A STATEMENT BY THE 

CENTERS FOR DISEASE CONTROL AND PREVENTION 

AUGUST 2005 

Preventing 

Lead 

Poisoning 

in 

Young 

Children 

U.S. DEPARTMENT OF HEALTH AND HUMAN SERVICES

Centers for Disease Control and Prevention
Preventing 

Lead Poisoning 

in 

Young Children

A Statement by the Centers for Disease Control and Prevention

August 2005

Centers for Disease Control and Prevention

Julie L. Gerberding, MD, MPH, Director

National Center for Environmental Health 

Tom Sinks, PhD, Acting Director 

Division of Emergency and Environmental Health Services 

Jim Rabb, Acting Director 

Lead Poisoning Prevention Branch 

Mary Jean Brown, ScD, RN, Chief 

U.S. Department of Health

and Human Services, Public Health Service

Suggested reference: 

Centers for Disease Control and Prevention. Preventing Lead Poisoning in Young Children. Atlanta: 

CDC; 2005. 

Table of Contents

Advisory Committee on Childhood Lead Poisoning Prevention 

Members, Ex-Officio and Liaison Representatives ...................................................... v

Preface ........................................................................................................................... ix

Introduction.................................................................................................................... 1

Preventing Childhood Lead Poisoning in the United States....................................... 1

CDC’s Blood Lead Level of Concern.............................................................................. 2

Responding to Data on Adverse Health Effects at Blood Lead 

Levels <10 μg/dL from a Public Health Perspective .................................................... 3

Recommendations .......................................................................................................... 5

Conclusion ...................................................................................................................... 8

References ...................................................................................................................... 8

Appendix: A Review of Evidence of Adverse Health Effects 

Associated with Blood Lead Levels <10 μg/dL in Children ....................................... 11

Appendix Table of Contents ............................................................................ i

Summary........................................................................................................ iii

Work Group Members.................................................................................... vi 

Abbreviations and Acronyms ....................................................................... vii

Background ..................................................................................................... 1

Review Methods .............................................................................................. 4

Results............................................................................................................. 8

Discussion ..................................................................................................... 13

Overall Conclusions ...................................................................................... 29

Research Needs............................................................................................. 32

Appendix A: Literature Review and Classification Update.......................A-1

Appendix B: Critique of NHANES III Data by Stone, et al. (2003)..........B-1

References ....................................................................................................R-1

iii

Advisory Committee on Childhood Lead Poisoning 

Prevention Members, Ex-Officio 

and Liaison Representatives

CHAIR 

Carla Campbell, MD, MS 

The Children’s Hospital of Philadelphia 

Philadelphia, Pennsylvania 

EXECUTIVE SECRETARY 

Mary Jean Brown, ScD, RN 

Chief, Lead Poisoning Prevention 

Branch 

National Center for Environmental 

Health 

Centers for Disease Control 

and Prevention 

Atlanta, Georgia 

MEMBERS 

William Banner, Jr. MD, PhD 

The Children’s Hospital at Saint Francis 

Tulsa, Oklahoma 

Helen J. Binns, MD, MPH* 

Children’s Memorial Hospital 

Chicago, Illinois 

Walter S. Handy, Jr., PhD 

Cincinnati Health Department 

Cincinnati, Ohio 

Ing Kang Ho, PhD 

University of Mississippi Medical 

Center 

Jackson, Mississippi 

Jessica Leighton, PhD, MPH 

New York City Department of Health 

& Mental Hygiene 

New York, New York 

Valarie Johnson 

Urban Parent to Parent 

Rochester, New York 

Tracey Lynn, DVM, MPH† 

Alaska Department of Health 

and Social Services 

Anchorage, Alaska 

Sally Odle 

SafeHomes, Inc. 

Waterbury, Connecticut 

George G. Rhoads, MD, MPH 

University of Medicine and Dentistry 

of New Jersey 

Piscataway, New Jersey 

Catherine M. Slota-Varma, MD 

Pediatrician 

Milwaukee, Wisconsin 

Wayne R. Snodgrass, PhD, MD 

University of Texas Medical Branch 

Galveston, Texas 

Kevin U. Stephens, Sr., MD, JD 

New Orleans Department of Health 

New Orleans, LA 

Kimberly M. Thompson, ScD 

Harvard School of Public Health 

Boston, Massachusetts 

*ACCLPP member until May 2004 

†ACCLPP member until October 2004 

v
 

 

 

 

 

EX-OFFICIO 

Centers for Disease Control 

and Prevention 

Robert J. Roscoe, MS 

Centers for Medicare and 

Medicaid Services 

Jerry Zelinger, MD 

National Institute for Occupational 

Safety and Health Sciences 

Walter Rogan, MD 

U.S. Agency for International 

Development 

John Borrazzo, PhD 

U.S. Consumer Product Safety 

Commission 

Lori Saltzman 

U.S. Department of Housing and 

Urban Development 

David E. Jacobs, Ph.D., CIH 

U.S. Environmental Protection Agency 

Jacqueline E. Mosby, MPH 

U.S. Food and Drug Administration 

Michael P. Bolger, PhD 

LIAISON REPRESENTATIVES 

Alliance for Healthy Homes 

Anne M. Guthrie, MPH 

American Academy of 

Nurse Practitioners 

Jan Towers, PhD 

American Academy of Pediatrics 

J. Routt Reigart, II, MD (1997-2004) 

American Association of Poison 

Control Centers 

George C. Rodgers, Jr., MD, PhD 

American Industrial Hygiene Association 

Steve M. Hays, CIH, PE 

American Public Health Association 

Ben Gitterman, MD 

Association of Public Health Laboratories 

Henry Bradford, Jr., PhD 

Council of State and Territorial 

Epidemiologists 

Ezatollah Keyvan-Larijani, MD, DrPH 

National Center for Healthy Housing 

Pat McLaine, RN, MPH 

REVIEW OF EVIDENCE FOR 

EFFECTS AT BLLS <10 μg/dL WORK 

GROUP 

Michael L. Weitzman, MD 

Work Group Chair 

Center for Child Health Research 

University of Rochester 

Tom Matte, MD, MPH 

National Center for 

Environmental Health 

Centers for Disease Control 

and Prevention 

David Homa, PhD 

National Center for 

Environmental Health 

Centers for Disease Control 

and Prevention 

Jessica Sanford, PhD 

Battelle Memorial Institute 

vi
 

Alan Pate 

Battelle Memorial Institute 

Joel Schwartz, Ph.D. 

Department of Environmental Health 

Harvard School of Public Health 

David Bellinger, PhD, 

Neuroepidemiology Unit Children’s 

Hospital 

Harvard Medical School 

David A. Savitz, PhD 

Department of Epidemiology 

University of North Carolina School 

of Public Health 

Carla Campbell, MD, MS 

Division of General Pediatrics 

The Children’s Hospital of Philadelphia 

Patrick J. Parsons, PhD 

Wadsworth Center for Laboratories 

and Research 

New York State Department of Health 

Betsy Lozoff, MD 

Center for Human Growth and 

Development 

University of Michigan 

Kimberly Thompson, ScD 

Department of Health Policy 

and Management 

Harvard School of Public Health 

Birt Harvey, MD 

Pediatrician 

Palo Alto, California 

vii

Preface 

This is the fifth revision of Preventing Lead Poisoning in Young Children by 

the Centers for Disease Control and Prevention (CDC). As with the previous 

statements, the recommendations presented here are based on scientific evidence 

and practical considerations. This revision accompanies a companion document, 

A Review of Evidence of Adverse Health Effects Associated with Blood Lead Levels 

<10 μg/dL in Children, developed by Advisory Committee on Lead Poisoning 

Prevention which reviews the scientific evidence for adverse effects in children at 

blood lead levels below 10 μg/dL. 

The data demonstrating that no “safe” threshold for blood lead levels (BLLs) 

in young children has been identified highlights the importance of preventing 

childhood exposures to lead. It confirms the need for a systematic and society wide 

effort to control or eliminate lead hazards in children’s environments before they 

are exposed. This emphasis on primary prevention, although not entirely new, is 

highlighted here and is clearly the foremost action supported by the data presented 

in A Review of Evidence of Adverse Health Effects Associated with Blood Lead Levels 

<10 μg/dL in Children. 

Although there is evidence of adverse health effects in children with blood lead 

levels below 10 μg/dL, CDC has not changed its level of concern, which remains 

at levels >10 μg/dL. We believe it critical to focus available resources where the 

potential adverse effects remain the greatest. If no threshold level exists for adverse 

health effects, setting a new BLL of concern somewhere below 10 μg/dL would 

be based on an arbitrary decision. In addition, the feasibility and effectiveness 

of individual interventions to further reduce BLLs below 10 μg/dL has not been 

demonstrated. 

CDC is conducting several activities to focus efforts on preventing lead exposures 

to children. First, beginning in 2003, CDC required state and local health 

departments receiving funding for lead poisoning prevention activities to develop 

and implement strategic childhood lead poisoning elimination plans. Second, CDC 

and its federal partners, the Department of Housing and Urban Development and 

the Environmental Protection Agency, launched new initiatives to control leadbased paint hazards in the highest risk housing, addressing where successive cases 

of lead poisoning have been identified. Third, CDC and other federal agencies are 

developing a systematic and coordinated response to identify and eliminate nonpaint sources of exposure (e.g., lead jewelry, food and traditional medicines, and 

cosmetics). 

CDC continues to monitor progress toward the Healthy People 2010 objective of 

eliminating elevated BLLs in children at the national level through the National 

Health and Nutritional Examination Survey and at the state and local levels 

through the blood lead surveillance system. These complementary data provide 

ix
essential information for the rational distribution of resources to communities with 

the highest risk for lead exposure. 

I wish to thank both current and former members of the Advisory Committee on 

Childhood Lead Poisoning Prevention and consultants who developed the documents in this statement and acknowledge their contribution to the health of the 

nation’s children. The Committee considered a number of controversial issues, 

examined the existing data and reviewed the report of the work group. This 2005 

statement represents agreement of 12 of the 13 Advisory Committee members serving on the committee as of October 19-20, 2004. 

Thomas Sinks, Ph.D. 

Acting Director 

National Center for Environmental Health/Agency for Toxic Substances 

and Disease Registry 

x
INTRODUCTION 

The U.S. Department of Health and Human Services has established an ambitious 

goal of eliminating elevated blood lead levels (BLLs) in children by 2010, a 

qualitatively different goal from earlier goals that focused on reducing the BLL 

considered toxic by various target amounts.1

 Recent research on lead’s health effects 

at low levels, which suggests societal benefits from preventing even low level lead 

exposure in childhood, underscores the importance of this public health goal. 

This revised statement describes the public health implications of research findings 

regarding adverse health effects at low BLLs summarized in the accompanying 

review, and focuses on the Centers for Disease Control and Prevention’s blood lead 

“level of concern.” This statement aims to guide public health practice and policy 

development and review necessary steps to ensure progress toward meeting the 

2010 goal. 

PREVENTING CHILDHOOD LEAD POISONING IN THE UNITED STATES 

The reduction of BLLs in the United States during 1970-1999, primarily because of 

implementation of federal and state regulations to control lead exposure, was one 

of the most significant public health successes of the last half of the 20th century.

2 

Nonetheless, some populations and geographic areas remain at disproportionately 

high risk for lead exposure.3-5 Specific strategies that target screening to high-risk 

children are essential to identify children with BLLs >10 μg/dL. Once identified, 

children with elevated BLLs should receive follow-up services as recommended in 

Managing Elevated Blood Lead Levels Among Young Children.

6 

However, preventing elevated BLLs is the preferred course of action. A compelling 

body of evidence points to the limited effectiveness of waiting until children’s 

BLLs are elevated before intervening with medical treatments, environmental 

remediation, or parental education. 7-12 Data indicate that in many cases it takes 

years to reduce children’s BLLs once levels are elevated whether the initial blood 

lead elevation is very high or moderate.13-15 The most common high-dose sources of 

lead exposure for U. S. children are lead-based paint and lead-contaminated house 

dust and soil. Recent studies have identified methods to reduce common household 

lead hazards safely.16 Thus, a multitiered approach that includes secondary 

prevention through case identification and management of elevated BLLs is needed 

to eliminate childhood lead poisoning. However, because no level of lead in a child’s 

blood can be specified as safe, primary prevention must serve as the foundation of 

the effort. 

1
CDC’S BLOOD LEAD LEVEL OF CONCERN 

The adverse health effects associated with elevated BLLs have been widely studied 

and documented. Previously, CDC responded to the accumulated evidence of 

adverse effects associated with lead exposures by lowering the BLL of concern. 

Between 1960 and 1990 the blood lead level for individual intervention in children 

was lowered from 60 μg/dL to 25 μg/dL. In 1991 the CDC recommended lowering 

the level for individual intervention to 15 μg/dL and implementing communitywide primary lead poisoning prevention activities in areas where many children 

have BLLs >10 μg/dL.17 Some activities, such as taking an environmental history, 

educating parents about lead, and conducting follow-up blood lead monitoring 

were suggested for children with BLLs of >10 μg/dL.7 However, this level, which 

was originally intended to trigger communitywide prevention activities, has been 

misinterpreted frequently as a definitive toxicologic threshold. 

As the accompanying review of recent studies indicates, additional evidence exits of 

adverse health effects in children at BLLs <10 μg/dL. The available data are based 

on a sample of fewer than 200 children whose BLLs were never above 10 μg/dL and 

questions remain about the size of the effect. 

At this time there are valid reasons not to lower the level of concern established in 

1991 including the following: 

• No effective clinical or public health interventions have been identified that 

reliably and consistently lower BLLs that already are <10 μg/dL. Nonetheless, 

the sources of lead exposure and the population-based interventions that can 

be expected to reduce lead exposure are similar in children with BLLs <10 μg/ 

dL and >10 μg/dL,18 so preventive lead hazard control measures need not be 

deferred pending further research findings or consensus. 

• No one threshold for adverse effects has been demonstrated. Thus the process for 

establishing a lower level of concern would be arbitrary and no particular BLL 

cutoff can be defended on the basis of the existing data. In addition, establishing 

a lower level of concern may provide a false sense of safety about the well being 

of children whose BLLs are below the threshold. 

• The adverse health effects associated with elevated BLLs are subtle. Individual 

variation in response to exposure and other influences on developmental status, 

make isolating the effect of lead or predicting the overall magnitude of potential 

adverse health effects exceedingly difficult. 

• Establishing a level of concern substantially <10 μg/dL probably would be 

accompanied by a sharp increase in misclassification of children as having an 

elevated BLL. The uncertainty associated with laboratory testing is too great 

to ensure that a single blood lead test reliably classifies individual children at 

2
levels <10 μg/dL. This misclassification could confuse both parents and clinicians 

and expenditure of resources on testing that does not aid decision making. 

• Efforts to identify and provide services to children with BLLs <10 μg/dL may 

deflect needed resources from children with higher BLLs who are likely to 

benefit most from individualized interventions. 

• Efforts to eliminate lead exposures through primary prevention have the 

greatest potential for success. Reducing exposures will benefit all children, 

regardless of their current BLL. 

RESPONDING TO DATA ON ADVERSE HEALTH EFFECTS AT BLOOD LEAD 

LEVELS <10 μg/dL FROM A PUBLIC HEALTH PERSPECTIVE 

Since 1991, CDC has emphasized the need to make primary prevention of lead 

poisoning, through interventions that control or eliminate lead hazards before 

children are exposed, a high priority for health, housing, and environmental 

agencies at the state, local, and federal levels.18-20 Federal and state policies and 

programs, largely as the result of Title X of the 1992 Housing and Community 

Development Act (Public Law 102-550), increasingly have focused on the need 

for primary prevention using strategies known to effectively reduce residential 

lead hazards.21 Research findings also indicate that primary prevention would be 

expected to benefit all children at high risk because communities with the largest 

percentages of children with BLLs >20 μg/dL also have the largest percentage 

of children with BLLs that are lower but still above the national average of 

approximately 2 μg/dL.18 These data underscore the importance of targeting efforts 

to communities where risk for exposure is highest and provide a strong rationale 

for primary prevention efforts. The strategies described below will effectively direct 

efforts to achieve the Healthy People 2010 objective to eliminate lead poisoning in 

young children and can be expected to reduce lead exposure for all children.1 

Primary Prevention 

CDC’s Advisory Committee on Childhood Lead Poisoning Prevention recently issued 

updated recommendations calling for the nation to focus on primary prevention 

of childhood lead poisoning.22 Because the 2010 health objective of eliminating 

childhood lead poisoning can be achieved only through primary prevention,22 this 

document provides important guidance to state and local agencies regarding the 

implementation of primary prevention activities. Given that the most important 

measure of a successful primary prevention strategy is elimination of lead exposure 

sources for young children, we focus here on the two main exposure sources for 

children in the United States: lead in housing and non-essential uses of lead in 

other products. 

3
 

Lead in Housing-Because lead-based paint is the most important source of lead 

exposure for young children, the first essential element of primary prevention is 

implementation of strategies to control lead paint-contaminated house dust and 

soil and poorly maintained lead paint in housing.23-25 After 10 or more years of 

widespread blood lead testing and data collection by CDC-supported state and local 

agencies, the specific addresses of housing units at which children repeatedly have 

been identified with elevated BLLs are known to local officials. Two examples are: 

• In Detroit, 657 addresses accounted for nearly 1,500 children with BLLs >20 

μg/dL during the last 10 years because the sources of lead were never controlled 

completely when the initial case occurred. These housing units also probably 

were the source of lead exposure for several thousand Detroit children with 

BLLs >10 μg/dL.26 

• In Louisville, Kentucky, 35% of children identified with elevated BLLs during 

the last 5 years resided in 79 housing units; these units represent <0.3% of all 

housing units in the community.27 

These experiences are repeated in high-risk communities across the country. The 

infrastructure needed to identify high-risk housing and to prevent and control 

lead hazards in such housing is largely in place. Established firms certified in 

lead hazard evaluation and control now exist in most communities, as do other 

skilled trades people trained in lead-safe work practices necessary during routine 

maintenance and painting. Systematic identification and reduction of residential 

lead sources, particularly in old, poorly maintained housing where children with 

elevated BLLs are known to have lived, combined with periodic monitoring of 

housing conditions to detect new deterioration and resultant lead hazards will 

prevent lead exposure to children in the future and break the cycle of repeated cases 

of elevated BLLs. 

Other steps critical to success in controlling lead hazards in housing and preventing 

lead exposure in the future are 1) enforcement of lead safety and housing code 

requirements to ensure good property maintenance; 2) widespread adoption of leadsafe work practices to control, contain, and clean up lead dust during painting and 

remodeling projects; and 3) periodic monitoring of housing conditions to detect new 

deterioration and resultant lead hazard. 

Nonessential Uses of Lead-Because areas of the United States report that as 

many as 35% of children identified with elevated BLLs have been exposed to items 

decorated or made with lead, in some cases resulting in life-threatening BLLs,28 

the second crucial element of a primary prevention strategy is identification and 

restriction or elimination of nonessential uses of lead, particularly in both imported 

and domestically manufactured toys, eating and drinking utensils, cosmetics, and 

traditional medicines. This effort requires identifying communities where cultural 

practices and traditional medicines may put children at risk and incorporating 

4
lead poisoning prevention activities into health and community services that 

reach families at high risk for lead exposure from nonpaint sources.7

 The 2010 

health objective cannot be achieved without a more systematic approach that, at 

a minimum, allows identification of lead-contaminated items and prohibits their 

sale before children are exposed. Ultimately, all nonessential uses of lead should be 

eliminated. 

RECOMMENDATIONS 

Changes in the Focus of CDC-Funded Programs 

To achieve these goals, CDC is focusing on eliminating childhood lead poisoning by 

preferentially funding programs to provide lead-related services for communities 

and populations with large numbers of children at high risk for lead exposure. The 

cooperative agreements with 42 state and local health departments funded for 2003-

2006 emphasize the importance of primary prevention and require funded state 

and local programs to work aggressively to develop and implement the necessary 

partnerships, programs and activities. CDC requires its state and local partners 

to undertake a strategic planning process, which includes gathering input from 

housing professionals, pediatric health-care providers, advocacy groups, parents of 

children with elevated BLLs, and others interested in preventing lead poisoning 

in children. These strategic plans, developed by local partners to respond to local 

conditions, drive primary prevention activities for the 3-year grant cycle. 

Progress toward eliminating childhood lead poisoning can be measured only by 

ongoing surveillance of BLLs in childhood populations where the risk for exposure 

is high, as well as continued monitoring of population-based BLLs through the 

National Health and Nutrition Examination Survey.29 CDC’s role in supporting 

state and local efforts and providing technical assistance to improve data 

management and reporting is essential to these activities. 

Recommendations to Federal, State, and Local Government Agencies 

Achieving the Healthy People 2010 objective to eliminate childhood lead poisoning 

requires collaboration by many different federal, state and local agencies. Many 

of the roles and responsibilities for federal partners in the elimination effort are 

detailed in the report of the President’s Task Force on Environmental Health 

Risks and Safety Risks in Children.29 However, all levels of government share 

responsibility for primary prevention of childhood lead poisoning. Government 

agencies have the ability, through legislative and enforcement actions to spearhead 

prevention efforts and articulate clear public health goals and strategic priorities at 

the federal, state, and local government levels. 

Federal agencies should: 

1. Support and disseminate information about, and adequately fund, programs and 

interventions that will lead to full implementation of primary prevention. 

5
 

2. Expand financial resources for permanent measures to control or eliminate 

residential lead hazards. 

3. Monitor and enforce regulations controlling lead content of various 

environmental media, including air, water, and soil. 

4. Identify populations in which the risk for exposure to nonpaint sources of lead is 

high, and develop strategies to minimize the risk. 

5. Develop and implement regulatory and voluntary strategies to control 

nonessential uses of lead, particularly in items that are easily accessible to 

young children, such as toys, jewelry, eating and drinking utensils, traditional 

remedies, and cosmetics. 

6. Evaluate the effectiveness of primary prevention activities in reducing lead 

exposure and eliminating childhood lead poisoning, particularly in areas where 

the risk for lead poisoning is substantially higher than for the general U. S. 

childhood population. 

7. Develop new mathematical models of lead exposure or modify existing models, 

e.g., the Integrated Exposure Uptake and BioKinetic (IEUBK) Model for lead in 

children, currently used to establish thresholds for lead exposure in consumer 

products and areas with pervasive lead contamination. The exposure modeling 

should predict the magnitude of the increase in BLLs in a child as a result of 

exposure to a specific lead source rather than the probability of a BLLs >10 μg/dL. 

State and local agencies should: 

1. Update or establish and enforce regulatory requirements for lead safe housing 

that link lead safety to the housing and/or sanitary code. 

2 Require that properties that have undergone lead paint abatement or 

substantial renovation to lead painted surfaces meet the EPA dust clearance 

testing prior to re-occupancy. Require dust testing in all cases where public 

health agencies have ordered paint repair, particularly in the homes of children 

already identified with elevated BLLs. 

3 Promote broad use of lead-safe work practices for routine painting and 

maintenance projects in older homes, and make training in such practices widely 

available at low or no cost to painters, remodelers, landlords, and maintenance 

workers. 

4. Establish formal agreements among health, social services, housing, and legal 

agencies to increase the sharing of data, educational information, violations, and 

success stories. 

6
5. Provide information to caregivers about temporary measures that can reduce 

lead exposure as described in Managing Elevated Blood Lead Levels Among 

Young Children,6

 as well as information and referral for permanent abatement 

services. 

Recommendations to Health-Care Providers and Community-Based Health 

and Social Service Agencies 

CDC recommends that health care providers continue their traditional role of 

providing anticipatory guidance as part of routine well-child care, assessing risk for 

exposure to lead, conducting blood lead screening in children, and treating children 

identified with elevated BLLs. In addition health-care and social service providers 

are urged to expand their roles. They should keep abreast of research data that 

clarify the relationship between lead exposure and neurocognitive development 

in children. They also can strongly advocate for children and foster lead exposure 

prevention by helping facilitate implementation of the specific strategic plans to 

eliminate childhood lead poisoning in their local and state communities. Health-care 

and social service providers are highly effective child advocates, and their active 

participation in the process provides the expertise and leadership needed to reach 

this goal. Health-care and social service providers should: 

1. Provide culturally appropriate education to all pregnant women and to families 

with young children about the principal sources of lead and ways to reduce 

exposure. 

2. Target outreach, education, and screening programs to populations with the 

greatest risk for lead exposure. 

3. Become aware of, and actively support, lead poisoning elimination efforts in the 

community. 

4. Express concern to federal, state, and local policy and decision makers that 

children live in a lead safe environment and actively support legislation and 

regulatory initiatives. Advocate for lead-safe, affordable housing by supporting 

appropriate legislation. 

5. Become aware of and comply with lead screening policies issued by Medicaid or 

state and local health departments. 

6. Ensure training of staff members engaged in housing renovation or 

rehabilitation in lead-safe work practices. 

7
 

 

 

CONCLUSION 

The Healthy People 2010 objective to eliminate BLLs >10 μg/dL in children is 

within our grasp. Research to further characterize and isolate the harmful effects 

of lead associated with various BLLs will help answer remaining questions 

and further refine the public health response. However, the approach needed is 

clear: identify and address existing lead hazards before children are exposed, 

otherwise hundreds of thousands of children will be placed at risk needlessly. 

The overall reduction of lead in the environment will benefit all children. 

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27Meyer PA, Staley F, Staley P, Curtis J, Blanton C, Brown MJ. Improving strategies to prevent 

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28CDC. Brief report: Lead poisoning from ingestion of a toy necklace —Oregon, 2003. MMWR 

2004;53:509–11. 

29President’s Task Force on Environmental Health Risks and Safety Risks to Children. Eliminating 

childhood lead poisoning: A federal strategy targeting lead paint hazards. Washington, DC: 

President’s Task Force on Environmental Health Risks and Safety Risks to Children; 2004. 

10

 


 


 


 


 

APPENDIX 

A REVIEW OF EVIDENCE OF ADVERSE HEALTH EFFECTS 

ASSOCIATED WITH BLOOD LEAD LEVELS <10 μg/dL IN CHILDREN

Reported by 

Work Group of the Advisory Committee on
 

Childhood Lead Poisoning Prevention
 

to
 

CENTERS FOR DISEASE CONTROL AND PREVENTION
 

National Center for Environmental Health
 

AUGUST 2005

11

 

Appendix Table of Contents

Page 

SUMMARY.................................................................................................................... iii

Studies Relating Postnatal Lead Exposure to IQ or 

Blood Lead Age Trend, Tracking, and Inference Concerning 

WORK GROUP MEMBERS .........................................................................................vi

ABBREVIATIONS AND ACRONYMS ........................................................................vii

BACKGROUND .............................................................................................................1

REVIEW METHODS .....................................................................................................4

RESULTS .......................................................................................................................8

General Cognitive Index ....................................................................................8

Studies of Health Endpoints Other than IQ and CGI .......................................10

DISCUSSION ...............................................................................................................13

Biologic Plausibility .............................................................................................14

Blood Lead Measurement ....................................................................................17

Blood Lead-Effect Relations in Children .........................................................18

Quality of Neurobehavioral Assessments ...........................................................21

Potential Confounding Factors ...........................................................................

Causal Direction ..................................................................................................28

OVERALL CONCLUSIONS ........................................................................................29

RESEARCH NEEDS ...................................................................................................32

APPENDIX A: LITERATURE REVIEW AND CLASSIFICATION UPDATE.........A-1

APPENDIX B: CRITIQUE OF NHANES III DATA BY STONE, ET AL. (2003) .... B-1

REFERENCES............................................................................................................ R-1

i
List of Figures 

Figure 1. Expected variation in regression slopes given hypothetical “true” 

threshold blood lead–IQ relation (A). ......................................................... 33

Figure 2. Cognitive Function Regression Coefficients for Blood Lead Age 

Figure 3. Cognitive Function Regression Coefficients for Blood Lead Age 

Figure 7. Hypothetical blood lead IQ slopes associated with residual 

<2 years and Outcome Age >4 years........................................................... 35

>4 years and Outcome Age >4 years........................................................... 36

Figure 4. Age trend in blood lead levels ..................................................................... 37

Figure 5. Hypothetical observed blood lead–IQ association...................................... 38

Figure 6. Hypothetical “true” blood lead–IQ relationship......................................... 38

confounding (see text).................................................................................. 39

List of Tables 

Table 1. Lowest blood lead level (BLL) considered elevated by CDC and 

the US Public Health Service...................................................................... 40

Table 2. Summary of studies estimating association of postnatal PbB 

with cognitive function ................................................................................ 41

Table 3. Summary of studies estimating association of postnatal PbB 

with performance scale IQ .......................................................................... 58

Table 4. Summary of studies estimating association of postnatal PbB 

with verbal scale IQ..................................................................................... 65

Table 5. Studies of health endpoints other than IQ or GCI in relation 

to BLLs <10 μg/dL ....................................................................................... 72

Table 6. Selected methodologic details from cohort studies .................................... 77

ii
EXECUTIVE SUMMARY
Ê

In March 2002, the Centers for Disease Control and Prevention (CDC) Advisory 

Committee on Childhood Lead Poisoning Prevention (ACCLPP) established a work 

group (WG) to review the available evidence of possible health effects of blood lead 

levels (BLLs) of below 10 micrograms per deciliter (μg/dL), the level of concern 

currently established by CDC. The WG was charged with designing and following 

a rigorous protocol to review studies of the health effects of lead exposure at very 

low BLLs. The workgroup intended to focus on studies of the effects of peak BLLs 

at <10 μg/dL in children never known to have a BLL exceeding 10 μg/dL. However, 

there are relatively few such studies and the workgroup decided to review the 

larger number of studies that could indirectly support or refute the existence of 

a threshold near 10 μg/dL. Although the workgroup members were the primary 

authors of this report, the ACCLPP reviewed the document and it was revised based 

on their comments. The majority of ACCLPP members accepted the findings of the 

report, with two members dissenting. 

Methods 

The following criteria were used for selecting relevant studies to review: 

• BLLs were measured using graphite furnace atomic absorption spectrometry 

(GFAAS) or anodic stripping voltammetry (ASV); 

• the study was published in English; 

• for studies in which IQ or General Cognitive Index (GCI) was a measured 

outcome, an assessment of the association between BLLs in children and IQ 

or GCI was included; and 

• for studies in which IQ or GCI was not a measured outcome, an assessment of 

the association between BLLs in children and a specified health outcome was 

included. 

For each relevant study, a structured abstraction was performed that captured the 

following: 

• study location and sample size; 

• age at which BLL and cognitive or health outcome was measured; 

• the distribution of BLLs (mean or other measure of central tendency and 

variance) and percentage of participants with BLL <10 μg/dL; 

iii
• crude and adjusted regression coefficients relating BLLs to outcome; 

• other measures of association (e.g., correlation coefficients); and 

• model type and covariates included in adjusted models. 

When reviewing the evidence, including indirect evidence from IQ studies, the 

workgroup considered both alternate explanations for study findings and potential 

effect of residual confounding. 

Conclusions 

The main conclusions reached by the WG are summarized as follows. 

1. Does available evidence support a negative association between 

measured BLLs <10 μg/dL and children’s health? 

• The overall weight of available evidence supports an inverse (negative) 

association between BLLs <10 μg/dL and the cognitive function of 

children. 

• A steeper slope in the dose-response curve was observed at lower 

rather than higher BLLs. 

• The available evidence has important limitations, including the small 

number of directly relevant cohort studies and the inherent limitations 

of cross-sectional studies (i.e., the lack of data regarding both BLLs 

earlier in life and key covariates). 

• For health endpoints other than cognitive function (i.e., other 

neurologic functions, stature, sexual maturation, and dental caries), 

consistent associations exist between BLLs <10 μg/dL and poorer 

health indicators. 

2. Are the observed associations likely to represent causal effects of 

lead on health? 

• Though not definitive, the available evidence supports the conclusion 

that the observed associations between BLLs <10 μg/dL and cognitive 

function are caused, at least in part, by lead toxicity. 

• The strength and shape of the causal relationship are uncertain 

because of limitations of the available evidence. 

iv
• The health effects of lead are uncertain in individual children who 

have BLLs measured at a single point in time. Thus, scientific evidence 

does not provide a basis for classifying individual children with BLLs 

<10 μg/dL as “lead poisoned,” as the term is used in the clinical setting. 

• The greatest source of uncertainty in evidence concerning the 

relationship between BLLs <10 μg/dL and children’s cognitive function 

is the potential for residual confounding, especially by socioeconomic 

factors. 

• The available data for health endpoints other than cognitive function, 

taken mostly from cross-sectional studies, are limited; therefore, firm 

conclusions concerning causation can not be made. 

Future Research Needs 

The WG identified the following research needs to address gaps in the existing 

base of evidence and to allow for more definite conclusions about the strength and 

shape of the causal relationship. 

• Prospective observational studies designed to minimize the chance of residual 

confounding. 

• Randomized trials to test interventions designed to reduce BLLs <10 μg/dL 

and assess the impact on children’s cognitive development. 

• Animal and in vitro studies to identify mechanisms of lead toxicity at low 

BLLs that could explain the observed steeper slope at lower compared with 

higher BLLs. 

v
A Review of Evidence of Adverse Health Effects Associated 

with Blood Lead Levels <10 μg/dL in Children 

Reported by 

A Work Group of the CDC Advisory Committee on Childhood Lead Poisoning 

Prevention on Health Effects of Blood Lead Levels <10 μg/dL in Children 

Work Group Members 

Michael Weitzman, MD Patrick J. Parsons, PhD 

Work Group Chair Wadsworth Center for 

Center for Child Health Research Laboratories and Research 

University of Rochester New York State Department 

of Health 

Joel Schwartz, PhD Betsy Lozoff, MD 

Department of Environmental Health Center for Human Growth 

Harvard School of Public Health and Development 

University of Michigan 

David Bellinger, PhD Kimberly M. Thompson, ScD 

Neuroepidemiology Unit Department of Health Policy 

Children’s Hospital and Management 

Harvard Medical School Harvard School of Public Health 

David A. Savitz, PhD Birt Harvey, MD 

Department of Epidemiology Pediatrician 

University of North Carolina School Palo Alto, California 

of Public Health 

Carla Campbell, MD 

Division of General Pediatrics 

The Children’s Hospital of Philadelphia 

This review was prepared for the work group by the following:

Thomas D. Matte, MD, MPH

David Homa, PhD

National Center for Environmental Health

Centers for Disease Control and Prevention

and

Jessica Sanford, PhD

Alan Pate

Battelle Memorial Institute 

vi
 

Abbreviations and Acronyms

AAS atomic absorption spectrometry 

ACCLPP Advisory Committee on Childhood Lead Poisoning Prevention 

ALAD amino levulinic acid dehydratase 

ALAU urinary amino levulinic acid 

ASV anodic stripping voltammetry 

ATSDR Agency for Toxic Substances and Disease Registry 

BLL blood lead level 

EBLL elevated blood lead level 

EP erythrocyte protoporphyrin 

EPA Environmental Protection Agency 

ETAAS electrothermal atomization techniques based on the graphite 

furnace 

ETS environmental tobacco smoke 

FEP free erythrocyte protoporphyrin 

GCI General Cognitive Index 

vii
GFAAS graphite furnace atomic absorption spectrophotometry 

HOME Home Observation for Measurement Environment 

ICP-MS inductively coupled plasma mass spectrometry 

ID-MS isotope dilution mass spectrometry 

MCV mean corpuscular volume 

MDI Mental Developmental Index of the Bayley Scales of Infant 

Development for children 

MeHg methylmercury 

MSCA McCarthy Scales of Children’s Ability 

NCCLS National Committee for Clinical Laboratory Standards 

NCEH National Center for Environmental Health 

NHANES National Health and Nutrition Examination Survey 

NMDA N-methyl-D-aspartate 

PbB Blood lead 

PCAACN Practice Committee of the American Academy of Clinical 

Neuropsychology 

PKC protein kinase C, a calcium dependent enzyme 

viii
QA/QC quality assurance/quality control 

SES socioeconomic status 

U-RBP urinary retinal binding protein 

WG work group 

WISC-R Wechsler Intelligence Scale for Children—Revised 

WISC-III Wechsler Intelligence Scale for Children—Third Edition 

WRAT Wide Ranging Achievement test arithmetic and reading scores 

ZPP zinc protoporphyrin 

ix

Background

Charge to the Work Group 

In March 2002, the Advisory Committee on Childhood Lead Poisoning 

Prevention agreed to establish a work group (WG) to review evidence of possible 

health effects of lead at blood lead levels less than 10 micrograms per deciliter 

(μg/dL), currently the threshold for defining an elevated blood lead level according 

to CDC guidelines (CDC 1991). The work group was charged as follows: 

“In October 1991, the Centers for Disease Control and Prevention 

issued Preventing Lead Poisoning in Young Children. This document 

heralded a change in the definition of the level for intervention for 

children with elevated blood lead levels (EBLLs) from a lead level of 

25 μg/dL to 10 μg/dL. The report explained that this change was due 

to new data that indicated significant adverse effects of lead exposure 

in children at levels once thought to be unassociated with adverse 

effects. The 1991 document identified a goal to reduce children’s blood 

lead levels below 10 μg/dL. Interventions for individual children were 

recommended at levels of 15 μg/dL and above. 

Research findings published and disseminated since October 1991 

suggest that adverse effects from lead exposure and toxicity occur 

at blood lead levels below 10 μg/dL. Some studies suggest that some 

effects may be greater at blood lead levels (BLLs) below 10 μg/dL 

than at higher BLLs. Such research findings raise concerns about the 

inability to control lead exposure with conventional methods and lend 

credence to the importance of primary prevention measures to prevent 

lead exposure to children. 

The work group will be convened by the Advisory Committee on 

Childhood Lead Poisoning Prevention to review the existing evidence 

for adverse effects of lead exposure and toxicity on children at very low 

blood lead levels and to focus on effects at levels of 10 μg/dL and below. 

Rigorous criteria will be established for the literature review. The work 

group will then create, in conjunction with the committee, a summary 

of the evidence for publication.” 

Scientific and Public Health Context for the WG Review 

Prior reviews that compiled the extensive evidence from in vitro, animal, 

and human studies established lead as a multi-organ toxicant, including studies 

showing health effects at BLLs near 10 μg/dL (ATSDR 1999; WHO 1995; USEPA 

1986). The published studies include a large body of literature establishing that 

1
lead is a developmental toxicant and that harmful effects of lead on children’s 

development can occur without clinical signs, symptoms, or abnormal routine 

laboratory tests. In addition, a growing number of studies suggest that BLLs 

prevalent in the general population are associated with adverse health effects 

in adults and in the offspring of pregnant women. Finally, in more recent years, 

bone-lead levels measured by x-ray fluorescence have been used in epidemiologic 

studies as a measure of cumulative lead exposure. Although these were not 

considered in this review, a number of studies showing inverse relations of 

bone-lead level to health in general population samples (e.g., Cheng et al. 2001) add 

further evidence that cumulative lead exposure may be harmful to health at typical 

background exposure levels for the population in the United States. 

The observation that available epidemiologic evidence does not demonstrate a 

threshold below which no effect of lead is possible is not new. A review prepared for 

a 1986 workshop on lead exposure and child development stated, “There is little 

evidence for a threshold or no-effect level below which the lead/IQ association is 

not found. IQ deficits have been reported in studies where the mean lead level is 13 

μg/dL (Yule et al. 1981) and similar deficits in the Danish study where the primary 

measure was tooth lead, but BLLs are lower at around 7 μg/dL.” (Smith 1989) A 

review, meta-regression, and reanalysis of existing data (Schwartz 1994) reached 

essentially the same conclusion. Available data did not suggest a threshold below 

which no association between BLLs and intelligence in young children was evident. 

Recent studies (Canfield et al. 2003; Lanphear et al. 2000; Moss et al. 1999; Wu 

et al. 2003) provided more direct evidence of an association between BLLs and 

adverse health effects in the domains of cognitive function, neurologic function, 

growth, dental caries, and onset of puberty at levels well below 10 μg/dL. Thus, a 

reexamination of this issue is in order. 

As evidence from experimental animal studies and human epidemiologic studies 

has grown, CDC has lowered the BLL considered elevated for the purpose of 

interpreting clinical test results of an individual child (Table 1). CDC guidelines also 

have provided criteria for identifying children who have more severe manifestations 

of lead toxicity and/or a higher risk of lead-related sequellae. For example, CDC’s 

1975 and 1978 guidelines defined clinical “lead poisoning” on the basis of BLLs, 

symptoms, and/or levels of erythrocyte protoporphyrin (EP) or other indicators of 

lead-related biochemical derangements. CDC’s 1985 guidelines used the terms “lead 

toxicity” and “lead poisoning” interchangeably to refer to BLLs >25 μg/dL with EP 

>35 μg/dL. However, the guidelines acknowledged that “lead poisoning” is generally 

understood for clinical purposes to refer to episodic, acute, symptomatic illness 

from lead toxicity. CDC’s 1985 guidance also cautioned that blood lead thresholds 

established to guide follow-up and treatment for individual children “should not 

be interpreted as implying that a safe level of blood lead has been established.” In 

1991, CDC guidelines more directly acknowledged the difficulty in assigning terms 

to specific ranges of BLLs given the different settings in which BLLs are interpreted 

and given that manifestations of lead toxicity occur along a continuum: “It is not 

2
possible to select a single number to define lead poisoning for the various purposes 

of all of these groups [e.g. clinicians, public health officials, and policy makers]” 

(CDC 1991). These guidelines also noted, “Some [epidemiologic] studies have 

suggested harmful effects at even lower levels [than a BLL of 10 μg/dL].” 

In addition to these changes in criteria used to evaluate blood lead test results 

for individual children, recent analyses by the U.S. Department of Housing and 

Urban Development (HUD 1999) and the U.S. Environmental Protection Agency 

(USEPA 2000) to support the development of regulations governing lead exposure 

have assumed that the relation of increasing blood lead to decrements in children’s 

IQ extends to BLLs <10 μg/dL. 

As BLLs considered elevated have fallen, measures to reduce or remove 

lead from a number of sources, including gasoline, soldered food and beverage 

containers, paint, drinking water, and industrial emissions have resulted in a 

dramatic decline in BLLs in the United States since the mid-1970s (Pirkle et al. 

1994). The Second National Health and Nutrition Examination Survey (NHANES 

II) conducted from 1976 to 1980 demonstrated that, among U.S. children ages 6 

months through 2 years, 84% of white children and more than 99% of black children 

had BLLs >10 μg/dL, and the median BLLs were 14 and 19 μg/dL, respectively 

(Mahaffey et al. 1982). A decline in BLLs during the course of that survey was 

noted, paralleling the falling consumption of leaded gasoline (Annest et al. 1983). 

A continued decline in BLLs was evident in subsequent NHANES surveys (Pirkle 

et al. 1994; NCEH 2003) and in clinical blood-lead test data compiled by state and 

local health agencies (Hayes et al. 1994; CDC 2003). Nationally, it is estimated that 

by 1999-2000, the prevalence of BLLs >10 μg/dL among children 1 to 5 years of age 

had fallen to 2.2% and the median level to 2.2 μg/dL (NCEH 2003). 

Although these reductions in lead exposure represent great progress, scientific 

advances have shed light on harmful effects of lead at levels of exposure once 

thought safe. In addition, industrial activity has widely dispersed lead in the 

environment from naturally occurring deposits. As a result, even at the lower 

exposure levels that prevail today, typical body burdens of lead are likely to be 

much higher than those present in pre-industrial humans, which by one estimate 

corresponded to a BLL of 0.016 μg/dL (Smith et al. 1992). Therefore, the potential 

for additional subclinical adverse effects of lead from currently prevailing 

exposures deserves careful study. Finally, although falling BLLs have benefited 

all demographic groups (Pirkle et al. 1994), stark demographic and geographic 

disparities continue to reflect the historic pattern; the risk of elevated BLLs in 

communities where poverty and older (i.e., that built before 1950) housing are 

prevalent remains several fold higher than the national average (Lanphear et al. 

1998). 

3
Review Methods

Scope and Approach

Given the charge to the work group and the scientific and public health context, 

the WG did not attempt a comprehensive review of all evidence relating lead 

exposure to health. Instead, the WG set out to answer the following questions: 

1. Does available evidence support negative associations between health 

indicators and children’s blood lead levels measured <10 μg/dL? Ê
 

2. Are the observed associations likely to represent a causal effect of lead on 

health? 

To address these questions, the WG established criteria (see Methods) for 

published studies that would address the first question. In addition, the work 

group identified issues relevant to making causal inference from any observed 

associations. Identifying such issues is an essential step in interpreting evidence 

relevant to the WG charge. Human studies to assess potential health effects of 

environmental toxicants, such as lead, are usually observational in design (i.e., the 

health status of participants is related to some measure of exposure, dose, or body 

burden that varies on the basis of environmental factors and not experimental 

manipulations by the investigator). For ethical reasons, the limited number of 

human experimental studies that have evaluated causal relations between toxicant 

exposures and health usually have involved attempts to reduce exposure or body 

burden and assess the impact on health status. Such studies of lead-exposed 

children are rare, and to date none have focused on children with BLLs <10 μg/dL. 

Observational studies have inherent limitations—not specific to studies of lead 

toxicity—with the potential to produce biased results. Biases from observational 

studies can obscure true causal effects of toxicant exposures or produce associations 

between toxicant exposures and health status when no causal relation is present. 

Thus, statistical associations from individual observational studies or multiple 

studies subject to similar biases cannot establish causal relationships; additional, 

non-statistical criteria may be used to evaluate such evidence. Although causal 

criteria have been stated in various ways, the Surgeon General’s Report on Smoking 

and Health (U.S. Public Health Service 1964) provides a useful set of criteria. They 

include: 

• The consistency of the association. Is a similar association observed across 

studies with varying methods and populations? 

• The strength of the association. The strength of an association is the 

extent to which the risk of a disease or a measure of health status varies in 

4
 

 

relation to exposure and can be expressed, for example, as a relative risk or 

regression coefficient. It is distinguished from the statistical significance of an 

association that reflects both the strength of the association and the sample 

size. An additional criterion, specificity of the association, is closely related to 

strength of the association and is considered less important in the context of 

multifactorial health conditions. 

• The temporal relationship of associated variables. Does the hypothesized 

causal exposure occur before the health outcome associated with it? 

• Coherence of the association. Is the observed association consistent with 

other relevant facts including, for example, experimental animal studies and 

the descriptive epidemiology of the health condition under study? 

The application of these criteria does not provide a clear demarcation for 

concluding definitive proof of causation versus inadequate evidence. Rather, the 

more the available evidence meets these criteria, the greater the confidence in 

causal inference about an association. Consistent with these criteria, the WG 

identified several issues specifically relevant to inferring causality from associations 

(or the lack of associations) of BLLs to health measures observed in studies of lowlevel lead exposure. These potential biases are not unique to studies of children 

with BLLs <10 μg/dL (e.g., Smith 1989). However, the larger number of human and 

experimental animal studies (including primate studies) and the nature of observed 

health effects associated with higher BLLs have conclusively demonstrated the 

adverse health effects of lead. However, far fewer studies of possible health effects of 

BLLs <10 μg/dL have been conducted, and the relative importance of some sources 

of bias may be greater at these lower levels. Therefore, the work group considered 

several issues in interpreting the findings of available studies (see Discussion). 

At the time of the WG’s review, a consortium of investigators from several longitudinal studies of lead exposure and cognitive function in children were conducting a reanalysis of data pooled from these studies. These studies included serial 

measures of blood lead level, cognitive function, and a large number of potential 

confounders, thus providing stronger evidence than is available from cross-sectional 

studies. A focus of the pooled reanalysis involved studying the shape of the association between postnatal lead exposure at low levels and measured IQ (B. Lanphear, 

personal communication, 2003). The WG reviewed published reports from individual cohort studies from which data were pooled, but the final results of this pooled reanalysis were not available for inclusion in the WG report. [Note: Results of the pooled 

renanlysis were published (Lanphear et al 2005) after the WG finished its review.] 

Because of the nature of its charge, the WG did not develop policy 

recommendations or address questions relevant to such recommendations. Such 

policy decisions and questions will, if appropriate, be considered by the full ACCLPP 

after reviewing the findings of this report. 

5
____________________ 

Criteria for Relevant Studies 

The WG initially considered, then rejected, limiting its review to studies for 

which published results provide direct comparisons between children with varying 

BLLs <10 μg/dL. Such a review would include a relatively small number of studies. 

Instead, the group decided that the larger number of studies that have included 

IQ as an outcome could, collectively, indirectly support or refute the existence 

a threshold near 10 μg/dL for the blood lead–IQ association. The rationale for 

this approach is based on that used in a review and metaregression reported by 

Schwartz (1994) and outlined in the following paragraphs. 

Suppose that, hypothetically, a threshold exists near 10 μg/dL, above which 

mean IQ decreases linearly with increasing blood lead, with a slope equal to x and 

below which mean IQ is not associated with blood lead1

 (see Figure 1—Hypothesized 

“true” relation A). In studies of children who have BLLs <10 μg/dL, estimated 

slopes would be, in the absence of sampling error, equal to 0. For studies in which 

all children have BLLs above the threshold, the estimated slope would be, again 

ignoring sampling error, equal to x. For studies in which some children have blood 

lead above and others below the threshold, estimated slopes will vary between 0 and 

x as shown in Figure 1. Thus, if regression coefficients estimating the IQ–blood lead 

slope are less negative (approaching 0) in populations with lower mean BLLs than 

in populations with higher mean levels, a threshold near 10 would be suggested. 

The absence of such a trend or an increase in slopes with decreasing mean blood 

lead level of the population studied would provide evidence against such a threshold 

and instead support “true” relations B and C, respectively. This ideal hypothetical 

case presumes that effect sizes from the studies compared are based on models that 

correctly specify the form of the BLL–IQ relation and that factors that might modify 

the relation do not vary across studies. 

Because of this approach, studies that assessed the association between blood 

lead and measured IQ were included in this review, even if the published results 

did not examine blood lead–IQ associations limited to BLLs <10 μg/dL (as was true 

in most cases). An additional reason for considering studies that measured IQ was 

the relationship of IQ to other outcomes of policy and public health importance 

including educational success and earnings potential (Grosse et al. 2002). Because 

the McCarthy Scales of Children’s Ability (MSCA) General Cognitive Index (GCI) 

was used in a number of studies to measure cognitive function in preschool children 

and because GCI and IQ scores have similar distributions, studies using GCI as an 

outcome were also included in this review. 

1

The concept of a threshold existing for the population makes little sense toxicologically since even if 

individual thresholds exist, these are likely to vary. Nonetheless, the threshold concept plays a major 

role in regulatory toxicology, and it only becomes clear in cases like lead that such constructs can be 

highly problematic. 

6
The following criteria were used to select relevant studies to review for this 

report: 

1. Blood lead levels were measured using graphite furnace atomic absorption 

spectrophotometry (GFAAS) or anodic stripping voltametry. 

2. The study was published in English. 

In addition, 

For studies in which IQ or GCI was a measured outcome, the 

study analyses included an assessment of the association between 

BLLs measured in children and IQ or GCI. 

For studies in which IQ or GCI was not a measured outcome, the 

study analyses included an assessment of the association between 

BLLs <10 μg/dL measured in children and a health outcome. The 

assessment could either be formal (e.g., non-linear modeling, linear 

modeling restricted to populations with all or at least 95% of children 

having BLLs <10 μg/dL, statistical comparison of two or more subgroups with BLLs <10 μg/dL) or informal (e.g., graphical display of 

results permitting visual assessment of blood lead–outcome relation in 

the range <10 μg/dL). 

Literature Search 

To identify potentially relevant articles, a comprehensive report published by the 

Agency for Toxic Substances and Disease Registry (ATSDR 1999) was reviewed first 

to identify cited articles that related to low-level lead exposure in children. The list 

of potentially relevant citations identified in the ATSDR report was supplemented 

by three computerized literature searches, using Dialog® to search Medline, Toxfile, 

and other bibliographic databases. Search terms (see Appendix A) were chosen to 

identify articles reporting on blood lead measurements and one or more domains 

of health related to lead exposure including neurodevelopment, cognitive function, 

intelligence, behavior, growth or stature, hearing, renal function, blood pressure, 

heme synthesis, hematopoiesis, and Vitamin D metabolism. The first search 

spanned articles published from 1995 through 2002 and indexed as of September 

2002, the month and year that the initial search was performed. The second search 

was performed in April 2003 and spanned the period 2002 through the search date. 

A third search, spanning the years 1990 through 1996, was performed when a 

relevant article not cited in the ATSDR toxicological profile was identified by one of 

the work group members. In addition, potentially relevant articles were identified 

by work group members and through citations in articles identified previously. 

7
Abstracts were reviewed initially. If they were ambiguous or if they suggested 

the article was relevant, full articles were checked for relevance. Articles deemed 

relevant were abstracted for this report. Appendix A summarizes the number of 

possibly relevant references identified, full articles checked for relevance, and 

relevant articles abstracted and considered in the review. 

Structured Abstracts 

For each relevant study, a structured study abstraction was performed that 

captured the following information: the study location, sample size, age at which 

blood lead was measured, age at which the outcome was measured, available 

information about the blood lead distribution (including mean or other measure 

of central tendency, variance, and percent of participants with BLLs <10 μg/dL), 

the crude and adjusted regression coefficients relating blood lead to outcome (if 

available), the type of model fit (linear, log linear, or other), and the covariates 

included in the adjusted model. If regression coefficients were not available, other 

measures of association reported (e.g., correlation coefficients) were noted. Because 

some studies fit multiple blood lead-outcome models (e.g., cohort studies with blood 

lead and IQ measured at multiple ages), relevant information about each model 

estimated was abstracted. For IQ studies, covariates measured and not included in 

adjusted models were recorded when available. 

Review of Cohort Study Methods 

Among relevant published results were those from cohort studies specifically 

designed and conducted to study the relation of BLLs to children’s cognitive 

function and other health outcomes. Because these studies had the strongest 

and best-documented study designs for this review, methods used for blood lead 

measurement and neuropsychological assessment were summarized for these 

studies. This information was collected from published studies; in some cases, the 

studies were supplemented by information provided through correspondence with 

the investigators. 

Results 

Studies Relating Postnatal Lead Exposure to IQ or General Cognitive 

Index 

Studies in which IQ or GCI were measured as an outcome and other criteria 

were met included 23 published reports from 16 separate study populations. Results 

from these studies are summarized in Table 2 (full scale IQ and GCI), Table 3 

(performance IQ), and Table 4 (verbal IQ). Within each table, results are grouped 

according to the age at blood-lead measurement and age at outcome measurement; 

8
 

each grouping displays results sorted according to the measure of central tendency 

of the blood-lead distribution. Because some studies used linear models (BLLs were 

untransformed) and some used log-linear models (BLLs were log transformed), 

estimated regression coefficients were, when possible, used to calculate the 

estimated change in IQ or GCI corresponding to a blood lead increase from 5 to 

15 μg/dL to allow for comparisons across studies. Covariates included in adjusted 

models are grouped into several broad domains that were addressed in most of the 

published studies. 

Among studies that provided results for the size and direction of the associations 

between BLLs and Full Scale IQ or GCI, regardless of statistical significance, 

a majority revealed that both crude and adjusted associations were consistent 

with an adverse effect—IQ decreases with increasing levels of blood lead. In most 

cases, covariate adjustment attenuated, but did not eliminate, these estimated 

associations. Findings for performance and verbal IQ were similar, with some 

studies showing stronger associations of lead with performance IQ and others with 

verbal IQ. 

Notable exceptions to this pattern, however, were found. Results from the 

Cleveland cohort (Ernhart et al. 1987, 1988, 1989) indicated a crude inverse 

association between blood lead and IQ but no association with covariate adjustment. 

In the Cincinnati and Boston cohort studies, BLLs measured at or below 12 months 

of age showed no association or a slightly positive association with covariateadjusted IQ (Dietrich et al. 1993; Bellinger et al. 1992). Though published results 

from a cohort study in Costa Rica (Wolf et al. 1994) did not provide the size and 

direction of the estimated blood lead–IQ slope, unpublished results provided to 

the WG did show covariate-adjusted IQ increasing with BLL (B. Lozoff, personal 

communication 2003). The estimated BLL–IQ association in the Kosovo cohort was 

strengthened substantially with covariate adjustment (Wasserman et al. 1997). 

No trend toward attenuation of the association between blood lead and IQ (or 

GCI) across studies with decreasing average BLLs is evident (Figures 2 and 3). In 

one of these studies, analyses were presented that provide more direct information 

concerning the association between BLL and cognitive function at BLLs <10 μg/dL. 

The steepest estimates of blood lead–IQ slope from the Rochester (Canfield et al. 

2003) studies were based on analyses restricted to children whose measured BLL 

never exceeded 10 μg/dL. The estimated slope was substantially larger than those 

estimated from the entire study population (9.2 versus 5.3 IQ point reduction 

in covariate adjusted IQ for BLL increase from 5 to 15 μg/dL). Canfield and his 

colleagues (2004) also reported a non-linear model supporting a steeper blood lead– 

IQ slope at lower levels. Though published as a letter to the editor, rather than in a 

peer-reviewed article (and therefore not included in the structured review), similar 

findings were reported for a reanalysis of the Boston cohort: a steeper BLL–IQ 

slope in the population of children whose measured BLLs never exceeded 10 μg/dL, 

compared with the entire study population (Bellinger et al. 2003). 

9
 

 

 

 Most of the published studies included at least one measure of socio-economic 

status. All of the published results from cohort studies were adjusted for Home 

Observation for Measurement Environment (HOME) score and birth weight; all 

except the Costa Rica cohort were adjusted for a measure of maternal intelligence. 

A reanalysis of the data from the Costa Rica cohort with adjustment for maternal 

IQ was consistent with the original finding of a non-significant positive blood 

lead–IQ slope (B. Lozoff, personal communication, 2003). Prenatal exposure to 

maternal smoking was adjusted in the majority of studies, whereas only in the Port 

Pirie cohort was a measure of postnatal environmental tobacco smoke exposure 

included. Iron deficiency anemia was included as a covariate in results from the 

Costa Rica study, which found no association of lead and IQ; the inverse blood 

lead–IQ associations in the Rochester study (Canfield et al. 2003) and the Karachi 

study (Rahman et al. 2002) were adjusted for serum transferrin saturation and 

hemoglobin, respectively. In addition, in the Kosovo study (Wasserman et al. 

1997), alternative models were fit with adjustment for hemoglobin, resulting in no 

appreciable change in the lead coefficient. 

Not all studies reported regression coefficients that could be used to estimate the 

change in IQ associated with a BLL change of 5 to 15 μg/dL, and the overall pattern 

of results summarized above and in Figures 2 and 3 might have been altered had 

regression coefficients been available from all studies. For example, a member 

of the WG provided results of reanalysis of the data from the Costa Rica cohort, 

which showed no evidence of an inverse relation of BLL to IQ with adjustment for 

maternal IQ and other covariates used in the published result (Wolff et al. 1994; 

B. Lozoff, personal communication, 2003). 

Studies of Health Endpoints Other than IQ and CGI 

More stringent criteria were required for inclusion of studies in this review if they 

assessed health endpoints other than general intelligence as measured by IQ or GCI. 

These studies are summarized in Table 5 and are described in the following paragraphs. 

Cognitive Function 

Lanphear et al. (2000) analyzed data on BLLs on performance on standardized 

tests of cognitive function of 4,853 children age 6 through 16 years who were 

evaluated as part of the NHANES III survey, a multiphasic health interview 

and examination survey of a stratified probability sample of the U.S. population, 

carried out from 1988 through 1994. In this population, with a geometric mean 

BLL of 1.9 μg/dL and 98% of children having BLLs <10 μg/dL, significant inverse 

relations were found between BLLs and scores on the Wide Ranging Achievement 

Test (WRAT) arithmetic and reading scores and on the WISC-R block design and 

digit span subscales. The relationships were strengthened (the slopes became more 

negative) as analyses were progressively restricted to children with lower BLLs. 

Stone et al. (2003) reanalyzed the data used by Lanphear et al. (2000). While the 

10
results they present are largely consistent with the findings of Lanphear et al., 

they provided a critique of the validity of the NHANES III data for evaluating leadrelated impacts on neuropsychological development in children. Their critique did 

not provide results that could be summarized in the structured abstract format used 

in this report, so a discussion of the Stone et al. critique is found in Appendix B. 

Other Neurobehavioral Measures and Visual Function 

Three reports (Altman et al. 1998; Walkowiak et al. 1998; Winneke et al. 1994) 

describe the relation of blood lead to several neurobehavioral measures and to 

visual function assessed in 384 school children 5 to 7 years of age in three cities in 

Eastern Germany. Blood lead levels were generally low, with a geometric mean of 

4.25 μg/dL and 95% of children having BLLs <10 μg/dL. Walkowiak et al. (1998) 

reported a significant negative association between BLLs and WISC vocabulary 

subscale scores. Continuous performance test false positive and false negative 

responses increased with increasing BLLs. Other measures inversely related to 

BLL included performance on a pattern comparison test, finger tapping speed 

(Winneke et al. 1994), and visual evoked potential interpeak latency (Altman et 

al. 1998). Mendelsohn and colleagues (1999) found a 6 point deficit in the Mental 

Developmental Index (MDI) of the Bayley Scales of Infant Development for children 

aged 12 to 36 months with BLLs 10-24 μg/dL compared with children who had BLLs 

<10 μg/dL. A scatterplot of covariate-adjusted MDI versus blood lead suggests the 

association continues at BLLs <10 μg/dL. 

Neurotransmitter Metabolite Levels 

Among children ages 8 through 12 years with mean BLL of 3.95 μg/dL, a direct 

relation of blood lead (PbB) to higher urinary homovanillic acid, a neurotransmitter 

metabolite, was found for the subset of children with BLLs >5 μg/dL (Alvarez Leite 

et al. 2002). 

Growth 

Two studies examined the relation of BLLs <10 μg/dL to somatic growth. Ballew 

et al. (1999), using the NHANES III data, found that BLLs were inversely related to 

height and to head circumference among children 1 to 7 years of age. A birth cohort 

of children in Mexico had BLLs and head circumference assessed every 6 months 

from 6 to 48 months of age, during which time the median BLL varied from 7 to 

10 μg/dL (Rothenberg et al. 1999). Most postnatal blood lead measures were 

inversely correlated with covariate adjusted head circumference, with the strongest 

relation found between blood lead at age 12 months and head circumference at 36 

months. Kafourou and colleagues (1997) reported a significant negative association 

between BLL and covariate-adjusted head circumference and height in a population 

of children with a median BLL of 9.8 μg/dL, with a scatterplot suggesting the 

relation extends to BLLs <10 μg/dL. 

11
 

 

 

Sexual Maturation 

Two studies, both based on analyses of the NHANES III data, found an 

association between BLLs <10 μg/dL and later puberty in girls. Selevan et al. (2003) 

found that BLLs of 3 μg/dL, compared with 1 μg/dL, were associated with significant 

delays in breast and pubic hair development in African American and Mexican 

girls. The trend was similar, but not significant, for non-Hispanic white girls. Age at 

menarche was also delayed in relation to higher BLLs, but the association was only 

significant for African-American girls. Wu et al. (2003) reported similar findings 

for girls in the NHANES III population but did not stratify the analysis by racial/ 

ethnic group. Compared with BLLs 2.0 μg/dL and below, BLLs of 2.1–4.9 μg/dL were 

associated with significantly lower odds of attaining Tanner 2 stage pubic hair and 

menarche; whereas no overall association with breast development was noted. 

Dental Caries 

In the NHANES III population, the odds of having dental caries, comparing 

children ages 5–17 years in the middle tertile of the BLL distribution (range of 

BLLs 1.7–4.1 μg/dL) with those in the lowest tertile, was significantly elevated 

(odds ratio=1.36, 95% confidence interval 1.01–1.83) (Moss et al. 1999). Gemmel 

et al. (2002) evaluated the association between BLLs and caries in 6–10 year old 

children from urban communities in eastern Massachusetts (mean BLL=2.9 μg/dL) 

and a rural community (mean BLL=1.7 μg/dL) in Maine. They found a significant 

direct relation of BLL to caries in the former, but not the latter population in which 

a non-significant decrease in caries’ frequency was observed with increasing blood 

lead. In the urban population, the trend of increasing caries with PbB level was 

evident comparing children with BLLs of 1, 2, and 3 μg/dL. 

Blood pressure and renal function 

Among 66-month-old children in Kosovo, a graph depicting adjusted mean 

systolic and diastolic blood pressure versus BLL showed no consistent trend across 

4 groups of children (approximately 28 per group) with BLLs spanning a range from 

approximately 5 to 10 μg/dL (Factor Litvak et al. 1996). In a population of 12- to 

15-year-old children living near a lead smelter and a control group, urinary retinal 

binding protein (U-RBP) was found to be significantly associated with BLL in a 

stepwise regression. When urinary RBP excretion was examined by BLL tertiles, 

significantly lower U-RBP was seen in the group with BLL < 8.64 μg/dL compared 

with BLLs 8.64–12.3 μg/dL. 

Heme synthesis biomarkers 

Roels et al. (1987) studied the relations of PbB to heme synthesis biomarkers 

and reported no evident threshold for inhibition of aminolevulinic acid dehydratase 

synthesis at PbB as low as 8–10 μg/dL, while the threshold for increasing erythrocyte 

12
 

 

 

protoporphyrin levels was evident in the range of 15–20 μg/dL, consistent with other 

studies, including two meeting criteria for inclusion in this report (Rabinowitz et al. 

1986; Hammond et al. 1985). 

Discussion 

Question 1: Does available evidence support an inverse association between 

children’s blood lead levels <10 μg/dL and children’s health? 

The weight of available evidence, both indirect and direct, clearly favors an 

inverse association between these BLLs and cognitive function among children. 

The indirect evidence comes from the great majority of studies that have examined 

BLLs in relation to standardized measures of overall cognitive function; these 

studies reveal an inverse relationship and no trend toward weaker associations 

in populations with lower BLL distributions. More direct evidence of such an 

association comes from a recent analysis of data from a cohort designed from the 

start to study the relation of blood lead to child development (Canfield et al. 2003). 

This study demonstrated that the inverse relation between BLL and cognitive 

function exists and is stronger at BLLs <10 μg/dL compared with higher BLLs; it 

also does not show a threshold within the range of routinely measured BLLs below 

which no association was present. A recent letter to the editor described a reanalysis 

of the Boston cohort data (Bellinger et al. 2003) with findings consistent with 

Canfield et al (2003). Several recent analyses of data from the NHANES III and 

other populations also provide direct evidence of associations that imply adverse 

impacts of lead on indicators of children’s neurocognitive development, stature, 

head circumference, dental caries, and sexual maturation in girls, occurring at 

measured BLLs <10 μg/dL. Though the number of studies providing direct evidence 

of associations at BLLs <10 μg/dL is limited and most are cross-sectional, they 

provide supporting evidence of an association in the context of the much larger 

number of studies that relate slightly higher levels of lead in blood to impairments 

of children’s health. 

Question 2: Are the observed associations likely to be causal? 

Though the weight of evidence favors an association between children’s BLLs 

<10 μg/dL and health and, indeed, suggests that such relationships become steeper 

as BLLs decrease, the WG considered a number of concerns that must be addressed 

in judging whether such associations are likely to be causal. The work group 

concluded that collectively, these concerns and limitations of the available evidence 

preclude definitive conclusions about causation and leave considerable uncertainty 

concerning the magnitude and form of causal relations that may underlie these 

associations. At the same time, available evidence does not refute the interpretation 

that these associations are, at least in part, causal. These issues are discussed 

individually in the following text, followed by overall conclusions. 

13
Biologic Plausibility 

Evidence from experimental animal and in vitro studies, which are not subject 

to confounding influences of concern in human observational studies, can establish 

causation and identify mechanisms that might be operative in humans assuming 

a suitable animal model. Thus, evidence from experimental animal and in vitro 

studies can help to assess potential dose–response relationships and thresholds 

within the context of any uncertainty added due to interspecies extrapolation. 

Therefore, an important consideration in judging whether associations between 

BLLs <10 μg/dL and health outcomes are likely to represent causal relationships is 

whether such relationships are biologically plausible on the basis of experimental 

animal and in vitro studies. These studies can also help to assess potential dose– 

response relationships and thresholds, but extrapolation from in vitro and animal 

models to human health risk adds additional uncertainty. 

Lead is the most extensively studied environmental neurotoxicant. Animal 

and in vitro studies have provided abundant information concerning biochemical 

and physiologic changes caused by lead. Along with clinical and epidemiologic 

data, this evidence has clearly established that lead is toxic to the developing and 

mature nervous system. These data have been extensively reviewed elsewhere 

(USEPA 1986; ATSDR 1999; WHO 1995; Davis et al. 1990) and are not exhaustively 

reviewed here. Rather, this discussion highlights evidence concerning potential 

mechanisms of lead toxicity and data from animal studies that are relevant to the 

biologic plausibility of the toxicity of lead, especially to the developing nervous 

systems of children exposed at BLLs <10 μg/dL. 

Although the precise mechanisms of action and their relative importance in 

different manifestations of lead toxicity are not known definitively, in vitro studies 

demonstrate that lead can interfere with fundamental biochemical processes. At the 

most basic level, many of the proposed mechanisms of lead toxicity involve binding 

to proteins and/or interference with calcium dependent processes (Goldstein 1993). 

For some of the adverse health effects of lead (e.g., anemia), the lead-associated 

biochemical changes that contribute to the effect in humans are well understood. 

Lead interferes with heme synthesis in part by binding to sulfhydryl groups in the 

enzyme amino levulinic acid dehydratase (ALAD) (ATSDR 1999), which is especially 

sensitive to inhibition by lead (less than 0.5 micromoles per liter in vitro) (Kusell 

et al. 1978; Dresner et al. 1982). This inhibition causes delta amino levulinic acid, 

a potential neurotoxic agent, to accumulate. Lead also inhibits ferrochelatase, an 

enzyme catalyzing the incorporation of iron into protoporphyrin to form heme. This 

inhibition also may involve lead binding to protein sulfhydryl groups. 

Although anemia and accumulation of protoporphyrin IX in erythrocytes are the 

most obvious consequence of impaired heme synthesis, this pathway could play a 

role in lead-related impairment of cellular function throughout the body (USEPA 

14
1986). By interfering with heme synthesis and perhaps by inducing enzymes that 

inactivate heme, lead can decrease the levels of heme in body tissues (Fowler et al. 

1980). A reduction in the body heme pool may impair heme-dependent biochemical 

processes, such as cellular respiration, energy production, and the function of the 

cytochrome p-450 monooxygenase system involved in detoxification of xenobiotics 

and in transformation of endogenous compounds such as vitamin D precursors 

(USEPA 1986). 

For other more complex health effects of lead, such as impaired neurocognitive 

development and behavioral change, a number of plausible mechanisms have 

been demonstrated in animal and in vitro systems. Lead’s impact on one or 

more biochemical systems needed for normal brain development and function 

could account for the neurobehavioral effects observed at low levels of exposure. 

Especially sensitive to lead in vitro is the activation of protein kinase C (PKC), a 

calcium dependent enzyme. Lead binds more avidly to PKC than its physiologic 

ligand, calcium, causing activation at picomolar concentrations in vitro. (Markovac 

and Goldstein 1988). The interactions between lead exposure and PKC activity in 

the brain are complex; chronic lead exposure may reduce activity of PKC associated 

with cell membranes while increasing cytosolic PKC activity. Lead effects on PKC 

activity have been proposed to mediate potential impacts of lead on cell growth and 

differentiation, including that of neural cells (Deng and Poretz 2002), the bloodbrain barrier, and long-term potentiation (a process related to memory) (Hussain et 

al. 2000). Lead also interferes with calcium-dependent control of neurotransmitter 

release at presynaptic nerve terminals; it may thereby interfere with signaling 

between neurons and possibly with development of neural networks. In both animal 

and in vitro studies, lead has been demonstrated to interfere with neurotransmitter 

systems, including interfering with dopamine binding and the inhibition of 

N-methyl-D-aspartate (NMDA) receptor activity. 

The large body of evidence from animal studies of lead exposure and 

neurodevelopment supports a causal effect that is persistent following exposure 

early in life and that generally parallels human studies in terms of the domains of 

function that are impaired (WHO 1995). Concerning blood lead–effect relationships, 

direct cross-species comparisons of BLLs cannot be made (Davis et al. 1990), and 

most animal studies demonstrating lead-related developmental neurotoxicity 

involved doses that produced BLLs well above 10 μg/dL. However, available studies 

provide strong evidence of adverse effects in animals with BLLs near 10 μg/dL. It 

should be noted that BLLs cited in animal studies generally involve mean levels 

achieved in experimental groups with individual animals varying, sometimes 

substantially, around that mean. 

Non-human primates experimentally exposed to lead early in life demonstrate 

dose related impairments in learning and behavior (Bushnell and Bowman 1979; 

Rice 1985; Levin and Boman 1986). One study, involving monkeys dosed during 

the first 200 days of life with 100 μg/kg/day lead or 50 μg/kg/day lead resulting 

15
in average peak BLLs of 25 and 15 μg/dL respectively, showed deficits relative 

to control monkeys (dose=0μg/kg/day lead; average peak BLL=3 μg/dL) at age 3 

years on “discrimination reversal” tasks (the animals are taught to respond to a 

cue and then the cue is changed and the ability to learn the new cue, with and 

without irrelevant cues, is measured). At the time of testing, mean BLLs in the 

exposed groups had fallen to 13 and 11 μg/dL, respectively. Both exposure groups 

showed deficits, but deficits in the lower exposed group were evident only with 

more complex tasks (e.g., including irrelevant cues) (Rice 1985). The same monkeys 

showed persistent impairments at 9 to 10 years of age (Gilbert and Rice 1987). 

Experimental studies in rats have demonstrated behavioral effects at mean BLLs 

of 10–20 μg/dL (Cory-Slechta et al. 1985; Brockel and Cory-Slechta 1998). 

There is uncertainty about the relationship of the tissue or cellular levels of lead 

linked to physiologic changes in animal and in vitro studies to the corresponding 

human blood lead level required to produce such levels at target sites. Although 

most (90 to 99%) lead in whole blood is in red cells, plasma lead level likely better 

reflects lead transferred from bone stores and available for transfer to target 

tissues (Cake et al. 1996). Because red cells have limited capacity to accumulate 

lead, the relation of blood lead to plasma or serum lead is non-linear with serum 

lead increasing more rapidly at higher BLLs (Leggett 1993). In subjects with a 

mean BLL of 11.9 μg/dL, plasma lead levels ranged from 0.3 to 0.7% of whole BLLs 

(Hernandez-Avila et al. 1998). The relation of plasma serum levels in intact animals 

to tissue levels measured in in vitro models is probably more complex. It is also 

uncertain whether in vitro studies demonstrating possible mechanisms for low-level 

lead toxicity reflect mechanisms operative in the intact animal. For example, Zhao 

et al. (1998) found that lead interfered with PKC in choroid plexus endothelial cells 

in a dose dependent fashion over the concentration range of 0.1-10 micromolar. 

However, no effect on choroid plexus PKC activity was seen in an in vivo model. 

Conclusions: The fundamental nature of biochemical and physiologic changes 

linked to lead in in vitro and experimental animal studies illustrates potential 

mechanisms for lead toxicity that might be operative in humans at very low 

exposure levels. Experimental animal studies support the biologic plausibility of 

adverse health effects of lead in children at BLLs near 10 μg/dL. However, definite 

conclusions concerning the relationship of health status of children and BLLs <10 

μg/dL cannot be drawn from these studies because of limitations of extrapolating 

from in vitro systems to intact animals and from animals to humans and because 

of the limited amount of data available from studies of animals dosed to produce a 

range of BLLs less than 10 μg/dL. Data from primates, which can most readily be 

extrapolated to humans, are especially limited. 

On the other hand, given the uncertainty in extrapolating across species, the 

fact that animal test systems cannot match the complexity of learning tasks faced 

by young children, and the relatively small relative difference in BLLs shown to be 

harmful in animals and those at issue in children, adverse health effects in children 

at BLLs <10 μg/dL are biologically plausible. 

16
Blood Lead Measurement 

The precision and accuracy of blood-lead measurements performed in an 

epidemiologic study impacts observed results. If BLLs are systematically over or 

underestimated, biases in estimated blood lead response relationships and/or no 

effect thresholds will result. All blood lead measurements involve some random 

error, which, if a true association between blood lead and health exists, will tend to 

bias estimates of the relation toward the null (i.e., no effect) value. The quality of 

blood lead measurements varies between laboratories, between different analytical 

technologies, and between different specimen collection techniques. In addition, 

laboratory performance for blood lead has improved markedly over the last three 

decades and continues to improve as new analytical technologies are developed. 

Each of these factors becomes important in assessing the quality of blood-lead 

measurements used in published studies. In this section, specimen collection and 

laboratory factors that can affect blood-lead precision and accuracy are considered. 

The widespread industrial use and dispersal of lead, particularly during the 

last century, has ensured that it is a ubiquitous contaminant. Therefore, to prevent 

false-positive results, stringent procedures are necessary to reduce environmental 

contamination of blood collection devices and supplies. Consequently, venous blood 

collected using evacuated tubes and needles certified as “lead-free” is considered 

the most appropriate specimen for blood lead measurements (NCCLS 2001). 

However, collection of venous blood from pediatric subjects is sometimes difficult; 

thus, capillary blood from a finger puncture is used widely for screening purposes. 

Published studies have compared the quality of blood lead results for capillary and 

venous specimens drawn simultaneously (Schlenker et al. 1994; Schonfeld et al. 

1994; Parsons et al. 1997). With stringent precautions, particularly rigorous hand 

washing, contamination errors can be held to <4% (Parsons et al. 1997). Therefore, 

although venous blood is preferable for epidemiologic studies of environmental lead 

exposure, use of capillary blood is acceptable if collected by staff specially trained 

in the technique using devices certified as “lead-free.” Data should be provided 

showing an acceptably low rate of contamination errors and low mean bias in the 

capillary BLLs as collected using the study protocol. 

Currently, three analytical approaches to blood lead measurement are used: 

atomic absorption spectrometry (AAS); anodic stripping voltammetry (ASV), and 

inductively coupled plasma mass spectrometry (ICP-MS). A thorough discussion 

of these analytical techniques is beyond the scope of this report; however, a 

comprehensive assessment has been published by the National Committee for 

Clinical Laboratory Standards (NCCLS 2001). Briefly, the older flame atomization 

AAS methods, which include MIBK-extraction and Delves cup, are less precise, 

with a detection limit near 5 μg/dL for Delves cup (Parsons and Slavin. 1993). 

Thus, they are not well suited for examining relationships between BLLs <10 μg/ 

dL and health. The electrothermal atomization techniques based on the graphite 

furnace (ETAAS) are more precise and more sensitive and, therefore, have better 

17
detection limits, typically around 1.0 μg/dL. A direct comparison between ASV and 

ETAAS techniques (Bannon et al. 2001) shows that the latter has better precision 

and better accuracy. Nonetheless, when operated in experienced hands and with 

a stringent quality assurance/quality control (QA/QC) program that includes 

calibration standards traceable to the mole via isotope dilution mass spectrometry 

(ID-MS), ASV can deliver blood-lead measurements with accuracy and precision 

sufficient to examine health effects at BLLs <10 μg/dL (Roda et al. 1988). 

In order to assess the accuracy and precision of blood-lead measurements made 

for research purposes, investigators should provide information on the laboratory’s 

performance in measuring external quality control samples and on the between-run 

standard deviation for routine quality control samples that span the relevant blood 

lead range for a given study. 

Conclusions: The key considerations relevant to judging the accuracy and 

precision of blood lead measurements in published studies include the type and 

quality of blood specimen collected, analytical methodology used by the laboratory, 

and internal and external QA/QC procedures in place. For the purpose of studying 

the relationship between BLLs <10 μg/dL and health endpoints venous samples are 

preferred and capillary samples are acceptable with evidence of a rigorous protocol 

to control contamination errors. Acceptable analytic methods include electrothermal 

AAS, ASV, and ICP-MS. Information on laboratory performance (i.e., accuracy and 

precision) from external and internal quality control data should be provided. 

To be included in this review, studies were required to have employed suitable 

measurement methods. In addition, venous samples were used for most postnatal 

blood lead measurements in the relevant cohort studies (Table 6) and others cited 

in this report. Given this and the blood lead quality control procedures reported 

in the most informative studies, it is highly unlikely that systematic errors in 

measurement in the relevant studies were sufficient to bias the observed blood 

lead distributions enough that associations observed <10 μg/dL were attributable 

to BLLs above that threshold. Random variation in BLLs and random error in 

BLL measurement would make it difficult to collect sufficient data to identify a 

threshold, if one were to exist. 

Blood Lead Age Trend, Tracking, and Inference Concerning Blood Lead 

— Effect Relations in Children 

Age-related changes in children’s BLLs and within-child correlation of blood lead 

measured at different ages may influence observed associations between BLL and 

health at a given age. In addition, the biologic impact of lead in children is likely 

determined not only to the BLL measured at any one time but, also, the ages at 

which a given level occurs and the duration of exposure. 

18
Under most exposure scenarios, children’s BLLs show a characteristic age trend. 

A newborn’s BLL will largely reflect the BLL of its mother. Because adult women 

tend to have lower BLLs than young children, umbilical cord BLLs are generally 

lower than BLLs during childhood. During the latter half of the first year of life, 

however, children’s BLLs begin to increase as the infant becomes more active, 

mobile, and exposed to ambient lead. The onset of ambulation during this period is 

likely to be important, as are play patterns that bring the child into contact with 

environmental media such as lead-contaminated dust and soils. Other factors that 

affect exposure include the increased hand-to-mouth activity of children, including 

the practice of eating “in place,” i.e., in play areas. Physiologic factors, such as more 

efficient absorption of ingested lead in children compared with adults, and their 

greater food and air intake on a body weight basis might also contribute to the early 

postnatal rise in BLL. 

The mean BLL within a study sample generally peaks during 18 to 36 months 

of age, and slowly declines over the next few years. This blood lead profile is seen 

among economically disadvantaged urban minority children (Dietrich et al. 2001) 

and among children living near lead smelters (Figure 4) (Tong et al. 1996). In 

cohorts with extremely high exposures, the blood lead decline might be very gradual 

(e.g., Wasserman et al. 1997). In the Cincinnati Study, the same general profile 

was evident in each of four strata defined by average lifetime BLL, suggesting that 

it is, to some extent, independent of the overall level of exposure. This blood lead 

profile has not been observed in all study cohorts, however. In the Boston Study, for 

example, mean BLL varied minimally, from 6.2 to 7.6 μg/dL, from birth through 5 

years of age (Rabinowitz et al. 1984; Bellinger et al. 1991). 

One implication of the typical profile is that maximum level is often associated 

with age, constituting an obstacle to an effort to identify age-specific vulnerability 

to lead toxicity. Compounding this challenge is that, under many exposure scenarios 

(particularly those involving higher exposures), intra-individual stability of BLL 

tends to be substantial. That is, BLL tends to “track,” so that if, at time 1, child A 

has a higher BLL than child B, child A is likely to have a higher BLL than child B 

at time 2 as well. Thus, children’s rank ordering tends to be similar over time even 

though, in absolute value, BLL rises and falls over the course of childhood. Again, 

however, the degree of intra-individual stability varies from cohort to cohort. In 

the Boston Study cohort, for instance, the extent was limited; this stability is likely 

attributable to the generally low BLLs of the study population (Rabinowitz et al. 

1984). 

A BLL measured after 36 months of age will, on average, be lower than the BLL 

that would have been measured if a child’s blood been sampled sometime during 

the 18 to 36 month period. Suppose, however, that the critical period with regard to 

producing an adverse health outcome is the 18 to 36 month period, and that, in a 

study conducted post-36 months, an inverse association is noted between concurrent 

BLL and a health endpoint. If the concurrent BLL is the only index of lead exposure 

19
 

 

 

 

 

 

history available, basing a dose–effect assessment on it will, to the extent that the 

natural history of BLLs in the study cohort follows the canonical form illustrated 

above, result in an underestimate of the BLL responsible for any adverse health 

effects noted at the time of or subsequent to blood sampling. In other words, one 

will conclude that adverse health effects occur at lower BLLs than is the case. For 

instance, assume that the inverse association shown in Figure 5 holds between IQ 

and concurrent blood lead in a cross-sectional study of 6 year olds. 

If, however, the BLL of each child was, on average, 5 μg/dL greater at age 2 than 

at age 6, and age 2 is the time of greatest toxicologic significance (i.e., it is age at 

which lead exposure produced the IQ deficit observed at age 6), then the dose–effect 

relationship that underlies the association seen at age 6 would be more accurately 

described as in Figure 6. 

This dataset would thus not be informative with respect to the functional form of 

the dose–effect relationship at levels below 10 μg/dL insofar as (hypothetically) all 

children had a BLL greater than 10 μg/dL at age 2. 

Other uncertainties apply to interpreting blood lead–health associations (or 

lack of associations) observed at any point in time. First, the relation of age to 

vulnerability to lead toxicity is not well understood. Is BLL during the age period 

18 to 36 months more toxicologically critical than a measure of cumulative lifetime 

exposure, such as the area under the curve or some other exposure index? Also, it is 

possible that the critical age varies with dose, health endpoint, or sociodemographic 

factors. Available studies do not provide consistent answers to these questions. 

For example, in the Boston cohort, blood lead at age 24 months was most strongly 

related to IQ at age 10 years (Bellinger et al. 1992), whereas in the Port Pirie 

Cohort, the lifetime average BLL through age 5 years was most predictive of IQ at 

age 11 to 13 years. 

If 18 to 36 months is the critical age of exposure, theoretically, it is possible to 

“adjust” an observed blood lead distribution measured at age 6 by some function 

to reflect the downward trend in BLL with age and estimate the blood lead 

distribution at a different age, (e.g., age 2 years). However, a “one size fits all” 

adjustment likely is not appropriate for all children. Moreover, the appropriate 

adjustment is likely to be study-site-specific (i.e., depend on the key exposure 

sources and pathways of a particular study cohort). 

It would be possible to get a general sense of how accurately past peak exposure can 

be estimated for children in cross-sectional studies by using data collected in prospective 

studies in which blood lead was measured frequently during the period spanning birth to 

school-age. Examining the distribution of the differences between BLLs measured at ages 

18 to 36 months and at age 6 would suggest the amount of exposure misclassification that 

would result from applying a constant adjustment factor. 

20
Conclusions: Because of age trends in blood lead and the tendency of BLLs 

to “track” within individual children, inferences drawn from cross-sectional 

associations between blood lead and health at a given age should be interpreted 

cautiously because of the influence of likely higher BLLs occurring earlier in life. It 

may be possible to apply data on age trends and within-subject correlation of blood 

lead to estimate, from an observed blood lead–health association, the approximate 

relation to BLLs at an earlier age. However, because age trends and the extent of 

“tracking” of blood lead levels vary from one population to another, it is not possible 

to estimate with confidence the distribution of blood lead levels earlier in life for any 

given population whose blood lead levels were only measured at one point in time. If 

the only relevant studies available are based on cross-sectional data (e.g., data from 

NHANES III), age trends and “tracking” of BLLs would represent a substantial 

challenge to inferring a causal link between BLLs <10 μg/dL and adverse health 

impacts. However, recently published results from two cohort studies (Canfield et 

al. 2003; Bellinger et al. 2003) showed inverse associations between BLLs measured 

early in life (6 to 24 months and 24 months, etc.) and IQ measured at older 

ages among children whose measured BLLs did not exceed 10 μg/dL. Therefore, 

associations observed in cross-sectional studies cited in this report likely do not 

exclusively result from the impact of higher BLLs experienced earlier in life. 

Quality of Neurobehavioral Assessments 

As with blood lead (exposure) measurements, the accuracy, precision, and 

consistency of neurobehavioral assessments can influence observed blood leadoutcome relations. In order to judge whether the data from a study should be 

considered in characterizing the functional form of the dose–effect relationship at 

BLLs <10 μg/dL, one would like to have access to the following information about 

the conduct of the neurobehavioral assessments: 

• Assurance that examiners were blinded to all aspects of children’s lead 

exposure histories.

• The assessment setting. Assessments can be standardized when carried out 

in a hospital, neighborhood health center, or community center, but may be 

difficult to standardize in a participant’s home. 

• Essentials of the process by which an examiner was trained, including the 

criterion used to certify an examiner (e.g., percent agreement on an item-byitem basis with some gold standard, average difference in scores assigned 

compared with gold standard, correlation with gold standard in terms of 

scores assigned). 

• The plan implemented for supervision of test administration over the 

course of data collection (e.g., periodic observation of test sessions, live or by 

videotape). 

21
• The plan implemented for supervision of test scoring over the course of data 

collection (e.g., double scoring of a sample of protocols). 

• The number of neurobehavioral examiners used over the course of data 

collection. 

• If more than one assessor was used, whether the data analysis plan included 

evaluation of an “assessor” effect (i.e., as a main effect and as a modifier of 

lead’s association with endpoints). 

While some have argued that neurobehavioral examiners should have 

professional qualifications (e.g., Kaufman 2001 cites the need for a clinician with 

graduate-level training in psychometrics, neuropsychology, etc.), the Practice 

Committee of the American Academy of Clinical Neuropsychology supports the 

widespread practice of using non-doctoral level personnel, with appropriate training 

and supervision by a doctoral-level psychologist, in the administration and scoring 

of clinical neuropsychological evaluations (Brandt et al. 1999). 

Assuming examiners are blinded regarding BLLs, most problems with quality 

of neurobehavioral assessment would be expected to mask or underestimate true 

associations rather than create spurious ones. It is possible, for example, that 

use of non-professional examiners might introduce noise into the data, masking 

an association between toxicant exposure and performance. In one study of 

methylmercury (MeHg) exposure (Grandjean et al. 1997), MeHg was inversely 

associated with children’s scores on the Similarities subtest of the WISC-III 

among children tested by the supervising doctoral-level study examiner. Assuming 

that blinding was preserved, use of non-professional examiners likely would not 

introduce a positive bias in effect estimates. 

Measurement quality problems causing bias of associations away from the null, 

without loss of blinding, are theoretically possible. For example, if one examiner 

consistently yields lower scores than another and that examiner, without knowledge 

of BLLs, is assigned to assessments of a segment of the study population at higher 

risk for lead exposure, a spurious inverse association could be created between lead 

level and neuropsychological test scores. 

Conclusions: The key considerations in judging the quality of neurobehavioral 

assessments in the research setting are the blinding of examiners to leadexposure history, the training and supervision of examiners, and the setting 

for examinations. If examiners are truly blinded, other data quality problems 

generally will bias estimated relationships between blood lead and outcomes 

toward the null. Therefore, given that examiners were blinded to BLLs in cohort 

studies demonstrating associations (Table 6) and the NHANES III survey, errors in 

measurement of neuropsychological function likely did not contribute to observed 

associations with BLLs <10 μg/dL. 

22
Potential Confounding Factors 

Social Factors 

Socioeconomic factors influence both lead exposure and many health outcomes, 

including intellectual development, growth, and a number of chronic conditions, 

creating the potential for social factors to confound associations between children’s 

lead exposure and health in observational studies. Because cognitive function 

as reflected in measured intelligence is strongly associated with socioeconomic 

status (SES) and because cognitive function in children is the most studied health 

endpoint in studies of lead-exposed children, this discussion is focused on possible 

SES confounding of associations between BLL and measured intelligence. The 

potential for reported subtle effects of lead on IQ and related measures of intellect 

to be attributable to confounding by socioeconomic factors warrants serious 

consideration (Bellinger et al. 1989). Key relations required for confounding to 

occur are almost certainly present—SES has been shown to be related to BLLs, 

presumably because the neighborhoods and homes in which families of lower 

income reside are associated with higher levels of lead in soil and residences. 

Socioeconomic status also is clearly related to measures of intelligence, whether 

through parental stimulation, nutrition, or resources available in the home. With an 

inverse relationship between socioeconomic factors and lead levels (i.e., higher SES 

predictive of lower lead levels) and a positive relationship between socioeconomic 

factors and measures of intelligence (higher SES predictive of higher intelligence 

test scores), failure to adjust for the confounding effect of socioeconomic factors will 

result in confounding that overstates the harmful effect of lead on IQ because the 

socioeconomic effect will be mixed with any true effect of lead exposure. In addition, 

confounding by social factors may be a concern for some other lead-associated 

health measures with social gradients such as height (Silventoinen 2003). 

Data presented from most of the key studies included in this review strongly 

suggest that substantial confounding by socioeconomic factors occurs. Even 

with adjustment for crude measures (e.g., parental education and household 

income ) (Lanphear et al. 2000), the apparent lead effect on cognitive function is 

greatly reduced. Such a pattern in which adjustment for a crude proxy results 

in a substantial decrement in the magnitude of association would suggest that 

“residual confounding” may be present in the adjusted estimate of effect. If residual 

confounding is indeed present, then tighter control for confounding with more 

refined measures of the social environment may further attenuate or eliminate the 

apparent effect (Savitz et al. 1989). 

The following factors complicate this scenario: 

1. Socioeconomic status is a very elusive construct to fully capture; it is far more 

complex than is reflected in parental education or income. Socioeconomic 

status includes many aspects of economic means and associated lifestyle, 

23
so that adjustment for operational measures, such as education or income, 

will always be incomplete. Adjustment for an imperfect proxy measure of a 

confounder results in residual confounding (Greenland et al. 1985; Savitz et 

al. 1989). 

2. Long-term lead exposure is imperfectly reflected in a current blood lead 

measure or to some extent, even from a series of blood lead measures (see 

Blood Lead Tracking) (Bellinger et al. 1989). Whatever physiologic effect lead 

might produce, available evidence suggests that the impact is chronic and 

cumulative. Beyond what is reflected in a blood-lead measure, SES may be 

indicative of historical exposure; thus, the observed effect of socioeconomic 

status would partly reflect an effect of lead exposure above and beyond the 

blood-lead measure. 

The nature and magnitude of these associations is less clear when focusing on 

BLLs <10 μg/dL. Measures of social advantage, including income and parental 

education, are associated with BLLs <10 μg/dL (e.g., Lanphear et al. 2000). 

However, the relative importance of different aspects of socioeconomic status 

and the pathways by which they affect lead exposure are not entirely clear. The 

association between lower income and deterioration of paint in older housing 

contributes to variation in BLLs, even BLLs <10 μg/dL. The increase in geometric 

mean blood lead associated with living in an older home is greater for children from 

low-income families than for those from middle income families (Pirkle et al. 1998). 

Nonetheless, with the elimination of lead in gasoline and the continued decline 

in the proportion of homes with leaded paint (Jacobs et al. 2002), the relative 

importance of lead exposure sources possibly is changing. It is also possible that 

the association of social factors with lead exposure is different for populations with 

BLLs <10 μg/dL than for those above that level. 

Several strategies have been applied to address the role of socioeconomic factors 

and isolate a non-specific effect of socioeconomic factors on IQ from an effect of 

lead exposure. First, populations can be sought or even constructed in which blood 

lead is not closely associated with SES as demonstrated most clearly in the Boston 

cohort (Bellinger et al. 1987). In that population, all in a relatively low blood lead 

range for that time and the great majority of relatively advantaged SES, there was 

a weak positive gradient between socioeconomic status and lead. The Kosovo cohort 

(Wasserman et al. 1997) also departed from the usual trend in that the more SES 

advantaged of the two communities studied was the site of a lead smelter. As a 

result, adjustment for social and other covariates actually strengthened the inverse 

relation of blood lead to IQ in that population. 

Second, improved measures of socioeconomic factors have been applied to better 

control for non-specific effects. That is, by refining and decomposing the construct 

of socioeconomic status, it is possible to adjust more fully for the confounding 

dimensions such as nutrition, parental stimulation, attitudes towards achievement, 

24
etc., and not adjust for the aspects that primarily serve as a proxy for lead exposure, 

such as age of housing and neighborhood. One example among published research 

of refining and decomposing the construct of socioeconomic status has been the use 

of the HOME scales to adjust for stimulation provided by caregivers. Use of HOME 

scales has in some cases further attenuated but not eliminated apparent lead–IQ 

associations. 

A third approach to examine the possibility of confounding of the blood lead–IQ 

relation at low levels would be to conduct a formal statistical assessment of the 

extent to which the strength of the observed association across studies varies in 

relation to control for relevant confounders, using meta-regression, as was applied 

by Schwartz (1994). This approach could be refined to assess possible residual 

confounding. One challenge in performing such an analysis using published 

summary data is the difficulty in operationalizing measures of the tightness of SES 

adjustment while controlling for other aspects of study design that might influence 

blood lead–IQ slopes. An alternative approach is discussed later in this report (see 

Research Needs). 

Conclusions: On the basis of available evidence the observed associations 

between blood lead below 10 μg/dL and cognitive function likely do not entirely 

result from confounding. This conclusion is supported by the following evidence: 

• The studies showing the strongest relationship (Canfield et al. 2003; 

Bellinger et al. 2003) at low levels employed the HOME scale for adjustment, 

which is the best available measure for assessing the impact of the home 

environment on child development. 

• Two cohorts, Kosovo and Boston, in which strong associations were found 

between blood lead and IQ, were characterized by a direct, rather than 

inverse, correlation of blood lead with social advantage. 

• Associations of children’s blood lead close to 10 μg/dL and intelligence have 

been seen in diverse geographic and social settings. 

• Animal data have demonstrated effects of lead at BLLs near 10 μg/dL. 

On the other hand, the ability to detect confounding by omitted covariates by 

comparisons across studies is limited because, for most covariates of potential 

interest, the number of relevant studies in one group being compared is limited. 

In other words, for a given covariate, either few studies included it (e.g., postnatal 

ETS exposure) or few excluded it (e.g., SES). At this point, the case for residual 

confounding by social environment is speculative, but available studies relating 

blood lead to cognitive function in children cannot entirely exclude the possibility 

that observed associations are at least partly influenced by it. Such a possibility 

does increase uncertainty about the actual strength and shape of blood lead 

relationships at BLLs less than 10 μg/dL. 

25
Iron Status 

Nutritional factors, such as iron and zinc intake, that might be correlated with 

lead uptake and might influence children’s health, could confound associations 

between BLLs and health from observational studies. The potential for iron 

deficiency to confound the association between blood lead and neurodevelopmental 

status has been of most concern and is the focus of this discussion. The likelihood 

of such bias is dependent upon the extent to which iron status was controlled in 

a given study and the prevalence of iron deficiency in a study population. Iron 

deficiency may impair neurodevelopment in a manner similar to low-level lead 

exposure and the populations at increased risk for iron deficiency and lead toxicity 

may overlap (Lozoff et al. 1991; Wasserman et al. 1999). However, the association 

between iron deficiency and blood lead is not consistent across populations (CDC 

2002). Therefore, the potential for iron to confound an association of blood lead with 

neurodevelopmental status will vary across populations, depending on both the 

prevalence of iron deficiency and its association with blood lead level. 

For research purposes adequate assessment of iron status entails determination 

of hemoglobin or hematocrit and at least two other measures of iron status. 

Generally accepted definitions of iron deficiency and iron deficiency anemia depend 

on age- and sex-specific normal ranges. The iron status measures most commonly 

used are mean corpuscular volume (MCV), free erythrocyte protoporphyrin (FEP) 

or zinc protoporphyrin (ZPP), transferrin saturation, ferritin, and, more recently, 

transferrin receptor. The standard for defining iron deficiency is values indicating 

iron deficiency on at least two of these measures and/or response to iron therapy 

with an increase in hemoglobin to at least 10 g/L. The utility of ferritin in young 

infants is under debate, making it important that functional measures, such as 

MCV or ZPP be obtained. There are limitations of each measure (e.g., ferritin goes 

up with infection, MCV is down in hemoglobinopathies, etc.). 

Although iron deficiency with low hemoglobin has been associated with later 

impairment of cognitive function (Grantham-McGregor et al. 2001), it is not certain 

which measure(s) of iron status are most strongly related to neurodevelopmental 

outcomes. In studies of children with higher BLLs, controlling for hemoglobin 

is problematic because lead toxicity can reduce hemoglobin in the normal range 

or cause frank anemia. This is less of a concern in studies of children with BLLs 

<10 μg/dL, a range in which no meaningful impact on hemoglobin levels has been 

observed. 

Conclusions: Measurement of iron deficiency has been absent or suboptimal in 

most of the studies reviewed. Two studies in which iron status was controlled for 

using transferrin saturation (Canfield et al. 2003) and serum ferritin (Lanphear 

et al. 2000) found strong inverse relationships between blood lead and cognitive 

function, whereas a third study that controlled for the presence of iron-deficiency 

anemia found the opposite (Wolf et al. 1994). Furthermore, iron-deficiency anemia 

26
is the measure of iron status most clearly linked to impaired cognitive function; 

therefore, it seems unlikely that the prevalence of iron deficiency anemia could be 

high enough in the populations showing the strongest inverse relations of blood 

lead to cognitive function (Canfield et al. 2003; Bellinger et al. 2003; Lanphear et 

al. 2000) to entirely explain these associations. In the NHANES III data used by 

Lanphear et al. (2000), the prevalence of iron deficiency ranged from 1% to 9%, 

depending on the age and sex group (CDC 2002). Finally, in Kosovo, following 

treatment of iron-deficient children with iron supplements, no association of earlier 

hemoglobin levels with IQ at age 4 (Wassserman et al. 1994) or age 7 (Wasserman 

et al. 1997) was found. Thus, iron deficiency likely does not completely explain the 

inverse associations between BLLs <10 μg/dL and cognitive function. 

Tobacco 

Blood lead levels in children have been associated with exposure to 

environmental tobacco smoke (assessed by caregiver report or by urinary cotinine 

levels) in both general population surveys (Stromberg et al. 2003; Mathee et al. 

2002; Lanphear et al. 2000; Mannino et al. 2003) and in studies of children living 

near lead smelters (Willers et al. 1988; Baghurst et al. 1992; Baghurst et al. 1999). 

The explanation for this association is not entirely clear; possibilities include 

enhancement of lead uptake by environmental tobacco smoke (ETS), exposure to 

lead in ETS itself, and differences in cleaning practices or child supervision between 

households with and without smokers. 

Maternal smoking during pregnancy has been associated with behavioral 

problems and impaired cognitive development in children; fetal hypoxia is one 

possible contributing mechanism (Habek et al. 2000). Evidence for an effect of 

prenatal or postnatal ETS exposure on neurodevelopment is less clear (Eskenazi 

et al. 1999). As with studies of lead and neurodevelopment, social factors may 

confound, at least in part, the association between maternal smoking and 

neurodevelopment (Baghurst et al. 1992). A child’s prenatal exposure to maternal 

smoking or pre- or postnatal exposure to ETS could, if these are causally related 

to impaired neurodevelopment or other adverse health outcomes, confound the 

observed associations of lead and health. In addition, if a relationship between 

postnatal ETS and neurodevelopment is established, lead exposure could be a 

mediating factor. 

Conclusions: Of the studies reviewed, most did not assess prenatal or postnatal 

ETS as a possible confounding factor. Those that assessed tobacco at all controlled 

for maternal smoking during pregnancy. However, the two exceptions, Lanphear 

et al. (2000) in which serum cotinine measurements were used to control for ETS 

and a study based on the Port Pirie cohort (Tong et al. 1996; Baghurst et al. 1992) 

which reported postnatal parental smoking, provide no evidence that confounding 

by tobacco exposure accounts for the associations observed between blood lead and 

adverse health effects. Limitations in available studies leave some uncertainty as 

27
to what contribution, if any, ETS might make to observed associations between BLL 

and health. 

Causal Direction 

Inference of causation from observational epidemiologic studies is sometimes 

complicated by the possibility that the health outcome under study could be a 

cause of the exposure or causally related to a third factor which itself is a cause of 

the exposure under study. Two factors that influence blood lead levels—mouthing 

behavior and calcium balance—are relevant to assessing causal direction in studies 

of the health effects of lead at low levels. 

Mouthing behavior 

An important pathway of lead uptake by young children is ingestion of leadcontaminated dust (Charney et al. 1980; Bornschein et al. 1985), presumably 

through mouthing of hands, surfaces, and objects on which the dust is deposited. 

Although mouthing behavior is difficult to measure, children with more reported 

mouthing behavior have higher BLLs in relation to environmental lead exposure 

(Lanphear et al. 1998; Bellinger et al. 1986; Baghurst et al. 1999). Pica (purposeful 

ingestion of non-food items) can be a consequence of impaired neurodevelopment 

and can predispose one to lead ingestion (Cohen et al. 1976; McElvaine et al. 1992; 

Shannon et al. 1996), but the relation of variation in “normal” age-appropriate 

mouthing behavior to neurodevelopment is uncertain. However, in groups of 

children, average measured or caregiver reported mouthing has been shown to 

diminish with age (Juberg et al. 2001; Tulve et al. 2002). Nonetheless, it is unclear 

whether, at the individual level, more frequent mouthing behavior is a marker 

(independent of its effect on lead ingestion) for delayed neurodevelopment. If such 

behavior is a marker, then an association between blood lead level and impaired 

neurodevelopment would result, and failure to adjust for mouthing behavior 

would result in an overestimate of the blood-lead effect. On the other hand, if 

measured mouthing behavior is associated with cumulative lead exposure above 

and beyond that reflected in measured BLLs, then controlling for mouthing 

behavior could amount to over control, underestimating the true effect of lead on 

neurodevelopmental measures. 

Conclusions: At this point, no direct evidence supports reverse causation by 

mouthing behavior, and this hypothesis remains speculative. Arguing against this 

possibility, Tong et al. (1996) reported that an early measure of neurocognitive 

development, the Bailey MDI, was not predictive of later BLLs. 

Calcium balance 

Calcium balance changes in relation to growth during childhood and during 

the rapid expansion of bone mass during puberty and the pubertal growth spurt 

28
(Bronner et al. 1998; van Coeverden et al. 2002; Bailey et al. 2000); estradiol may 

influence bone mineral deposition in pubertal girls (Cadogan et al. 1998). It is 

possible that effect of skeletal growth and puberty on calcium balance could cause 

lower BLLs (Thane et al. 2002), just as the opposite changes in calcium balance 

during menopause appear to cause an increase in blood lead (Hernandez-Avila et 

al. 2000; Garrido Latorre et al. 2003). It should be noted that the average age at 

menarche among U.S. adolescents dropped by approximately 2.5 months between 

the periods 1963-1970 and 1988-94 and that this trend was accounted for in part 

by a rising prevalence of obesity (Anderson et al. 2003). Average BLLs were likely 

falling substantially during this same period. 

Conclusions: Because human studies linking blood lead at levels <10 μg/dL to 

delayed puberty and smaller stature are, with one exception, cross-sectional and 

evidence is limited on this topic, reverse causation via changes in calcium balance 

cannot be ruled out as accounting for at least some of the observed associations. 

While the parallel secular trends in decreasing age at menarche and decreasing 

BLLs could be explained in part to a causal effect of lead delaying age at menarche, 

it is also possible that other secular trends (e.g. increasing obesity rates) have 

caused the trend toward earlier menarche. 

Overall Conclusions 

Question 1: Does available evidence support an inverse association between 

children’s blood lead levels <10 μg/dL and children’s health? 

Because of the large number of studies that have assessed cognitive function as 

an outcome, the review and conclusions by the WG primarily focus on this health 

domain. The consensus of the WG is that the overall weight of available evidence 

supports an inverse association between BLLs <10 μg/dL and the cognitive function 

of children. The evidence for such an association is bolstered by the consistency 

across both cross-sectional and longitudinal studies in varied settings with blood 

lead distributions overlapping 10 μg/dL and by the lack of any trend towards a 

weaker association in studies with lower population mean BLLs. More recent 

studies and analyses best suited to examining this association (Canfield et al. 2003; 

Bellinger et al. 2003) have added to, rather than refuted, evidence for such an 

association noted in prior CDC guidance (1991). 

In reaching this conclusion, the WG is mindful of limitations in the available 

evidence base. Relatively few studies have directly examined the association 

between BLLs <10 μg/dL and health status among children and many of those that 

have are cross sectional studies in which data are unavailable on BLLs earlier in 

life and key covariates. The WG concluded that findings from numerous published 

studies relating BLL to cognitive function, while not limited to children with BLLs 

29
 

<10 μg/dL, collectively were not consistent with a threshold for the BLL-cognitive 

function association at 10 μg/dL. This indirect evidence, however, is less persuasive 

than cohort studies and analyses that directly assess the relationship between BLL 

and health <10 μg/dL. These directly relevant studies analyzed data for children 

whose measured BLLs did not exceed 10 μg/dL (to the investigator’s knowledge). 

Likely included in these analyses were some children who, because of random 

variation in BLL or age trends, did at some time have a BLL >10 μg/dL that was 

not measured. Such misclassification could produce an apparent inverse association 

between BLLs <10 μg/dL and health status even if a threshold existed at 10 μg/dL. 

Such misclassification, however, could not account for the observed BLL–IQ relation 

in the Canfield (2003) study, in which a steeper slope was observed at BLLs <5 μg/dL 

than at levels 5–10 μg/dL. 

For health endpoints other than cognitive function, including other neurologic 

functions, stature, sexual maturation, and dental caries, available data are more 

limited and less replication of findings exists across studies. Nonetheless, the 

available data from these studies are consistent with associations between higher 

BLLs and poorer health indicators for values <10 μg/dL . 

Question 2: Are the observed associations likely to be causal? 

The work group concluded that, while available evidence does not permit a 

definitive causal interpretation of the observed associations between higher BLLs 

and adverse health indicators for values <10μg/dL, the weight of available evidence 

favors, and does not refute, the interpretation that these associations are, at least in 

part, causal. The WG also concluded that the limitations of the available evidence, 

including likely residual confounding by social environment, leave uncertainty 

about the absolute strength and shape of the causal relation at the population level. 

Even greater uncertainty attends the use of associations observed in the relevant 

population studies for interpretation of BLLs measured in individual children at a 

single point in time. Thus, the WG does not believe that the individual children can 

be classified as “lead poisoned,” as the term is used in the clinical setting, on the 

basis of the associations observed in studies reviewed for this report. The basis of 

the overall WG conclusions is discussed below and is followed by a summary of the 

important limitations in the available evidence. 

The WG explored other possible explanations (aside from causation) for these 

associations and concluded that none are likely to fully explain the observed 

data. The context of evidence from animal, in vitro, and human studies of adult 

populations, also supports the consensus of the WG conclusion that the observed 

associations most likely represent, at least in part, causal adverse impacts of lead 

on children’s cognitive function at BLLs <10 μg/dL. 

The greatest source of uncertainty in interpreting the relationship between BLLs 

<10 μg/dL and cognitive function is the potential for residual confounding by social 

30
factors. The conditions for residual confounding appear to be present: BLLs are 

strongly influenced by SES, SES is clearly related to measured cognitive function, 

and social factors that could influence BLL and cognitive function are difficult to 

measure precisely. Other sources of potential bias are, individually, less concerning 

than social confounding, but collectively they add to the overall uncertainty about 

the absolute strength and shape of the relation of BLL to impaired cognitive 

function. These include, random error in blood lead measurement and in a single 

BLL as a measure of chronic exposure, possible influence of factors that have not 

been fully addressed in published studies, including blood lead tracking and age 

trend, which limits cross-sectional studies in particular, tobacco smoke exposure, 

iron deficiency, and mouthing behavior. Error in measuring lead exposure would 

bias observed associations towards the null, while failure to adjust for the other 

factors noted would most likely bias observed associations away from the null. 

The recently reported trend of asymptotically increasing slopes of lead-associated 

decrements in cognitive test scores at lower BLLs (Bellinger et al. 2003; Canfield 

et al. 2003; Lanphear et al. 2000) would be expected if residual confounding were 

operative as illustrated in Figure 7. The graph on the left depicts a comparison of 

two groups of children who live in a high exposure setting. They differ, on average, 

with respect to aspects of the home and social environment that are not captured 

in measured covariates. This results in one group ingesting and absorbing twice 

as much lead and having, after adjustment for measured covariates, a mean IQ 1 

point lower than the children raised in a more favorable environment. Assuming a 

roughly linear relation of lead intake to blood lead, the result is that one group has 

a mean blood lead twice as high, corresponding to a 10 μg/dL difference in blood 

lead and an estimated blood lead-IQ slope attributable to residual confounding 

of 0.1 IQ points per μg/dL. The figure on the right depicts the same hypothetical 

two populations living in a low exposure setting. The same imperfectly measured 

differences in social environment contribute to the equivalent covariate-adjusted 

difference in mean IQ, but in this case, although one group ingests twice as much 

contaminated dust as before, lower levels of lead contamination result in the two 

children having a blood lead difference of only 1 μg/dL in blood lead level. The 

result is an estimated blood lead-IQ slope attributable to residual confounding of 

1.0 IQ points per μg/dL. In addition, a convincing and directly relevant biologic 

mechanism for such a dose response relation has yet to be demonstrated. Though 

this hypothetical example cannot demonstrate that residual confounding underlies 

the steep blood lead-IQ slopes observed at low levels, it does support the need for 

caution in interpreting the absolute value of the estimated effect sizes. 

The available data for these other health endpoints, taken mostly from crosssectional studies, are more limited and firm conclusions concerning causation 

cannot be made at this time. 

31
 

 

 

Research Needs

Resolving residual confounding through observational studies 

It may be somewhat easier to identify study populations with BLLs <10 μg/dL 

in which socioeconomic factors are not associated with exposure as compared to 

populations with more widely varying blood lead levels within many low SES 

children, but few high SES children, may have blood lead levels above 20 or 30 μg/dL. 

Configuring a cohort similar to the one in Boston or assembling one from the pieces 

of others already studied could be helpful in isolating socioeconomic and lead effects 

from one another. Another formal statistical approach that could be applied to 

pooled data across multiple studies is the application of a hierarchical modeling 

approach as proposed by Schwartz et al. (2003, in press). 

Controlled intervention trials 

While experimental designs can establish causation with greater confidence 

than observational studies, intentionally exposing some children to higher BLLs 

in a randomized controlled design would be unethical. However, randomized 

trials in which interventions are tested for their ability to reduce BLLs <10 μg/dL 

or prevent their increase provide an opportunity to support or refute a causal 

relationship between BLLs <10 μg/dL and adverse health outcomes. Studies testing 

such interventions should measure covariates relevant to assessing health effects, 

allowing a test of the causal hypothesis should they be successful at sufficiently 

reducing BLLs. 

Animal and in vitro studies to explore mechanisms and dose-response 

relations 

While the overall evidence from animal or in vitro models supports the biologic 

plausibility of adverse effects of lead at BLLs <10 μg/dL, the WG is unaware of 

directly relevant animal or in vitro studies that demonstrate a steeper slope for 

adverse effects of lead exposure at lower BLLs than observed at higher levels. 

Demonstrating such a relationship in experimental studies and identifying possible 

mechanisms would increase confidence in a causal interpretation of the observed 

blood lead-response relationship in studies such as Canfield et al. (2003). 

32
Figure 1. Expected variation in regression slopes given hypothetical 

 

 

 

 

Hypothetical mean and range of observed 

data from epidemiologic studies 

IQ 

-Hypothesized threshold 

Hypothesized “true” 

relations 

A 

B 

C 

Blood lead level ­


“true” threshold blood lead - IQ relation (A).

Notes: Figures 2 and 3 

Selected estimates of change in outcome (Full Scale IQ or McCarthy General 

Cognitive Index (GCI) derived from regression coefficients and listed in Table 2 and 

the corresponding mean BLLs of the study population are displayed in Figures 2 

and 3. Figure 2 contains results from studies where the BLLs were measured at 

ages <2 years, and outcome measures were measured at ages >4 years. Figure 3 

contains the results when both the BLLs and outcome measures were measured 

at ages >4 years. Both the crude (open dot) and adjusted (solid dot) coefficients 

are displayed in the figures when both are available. (The Kosovo and European 

Multicenter Study papers did not provide the crude coefficient). Although multiple 

models for a single study population may have been fit to results from differing 

ages within the defined age categories, only the regression coefficients for the 

highest age at which blood lead was measured (per study population) are included 

in the figures. (The highest outcome measure age was used as a tiebreaker when 

necessary.) Also, when models for both a concurrent blood lead measure and a 

lifetime average blood lead measure existed for the highest age at which blood lead 

was measured (Port Pirie and Rochester), the concurrent results were included. 

For the study that provided multiple models for the same highest-age blood lead 

versus outcome measure (Lavrion, Greece), the results from the model that included 

the most covariates were included. Any studies not providing both a regression 

coefficient and blood lead mean were excluded. Three-letter abbreviations for each 

study population, defined in the legends below, were used on the plots. 

33
Legend for Figure 2

Abbreviation Study population Reference 

number 

Blood lead and 

outcome ages 

Bos Boston, Massachusetts 7 24 months / 10 years 

Cin Cincinnati, Ohio 13 15-24 months / 6.5 years 

Kos Kosovo, Serbia 37 24 months / 4 years 

Por Port Pirie, Australia 23 24 months / 4 years 

Roc Rochester, New York 11 6-24 months / 5 years 

Legend for Figure 3

Abbreviation Study 

population 

Reference 

number 

Blood lead and 

outcome ages 

Bos Boston, Massachusetts 7 10 years / 10 years 

Cin Cincinnati, Ohio 13 51-60 months / 6.5 years 

Eur European Multicenter 

Study 

39 6-11 years / 6-11 years 

Kar Karachi, Pakistan 28 6-8 years / 6-8 years 

Kos Kosovo, Serbia 37 48 months / 4 years 

Lav Lavrion, Greece 20 primary school / primary 

school 

Por Port Pirie, Australia 35 11-13 years / 11-13 years 

Roc Rochester, New York 11 5 years / 5 years 

34
Figure 2. Cognitive Function Regression Coefficients for Blood Lead Age 

<2 years and Outcome Age >4 years. 

Estimated Outcome Measure for PbB 5 to 15 μg/dL

Mean Blood Lead (μg/dL)

35
Figure 3. Cognitive Function Regression Coefficients for Blood Lead Age 

>4 years and Outcome Age >4 years. 

Estimated Outcome Measure for PbB 5 to 15 μg/dL

Mean Blood Lead (μg/dL)

36
Figure 4. Age trend in blood lead levels (BLLs). μg/dL

Source: Tong et al. 1996. 

37
 

 


 


 


 

Figure 5. Hypothetical observed association between blood lead and IQ.

IQ

5 10 15

Blood lead level (μg/dL) at age 6
 

Figure 6. Hypothetical “true” association between blood lead and IQ. 

IQ

 10 15 20
 

Blood lead level (μg/dL) at age 2
 

38
	 
 
 


 

	 

	 

0

High exposure setting Low exposure setting

0

IQ difference

IQ difference

-1
 -1
 10 20 1 2

Blood lead level (μg/dL) Blood lead level (μg/dL)

Figure 7. Hypothetical slopes of the relationship between blood lead 

and IQ associated with residual confounding (see Overall 

Conclusions). 

39
Table 1. Lowest blood lead level (BLL) considered elevated by CDC and the US 

Public Health Service

Year and Reference BLL 

(μg/dL) 

1971 (Surgeon General) 40 

1975 (CDC) 30 

1978 (CDC) 30 

1985 (CDC) 25 

1991 (CDC) 10 

40

 

Table 2. Summary of studies estimating association of postnatal PbB with cognitive function


Covariates in Model Estimated Delta

Study for PbB 5 -> 15**

Population* PbB Outcome Mean PbB Fetal Family Parental Iron 

(ref., type, n) Age Age # (ug/dL) Crude Adj SES Smoking Growth Environment HOME Race Intelligence Status Other 

(<= 2 years) (>= 4 years) 

Kosovo 24 months # 4 years 21.8 (GM) Not stated -5 (log10)^ Maternal Birth Weight Family Structure, Unspecified Child Maternal Child's Sex 

(37, L ,332) Education Maternal Age 

Port Pirie 24 months # 4 years 21.3 (GM) -12.3 -5.3 (log10)^ Maternal Birth Weight, Marital Status, Unspecified Maternal Maternal 

(23, L ,537) (log10)^ Education, Gestation Maternal Age Medication/Drug

Paternal Use, PostnatalEducation, Factors, BirthPaternal Order, Birth Type,Occupation Birth Problems,

Child's Sex,Residence inRegions, Child'sMedical History,Mother's Work 

Site 

Port Pirie 15 months # 4 years 20.9 (GM) -6.8 (log10)^ -1.7 (log10) Maternal Birth Weight, Marital Status, Unspecified Maternal Maternal 

(23, L ,537) Education, Gestation Maternal Age Medication/Drug

Paternal Use, PostnatalEducation, Factors, BirthPaternal Order, Birth Type,Occupation Birth Problems,

Child's Sex,Residence inRegions, Child'sMedical History,Mother's Work 

Site 

Port Pirie 15 months 11-13 years 20.9 (GM) -6.8 (ln)^ -2 (ln) Daniel's Scale Parental Birth Weight Family Structure, Unspecified Maternal Breast Feeding,

(35, L ,367) of Prestige of Smoking Family Functioning, Feeding Method,

Occupations in Habits Marital Status, Birth Order, Australia, Maternal Age, Life Child's Sex, Maternal Events Child's Age, Education School Grade,

School Absence 

{£
 

* L=Longitudinal cohort, X=Cross-sectional.
** (ln)/(log10) = Original coefficient reported in log scale.


# = McCarthy GCI, all unmarked are full-scale IQ measures.
^ statistically significant (p < 0.05)
 

{Ó
 

Covariates in Model

Study for PbB 5 -> 15**

Population* PbB Outcome Mean PbB Fetal Family Parental Iron 

(ref., type, n) Age Age # (ug/dL) Crude Adj SES Smoking Growth Environment HOME Race Intelligence Status Other 

Estimated Delta 

Port Pirie Lifetime 7 years 16.6-20.5 Not stated -5.1 (ln)^ Daniel's Scale Parental Birth Weight Family Structure, Unspecified Maternal Breast Feeding,

(4, L ,494) average - 2 (means of of Prestige of Smoking Maternal Age Feeding Method,

years	 	 2nd & 3rd Occupations in Birth Order, 

quartiles) Australia, Child's Sex (GM) Maternal

Education,PaternalEducation 

Kosovo 18 months # 4 years 20.0 (GM) Not stated -2.3 (log10) Maternal Birth Weight Family Structure, Unspecified Child Maternal Child's Sex 

(37, L ,332) Education Maternal Age 

Port Pirie Lifetime 7 years 14.3-18.0 Not stated -4.4 (ln)^ Daniel's Scale Parental Birth Weight Family Structure, Unspecified Maternal Breast Feeding,

(4, L ,494) average - 15 (means of of Prestige of Smoking Maternal Age Feeding Method,

months	 	 2nd & 3rd Occupations in Birth Order, 

quartiles) Australia, Child's Sex (GM) Maternal

Education,PaternalEducation 

Kosovo 12 months # 4 years 17.2 (GM) Not stated -3.6 (log10)^ Maternal Birth Weight Family Structure, Unspecified Child Maternal Child's Sex 

(37, L ,332) Education Maternal Age 

Cincinnati Mean 15-24 6.5 years 17.1 -1.3 -0.2	 	 Cigarette Birth Weight, Unspecified Maternal Child's Sex 

(13, L ,253) months	 	 Consumption Birth Length 

duringPregnancy 

Cleveland 2 years 4 years 10 16.70 r=-.38^ Not stated Maternal	 	 Cigarettes per Birth Weight, Authoritarian Family Total Child Maternal Child Stress, 

(16, L ,149) months Education Day Gestation Ideology		 (mean of Maternal 

1, 2, 3, and Medication/Drug

4 years 10 Use, Maternalmonths) Alcohol

Consumption,Birth Order,Child's Sex,History AlcoholAbuse 

* L=Longitudinal cohort, X=Cross-sectional.** (ln)/(log10) = Original coefficient reported in log scale.

# = McCarthy GCI, all unmarked are full-scale IQ measures.^ statistically significant (p < 0.05) 

 

Covariates in Model

Study for PbB 5 -> 15**

Population* PbB Outcome Mean PbB Fetal Family Parental Iron 

(ref., type, n) Age Age # (ug/dL) Crude Adj SES Smoking Growth Environment HOME Race Intelligence Status Other 

Estimated Delta 

Sydney Mean 18,24 # 48 months 15.8 (GM) Not stated Not stated	 	 Daniel's Scale Gestation Total at 48 Maternal 

(12, L ,318) months	 	 of Prestige of months 

Occupations inAustralia,MaternalEducation,PaternalEducation 

Sydney Mean 6,12 # 48 months 15.2 (GM) Not stated Not stated	 	 Daniel's Scale Gestation Total at 48 Maternal (12, L ,318) months	 	 of Prestige of months 

Occupations inAustralia,MaternalEducation,PaternalEducation 

Kosovo 6 months # 4 years 15.0 (GM) Not stated -2 (log10) Maternal Birth Weight Family Structure, Unspecified Child Maternal Child's Sex 

(37, L ,332) Education Maternal Age Port Pirie 6 months # 4 years 14.5 (GM) -7.2 (log10)^ -4.1 (log10)	 	Maternal Birth Weight, Marital Status, unspecified Maternal Maternal 

(23, L ,537)	 	 Education, Gestation Maternal Age Medication/Drug

Paternal Use, PostnatalEducation, Factors, BirthPaternal Order, Birth Type,

Occupation Birth Problems,

Child's Sex,Residence inRegions, Child'sMedical History,Mother's Work Site 

Costa Rica 12-23 months 5 years 11.0 r=.06 Not stated (41, L ,184)Cincinnati Mean 3-12 6.5 years 10.6 -2.2 0.1		 Cigarette Birth Weight, Unspecified Maternal Child's Sex 

(13, L ,253) months	 	 Consumption Birth Length 

duringPregnancy 

Mexico City Mean 6-18 # 36-60 months 10.1 (GM) Not stated Mean Family Birth Weight Maternal Postnatal Factors,

(31, L ,112) months square = Socioeconomic Birth Order, 

87.81 (neg) Level, Maternal Child's Sex 

(ln) Education 

* L=Longitudinal cohort, X=Cross-sectional.
 

** (ln)/(log10) = Original coefficient reported in log scale.


# = McCarthy GCI, all unmarked are full-scale IQ measures.
^ statistically significant (p < 0.05) 


{Î
 
{{
 

Covariates in Model

Study for PbB 5 -> 15**

Population* PbB Outcome Mean PbB Fetal Family Parental Iron 

(ref., type, n) Age Age # (ug/dL) Crude Adj SES Smoking Growth Environment HOME Race Intelligence Status Other 

Estimated Delta 

Cleveland 6 months 4 years 10 9.99 r=-.06 Not stated Maternal Cigarettes per Birth Weight, Authoritarian Family

(16, L ,122) months Education Day Gestation Ideology Boston 18 months # 57 months 8.0 -3.3 (ln)^ -1.8 (ln) Hollingshead Birth Weight Family Structure,

(6, L ,170) Index of Social Marital Status,

Class Residence

Changes, Day Care 

Boston 12 months # 57 months 7.8 -2.4 (ln) -1.6 (ln) Hollingshead Birth Weight Family Structure,

(6, L ,170) Index of Social Marital Status,

Class Residence

Changes, Day Care 

Boston 18 months 10 years 7.8 -2.8 -1.2	 	 Hollingshead Family Stress,

(7, L ,116)	 	 Four-Factor Marital Status,

Index of Social Residence Class Changes, Maternal 

Age 

Boston 12 months 10 years 7.7 -2 0		 Hollingshead Family Balance,

(7, L ,116)	 	 Four-Factor Family Stress,

Index of Social Marital Status

Class 

Boston 24 months # 57 months 7.0 -3.4 (ln)^ -3.2 (ln)^ Hollingshead Birth Weight Family Structure,

(6, L ,170) Index of Social Marital Status,

Class Residence

Changes, Day Care 

* L=Longitudinal cohort, X=Cross-sectional.
** (ln)/(log10) = Original coefficient reported in log scale.


# = McCarthy GCI, all unmarked are full-scale IQ measures.
^ statistically significant (p < 0.05)
 


Total Child Maternal	 	 Child Stress, (mean of 	 Maternal 1, 2, 3, and 	 	 Medication/Drug4 years 10	 	 Use, Maternalmonths)	 	 Alcohol

Consumption,Birth Order,Child's Sex,History AlcoholAbuse 

Total Child Maternal	 	 Birth Order,

Child's Sex,Medication Usedby Child,PreschoolAttendance 

Total Child Maternal	 	 Birth Order,

Child's Sex,Medication Usedby Child,PreschoolAttendance 

Scales V & Child Maternal Child Stress, Birth


VI at 120 Order, Child's Sex


months,
Total at 57


months


Scales V & Child Maternal Child Stress,
 
VI at 120 Parents' Sense


months, Competence,
Total at 57 Birth Order,
 


months Child's Sex
 


Total Child Maternal	 	 Birth Order,

Child's Sex,Medication Usedby Child,PreschoolAttendance 

 

Covariates in Model

Study for PbB 5 -> 15**

Population* PbB Outcome Mean PbB Fetal Family Parental Iron 

(ref., type, n) Age Age # (ug/dL) Crude Adj SES Smoking Growth Environment HOME Race Intelligence Status Other 

Estimated Delta 

Rochester Average in 5 years 7.0 -9.7^ -5.3^ Yearly Tobacco Use Birth Weight Total Mother Maternal Serum Child's Sex 

(11, L ,172) infancy - 6-24 Household during Transferrin 

[all] months Income, Pregnancy Saturation 

Maternal (user/nonuser)Education 

Boston 6 months # 57 months 6.8 0.3 (ln) 0.3 (ln) Hollingshead Birth Weight Family Structure, Total Child Maternal Birth Order, 

(6, L ,170) Index of Social Marital Status, Child's Sex, 

Class Residence Medication Used

Changes, Day Care	 	 by Child,

PreschoolAttendance 

Boston 6 months 10 years 6.7 -2 -1.3	 	 Hollingshead Marital Status Scales V & Child Maternal Child Stress, Birth

(7, L ,116)	 	 Four-Factor VI at 120 Order, Child's Sex

Index of Social months, Class Total at 57

months 

Boston 24 months 10 years 6.5 -7.1^ -5.8^	 	 Hollingshead Marital Status, Scales V & Child Maternal Child Stress, Birth

(7, L ,116)	 	 Four-Factor Residence VI at 120 Order, Child's Sex

Index of Social Changes, Maternal months, 

Class Age Total at 57

months 

Cincinnati 10 Days 6.5 years 5 -1 -0.3	 	 Cigarette Birth Weight, Unspecified Maternal Child's Sex 

(13, L ,253)	 	 Consumption Birth Length 

duringPregnancy 

Boston 24 months 10 years < 8 Not stated -5.8^	 	 Hollingshead Marital Status, Scales V & Child Maternal Child Stress, Birth

(34, L ,148)	 	 Four-Factor Residence VI at 120 Order, Child's Sex

Index of Social Changes, Maternal months, Class Age Total at 57

months 

Rochester Average in 5 years Not stated -15.8^ -9.2 Yearly Tobacco Use Birth Weight Total Mother Maternal Serum Child's Sex 

(11, L ,105) infancy - 6-24 Household during Transferrin 

[<10 group] months Income, Pregnancy Saturation 

Maternal (user/nonuser)Education 

(>2 - <4 years) (>= 4 years) 

Kosovo 36 months # 4 years 24.1 (GM) Not stated -4.5 (log10)^ Maternal Birth Weight Family Structure, Unspecified Child Maternal Child's Sex 

(37, L ,332) Education Maternal Age 

{x
 

* L=Longitudinal cohort, X=Cross-sectional.
** (ln)/(log10) = Original coefficient reported in log scale.


# = McCarthy GCI, all unmarked are full-scale IQ measures.
^ statistically significant (p < 0.05)
 

{È
 

Covariates in Model

Study for PbB 5 -> 15**

Population* PbB Outcome Mean PbB Fetal Family Parental Iron 

(ref., type, n) Age Age # (ug/dL) Crude Adj SES Smoking Growth Environment HOME Race Intelligence Status Other 

Estimated Delta 

Kosovo 42 months # 4 years 23.2 (GM) Not stated -5 (log10)^ Maternal Birth Weight Family Structure, Unspecified Child Maternal Child's Sex 

(37, L ,332) Education Maternal Age 

Kosovo 30 months # 4 years 22.1 (GM) Not stated -4.6 (log10)^ Maternal Birth Weight Family Structure, Unspecified Child Maternal Child's Sex 

(37, L ,332) Education Maternal Age 

Port Pirie Lifetime 7 years 17.4-21.7 Not stated -5.3 (ln)^ Daniel's Scale Parental Birth Weight Family Structure, Unspecified Maternal Breast Feeding,

(4, L ,494) average - 3 (means of of Prestige of Smoking Maternal Age Feeding Method,

years 2nd & 3rd Occupations in Birth Order, 

quartiles) Australia, Child's Sex (GM) Maternal

Education,PaternalEducation 

Port Pirie 36 months # 4 years 19.5 (GM) -12 (log10)^ -6.3 (log10)^ Maternal Birth Weight, Marital Status, Unspecified Maternal Maternal 

(23, L ,537) Education, Gestation Maternal Age Medication/Drug

Paternal Use, PostnatalEducation, Factors, BirthPaternal Order, Birth Type,

Occupation Birth Problems,

Child's Sex,Residence inRegions, Child'sMedical History,Mother's Work Site 

Port Pirie 3 years 11-13 years 19.3 (GM) -10.8 (ln)^ -4.2 (ln) Daniel's Scale Parental Birth Weight Family Structure, Unspecified Maternal Breast Feeding,

(35, L ,372) of Prestige of Smoking Family Functioning, Feeding Method,

Occupations in Habits Marital Status, Birth Order, 

Australia, Maternal Age, Life Child's Sex, Maternal Events Child's Age, Education School Grade,

School Absence 

Cleveland 3 years 4 years 10 16.70 r=-.31^ Not stated Maternal Cigarettes per Birth Weight, Authoritarian Family Total Child Maternal Child Stress, (16, L ,155) months Education Day Gestation Ideology (mean of Maternal 

1, 2, 3, and Medication/Drug

4 years 10 Use, Maternalmonths) Alcohol

Consumption,Birth Order,Child's Sex,History AlcoholAbuse 

* L=Longitudinal cohort, X=Cross-sectional.
** (ln)/(log10) = Original coefficient reported in log scale.


# = McCarthy GCI, all unmarked are full-scale IQ measures.
^ statistically significant (p < 0.05)
 


 

Covariates in Model

Study for PbB 5 -> 15**

Population* PbB Outcome Mean PbB Fetal Family Parental Iron 

(ref., type, n) Age Age # (ug/dL) Crude Adj SES Smoking Growth Environment HOME Race Intelligence Status Other 

Estimated Delta 

Cincinnati Mean 27-36 6.5 years 16.3 -2.6^ -1.3	 	 Cigarette Birth Weight, Unspecified Maternal Child's Sex 

(13, L ,253) months	 	 Consumption Birth Length 

duringPregnancy 

Sydney Mean 30,36 # 48 months 12.4 (GM) Not stated Not stated	 	 Daniel's Scale Gestation Total at 48 Maternal (12, L ,318) months	 	 of Prestige of months 

Occupations inAustralia,MaternalEducation,PaternalEducation 

Cleveland Mean 0.5-3 4 years 10 9.99 at 6 r=-.25 Not stated Maternal Cigarettes per Birth Weight, Authoritarian Family Total Child Maternal Child Stress, 

(16, L ,212) years months months & Education Day Gestation Ideology (mean of Maternal 

16.70 at 1, 2, 3, and Medication/Drug

both 2 4 years 10 Use, Maternal

years & 3 months) Alcohol 

years Consumption,

Birth Order,Child's Sex,History AlcoholAbuse 

Mexico City Mean 24-36 # 36-60 months 9.7 (GM) Not stated Mean Family Birth Weight Maternal Postnatal Factors,

(31, L ,112) months square = Socioeconomic Birth Order, 

101.62 Level, Maternal Child's Sex 

(neg) (ln) Education 

Port Pirie Lifetime 11-13 years Not stated -10.4 (ln)^ -4.7 (ln) Daniel's Scale Parental Birth Weight Family Structure, Unspecified Maternal Breast Feeding,

(35, L ,326) average - 3 of Prestige of Smoking Family Functioning, Feeding Method,

years	 	 Occupations in Habits Marital Status, Birth Order, 

Australia, Maternal Age, Life Child's Sex, Maternal Events Child's Age, 

Education School Grade,

School Absence 

(>= 4 years) (>= 4 years) 

Kosovo 48 months # 4 years 25.1 (GM) Not stated -4.5 (log10)^ Maternal Birth Weight Family Structure, Unspecified Child Maternal Child's Sex 

(37, L ,332) Education Maternal Age 

{Ç
 

* L=Longitudinal cohort, X=Cross-sectional.
** (ln)/(log10) = Original coefficient reported in log scale.


# = McCarthy GCI, all unmarked are full-scale IQ measures.
^ statistically significant (p < 0.05) 

{n
 

Covariates in Model

Study for PbB 5 -> 15**

Population* PbB Outcome Mean PbB Fetal Family Parental Iron 

(ref., type, n) Age Age # (ug/dL) Crude Adj SES Smoking Growth Environment HOME Race Intelligence Status Other 

Estimated Delta 

Lavrion, Greece Primary school Primary school 23.7 -3.76^ -2.66^ Maternal Family Structure Both Birth Order, 

(20, X ,509) children - not children - not Education, History Alcohol

[cov. model b] specified years specified years Paternal Abuse, Father's

Education, Age PaternalOccupation 

Lavrion, Greece Primary school Primary school 23.7 -3.76^ -2.7^ Maternal Birth Weight Family Structure, Both Birth Order, (20, X ,509) children - not children - not Education, Marital Status, Life Child's Age, 

[cov. model c] specified years specified years Paternal Events Child's Medical

Education, History, History

Paternal Alcohol Abuse,Occupation Father's Age,

Bilingualism,Length of Child'sHospital Stayafter Birth 

Lavrion, Greece Primary school Primary school 23.7 -3.76^ -2.6^ Maternal Birth Weight Family Structure, Both Birth Order, (20, X ,509) children - not children - not Education, Marital Status, Life Child's Sex, 

[cov. model d] specified years specified years Paternal Events Child's Age, 

Education, Residence inPaternal Regions, Child'sOccupation Medical History,

History AlcoholAbuse, MouthingBehavior, Father'sAge, Bilingualism,Length of Child'sHospital Stayafter Birth 

Lavrion, Greece Primary school Primary school 23.7 -3.76^ -2.4^ Maternal Birth Weight Family Structure, Both Birth Order, (20, X ,509) children - not children - not Education, Marital Status, Life Child's Age, 

[cov. model e] specified years specified years Paternal Events School Grade,

Education, Child's MedicalPaternal History, HistoryOccupation Alcohol Abuse,

Father's Age,Bilingualism,Length of Child'sHospital Stayafter Birth 

* L=Longitudinal cohort, X=Cross-sectional.
** (ln)/(log10) = Original coefficient reported in log scale.


# = McCarthy GCI, all unmarked are full-scale IQ measures.
^ statistically significant (p < 0.05)
 


 

Covariates in Model Estimated Delta

Study for PbB 5 -> 15**

Population* PbB Outcome Mean PbB Fetal Family Parental Iron 

(ref., type, n) Age Age # (ug/dL) Crude Adj SES Smoking Growth Environment HOME Race Intelligence Status Other 

Port Pirie Lifetime 7 years 17.6-21.5 Not stated -5.1 (ln)	 	 Daniel's Scale(4, L ,494) average - 4 (means of of Prestige of

years 2nd & 3rd Occupations in

quartiles) Australia, (GM) Maternal

Education,PaternalEducation 

Port Pirie Lifetime 7 years 15.7-19.7 Not stated -4.1 (ln)	 	 Daniel's Scale(4, L ,494) average - 7 (means of of Prestige of

years 2nd & 3rd Occupations in

quartiles) Australia, (GM) Maternal

Education,PaternalEducation 

Mexico City II 7-9 years 7-9 years 19.4 r=-.33 (ln) r=-.32 (ln)	 	 Income, 

(26, X ,139)	 	 Maternal

Education,PaternalEducation 

European 6-11 years 6-11 years 17.1 (GM) Not stated -5.3	 	 Maternal Multicenter Study	 	 Education, (39, M ,1639)	 	 Paternal

Occupation 

Port Pirie 48 months # 4 years 16.4 (GM) -9.6 (log10)^ -2.6 (log10)	 	Maternal 

(23, L ,537)	 	 Education,

PaternalEducation,PaternalOccupation 

Karachi 6-8 years 6-8 years 16.08 -4.3^ -6.3^ (28, X ,138)* L=Longitudinal cohort, X=Cross-sectional.
** (ln)/(log10) = Original coefficient reported in log scale.


# = McCarthy GCI, all unmarked are full-scale IQ measures.
^ statistically significant (p < 0.05)
 


Parental Birth Weight Family Structure, Unspecified Maternal	 	 Breast Feeding,

Smoking Maternal Age	 	 Feeding Method,

Birth Order,Child's Sex 

Parental Birth Weight Family Structure, Unspecified Maternal	 	 Breast Feeding,

Smoking Maternal Age	 	 Feeding Method,

Birth Order,Child's SexChild's Sex, Type 

of Housing,Nutritional Status(weight for height& height for age)

Child's Sex,Child's Age 

Birth Weight, Marital Status, Unspecified Maternal	 	 Maternal Gestation Maternal Age	 	 Medication/Drug

Use, PostnatalFactors, BirthOrder, Birth Type,Birth Problems,Child's Sex,Residence inRegions, Child'sMedical History,Mother's Work Site 

Haemoglobin		 Child's Height for 

Age 

{
 
xä
 

Covariates in Model

Study for PbB 5 -> 15**

Population* PbB Outcome Mean PbB Fetal Family Parental Iron 

(ref., type, n) Age Age # (ug/dL) Crude Adj SES Smoking Growth Environment HOME Race Intelligence Status Other 

Estimated Delta 

Port Pirie 5 years 11-13 years 14.3 (GM) -9.8 (ln)^ -4.4 (ln)^ Daniel's Scale	 	 Parental Birth Weight Family Structure, Unspecified Maternal Breast Feeding,

(35, L ,368) of Prestige of Smoking Family Functioning, Feeding Method,

Occupations in Habits Marital Status, Birth Order, 

Australia, Maternal Age, Life Child's Sex, 

Maternal Events Child's Age, 

Education School Grade,

School Absence 

Port Pirie Lifetime 11-13 years 14.1 (GM) -12.7 (ln)^ -4.7 (ln)^ Daniel's Scale	 	 Parental Birth Weight Family Structure, Unspecified Maternal Breast Feeding,

(35, L ,326) average - 11- of Prestige of Smoking Family Functioning, Feeding Method,

13 years Occupations in Habits Marital Status, Birth Order, 

Australia, Maternal Age, Life Child's Sex, 

Maternal Events Child's Age, 

Education School Grade,

School Absence 

Cincinnati Mean 39-48 6.5 years 14.0 -3.1^ -1.5	 	 Cigarette Birth Weight, Unspecified Maternal Child's Sex 

(13, L ,253) months	 	 Consumption Birth Length 

duringPregnancy 

Cincinnati Mean 51-60 6.5 years 11.8 -4.2^ -2.3^	 	 Cigarette Birth Weight, Unspecified Maternal Child's Sex 

(13, L ,253) months	 	 Consumption Birth Length 

duringPregnancy 

Port Pirie 7 years 11-13 years 11.6 (GM) -9.8 (ln)^ -3.7 (ln)^ Daniel's Scale	 	 Parental Birth Weight Family Structure, Unspecified Maternal Breast Feeding,

(35, L ,360) of Prestige of Smoking Family Functioning, Feeding Method,

Occupations in Habits Marital Status, Birth Order, 

Australia, Maternal Age, Life Child's Sex, 

Maternal Events Child's Age, Education School Grade,

School Absence 

Dunedin, New 11 years 11 years 11.1 r=-0.05 (ln) Not stated Zealand(33, L ,579)Sassuolo, Italy 7-8 years 7-8 years 10.99 (GM) r = -0.064 Not stated 

(8, X ,211) (log10) 

* L=Longitudinal cohort, X=Cross-sectional.
** (ln)/(log10) = Original coefficient reported in log scale.


# = McCarthy GCI, all unmarked are full-scale IQ measures.
^ statistically significant (p < 0.05)
 


 

Covariates in Model

Study for PbB 5 -> 15**

Population* PbB Outcome Mean PbB Fetal Family Parental Iron 

(ref., type, n) Age Age # (ug/dL) Crude Adj SES Smoking Growth Environment HOME Race Intelligence Status Other 

Estimated Delta 

Sydney Mean 42,48 # 48 months 10.4 (GM) Not stated Not stated	 	 Daniel's Scale Gestation Total at 48 Maternal 

(12, L ,318) months	 	 of Prestige of months 

Occupations inAustralia,MaternalEducation,PaternalEducation 

San Luis Potosi, 6-9 years 6-9 years 9.73 (GM) r=.06 (ln) r=.02 (ln) Bronffman Child's Sex,
 


Mexico Index of Child's Age
 


(10, X ,39) Socioeconomic
[reference group] Status,


MaternalEducation,PaternalEducation 

San Luis Potosi, 6-9 years 6-9 years 8.98 (GM) r=-.14 (ln) r=-.12 (ln) Bronffman Child's Sex,
 


Mexico Index of Child's Age
 


(10, X ,41) Socioeconomic
[exposed group] Status,


MaternalEducation,PaternalEducation 

Mexico City Mean 42-54 # 42-54 months 8.4 (GM) Not stated Mean Family Birth Weight Maternal Postnatal Factors,

(31, L ,112) months square = Socioeconomic Birth Order, 

6.23 (neg) Level, Maternal Child's Sex (ln) Education 

Port Pirie 11-13 years 11-13 years 7.9 (GM) -7.1 (ln)^ -3.4 (ln)^	 	 Daniel's Scale Parental Birth Weight Family Structure, Unspecified Maternal Breast Feeding,

(35, L ,326)	 	 of Prestige of Smoking Family Functioning, Feeding Method,

Occupations in Habits Marital Status, Birth Order, Australia, Maternal Age, Life Child's Sex, 

Maternal Events Child's Age, 

Education School Grade,

School Absence 

Rochester Lifetime 5 years 7.4 -10^ -5.7^ Yearly Tobacco Use Birth Weight Total Mother Maternal Serum Child's Sex (11, L ,172) average - 5 Household during Transferrin 

[all] years Income, Pregnancy Saturation 

Maternal (user/nonuser)Education 

* L=Longitudinal cohort, X=Cross-sectional.
** (ln)/(log10) = Original coefficient reported in log scale.


# = McCarthy GCI, all unmarked are full-scale IQ measures.
^ statistically significant (p < 0.05)
 


x£
 
xÓ
 

Covariates in Model

Study for PbB 5 -> 15**

Population* PbB Outcome Mean PbB Fetal Family Parental Iron 

(ref., type, n) Age Age # (ug/dL) Crude Adj SES Smoking Growth Environment HOME Race Intelligence Status Other 

Estimated Delta 

Boston 57 months # 57 months 6.4 -4.7 (ln)^ -2.5 (ln) Hollingshead Birth Weight Family Structure, Total Child Maternal Birth Order, 

(6, L ,170) Index of Social Marital Status, Child's Sex, 

Class Residence Medication Used

Changes, Day Care	 	 by Child,

PreschoolAttendance 

Boston 57 months 10 years 6.3 -9^ -2.6	 	 Hollingshead Birth Weight Family Stress, Scales V & Child Maternal Child Stress, Birth

(7, L ,116)	 	 Four-Factor Marital Status, VI at 120 Order, Child's Sex

Index of Social Maternal Age months, Class Total at 57

months 

Rochester Concurrent - 5 5 years 5.9 -10.2^ -6.1^ Yearly Tobacco Use Birth Weight Total Mother Maternal Serum Child's Sex 

(11, L ,171) years Household during Transferrin 

[all] Income, Pregnancy Saturation 

Maternal (user/nonuser)Education 

Boston 10 years 10 years 2.9 -15.3^ -4.6	 	 Hollingshead Birth Weight Family Stress, Scales V & Child Maternal Child Stress, Birth

(7, L ,116)	 	 Four-Factor Marital Status, Day VI at 120 Order, Child's Sex

Index of Social Care, Maternal Age months, Class Total at 57

months 

Kosovo Mean AUC7 7 years	 	 PbB at age -1.4 (log10) -4.1 (log10)^ Maternal Birth Weight Family Structure, Unspecified Child Maternal Child's Sex 

(38, L ,258) years		 7 years = Education Maternal Age

21.2;cumulative

PbB

through age7 years = 

1.21 

Rochester Concurrent - 5 5 years Not stated -25.6^ -17.9^ Yearly Tobacco Use Birth Weight Total Mother Maternal Serum Child's Sex 

(11, L ,101) years Household during Transferrin 

[<10 group] Income, Pregnancy Saturation 

Maternal (user/nonuser)Education 

Rochester Lifetime 5 years Not stated -25.4^ -15.2^ Yearly Tobacco Use Birth Weight Total Mother Maternal Serum Child's Sex 

(11, L ,101) average - 5 Household during Transferrin 

[<10 group] years Income, Pregnancy Saturation 

Maternal (user/nonuser)Education 

* L=Longitudinal cohort, X=Cross-sectional.
** (ln)/(log10) = Original coefficient reported in log scale.


# = McCarthy GCI, all unmarked are full-scale IQ measures.
^ statistically significant (p < 0.05)
 


 

Covariates in Model

Study for PbB 5 -> 15**

Population* PbB Outcome Mean PbB Fetal Family Parental Iron 

(ref., type, n) Age Age # (ug/dL) Crude Adj SES Smoking Growth Environment HOME Race Intelligence Status Other 

Estimated Delta 

Sydney Lifetime # 48 months Not stated Not stated Not stated Daniel's Scale Gestation Total at 48 Maternal 

(12, L ,318) average - 48 of Prestige of months 

months	 	 Occupations in


Australia,
Maternal
Education,
Paternal
Education
 


Port Pirie Lifetime 11-13 years Not stated -11.1 (ln)^ -5.6 (ln)^ Daniel's Scale Parental Birth Weight Family Structure, Unspecified Maternal Breast Feeding,

(35, L ,326) average - 5 of Prestige of Smoking Family Functioning, Feeding Method,

years	 	 Occupations in Habits Marital Status, Birth Order, 

Australia, Maternal Age, Life Child's Sex, Maternal Events Child's Age, 

Education School Grade,

School Absence 

Port Pirie Lifetime 11-13 years Not stated -11 (ln)^ -5.1 (ln) Daniel's Scale Parental Birth Weight Family Structure, Unspecified Maternal Breast Feeding,

(35, L ,326) average - 7 of Prestige of Smoking Family Functioning, Feeding Method,

years	 	 Occupations in Habits Marital Status, Birth Order, 

Australia, Maternal Age, Life Child's Sex, Maternal Events Child's Age, 

Education School Grade,

School Absence 

Cincinnati Mean 66-72 6.5 years Not stated -5.8^ -3.3^	 	 Cigarette Birth Weight, Unspecified Maternal Child's Sex 

(13, L ,253) months	 	 Consumption Birth Length 

duringPregnancy 

Cincinnati Lifetime 6.5 years Not stated -3.1^ 1.3 Cigarette Birth Weight, Unspecified Maternal Child's Sex 

(13, L ,253) average - 72 Consumption Birth Length 

months during

Pregnancy 

(Other) (Other) 

Cleveland 3 years 3 years 16.95 r=-.27^ Not stated Maternal Authoritarian Family Total Child Maternal Birth Order, 

(15, L ,167) Education Ideology Child's Sex,

Child's Age 

xÎ
 

* L=Longitudinal cohort, X=Cross-sectional.
** (ln)/(log10) = Original coefficient reported in log scale.


# = McCarthy GCI, all unmarked are full-scale IQ measures.
^ statistically significant (p < 0.05) 

x{
 

Covariates in Model

Study for PbB 5 -> 15**

Population* PbB Outcome Mean PbB Fetal Family Parental Iron 

(ref., type, n) Age Age # (ug/dL) Crude Adj SES Smoking Growth Environment HOME Race Intelligence Status Other 

Estimated Delta 

Cleveland 2 years 3 years 16.74 r=-.31^ Not stated 

(14, L ,153)

Cleveland 2 years 3 years 16.74 r=-.31^ Not stated 

(15, L ,153)

Cleveland 3 years 3 years 16.68 r=-.29^ Not stated 

(14, L ,165)

Rochester Peak - 5 years 5 years 11.3 -4.7^ -2.6^
 


(11, L ,172)


[all]
Cleveland 6 months 3 years 10.05 r=-.04 Not stated
 
(14, L ,126)
Cleveland 6 months 3 years 10.05 r=-.04 Not stated (15, L ,126)Rochester Lifetime 3 years 7.7 -7.4^ -3.5 

(11, L ,172) average - 3 [all] years * L=Longitudinal cohort, X=Cross-sectional.
** (ln)/(log10) = Original coefficient reported in log scale.


# = McCarthy GCI, all unmarked are full-scale IQ measures.
^ statistically significant (p < 0.05)
 


Maternal

Education

Maternal

Education

Maternal

Education

Yearly

HouseholdIncome,MaternalEducation

Maternal

Education

Maternal

Education

Yearly

HouseholdIncome,MaternalEducation 

MaternalCigarettes per

DayMaternalCigarettes perDayTobacco UseduringPregnancy(user/nonuser)MaternalCigarettes perDay Tobacco UseduringPregnancy(user/nonuser) 

Birth Weight Authoritarian Family Preschool Child Maternal 

Ideology Inventory

at 3 years 

Authoritarian Family Total Child Maternal Ideology 

Birth Weight Authoritarian Family Preschool Child Maternal 

Ideology Inventory

at 3 years 

Birth Weight Total Mother Maternal	 	 Serum

TransferrinSaturation 

Birth Weight Authoritarian Family Preschool Child Maternal 

Ideology Inventory

at 3 years 

Authoritarian Family Total Child Maternal Ideology 

Birth Weight Total Mother Maternal	 	 Serum

TransferrinSaturation 

Maternal

Medication/DrugUse, MaternalAlcoholConsumption,Birth Order,Child's Sex,Child's Age

Birth Order,

Child's Sex,Child's Age

Maternal

Medication/DrugUse, MaternalAlcoholConsumption,Birth Order,Child's Sex,Child's Age

Child's Sex

Maternal

Medication/DrugUse, MaternalAlcoholConsumption,Birth Order,Child's Sex,Child's Age

Birth Order,

Child's Sex,Child's Age

Child's Sex 
Covariates in Model

Study for PbB 5 -> 15**

Population* PbB Outcome Mean PbB Fetal Family Parental Iron 

(ref., type, n) Age Age # (ug/dL) Crude Adj SES Smoking Growth Environment HOME Race Intelligence Status Other 

Estimated Delta 

Rochester Average in 3 years 7.0 -7.3^ -3.2 Yearly Tobacco Use Birth Weight Total Mother Maternal Serum Child's Sex 

(11, L ,172) infancy - 6-24 Household during Transferrin 

[all] months Income, Pregnancy Saturation 

Maternal (user/nonuser)Education 

Rochester Average in 3 & 5 years 7.0 -8.5^ -4.3^ Yearly Tobacco Use Birth Weight Total Mother Maternal Serum Child's Sex 

(11, L ,172) infancy - 6-24 Household during Transferrin 

[all] months Income, Pregnancy Saturation 

Maternal (user/nonuser)Education 

Rochester Lifetime 3 & 5 years Not stated -8.7^ -4.6^ Yearly Tobacco Use Birth Weight Total Mother Maternal Serum Child's Sex 

(11, L ,172) average - 3 & Household during Transferrin 

[all] 5 years Income, Pregnancy Saturation 

Maternal (user/nonuser)Education 

Rochester Peak - 3 years 3 years Not stated -4^ -1.9 Yearly Tobacco Use Birth Weight Total Mother Maternal Serum Child's Sex 

(11, L ,172) Household during Transferrin 

[all] Income, Pregnancy Saturation 

Maternal (user/nonuser)Education 

Rochester Concurrent - 3 3 years Not stated -6^ -3.1^ Yearly Tobacco Use Birth Weight Total Mother Maternal Serum Child's Sex 

(11, L ,171) years Household during Transferrin 

[all] Income, Pregnancy Saturation 

Maternal (user/nonuser)Education 

Rochester Concurrent - 3 3 & 5 years Not stated -8.1^ -4.6^ Yearly Tobacco Use Birth Weight Total Mother Maternal Serum Child's Sex (11, L ,171) & 5 years Household during Transferrin 

[all] Income, Pregnancy Saturation 

Maternal (user/nonuser)Education 

Rochester Peak - 3 & 5 3 & 5 years Not stated -4.4^ -2.3^ Yearly Tobacco Use Birth Weight Total Mother Maternal Serum Child's Sex 

(11, L ,172) years Household during Transferrin 

[all] Income, Pregnancy Saturation 

Maternal (user/nonuser)Education 

* L=Longitudinal cohort, X=Cross-sectional.
** (ln)/(log10) = Original coefficient reported in log scale.


# = McCarthy GCI, all unmarked are full-scale IQ measures.
^ statistically significant (p < 0.05)
 


xx
xÈ
 

Covariates in Model Estimated Delta

Study for PbB 5 -> 15**

Population* PbB Outcome Mean PbB Fetal Family Parental Iron 

(ref., type, n) Age Age # (ug/dL) Crude Adj SES Smoking Growth Environment HOME Race Intelligence Status Other 

Rochester Lifetime 3 years Not stated -23^ -12.2 Yearly Tobacco Use Birth Weight Total Mother Maternal Serum Child's Sex 

(11, L ,101) average - 3 Household during Transferrin 

[<10 group] years Income, Pregnancy Saturation 

Maternal (user/nonuser)Education 

Rochester Lifetime 3 & 5 years Not stated -24.2^ -13.7^ Yearly Tobacco Use Birth Weight Total Mother Maternal Serum Child's Sex 

(11, L ,101) average - 3 & Household during Transferrin 

[<10 group] 5 years Income, Pregnancy Saturation 

Maternal (user/nonuser)Education 

Rochester Peak - 3 years 3 years Not stated -20.9^ -13.6^ Yearly Tobacco Use Birth Weight Total Mother Maternal Serum Child's Sex 

(11, L ,101) Household during Transferrin 

[<10 group] Income, Pregnancy Saturation 

Maternal (user/nonuser)Education 

Rochester Peak - 5 years 5 years Not stated -21.2^ -14.4^ Yearly Tobacco Use Birth Weight Total Mother Maternal Serum Child's Sex 

(11, L ,101) Household during Transferrin 

[<10 group] Income, Pregnancy Saturation 

Maternal (user/nonuser)Education 

Rochester Peak - 3 & 5 3 & 5 years Not stated -21^ -14^ Yearly Tobacco Use Birth Weight Total Mother Maternal Serum Child's Sex 

(11, L ,101) years Household during Transferrin 

[<10 group] Income, Pregnancy Saturation 

Maternal (user/nonuser)Education 

Rochester Concurrent - 3 3 & 5 years Not stated -23.8^ -15.8^ Yearly Tobacco Use Birth Weight Total Mother Maternal Serum Child's Sex 

(11, L ,101) & 5 years Household during Transferrin 

[<10 group] Income, Pregnancy Saturation 

Maternal (user/nonuser)Education 

Rochester Average in 3 years Not stated -12.9 -5.8 Yearly Tobacco Use Birth Weight Total Mother Maternal Serum Child's Sex (11, L ,105) infancy - 6-24 Household during Transferrin 

[<10 group] months Income, Pregnancy Saturation 

Maternal (user/nonuser)Education 

* L=Longitudinal cohort, X=Cross-sectional.
** (ln)/(log10) = Original coefficient reported in log scale.


# = McCarthy GCI, all unmarked are full-scale IQ measures.
^ statistically significant (p < 0.05)
 


 

Covariates in Model

Study for PbB 5 -> 15**

Population* PbB Outcome Mean PbB Fetal Family Parental Iron 

(ref., type, n) Age Age # (ug/dL) Crude Adj SES Smoking Growth Environment HOME Race Intelligence Status Other 

Estimated Delta 

Rochester Average in 3 & 5 years Not stated -14.3^ -7.5 Yearly 

(11, L ,105) infancy - 6-24 Household [<10 group] months Income,

MaternalEducation 

Rochester Concurrent - 3 3 years Not stated -21.9^ -13.6^ Yearly 

(11, L ,101) years Household 

[<10 group] Income,

MaternalEducation 

* L=Longitudinal cohort, X=Cross-sectional.
** (ln)/(log10) = Original coefficient reported in log scale.


# = McCarthy GCI, all unmarked are full-scale IQ measures.
^ statistically significant (p < 0.05)
 


Tobacco Use Birth Weight Total Mother Maternal Serum Child's Sex during Transferrin Pregnancy Saturation 

(user/nonuser)Tobacco Use Birth Weight Total Mother Maternal Serum Child's Sex 

during Transferrin Pregnancy Saturation 

(user/nonuser) 

xÇ
 
xn
 

Table 3. Summary of studies estimating association of postnatal PbB with performance scale IQ


Covariates in Model

Study for PbB 5 -> 15**

Population* Parental 

Estimated Delta IQ 

PbB Outcome Mean PbB Fetal Family Iron 

(ref., type, n) IQ Age Age (ug/dL) Crude Adj SES Smoking Growth Environment HOME Race Status Other 

(<= 2 years) (>= 4 years) 

Port Pirie 15 months 11-13 years 20.9 (GM) -5.7 (ln)^ -0.7 (ln) Daniel's Scale	 	 Parental Birth Weight Family Structure, Unspecified Maternal Breast Feeding,

(35, L ,367) of Prestige of Smoking Family Functioning, Feeding Method,

Occupations in Habits Marital Status, Birth Order, Australia, Maternal Age, Life Child's Sex, Maternal Events Child's Age, 

Education School Grade,

School Absence 

Port Pirie Lifetime 7 years 16.6-20.5 Not stated -2.6 (ln) Daniel's Scale	 	 Parental Birth Weight Family Structure, Unspecified Maternal Breast Feeding,

(4, L ,494) average - 2 (means of of Prestige of Smoking Maternal Age Feeding Method,

years 2nd & 3rd Occupations in Birth Order, 

quartiles) Australia, Child's Sex (GM) Maternal

Education,PaternalEducation 

Port Pirie Lifetime 7 years 14.3-18.0 Not stated -2.5 (ln) Daniel's Scale	 	 Parental Birth Weight Family Structure, Unspecified Maternal Breast Feeding,

(4, L ,494) average - 15 (means of of Prestige of Smoking Maternal Age Feeding Method,

months 2nd & 3rd Occupations in Birth Order, 

quartiles) Australia, Child's Sex (GM) Maternal

Education,PaternalEducation 

Cincinnati Mean 15-24 6.5 years 17.1 -2^ -1		 Cigarette Birth Weight, Unspecified Maternal Child's Sex 

(13, L ,253) months	 	 Consumption Birth Length 

duringPregnancy 

Cleveland 2 years 4 years 10 16.70 r=-.34 Not stated Maternal	 	 Cigarettes per Birth Weight, Authoritarian Family Total Child Maternal Child Stress, (16, L ,149) months Education Day Gestation Ideology (mean of Maternal 

1, 2, 3, and Medication/Drug

4 years 10 Use, Maternalmonths) Alcohol

Consumption,Birth Order,Child's Sex,History AlcoholAbuse 

* L=Longitudinal cohort, X=Cross-sectional.** (ln)/(log10) = Original coefficient reported in log scale.

^ statistically significant (p < 0.05) 

 

Covariates in Model

Study for PbB 5 -> 15**

Population* Parental 

Estimated Delta IQ 

PbB Outcome Mean PbB Fetal Family Iron 

(ref., type, n) Age Age (ug/dL) Crude Adj SES Smoking Growth Environment HOME Race IQ Status Other 

Costa Rica 12-23 months 5 years 11.0 r=.05 Not stated (41, L ,184)Cincinnati Mean 3-12 6.5 years 10.6 -3.9^ -1.6	 	 Cigarette Birth Weight, Unspecified Maternal Child's Sex 

(13, L ,253) months	 	 Consumption Birth Length 

duringPregnancy 

Cleveland 6 months 4 years 10 9.99 r=-.06 Not stated Maternal	 	 Cigarettes per Birth Weight, Authoritarian Family Total Child Maternal Child Stress, (16, L ,122) months Education Day Gestation Ideology		 (mean of Maternal 

1, 2, 3, and Medication/Drug4 years 10 Use, Maternal

months) Alcohol

Consumption,Birth Order,Child's Sex,History AlcoholAbuse 

Boston 18 months 10 years 7.8 Not stated 0 Hollingshead Family Stress,	 	 Scales V & Child Maternal Child Stress, Birth

(7, L ,116)	 	 Four-Factor Marital Status, VI at 120 Order, Child's Sex

Index of Social Residence months, Class Changes, Maternal Total at 57 

Age months 

Boston 12 months 10 years 7.7 Not stated 1.4 Hollingshead Family Balance,	 	 Scales V & Child Maternal Child Stress, 

(7, L ,116)	 	 Four-Factor Family Stress, VI at 120 Parents' Sense

Index of Social Marital Status months, Competence,Class Total at 57 Birth Order, 

months	 	 Child's Sex 

Boston 6 months 10 years 6.7 Not stated 0.3 Hollingshead Marital Status	 	 Scales V & Child Maternal Child Stress, Birth

(7, L ,116)	 	 Four-Factor VI at 120 Order, Child's Sex

Index of Social months, 

Class Total at 57

months 

Boston 24 months 10 years 6.5 Not stated -3.9 Hollingshead Family Stress,	 	 Scales V & Child Maternal Child Stress, Birth

(7, L ,116)	 	 Four-Factor Marital Status, VI at 120 Order, Child's Sex

Index of Social Residence months, Class Changes, Maternal Total at 57 

Age months 

Cincinnati 10 Days 6.5 years 5 -4 -2.2	 	 Cigarette Birth Weight, Unspecified Maternal Child's Sex 

(13, L ,253)	 	 Consumption Birth Length 

duringPregnancy 

x
 

* L=Longitudinal cohort, X=Cross-sectional.** (ln)/(log10) = Original coefficient reported in log scale.

^ statistically significant (p < 0.05) 
Èä
 

Covariates in Model

Study for PbB 5 -> 15**

Population* Parental 

Estimated Delta IQ 

PbB Outcome Mean PbB Fetal Family Iron 

(ref., type, n) IQ Age Age (ug/dL) Crude Adj SES Smoking Growth Environment HOME Race Status Other 

Boston 24 months 10 years < 8 Not stated -3.9	 	 Hollingshead Marital Status, Scales V & Child Maternal Child Stress, Birth

(34, L ,148)	 	 Four-Factor Residence VI at 120 Order, Child's Sex

Index of Social Changes, Maternal months, Class Age Total at 57 

mo 

(>2 - <4 years) (>= 4 years)

Port Pirie Lifetime 7 years 17.4-21.7 Not stated -3.1 (ln)	 	 Daniel's Scale(4, L ,494) average - 3 (means of of Prestige of

years 2nd & 3rd Occupations in

quartiles) Australia, (GM) Maternal

Education,PaternalEducation 

Port Pirie 3 years 11-13 years 19.3 (GM) -10.3 (ln)^ -4.6 (ln)	 	 Daniel's Scale(35, L ,372)	 	 of Prestige of

Occupations inAustralia,MaternalEducation 

Cleveland 3 years 4 years 10 16.70 r=-.28 Not stated Maternal 

(16, L ,155) months Education 

Cincinnati Mean 27-36 6.5 years 16.3 -3.4^ -2.2^ 

(13, L ,253) months 

Parental Birth Weight Family Structure, Unspecified Maternal	 	 Breast Feeding,

Smoking Maternal Age	 	 Feeding Method,

Birth Order,Child's Sex 

Parental Birth Weight Family Structure, Unspecified Maternal Breast Feeding,Smoking Family Functioning, Feeding Method,

Habits Marital Status, Birth Order, 

Maternal Age, Life	 	 Child's Sex, Events	 	 Child's Age,

School Grade,School Absence 

Cigarettes per Birth Weight, Authoritarian Family Total Child Maternal	 	 Child Stress, 

Day Gestation Ideology		 (mean of Maternal 

1, 2, 3, and Medication/Drug

4 years 10 Use, Maternalmonths) Alcohol

Consumption,Birth Order,

Child's Sex,History AlcoholAbuse 

Cigarette Birth Weight, Unspecified Maternal Child's Sex 

Consumption Birth Length duringPregnancy 

* L=Longitudinal cohort, X=Cross-sectional.** (ln)/(log10) = Original coefficient reported in log scale.

^ statistically significant (p < 0.05) 

 

Covariates in Model

Study for PbB 5 -> 15**

Population* Parental 

Estimated Delta IQ 

PbB Outcome Mean PbB Fetal Family Iron 

(ref., type, n) Age Age (ug/dL) Crude Adj SES Smoking Growth Environment HOME Race IQ Status Other 

Cleveland Mean 0.5-3 4 years 10 9.99 at 6 r=-.25 Not stated Maternal Cigarettes per Birth Weight, Authoritarian Family Total Child Maternal Child Stress, 

(16, L ,212) years months months & Education Day Gestation Ideology (mean of Maternal 

16.70 at 1, 2, 3, and Medication/Drug

both 2 4 years 10 Use, Maternalyears & 3 months) Alcohol years Consumption,

Birth Order,Child's Sex,History AlcoholAbuse 

Port Pirie Lifetime 11-13 years Not stated -8.6 (ln)^ -3.5 (ln) Daniel's Scale Parental Birth Weight Family Structure, Unspecified Maternal Breast Feeding,

(35, L ,326) average - 3 of Prestige of Smoking Family Functioning, Feeding Method,

years	 	 Occupations in Habits Marital Status, Birth Order, 

Australia, Maternal Age, Life Child's Sex, 

Maternal Events Child's Age, 

Education School Grade,

School Absence 

(>= 4 years) (>= 4 years) 

Lavrion, Greece Primary school Primary school 23.7 Not stated -2.3^ Maternal 

(20, X ,509) children - not children - not Education, 

specified years specified years Paternal

Education,PaternalOccupation 

Port Pirie Lifetime 7 years 17.6-21.5 Not stated -3.6 (ln) Daniel's Scale(4, L ,494) average - 4 (means of of Prestige of

years 2nd & 3rd Occupations in

quartiles) Australia, (GM) Maternal

Education,PaternalEducation 

Birth Weight	 	 Family Structure, Both Birth Order, 

Marital Status, Life Child's Age, 

Events Child's Medical

History, HistoryAlcohol Abuse,Father's Age,Bilingualism,Length of Child'sHospital Stayafter Birth 

Parental Birth Weight Family Structure, Unspecified Maternal		 Breast Feeding,Smoking Maternal Age	 	 Feeding Method,

Birth Order,Child's Sex 

È£
 

* L=Longitudinal cohort, X=Cross-sectional.

** (ln)/(log10) = Original coefficient reported in log scale.

^ statistically significant (p < 0.05) 
ÈÓ
 

Covariates in Model

Study for PbB 5 -> 15**

Population* Parental 

Estimated Delta IQ 

PbB Outcome Mean PbB Fetal Family Iron 

(ref., type, n) Age Age (ug/dL) Crude Adj SES Smoking Growth Environment HOME Race IQ Status Other 

Port Pirie Lifetime 7 years 15.7-19.7 Not stated -2.5 (ln)	 	 Daniel's Scale Parental Birth Weight Family Structure, Unspecified Maternal Breast Feeding,

(4, L ,494) average - 7 (means of of Prestige of Smoking Maternal Age Feeding Method,

years 2nd & 3rd Occupations in Birth Order, 

quartiles) Australia, Child's Sex (GM) Maternal

Education,PaternalEducation 

Mexico City II 7-9 years 7-9 years 19.4 r=-.24 (ln) r=-.28 (ln)	 	 Income, Child's Sex, Type

(26, X ,139)	 	 Maternal of Housing, 

Education, Nutritional StatusPaternal (weight for heightEducation & height for age) 

Port Pirie 5 years 11-13 years 14.3 (GM) -7.9 (ln)^ -4.1 (ln)	 	 Daniel's Scale Parental Birth Weight Family Structure, Unspecified Maternal Breast Feeding,(35, L ,368) of Prestige of Smoking Family Functioning, Feeding Method,

Occupations in Habits Marital Status, Birth Order, Australia, Maternal Age, Life Child's Sex, 

Maternal Events Child's Age, 

Education School Grade,

School Absence 

Port Pirie Lifetime 11-13 years 14.1 (GM) -11.9 (ln)^ -5.2 (ln)	 	 Daniel's Scale Parental Birth Weight Family Structure, Unspecified Maternal Breast Feeding,(35, L ,326) average - 11- of Prestige of Smoking Family Functioning, Feeding Method,

13 years Occupations in Habits Marital Status, Birth Order, 

Australia, Maternal Age, Life Child's Sex, 

Maternal Events Child's Age, 

Education School Grade,

School Absence 

Cincinnati Mean 39-48 6.5 years 14.0 -4.3^ -2.7^	 	 Cigarette Birth Weight, Unspecified Maternal Child's Sex (13, L ,253) months	 	 Consumption Birth Length 

duringPregnancy 

Cincinnati Mean 51-60 6.5 years 11.8 -5.5^ -3.8^	 	 Cigarette Birth Weight, Unspecified Maternal Child's Sex (13, L ,253) months	 	 Consumption Birth Length 

duringPregnancy 

* L=Longitudinal cohort, X=Cross-sectional.** (ln)/(log10) = Original coefficient reported in log scale.

^ statistically significant (p < 0.05) 

 

Covariates in Model

Study for PbB 5 -> 15**

Population* Parental 

Estimated Delta IQ 

PbB Outcome Mean PbB Fetal Family Iron 

(ref., type, n) IQ Age Age (ug/dL) Crude Adj SES Smoking Growth Environment HOME Race Status Other 

Port Pirie 7 years 11-13 years 11.6 (GM) -9.4 (ln)^ -4.2 (ln)	 	 Daniel's Scale Parental Birth Weight Family Structure, Unspecified Maternal Breast Feeding,(35, L ,360) of Prestige of Smoking Family Functioning, Feeding Method,

Occupations in Habits Marital Status, Birth Order, Australia, Maternal Age, Life Child's Sex, Maternal Events Child's Age, Education School Grade,

School Absence 

Dunedin, New 11 years 11 years 11.1 r=-0.03 (ln) Not stated 

Zealand(33, L ,579)

Sassuolo, Italy 7-8 years 7-8 years 10.99 (GM) r = -0.100 Not stated 

(8, X ,211) (log10) 

San Luis Potosi, 6-9 years 6-9 years 9.73 (GM) r=.04 (ln) r=-.10 (ln)	 	 Bronffman Child's Sex, 

Mexico	 	 Index of Child's Age 

(10, X ,39)	 	 Socioeconomic[reference group]	 	 Status,

MaternalEducation,PaternalEducation 

San Luis Potosi, 6-9 years 6-9 years 8.98 (GM) r=-.08 (ln) r=.005 (ln)	 	 Bronffman Child's Sex, 

Mexico	 	 Index of Child's Age 

(10, X ,41)	 	 Socioeconomic[exposed group]	 	 Status,

MaternalEducation,PaternalEducation 

Port Pirie 11-13 years 11-13 years 7.9 (GM) -6.8 (ln)^ -2.2 (ln)	 	 Daniel's Scale Parental Birth Weight Family Structure, Unspecified Maternal Breast Feeding,

(35, L ,326) of Prestige of Smoking Family Functioning, Feeding Method,

Occupations in Habits Marital Status, Birth Order, 

Australia, Maternal Age, Life Child's Sex, Maternal Events Child's Age, Education School Grade,

School Absence 

Boston 57 months 10 years 6.3 Not stated -4.4	 	 Hollingshead Birth Weight Family Stress, Scales V & Child Maternal Child Stress, Birth

(7, L ,116) Four-Factor Marital Status, VI at 120 Order, Child's Sex

Index of Social Maternal Age months, Class Total at 57

months 

ÈÎ
 

* L=Longitudinal cohort, X=Cross-sectional.** (ln)/(log10) = Original coefficient reported in log scale.

^ statistically significant (p < 0.05) 
È{
 

Covariates in Model

Study for PbB 5 -> 15**

Population* Parental 

Estimated Delta IQ 

PbB Outcome Mean PbB Fetal Family Iron 

(ref., type, n) Age Age (ug/dL) Crude Adj SES Smoking Growth Environment HOME Race IQ Status Other 

Boston 10 years 10 years 2.9 Not stated -1.7	 	 Hollingshead Birth Weight Family Stress, Scales V & Child Maternal Child Stress, Birth

(7, L ,116)	 	 Four-Factor Marital Status, Day VI at 120 Order, Child's Sex

Index of Social Care, Maternal Age months, 

Class Total at 57

months 

Kosovo Mean AUC7 7 years	 	 PbB at age Not stated -4.5 (log10)^ Maternal Birth Weight Family Structure, Unspecified Child Maternal Child's Sex 

(38, L ,261) years	 	 7 years = Education Maternal Age

21.2;cumulative

PbB

through age7 years = 

1.21 

Port Pirie Lifetime 11-13 years Not stated -9.6 (ln)^ -4.7 (ln) Daniel's Scale Parental Birth Weight Family Structure, Unspecified Maternal Breast Feeding,

(35, L ,326) average - 7 of Prestige of Smoking Family Functioning, Feeding Method,

years	 	 Occupations in Habits Marital Status, Birth Order, 

Australia, Maternal Age, Life Child's Sex, 

Maternal Events Child's Age, 

Education School Grade,

School Absence 

Port Pirie Lifetime 11-13 years Not stated -9.4 (ln)^ -4.8 (ln) Daniel's Scale Parental Birth Weight Family Structure, Unspecified Maternal Breast Feeding,

(35, L ,326) average - 5 of Prestige of Smoking Family Functioning, Feeding Method,

years	 	 Occupations in Habits Marital Status, Birth Order, 

Australia, Maternal Age, Life Child's Sex, 

Maternal Events Child's Age, 

Education School Grade,

School Absence 

Cincinnati Mean 66-72 6.5 years	 	 Not stated -7.5^ -5.2^ Cigarette Birth Weight, Unspecified Maternal Child's Sex 

(13, L ,253) months	 	 Consumption Birth Length 

duringPregnancy 

Cincinnati Lifetime 6.5 years Not stated -4.3^ -2.6^ Cigarette Birth Weight, Unspecified Maternal Child's Sex 

(13, L ,253) average - 72 Consumption Birth Length 

months during

Pregnancy 

* L=Longitudinal cohort, X=Cross-sectional.** (ln)/(log10) = Original coefficient reported in log scale.

^ statistically significant (p < 0.05) 

 

Table 4. Summary of studies estimating association of postnatal PbB with verbal scale IQ


Covariates in Model

Study for PbB 5 -> 15**

Population* PbB Outcome Mean PbB Fetal Family Parental Iron 

(ref., type, n) Age Age (ug/dL) Crude Adj SES Smoking Growth Environment HOME Race IQ Status Other 

Estimated Delta IQ 

(<= 2 years) (>= 4 years) 

Port Pirie 15 months 11-13 years 20.9 (GM) -7 (ln)^ -3.2 (ln)^ Daniel's Scale	 	 Parental Birth Weight Family Structure, Unspecified Maternal Breast Feeding,

(35, L ,367) of Prestige of Smoking Family Functioning, Feeding Method,

Occupations in Habits Marital Status, Birth Order, Australia, Maternal Age, Life Child's Sex, Maternal Events Child's Age, Education School Grade,

School Absence 

Port Pirie Lifetime 7 years 16.6-20.5 Not stated -6.4 (ln)^ Daniel's Scale	 	 Parental Birth Weight Family Structure, Unspecified Maternal Breast Feeding,

(4, L ,494) average - 2 (means of of Prestige of Smoking Maternal Age Feeding Method,

years 2nd & 3rd Occupations in Birth Order, 

quartiles) Australia, Child's Sex (GM) Maternal

Education,PaternalEducation 

Port Pirie Lifetime 7 years 14.3-18.0 Not stated -5.5 (ln)^ Daniel's Scale	 	 Parental Birth Weight Family Structure, Unspecified Maternal Breast Feeding,

(4, L ,494) average - 15 (means of of Prestige of Smoking Maternal Age Feeding Method,

months 2nd & 3rd Occupations in Birth Order, 

quartiles) Australia, Child's Sex (GM) Maternal

Education,PaternalEducation 

Cincinnati Mean 15-24 6.5 years 17.1 -0.3 0.2		 Cigarette Birth Weight, Unspecified Maternal Child's Sex 

(13, L ,253) months	 	 Consumption Birth Length 

duringPregnancy 

Cleveland 2 years 4 years 10 16.70 r=-.37 Not stated Maternal	 	 Cigarettes per Birth Weight, Authoritarian Family Total Child Maternal Child Stress, 

(16, L ,149) months Education Day Gestation Ideology (mean of Maternal 

1, 2, 3, and Medication/Drug4 years 10 Use, Maternal

months) Alcohol

Consumption,Birth Order,Child's Sex,History AlcoholAbuse 

Èx
 * L=Longitudinal cohort, X=Cross-sectional. ** (ln)/(log10) = Original coefficient reported in log scale.

^ statistically significant (p < 0.05) 
ÈÈ
 

Covariates in Model

Study for PbB 5 -> 15**

Population* PbB Outcome Mean PbB Fetal Family Parental Iron 

(ref., type, n) Age Age (ug/dL) Crude Adj SES Smoking Growth Environment HOME Race IQ Status Other 

Estimated Delta IQ 

Costa Rica 12-23 months 5 years 11.0 r=.06 Not stated (41, L ,184)Cincinnati Mean 3-12 6.5 years 10.6 0 1.2	 	 Cigarette Birth Weight, Unspecified Maternal Child's Sex 

(13, L ,253) months	 	 Consumption Birth Length 

duringPregnancy 

Cleveland 6 months 4 years 10 9.99 r=-.05 Not stated Maternal	 	 Cigarettes per Birth Weight, Authoritarian Family Total Child Maternal Child Stress, (16, L ,122) months Education Day Gestation Ideology		 (mean of Maternal 

1, 2, 3, and Medication/Drug4 years 10 Use, Maternal

months) Alcohol

Consumption,Birth Order,Child's Sex,History AlcoholAbuse 

Boston 18 months 10 years 7.8 Not stated -2 Hollingshead Family Stress,	 	 Scales V & Child Maternal Child Stress, Birth

(7, L ,116)	 	 Four-Factor Marital Status, VI at 120 Order, Child's Sex

Index of Social Residence months, Class Changes, Maternal Total at 57 

Age months 

Boston 12 months 10 years 7.7 Not stated -1.3 Hollingshead Family Balance,	 	 Scales V & Child Maternal Child Stress, (7, L ,116)	 	 Four-Factor Family Stress, VI at 120 Parents' Sense

Index of Social Marital Status months, Competence,Class Total at 57 Birth Order, 

months	 	 Child's Sex 

Boston 6 months 10 years 6.7 Not stated -2.4 Hollingshead Marital Status	 	 Scales V & Child Maternal Child Stress, Birth

(7, L ,116)	 	 Four-Factor VI at 120 Order, Child's Sex

Index of Social months, 

Class Total at 57

months 

Boston 24 months 10 years 6.5 Not stated -6.3^ Hollingshead Marital Status,	 	 Scales V & Child Maternal Child Stress, Birth

(7, L ,116)	 	 Four-Factor Residence VI at 120 Order, Child's Sex

Index of Social Changes, Maternal months, Class Age Total at 57

months 

Cincinnati 10 Days 6.5 years 5 -0.1 1.1	 	 Cigarette Birth Weight, Unspecified Maternal Child's Sex 

(13, L ,253)	 	 Consumption Birth Length 

duringPregnancy 

* L=Longitudinal cohort, X=Cross-sectional.** (ln)/(log10) = Original coefficient reported in log scale.

^ statistically significant (p < 0.05) 

 

Covariates in Model Estimated Delta IQ

Study for PbB 5 -> 15**

Population* PbB Outcome Mean PbB Fetal Family Parental Iron 

(ref., type, n) Age Age (ug/dL) Crude Adj SES Smoking Growth Environment HOME Race IQ Status Other 

Boston 24 months 10 years < 8 Not stated -6.3^	 	 Hollingshead Marital Status, Scales V & Child Maternal Child Stress, Birth

(34, L ,148)	 	 Four-Factor Residence VI at 120 Order, Child's Sex

Index of Social Changes, Maternal months, Class Age Total at 57

months 

(>2 - <4 years) (>= 4 years)

Port Pirie Lifetime 7 years 17.4-21.7 Not stated -6.3 (ln)^	 	 Daniel's Scale

(4, L ,494) average - 3 (means of of Prestige of

years 2nd & 3rd Occupations in

quartiles) Australia, (GM) Maternal

Education,PaternalEducation 

Port Pirie 3 years 11-13 years 19.3 (GM) -9.3 (ln)^ -2.9 (ln)	 	 Daniel's Scale(35, L ,372)	 	 of Prestige of

Occupations inAustralia,MaternalEducation 

Cleveland 3 years 4 years 10 16.70 r=-.37 Not stated Maternal 

(16, L ,155) months Education 

Cincinnati Mean 27-36 6.5 years 16.3 -1.4 -0.4 (13, L ,253) months 

Parental Birth Weight Family Structure, Unspecified Maternal	 	 Breast Feeding,

Smoking Maternal Age	 	 Feeding Method,

Birth Order,Child's Sex 

Parental Birth Weight Family Structure, Unspecified Maternal Breast Feeding,Smoking Family Functioning, Feeding Method,

Habits Marital Status, Birth Order, 

Maternal Age, Life	 	 Child's Sex, 

Events	 	 Child's Age,

School Grade,School Absence 

Cigarettes per Birth Weight, Authoritarian Family Total Child Maternal	 	 Child Stress, Day Gestation Ideology		 (mean of Maternal 

1, 2, 3, and Medication/Drug

4 years 10 Use, Maternalmonths) Alcohol

Consumption,Birth Order,

Child's Sex,History AlcoholAbuse 

Cigarette Birth Weight, Unspecified Maternal Child's Sex 

Consumption Birth Length duringPregnancy 

ÈÇ
 

* L=Longitudinal cohort, X=Cross-sectional.** (ln)/(log10) = Original coefficient reported in log scale.

^ statistically significant (p < 0.05) 
Èn
 

Covariates in Model

Study for PbB 5 -> 15**

Population* PbB Outcome Mean PbB Fetal Family Parental Iron 

(ref., type, n) Age Age (ug/dL) Crude Adj SES Smoking Growth Environment HOME Race IQ Status Other 

Estimated Delta IQ 

Cleveland Mean 0.5-3 4 years 10 9.99 at 6 r=-.29 Not stated Maternal Cigarettes per Birth Weight, Authoritarian Family Total Child Maternal Child Stress, 

(16, L ,212) years months months & Education Day Gestation Ideology (mean of Maternal 

16.70 at 1, 2, 3, and Medication/Drug

both 2 4 years 10 Use, Maternalyears & 3 months) Alcohol years Consumption,

Birth Order,Child's Sex,History AlcoholAbuse 

Port Pirie Lifetime 11-13 years Not stated -10.2 (ln)^ -5.1 (ln)^ Daniel's Scale Parental Birth Weight Family Structure, Unspecified Maternal Breast Feeding,

(35, L ,326) average - 3 of Prestige of Smoking Family Functioning, Feeding Method,

years	 	 Occupations in Habits Marital Status, Birth Order, 

Australia, Maternal Age, Life Child's Sex, 

Maternal Events Child's Age, 

Education School Grade,

School Absence 

(>= 4 years) (>= 4 years) 

Lavrion, Greece Primary school Primary school 23.7 Not stated -2.52^ Maternal 

(20, X ,509) children - not children - not Education, 

specified years specified years Paternal

Education,PaternalOccupation 

Port Pirie Lifetime 7 years 17.6-21.5 Not stated -5.5 (ln)^ Daniel's Scale(4, L ,494) average - 4 (means of of Prestige of

years 2nd & 3rd Occupations in

quartiles) Australia, (GM) Maternal

Education,PaternalEducation 

Birth Weight	 	 Family Structure, Both Birth Order, 

Marital Status, Life Child's Age, 

Events Child's Medical

History, HistoryAlcohol Abuse,Father's Age,Bilingualism,Length of Child'sHospital Stayafter Birth 

Parental Birth Weight Family Structure, Unspecified Maternal		 Breast Feeding,Smoking Maternal Age	 	 Feeding Method,

Birth Order,Child's Sex 

* L=Longitudinal cohort, X=Cross-sectional.** (ln)/(log10) = Original coefficient reported in log scale.

^ statistically significant (p < 0.05) 

 

Covariates in Model

Study for PbB 5 -> 15**

Population* PbB Outcome Mean PbB Fetal Family Parental Iron 

(ref., type, n) Age Age (ug/dL) Crude Adj SES Smoking Growth Environment HOME Race IQ Status Other 

Estimated Delta IQ 

Port Pirie Lifetime 7 years 15.7-19.7 Not stated -4.7 (ln)	 	 Daniel's Scale Parental Birth Weight Family Structure, Unspecified Maternal Breast Feeding,

(4, L ,494) average - 7 (means of of Prestige of Smoking Maternal Age Feeding Method,

years 2nd & 3rd Occupations in Birth Order, 

quartiles) Australia, Child's Sex (GM) Maternal

Education,PaternalEducation 

Mexico City II 7-9 years 7-9 years 19.4 r=-.24 (ln) r=-.19 (ln)	 	 Income, Child's Sex, Type

(26, X ,139)	 	 Maternal of Housing, 

Education, Nutritional StatusPaternal (weight for heightEducation & height for age) 

Port Pirie 5 years 11-13 years 14.3 (GM) -9.2 (ln)^ -4.1 (ln)^	 	 Daniel's Scale Parental Birth Weight Family Structure, Unspecified Maternal Breast Feeding,

(35, L ,368) of Prestige of Smoking Family Functioning, Feeding Method,

Occupations in Habits Marital Status, Birth Order, Australia, Maternal Age, Life Child's Sex, 

Maternal Events Child's Age, 

Education School Grade,

School Absence 

Port Pirie Lifetime 11-13 years 14.1 (GM) -11.9 (ln)^ -4.3 (ln)^	 	 Daniel's Scale Parental Birth Weight Family Structure, Unspecified Maternal Breast Feeding,

(35, L ,326) average - 11- of Prestige of Smoking Family Functioning, Feeding Method,

13 years Occupations in Habits Marital Status, Birth Order, 

Australia, Maternal Age, Life Child's Sex, 

Maternal Events Child's Age, 

Education School Grade,

School Absence 

Cincinnati Mean 39-48 6.5 years 14.0 -1.4 -0.2		 Cigarette Birth Weight, Unspecified Maternal Child's Sex 

(13, L ,253) months	 	 Consumption Birth Length 

duringPregnancy 

Cincinnati Mean 51-60 6.5 years 11.8 -2.2 -0.7		 Cigarette Birth Weight, Unspecified Maternal Child's Sex 

(13, L ,253) months	 	 Consumption Birth Length 

duringPregnancy 

È
 

* L=Longitudinal cohort, X=Cross-sectional.** (ln)/(log10) = Original coefficient reported in log scale.

^ statistically significant (p < 0.05) 
Çä
 

Covariates in Model Estimated Delta IQ

Study for PbB 5 -> 15**

Population* PbB Outcome Mean PbB Fetal Family Parental Iron 

(ref., type, n) Age Age (ug/dL) Crude Adj SES Smoking Growth Environment HOME Race IQ Status Other 

Port Pirie 7 years 11-13 years 11.6 (GM) -8.7 (ln)^ -3.1 (ln)	 	 Daniel's Scale Parental Birth Weight Family Structure, Unspecified Maternal Breast Feeding,(35, L ,360) of Prestige of Smoking Family Functioning, Feeding Method,

Occupations in Habits Marital Status, Birth Order, Australia, Maternal Age, Life Child's Sex, Maternal Events Child's Age, Education School Grade,

School Absence 

Dunedin, New 11 years 11 years 11.1 r=-0.06 (ln) Not stated 

Zealand(33, L ,579)

Sassuolo, Italy 7-8 years 7-8 years 10.99 (GM) r = -0.101 Not stated 

(8, X ,212) (log10) 

San Luis Potosi, 6-9 years 6-9 years 9.73 (GM) r=.04 (ln) r=.07 (ln)	 	 Bronffman Child's Sex, 

Mexico	 	 Index of Child's Age 

(10, X ,39)	 	 Socioeconomic[reference group]	 	 Status,

MaternalEducation,PaternalEducation 

San Luis Potosi, 6-9 years 6-9 years 8.98 (GM) r=-.12 (ln) r=-.25 (ln)	 	 Bronffman Child's Sex, 

Mexico	 	 Index of Child's Age 

(10, X ,41)	 	 Socioeconomic[exposed group]	 	 Status,

MaternalEducation,PaternalEducation 

Port Pirie 11-13 years 11-13 years 7.9 (GM) -6.3 (ln)^ -2.6 (ln)	 	 Daniel's Scale Parental Birth Weight Family Structure, Unspecified Maternal Breast Feeding,

(35, L ,326) of Prestige of Smoking Family Functioning, Feeding Method,

Occupations in Habits Marital Status, Birth Order, Australia, Maternal Age, Life Child's Sex, Maternal Events Child's Age, Education School Grade,

School Absence 

Boston 57 months 10 years 6.3 Not stated -0.7	 	 Hollingshead Birth Weight Family Stress, Scales V & Child Maternal Child Stress, Birth

(7, L ,116) Four-Factor Marital Status, VI at 120 Order, Child's Sex

Index of Social Maternal Age months, Class Total at 57

months 

* L=Longitudinal cohort, X=Cross-sectional.** (ln)/(log10) = Original coefficient reported in log scale.

^ statistically significant (p < 0.05) 

 

Covariates in Model

Study for PbB 5 -> 15**

Population* PbB Outcome Mean PbB Fetal Family Parental Iron 

(ref., type, n) Age Age (ug/dL) Crude Adj SES Smoking Growth Environment HOME Race IQ Status Other 

Estimated Delta IQ 

Boston 10 years 10 years 2.9 Not stated -5.9	 	 Hollingshead Birth Weight Family Stress, Scales V & Child Maternal Child Stress, Birth

(7, L ,116)	 	 Four-Factor Marital Status, Day VI at 120 Order, Child's Sex

Index of Social Care, Maternal Age months, 

Class Total at 57

months 

Kosovo Mean AUC7 7 years	 	 PbB at age Not stated -3.4 (log10)^ Maternal Birth Weight Family Structure, Unspecified Child Maternal Child's Sex 

(38, L ,259) years	 	 7 years = Education Maternal Age

21.2;cumulativePbBthrough age7 years = 1.21 

Port Pirie Lifetime 11-13 years Not stated -10.8 (ln)^ -5.5 (ln)^ Daniel's Scale Parental Birth Weight Family Structure, Unspecified Maternal Breast Feeding,

(35, L ,326) average - 5 of Prestige of Smoking Family Functioning, Feeding Method,

years	 	 Occupations in Habits Marital Status, Birth Order, 

Australia, Maternal Age, Life Child's Sex, 

Maternal Events Child's Age, 

Education School Grade,

School Absence 

Port Pirie Lifetime 11-13 years Not stated -10.5 (ln)^ -4.7 (ln)^ Daniel's Scale Parental Birth Weight Family Structure, Unspecified Maternal Breast Feeding,

(35, L ,326) average - 7 of Prestige of Smoking Family Functioning, Feeding Method,

years	 	 Occupations in Habits Marital Status, Birth Order, 

Australia, Maternal Age, Life Child's Sex, 

Maternal Events Child's Age, 

Education School Grade,

School Absence 

Cincinnati Mean 66-72 6.5 years	 	 Not stated -3.3^ -1.2 Cigarette Birth Weight, Unspecified Maternal Child's Sex 

(13, L ,253) months	 	 Consumption Birth Length 

duringPregnancy 

Cincinnati Lifetime 6.5 years Not stated -1.3 -0.1 Cigarette Birth Weight, Unspecified Maternal Child's Sex 

(13, L ,253) average - 72 Consumption Birth Length 

months during

Pregnancy 

Ç£
 

* L=Longitudinal cohort, X=Cross-sectional.** (ln)/(log10) = Original coefficient reported in log scale.

^ statistically significant (p < 0.05) 

 

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Table 6. Selected methodologic details from cohort studies

Quality Assurance Comments Study

Population Blood-lead Measurement Cognitive Function Measurement 

ÇÇ
 

Boston	 	 Samples were measured by capillary and venous and were analyzed by ASV and GFAAS. Blood (6, 7, 34)	 	 specimens for 6-, 12-, 18, and 24-month specimens were collected in capillary tubes by trained

technicians. Blood samples were assayed in duplicate or triplicate. The analytical system was calibrated with aqueous standards of known lead concentrations. Each batch of samples was accompanied by a blood sample of known lead concentrations to quantify intralaboratory reliability. Several standardized blood samples with lead concentrations also were included after they becameavailable in 1982 from CDC. (Rabinowitz, et al., 1985) 57-month venous blood samples were obtained.Lead was measured in duplicate by GFAAS. An aliquot of a standardized blood sample provided by theNational Bureau of Standards was included in each batch of samples. (Bellinger, et al.,1991) 

Cincinnati	 	 Samples were measured by venipuncture, heel stick, and finger stick for infants and were analyzed by 

(13)	 	 ASV. Blood samples were obtained using either venipuncture or heel stick. Approximately 72% of all 

samples are venipuncture. For heel stick, two capillary tubes were filled for duplicate PbB determination. If venipuncture was possible, pediatric vacutainer tubes were filled, one for PbB determination and a second for serum iron and total iron binding capacity (TIBC) analyses. Thesample was aliquoted and duplicate analyses performed according to a predetermined protocol usingASV. The laboratory participates in both the CDC and PA State Blood Lead and ProtoporphyrinPrograms. A series of bench-top QC samples and blind QC samples were analyzed with each run.(Bornschein et al., 1985) 

Cleveland	 	 Samples were measured by venous and were analyzed by GFAAS. Blood samples were collected in (14, 15, 16)	 	 heparinized plastic syringes which had been determined to be free of trace metals. The concentration

of lead in whole blood samples was determined by GFAAS. All samples were run in duplicate. Thewithin-run (same day) reproducibility was evaluated for a sample of adult whole blood. The obtainedvalues were 55.2 ug/dl, 1.34, and 2.4%, respectively, for the mean, SD, and coefficient of variation.Regular assessment of accuracy and precision using CDC samples of bovine blood were conducted and found to be within the certified range. Two inter-laboratory reviews were conducted for furtherdetermination of accuracy. Blood-lead levels were not adjusted for hematocrit. (Ernhart, et al., 1985)

Costa Rica	 	 Samples were measured by venous and were analyzed by GFAAS. Venipuncture samples were taken

(41)	 	 and red blood cells were promptly separated and frozen for future analysis in the U.S. The frozen red

cells were analyzed using GFAAS in a laboratory that participates in CDC's Maternal and Child HealthResources Development Proficiency Testing Program for Blood Lead. Quality control was monitored through certified controls obtained from the National Bureau of Standards. Red cell lead values wereconverted to whole blood-lead levels using the formula of Rosen et al.(1974).

Kosovo	 	 Samples were measured by venous and were analyzed by GFAAS. All blood specimens were (37, 38)	 	 refrigerated on site and transported on wet ice to Columbia University where all assays were 

performed. The laboratory participates in CDC's PBB QC program and is certified by OSHA. Over thestudy period, interclass correlation with QC values was computed, with correlation coefficients of .95 forPbB. 

Mexico City	 	 Samples were measured by venous and were analyzed by ASV. Samples were analyzed at (31)	 	 Environmental Sciences Associates (ESA) Laboratories, Inc., which is a CDC reference lab for the

Blood Lead Proficiency Testing Program and also participates in the New York State Department ofControl Program. All samples were analyzed using ASV. Samples with mean duplicate values < 5ug/dl were reanalyzed in duplicate by graphite furnace AAS. Mean values of the duplicates were used as data. (Rothenberg, et al., 1994) 

MDI was administered at 6-month intervals beginning at 6 months of age, by examiners blind to the infants’

lead levels. (Bellinger, et al., 1985) For WISC-R , most children were tested in a single session, 2 were seen

in a second session to complete testing, and 7 were tested in their homes by parental request. Psychologists

were blind to all aspects of child's developmental and lead exposure histories. 

For WISC-R, one experienced psychometrician performed all the assessments. Children were tested at a

pediatric clinic. The examiner was blind to the exposure levels of the child. For MDI, all assessments took

place in a prenatal and child welfare clinic. Psychometric tests were administered at an inner-city health clinic

by the study leader or trained assistant with whom inter-tester reliability had been previously established.

Testers were blind to children's blood-lead levels.

WPPSI, MDI, and Stanford Binet IQ tests were conducted by well-trained examiners blind to all risk and

background information. Home testing was used to control attrition, to minimize bias in attrition, and to

facilitate administration of the HOME Inventory. Inter-observer agreement was checked through observation

and duplicate scoring by a supervisor for approximately one out of every 26 examinations. Agreement was

maintained at r=.99. Answer sheets were checked for possible irregularities by the supervisor within a few

days of each administration.

Spanish versions of Bayley MDI and WPPSI were used in the assessment. A single tester, trained by one of

the primary investigators and the most senior research psychologist in the country, administered the 

assessments. The tester was blind to the children's iron status and never knew the blood-lead levels (these

were performed in the U.S.). (Lozoff, personal communication)

Three Yugoslavian psychologists scored the WISC-R and the McCarthy GCI independently. All interviews and

assessment instruments were translated and administered in the two dominant languages of the region, SerboCroatian and Albanian. Training and reliability visits occurred. The average interclass correlation for 96 tests

over study period was calculated.

Four trained psychologists blind to children's lead levels administered the McCarthy GCI. As there were no

norms for the McCarthy scale in the Mexican population, the U.S. norms were used to calculate GCI, with a

Spanish translation of the test. Interexaminer reliability was assessed by calculating the correlation in GCI

scores assigned by two of the psychologists with the scores of a third psychologist whom they observed

applying the test in all possible combinations with 10 subjects for each combination. Mean observer-examiner

correlation was .99. 
APPENDIX A:

LITERATURE REVIEW AND CLASSIFICATION UPDATE

A-1

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

The literature review began with the Agency for Toxic Substances and Disease 

Registry’s Toxicological Profile for Lead (ATSDR Tox Profile), published July 1999. 

The Health Effects chapter was thoroughly read and all articles relating to low 

blood lead levels in children were chosen, regardless of whether they demonstrated 

significant results. New literature searches were then performed by Battelle’s 

Technical Information Center. The year 1995 was chosen as the cutoff date for the 

new searches because the WG felt that, before this time, research rarely focused 

on BLLs <10 μg/dL, and that most relevant articles before 1995 were cited in the 

ATSDR Toxicological Profile. Searches were performed on a variety of databases 

using DIALOG and a set of keywords. 

The following is an example of the DIALOG, including databases and keywords: 

SYSTEM:OS - DIALOG OneSearch 

File 6:NTIS 1964-2003/May W3 (c) 2003 NTIS, Intl Cpyrght All Rights Res 

File 103:Energy SciTec 1974-2003/May B1 (c) 2003 Contains copyrighted material 

File 266:FEDRIP 2003/Mar Comp & dist by NTIS, Intl Copyright All Rights Res 

File 161:Occ.Saf.& Hth. 1973-1998/Q3 (c) Format only 1998 The Dialog Corp. 

File 156:ToxFile 1965-2003/May W2 (c) format only 2003 The Dialog Corporation 

File 155:MEDLINE(R) 1966-2003/May W2 (c) format only 2003 The Dialog Corp. 

File 162:Global Health 1983-2003/Apr (c) 2003 CAB International 

File 71:ELSEVIER BIOBASE 1994-2003/May W3 (c) 2003 Elsevier Science B.V. 

File 40:Enviroline(R) 1975-2003/May 

File 73:EMBASE 1974-2003/May W1 (c) 2003 Elsevier Science B.V. 

File 34:SciSearch(R) Cited Ref Sci 1990-2003/May W2 (c) 2003 Inst for Sci Info 

File 5:Biosis Previews(R) 1969-2003/May W2 (c) 2003 BIOSIS 

Set Items Description 

S1 512735 NATAL? OR PRENATAL? OR PERINATAL? OR POSTNATAL? 

S2 1244432 INFANT? ? OR INFANCY 

S3 2607491 CHILD? ? OR CHILDREN? ? 

S4 253558 LEAD/TI,DE,ID 

S5 184354 PB 

S6 68959 RN=7439-92-1 

S7 5798237 BLOOD 

S8 14048 (S1:S3) AND (S4:S6) AND S7 

S9 2153692 GROWTH/TI,DE,ID 

S10 31450 STATURE 

S11 634981 NUTRITION 

S12 169948 HEARING 

S13 200409 (RENAL OR KIDNEY)(3N)FUNCTION? 

S14 669012 BLOOD()PRESSURE 

S15 13 HEMESYNTHESIS 

S16 61334 HEMATOPOIESIS 

S17 20269 (VITAMIN()D)(3N)METABOLI? 

S18 1441 S8 AND (S9:S17) 

S19 438 S18 AND PY=1990:1996 

S20 422 S19/ENG OR (S19 AND LA=ENGLISH) 

S21 353 S20/HUMAN 

S22 190 RD (unique items) 

S23 190 Sort S22/ALL/PY,D 

A-3
 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

S24 19583 NEUROBEHAVIO?

S25 272980 NEUROLOGICAL?

S26 166224 NEUROLOGIC

S27 148942 NEUROTOXIC?

S28 15459 NEURODEVELOPMENT?

S29 7061 COGNITIVE()DEVELOPMENT

S30 2878983 BEHAVIOR? OR BEHAVIOUR?

S31 3 IMPULSITIVITY

S32 54987 HYPERACTIVITY

S33 10725 ADHD

S34 31451 IQ OR (INTELLIGENCE()QUOTIENT? ?)

S35 3350 WISC

Ref Items Index-term

E1 715223 *DC=A8.186. (Central nervous system)

E2 645734 DC=A8.186.211. (Brain)

E3 23250 DC=A8.186.211.132. (Brain stem)

S36 715223 DC=’A8.186.’:DC=’A8.186.211.132.’

S37 2936 (S8 AND (S24:S36)) NOT S18

S38 964 S37 AND PY=1990:1996

S39 941 S38/ENG OR (S38 AND LA=ENGLISH)

S40 808 S39/HUMAN

S41 415 RD (unique items)

This literature search was first run for the years 1995-2002. In spring, 2003, the 

search was rerun for the years 2002-2003 to determine the relevance of recently 

published articles. Also at this time, the search was rerun for the years 1990-1996 

for relevant articles that were not cited in the ATSDR Toxicological Profile. Titles 

and abstracts from each literature search were reviewed, and relevant articles were 

ordered for further review. Additional articles were identified while reviewing the 

selected articles and were added to the list of references, as were several articles 

recommended by workgroup members. 

The table below provides a summary of all the articles obtained from the various 

sources. This table shows when the search was performed, the years covered in the 

search, the number of articles found in the literature search, the number of articles 

ordered after the titles and abstracts had been reviewed, and the number of articles 

that were relevant for abstraction. 

A-4
 

 

 

 

Summary of Literature Review Results

Date of 

Search 

Years 

Covered 

Number 

of Unique 

References 

Found 

Number of 

reviewed for 

relevance 

Number of Articles 

Abstracted into the 

Database 

9/02 1995-2002 327 79 12

4/03 2002-2003 119 14 4a

5/03 1990-1996 605 25 4

ATSDR 

Tox Profile

Prior to 

1996 - 107 24

Referralsb various 10 12 6

Total: 235 50 

Relevant articles cited in Tables 2- 5 42 

aA 5th article, Stone et al. 2003, was obtained from this search and is not abstracted into the database but 

its relevance is discussed elsewhere in the report.

bReferrals include articles that were recommended by workgroup members, as well as those articles cited as 

references in studies identified in the ATSDR Tox Profile or literature searches.

A-5

APPENDIX B:

DISCUSSION OF CRITIQUE OF

NHANES III DATA BY STONE ET AL. (2003)

B-1

 

 

 

 

 

 

 

 

Stone et al. (2003) reanalyzed the data used by Lanphear et al. (2000). While 

the results they present are largely consistent with the findings of Lanphear et 

al. (2000), they provided a critique of the validity of the NHANES III data for 

evaluating lead-related impacts on neuropsychological development in children. 

Because their critique cuts across on neuropyschological measurements performed 

in the survey, the main points of their paper are summarized in this appendix, as 

follows. 

• Stone et al. note that the weighted mean values for the four measures used 

by Lanphear et al. are below the predicted mean based on standardization 

data for these tests collected in the early 1970s for the WISC-R) and early 

1980s for the WRAT. Stone et al. argue that the mean values should be 

higher than predicted by the standardization means because of secular 

improvements in cognitive test scores. One possible reason cited for the 

discrepancy is that NHANES tests were not administered by a psychologist. 

It is unclear, however, if the population sample used in the standardization 

data was equally representative of the U.S. population at that time or if 

changes in the population composition since then would lead to an increase 

or decrease in overall mean test performance. More importantly, it is unclear 

how a bias in mean score, even if real, and the use of non-psychologists for 

testing could produce associations between BLLs and test scores, given 

that examiners could not have known the BLLs of participants. If nonpsychologists produced less precise test results than psychologists would 

have, the expected impact on regression coefficients would be a bias toward 

the null. 

• The age-adjusted scores used in NHANES are correlated with age, and 

they should not be. Stone et al. show that age is negatively correlated with 

arithmetic, block design, and digit span and positively correlated with reading. 

However, since BLLs decrease with age across the age range studied, the 

negative correlations would tend to produce a trend towards higher scores with 

increasing blood lead for those tests, the opposite of the findings of Stone et al. 

• Imputation of missing covariate values was performed for a substantial 

proportion of observations in the analyses performed by Lanphear et al. 

While imputation could increase covariate mismeasurement and residual 

confounding, analyses presented by Stone et al. demonstrate essentially similar 

findings when analyses are restricted to observations with full rank data. 

• Relevant covariates, including whether a child has repeated a grade, 

whether interviews were in Spanish, and several other factors, were not 

included in analyses. However, two problems are evident in alternative “two 

stage” analysis provided by Stone et al. First, it uses predicted rather than 

residual blood lead level as an independent variable in a model relating 

blood lead to test scores. This amounts to testing the relation to test scores 

of a linear combination of covariates, many included in the model with test 

score as the outcome. In addition at least one variable – having to repeat 

a grade – is included as a covariate, possibly result serious over control as 

B-3
discussed earlier. Lead associated cognitive and behavioral effects have, not 

surprisingly, been associated with an increased risk of failure to complete 

high school. Thus, controlling for failure to complete a grade could amount to 

controlling for an effect of, rather than a confounder of the lead effect. 

As a whole, the Stone et al. critique of the NHANES III data do not provide a 

convincing argument that the findings reported by Lanphear et al. (2000) result 

from problems with the sample or testing methods. However, the WG did consider 

the limitations of the Lanphear et al. study, including its cross-sectional design 

and limited data on potential confounders. This study was weighed in the overall 

context of other relevant studies, including the more persuasive cohort studies, 

which are largely consistent with the associations Lanphear et al. report. 

B-4
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Table R-1. Numbered references used in Tables 2 through 6.

Reference 

Number First Author Publication Date Journal Title 

1 Altmann, L. 1997

Assessment of neurophysiologic and 

neurobehavioral effects of environmental 

pollutants in 5- and 6-year-old children

2 Altmann, L. 1998 Visual functions in 6-year old children in 

relation to lead and mercury levels

3 Alvarez Leite, E. M. 2002

Urinary homovanillic acid and serum prolactin 

levels in children with low environmental 

exposure to lead

4 Baghurst, P. A. 1992

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intelligence at the age of seven years. The Port 

Pirie Cohort Study

5 Ballew, C. 1999

Blood lead concentration and children’s 

anthropometric dimensions in the third 

National Health and Nutrition Examination 

Survey (NHANES III), 1988-1994

6 Bellinger, D. C. 1991 Low-level lead exposure and children’s 

cognitive function in the preschool years

7 Bellinger, D. C. 1992

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academic achievementμ a long-term follow-up 

study

8 Bergomi, M. 1989

Relationship between lead exposure indicators 

and neuropsychological performance in 

children

9 Bernard, A. 1995 Renal effects in children living in the vicinity of 

a lead smelter

10 Calderon, J. 2001

Exposure to arsenic and lead and 

neuropsychological development in Mexican 

children

11 Canfield, R. L. 2003 Intellectual Impairment in Children with Blood 

Lead Concentrations below 10 μg per deciliter

12 Cooney, G. H. 1989 Low-level exposures to leadμ the Sydney lead 

study

13 Dietrich, K. N. 1993

The developmental consequences of low 

to moderate prenatal and postnatal lead 

exposure: intellectual attainment in the 

Cincinnati Lead Study Cohort following school 

entry

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Table R-1. Numbered references used in Tables 2 through 6. (Continued)

Reference 

Number First Author Publication Date Journal Title 

14 Ernhart, C. B. 1987

Low level lead exposure in the prenatal and 

early preschool periods: early preschool 

development

15 Ernhart, C. B. 1988 Low level lead exposure and intelligence in 

the preschool years

16 Ernhart, C. B. 1989

Low level lead exposure in the prenatal and 

early preschool periods: intelligence prior to 

school entry

17 Factor-Litvak, P. 1996 Blood lead and blood pressure in young 

children

18 Gemmel, A. 2002 Blood lead level and dental caries in schoolage children

19 Hammond, P. B. 1985

Dose-effect and dose-response relationships of 

blood lead to erthryocytic protoporphyrin in 

young children

20 Hatzakis, A. 1987 Psychometric intelligence and attentional 

performance deficits in lead-exposed children

21 Kafourou, A. 1997 Effects of lead on the somatic growth of 

children

22 Lanphear, B. P. 2000 Cognitive deficits associated with blood lead 

concentrations 

23 McMichael, A. J. 1988

Port Pirie Cohort Study: environmental 

exposure to lead and children’s abilities at the 

age of four years

24 Mendelsohn, A. L. 1999 Low-level lead exposure and cognitive 

development in early childhood

25 Moss, M. E. 1999 Association of dental caries and blood lead 

levels

26 Munoz, H. 1993

Blood Lead Level and Neurobehavioral 

Development among Children Living in 

Mexico City

27 Rabinowitz, M. B. 1986 Occurrence of elevated protoporphyrin levels 

in relation to lead burden in infants

28 Rahman, A. 2002 Lead-associated deficits in stature, mental 

ability and behaviour in children in Karachi

R-15
 
 

 


 

Table R-1. Numbered references used in Tables 2 through 6. (Continued)

Reference 

Number First Author Publication Date Journal Title 

29 Roels, H. A. 1987

Evaluation of dose-effect and dose-response 

relationships for lead exposure in different 

Belgian population groups (fetus, child, adult 

men and women)

30 Rothenberg, S. J. 1999 Pre- and postnatal lead effect on head 

circumference: a case for critical periods

31 Schnaas, L. 2000

Temporal pattern in the effect of postnatal 

blood lead level on intellectual development 

of young children

32 Selevan, S. G. 2003 Blood lead concentration and delayed 

puberty in girls

33 Silva, P. A. 1988

Blood lead, intelligence, reading attainment, 

and behavior in eleven year old children in 

Dunedin, New Zealand

34 Stiles, K. M. 1993

Neuropsychological correlates of low-level 

lead exposure in school-age children: A 

prospective study

35 Tong, S. L. 1996

Lifetime exposure to environmental lead and 

children’s intelligence at 11-13 years: the Port 

Pirie cohort study

36 Walkowiak, J. 1998

Cognitive and sensorimotor functions in 

6-year-old children in relation to lead and 

mercury levels: adjustment for intelligence and 

contrast sensitivity in computerized testing

37 Wasserman, G. A. 1994

Consequences of lead exposure and iron 

supplementation on childhood development at 

age 4 years

38 Wasserman, G. A. 1997 Lead exposure and intelligence in 7-year-old 

children: the Yugoslavia Prospective Study

39 Winneke, G. 1990

Results from the European Multicenter Study 

on lead neurotoxicity in children: implications 

for risk assessment

40 Winneke, G. 1994

Neurobehavioral and neurophysiological 

observations in six year old children with low 

lead levels in East and West Germany

R-16
 

 

Table R-1. Numbered references used in Tables 2 through 6. (Continued)

Reference 

Number First Author Publication Date Journal Title 

41 Wolf, A. W. 1994

No Evidence of Developmental III Effects of 

Low-Level Lead Exposure in a Developing 

Country

42 Wu, T. 2003

Blood lead levels and sexual maturation 

in US girls: the Third National Health and 

Nutritional Examination Survey, 1988-1994

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