outcomes inadequately assessed 

Sinoff G, Werner P. Anxiety disorder and accompanying 

subjective memory loss in the elderly as a predictor of 

future cognitive decline. Int J Geriatr Psychiatry 

2003;18(10):951-9. 

Full Text: Exclude - observational N<300 

Skoog I, Lernfelt B, Landahl S, et al. 15-year longitudinal 

study of blood pressure and dementia. Lancet 

1996;347(9009):1141-5. 

Full Text: Exclude - <60% of dementia is AD 

Slooter AJ, Cruts M, Ott A, et al. The effect of APOE on 

dementia is not through atherosclerosis: the Rotterdam 

Study.[see comment]. Neurology 1999;53(7):1593-5. 

Full Text: Exclude - <60% of dementia is AD 

Small GW, La Rue A, Komo S, et al. Mnemonics usage 

and cognitive decline in age-associated memory 

impairment. Int Psychogeriatr 1997;9(1):47-56. 

Full Text: Exclude - observational N<300 

Small GW, Siddarth P, Silverman DH, et al. Cognitive and 

cerebral metabolic effects of celecoxib versus placebo in 

people with age-related memory loss: randomized 

controlled study. Am J Geriatr Psychiatry 2008;16(12):999-

1009. 

Full Text: Exclude - RCT N < 50 

Smith CD, Walton A, Loveland AD, et al. Memories that 

last in old age: motor skill learning and memory 

preservation. Neurobiol Aging 2005;26(6):883-90. 

Full Text: Exclude - observational N<300 

Smith EE, Egorova S, Blacker D, et al. Magnetic resonance 

imaging white matter hyperintensities and brain volume in 

the prediction of mild cognitive impairment and dementia. 

Arch Neurol 2008;65(1):94-100. 

Full Text: Exclude - observational N<300 

Smith GE, Housen P, Yaffe K, et al. A cognitive training 

program based on principles of brain plasticity: results from 

the Improvement in Memory with Plasticity-based 

Adaptive Cognitive Training (IMPACT) study. J Am 

Geriatr Soc 2009;57(4):594-603. 

Full Text: Exclude - AD/CD f/u < 1 yr 

Smyth KA, Fritsch T, Cook TB, et al. Worker functions 

and traits associated with occupations and the development 

of AD. Neurology 2004;63(3):498-503. 

Full Text: Exclude - not longitudinal 

Snowdon DA, Kemper SJ, Mortimer JA, et al. Linguistic 

ability in early life and cognitive function and Alzheimer's 

disease in late life. Findings from the Nun Study.[see 

comment]. JAMA 1996;275(7):528-32. 

Full Text: Exclude - observational N<300 

Sobel E, Davanipour Z, Sulkava R, et al. Occupations with 

exposure to electromagnetic fields: a possible risk factor for 

Alzheimer's disease. Am J Epidemiol 1995;142(5):515-24. 

Full Text: Exclude - dementia @ baseline 

Sole-Padulles C, Bartres-Faz D, Junque C, et al. Brain 

structure and function related to cognitive reserve variables 

in normal aging, mild cognitive impairment and 

Alzheimer's disease. Neurobiol Aging 2009;30(7):1114-24. 

Full Text: Exclude - risk factor out of scope 

Solfrizzi V, Colacicco AM, D'Introno A, et al. Dietary fatty 

acids intakes and rate of mild cognitive impairment. The 

Italian Longitudinal Study on Aging. Exp Gerontol 

2006;41(6):619-27. 

Full Text: Exclude - observational N<300 

Solfrizzi V, Colacicco AM, D'Introno A, et al. Dietary 

intake of unsaturated fatty acids and age-related cognitive 

decline: a 8.5-year follow-up of the Italian Longitudinal 

Study on Aging. Neurobiol Aging 2006;27(11):1694-704. 

Full Text: Exclude - observational N<300 

Solfrizzi V, Panza F, Torres F, et al. High monounsaturated 

fatty acids intake protects against age-related cognitive 

decline. Neurology 1999;52(8):1563-9. 

Full Text: Exclude - observational N<300 

Solomon PR, Adams F, Silver A, et al. Ginkgo for memory 

enhancement: a randomized controlled trial. JAMA 

2002;288(7):835-40. 

Full Text: Exclude - AD/CD f/u < 1 yr 

Solomon S, Hotchkiss E, Saravay SM, et al. Impairment of 

memory function by antihypertensive medication. Arch 

Gen Psychiatry 1983;40(10):1109-12. 

Full Text: Exclude - observational N<300 

Sonnen JA, Larson EB, Brickell K, et al. Different patterns 

of cerebral injury in dementia with or without diabetes. 

Arch Neurol 2009;66(3):315-22. 

Full Text: Exclude - observational N<300 

Sparks D, Kryscio R, Sabbagh M, et al. Reduced risk of 

incident AD with elective statin use in a clinical trial 

cohort. Curr Alzheimer Res 2008;5(4):416-21. 

Full Text: Exclude - dementia @ baseline 

Sparks D, Petanceska S, Sabbagh M, et al. Cholesterol, 

copper and Abeta in controls, MCI, AD and the AD 

cholesterol-lowering treatment trial (ADCLT). Curr 

Alzheimer Res 2005;2(5):527-39. 

Full Text: Exclude - not longitudinal 

Spindler AA, Renvall MA. Nutritional status and 

psychometric test scores in cognitively impaired elders. 

Ann N Y Acad Sci 1989;561:167-77. 
G-33

Full Text: Exclude - dementia @ baseline 

Spinks H, Dalgleish T. Attentional processing and levels of 

symptomatology in Seasonal Affective Disorder (SAD): a 

preliminary longitudinal study. J Affect Disord 

2001;62(3):229-32. 

Full Text: Exclude - observational N<300 

Stanley TO, Mackensen GB, Grocott HP, et al. The impact 

of postoperative atrial fibrillation on neurocognitive 

outcome after coronary artery bypass graft surgery. Anesth 

Analg 2002;94(2):290-5, table of contents. 

Full Text: Exclude - risk factor out of scope 

Starr J, McGurn B, Whiteman M, et al. Life long changes 

in cognitive ability are associated with prescribed 

medications in old age. Int J Geriatr Psychiatry 

2004;19(4):327-32. 

Full Text: Exclude - not longitudinal 

Starr JM, Deary IJ, Fox H, et al. Blood pressure and 

cognition in the Aberdeen 1936 birth cohort. Gerontology 

2007;53(6):432-7. 

Full Text: Exclude - not longitudinal 

Starr JM, Deary IJ, Fox HC, et al. Smoking and cognitive 

change from age 11 to 66 years: a confirmatory 

investigation. Addict Behav 2007;32(1):63-8. 

Full Text: Exclude - observational N<300 

Starr JM, Deary IJ, Inch S, et al. Age-associated cognitive 

decline in healthy old people. Age Ageing 1997;26(4):295-

300. 

Full Text: Exclude - not longitudinal 

Starr JM, Deary IJ, Inch S, et al. Blood pressure and 

cognitive decline in healthy old people. J Hum Hypertens 

1997;11(12):777-81. 

Full Text: Exclude - not general population 

Starr JM, McGurn B, Whiteman M, et al. Life long changes 

in cognitive ability are associated with prescribed 

medications in old age. Int J Geriatr Psychiatry 

2004;19(4):327-32. 

Full Text: Exclude - outcomes unacceptably assessed 

Starr JM, Whalley LJ. Differential cognitive outcomes in 

the Hypertensive Old People in Edinburgh study. J Neurol 

Sci 2005;229-230:103-7. 

Full Text: Exclude - AD/CD f/u < 1 yr 

Starr JM, Whalley LJ, Deary IJ. The effects of 

antihypertensive treatment on cognitive function: results 

from the HOPE study. J Am Geriatr Soc 1996;44(4):411-5. 

Full Text: Exclude - AD/CD f/u < 1 yr 

Stefanick ML, Cochrane BB, Hsia J, et al. The Women's 

Health Initiative postmenopausal hormone trials: overview 

and baseline characteristics of participants. Ann Epidemiol 

2003;13(9 Suppl):S78-86. 

Full Text: Exclude - outcomes not AD/CD 

Steffens DC, Welsh-Bohmer KA, Burke JR, et al. 

Methodology and preliminary results from the 

neurocognitive outcomes of depression in the elderly study. 

J Geriatr Psychiatry Neurol 2004;17(4):202-11. 

Full Text: Exclude - not applicable population 

Stepaniuk J, Ritchie LJ, Tuokko H. Neuropsychiatric 

impairments as predictors of mild cognitive impairment, 

dementia, and Alzheimer's disease. Am J Alzheimers Dis 

Other Demen 2008;23(4):326-33. 

Full Text: Exclude - risk factor out of scope 

Stephens R, Sreenivasan B. Neuropsychological effects of 

long-term low-level organophosphate exposure in orchard 

sprayers in England. Arch Environ Health 

2004;59(11):566-74. 

Full Text: Exclude - observational N<300 

Stewart R, Hirani V. Dental health and cognitive 

impairment in an English national survey population. J Am 

Geriatr Soc 2007;55(9):1410-4. 

Full Text: Exclude - risk factor out of scope 

Stewart R, Masaki K, Xue QL, et al. A 32-year prospective 

study of change in body weight and incident dementia: the 

Honolulu-Asia Aging Study. Arch Neurol 2005;62(1):55-

60. 

Full Text: Exclude - risk factor out of scope 

Stewart R, Prince M, Mann A. Age, vascular risk, and 

cognitive decline in an older, British, African-Caribbean 

population. J Am Geriatr Soc 2003;51(11):1547-53. 

Full Text: Exclude - observational N<300 

Sturmer T, Glynn RJ, Field TS, et al. Aspirin use and 

cognitive function in the elderly. Am J Epidemiol 

1996;143(7):683-91. 

Full Text: Exclude - SPMSQ single test 

Suhr JA, Stewart JC, France CR. The relationship between 

blood pressure and cognitive performance in the Third 

National Health and Nutrition Examination Survey 

(NHANES III). Psychosom Med 2004;66(3):291-7. 

Full Text: Exclude - <80% >= 50 yo 

Sulbaran TA, Silva ER, Maestre G. Isolated systolic 

hypertension: a new challenge in medicine. J Hum 

Hypertens 2002;16 Suppl 1:S44-7. 

Full Text: Exclude - non-Western country 

Summers M, Oliver K, Coombes JS, et al. Effect of 

atorvastatin on cognitive function in patients from the Lipid 

Lowering and Onset of Renal Disease (LORD) trial. 

Pharmacotherapy 2007;27(2):183-90. 

Full Text: Exclude - AD/CD f/u < 1 year 

Sun Q, Townsend MK, Okereke OI, et al. Adiposity and 

weight change in mid-life in relation to healthy survival 

after age 70 in women: prospective cohort study. BMJ 

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Full Text: Exclude - AD/CD unacceptably assessed 
G-34

Sundelof J, Arnlov J, Ingelsson E, et al. Serum cystatin C 

and the risk of Alzheimer disease in elderly men. 

Neurology 2008;71(14):1072-9. 

Full Text: Exclude - risk factor out of scope 

Swan GE, Carmelli D, Larue A. Systolic blood pressure 

tracking over 25 to 30 years and cognitive performance in 

older adults. Stroke 1998;29(11):2334-40. 

Full Text: Exclude - not longitudinal 

Sweetow RW, Sabes JH. The need for and development of 

an adaptive Listening and Communication Enhancement 

(LACE) Program. J Am Acad Audiol 2006;17(8):538-58. 

Full Text: Exclude - risk factor out of scope 

Sze KH, Sim TC, Wong E, et al. Effect of nimodipine on 

memory after cerebral infarction. Acta Neurol Scand 

1998;97(6):386-92. 

Full Text: Exclude - risk factor out of scope 

Szekely CA, Green RC, Breitner JC, et al. No advantage of 

A beta 42-lowering NSAIDs for prevention of Alzheimer 

dementia in six pooled cohort studies. Neurology 

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Full Text: Exclude - not longitudinal 

Tabbarah M, Crimmins EM, Seeman TE. The relationship 

between cognitive and physical performance: MacArthur 

Studies of Successful Aging. J Gerontol A Biol Sci Med 

Sci 2002;57(4):M228-35. 

Full Text: Exclude - outcomes unacceptably assessed 

Tan ZS, Beiser A, Vasan RS, et al. Thyroid function and 

the risk of Alzheimer disease: the Framingham Study. Arch 

Intern Med 2008;168(14):1514-20. 

Full Text: Exclude - risk factor out of scope 

Tan ZS, Seshadri S, Beiser A, et al. Bone mineral density 

and the risk of Alzheimer disease. Arch Neurol 

2005;62(1):107-11. 

Full Text: Exclude - risk factor out of scope 

Tang MX, Maestre G, Tsai WY, et al. Effect of age, 

ethnicity, and head injury on the association between 

APOE genotypes and Alzheimer's disease. Ann N Y Acad 

Sci 1996;802:6-15. 

Full Text: Exclude - dementia @ baseline 

Tang WK, Chan SS, Chiu HF, et al. Frequency and 

determinants of prestroke dementia in a Chinese cohort. J 

Neurol 2004;251(5):604-8. 

Full Text: Exclude - <60% of dementia is AD 

Tanne D, Freimark D, Poreh A, et al. Cognitive functions 

in severe congestive heart failure before and after an 

exercise training program. Int J Cardiol 2005;103(2):145-9. 

Full Text: Exclude - risk factor out of scope 

Tedesco MA, Ratti G, Mennella S, et al. Comparison of 

losartan and hydrochlorothiazide on cognitive function and 

quality of life in hypertensive patients. Am J Hypertens 

1999;12(11 Pt 1):1130-4. 

Full Text: Exclude - AD/CD f/u < 1 yr 

Teunissen CE, Blom AH, Van Boxtel MP, et al. 

Homocysteine: a marker for cognitive performance? A 

longitudinal follow-up study. J Nutr Health Aging 

2003;7(3):153-9. 

Full Text: Exclude - observational N<300 

Teunissen CE, van Boxtel MP, Bosma H, et al. 

Inflammation markers in relation to cognition in a healthy 

aging population. J Neuroimmunol 2003;134(1-2):142-50. 

Full Text: Exclude - observatioanl N<300 

Thomas T, Thomas G, McLendon C, et al. beta-Amyloidmediated vasoactivity and vascular endothelial damage.[see 

comment]. Nature 1996;380(6570):168-71. 

Full Text: Exclude - risk factor out of scope 

Thyrum ET, Blumenthal JA, Madden DJ, et al. Family 

history of hypertension influences neurobehavioral function 

in hypertensive patients. Psychosom Med 1995;57(5):496-

500. 

Full Text: Exclude - risk factor out of scope 

Tierney MC, Yao C, Kiss A, et al. Neuropsychological 

tests accurately predict incident Alzheimer disease after 5 

and 10 years. Neurology 2005;64(11):1853-9. 

Full Text: Exclude - risk factor out of scope 

Tilvis RS, Kahonen-Vare MH, Jolkkonen J, et al. 

Predictors of cognitive decline and mortality of aged people 

over a 10-year period. J Gerontol A Biol Sci Med Sci 

2004;59(3):268-74. 

Full Text: Exclude - dementia @ baseline 

Tinetti ME, McAvay GJ, Fried TR, et al. Health outcome 

priorities among competing cardiovascular, fall injury, and 

medication-related symptom outcomes. J Am Geriatr Soc 

2008;56(8):1409-16. 

Full Text: Exclude - risk factor out of scope 

Toobert DJ, Strycker LA, Glasgow RE, et al. Enhancing 

support for health behavior change among women at risk 

for heart disease: the Mediterranean Lifestyle Trial. Health 

Educ Res 2002;17(5):574-85. 

Full Text: Exclude - risk factor out of scope 

Toro P, Schonknecht P, Schroder J. Type II diabetes in 

mild cognitive impairment and Alzheimer's disease: results 

from a prospective population-based study in Germany. J 

Alzheimers Dis 2009;16(4):687-91. 

Full Text: Exclude - observational N<300 

Trompet S, de Craen AJ, Slagboom P, et al. Genetic 

variation in the interleukin-1 beta-converting enzyme 

associates with cognitive function. The PROSPER study. 

Brain 2008;131(Pt 4):1069-77. 

Full Text: Exclude - risk factor out of scope 

Trompet S, Westendorp RG, Kamper AM, et al. Use of 

calcium antagonists and cognitive decline in old age. The 

Leiden 85-plus study. Neurobiol Aging 2008;29(2):306-8. 
G-35

Full Text: Exclude - observational N<300 

Troyer AK, Murphy KJ, Anderson ND, et al. Changing 

everyday memory behaviour in amnestic mild cognitive 

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Full Text: Exclude - risk factor out of scope 

Tsivgoulis G, Alexandrov AV, Wadley VG, et al. 

Association of higher diastolic blood pressure levels with 

cognitive impairment. Neurology 2009;73(8):589-95. 

Full Text: Exclude - not longitudinal 

Tsutsumi T, Don BM, Zaichkowsky LD, et al. Physical 

fitness and psychological benefits of strength training in 

community dwelling older adults. Appl Human Sci 

1997;16(6):257-66. 

Full Text: Exclude - AD/CD f/u < 1 yr 

Tucker KL, Qiao N, Scott T, et al. High homocysteine and 

low B vitamins predict cognitive decline in aging men: the 

Veterans Affairs Normative Aging Study. Am J Clin Nutr 

2005;82(3):627-35. 

Full Text: Exclude - observational N<300 

Tucker-Drob EM, Johnson KE, Jones RN. The cognitive 

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Full Text: Exclude - risk factor out of scope 

Uusvaara J, Pitkala KH, Tienari PJ, et al. Association 

between anticholinergic drugs and apolipoprotein E 

epsilon4 allele and poorer cognitive function in older 

cardiovascular patients: a cross-sectional study. J Am 

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Full Text: Exclude - risk factor out of scope 

van de Rest O, Geleijnse JM, Kok FJ, et al. Effect of fish 

oil on cognitive performance in older subjects: a 

randomized, controlled trial. Neurology 2008;71(6):430-8. 

Full Text: Exclude - AD/CD f/u < 1 yr 

van den Berg E, Biessels GJ, de Craen AJ, et al. The 

metabolic syndrome is associated with decelerated 

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Full Text: Exclude - observational N<300 

van den Berg E, de Craen AJ, Biessels GJ, et al. The impact 

of diabetes mellitus on cognitive decline in the oldest of the 

old: a prospective population-based study. Diabetologia 

2006;49(9):2015-23. 

Full Text: Exclude - obervational N<300 

van den Berg E, Dekker JM, Nijpels G, et al. Cognitive 

functioning in elderly persons with type 2 diabetes and 

metabolic syndrome: the Hoorn study. Dement Geriatr 

Cogn Disord 2008;26(3):261-9. 

Full Text: Exclude - observational N<300 

Van den Heuvel DM, ten Dam VH, de Craen AJ, et al. 

Increase in periventricular white matter hyperintensities 

parallels decline in mental processing speed in a nondemented elderly population. J Neurol Neurosurg 

Psychiatry 2006;77(2):149-53. 

Full Text: Exclude - risk factor out of scope 

van den Heuvel N, Smits CH, Deeg DJ, et al. Personality: a 

moderator of the relation between cognitive functioning 

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1996;41(3):229-40. 

Full Text: Exclude - not longitudinal 

van Dongen MC, van Rossum E, Kessels AG, et al. The 

efficacy of ginkgo for elderly people with dementia and 

age-associated memory impairment: new results of a 

randomized clinical trial. J Am Geriatr Soc 

2000;48(10):1183-94. 

Full Text: Exclude - dementia @ baseline 

van Gelder BM, Tijhuis M, Kalmijn S, et al. Fish 

consumption, n-3 fatty acids, and subsequent 5-y cognitive 

decline in elderly men: the Zutphen Elderly Study. Am J 

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Full Text: Exclude - observational N<300 

van Gelder BM, Tijhuis MA, Kalmijn S, et al. Physical 

activity in relation to cognitive decline in elderly men: the 

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Full Text: Exclude - observational N<300 

van Kooten F, Ciabattoni G, Koudstaal PJ, et al. Increased 

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Full Text: Exclude - risk factor out of scope 

Van Ness PH, Kasl SV. Religion and cognitive dysfunction 

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2003;58(1):S21-9. 

Full Text: Exclude - SPMSQ single test 

van Oijen M, Okereke OI, Kang JH, et al. Fasting insulin 

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diabetes. Neuroepidemiology 2008;30(3):174-9. 

Full Text: Exclude - risk factor out of scope 

van Swieten JC, Geyskes GG, Derix MM, et al. 

Hypertension in the elderly is associated with white matter 

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30. 

Full Text: Exclude - observational N<300 

van Uffelen JG, Hopman-Rock M, Chin APMJ, et al. 

Protocol for Project FACT: a randomised controlled trial on 

the effect of a walking program and vitamin B 

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Full Text: Exclude - methods paper, no primary data 

Vanhanen M, Koivisto K, Kuusisto J, et al. Cognitive 

function in an elderly population with persistent impaired 

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G-36

Full Text: Exclude - not longitudinal 

Vanhanen M, Koivisto K, Moilanen L, et al. Association of 

metabolic syndrome with Alzheimer disease: a populationbased study. Neurology 2006;67(5):843-7. 

Full Text: Exclude - not longitudinal 

Vaughan C, Goldstein FC, Tenover JL. Exogenous 

testosterone alone or with finasteride does not improve 

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serum testosterone. J Androl 2007;28(6):875-82. 

Full Text: Exclude - RCT N<50 

Velho S, Marques-Vidal P, Baptista F, et al. Dietary intake 

adequacy and cognitive function in free-living active 

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Clin Nutr 2008;27(1):77-86. 

Full Text: Exclude - AD/CD f/u < 1 yr 

Vercambre MN, Boutron-Ruault MC, Ritchie K, et al. 

Long-term association of food and nutrient intakes with 

cognitive and functional decline: a 13-year follow-up study 

of elderly French women. Br J Nutr 2009;102(3):419-27. 

Full Text: Exclude - not longitudinal 

Verhaegen P, Borchelt M, Smith J. Relation between 

cardiovascular and metabolic disease and cognition in very 

old age: cross-sectional and longitudinal findings from the 

berlin aging study. Health Psychol 2003;22(6):559-69. 

Full Text: Exclude - observational N<300 

Vicario A, Martinez CD, Baretto D, et al. Hypertension and 

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Hypertens (Greenwich) 2005;7(10):598-604. 

Full Text: Exclude - observational N<300 

Vicini Chilovi B, Conti M, Zanetti M, et al. Differential 

impact of apathy and depression in the development of 

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Geriatr Cogn Disord 2009;27(4):390-8. 

Full Text: Exclude - observational N<300 

Vincze G, Almos P, Boda K, et al. Risk factors of cognitive 

decline in residential care in Hungary. Int J Geriatr 

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Full Text: Exclude - non-Western country 

Vinkers DJ, Gussekloo J, Stek ML, et al. Temporal relation 

between depression and cognitive impairment in old age: 

prospective population based study. BMJ 

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Full Text: Exclude - Q2 continuous data only 

Vinkers DJ, Stek ML, van der Mast RC, et al. Generalized 

atherosclerosis, cognitive decline, and depressive 

symptoms in old age. Neurology 2005;65(1):107-12. 

Full Text: Exclude - risk factor out of scope 

Viramo P, Luukinen H, Koski K, et al. Orthostatic 

hypotension and cognitive decline in older people. J Am 

Geriatr Soc 1999;47(5):600-4. 

Full Text: Exclude - risk factor out of scope 

Viswanath B, Janardhan Reddy YC, Kumar KJ, et al. 

Cognitive endophenotypes in OCD: a study of unaffected 

siblings of probands with familial OCD. Prog 

Neuropsychopharmacol Biol Psychiatry 2009;33(4):610-5. 

Full Text: Exclude - risk factor out of scope 

Vitaliano PP, Echeverria D, Yi J, et al. Psychophysiological 

mediators of caregiver stress and differential cognitive 

decline. Psychol Aging 2005;20(3):402-11. 

Full Text: Exclude - dementia @ baseline 

Vlad SC, Miller DR, Kowall NW, et al. Protective effects 

of NSAIDs on the development of Alzheimer disease. 

Neurology 2008;70(19):1672-7. 

Full Text: Exclude - outcomes unacceptably assessed 

Vogiatzoglou A, Refsum H, Johnston C, et al. Vitamin B12 

status and rate of brain volume loss in community-dwelling 

elderly. Neurology 2008;71(11):826-32. 

Full Text: Exclude - outcomes unacceptably assessed 

von Muhlen D, Laughlin GA, Kritz-Silverstein D, et al. 

The Dehydroepiandrosterone And WellNess (DAWN) 

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2007;28(2):153-68. 

Full Text: Exclude - methods paper, no results 

Wadley VG, McClure LA, Howard VJ, et al. Cognitive 

status, stroke symptom reports, and modifiable risk factors 

among individuals with no diagnosis of stroke or transient 

ischemic attack in the REasons for Geographic and Racial 

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Full Text: Exclude - not longitudinal 

Wagner S, Kaschel R, Paulsen S, et al. Does a cognitivetraining programme improve the performance of middleaged employees undergoing in-patient psychosomatic 

treatment? Disabil Rehabil 2008;30(23):1786-93. 

Full Text: Exclude - selected population 

Waldstein SR, Brown JR, Maier KJ, et al. Diagnosis of 

hypertension and high blood pressure levels negatively 

affect cognitive function in older adults. Ann Behav Med 

2005;29(3):174-80. 

Full Text: Exclude - observational N<300 

Waldstein SR, Katzel LI. Gender differences in the relation 

of hypertension to cognitive function in older adults. 

Neurol Res 2004;26(5):502-6. 

Full Text: Exclude - observational N<300 

Waldstein SR, Rice SC, Thayer JF, et al. Pulse pressure and 

pulse wave velocity are related to cognitive decline in the 

Baltimore Longitudinal Study of Aging. Hypertension 

2008;51(1):99-104. 

Full Text: Exclude - risk factor out of scope 

Wallin MT, Wilken J, Alfaro MH, et al. Neuropsychologic 

assessment of a population-based sample of Gulf War 

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G-37

Full Text: Exclude - risk factor out of scope 

Wang FT, Hu H, Schwartz J, et al. Modifying effects of the 

HFE polymorphisms on the association between lead 

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Full Text: Exclude - risk factor out of scope 

Wang H-X, Karp A, Winblad B, et al. Late-life engagement 

in social and leisure activities is associated with a 

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Kungsholmen project. Am J Epidemiol 2002;155(12):1081-

7. 

Full Text: Exclude - <60% of dementia is AD 

Wang JY, Zhou DH, Li J, et al. Leisure activity and risk of 

cognitive impairment: the Chongqing aging study. 

Neurology 2006;66(6):911-3. 

Full Text: Exclude - non-Western country 

Wang L, van Belle G, Kukull WB, et al. Predictors of 

functional change: a longitudinal study of nondemented 

people aged 65 and older. J Am Geriatr Soc 

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Full Text: Exclude - outcomes unacceptably assessed 

Wang XM, Fu H, Liu GX, et al. Effect of modified wuzi 

yanzong granule on patients with mild cognitive 

impairment from oxidative damage aspect. Chin J Integr 

Med 2007;13(4):258-63. 

Full Text: Exclude - non-Western country 

Wardle J, Rogers P, Judd P, et al. Randomized trial of the 

effects of cholesterol-lowering dietary treatment on 

psychological function. Am J Med 2000;108(7):547-53. 

Full Text: Exclude - AD f/u < 2 yr 

Weber P, Meluzinova H, Kubesova H, et al. Insulin 

treatment in diabetics 75+ years: experiences and results in 

outpatient care. Adv Gerontol 2008;21(1):143-7. 

Full Text: Exclude - comparator is not placebo/control 

Weil M, Bressler J, Parsons P, et al. Blood mercury levels 

and neurobehavioral function. JAMA 2005;293(15):1875-

82. 

Full Text: Exclude - not longitudinal 

Wenisch E, Cantegreil-Kallen I, De Rotrou J, et al. 

Cognitive stimulation intervention for elders with mild 

cognitive impairment compared with normal aged subjects: 

preliminary results. Aging Clin Exp Res 2007;19(4):316-

22. 

Full Text: Exclude - AD/CD f/u < 1 yr 

Weuve J, Korrick SA, Weisskopf MG, et al. Cumulative 

exposure to lead in relation to cognitive function in older 

women. Environ Health Perspect 2009;117(4):574-80. 

Full Text: Exclude - not longitudinal 

Whalley LJ, Deary IJ, Starr JM, et al. n-3 Fatty acid 

erythrocyte membrane content, APOE varepsilon4, and 

cognitive variation: an observational follow-up study in late 

adulthood. Am J Clin Nutr 2008;87(2):449-54. 

Full Text: Exclude - observational N<300 

Whalley LJ, Fox HC, Deary IJ, et al. Childhood IQ, 

smoking, and cognitive change from age 11 to 64 years. 

Addict Behav 2005;30(1):77-88. 

Full Text: Exclude - observational N<300 

White L, Katzman R, Losonczy K, et al. Association of 

education with incidence of cognitive impairment in three 

established populations for epidemiologic studies of the 

elderly. J Clin Epidemiol 1994;47(4):363-74. 

Full Text: Exclude - SPMSQ single test 

White LR, Petrovitch H, Ross GW, et al. Brain aging and 

midlife tofu consumption. J Am Coll Nutr 2000;19(2):242-

55. 

Full Text: Exclude - not longitudinal 

Whitmer RA, Gunderson EP, Quesenberry CP, Jr., et al. 

Body mass index in midlife and risk of Alzheimer disease 

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9. 

Full Text: Exclude - not longitudinal 

Whitmer RA, Sidney S, Selby J, et al. Midlife 

cardiovascular risk factors and risk of dementia in late life. 

Neurology 2005;64(2):277-81. 

Full Text: Exclude - outcomes unacceptably assessed 

Wilkie FL, Eisdorfer C, Nowlin JB. Memory and blood 

pressure in the aged. Exp Aging Res 1976;2(1):3-16. 

Full Text: Exclude - observational N<300 

Williamson JD, Vellas B, Furberg C, et al. Comparison of 

the design differences between the Ginkgo Evaluation of 

Memory study and the GuidAge study. J Nutr Health Aging 

2008;12(1):73S-9S. 

Full Text: Exclude - methods - no data 

Wilson RS, Arnold SE, Schneider JA, et al. Chronic 

distress, age-related neuropathology, and late-life dementia. 

Psychosom Med 2007;69(1):47-53. 

Full Text: Exclude - observational N<300 

Wilson RS, Barnes LL, Bennett DA, et al. Proneness to 

psychological distress and risk of Alzheimer disease in a 

biracial community. Neurology 2005;64(2):380-2. 

Full Text: Exclude - risk factor out of scope 

Wilson RS, Mendes De Leon CF, Bennett DA, et al. 

Depressive symptoms and cognitive decline in a 

community population of older persons. J Neurol 

Neurosurg Psychiatry 2004;75(1):126-9. 

Full Text: Exclude - Q2 continuous data only 

Wolf PA, Beiser A, Elias MF, et al. Relation of obesity to 

cognitive function: importance of central obesity and 

synergistic influence of concomitant hypertension. The 

Framingham Heart Study. Curr Alzheimer Res 

2007;4(2):111-6. 

Full Text: Exclude - not longitudinal 
G-38

Wolfson C, Perrault A, Moride Y, et al. A case-control 

analysis of nonsteroidal anti-inflammatory drugs and 

Alzheimer's disease: are they protective? 

Neuroepidemiology 2002;21(2):81-6. 

Full Text: Exclude - AD f/u < 2 yr 

Wolinsky FD, Unverzagt FW, Smith DM, et al. The 

ACTIVE cognitive training trial and health-related quality 

of life: protection that lasts for 5 years. J Gerontol A Biol 

Sci Med Sci 2006;61(12):1324-9. 

Full Text: Exclude - no cognitive end points 

Wolkowitz OM, Kramer JH, Reus VI, et al. DHEA 

treatment of Alzheimer's disease: a randomized, doubleblind, placebo-controlled study. Neurology 

2003;60(7):1071-6. 

Full Text: Exclude - dementia @ baseline 

Wolozin B, Kellman W, Ruosseau P, et al. Decreased 

prevalence of Alzheimer disease associated with 3-

hydroxy-3-methyglutaryl coenzyme A reductase inhibitors. 

Arch Neurol 2000;57(10):1439-43. 

Full Text: Exclude - not longitudinal 

Wolters M, Hickstein M, Flintermann A, et al. Cognitive 

performance in relation to vitamin status in healthy elderly 

German women-the effect of 6-month multivitamin 

supplementation. Prev Med 2005;41(1):253-9. 

Full Text: Exclude - AD/CD f/u < 1 yr 

Woo J, Lau E, Ho SC, et al. Comparison of Pueraria lobata 

with hormone replacement therapy in treating the adverse 

health consequences of menopause. Menopause 

2003;10(4):352-61. 

Full Text: Exclude - AD/CD f/u < 1 yr 

Woo J, Lynn H, Lau WY, et al. Nutrient intake and 

psychological health in an elderly Chinese population. Int J 

Geriatr Psychiatry 2006;21(11):1036-43. 

Full Text: Exclude - AD f/u < 2 yr 

Woods NF, Carr MC, Tao EY, et al. Increased urinary 

cortisol levels during the menopausal transition. 

Menopause 2006;13(2):212-21. 

Full Text: Exclude - risk factor out of scope 

Worth RM, Kagan A. Ascertainment of men of Japanese 

ancestry in Hawaii through World War II Selective Service 

registration. J Chronic Dis 1970;23(5):389-97. 

Full Text: Exclude - risk factor out of scope 

Wright CE, Kunz-Ebrecht SR, Iliffe S, et al. Physiological 

correlates of cognitive functioning in an elderly population. 

Psychoneuroendocrinology 2005;30(9):826-38. 

Full Text: Exclude - AD f/u < 2 yr 

Wroolie TE, Kenna HA, Williams KE, et al. Cognitive 

effects of memantine in postmenopausal women at risk of 

dementia: a pilot study. Acta Neurol Scand 

2009;119(3):172-9. 

Full Text: Exclude - AD/CD f/u < 1 yr 

Wu JH, Haan MN, Liang J, et al. Impact of antidiabetic 

medications on physical and cognitive functioning of older 

Mexican Americans with diabetes mellitus: a populationbased cohort study. Ann Epidemiol 2003;13(5):369-76. 

Full Text: Exclude - risk factor out of scope 

Wu YH, Feenstra MG, Zhou JN, et al. Molecular changes 

underlying reduced pineal melatonin levels in Alzheimer 

disease: alterations in preclinical and clinical stages. J Clin 

Endocrinol Metab 2003;88(12):5898-906. 

Full Text: Exclude - risk factor out of scope 

Wurzelmann J, Frishman WH, Aronson M, et al. 

Neuropsychological effects of antihypertensive drugs. 

Cardiol Clin 1987;5(4):689-701. 

Full Text: Exclude - not longitudinal 

Xiong GL, Plassman BL, Helms MJ, et al. Vascular risk 

factors and cognitive decline among elderly male twins. 

Neurology 2006;67(9):1586-91. 

Full Text: Exclude - <60% of dementia is AD 

Xu G, Liu X, Yin Q, et al. Alcohol consumption and 

transition of mild cognitive impairment to dementia. 

Psychiatry Clin Neurosci 2009;63(1):43-9. 

Full Text: Exclude - non-Western country 

Xu W, Qiu C, Winblad B, et al. The effect of borderline 

diabetes on the risk of dementia and Alzheimer's disease. 

Diabetes 2007;56(1):211-6. 

Full Text: Exclude - risk factor out of scope 

Yaffe K, Barnes D, Lindquist K, et al. Endogenous sex 

hormone levels and risk of cognitive decline in an older 

biracial cohort. Neurobiol Aging 2007;28(2):171-8. 

Full Text: Exclude - risk factor out of scope 

Yaffe K, Barrett Connor E, Lin F, et al. Serum lipoprotein 

levels, statin use, and cognitive function in older women. 

Arch Neurol 2002;59(3):378-84. 

Full Text: Exclude - not longitudinal 

Yaffe K, Ettinger B, Pressman A, et al. Neuropsychiatric 

function and dehydroepiandrosterone sulfate in elderly 

women: a prospective study. Biol Psychiatry 

1998;43(9):694-700. 

Full Text: Exclude - risk factor out of scope 

Yaffe K, Lindquist K, Shlipak MG, et al. Cystatin C as a 

marker of cognitive function in elders: findings from the 

health ABC study. Ann Neurol 2008;63(6):798-802. 

Full Text: Exclude - risk factor out of scope 

Yaffe K, Lui LY, Grady D, et al. Cognitive decline in 

women in relation to non-protein-bound oestradiol 

concentrations. Lancet 2000;356(9231):708-12. 

Full Text: Exclude - risk factor out of scope 

Yamada M, Kasagi F, Sasaki H, et al. Association between 

dementia and midlife risk factors: the Radiation Effects 

Research Foundation Adult Health Study. J Am Geriatr Soc 
G-39

2003;51(3):410-4. 

Full Text: Exclude - not general population 

Yamada M, Mimori Y, Kasagi F, et al. Incidence and risks 

of dementia in Japanese women: Radiation Effects 

Research Foundation Adult Health Study. J Neurol Sci 

2009;283(1-2):57-61. 

Full Text: Exclude - not general population 

Yen PK. Maintaining cognitive function with diet. Geriatr 

Nurs 2003;24(1):62-3. 

Full Text: Exclude - risk factor out of scope 

Yip AG, Brayne C, Matthews FE. Risk factors for incident 

dementia in England and Wales: The Medical Research 

Council Cognitive Function and Ageing Study. A 

population-based nested case-control study. Age Ageing 

2006;35(2):154-60. 

Full Text: Exclude - <60% of dementia is AD 

Yip AG, Green RC, Huyck M, et al. Nonsteroidal antiinflammatory drug use and Alzheimer's disease risk: the 

MIRAGE Study. BMC Geriatr 2005;5:2. 

Full Text: Exclude - dementia @ baseline 

Yodfat Y, Bar-On D, Amir M, et al. Quality of life in 

normotensives compared to hypertensive men treated with 

isradipine or methyldopa as monotherapy or in combination 

with captopril: the LOMIR-MCT-IL study. J Hum 

Hypertens 1996;10(2):117-22. 

Full Text: Exclude - comparator not placebo/control 

Young SE, Mainous AG, 3rd, Carnemolla M. 

Hyperinsulinemia and cognitive decline in a middle-aged 

cohort. Diabetes Care 2006;29(12):2688-93. 

Full Text: Exclude - risk factor out of scope 

Zamrini E, McGwin G, Roseman JM. Association between 

statin use and Alzheimer's disease. Neuroepidemiology 

2004;23(1-2):94-8. 

Full Text: Exclude - outcome non-specific AD 

Zhang Z, Gu D, Hayward MD. Early life influences on 

cognitive impairment among oldest old Chinese. J Gerontol 

B Psychol Sci Soc Sci 2008;63(1):S25-33. 

Full Text: Exclude - non-Western country 

Zhang ZX, Plassman BL, Xu Q, et al. Lifespan influences 

on mid- to late-life cognitive function in a Chinese birth 

cohort. Neurology 2009;73(3):186-94. 

Full Text: Exclude - non-Western country 

Zielinska J, Ryglewicz D, Wierzchowska E, et al. 

Anticardiolipin antibodies are an independent risk factor 

for ischemic stroke. Neurol Res 1999;21(7):653-7. 

Full Text: Exclude - risk factor out of scope 

Zimpfer D, Czerny M, Vogt F, et al. Neurocognitive deficit 

following coronary artery bypass grafting: a prospective 

study of surgical patients and nonsurgical controls. Ann 

Thorac Surg 2004;78(2):513-8; discussion 518-9. 

Full Text: Exclude - risk factor out of scope 

Zunzunegui MV, Beland F, Gutierrez-Cuadra P. Loss to 

follow-up in a longitudinal study on aging in Spain. J Clin 

Epidemiol 2001;54(5):501-10. 

Full Text: Exclude - risk factor out of scope