bluuebunny/crossref_metadata_2025_split huggingface dataset:
Public health interventions to reduce Alzheimer’s risk: Need for tailored approaches
Authors: Nianogo Roch A , Rosenwohl‐Mack Amy , Yaffe Kristine , Carrasco Anna , Barnes Deborah 
Published: December 2021

AbstractBackgroundWe have previously estimated that 30% of Alzheimer’s disease in the U.S. may be attributable to modifiable risk factors, and that the most important risk factors to target are physical inactivity, depression, and smoking. However, estimates in the U.S. population as a whole may not be ideal for guiding public health messaging about Alzheimer's risk reduction because they do not take into consideration the unique risk factor profiles of different regions. In this study, we estimate the proportion of Alzheimer’s disease cases that are potentially attributable to modifiable risk factors in California, which has the largest and most diverse population in the U.S.MethodWe calculated individual and combined population attributable risks (PARs) for Alzheimer’s disease in California for eight modifiable risk factors: physical inactivity, smoking, depression, low education, diabetes, midlife obesity, midlife hypertension, and hearing loss. Relative risks for each risk factor were extracted from recent meta‐analyses. Risk factor prevalence and communality were determined using data from the 2017 and 2018 California Behavioral Risk Factor Surveillance Survey, a population‐based survey weighted to provide representative estimates. To account for non‐independence of the risk factors, we estimated the communality and uniqueness of each risk factor via principal component analysis and applied them to Levin’s formula.ResultsIn California, the estimated PARs (95% confidence intervals) for modifiable risk factors were as follows: low education: 14.0% (13.3%, 14.8%), midlife obesity: 13.4% (12.9%, 13.9%), physical inactivity: 10.3% (9.8%, 10.8%), midlife hypertension: 7.4% (7.2%, 7.7%), depression: 7.4% (7.0%, 7.7%), diabetes: 6.7% (6.2%, 7.2%), smoking: 4.5% (4.2%, 4.8%), and hearing loss: 1.9% (1.7%, 2.1%). The combined PAR estimate was 29.4% (28.1%, 30.7%) incorporating the correlations between risk factors.ConclusionConsistent with our previous U.S. estimates, we found that about a third of Alzheimer’s disease cases in California might be attributable to modifiable risk factors. However, the most important risk factors differed, with low education, midlife obesity and physical inactivity contributing to the largest proportion of cases. Public health interventions to reduce dementia risk may be more effective if tailored to address the most important risk factors in the region.
Generational differences in cognitive function in middle‐aged to older adults
Authors: Merten Natascha , Pinto A Alex , Paulsen Adam J , Carlsson Cynthia M , Chen Yanjun , Schubert Carla R , Cruickshanks Karen J 
Published: December 2021

AbstractBackgroundCognitive impairment and dementia are major health concerns. While the number of cases is expected to increase with the aging populations, recent research shows that age‐specific dementia prevalence rates are declining. This may be due to reduced risks of cardiovascular and metabolic diseases and harmful environmental exposures and healthier lifestyles. Given the decades‐long preclinical phase of dementia, detection of early cognitive changes might improve future treatment and prevention methods. However, research on generational differences in cognitive function in middle‐aged to older adults is limited. The aim of this study was to determine whether individuals from more recent generations show better cognitive function.MethodThis cross‐sectional study is based on data from 4439 participants from the Epidemiology of Hearing Loss Study (EHLS) and Beaver Dam Offspring Study (BOSS), two studies of adults in Beaver Dam, Wisconsin. Each participant’s birth year was used to assign a birth cohort (1901‐1924: Greatest Generation; 1925‐1945: Silent Generation; 1946‐1964: Baby Boom Generation; 1965‐1984: Generation X). Cognitive function was assessed by Trail‐making Test A and B (TMTA, TMTB). We used multivariable linear regression models adjusted for age and sex to determine birth cohort (generational) differences in TMT performance. We repeated models adjusting for education.ResultIn preliminary analyses, TMTA performance was better in more recent generations as compared to the Greatest Generation (Silent: ‐26.88 seconds (s); 95 % confidence interval (CI) ‐30.60,‐23.15; Baby Boom: ‐25.70s; 95% CI ‐30.64,‐20.77; Generation X: ‐17.82s; 95% CI ‐24.37,‐11.27). Performance on TMTB showed larger generational differences as compared to the Greatest Generation: Silent: ‐50.04s; 95% CI ‐58.11,‐41.97; Baby Boom: ‐63.38s; 95% CI ‐73.83,‐52.93; Generation X: ‐43.53s; 95% CI ‐57.23,‐29.83. Although education levels differed by generation, including education did not change these patterns.ConclusionThis study suggests better processing speed and executive function performance among more recent generations even when adjusting for educational levels. This implies that future burdens of cognitive decline and dementia may be lower than currently estimated. The difference also suggests that there are modifiable risk factors that may help to explain the etiology of cognitive decline and provide potential pathways for healthy brain aging and prevention of Alzheimer’s disease and other dementias.
Soluble P‐tau217 reflects both amyloid and tau pathology in the human brain and mediates the association of amyloid with neocortical tau
Authors: Mattsson‐Carlgren Niklas , Janelidze Shorena , Bateman Randall J. , Smith Ruben , Stomrud Erik , Serrano Geidy E. , Reiman Eric M. , Palmqvist Sebastian , Dage Jeffrey L. , Beach Thomas G. , Hansson Oskar 
Published: December 2021

AbstractBackgroundAlzheimer’s disease is characterized by β‐amyloid plaques and tau tangles. Plasma levels of phospho‐tau217 (P‐tau217) accurately differentiate Alzheimer’s disease dementia from other dementias, but it is unclear to what degree this reflects β‐amyloid plaque accumulation, tau tangle accumulation, or both.MethodWe studied plasma P‐tau217 in a cohort with post‐mortem neuropathological data (N=88), for correlations with plaque and tangle density, and in a cohort with β‐amyloid and tau PET imaging (“BioFINDER‐2”, N=426).ResultIn the cohort with post‐mortem neuropathological data, both plaque and tangle density contributed independently to higher P‐tau217 (Fig 1). Several findings were replicated in the cohort with PET imaging, where β‐amyloid and tau PET were independently associated to P‐tau217. P‐tau217 correlated with β‐amyloid PET (but not tau PET) in early disease stages, and with both β‐amyloid and (more strongly) tau PET in late disease stages (Fig 2). Finally, P‐tau217 mediated the association between β‐amyloid and tau in both cohorts, especially for tau outside of the medial temporal lobe (Fig 3).ConclusionThese findings support the hypothesis that plasma P‐tau217 is associated with both β‐amyloid plaques and tau tangles and is congruent with the hypothesis that P‐tau is involved in β‐amyloid‐dependent formation of neocortical tau tangles (Fig 4).
Digital Trail Making Test‐Black & White: Normal vs MCI
Authors: Simfukwe Chanda , Youn Young Chul , Kim Sangyun , An Seong Soo 
Published: December 2021

AbstractBackgroundTrail Making Test‐Black and White (TMT‐B&W) was developed to assess the cognition of patients with mild cognitive impairment (MCI), dementia, and Alzheimer’s disease. Collection and analysis of test results have been limited due to scoring time and efforts required from both administrators and patients during and after taking the test. To increase efficiency and reducing scoring time, a computer version touchscreen‐based digital trail making test‐black and white (dTMT‐B&W) was developed on Android and it was administered on MCI versus cognitively normal controls (NC) participants. The current study examines the sensitivity of newly developed computer version dTMT‐B&W on NC and MCI subjects.MethoddTMT‐B&W was developed using MIT app inventor software, a web‐based integrated development environment (IDE) with the Android development tools that are used to build fully functional applications for smartphones and tablets. A total of 44 participants were included, comprised of 22 NC and 22 MCI. The dTMT‐TMT‐B&W was administered to all NC and MCI subjects.ResultdTMT‐B&W was designed to be as consistent with the pen‐paper TMT‐B&W (ppTMT‐B&W) where the application is a standalone installation. dTMT‐B&W is divided into two parts (Part‐A and Part‐B), in which the subject attempts to connect black and white numbered circles sequentially as quickly as possible, while still maintaining accuracy. Similarly, the paper‐based TMT‐B&W requires the subject to connect black and white numbered circles in ascending order, except on a sheet of paper rather than a tablet. dTMT‐B&W successfully distinguished NC from MCI subjects.ConclusiondTMT‐B&W is an Android application that was successfully developed to be as consistent as possible with the original pen‐paper TMT‐B&W to establish equal concurrent validity, with some improved features embedded into the design and dTMT‐B&W revealed a significant correlation with frontal executive function and this can help in early diagnosing subjects with MCI among NC subjects.
Comparison of RCF scoring system to clinical decision for the Rey complex figure using machine‐learning algorithm
Authors: Simfukwe Chanda , Youn Young Chul , An Seong Soo 
Published: December 2021

AbstractBackgroundThe interpreting of RCF scoring requires the standard RCF scoring system and the clinical decision, based on clinical dementia rate (CDR) by clinicians. The interpretation of RCF using clinical decision might not be accurate in the detection of mild cognitive impairment (MCI), or dementia patients in comparison to the RCF scoring system. For this reason, a machine‐learning algorithm was used to demonstrate that scoring RCF using clinical decision was not as accurate as the RCF scoring system in predicting MCI or dementia patients from healthy subjects.MethodThe RCF dataset, which consisted of 2,232 subjects, was collected from formal neuropsychological assessments at Chung‐Ang University Hospital. The RCF dataset was classified according to different criteria, where the first dataset had normal and abnormal subjects. They were grouped depending on the threshold cutoff point of 16%, based on the RCF scoring system. The second dataset had normal, MCI, and dementia subjects, classified depending on the clinical decision from patient CDR scores. The models were trained using a convolutional neural network (CNN) for machine learning, and an artificial neural network algorithm Tensorflow was implemented to distinguish the prediction accuracies of cognitive states of two models: the first model (Normal, Abnormal), and the second model (Normal, MCI, and Dementia).ResultThe trained model's accuracy for predicting cognitive states was as following; 96% and 88% were from the first and second models, respectively. The first model had the sensitivity for detecting abnormal of 85% with an area under the receiver operating characteristic (ROC) curve of 0.847, and the second model had the sensitivity for detecting MCI or Dementia of 78% with an area under the ROC curve of 0.778.ConclusionThe first model, trained using a machine learning algorithm for predicting abnormal patients, was more accurate in comparison to the second model for predicting MCI or Dementia. Based on these results, the RCF scoring system has the potential of presenting better accurate criteria in distinguishing cognitive impairment among patients in comparison to the clinical decision.
Novel models of dementia care: Evidence from national dementia behavior support programs in Australia
Authors: Atee Mustafa , Morris Thomas , Macfarlane Stephen , Alford Marie , Cunningham Colm 
Published: December 2021

AbstractBackgroundBehaviors and psychological symptoms of dementia (BPSD) are frequently experienced by this population, as they reflect unmet biopsychosocial needs.[1] The occurrence of BPSD can be debilitating, distressing and impair quality of life, not only for the person living with dementia but also for their caregivers.[1] As such, people with BPSD have complex care needs that demand dedicated resources, tailored programs and specialized skills which are often missing in mainstream aged care services. To address these needs and to achieve a nationally consistent approach, the Australian Government has been funding the services of Dementia Support Australia (DSA). DSA is the leading national provider of 24/7 dementia‐specific behavior support programs in Australia. DSA programs include the Dementia Behavior Management Advisory Service (DBMAS) for mild‐moderate BPSD and the Severe Behavior Response Teams (SBRT) for moderate‐severe BPSD. These programs entail person‐centered and multimodal nonpharmacological, psychosocial and/or psychoeducational interventions to support people with BPSD and their caregivers. These are achieved through a case management framework that includes an onsite comprehensive/holistic assessment of medicosocial history (e.g. pain), surrounding environment (e.g. over/under‐stimulation) and prescribed medications to identify causes or triggers of BPSD (Figure 1).[1] DSA is delivered through a multidisciplinary and mobile workforce of dementia consultants, geriatricians/psychogeriatricians and support staff. DSA consultants are accredited against an industry‐specific program focused on dementia‐specific competencies and capabilities. Consultants include, but are not limited to, registered and mental health nurses, occupational therapists, physiotherapists, social workers, psychologists, dieticians, speech pathologists, and diversional therapists with significant experience working in dementia and aged care settings. Since establishment in 2016, DSA programs have supported over 30,000 client referrals from residential, community and acute care settings and have supported >80% of residential aged care homes in Australia. Typical demographics for DBMAS and SBRT clients are displayed in Figure 2. Data collected on referrals demonstrated reduced frequency and severity rates of BPSD and high levels of caregiver satisfaction. Thus, DSA programs provide a novel, effective, feasible and sustainable model of care and service delivery specifically designed to address perceived gaps in aged care systems. References [1] The IPA complete guides to BPSD‐Specialists guide. Northfield (Illinois) 2012.
B vitamins and prevention of cognitive decline and incident dementia: A systematic review and meta‐analysis
Authors: Wang Zhibin , Zhu Wei , Xing Yi , Tang Yi , Jia Jianping 
Published: December 2021

AbstractBackgroundElevation of homocysteine levels is a well‐established risk factor for dementia, yet controversy exists regarding whether B‐vitamin‐mediated reduction of homocysteine levels can benefit cognitive function. We aimed to investigate whether B vitamins can reduce the risk of cognitive decline and incident dementia.MethodPubMed, EMBASE, Cochrane Library, and Web of Science were searched for articles published from the inception dates to March 1, 2020. Studies were eligible if the endpoints included MMSE changes and risk of cognitive decline and/or dementia. Random‐effect or fixed‐effect models, depending on the degree of heterogeneity, were performed to calculate mean differences (MDs), hazard ratios (HRs), and odds ratios (ORs).ResultA total of 95 studies with 46175 participants (25 RCTs, 20 cohorts, and 50 cross‐sectional studies) were included. B vitamins can benefit cognitive function as measured by MMSE changes (MD, 0.13, 95% CI 0.04‐0.23), and this result was also significant in studies where placebo groups developed cognitive decline, suggesting that B vitamins slow cognitive decline. For the > 12 months interventional period stratum, B vitamins decreased cognitive decline (MD, 0.15, 95% CI 0.05‐0.25) compared to placebo; no such outcome was detected for the shorter interventional stratum. In the non‐dementia population, B vitamins slowed cognitive decline (MD, 0.15, 95% CI 0.04‐0.25) compared to placebo; this outcome was not found for the dementia population. Lower folate levels (but not B12 or B6) were associated with higher risk of dementia (OR, 1.76, 95% CI 1.24‐2.50) and cognitive decline (OR, 1.26, 95% CI 1.02‐1.55). Among the population without dementia aged 50 years and above, the risk of incident dementia was significantly decreased among individuals with higher intake of folate (HR, 0.61, 95% CI 0.47‐0.78) (but not B12 or B6).ConclusionOur meta‐analysis suggests that B vitamin supplementation is associated with slowing of cognitive decline, especially in populations who received early and long‐term intervention; higher intake of dietary folate is associated with a reduced risk of incident dementia in non‐dementia aged population.
Effects of education and occupational status on incident dementia: A COSMIC collaborative cohort study
Authors: Hyun Jinshil , Katz Mindy J , Hall Charles B , Lipton Richard B , Brodaty Henry , Guaita Antonio , Lobo Antonio , Riedel‐Heller Steffi G , Lipnicki Darren M , Sachdev Perminder S ,   Cohort Studies of Memory in an International Consortium (COSMIC)
Published: December 2021

AbstractBackgroundEducation and occupational status are expected to protect against dementia, but the research findings have been inconsistent. This project aimed to examine 1) the unique contributions of education and occupational status to incident dementia, and 2) the mediating effects of occupational status on the association between education and dementia across diverse cohorts.MethodEducation and occupational status were harmonized as binary variables (education: ‘High school completion or above’ vs. ‘Less than high school completion; occupational status: ‘Mid to high status’ vs. ‘Low status’) due to the potential threshold effects and availability across datasets. Clinical diagnosis of dementia was used as an outcome. Using a Coordinated Analysis with 9 international datasets from 7 countries over 4 continents (Table 1; Australia, Germany, Italy, South Korea, Spain, and USA), the Cox proportional hazard regression model was applied to each dataset with participants’ age as the reference point, followed by meta‐analysis to provide the weighted summary effect sizes. Mediation analysis was conducted using the causal mediation approach with survival data (VanderWeele, 2011).ResultWe used data from 10,203 participants whose baseline age ranged from 58 to 103 years. Higher levels of education and occupational status were independently associated with decreased risk of incident dementia (Table 2; HR=0.70, 95% CI=[0.54, 0.92] for education; HR=0.79, HR=[0.66, 0.94] for occupational status). Heterogeneity across datasets was moderate for the education model (I
2=37%) and low for the occupation model (I
2= 0%). For the mediation analysis, the indirect effect was marginally significant (HR=0.94, 95% CI=[0.87, 1.00]) and 12% of the effect of education was mediated by occupational status.ConclusionUsing datasets from wide geographical regions, we found that both early life education and adulthood occupational status were independently predictive of incident dementia. Occupational status showed a weak mediating effect on the association between education and dementia. This finding suggests the importance of dementia prevention efforts in any stage of life course. Policy needs to prioritize early life education (possibly up to secondary education) and also target individuals with low occupational status to deliver dementia prevention and intervention.
Effects of the COVID‐19 pandemic on healthcare and community‐based service use for people living with dementia: Perspectives from dementia care professionals
Authors: Hunt Jack FV , Schroeder Molly , LeCaire Tamara , O'Toole Smith Kathleen , Marschall Katelyn , Walaszek Art 
Published: December 2021

AbstractBackgroundDementia care and healthcare delivery systems have changed substantially as a result of the COVID‐19 pandemic (Wang et al., 2020). Experts have identified a number of barriers to health care access for people living with dementia (PLWD) during the pandemic, including difficulty implementing telemedicine practices, discontinuation of home care services, increased caregiver burden and financial hardship (Brown et al., 2020; Greenberg et al., 2020). Assessment of dementia care providers’ perceptions of the change in use of healthcare and community‐based services by PLWD is needed to identify gaps and to improve care for this vulnerable population during the COVID‐19 pandemic.MethodsWe designed an online survey asking about changes to PLWD and caregiver use of 14 healthcare and community‐based services during the COVID‐19 pandemic and about 15 factors that may have contributed to these changes. The survey was distributed to a network of dementia care professionals across the state of Wisconsin between August 28th and October 9th, 2020.ResultA total of 102 individuals completed the survey. Most respondents worked in the Wisconsin Department of Health Services dementia care specialist system, were employed by Aging and Disability Resource Centers (53.5%), identified as female, White race and worked in rural settings. Services most frequently reported as no longer in use included senior center programs, adult day programs, and companion/friendly visitor services, while meal delivery was reported as having increased use by PLWD. Factors identified most frequently as barriers to service use included changes in access to caregiver support/respite services, access to natural supports, compassion fatigue/caregiver burnout and both knowledge of and access to technology/virtual tools.ConclusionThe results highlight the increased demand for certain services like meal delivery and the need to find alternatives to in‐person enrichment/recreational and caregiver respite opportunities such as senior center and adult day programs that are being used less. Access to and knowledge of technology and increased stress on caregivers and support systems were identified as some of the more frequent barriers to service use, thus allocating resources towards these areas may be particularly impactful towards improving service use for PLWD during the COVID‐19 pandemic.