Infant Environmental

Exposure to Thimerosal

and Neuropsychological

Outcomes at Ages 7 to

10 Years

Technical Report

Volume I

Date 9-6-07

Prepared for

Immunization Safety Office

Centers for Disease Control and

Prevention

1600 Clifton Rd, NE

Atlanta, GA 30333

Prepared by

Cristofer Price

Barbara Goodson

Gerrie Stewart

Cambridge, MA

Lexington, MA

Hadley, MA

Bethesda, MD

Chicago, IL

Abt Associates Inc.

Suite 800 North

4550 Montgomery Avenue

Bethesda, MD 20814-3343
Abt Associates Inc. Technical Report – Volume I i

The interpretations of results presented in this report represent the

views of the authors and do not necessarily represent the views of

the Centers for Disease Control and Prevention (CDC).
Abt Associates Inc. Technical Report – Volume I ii

Acknowlegements

We have many people to thank for their contributions to this study. We thank the Clinic

Managers, Child Assessors, and Consulting Psychologists for their efforts and dedication

to obtaining high quality data. Clinic Managers: Jean Caiani, Ramon Campana,

Katherine Eng, Ph.D., Elle Garcia, Julie Gronouski, Joanne Melton, Victoria Mendez,

Judith Meyer, Valerie S. Miran, MA, Elizabeth Munoz, MSW, Diane G. Preciado, P. Ana

Silfer, MA, Child Assessors: Aimee L. Adray, Kathy Angell, Ph.D., Candace Wollard

Bivona, Ph.D., Karrie Campbell, Maureen O’Kane Grissom, Ph.D., Debbie Groff, Anne

E. Hay, Kerri Johnson, Psy.D., Darcey A. Reeves, Angela J. Stewart, Ph.D., Mery

Macaluso, Tracie Takeshita, Psy.D., Jolie C.von Suhr, Ph.D., Jennifer A. Wittert, M.A.,

Kevin Wittenberg, Ph.D., Christine Zalecki, Consulting Psychologists: Christine H.

Duong-Perez, Ph.D., Maury Eldridge, Ph.D., Susan Yuh Harrison, Ed.M., Kelly A.

Johnson, Ph.D., Robert Kretz, Psy.D., Stephanie Marcy, Ph.D., Denise Noonan, Ph.D.,

Mina D. Nguyen, Psy.D., Susan Toth Patiejunas, Ph.D., David Scott, Ph.D., T. Kristian

von Almen, PhD, Michael White, Ph.D.

Many thanks are given to the study’s External Expert Consultants who volunteered their

time to make substantive contributions to the study design, to review and comment on the

study’s analysis plan, to review progress reports, and to review and advise on next steps

after they were presented the results of preliminary results from the first round of fitting

the models specified in the analysis plan. External Expert Consultants: Ann Abramowitz,

Sallie Bernard, Lorne Garretson, Stanley Lemeshow, Roberta White, Robert Wright.

We wish to thank the Michael Shannon, Jane Bernstein, and Tom Campbell who

subcontracted to Abt Associates Inc. to provide the study with expertise in the areas of

toxicolology, neuropsychology, in speech and language development, respectively.

We wish to express special gratitude to our colleagues at the CDC and, the four HMOs

that participated in the study. These staff included Principal Investigators, Study

Managers and Data Managers who participated in countless phone conferences to discuss

study design, analysis plans, data quality, and interpretation of medical codes. They

brought a wealth of knowledge regarding vaccination and health care practices, child

development, data management, and research methodology. The shared dedication and

commitment among this group to obtaining high quality data, and producing the most

scientifically rigorous and useful study possible was inspiring. The group included:

GHC - Health Center for Health Studies, Seattle, WA

Patti Benson, M.P.H.

Lisa A. Jackson, M.D.

John Dunn, MD, M.P.H.

HPHC - Department of Ambulatory Care and Prevention, Harvard Pilgrim Health Care

and Harvard Medical School, Boston, MA

Virginia Hinrichsen, M.S., M.P.H.

Tracy Lieu, M.D.
Abt Associates Inc. Technical Report – Volume I iii

Xian-Jie Yu

NCK - Kaiser Permanente Kaiser Permanente Division of Research and Vaccine Study

Center, Northern California, Oakland, CA

Edwin Lewis, M.P.H.

Paula Ray, M.P.H.

Patricia Ross, S.

Steve Black, M.D.

SCK - UCLA - Southern California Kaiser Permanente, Torrance, CA

Eileen Eriksen, M.P.H.

Michael Marcy, M.D., M.P.H.

CDC - Immunization Safety Office, US Centers for Disease Control and Prevention,

Atlanta, GA

William W. Thompson, Ph.D.

Frank Destefano, M.D., M.P.H.

Robert L. Davis, M.D., M.P.H.

David Shay, M.D., M.P.H.

Eric S. Weintraub, M.P.H.

Thanks also to Bob Chen from the CDC for his support of the project.

And finally, we wish to thank our colleagues at Abt Associates Inc. who worked on the

project for their effort and dedication to the study. The list below summarizes the key

Abt staff that had substantive roles on the project:

Abt Associates - Abt Associates Inc., Bethesda, MD and Cambrige, MA

Patty Connor – Field Director

Carter Smith – Design phase

Amanda Parsad – Data analysis

Laura Simpson – Data analysis

Attina White – Data management

Julia Foodman – Data management

Kate Benson – Data management

Stephen Kennedy – Project Quality Advisor

Gerrie Stewart– Project Director

Barbara Goodson – Principal Investigator

Cristofer Price – Director of Analysis
Abt Associates Inc. Table of Contents iv

Volume I Table of Contents

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

2. Document Overview................................................................................................... 4

3. Background and Research Questions....................................................................... 5

3.1. Statement of the Problem............................................................................................ 5

3.2. Background on Mercury ............................................................................................. 5

3.3. Research on Neurotoxicity of Methylmercury .......................................................... 6

3.3.1. Neurological Effects of Children’s Dietary Exposure to Methylmercury .............................. 7

3.3.2. Mercury Exposure May Present Greater Risk for Infants....................................................... 9

3.4. Uses of Thimerosal in Vaccines.................................................................................. 9

3.5. Recommendation to Remove Thimerosal from Infant Vaccines........................... 10

3.6. Research on Neurotoxicity of Ethylmercury/Thimerosal....................................... 12

3.6.1.1. The CDC Research Program....................................................................................... 14

3.7. Research Questions for the Current Study.............................................................. 15

4. Study Design............................................................................................................. 16

5. Sample ...................................................................................................................... 17

5.1. Eligibility Criteria...................................................................................................... 19

5.2. Sampling Frame ......................................................................................................... 25

5.3. Sample Selection......................................................................................................... 26

5.4. Physician, Sibling, and Out-of-Area Exclusions...................................................... 27

5.5. Recruitment in Batches ............................................................................................. 28

5.6. Recruitment and Eligibility Outcomes..................................................................... 29

5.7. Size of Analysis Sample ............................................................................................. 30

6. Data Sources ............................................................................................................ 32

6.1. The Clinic Visit........................................................................................................... 32

6.1.1. Clinic Staff............................................................................................................................ 33

6.1.1.1. Training and Quality Control ...................................................................................... 34

6.1.2. Child Assessments................................................................................................................ 34

6.1.3. Parent Interview.................................................................................................................... 39

6.2. Teacher Mail Survey.................................................................................................. 39

6.3. Medical Record Abstractions.................................................................................... 39

6.4. VSD Computer-Automated Data.............................................................................. 40

7. Measures................................................................................................................... 41

7.1. Outcome Measures..................................................................................................... 41

7.1.1. Outcomes Measured on Continuous Scales.......................................................................... 41

7.1.2. Dichotomous Outcomes: Tics and Stuttering ....................................................................... 41
Abt Associates Inc. Table of Contents v

7.1.2.1. Tics.............................................................................................................................. 42

7.1.2.2. Stuttering..................................................................................................................... 43

7.2. Measures of Postnatal Exposure to Ethylmercury ................................................. 44

7.2.1. Introduction to the Vaccination Histories File...................................................................... 44

7.2.2. Overview of Steps from Raw Data to Creation of Analysis Variables................................. 45

7.2.3. Data Cleaning for Child Vaccination Histories .................................................................... 48

7.2.3.1. Step 1: Preliminary Vaccine History........................................................................... 49

7.2.3.2. Step 2: Application of 30-day and 15-day Algorithms................................................ 49

7.2.3.3. Step 3: Check, Verify or Fix ....................................................................................... 51

7.2.4. Mercury Amount Assigned to Each Childhood Vaccine or Immune Globulin Receipt ....... 58

7.3. Measures of Prenatal Exposure to Ethylmercury................................................... 60

7.3.1. Introduction to the Prenatal Ethylmercury Exposures File ................................................... 60

7.3.2. Overview of Steps from Raw Data to Creation of Analysis Variables................................. 61

7.3.3. Cleaning of Prenatal Ethylmercury Exposures Data............................................................. 62

7.3.4. Mercury Amount Assigned to Each Prenatal Vaccine or Immune Globulin Receipt........... 68

7.4. Covariates................................................................................................................... 71

7.5. Imputation of Missing Values................................................................................... 78

8. Analysis Approach ................................................................................................... 82

8.1. Overview of Analytical Models................................................................................. 84

8.2. Inclusion of Covariates.............................................................................................. 85

8.3. Testing for Effect Modifiers...................................................................................... 97

8.4. Multiple Testing ......................................................................................................... 97

8.5. Reporting Effect Sizes................................................................................................ 98

9. Results..................................................................................................................... 100

9.1. Descriptive Statistics................................................................................................ 100

9.1.1. Characteristics of the Analysis Sample .............................................................................. 100

9.1.1.1. Demographics ........................................................................................................... 100

9.1.1.2. Outcomes .................................................................................................................. 102

9.1.1.3. Exposures.................................................................................................................. 104

9.1.2. Descriptive Statistics on Variables Used in Analysis Models............................................ 109

9.2. Model Results........................................................................................................... 117

9.2.1. Overview ............................................................................................................................ 117

9.2.2. Main Effect Models............................................................................................................ 118

9.2.2.1. Introduction............................................................................................................... 118

9.2.2.2. Model Specifications................................................................................................. 118

9.2.2.3. Explanation of Model Results Summary Table......................................................... 119

9.2.2.4. Results....................................................................................................................... 120

9.2.2.4.1. Main Effect Models with Single Imputation for Covariates with Missing Values

120

9.2.2.4.2. Main Effect Models With Multiple Imputation for Covariates with Missing Values

123

9.2.2.4.3. Main Effect Models with Alternative Prenatal Mercury Amount Assignments.. 125

9.2.2.4.4. Additional Main Effect Models for ADHD Outcomes........................................ 127

9.2.3. Sex-by-Exposure Interaction Models ................................................................................. 129

9.2.3.1. Introduction............................................................................................................... 129

9.2.3.2. Model Specifications................................................................................................. 129

9.2.3.3. Results....................................................................................................................... 132

9.2.3.3.1. Prenatal Exposure ................................................................................................ 132
Abt Associates Inc. Table of Contents vi

9.2.3.3.2. Cumulative Exposure Birth to Seven Months...................................................... 132

9.2.3.3.3. Neonatal Exposure (Birth to 28 Days)................................................................. 133

9.2.4. Cumulative Effects of Exposures Spanning the Prenatal Period Though Age 7 Months... 136

9.2.4.1. Introduction............................................................................................................... 136

9.2.4.2. Model Specifications for Two Additional Hypothesis Tests..................................... 136

9.2.4.3. Results....................................................................................................................... 137

9.2.4.3.1. Joint Test for Additive Effect .............................................................................. 137

9.2.4.3.2. Test of Prental-by-Postnatal Exposure Interaction Effect.................................... 142

9.2.5. Models for Multiple Sources of Prenatal Exposure Interacted with Postnatal Exposure from

Thimerosal ........................................................................................................................................ 152

9.2.5.1. Introduction............................................................................................................... 152

9.2.5.2. Model Specifications................................................................................................. 154

9.2.5.3. Results....................................................................................................................... 155

9.2.6. Concurrent Antibiotics-by-Exposure Interaction Models................................................... 157

9.2.6.1. Introduction............................................................................................................... 157

9.2.6.2. Model Specifications................................................................................................. 157

9.2.6.3. Results....................................................................................................................... 160

10. References .......................................................................................................... 163
Abt Associates Inc. Table of Contents vii

Volume II Table of Contents
Abt Associates Inc. Chapter 1 1

1. Executive Summary

The current study was conducted to investigate whether there are relationships between

prenatal and/or early childhood exposure to thimerosal-containing vaccines and immune

globulins and neurodevelopmental functioning at ages seven to ten years. The study

utilized a retrospective cohort design wherein computerized medical records were used to

select a sample of children who had been exposed to varying amounts of thimerosalcontaining vaccines and immune globulins during infancy. The children were assessed at

ages 7 to 10 years using a battery of neurodevelopmental assessments administered in a

clinical setting. Results are based on data obtained from 1,047 study participants.

There are three major strengths of the study. The first is that we were are able to compute

accurate measures of each child’s prenatal and early childhood exposures to ethylmercury

from thimerosal-containing vaccines and immune globulins. We used three sources of

data on vaccination and immune globulin receipt to develop measures of exposure levels.

The first source was computer-automated records maintained by the HMOs as part of the

Vaccine Safety Datalink system and as part of their administrative record keeping

systems. The second source was from detailed abstractions of medical charts of children

and their mothers. These data were collected by a team of experienced chart abstractors.

The third source was from personal records and responses to survey items provided by

parents during a detailed interview with each child’s biological mother.

The second major strength of the study was that outcomes were measured in a clinical

setting using a battery of standardized assessment tools. Outcome measures spanned

domains of speech and language, verbal memory, reading achievement, fine motor

coordination, visual spatial ability, attention/executive functioning, behavior regulation,

tics, and general intellectual functioning.

The third major strength of the study is that we were able to obtain detailed information

for each child on potential confounding factors. These included data on other prenatal

and early childhood exposures, on other diagnoses and medical conditions of children

and their mothers, and on whole range of child and family characteristics. These included

income, maternal education, birth order, plurality, family size/structure, language spoken

in the home, maternal age, duration of breastfeeding, and maternal diagnoses of

neuropsychological disorders. These data were obtained from parent interview, from

medical record abstraction, and from the computer-automated records.

The primary weakness of the current study is that exposure levels were not determined in

a randomized, controlled trial (RCT) design. Although the study measured and controlled

for a wide range of potential confounders, it is impossible to know with certainty whether

the threat of selection bias has been eliminated. Selection bias will have affected the

results if one or more unmeasured factors have causal effects on both the amount of

exposure that children receive, and on outcome measures. Given this important limitation

of the design of the study, results can only be judged as informative, not conclusive. The

study was intended to be an important contribution to a growing literature regarding the
Abt Associates Inc. Chapter 1 2

possible effects of ethylmercury, and was not intended to be a definitive concluding

statement of whether the ethylmercury in thimerosal-containing vaccines and immune

globulins does or does not cause harm.

Associations between each of 42 outcome measures and exposure to thimerosalcontaining vaccines and immune globulins were estimated from linear and logistic

regression models that controlled for potential confounding effects of family

demographics and other factors. Models were fit to each of the 42 outcome measures to

estimate the effects of:

 Prenatal exposure;

 Neonatal exposure (cumulative exposure birth to one month);

 Birth to 7 months exposure (cumulative exposure birth to seven months);

 For males - Prenatal exposure;

 For males – Neontal exposure;

 For males – Birth to 7 months exposure;

 For females - Prenatal exposure;

 For females – Neontal exposure;

 For females – Birth to 7 months exposure;

 Interaction effects of prenatal exposure and cumulative exposure birth to seven

months;

 Interaction effects of antibiotic treatment concurrent with receipt of thimerosalcontaining vaccines or immune globulins birth to one month;

 Interaction effects of antibiotic treatment concurrent with receipt of thimerosalcontaining vaccines or immune globulins birth to seven months.

Across the models for the 42 outcome measures we found small numbers of statistically

significant effects that were roughly balanced between findings where increased exposure

was associated with better outcomes, and findings where increased exposure was

associated with worse outcomes. For example, in the model used to estimate main effects

on the combined group of males and females, higher prenatal exposure was associated

with better scores on one outcome measure, and worse scores on another. Cumulative

exposure birth to one month was associated with a better outcome on one measure, and a

worse outcome for another. Cumulative exposure birth to seven months was associated

with better outcomes for two measures. This pattern of results is consistent with what

would be expected to occur by chance if exposure had no relationship to outcomes. Using

a p<0.05 criterion, the expected number of false rejections of the null hypothesis for 42

tests for a single exposure measure (e.g., birth to seven months) is obtained as the product

of 0.05 and 42, which is equal to three. The three false rejections of the null hypothesis

are expected to be roughly equally distributed between positive and negative associations.

The pattern of finding small numbers of beneficial effects, approximately equally

balanced with findings of harmful effects was replicated over all sets of analyses. This

type of pattern was found for prenatal, neonatal (birth to 1 month) and birth to 7 months

exposure effects for the full sample, for boys, for girls, for interaction effects of prenatal

with birth to 7 months exposures, and for interaction effects of antibiotic treatment

concurrent with neonatal and birth to 7 months receipt of thimerosal-containing vaccines
Abt Associates Inc. Chapter 1 3

or immune globulins. For example, the evaluation of three exposure measures (prenatal,

neonatal, birth to 7 months) across the 42 outcome measures, for each of the two sexes

required 152 hypothesis tests. Among those tests, 13 were significant at the p<0.05 level.

The associations were in the direction of increased exposure being associated with better

outcomes for seven of the significant tests. The remaining five were in the direction

worse outcomes. Under a null hypothesis of no association between exposure and

outcomes, the expected number of false rejections of the null hypothesis for 152 tests at

the p<0.05 level is 13.

Results of two large studies conducted in Great Britain indicated mixes of beneficial and

harmful associations between exposure to ethylmercury from vaccines and outcomes

similar to those measured in the current study (Heron et al., 2004; Andrews et. al, 2004).

Results from the current study showing significant associations between exposures in

birth to 7 months and assessor rated motor and phonic tics in boys appear to support two

sets of findings from previous studies. The study by Verstraeten et al (2003) found a

significant association between exposure and tics at one of three HMOs. And Andrews et

al. (2004) found a significant harmful association between exposure and tics in a special

sub-analysis. However, Heron et al. (2003) reported a beneficial association between

exposure and tics. And among the findings of the current study was a beneficial

association between parent reported motor tics and neonatal exposure for girls.

The beneficial associations between exposures and outcomes in the fine motor domain

found in the current study coincide with a finding reported by Heron et al. (2003) of a

beneficial association between exposure and fine motor skills. However, these findings

do not align with the estimated harmful effects of methylmercury exposure from fish

consumption on performance on the finger tapping test, as reported by Grandjean et. al.

(1997).

The results of models used to test interaction effects between prenatal and postnatal

exposure did not support the hypothesis that prenatal exposure would exacerbate the

effects of postnatal exposure. Nor did the results of this study support the hypothesis that

antibiotic treatment would worsen the effects of postnatal exposure.

We conclude that we did not find clear and convincing evidence of harm. While studies

of the sort conducted here cannot disprove the null hypothesis, we consider the pattern of

positive and negative associations to be consistent with what we would expect to occur

by chance if exposure had no relationship to outcomes. We note, however, that the

previously stated caution regarding the threat of selection bias should not be ignored. We

urge the reader to consider the results of this study as one piece of evidence in the context

of a growing literature on the effects of exposure to ethylmercury.
Abt Associates Inc. Chapter 2 4

2. Document Overview

The current document is intended to present both study results and the technical details of

study design, sampling, data sources, variable construction, and methods of analysis. This

document allows for a more complete presentation of details than was possible within the

space constraints on the presentation of the same study published by Thompson et. al. (in

press, 2007).

Section 3 presents the historical factors that motivated the study, some background on

mercury exposure and its effects on neurological development, the history and use of

thimerosal in vaccines, a brief review of the literature on thimerosal and

neurodevelopmental outcomes, an introduction to the Centers for Disease Control’s

research program on thimerosal and vaccines, and the study’s motivating research

questions. Sections 4, 5, and 6 describe the study’s design, sample, and data sources.

Section 7 presents detail on the construction of outcome measures, exposure measures,

and covariates. This section also includes an explanation of imputations of missing values

on covariates. Section 8 describes the analysis approach. Section 9 presents results.

Included in Section 9 are descriptive statistics that describe the characteristics of the

study participants and their amounts of exposure to ethylmercury from thimerosalcontaining vaccines and immune globulins. The latter part of Section 9 presents

summaries of the results of models used to estimate the size and statistical significance

of associations between neurodevelopmental outcomes and exposure to ethylmercury

from thimerosal-containing vaccines and immune globulins.
Abt Associates Inc. Chapter 3 5

3. Background and Research Questions

3.1. Statement of the Problem

During the 1990s the nation's childhood immunization rates increased dramatically.

While the overall immunization rate for preschool children was approximately 55 percent

in 1992, it rose to 79 percent in 2000. Over approximately the same time period, the

recommended number of vaccines to be received by a child during the age range from

birth through seven months more than doubled. In 1988, a child immunized according to

the recommended schedule1 would have received three DTP vaccines and two polio shots

during his/her first seven months of life. By 1999, a child immunized according to the

recommended schedule would have received as many as three hepatitis-b vaccines, three

DTaP vaccines, three Hib vaccines, and three polio shots during his/her first seven

months. Over the same approximate time frame the rates of diagnoses of a range of

neurodevelopmental diseases such as autism and attention hyperactivity deficit disorder

(ADHD) increased dramatically (Mandell et. al., 2005; Newschaffer et. al, 2006).

Until the phase-out of thimerosal-containing childhood vaccines that began in 1999,

many of the regularly administered infant vaccines contained mercury. Thimerosal,

which had been used as a preservative in vaccines since the 1930s, is 49.6% mercury by

weight and is metablolized into ethylmercury and thiosalicylate.

In 1999, the U.S. Food and Drug Administration (FDA) estimated that adherence to the

schedule of immunizations recommended by the Advisory Committee on Immunization

Practices (ACIP) could result in ethylmercury exposure that exceeded the Environmental

Protection Agency’s (EPA) limits for methylmercury exposure. At the time, there was

little known about similarities or difference in the metabolism and excretion of these two

forms of mercury, but the chemical similarities of the two, combined with the known

toxic effects of exposure to methylmercury, was cause for alarm.

Consequently, the U.S. Public Health Service and the American Academy of Pediatrics

urged vaccine manufacturers to removed thimerosal from all infant vaccines as soon as

possible, and recommended that studies be carried out to assess the risks associated with

exposure to mercury from thimerosal-containing vaccines.

3.2. Background on Mercury

Mercury is an element that cycles through three different chemical forms in the

environment: methylmercury, ethylmercury, and phenylmercury. Research has

confirmed that determination of the toxicity of mercury is complicated and dependent on

the form of mercury, route of entry, dose, and age at exposure (AAP, 1999). Humans are

exposed to mercury in its different forms from various sources. Modern industrial

1 The vaccine schedule recommended and approved by the Advisory Committee on Immunization Practices

(ACIP), the American Academy of Pediatrics (AAP), and the American Academy of Family Physicians

(AAFP).
Abt Associates Inc. Chapter 3 6

processes, especially fossil fuel combustion and waste incineration, are responsible for a

recent dramatic increase in environmental levels of methylmercury. The major source of

non-occupational methylmercury exposure is dietary intake, with fish and seafood as the

main sources because of their propensity to bioaccumulate mercury up the food chain.

Vaccinations are the major source of exposure to ethylmercury, because the Thimerosal

used as a preservative contains 49.6 percent mercury by weight and is metabolized to

ethylmercury and thiosalicylate (AAP, 1999; Pless and Risher, 2000).

The major impact of organic mercury compounds is on the central nervous system,

although the kidneys and the immune system also may be affected. Furthermore, organic

mercury easily crosses placenta and blood-brain barriers (AAP, 1999). Although the

CDC and others have recently made strides in understanding the effects of the

ethylmercury in Thimerosal-containing vaccines, the exact nature of toxicity and

neurodevelopmental effects from exposure are essentially unknown. At doses

considerably higher than what the children would be exposed to from a normal schedule

of vaccines, ethylmercury has been reported to cause neurotoxicity, but the effects of

exposure to low concentrations have not been established (Ball et al., 2001).

Much of the concern about the potential hazards of ethylmercury comes from research on

the effects of mercury in the form of methylmercury. Below we summarize the research

on methylmercury neurotoxicity and present the argument for its relevance to concerns

about possible ethylmercury toxicity from Thimerosal exposure.

3.3. Research on Neurotoxicity of Methylmercury

Research on the adverse effects of human mercury exposure dates to the 1950s, when the

consumption of fish contaminated by industrial waste in the Minamata Bay region of

Japan was linked to an epidemic of severe neurological disease (Harada, 1995). A

similar epidemic occurred in Iraq in the 1970s from consumption of mercury-containing

fungicide in seed grain (Bakir et al., 1973; Marsh et al., 1980). In both these outbreaks

mercury poisoning was documented in all age groups, but infants seemed particularly

vulnerable, and maternal methylmercury exposure was associated with nervous system

abnormalities, such as mental retardation and impaired motor function among children

exposed in utero. In the Minamata epidemic, some infants with severe brain damage

were born to exposed mothers who were themselves barely affected. Similar effects on

infants were seen in the Iraqi outbreak, which also raised questions about more subtle,

delayed effects of prenatal exposure. These epidemics provided strong evidence linking

exposure to high levels of methylmercury with severe neurological damage, and also led

to the confirmation of mercury as a neurotoxicant and to the establishment of early

exposure guidelines.

Concern about the potential health threat from methylmercury grew in the early 1970s

when elevated concentrations were found in fish from the Great Lakes. Inorganic

mercury released into large bodies of water is converted to methylmercury by

microorganisms and bioaccumulated up the aquatic food chain (Davidson et al., 1998;

Mahaffey, 1999). Accumulation of mercury in fish can result in increased human
Abt Associates Inc. Chapter 3 7

exposures to this metal, particularly in populations whose diets include a high intake of

marine food (Turner et al., 1980).

Recently, increased attention has focused on what levels of exposure to methylmercury

can be considered safe. Agencies such as the World Health Organization (WHO), the

U.S. Environmental Protection Agency (EPA), the U.S. Agency for Toxic Substances and

Disease Registry, and the U.S. Food and Drug Administration (FDA) provide

recommendations for safe exposure to methylmercury in the diet; suggested “safe” levels

range from 0.7 μg/kg bodyweight/week (EPA) to 3.3 μg/kg bodyweight/week (WHO)

(Clements et al., 2000). Most recommendations for methylmercury exposure limits are

based on data from the Iraqi epidemic (Bakir et al., 1973; Marsh et al., 1980), but because

the exposures in Iraq were about six months in duration and at high concentrations,

questions remain about generalizing the effects of this exposure period and concentration

level (Mahaffey, 1999). Recently, however, epidemiological studies of lower levels of

methylmercury exposure have begun to emerge, heightening concern over potential

effects of chronic, low level exposure to methylmercury, particularly for children

exposed prenatally from maternal fish consumption.

3.3.1. Neurological Effects of Children’s Dietary Exposure to

Methylmercury

In 1998, conflicting findings from two seminal studies on the effects of children’s dietary

exposure to methylmercury prompted the White House Office on Science and

Technology Policy (OSTP) to convene a multi-agency scientific review of risks

associated with chronic, low levels of methylmercury exposure (National Institute of

Environmental Health Sciences, 1998). Both of these studies, located in vastly different

geographic areas, one in the Seychelle Islands in the Indian Ocean (Davidson et al., 1998)

and the other in the Faroe Islands in the North Atlantic (Grandjean et al., 1997), are

longitudinal examinations of children’s neuropsychological functioning after prenatal

exposure to methylmercury, in which mothers were enrolled in the studies during

pregnancy and their child’s development was followed into elementary school.

Both the Faroese and Seychellois consume a steady fish diet; the Faroese also consume

intermittent meals of pilot whale muscle. Despite comparable mercury levels from

maternal hair samples in the two populations—a geometric mean of 4.3 ppm in the Faroe

Islands (Grandjean, et al., 1997) and an arithmetic mean of 6.8 ppm in the Seychelles

(Davidson, et al., 1998)—investigators came to opposite conclusions about the effects of

mercury exposure on children’s intellectual functioning. In the Seychelle Islands, a

preliminary pilot study revealed effects of prenatal methylmercury exposure on several

neurobehavioral assessments, but the researchers discounted these results when the

exclusion of four “outlier” cases from the analysis dropped the effects below statistical

significance and because the pilot failed to include potential socioenvironenmental

confounding variables (Myers et al., 1995). In the subsequent main study, researchers

found no association between 5.5-year-olds’ performance on global assessments of

intellectual functioning and mercury exposure measured in maternal hair samples

(Davidson et al., 1998). In contrast, Faroe Islands investigators reported that each
Abt Associates Inc. Chapter 3 8

doubling in prenatal mercury exposure corresponded to a delay of one to two months in

mental development at age seven (Grandjean et al., 1997).

In an attempt to account for these divergent findings, the OSTP panel identified five

major differences between the studies (Jacobson, 2001). First, the determination of

mercury exposure in the Faroe Islands study included measurement of the concentration

of methylmercury in umbilical cord blood, which primarily indicates exposure occurring

during the last trimester, a time of relatively rapid neuronal development. In the

Seychelles Islands study, the measure of mercury exposure was limited to maternal hair

samples, which reflect exposure over the entire pregnancy. Second, children in the

Seychelles Islands study were assessed at 5.5 years, an age during which rapid

developmental change and substantial individual differences in maturation may mask

neurodevelopmental delays, whereas children in the Faroe Islands study were assessed at

age 7, a time of relative developmental stability (Jacobson and Jacobson, 1991). Third,

the assessments used in the Faroe Islands study were targeted at specific domains of

neuropsychological functioning, including measures sensitive to particular aspects of

function in language, memory, and attention, in contrast to more global measures of

cognitive functioning used in the Seychelles study. Thus, the measures and timing of

assessments in the Faroes study may have been better suited to detect an association

between exposure and neurodevelopmental delays. In addition to these methodological

differences, panelists identified two potentially important environmental differences.

First, the Seychellois’ steady diet of fish the Faroese diet includes intermittent

consumption of pilot whale meat, a source of methylmercury concentrations 10-20 times

stronger than those in fish (Grandjean, et al., 1992). Second, because environmental

contaminants tend to be transported northward along prevailing currents, the North

Atlantic region in which the Faroe Islands are located is subjected to much stronger

concentrations of polychlorinated biphenyls (PCBs) than the Seychelles Islands in the

Indian Ocean. Some panelists suggested that prenatal methylmercury exposure may

affect neurodevelopment only in the presence of significant PCB exposure (Jacobson,

2001).

The OSTP panel concluded that uncertainty remained over low levels of methylmercury

exposure from fish (NIEHS, 1998). Subsequently, however, a National Academy of

Sciences panel conducted further examination of these same two studies in conjunction

with other data not considered by the OSTP panel. The NAS panel’s findings cast doubt

on the explanations offered to account for differences in the Faroese and Seychellois

findings.

Specifically, the NAS panel evaluated the findings in light of a New Zealand study

conducted in the 1980s but published without formal peer review (Kjellstrom et al.,

1989). Though similar in methodology to the Seychelles Island study, the New Zealand

investigators did find effects of methylmercury. As in the Seychelles study, the New

Zealand study: used maternal hair samples to measure methylmercury exposure; included

a global assessment of intelligence; and focused on a population likely exposed to very

low levels of PCBs. Moreover, the New Zealand study tested children close in age (i.e.,

six-year-olds) to the 5.5-year-olds in the Seychelles. Finally, the diet of the New
Abt Associates Inc. Chapter 3 9

Zealanders was similar to that of the Seychellois, in that neither population consumed

whale meat; thus, the episodic peak doses of high levels of methylmercury among the

Faroese could not account for the differences in the conclusions of the two islands

studies. In light of these findings, arguments that research design differences between the

Faroese and Seychellois studies could account for their conflicting conclusions were

deemed no longer persuasive (National Research Council, 2000). Further analysis by the

NAS panel suggested that the Seychelles study may have lacked sufficient power to

detect the relatively small effect sizes computed for the Faroe Islands data (NRC, 2000;

Jacobson, 2001).

Because the data from all three studies more likely represent the typical exposure

scenario of North American populations than did the Iraqi experience, the NAS panel

recommended that the EPA compute a new reference dose for methylmercury. In light of

their evaluation of the Faroese, Seychellois and New Zealand studies and the burden of

preventing potential risks to public health, the NAS panel argued that the positive

findings from the Faroe Islands data be accorded more weight than the lack of findings

among the Seychellois cohort. Nevertheless, the NAS panel could not fully account for

the lack of findings in the Seychellois studies.

3.3.2. Mercury Exposure May Present Greater Risk for Infants

Despite unresolved differences in the findings of the Faroese and Seychellois studies,

scientific review indicates general concern over the health effects of human exposure to

even low levels of mercury, particularly for infants. The developing fetus and young

children may be disproportionately affected by mercury exposure because many aspects

of development, particularly brain maturation, can be disturbed by the presence of

mercury (Mahaffey, 1999). Because newborns may have decreased ability to both

oxidize and eliminate mercury (Goldman et al., 2001), the resulting higher concentrations

of unoxidized mercury for longer durations than would typically be found in adults could

lead to toxic levels of accumulation. In addition, the primary way that the body gets rid

of mercury is through bile, which infants do not produce (AAP, 1999). Also, the long

half-life of methylmercury (average 50 days) results in accumulation that could be

harmful to the developing fetal brain, which is much more susceptible to organomercurial

compounds than is the adult brain (Choi, 1989).

3.4. Uses of Thimerosal in Vaccines

Thimerosal is necessary for use as a preservative only when the vaccine is packaged in a

multi-dose vial. In this circumstance, the thimerosal acts as a preservative to protect the

remaining doses of the vaccine from bacterial and fungal contamination after a single

dose is administered. Although in the United States multi-dose vials are currently not

being used for vaccines administered as part of the recommended childhood

immunization schedule, they remain the only option in many parts of the developing

world, as they are less expensive and require less storage space (Ball et al., 2001).
Abt Associates Inc. Chapter 3 10

In the late 1990s, childhood vaccines that contained thimerosal included hepatititis-b

(HepB) vaccines , diphtheria-pertussis-tetanus (DPT) vaccines, some Haemophilus

influenzae type b (HiB) vaccines, and the influenza vaccine. An additional potential

source of mercury exposure was from receipt of hepatitis B immune globulins. Polio and

measles-mumps-rubella vaccines did not contain thimerosal.

In addition to the postnatal sources of thimerosal, in utero exposure was possible via

administration of thimerosal-containing preparations administered to mothers during

pregnancy. These included the influenza, tetanus, hepatitis B, and diphtheria-tetatnus

vaccines, and anti-Rh immunoglobulins, which is used to suppress Rh-sensitization in

Rh-negative mothers who give birth to Rh-positive babies.

In addition to its use as a preservative, thimerosal is used as an inactivating agent in the

manufacture of certain vaccines, and as a bacteriostatic agent during the production

process of other vaccines (Ball et al., 2001). Its use in manufacturing and production

processes, however, contributes little to the final concentration of ethylmercury in a

single vaccine. In the 1990s, receipt of a hepatitis B vaccine would result in exposure to

12.5 micrograms of ethylmercury from the thimerosal used as a preservative. Most DTP

and Hib vaccines in use at that time would have resulted in exposure to 25 micrograms of

ethylmercury from the thimerosal used as a preservative, for each receipt. In contrast,

thimerosal’s use in manufacturing and production results in, at most, exposure to 0.25 to

0.75 micrograms of ethylmercury per vaccine receipt (Ball et al., 2001)2.

3.5. Recommendation to Remove Thimerosal from Infant

Vaccines

In July of 1999 the U.S. Public Health Service and the American Academy of Pediatrics

issued a joint statement which established the goal of removing thimerosal as soon as

possible from vaccines customarily recommended for infants (AAP, 1999). Until

sufficient supplies of thimerosal-free vaccines were available, recommendations were

made to postpone the first hepatitis B (HepB) vaccine dose until two to six months of age

for infants born to hepatitis B-negative women, to avoid exposing newborn children to

ethylmercury at a time when they were especially vulnerable to neurotoxicity because of

their small body mass and their inability to excrete the ethylmercury effectively.

Pediatricians were further advised that the use of thimerosal-containing vaccines was

preferred to withholding vaccinations if no alternative was available

At the time of the recommendation, little was known about the toxicity of ethylmercury

and a review by Ball et al., (2001) revealed no evidence of harm caused by the doses of

thimerosal found in vaccines, except for local hypersensitivity reactions. That is, when

vaccines containing thimerosal had been administered in recommended doses,

hypersensitivity had been noted, but no other harmful effects had been reported (CDC,

2000). The case against ethylmercury was made primarily on the basis of the data on the

2 Ball et. al (2001) report that these processes result in a maximum of 2-3 micrograms of thimerosal / mL.

Thimerosal is 49.6% mercury by weight. Multiplication of of relevant terms yields an estimate of 0.5 – 0.75

micrograms of mercury per 0.5 mL dose.
Abt Associates Inc. Chapter 3 11

toxicity of methylmercury and clinical similarities between cases of ethyl- and

methylmercury poisoning.

Two ethylmercury epidemics in Iraq in the 1960s were remarkably similar to the

methylmercury epidemics that occurred there in the 1970s: victims had consumed grain,

or animals fed grain, that had been improperly treated with an ethylmercury-containing

fungicide (Damluji, 1962; Jalili and Abbasi, 1961). The range of symptoms reported

included difficulty walking, ataxia, other motor function impairment, speech disorders,

and visual field constriction. In addition to such dietary exposure, there are also reports

of neurologic symptoms in patients who received large overdoses of ethylmercury from

medicinal preparations (e.g., Axton, 1972; Fagan et al., 1977; Lowell et al., 1996). For

example, a liver transplant patient given high doses of hepatitis-B immunoglobulins in

preparations containing thimerosal developed speech articulation difficulties, general

slowing of motor movements, and an inability to walk; chelation therapy eliminated these

symptoms within four to five weeks (Lowell et al., 1996). Interestingly, hair samples

indicated that he had had prior environmental exposure to mercury, though from an

undetermined source.

Although ethylmercury, in sufficiently high doses, has neurotoxic properties similar to

those of methylmercury, the relative toxicities of ethylmercury and methylmercury had

not been well established (Ball et al., 2001). At the time of the recommendation for

removal of thimerosal, the effect of intermittent intramuscular doses of thimerosalcontaining vaccines on neurodevelopmental outcomes had not been studied. One study

did measure the effect of a single dose of a thimerosal-containing HepB vaccination,

administered within three days of birth, on infants’ blood-mercury levels. With one 0.5

mL dose of the vaccine (approximately 12.5 μg of mercury), the mean mercury blood

level increased from . 54 to 7.36 μg/L in 15 preterm infants and .04 to 2.24 μg/L in five

term infants. These were statistically significant increases (Stajich et al., 2000).

Therefore, a birth dose of the hepatitis B vaccine may measurably increase infant blood

mercury levels.

Calculations of the maximum potential exposure to ethylmercury from recommended

childhood immunization schedules in effect in the 1990s suggest that infants could

receive total doses of ethylmercury in excess of various agencies’ exposure limits for

methylmercury during the first six months of life (Ball et al., 2001). The exact dosage of

thimerosal received depended on the vaccine schedule followed by the child and the

manufacturer of the vaccine, but a worst-case scenario would be an infant who received a

series of vaccinations resulting in a maximum exposure to ethylmercury by age six

months that could reach approximately 187.5 μg. With limits for safe methylmercury

exposure between 34 and 159 μg, this suggested that some infants may have received

doses of mercury from vaccines that may have been of concern (WHO, 2000). An

additional issue was that infants may not eliminate mercury as efficiently as older

children or adults (Goldman et al., 2001).
Abt Associates Inc. Chapter 3 12

3.6. Research on Neurotoxicity of Ethylmercury/Thimerosal

Subsequent to the recommendation to remove thimerosal from childhood vaccines

several studies have been published that focus on the relationships between exposure to

ethylmercury from thimerosal-containing vaccines and neurodevelopmental outcomes of

children. These include studies by Verstraeten et al. (2003), Hviid et. al. (2003), Geier

and Geier (2003a, 2003c, 2003c, 2004, 2005, 2006a, 2006b), Heron et. al. (2004),

Andrews et. al. (2004), and Fombonne et al. (2006).

The study by Verstraeten et al. (2003) calculated measures of exposure and outcomes

using computerized records of three large HMOs. These records were developed and

maintained as part of the Vaccine Safety Datalink (VSD) system, and as part of

administrative record keeping systems. Three measures of exposure were calculated from

the computerized records of vaccine receipts. These were cumulative mercury exposure

from birth to 1 month, cumulative mercury exposure from birth to 3 months, and

cumulative mercury exposure from birth to 7 months. Outcome measures were obtained

from ICD-9 codes3and were coded as the presence/absence of diagnoses of

neurodevelopmental disorders. Outcomes included autism, “other child psychosis”,

stammering, tics, sleep disorders, eating disorders, emotional disturbances, ADD,

developmental language delay, developmental speech delay, speech or language delay,

and coordination disorder. Results were reported separately for each of the three HMOs.

The study reported no significant associations between outcomes and 1-month

cumulative exposure for any of the three HMOs. Significant findings were reported for

associations between 3-month cumulative exposure and tics at one HMO, and 3-month

exposure and language delay at a second HMO, and between 7-month cumulative

exposure and language delay at the same HMO.

The study had several important design weaknesses. First, it relied on physician

diagnosis of childhood neurodevelopmental delays and other developmental outcomes,

rather than a standardized assessment of children’s developmental status. Physician

diagnosis is likely to introduce unreliability in the outcome measures, since different

physicians may be using different criteria for classifying children as developmentally

delayed or as demonstrating behavioral problems such as ADHD. Second, using

physician diagnosis introduces the possibility of bias in the measurement of child

outcomes, since children from families that are more attentive to seeking health care may

be both more likely to receive a diagnosis and more likely to have received all of his/her

vaccinations on time, thus potentially having higher ethylmercury exposure. Third, the

study did not have family demographic information and therefore the analyses could not

control for factors known to be associated with the outcomes.

The study by Hviid et al. (2003) used computerized records corresponding to all children

born in Denmark over the period January 1, 1990 to December 31, 1996, to estimate the

relative risk of autism corresponding to cumulative ethylmercury exposure amounts of 0,

25, 75, and 125 micrograms. No significant associations were reported.

3

ICD-9 = International Classification of Diseases, Nineth Revision, Clinical Modification.
Abt Associates Inc. Chapter 3 13

Each of the Geier and Geier (2003a, 2003c, 2003c, 2004, 2005, 2006a, 2006b) studies

reported finding associations between thimerosal-containing vaccines and

neurodevelopmental disorders. However, the Institute of Medicine (IOM) (2004),

characterized the first four of those studies (2003a, 2003c, 2003c, 2004) as having serious

methodological limitations that render the results uninterpretable. Parker et. al, (2004)

also identifies multiple methodological concerns with the same studies. Like the earlier

studies, the latter three papers (2005, 2006a, 2006b) report results of analyses of the

Vaccine Adverse Events Reporting System (VAERS) database. Detailed descriptions of

potential biases and pitfalls that could arise from attempting to use the VAERS data to

make causal inferences are provided in IOM (2004) and Parker et. al (2004).

In addition to the results from analysis of VAERS data, the Geier and Geier (2005) paper

reports results from analyses of VSD data. Although the authors of the Geier and Geier

(2005) paper claim to have analyzed the VSD data as independent researchers, major

sections the text and several tables match almost identically to text and tables included in

a preliminary draft of the Verstraeten et. al. paper, described above4.

The results reported by Heron et al (2004) were based on a study of over 13,000 children

in the United Kingdom. Exposure data came from the Bristol-based Child Health

Surveillance Database. Outcome measures were created from maternal responses to the

Strengths and Difficulties Questionnaire and the Child Behavior Checklist (behavior

ratings), the Revised Denver Scale (fine motor development) and from other items in the

maternal questionnaire (speech problems, tics, and special needs). Results of 69

hypothesis tests (23 outcomes times 3 exposure measures) from models that controlled

for birth weight, gestation, maternal education, and other demographic characteristics of

the child and family indicated nine significant associations between exposures and

outcomes. One was in the direction of increased exposure being related to harm, the

remaining 8 were in the direction of benefit. Poor prosocial behavior at 47 months of age

was associated with higher 3-month exposure. Outcomes with associations in the

direction of benefit were conduct problems, fine motor skills at 30 months of age, tics at

91 months of age, and two measures that are each indicators that the child has special

needs. Several of these 5 beneficial outcomes had significant associations with two

exposure measures, totaling 8 significant hypothesis tests.

The results reported by Andrews et al. (2004) were based on data obtained from over 103

thousand children. Exposure and outcome data were extracted from computerized

medical records. Outcome measures were created from ICD-9 codes. Confounder

variables used in their statistical models included gender, year of birth, and when

significant, month of birth. They reported beneficial associations between increased

exposure and general developmental disorders, ADD, speech or language delay, and

4 Early pre-publication write-ups of the Verstraeten et. al. analyses obtained via the Freedom of Information

act were posted on a web site and, at the time of this writing, are currently available on the web. See

Verstraeten et. al. (2000) for details. For criticism regarding the differences in findings between preliminary

and final analyses conducted by Verstraeten et. al. see Redwood (2004). For a response to criticism, see

Verstraeten (2004).
Abt Associates Inc. Chapter 3 14

unspecified developmental delay. In a special sub-analysis that excluded children who

had not received all three recommended DTP vaccinations by one year of age, a

significant harmful association between increased exposure and tics was found. In the full

data set, the estimates for tics were in the harmful direction, but not statistically

significant.

Fombonne et al. (2006) estimated the prevalence of pervasive developmental disorder

(PDD) in cohorts of children in Montreal Canada over a span of time that included the

removal of thimerosal from childhood vaccines. They reported a statistically significant

linear trend in the prevalence of PDD during the study period. They also reported that the

prevalence of PDD in thimerosal-free birth cohorts was significantly higher than that in

thimerosal-exposed cohorts. They concluded that thimerosal exposure was unrelated to

the increasing trend in PDD prevalence in Montreal Canada.

3.6.1.1. The CDC Research Program

To study the potential health risks of thimerosal in vaccines, the CDC has utilized data

from a vaccine safety monitoring project (the VSD) and has mounted a program of

research that includes a series of studies.

The CDC established the VSD Project in 1990 to improve the capability to study side

effects of vaccines through large-linked databases of computerized vaccination and

medical records. This project involves partnerships with several large HMOs to

continually monitor vaccine safety. The database includes information on more than six

million people. All vaccines administered within the study population are recorded, as

well as data on vaccine type, date of vaccination, concurrent vaccinations, manufacturer,

lot number, and injection site. Records are monitored for potential adverse events

resulting from immunization.

The first in the CDC’s series of studies on health effects of exposure to thimerosal was

the screening study by Verstraeten et al. (2003), described previously. The intent of this

study was to determine if there were any adverse associations that could be subsequently

investigated using more rigorous study designs.

The next three studies in the CDC’s series of investigations were:

 The Infant Environmental Exposures and Neurodevelopmental Outcomes at Ages 7-10

Years – This study is the focus of this report. This study was designed to

follow-up on the conflicting results from the screening study, as well as the

results Sechelles and Faroe Islands studies. To overcome some of the

methodological limitations of the screening study, the current study conducted

in-person assessments of children using a standardized battery of

neuropsychological assessments, sampled children based on vaccine exposure

without regard health care utilization or neurodevelopmental diagnosis, and

included extensive additional data on potential confounding factors.
Abt Associates Inc. Chapter 3 15

 The Italian Trial on Acellular Pertussis Vaccines – This study compares

neuropsychological outcomes of children at ages 10-12 years that were

randomly assigned to receive either of two forms of diphtheria-tetanusacellular pertusis vaccine (DTaP) in the first year of life. One of the two forms

of DTaP included thimerosal as a preservative, the other included 2-

phenoxyethanol as a preservative. Children that received the thimerosalcontaining DTaPs had cumulative exposure to 137.5 micrograms of

ethylmercury during the age range spanning birth to twelve months, from all

vaccines including hepatitis-b receipts, while children receiving the other form

of DTaP had total cumulative exposure of 62.5 micrograms during the same

age range. The study is currently in progress.

 The Autism Case-Control Study – This study is using a case-control design to

investigate whether there are associations between exposure to mercury from

thimerosal-containing vaccines and immune globulins, and autistic disorder

and autism spectrum disorder. At the time of this writing, data collection was

underway for this study.

3.7. Research Questions for the Current Study

The primary research questions that motivated the design and guided the analyses were as

follows:

1) Is there an association between neuropsychological outcomes and cumulative

exposure to mercury from thimerosal-containing vaccines and immune globulins

received during the age range spanning birth to seven months?

2) Is there an association between neuropsychological outcomes and cumulative

exposure to mercury from thimerosal-containing vaccines and immune globulins

received during the age range spanning birth to one month?

3) Is there an association between neuropsychological outcomes and prenatal

exposure to mercury from thimerosal-containing vaccines and immune globulins

received by the mother during her pregnancy with the focus child?

Secondary research questions motivated additional analyses. These were:

 Do exposure effects vary by the sex of the child?

 Does prenatal exposure to mercury modify the effects of postnatal exposure to

mercury from thimerosal-containing vaccines and immune globulins?

 Does receipt of antibiotics, concurrent with receipt of thimerosal-containing vaccines

or immune globulins, modify the exposure effects?
Abt Associates Inc. Chapter 4 16

4. Study Design

The current study utilized a retrospective cohort design5(Kleinbaum, Kupper, &

Morgenstern, 1982) wherein historical (administrative) data were used to select a cohort

of children with a wide range of cumulative exposure to ethylmercury from thimerosal

during the age range spanning birth to seven months. This cohort of children was

“followed” into the present, when the children were in the age range of 7-10 years, at

which time outcomes were measured using a battery of neurodevelopmental assessments

Inferences regarding the relationships of prental and early childhood exposure to

ethylmercury from thimerosal-containing vaccines and immune globulins to

neurodevelopmental outcomes were made from results of linear and logistic regression

models where outcomes were modeled as functions of the exposure variables, covariates,

and residual error.

The choice of which tests to include in the battery of assessments was guided by the

results of the Faroe Islands study (Grandjean et al., 1997), the Sechelles Islands study

(Davidson et al., 1998), and the CDC screening study (Verstraeten et al., 2003)), and by

the recommendations from the External Expert Consultants. Outcomes that were found to

have associations with mercury exposure in any of those studies were considered to be

important outcomes for the current study. The battery of outcome assessments included

measures of speech and language, verbal memory, literacy achievement, fine motor

coordination, visual spatial ability, attention / executive functioning, behavior regulation,

tics, and general intellectual functioning.

Data on prenatal and early childhood exposure to ethylmercury from thimerosalcontaining vaccines and immune globulins were obtained from several sources: Medical

record abstractions, computer-automated medical records that are maintained as part the

Vaccine Safety Datalink system or as part of HMO administrative records, parentprovided immunization records, and parent interview.

Measures of child and family demographic characteristics, child birth conditions, prental

and childhood exposure to neurotoxins, child medical conditions, and measures of

maternal diagnoses of speech delay, language delay, stuttering and attention deficit

hyperactivity disorder were used as covariates. The data required to construct these

measures were obtained from parent interview and from child and maternal medical

record abstraction.

5 Also known as a historical prospective design (Mausner & Bahn, 1985)
Abt Associates Inc. Chapter 5 17

5. Sample

The sample of study participants was drawn from a sampling frame created from VSD

records from four participating health maintenance organizations (HMOs). Eligibility

criteria are described in Section 5.1. The steps from creation of the sampling frame, to

sample selection, to recruitment and data collection, to creation of the final analysis

sample are depicted in the flow chart in Exhibit 5.1 and are described in subsequent

sections. The numbers appear smaller in each successive step as samples and sub-samples

were drawn, as new information on eligibility was acquired in several steps that

necessitated the omission of ineligible children, and for other reasons such as inability to

locate families or families’ refusal to participate.
Abt Associates Inc. Chapter 5 18

Exhibit 5.1. Data Collection Flow Chart

Sample Frame

n = 27,240

Selected Sample

n = 7,982

Retained in Sample Physician, Geographic, Sibling,

Membership Exclusions

n = 7,088 n = 894

Attempted to Recruit No Attempt to Recruit

n = 3,648 (reserve sample that was not utilized)

n = 3,440

Child Assessed Child Not Assessed (n=2,541)

n = 1,107

512

44

1,985

2,541

Ineligible

Clinic ended

Refused / unable to locate

Analysis Data Set Excluded (n=60)

n = 1,047

1

24

7

5

23

60

Year 1 care not in HMO

Low birth weight

No weight data

No prenatal exposure data

Exclusionary medical condition
Abt Associates Inc. Chapter 5 19

5.1. Eligibility Criteria

Eligibility criteria are listed in Exhibit 5.2. Children with particular medical conditions

were excluded from the study. The list of exclusionary medical conditions was developed

by a team of five pediatricians from the CDC and from the HMOs. These conditions had

to be present at birth or diagnosed and recorded before the first birthday, and were

conditions that were deemed likely to have adverse effects on neurodevelopmental

outcomes. Most exclusions due to medical conditions were applied during the creation of

the sampling frame, using ICD-9 codes from the VSD database. Other exclusions were

applied at the time of the telephone eligibility interview, and a small number of

exclusions were applied only after the sample child’s medical records had been

abstracted. Exclusionary medical conditions are shown Exhibit 5.3. Additionally,

children who had ever been diagnosed with lead poisoning, or who had ever had blood

lead levels greater than 10 were excluded, as were children with uncorrected hearing loss.

Prior to recruitment, the children’s primary care physicians were informed of the names

of their patients that were selected to participate in the study, and the physicians had the

opportunity to exclude any or all their patients if they so desired.

Exhibit 5.2. Eligibility Criteria

Eligibility Criterion Comments

Child’s birth date between Jan 1, 1993 and Dec

31, 1997

Children born during this period would be 7 to

10 years of age at the time of assessment.

Child is currently a member of HMO. This criterion increased the likelihood that

current contact information would be available

for sample members.

Child must be born into HMO system This criterion increased the likelihood of having

complete prenatal and birth records

Child must be a member of HMO for entire first

year of life.

This criterion increased the likelihood of having

a complete vaccination history and medical

records for entire first year of life.

Child must have received all year 1

vaccinations at HMO

This criterion increased the likelihood of having

complete vaccination for entire first year of life.

Child must not have received any experimental

vaccines that had unknown thimerosal

amounts.

If thimerosal amount was unknown, accurate

ethylmercury exposure could not be

ascertained.

Child must not have any siblings in the sample. If two or more eligible children from a single

family were randomly selected for inclusion in

the sample, only one of the children, chose at

random, was retained in the sample.

Child and mother must speak English well

enough to participate in English language

interviews and/or assessments.

Assessment of English language ability was

assessed during eligibility and recruitment

calls.

Child must be singleton. Twins, triplets, multiple births were excluded.

Child must live with biological mother at least 4

days per week on average.

Child must live with biological mother to ensure

that questions on parent interview about

prenatal and early experiences could be

answered, and must live with mother at least 4

days per week to ensure that mother is very

knowledgeable about child’s development.
Abt Associates Inc. Chapter 5 20

Exhibit 5.2. Eligibility Criteria

Eligibility Criterion Comments

Child must not have been taking

antidepressant or anticonvulsant medication or

have been taking Clonopin (a type of

antihypertension medication).

Child must live within 50 miles of the clinic site

where assessments were administered.

Child must not have had any of the

exclusionary medical conditions listed in Exhibit

5.3.

The exclusionary conditions were medical

conditions diagnosed within the first year of life

that are known or expected to be associated

with poor scores on the outcome measures.

Children who had ever been diagnosed with

lead poisoning, or who had ever had blood lead

levels greater than 10 were excluded.

Children with uncorrected hearing loss were

excluded.

Exhibit 5.3. Exclusionary Medical Conditions

ICD-9 Code Condition

Low birth weight (<2500 grams)

0478 VIRAL MENINGITIS NEC

0479 VIRAL MENINGITIS NOS

0490 LYMPHOCYTIC CHORIOMENING

0498 VIRAL ENCEPHALITIS NEC

0499 VIRAL ENCEPHALITIS NOS

24200 TOX DIF GOITER NO CRISIS

243 CONGENITAL HYPOTHYROIDSM

244 ACQUIRED HYPOTHYROIDISM*

2440 POSTSURGICAL HYPOTHYROID

2443 IATROGEN HYPOTHYROID NEC

2449 HYPOTHYROIDISM NOS

245 THYROIDITIS*

2452 CHR LYMPHOCYT THYROIDIT

2459 THYROIDITIS NOS

2461 DYSHORMONOGENIC GOITER

2462 CYST OF THYROID

2468 DISORDERS OF THYROID NEC

2469 DISORDER OF THYROID NOS

3200 HEMOPHILUS MENINGITIS

3201 PNEUMOCOCCAL MENINGITIS

3202 STREPTOCOCCAL MENINGITIS

3203 STAPHYLOCOCC MENINGITIS

32081 ANAEROBIC MENINGITIS
Abt Associates Inc. Chapter 5 21

Exhibit 5.3. Exclusionary Medical Conditions

ICD-9 Code Condition

32082 MNINGTS GRAM-NEG BCT NEC

3209 BACTERIAL MENINGITIS NOS

3222 CHRONIC MENINGITIS

3229 MENINGITIS NOS

3231 RICKETTSIAL ENCEPHALITIS

3234 OTH ENCEPHALIT D/T INFEC

3236 POSTINFECT ENCEPHALITIS

3239 ENCEPHALITIS NOS

3240 INTRACRANIAL ABSCESS

325 PHLEBITIS INTRCRAN SINUS

326 LATE EFF CNS ABSCESS

330 CEREBRAL DEGEN IN CHILD*

3300 LEUKODYSTROPHY

3301 CEREBRAL LIPIDOSES

3308 CEREB DEGEN IN CHILD NEC

3309 CEREB DEGEN IN CHILD NOS

36900 BOTH EYES BLIND-WHO DEF

36923 ONE EYE-MODERATE/OTH-NOS

36960 BLINDNESS, ONE EYE

3699 VISUAL LOSS NOS

3897 DEAF MUTISM NEC

7400 ANENCEPHALUS

7401 CRANIORACHISCHISIS

7410 SPINA BIF W HYDROCEPHAL*

74100 SPIN BIF W HYDROCEPH NOS

74103 SPIN BIF W HYDRCEPH-LUMB

7420 ENCEPHALOCELE

7421 MICROCEPHALUS

7422 REDUCTION DEFORM, BRAIN

7423 CONGENITAL HYDROCEPHALUS

7424 BRAIN ANOMALY NEC

74300 CLINIC ANOPHTHALMOS NOS

74310 MICROPHTHALMOS NOS

74312 MICROPHTH W OTH EYE ANOM

7433 CONG CATARACT/LENS ANOM*

74330 CONGENITAL CATARACT NOS

74335 CONGENITAL APHAKIA

74339 CONG CATAR/LENS ANOM NEC

74343 CONG CORNEAL OPACIT NEC

7467 HYPOPLAS LEFT HEART SYND
Abt Associates Inc. Chapter 5 22

Exhibit 5.3. Exclusionary Medical Conditions

ICD-9 Code Condition

74682 COR TRIATRIATUM

747 OTH CONG CIRC SYST ANOM*

74869 LUNG ANOMALY NEC

749 CLEFT PALATE & CLEFT LIP*

7490 CLEFT PALATE*

74900 CLEFT PALATE NOS

74901 UNILAT CLEFT PALATE-COMP

74902 UNILAT CLEFT PALATE-INC

74903 BILAT CLEFT PALATE-COMPL

74904 BILAT CLEFT PALATE-INC

7491 CLEFT LIP*

74910 CLEFT LIP NOS

74911 UNILAT CLEFT LIP-COMPL

74912 UNILAT CLEFT LIP-IMCOMPL

74914 BILAT CLEFT LIP-INCOMPL

7492 CLEFT PALATE W CLEFT LIP*

74920 CLEFT PALATE & LIP NOS

74921 UNIL CLEFT PALAT/LIP-COM

74922 UNIL CLEFT PALAT/LIP-INC

74923 BILAT CLFT PALAT/LIP-COM

74924 BILAT CLFT PALAT/LIP-INC

74925 CLEFT PALATE & LIP NEC

75010 TONGUE ANOMALY NOS

75012 CONG ADHESIONS OF TONGUE

75015 CONG MACROGLOSSIA

75019 TONGUE ANOMALY NEC

75026 MOUTH ANOMALY NEC

75029 PHARYNGEAL ANOMALY NEC

7507 GASTRIC ANOMALY NEC

7560 ANOMAL SKULL/FACE BONES

75616 KLIPPEL-FEIL SYNDROME

758 CHROMOSOMAL ANOMALIES*

7580 DOWN'S SYNDROME

7581 PATAU'S SYNDROME

7582 EDWARDS' SYNDROME

7583 AUTOSOMAL DELETION SYND

7584 BALANCE AUTOSOM TRANSLOC

7585 AUTOSOMAL ANOMALIES NEC

7586 GONADAL DYSGENESIS

7587 KLINEFELTER'S SYNDROME
Abt Associates Inc. Chapter 5 23

Exhibit 5.3. Exclusionary Medical Conditions

ICD-9 Code Condition

7588 SEX CHROMOSOME ANOM NEC*

75889 OTH CON D/T CHRM ANM NEC

7589 CHROMOSOME ANOMALY NOS

7594 CONJOINED TWINS

7595 TUBEROUS SCLEROSIS

7596 HAMARTOSES NEC

7597 MULT CONGEN ANOMAL NEC

75981 PRADER-WILLI SYNDROME

75983 FRAGILE X SYNDROME

7600 MATERN HYPERTEN AFF NB

7601 MATERN URINE DIS AFF NB

7602 MATERNAL INFEC AFF NB

7603 MATERN CARDIORESP AFF NB

76070 NOXIOUS SUBST NOS AFF NB

76071 MATERNAL ALCOHOL AFF NB

76072 MATERNAL NARCOTIC AFF NB

76073 MATERNAL HALLUCIN AFF NB

76075 COCAINE - NXS INFL FETUS

76079 NOXIOUS SUBST NEC AFF NB

7608 MATERNAL COND NEC AFF NB

7611 PREMAT RUPT MEMB AFF NB

7612 OLIGOHYDRAMNIOS AFF NB

7613 POLYHYDRAMNIOS AFF NB

7615 MULT PREGNANCY AFF NB

7617 ANTEPART MALPRES AFF NB

7618 MATERN COMPL NEC AFF NB

7640 LT-FOR-DATES W/O FET MAL*

76400 LIGHT-FOR-DATES WTNOS

76401 LIGHT-FOR-DATES <500G

76402 LT-FOR-DATES 500-749G

76403 LT-FOR-DATES 750-999G

76404 LT-FOR-DATES 1000-1249G

76405 LT-FOR-DATES 1250-1499G

76406 LT-FOR-DATES 1500-1749G

76407 LT-FOR-DATES 1750-1999G

76408 LT-FOR-DATES 2000-2499G

7641 LT-FOR-DATES W FETAL MAL*

76410 LT-FOR-DATE W/MAL WTNOS

76413 LT-DATE W/MAL 750-999G

76418 LT-DATE W/MAL 2000-2499G
Abt Associates Inc. Chapter 5 24

Exhibit 5.3. Exclusionary Medical Conditions

ICD-9 Code Condition

7649 FETAL GROWTH RETARD NOS*

76490 FET GROWTH RETARD WTNOS

76492 FET GROWTH RET 500-749G

76493 FET GROWTH RET 750-999G

76494 FET GRWTH RET 1000-1249G

76495 FET GRWTH RET 1250-1499G

76496 FET GRWTH RET 1500-1749G

76497 FET GRWTH RET 1750-1999G

76498 FET GRWTH RET 2000-2499G

765 EXTREME IMMATURITY

7650 EXTREME IMMATURITY*

76500 EXTREME IMMATUR WTNOS

76501 EXTREME IMMATUR <500G

76502 EXTREME IMMATUR 500-749G

76503 EXTREME IMMATUR 750-999G

76504 EXTREME IMMAT 1000-1249G

76505 EXTREME IMMAT 1250-1499G

76506 EXTREME IMMAT 1500-1749G

76507 EXTREME IMMAT 1750-1999G

76508 EXTREME IMMAT 2000-2499G

7651 OTHER PRETERM INFANTS*

76510 PRETERM INFANT NEC WTNOS

76511 PRETERM NEC <500G

76512 PRETERM NEC 500-749G

76513 PRETERM NEC 750-999G

76514 PRETERM NEC 1000-1249G

76515 PRETERM NEC 1250-1499G

76516 PRETERM NEC 1500-1749G

76517 PRETERM NEC 1750-1999G

76518 PRETERM NEC 2000-2499G

767 BIRTH TRAUMA*

7670 CEREBRAL HEM AT BIRTH

768 INTRAUTERINE ASPHYXIA*

7681 FET DEATH-ANOXIA DUR LAB

7685 SEVERE BIRTH ASPHYXIA

769 RESPIRATORY DISTRESS SYN

7702 NB INTERSTIT EMPHYSEMA

7703 NB PULMONARY HEMORRHAGE

7707 PERINATAL CHR RESP DIS

7721 NB INTRAVENTRICULAR HEM
Abt Associates Inc. Chapter 5 25

Exhibit 5.3. Exclusionary Medical Conditions

ICD-9 Code Condition

7722 NB SUBARACHNOID HEMORR

7725 NB ADRENAL HEMORRHAGE

7757 LATE METAB ACIDOSIS NB

7762 DISSEM INTRAVASC COAG NB

7790 CONVULSIONS IN NEWBORN

7792 CNS DYSFUNCTION SYN NB

7794 NB DRUG REACTION/INTOXIC

7795 NB DRUG WITHDRAWAL SYNDR

V310 TWIN, MATE LB-IN HOSP*

V3100 TWIN-MATE LB-HOSP W/O CS

V3101 TWIN-MATE LB-IN HOS W CS

V311 TWIN, MATE LB-BEFORE ADM

V3200 TWIN-MATE SB-HOSP W/O CS

V3201 TWIN-MATE SB-HOSP W CS

V3300 TWIN-NOS-IN HOSP W/O CS

V3301 TWIN-NOS-IN HOSP W CS

V331 TWIN NOS-BEFORE ADMISSN

V3400 OTH MULT LB-HOSP W/O CS

V3401 OTH MULT LB-IN HOSP W CS

V370 MULT BIRTH NOS-IN HOSP*

V3700 MULT BRTH NOS-HOS W/O CS

V3701 MULT BIRTH NOS-HOSP W CS

V3710 MULT BIRTH NOS-HOSP

5.2. Sampling Frame

The sampling frame for the current study, (i.e., the list from which the sample was

drawn,) was created in collaboration with the data managers from each of the four HMOs

participating in the study. HMO data managers first selected records from their VSD

database that satisfied birth year and HMO enrollment criteria. Abt Associates then

created the final sampling frame by applying additional exclusionary criteria based on

child age, medical conditions, and primary care facilities. The numbers of children in the

sampling frame by HMO and exposure categories are displayed in Exhibit 5.4. The

exposure categories represent levels of exposure to ethylmercury from thimerosal in

vaccines during the age range of one to seven months, crossed with exposure to

thimerosal from receipt of hepatitis B vaccine during the first month of life.
Abt Associates Inc. Chapter 5 26

Exhibit 5.4

Size of Sampling Frame by Exposure Category for Each HMO

HMO-A HMO-B HMO-C HMO-D Total

VSD Exposures HepB at

Birth

HepB at

Birth

HepB at

Birth

HepB at

Birth

HepB at

Birth

Cumulative 1-7

Months No Yes No Yes No Yes No Yes No Yes

(0 to 62.5 g ) 226 489 224 342 53 40 5 6 508 877

(75.0 to 87.5 g ) 1122 1060 230 1272 2 3 1 10 1355 2345

(100.0 to 112.5 g ) 4376 1328 463 4762 39 321 4 17 4882 6428

(125.0 to 137.5 g ) 229 108 397 4703 20 34 1 157 647 5002

(150.0 to 162.5 g ) 104 32 26 536 202 2424 18 120 350 3112

(175.0 to 187.5 g ) 145 11 1 47 79 154 13 769 238 981

(200.0 g & up ) 0 0 0 6 3 9 21 476 24 491

Total 6202 3028 1341 11668 398 2985 63 1555 8004 19236

HMO / Grand Total 9230 13009 3383 1618 27240

Note: g = micrograms.

5.3. Sample Selection

The primary objectives of the sample selection were to obtain a) a sample with a wide

distribution of exposures, and b) an analysis sample of approximately 1,200 assessed

children. Due to budget constraints the target sample size was subsequently reduced to

1,100 assessed children. Power calculations had indicated that an analysis sample of this

size would have more than 90 percent power to detect hepatitis B at birth and cumulative

exposures in the one to seven month age range effects as small as r

2

= 0.01 (i.e., the effect

explains one percent of total variance in the outcome measure). To obtain an analysis

sample of size n=1,100, we had to select a much larger sample in order to account for

sample loss due to factors such as physician refusals, geographic criteria, inability to find

sampled families, additional eligibility criteria ascertained during eligibility call, and

unwillingness to participate in the study.

We had originally hoped to select a sample that was balanced across the four HMOs, and

across exposure categories within HMOs, and across age groups and primary care

facilities within exposure categories. Perfect balance across all of those factors would

eliminate the possibility of confounding on those factors. Such balance was not feasible,

however, due to the sizes of the sampling frame and the distribution of exposures within

each of the four HMOs. Based on the sizes and exposures across HMOs, the decision was

made to allocate the sample unequally across the four HMOs. Stratified random samples

were drawn from each HMO, where the strata were defined by exposure levels, with

implicit stratification by age cohort and primary care facility via the use of a systematic

random sampling paradigm.

The sizes of the selected samples at each HMO are displayed in Exhibit 5.5.
Abt Associates Inc. Chapter 5 27

Exhibit 5.5

Size of Samples Selected from Each HMO by Exposure Category

HMO-A HMO-B HMO-C HMO-D Total

VSD Exposures HepB at

Birth

HepB at

Birth

HepB at

Birth

HepB at

Birth

HepB at

Birth

Cumulative 1-7

Months No Yes No Yes No Yes No Yes No Yes

(0 to 62.5 g ) 226 489 224 342 53 40 5 6 508 877

(75.0 to 87.5 g ) 534 534 230 483 2 3 1 10 767 1030

(100.0 to 112.5 g ) 534 534 463 483 39 71 4 17 1040 1105

(125.0 to 137.5 g ) 229 108 397 483 20 34 1 45 647 670

(150.0 to 162.5 g ) 104 32 26 483 71 71 18 45 219 631

(175.0 to 187.5 g ) 145 11 1 47 71 71 13 45 230 174

(200.0 g & up ) 0 0 0 6 3 9 21 45 24 60

Total 1772 1708 1341 2327 259 299 63 213 3435 4547

3480 3668 558 276 7982

Note: g = micrograms.

5.4. Physician, Sibling, and Out-of-Area Exclusions

After sample selection, Abt Associates sent the IDs of the sampled children to the four

HMOs. Those IDs were used to generate letters to physicians informing them of which

of their patients had been selected for the study and allowing the physician to ask that any

child or family be removed from the sample. The HMOs tracked any families that

needed to be removed from the sample based on physician requests. At HMO-B, if the

child’s primary care provider was unknown, the child was excluded from the sample at

this point.

The HMOs also identified sibling pairs within the sample (in a few cases, three siblings

were selected in the sample). The HMOs sent the IDs of the sibling groupings back to

Abt Associates, where a random sample from each sibling group was selected to remain

in the sample. The other member of the sibling pair (or members of the sibling group)

was excluded from the sample.

At this phase, the HMOs also applied geographical exclusions whenever it was

discovered that some of the sampled children lived outside of the geographic boundaries

of the defined study populations. Additionally, a small number of exclusions occurred at

HMO-D during this phase due to membership criteria. Exhibit 5.6 summarizes

exclusions made during this phase and the sizes of the remaining samples.
Abt Associates Inc. Chapter 5 28

Exhibit 5.6

Sample Loss Due to Physician, Sibling, and Out-of-Area Exclusions

by HMO

HMO

HMO-A HMO-B HMO-C HMO-D Total

N in Selected Sample 3480 3668 558 276 7982

Exclusions: n % n % n % n % n %

 Physician exclusions 31 0.9 3 0.1 0 0.0 5 1.8 39 0.5

 Physician Unknown 0 0.0 114 3.1 0 0.0 0 0.0 114 1.4

 Sibling exclusions 138 4.0 177 4.8 10 1.8 9 3.3 334 4.2

 Geographic exclusions 0 0.0 392 10.7 0 0.0 7 2.5 399 5.0

 Membership exclusions 0 0.0 0 0.0 0 0.0 8 2.9 8 0.1

Total Excluded 169 4.9 686 18.7 10 1.8 29 10.5 894 11.2

Remaining Sample 3311 95.1 2982 81.3 548 98.2 247 89.5 7088 88.8

5.5. Recruitment in Batches

Samples were released for recruitment in randomly selected batches. We monitored the

participation rates across all four HMOs as recruitment and testing was underway. The

batch release of sample allowed us to keep assessment clinics full to the maximum extent

possible as the various assessment sites got up and running at various rates. The batch

release also made possible the inclusion of children in later batches that were too young

to satisfy eligibility criteria in earlier batches. Batches were selected as stratified random

samples of the full samples, where strata were defined by exposure levels, with implicit

stratification by age cohort and facility via the use of a systematic random sampling

paradigm.

The batch histories are shown in Exhibit 5.7. All IDs from the two smaller HMOs

(HMO-C and HMO-D) were released for recruitment in batches. At the two large

HMOs, the full samples were not needed in order to achieve the overall targeted size for

the analysis sample of tested children. Therefore, only a subset of the samples was

released for recruitment. At each of the two large HMOs, there were small numbers of

children for whom no attempt at recruitment was made because the study ended and

clinics closed before the recruitment calls were made.

Exhibit 5.7

Batch History by HMO

HMO

HMO-A HMO-B HMO-C HMO-D Total

N in Sample 3311 2982 548 247 7088

Batches: Month n Month n Month n Month n

 1

st Batch June 839 June 600 May 548 May 110 2097

 2

nd Batch Jan. 250 June 220 Aug. 137 607

 3

rd Batch Sept. 800 800

 4

th Batch March 250 250

Total Batches 1089 1870 548 247 3754

Recruitment endeda-61 -45 -106

Total Attemptsb1028 1825 548 247 3648

a

“Recruitment ended” means clinics closed prior to recruitment call. No attempt was ever made to contact these families.

b

“Total Attempts” are the numbers of children for whom eligibility and/or recruitment calls were made.
Abt Associates Inc. Chapter 5 29

5.6. Recruitment and Eligibility Outcomes

Families whose physicians allowed them to be contacted by the study were sent a letter

and informational brochure. A postcard was enclosed that the family could return to the

HMO indicating their willingness (or refusal) to participate in the study. If no return

postcard was received from a family, this mailing was followed by a telephone call from

an HMO study team member, who followed a recruitment script to ascertain (a) if the

mother had any questions about the materials received, and (b) if the mother was willing

to be contacted by a representative of Abt Associates Inc.

Families who did not agree to be contacted by Abt Associates were asked if they were

willing to provide reasons for their refusal, so that the study could track non-response

data. For the families who agreed to be contacted, locating information was given to Abt

Associates for follow-up to confirm the child’s eligibility and the family’s willingness to

participate. Subsequently, a Screening Interview was conducted with each family by

telephone by a trained Abt Associates interviewer. In addition to confirming that the

family and child met the eligibility criteria previously discussed, additional criteria were

applied: the child could not be one of a multiple birth (e.g., twin, triplet), and the

biological mother had to have been at least 16 years old at the time of the target child’s

birth. The Screening Interview also collected information on additional criteria for

participation: the biological mother had to be available to participate in the assessment,

had to be mentally competent to understand the consent form and the research

instruments, could be interviewed in English, and lived with the target child at least four

days a week.

Exhibit 5.8 summarizes the results of the recruitment effort. The row labeled “complete”

indicates children who were recruited, were determined to be eligible, and who

participated in testing. Summed across the four HMOs, the total number of children that

participated in the assessments was n=1,107. The row labeled “ineligible” shows the

numbers of children that were determined to be ineligible during the eligibility call. The

row labeled “clinic ended” shows the numbers of families that had had been contacted

and who indicated a willingness to participate, but who were never assessed because data

collection ended before they were scheduled to come to the clinic for an assessment. The

row labeled “Refused (active)” indicates families that were contacted but who declined to

participate in the study. The row labeled “Refused (passive)” shows the numbers of

families that either could not be located, or had been contacted but were never assessed

for any of a number of reasons, e.g. scheduling issues and failure to return phone calls.

There is little information available on the families that refused to participate. Some of

the study’s internal review boards (IRBs) specified that after a family had actively

refused participation, no further analyses of any of the electronic data that had been

available during construction of the sampling frame were allowed. At two of the sites, a
Abt Associates Inc. Chapter 5 30

small sub-sample of families that actively refused was administered a refusal interview.

Eighty-four refusal interviews were obtained from refusers from HMO-B, and 118 refusal

interviews were obtained from HMO-C. Of the families that provided reasons for nonparticipation, 68 percent said it was due to lack of time or a busy schedule, and 13

percent gave reasons that indicated they distrusted or were ambivalent towards research.

Exhibit 5.8

Recruitment & Eligibility Outcomes by HMO

HMO

HMO-A HMO-B HMO-C HMO-D Total

Total Attemptsa

1028 1825 548 247 3648

Outcomes n % n % n % n % n %

Ineligible 182 17.7 235 12.9 78 14.2 17 6.9 512 14.0

Refused (active) 297 28.9 408 22.4 174 31.8 80 32.4 959 26.3

Refused (passive) 167 16.3 723 39.6 75 13.7 61 24.7 1026 28.1

Clinic ended 30 2.9 13 0.7 0 0.0 1 0.4 44 1.2

Complete 352 34.2 446 24.4 221 40.3 88 35.6 1107 30.3

Total 1028 100.0 1825 100.0 548 100.0 247 100.0 3648 100.0

“Total Attempts” = the numbers of children for whom eligibility and/or recruitment calls were made.

“Ineligible” = child was determined to be ineligible during eligibility call.

“Refuse (active)” = Contact was made with child’s mother and she indicated that she could not or would not participate.

“Refuse (passive)” = Includes unable to locate, non-working phone number, maximum number of telephone attempts

exceeded, calls not returned, willing to participate by repeated postponements to scheduled assessment, no-show at clinic.

“Clinic ended” = Clinic ended after recruitment call. These families had expressed a willingness to participate, but clinics

closed prior to testing.

“Complete” = child was assessed.

5.7. Size of Analysis Sample

A total of 1,107 children were assessed for the study. After each child participated in

testing, his/her medical records were abstracted and his/her mother’s medical records for

the period covering her pregnancy with the focus child were abstracted. Review of these

data abstracted from medical charts resulted in the identification of a set of children that

were ineligible for the study. In this section we describe 60 children that were excluded

from the analysis data set. After applying exclusions, the analysis data set included IDs

from 1,107 – 60 = 1,047 children. The 60 excluded children included:

 1 that was excluded because the child did not receive care from the participating

HMO during his/her first year of life.

 24 that were excluded because they were low birth weight.

 8 that were excluded because they have no weight data at any age (no birth

weight, no weights at subsequent ages).

 6 that were excluded because they had no information on prenatal exposures.

 23 that were excluded due to exclusionary medical conditions.
Abt Associates Inc. Chapter 5 31

One child was excluded because she/he did not receive care from the participating HMO,

and we therefore did not have the necessary data on exposures. During creation of the

sampling frame, low birth weight children (less than 2,500 grams) were identified via

VSD diagnosis codes and were excluded. The 24 low birth weight children excluded

from the analysis data set did not have the relevant VSD diagnosis codes so were not

excluded during sample frame creation, but were identified as low birth weight from the

data abstracted from their medical charts. Birth weights and body weights measured at

subsequent ages were used in the calculation of exposure levels6. For the eight children

with no recorded weight measurements, the postnatal measures of exposure to

ethylmercury from thimerosal could not be calculated. Therefore, those children were

excluded from the analysis data set. Six children were excluded because no information

on prenatal exposures to mercury from thimerosal were available from either maternal

medical records or from the parent interview.

During the creation of the sampling frame, records were excluded from the sample based

on exclusionary medical conditions that were identified via codes in the VSD database.

After chart abstractions were completed, we created a document summarizing all medical

conditions identified in the abstracted chart data for any of the 1107 children. A team of

five pediatricians reviewed the data and identified a set of conditions that were consistent

with the exclusions applied during the creation of the sampling frame. In addition to the

24 low birth weight children, described previously, 23 additional children were excluded

due to exclusionary medical conditions identified from the chart-abstracted data.

6 The measures of postnatal exposure to ethylmercury from thimerosal were calculated as a function of the

amount of mercury received and the child’s weight at the time of vaccine receipt.
Abt Associates Inc. Chapter 6 32

6. Data Sources

Data were obtained for the current study from a variety of sources, as shown in Exhibit

6.1.1. These include: (a) parent interviews; (b) records of children vaccine histories from

pediatrician/clinic visits; (c) direct child assessments, (d) scoring of a language sample

from each child, conducted by professionals at a specialized speech and language

laboratory; (e) behavior ratings of the child by the mother and the child’s primary school

teacher (the latter administered by mail survey); (f) ratings of the presence of tics and

stuttering, collected from the child’s mother, teacher, and the child assessor at the clinic;

(g) medical record abstraction, and (h) computer-automated medical data on children’s

health conditions and vaccinations, collected in accordance with the Vaccine Safety

Datalink (VSD) system. Each data source is described below.

6.1. The Clinic Visit

Testing clinics were established at each of the participating HMOs. The clinics were

organized to provide a standardized testing situation for children and a site where

mothers could be interviewed without distractions. At the clinic visit, a trained

interviewer conducted the Parent Interview, conducted the parent IQ test, obtained parent

ratings of the child’s behavior and neurological functioning, and collected any records the

parent kept on the child’s schedule of vaccinations. A trained child tester, who was

blinded to the child’s vaccine history, conducted a battery of neuropsychological

assessments with the child.

As shown in Exhibit 6.1.1, the clinic visit produced data on outcomes, exposures, and

covariates. Clinic visits took between 3 and 4 hours to complete, with breaks and snacks

for the mother and child. For the clinic visit, children who were taking medication(s) for

attention deficit hyperactivity disorder (ADHD) were asked to refrain from taking the

medication 12 hours prior to the clinic visit.
Abt Associates Inc. Chapter 6 33

Exhibit 6.1.1

Sources for each Type of Data

Data Source Method

Child outcomes

 Neuropsychological

outcomes

Direct assessment Clinic visit: assessments administered at clinic by

trained child tester

 Speech anomalies Direct evaluation of

taped speech sample

Clinic visit/outside evaluation: taped speech

sample from child evaluated at speech/language

laboratory (University of Pittsburgh)

 Attention, executive

functioning, and behavior

regulation at home

Parent rating Clinic visit: parent ratings as part of Parent

Interview

 Attention, executive

functioning, and behavior

regulation at school

Teacher ratings Mail questionnaire: Sent out to child’s teacher

 Tics and stuttering Parent rating Clinic visit: parent ratings as part of Parent

Interview

Teacher rating Mail questionnaire: Sent out to child’s teacher

Assessor rating Clinic visit: assessor rating as end of assessments

Exposures

 Child Medical report Data abstraction: data from VSD computerized

database

Clinic visit: vaccination record brought by parent

into clinic visit

Parent report Clinic visit: Parent Interview questions on child’s

receipt of vaccinations

Child medical records Data abstraction: Medical record data

 Mother Mother medical records Data abstraction: Medical record data

Parent report Parent interview

Covariates

 Maternal IQ KBIT (Kaufman Brief

Intelligence Test)

Clinic visit: administered at clinic by trained

interviewer

 Characteristics of child,

family, home

Parent report Clinic visit: Parent Interview

 Exposure to other toxins Parent report Clinic visit: Parent Interview

 Medical history Child medical record Data abstraction: Medical record data

6.1.1. Clinic Staff

Two kinds of staff operated the clinic sessions: the Clinic Managers (parent interviewer)

Child Assessors. Clinic Managers were college graduates who had extensive experience

either in office management or in coordinating research studies. These staff people were

responsible for administering the informed consent, conducting the Mother Interview

(described in a subsequent section), providing guidance to the mother for completing the

self-administered rating scales, conducting the mother IQ measure, and performing all of

the administrative tasks that were necessary for the coordination of the data collection.

The Clinic Manager scheduled all clinic visits, sent data to Abt Associates, ordered

supplies, and acted as coordinator on site.

Child Assessors had at least a Master’s degree, some had PhDs, and all had training and

experience in testing children. These staff were critical to the study and were extensively

trained to be proficient in the administration and scoring of the child tests. In addition,

they were responsible for making sure that the data that they collected were sent to the

appropriate people for subsequent review and processing.
Abt Associates Inc. Chapter 6 34

In addition to the two types of clinic staff, a third type of professional provided overall

supervision of the child assessors. At each HMO, the study hired licensed Clinical

Psychologists who were trained to review the administration and scoring of the tests. The

Clinical Psychologists double-scored the data provided by the Child Assessors. Child

Psychologists reviewed all child assessment data (previously scored and entered by the

Child Assessors) for completeness and accuracy and were responsible for interpretation

of the tests and for writing the letters to the parents informing them of their children’s

results. Clinical Psychologists also were available to parents to discuss their children’s

scores. Furthermore, a Clinical Psychologists was on call each time the clinic was in

session, to provide backup support for the Child Assessors and to be available for

consultation on the phone or in-person in case of emergencies

6.1.1.1. Training and Quality Control

One of the most important activities of this project was the training and testing of Clinic

Managers and Child Assessors for inter-rater reliability. This training was conducted by

experienced neuropsychologists. Clinic Managers and Child Assessors had to pass two

kinds of reliability testing. First, they were tested for administrative fidelity during

training, based on mock scripts and were tested for scoring accuracy using written

scoring tests. At training, Clinic Managers and Child Assessors had to pass tests of

administration and scoring for all of the instruments for which he/she was responsible.

Any Clinic Manager or Child Assessor who did not pass these tests was not hired for the

study.

Training and reliability checks continued for Clinic Managers and Child Assessors in the

field. Prior to the actual data collection, pilot testing with non-study families was

conducted to test the data collection protocol, check timing of clinic assessments and total

clinic visit, and to further establish reliability of the Clinic Managers and Child

Assessors. Clinic managers audiotaped these pilot interviews and tests and sent these

tapes along with their scored tests and edited interviews to Abt staff for review.

Each Child Assessors was observed conducting a test session by a Consulting

Psychologists with pilot test children. Consulting Psychologists were given specific

criteria to use for monitoring the Child Assessors during each subtest. They were asked

to make judgments about each Child Assessor’s fidelity to the test administration based

on the project training and the assessor’s ability to establish rapport with the child during

testing.

6.1.2. Child Assessments

At the clinic, each child was administered a battery of 14 tests comprising 26 subtests and

covering nine developmental domains. Additional measures of child outcomes were

obtained from parent interview and teacher surveys (described subsequently) and from

child assessor ratings of the presence of tics and stuttering. The battery of assessments is

summarized in Exhibit 6.1.2. Note that one of the measures, the Goldman-Firstoe, was
Abt Associates Inc. Chapter 6 35

scored outside of the clinic in a language laboratory under the supervision of Dr. Tom

Campbell of the University of Pittsburgh.
Abt Associates Inc. Chapter 6 36

Exhibit 6.1.2

Child Assessment Battery

Measurement Instrument Subtest(s)/Constructs Tested Outcome(s) Data Collection Method

Speech and Language

Boston Naming Test Naming vocabulary Total number of correctly-named

pictures

Direct assessment at clinic

NEPSY

(2 subtests)

Language subtests:

Speeded Naming (rapid access

to/production of names of recurring colors,

sizes, shapes)

Comprehension of Instructions

(process/respond quickly to verbal

instructions of increasing syntactic

complexity)

Total score

(based on Time to Completion and

Total Number Correct)

Total correct responses

Direct assessment at clinic

Clinical Evaluation of Language

Fundamentals–Third Edition (CELF-3)

(2 subtests)

Expressive language subtests:

Formulated Sentences (formulation of

simple, compound, complex sentences)

Recalling Sentences (recall/ reproduction of

sentence surface structure as a function of

syntactic complexity)

Total score based on

completeness of sentence

Total score based on

accuracy of sentence recall

Direct assessment at clinic

Goldman-Fristoe 2 Test of Articulation

(GFTA-2)

Sounds-in-Words (spontaneous speech

production of single words)

Total number of articulation errors Audio recording of child sent

to speech laboratory for

scoring on articulation.

Iowa Scale for Rating Severity of

Stuttering

Speech/language dysfluencies Parent rating (1-7)

Clinical assessor rating (1-7)

Teacher rating (1-7)

Rating by parent and clinical

assessor at the clinic visit

Rating by teacher via mail

survey

Verbal Memory

California Verbal Learning Test—

Children’s Version (CVLT-C)

(5 subtests)

Immediate Free Recall

Short Delay Free Recall

Short Delay Cued Recall

Long Delay Free Recall

Long Delay Cued Recall

Total number correctly recalled

Total number correctly recalled

Total number correctly recalled

Total number correctly recalled

Total number correctly recalled

Direct assessment at clinic

Children’s Memory Scale Stories 1 and

Stories 2 (2 subtests)

Immediate Recall of connected, meaningful

text

Delayed Recall of connected, meaningful text

Number correctly recalled story units

Number correctly recalled story units

Direct assessment at clinic

Achievement

Woodcock-Johnson Psycho-Educational

Battery-Revised: Tests of Achievement

Letter-Word Identification (phonemic

awareness--ability to match a rebus with

actual picture; ability to identify isolated letters

and words)

Total number correct converted to

“W” [Rasch logit score]

Direct assessment at clinic
Abt Associates Inc. Chapter 6 37

Exhibit 6.1.2

Child Assessment Battery

Measurement Instrument Subtest(s)/Constructs Tested Outcome(s) Data Collection Method

Fine Motor Coordination

Grooved Pegboard

(2 subtests)

Manipulative dexterity- Dominant hand

Manipulative dexterity- Non-dominant hand

Total time to completion: dominant

hand

Total time to completion: nondominant hand

Direct assessment at clinic

Finger Tapping Test

(2 subtests)

Manipulative dexterity- Dominant hand

Manipulative dexterity- Non-dominant hand

Maximum number of taps: dominant

hand

Maximum number of taps: nondominant hand

Direct assessment at clinic

Visual Spatial Ability

Stanford-Binet Intelligence Test Copying

subtest

Visuomotor coordination (reproduce designs

with blocks/ copy simple and complex

geometric patterns from pictures on cards)

Total number correct Direct assessment at clinic

Attention /Executive Functioning

Gordon Diagnostic System (GDS)

(2 subscores)

Vigilance Task: ability to respond accurately

and quickly to presentation of paired numbers

on screen

Number correct responses

Number commissions

Direct assessment at clinic

WISC III Digit Span subtest

(3 subscores)

Memory for digit strings Score for digits forwards

Score for digits backwards

Combined score

Direct assessment at clinic

Behavior Rating Inventory of Executive

Function (BRIEF)

Metacognition Index (child’s ability to plan,

organize, sustain future-oriented problem

solving in working memory)

Parent rating: Total score

Teacher rating: Total score

Separate ratings by child’s

teacher (mail survey) and

parent (parent interview)

Behavior Regulation

Conners’ Rating Scales—Revised

(2 subscores)

Inattentive (cluster of symptoms on DSM-IV

diagnosis of ADHD--predominantly

inattention)

Hyperactive-Impulsive (cluster of symptoms

on DSM-IV diagnosis of ADHD--

predominantly hyperactivity-impulsivity)

Parent rating: Total score

Teacher rating: Total score

Separate ratings by child’s

teacher (mail survey) and

parent (parent interview)

Behavior Rating Inventory of Executive

Function (BRIEF)

Behavioral Regulation Index (shifting of

cognitive set and modulating emotions and

behavior to achieve goal)

Parent rating: Total score

Teacher rating: Total score

Separate ratings by child’s

teacher (mail survey) and

parent (parent interview)

Tics

Yale Global Tic Severity Scale

(scores for 2 types of tics)

Motor tics

Phonic tics

Clinical assessor report of motor

tics/phonic tics during assessment

Parent report on motor tics/phonic

tics shown by child in prior 7 days

Ratings by parent as part of

parent interview at clinic and

by child assessor at end of

clinic visit
Abt Associates Inc. Chapter 6 38

Exhibit 6.1.2

Child Assessment Battery

Measurement Instrument Subtest(s)/Constructs Tested Outcome(s) Data Collection Method

General Intellectual Functioning

WASI

(4 subtests resulting in Verbal and

Performance scores)

Verbal subtests:

Vocabulary (oral definition of orallypresented words)

Similarities (state rule for how two objects

or concepts are similar)]

Performance subtests:

Block Design (2-dimensional geometric

patterns to be replicated with two-color cubes)

Matrix Reasoning (choosing piece of matrix

that best completes the designs—untimed;

taps analogic reasoning, spatial visualization,

visuospatial reasoning)

Verbal IQ standard score

(M=100, SD=15)

Performance IQ standard score

(M=100, SD=15)

Full scale IQ standard score

(M=100, SD=15)

Direct assessment at clinic
Abt Associates Inc. Chapter 6 39

6.1.3. Parent Interview

The parent interview was administered to the child’s biological mother during the clinic

visit. The interview produced detailed data on:

 Family structure and demographics

 Family educational history

 Home characteristics

 Prenatal medical care

 Events and exposures during pregnancy with focus child

 Events and exposures during infancy

 Child’s use of medications

 Child’s developmental diagnoses

 Maternal developmental diagnoses

To obtain a measure of the mother’s IQ, the Kaufman Brief Intelligence Test (KBIT) was

administered to each mother by the clinic coordinator.

Mothers were also asked to bring their child’s immunization records from their personal

files to the clinic visit.

As part of the parent interview, the mother rated the child’s behavior at home, using the

Conners Rating Scales and the Behavior Rating Inventory of Executive Function

(BRIEF).

Mothers were also asked whether the child had exhibited any stuttering or tics in the

seven-day period leading up to the clinic visit.

6.2. Teacher Mail Survey

The child’s primary school teacher also was asked to (a) rate the child’s behavior using

Conners’ Rating Scales and the BRIEF , which produced measures of children’s

attention/executive functioning, and behavior regulation, and (b) indicate whether the

child exhibited stuttering at school in the seven-day period leading up to date that the

teacher completed the child ratings. This information was obtained from teachers via

mail-return questionnaire.

6.3. Medical Record Abstractions

Data from both the mother’s and the child’s medical records was abstracted by trained

record abstractors at each HMO (typically, HMO medical staff). The abstraction were

developed to collect the following information from the maternal medical record: 1)

pregnancy history; 2) complications, illness, procedures and treatments during the

pregnancy with the target child; 3) procedures or complications of labor and delivery,

including method of delivery and any drugs administered during labor; 4) maternal

hepatitis B antigen status, receipt of Rhogam (or other Rh(D) immunoglobulin), and
Abt Associates Inc. Chapter 6 40

receipt of any vaccines during pregnancy with target child; and 5) maternal medical

history for developmental outcomes.

Data abstracted from the child’s medical records included: 1) perinatal data, such as

gestational age, birth weight, birth length, head circumference at birth, Apgar scores and

birth plurality; 2) abnormal conditions and clinical procedures relating to newborn; 3)

infant medications; 4) all receipts of any vaccines or immune globulins; 6) all receipts of

antibiotics; 7) developmental delays or conditions and psychiatric conditions, including

date of the first mention of the condition in the medical chart, date of first prescribed

medications, date of first referral, and type of service provider; and 8) medical conditions,

such as lead poisoning and anemia/iron deficiency, including date of first mention in the

medical chart.

Each medical record abstractor attended a half-day training session that covered the

background and purpose of the study; medical abstraction forms for the mother and child;

working with the clinician to obtain copies of medical release forms of the clinically

assessed children in order to obtain medical records; maintaining subject confidentiality;

transmittal of data to Abt’s central office; and quality assurance.

All medical abstraction data were double entered by a professional data-entry house.

6.4. VSD Computer-Automated Data

The computer-automated data, collected and maintained in accordance with the Vaccine

Safety Datalink (VSD) system (Chen et. al, 2000), were provided to the study from each

of the four participating HMOs. These data were used in the creation of the sample frame

(see Chapter 5) and used in the analysis phase to create measures of exposure and

covariate measures. These data sets included information on child’s sex and date of birth;

vaccination information including date and type of vaccine received, vaccine

manufacturer and lot number and indicators of whether vaccines were received inside or

outside of the HMO; inpatient and outpatient medical care information including ICD-9

codes and dates; and information about child’s birth including gestational age, birth

weight, apgar score, and mother’s date of birth.
Abt Associates Inc. Chapter 7 41

7. Measures

7.1. Outcome Measures

7.1.1. Outcomes Measured on Continuous Scales

Thirty-five of the 42 outcomes in this study were measured on a continuous scale. Each

of these 35 outcome measures was obtained from administration of commercially

available assessment instruments and in each case we followed the test publisher’s

instructions for administering the assessments and assigning scores. After the outcome

measures were entered into a computerized database, each measure was subjected to a

series of checks prior to its inclusion in the analysis data set. A record identified in any of

the following checks triggered a process of looking up the original hand-recorded

assessment form, recalculating summary scores (if applicable), and checking against the

value shown in the computerized database:

1. Either raw or scale score outside the range of values indicated in the test’s

technical manual.

2. Child had either a raw score but a missing scale score, or a scale score but a

missing raw score.

3. Standardized (studentized) residuals from model with scale score regressed on

raw score exceeds cut-off level7.

4. Standardized (studentized) residuals from model with scale score regressed on age

and sex exceeds cut-off level.

5. Standardized (studentized) residuals from model with raw score regressed on age

and sex exceeds cut-off level.

6. Very unusual value identified in scatter-plot of raw score versus age.

7. Very unusual value identified in scatter-plot of scale score versus age.

7.1.2. Dichotomous Outcomes: Tics and Stuttering

Unlike the previously described continuous outcome measures, the tics and stuttering

outcomes were not obtained from commercially available assessment batteries. As will be

described below, assessments of the presence of tics and stuttering among study

participants were obtained from multiple sources. As part of determining the most valid

way to construct the child outcomes for tics and stuttering, we consulted with a speech

and language expert, Dr. Thomas Campbell of the University of Pittsburgh. We reviewed

our tics and stuttering data with Dr. Campbell and made final decisions about how to

construct the outcomes. The decisions regarding the creation of the tics and stuttering

measures were made prior to any linking of exposure and outcome data.

7 We used a cut-off suggested by Bollen and Jackman (1990) to identify distance outliers (i.e., highly

unusual observations). Their suggested cutoff is the quantile of a t-distribution corresponding to probability

equal to  / 2n and degrees of freedom equal to the number of observations minus 1. With alpha set to

0.05 and n equal to 1,047, the value of the cut-off level is +/- 4.08.
Abt Associates Inc. Chapter 7 42

7.1.2.1. Tics

The study collected information on children’s tics from two sources: the parent reported

on any tics shown by their child currently (in the seven days prior to and including the

day of assessment) or ever, and the clinical assessor reported on any tics manifested by

the child during the testing session. Parents were given instructions on how to recognize

phonic and motor tics, and were asked to indicate whether the child exhibited each type

of tic. The clinical assessors were provided with standardized training on how tics might

be manifested in children.

Four binary outcome variables were created to indicate the presence of tics:

 Any motor tic observed by the clinical assessor at the time of the testing;

 Any phonics tic observed by the clinical assessor at the time of the testing;

 Any current motor tic reported by the child’s mother;

 Any current phonics tic reported by the child’s mother.

1. Separate tic variables were constructed for the assessor and the parent for three

reasons:

 The two reporters did not agree on which children had tics. Although both

the parents and the assessors identified 95 children as having motor tics,

only 22 of the 95 children were identified by both having motor tics. The

assessors identified 73 children as having motor tics that were not

identified by the parents, and the parents identified a different 73 children

as having motor tics that were not identified by the assessors. Similarly,

assessors identified 76 children as having phonic tics, the parents

identified 107 children as having phonic tics, and only 17 children were

identified as having phonic tics by both assessors and parents.

 There are logical reasons to believe that the two reporters might identify

different children as having tics, based on the fact that parents have a more

thorough knowledge of their child in various types of situations but the

assessor, unlike the parent, was observing the child in a potentially

stressful situation where any tics might be likely to appear.

 In previous studies using tics as a child outcome, physician reports are the

commonly used basis for identifying tics. Since physician reports of tics

are likely to reflect parent report rather than direct physician observation

of tics, we wanted to maintain a tic variable that comes closest to

approximating the reporting basis in the literature.

2. Our rationale for constructing separate variables for motor and phonics tics rather

than combining them into a single binary variable (any type of tic or none) is as follows.

When clinicians discuss tics, they typically are referring to motor tics. In order to

maintain a variable that links most directly to the way the field thinks about tics, we

decided to create separate variables for motor and phonics tics.
Abt Associates Inc. Chapter 7 43

3. Although both the parent and the assessor could report multiple types of motor or

phonics tics, we constructed a binary variable (any tic) rather than a count of tics, since

we believed that the actual number of tics identified may not have been reliable.

4. Parents reported both any current motor or phonics tics and any tics that the child ever

manifested. We decided to construct the tic variables for parents based only on their

reports of current tics. This is based on the recommendation of our technical expert that

transient tics are less likely to be severe or notable and therefore should not be

considered.

7.1.2.2. Stuttering

The study collected information on children’s stuttering from three sources: parent report

on whether the child currently stuttered; the clinical assessor report on any stuttering

exhibited by the child during the testing session; and reports from the children’s teachers

on any stuttering by the child while in school. Each reporter was asked to indicate the

severity of the child’s stuttering on a 7-point scale, where 1 = very mild and 7 = very

severe.

Three binary outcome variables were created to indicate the presence of stuttering:

 Any stuttering observed by the clinical assessor during the

testing;

 Any stuttering reported by the parent;

 Any stuttering at school reported by the teacher.

1. Reports on stuttering from parents, clinical assessors, and teachers were kept separate,

to maintain parallelism with the tic variables.

2. A child was identified as having a stutter only if the reporter indicated the severity of

the stuttering was at least 2 on the 7-point scale, where 2 = mild. This means that no

stuttering and very mild stuttering form the “0” value on the binary stuttering variable

and mild to very severe (2 and above) form the “1” value. This criterion was based on a

recommendation by the technical expert, who felt that a child rated as having very mild

stuttering probably does not have a stuttering disorder.
Abt Associates Inc. Chapter 7 44

7.2. Measures of Postnatal Exposure to Ethylmercury

7.2.1. Introduction to the Vaccination Histories File

Three sources of postnatal vaccination data (computer-automated, chart abstraction, and

parent provided immunization records) were combined to create a Vaccination Histories

File. This file contains the vaccination histories of the n=1,047 children in the analysis

data set. Each row of the Vaccination Histories File represents a record of a vaccine

received on a particular day. Thus, the file has many records per child. The file includes

each child’s “resolved vaccine history”, and also includes the raw, original, un-cleaned

vaccine data from each of three data sources. The resolved vaccine histories were

obtained from cleaning the raw, original data and resolving any discrepancies among the

three data sources and any discrepancies between the records and recommended

childhood vaccination schedules. Cumulative exposure amounts were calculated from

each child’s resolved vaccine history. Data cleaning procedures are described

subsequently.

Exhibit 7.2.1.1 shows an example resolved vaccine history for one child. The column

“Res_Vacdays1” shows the child’s age in days at the time of each vaccine receipt. The

exhibit shows that the child received vaccines on the day she/he was born (day 1), and at

ages 63, 126, and 183 days. The next three columns to the right show the type of vaccine

received (Res_VacType), the manufacturer (Res_Mfr), and the ethylmercury amount

contained in each vaccine (MercAmt). Additional detail is provided subsequently in this

document regarding vaccine types and the assignments of mercury amounts associated

with each receipt. The column labeled “RecptWtKG1” shows the child’s weight (in

kilograms) at the time of vaccine receipt. And the final column (Amt_wt1) shows the

mercury amount for each receipt divided by the child’s weight at the time of the vaccine

receipt. To create the exposure variables used in the analyses, the values of “Amt_wt1”

were summed over particular age ranges.
Abt Associates Inc. Chapter 7 45

Exhibit 7.2.1.1 Example of a Resolved Vaccine History

ChildID Res_Vacdays1 Res_VacType Res_MFR MercAmt RecptWtKG1 Amt_wt1

0001 1 HepB SKB 12.50 3.65 3.42

0001 63 DTP CON 25.00 5.90 4.24

0001 63 HIB MSD 12.50 5.90 2.12

0001 63 HepB SKB 12.50 5.90 2.12

0001 63 Polio LED 0.00 5.90 0.00

0001 126 DTP CON 25.00 7.17 3.49

0001 126 HIB MSD 12.50 7.17 1.74

0001 126 Polio LED 0.00 7.17 0.00

0001 183 DTP CON 25.00 8.51 2.94

0001 183 HepB SKB 12.50 8.51 1.47

0001 183 Polio LED 0.00 8.51 0.00

7.2.2. Overview of Steps from Raw Data to Creation of

Analysis Variables

Data on early childhood exposure to ethylmercury from thimerosal containing vaccines

and immune globulins were obtained from three sources: From computer-automated data

files, from abstractions of each child’s medical records, and from records provided by

parents at the time of the parent interview. An overview of the data processing steps from

the receipt of raw data files to the creation of the exposure variables used in analyses is as

follows:

1. The master list of study IDs was merged to each of the three vaccine files

(computer-automated, chart abstraction, and parent provided immunization

records). Any problems with ID discrepancies were resolved at this stage. Each of

the three files contained many records per child ID, where each record

represented a single vaccine receipt. Each file contained fields for child’s ID, type

of vaccine received, and either the date the vaccine was received or the child’s

age in days at the time of vaccine receipt. The computer-automated and chart

abstracted data sets also contained fields for vaccine manufacturer and lot

number. The master list of study IDs contained each child’s ID and date of birth.

2. For each of the three files (chart, computer automated, parent provided

immunization records) a new VacType (vaccine type) variable was created, where

the possible values taken by the variable, and the spelling of each vaccine type

were standardized across all three files. For example, in the computer-automated

data set, the codes 08, 43, and 45 took the value “HepB” on the VacType variable.

In the chart data set, entries originally recorded as “HEP B”, “HEP-B”, “HEP B

RECOMB”, and several others were assigned the value “HepB” on the VacType

variable. In the parent report data set, entries originally coded as “hepb”, “HepB”,

and several others were assigned the value “HepB” on the VacType variable. The

common coding of the VacType variable made possible the merging and

alignment of the three data sources on receipts of particular types of vaccines. All
Abt Associates Inc. Chapter 7 46

recodes were discussed and confirmed during weekly conference calls with the

whole study team (the team included CDC staff, principal investigators from each

of the HMOs, many of whom are pediatricians, data managers from each of the

HMOs, and Abt staff).

3. For the chart abstraction and parent provided immunization records files, each

child’s age in days corresponding to each vaccine receipt was calculated. The

computer-automated data set was delivered to Abt Associates with a field for

child’s age in days at time of vaccine receipt.

4. The three files were merged by child’s ID, child’s age in days at time of vaccine

receipt, and vaccine type.

5. The next step was to resolve discrepancies in vaccine histories. Discrepancies

included differences between the three data sources regarding the receipt of a

vaccine on a particular day, or between the vaccine history indicated in the data

set and the recommended vaccine schedule. An example of the former is a case

where the medical chart abstraction data set indicated receipt of hepatitis-B

vaccine for a child on day 1 (i.e. on day child was born), but where the computerautomated data showed no receipt on that day, and where the parent did not

provide a vaccine record. An example of the latter is when a particular data

source (e.g. chart or computer automated) indicated receipt of two full series of

DTaP, HIB, and HepB only two days apart. Receipt of two full series separated

by only two days represents a major discrepancy from recommended vaccine

schedules. It is exceedingly unlikely that a child would have received these series

two days apart. It is much more likely that the duplicate records are due to clerical

errors. Resolution of discrepancies was a major task and is considered in greater

detail in Section 7.2.3. This data cleaning phase focused exclusively on vaccines

and immune globulins received during the age range from birth to one year.

Resolution of discrepancies resulted in a “resolved vaccine history” for each

child.

6. In the next step we assigned a mercury exposure amount corresponding to each

vaccine receipt shown in each child’s resolved vaccine history. For example,

polio vaccine receipts were assigned an exposure amount equal to zero

micrograms of ethylmercury, hepatitis-b vaccines were assigned an exposure

amount equal to 12.5 micrograms of ethylmercury, and HIB vaccines were

assigned values of 0, 12.5, or 25 micrograms depending on the type of HIB

vaccine received. Additional details on the exposure amounts corresponding to

each vaccine type are provided in Section 7.2.4.

7. Next, we needed to obtain the child’s weight (in kilograms) corresponding to each

age (in days) that the child received a vaccine. For most records the process was

straightforward because children’s weights are often recorded in medical records

at the same time that vaccines are administered. In some cases, however, the data

on children’s weights were incomplete or did not align perfectly to the dates of

vaccine receipt. When a vaccine receipt did not have a corresponding weight, one

of two methods was used to impute a weight. If there were recorded weights

before and after the vaccine receipt, then linear interpolation was used to predict

the child’s weight on the day of vaccine receipt. If there were no recorded weights

after the vaccine receipt, then all of the child’s recorded weights were used in a
Abt Associates Inc. Chapter 7 47

growth curve model to predict the child’s weight at the time of the vaccine

receipt. The predictions from the growth curve models aligned very closely with

the growth curves published in the 2000 CDC Growth Charts for the United

States: Methods and Developments. Children with no recorded weights were

excluded from the analysis data set.

8. For each vaccine receipt, the mercury exposure amount (expressed as micrograms

of ethylmercury contained in the vaccine) was divided by the child’s weight (in

kilograms) at the time of vaccine receipt, resulting in a measure of exposure per

kilogram per vaccine receipt. For example, if a child weighed 8 kilograms at the

time of receipt of a vaccine containing 12.5 micrograms of ethylmercury, then the

value on this variable corresponding to this vaccine receipt would be equal to 12.5

/ 8 = 1.56 micrograms per kilogram.

9. Finally, for each child, the variables representing exposure per kilogram per

vaccine receipt were summed over all vaccines and immune globulins received

within each of three age ranges (0 to 7 months; 0 to 1 month; 1 to 7 months) to

produce the following three variables that were used in the analytical models:

 Exp07mos = “Exposure zero to 7 months” = Exposure per kilogram per

vaccine receipt summed over all vaccines and immune globulins received

during the age range from birth to seven months of age (1 to 214 days).

 HepB = “Exposure zero to 1 month” = Exposure per kilogram per vaccine

receipt summed over all vaccines and immune globulins received during the

age range from birth to one month of age (1 to 28 days). This variable was

named “HepB” because all vaccine received during this age range were either

hepatitis-b vaccines or hepatitis-b immune globulins.

 Exp17mos = “Exposure one to 7 months” = Exposure per kilogram per

vaccine receipt summed over all vaccines received during the age range from

one to seven months of age (29 to 214 days).

Several additional exposure variables were created and used in models to estimate

exposure effects when the receipt of thimerosal-containing vaccines coincided with

antibiotic treatment. Those variables are described in the section titled “Concurrent

Antibiotics-by-Exposure Interaction Models” (Section 9.2.6).

Three additional variables were created that were not used in the analytical models, but

were used for descriptive purposes. These three variables were similar to those defined

above, except that there was no division by the child’s weight at the time of vaccine

receipt. They are:

 Amt07mos = “Amount zero to 7 months” = Amount of ethylmercury per

vaccine receipt summed over all vaccines and immune globulins received

during the age range from birth to seven months of age (1 to 214 days).

 Amt01mos = “Amount zero to 1 month” = Amount of ethylmercury per

vaccine receipt summed over all vaccines and immune globulins received

during the age range from birth to one month of age (1 to 28 days).

 Amt17mos = “Amount one to 7 months” = Amount of ethylmercury per

vaccine receipt summed over all vaccines received during the age range from

one to seven months of age (29 to 214 days).
Abt Associates Inc. Chapter 7 48

7.2.3. Data Cleaning for Child Vaccination Histories

Data on early childhood exposure to Thimerosal from vaccines and Hepatitis-B immune

globulins were obtained from three sources: From computer automated data files8, from

abstractions of each child’s medical records, and from records provided by parents at the

time of the parent interview. Section 7.2.2 provided an overview of the data processing

steps from the receipt of raw data files to the creation of the exposure variables. The

purpose of the current section is to provide detail on the data cleaning procedures used to

derive a “resolved vaccine history” for each child. We use the term “resolved vaccine

history” to mean the final vaccine history for a child after having resolved any

discrepancies among the three data sources regarding the receipt of a vaccine on a

particular day, or between the vaccine history indicated in the raw data set and the

recommended vaccine schedule.

In the sections that follow we describe each of several data cleaning procedures that were

applied to the combined data set. Explanations of these procedures are accompanied by

examples. The data cleaning procedures were developed in close consultation with data

managers and investigators at each of the four participating HMOs, and with

investigators at the CDC. This team included several pediatricians with firsthand

experience in administering childhood vaccinations and in-depth knowledge of

vaccination policies and practices used during the time period covered by the study. The

team also included data managers and analysts from the HMOs who had a great deal of

experience in the use of vaccination data for research purposes.

In a process spanning several months, the entire team scrutinized countless records to

help develop and validate the data cleaning procedures. As computer automated cleaning

algorithms were developed, samples of resulting vaccine histories, shown along with the

raw data from each of the three data sources, were sent out to all team members and were

discussed during weekly telephone conferences. Near the end of the process, in order to

validate that the computerized algorithms did not generate any unexpected results, Abt

staff scrutinized printouts showing the resolved histories and the raw data for every child

in the data set.

8 Each HMO that participated in the study maintains computer-automated vaccine records for

administrative use and for research purposes. These computer-automated files are part of the Vaccine

Safety Datalink system.
Abt Associates Inc. Chapter 7 49

7.2.3.1. Step 1: Preliminary Vaccine History

After combining vaccination data from all three sources (chart, computer-automated,

parent provided immunization records) we preliminarily assumed, when a vaccine receipt

appears in one or more, but not all three data sources, that the vaccine was received by

the child. In other words, a vaccine did not need to appear in all three data sources in

order to be counted. As will be shown later, the assumption is preliminary because

subsequent cleaning rules may remove one or more of the vaccines from the resolved

history. An example of the application of this assumption is shown in Exhibit 7.2.3.1,

where the resolved vaccine history includes a hepatitis-B vaccine receipt at age 2-days.

The right-hand panel of the exhibit shows the vaccine records from the chart, computerautomated and parent provided immunization records data sets. The relevance of the

columns for manufacturer and lot number will become apparent in subsequent examples.

As shown in the exhibit, this receipt was indicated in the chart data, but was not present

in the computer-automated data. There were no parent provided immunization data for

this child. The left-hand panel of the exhibit shows the resolved vaccine history for ID #

258. This child received hepatitis-B vaccines at ages 2, 54, and 282 days, and several

other vaccines on ages 60, 178, and 233 days. The resolved vaccine history includes only

vaccines received during the age range spanning from birth to 365 days, i.e. from age (in

days) = 1 to 365. The columns of the middle panel of the exhibit are for indicators for

decision rules. None of those rules were applied in this example, but will be discussed in

a subsequent section.

7.2.3.2. Step 2: Application of 30-day and 15-day Algorithms

A set of algorithms was developed to detect duplicate records of receipts of HepB, Hib,

DTP, DTaP, combined DTP-Hib, combined DTaP-Hib, and polio vaccines within the

first year of life. Since polio vaccines did not contain thimerosal, it was not strictly

necessary to include them in the cleaning processes, but they were included nonetheless.

However, for the other vaccines listed above, failure to identify and remove duplicate

records from the resolved vaccine history would result in an overestimate of a child’s

mercury exposure. Checks for other, less commonly administered childhood vaccines are

described in a subsequent section of this document.

For all of the vaccine types listed above, except HepB, the algorithms were based on an

assumption that two receipts of a single type of vaccine separated by a period of 30 days

or less, represents a major discrepancy from the recommended vaccination schedule.

When such cases were detected, the algorithms marked one of the assumed duplicates for

removal, and retained the other in the resolved vaccine history. The process for deciding

which to keep and which to remove is described subsequently. These algorithms were

created with the full awareness that, in the rare instance that a child was mistakenly

administered one or more of these vaccines twice in a period of less than 30 days, the

application of the algorithm would result in an underestimate of the child’s actual

exposure. However, there was consensus among the study team that those instances were
Abt Associates Inc. Chapter 7 50

expected to be exceedingly rare, whereas duplicate entries of the same vaccine were

known to be common. Therefore, the algorithms focused on solving the common

problem, hence preventing overestimates of exposure, while simultaneously, in rare

instances, potentially causing underestimates.

The assumptions underlying the algorithms for HepB were similar to those described

above, except that, when one of the receipts is a HepB that was received in the first

month of life, it is plausible for two doses to be separated by a period of less than 30

days. This occurs, for example, in cases when a child receives a late birth dose of HepB,

or an early month-1 dose of HepB. Examples include records of children who received

HepB vaccinations on days 1 and 29, on days 15 and 43, and on days 2 and 31. The team

considered it to be implausible to receive two doses within a period of 15 days or less

when one of the receipts occurs in the first month of life, so the algorithm was

programmed accordingly. When neither receipt fell within the first 30 days of life, the 30-

day algorithm as previously described was applied for HepB vaccinations.

Detecting duplicate records for DTPs and Hibs was complicated by the fact that some

discrepancies were caused by situations such as a record of a combined DTP-Hib vaccine

in one data source, but separate DTP and Hib vaccines in another source, or entry of a

DTP in one source, but entry of a DTaP in another source. The algorithms were designed

to detect duplicates in all permutations of individual DTP, DTaP, DT TD, TT,

experimental DTaP, and HIB vaccines, and combined DTP, DTaP, and HIB vaccines.

When duplicate records were detected, a set of decision rules was applied to determine

which of the two records should be omitted and which should be retained in the resolved

vaccine history. The first decision rule was dependent on which of the two records had

non-missing information on manufacturer and/or lot number. The record containing

information on manufacturer and lot number was deemed to be more reliable and was

therefore retained. In order to facilitate the comparisons, a manufacturer and lot number

information score was computed for each record as follows. The combined data set

included two variables from the chart data set that listed vaccine manufacture and lot

number, and two additional variables listing vaccine manufacture and lot number from

the computer-automated data set. For each of those four variables, we created a

corresponding dummy variable that took the value “1” if the manufacturer or lot number

was non-missing, and took the value “0” otherwise. We then calculated the sum of the

four dummy variables to obtain the manufacturer and lot number information score for

each vaccine record. Possible values on this score were 0, 1, 2, 3, or 4. If one of the two

duplicates had a higher score, it was retained, and the other was omitted.

Exhibit 7.2.3.2 shows an example where combined DTP-HIB vaccines were retained on

days 121, and 185, while separate DTP and HIBs were omitted from the same days

because the former had non-missing manufacturer and lot number, while the latter did

not. This example also shows same-day-duplicate HIBs that were omitted on day 63. In

the “decision rules” columns of the exhibit, “1”s indicate omitted duplicates.
Abt Associates Inc. Chapter 7 51

In cases of a tie on the manufacturer and lot information score, a second decision rule

was implemented. Many duplicates were caused by slight discrepancies between the

computer-automated and Chart data sources on the child’s age in days at the time of

vaccine receipt. If either of the two duplicates matched the parent provided data regarding

the age in days at time of vaccine receipt, and the other did not, the record with the match

in the parent data set was retained and the other was omitted.

An example of the application of the second decision rule is presented in Exhibit.7.2.3.3

where HIB and polio vaccines recorded on day 117 were omitted from the resolved

history because the same vaccine types were recorded on day 120, and the latter had

matching parent provided data. This exhibit also has an example of an application of the

first decision rule. The exhibit shows DTaPs on days 62, 120, and 174 that were omitted

because the records of DTPs on the same days had non-missing manufacturer and lot

numbers.

Finally, if neither of the two previous rules produced a decision of which to retain and

which to omit, then one was chosen at random to retain, and the other was omitted. An

example is presented in Exhibit 7.2.3.4, where records of HIB and polio receipts on day

130 were omitted, but records of the same vaccines received on day 131 were retained in

the resolved vaccine history. The choice of which to omit and which to retain was

random.

7.2.3.3. Step 3: Check, Verify or Fix

This section summarizes a set of checks that were carried out on the children’s vaccine

histories to identify potential errors. Vaccine histories identified by this set of checks

were scrutinized by the study team during weekly phone conferences and decisions were

made either verifying that the history was already correct, or that fixes were needed.

Often a decision was made that a child’s medical records should be pulled and studied for

clues on how to resolve potential discrepancies. The process of checking and fixing was

iterative, such that after programming code was written and executed resulting in a

change in a set of resolved vaccine histories, the set of checks was run again. The

programming code used to make changes was applied only to the resolved vaccine

history. The original data from the chart, computer-automated, and parent immunization

records sources were never changed. A summary of the set of checks is as follows:

1) Verify that there are no two receipts of vaccines of a single type separated by less than

30 days, unless one is a HepB that was received during the first month of life.

2) Check for any receipts shown as having occurred before the child was born.

This type of error was caused by incorrect date entries. These errors were rectified by

examination of the child’s full vaccine history, followed by a decision regarding the most

likely correct date of receipt. For example, in one case a DTP-HIB vaccine was shown as

having been received 180 days prior to the birth of the child. By changing the date of
Abt Associates Inc. Chapter 7 52

receipt by one year, the vaccine lined up with other vaccine receipts that occurred when

the child was 185 days old.

3) Check for receipts of anything other than HepB during first 30 days of life.

Receipts of anything other than HepB or HepB immune globulin were treated as data

entry errors. Examples include a record of a receipt of HIB at age 2-days, and for a

different child, a receipt of DTP at age 1-day. In both cases the children received HepB

vaccinations on those days. In both cases it was believed that the entries of the HIB and

DTP vaccines were inadvertent.

4) Identify and check any histories indicating more than 3 HepB receipts in the first year

of life.

The vaccine histories of children with more than three HepB receipts during the first year

of life were examined by the study team. In instances where the receipts occurred around

birth, 2 months, 4 months, and 6 to 12 months, the histories were deemed to be plausible

and no further action was taken. When the four receipts deviated considerably from that

pattern, staff from the relevant HMO went back to the child’s medical charts to look for

clues as to what might have happened. In one example, receipts were listed at birth,

around 1 month, around 6 months, and around 7 months. Review of the charts indicated

that the record of receipt near 7 months was an error. That receipt was omitted from the

child’s resolved vaccine history.

5) Identify and check any histories indicating more than 3 DT receipts (including DTPs,

DTaPs, TT, experimental DTaP vaccines, DTaP-HIB or DTP-HIB combinations, etc) in

the first year of life.

The vaccine histories of children with more than three DT receipts during the first year

of life were examined by the study team. In instances where the receipts occurred around

2, 4, 6, and 12 months, the histories were deemed to be plausible and no further action

was taken. When the four receipts deviated considerably from that pattern, staff from the

relevant HMO went back to the child’s medical charts to look for clues as to what might

have happened. In one example, receipts were listed at days 66, 121, 154, and 188.

Review of the charts indicated that the record of receipt at 154 days was an error. That

receipt was omitted from the child’s resolved vaccine history.

6) Identify and check any histories indicating more than 4 HIB receipts (including

combination vaccines with DTP or DTaP) in the first year of life.

A finding that a child’s vaccine history indicated more than 4 HIB receipts triggered a

chart review by staff at the relevant HMO. In one case, the receipt of 5 HIBs by a single

child within the first year of life was deemed to be accurate.

7) Identify and check any histories indicating a receipt of an influenza vaccine in the first

120 days of life.
Abt Associates Inc. Chapter 7 53

It would be unusual to receive a flu shot in this age range. None were found.

8) Checks for Hepatitis-A, MMR, varicella and polio vaccines.

These vaccines never contained thimerosal, so obtaining clean histories was not critical

for these vaccines. However, checks were run to help identify anomalies in the children’s

histories. Checks included identification of histories where either varicella or MMR

vaccine was received in the first 180 days of life, histories where any hepatitis-A vaccine

was received before age 1 year, and histories indicating more than three polio receipts in

the first year

A list of all vaccine types remaining in the resolved vaccine histories of all children, and

the amount and the mercury amount assigned to each receipt is shown in Section 7.2.4.
Abt Associates Inc. Chapter 7 54

Exhibit 7.2.3.1

Example Vaccine History: Record of HepB Vaccine Receipt at Age 2-Days Shown in Chart Data, but no Corresponding Record

in Computer-Automated Data.

Resolved Vaccine Decision Rule Indicators Chart, Computer-automated, and Parent Provided

Immunization Data

History HepB HepB DTP DTP Same Bad Look

ID Age Res. Res. Polio Polio HIB HIB Day Date up Age Chart Cmptr Parent Chart Cmptr Chart Cmptr

Days Vac. Mfr. R1 R2 R1 R2 Dup. Days Vac. Vac. Vac. Mfr. Mfr. Lot Lot

258 2 HepB MIS 2 HepB MIS MIS

258 54 HepB SKB 54 HepB HepB ENG SKB ENG 110

258 60 DTP CON 60 DTP DTP CON CON 2B4 2B4

258 60 HIB PRX 60 HIB HIB PRA PRX M13 M13

258 60 Polio LED 60 Polio Polio LED LED 67 67

258 178 DTP LED 178 DTP DTP LED LED 350 350

258 178 HIB PRX 178 HIB HIB PRA PRX M13 M13

258 178 Polio LED 178 Polio Polio LED LED 352 352

258 233 DTP CON 233 DTP DTP CON CON 3J4 3J4

258 233 HIB PRX 233 HIB HIB PRA PRX M13 M13

258 233 Polio LED 233 Polio Polio LED LED 352 352

258 282 HepB SKB 282 HepB HepB ENG SKB 128 128

258 465 DTP DTP CON CON 3F5 3F5

258 465 HIB HIB PRA PRX M71 M71

258 465 MMR MMR MSD MSD 116 116

Notes: For brevity, manufacturer and lot numbers are truncated to three characters. Actual values span more characters and may include blank spaces.

Resolved vaccine history includes only vaccines received in the age range of 1 to 365 days.
Abt Associates Inc. Chapter 7 55

Exhibit 7.2.3.2

Example Vaccine History: Combined DTP-HIB Vaccines Retained on Days 121, and 185 While Separate DTP and HIBs Omitted

from Same Days Because Former Had Manufacturer and Lot Number. Same-Day-Duplicate HIBs Omitted on Day 63.

Resolved Vaccine Decision Rule Indicators Chart, VSD, and Parent Provided Immumization

Records Data

History HepB HepB DTP DTP Same Bad Look

ID Age Res. Res. Polio Polio HIB HIB Day Date up Age Chart Cmptr Parent Chart Cmptr Chart Cmptr

Days Vac. Mfr. R1 R2 R1 R2 Dup. Days Vac. Vac. Vac. Mfr. Mfr. Lot Lot

26 1 HepB MIS 1 HepB HepB MIS UNK MIS

26 1 63 HIB MSD 136

26 1 63 HIB UNK

26 63 DTP CON 63 DTP DTP MIS CON MIS 3D5

26 63 HIB MSD 63 HIB HIB MIS MSD MIS 136

26 63 HepB SKB 63 HepB HepB MIS SKB MIS ENG

26 63 Polio LED 63 Polio Polio MIS LED MIS 71

26 121 DTP-HIB LED 121 DTP-HIB LED 390

26 1 121 DTP DTP MIS UNK MIS

26 1 121 HIB HIB MIS UNK MIS

26 121 Polio LED 121 Polio Polio MIS LED MIS 71

26 185 DTP-HIB LED 185 DTP-HIB LED 390

26 1 185 DTP DTP MIS UNK MIS

26 1 185 HIB HIB MIS UNK MIS

26 185 HepB SKB 185 HepB HepB MIS SKB MIS ENG

26 185 Polio LED 185 Polio Polio MIS LED MIS 71

26 371 DTP-HIB UNK

26 371 MMR UNK

26 371 DTP DTP MIS UNK MIS

26 371 HIB HIB MIS UNK MIS

Notes: For brevity, manufacturer and lot numbers are truncated to three characters. Actual values span more characters and may include blank spaces.

Resolved vaccine history includes only vaccines received in the age range of 1 to 365 days.
Abt Associates Inc. Chapter 7 56

Exhibit 7.2.3.3

Example Vaccine History: Day 117 HIB and Polio Vaccines Omitted from Resolved History Because Same Vaccines on Day

120 Have Matching Parent Provided Data. DTaPs on Days 62, 120, and 174 Omitted Because DTPs on Same Days Have

Manufacturer and Lot Numbers.

Resolved Vaccine Decision Rule Indicators Chart, VSD, and Parent Provided Immunization

Records Data

History HepB HepB DTP DTP Same Bad Look

ID Age Res. Res. Polio Polio HIB HIB Day Date up Age Chart Cmptr Parent Chart Cmptr Chart Cmptr

Days Vac. Mfr. R1 R2 R1 R2 Dup. Days Vac. Vac. Vac. Mfr. Mfr. Lot Lot

373 1 HepB MIS 1 HepB HepB HepB MIS MIS

373 1 62 DTaP

373 62 DTP CON 62 DTP DTP CON CON 400 400

373 62 HIB PRX 62 HIB HIB HIB PRA PRX M00 M00

373 62 HepB SKB 62 HepB HepB HepB SKE SKB ENG 173

373 62 Polio LED 62 Polio Polio Polio LED LED 428 428

373 1 117 HIB PRX M00

373 1 117 Polio LED 432

373 1 120 DTaP

373 120 DTP LED 120 DTP LED 431

373 120 HIB PRA 120 HIB HIB PRA M00

373 120 Polio LED 120 Polio Polio LED 432

373 1 174 DTaP

373 174 DTP CON 174 DTP DTP CON CON M56 5M6

373 174 HIB PRX 174 HIB HIB HIB PRA PRX M23 M23

373 174 Polio LED 174 Polio Polio Polio LED LED 430 430

373 306 HepB SKB 306 HepB HepB HepB SKB SKB ENG ENG

Notes: For brevity, manufacturer and lot numbers are truncated to three characters. Actual values span more characters and may include blank spaces.

Resolved vaccine history includes only vaccines received in the age range of 1 to 365 days.
Abt Associates Inc. Chapter 7 57

Exhibit 7.2.3.4

Example Vaccine History: HIB and Polio Receipts from Day 130 Omitted, Same Vaccines Received on Day 131 Retained.

Choice of Which to Omit and Which to Retain was Random.

Resolved Vaccine Decision Rule Indicators Chart, VSD, and Parent Provided Immunization

Records Data

History HepB HepB DTP DTP Same Bad Look

ID Age Res. Res. Polio Polio HIB HIB Day Date up Age Chart Cmptr Parent Chart Cmptr Chart Cmptr

Days Vac. Mfr. R1 R2 R1 R2 Dup. Days Vac. Vac. Vac. Mfr. Mfr. Lot Lot

300 11 HepB SKB 11 HepB SKB 139

300 60 HIB PRX 60 HIB HIB PRA PRX M17 M17

300 60 HepB SKB 60 HepB HepB SKB SKB ENG ENG

300 60 Polio PMC 60 Polio Polio PAS PMC J06 JO6

300 1 130 HIB PRA M28

300 1 130 Polio PAS J11

300 131 HIB PRX 131 HIB PRX M28

300 131 Polio PMC 131 Polio PMC J11

300 183 HIB PRX 183 HIB HIB PRA PRX M28 M28

300 183 Polio PMC 183 Polio Polio CON PMC J11 J11

Notes: For brevity, manufacturer and lot numbers are truncated to three characters. Actual values span more characters and include may blank spaces.

Resolved vaccine history includes only vaccines received in the age range of 1 to 365 days.
Abt Associates Inc. Chapter 7 58

7.2.4. Mercury Amount Assigned to Each Childhood Vaccine

or Immune Globulin Receipt

Each vaccine or immune globulin listed in each child’s resolved vaccine history was

assigned a mercury amount. Our reference sources for determining the amount of

mercury contained in each receipt included the 1995 and 2000 Physician’s Desk

References (PDRs), Pediatrics (1999), Plotkin & Orenstein (1999), Plotkin & Mortimer

(1994), the Food and Drug Administration (FDA) website (accessed on 2/28/2003), and

personal communication with vaccine experts at the FDA. The mercury amounts

contained in experimental vaccines were provided by the participating HMOs, using data

from their own records.

Exhibit 7.2.4.1 shows all of the vaccine types listed in the children’s resolved vaccination

histories, their frequency of occurrence, and the mercury amount assigned to each. For

the time frame in which these vaccines were administered (all were received between

01/03/1993 and 01/08/1998), most of the vaccines had a single, constant mercury amount

that did not vary by manufacturer. For example, all hepatitis-b vaccines available during

that time contained 12.5 micrograms of ethylmercury per dose. Exceptions were DTaP,

TD, pneumococcal, HIB vaccines, and experimental vaccines. Smithkline Beecham

licensed a thimerosal-free DTaP vaccine under the name Infanrix on 1/29/1997. Prior to

that all available DTaP vaccines contained 25 micrograms of ethylmercury per dose. The

database of resolved vaccine histories include two receipts of Smithkline Beecham

DTaPs after 1/29/1997, but both were so soon after the license date that we made the

assumption that these two instances were not receipts thimerosal-free vaccine. We

therefore assumed these two doses contained 25 micrograms of ethylmercury each. The

receipt dates were 2/19/97, and 3/21/97.

Almost all of the tetanus/diphtheria (TD) in use during that time frame contained 25

micrograms of ethylmercury per dose. An exception was a TD vaccine manufactured by

Massachusetts Biologic Laboratories, which contained only 8.3 micrograms per dose.

However, the database contained no TD receipts where the manufacturer was

Massachusetts Biologic Laboratories.

Lederle made two pneumococcal vaccines in that time frame, one of which contained 25

micrograms of ethylmercury (product name = Pnu-Imune 23), while the other contained

zero micrograms of mercury (product name = Prevnar). The resolved vaccine histories do

include pneumococcal receipts where the manufacturer was Lederle. We know, however,

that at the one HMO where these pneumococcal receipts occurred, that the only product

in use at the time was the Prevnar product. Therefore, all pneumococcal receipts from

that HMO were assigned a mercury amount equal to zero micrograms. Children from

other HMOs with pneumococcal receipts in their resolved vaccine histories were known

or assumed9to have received the Merck product, which contained zero micrograms of

ethylmercury.

9 Of the 92 pneumococcal receipts in the resolved vaccine histories, only 1 receipt did not have any

information on manufacturer. We assumed this receipt contained zero micrograms of ethylmercury.
Abt Associates Inc. Chapter 7 59

HIB vaccines in use at that time contained zero, 12.5, or 25 micrograms of ethylmercury,

depending on the type and manufacturer. The HIB PRP-T vaccines made by Connaught,

Aventis Pasteur, Pasteur Merieux Connaught, and Smithkline Beecham with product

names ActHIB and OmniHIB contained zero micrograms of ethylmercury per dose. The

HIB PRP-OMP manufactured by Merck & Company with product name PedvaxHIB

contained 12.5 micrograms of ethylmercury per dose. And HIB HbOC vaccine made by

Lederle / Praxis with product name HibTITER contained 25 micrograms of ethylmercury

per dose.

Exhibit 7.2.4.1

Vaccine Types in Resolved Vaccine Histories and Amount of Ethylmercury in Each Receipt

Vaccine Type

Mercury

Amount

(Micrograms)

Frequency Comment

DT TD 25 23 Diphtheria and tetanus

DTP 25 1477 Diphtheria, tetanus, pertussis

DTP-HIB 25 1328 Combined DTP-HIB

DTaP 25 135 Diphtheria, tetanus andacellular pertussis

DTaP-HIB 25 4 Combined DTaP-HIB

DTaPHepB 12.5 6 Experimental combined DTaP-HepB

Flu 12.5 4 Influenza

HBIG 25 7 Hepatitis B immune globulin

HIB 0 47

H. influenzae type b

MercAmt=0 if Connaught/Merieux/Pasteur PRP-T

ActHIB, or SKB/GSK PRP-T OmniHIB

HIB 12.5 472 H. influenzae type b

MercAmt=12.5 if MSD PedVax-HIB

HIB 25 983 H. influenzae type b

MercAmt=25 if Lederle/Praxis/WAL HbOC Hibtiter.

HepA 0 5 Hepatitis A

HepB 12.5 2828 Hepatitis B

MMR 0 17 Measles, Mumps, Rubella

Pneumo 0 92 Pneumococcal

Polio 0 2740 Polio

TT 25 3 Tetanus toxoid

Varicel 0 3 Varicella

X01DTaP 0 9 X01 Experimental DTaP

X02(DTaP 25 9 X02 Experimental (Acelimune)

X03 25 3 X03 Experimental (Tetracel)

X03(D-H) 25 3 X03 Experimental (Tetracel)

X10 0 6 X10 Experimental Meningicoccal

10204
Abt Associates Inc. Chapter 7 60

7.3. Measures of Prenatal Exposure to Ethylmercury

7.3.1. Introduction to the Prenatal Ethylmercury Exposures

File

Two sources of prenatal vaccination data (maternal medical chart abstraction, and

maternal interview) were combined to create a Prenatal Ethylmercury Exposures File.

This file contains data on maternal exposure to ethylmercury from thimerosal-containing

vaccines and immune globulins received by the mothers of study participants during their

pregnancies with the focus children. The file contains one record per mother (n=1,047).

Each record lists the types of vaccines and immune globulins received, the amounts of

ethylmercury corresponding to each receipt, and the timing of each receipt. The timing of

receipt is expressed as the number of months from the receipt to the birth of the focus

child.

Examples of several prenatal records are shown in Exhibit 7.3.1.1. The first record (ID =

“x1”) corresponds to a mother who received a Gamulin injection (an immune globulin)

3.0 months prior to the birth of the focus child. The mercury amount corresponding to a

Gamulin receipt was assigned as 50 micrograms of ethylmercury. The example in the

second row (ID= “x2”) is a mother who received a rhogam injection (an immune

globulin) 2.8 months prior to the birth of the focus child. Rhogam is assumed to have

contained 12.75 micrograms of ethylmercury per receipt10. ID “x3” received two immune

globulin injections during her pregnancy, each containing 50 micrograms of

ethylmercury, resulting in a total prenatal exposure amount equal to 100 micrograms.

ID “x4” received an immune globulin 2.6 months before the focus child was born, and

received another on the day the child was born. Receipts on the day of the birth of the

focus child were assumed to have occurred after delivery, and are therefore not counted

in the total prenatal exposure amount. ID “x5” received adult dose influenza and tetatnus

vaccines during her pregnancy, resulting a total exposure amount equal to 50

micrograms. ID “x6” received a hepatitis-B vaccination resulting in 12.5 micrograms of

ethylmercury exposure. And, ID “x7” did not receive any vaccinations or immune

globulins during her pregnancy with the focus child.

10 Additional detail is provided in Section 7.3.3
Abt Associates Inc. Chapter 7 61

Exhibit 7.3.1.1

Example Records of Prenatal Ethylmercury Exposures from Thimerosal-containing Vaccines and Immune Globulins

Prenat- Immune Globulin 1 Immune Globulin 2 Flu HepB Tetanus DT

ID thimer Type Amt Mos Dose Type Amt Mos Dose Amt Mos Amt Mos Amt Mos Amt Mos

x1 50 GAMULIN 50 3.0 1CC

x2 12.75 RHOGAM 12.75 2.8 SINGLE DOS

x3 100 GAMULIN 50 5.3 UNK (FULL) GAMULIN 50 2.5 UNK (FULL)

x4 50 GAMULIN 50 2.6 J23003 GAMULIN 0 0 J24110

x5 50 25 7.0 25 0.8

x6 12.5 12.5 6.6

x7 0

PrenatThimer = total ethylmercury exposure from vaccines and immune globulins during pregnancy with focus child.

Columns labled “Amt” show the ethylmercury amount corresponding to a vaccine or immune globulin receipt.

Columns labeled “Mos” show the number of months between receipt and birth of the focus child.

“Flu” = influenza vaccine, “HepB” = hepatitis-B vaccine, “Tetanus” = tetanus, and ”DT” = diphtheria-tetanus. Records

indicated that these were the only types of thimerosal-containing vaccines received by the mothers of study participants

during their pregnancies with the focus children.

7.3.2. Overview of Steps from Raw Data to Creation of

Analysis Variables

Data on prenatal exposure to ethylmercury from thimerosal containing vaccines and

immune globulins were obtained from two sources: From abstractions of maternal

medical charts covering the period that the mother was pregnant with the focus child, and

from questionnaire items from the parent interview. An overview of the data processing

steps from the receipt of raw data files to the creation of the exposure variables used in

analyses is as follows:

1. The master list of study IDs was merged to the maternal medical chart and parent

interview files. Any problems with ID discrepancies were resolved at this stage.

The master list of IDs, the maternal medical chart, and the parent interview data

files each contained one record per child ID. The master list of study IDs

contained each child’s ID and date of birth. The maternal chart file contained a

field for Rh-blood group status of the mother. It also contained fields for the date,

dosage, manufacturer, and product names of immune globulins received, and for

dates and types of vaccines received by the mother. The parent interview file

contained data from questionnaire items that explained that women with Rhnegative blood types often receive rhogam or other immune globulins during

pregnancy to prevent problems with blood incompatibility, and asked the mother

if she had received any rhogam or other immune globulins during her pregnancy

with the focus child.

2. For chart records, all entries indicating the type of immune globulin received were

recoded to correct spelling errors and variations in abbreviations. For example, an

incorrectly spelled entry indicating receipt of “rhogan” would have been recoded

to take the value “RHOGAM”.
Abt Associates Inc. Chapter 7 62

3. Next, we calculated the number of months between vaccine or immune globulin

receipt and the date of delivery. Only those receipts that occurred within the

period spanning ten months (256 days) prior to the delivery date were counted

towards the total amount of prenatal exposure to ethylmercury from thimerosal.

Immune globulins received on the day of delivery were assumed to have occurred

after delivery, and were therefore not counted in the calculation of prenatal

exposure.

4. In the next step, discrepancies between the maternal medical chart-abstracted data

and the parent interview data on receipt of immune globulins during pregnancy

were resolved. During the weekly conference calls, the entire study team

reviewed all available data for discrepant cases. If the mother was rh-negative,

and either of the two data sources indicated receipt of an immune globulin during

pregnancy, then it was assumed that a receipt had occurred. Additional details on

this step are provided in Section 7.3.4 of this document.

5. A mercury exposure amount was assigned to each vaccine or immune globulin

receipt. See Section 7.3.5 for details.

6. Finally, a measure of total ethylmercury exposure from vaccine and immune

globulins received during pregnancy was created. For example, a child whose

mother received two vaccines during her pregnancy that each contained 25

micrograms of ethylmercury, e.g., a flu shot and a tetanus shot, would have a

received a value of 50 micrograms on this measure. This measure was used in the

analytical models and was defined as follows:

 PrenatThimer = “Prenatal exposure to ethylmercury from thimerosal” = The

sum total of mercury amounts from all thimerosal containing vaccines and

immune globulins received by the mother during her pregnancy with the focus

child.

7.3.3. Cleaning of Prenatal Ethylmercury Exposures Data

The chart-abstracted data on vaccine receipts during pregnancy were straightforward.

The records listed the types of and dates of vaccine receipts. Using the date of vaccine

receipt and the child’s date of birth, we calculated the number of months from receipt to

birth and assigned an exposure amount to the vaccine receipt only if the receipt occurred

before the child was born, and less than 10 months prior to the birth of the child.

Although the rule we applied would have counted receipts 10 months prior to birth (to

account for the possibility of late births) there were no receipts listed in the data set that

were near 10 months. In these data we found one occurrence of a diphtheria-tetanus (DT)

receipt that was 9.2 months prior to the birth of the child. All other vaccine receipts that

were counted toward the total exposure amounts were less than 9 months prior to birth.

The chart-abstracted data included records of receipts of the following thimerosalcontaining vaccines: Influenza, tetanaus, diphtheria-tetanus, and hepatitis-B. There were

also records of rubella vaccine receipts, but the rubella vaccines did not contain

thimerosal and were therefore of no consequence to the analyses.

The data on immune globulin receipts were less straightforward for several reasons. The

first was that the information on the product name and manufacturer sometimes
Abt Associates Inc. Chapter 7 63

conflicted with one another, or was sometimes missing entirely. This was a problem

because the amount of mercury included in a dose varied according to the product

received. A second potential conflict was between the mother’s recorded rh-status and

immune globulin receipt. The expectation is that rh-positive mothers would not receive

immune globulins and rh-negative mothers would usually receive immune globulins,

although this was not always the case. Finally, there was the potential for discrepancy

between the mother’s recollection of immune globulin receipt, as reported in the parent

interview, and the data recorded in the medical charts. The resolutions for each of these

types of discrepancies are described below.

An example of a discrepancy between a product name (type) and the product

manufacturer is a record that indicates that the product received was Rhogam and the

manufacturer was Armour. The product made by Armour was called Gamulin, and

thimerosal content in Gamulin was different than that of Rhogam. This discrepancy

probably occurred because, even though Rhogam is a specific product, the name

“rhogam” is often used as a generic term similar to the way “kleenex” is often used a

generic term to refer to facial tissues, even though Kleenex is a specific product.

Therefore, whenever a manufacturer or lot number was listed in the record that pointed

toward the receipt of a specific product, that information took precedence over the

information listed in the product type field. The Prenatal Ethylmercury Exposures File

includes the original text for product type and manufacturer, as well as the resolved

product type. The resolved product type represents our best estimate of what was actually

received, and was used for the purpose of assigning a mercury exposure amount.

Rhogam was the most commonly listed type of immune globulin at all four HMOs. In

cases where the evidence pointed to the receipt of an immune globulin, but where there

was no information on product type, manufacturer, or lot number, we assumed the receipt

was Rhogam. Section 7.3.4 describes variables that were created and analyses that were

conducted to evaluate the sensitivity of the model results to this assumption.

For each record we had to make a judgment, based on the available evidence, as to

whether the mother received an immune globulin during her pregnancy with the focus

child, and if so, what type of immune globulin was received. A set of codes was

developed to document the decisions that were made. The codes are shown in the column

labeled “Decision code” of Exhibit 7.3.3.1 and are defined as follows:

 Decision code 1 = prenatal immune globulin received: The chart indicated that the

mother was rh-negative, the mother reported having received an immune globulin

during her pregnancy with the focus child, and the chart abstraction listed an

immune globulin receipt within the period spanning ten months prior to the birth

of the child.

 Decision code 2 = prenatal immune globulin received: Although the mother did

not know whether she had received an immune globulin during her pregnancy

with the focus child, the chart clearly indicated that the mother was rh-negative,
Abt Associates Inc. Chapter 7 64

and the chart abstraction listed an immune globulin receipt within the period

spanning ten months prior to the birth of the child.

 Decision code 3 = prenatal immune globulin received: For these records there was

a discrepancy between the mother report and the chart-abstracted data. Although

the mother reported that she did not receive an immune globulin during her

pregnancy with the focus child, the chart clearly indicated that the mother was rhnegative, and the chart abstraction listed an immune globulin receipt within the

period spanning ten months prior to the birth of the child. We assumed the

mothers’ memories were in error and the chart data were correct.

 Decision code 4 = prenatal immune globulin received: The mother and the chart

agreed that there had been an immune globulin receipt, but the type of immune

globulin was not recorded in the records. Receipt of Rhogam was assumed.

 Decision code 5 = prenatal immune globulin received: The mother indicated that

she had received a prenatal immune globulin. According to the chart abstracted

data, these mothers were either rh-negative or their rh-status was not recorded.

The types and dates of receipts were not recorded. For these records we assumed

the mother report was correct and assumed Rhogam receipts were prior to the

birth of the child.

 Decision code 6 = prenatal immune globulin received: For this record, we

assumed that the chart data indicating that the mother was rh-positive was an

error, and assumed the remaining data from both the mother report and the chart

were correct. The mother and the chart agreed that there had been an immune

globulin receipt, and the chart indicated the type and date of receipt.

 Decision code 7 = no prenatal immune globulin received: For each of these

records, the mother indicated that she had received a prenatal immune globulin,

but the chart indicated that she was rh-positive and that no receipts had occurred.

We assumed the mother’s recollection was in error and that the chart was

accurate.

 Decision code 8 = no prenatal immune globulin received: The charts indicated

that the mother was rh-positive and contained no indication of immune globulin

receipt. The mothers in this group either said ‘no’ or they did not know whether

they had received and immune globulin during their pregnancies with the focus

children.

 Decision code 9 = no prenatal immune globulin received: For each of these

records, both the mother and the chart indicated receipts of immune globulins, but

the chart showed that the receipts occurred after the birth of the child. Note that

receipts that occurred on the day of the child’s birth (indicated as Months Prior to

Birth =0 in Exhibit 7.3.3.1) were assumed to have occurred after delivery and

were not counted as prenatal exposures.
Abt Associates Inc. Chapter 7 65

 Decision code 10 = no prenatal immune globulin received: Although the chart

indicated that the mother was rh-negative, a check-box on the chart abstraction

form indicated that no immune globulins had been received. The mother also

reported that she had not received an immune globulin during her pregnancy with

the focus child.

 Decision code 11 = no prenatal immune globulin received: The mothers in this

group indicated that they had not received an immune globulin during their

pregnancies with the focus children. The chart data fields were mostly missing or

incomplete. The assumption of no prenatal immune globulin receipts was based

primarily on the maternal report.

 Decision code 12 = no prenatal immune globulin received: Notes written on the

chart indicated that no immune globulins were needed. In one case the mother’s

husband was rh-negative, in the other case there was no note about the father rhstatus but the child was rh-negative so there was no issue of incompatibility.

Exhibit 7.3.3.1

Data Cleaning Decision Codes for Prenatal Immune Globulin Receipts

Chart Mother Original Chart Cleaned Assigned Months Chart

Decision Rh Reported IG Text for Text for Mercury Prior to Check Box

Code Status Receipt IG Receipt IG Receipt Amount Birth IG Received Freq.

1 RhNeg Yes GAMULIN GAMULIN 50 2.83 Yes 1

1 RhNeg Yes GAMULIN GAMULIN 50 3.03 Yes 1

1 RhNeg Yes HYP RHO-D HYPRHO-D 50 1.61 Yes 1

1 RhNeg Yes HYPRHO-D HYPRHO-D 50 2.47 Yes 1

1 RhNeg Yes J24211 GAMULIN 50 2.66 Yes 1

1 RhNeg Yes MISSING RHOGAM 12.75 2.14 Yes 1

1 RhNeg Yes MISSING RHOGAM 12.75 2.57 Yes 1

1 RhNeg Yes MISSING RHOGAM 12.75 2.93 Yes 1

1 RhNeg Yes MISSING RHOGAM 12.75 2.96 Yes 1

1 RhNeg Yes MISSING RHOGAM 12.75 3.09 Yes 1

1 RhNeg Yes MISSING RHOGAM 12.75 5.56 Yes 1

1 RhNeg Yes RHL174 RHOGAM 12.75 2.89 Yes 1

1 RhNeg Yes RHL228 RHOGAM 12.75 5.72 Yes 1

1 RhNeg Yes RHO GAM RHOGAM 12.75 2.3 Yes 1

1 RhNeg Yes RHOD HYPRHO-D 50 2.57 Yes 1

1 RhNeg Yes RHOGAM GAMULIN 50 2.11 Yes 1

1 RhNeg Yes RHOGAM GAMULIN 50 2.6 Yes 1

1 RhNeg Yes RHOGAM GAMULIN 50 5.33 Yes 1

1 RhNeg Yes RHOGAM RHOGAM 12.75 1.71 Yes 1

1 RhNeg Yes RHOGAM RHOGAM 12.75 1.74 Yes 1

1 RhNeg Yes RHOGAM RHOGAM 12.75 1.84 Yes 1

1 RhNeg Yes RHOGAM RHOGAM 12.75 1.97 Yes 1

1 RhNeg Yes RHOGAM RHOGAM 12.75 2.04 Yes 1

1 RhNeg Yes RHOGAM RHOGAM 12.75 2.14 Yes 1
Abt Associates Inc. Chapter 7 66

Exhibit 7.3.3.1

Data Cleaning Decision Codes for Prenatal Immune Globulin Receipts

Chart Mother Original Chart Cleaned Assigned Months Chart

Decision Rh Reported IG Text for Text for Mercury Prior to Check Box

Code Status Receipt IG Receipt IG Receipt Amount Birth IG Received Freq.

1 RhNeg Yes RHOGAM RHOGAM 12.75 2.17 Yes 2

1 RhNeg Yes RHOGAM RHOGAM 12.75 2.24 Yes 2

1 RhNeg Yes RHOGAM RHOGAM 12.75 2.34 Yes 1

1 RhNeg Yes RHOGAM RHOGAM 12.75 2.4 Yes 1

1 RhNeg Yes RHOGAM RHOGAM 12.75 2.57 Yes 1

1 RhNeg Yes RHOGAM RHOGAM 12.75 2.76 Yes 4

1 RhNeg Yes RHOGAM RHOGAM 12.75 2.8 Yes 3

1 RhNeg Yes RHOGAM RHOGAM 12.75 2.89 Yes 4

1 RhNeg Yes RHOGAM RHOGAM 12.75 3.03 Yes 1

1 RhNeg Yes RHOGAM RHOGAM 12.75 3.06 Yes 1

1 RhNeg Yes RHOGAM RHOGAM 12.75 3.09 Yes 2

1 RhNeg Yes RHOGAM RHOGAM 12.75 3.26 Yes 1

1 RhNeg Yes RHOGAM RHOGAM 12.75 3.29 Yes 1

1 RhNeg Yes RHOGAM RHOGAM 12.75 3.42 Yes 1

1 RhNeg Yes RHOGAM RHOGAM 12.75 3.45 Yes 1

1 RhNeg Yes RHOGAM RHOGAM 12.75 3.55 Yes 2

1 RhNeg Yes RHOGAM RHOGAM 12.75 4.87 Yes 1

1 RhNeg Yes RHOGAM RHOGAM 12.75 5.3 Yes 1

1 RhNeg Yes RHOGAM RHOGAM 12.75 5.69 Yes 1

1 RhNeg Yes RHOGAM RHOGAM 12.75 5.72 Yes 1

1 RhNeg Yes RHOGAM RHOGAM 12.75 6.74 Yes 1

1 RhNeg Yes RHOGAN RHOGAM 12.75 4.47 Yes 1

1 RhNeg Yes Rhogam RHOGAM 12.75 2.5 Yes 1

1 RhNeg Yes Rhogam RHOGAM 12.75 2.83 Yes 1

1 RhNeg Yes Rhogam RHOGAM 12.75 3.03 Yes 1

1 RhNeg Yes UNK RHOGAM 12.75 2.8 Yes 1

2 RhNeg DK MISSING RHOGAM 12.75 2.04 Yes 1

2 RhNeg DK RHOGAM RHOGAM 12.75 1.22 Yes 1

2 RhNeg DK RHOGAM RHOGAM 12.75 2.93 Yes 1

2 RhNeg DK UNK RHOGAM 12.75 2.76 Yes 1

3 RhNeg No MICROHOGAMMICRHOGAM 11.25 5.66 Yes 1

3 RhNeg No MISSING RHOGAM 12.75 3.16 Yes 1

3 RhNeg No MISSING RHOGAM 12.75 5.39 Yes 1

3 RhNeg No MISSING RHOGAM 12.75 6.61 Yes 1

3 RhNeg No RHOGAM GAMULIN 50 5 Yes 1

3 RhNeg No RHOGAM RHOGAM 12.75 2.01 Yes 1

3 RhNeg No RHOGAM RHOGAM 12.75 2.53 Yes 1

3 RhNeg No RHOGAM RHOGAM 12.75 2.73 Yes 1

3 RhNeg No RHOGAM RHOGAM 12.75 3.22 Yes 1

4 RhNeg Yes RHOGAM 12.75 2.34 Yes 1

4 RhNeg Yes RHOGAM 12.75 3.03 Yes 1

4 RhNeg Yes RHOGAM 12.75 5.26 Yes 1
Abt Associates Inc. Chapter 7 67

Exhibit 7.3.3.1

Data Cleaning Decision Codes for Prenatal Immune Globulin Receipts

Chart Mother Original Chart Cleaned Assigned Months Chart

Decision Rh Reported IG Text for Text for Mercury Prior to Check Box

Code Status Receipt IG Receipt IG Receipt Amount Birth IG Received Freq.

4 RhNeg Yes RHOGAM 12.75 7.3 Yes 1

4 RhNeg Yes RHOGAM 12.75 7.83 1

5 RhNeg Yes RHOGAM 12.75 3 1

5 Unk Yes RHOGAM 12.75 3 6

6 RhPos Yes RHOGAM GAMULIN 50 2.66 Yes 1

7 RhPos Yes . . No 2

8 RhPos DK . . 1

8 RhPos DK . . No 13

8 RhPos No . . 113

8 RhPos No . . No 748

9 RhNeg Yes . -21.18 Yes 1

9 RhNeg Yes MISSING . -0.03 Yes 1

9 RhNeg Yes RHIMGLOB . 0 Yes 1

9 RhNeg Yes RHL241A . -0.03 Yes 1

9 RhNeg Yes RHOGAM . 0 Yes 1

9 RhNeg Yes Rhogam . -0.03 No 1

9 RhNeg Yes UNKNOWN . 0 Yes 1

10 RhNeg No . . No 7

11 Unk No . . 64

11 Unk No . . No 2

12 RhNeg Yes . . No 2

Total: 1047
Abt Associates Inc. Chapter 7 68

7.3.4. Mercury Amount Assigned to Each Prenatal Vaccine or

Immune Globulin Receipt

Similar to the process described for childhood vaccine receipts, each vaccine or immune

globulin received by the mother during the prenatal period was assigned a mercury

amount. Our reference sources for determining the amount of mercury contained in each

vaccine receipt included the 1995 and 2000 Physician’s Desk References (PDRs),

Pediatrics (1999), Plotkin & Orenstein (1999), Plotkin & Mortimer (1994), the Food and

Drug Administration (FDA) website (accessed on 2/28/2003).

Final determination of the amounts of ethylmercury in prenatal immune globulins were

made in consultation with experts at the FDA and with the manufacturers of immune

globulin products. The amounts assigned were as follows:

 Rhogam: Between 1993 and 1997 the fill volumes ranged from 0.5 to 1.2

milliliters (ml), with an assumed average fill volume of 0.85 ml. Thimerosal was

present in Rhogam at 0.003% w/v, which is equivalent to 30 micrograms ( g )

per ml. Thimerosal was 50 percent ethylmercury by weight. Multiplying the three

quantities gives ml g

ml

g





30  0.85  0.50  12.75 of ethylmercury per receipt.

 MicRhogam: Between 1993 and 1997 the fill volumes ranged from 0.3 to 1.2

milliliters (ml), with an assumed average fill volume of 0.75 ml. Thimerosal was

present in MicRhogam at 0.003% w/v, which is equivalent to 30 g per ml.

Thimerosal was 50 percent ethylmercury by weight. Multiplying the three

quantities gives ml g

ml

g





30  0.75  0.50  11.25 of ethylmercury per receipt.

 Gamulin and Hyprho-d: The average fill volumes for Gamulin and Hyprho-d used

between 1993 and 1997 are assumed to be 1.0 ml. Thimerosal was present in each

type at 0.01% w/v, which is equivalent to 100 micrograms g per ml. Thimerosal

was 50 percent ethylmercury by weight. Multiplying the three quantities gives

ml g

ml

g





100 1.0  0.50  50 of ethylmercury per receipt.

Exhibit 7.3.4.1 lists all of the thimerosal-containing vaccines and immune globulins

received by the mothers during their pregnancies with the focus children. The exhibit also

shows the amount of ethylmercury assigned to each receipt.

As described previously, the word “rhogam” is often used as a generic term even though

it is a specific product. Since lot numbers and manufacturers were infrequently listed in

the medical charts, there are many instances where the product type was listed as

“rhogam”, but where we are uncertain whether the term was being used generically or
Abt Associates Inc. Chapter 7 69

was referring to the specific product “Rhogam”. If the term was being used generically,

then we may have assigned the wrong mercury amount to the receipt. For example, if a

Gamulin was administered, but the administering physician wrote in the chart that

“rhogam” was given, then we would have mistakenly assigned the receipt a mercury

amount equal to 12.75, instead of 50. The data set includes two variables, corresponding

to IG receipts 1 and 2, that each reflect the level of uncertainty regarding the type of

immune globulin received. Recall that up to two immune globulins were listed in the

chart abstracted data.

For receipt number 1, we defined a variable named PN_ProductInfo1 that could take the

values “1” or “0”. A value of “1” reflects a high level of confidence that we have correct

information on the type of product that was administered. The variable took the value “1”

if the lot number or the manufacturer, or a product other than “rhogam” was recorded in

the chart. These pieces of information provided specifics about the product that was

received. Immune globulin receipts where PN_ProductInfo1 takes the value “0” are

those where we lack the specific information on the product received. In several cases we

assumed that rhogam was received because we had no information on product type, and

in the remaining cases the chart listed the type as “rhogam”, but we are unsure of whether

the term “rhogam” was being used generically or was a reference to the specific product.

For receipt number 2, the same type of variable was created and named

PN_ProductInfo2.

We used the variables PN_ProductInfo1 and PN_ProductInfo2 in the following way. Our

primary set of analyses utilized the prenatal mercury amounts listed in Exhibit 7.3.4.1.

This is equivalent to an assumption that all receipts with low levels of certainty about the

product types were Rhogam receipts, and hence contained 12.75 micrograms of

ethylmercury. To evaluate the sensitivity of the model results to the potential

misspecification of the type of immune globulin received (and hence the total prenatal

mercury exposure amount) we fit an alternate set of models where we made an alternative

assumption that all receipts with low levels of certainty about the product types, were

Gamulin or Hyprho-d receipts, with 50 micrograms of ethylmercury. In these alternative

models, if PN_ProductInfo1 or PN_ProductInfo2 was equal to zero, than mercury

amount for the corresponding immune globulin receipt was set to 50 micrograms.

Exhibit 7.3.4.2 shows a three-way cross-tabulation of the variable PN_ProductInfo1 with

the variable containing the primary mercury amount assignments for immune globulin

receipt number one (PN_IG1_Amt), and with the variable containing the alternate

mercury amount assignments for immune globulin receipt number one

(PN_IG1_Amt_Alt). The exhibit shows that there were 75 immune globulin receipts

where the value of PN_ProductInfo1 was 0 and the primary mercury amount was

assigned as 12.75 micrograms. The alternate value for these 75 receipts was set to 50

micrograms. The same type of cross-tabulation for variables corresponding to immune

globulin receipt number two are shown in Exhibit 7.3.4.3. Finally, Exhibit 7.3.4.4 shows

a cross-tabulation of the primary variable measuring total prenatal mercury exposure

from thimerosal (PreNatThimer), with the variable measuring total exposure calculated

using the alternate amounts (PreNatThimer_Alt).
Abt Associates Inc. Chapter 7 70

Exhibit 7.3.4.1

Thimerosal-containing Prenatal Vaccines and Immune Globulins and Amount of

Ethylmercury in Each Receipt

Vaccine or

Immune

Globulin Type

Mercury

Amount

(Micrograms) Freq. Comment

Rhogam 12.75 88 Immune globulin

Micrhogam 11.25 1 Immune globulin

Gamulin 50 11 Immune globulin

Hyprho-d 50 3 Immune globulin

Influenza 25 9 Influenza (Adult Dose)

Tetanus 25 3 Tetanus

DT 25 8 Diphtheria-tetanus

HepB 12.5 1 Hepatitis – B

Exhibit 7.3.4.2

Cross-tabulation of PN_ProductInfo1, PN_IG1_Amt, and PN_IG1_Amt_Alt Variables

Cumulative

PN_ProductInfo1 PN_IG1_Amt PN_IG1_Amt_Alt Frequency Frequency

. . . 959 959

0 12.75 50 74 1033

1 11.25 11.25 1 1034

1 12.75 12.75 2 1036

1 50 50 11 1047

Exhibit 7.3.4.3

Cross-tabulation of PN_ProductInfo2, PN_IG2_Amt, and PN_IG_Amt_Alt Variables

Cumulative

PN_ProductInfo2 PN_IG2_Amt PN_IG2_Amt_Alt Frequency Frequency

. . . 1032 1032

0 12.75 50 11 1042

1 12.75 12.75 2 1044

1 50 50 3 1047
Abt Associates Inc. Chapter 7 71

Exhibit 7.3.4.4

Cross-tabulation of PreNatThimer and PreNatThimer_Alt Variables

Cumulative

PreNatThimer PreNatThimer_Alt Frequency Frequency

0 0 936 936

11.25 11.25 1 937

12.5 12.5 1 938

12.75 12.75 4 942

12.75 50 65 1007

25 25 18 1025

25.5 100 9 1034

50 50 10 1044

62.75 100 1 1045

100 100 2 1047

7.4. Covariates

Exhibit 7.4.1 summarizes the data sources and construction of all variable that were used

as covariates in the analytic models.
Abt Associates Inc. Chapter 7 72

Exhibit 7.4.1 Data Sources and Construction of Variables Used as Covariates in Analytical Models

Data Sources

Variable Description Parent

Interview

Medical

Abstract

Computer

Automated Additional Details

Variables Included in Every Model

ChildAge Child Age (Yrs) at assessment X X

sexmale Sex of child 0=female, 1=male X X

Birth weight 1 = if birth weight 2500-2999 grams

2 = Birth weight 3000-3999 grams

3 = Birth weight 4000+ grams

X X

Maternal IQ 1= Score in lower third of distribution

2= Score in middle third of distribution

3= Score in upper third of distribution

The Kaufman Brief Intelligence test

HOME_TotalIndex “HOME” Total Index X

Home Observation for Measurement of the

Environment was administered as part of the

parent interview. It is a measure of a child’s home

environment based on maternal self-report and

interviewer observations. The total score is a sum

of two subscores, a cognitive stimulation and an

emotional support score. The total score has a

wide variety of inputs that measure the quality of

the home environment including family interaction

patterns, physical attributes of the home, and

intellectual attributes.

PctPoverty1 (Percent of poverty line)/100

X

Percent of poverty line calculated from household

size, household income, and the 2004 poverty

guidelines for the48 contiguous states and the

District of Columbia shown in Department of

Health and Human Services Annual Update of

the HHS Poverty Guidelines; Federal Register,

Vol. 69, No. 30, February 13, 2004 / Notices

according to the following algorithm:

if HH size=2 then Pov=HH Income/12490;

if HH size=3 then Pov=HH Income/15670;

if HH size=4 then Pov=HH Income/18850;
Abt Associates Inc. Chapter 7 73

Exhibit 7.4.1 Data Sources and Construction of Variables Used as Covariates in Analytical Models

Data Sources

Variable Description Parent

Interview

Medical

Abstract

Computer

Automated Additional Details

if HH size=5 then Pov=HH Income/22030;

if HH size=6 then Pov=HH Income/25210;

if HH size=7 then Pov=HH Income/28390;

if HH size=8 then Pov=HH Income/31570;

if HH size=9 then Pov=HH

Income/(31570+3180);

if HH size=10 then Pov=HH

Income/(31570+6360);

Maternal Education 0= No HS degree

1=High school diploma or GED

2=attended some college, but no

degree

3=Associate’s degree or higher

X

SingleParent Child lives in a single parent

household(0/1) X

Site HMO-A

HMO-B

HMO-C

HMO-D

Variable defines four categories of HMO sites

where assessments took place.

Child and Family Characteristics

Computer

Experience

Child’s experience with using

computers X

0=No experience, 1=some experience, 2=much

experience.

Maternal Age 1= Maternal Age at Ch Birth: <=16

years

2=Maternal Age at Ch Birth: 17-39

years

3=Maternal Age at Ch Birth: >=40

years

X X X

OlderSibs Child has an older sibling (0/1) X =1 if child has older sibling living in home

YoungerSibs Child has a younger sibling (0/1) X =1 if child has younger sibling living in home

DayCareCentr # of center-based day care settings

prior to KG X

Number of center-based daycare settings

attended by child prior to kindergarten.
Abt Associates Inc. Chapter 7 74

Exhibit 7.4.1 Data Sources and Construction of Variables Used as Covariates in Analytical Models

Data Sources

Variable Description Parent

Interview

Medical

Abstract

Computer

Automated Additional Details

DayCareHome # of home-based day care settings

prior to KG X

Number of home-based daycare settings

attended by child prior to kindergarten.

EngOnly English only at home X

Binary indicator of whether English was the only

language spoken in the child’s home

Breast Feeding

(Duration)

0 = Breast Fed: <1mo

1 =Breast Fed: 1-6mos

2 = Breast Fed: 6+ mos

X

Child Birth Conditions

cMedicalHist_1 =1 if IUGR or birth headCM +/- 2SD

from Mean

X

A binary indicator of whether intrauterine growth

retardation was diagnosed at birth or head

circumference was +/- 2 standard deviations from

national mean at birth. National means and

standard deviations for head circumference

measurements of U.S. boys and girls at birth

obtained from Kuczmarski RJ, Ogden CL, Guo

SS, et al. 2000 CDC growth charts for the United

States: Methods and development. National

Center for Health Statistics. Vital Health Stat

11(246). 2002

C5APGARImpVal1 5-minute apgar

X

Child’s score on the 5 minute APGAR, which is a

test given to newborns five minutes after birth to

measure activity, pulse, grimace, appearance,

and respiration.

Prenatal Exposures (non-vaccine related)

PreNatNicotine_1 Used tobacco during pregnancy X X

= 1 if mother used any tobacco products during

pregnancy.

PreNatAlcohol_1 Alcohol use during pregnancy:

X X

0= none

1= occasional (1-4 drinks per month)

2= light (20-24 drinks/month or 5-6 per week)

3=moderat e(10-15 drinks per week)

4=heavy (more than 15 drinks per week)

Tuna Consumption Maternal tuna consumption during X 0= no consumption of tuna during pregnancy.
Abt Associates Inc. Chapter 7 75

Exhibit 7.4.1 Data Sources and Construction of Variables Used as Covariates in Analytical Models

Data Sources

Variable Description Parent

Interview

Medical

Abstract

Computer

Automated Additional Details

pregnancy 1 = moderate consumption (less than one serving

per week)

2 = high consumption (more than one serving per

week)

PreNatFish_1 High consumption of fish during

pregnancy. X

1= if mother reported eating tuna, and ocean fish,

and home-caught fish during pregnancy.

0 = else.

PreNatOrgMerc_1 Use of mercury-containing contact

lens solutions or nasal sprays during

pregnancy.

X

PreNatOrgMerc calculated as sum of PreNatContacts

and PreNatNasal, defined below:

PreNatContacts

Use of thimerosal-containing contact lens solution

during pregancy

2=high (regular use of this agent)

1=moderate (any non- regular use of this agent)

0=no use of this agent

PreNatNasal

Use of thimerosal-containing nasal sprays during

pregancy

2=high (regular use of this agent)

1=moderate (any non- regular use of this agent )

0=no use of this agent

PreNatHomePro_1 Prenatal exposure to mercury from

home products X

=1 if any exposure to mercury during pregnancy

from thermometers, florescent light bulbs, shoes,

or switches; =0 else.

Tooth Amalgams Mercury-containing dental amalgams

X

Amalgam fillings during pregnancy:

0 = mother had no amalgam fillings

1 = had amalgam filling, but no dental work and

did not chew gum during pregnancy

2= had amalgam fillings and had dental work or

chewed gum during pregnancy.

PreNatlead_1 Prenatal exposure to lead from

occupational or residential sources X

=1 if during pregnancy

mother worked in:
Abt Associates Inc. Chapter 7 76

Exhibit 7.4.1 Data Sources and Construction of Variables Used as Covariates in Analytical Models

Data Sources

Variable Description Parent

Interview

Medical

Abstract

Computer

Automated Additional Details

Worked in smelting, soldering, construction, or

demolition

or if during pregnancy mother lived in :

a pre-1950 home, or

a pre-1978 home that underwent painting or

renovation during her pregnancy.

PreNatIllDrug 1=Cocaine or Narcotic

X X

1= if mother reported any use of cocaine, crack,

heroin, methamphetamines, or speed during

pregnancy, or maternal medical chart indicated

suspected use or suspected use of cocaine or

narcotics during pregnancy.

0 = else.

Child Medical Conditions

IronDef_1 Anemia or iron deficiency X

=1 if any records of anemia and iron deficiency in

child’s chart. =0 else.

ADHDstimulant Use of ADHD stimulant in 12 hours

prior to assessment

X X X

=1 if child used any of the following stimulant

medications in the 12 hours prior to the clinical

assessment: Focalin; Ritalin; Methylin; Ritalin

SR; Methylin ER; Metadate ER; Ritalin LA;

Metadate CD; Concerta; Desoxyn;

Dextroamphetamine tablets (generic); DextroStat

tablets; Dexedrine tablets; Adderall tablets;

Dexedrine Spansules; Adderall XR capsules.

ChdPICA_1 Child Pica

X X

= 1 if child has pica, which is characterized by

persistent and compulsive cravings (lasting one

month or longer) to eat nonfood items.

=0 else.

Maternal Diagnoses

MatLangDel Maternal Language Delay X X

=1 if mother ever diagnosed as having language

delay; =0 else.

MatSpeechDel Maternal speech delay X X

=1 if mother ever diagnosed as having speech

delay; =0 else.
Abt Associates Inc. Chapter 7 77

Exhibit 7.4.1 Data Sources and Construction of Variables Used as Covariates in Analytical Models

Data Sources

Variable Description Parent

Interview

Medical

Abstract

Computer

Automated Additional Details

MatSTUTTER Maternal stuttering X X

=1 if mother ever diagnosed as having stuttering;

=0 else.

MatADHD Maternal ADHD X X

=1 if mother ever diagnosed as having ADHD; =0

else.

MatTIC Maternal tics

(No mothers in this sample had this

diagnosis. This variable not used in

models.)

X X

=1 if mother ever diagnosed as tics; =0 else.

Quadratic and Cubic Forms

ChildAge2 ChildAge2(squared) X X

ChildAge3 ChildAge3(cubed) X X

PctPoverty1_2 (PctPoverty1/100) 2(squared) X

PctPoverty1_3 (PctPoverty1/100) 3(cubed) X

HOME_TotalIndex2 HOME_TotalIndex2(squared) X

HOME_TotalIndex3 HOME_TotalIndex3(cubed) X

Variables Used Only in Models for Finger Tapping Outcomesa

Spline9 =1 if ChildAge > 9.0; =0 Else X X

ChildAge_Spline9 Childage * Spline9 X X

ChildAge2_Spline9 Childage2* Spline9 X X

a

Finger tapping tests for children aged 9 and above were slightly different than tests for younger children. Spline term allows for separate intercepts for children above and below

9 years. Spline*ChildAge and Spline*ChildAge2 terms allow for different age slopes for children above and below 9 years.
Abt Associates Inc. Chapter 7 78

7.5. Imputation of Missing Values

The analysis data set contained no missing values on measures of ethylmercury exposure

from thimerosal-containing vaccines and immune globulins. Having non-missing values

on exposure measures was a requirement for inclusion in the study. The postnatal

exposure measures were calculated as the amount of mercury contained in a received

vaccine or immune globulin, divided by the child’s weight at time of vaccine receipt, and

summed over the appropriate age range. Thus, there was a requirement for data on each

child’s weight at the time of vaccine receipt. An explanation of imputation of missing

weight data was provided in Section 7.2.2. To re-cap, linear interpolation was used if the

missing weight value was between two known weight values, and predicted values from a

growth-curve model were used as imputed values when missing weight values were not

followed by recorded weight values. Children with no recorded weights were excluded

from the analysis data set.

We did not conduct imputations for missing values on outcome measures. The consensus

among the Principal Investigators at the CDC, the four participating HMOs, and Abt

Associates, and the view shared by the study’s External Expert Consultants, was that the

analyses should be limited to records with non-missing values on outcome measures.

Most of missing values on outcome measures were due to children not completing

assessments when they became fatigued or emotional. In a few cases, the tests were

administered incorrectly. For example, in some cases an incorrect basal or ceiling was

used. On the finger tapping and grooved pegboard outcomes, some of the missing values

were caused by equipment failures. Missing values on tics and stuttering outcomes

occurred when parents or assessors failed to fill-out the relevant forms. On parent ratings

of attention/executive functioning, and behavior regulation, some of the missing values

were due to language barriers, i.e., when parents did not understand the instruments. A

relatively large proportion of teachers failed to return rating forms for stuttering and for

attention/executive functioning, and behavior regulation. The numbers of missing and

non-missing values for each outcome measure are shown in Section 9.1.2., Exhibit

9.1.2.1.

In cases where there were missing values on covariate measures, we compared results

from a single-imputation analysis methodology to a multiple-imputation methodology.

Details follow.

There are two separate issues to consider in the imputation process. One is the method for

obtaining an imputed value. Examples of methods include stochastic regression

imputation, hot deck, cold deck, and mean value imputation. We used a stochastic

regression imputation method, as described below. The second issue is whether the

analysis is based on a single-imputation or on multiple-imputations.
Abt Associates Inc. Chapter 7 79

In the single-imputation methodology, each missing value is replaced with a single

imputed value, and the analysis proceeds as if the imputed data were comprised of actual,

observed values. In multiple imputation, there are several (usually 5 or 10) imputed

values calculated for each missing value. In our analyses we calculated 10 imputed values

for each missing value. None of these several values are exactly equal to one another

because there is a “random draw” component included in each of the imputed values. The

multiple-imputation analysis uses the data from all 10 random draws. The advantage of

multiple imputation is that it more fully accounts for the uncertainty arising from the use

of imputed values in place of observed data. Its disadvantage is that it is more

cumbersome to implement.

Our stochastic regression imputation method proceeded in the following manner.

Suppose a variable, x2, had several missing values. We fit a regression model to all of the

non-missing values of x2, where x2 was the outcome variable and all other covariates in

the data set were used on the right-hand side of the regression equation as independent

(predictor) variables. We saved the residuals from this model in a data set. Next, using

the parameter estimates from the fitted model, and the values on all of the other

covariates in the data set, we calculated the predicted value of x2, for each non-missing

record in the data set. Let us call the predicted value x2 of for child i,

i

x2

ˆ ,

Suppose child j had a missing value on the variable x2. Let us denote the imputed value

for child j as .

~

2 j

x To obtain the imputed value, we randomly selected a residual from the

previously described data set of residuals. Let us denote the randomly selected residual

value as rrandom. We then calculated the imputed value as the sum of the predicted value

obtained from the regression model, jx2

ˆ , and the randomly selected residual, rrandom. That

is, j j random x  x  r 2 2

ˆ

~ . This is called stochastic regression imputation because the imputed

value is obtained from the predicted value from a regression model and a random

(stochastic) component. The reason for adding the randomly selected residual to the

predicted value was to retain the same amount of variability in imputed values as exists in

the observed values.

After completing the stochastic regression imputation process on all variables that had

missing values, we obtained a data set with no missing values on covariates. The singleimputation analyses were based on that data set.

In the multiple imputation method, we created 10 data sets in the same manner as

described above. Each data set was slightly different from one another because of the

random component in each imputed value. In this method, our analysis models, (i.e., the

models used to estimate the effects of ethylmercury exposure on outcomes), were fit to

each of the 10 data sets. This resulted in 10 estimates for each model parameter, and 10

standard error estimates for each model parameter. The final estimate for a particular

model parameter was calculated as the mean of the 10 separate estimates from the 10 data

sets. And the final standard error for that parameter was calculated as a function of the

mean of the standard errors estimated from the 10 regression models, a component
Abt Associates Inc. Chapter 7 80

measuring the variation between the estimates obtained from the 10 regression models,

and an adjustment factor for the 10 repetitions. A more formal explanation of the

calculations used in the multiple imputation procedure follows.

We fit a model of the general form below to each of the D data sets, (D = 1, 2, ... 10)

D d d d d d k d k d d Y     x   x   x   0, 1, 1, 2, 2, , ,

... ,

producing 10 estimates for each parameter

,...

ˆ

,...

ˆ

,

ˆ

...,

,

ˆ

,...

ˆ

,

ˆ

,

ˆ

,...

ˆ

,

ˆ

,1 ,2 ,10

1,1 1,2 1,10

0,1 0,2 0,10

 k  k  k

  

  

The final estimate for a parameter was calculated a the mean of the estimates from the 10

repetitions, e.g.,

10

ˆ

10

1

1,

1





d

 d



The standard error of the combined estimate, s.e.( ) , was calculated from a withinimputation variance component, and a between-imputation variance component, and an

adjustment factor for the number of repetitions (D).

Let Wd be the estimated variance of the parameter from repetition d,

i.e., 2

1,

)] ˆ[ . .( d d W  s e  .

The within-imputation variance was calculated as the average of the D=10 estimated

variances

10

10

1





d

d

D

W

W .

The between-imputation variance component was calculated as

2

1

1, 1

)

ˆ

(

1

1









D

d

D d D

B   .
Abt Associates Inc. Chapter 7 81

And the total was calculated as

D D BD D

D

T W

1

  ,

where (D+1)/D is the correction factor for D repetitions.

The standard error of 1 was calculated as TDs.e.( )  .

We applied both single-imputation and multiple-imputation methods to the main effects

models corresponding to the study’s primary research questions, and found that both

methods produced very similar results. In two sets of results the parameter estimates were

very similar, and the associations between exposure and outcome measures were

statistically significant or non-significant for the same outcomes and exposure measures

in both sets. These results are reported in Section 9.2.2.4.2. Since the analyses with the

single-imputation were far less cumbersome, all subsequent analyses used the singleimputation methodology.
Abt Associates Inc. Chapter 8 82

8. Analysis Approach

During the design phase of this study an analysis plan was developed that detailed what

outcomes were to be measured, what the data sources would be, how exposure measures

and covariates were to be coded, the forms of the statistical models that were to be fit to

the data, and the method for deciding which covariates were to be retained or dropped for

inclusion in the models for any particular outcome variable. The analysis plan went

through several iterations of review and comment by the Principal Investigators at the

CDC, at each of the four participating HMOs, and at Abt Associates, and by the study’s

External Expert Consultants11. Variable construction and the modeling approach

followed very closely to that analysis plan. In the first phase of analysis, only models that

were specified in the analysis plan were fit to the data. Following an agreed upon

protocol, none of the preliminary results were shown to or discussed with anyone outside

of the analysis team at Abt Associates prior to a meeting meeting that took place on April

8, 2005. At that meeting the preliminary results from those models were presented to the

group of Principal Investigators and the study’s External Expert Consultants. Those

results generated new ideas and motivated new lines of inquiry. Subsequent to the

meeting, requests to fit additional models came from the group of principal investigators

and the External Expert Consultants. Consequently, many of the results presented in

Section 9 are from models that were not specified in the original analysis plan. The

analyses that were specified in the original analysis plan, and the analyses that were

requested subsequent to the April 8, 2005 meeting are indicated in Exhibit 8.1.1.

The data sources and construction of measures were described previously in Sections 6

and 7. The remainder of Section 8 focuses on the analytical models used and on model

selection (i.e., which covariates are included in each model). The design and analysis

plans of the current study were strongly influenced by the Faroe Islands (Grandjean et al.,

1997) and Seychelles Islands (Davidson et al., 1998) studies of the effects of dietary

exposure to methylmercury during pregnancy on subsequent child outcomes.

Consequently, the designs and methods implemented in those studies are frequently

referenced in the discussion that follows.

Section 8.1 presents an example model specification and introduces notation that is used

throughout the remainder of the report. The full set of models is documented in Section 9.

The model specifications are presented in that section in order to clarify the interpretation

of the results that are presented there.

Section 8.2 documents the methods used for model selection. Discussions of how we

tested for effect modifiers, and how we approach the issue of multiple comparisons

follow in Sections 8.3 and 8.4.

11 See Acknowledgements section for listing of the Panel of External Consultants
Abt Associates Inc. Chapter 8 83

Exhibit 8.1.1.

Explanation of Analyses That Were Specified in Original Analysis Plan, and Analyses That

Were Requested Subsequent to Review of Preliminary Analysis Results.

Analyses Specified in Original Analysis

Plan

Analyses Requested Subsequent to April 8,

2005 Meeting

Exhibit 9.2.2.1 Main Effect Models (1) and (2)

Exhibit 9.2.2.2 Main Effect Models (1) and (2)

with Multiple Imputation for Missing Values of

Covariates

Exhibit 9.2.2.3 Main Effect Models (1) and (2)

with Alternative Coding of Prenatal Exposure

Variable

Exhibit 9.2.2.4 Additional Main Effect Models

for ADHD Outcomes

Exhibit 9.2.3.1. Summary of Thimerosal Effects

for Females

Exhibit 9.2.3.2. Summary of Thimerosal Effects

for Males

Exhibit 9.2.4.1. Summary of Models Testing

Effects of Cumulative Exposure Prenatal

Through Seven Months – Full Data Set

Exhibit 9.2.4.2. Summary of Models Testing

Effects of Cumulative Exposure Prenatal

Through Seven Months – Females

Exhibit 9.2.4.3. Summary of Models Testing

Effects of Cumulative Exposure Prenatal

Through Seven Months – Males

Exhibit 9.2.5.2. Summary of Multiple Sources

of Prenatal Mercury Models

Exhibit 9.2.6.1. Summary of Models for

Concurrent Antibiotics Effect –Birth to Seven

Months

Exhibit 9.2.6.2. Summary of Models for

Concurrent Antibiotics Effect –Birth to 28 Days,

and 29 Days to Seven Months

Read Table: The results summarized in Exhibit 9.2.2.1 were from models that were specified in the original analysis

plan. The results summarized in Exhibit 9.2.2.3 were from models that were requested subsequent to the presentation of

preliminary analysis results that took place on April 8, 2005.
Abt Associates Inc. Chapter 8 84

8.1. Overview of Analytical Models

In this section, we present an example model specification. This will allow us to

introduce some notation and some terminology and conventions that will be used

throughout the remainder of the document. The example model shown below is specified

to produce estimates of the effects of prenatal exposure, neonatal (birth to 28 days)

exposure, and cumulative exposure for the age range spanning 29 days to 217 days

months (1 to 7 months), on an outcome measure, Y:

               

l

j k l l

k

j k k

j

j j Y preNatThimer HepB Exp17mos oe cf St 0 1 2 3

The model is specified as an ordinary least squares regression model. The outcome

variable, Y, is assumed to be measured on a continuous scale. The error term,  , is

assumed to be conditionally independent and identically distributed normal with mean

zero and variance 2  .

There are three classes of right-hand-side variables in the model. The first class consists

of the ethylmercury exposure variables. In this model, the preNatThimer variable is a

measure of prenatal exposure to ethylmercury from thimerosal-containing vaccines and

immune globulins, the variable HepB is a measure of exposure to Hepatitis B vaccines

and immune globlins received in the first 28 days of life, and Exp17mos is a measure of

exposure from vaccines received in the age range of one to seven months (29-214 days)

(for details see Section 7.2).

The second class of right-hand-side variables represents other exposures. These are

prenatal or postnatal exposures to neurotoxins that may be related to the outcome

measures. We included this class of variables in the model in order to account for

relationships between exposures to neurotoxins and the outcome measures, when making

inferences about the effects of ethylmercury exposure on the outcome variable. Examples

include maternal alcohol use and maternal smoking during pregnancy. These terms are

represented in the model specification by joe , where “oe” stands for “other exposures”,

and the  jrepresent fixed effect parameters. The summation symbol means that we will

have 0, 1, 2, 3... up to “J” such terms in the model specification.

We have labeled the third class of right-hand-side variables as “child and family

statistical control variables”. This class of variables includes child and family

demographic factors, birth conditions, child medical conditions, and maternal diagnoses.

These are factors that we want to control for when making inferences about the

relationship of ethylmercury exposure to the outcome variable. Examples include age

and sex of the child, maternal age, and family socio-economic status. This class of

variables is represented in the model specification by kcf , where the subscript “k”
Abt Associates Inc. Chapter 8 85

indicates that we will have 1, 2, 3, ... up to “K” such terms in the model. The

corresponding parameters are numbered “J + k”, to indicate that the numbering follows

sequentially, after the “other exposures” variables. For example, if there were two “other

exposures” variables, then the first child and family statistical control variable in the

model would be subscripted with a 3 (J + k = 2 + 1 = 3). The second cf variable would

be numbered 4, (J + k = 2+2=4), etc.

The fourth class of variables in the model consists of site dummy variables. These are

variables that indicate each of HMOs where data were collected. The site dummies are

represented in the model specification by the terms Stl.

There are three hypotheses to be tested using the model shown in the example above.

The first is the test of the null hypothesis that there is no linear relationship of prenatal

ethylmercury exposure to the outcome variable. The second is a test of whether there is a

relationship between receipt of Hepatitis B vaccines or immune globulins in the first 28

days of life, and the outcome measure. And the third is a test for a linear relationship

between exposure to ethylmercury from vaccines received in the age range of one month

to seven months, and the outcome variable. These are two-sided hypothesis tests, and we

used a p<0.05 criterion for statistical significance. We use the following notation for

these three tests.

H0: 1  0 vs Ha: 1  0 ,

H0:  2  0 vs Ha:  2  0 ,

H0:  3  0 vs Ha:  3  0 .

Thirty five of the 42 outcomes analyzed in this study were measured on a continuous

scale. The example model shown above was specified as a linear regression model,

suitable for continuous outcome variables. Logistic regression models, that are

analogous to the linear regression models shown here, were fit to the data for the 7

outcomes that were coded as binary measures.

8.2. Inclusion of Covariates

Consulting pediatricians, neurotoxicolgists, and other experts identified a long list of

factors that were expected to have relationships with the neuropsychological measures

that are the outcome variables in this study. It is not feasible to implement an

experimental design that would strictly eliminate the potential influence of all of these

factors on the outcome measures. However, by specifying some or all of them as

covariates in our statistical models, we attempt to control for the influences of these

factors on the outcome variables, when making inferences about the relationship between

exposure to ethylmercury and the outcome measures.

In observational studies, selection of covariates can have a large impact on the inferences

about exposure variables. Statisticians consulting on the design of the current study
Abt Associates Inc. Chapter 8 86

(from External Expert Consultants, the CDC, the HMOs, and Abt Associates Inc.)

suggested and discussed three different approaches to covariate selection. The three

methods are not necessarily mutually exclusive. We will refer to the first method as the a

priori selection method. In this approach, model covariates are selected during the

design phase, well before data are collected. This method is based on the assumption that

there is strong prior knowledge of the relationships between outcomes and the variables

that are being considered as covariates and/or the relationships between ethylmercury

exposure and the variables that are being considered as covariates. In many cases, strong

prior knowledge exists. For example, for most of the outcome measures, we knew, a

priori, that the age of the child at the time of testing would be related to the outcome.

We will refer to the second method as backward elimination. This is a very commonly

used method of covariate selection in which one begins a step-wise process by fitting a

model with a full set of covariates, and identifying the covariate with the largest p-value.

That variable is dropped in the second iteration and a new model is fit, and the process is

repeated. This procedure continues until all covariates that do not reach a pre-set

significance criterion are dropped from the model.

Several consulting statisticians advocated the use of a change-in-estimate methodology.

In this approach, the decision of whether or not to include a variable as a covariate is

decided by fitting models with and without the covariate and comparing the estimates of

the target parameter(s) (i.e., the exposure variables) in the two models. If the difference

between the estimates from the two models of the target parameter(s) changes by more

than some pre-determined cut-off level (e.g., 10%), then the covariate is retained in

subsequent models, otherwise it is dropped.

Before considering the pros and cons of each approach, and describing the approach we

used, we review the typical reasons that covariates are included in models. Then we

review the covariate selection strategies used by Grandjean et. al (1997) for the Faroe

Islands study, and by Davidson, et. al. (1998) for the Seychelles study. And we review a

study by Budtz-Jorgensen et. al. (2007) that used the Faroe Islands data to compare the

resulting inferences on exposure variables when several different covariate selection

strategies were used.

Typically, covariates are included in regression models for any or all of the following

three reasons:

 To Reduce Residual Error and Increase Power. To the extent that a covariate

reduces the variance of the residual error, the power to detect a relationship

between the exposure variables and the outcome measure will be increased. On

the other hand, addition of covariates that are not related to the outcome measure

can have the effect of decreasing the precision of the exposure estimates and,

hence, decreasing power.

 To Control for Confounding. As an example of a confounder, suppose that for a

particular outcome measure, lower maternal IQ was related to lower scores on the

outcome measure. Furthermore, suppose there was a relationship between

maternal IQ and exposure such that lower maternal IQ tended to be associated
Abt Associates Inc. Chapter 8 87

with lower exposure. Then, in this scenario, maternal IQ is a confounder, and

omission of the variable could lead to a spurious finding that lower exposure is

related to lower scores on the outcome measure.

 To Test for Effect Modification. For example, suppose that biological differences

between boys and girls were such that the neurocognitive development of boys

was adversely affected by exposure to ethylmercury from vaccines or immune

globulins, whereas girls were not sensitive to exposure. Then sex would be an

effect modifier. If sex were an effect modifier, we would like to produce separate

estimates of exposure effects for boys and girls. This is accomplished by adding

sex-by-exposure interaction terms to the model. Without the interaction terms, the

overall estimated exposure effect on both boys and girls combined would fall

somewhere in between the two separate estimates. The sex variable could also be

a confounder, if, for example, boys scored lower than girls regardless of their

exposure and if the distribution of exposure levels was not the same for boys and

girls.

The method for selecting covariates in the Faroe Island study is described by BudtzJorgensen et. al. (2007):

“In the original analysis of the Faroese data Grandjean et al. (1997) developed an ad hoc criterion

for confounder selection combining information across different outcome variables. According to

this method the child's sex and age in addition to the maternal Raven score were considered

obligatory confounders for all outcome variables. Additional confounders were selected

approximately as follows. For each neuropsychological test important predictors were identified

using backward elimination (adjusted for the obligatory covariates) with p=0.10. Predictors that

were important for more than 3 outcomes (out of 17) were then included in the final regression

model for all outcomes.”

In the Seychelles study (Davidson, et. al., 1998), covariates were specified as part of the

study design and were “selected because of their potential to bias the assessment of the

association beween Hg and outcome”. A full model and a reduced model were fit to the

data for each outcome variable. The full model included all of the a priori selected

covariates and the reduced model “included only those covariates that did not duplicate

others or were felt to be the most relevant to child development in the Seychelles” (Marsh

et. al, 1995).

Thus, the covariate selection strategy used in the Faroe Islands study was a mix of the a

priori and backwards elimination methods. In the Seychelles study, the a priori method

was used. None of the covariates used in the Faroe Islands study were tested as effect

modifiers. In the Seychelles study, only one covariate, sex, was tested as an effect

modifier. “Each full and reduced model was run both with and without mercury

exposure by sex interaction terms to test the hypothesis that males and females have

different mercury exposure slopes” (Davidson, et. al., 1998).

An attractive aspect of the a priori method of covariate selection is that it reduces the

potential for criticism that the analysis will become some kind of data snooping exercise.

That is, it completely precludes the possibility of an analyst choosing covariates in such a
Abt Associates Inc. Chapter 8 88

way that the estimated exposure effects come as close as possible to some pre-conceived

notion held by the analyst. A negative aspect of this approach is that you might end up

specifying a model that does not fit the data well. And, if some of the covariates are not

correlated with the outcome, the standard errors on the key exposure variables can be

larger than they would have been had the non-significant covariate been eliminated.

Furthermore, there may be potential confounders for which there is not enough prior

knowledge for the decision of whether or not they should be included.

Backwards elimination methods are attractive from the point of view that they are often

used and familiar. But use of this method using the conventional p<0.05 criterion has

been criticized from the point of view that the selection criteria tends to favor covariates

with strong relationships to the outcome, but may omit important confounders (i.e.,

variables that have a weaker relationship to the outcome, but have a strong relationship to

exposure). Maldonado and Greenland (1993) evaluated a backwards elimination strategy

and a change-in-estimate strategy using simulated data from a poisson regression model.

They found that the p-value based method performed adequately when the alpha levels

were higher than conventional levels (0.20 or more), and found that the change-inestimate strategy performed adequately when the cut point was set to 10 percent.

However, their data, generated from a poisson model, and their analysis model, with only

a single covariate in addition to the key exposure variable, are very different than the

models anticipated for the current study.

Using the Faroe Islands data, Budtz-Jorgensen et. al. (2007) compared several covariate

selection strategies including backwards elimination, change-in-estimate, and the original

covariate selection strategy used by Grandjean et. al. 1997. They looked at the backwards

elimination strategy with three p-value cut-off levels, 0.05, 0.10, and 0.20, and, following

the recommendation of Maldonado and Greenland (1993) used a 10% criterion for the

change-in-estimate method. The measures that formed the basis of the comparisons were

the standard errors and the biases on the exposure variables. To assess bias, they

assumed that the full model with all 20 covariates produced an unbiased estimate of the

exposure effect. Bias was defined to be the difference between the exposure coefficient

estimated from the full model, and the coefficient estimated from the model with

covariates selected with a competing selection approach. They compared results of the

various selection strategies on models for two outcome variables. Both of these were also

used as outcome measures in the current study (the California Verbal Learning Test, and

the Boston Naming Test).

They found that, although the change-in-estimate strategy did an adequate job of

identifying confounders and keeping them in the model, it sometimes threw out variables

that were correlated with the outcome, but were not confounders. Therefore, this method

threw out variables that, if retained, would have reduced the residual error and reduced

the standard error of the exposure coefficient (thus increasing the power to detect

exposure effects). Although they found that backwards elimination with a p<0.05

criterion was un-suited for confounder identification, they found that when the p-value

criterion was set to p<0.20, backwards elimination strategy resulted in a reduction of

residual error variance and did not throw out important confounders. They recommended
Abt Associates Inc. Chapter 8 89

the backwards elimination strategy with a p<0.20 criterion over the change-in-estimate

strategy. The original strategy used by Grandjean et. al. was comparable to the

backwards selection strategy using the p<0.20 criterion in terms of reduction in bias and

standard error of the exposure effect.

For the current study, we used a covariate selection method that was a mix of all three of

the previously described methods, the a priori method, backwards elimination, and the

change-in-estimate method. Our philosophical starting point was that if there were

enough prior knowledge about all of the potential covariates then the ideal method for the

current study would have been an a priori only method for the selection of covariates.

We saw this as the ideal for the current study because a priori selection of covariates

would allay fears on the part of stakeholders about potential post-hoc manipulation of the

data to fit some prior notion. An a priori only method, however, was not practical for the

current study because there were too many variables for which we did not have prior

knowledge about their relationships to the outcome variables. This was especially true

for the “other exposures” variables. Including a large number of covariates that are not

related to the outcome, in the model, would have undesirable effects on the precision of

the exposure estimates.

Our strategy for selecting covariates was as follows. We identified a set of a priori

selected covariates that were included in all models for all outcomes. There was a second

set of variables that were tested for inclusion. There were two ways that the testing could

result in the determination that a particular variable would be retained in the final model

for a particular outcome. The first way utilized the backwards elimination strategy using

a p<0.20 cutoff. If the p-value for a particular variable was less that 0.20, then it was

retained in the final model. Each variable was simultaneously evaluated using a changein-estimate method with a 10 percent change criterion. When either method indicated

that a particular variable should be retained as a covariate, then that variable was retained

in the final model. This ensured that we did not drop variables that, if retained, would

substantially reduce residual error variance, and ensured that we did not drop variables

that are confounders.

We included dummy variables for HMO in all models. All but three of the remaining a

priori selected covariates that were used in our study were used as covariates in the final

models in both the Faroe Islands study and the Seychelles study. The three exceptions

were age, child’s computer experience, and the HOME score. Age was not used as a

covariate in the Seychelles study, presumably because all of children tested were in a

very narrow age range. The design of the current study was such that we tested subjects

in the age range of 7 to 10 years. Age was expected to have a strong relationship to the

outcome measures for the current study. Age was significant for both outcomes reported

by Budtz-Jorgensen et. al. (2007). Computer experience was not used as a covariate in

the Seychelles study because none of the outcome measures were based on a computer

interactive assessment. In the Faroe Islands study, computer experience was an important

predictor for the assessments that used a computer interactive testing regime. In the

current study, computer experience was an a priori covariate only for those particular

outcome measures that used a computerized assessment (the finger tapping and GDS
Abt Associates Inc. Chapter 8 90

vigilance tasks). It was tested for inclusion in models for all other outcomes. Finally, the

HOME scale score was not used in the Faroe Islands study. However, in the Seychelles

study, it was a significant predictor at the p<0.01 level for five of the six outcomes, and

significant at the p<0.05 level for the sixth.

In deciding which variables to treat as a priori selected, we looked at the statistical

significance associated with each covariate as reported in Budtz-Jorgensen et. al. (2007),

for the Faroe Islands study, and Davidson et. al. (1998), for the Seychelles Islands study.

Budtz-Jorgensen et. al. (2007) showed significance levels for covariates for two

outcomes and Davidson et. al. (1998) showed results associated with six outcomes.

Exhibit 8.2.1 shows that, with the exceptions of age, child’s computer experience, and the

HOME score, our a priori selected covariates were statistically significant at a p<0.20

criterion for at least four of the six total outcomes shown in the two papers.

For each outcome variable, the remaining covariates shown in Exhibit 8.2.1 were tested

for inclusion in the final model. These include variables that were used in the Faroe and

the Seychelles studies, but that were not consistently found to be confounders or reducers

of residual in those studies. These also include variables that were not examined in the

Faroe or Seychelles studies, but that had been suggested by consulting neurologists,

toxicologists or pediatricians because of their hypothesized relationship to the outcome

measures. We also tested higher order functional forms of age, percent poverty, and the

HOME score for inclusion. We included tests for these forms because, for example, we

did not know, a priori, whether a linear coding of the age variable would be the most

appropriate functional form to assume for each outcome measure. For some outcome

measures, quadratic or cubic forms of these variables significantly improved the fit.

The variable selection routine was implemented for each outcome measure using the

main effect model for prenatal exposure and cumulative exposure during the age range

from birth to 7 months (See Model 1, of Section 9.2.2.2 for specifications of this model).

For each outcome measure, variables that were selected for inclusion in that model were

retained as covariates in all other models for that outcome measure. All models for any

one particular outcome measure used the same covariate set. However, the selection

process was such that different outcome measures had different covariate sets. The list of

covariates that were used in models for each outcome measure is shown in Exhibit 8.2.2.
Abt Associates Inc. Chapter 8 91

Exhibit 8.2.1. A Priori Variables and Variables Tested for Inclusion as Model Covariates

Research Evidence

Variable Description / Levels Faroe

Islandsa

Seychelles

Islandsb

Variables Included in Every Model (a priori selected)

ChildAge Child Age (Yrs) at assessment 2/2c

: p=.20

2/2: p=.05

Not entered

sexmale Sex of child 0=female, 1=male 2/2: p=.20

0/2: p=.05

4/6: p=.20

3/6: p=.05

Birth weight

1 = if birth weight 2500-2999 grams

2 = Birth weight 3000-3999 grams

3 = Birth weight 4000+ grams

2/2: p=.20

1/2: p=.05

4/6: p=.20

3/6: p=.05

Maternal IQ

1= Score in lower third of distribution

2= Score in middle third of distribution

3= Score in upper third of distribution

2/2: p=.20

2/2: p=.05

4/6: p=.20

3/6: p=.05

HOME_TotalIndex “HOME” Total Index Not entered 6/6: p<.05

PctPoverty1 (Percent of poverty line)/100

SESd:

2/2: p=.20

2/2: p=.05

SESd:

5/6: p=.20

5/6: p=.05

Maternal Education 0= No HS degree

1=High school diploma or GED

2=attended some college, but no degree

3=Associate’s degree or higher

SESd:

2/2: p=.20

2/2: p=.05

SESd:

5/6: p=.20

5/6: p=.05

SingleParent Child lives in a single parent household (0/1)

SESd:

2/2: p=.20

2/2: p=.05

SESd:

5/6: p=.20

5/6: p=.05

Site HMO-A

HMO-B

HMO-C

HMO-D

Variables Tested for Inclusion: Child and Family Characteristics

Computer Experience

0=No experience

1=some experience

2=much experience.

Computerized

tests:

p=.05

Maternal Age

1= Maternal Age at Ch Birth: <=16 years

2=Maternal Age at Ch Birth: 17-39 years

3=Maternal Age at Ch Birth: >=40 years

1/2: p=.20

0/2: p=.05

1/6: p=.20

1/6: p=.05

OlderSibs Child has an older sibling (0/1) 1/2: p=.20

0/2: p=.05 Not entered

YoungerSibs Child has a younger sibling (0/1) 1/2: p=.20

0/2: p=.05 Not entered

DayCareCentr # of center-based day care settings prior to KG 1/2: p=.20

1/2: p=.05 Not entered

DayCareHome # of home-based day care settings prior to KG 1/2: p=.20

1/2: p=.05 Not entered

EngOnly English only at home Not entered full model

only/ ? signif.e

Breast Feeding

(Duration)

0 = Breast Fed: <1mo

1 =Breast Fed: 1-6mos

2 = Breast Fed: 6+ mos

0/2: p=.20

0/2: p=.05

full model

only/ ? signif.e

Variables Tested for Inclusion: Child Birth Conditions

cMedicalHist_1 =1 if birth headCM +/- 2SD from Mean Not entered 2/6e

: p=.20

0/6: p=.05
Abt Associates Inc. Chapter 8 92

Exhibit 8.2.1. A Priori Variables and Variables Tested for Inclusion as Model Covariates

Research Evidence

Variable Description / Levels Faroe

Islandsa

Seychelles

Islandsb

C5APGARImpVal1 5-minute apgar

Variables Tested for Inclusion: Prenatal Exposures (non-vaccine related)

PreNatNicotine_1 Used tobacco during pregnancy 0/2: p=.20

0/2: p=.05

full model

only/ ? signif.f

PreNatAlcohol_1 0=never - 4 heavy Not entered full model

only/ ? signif.f

Tuna Consumption

0= no consumption of tuna during pregnancy.

1 = moderate consumption (less than one serving/week)

2 = high consumption (more than one serving per week)

PreNatFish_1

1= if mother reported eating tuna, and ocean fish, and home-caught fish during

pregnancy.

0 = else.

PreNatOrgMerc_1 Use of mercury-containing contact lens solutions or nasal sprays during pregnancy.

PreNatHomePro_1 Prenatal exposure to mercury from home products

Tooth Amalgams

0 = mother had no amalgam fillings during pregnancy

1 = had amalgam fillings, but no dental work and did not chew gum during pregnancy

2= had amalgam fillings and had dental work or chewed gum during pregnancy.

PreNatlead_1 Prenatal exposure to lead from occupational or residential sources

PreNatIllDrug 1=Cocaine or Narcotic

Variables Tested for Inclusion: Child Medical Conditions

IronDef_1 Anemia or iron deficiency

ADHDstimulant Use of ADHD stimulant in 12 hours prior to assessment

ChdPICA_1 Child Pica

Variables Tested for Inclusion: Maternal Diagnoses

MatLangDel Maternal Language Delay

MatSpeechDel Maternal speech delay

MatSTUTTER Maternal stuttering

MatADHD Maternal ADHD

MatTIC Maternal tics

Variables Tested for Inclusion: Quadratic and Cubic Forms

ChildAge2 ChildAge**2 (squared)

ChildAge3 ChildAge**3 (cubed)

PctPoverty1_2 (PctPoverty1/100)**2 (squared)

PctPoverty1_3 (PctPoverty1/100)**3 (cubed)

HOME_TotalIndex2 HOME_TotalIndex**2 (squared)

HOME_TotalIndex3 HOME_TotalIndex**3 (cubed)

a Budtz-Jorgenson et al. (2007) Confounder Identification in Environmental Epidemiology. Assessment of Health effects of Prenatal

Mercury Exposure.

b Davidson et al. (1998). Effects of prenatal and postnatal methylmercury exposure from fish consumption on neurodevelopment.

Outcomes at 66 months of age in the Seychelles Child Development Study. JAMA 280(8): 701-707.

c Notation represents number of outcomes for which covariate was significant. For example, "1⁄2" should be interpreted to mean that

the covariate was significant for 1 of the 2 outcomes that were tested.

d

In Faroe Island study, a single measure of socio-economic status (the Hollingsead) was used. In Seychelles study SES variables

were paternal employment, paternal education, and maternal education.

e

In Davidson et. al, this variable took the value “1” if child had intrauterine growth retardation (IUGR) or if head size was > 2

standard deviations from mean at birth. In the current study, IUGR was an exclusionary condition.

e These covariates were included in the full model only. Their level of significance was not reported.
Abt Associates Inc. Chapter 8 93

Exhibit 8.2.2. Covariates Used in Models for Each Outcome Measure

Age

SexMale

Birth Wt.

Matern. IQ

Home

Pct Pov

Mat. Educ

Single Par.

Site

Comp Exp.

Mat Age

Older Sib

Young. Sib

DayCenter

DayHome

Eng Only

B Feed Dur

cMed HIst

Apgar

Pre Nicotine

Pre Alcohol

Pre Tuna

Pre Fish

Pre Org MerPre HomePr

A

malgams

Pre Lead

Pre Ill Drug

Iron Def

A

D

H

D

Stim

Chld Pica

Mat Lang

Mat Speech

Mat Stutt

Mat A

D

H

D

Mat Tic

Age2

Age 3

PctPov2

Pct Pov3

Home2Home3

Spline

Spline*Age

Spline*Age2

Speech and

Language

Boston Naming

Test X X X X X X X X X X X X X X X X X X X X X

NEPSY: Speeded

Naming X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X

NEPSY:

Comprehension of

Instructions

X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X

CELF: Formulated

Sentences X X X X X X X X X X X X X X X X X X X X X X

CELF: Recalling

Sentences X X X X X X X X X X X X X X X X X X X X X X

GFTA: Articulation

(lower = better) X X X X X X X X X X X X X X X X X X

Stuttering:

Assessor Rating

(lower = better)

X X X X X X X X X X X X X X X X

Stuttering: Parent

Rating (lower =

better)

X X X X X X X X X

Stuttering:

Teacher Rating

(lower = better)

X X X X X X X X X X X X X X X X X

Verbal Memory

CVLT-C: Free

Recall, No Delay X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X

CVLT-C: Free

Recall, Short

Delay

X X X X X X X X X X X X X X X X X X

CVLT-C: Cued

Recall, Short

Delay

X X X X X X X X X X X X X X X X X X X

CVLT-C: Free X X X X X X X X X X X X X X X X X X X X X X X X
Abt Associates Inc. Chapter 8 94

Exhibit 8.2.2. Covariates Used in Models for Each Outcome Measure

Age

SexMale

Birth Wt.

Matern. IQ

Home

Pct Pov

Mat. Educ

Single Par.

Site

Comp Exp.

Mat Age

Older Sib

Young. Sib

DayCenter

DayHome

Eng Only

B Feed Dur

cMed HIst

Apgar

Pre Nicotine

Pre Alcohol

Pre Tuna

Pre Fish

Pre Org MerPre HomePr

A

malgams

Pre Lead

Pre Ill Drug

Iron Def

A

D

H

D

Stim

Chld Pica

Mat Lang

Mat Speech

Mat Stutt

Mat A

D

H

D

Mat Tic

Age2

Age 3

PctPov2

Pct Pov3

Home2Home3

Spline

Spline*Age

Spline*Age2

Recall, Long

Delay

CVLT-C: Cued

Recall, Long

Delay

X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X

CMS Stories 1:

Immediate Recall X X X X X X X X X X X X X X X X X

CMS Stories 2:

Delayed Recall X X X X X X X X X X X X X X X X X X X X X X X X X

Achievement

WJIII: LetterWord

Identification

X X X X X X X X X X X X X X X X X X X X X X X

Fine Motor

Coordination

Grooved

Pegboard:

Dominant Hand

(lower = better)

X X X X X X X X X X X X X X X X X X X

Grooved

Pegboard: Nondom Hand (lower

= better)

X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X

Finger Tapping:

Dominant Hand X X X X X X X X X X X X X X X X X X X X

Finger Tapping:

Non-dominant

Hand

X X X X X X X X X X X X X X X X X X X X X X X X X X

Visual Spatial

Ability

Stanford Binet:

Copying X X X X X X X X X X X X X X X X X X X X X X X X X X X

Attention/

Executive

Functioning

GDS Vigilance

Task: Correct X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X
Abt Associates Inc. Chapter 8 95

Exhibit 8.2.2. Covariates Used in Models for Each Outcome Measure

Age

SexMale

Birth Wt.

Matern. IQ

Home

Pct Pov

Mat. Educ

Single Par.

Site

Comp Exp.

Mat Age

Older Sib

Young. Sib

DayCenter

DayHome

Eng Only

B Feed Dur

cMed HIst

Apgar

Pre Nicotine

Pre Alcohol

Pre Tuna

Pre Fish

Pre Org MerPre HomePr

A

malgams

Pre Lead

Pre Ill Drug

Iron Def

A

D

H

D

Stim

Chld Pica

Mat Lang

Mat Speech

Mat Stutt

Mat A

D

H

D

Mat Tic

Age2

Age 3

PctPov2

Pct Pov3

Home2Home3

Spline

Spline*Age

Spline*Age2

Responses

GDS Vigilance

Task: Errors

(lower = better)

X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X

WISC III: Digit

Span, Forward

Recall

X X X X X X X X X X X X X X X X X X X X X X X X X X

WISC III: Digit

Span, Backward

Recall

X X X X X X X X X X X X X X

WISC III: Digit

Span, Combined X X X X X X X X X X X X X X X X X X X X X

BRIEF Parent

Rating:

Metacognition

(lower = better)

X X X X X X X X X X X X X X X X X X X X X X X X X X X

BRIEF Teacher

Rating:

Metacognition

(lower = better)

X X X X X X X X X X X X X X X X X X X X X X X X X X X X

Behavior

Regulation

(lower = better)

CRS-R: Parent

Rating:

Hyperactive/Impul

sive

X X X X X X X X X X X X X X X X X X X X X

CRS-R: Teacher

Rating:

Hyperactive/Impul

sive

X X X X X X X X X X X X X X X X X X X

CRS-R: Parent

Rating: Inattentive X X X X X X X X X X X X X X X X X X X X X X X X

CRS-R: Teacher

Rating: Inattentive X X X X X X X X X X X X X X X X X X X X X

BRIEF Parent

Rating: Behavior X X X X X X X X X X X X X X X X X X X X X
Abt Associates Inc. Chapter 8 96

Exhibit 8.2.2. Covariates Used in Models for Each Outcome Measure

Age

SexMale

Birth Wt.

Matern. IQ

Home

Pct Pov

Mat. Educ

Single Par.

Site

Comp Exp.

Mat Age

Older Sib

Young. Sib

DayCenter

DayHome

Eng Only

B Feed Dur

cMed HIst

Apgar

Pre Nicotine

Pre Alcohol

Pre Tuna

Pre Fish

Pre Org MerPre HomePr

A

malgams

Pre Lead

Pre Ill Drug

Iron Def

A

D

H

D

Stim

Chld Pica

Mat Lang

Mat Speech

Mat Stutt

Mat A

D

H

D

Mat Tic

Age2

Age 3

PctPov2

Pct Pov3

Home2Home3

Spline

Spline*Age

Spline*Age2

Regulation

BRIEF Teacher

Rating: Behavior

Regulation

X X X X X X X X X X X X X X X X X X X X X X X X X X X

Tics (lower =

better)

Motor tics

(current):

Assessor Rating

X X X X X X X X X X X X X X X X X X X X X X X X X

Phonics tics

(current):

Assessor Rating

X X X X X X X X X X X X X X X X

Motor tics

(current): Parent

Rating

X X X X X X X X X X X X X X X X X X X X X X X X X X X

Phonics tics

(current): Parent

Rating

X X X X X X X X X X X X X X X X X X X X X X X X

General

Intellectual

Functioning

WASI Verbal IQ X X X X X X X X X X X X X X X X X X X X X

WASI

Performance IQ X X X X X X X X X X X X X X X X X

WASI Full Scale

IQ X X X X X X X X X X X X X X X X X X X X X X X X X X X

“X” indicates that the variable shown in the column was used as a covariate in all models for the outcome variable shown on the row.
Abt Associates Inc. Chapter 8 97

8.3. Testing for Effect Modifiers

The test for whether a covariate is an effect modifier involves creating an interaction term

between the covariate and the exposure variables, and conducting tests of the null hypotheses

that the coefficients for the interactions term are zero. Grandjean et. al. (1997), did not test

for effect modifiers. Davidson et. al. (1998) tested for interactions between sex and exposure

and found a significant sex-by-prenatal exposure interaction for one of their six outcome

measures. Following the lead of Davidson et. al., (1998), our analysis plan specified models

to test for sex-by-exposure interactions.

Additionally, several studies of the rates of excretion of methylmercuric chloride in rodents

have indicated that oral antibiotics taken concurrently with oral ingestion of methylmercuric

chloride is associated with slower excretion (Rowland et. al., 1977, 1980,1984). It has

therefore been suggested that if children are on antibiotics at the time of exposure to

ethylmercury from thimerosal-containing vaccines or immuned globulins, that the antibiotic

use could act as a modifier of an exposure effect. Therefore, we included specifications for

models to test for these interaction effects in the analysis plan.

The current report also includes results from two models with tests for effect modification

that were not included in the original analysis plan. The requests for these analyses were

generated after the April 8th, 2005 presentation of preliminary results to group of Principal

Investigators and the study’s External Expert Consultants. One is a test for an interaction

effect between prenatal and postnatal exposure to ethylmercury from thimerosal-containing

vaccines and immune globulins. This test was motivated by a theory that prenatal exposure

could exacerbate the effects of postnatal exposure. Details are provided in Section 9.2.4.

A second model is similar to the first except that the measure of prenatal exposure includes

exposures to mercury from sources other than vaccines and immune globulins. The other

sources include prenatal mercury exposures from consumption of fish, from mercurycontaining contact lens and nasal spray solutions, from home products, and from dental

amalgams. Details are provided in Section 9.2.5.

8.4. Multiple Testing

We fit models to data for 42 outcome variables. The example model specified in Section 8.1

produces three hypothesis tests. Multiplying the three hypothesis tests by the 42 outcomes

results in 126 hypothesis tests. A similar model to the one presented in the example, but

where a test for the effect of cumulative exposure in the age range of birth to 7 months

replaces the two separate terms for birth to one month, and 1 to 7 months in the example

model, was fit to all 42 outcomes. Multiplying the two hypothesis from this model by the 42

outcomes results in 84 additional tests. Furthermore, separate estimates were calculated for

boys and girls, resulting in yet more tests. During the design phase, we tried to limit the

proliferation of statistical tests by focusing on a few key research questions, and a few model

specifications to answer those questions. However, the number of tests inevitably multiplied
Abt Associates Inc. Chapter 8 98

after the presentation of preliminary results motivated interest in additional analyses. Across

all of the models that were fit to the 42 outcome variables, Section 9 reports results of more

than 2,500 hypothesis tests.

With such a large number of tests, we expect to see a large number of statistically significant

results that are due to chance alone. During the design phase we considered the use of

methods, such as a Bonferonni adjustment to control for the overall type I error rate.

However, the group of Principal Investigators and the study’s External Expert Consultants

were not in favor of such an adjustment. Their recommendations were to report the

conventional levels of statistical significance with appropriate caveats in the written text

regarding the number of tests that were performed.

8.5. Reporting Effect Sizes

In addition to reporting the parameter estimated and standard errors corresponding to the

exposure variables from the linear and logistic regression models, we sought to present

measures that could be interpreted and compared as measures of effect size. In order to

facilitate comparisons of effect sizes from the current study to the methylmercury effects

reported from the Faroe Islands study, we followed the lead of Jacobson (2001) who had

converted the raw regression coefficients reported by Grandjean et. al. (1997) into

standardized regression coefficients. The standardized regression coefficient is calculated by

multiplying the estimated regression coefficient from the model (the unstandardized

coefficient) by the ratio of the standard deviation of X (the exposure variable) to the standard

deviation of Y (the outcome variable). This calculation is equivalent to standardizing all

independent and dependent variables in the model and fitting a model to the standardized

variables12. The raw and standardized regression coefficients reported by Jacobson (2001) for

the Faroe Islands results are shown in Exhibit 8.5.1.

An odds ratio is a standardized measure of effect size. The parameter estimates for the

logistic regression models are easily converted to odds ratios by taking their exponent.

However, this simple procedure produces the odds ratio of the outcome associated with a

one-point increase in the exposure measure. Since a one-point increase in exposure does not

have any intuitive meaning, we converted the standardized result to be the odds ratio

associated with a two standard deviation increase in the exposure measure. We chose two

standard deviations of the exposure measure to roughly correspond to the difference between

low and high exposure.

12 A proof is provided by R. William at: http://www.nd.edu/~rwilliam/xsoc592/lectures/x92.pdf.
Abt Associates Inc. Chapter 8 99

Exhibit 8.5.1. Results Reported by Jacobson (2001) for Faroe Islands Data

Exposure SD Endpoint Endpoint S.D.

Raw Regression

Coefficient

Standardized

Regression

Coefficient

Finger Tapping 6.15 -1.10 -0.07

CPT Errors 0.54 0.12 0.08

CPT Reaction

Time

80.00 40.30 0.18

Digit Span 1.50 -0.27 -0.06

Boston Naming

Test: no cues

5.30 -1.77 -0.12

Boston Naming

Test: cues

5.30 -1.91 -0.13

CVLT short-term

recall

3.10 -0.57 -0.06

0.375

CVLT long-term

recall

3.80 -0.55 -0.05
Abt Associates Inc. Chapter 9 100

9. Results

9.1. Descriptive Statistics

We present two sets of descriptive statistics. The first set is provided in order to describe the

characteristics of the study participants, the variation across the four HMOs from which the

sample was drawn, and for some variables, comparisons to national population means. The

second set specifically describes the variables used in the analysis models. The former draws

on information that illuminates information on who the study participants were, but includes

variables or forms of variables that were not part of the analytic models. For example, the

first section presents the proportions of participants that were 7, 8, 9, and 10 years old at the

time of assessment. However, the analytic models did not utilize a categorical age variable.

For the models, age was a continuous variable with values that ranged from 7.07 to 10.99.

The continuous age variable is described in the second section.

9.1.1. Characteristics of the Analysis Sample

9.1.1.1. Demographics

The sampling method was designed to obtain a sample with a wide distribution of exposures

for the neonatal period (1-28 days), and early infancy (29-214 days). The method did not

include explicit stratification on age of child, but included implicit stratification on age via a

systematic sampling routine (see Section 5.5 for details). This method increases the

probability that children in all age ranges will be included in the sample. Exhibit 9.1.1.1

shows the proportions of assessed children at each of the four HMOs that were 7, 8, 9, and 10

year-old children. In the total sample, and at each of the four HMOs, roughly half of the

study participants were boys, and roughly half were girls. The birth weights of almost three

quarters of study participants were between 3 and 4 kilograms. Children with birth weights

that were below 2.5 kilograms were excluded from the study.

The maternal IQ score was a population-normalized measure with a mean of 100 and a

standard deviation of 15. Approximately 16 percent of the national population has IQ scores

below 85 (one standard deviation below the mean), and approximately 16 percent has IQ

scores above 115 (one standard deviation above the mean). Exhibit 9.1.1.1 shows that the

distribution of IQ scores in the total sample was slightly skewed towards higher scores than

the national population. Cumulative exposures from birth to seven months varied across

maternal IQ levels (p<0.001). Higher maternal IQ was associated with higher exposure

levels.

The mothers of participants also appeared to have higher educational attainment, on average,

than the national population. Nationally, in 2003, around 87 percent of women between the

ages of 25 and 40 had a high school degree or above, 57 percent had some college or more,

and roughly 30 percent had bachelor’s degrees (Stoops, 2004). In the total sample, about 96

percent had a high school degree or above, 79 percent had some college or more, and

although not directly comparable to the national numbers, about one half of the mothers of

participants reported having associate’s degrees or above. Higher maternal education level

was associated with higher cumulative exposures from birth to seven months (p<0.001).
Abt Associates Inc. Chapter 9 101

An eligibility criterion for the study was that children must live with their biological mothers

at least four days per week. In the total sample, 19 percent of focus children lived in single

parent households, i.e., lived with their mother but not with their father. Living in single

parent household was associated with lower exposure levels (p<0.01). Seven percent of the

focus children were born to mothers who were 40 years or older at the time of birth of the

child, and 63 percent lived in household where English was the only language spoken. Older

maternal age and English language households were associated with higher exposure levels

(p=0.05, and p<0.001, respectively).

Exhibit 9.1.1.1 Descriptive Statistics for Demographic Measures

By Cumulative Exposures Birth to 7 Months Full

Sample 0 -

62.5 g

75 –

137.5 g

150.0 –

187.5 g

n=1047 n=93 n=691 n=263

Demographics Percent Percent Percent Percent Pvalueb

Child Age

(Years): 7

17 18 16 17 0.33

8 23 26 23 22

9 28 35 28 28

10 32 20 33 33

Sex: Male 49 54 48 48 0.57

Birth weight: 2500-2999 grams 11 11 10 15 0.34

3000-3999 grams 73 75 75 69

4000+ grams 15 14 15 16

Maternal IQ: <85 10 12 12 5 <0.001

85 – 115 73 73 75 66

>115 17 15 13 29

Maternal No High School degree 4 3 5 2 <0.001

Education: High School /GEDa16 16 18 10

Some College 28 38 29 24

College degree 51 43 48 65

Child lives in a single parent household 19 29 21 13 0.008

Maternal Age 16-39 years 93 91 94 89 0.050

(at Child’s Birth): >=40 years 7 9 6 10

Only English spoken at home 63 63 58 75 <0.001

Sample size = 1,047 assessed children.

a GED is a certificate given for the completion of the Tests of General Educational Development, a series of five tests.

It is the equivalent of a high school diploma.

b

P-value is from chi-square test of independence between the demographic characteristic and the three levels of cumulative

exposure.

Read Table: Seventeen percent of children were 7 years-old at the time of assessment. Eighteen percent

of low exposure children (0 - 62.5 g ) were 7 years-old at the time of assessment.
Abt Associates Inc. Chapter 9 102

9.1.1.2. Outcomes

Exhibit 9.1.1.2 provides a basis for comparison between the study sample and the national

population of children of the same age on assessment results. The results indicate that for

most of the measures that have national norms, the sample of study participants scored

higher, on average, than the national population. For example, the WASI measures of general

intellectual functioning are standardized such that the national population mean and standard

deviation are 100 and 15, respectively. The last columns in the exhibit show the means for

the full sample, i.e. children from all four HMOs. The means for the three measures range

from around 105 to 107. Thus this sample of children scored 5 to 7 points, or roughly a third

of a standard deviation unit, higher than the national average on these measures. The

variation among the scores of children in the sample was similar to the variation in test scores

that would be obtained from a national sample. That is, the standard deviations of the

measures are close to the standard deviations expected from a national sample.

For most of the speech and language measures the sample means were roughly a tenth to a

half a standard deviation unit higher than the national population means. On three of the four

parent ratings of behavior regulation and attention/executive functioning, the sample children

had slightly higher scores than the national population. On these measures higher scores

indicate the presence of a greater number of undesirable behaviors or symptoms. On one

measure their average scores were slightly lower.

The exhibit also shows the variation of means among HMOs. Children from HMOs C and D

tended to have higher average scores on general intellectual functioning, achievement,

language, and memory measures than children assessed at HMOs A and B.
Abt Associates Inc. Chapter 9 103

Exhibit 9.1.1.2

Means and Standard Deviations on Normed Tests for Sample

By HMO

HMO

HMO-A HMO-B HMO-C HMO-D Total

(n = 1047)

Tests with Standardized Score for National Norming Sample: Mean = 100; Standard Deviation = 15

Measurea

x s.d. x s.d. x s.d. x s.d. x s.d.

General Intellectual Functioning

WASI Full Scale IQ 106.3 14.3 104.4 13.3 111.7 15.0 116.1 15.3 107.4 14.6

WASI Performance IQ 105.7 15.1 101.7 14.3 108.2 15.2 110.9 17.1 105.1 15.3

WASI Verbal IQ 106.7 14.3 103.6 13.3 111.5 14.5 114.9 16.2 107.1 14.6

Achievement

WJR Letter-Word 108.1 11.2 105.8 11.1 106.4 13.0 110.4 11.5 107.0 11.7

Measures with Standardized T-Scores: Mean = 50 and Standard Deviation = 10

Memory for Words x s.d. x s.d. x s.d. x s.d. x s.d.

CVLT: Free Recall, No Del. 53.9 9.7 53.5 10.2 54.4 9.9 56.5 9.3 54.0 9.9

Parent Ratings of Behavior Regulation

Connors Inattention 51.7 10.4 52.4 10.6 52.3 10.0 51.7 11.6 52.1 10.5

Connors Hyperactivity 53.7 10.6 54.9 11.4 53.7 10.0 52.9 11.5 54.1 10.9

Parent Ratings of Attention/Executive Functioning

BRIEF Meta-cognition 51.0 10.7 51.6 11.6 51.4 10.8 49.0 12.6 51.2 11.2

BRIEF Behavioral Control 48.7 10.2 49.7 10.7 49.4 10.3 47.2 11.2 49.1 10.5

Tests with Standardized Score for National Norming Sample: Mean = 10; Standard Deviation = 3

Language Use x s.d. x s.d. x s.d. x s.d. x s.d.

NEPSY Speeded Naming 10.2 2.7 10.0 2.7 10.9 2.7 11.2 2.7 10.4 2.7

NEPSY Compren of Instr 10.9 2.7 10.2 2.9 11.6 2.6 11.9 2.5 10.9 2.8

CELF-3 Formulated Sent 11.0 2.6 10.6 2.6 11.6 2.9 11.6 2.7 11.0 2.7

Memory for Connected Text

CMS Short-term Memory 10.7 3.0 10.6 3.0 11.5 2.9 12.3 2.8 10.9 3.0

CMS Long term Memory 11.0 3.0 10.7 3.0 11.5 3.0 12.4 2.9 11.1 3.0

Tests with Standardized Score for National Norming Sample: Mean = 0; Standard Deviation = 1

Verbal Memory x s.d. x s.d. x s.d. x s.d. x s.d.

CVLT Free ST 0.4 1.0 0.5 1.0 0.4 0.9 0.5 1.0 0.4 0.9

CVLT Cued Free ST 0.5 1.0 0.5 1.0 0.6 1.0 0.7 1.0 0.5 1.0

CVLT Free LT 0.5 0.9 0.5 0.9 0.6 0.9 0.6 0.9 0.5 0.9

CVLT Cued Free LT 0.4 0.9 0.5 0.9 0.6 0.9 0.7 0.9 0.5 0.9
Abt Associates Inc. Chapter 9 104

9.1.1.3. Exposures

The postnatal exposure measures used in the analytical models were calculated as

micrograms of ethylmercury divided by weight of the child (in kilograms) at the time of

receipt of the vaccine or immune globulin, and summed over the relevant time period (i.e., 0-

28days, 29-214 days, or 0-214 days). Those measures are described in the Section 9.2. In the

current section we describe postnatal exposures without the division by child’s weight. These

latter measures are useful for descriptive purposes because they are easier to relate to the

mercury amounts contained in individual vaccines. A single dose of most childhood vaccines

in use during the mid to late 1990s contained 0, 12.5, or 25 micrograms of ethylmercury.

Thus, an exposure amount equal to, for example, 37.5 micrograms, implies receipt of either

three vaccines that each contained 12.5 micrograms of mercury, or receipt of two vaccines,

one containing 12.5 micrograms, the other containing 25 microgram of ethylmercury.

The leftmost panel of Exhibit 9.1.1.3 shows the frequency distribution of cumulative

exposure during the age range from birth to 7 months. It shows, for example, that 16 of the

study children had zero micrograms of exposure during this age range. The middle panel of

the exhibit shows neonatal exposures (1-28 days) crossed with cumulative exposure during

the age range from one to seven months (29-214 days). It shows, for example, that three

children had a birth dose of HepB (12.5 g during the age range 0-28 days), but had zero

exposure during the age range spanning 29-214 days. The column totals of the middle panel

show that 312 of the study participants did not receive a hepatitis-b vaccination (HepB) at

birth (or within the first 28 days of life). The 718 study participants that had 12.5 micrograms

of mercury exposure within the first 28 days had received a single HepB at birth or soon

after. The 10 subjects that had 25 micrograms of neonatal exposure had received a HepB at

birth, or within one day of birth, and had received a second dose around age 27 or 28 days.

The second dose was an early administration of HepB that typically would have been

received after turning one or two months of age. The seven children that had 37.5

micrograms of neonatal exposure had received a hepatitis-b immune globulin and a hepatitisB vaccine at birth, or within a day or two of birth.

Exhibit 9.1.1.4 is a graphical depiction of the postnatal exposure distributions that shows that

there was considerable variation in cumulative exposures for the age ranges spanning 29-214

days, both for children who received a birth dose of hepatitis-b vaccine and for those who did

not. Exhibit 9.1.1.5 shows the variation in frequency distributions across the four HMOs.

In 1999, children that were vaccinated on time and according to the recommended childhood

immunization schedule13 may have been exposed to 187.5 micrograms of ethylmercury from

thimerosal during the age range spanning birth and seven months. This amount could have

been achieved if the child received HepB vaccinations (12.5 g ) at birth, between the ages

of 1 and 4 months, and at age 6 months, and received DTaP and Hib vaccinations (each with

as much 25 g of ethylmercury per dose) at ages 2, 4, and 6 months.

13 The vaccine schedule recommended and approved by the Advisory Committee on Immunization Practices

(ACIP), the American Academy of Pediatrics (AAP), and the American Academy of Family Physicians

(AAFP).
Abt Associates Inc. Chapter 9 105

There are several possible sources of variation among children in exposure amounts. The first

is variation in vaccination policies among health care providers. For example, at some

hospitals, HepB vaccinations were given to new-borns as a matter of policy, others did not

have that policy. And some health care providers typically did not administer a Hib vaccine

at age 6 months. Another source of variation is the mercury amounts contained within one

dose of a vaccine. For example, depending on the manufacturer, Hib vaccines in use at that

time contained 0, 12.5, or 25 g of ethylmercury per dose. Another source of variation was

the use of combined DTaP-Hib vaccines. The combined vaccine contained 25 g of

ethylmercury per dose. Receipt of separate DTaP and Hib vaccines at one visit could result

exposure to 50 g of ethylmercury. And finally, there was variation in exposure due to

delayed or skipped vaccinations. Recommended vaccines were skipped or delayed due to

personal circumstances, beliefs, and preferences. A total of 16 study participants were not

vaccinated at all during the age range spanning birth to 7 months.

Exhibit 9.1.1.6 shows a schematic of the pattern of receipts that would result in 187.5

micrograms of cumulative exposure to ethylmercury. The exhibit also shows the modal (most

frequently occurring) pattern of receipts of thimerosal-containing vaccines during the age

range from birth to 7 months at each HMO. See Section 7.2 for additional information on

vaccine types and exposure amounts.

One hundred eleven (11 percent) of the 1,047 study participants had prenatal exposure to

ethylmercury from thimerosal-containing vaccines or immune globulins administered to their

mothers during pregnancy. See Section 7.2 for additional details.

Exhibit 9.1.1.7 shows the intercorrelation among the variables measuring amounts of

cumulative exposure in each age range. It shows that there are weak positive correlations

between prenatal exposure and postnatal receipts of thimerosal-containing vaccines and

immune globulins. Children that were exposed at birth (within the first 28 days) were slightly

more likely to have higher exposure during the age range from 29 days to 7 months, as

indicated by the weak positive correlation among the Amt01mos and Amt17mos variables.

Since the Amt07mos variable is equal to the sum of the Amt01mos and Amt17mos variables, it

is positively correlated to both.
Abt Associates Inc. Chapter 9 106

Exhibit 9.1.1.3

Descriptive Statistics for Exposure Amounts

Cumulative Exposure

Birth to 7 Months

Cumulative Exposure Birth to 1 Month Crossed with

Cumulative Exposure 1 to 7 Months

Birth to 1 Month (0-28 Days)

Birth to 7

Months

(1-214 Days)

Total 1 to 7 Months

(29-214 Days)

0 g 12.5 g 25 g 37.5 g Total

0 g 16 0 g 16 3 0 0 19

12.5 g 3 12.5 g 0 0 0 0 0

25 g 2 25 g 2 2 1 0 5

37.5 g 12 37.5 g 10 24 0 0 34

50 g 37 50 g 12 14 1 0 27

62.5 g 23 62.5 g 9 89 0 0 98

75 g 146 75 g 56 20 1 0 77

87.5 g 27 87.5 g 7 69 1 0 77

100 g 116 100 g 46 121 1 2 170

112.5 g 164 112.5 g 42 70 0 2 114

125 g 115 125 g 44 105 0 3 152

137.5 g 123 137.5 g 16 35 0 0 51

150 g 52 150 g 15 7 5 0 27

162.5 g 19 162.5 g 9 103 0 0 112

175 g 130 175 g 22 56 0 0 78

187.5 g 62 187.5 g 6 0 0 0 6

Total 1047 Total 312 718 10 7 1047

g = micrograms of ethylmercury from thimerosal in vaccines or immune globulins

Read table: Sixteen of the 1,047 study participants were exposed to 0 g in the age range from birth to one month, and

0 g in the age range spanning one to seven months.
Abt Associates Inc. Chapter 9 107

Exhibit 9.1.1.4.

Frequency Distribution of Neonatal Exposure by Exposures 1-7 Months

Frequency Counts of Cumulative Exposure for Age Range of 1 to 7 Months Crossed with

Exposure from Birth Dose of Hepatitis-B Vaccine

0 50 100 150 200

Frequency

28 31

21

105

63

92 89

196

60

144

25

116

28

56

No HepB at Birth

Received HepB at Birth

0- 37.5

50.0- 62.575.0- 87.5

100.0-112.5125.0-137.5150.0-162.5175.0-187.5

Cumulative Exposure Ages 1 to 7 Months

Read: “The study included 28 children who did not received a hepatitis-B vaccination in first month of life, and whose

cumulative exposure to ethylmercury from vaccines during the age range from one to seven months was in the range of 0 to

37.5 micrograms.”

Exhibit 9.1.1.5

Size of Analysis Sample from Each HMO by Exposure Category

HMO-A HMO-B HMO-C HMO-D Total

VSD Exposures HepB at Birth HepB at

Birth

HepB at

Birth

HepB at

Birth

HepB at

Birth

Cumulative 1-7

Months No Yes No Yes No Yes No Yes No Yes

(0 to 62.5 g ) 26 49 11 69 10 10 2 6 49 134

(75.0 to 87.5 g ) 47 51 15 38 0 2 1 0 63 91

(100.0 to 112.5 g ) 44 55 40 94 3 36 1 11 88 196

(125.0 to 137.5 g ) 25 20 28 113 6 7 1 3 60 143

(150.0 to 162.5 g ) 7 7 2 3 8 74 7 31 24 115

(175.0 to 187.5 g ) 9 0 0 0 16 40 3 16 28 56

Total 158 182 96 317 43 169 15 67 312 735

340 413 212 82 1047

Note: g = micrograms.
Abt Associates Inc. Chapter 9 108

Exhibit 9.1.1.6.

Pattern of Receipts of Thimerosal-containing Vaccines Resulting in

Maximum Cumulative Exposure Birth to 7 Months

and

Modal Patterns of Receipts at Each HMO

Pattern Resulting in

Maximum

Cumulative Modal Patterns at each HMO

Age Vaccine Exposure HMO-A HMO-B HMO-C HMO-D

Birth HepB 12.5 12.5 12.5 12.5 12.5

1-4 months HepB 12.5 12.5 12.5 12.5 12.5

6-7 months HepB 12.5 12.5 12.5 . .

2 months DTaP 25 . 25 25 25

2 months Hib 25 . 12.5 25 25

2months DtaP-Hib . 25 . . .

4 months DtaP 25 . 25 25 25

4 months Hib 25 . 12.5 25 25

4 months DtaP-Hib . 25 . . .

6 months DtaP 25 . 25 25 25

6 months Hib 25 . . 25 25

6 months DtaP-Hib . 25 . . .

Cumulative Exposure Birth to 7 months: 187.5 112.5 137.5 175 175

Note: Ball et al (2001) estimated that a thimerosal-containing influenza vaccine that would have been recommended for

children in selected populations could have been added to the maximum pattern shown above, resulting in 200 micrograms

of cumulative exposure. In the current study, while there were four children that received the influenza vaccine before age

seven months, none of these children had received all of the vaccinations in the pattern resulting in maximum exposure,

depicted above. It is also conceptually possible for a child to have received more than 187.5 micrograms of cumulative

exposure in the first seven months if the child had received a hepatitis-b immune globulin, in addition to all the vaccines

depicted in the maximum pattern. That scenario, however, did not occur in the sample of children analyzed in the current

study.

Exhibit 9.1.1.7. Correlation Among Exposure Amount Variables

PreNat

Thimer Amt01mos Amt17mos

PreNatThimer

Cumulative g : Prenatal

1

Amount 0-1 mos

Cumulative g : birth-28 days

0.05

(0.137)

1

Amt17mos

Cumulative g : 29-214 days

0.09

(0.003)

0.09

(0.003)

1

Amt07mos

Cumulative g : birth-214 days

0.10

(0.002)

0.24

(<0.001)

0.99

(<0.001)

Pearson Correlation Coefficients, N = 1047
Abt Associates Inc. Chapter 9 109

9.1.2. Descriptive Statistics on Variables Used in Analysis

Models

The means, standard deviations, minimums and maximums of the variables used in the

analytical models are displayed in Exhibits 9.1.2.1 - 9.1.2.3. The correlations among the

exposure variables that were used in the analytical models are shown in Exhibit 9.1.2.4, and

the correlation among outcome variables is shown in Exhibit 9.1.2.5.

Exhibit 9.1.2.1. Descriptive Statistics on Outcome Measures

Test Form of Score N Miss. Mean Std Min Max

Speech and Language

Boston Naming Test Raw score 1045 2 39.55 7.97 14 58

NEPSY: Speeded Naming Raw score 1040 7 27.39 8.12 1 42

NEPSY: Comprehension of Instructions Raw score 1034 13 23.58 2.82 12 28

CELF: Formulated Sentences Raw score 1038 9 32.76 6.7 0 44

CELF: Recalling Sentences Raw score 1044 3 44.59 14.32 5 78

GFTA: Articulation (lower = better) Raw score 1025 22 1.57 1.88 0 18

Stuttering: Assessor Rating (lower = better) 0=None/very mild; 1=mild/severe 1043 4 0.03 0.18 0 1

Stuttering: Parent Rating (lower = better) 0=None/very mild; 1=mild/severe 1035 12 0.02 0.15 0 1

Stuttering: Teacher Rating (lower = better) 0=None/very mild; 1=mild/severe 728 319 0.09 0.29 0 1

Verbal Memory

CVLT-C: Free Recall, No Delay Raw score 1046 1 46.51 9.69 0 71

CVLT-C: Free Recall, Short Delay Raw score 1047 0 9.73 2.72 0 15

CVLT-C: Cued Recall, Short Delay Raw score 1045 2 10.3 2.4 1 15

CVLT-C: Free Recall, Long Delay Raw score 1044 3 10.38 2.53 0 15

CVLT-C: Cued Recall, Long Delay Raw score 1043 4 10.65 2.46 1 15

CMS Stories 1: Immediate Recall Raw score 1038 9 47.36 15.5 0 77

CMS Stories 2: Delayed Recall Raw score 1037 10 44.49 15.09 0 76

Achievement

WJIII: Letter- Word Identification Raw score 1043 4 50.9 9.38 16 73

Fine Motor Coordinatioin

Grooved Pegboard: Dominant Hand (lower = Time to completion (minutes) 1045 2 65.88 27.54 21 300

Grooved Pegboard: Non-dom Hand (lower = better) Time to completion (minutes) 1039 8 73.69 31.72 20 300

Finger Tapping: Dominant Hand Number of taps 1037 10 38.81 6.8 15.6 107

Finger Tapping: Non-dominant Hand Number of taps 1034 13 34.47 6.25 15 86

Visual Spatial Ability

Stanford Binet: Copying Raw score 1038 9 18.2 3 3 28

Attention/Executive Functioning

GDS Vigilance Task: Correct Responses Raw score (# correct) 1042 5 40.47 5.13 0 45

GDS Vigilance Task: Errors (lower = better) Raw score (# errors) 1042 5 7.55 13.31 0 162

WISC III: Digit Span, Forward Recall Raw score 1045 2 8.06 1.88 3 15

WISC III: Digit Span, Backward Recall Raw score 1046 1 4.53 1.64 0 13

WISC III: Digit Span, Combined Raw score 1045 2 12.58 2.94 4 26

BRIEF Parent Rating: Metacognition (lower = Raw score 1042 5 74.28 18.1 44 128

BRIEF Teacher Rating: Metacognition (lower = Raw score 782 265 67.31 22.5 44 129

Behavior Regulation (lower = better)

CRS-R: Parent Rating: Hyperactive/Impulsive Raw score (# reported problems) 1041 6 5.42 5.1 0 25

CRS-R: Teacher Rating: Hyperactive/Impulsive Raw score (# reported problems) 777 270 3.94 5.75 0 27

CRS-R: Parent Rating: Inattentive Raw score (# reported problems) 1041 6 6.3 5.94 0 26

CRS-R: Teacher Rating: Inattentive Raw score (# reported problems) 777 270 6.68 7.33 0 28

BRIEF Parent Rating: Behavior Regulation Raw score (# reported problems) 1042 5 42.28 10.79 26 82

BRIEF Teacher Rating: Behavior Regulation Raw score (# reported problems) 782 265 38.79 12 29 87

Tics (lower = better)

Motor tics (current): Assessor Rating 0=None; 1=Any 1044 3 0.09 0.28 0 1

Phonics tics (current): Assessor Rating 0=None; 1=Any 1044 3 0.07 0.26 0 1

Motor tics (current): Parent Rating 0=None; 1=Any 1035 12 0.09 0.29 0 1

Phonics tics (current): Parent Rating 0=None; 1=Any 1037 10 0.1 0.3 0 1
Abt Associates Inc. Chapter 9 110

Exhibit 9.1.2.1. Descriptive Statistics on Outcome Measures

Test Form of Score N Miss. Mean Std Min Max

General Intellectual Functioning

WASI Verbal IQ Standardized score 1032 15 107.39 14.6 62 153

WASI Performance IQ Standardized score 1038 9 105.06 15.27 67 147

WASI Full Scale IQ Standardized score 1025 22 107.1 14.56 71 153

Exhibit 9.1.2.2 Descriptive Statistics on Exposure Variables

Variable Description N Miss. Mean Std. Min. Max.

Variables Used in Primary Models

PreNatThimer Total prenatal mercury from thimerosal 1047 0 2.2 8.3 0 100

Exp07mos Amt/Wt(KGs) birth-214 days 1047 0 19.8 7.1 0 38.3

HepB Amt/Wt(KGs) birth-28 days 1047 0 2.6 1.8 0 12.7

Exp17mos Amt/Wt(KGs) 29-214 days 1047 0 17.2 6.6 0 33.8

Variables Used in Models to Assess Influence of High Leverage Observations on Results

PreNatThimer_Alt Alternative Tot prenat (for sensitivity analysis) 1047 0 5.2 16.7 0 100

PN_Trunc if PreNatThimer>25 then PN_Trunc=25 1047 0 1.8 5.6 0 25

HepBYN 1 if any HepB, 0 else 1047 0 0.7 0.5 0 1

Variable Used in Model for Multiple Sources of Prenatal Mercury Exposure

PreNatAllMerc Prenatal mercury from any source 1047 0 1.8 0.9 0 5

Variables Used in Concurrent Antibiotics-by-Exposure Interaction Models

AbDays # days child on antibiotics in period 1-214 days 1047 0 8.7 17.7 0 214

AbDays1_28 # days child on antibiotics in period 1-28 days 1047 0 0.4 2.1 0 28

AbDays29_214 # days child on antibiotics in period 29-214 days 1047 0 8.2 17 0 186

AbExp07mos Exposure concurrent w/ antibiotics (ages 1-214 days) 1047 0 2.3 4.3 0 32.9

AbHepB Exposure concurrent w/ antibiotics (ages 1-28 days) 1047 0 0.1 0.6 0 4.3

AbExp17mos Exposure concurrent w/ antibiotics (ages 29-214 days) 1047 0 2.2 4.2 0 32.9
Abt Associates Inc. Chapter 9 111

Exhibit 9.1.2.3. Descriptive Statistics on Covariates

Variable Label N Impa Mean Std Min Max

Variables Included in Every Model

ChildAge Child Age (Yrs) at assessment 1047 0 9.28 1.08 7.07 11

sexmale Sex of child 0=female, 1=male 1047 0 0.49 0.50 0 1

Birth weight Birth weight 2500-2999 grams 1047 0 0.11 0.32 0 1

Birth weight 3000-3999 grams 1047 0 0.73 0.44 0 1

Birth weight 4000+ grams 1047 0 0.15 0.36 0 1

Maternal IQ Maternal IQ: Lower third of Distbn 1047 0 0.34 0.48 0 1

Maternal IQ: Midd. third of Distbn 1047 0 0.30 0.46 0 1

Maternal IQ: Upper third of Distbn 1047 23 0.35 0.48 0 1

HOME_TotalIndex “HOME” Total Index 1047 0 11.98 1.95 3 16

PctPoverty1 (Percent of poverty line)/100 1047 15 4.12 2.60 0.2 22.7

Maternal Education Mother EduH: No HS degree 1047 0 0.04 0.21 0 1

Mother EduH: HS /GED 1047 0 0.16 0.36 0 1

Mother EduH: Some College 1047 0 0.28 0.45 0 1

Mother EduH: College degree 1047 0 0.51 0.50 0 1

SingleParent Child lives in a single parent household(0/1) 1047 0 0.19 0.40 0 1

Site =1 if HMO-A 1047 0 0.32 0.47 0 1

=1 if HMO-B 1047 0 0.39 0.49 0 1

=1 if HMO-C 1047 0 0.20 0.40 0 1

=1 if HMO-D 1047 0 0.08 0.27 0 1

Child and Family Characteristics

Computer Experience Computer Experience = None 1047 1 0.01 0.10 0 1

Computer Experience = Some 1047 1 0.41 0.49 0 1

Computer Experience = Much 1047 1 0.58 0.49 0 1

Maternal Age Maternal Age at Ch Birth: <=16 years 1047 0 0.00 0.05 0 1

Maternal Age at Ch Birth: 17-39 years 1047 0 0.93 0.26 0 1

Maternal Age at Ch Birth: >=40 years 1047 0 0.07 0.26 0 1

OlderSibs Child has an older sibling (0/1) 1047 0 0.64 0.48 0 1

YoungerSibs Child has a younger sibling (0/1) 1047 0 0.41 0.49 0 1

DayCareCentr # of center-based day care settings prior to KG 1047 4 0.81 1.02 0 9

DayCareHome # of home-based day care settings prior to KG 1047 4 1.48 1.44 0 14

EngOnly English only at home 1047 0 0.63 0.48 0 1

Breast Feeding Breast Fed: <1mo 1047 0 0.22 0.41 0 1

(Duration) Breast Fed: 1-6mos 1047 0 0.37 0.48 0 1

Breast Fed: 6+ mos 1047 0 0.42 0.49 0 1

Child Birth Conditions

cMedicalHist_1 =1 if birth headCM +/- 2SD from Mean 1047 0 0.02 0.15 0 1

C5APGARImpVal1 5-minute apgar 1047 75 8.93 0.49 4 10

Prenatal Exposures (non-vaccine related)

PreNatNicotine_1 Used tobacco during pregnancy 1047 2 0.08 0.26 0 1

PreNatAlcohol_1 0=never - 4 heavy 1047 4 0.09 0.37 0 4

Tuna Consumption Prenatal Tuna: None 1047 55 0.31 0.46 0 1

Prenatal Tuna: Moderate 1047 55 0.65 0.48 0 1

Prenatal Tuna: High 1047 55 0.04 0.20 0 1

PreNatFish_1 1=Tuna, Ocean and Home Caught 1047 47 0.07 0.25 0 1
Abt Associates Inc. Chapter 9 112

Exhibit 9.1.2.3. Descriptive Statistics on Covariates

Variable Label N Impa Mean Std Min Max

PreNatOrgMerc_1 # Merc containing contact lens, ear, eye, nasal 1047 34 0.11 0.46 0 4

PreNatHomePro_1 # Merc exp from therm, bulbs, switches etc. 1047 40 0.04 0.19 0 1

Tooth Amalgams Amalgams: None 1047 39 0.19 0.39 0 1

PreNatFillings_1_L1 Amalgams: yes 1047 39 0.11 0.31 0 1

PreNatFillings_1_L2 Amalgams: yes & work, grind, or gum 1047 39 0.71 0.46 0 1

PreNatlead_1 Prenat lead from occup or residential 1047 8 0.15 0.36 0 1

PreNatIllDrug 1=Cocaine or Narcotic 1047 0 0.01 0.10 0 1

Child Medical Conditions

IronDef_1 Anemia or iron deficiency 1047 0 0.02 0.15 0 1

ADHDstimulant ADHD stim in 12 hrs prior to assessment 1047 0 0.00 0.04 0 1

ChdPICA_1 Child Pica 1047 10 0.04 0.20 0 1

Maternal Diagnoses

MatLangDel Maternal Language Delay 1047 0 0.00 0.07 0 1

MatSpeechDel Maternal speech delay 1047 0 0.01 0.10 0 1

MatSTUTTER Maternal stuttering 1047 0 0.01 0.11 0 1

MatADHD Maternal ADHD 1047 0 0.01 0.11 0 1

MatTIC Maternal tics 1047 0 0.00 0.00 0 0

Quadratic and Cubic Forms

ChildAge2 ChildAge2

(squared) 1047 0 87.31 19.87 50.01 120.95

ChildAge3 ChildAge3

(cubed) 1047 0 831.84 276.88 353.67 1330.25

PctPoverty1_2 (PctPoverty1/100)**2 (squared) 1047 15 23.75 42.27 0.04 515.12

PctPoverty1_3 (PctPoverty1/100)**3 (cubed) 1047 15 198.26 768.15 0.01 11691.4

HOME_TotalIndex2 HOME_TotalIndex**2 (squared) 1047 0 147.35 44.69 9 256

HOME_TotalIndex3 HOME_TotalIndex**3 (cubed) 1047 0 1851.88 800.69 27 4096

Variables Used Only in Models for Finger Tapping Outcomesb

Spline9 =1 if ChildAge > 9.0; =0 Else 1047 0 0.60 0.49 0 1

ChildAge_Spline9 Childage * Spline9 1047 0 6.04 4.93 0 11

ChildAge2_Spline9 Childage2* Spline9 1047 0 60.82 50.25 0 120.95

a Numbers listed in “Imp” column show the number of missing values that were replaced with imputed values.

b

Finger tapping tests for children aged 9 and above were slightly different than tests for younger children. Spline term allows for

separate intercepts for children above and below 9 years. Spline*ChildAge and Spline*ChildAge2 terms allow for different

age slopes for children above and below 9 years.
Abt Associates Inc. Chapter 9 113

Exhibit 9.1.2.4. Correlation Among Exposure Variables

PreNat

Thimer HepB Exp17mos

PreNatThimer

Total prenat merc from thimerosal

1

HepB

Amt/Wt(KGs) birth-28 days

0.04

(0.204)

1

Exp17mos

Amt/Wt(KGs) 29-214 days

0.08

(0.012)

0.13

(<0.001) 1

Exp07mos

Amt/Wt(KGs) birth-214 days

0.08

(0.007)

0.38

(<0.001)

0.97

(<0.001)

Pearson Correlation Coefficients, N = 1047
Abt Associates Inc. Chapter 9 114

Exhibit 9.1.2.5. Correlation Among Outcome Measures

Boston Nam

NEPS

Y: SP

NEPS

Y: C.I.

CELF: F.S.

CELF: R.S.

GFT

A

Stutter -A

Stutter - P

Stutter - T

C

VLT: FN

D

C

VLT: FS

D

C

V:T” C

S

D

C

VLT: FLD

C

VLT: CLD

C

M

S -1

C<S-2

WJ -LWID

Peg -Dom

Peg -N

D

Tap - Dom

Tap - N

D

SB Copy

G

D

S-Corr

G

D

S-Err

Digit - F

Digit - B

Digit - C

Meta -P

Meta- T

Hyper- P

Hyper -T

Inatt -P

Inatt - T

Behavior - P

Behavior - T

Motor Tics-A

Motor Tics P

Phon Tics-APhon Tics-P

Verbal IQ

Perf IQ

Full IQ

Speech and Language

Boston Naming Test 1 .52 .58 .61 .65 -.31 -.04 -.09 -.02 .42 .34 .39 .35 .37 .6 .62 .64 .14 .15 .29 .28 .29 .32 -.22 .35 .34 .41 -.08 -.14 -.11 -.08 -.09 -.14 -.08 -.11 -.02 -.08 .00 -.1 .66 .48 .65

NEPSY: Speeded

Naming .52 1 .51 .48 .51 -.24 -.06 -.06 -.07 .49 .45 .47 .46 .46 .45 .46 .6 .11 .13 .3 .26 .31 .35 -.32 .31 .39 .42 -.28 -.34 -.22 -.19 -.29 -.31 -.2 -.24 -.04 -.06 .00 -.06 .41 .37 .44

NEPSY:

Comprehension of

Instructions

.58 .51 1 .52 .63 -.18 -.08 -.08 -.05 .41 .31 .35 .35 .37 .49 .48 .5 .07 .08 .18 .17 .22 .32 -.26 .39 .4 .47 -.15 -.25 -.15 -.08 -.18 -.24 -.14 -.14 -.06 -.03 -.06 -.1 .52 .48 .57

CELF: Formulated

Sentences .61 .48 .52 1 .63 -.26 -.11 -.06 -.04 .4 .31 .33 .31 .32 .53 .54 .6 .17 .18 .3 .28 .26 .34 -.28 .31 .34 .39 -.12 -.18 -.13 -.09 -.14 -.16 -.15 -.14 -.07 -.11 .01 -.11 .52 .35 .5

CELF: Recalling

Sentences .65 .51 .63 .63 1 -.21 -.03 -.04 -.05 .44 .3 .33 .32 .32 .56 .56 .57 .17 .18 .22 .24 .28 .3 -.25 .57 .42 .6 -.14 -.21 -.14 -.11 -.14 -.19 -.12 -.16 -.08 -.05 -.05 -.13 .6 .4 .57

GFTA: Articulation

(lower = better) -.31 -.24 -.18 -.26 -.21 1 -.03 .02 .12 -.18 -.14 -.19 -.16 -.16 -.24 -.23 -.24 -.1 -.08 -.1 -.12 -.14 -.16 .14 -.11 -.09 -.12 -.04 .03 -.01 .07 -.03 .04 .01 .05 .03 -.02 -.05 .04 -.19 -.13 -.18

Stuttering: Assessor

Rating (lower = better) -.04 -.06 -.08 -.11 -.03 -.03 1 .09 .14 -.03 -.02 -.03 -.07 -.04 -.04 -.05 -.09 .03 .03 .02 .03 -.01 -.08 .15 -.01 .01 .00 .04 .09 .02 .02 .00 .09 .06 .1 .24 .24 .00 .04 -.08 -.04 -.07

Stuttering: Parent

Rating (lower = better) -.09 -.06 -.08 -.06 -.04 .02 .09 1 .17 -.04 -.02 -.02 -.02 -.05 -.05 -.04 -.06 .11 .11 -.04 .00 -.14 -.07 .17 -.01 -.07 -.05 .08 .1 .03 .02 .06 .12 .03 .05 .04 .05 .13 .11 -.13 -.1 -.13

Stuttering: Teacher

Rating (lower = better) -.02 -.07 -.05 -.04 -.05 .12 .14 .17 1 -.06 -.05 -.04 -.08 -.05 -.04 -.02 -.01 .05 .13 -.01 -.04 -.1 -.05 .07 -.04 -.02 -.04 .07 .14 .00 .1 .07 .14 .06 .18 .09 .07 .02 .08 -.02 -.05 -.04

Verbal Memory

CVLT-C: Free Recall,

No Delay .42 .49 .41 .4 .44 -.18 -.03 -.04 -.06 1 .67 .7 .69 .68 .46 .46 .46 .14 .17 .18 .18 .23 .31 -.25 .23 .29 .31 -.17 -.21 -.16 -.14 -.16 -.2 -.16 -.19 -.03 .01 -.01 -.07 .3 .25 .32

CVLT-C: Free Recall,

Short Delay .34 .45 .31 .31 .3 -.14 -.02 -.02 -.05 .67 1 .74 .8 .74 .41 .42 .41 .14 .16 .16 .16 .23 .25 -.27 .14 .28 .24 -.18 -.22 -.16 -.16 -.18 -.21 -.15 -.18 -.03 -.04 .00 -.02 .24 .21 .25

CVLT-C: Cued Recall,

Short Delay .39 .47 .35 .33 .33 -.19 -.03 -.02 -.04 .7 .74 1 .79 .87 .43 .44 .42 .13 .15 .15 .17 .29 .25 -.25 .13 .26 .23 -.15 -.21 -.13 -.12 -.17 -.2 -.12 -.16 -.01 .00 -.01 -.04 .28 .25 .3

CVLT-C: Free Recall,

Long Delay .35 .46 .35 .31 .32 -.16 -.07 -.02 -.08 .69 .8 .79 1 .82 .38 .4 .42 .13 .14 .17 .18 .27 .22 -.27 .16 .28 .26 -.17 -.25 -.13 -.16 -.16 -.25 -.14 -.2 -.05 -.02 .01 -.03 .26 .25 .29

CVLT-C: Cued Recall,

Long Delay .37 .46 .37 .32 .32 -.16 -.04 -.05 -.05 .68 .74 .87 .82 1 .43 .44 .41 .15 .16 .13 .15 .31 .24 -.28 .17 .27 .26 -.14 -.21 -.12 -.12 -.15 -.21 -.11 -.16 -.02 -.04 -.01 -.03 .27 .27 .31

CMS Stories 1:

Immediate Recall .6 .45 .49 .53 .56 -.24 -.04 -.05 -.04 .46 .41 .43 .38 .43 1 .96 .55 .52 .52 .32 .32 .22 .28 -.16 .24 .3 .32 .01 -.09 -.05 -.05 -.02 -.07 -.03 -.07 -.07 -.03 .00 -.06 .36 .26 .36

CMS Stories 2:

Delayed Recall .62 .46 .48 .54 .56 -.23 -.05 -.04 -.02 .46 .42 .44 .4 .44 .96 1 .56 .5 .5 .3 .31 .22 .29 -.19 .24 .31 .33 .00 -.09 -.06 -.05 -.04 -.08 -.05 -.07 -.07 -.04 .01 -.05 .38 .27 .37

Achievement

WJIII: Letter- Word

Identification .64 .6 .5 .6 .57 -.24 -.09 -.06 -.01 .46 .41 .42 .42 .41 .55 .56 1 .29 .31 .38 .39 .34 .39 -.24 .35 .44 .47 -.2 -.26 -.19 -.16 -.17 -.25 -.19 -.19 -.02 -.05 .03 -.09 .47 .37 .48

Fine Motor

Coordination

Grooved Pegboard: .14 .11 .07 .17 .17 -.1 .03 .11 .05 .14 .14 .13 .13 .15 .52 .5 .29 1 .9 .21 .25 .05 .09 .02 .04 .07 .06 .16 .08 .04 -.01 .15 .1 .07 -.01 -.04 .05 .00 .01 -.13 -.18 -.18
Abt Associates Inc. Chapter 9 115

Exhibit 9.1.2.5. Correlation Among Outcome Measures

Boston Nam

NEPS

Y: SP

NEPS

Y: C.I.

CELF: F.S.

CELF: R.S.

GFT

A

Stutter -A

Stutter - P

Stutter - T

C

VLT: FN

D

C

VLT: FS

D

C

V:T” C

S

D

C

VLT: FLD

C

VLT: CLD

C

M

S -1

C<S-2

WJ -LWID

Peg -Dom

Peg -N

D

Tap - Dom

Tap - N

D

SB Copy

G

D

S-Corr

G

D

S-Err

Digit - F

Digit - B

Digit - C

Meta -P

Meta- T

Hyper- P

Hyper -T

Inatt -P

Inatt - T

Behavior - P

Behavior - T

Motor Tics-A

Motor Tics P

Phon Tics-APhon Tics-P

Verbal IQ

Perf IQ

Full IQ

Dominant Hand (lower

= better)

Grooved Pegboard:

Non-dom Hand (lower

= better)

.15 .13 .08 .18 .18 -.08 .03 .11 .13 .17 .16 .15 .14 .16 .52 .5 .31 .9 1 .2 .21 .03 .08 .03 .05 .05 .06 .14 .07 .03 -.02 .15 .1 .06 .01 -.03 .05 .02 .01 -.1 -.18 -.16

Finger Tapping:

Dominant Hand .29 .3 .18 .3 .22 -.1 .02 -.04 -.01 .18 .16 .15 .17 .13 .32 .3 .38 .21 .2 1 .81 .22 .23 -.08 .14 .23 .22 -.02 -.01 -.01 .07 -.02 .00 -.05 .03 -.05 -.03 .07 .04 .07 .15 .13

Finger Tapping: Nondominant Hand .28 .26 .17 .28 .24 -.12 .03 .00 -.04 .18 .16 .17 .18 .15 .32 .31 .39 .25 .21 .81 1 .24 .2 -.06 .15 .2 .21 .00 .05 .00 .11 .00 .06 -.02 .06 -.03 .00 .07 .03 .07 .14 .13

Visual Spatial Ability

Stanford Binet:

Copying .29 .31 .22 .26 .28 -.14 -.01 -.14 -.1 .23 .23 .29 .27 .31 .22 .22 .34 .05 .03 .22 .24 1 .23 -.22 .19 .24 .26 -.2 -.24 -.17 -.17 -.17 -.22 -.15 -.2 -.03 -.01 .02 -.02 .21 .34 .31

Attention/ Executive

Functioning

GDS Vigilance Task:

Correct Responses .32 .35 .32 .34 .3 -.16 -.08 -.07 -.05 .31 .25 .25 .22 .24 .28 .29 .39 .09 .08 .23 .2 .23 1 -.41 .18 .25 .26 -.17 -.17 -.15 -.09 -.14 -.16 -.17 -.11 -.06 -.03 .02 -.02 .22 .2 .24

GDS Vigilance Task:

Errors (lower = better) -.22 -.32 -.26 -.28 -.25 .14 .15 .17 .07 -.25 -.27 -.25 -.27 -.28 -.16 -.19 -.24 .02 .03 -.08 -.06 -.22 -.41 1 -.15 -.22 -.22 .24 .23 .19 .14 .26 .24 .18 .2 .05 .04 .07 .07 -.24 -.22 -.26

WISC III: Digit Span,

Forward Recall .35 .31 .39 .31 .57 -.11 -.01 -.01 -.04 .23 .14 .13 .16 .17 .24 .24 .35 .04 .05 .14 .15 .19 .18 -.15 1 .38 .86 -.1 -.15 -.1 -.06 -.12 -.15 -.08 -.1 -.08 -.07 -.08 -.1 .34 .31 .38

WISC III: Digit Span,

Backward Recall .34 .39 .4 .34 .42 -.09 .01 -.07 -.02 .29 .28 .26 .28 .27 .3 .31 .44 .07 .05 .23 .2 .24 .25 -.22 .38 1 .8 -.19 -.25 -.16 -.12 -.2 -.25 -.11 -.18 -.06 -.02 -.08 -.05 .29 .34 .36

WISC III: Digit Span,

Combined .41 .42 .47 .39 .6 -.12 .00 -.05 -.04 .31 .24 .23 .26 .26 .32 .33 .47 .06 .06 .22 .21 .26 .26 -.22 .86 .8 1 -.17 -.24 -.15 -.11 -.18 -.24 -.11 -.17 -.09 -.06 -.1 -.09 .38 .39 .44

BRIEF Parent Rating:

Metacognition (lower =

better)

-.08 -.28 -.15 -.12 -.14 -.04 .04 .08 .07 -.17 -.18 -.15 -.17 -.14 .01 .00 -.2 .16 .14 -.02 .00 -.2 -.17 .24 -.1 -.19 -.17 1 .57 .63 .35 .88 .54 .7 .39 .04 .01 .17 .18 -.18 -.17 -.2

BRIEF Teacher Rating:

Metacognition (lower =

better)

-.14 -.34 -.25 -.18 -.21 .03 .09 .1 .14 -.21 -.22 -.21 -.25 -.21 -.09 -.09 -.26 .08 .07 -.01 .05 -.24 -.17 .23 -.15 -.25 -.24 .57 1 .44 .67 .6 .93 .38 .74 .06 .07 .11 .13 -.23 -.18 -.23

Behavior Regulation

(lower = better)

CRS-R: Parent Rating:

Hyperactive/Impulsive -.11 -.22 -.15 -.13 -.14 -.01 .02 .03 .00 -.16 -.16 -.13 -.13 -.12 -.05 -.06 -.19 .04 .03 -.01 .00 -.17 -.15 .19 -.1 -.16 -.15 .63 .44 1 .45 .67 .41 .75 .45 .07 .06 .15 .17 -.15 -.14 -.17

CRS-R: Teacher

Rating:

Hyperactive/Impulsive

-.08 -.19 -.08 -.09 -.11 .07 .02 .02 .1 -.14 -.16 -.12 -.16 -.12 -.05 -.05 -.16 -.01 -.02 .07 .11 -.17 -.09 .14 -.06 -.12 -.11 .35 .67 .45 1 .37 .63 .34 .8 .01 .08 .03 .09 -.12 -.04 -.09

CRS-R: Parent Rating:

Inattentive -.09 -.29 -.18 -.14 -.14 -.03 .00 .06 .07 -.16 -.18 -.17 -.16 -.15 -.02 -.04 -.17 .15 .15 -.02 .00 -.17 -.14 .26 -.12 -.2 -.18 .88 .6 .67 .37 1 .57 .61 .44 .05 .02 .19 .18 -.19 -.15 -.19

CRS-R: Teacher -.14 -.31 -.24 -.16 -.19 .04 .09 .12 .14 -.2 -.21 -.2 -.25 -.21 -.07 -.08 -.25 .1 .1 .00 .06 -.22 -.16 .24 -.15 -.25 -.24 .54 .93 .41 .63 .57 1 .35 .65 .05 .05 .11 .11 -.24 -.18 -.24
Abt Associates Inc. Chapter 9 116

Exhibit 9.1.2.5. Correlation Among Outcome Measures

Boston Nam

NEPS

Y: SP

NEPS

Y: C.I.

CELF: F.S.

CELF: R.S.

GFT

A

Stutter -A

Stutter - P

Stutter - T

C

VLT: FN

D

C

VLT: FS

D

C

V:T” C

S

D

C

VLT: FLD

C

VLT: CLD

C

M

S -1

C<S-2

WJ -LWID

Peg -Dom

Peg -N

D

Tap - Dom

Tap - N

D

SB Copy

G

D

S-Corr

G

D

S-Err

Digit - F

Digit - B

Digit - C

Meta -P

Meta- T

Hyper- P

Hyper -T

Inatt -P

Inatt - T

Behavior - P

Behavior - T

Motor Tics-A

Motor Tics P

Phon Tics-APhon Tics-P

Verbal IQ

Perf IQ

Full IQ

Rating: Inattentive

BRIEF Parent Rating:

Behavior Regulation -.08 -.2 -.14 -.15 -.12 .01 .06 .03 .06 -.16 -.15 -.12 -.14 -.11 -.03 -.05 -.19 .07 .06 -.05 -.02 -.15 -.17 .18 -.08 -.11 -.11 .7 .38 .75 .34 .61 .35 1 .41 .08 .04 .14 .23 -.13 -.15 -.16

BRIEF Teacher Rating:

Behavior Regulation -.11 -.24 -.14 -.14 -.16 .05 .1 .05 .18 -.19 -.18 -.16 -.2 -.16 -.07 -.07 -.19 -.01 .01 .03 .06 -.2 -.11 .2 -.1 -.18 -.17 .39 .74 .45 .8 .44 .65 .41 1 .1 .07 .05 .12 -.13 -.09 -.13

Tics (lower = better)

Motor tics (current):

Assessor Rating -.02 -.04 -.06 -.07 -.08 .03 .24 .04 .09 -.03 -.03 -.01 -.05 -.02 -.07 -.07 -.02 -.04 -.03 -.05 -.03 -.03 -.06 .05 -.08 -.06 -.09 .04 .06 .07 .01 .05 .05 .08 .1 1 .31 .18 .1 -.03 -.03 -.03

Phonics tics (current):

Assessor Rating -.08 -.06 -.03 -.11 -.05 -.02 .24 .05 .07 .01 -.04 .00 -.02 -.04 -.03 -.04 -.05 .05 .05 -.03 .00 -.01 -.03 .04 -.07 -.02 -.06 .01 .07 .06 .08 .02 .05 .04 .07 .31 1 .03 .13 -.08 -.03 -.07

Motor tics (current):

Parent Rating .00 .00 -.06 .01 -.05 -.05 .00 .13 .02 -.01 .00 -.01 .01 -.01 .00 .01 .03 .00 .02 .07 .07 .02 .02 .07 -.08 -.08 -.1 .17 .11 .15 .03 .19 .11 .14 .05 .18 .03 1 .43 -.06 -.02 -.05

Phonics tics (current):

Parent Rating -.1 -.06 -.1 -.11 -.13 .04 .04 .11 .08 -.07 -.02 -.04 -.03 -.03 -.06 -.05 -.09 .01 .01 .04 .03 -.02 -.02 .07 -.1 -.05 -.09 .18 .13 .17 .09 .18 .11 .23 .12 .1 .13 .43 1 -.13 -.08 -.12

General Intellectual

Functioning

WASI Verbal IQ .66 .41 .52 .52 .6 -.19 -.08 -.13 -.02 .3 .24 .28 .26 .27 .36 .38 .47 -.13 -.1 .07 .07 .21 .22 -.24 .34 .29 .38 -.18 -.23 -.15 -.12 -.19 -.24 -.13 -.13 -.03 -.08 -.06 -.13 1 .53 .87

WASI Performance IQ .48 .37 .48 .35 .4 -.13 -.04 -.1 -.05 .25 .21 .25 .25 .27 .26 .27 .37 -.18 -.18 .15 .14 .34 .2 -.22 .31 .34 .39 -.17 -.18 -.14 -.04 -.15 -.18 -.15 -.09 -.03 -.03 -.02 -.08 .53 1 .88

WASI Full Scale IQ .65 .44 .57 .5 .57 -.18 -.07 -.13 -.04 .32 .25 .3 .29 .31 .36 .37 .48 -.18 -.16 .13 .13 .31 .24 -.26 .38 .36 .44 -.2 -.23 -.17 -.09 -.19 -.24 -.16 -.13 -.03 -.07 -.05 -.12 .87 .88 1

Pearson Correlation Coefficients
Abt Associates Inc. Chapter 9 117

9.2. Model Results

9.2.1. Overview

The model results section introduces the factors that motivated fitting each model, provides

specifications of the models and interpretation of parameter estimates, and provides

summaries of results fit to the data from the n=1,047 assessed children. Section 9.2.2 is

devoted to main effect models that estimate exposure effects on the combined population of

males and females. This section includes results of several variants of data subsets or coding

of particular variables. These variants are used to assess the sensitivity of results to particular

assumptions, analysis methods, or inclusion or omission of particular observations. The

results in this section are approximately equally balanced between findings where increased

exposure is associated with better outcome measures and findings where increased exposure

is associated with worse outcomes.

Section 9.2.3 focuses on sex-by-exposure interaction models. Estimates of exposure effects

on females and males are presented, as well as results of tests of sex-by-exposure interaction

effects.

Sections 9.2.4 and 9.2.5 are devoted to the question of whether prenatal exposure exacerbates

the effects of postnatal exposure. The results do not provide evidence to support the

hypothesis.

Section 9.2.6 concentrates on analyses to determine whether concurrent antibiotic receipt

exacerbates the effects of postnatal exposure. The pattern of results suggests random scatter

of small numbers of positive and negative effects.
Abt Associates Inc. Chapter 9 118

9.2.2. Main Effect Models

9.2.2.1. Introduction

This section summarizes the results of two main effects models that were fit to each of the 42

outcome variables. These models are considered to be of primary importance as they directly

address the study’s primary research questions. The first of the two models produces two

hypothesis tests. One is a test of the null hypothesis that prenatal exposure to ethylmercury

from thimerosal in vaccines and immune globulins is unrelated to the outcome measure. The

second is a test of the null hypothesis that cumulative exposure, over the age range spanning

birth to seven months, to ethylmercury from thimerosal used in vaccines and immune

globulins is unrelated to the outcome measure.

The second of the two models produces three hypothesis tests. One is a test of the null

hypothesis that ethylmercury exposures from thimerosal used in vaccines and immune

globulins received during the age range spanning birth to 28 days is unrelated to the outcome

measure. The second test is of the null hypothesis that cumulative exposures spanning the

age range from 29 days to seven months is unrelated to the outcome. And the third is a test of

the null hypothesis that prenatal exposure is unrelated to the outcome. The hypothesis tests

concerning prenatal exposures in models 1 and 2 produce almost identical results.

These two models were fit to a full data set with single imputation for missing values on

covariates, to a full data set with multiple imputation for missing values on covariates, to a

data set with an alternative coding for prenatal exposure, to several variants used to assess the

sensitivity of results regarding ADHD outcomes to coding of outcomes or inclusion/omission

of children who have taken medication for ADHD, and to a data set with a single outlier

omitted. Details on each are provided subsequently.

9.2.2.2. Model Specifications

The notation and variables shown in the model specifications below are defined in Chapter 8.

For tics and stuttering outcomes, logistic regression models that are analogous to the linear

regression models specified below, were fit to the data.

Model (1) Specification: Main Effects of Prenatal, and Cumulative Exposures from Birth to 7

Months

             

l

j k l l

k

j k k

j

j j Y preNatThimer Exp07mos oe cf St 0 1 2

: 0 : 0

: 0 : 0

0 2 2

0 1 1

 

 

 

 

a

a

H vs H

H vs H

Model (2) Specification: Main Effects of Prenatal, Hepatitis B at Birth, 1-7 Month Exposures
Abt Associates Inc. Chapter 9 119

   

   

  

    

     

l

j k l l

k

j k k

j

j j

oe cf St

Y preNatThimer HepB Exp17mos 0 1 2 3

H0: 1  0 vs Ha: 1  0

H0:  2  0 vs Ha:  2  0

H0:  3  0 vs Ha:  3  0

9.2.2.3. Explanation of Model Results Summary Table

Results from Models (1) and (2) are summarized in Exhibit 9.2.1. Model (1) is summarized

in the left side of the exhibit, and the summary for Model (2) appears on the right-hand side.

For each model and each outcome variable, the exhibit shows the parameter estimate,

standard error, p-value from the hypothesis test, and a standardized regression coefficient for

each of the ethylmercury exposure variables. As indicated in the exhibit, for some values, a

higher score (positive value for parameter estimate) indicates a better outcome, and for others

a lower score (negative value for parameter estimate) indicates a more desirable outcome.

Statistically significant relationships (i.e., p<0.05) are highlighted with a box around the pvalue, shading inside the box, and either a “+” or a “*” next to the p-value, depending on the

direction of the relationship. When the relationship was such that higher mercury exposure

was related to worse values on the outcome measure, the significant p-value was highlighted

with a blue box and a “*” appears next to the value. When the relationship was such that

higher mercury exposure was related to better values on the outcome measure, the significant

p-value was highlighted with a red box and a “+” appears next to the value. P-values that

were above the p<0.05 criterion, but below p<0.10 are also highlighted in the exhibit with

red or blue boxes. While these relationships do not satisfy the study’s criterion for statistical

significance, we felt that highlighting these weaker effects would help illuminate any pattern

of relationships in the results.

For outcomes analyzed using linear regression models (i.e., outcomes other than tics and

stuttering), the values in the standardized regression coefficient column (labeled “StCf” in

the exhibit) indicate the model predicted difference of the outcome measure, expressed in

standard deviation units, associated with an increase of one standard deviation unit of the

exposure measure. For example, in Exhibit 9.2.1, the standardized coefficient for the

significant relationship of prenatal exposure to the NEPSY speeded naming outcome

measure is 0.058. Therefore, the model predicts that an increase of one standard deviation

unit of prenatal exposure is associated with improved scores on this outcome measure where

the amount of improvement is equal to 0.058 standard deviation units of the outcome

measure. Within the prenatal exposure column, it is reasonable to compare values of the

standardized coefficients among all of the outcomes (except the tics and stuttering outcomes,

which will be discussed subsequently). Therefore we may conclude that the size of the

estimated beneficial effect of prenatal exposure on the NEPSY Speeded Naming outcome

(0.058 standard deviation units), is similar to the size of the estimated harmful effect of

prenatal exposure on the WISC III Digit Span Backward Recall outcome measure (-0.066

standard deviation units).
Abt Associates Inc. Chapter 9 120

For each of the exposure measures, one can think of a difference of two standard deviation

units as approximately corresponding to the difference between high and low exposure.

Therefore, for the outcomes analyzed using linear regression models, doubling the

standardized regression coefficient gives an effect size that roughly corresponds to the

difference between high and low exposure. Returning to the NEPSY Speeded Naming

example, one can think of the model predicted results as indicating that the difference

between high and low prenatal exposure roughly corresponds to an effect size of 0.116.

For the tics and stuttering outcomes, which were analyzed in logistic regression models, the

value in the standardized regression coefficient column corresponds to the odds ratio

associated with an increase of two standard deviation units of the exposure measure. For

example, in Exhibit 9.2.1, the value in the “SdCF” column of the “Exp07Mos” exposure

variable for “Motor tics (current): Assessor Rating” is 1.357. That means that the estimated

effect of a two standard deviation increase in cumulative exposures in the age range from

birth to seven months, is a 36 percent increase in the likelihood of assessor reported motor

tics. When increased exposure is related to a decrease in the probability of the outcome, the

odds ratio takes a value less than one. An example from Model (2), corresponding to HepB

exposure for parent reported motor tics, is a value in the “SdCF” column equal to 0.665. In

order to get a sense of the relative magnitude of values that are less than one, as compared to

values that are greater than one, the reader can invert the values. Inverting the value in this

example gives 1/0.665 = 1.50. Thus the model predicted effect of a two standard deviation

increase in HepB exposure, is a 50 percent increase in the likelihood of not having parent

reported motor tics. This effect was not significantly different than zero.

For details on the calculation of the values in the StCF columns of the exhibit, see Chapter 8.

9.2.2.4. Results

9.2.2.4.1. Main Effect Models with Single Imputation for

Covariates with Missing Values

Across the collection of outcome measures that were assessed in this study, the model results

summarized in Exhibit 9.2.2.1 do not suggest clear evidence of either harm or benefit of

increased exposure to ethylmercury from vaccines or immune globulins. The results indicate

that increased mercury exposure was about as likely to be associated with better outcomes as

it was to be associated with worse outcomes. Higher levels of prenatal exposure was related

to worse scores on the WISC III Digit Span Backward Recall assessment, but was associated

with better scores on the NEPSY Speeded Naming test. Cumulative exposures spanning the

age range from birth to seven months was associated with better scores on the Grooved

Pegboard test with the non-dominant hand, and with better scores on WISC III Digit Span

Backward Recall assessment. Higher exposure in the first month of life (HepB exposure)

was associated with more errors on the GFTA Test of Articulation, but with higher scores on

the Finger Tapping test with the dominant hand. And finally, cumulative exposures during

the age range spanning 1 to 7 months had no significant associations that were in the

direction of worse outcomes, but was associated with better scores on the WJIII Letter Word

Identification test, and better scores on the Grooved Pegboard test with the non-dominant

hand.
Abt Associates Inc. Chapter 9 121

Among the results that were highlighted because the p-values were above 0.05, but below

0.10, there was a similar pattern of approximate balance between findings where the

association was in the direction of higher exposure being related to worse outcomes and

associations that were in direction of higher exposure being related to better outcomes.
Abt Associates Inc. Chapter 9 122

Exhibit 9.2.2.1 Main Effect Models (1) and (2) (n=1,047)

Est S.E. P StCf

0.061 0.032 0.058 0.051

0.019 0.041 0.650 0.015

-0.012 0.015 0.412 -0.028

-0.031 0.032 0.337 -0.030

0.008 0.066 0.908 0.004

0.004 0.010 0.718 0.013

0.022 0.035 0.521 1.346

0.034 0.045 0.451 1.571

0.008 0.026 0.753 1.117

-0.003 0.049 0.950 -0.002

-0.025 0.014 0.076 -0.060

-0.009 0.012 0.464 -0.025

-0.019 0.013 0.139 -0.050

0.000 0.013 0.981 0.001

-0.024 0.063 0.701 -0.010

0.013 0.063 0.834 0.006

0.079 0.039 0.045 + 0.056

-0.058 0.094 0.542 -0.014

-0.279 0.116 0.017+ -0.059

0.013 0.033 0.705 0.012

0.016 0.030 0.605 0.017

0.010 0.016 0.542 0.022

0.037 0.027 0.176 0.048

-0.025 0.071 0.730 -0.012

0.000 0.010 0.964 -0.002

0.016 0.009 0.069 0.064

0.017 0.015 0.262 0.039

-0.059 0.098 0.549 -0.022

-0.165 0.140 0.241 -0.049

0.013 0.028 0.641 0.017

-0.051 0.036 0.150 -0.059

-0.028 0.032 0.374 -0.032

-0.039 0.046 0.390 -0.036

0.093 0.059 0.115 0.057

-0.071 0.076 0.353 -0.039

0.039 0.023 0.094 1.680

0.037 0.024 0.120 1.634

0.012 0.022 0.599 1.167

0.005 0.020 0.803 1.068

-0.003 0.070 0.961 -0.002

0.110 0.079 0.162 0.048

0.075 0.072 0.295 0.034

Exp17mos

Est S.E. P StCf Est S.E. P StCf Est S.E. P StCf Est S.E. P StCf

Speech and Language

Boston Naming Test 0.032 0.022 0.143 0.033 0.050 0.030 0.096 0.045 0.032 0.022 0.133 0.034 -0.044 0.101 0.664 -0.011

NEPSY: Speeded Naming 0.057 0.027 0.034 + 0.058 0.010 0.038 0.784 0.009 0.058 0.027 0.033 + 0.059 -0.058 0.126 0.646 -0.014

NEPSY: Comprehension of Instructions -0.002 0.010 0.860 -0.005 -0.014 0.014 0.310 -0.035 -0.002 0.010 0.873 -0.005 -0.030 0.045 0.504 -0.020

CELF: Formulated Sentences 0.021 0.021 0.327 0.026 -0.035 0.030 0.237 -0.038 0.021 0.021 0.319 0.026 -0.077 0.099 0.435 -0.022

CELF: Recalling Sentences 0.058 0.044 0.187 0.034 -0.001 0.062 0.984 -0.001 0.059 0.044 0.182 0.034 -0.079 0.206 0.703 -0.011

GFTA: Articulation (lower = better) -0.002 0.007 0.804 -0.007 0.011 0.010 0.249 0.042 -0.002 0.007 0.735 -0.010 0.075 0.032 0.017 * 0.077

Stuttering: Assessor Rating (lower = better) -0.002 0.021 0.907 0.959 0.026 0.033 0.434 1.443 -0.003 0.021 0.898 0.956 0.054 0.103 0.599 1.229

Stuttering: Parent Rating (lower = better) -0.024 0.048 0.616 0.668 0.020 0.043 0.644 1.327 -0.024 0.049 0.620 0.667 -0.118 0.125 0.346 0.638

Stuttering: Teacher Rating (lower = better) -0.042 0.030 0.160 0.500 0.011 0.025 0.674 1.163 -0.041 0.030 0.162 0.503 0.029 0.074 0.696 1.118

Verbal Memory

CVLT-C: Free Recall, No Delay 0.029 0.033 0.385 0.024 -0.001 0.046 0.975 -0.001 0.028 0.033 0.389 0.024 0.013 0.153 0.935 0.002

CVLT-C: Free Recall, Short Delay -0.001 0.009 0.887 -0.004 -0.024 0.013 0.066 -0.063 -0.001 0.009 0.884 -0.004 -0.019 0.043 0.664 -0.013

CVLT-C: Cued Recall, Short Delay -0.001 0.008 0.910 -0.003 -0.005 0.011 0.639 -0.016 -0.001 0.008 0.889 -0.004 0.026 0.038 0.497 0.020

CVLT-C: Free Recall, Long Delay 0.001 0.009 0.917 0.003 -0.019 0.012 0.108 -0.054 0.001 0.009 0.914 0.003 -0.023 0.040 0.562 -0.018

CVLT-C: Cued Recall, Long Delay 0.005 0.008 0.568 0.016 0.001 0.012 0.928 0.003 0.005 0.008 0.574 0.016 0.008 0.039 0.845 0.006

CMS Stories 1: Immediate Recall 0.024 0.042 0.570 0.013 -0.030 0.060 0.610 -0.014 0.024 0.042 0.563 0.013 -0.084 0.197 0.671 -0.010

CMS Stories 2: Delayed Recall -0.010 0.041 0.817 -0.005 0.005 0.059 0.936 0.002 -0.009 0.041 0.828 -0.005 -0.066 0.193 0.732 -0.008

Achievement

W JIII: Letter- W ord Identification 0.011 0.026 0.675 0.010 0.062 0.037 0.094 0.047 0.012 0.026 0.639 0.011 -0.089 0.122 0.469 -0.018

Fine Motor Coordination

Grooved Pegboard: Dominant Hand (lower = better) -0.109 0.064 0.089 -0.033 -0.080 0.089 0.371 -0.021 -0.107 0.064 0.095 -0.032 -0.282 0.299 0.347 -0.020

Grooved Pegboard: Non-dom Hand (lower = better) -0.083 0.077 0.284 -0.022 -0.274 0.109 0.012 + -0.062 -0.083 0.077 0.282 -0.022 -0.226 0.362 0.532 -0.014

Finger Tapping: Dominant Hand -0.015 0.022 0.502 -0.018 0.034 0.031 0.271 0.036 -0.016 0.022 0.459 -0.020 0.222 0.103 0.032 + 0.062

Finger Tapping: Non-dominant Hand -0.015 0.020 0.455 -0.020 0.018 0.028 0.524 0.020 -0.015 0.020 0.451 -0.020 0.039 0.093 0.676 0.012

Visual Spatial Ability

Stanford Binet: Copying 0.005 0.011 0.628 0.014 0.007 0.015 0.667 0.016 0.005 0.011 0.611 0.015 -0.022 0.050 0.662 -0.014

Attention/Executive Functioning

GDS Vigilance Task: Correct Responses -0.013 0.018 0.470 -0.021 0.032 0.026 0.209 0.045 -0.013 0.018 0.485 -0.021 -0.009 0.085 0.914 -0.003

GDS Vigilance Task: Errors (lower = better) 0.033 0.047 0.489 0.020 -0.022 0.067 0.742 -0.012 0.032 0.047 0.493 0.020 0.000 0.220 0.999 0.000

W ISC III: Digit Span, Forward Recall 0.000 0.007 0.983 0.001 -0.002 0.010 0.820 -0.008 0.000 0.007 0.965 0.001 -0.017 0.032 0.594 -0.017

W ISC III: Digit Span, Backward Recall -0.013 0.006 0.027 * -0.066 0.018 0.008 0.028 + 0.078 -0.013 0.006 0.025 * -0.067 0.038 0.028 0.170 0.044

W ISC III: Digit Span, Combined -0.012 0.010 0.244 -0.034 0.017 0.015 0.242 0.041 -0.012 0.010 0.245 -0.034 0.014 0.048 0.773 0.009

BRIEF Parent Rating: Metacognition (lower = better) 0.021 0.066 0.744 0.010 -0.052 0.092 0.573 -0.020 0.021 0.066 0.750 0.010 0.009 0.307 0.976 0.001

BRIEF Teacher Rating: Metacognition (lower = better) 0.026 0.088 0.764 0.010 -0.147 0.133 0.268 -0.046 0.024 0.088 0.784 0.009 0.011 0.431 0.980 0.001

Behavior Regulation (lower = better)

CRS-R: Parent Rating: Hyperactive/Impulsive 0.007 0.019 0.725 0.011 0.019 0.026 0.469 0.026 0.006 0.019 0.745 0.010 0.071 0.087 0.414 0.027

CRS-R: Teacher Rating: Hyperactive/Impulsive 0.023 0.022 0.301 0.033 -0.048 0.034 0.157 -0.059 0.023 0.022 0.310 0.032 -0.016 0.110 0.883 -0.005

CRS-R: Parent Rating: Inattentive 0.011 0.022 0.606 0.016 -0.024 0.030 0.433 -0.028 0.011 0.022 0.619 0.015 0.019 0.100 0.848 0.006

CRS-R: Teacher Rating: Inattentive 0.002 0.029 0.939 0.002 -0.034 0.043 0.432 -0.033 0.002 0.029 0.957 0.002 0.014 0.141 0.919 0.004

BRIEF Parent Rating: Behavior Regulation -0.021 0.040 0.594 -0.016 0.077 0.055 0.167 0.050 -0.020 0.040 0.616 -0.015 -0.069 0.185 0.711 -0.012

BRIEF Teacher Rating: Behavior Regulation 0.035 0.048 0.455 0.024 -0.045 0.072 0.535 -0.026 0.032 0.048 0.498 0.022 0.182 0.231 0.432 0.029

Tics (lower = better)

Motor tics (current): Assessor Rating 0.017 0.011 0.104 1.336 0.032 0.022 0.142 1.586 0.018 0.011 0.089 1.357 -0.026 0.068 0.696 0.904

Phonics tics (current): Assessor Rating -0.011 0.018 0.560 0.839 0.037 0.023 0.102 1.702 -0.011 0.018 0.560 0.839 0.041 0.073 0.574 1.169

Motor tics (current): Parent Rating 0.003 0.012 0.832 1.043 -0.001 0.021 0.963 0.986 0.004 0.012 0.768 1.062 -0.107 0.069 0.122 0.665

Phonics tics (current): Parent Rating -0.014 0.016 0.409 0.798 0.007 0.019 0.699 1.109 -0.014 0.016 0.401 0.795 0.028 0.064 0.666 1.112

General Intellectual Functioning

W ASI Verbal IQ 0.054 0.047 0.252 0.030 -0.044 0.066 0.506 -0.021 0.057 0.047 0.224 0.032 -0.408 0.219 0.063 -0.053

W ASI Performance IQ -0.008 0.054 0.881 -0.004 0.130 0.074 0.080 0.061 -0.010 0.054 0.856 -0.005 0.323 0.252 0.200 0.040

W ASI Full Scale IQ 0.026 0.048 0.594 0.015 0.059 0.068 0.383 0.029 0.027 0.048 0.575 0.015 -0.084 0.225 0.707 -0.011

< .05 >.05, <.10 < .05 >.05, <.10

Key: Mercury effect = Better Outcome p-value+ p-value Mercury effect =W orse Outcome p-value* p-value

P-values shown are rounded to 3 decimal places. Therefore, a value shown as 0.050 may satisify p<0.05 criterion if the original value was rounded up, or may not satisify the criterion if the value was rounded down.

PreNatThimer HepB

Main Effects Model (2)

Exp07mos

Test

Main Effects Model (1)

PreNatThimer
Abt Associates Inc. Chapter 9 123

9.2.2.4.2. Main Effect Models With Multiple Imputation

for Covariates with Missing Values

When covariates had missing values, the missing values were replaced with imputed

values. The imputed values were the predicted values from regression models with

random noise added. The amount of missing data on covariates is shown in Section 9.1.

For the models summarized in the previous section, and all other models except those

summarized in the current section, a single imputed value replaced each missing value.

In order to assess whether the model results were sensitive to the imputation, we the

applied method of multiple imputation described in Little and Rubin (2002) to the two

main effects models previously discussed. Briefly, the method of multiple imputation

involves imputing ten separate values for each missing value. Each is a little different

because of the random noise added to the predicted value from the regression. Ten

separate data sets are created to accommodate the ten sets of imputations. Next, ten

separate regression models are fit to the ten data sets. A parameter estimate from the

multiple imputation method is the mean of the parameter estimates from the 10 separate

models fit to the 10 separate data sets. The standard error of the coefficient is calculated

as a function of the average of the standard errors from the 10 models, and the amount of

between-imputation variation in parameter estimates.

We fit multiple imputation models for the two main effects models to the data from the

42 outcome variables. The results are summarized in Exhibit 9.2.2.2. There were no

substantive difference between results from the multiple- and single-imputation methods.

It is not surprising that the multiple imputation results are very close to the single

imputation results. The imputations were for covariates only, and most covariates had

only small amounts of missing data.
Abt Associates Inc. Chapter 9 124

Exhibit 9.2.2.2 Main Effect Models (1) and (2) with Multiple Imputation for Missing Values of Covariates (n=1,047)

Est S.E. P StCf Est S.E. P StCf Est S.E. P StCf Est S.E. P StCf

Speech and Language

Boston Naming Test 0.031 0.022 0.145 0.033 0.052 0.030 0.087 0.046 0.032 0.022 0.135 0.034 -0.040 0.101 0.695 -0.009

NEPSY: Speeded Naming 0.057 0.027 0.033+ 0.059 0.011 0.038 0.771 0.010 0.058 0.027 0.032+ 0.059 -0.053 0.126 0.674 -0.012

NEPSY: Comprehension of Instructions -0.002 0.010 0.868 -0.005 -0.014 0.014 0.316 -0.035 -0.001 0.010 0.880 -0.004 -0.029 0.045 0.528 -0.019

CELF: Formulated Sentences 0.020 0.021 0.343 0.025 -0.035 0.030 0.244 -0.037 0.020 0.021 0.335 0.025 -0.076 0.099 0.440 -0.022

CELF: Recalling Sentences 0.057 0.044 0.194 0.033 0.002 0.062 0.979 0.001 0.058 0.044 0.189 0.034 -0.073 0.206 0.724 -0.010

GFTA: Articulation (lower = better) -0.002 0.007 0.811 -0.007 0.011 0.010 0.255 0.041 -0.002 0.007 0.741 -0.010 0.075 0.032 0.018* 0.076

Stuttering: Assessor Rating (lower = better) -0.002 0.021 0.907 0.959 0.026 0.033 0.434 1.443 -0.003 0.021 0.899 0.956 0.054 0.103 0.599 1.229

Stuttering: Parent Rating (lower = better) -0.024 0.048 0.616 0.668 0.020 0.043 0.644 1.327 -0.024 0.049 0.620 0.667 -0.118 0.125 0.346 0.638

Stuttering: Teacher Rating (lower = better) -0.042 0.030 0.160 0.500 0.011 0.025 0.674 1.163 -0.041 0.030 0.162 0.503 0.029 0.074 0.696 1.118

Verbal Memory

CVLT-C: Free Recall, No Delay 0.028 0.033 0.393 0.024 -0.001 0.046 0.982 -0.001 0.028 0.033 0.397 0.024 0.015 0.154 0.924 0.003

CVLT-C: Free Recall, Short Delay -0.001 0.009 0.903 -0.003 -0.024 0.013 0.065 -0.063 -0.001 0.009 0.899 -0.004 -0.019 0.043 0.666 -0.013

CVLT-C: Cued Recall, Short Delay -0.001 0.008 0.912 -0.003 -0.005 0.011 0.649 -0.015 -0.001 0.008 0.891 -0.004 0.026 0.038 0.491 0.021

CVLT-C: Free Recall, Long Delay 0.001 0.009 0.907 0.003 -0.019 0.012 0.109 -0.054 0.001 0.009 0.904 0.003 -0.023 0.040 0.570 -0.017

CVLT-C: Cued Recall, Long Delay 0.005 0.008 0.560 0.017 0.001 0.012 0.942 0.003 0.005 0.008 0.567 0.016 0.008 0.039 0.838 0.006

CMS Stories 1: Immediate Recall 0.024 0.042 0.573 0.013 -0.030 0.060 0.613 -0.014 0.024 0.042 0.566 0.013 -0.084 0.197 0.671 -0.010

CMS Stories 2: Delayed Recall -0.010 0.041 0.805 -0.006 0.003 0.059 0.953 0.002 -0.010 0.041 0.816 -0.005 -0.066 0.194 0.734 -0.008

Achievement

WJIII: Letter- Word Identification 0.011 0.026 0.676 0.010 0.063 0.037 0.091 0.048 0.012 0.026 0.639 0.011 -0.089 0.123 0.470 -0.018

Fine Motor Coordination

Grooved Pegboard: Dominant Hand (lower = better) -0.109 0.064 0.089 -0.033 -0.081 0.089 0.362 -0.021 -0.107 0.064 0.095 -0.032 -0.298 0.299 0.319 -0.021

Grooved Pegboard: Non-dom Hand (lower = better) -0.086 0.077 0.267 -0.023 -0.276 0.109 0.012+ -0.062 -0.086 0.077 0.266 -0.023 -0.241 0.362 0.507 -0.015

Finger Tapping: Dominant Hand -0.015 0.022 0.502 -0.018 0.035 0.031 0.255 0.037 -0.016 0.022 0.459 -0.020 0.224 0.103 0.030+ 0.063

Finger Tapping: Non-dominant Hand -0.014 0.020 0.490 -0.018 0.020 0.028 0.477 0.023 -0.014 0.020 0.484 -0.019 0.043 0.094 0.650 0.013

Visual Spatial Ability

Stanford Binet: Copying 0.005 0.011 0.610 0.015 0.006 0.015 0.686 0.015 0.006 0.011 0.593 0.016 -0.022 0.050 0.661 -0.014

Attention/Executive Functioning

GDS Vigilance Task: Correct Responses -0.013 0.018 0.484 -0.021 0.034 0.026 0.188 0.047 -0.012 0.018 0.499 -0.020 -0.007 0.085 0.932 -0.003

GDS Vigilance Task: Errors (lower = better) 0.031 0.047 0.506 0.020 -0.024 0.067 0.717 -0.013 0.031 0.047 0.509 0.020 -0.005 0.220 0.981 -0.001

WISC III: Digit Span, Forward Recall 0.000 0.007 0.999 0.000 -0.002 0.010 0.852 -0.007 0.000 0.007 0.982 0.001 -0.016 0.032 0.607 -0.017

WISC III: Digit Span, Backward Recall -0.013 0.006 0.028* -0.065 0.018 0.008 0.027+ 0.079 -0.013 0.006 0.027* -0.066 0.038 0.028 0.169 0.044

WISC III: Digit Span, Combined -0.012 0.010 0.243 -0.034 0.018 0.015 0.226 0.043 -0.012 0.010 0.244 -0.034 0.015 0.048 0.753 0.010

BRIEF Parent Rating: Metacognition (lower = better) 0.018 0.066 0.785 0.008 -0.050 0.092 0.584 -0.020 0.017 0.066 0.791 0.008 0.006 0.307 0.984 0.001

BRIEF Teacher Rating: Metacognition (lower = better) 0.026 0.088 0.766 0.010 -0.144 0.133 0.278 -0.045 0.024 0.088 0.787 0.009 0.018 0.431 0.966 0.002

Behavior Regulation (lower = better)

CRS-R: Parent Rating: Hyperactive/Impulsive 0.007 0.019 0.709 0.011 0.019 0.026 0.461 0.027 0.006 0.019 0.729 0.010 0.072 0.087 0.409 0.027

CRS-R: Teacher Rating: Hyperactive/Impulsive 0.023 0.022 0.307 0.033 -0.047 0.034 0.163 -0.058 0.022 0.022 0.317 0.032 -0.012 0.110 0.911 -0.004

CRS-R: Parent Rating: Inattentive 0.011 0.022 0.625 0.015 -0.023 0.030 0.443 -0.028 0.010 0.022 0.637 0.014 0.019 0.100 0.846 0.006

CRS-R: Teacher Rating: Inattentive 0.001 0.029 0.971 0.001 -0.034 0.043 0.432 -0.033 0.000 0.029 0.989 0.000 0.015 0.141 0.915 0.004

BRIEF Parent Rating: Behavior Regulation -0.022 0.040 0.577 -0.017 0.077 0.055 0.166 0.050 -0.021 0.040 0.599 -0.016 -0.069 0.185 0.711 -0.012

BRIEF Teacher Rating: Behavior Regulation 0.038 0.047 0.421 0.026 -0.041 0.072 0.566 -0.024 0.035 0.048 0.463 0.024 0.189 0.231 0.414 0.030

Tics (lower = better)

Motor tics (current): Assessor Rating 0.017 0.011 0.104 1.336 0.032 0.022 0.142 1.586 0.018 0.011 0.089 1.357 -0.026 0.068 0.696 0.904

Phonics tics (current): Assessor Rating -0.011 0.018 0.560 0.839 0.037 0.023 0.102 1.702 -0.011 0.018 0.560 0.839 0.041 0.073 0.575 1.169

Motor tics (current): Parent Rating 0.003 0.012 0.832 1.043 -0.001 0.021 0.963 0.986 0.004 0.012 0.768 1.062 -0.107 0.069 0.122 0.665

Phonics tics (current): Parent Rating -0.014 0.016 0.409 0.798 0.007 0.019 0.699 1.109 -0.014 0.016 0.401 0.795 0.028 0.064 0.666 1.112

General Intellectual Functioning

WASI Verbal IQ 0.053 0.047 0.253 0.030 -0.039 0.066 0.557 -0.019 0.057 0.047 0.225 0.032 -0.402 0.219 0.067 -0.053

WASI Performance IQ -0.007 0.054 0.902 -0.004 0.132 0.074 0.077 0.062 -0.008 0.054 0.877 -0.005 0.332 0.252 0.188 0.041

WASI Full Scale IQ 0.026 0.048 0.585 0.015 0.062 0.068 0.361 0.030 0.028 0.048 0.567 0.016 -0.074 0.225 0.741 -0.010

< .05 >.05, <.10 < .05 >.05, <.10

Key: Mercury effect = Better Outcome p-value+ p-value Mercury effect =Worse Outcome p-value* p-value

P-values shown are rounded to 3 decimal places. Therefore, a value shown as 0.050 may satisify p<0.05 criterion if the original value was rounded up, or may not satisify the criterion if the value was rounded down.

PreNatThimer HepB

Main Effects Model (2)

Exp07mos

Test

Main Effects Model (1)

PreNatThimer

Est S.E. P StCf

0.062 0.032 0.054 0.052

0.019 0.041 0.647 0.015

-0.012 0.015 0.412 -0.028

-0.030 0.032 0.344 -0.030

0.010 0.066 0.877 0.005

0.004 0.010 0.724 0.013

0.022 0.035 0.521 1.346

0.034 0.045 0.451 1.571

0.008 0.026 0.754 1.117

-0.003 0.049 0.954 -0.002

-0.025 0.014 0.075 -0.060

-0.009 0.012 0.471 -0.024

-0.019 0.013 0.139 -0.050

0.000 0.013 0.999 0.000

-0.024 0.063 0.705 -0.010

0.012 0.063 0.853 0.005

0.080 0.039 0.042+ 0.057

-0.057 0.094 0.544 -0.014

-0.281 0.117 0.016+ -0.059

0.014 0.033 0.681 0.013

0.018 0.030 0.560 0.019

0.009 0.016 0.561 0.021

0.039 0.027 0.158 0.050

-0.026 0.071 0.711 -0.013

0.000 0.010 0.993 0.000

0.016 0.009 0.066 0.065

0.018 0.015 0.248 0.040

-0.057 0.098 0.562 -0.021

-0.162 0.140 0.249 -0.048

0.013 0.028 0.632 0.017

-0.051 0.036 0.154 -0.059

-0.028 0.032 0.383 -0.031

-0.040 0.046 0.389 -0.036

0.093 0.059 0.114 0.057

-0.068 0.076 0.372 -0.038

0.039 0.023 0.094 1.680

0.037 0.024 0.120 1.634

0.012 0.022 0.599 1.167

0.005 0.020 0.803 1.068

0.002 0.070 0.982 0.001

0.111 0.079 0.158 0.048

0.077 0.072 0.283 0.035

>.05, <.10

Exp17mos
Abt Associates Inc. Chapter 9 125

9.2.2.4.3. Main Effect Models with Alternative

Prenatal Mercury Amount Assignments

The measure of prenatal exposure to ethylmercury was calculated as the sum of

ethylmercury amounts from maternal receipt of vaccines and immune globulins received

during pregnancy with the focus child. As explained in Section 7.2, different immune

globulin products contained different amounts of ethylmercury, and for many receipts

there was uncertainty regarding the specific product that was received. The medical

charts often indicated that the immune globulin product received was “rhogam”. The

uncertainty arises from the fact that while Rhogam is a specific product, the name

“rhogam” is also often used as a generic term, similar to the way “kleenex” if often used

as a generic term to refer to facial tissues, even though Kleenex is a specific product

name. For assigning mercury content amounts to each receipt, if the chart indicated

receipt of “rhogam”, we assigned a mercury amount equal to 12.75 micrograms.

However, if the term “rhogam” was being used generically, then some other product may

have been administered which may have contained up to 50 micrograms per dose.

Out of 88 prenatal rhogam receipts in the database, only four had a lot number or

manufacturer written on the record that clearly confirmed that the receipt was the product

“Rhogam”. In order to assess the sensitivity of the model results to our assumption that

the remaining 84 rhogam receipts were, in fact, receipts of the product “Rhogam” and

hence resulted in 12.75 micrograms of ethylmercury exposure, we created an alternative

version of the prenatal exposure variable where we made an alternative assumption that

each of these 84 receipts contained 50 micrograms of ethylmercury. Under the alternative

assumptions, these “rhogam” receipts were higher exposure events than prenatal receipts

of vaccines (influenza, tetatnus, diphtheria-tetanus, hepatitis-b). Under the original

assumptions, the prenatal vaccine receipts where higher exposure events, relative to the

“rhogam” receipts.

Exhibit 9.2.2.3 shows a summary of model results when the alternatively coded prenatal

exposure variable (PreNatThimer_Alt) was substituted for the original prenatal exposure

variable (PreNatThimer). Comparison of Exhibits 9.2.2.3 to 9.2.2.1 shows that alternative

coding does not produce dramatic differences from original results. The alternative

coding results in a slightly larger estimated beneficial effect of prenatal exposure on the

NEPSY Speeded Naming outcome, and a slightly smaller estimate of a harmful effect on

WISC III Digit Span, Backward Recall.
Abt Associates Inc. Chapter 9 126

Est S.E. P StCf

0.062 0.032 0.053 0.052

0.021 0.041 0.599 0.018

-0.012 0.015 0.411 -0.028

-0.030 0.032 0.350 -0.030

0.010 0.066 0.883 0.005

0.003 0.010 0.730 0.012

0.022 0.035 0.524 1.344

0.034 0.045 0.449 1.575

0.006 0.026 0.808 1.090

-0.002 0.049 0.973 -0.001

-0.024 0.014 0.077 -0.060

-0.009 0.012 0.461 -0.025

-0.019 0.013 0.141 -0.049

0.001 0.013 0.967 0.001

-0.023 0.063 0.717 -0.010

0.013 0.063 0.836 0.006

0.079 0.039 0.044+ 0.056

-0.062 0.094 0.511 -0.015

-0.283 0.116 0.015+ -0.060

0.012 0.033 0.727 0.011

0.015 0.030 0.625 0.016

0.010 0.016 0.530 0.023

0.037 0.027 0.182 0.047

-0.023 0.071 0.742 -0.012

0.000 0.010 0.965 -0.002

0.015 0.009 0.078 0.062

0.017 0.015 0.273 0.038

-0.058 0.098 0.550 -0.021

-0.164 0.140 0.243 -0.048

0.013 0.028 0.640 0.017

-0.050 0.036 0.157 -0.058

-0.028 0.032 0.379 -0.031

-0.039 0.046 0.391 -0.036

0.092 0.059 0.119 0.056

-0.070 0.076 0.360 -0.039

0.040 0.023 0.085 1.703

0.037 0.024 0.119 1.637

0.012 0.022 0.591 1.171

0.004 0.020 0.827 1.060

-0.001 0.070 0.988 -0.001

0.110 0.079 0.162 0.048

0.077 0.072 0.286 0.035

Exp17mos

Est S.E. P StCf Est S.E. P StCf Est S.E. P StCf Est S.E. P StCf

Speech and Language

Boston Naming Test 0.013 0.011 0.242 0.026 0.052 0.030 0.086 0.046 0.013 0.011 0.232 0.027 -0.039 0.101 0.698 -0.009

NEPSY: Speeded Naming 0.033 0.013 0.014+ 0.068 0.014 0.038 0.719 0.012 0.033 0.013 0.014+ 0.068 -0.051 0.126 0.683 -0.012

NEPSY: Comprehension of Instructions 0.001 0.005 0.791 0.008 -0.014 0.014 0.307 -0.035 0.001 0.005 0.783 0.008 -0.031 0.045 0.494 -0.021

CELF: Formulated Sentences 0.008 0.010 0.444 0.020 -0.034 0.030 0.251 -0.036 0.008 0.010 0.439 0.020 -0.074 0.099 0.455 -0.021

CELF: Recalling Sentences 0.018 0.022 0.415 0.021 0.002 0.062 0.980 0.001 0.018 0.022 0.410 0.021 -0.069 0.206 0.739 -0.009

GFTA: Articulation (lower = better) -0.003 0.003 0.316 -0.030 0.011 0.010 0.253 0.041 -0.004 0.003 0.290 -0.032 0.076 0.031 0.016* 0.077

Stuttering: Assessor Rating (lower = better) -0.004 0.012 0.752 0.879 0.026 0.033 0.435 1.441 -0.004 0.012 0.748 0.877 0.054 0.102 0.599 1.228

Stuttering: Parent Rating (lower = better) -0.002 0.015 0.876 0.926 0.020 0.043 0.639 1.333 -0.002 0.015 0.878 0.927 -0.118 0.125 0.345 0.636

Stuttering: Teacher Rating (lower = better) -0.011 0.010 0.307 0.701 0.009 0.025 0.731 1.131 -0.010 0.010 0.311 0.703 0.027 0.074 0.717 1.109

Verbal Memory

CVLT-C: Free Recall, No Delay 0.021 0.016 0.202 0.036 0.000 0.046 0.999 0.000 0.021 0.016 0.203 0.036 0.015 0.153 0.922 0.003

CVLT-C: Free Recall, Short Delay 0.003 0.005 0.510 0.019 -0.024 0.013 0.065 -0.063 0.003 0.005 0.512 0.019 -0.020 0.043 0.652 -0.014

CVLT-C: Cued Recall, Short Delay 0.000 0.004 0.924 -0.003 -0.005 0.011 0.636 -0.016 0.000 0.004 0.912 -0.003 0.026 0.038 0.499 0.020

CVLT-C: Free Recall, Long Delay 0.003 0.004 0.508 0.019 -0.019 0.012 0.110 -0.054 0.003 0.004 0.507 0.019 -0.024 0.040 0.556 -0.018

CVLT-C: Cued Recall, Long Delay 0.003 0.004 0.547 0.017 0.001 0.012 0.910 0.004 0.002 0.004 0.551 0.017 0.008 0.039 0.833 0.006

CMS Stories 1: Immediate Recall 0.022 0.021 0.292 0.024 -0.029 0.059 0.625 -0.013 0.022 0.021 0.289 0.024 -0.083 0.197 0.674 -0.010

CMS Stories 2: Delayed Recall 0.004 0.020 0.827 0.005 0.004 0.059 0.942 0.002 0.005 0.020 0.820 0.005 -0.069 0.193 0.720 -0.009

Achievement

WJIII: Letter- Word Identification -0.006 0.013 0.669 -0.010 0.062 0.037 0.092 0.047 -0.005 0.013 0.691 -0.009 -0.085 0.122 0.488 -0.017

Fine Motor Coordination

Grooved Pegboard: Dominant Hand (lower = better) -0.048 0.032 0.130 -0.030 -0.085 0.089 0.338 -0.022 -0.048 0.032 0.135 -0.029 -0.296 0.299 0.323 -0.021

Grooved Pegboard: Non-dom Hand (lower = better) -0.039 0.038 0.313 -0.021 -0.278 0.109 0.011+ -0.063 -0.039 0.038 0.312 -0.021 -0.237 0.362 0.513 -0.014

Finger Tapping: Dominant Hand -0.014 0.011 0.207 -0.034 0.033 0.031 0.282 0.035 -0.014 0.011 0.191 -0.035 0.221 0.103 0.032+ 0.062

Finger Tapping: Non-dominant Hand -0.015 0.010 0.119 -0.042 0.017 0.028 0.543 0.020 -0.015 0.010 0.118 -0.042 0.038 0.093 0.681 0.012

Visual Spatial Ability

Stanford Binet: Copying 0.004 0.005 0.436 0.023 0.007 0.015 0.653 0.016 0.004 0.005 0.427 0.024 -0.022 0.050 0.667 -0.014

Attention/Executive Functioning

GDS Vigilance Task: Correct Responses -0.005 0.009 0.560 -0.017 0.032 0.026 0.220 0.044 -0.005 0.009 0.570 -0.017 -0.011 0.085 0.896 -0.004

GDS Vigilance Task: Errors (lower = better) 0.006 0.023 0.801 0.007 -0.020 0.067 0.762 -0.011 0.006 0.023 0.805 0.007 0.007 0.219 0.974 0.001

WISC III: Digit Span, Forward Recall 0.000 0.003 0.970 0.001 -0.002 0.010 0.820 -0.008 0.000 0.003 0.959 0.002 -0.017 0.032 0.594 -0.017

WISC III: Digit Span, Backward Recall -0.005 0.003 0.078 -0.053 0.017 0.008 0.034+ 0.076 -0.005 0.003 0.075 -0.054 0.036 0.028 0.190 0.042

WISC III: Digit Span, Combined -0.005 0.005 0.367 -0.026 0.017 0.015 0.257 0.040 -0.005 0.005 0.369 -0.026 0.012 0.048 0.798 0.008

BRIEF Parent Rating: Metacognition (lower = better) -0.016 0.032 0.613 -0.015 -0.051 0.092 0.581 -0.020 -0.017 0.032 0.610 -0.015 0.017 0.306 0.956 0.002

BRIEF Teacher Rating: Metacognition (lower = better) -0.004 0.045 0.927 -0.003 -0.145 0.132 0.274 -0.046 -0.005 0.045 0.917 -0.003 0.022 0.430 0.960 0.002

Behavior Regulation (lower = better)

CRS-R: Parent Rating: Hyperactive/Impulsive -0.004 0.009 0.625 -0.015 0.019 0.026 0.462 0.027 -0.005 0.009 0.612 -0.015 0.074 0.087 0.397 0.028

CRS-R: Teacher Rating: Hyperactive/Impulsive 0.004 0.011 0.745 0.011 -0.046 0.034 0.170 -0.057 0.004 0.011 0.751 0.011 -0.009 0.110 0.933 -0.003

CRS-R: Parent Rating: Inattentive -0.001 0.011 0.911 -0.003 -0.023 0.030 0.443 -0.028 -0.001 0.011 0.903 -0.004 0.022 0.100 0.828 0.007

CRS-R: Teacher Rating: Inattentive -0.001 0.015 0.971 -0.001 -0.034 0.043 0.434 -0.033 -0.001 0.015 0.964 -0.002 0.015 0.140 0.915 0.004

BRIEF Parent Rating: Behavior Regulation -0.020 0.020 0.317 -0.030 0.075 0.055 0.173 0.049 -0.019 0.020 0.326 -0.030 -0.069 0.185 0.708 -0.012

BRIEF Teacher Rating: Behavior Regulation 0.006 0.024 0.805 0.008 -0.042 0.072 0.556 -0.025 0.005 0.024 0.825 0.007 0.193 0.231 0.405 0.030

Tics (lower = better)

Motor tics (current): Assessor Rating 0.010 0.006 0.086 1.400 0.034 0.022 0.125 1.619 0.010 0.006 0.081 1.409 -0.021 0.068 0.754 0.922

Phonics tics (current): Assessor Rating 0.002 0.007 0.777 1.070 0.037 0.023 0.102 1.702 0.002 0.007 0.778 1.070 0.039 0.073 0.587 1.163

Motor tics (current): Parent Rating 0.000 0.007 0.944 0.984 -0.001 0.021 0.972 0.990 0.000 0.007 0.983 0.995 -0.106 0.069 0.126 0.668

Phonics tics (current): Parent Rating -0.004 0.007 0.558 0.870 0.006 0.019 0.728 1.097 -0.004 0.007 0.548 0.867 0.026 0.064 0.686 1.104

General Intellectual Functioning

WASI Verbal IQ 0.019 0.023 0.414 0.022 -0.041 0.066 0.534 -0.020 0.020 0.023 0.392 0.023 -0.398 0.219 0.069 -0.052

WASI Performance IQ 0.016 0.026 0.539 0.018 0.130 0.074 0.081 0.061 0.016 0.026 0.551 0.017 0.317 0.251 0.207 0.040

WASI Full Scale IQ 0.018 0.024 0.447 0.021 0.060 0.068 0.372 0.030 0.018 0.024 0.436 0.021 -0.083 0.224 0.713 -0.011

< .05 >.05, <.10 < .05 >.05, <.10

Key: Mercury effect = Better Outcome p-value+ p-value Mercury effect =Worse Outcome p-value* p-value

P-values shown are rounded to 3 decimal places. Therefore, a value shown as 0.050 may satisify p<0.05 criterion if the original value was rounded up, or may not satisify the criterion if the value was rounded down.

PreNatThimer_Alt HepB

Main Effects Model (2)

Exp07mos

Test

Main Effects Model (1)

PreNatThimer_Alt

Exhibit 9.2.2.3 Main Effect Models (1) and (2) with Alternative Coding of Prenatal Exposure Variable (n=1,047)
Abt Associates Inc. Chapter 9 127

9.2.2.4.4. Additional Main Effect Models for ADHD

Outcomes

Measures of attention deficit hyperactivity disorder (ADHD) symptomatology were

obtained from administration of Conners and BRIEF assessments14 to parents of teachers

of focus children. There was concern among the study’s external advisors that children

that were on ADHD medications in the time frame that parents and teachers completed

the Conners and BRIEF assessments might have lower scores than they would have had

if they had not been taking the medications. In order to address the concern, the study’s

external advisors recommended several additional analyses, described below.

The parent interview data indicate that 38 children took ADHD medications, including

two that had taken an ADHD stimulant within twelve hours of the clinical assessment.

We did three sets of follow-up analyses to better understand the results for these 38

children and to assess whether the findings from the full sample (including those 38)

were sensitive to the inclusion/exclusion of these 38 children from the analyses.

In the first set of analyses, we asked, how do the Conners and BRIEF scores of 38

children who took ADHD medications compare to the scores of children who did not take

medications? Those analyses indicate that the children who took ADHD medications had

significantly higher symptomotolgy scores on all 8 of the Conners and BRIEF assessment

scales.

In the second set of analyses, we re-fit the main effects models for the 8 Conners and

BRIEF outcomes, where the data from the 38 children who had taken ADHD medications

were excluded.

In the third set of analyses we made binary outcome measures for each of the 8

assessments. These binary measures took the value 1 if the child was above a clinically

relevant cut point15 on the assessment scale or if the child had taken ADHD medications;

and took the value zero of neither of those conditions occurred. We fit logistic regression

models to tests the main effects hypotheses to these binary outcome data.

The results of the second and third analyses described above, as well as the results from

the analyses on the full data set (these are the same results that are shown in Exhibit

9.2.2.1) are summarized in the Exhibit 9.2.2.4. Similar to the results from the full data

set, there were no significant effects from the models where the 38 children who took

ADHD medications were omitted. There were also no significant effects found in the

logistic models for the binary outcomes.

14 Conners’ Rating Scales – Revised, and Brief Behavior Rating Inventory of Executive Function. See

Section 7.1 for details.

15 Children scoring above this cut-point were at the 90th percentile or above on the symptoms rated in the

scale.
Abt Associates Inc. Chapter 9 128

Exhibit 9.2.2.4 Additional Main Effect Models for ADHD Outcomes (n=1,047)

Est S.E. P StCf Est S.E. P StCf Est S.E. P StCf Est S.E. P StCf

Linear Model (Thesearethesameresultsasshowninmainsummarytable.)

Attention/ExecutiveFunctioning(lower =better)

BRIEFParent Rating: Metacognition 0.021 0.066 0.744 0.010 -0.052 0.092 0.573 -0.020 0.021 0.066 0.750 0.010 0.009 0.307 0.976 0.001

BRIEFTeacher Rating: Metacognition 0.026 0.088 0.764 0.010 -0.147 0.133 0.268 -0.046 0.024 0.088 0.784 0.009 0.011 0.431 0.980 0.001

Behavior Regulation(lower =better)

CRS-R: Parent Rating: Hyperactive/Impulsive 0.007 0.019 0.725 0.011 0.019 0.026 0.469 0.026 0.006 0.019 0.745 0.010 0.071 0.087 0.414 0.027

CRS-R: Teacher Rating: Hyperactive/Impulsive 0.023 0.022 0.301 0.033 -0.048 0.034 0.157 -0.059 0.023 0.022 0.310 0.032 -0.016 0.110 0.883 -0.005

CRS-R: Parent Rating: Inattentive 0.011 0.022 0.606 0.016 -0.024 0.030 0.433 -0.028 0.011 0.022 0.619 0.015 0.019 0.100 0.848 0.006

CRS-R: Teacher Rating: Inattentive 0.002 0.029 0.939 0.002 -0.034 0.043 0.432 -0.033 0.002 0.029 0.957 0.002 0.014 0.141 0.919 0.004

BRIEFParent Rating: Behavior Regulation -0.021 0.040 0.594 -0.016 0.077 0.055 0.167 0.050 -0.020 0.040 0.616 -0.015 -0.069 0.185 0.711 -0.012

BRIEFTeacher Rating: Behavior Regulation 0.035 0.048 0.455 0.024 -0.045 0.072 0.535 -0.026 0.032 0.048 0.498 0.022 0.182 0.231 0.432 0.029

Linear Model (excludingn=39childrenwhosemothersindicatedthat childtakesdrugsfor ADHD)

Attention/ExecutiveFunctioning(lower =better)

BRIEFParent Rating: Metacognition -0.008 0.066 0.902 -0.004 -0.033 0.091 0.719 -0.013 -0.009 0.066 0.892 -0.004 0.051 0.304 0.867 0.005

BRIEFTeacher Rating: Metacognition -0.008 0.090 0.927 -0.003 -0.147 0.133 0.270 -0.046 -0.012 0.090 0.890 -0.005 0.117 0.433 0.787 0.010

Behavior Regulation(lower =better)

CRS-R: Parent Rating: Hyperactive/Impulsive -0.003 0.018 0.882 -0.004 0.020 0.025 0.426 0.028 -0.003 0.018 0.855 -0.005 0.082 0.085 0.338 0.031

CRS-R: Teacher Rating: Hyperactive/Impulsive 0.012 0.022 0.582 0.018 -0.059 0.034 0.081 -0.072 0.011 0.022 0.616 0.016 0.019 0.109 0.862 0.006

CRS-R: Parent Rating: Inattentive 0.001 0.021 0.957 0.002 -0.011 0.029 0.719 -0.013 0.001 0.021 0.967 0.001 0.018 0.098 0.855 0.006

CRS-R: Teacher Rating: Inattentive -0.010 0.029 0.722 -0.012 -0.032 0.043 0.466 -0.031 -0.011 0.029 0.693 -0.013 0.052 0.140 0.710 0.014

BRIEFParent Rating: Behavior Regulation -0.038 0.040 0.336 -0.029 0.083 0.055 0.133 0.054 -0.037 0.040 0.351 -0.029 -0.045 0.184 0.805 -0.008

BRIEFTeacher Rating: Behavior Regulation 0.000 0.048 0.996 0.000 -0.050 0.071 0.484 -0.029 -0.005 0.048 0.924 -0.003 0.230 0.229 0.316 0.036

Logistic Model (Outcome=1if childtakesdrugsfor ADHDor if childscoredabovecriteriononConners/Brief assessments)

Attention/ExecutiveFunctioning(lower =better)

BRIEFParent Rating: Metacognition -0.002 0.011 0.872 -0.005 0.016 0.745 -0.002 0.011 0.861 0.027 0.053 0.613

BRIEFTeacher Rating: Metacognition -0.005 0.010 0.634 -0.003 0.016 0.844 -0.005 0.010 0.636 -0.007 0.049 0.888

Behavior Regulation(lower =better)

CRS-R: Parent Rating: Hyperactive/Impulsive -0.010 0.013 0.405 0.006 0.015 0.693 -0.011 0.013 0.402 0.016 0.050 0.756

CRS-R: Teacher Rating: Hyperactive/Impulsive 0.010 0.011 0.366 -0.005 0.020 0.790 0.010 0.011 0.361 -0.015 0.062 0.815

CRS-R: Parent Rating: Inattentive 0.006 0.011 0.582 -0.025 0.016 0.113 0.006 0.011 0.582 -0.026 0.055 0.636

CRS-R: Teacher Rating: Inattentive -0.003 0.012 0.808 0.010 0.019 0.589 -0.003 0.012 0.815 -0.009 0.057 0.880

BRIEFParent Rating: Behavior Regulation -0.003 0.013 0.841 0.021 0.018 0.238 -0.003 0.013 0.844 0.007 0.059 0.903

BRIEFTeacher Rating: Behavior Regulation 0.002 0.011 0.825 0.001 0.018 0.940 0.002 0.011 0.836 0.017 0.055 0.756

<.05 >.05, <.10 <.05 >.05, <.10

Key: Mercuryeffect =Better Outcome p-value+ p-value Mercuryeffect =WorseOutcome p-value* p-value

P-valuesshownareroundedto3decimal places. Therefore, avalueshownas 0.050maysatisifyp<0.05criterionif theoriginal valuewas roundedup, or maynot satisifythecriterionif thevaluewasroundeddown.

PreNatThimer HepB

MainEffectsModel (2)

Exp07mos

Test

MainEffectsModel (1)

PreNatThimer

Est S.E. P StCf

-0.059 0.098 0.549 -0.022

-0.165 0.140 0.241 -0.049

0.013 0.028 0.641 0.017

-0.051 0.036 0.150 -0.059

-0.028 0.032 0.374 -0.032

-0.039 0.046 0.390 -0.036

0.093 0.059 0.115 0.057

-0.071 0.076 0.353 -0.039

-0.042 0.097 0.663 -0.016

-0.177 0.141 0.210 -0.052

0.013 0.027 0.624 0.017

-0.067 0.035 0.059 -0.077

-0.014 0.031 0.659 -0.015

-0.041 0.046 0.373 -0.037

0.097 0.058 0.097 0.059

-0.082 0.075 0.275 -0.045

-0.009 0.017 0.605

-0.003 0.017 0.875

0.005 0.016 0.759

-0.004 0.021 0.840

-0.025 0.017 0.136

0.012 0.020 0.533

0.023 0.019 0.230

-0.001 0.019 0.976

>.05, <.10

Exp17mos
Abt Associates Inc. Chapter 9 129

9.2.3. Sex-by-Exposure Interaction Models

9.2.3.1. Introduction

The decision to test for differential exposure effects for boys and girls was motivated by

two considerations. The first was that the design of the current study was strongly

influenced by precedents set in the Faroe and Seychelles Island studies (Grandjean et. al,

1997; Davidson et. al 1998), and the Davidson study had tested for sex-by-exposure

interaction effects. The second consideration was that among the types of

neurodevelopmental outcomes measured in the current study, the frequency and severity

of delays or problems in the general population are often unequal for boys and girls, thus

generating the question of whether differential sensitivity to exposure might be related to

differential performance on the outcome measures.

The analysis summaries shown in this section present results of tests for interactions of

sex with prenatal exposure, cumulative exposure from birth to seven months, neonatal

exposure, and cumulative exposure from 1 to seven months. A commonly used reporting

convention is to report separate estimates of exposure effects for boys and girls only if

the interaction meets a pre-specified criterion for statistical significance. In this

convention, whenever the interaction is non-significant, only the combined effect for both

boys and girls is reported. For this report we have chosen not to adopt that reporting

convention. Instead, we report separate estimates of exposure effects, for boys and girls,

regardless of the result of the interaction test. We felt that the readers of this report would

be better served by having the more detailed set of results, even if the additional detail

presents them with greater challenges in terms of interpretation of results.

9.2.3.2. Model Specifications

The notation and variables shown in the model specifications below are defined in

Chapters 8. For tics and stuttering outcomes, logistic regression models that are

analogous to the linear regression models specified below, were fit to the data.

Interaction Model (1): Sex by Prenatal, and Birth-7 Month Exposures

The model shown below was used to estimate separate exposure effects for males and

females, and to test whether sex is an effect modifier for thimerosal exposure received

either by the mother during pregnancy (prenatal exposure) or received by the child during

period spanning birth to seven months of age. Sex is expressed as a dummy variable,

which takes the value 1 if the child is male, and takes the value zero if the child is female.

   





   

  





    

     

l

j k l l

k

j k k

j

j j

oe cf St

Exp mos Sexmale

preNatThimer Sexmale

Y preNatThimer Exp mos Sexmale

07 *

*

07

5

4

0 1 2 3
Abt Associates Inc. Chapter 9 130

1

ˆ = The estimated effect of prenatal exposure to ethylmercury from vaccines

and immune globulins received by the mother during pregnancy, for

females.

2

ˆ = The estimated effect of cumulative exposure to ethylmercury from

vaccines and immune globulins received by the child during the age

range from birth to seven months, for females.

3

ˆ = The average difference between males and females on the outcome

measure, after controlling for other terms in the model.

4

ˆ = The average difference between males and females in the effect of

prenatal exposure.

1 4

ˆ ˆ    = The estimated effect of prenatal exposure to ethylmercury from vaccines

and immune globulins received by the mother, for males.

5

ˆ = The average difference between males and females in the effect of

postnatal exposure.

2 5

ˆ ˆ    = The estimated effect of exposure to ethylmercury from vaccines and

immune globulins received by the child during the age range from birth

to seven months, for males.

 j  jk l

ˆ ... ˆ = Parameter estimates corresponding to model covariates. See Chapter 8

for details.

The model resulted in two tests of the null hypotheses that exposure effects are equal to

zero for females:

: 0 : 0

: 0 : 0

0 2 2

0 1 1

 

 

 

 

a

a

H vs H

H vs H

The model also resulted in two tests of the null hypotheses that exposure effects are equal

to zero for males:

: 0 : 0

: 0 : 0

0 2 5 2 5

0 1 4 1 4

   

   

   

   

a

a

H vs H

H vs H

And, the model resulted in two tests of the null hypotheses that the interaction

coefficients are equal to zero.

: 0 : 0

: 0 : 0

0 5 5

0 4 4

 

 

 

 

a

a

H vs H

H vs H

All tests were conducted using the p<0.05 criterion16.

Interaction Model (2): Sex by Prenatal, HepB at Birth, and 1-7 Month Exposures

The model shown below is similar to the previous model except that postnatal exposures

are separated into two time periods – birth to 28 days (represented by the HepB variable),

16 Since there is generally less power to detect interaction effects than main effects, it is not uncommon to

specify higher alpha levels for interaction tests. However, for the sake of consistency and simplicity, we

have elected to use a single alpha level criterion (p<0.05) for all tests of exposure effects.
Abt Associates Inc. Chapter 9 131

and cumulative exposures during the periods spanning 29 days to 7 months of age

(represented by the Exp17mos variable). As before, the model was used to estimate

separate exposure effects for males and females, and to test whether sex is an effect

modifier for prenatal or postnatal exposures.

   

  



   

  

   



    

     

l

j k l l

k

j k k

j

joe j

cf St

preNatThimer sexmale HepB sexmale Exp mos sexmale

sexmale

Y preNatThimer HepB Exp mos

* * 17 *

17

5 6 7

4

0 1 2 3

1

ˆ = The estimated effect of prenatal exposure to ethylmercury from vaccines

and immune globulins received by the mother, for females.

2

ˆ = The estimated effect of exposure to ethylmercury from vaccines and

immune globulins received by the child during the age range from birth

to one month (28 days), for females.

3

ˆ = The estimated effect of exposure to ethylmercury from vaccines received

by the child during the age range from one month (29 days) to seven

months, for females.

4

ˆ = The average difference between males and females on the outcome

measure, after controlling for other terms in the model.

5

ˆ = The average difference between males and females in the effect of

prenatal exposure.

1 5

ˆ ˆ    = The estimated effect of prenatal exposure to ethylmercury from vaccines

and immune globulins received by the mother, for males.

6

ˆ = The average difference between males and females in the effects of

exposures received during the age range spanning birth to 1 month (28

days).

2 6

ˆ ˆ    = The estimated effect of exposure to ethylmercury from vaccines and

immune globulins received by the child during the age range from birth

to one month, for males.

7

ˆ = The average difference between males and females in the effects of

exposures received during the age range spanning one to seven months.

3 7

ˆ ˆ    = The estimated effect of exposure to ethylmercury from vaccines and

immune globulins received by the child during the age range from one to

seven months, for males.

 j  jk l

ˆ ... ˆ = Parameter estimates corresponding to model covariates. See Chapter 8

for details.

The model resulted in three tests of the null hypotheses that exposure effects are equal to

zero for females:

: 0 : 0

: 0 : 0

: 0 : 0

0 3 3

0 2 2

0 1 1

 

 

 

 

 

 

a

a

a

H vs H

H vs H

H vs H
Abt Associates Inc. Chapter 9 132

The model also resulted in three tests of the null hypotheses that exposure effects are

equal to zero for males:

: 0 : 0

: 0 : 0

: 0 : 0

0 3 7 3 7

0 2 6 2 6

0 1 5 1 5

   

   

   

   

   

   

a

a

a

H vs H

H vs H

H vs H

And, the model resulted in three tests of the null hypotheses that the interaction

coefficients are equal to zero.

H0:  5  0 vs Ha:  5  0

H0:  6  0 vs Ha:  6  0

H0:  7  0 vs Ha:  7  0

9.2.3.3. Results

The results summarized in Exhibits 9.2.3.1 and 9.2.3.2 correspond to models fit to the full

data set and show the estimated exposure effects on females and males, respectively. For

each of the two sexes, there is an approximate balance between the number of significant

effects that are in the direction of harm and benefit.

9.2.3.3.1. Prenatal Exposure

There are four significant sex-by-prenatal-exposure interaction effects shown in the

summary tables. They are indicated by and “S*” next to the parameter estimate. For the

Stanford Binet Copying outcome measure, the interaction effect was such that the

estimated exposure effect for males was significant and beneficial, whereas the estimated

exposure effect was non-significant and in the direction of harm for females. For the

remaining three outcome measures with significant sex-by-prenatal-exposure

interactions, the estimated effects were in the direction of harm for one sex, but in the

direction of benefit for the other. In none of these was the estimated exposure effect

significantly different than zero for either sex.

For males, the estimated effect of prenatal exposure on performance of the WISC III Digit

Span Backwards Recall tests was significant and in the direction of harm. Although the

interaction test was not significant, indicating that we cannot reject the null hypothesis of

a common effect for males and females, the estimate for females was non-significant, but

also in the direction of harm.

9.2.3.3.2. Cumulative Exposure Birth to Seven Months

There is one significant sex-by-birth-to-seven-months-exposure interaction effect shown

in the summary tables. It corresponds to the Parent Rated Phonic Tics outcome measure,

and it is such that estimated effect is in the direction of harm for males, but is similar in
Abt Associates Inc. Chapter 9 133

magnitude but in the direction of benefit for females, and is non-significant for both

sexes.

There were three outcome measures where the estimated effects of cumulative exposure

in the age range spanning birth to seven months was associated with significant harmful

effects for males. However, there were also three outcome measures where the estimated

exposure effects were significant and beneficial. One was for males and two were for

females.

The estimated effects of exposures in the age range of one to seven months are very

similar to the estimated birth to seven month exposure effects, and are not discussed

further.

9.2.3.3.3. Neonatal Exposure (Birth to 28 Days)

There are six significant sex-by-neonatal-exposure interaction effects shown in the

summary tables. All are such that the estimated effects are in the direction of harm for

one sex, but in the direction of benefit for the other. In only one was the estimated

exposure effect significantly different than zero for either sex. That is the estimated

beneficial effect of increased exposure on the Finger Tapping Non-dominant Hand

outcome measure for males.

For females, increased neonatal exposure was associated with poorer scores on the WASI

Verbal IQ measure, whereas increased neonatal exposure was associated with better

scores on the WASI Performance IQ measure for males. Increased neonatal exposure was

associated with beneficial effects on Parent Rated Motor Tics for females, and for Finger

Tapping Dominant and Non-dominant Hands for males.
Abt Associates Inc. Chapter 9 134

Exhibit 9.2.3.1. Summary of Thimerosal Effects for Females (n=1,047; Data set included 538 females and 509 males)

Est S.E. P StCf

0.080 0.042 0.056 0.067

0.033 0.053 0.530 0.027

0.003 0.019 0.875 0.007

-0.034 0.041 0.409 -0.034

0.028 0.086 0.745 0.013

0.001 0.013 0.937 0.004

0.028 0.047 0.556 1.449

0.051 0.064 0.419 1.982

0.011 0.039 0.772 1.163

0.012 0.064 0.853 0.008

-0.023 0.018 0.195 -0.057

-0.006 0.016 0.691 -0.017

-0.011 0.017 0.522 -0.028

0.004 0.016 0.813 0.011

0.037 0.082 0.648 0.016

0.061 0.081 0.453 0.027

0.030 0.051 0.552 0.022

-0.042 0.123 0.732 -0.010

-0.347 0.151 0.022 + -0.073

0.003 0.043 0.950 0.003

0.013 0.039 0.745 0.014

S 0.033 0.021 0.113 0.074

0.050 0.036 0.159 0.065

-0.121 0.092 0.189 -0.061

-0.004 0.013 0.775 -0.013

0.025 0.011 0.027 + 0.102

0.022 0.020 0.276 0.050

-0.058 0.127 0.649 -0.021

-0.126 0.182 0.489 -0.037

-0.001 0.036 0.978 -0.001

-0.044 0.046 0.339 -0.051

-0.017 0.042 0.690 -0.019

-0.051 0.059 0.393 -0.046

0.019 0.077 0.805 0.012

-0.088 0.099 0.373 -0.049

0.020 0.031 0.531 1.300

0.004 0.034 0.899 1.059

0.016 0.032 0.624 1.234

S* -0.044 0.028 0.115 0.559

-0.035 0.091 0.696 -0.016

0.140 0.103 0.173 0.061

0.097 0.093 0.299 0.044

>.05, <.10

Exp17mos

Est S.E. P StCf Est S.E. P StCf Est S.E. P StCf Est S.E. P StCf

Speech and Language

Boston Naming Test 0.027 0.035 0.441 0.028 0.060 0.040 0.131 0.054 0.031 0.035 0.385 0.032 -0.147 0.141 0.300 -0.035

NEPSY: Speeded Naming 0.046 0.044 0.297 0.047 0.027 0.050 0.588 0.024 0.047 0.044 0.288 0.048 -0.026 0.177 0.882 -0.006

NEPSY: Comprehension of Instructions 0.003 0.016 0.831 0.010 -0.007 0.018 0.676 -0.019 0.005 0.016 0.746 0.015 S -0.113 0.063 0.075 -0.076

CELF: Formulated Sentences 0.026 0.035 0.456 0.032 -0.044 0.039 0.262 -0.047 0.027 0.035 0.429 0.034 -0.146 0.139 0.295 -0.041

CELF: Recalling Sentences 0.058 0.072 0.418 0.034 0.011 0.081 0.888 0.006 0.061 0.072 0.396 0.036 -0.157 0.289 0.585 -0.021

GFTA: Articulation (lower = better) -0.005 0.011 0.683 -0.020 0.008 0.013 0.533 0.030 -0.006 0.011 0.601 -0.026 0.073 0.044 0.098 0.075

Stuttering: Assessor Rating (lower = better) 0.037 0.024 0.120 1.847 0.025 0.045 0.571 1.439 0.037 0.024 0.119 1.855 -0.001 0.155 0.997 0.998

Stuttering: Parent Rating (lower = better) -0.717 8.949 0.936 0.000 0.038 0.062 0.536 1.726 -0.715 8.701 0.935 0.000 -0.141 0.195 0.468 0.583

Stuttering: Teacher Rating (lower = better) -0.046 0.049 0.348 0.467 0.005 0.038 0.901 1.071 -0.046 0.049 0.352 0.467 -0.095 0.123 0.441 0.695

Verbal Memory

CVLT-C: Free Recall, No Delay 0.033 0.054 0.543 0.028 -0.006 0.060 0.918 -0.005 0.036 0.054 0.502 0.031 -0.203 0.215 0.345 -0.040

CVLT-C: Free Recall, Short Delay -0.001 0.015 0.922 -0.005 -0.028 0.017 0.106 -0.072 -0.001 0.015 0.959 -0.002 -0.072 0.061 0.243 -0.050

CVLT-C: Cued Recall, Short Delay -0.007 0.013 0.577 -0.026 -0.009 0.015 0.529 -0.028 -0.007 0.013 0.599 -0.024 S -0.044 0.053 0.412 -0.035

CVLT-C: Free Recall, Long Delay -0.008 0.014 0.566 -0.026 -0.016 0.016 0.314 -0.045 -0.007 0.014 0.615 -0.023 -0.072 0.057 0.204 -0.054

CVLT-C: Cued Recall, Long Delay -0.008 0.014 0.541 -0.028 -0.002 0.016 0.898 -0.006 -0.007 0.014 0.600 -0.024 S* -0.069 0.055 0.212 -0.053

CMS Stories 1: Immediate Recall -0.021 0.069 0.765 -0.011 0.025 0.078 0.751 0.011 -0.018 0.069 0.792 -0.010 -0.110 0.276 0.690 -0.014

CMS Stories 2: Delayed Recall -0.060 0.068 0.372 -0.033 0.039 0.077 0.616 0.018 -0.056 0.068 0.410 -0.031 -0.199 0.272 0.463 -0.025

Achievement

WJIII: Letter- Word Identification -0.025 0.043 0.557 -0.022 S 0.009 0.048 0.856 0.007 -0.021 0.043 0.620 -0.019 -0.205 0.171 0.232 -0.042

Fine Motor Coordination

Grooved Pegboard: Dominant Hand (lower = better) -0.046 0.105 0.658 -0.014 -0.054 0.117 0.645 -0.014 -0.044 0.105 0.678 -0.013 -0.155 0.419 0.712 -0.011

Grooved Pegboard: Non-dom Hand (lower = better) -0.035 0.126 0.783 -0.009 -0.344 0.143 0.016 + -0.078 -0.035 0.127 0.781 -0.009 -0.316 0.509 0.535 -0.019

Finger Tapping: Dominant Hand 0.001 0.036 0.969 0.002 0.007 0.041 0.856 0.008 0.000 0.036 0.994 0.000 S 0.026 0.144 0.859 0.007

Finger Tapping: Non-dominant Hand 0.024 0.033 0.470 0.031 -0.006 0.037 0.871 -0.007 0.027 0.033 0.412 0.036 S* -0.204 0.131 0.118 -0.062

Visual Spatial Ability

Stanford Binet: Copying S* -0.033 0.017 0.057 -0.093 S 0.028 0.020 0.163 0.066 S* -0.032 0.018 0.065 -0.090 -0.029 0.071 0.685 -0.018

Attention/Executive Functioning

GDS Vigilance Task: Correct Responses -0.014 0.030 0.647 -0.022 0.036 0.034 0.282 0.050 -0.011 0.030 0.710 -0.018 -0.105 0.119 0.378 -0.039

GDS Vigilance Task: Errors (lower = better) 0.040 0.077 0.600 0.025 -0.111 0.087 0.201 -0.060 0.038 0.077 0.617 0.024 -0.007 0.308 0.981 -0.001

WISC III: Digit Span, Forward Recall S* -0.017 0.011 0.119 -0.076 -0.003 0.012 0.787 -0.013 S* -0.017 0.011 0.118 -0.076 0.004 0.044 0.928 0.004

WISC III: Digit Span, Backward Recall -0.004 0.010 0.656 -0.022 0.025 0.011 0.021 + 0.109 -0.004 0.010 0.654 -0.022 0.020 0.039 0.610 0.023

WISC III: Digit Span, Combined -0.021 0.017 0.208 -0.060 0.022 0.019 0.258 0.052 -0.021 0.017 0.211 -0.060 0.018 0.068 0.788 0.012

BRIEF Parent Rating: Metacognition (lower = better) S* -0.159 0.107 0.138 -0.073 -0.082 0.120 0.494 -0.032 S* -0.155 0.107 0.150 -0.071 -0.345 0.431 0.423 -0.036

BRIEF Teacher Rating: Metacognition (lower = better) -0.042 0.143 0.769 -0.016 -0.177 0.174 0.308 -0.056 -0.031 0.144 0.829 -0.011 S* -0.826 0.596 0.166 -0.070

Behavior Regulation (lower = better)

CRS-R: Parent Rating: Hyperactive/Impulsive -0.019 0.030 0.529 -0.031 -0.001 0.034 0.972 -0.002 -0.019 0.030 0.529 -0.031 -0.011 0.122 0.929 -0.004

CRS-R: Teacher Rating: Hyperactive/Impulsive 0.011 0.037 0.755 0.016 -0.055 0.045 0.219 -0.068 0.013 0.037 0.716 0.019 -0.186 0.153 0.225 -0.061

CRS-R: Parent Rating: Inattentive S* -0.048 0.035 0.175 -0.067 -0.020 0.039 0.609 -0.024 S* -0.047 0.035 0.180 -0.066 -0.061 0.141 0.664 -0.020

CRS-R: Teacher Rating: Inattentive 0.001 0.047 0.986 0.001 -0.070 0.057 0.222 -0.068 0.004 0.047 0.931 0.005 S* -0.312 0.195 0.109 -0.081

BRIEF Parent Rating: Behavior Regulation -0.060 0.065 0.353 -0.046 S -0.008 0.073 0.912 -0.005 -0.055 0.065 0.396 -0.042 -0.280 0.260 0.282 -0.049

BRIEF Teacher Rating: Behavior Regulation 0.013 0.077 0.871 0.009 -0.084 0.095 0.376 -0.049 0.013 0.078 0.872 0.009 -0.104 0.322 0.746 -0.016

Tics (lower = better)

Motor tics (current): Assessor Rating 0.033 0.020 0.104 1.733 0.003 0.030 0.928 1.039 0.036 0.020 0.083 1.806 S -0.174 0.108 0.109 0.515

Phonics tics (current): Assessor Rating -0.029 0.046 0.529 0.620 S -0.002 0.033 0.945 0.969 -0.029 0.046 0.532 0.621 -0.078 0.115 0.498 0.743

Motor tics (current): Parent Rating -0.052 0.054 0.335 0.424 -0.008 0.030 0.788 0.891 -0.051 0.054 0.344 0.425 -0.234 0.108 0.030 + 0.409

Phonics tics (current): Parent Rating -0.069 0.051 0.182 0.320 S* -0.038 0.026 0.149 0.584 -0.070 0.052 0.173 0.310 0.030 0.101 0.768 1.121

General Intellectual Functioning

WASI Verbal IQ 0.039 0.076 0.607 0.022 -0.097 0.086 0.263 -0.047 0.051 0.076 0.508 0.029 -0.738 0.307 0.017 * -0.097

WASI Performance IQ -0.032 0.092 0.726 -0.018 0.113 0.098 0.246 0.053 -0.029 0.092 0.756 -0.016 S* -0.211 0.349 0.546 -0.026

WASI Full Scale IQ -0.005 0.082 0.948 -0.003 0.044 0.089 0.622 0.021 0.004 0.082 0.957 0.002 S* -0.519 0.313 0.098 -0.068

< .05 >.05, <.10 < .05 >.05, <.10

Key: Mercury effect = Better Outcome p-value+ p-value Mercury effect =Worse Outcome p-value* p-value

P-values shown are rounded to 3 decimal places. Therefore, a value shown as 0.050 may satisify p<0.05 criterion if the original value was rounded up, or may not satisify the criterion if the value was rounded down.

S* (S) = Coefficient for females is significantly different than coefficient for males at the 0.05 (0.10) level

PreNatThimer HepB

Model (2)

Exp07mos

Test

Model (1)

PreNatThimer
Abt Associates Inc. Chapter 9 135

Exhibit 9.2.3.2. Summary of Thimerosal Effects for Males (n=1,047; Data set included 538 females and 509 males)

Est S.E. P StCf Est S.E. P StCf Est S.E. P StCf Est S.E. P StCf

Speech and Language

Boston Naming Test 0.034 0.027 0.207 0.036 0.041 0.040 0.304 0.036 0.035 0.027 0.195 0.037 0.062 0.141 0.658 0.015

NEPSY: Speeded Naming 0.064 0.034 0.059 0.066 -0.006 0.050 0.899 -0.006 0.064 0.034 0.058 0.066 -0.085 0.177 0.631 -0.020

NEPSY: Comprehension of Instructions -0.004 0.012 0.714 -0.013 -0.020 0.018 0.258 -0.051 -0.004 0.012 0.737 -0.012 S 0.053 0.063 0.401 0.036

CELF: Formulated Sentences 0.017 0.027 0.515 0.021 -0.027 0.039 0.488 -0.029 0.018 0.027 0.507 0.022 -0.012 0.137 0.930 -0.003

CELF: Recalling Sentences 0.059 0.056 0.294 0.034 -0.014 0.081 0.864 -0.007 0.059 0.056 0.289 0.034 0.003 0.288 0.991 0.000

GFTA: Articulation (lower = better) 0.000 0.009 0.990 0.000 0.014 0.012 0.259 0.053 0.000 0.009 0.970 -0.001 0.077 0.044 0.076 0.079

Stuttering: Assessor Rating (lower = better) -0.466 1.145 0.684 0.000 0.025 0.040 0.537 1.422 -0.465 1.136 0.682 0.000 0.077 0.129 0.552 1.340

Stuttering: Parent Rating (lower = better) -0.005 0.043 0.912 0.925 0.008 0.052 0.870 1.129 -0.005 0.044 0.918 0.928 -0.100 0.161 0.534 0.683

Stuttering: Teacher Rating (lower = better) -0.039 0.036 0.283 0.521 0.014 0.030 0.645 1.214 -0.036 0.035 0.300 0.545 0.095 0.089 0.288 1.436

Verbal Memory

CVLT-C: Free Recall, No Delay 0.026 0.042 0.533 0.022 0.003 0.061 0.954 0.003 0.027 0.042 0.523 0.023 0.225 0.213 0.291 0.044

CVLT-C: Free Recall, Short Delay -0.001 0.012 0.909 -0.004 -0.020 0.017 0.233 -0.053 -0.001 0.012 0.925 -0.003 0.032 0.060 0.594 0.022

CVLT-C: Cued Recall, Short Delay 0.003 0.010 0.784 0.010 -0.002 0.015 0.917 -0.005 0.003 0.010 0.762 0.011 S 0.094 0.052 0.072 0.075

CVLT-C: Free Recall, Long Delay 0.006 0.011 0.562 0.021 -0.023 0.016 0.144 -0.065 0.006 0.011 0.550 0.021 0.028 0.056 0.618 0.021

CVLT-C: Cued Recall, Long Delay 0.013 0.011 0.236 0.043 0.004 0.016 0.800 0.011 0.013 0.011 0.231 0.043 S* 0.087 0.055 0.115 0.067

CMS Stories 1: Immediate Recall 0.051 0.053 0.329 0.028 -0.086 0.078 0.267 -0.040 0.052 0.053 0.325 0.028 -0.037 0.274 0.893 -0.005

CMS Stories 2: Delayed Recall 0.022 0.052 0.678 0.012 -0.029 0.076 0.705 -0.014 0.022 0.052 0.670 0.012 0.086 0.270 0.749 0.011

Achievement

WJIII: Letter- Word Identification 0.030 0.033 0.358 0.027 S 0.113 0.048 0.019 + 0.086 0.031 0.033 0.347 0.027 0.022 0.170 0.897 0.004

Fine Motor Coordination

Grooved Pegboard: Dominant Hand (lower = better) -0.145 0.081 0.073 -0.044 -0.103 0.117 0.378 -0.027 -0.145 0.081 0.073 -0.044 -0.419 0.417 0.315 -0.029

Grooved Pegboard: Non-dom Hand (lower = better) -0.115 0.098 0.242 -0.030 -0.203 0.143 0.155 -0.046 -0.115 0.098 0.242 -0.030 -0.161 0.504 0.750 -0.010

Finger Tapping: Dominant Hand -0.025 0.028 0.364 -0.031 0.062 0.041 0.130 0.065 -0.024 0.027 0.375 -0.030 S 0.411 0.144 0.004 + 0.115

Finger Tapping: Non-dominant Hand -0.038 0.025 0.126 -0.051 0.043 0.037 0.244 0.049 -0.037 0.025 0.138 -0.049 S* 0.268 0.129 0.038 + 0.082

Visual Spatial Ability

Stanford Binet: Copying S* 0.029 0.014 0.033 + 0.080 S -0.015 0.020 0.444 -0.036 S* 0.029 0.014 0.032 + 0.081 -0.004 0.070 0.960 -0.002

Attention/Executive Functioning

GDS Vigilance Task: Correct Responses -0.013 0.023 0.580 -0.021 0.028 0.034 0.398 0.039 -0.012 0.023 0.596 -0.020 0.088 0.119 0.457 0.033

GDS Vigilance Task: Errors (lower = better) 0.025 0.060 0.674 0.016 0.066 0.087 0.444 0.036 0.025 0.060 0.677 0.016 -0.013 0.305 0.966 -0.002

WISC III: Digit Span, Forward Recall S* 0.010 0.009 0.220 0.046 -0.001 0.012 0.924 -0.004 S* 0.011 0.009 0.219 0.046 -0.036 0.044 0.419 -0.036

WISC III: Digit Span, Backward Recall -0.018 0.007 0.015 * -0.091 0.011 0.011 0.288 0.050 -0.018 0.007 0.016 * -0.090 0.055 0.038 0.148 0.065

WISC III: Digit Span, Combined -0.006 0.013 0.619 -0.018 0.012 0.019 0.512 0.030 -0.006 0.013 0.620 -0.018 0.013 0.068 0.851 0.008

BRIEF Parent Rating: Metacognition (lower = better) S* 0.128 0.083 0.123 0.058 -0.030 0.120 0.803 -0.012 S* 0.129 0.083 0.119 0.059 0.388 0.423 0.360 0.041

BRIEF Teacher Rating: Metacognition (lower = better) 0.068 0.112 0.546 0.025 -0.121 0.172 0.483 -0.038 0.063 0.112 0.570 0.023 S* 0.904 0.606 0.137 0.076

Behavior Regulation (lower = better)

CRS-R: Parent Rating: Hyperactive/Impulsive 0.021 0.023 0.369 0.034 0.038 0.034 0.266 0.053 0.021 0.023 0.368 0.034 0.156 0.121 0.200 0.058

CRS-R: Teacher Rating: Hyperactive/Impulsive 0.029 0.028 0.291 0.042 -0.042 0.044 0.341 -0.052 0.029 0.028 0.294 0.042 0.159 0.153 0.299 0.053

CRS-R: Parent Rating: Inattentive S* 0.046 0.027 0.090 0.064 -0.030 0.039 0.448 -0.036 S* 0.046 0.027 0.087 0.065 0.112 0.138 0.417 0.036

CRS-R: Teacher Rating: Inattentive 0.002 0.036 0.946 0.003 0.001 0.057 0.991 0.001 0.001 0.036 0.976 0.001 S* 0.342 0.196 0.081 0.089

BRIEF Parent Rating: Behavior Regulation 0.000 0.050 0.994 0.000 S 0.157 0.072 0.030 * 0.103 0.000 0.050 0.995 0.000 0.128 0.255 0.615 0.023

BRIEF Teacher Rating: Behavior Regulation 0.049 0.060 0.421 0.033 -0.008 0.093 0.931 -0.005 0.045 0.060 0.453 0.031 0.474 0.325 0.145 0.075

Tics (lower = better)

Motor tics (current): Assessor Rating 0.012 0.013 0.361 1.213 0.055 0.027 0.043 * 2.186 0.012 0.013 0.355 1.217 S 0.062 0.083 0.453 1.267

Phonics tics (current): Assessor Rating -0.007 0.019 0.705 0.888 S 0.063 0.028 0.026 * 2.443 -0.007 0.019 0.698 0.886 0.108 0.088 0.218 1.513

Motor tics (current): Parent Rating 0.008 0.012 0.519 1.141 0.003 0.024 0.897 1.046 0.009 0.012 0.460 1.164 -0.032 0.085 0.710 0.886

Phonics tics (current): Parent Rating -0.002 0.016 0.919 0.973 S* 0.040 0.024 0.088 1.780 -0.002 0.016 0.914 0.971 0.027 0.082 0.743 1.109

General Intellectual Functioning

WASI Verbal IQ 0.060 0.059 0.308 0.034 0.008 0.086 0.924 0.004 0.062 0.059 0.291 0.035 -0.090 0.303 0.766 -0.012

WASI Performance IQ 0.004 0.067 0.955 0.002 0.145 0.098 0.137 0.068 0.005 0.067 0.938 0.003 S* 0.876 0.352 0.013 + 0.110

WASI Full Scale IQ 0.042 0.060 0.487 0.024 0.073 0.088 0.407 0.036 0.043 0.060 0.476 0.024 S* 0.362 0.314 0.249 0.048

< .05 >.05, <.10 < .05 >.05, <.10

Key: Mercury effect = Better Outcome p-value+ p-value Mercury effect =Worse Outcome p-value* p-value

P-values shown are rounded to 3 decimal places. Therefore, a value shown as 0.050 may satisify p<0.05 criterion if the original value was rounded up, or may not satisify the criterion if the value was rounded down.

S* (S) = Coefficient for males is significantly different than coefficient for females at the 0.05 (0.10) level

PreNatThimer HepB

Model (2)

Exp07mos

Test

Model (1)

PreNatThimer

Est S.E. P StCf

0.037 0.043 0.386 0.031

0.004 0.054 0.948 0.003

-0.029 0.019 0.131 -0.069

-0.029 0.042 0.491 -0.029

-0.016 0.088 0.854 -0.008

0.006 0.014 0.650 0.022

0.017 0.044 0.693 1.257

0.020 0.055 0.715 1.310

0.002 0.032 0.962 1.021

-0.025 0.066 0.709 -0.017

-0.027 0.018 0.147 -0.065

-0.013 0.016 0.405 -0.037

-0.029 0.017 0.085 -0.077

-0.007 0.017 0.696 -0.018

-0.093 0.084 0.272 -0.040

-0.043 0.083 0.600 -0.019

0.124 0.052 0.018 + 0.088

-0.065 0.127 0.609 -0.016

-0.208 0.155 0.180 -0.044

0.018 0.044 0.681 0.018

0.015 0.040 0.714 0.016

S -0.017 0.021 0.441 -0.037

0.021 0.037 0.569 0.027

0.076 0.094 0.418 0.038

0.003 0.014 0.815 0.011

0.006 0.012 0.616 0.024

0.012 0.021 0.550 0.028

-0.082 0.130 0.528 -0.030

-0.251 0.187 0.179 -0.074

0.023 0.037 0.533 0.030

-0.069 0.048 0.150 -0.079

-0.048 0.043 0.265 -0.053

-0.045 0.061 0.466 -0.041

0.159 0.078 0.042 * 0.097

-0.070 0.101 0.492 -0.038

0.053 0.029 0.065 2.030

0.057 0.029 0.053 2.137

0.006 0.027 0.813 1.087

S* 0.042 0.026 0.099 1.754

0.017 0.093 0.858 0.008

0.056 0.105 0.597 0.024

0.038 0.095 0.691 0.017

Exp17mos
Abt Associates Inc. Chapter 9 136

9.2.4. Cumulative Effects of Exposures Spanning the

Prenatal Period Though Age 7 Months

9.2.4.1. Introduction

The analyses summarized in this section present the results of two additional hypothesis

tests conducted to evaluate the combined effects of prenatal and postnatal exposures. The

first is a joint test for additive effects of prenatal and postnatal exposure, and the second

is an interaction test. The first simply tests the joint hypothesis that both effects are zero.

This is done to guard against the possibility that prenatal or postnatal exposure effects are

obscured by correlated errors of estimate. Because we are concerned with the cumulative

effect, we only use this test when the two estimated effects are in the same direction (i.e.,

both prenatal and postnatal estimates are in the direction of harm, or both are in the

direction of benefit). The second is a test for an interaction effect of prenatal and

postnatal exposure. This test was motivated by a theory that prenatal exposure could

exacerbate the effects of postnatal exposure.

The models producing the two additional hypothesis tests were fit to three sets of data.

The first set was comprised of the entire sample of 1,047 assessed children. The second

was a subset comprised only of data from females (n=538), and the third was the subset

comprised only of males (n=509).

9.2.4.2. Model Specifications for Two Additional Hypothesis

Tests

Joint Test

The first of the two tests is a test of the joint hypothesis that the effects of prenatal

exposure and cumulative exposures from birth through seven months are both zero. The

model is the same as model (1), presented in Section 9.2.2.2., but with an additional

hypothesis as specified below. Because we are concerned with cumulative effects, this

test is conducted only when coefficients for PreNatThimer and Exp07mos have the same

sign (i.e., both are positive or both are negative). We used an F-test for linear

regressions, and a likelihood ratio test for outcomes where logistic regression models

were used to obtain estimates of the effects on binary outcomes.

             

l

j k l l

k

j k k

j

j j Y preNatThimer Exp07mos oe cf St 0 1 2













 

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







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

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





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0

0

:

0

0

:

2

1

2

1

0









Ha H vs

Interaction Model
Abt Associates Inc. Chapter 9 137

This model produces a test of whether there is an interaction effect of PreNatThimer and

Exp07mos that goes above and beyond the additive effects of the two terms.

   

   

  

    

     

l

j k l l

k

j k k

j

j j

oe cf St

Y preNatThimer Exp07mos preNatThimer * Exp07mos 0 1 2 3

: 0 : 0 H0  3  vs Ha  3 

9.2.4.3. Results

A summary of models fit to the full data set is shown in Exhibit 9.2.4.1. Summaries of

models fit to the subsets of data from females, and males are shown in Exhibits 9.2.4.2

and 9.4.2.3, respectively.

9.2.4.3.1. Joint Test for Additive Effect

The test for a cumulative effect makes sense only when the direction of the effect for

PreNatThimer is consistent with the direction of the Exp07mos effect (i.e., coefficients

for both are negative or coefficients for both are positive). When both are in a consistent

direction, it is possible to find that a small, statistically non-significant effect of

PreNatThimer can combine with a small, statistically non-significant effect of Exp07mos

to result in a statistically significant combined effect of both. When the directions of the

two effects are not consistent (e.g., PreNatThimer weakly associated with better outcome

scores, and Exp07mos weakly associated with worse outcome scores) it makes no sense

to conduct a joint test of a combined additive effect for both.

Full Data Set

Of the 42 outcome measures, there were 13 for which the effects of PreNatThimer and

Exp07mos were in a consistent direction. For five outcomes the effects were in the

direction of worse outcomes and for eight the effects were in the direction of better

outcomes.

For the following five outcome measures, both the coefficients for of PreNatThimer and

Exp07mos were in the direction of increased exposure being related to worse outcomes:

 NEPSY: Comprehension of instructions

 CVLT-C Free Recall, Short Delay

 CVLT-C Cued Recall, Short Delay

 CRS-R: Parent Rating: Hyperactive / impulsive

 Motor tics (current): Assessor rating

For the following eight outcome measures, both the coefficients for of PreNatThimer and

Exp07mos were in the direction of increased exposure being related to better outcomes:

 Boston Naming Test

 NEPSY: Speeded Naming

 CVLT-C Cued Recall, Long Delay

 WJIII: Letter- Word Identification

 Grooved Pegboard: Dominant hand (lower=better)
Abt Associates Inc. Chapter 9 138

 Grooved Pegboard: Non-Dominant hand (lower=better)

 Stanford Binet: Copying

 WASI Full Scale IQ

The joint hypothesis test was conducted for the 13 outcome measures listed above. Only

one test was significant at the p<0.05 level. For the outcome measure, Grooved

Pegboard: Non-dominant Hand, the weak prenatal effect combined with the stronger

postnatal effect to result in a significant combined effect (p=0.02 for the hypothesis that

both effects are zero). This effect was in the direction of higher exposure to ethylmercury

from thimerosal being associated with lower response times (better scores) on the test.

Models Fit to Data from Females Only

For females, 21 of the 42 outcome measures had PreNatThimer and Exp07mos effects

that were both in the same direction. For 14 of the outcome measures both estimates were

in the direction of benefit, and for the remaining 7 outcome measures both estimates were

in the direction of harm. None of the joint tests were statistically significant.

Models Fit to Data from Males Only

For males, 16 of the 42 outcome measures had PreNatThimer and Exp07mos effects that

were both in the same direction. For 10 of the outcome measures both estimates were in

the direction of benefit, and for the remaining 6 outcome measures both estimates were in

the direction of harm. Two of the joint tests were significant at the p<0.05 level. For the

outcome measure, WJIII Letter Word Identification, the weak prenatal effect combined

with the stronger postnatal effect to result in a significant combined effect (p=0.03 for

the hypothesis that both effects are zero). This effect was in the direction of higher

exposure to ethylmercury from thimerosal being associated with better scores on the test.

For the outcome measure, Grooved Pegboard Dominant Hand, the weak postnatal effect

combined with the stronger prenatal effect to result in a significant combined effect

(p=0.045 for the hypothesis that both effects are zero). This effect was in the direction of

higher exposure to ethylmercury from thimerosal being associated with better scores on

the test.
Abt Associates Inc. Chapter 9 139

Exhibit 9.2.4.1. Summary of Models Testing Effects of Cumulative Exposure Prenatal Through Seven Months–Full Data Set (n=1,047)

Est S.E. P StCf Est S.E. P StCf Est S.E. P

Speech and Language

Boston Naming Test 0.032 0.022 0.143 0.033 0.050 0.030 0.096 0.045 0.078 0.092 0.087 0.294

NEPSY: Speeded Naming 0.057 0.027 0.034+ 0.058 0.010 0.038 0.784 0.009 0.100 0.281 0.109 0.010+

NEPSY: Comprehension of Instructions -0.002 0.010 0.860 -0.005 -0.014 0.014 0.310 -0.035 0.583 -0.012 0.039 0.758

CELF: Formulated Sentences 0.021 0.021 0.327 0.026 -0.035 0.030 0.237 -0.038 . 0.042 0.085 0.621

CELF: Recalling Sentences 0.058 0.044 0.187 0.034 -0.001 0.062 0.984 -0.001 . 0.169 0.178 0.341

GFTA: Articulation (lower = better) -0.002 0.007 0.804 -0.007 0.011 0.010 0.249 0.042 . -0.033 0.027 0.229

Stuttering: Assessor Rating (lower = better) -0.002 0.021 0.907 0.959 0.026 0.033 0.434 1.443 . 0.068 0.097 0.482

Stuttering: Parent Rating (lower = better) -0.024 0.048 0.616 0.668 0.020 0.043 0.644 1.327 . -0.033 0.158 0.836

Stuttering: Teacher Rating (lower = better) -0.042 0.030 0.160 0.500 0.011 0.025 0.674 1.163 . -0.011 0.094 0.905

Verbal Memory

CVLT-C: Free Recall, No Delay 0.029 0.033 0.385 0.024 -0.001 0.046 0.975 -0.001 . 0.094 0.134 0.484

CVLT-C: Free Recall, Short Delay -0.001 0.009 0.887 -0.004 -0.024 0.013 0.066 -0.063 0.181 0.016 0.038 0.663

CVLT-C: Cued Recall, Short Delay -0.001 0.008 0.910 -0.003 -0.005 0.011 0.639 -0.016 0.888 -0.001 0.033 0.975

CVLT-C: Free Recall, Long Delay 0.001 0.009 0.917 0.003 -0.019 0.012 0.108 -0.054 . 0.040 0.035 0.248

CVLT-C: Cued Recall, Long Delay 0.005 0.008 0.568 0.016 0.001 0.012 0.928 0.003 0.844 0.023 0.034 0.507

CMS Stories 1: Immediate Recall 0.024 0.042 0.570 0.013 -0.030 0.060 0.610 -0.014 . 0.254 0.169 0.134

CMS Stories 2: Delayed Recall -0.010 0.041 0.817 -0.005 0.005 0.059 0.936 0.002 . 0.258 0.167 0.123

Achievement

W JIII: Letter- Word Identification 0.011 0.026 0.675 0.010 0.062 0.037 0.094 0.047 0.220 0.071 0.106 0.503

Fine Motor Coordination

Grooved Pegboard: Dominant Hand (lower = better) -0.109 0.064 0.089 -0.033 -0.080 0.089 0.371 -0.021 0.149 -0.141 0.259 0.587

Grooved Pegboard: Non-dom Hand (lower = better) -0.083 0.077 0.284 -0.022 -0.274 0.109 0.012+ -0.062 0.022+ -0.336 0.315 0.286

Finger Tapping: Dominant Hand -0.015 0.022 0.502 -0.018 0.034 0.031 0.271 0.036 . -0.063 0.089 0.477

Finger Tapping: Non-dominant Hand -0.015 0.020 0.455 -0.020 0.018 0.028 0.524 0.020 . -0.056 0.080 0.482

Visual Spatial Ability

Stanford Binet: Copying 0.005 0.011 0.628 0.014 0.007 0.015 0.667 0.016 0.804 0.094 0.043 0.030+

Attention/Executive Functioning

GDS Vigilance Task: Correct Responses -0.013 0.018 0.470 -0.021 0.032 0.026 0.209 0.045 . -0.032 0.074 0.663

GDS Vigilance Task: Errors (lower = better) 0.033 0.047 0.489 0.020 -0.022 0.067 0.742 -0.012 . -0.036 0.191 0.852

W ISC III: Digit Span, Forward Recall 0.000 0.007 0.983 0.001 -0.002 0.010 0.820 -0.008 . -0.018 0.027 0.511

W ISC III: Digit Span, Backward Recall -0.013 0.006 0.027* -0.066 0.018 0.008 0.028 + 0.078 . -0.057 0.024 0.016*

W ISC III: Digit Span, Combined -0.012 0.010 0.244 -0.034 0.017 0.015 0.242 0.041 . -0.069 0.042 0.097

BRIEF Parent Rating: Metacognition (lower = better) 0.021 0.066 0.744 0.010 -0.052 0.092 0.573 -0.020 . -0.068 0.266 0.800

BRIEF Teacher Rating: Metacognition (lower = better) 0.026 0.088 0.764 0.010 -0.147 0.133 0.268 -0.046 . -0.571 0.357 0.110

Behavior Regulation (lower = better)

CRS-R: Parent Rating: Hyperactive/Impulsive 0.007 0.019 0.725 0.011 0.019 0.026 0.469 0.026 0.717 -0.103 0.074 0.168

CRS-R: Teacher Rating: Hyperactive/Impulsive 0.023 0.022 0.301 0.033 -0.048 0.034 0.157 -0.059 . -0.219 0.090 0.015+

CRS-R: Parent Rating: Inattentive 0.011 0.022 0.606 0.016 -0.024 0.030 0.433 -0.028 . 0.068 0.087 0.438

CRS-R: Teacher Rating: Inattentive 0.002 0.029 0.939 0.002 -0.034 0.043 0.432 -0.033 . -0.200 0.116 0.086

BRIEF Parent Rating: Behavior Regulation -0.021 0.040 0.594 -0.016 0.077 0.055 0.167 0.050 . -0.249 0.160 0.119

BRIEF Teacher Rating: Behavior Regulation 0.035 0.048 0.455 0.024 -0.045 0.072 0.535 -0.026 . -0.249 0.192 0.195

Tics (lower = better)

Motor tics (current): Assessor Rating 0.017 0.011 0.104 1.336 0.032 0.022 0.142 1.586 0.326 0.121 0.051 0.017 *

Phonics tics (current): Assessor Rating -0.011 0.018 0.560 0.839 0.037 0.023 0.102 1.702 . 0.066 0.073 0.362

Motor tics (current): Parent Rating 0.003 0.012 0.832 1.043 -0.001 0.021 0.963 0.986 . 0.021 0.054 0.700

Phonics tics (current): Parent Rating -0.014 0.016 0.409 0.798 0.007 0.019 0.699 1.109 . 0.048 0.061 0.428

General Intellectual Functioning

W ASI Verbal IQ 0.054 0.047 0.252 0.030 -0.044 0.066 0.506 -0.021 . 0.136 0.189 0.472

W ASI Performance IQ -0.008 0.054 0.881 -0.004 0.130 0.074 0.080 0.061 . 0.303 0.224 0.177

W ASI Full Scale IQ 0.026 0.048 0.594 0.015 0.059 0.068 0.383 0.029 0.584 0.244 0.201 0.226

< .05 >.05, <.10

Key: Mercury effect = Better Outcome p-value+ p-value Mercury effect =Worse Outcome

P-values shown are rounded to 3 decimal places. Therefore, a value shown as 0.050 may satisify p<0.05 criterion if the original value was rounded up, or may not satisify the criterion if the value was rounded down.

Test

Model w/ Joint Test

PreNatThimer Exp07mos Joint

Test

PreNatThimer

Est S.E. P Est S.E. P

0.054 0.031 0.077 -0.003 0.004 0.477

0.026 0.039 0.504 -0.010 0.005 0.034*

-0.015 0.014 0.295 0.000 0.002 0.785

-0.034 0.030 0.267 -0.001 0.004 0.795

0.006 0.063 0.922 -0.005 0.007 0.520

0.009 0.010 0.365 0.001 0.001 0.238

0.030 0.033 0.361 -0.003 0.005 0.477

0.019 0.044 0.659 0.000 0.007 0.955

0.012 0.026 0.629 -0.001 0.004 0.741

0.003 0.047 0.950 -0.003 0.006 0.616

-0.023 0.013 0.087 -0.001 0.002 0.626

-0.005 0.012 0.644 0.000 0.001 0.997

-0.017 0.012 0.175 -0.002 0.001 0.244

0.002 0.012 0.849 -0.001 0.001 0.589

-0.014 0.061 0.816 -0.010 0.007 0.161

0.023 0.060 0.702 -0.012 0.007 0.099

0.066 0.038 0.080 -0.003 0.004 0.559

-0.082 0.091 0.367 0.001 0.011 0.899

-0.291 0.111 0.009 + 0.011 0.013 0.407

0.031 0.032 0.330 0.002 0.004 0.574

0.015 0.029 0.604 0.002 0.003 0.593

0.013 0.015 0.406 -0.004 0.002 0.035*

0.031 0.026 0.237 0.001 0.003 0.791

-0.027 0.068 0.694 0.003 0.008 0.713

-0.003 0.010 0.722 0.001 0.001 0.494

0.015 0.008 0.070 0.002 0.001 0.055

0.013 0.015 0.372 0.002 0.002 0.157

-0.058 0.094 0.535 0.004 0.011 0.730

-0.193 0.135 0.154 0.025 0.015 0.085

0.012 0.026 0.659 0.005 0.003 0.130

-0.066 0.034 0.054 0.010 0.004 0.006*

-0.020 0.031 0.524 -0.002 0.004 0.504

-0.050 0.044 0.260 0.009 0.005 0.074

0.061 0.056 0.278 0.010 0.007 0.141

-0.066 0.073 0.367 0.012 0.008 0.127

0.040 0.022 0.070 -0.004 0.002 0.046+

0.042 0.023 0.070 -0.004 0.004 0.305

0.000 0.021 0.990 -0.001 0.002 0.732

0.011 0.019 0.556 -0.003 0.003 0.317

-0.038 0.067 0.571 -0.004 0.008 0.652

0.151 0.076 0.046+ -0.014 0.010 0.153

0.074 0.069 0.284 -0.010 0.009 0.265

< .05 >.05, <.10

p-value* p-value

P-values shown are rounded to 3 decimal places. Therefore, a value shown as 0.050 may satisify p<0.05 criterion if the original value was rounded up, or may not satisify the criterion if the value was rounded down.

Exp07mos PreNatThimer X Exp07mos

Interaction Model: Prenatal by

Postnatal
Abt Associates Inc. Chapter 9 140

.

Exhibit 9.2.4.2. Summary of Models Testing Effects of Cumulative Exposure Prenatal Through Seven Months – Females (n=538)

Est S.E. P

-0.004 0.006 0.441

-0.010 0.006 0.139

0.000 0.002 0.840

-0.003 0.005 0.598

-0.006 0.011 0.560

0.002 0.002 0.289

-0.011 0.007 0.124

-0.001 0.571 0.998

0.005 0.007 0.509

-0.006 0.008 0.428

-0.003 0.002 0.255

-0.001 0.002 0.557

-0.005 0.002 0.023*

-0.002 0.002 0.283

-0.007 0.010 0.513

-0.007 0.010 0.506

-0.004 0.006 0.551

0.001 0.017 0.943

0.014 0.019 0.464

0.000 0.005 0.995

0.002 0.005 0.676

-0.004 0.003 0.163

0.001 0.004 0.773

0.005 0.009 0.538

0.000 0.002 0.890

0.001 0.001 0.420

0.001 0.003 0.583

0.020 0.016 0.202

0.025 0.021 0.222

0.003 0.004 0.489

0.001 0.004 0.742

0.004 0.005 0.469

0.007 0.006 0.281

0.014 0.009 0.141

0.005 0.011 0.639

-0.010 0.006 0.089

-0.004 0.009 0.675

-0.014 0.010 0.182

-0.017 0.010 0.097

0.005 0.012 0.691

-0.003 0.015 0.852

0.003 0.013 0.844

PreNatThim er X Exp07mos

Est S.E. P StCf Est S.E. P StCf Est S.E. P Est S.E. P

Speech and Language

Boston Nam ing Test 0.037 0.036 0.303 0.039 0.053 0.045 0.240 0.048 0.294 0.139 0.137 0.310 0.060 0.046 0.192

NEPSY: Speeded Nam ing 0.041 0.042 0.337 0.042 0.018 0.054 0.738 0.016 0.595 0.269 0.160 0.093 0.035 0.055 0.523

NEPSY: Com prehension of Instructions 0.007 0.016 0.658 0.021 -0.005 0.020 0.815 -0.012 . -0.005 0.060 0.938 -0.006 0.021 0.786

CELF: Form ulated Sentences 0.035 0.032 0.273 0.043 -0.022 0.040 0.593 -0.023 . 0.097 0.121 0.424 -0.017 0.041 0.681

CELF: Recalling Sentences 0.060 0.072 0.403 0.035 0.025 0.090 0.780 0.013 0.677 0.212 0.271 0.433 0.036 0.092 0.693

GFTA: Articulation (lower = better) -0.006 0.011 0.547 -0.029 0.007 0.014 0.600 0.027 . -0.048 0.040 0.237 0.004 0.014 0.778

Stuttering: Assessor Rating (lower = better) 0.043 0.025 0.086 2.033 0.043 0.059 0.467 1.839 0.760 0.293 0.151 0.052 0.066 0.061 0.285

Stuttering: Parent Rating (lower = better) -0.712 8.358 0.932 0.000 0.096 0.080 0.230 3.927 . -0.529 13.692 0.969 0.096 0.080 0.230

Stuttering: Teacher Rating (lower = better) -0.041 0.050 0.410 0.503 -0.001 0.045 0.987 0.990 1.000 -0.172 0.216 0.426 -0.005 0.045 0.904

Verbal M emory

CVLT-C: Free Recall, No Delay 0.017 0.053 0.752 0.014 -0.008 0.066 0.907 -0.006 . 0.170 0.200 0.397 0.004 0.068 0.955

CVLT-C: Free Recall, Short Delay -0.004 0.015 0.793 -0.012 -0.031 0.018 0.091 -0.082 0.232 0.058 0.056 0.304 -0.026 0.019 0.165

CVLT-C: Cued Recall, Short Delay -0.012 0.012 0.336 -0.041 -0.013 0.015 0.387 -0.040 0.432 0.014 0.046 0.756 -0.011 0.016 0.475

CVLT-C: Free Recall, Long Delay -0.010 0.013 0.446 -0.033 -0.022 0.017 0.190 -0.061 0.320 0.099 0.050 0.047+ -0.013 0.017 0.435

CVLT-C: Cued Recall, Long Delay -0.010 0.012 0.412 -0.034 0.003 0.016 0.841 0.009 . 0.039 0.047 0.413 0.007 0.016 0.675

CMS Stories 1: Im m ediate Recall 0.003 0.067 0.964 0.002 0.071 0.084 0.400 0.032 0.701 0.162 0.252 0.520 0.083 0.086 0.337

CMS Stories 2: Delayed Recall -0.049 0.065 0.451 -0.027 0.092 0.083 0.268 0.043 . 0.108 0.245 0.659 0.103 0.085 0.221

Achievem ent

W JIII: Letter- W ord Identification -0.031 0.042 0.452 -0.028 -0.015 0.053 0.776 -0.012 0.724 0.060 0.158 0.706 -0.008 0.054 0.879

Fine M otor Coordination

Grooved Pegboard: Dom inant Hand (lower = better) -0.070 0.108 0.515 -0.021 -0.064 0.134 0.631 -0.017 0.722 -0.099 0.407 0.809 -0.066 0.137 0.628

Grooved Pegboard: Non-dom Hand (lower = better) -0.037 0.127 0.771 -0.010 -0.308 0.161 0.056 -0.070 0.155 -0.375 0.478 0.433 -0.334 0.165 0.043+

Finger Tapping: Dom inant Hand 0.004 0.034 0.899 0.005 -0.005 0.043 0.903 -0.006 . 0.004 0.129 0.978 -0.005 0.044 0.904

Finger Tapping: Non-dom inant Hand 0.022 0.030 0.468 0.029 -0.024 0.039 0.532 -0.028 . -0.024 0.115 0.833 -0.028 0.040 0.484

Visual Spatial Ability

Stanford Binet: Copying -0.039 0.018 0.026* -0.110 0.016 0.022 0.480 0.038 . 0.050 0.066 0.452 0.023 0.023 0.324

Attention/Executive Functioning

GDS Vigilance Task: Correct Responses -0.018 0.028 0.515 -0.030 0.046 0.036 0.195 0.064 . -0.048 0.106 0.652 0.044 0.037 0.230

GDS Vigilance Task: Errors (lower = better) 0.023 0.057 0.685 0.014 -0.123 0.072 0.090 -0.066 . -0.104 0.214 0.627 -0.132 0.074 0.074

W ISC III: Digit Span, Forward Recall -0.015 0.011 0.195 -0.065 -0.008 0.014 0.578 -0.030 0.368 -0.009 0.043 0.835 -0.008 0.015 0.606

W ISC III: Digit Span, Backward Recall -0.004 0.009 0.684 -0.020 0.026 0.012 0.025+ 0.115 . -0.032 0.036 0.376 0.024 0.012 0.044+

W ISC III: Digit Span, Com bined -0.019 0.017 0.254 -0.054 0.023 0.021 0.265 0.057 . -0.053 0.064 0.407 0.021 0.022 0.329

BRIEF Parent Rating: Metacognition (lower = better) -0.159 0.102 0.120 -0.073 -0.084 0.126 0.506 -0.033 0.241 -0.633 0.385 0.101 -0.121 0.129 0.352

BRIEF Teacher Rating: Metacognition (lower = better) -0.043 0.133 0.745 -0.016 -0.011 0.181 0.952 -0.003 0.947 -0.663 0.524 0.206 -0.073 0.188 0.699

Behavior Regulation (low er = better)

CRS-R: Parent Rating: Hyperactive/Im pulsive -0.020 0.029 0.475 -0.033 -0.030 0.036 0.402 -0.042 0.547 -0.092 0.107 0.391 -0.036 0.037 0.336

CRS-R: Teacher Rating: Hyperactive/Im pulsive 0.008 0.029 0.779 0.012 -0.051 0.039 0.193 -0.063 . -0.028 0.114 0.805 -0.055 0.041 0.180

CRS-R: Parent Rating: Inattentive -0.048 0.032 0.139 -0.067 -0.020 0.040 0.627 -0.023 0.300 -0.132 0.121 0.276 -0.026 0.041 0.525

CRS-R: Teacher Rating: Inattentive -0.001 0.041 0.989 -0.001 -0.048 0.056 0.391 -0.046 0.692 -0.169 0.162 0.296 -0.064 0.058 0.266

BRIEF Parent Rating: Behavior Regulation -0.058 0.062 0.349 -0.044 -0.044 0.077 0.566 -0.029 0.549 -0.386 0.231 0.095 -0.070 0.079 0.379

BRIEF Teacher Rating: Behavior Regulation 0.037 0.070 0.596 0.026 -0.019 0.096 0.839 -0.012 . -0.087 0.274 0.750 -0.031 0.099 0.752

Tics (low er = better)

Motor tics (current): Assessor Rating 0.041 0.022 0.065 1.972 0.019 0.038 0.619 1.306 0.882 0.244 0.112 0.029* 0.036 0.039 0.350

Phonics tics (current): Assessor Rating -0.018 0.044 0.688 0.747 0.039 0.039 0.316 1.757 . 0.065 0.192 0.734 0.042 0.040 0.291

Motor tics (current): Parent Rating -0.064 0.059 0.277 0.344 0.010 0.041 0.800 1.159 . 0.211 0.191 0.270 0.022 0.042 0.595

Phonics tics (current): Parent Rating -0.102 0.063 0.107 0.184 -0.035 0.035 0.321 0.609 0.614 0.198 0.170 0.244 -0.022 0.036 0.544

General Intellectual Functioning

W ASI Verbal IQ 0.021 0.076 0.788 0.012 -0.087 0.096 0.363 -0.043 . -0.089 0.287 0.756 -0.095 0.098 0.332

W ASI Perform ance IQ -0.034 0.086 0.696 -0.018 0.129 0.102 0.206 0.060 . 0.028 0.342 0.935 0.134 0.105 0.203

W ASI Full Scale IQ -0.022 0.079 0.785 -0.012 0.079 0.097 0.415 0.039 . -0.081 0.313 0.795 0.075 0.100 0.454

< .05 >.05, <.10 < .05 >.05, <.10

Key: Mercury effect = Better Outcom e p-value+ p-value Mercury effect =W orse Outcom e p-value* p-value

P-values shown are rounded to 3 decim al places. Therefore, a value shown as 0.050 m ay satisify p<0.05 criterion if the original value was rounded up, or m ay not satisify the criterion if the value was rounded down.

Test

M odel w / Joint Test

PreNatThimer Exp07mos Joint

Test

PreNatThim er Exp07m os

Interaction M odel: Prenatal by

Postnatal
Abt Associates Inc. Chapter 9 141

.

Exhibit 9.2.4.3. Summary of Models Testing Effects of Cumulative Exposure Prenatal Through Seven Months – Males (n=509)

E st S .E . P

-0.001 0.005 0.910

-0.007 0.007 0.294

0.002 0.002 0.414

0.003 0.005 0.588

-0.002 0.011 0.854

0.001 0.002 0.530

0.007 0.224 0.974

0.000 0.006 0.969

-0.008 0.007 0.242

-0.003 0.008 0.761

0.001 0.002 0.736

0.002 0.002 0.460

0.001 0.002 0.734

0.001 0.002 0.705

-0.011 0.010 0.300

-0.014 0.010 0.172

0.001 0.006 0.834

-0.009 0.015 0.552

-0.006 0.019 0.737

0.004 0.005 0.475

0.000 0.005 0.934

-0.003 0.003 0.273

0.003 0.005 0.458

-0.008 0.013 0.530

0.002 0.002 0.230

0.002 0.001 0.116

0.003 0.003 0.200

-0.008 0.017 0.628

0.032 0.023 0.161

0.006 0.005 0.202

0.020 0.006 0.002*

-0.009 0.006 0.129

0.012 0.008 0.128

0.005 0.010 0.628

0.021 0.013 0.105

-0.004 0.003 0.129

-0.006 0.005 0.171

0.000 0.003 0.913

-0.002 0.003 0.553

-0.009 0.011 0.417

-0.019 0.013 0.146

-0.016 0.012 0.177

P reN atT him er X E xp 07m os

E st S .E . P S tC f E st S .E . P S tC f E st S .E . P E st S .E . P

S p eec h an d Lan g uag e

B o ston N a m ing Te st 0.0 40 0.028 0.152 0.041 0.0 52 0 .04 2 0 .21 6 0.047 0.149 0.053 0.119 0.659 0.053 0.043 0.217

N E P S Y: S p eeded N a m ing 0.0 56 0.036 0.123 0.057 0.0 02 0 .05 6 0 .97 1 0.002 0.300 0.217 0.158 0.169 0.011 0.057 0.840

N E P S Y: C om prehen sion of Instructions -0.0 11 0.013 0.412 -0.031 -0.0 27 0 .02 0 0 .16 9 -0.069 0.253 -0.056 0.057 0.326 -0.030 0.020 0.137

C E LF : Fo rm u late d S e nte nces 0.0 17 0.029 0.554 0.021 -0.0 45 0 .04 5 0 .31 4 -0.048 . -0.049 0.125 0.698 -0.050 0.046 0.279

C E LF : R ecalling S entences 0.0 65 0.059 0.272 0.038 -0.0 39 0 .08 9 0 .66 6 -0.019 . 0.110 0.254 0.664 -0.036 0.091 0.692

G F TA : A rticulation (low er = b etter) 0.0 02 0.009 0.802 0.010 0.0 18 0 .01 4 0 .18 2 0.070 0.390 -0.021 0.038 0.581 0.017 0.014 0.228

S tutte ring: A ssessor R ating (low er = bette r) -0.4 70 1.061 0.658 0.000 0.0 15 0 .04 1 0 .71 0 1.246 . -0.636 4.816 0.895 0.015 0.041 0.710

S tutte ring: P a rent R a tin g (low er = better) -0.0 04 0.042 0.917 0.930 -0.0 19 0 .05 4 0 .72 9 0.767 0.943 -0.010 0.150 0.947 -0.019 0.055 0.729

S tutte ring: Te ach er R ating (low er = b etter) -0.0 33 0.037 0.381 0.579 0.0 19 0 .03 2 0 .55 4 1.311 . 0.116 0.122 0.344 0.029 0.033 0.389

V e rb al M em o ry

C V LT-C : Free R e ca ll, N o D elay 0.0 26 0.044 0.554 0.022 -0.0 19 0 .06 8 0 .78 2 -0.014 . 0.084 0.194 0.666 -0.015 0.069 0.822

C V LT-C : Free R e ca ll, S ho rt D elay -0.0 05 0.013 0.688 -0.015 -0.0 16 0 .01 9 0 .40 6 -0.041 0.637 -0.023 0.054 0.674 -0.017 0.019 0.384

C V LT-C : C ued R e ca ll, S ho rt D elay 0.0 02 0.011 0.881 0.006 0.0 00 0 .01 7 0 .97 9 -0.001 . -0.033 0.048 0.494 -0.002 0.017 0.888

C V LT-C : Free R e ca ll, Lo ng D ela y 0.0 03 0.012 0.769 0.011 -0.0 19 0 .01 8 0 .30 5 -0.052 . -0.014 0.052 0.792 -0.020 0.018 0.288

C V LT-C : C ued R e ca ll, Lo ng D ela y 0.0 13 0.012 0.291 0.044 0.0 00 0 .01 9 0 .99 5 0.000 0.570 -0.007 0.054 0.899 -0.001 0.019 0.955

C M S S tories 1: Im m ediate R ecall 0.0 44 0.056 0.433 0.023 -0.1 18 0 .08 7 0 .17 7 -0.054 . 0.285 0.239 0.234 -0.103 0.089 0.247

C M S S tories 2: D elayed R e ca ll 0.0 18 0.056 0.753 0.010 -0.0 54 0 .08 7 0 .53 3 -0.025 . 0.343 0.244 0.161 -0.037 0.087 0.674

A ch ieve m en t

W JIII: Le tter- W o rd Iden tification 0.0 39 0.035 0.261 0.035 0.1 26 0 .05 4 0.020+ 0.096 0 .03 0+ 0.009 0.150 0.953 0.124 0.055 0.0 24+

F ine M oto r C o ordin atio n

G roo ved P egboa rd: D o m inant H and (low er = bette r) -0.1 83 0.080 0.0 22+ -0.055 -0.0 97 0 .12 1 0 .42 3 -0.025 0 .04 5+ 0.016 0.344 0.962 -0.086 0.122 0.481

G roo ved P egboa rd: N o n-dom H and (lo we r = better) -0.1 31 0.102 0.199 -0.034 -0.1 86 0 .15 5 0 .23 0 -0.042 0.191 0.015 0.446 0.973 -0.179 0.157 0.255

F ing er Ta pping: D om ina nt H a nd -0.0 20 0.029 0.493 -0.025 0.0 62 0 .04 6 0 .18 0 0.065 . -0.108 0.127 0.393 0.056 0.047 0.229

F ing er Ta pping: N on-d om inant H and -0.0 28 0.027 0.296 -0.038 0.0 36 0 .04 2 0 .39 1 0.041 . -0.038 0.117 0.746 0.036 0.043 0.406

V isu al S p atial A bility

S tanford B ine t: C opyin g 0.0 34 0.014 0.0 15+ 0.095 -0.0 13 0 .02 1 0 .55 8 -0.030 . 0.099 0.061 0.103 -0.008 0.022 0.702

A tten tion /E x ecutive F u nctio ning

G D S V ig ilance Task: C orre ct R espon se s -0.0 24 0.025 0.337 -0.039 0.0 22 0 .03 9 0 .57 3 0.030 . -0.104 0.110 0.346 0.017 0.039 0.665

G D S V ig ilance Task: E rrors (low er = b etter) 0.0 34 0.073 0.643 0.021 -0.0 19 0 .11 0 0 .86 5 -0.010 . 0.228 0.317 0.472 -0.006 0.112 0.954

W IS C III: D igit S pan , Fo rwa rd R ecall 0.0 11 0.009 0.198 0.050 0.0 01 0 .01 3 0 .94 9 0.003 0.433 -0.032 0.037 0.385 -0.002 0.013 0.881

W IS C III: D igit S pan , B ackwa rd R ecall -0.0 20 0.008 0.0 09* -0.102 0.0 08 0 .01 2 0 .47 8 0.036 . -0.071 0.033 0.0 33* 0.006 0.012 0.643

W IS C III: D igit S pan, C om bine d -0.0 10 0.014 0.452 -0.029 0.0 10 0 .02 1 0 .61 7 0.025 . -0.083 0.058 0.155 0.006 0.021 0.763

B R IE F P arent R ating: M etacognition (lo we r = better) 0.1 31 0.091 0.153 0.060 -0.0 20 0 .14 0 0 .88 5 -0.008 . 0.318 0.397 0.423 -0.008 0.142 0.954

B R IE F Teacher R ating: M etacogn ition (low er = b etter) 0.1 17 0.125 0.352 0.043 -0.2 72 0 .20 0 0 .17 4 -0.086 . -0.632 0.547 0.249 -0.311 0.201 0.124

B eh avio r R eg ulation (lo w er = be tter)

C R S -R : P arent R ating: H ypera ctive /Im pulsive 0.0 26 0.025 0.308 0.042 0.0 52 0 .03 8 0 .17 4 0.073 0.213 -0.109 0.109 0.316 0.045 0.039 0.247

C R S -R : Teacher R ating : H yp eractive/Im pulsive 0.0 36 0.034 0.291 0.052 -0.0 58 0 .05 6 0 .30 3 -0.072 . -0.417 0.147 0.0 05+ -0.082 0.056 0.144

C R S -R : P arent R ating: Inattentive 0.0 43 0.031 0.158 0.061 -0.0 32 0 .04 7 0 .49 7 -0.038 . 0.240 0.133 0.071 -0.019 0.047 0.685

C R S -R : Teacher R ating : In attentive 0.0 06 0.042 0.888 0.007 -0.0 24 0 .06 9 0 .72 9 -0.023 . -0.266 0.183 0.147 -0.040 0.070 0.571

B R IE F P arent R ating: B eh avior R e gulation 0.0 24 0.054 0.659 0.018 0.1 66 0 .08 1 0.040* 0.109 0.103 -0.086 0.232 0.712 0.160 0.082 0.051

B R IE F Teacher R ating: B ehavior R egulation 0.0 79 0.070 0.261 0.055 -0.0 90 0 .11 2 0 .42 2 -0.053 . -0.397 0.301 0.188 -0.111 0.112 0.322

T ics (lo w er = be tter)

M otor tics (cu rrent): A ssessor R ating 0.0 17 0.013 0.218 1.317 0.0 53 0 .03 0 0 .07 6 2.143 0.187 0.118 0.066 0.074 0.059 0.030 0.0 49*

P h onics tics (curren t): A ssessor R ating -0.0 09 0.020 0.665 0.865 0.0 51 0 .02 9 0 .08 5 2.060 . 0.123 0.091 0.177 0.060 0.030 0.0 47*

M otor tics (cu rrent): P arent R ating 0.0 07 0.013 0.605 1.116 -0.0 11 0 .02 5 0 .65 7 0.851 . 0.013 0.062 0.831 -0.011 0.026 0.676

P h onics tics (curren t): P a rent R ating -0.0 02 0.017 0.929 0.975 0.0 30 0 .02 5 0 .21 7 1.541 . 0.043 0.075 0.567 0.033 0.025 0.185

G en eral Intellectua l Fu n ctio n in g

W A S I V erbal IQ 0.0 68 0.062 0.270 0.039 -0.0 19 0 .09 4 0 .84 1 -0.009 . 0.279 0.267 0.297 -0.006 0.095 0.953

W A S I P erfo rm an ce IQ 0.0 24 0.071 0.733 0.013 0.1 11 0 .11 0 0 .31 1 0.052 0.548 0.460 0.308 0.136 0.139 0.111 0.213

W A S I Full S cale IQ 0.0 52 0.064 0.417 0.030 0.0 20 0 .09 9 0 .84 2 0.010 0.695 0.422 0.281 0.134 0.042 0.100 0.673

< .0 5 >.05, < .10 < .0 5 > .0 5, <.10

K ey: M ercury effect = B etter O utcom e p-value+ p -value M ercury effect = W orse O utcom e p-va lue* p-value

P -values show n a re ro unded to 3 d ecim al places. There fore , a value show n as 0 .05 0 m ay satisify p <0.05 criterion if the origin al value w as ro unded up , or m ay no t satisify the criterion if the value w as ro unded do wn .

P re N atT him er E xp0 7m o s

Interaction M o de l: P rena tal by

P o stn atal

T est

M od el w / J oint Te st

P re N atT him er E x p07 m os Jo in t

Te st
Abt Associates Inc. Chapter 9 142

9.2.4.3.2. Test of Prental-by-Postnatal Exposure

Interaction Effect

Full Data Set

Among the hypothesis tests for an interaction effect conducted for the 42 outcome

measures, four were significant at the p<0.05 level, and three additional tests fell below

0.10. If the direction of the main effects of PreNatThimer and Exp07mos had been

consistent with the direction of the interaction effect (PreNatThimer*Exp07mos), the

interpretation of a significant interaction would be straightforward. For example, if a

higher score were considered a better outcome, and the coefficients for all three effects

were negative, one could conclude that higher exposure was associated with a worse

outcome, and that the effect of having both high prenatal and high postnatal exposure

results in a negative effect above and beyond the individual additive effects of exposure

during the two periods. But that kind of consistency did not occur in any of the models

where the p-value for the interaction was less than 0.10. In each model there was a mix of

positive and negative coefficients for the three terms.

In order to understand the complex results produced from these models, we produced

plots of the values on the outcome variables that would be predicted from the models for

various exposure levels. The plots show the predicted values of the outcome variable

(Y), for increasing values of the exposure variables (PreNatThimer, and Exp07mos).

Based on the distributions of exposures for the entire sample of girls and boys combined,

we made cut-points to classify prenatal and postnatal exposures as Very Low, Low, High,

and Very High. Our goal was to show the predicted value of Y for all sixteen possible

combinations of the four prenatal groups (very low to very high) crossed with the four

postnatal groups (very low to very high). However, for cells with no observations (e.g.,

there were zero children in the “high PreNatThimer” and “very low Exp07mos” group),

no predicted value is shown. We picked the most extreme values of PreNatThimer and

Exp07mos observed within each crossed group and plotted a set of predicted values for

different postnatal exposures within each prenatal exposure category. The exposure

categories used for the plots of predicted values are shown below.

Exposure Categories

Very Low Low High Very High

PreNatThimer

(Prenatal)

0 11.25 – 12.75 25 to 25.5 50 to 100

Exp07mos

(postnatal)

0 to 11.59 11.6 to 19.99 20 to 30 30.01 to 38.3

PreNatThimer is a measure of cumulative exposure to ethylmercury from vaccines and

immune globulins during the prenatal period and is expressed in micrograms.

Exp07mos is a cumulative measure of exposure to ethylmercury from vaccines and immune

globulins for the period from birth through seven months of age and is expressed as

micrograms of mercury divided by child’s body weight at the time of receipt, summed over

all receipts in the age range.

The plot shown in Exhibit 9.2.4.4b is a hypothetical example wherein the coefficients for

all three terms are negative (i.e., the terms for PreNatThimer, Exp07mos, and
Abt Associates Inc. Chapter 9 143

PreNatThimer*Exp07mos are all in a consistent direction). This hypothetical example

can be contrasted to the results from the observed data, shown later, where the

coefficients for the three terms are not in a consistent direction.

The plot of the hypothetical data shows that as PreNatThimer increases in value, the

predicted value of the outcome variable Y decreases. And as Exp07mos increases in

value, the predicted value of the outcome variable Y decreases. It also shows that the

slope of the Exp07mos effect is steeper for higher values of PreNatThimer. The plot has

four panels indicated by the vertical dotted lines. The leftmost panel is for Very Low

prenatal exposures. The Very Low prenatal exposure category corresponds to zero

prenatal exposure, so the plots in this group use predictions with PreNatThimer = 0, as

indicated in the first row of numbers at the bottom of the plot. The Exp07mos values used

are shown in the second row of numbers at the bottom of the plot. We used the low point

of the range for the two lower postnatal exposure categories (0 for Very Low and 11.6 for

Low) and the high point of the range for the higher exposure categories (30 for High and

42 for Very High). The plotting symbols (open circles) in this panel show the predicted

values of Y when PreNatThimer is equal to zero, and Exp07mos is at values 0, 11.6, 30,

and 42. In this example there is a slight downward slope associated with increasing

values of Exp07mos when the value of PreNatThimer is held constant at zero. The third

row of numbers shown along the bottom of the plot is labeled “n in group”. This

hypothetical example used the observed numbers in each exposure group. For example,

there were 106 children that had zero prenatal exposure and were in the very low group

for Exp07mos.

Exhibits 9.2.4.5 through 9.2.4.8 show the estimates and plots for four outcome measures

that had significant interaction effect at the 0.05 level in the models fit to the full data set.

Exhibits 9.2.4.9 and 9.2.4.10 correspond to the one significant interaction effect for

females and the one significant interaction effect for males.

Exhibit 9.2.4.5a is a summary of results from the interaction model for the NEPSY

Speeded Naming outcome measure. The summary shows the estimates (regression

coefficients) and their standard errors and p-values for the thimerosal exposure variables.

For the sake of brevity, the estimates for the intercept term and all of the covariates are

omitted from the summary. For this particular outcome measure, a higher score is better.

The coefficients for the PreNatThimer and Exp07mos terms are positive, and the

coefficient for the interaction term (PreNatThimer * Exp07mos) is negative. The p-value

for the interaction is below 0.05, indicating a statistically significant interaction effect.

The coefficient for the PreNatThimer term is large, relative to its standard error, and

positive, suggesting that, holding postnatal exposure constant at zero, one would expect

that higher prenatal exposures would be related to more desirable scores on the outcome

measure.

The estimated main effects from the model without the (PreNatThimer*Exp07mos)

interaction are shown in Exhibit 9.2.4.5b . Comparing Exhibits 9.2.4.5a and 9.2.4.5b, it

is evident that the addition of the interaction term substantially increased the size of the
Abt Associates Inc. Chapter 9 144

estimated positive coefficients for both main effects, with an offsetting negative

interaction.

Plots of predicted values from the interaction model are shown in Exhibit 9.2.4.5c. The

left-most panel of the plot shows that when PreNatThimer is held constant at zero,

increases in the value of Exp07mos have a very weak positive association with the

outcome measure. In this portion of the plot, as the values of Exp07mos increase, the

predicted values of Y increase a small amount. Note that, by far, most children had zero

prenatal thimerosal exposure, so the left-most panel of the plot represents the data for

roughly 90 percent of the children in the sample. The next panel to the right shows the

predicted values of Y when PreNatThimer is equal to 11.25, for several increasing values

of Exp07mos. The plot shows that when Exp07mos is at very low or low values, the

model predicts that 11.25 micrograms of prenatal exposure is associated with better

outcome scores than are predicted when prenatal exposure is zero, and postnatal exposure

is at any value, low or high. When postnatal cumulative exposure is at high or very high

levels, the predicted benefit of 11.25 micrograms of prenatal exposure diminishes to near

zero. The predicted values of Y when PreNatThimer is 11.25, and Exp07mos is high or

very high are very close to the predicted values of Y when PreNatThimer is zero. The

two right-most panels of the exhibit tell a very similar story. The predicted benefits of

higher prenatal exposure diminish to near zero as postnatal exposure increases.

For Stanford Binet Copying and CRS-R Teacher Rated Hyperactive/Impulsive outcome

measures (Exhibits 9.2.4.6 and 9.2.4.7), the models predict beneficial effects of postnatal

exposure when prenatal exposure is zero, and harmful effects when both prenatal and

postnatal exposures are high, but at the lower levels postnatal exposure, the predicted

benefits of high or very high prenatal exposure are large.

When there is zero prental exposure, the model for Assessor Rated Motor Tics (Exhibit

9.2.4.8) predicts that the risk of tics with increases with increasing postnatal exposure,

but when there is prenatal exposure, increasing postnatal exposure is associated with

decreased risk of tics.

For females, the predicted beneficial effects of high prenatal exposure on the CVLT-C

Free Recall Long Delay outcome measure are similar in magnitude to the predicted

harmful effects of having both high prenatal and high postnatal exposure (Exhibit

9.2.4.9). The results for males on CRS-R Teacher Rated Hyperactive/Impulsive outcome

(Exhibit 9.2.4.10) are very similar to the previously displayed results on the same

outcome measure for the full data set (Exhibit 9.2.4.7).

None of the significant interaction effects suggest clear evidence of either harm or benefit

associated with the interaction between prenatal and postnatal exposure.
Abt Associates Inc. Chapter 9 145

Exhibit 9.2.4.4a. Hypothetical Example Where Coefficients for PreNatThimer, Exp07mos,

and the Interaction of PreNatThimer by Exp07mos are all Negative

Summary of Regression Coefficients from Interaction Model

Variable Name Estimate Standard Error P-Value

PreNatThimer -0.014

Exp07mos -.005

PreNatThimer*Exp07mos -0.002

Exhibit 9.2.4.4b. Hypothetical Example Where Coefficients for PreNatThimer, Exp07mos,

and the Interaction of PreNatThimer by Exp07mos are all Negative

Plot of Predicted Values of Y

Exposure Levels

Predicted Value of Y

4 6 8 10 12 14 16 18

Predicted Values from Interaction Model: PreNatThimer X Exp07mos

Outcome = Hypothetical

0

0

106

0

11.6

392

0

30

365

0

38

73

11.25

0

6

11.25

11.6

27

11.25

30

35

11.25

38

3

25

0

0

25

11.6

12

25

30

11

25

38

4

100

19

3

100

30

9

50

34

1

PreNatThimer=Zero

Increasing Exp07mos -->

PreNatThimer=Low

Increasing Exp07mos -->

PreNatThimer=High

Increasing Exp07mos -->

PreNatThimer=Highest

Observed Exp07mos

PreNatThimer:

Exp07mos:

n in group

Notes: Plot symbol indicates predicted value of Y when the values if PreNatThimer and Exp07mos are equal to the

values shown below the x-axis. For example, the left-most plotting symbol shows the predicted value of Y when

PreNatThimer = 0 and Exp07mos = 0. The next symbol to the right shows the predicted value when PreNatThimer = 0

and Exp07mos = 11.6, and so on.
Abt Associates Inc. Chapter 9 146

Exhibit 9.2.4.5a. NEPSY Speeded Naming

Summary of Regression Coefficients from Interaction Model

Variable Name Estimate Standard Error P-Value

PreNatThimer 0.281 0.109 0.010

Exp07mos 0.026 0.039 0.504

PreNatThimer*Exp07mos -0.010 0.005 0.034

Exhibit 9.2.4.5b. NEPSY Speeded Naming

Summary of Regression Coefficients from Model Without The Interaction

Variable Name Estimate Standard Error P-Value

PreNatThimer 0.057 0.027 0.034

Exp07mos 0.010 0.038 0.784

Exhibit 9.2.4.5c. NEPSY Speeded Naming

Plot of Predicted Values of Y

Exposure Levels

Predicted Value of Y

10 15 20 25 30 35 40

Predicted Values from Interaction Model: PreNatThimer X Exp07mos

Outcome = NEPSY Speeded Naming

0

0

106

0

11.6

392

0

30

365

0

38

73

11.25

0

6

11.25

11.6

27

11.25

30

35

11.25

38

3

25

0

0

25

11.6

12

25

30

11

25

38

4

100

19

3

100

30

9

50

34

1

PreNatThimer=Zero

Increasing Exp07mos -->

PreNatThimer=Low

Increasing Exp07mos -->

PreNatThimer=High

Increasing Exp07mos -->

PreNatThimer=Highest

Observed Exp07mos

PreNatThimer:

Exp07mos:

n in group

Notes: Plot symbol indicates predicted value of Y when the values if PreNatThimer and Exp07mos are equal to the

values shown below the x-axis. For example, the left-most plotting symbol shows the predicted value of Y when

PreNatThimer = 0 and Exp07mos = 0. The next symbol to the right shows the predicted value when PreNatThimer = 0

and Exp07mos = 11.6, and so on.
Abt Associates Inc. Chapter 9 147

Exhibit 9.2.4.6a. Stanford Binet: Copying

Summary of Regression Coefficients from Interaction Model

Variable Name Estimate Standard Error P-Value

PreNatThimer 0.094 0.043 0.030

Exp07mos 0.013 0.015 0.406

PreNatThimer*Exp07mos -0.004 0.002 0.035

Exhibit 9.2.4.6b. Stanford Binet: Copying

Summary of Regression Coefficients from Model Without Interaction

Variable Name Estimate Standard Error P-Value

PreNatThimer 0.005 0.011 0.628

Exp07mos 0.007 0.015 0.667

Exhibit 9.2.4.6c. Stanford Binet: Copying

Plot of Predicted Values of Y

Exposure Levels

Predicted Value of Y

12 14 16 18 20 22 24

Predicted Values from Interaction Model: PreNatThimer X Exp07mos

Outcome = Stanford Binet Copying

0

0

106

0

11.6

392

0

30

365

0

38

73

11.25

0

6

11.25

11.6

27

11.25

30

35

11.25

38

3

25

0

0

25

11.6

12

25

30

11

25

38

4

100

19

3

100

30

9

50

34

1

PreNatThimer=Zero

Increasing Exp07mos -->

PreNatThimer=Low

Increasing Exp07mos -->

PreNatThimer=High

Increasing Exp07mos -->

PreNatThimer=Highest

Observed Exp07mos

PreNatThimer:

Exp07mos:

n in group

Notes: Plot symbol indicates predicted value of Y when the values if PreNatThimer and Exp07mos are equal to the

values shown below the x-axis. For example, the left-most plotting symbol shows the predicted value of Y when

PreNatThimer = 0 and Exp07mos = 0. The next symbol to the right shows the predicted value when PreNatThimer = 0

and Exp07mos = 11.6, and so on.
Abt Associates Inc. Chapter 9 148

Exhibit 9.2.4.7a. CRS-R: Teacher--Hyperactive/Impulsive Cluster

Summary of Regression Coefficients from Interaction Model

Variable Name Estimate Standard Error P-Value

PreNatThimer -0.219 0.090 0.015

Exp07mos -0.066 0.034 0.054

PreNatThimer*Exp07mos 0.010 0.004 0.006

Exhibit 9.2.4.7b. CRS-R: Teacher--Hyperactive/Impulsive Cluster

Summary of Regression Coefficients from Model Without The Interaction

Variable Name Estimate Standard Error P-Value

PreNatThimer 0.023 0.022 0.301

Exp07mos -0.048 0.034 0.157

Exhibit 9.2.4.7c. CRS-R: Teacher--Hyperactive/Impulsive Cluster

Plot of Predicted Values of Y

Exposure Levels

Predicted Value of Y

-5 0 5 10 15

Predicted Values from Interaction Model: PreNatThimer X Exp07mos

Outcome = CRS-R: Teacher Rating Hyperactive/Impulsive

0

0

106

0

11.6

392

0

30

365

0

38

73

11.25

0

6

11.25

11.6

27

11.25

30

35

11.25

38

3

25

0

0

25

11.6

12

25

30

11

25

38

4

100

19

3

100

30

9

50

34

1

PreNatThimer=Zero

Increasing Exp07mos -->

PreNatThimer=Low

Increasing Exp07mos -->

PreNatThimer=High

Increasing Exp07mos -->

PreNatThimer=Highest

Observed Exp07mos

PreNatThimer:

Exp07mos:

n in group

Notes: Plot symbol indicates predicted value of Y when the values if PreNatThimer and Exp07mos are equal to the

values shown below the x-axis. For example, the left-most plotting symbol shows the predicted value of Y when

PreNatThimer = 0 and Exp07mos = 0. The next symbol to the right shows the predicted value when PreNatThimer = 0

and Exp07mos = 11.6, and so on.
Abt Associates Inc. Chapter 9 149

Exhibit 9.2.4.9a. Assessor Rated Motor Tics

Summary of Regression Coefficients from Interaction Model

Variable Name Estimate Standard Error P-Value

PreNatThimer 0.121 0.051 0.017

Exp07mos 0.040 0.022 0.070

PreNatThimer*Exp07mos -0.004 0.002 0.046

Exhibit 9.2.4.9b. Assessor Rated Motor Tics

Summary of Regression Coefficients from Model Without The Interaction

Variable Name Estimate Standard Error P-Value

PreNatThimer 0.017 0.011 0.104

Exp07mos 0.032 0.022 0.142

Exhibit 9.2.4.9c. Assessor Rated Motor Tics

Plot of Predicted Values of Y

Predicted Values from Interaction Model: PreNatThimer X Exp07mos

Outcome = (Motor Tics Current): Assessor Rating

Exposure Levels

Model Predicted Proportion with Tics

-0.5 0.0 0.5

0

0

106

0

11.6

392

0

30

365

0

38

73

11.25

0

6

11.25

11.6

27

11.25

30

35

11.25

38

3

25

0

0

25

11.6

12

25

30

11

25

38

4

100

19

3

100

30

9

50

34

1

PreNatThimer=Zero

Increasing Exp07mos -->

PreNatThimer=Low

Increasing Exp07mos -->

PreNatThimer=High

Increasing Exp07mos -->

PreNatThimer=Highest

Observed Exp07mos

PreNatThimer:

Exp07mos:

n in group

Notes: Plot symbol indicates predicted value of Y when the values if PreNatThimer and Exp07mos are equal to the

values shown below the x-axis. For example, the left-most plotting symbol shows the predicted value of Y when

PreNatThimer = 0 and Exp07mos = 0. The next symbol to the right shows the predicted value when PreNatThimer = 0

and Exp07mos = 11.6, and so on.
Abt Associates Inc. Chapter 9 150

Exhibit 9.2.4.9a. Females – CVLT-C: Free Recall Long Delay

Summary of Regression Coefficients from Interaction Model

Variable Name Estimate Standard Error P-Value

PreNatThimer 0.099 0.050 0.047

Exp07mos -0.013 0.017 0.435

PreNatThimer*Exp07mos -0.005 0.002 0.023

Exhibit 9.2.4.9b. Females – CVLT-C: Free Recall Long Delay

Summary of Regression Coefficients from Model Without The Interaction

Variable Name Estimate Standard Error P-Value

PreNatThimer -0.010 0.013 0.446

Exp07mos -0.022 0.017 0.190

Exhibit 9.2.4.9c. Females – CVLT-C: Free Recall Long Delay

Plot of Predicted Values of Y

Exposure Levels

Predicted Value of Y

6 8 10 12 14

Predicted Values from Interaction Model: PreNatThimer X Exp07mos

Outcome = CVLT-C: Free Recall, Long Delay

0

0

43

0

11.6

196

0

30

191

0

38

50

11.25

0

1

11.25

11.6

16

11.25

30

20

11.25

38

3

25.5

0

0

25.5

11.6

3

25.5

30

5

25.5

38

4

50

19

2

50

30

3

50

34

1

PreNatThimer=Zero

Increasing Exp07mos -->

PreNatThimer=Low

Increasing Exp07mos -->

PreNatThimer=High

Increasing Exp07mos -->

PreNatThimer=Highest

Observed Exp07mos

PreNatThimer:

Exp07mos:

n in group

Notes: Plot symbol indicates predicted value of Y when the values if PreNatThimer and Exp07mos are equal to the

values shown below the x-axis. For example, the left-most plotting symbol shows the predicted value of Y when

PreNatThimer = 0 and Exp07mos = 0. The next symbol to the right shows the predicted value when PreNatThimer = 0

and Exp07mos = 11.6, and so on.
Abt Associates Inc. Chapter 9 151

Exhibit 9.2.4.10a. Males – CRS-R: Teacher--Hyperactive/Impulsive Cluster

Summary of Regression Coefficients from Interaction Model

Variable Name Estimate Standard Error P-Value

PreNatThimer -0.417 0.147 0.005

Exp07mos -0.082 0.056 0.144

PreNatThimer*Exp07mos 0.020 0.006 0.002

Exhibit 9.2.4.10b. Males – CRS-R: Teacher--Hyperactive/Impulsive Cluster

Summary of Regression Coefficients from Model Without The Interaction

Variable Name Estimate Standard Error P-Value

PreNatThimer 0.036 0.034 0.291

Exp07mos -0.058 0.056 0.303

Exhibit 9.2.4.10c. Males – CRS-R: Teacher--Hyperactive/Impulsive Cluster

Plot of Predicted Values of Y

Exposure Levels

Predicted Value of Y

-20 -10 0 10 20

Predicted Values from Interaction Model: PreNatThimer X Exp07mos

Outcome = CRS-R: Teacher Rating Hyperactive/Impulsive

0

0

63

0

11.6

196

0

30

174

0

38

23

11.25

0

5

11.25

11.6

11

11.25

30

15

11.25

38

0

25.5

0

0

25.5

11.6

9

25.5

30

6

25.5

38

0

100

19

1

100

28

1

50

29

5

PreNatThimer=Zero

Increasing Exp07mos -->

PreNatThimer=Low

Increasing Exp07mos -->

PreNatThimer=High

Increasing Exp07mos -->

PreNatThimer=Highest

Observed Exp07mos

PreNatThimer:

Exp07mos:

n in group

Notes: Plot symbol indicates predicted value of Y when the values if PreNatThimer and Exp07mos are equal to the

values shown below the x-axis. For example, the left-most plotting symbol shows the predicted value of Y when

PreNatThimer = 0 and Exp07mos = 0. The next symbol to the right shows the predicted value when PreNatThimer = 0

and Exp07mos = 11.6, and so on.
Abt Associates Inc. Chapter 9 152

9.2.5. Models for Multiple Sources of Prenatal Exposure

Interacted with Postnatal Exposure from Thimerosal

9.2.5.1. Introduction

The models summarized in this section were motivated by the same hypothesis as

described in the previous section – that is, children who had prenatal exposure to mercury

could be more susceptible to additional doses of postnatal exposure than children who

were not exposed in utero. In the current section, however, a broader measure of prenatal

exposure is introduced and modeled. The broader measures of prenatal exposure includes

mercury exposures from thimerosal in vaccines and immune globulins, maternal fish

consumption, maternal use of mercury containing health care produces (contact lens,

nasal, ear, eye drops), maternal exposure from home products, and from amalgam

fillings. This new measure was modeled as an interaction effect with cumulative

exposure from birth through seven months.

The broader measure of prenatal exposure was created by dichotomizing the component

variables17 into categories “1 = any exposure”, and “0 = no exposure”, and summing to

create a composite score. The following variables were summed to create the composite

(named PrenatAllMerc):

Variable Defintion

= 0 if PreNatThimer = 0 Pre_VacIG { = 1 if PreNatThimer > 0 }

= 1 if PreNatTuna > 0 Pre_Tuna { = 0 if PrenatTuna = 0 }

= 0 PreNatOrgMerc = 0 PreOrg { = 1 if PreNatOrgMerc > 0 }

= 0 if PreNatFillings = 0 PreAmalgam { = 1 if PreNatFillings > 0 }

PreNatFish = PreNatFish variable as currently defined (0/1).

PreNatHomePro = PreNatHomePro as currently defined (0/1).

PreNatAllMerc = Pre_VacIG + Pre_Tuna + PreOrg + PreAmalgam +

PreNatFish + PreNatHomePro

A frequency crosstab of the PreNatAllMerc variable crossed with the components used in

its creation is shown in Exhibit 9.2.5.1.

17 For definitions of component variables, see Section 7.3.
Abt Associates Inc. Chapter 9 153

Exhibit 9.2.5.1. PreNatAllMerc_1 Crossed with Six Component Variables Used to Construct It

PreNat

AllMerc

_1

PreNat

Thimer

PreNat

Tuna

_1

PreNat

Fish

_1

PreNat

OrgMerc

_1

PreNat

Home

Pro_1

PreNat

Fillings

_1

Freq. Percent Cum.

Freq.

Cum.

Percent

0 0 0 0 0 0 0 71 6.78 71 6.78

1 0 0 0 0 0 1 36 3.44 107 10.22

1 0 0 0 0 0 2 170 16.24 277 26.46

1 0 0 0 0 1 0 1 0.1 278 26.55

1 0 0 0 2 0 0 1 0.1 279 26.65

1 0 1 0 0 0 0 87 8.31 366 34.96

1 0 2 0 0 0 0 6 0.57 372 35.53

1 12.75 0 0 0 0 0 3 0.29 375 35.82

1 25 0 0 0 0 0 1 0.1 376 35.91

2 0 0 0 0 1 1 1 0.1 377 36.01

2 0 0 0 0 1 2 3 0.29 380 36.29

2 0 0 0 1 0 1 1 0.1 381 36.39

2 0 0 0 1 0 2 1 0.1 382 36.49

2 0 0 0 2 0 1 2 0.19 384 36.68

2 0 0 0 2 0 2 10 0.96 394 37.63

2 0 1 0 0 0 1 53 5.06 447 42.69

2 0 1 0 0 0 2 354 33.81 801 76.5

2 0 1 0 0 1 0 1 0.1 802 76.6

2 0 1 0 1 0 0 1 0.1 803 76.7

2 0 1 0 2 0 0 4 0.38 807 77.08

2 0 1 0 3 0 0 1 0.1 808 77.17

2 0 1 1 0 0 0 8 0.76 816 77.94

2 0 2 0 0 0 1 3 0.29 819 78.22

2 0 2 0 0 0 2 19 1.81 838 80.04

2 11.25 0 0 0 0 1 1 0.1 839 80.13

2 12.75 0 0 0 0 1 2 0.19 841 80.32

2 12.75 0 0 0 0 2 12 1.15 853 81.47

2 12.75 1 0 0 0 0 3 0.29 856 81.76

2 12.75 2 0 0 0 0 1 0.1 857 81.85

2 25 0 0 0 0 2 2 0.19 859 82.04

2 25 1 0 0 0 0 2 0.19 861 82.23

2 25.5 0 0 0 0 2 1 0.1 862 82.33

2 50 0 0 0 0 2 3 0.29 865 82.62

2 50 1 0 0 0 0 1 0.1 866 82.71

2 100 0 0 0 0 2 1 0.1 867 82.81

3 0 0 0 2 1 2 1 0.1 868 82.9

3 0 1 0 0 1 1 2 0.19 870 83.09

3 0 1 0 0 1 2 19 1.81 889 84.91

3 0 1 0 1 0 2 8 0.76 897 85.67

3 0 1 0 2 0 1 3 0.29 900 85.96

3 0 1 0 2 0 2 15 1.43 915 87.39

3 0 1 1 0 0 1 2 0.19 917 87.58

3 0 1 1 0 0 2 34 3.25 951 90.83

3 0 2 0 0 1 1 1 0.1 952 90.93

3 0 2 0 0 1 2 1 0.1 953 91.02

3 0 2 0 2 0 2 2 0.19 955 91.21

3 0 2 1 0 0 2 4 0.38 959 91.6

3 12.5 1 0 0 0 2 1 0.1 960 91.69

3 12.75 0 0 0 1 2 1 0.1 961 91.79

3 12.75 0 0 2 0 2 1 0.1 962 91.88

3 12.75 1 0 0 0 1 3 0.29 965 92.17
Abt Associates Inc. Chapter 9 154

Exhibit 9.2.5.1. PreNatAllMerc_1 Crossed with Six Component Variables Used to Construct It

PreNat

AllMerc

_1

PreNat

Thimer

PreNat

Tuna

_1

PreNat

Fish

_1

PreNat

OrgMerc

_1

PreNat

Home

Pro_1

PreNat

Fillings

_1

Freq. Percent Cum.

Freq.

Cum.

Percent

3 12.75 1 0 0 0 2 29 2.77 994 94.94

3 12.75 1 1 0 0 0 2 0.19 996 95.13

3 12.75 2 0 0 0 2 1 0.1 997 95.22

3 25 1 0 0 0 1 1 0.1 998 95.32

3 25 1 0 0 0 2 7 0.67 1005 95.99

3 25 1 1 0 0 0 1 0.1 1006 96.08

3 25 2 0 0 0 2 2 0.19 1008 96.28

3 25.5 1 0 0 0 1 1 0.1 1009 96.37

3 25.5 1 0 0 0 2 5 0.48 1014 96.85

3 25.5 2 0 0 0 2 1 0.1 1015 96.94

3 50 0 0 0 1 2 1 0.1 1016 97.04

3 50 0 0 2 0 2 1 0.1 1017 97.13

3 50 1 0 0 0 2 2 0.19 1019 97.33

3 62.75 2 0 0 0 2 1 0.1 1020 97.42

3 100 1 0 0 0 2 1 0.1 1021 97.52

4 0 1 0 1 1 2 1 0.1 1022 97.61

4 0 1 1 0 1 2 4 0.38 1026 97.99

4 0 1 1 1 0 1 1 0.1 1027 98.09

4 0 1 1 2 0 2 2 0.19 1029 98.28

4 0 1 1 4 0 2 1 0.1 1030 98.38

4 12.75 1 0 2 0 2 5 0.48 1035 98.85

4 12.75 1 1 0 0 2 6 0.57 1041 99.43

4 25 1 1 0 0 2 2 0.19 1043 99.62

4 25.5 2 1 0 0 2 1 0.1 1044 99.71

4 50 1 0 0 1 2 1 0.1 1045 99.81

4 50 1 0 2 0 2 1 0.1 1046 99.9

5 0 1 1 2 1 2 1 0.1 1047 100

9.2.5.2. Model Specifications

Interaction Model

This model tests for an interaction effect of PreNatAllMerc and Exp07mos.

   

   

  

    

     

l

j k l l

k

j k k

j

j j

oe cf St

Y preNatAllMerc Exp07mos preNatAllMerc * Exp07mos 0 1 2 3

: 0 : 0 H0  3  vs Ha  3 

Main Effect Model

The summary table also shows results from models where the non-significant interaction

effects were dropped. These models are of the form:
Abt Associates Inc. Chapter 9 155

             

l

j k l l

k

j k k

j

Y preNatAllMerc Exp07mos joejcf St 0 1 2

: 0 : 0 H0 1  vs H a 1 

9.2.5.3. Results

Results are summarized in Exhibit 9.2.5.2. There were two significant PreNatAllMerc by

Exp07mos interaction effects. Similar to the results in the previous section, both sets of

significant results were cases where the signs of the coefficients for prenatal, postnatal,

and interaction effects were not consistent. For these two results, the coefficients for

prenatal and postnatal effects were positive, while the coefficient for the interaction effect

was negative. And, comparing the coefficient from the interaction model in the righthand panel of the summary, to the main effect model in the left-hand panel of the

summary, it is evident that the addition of the interaction term substantially increased the

size of the estimated positive coefficients for both main effects, with offsetting negative

interaction effects.

The exhibit also highlights three interaction effects that fell below a p<0.10 criterion. In

none of these three cases were the coefficients for the prenatal, postnatal, and interaction

effects in a consistent direction of either benefit or harm.

Similar to the results from the previous section, none of the interaction effects shown in

Exhibit 9.2.5.2 suggest clear evidence of either harm or benefit associated with the

interaction between prenatal and postnatal exposure.
Abt Associates Inc. Chapter 9 156

Exhibit 9.2.5.2. Summary of Multiple Sources of Prenatal Mercury Models (n=1,047)

E st S .E. P

-0.034 0.030 0.258

0.014 0.038 0.711

-0.007 0.014 0.625

-0.038 0.029 0.193

-0.039 0.061 0.524

0.007 0.009 0.455

-0.026 0.030 0.387

0.058 0.045 0.199

-0.036 0.027 0.177

-0.011 0.046 0.807

-0.002 0.013 0.887

0.001 0.011 0.929

-0.010 0.012 0.416

0.000 0.012 0.997

-0.123 0.059 0.036*

-0.125 0.058 0.031*

-0.060 0.036 0.097

-0.057 0.089 0.523

-0.051 0.109 0.639

-0.007 0.031 0.815

-0.017 0.028 0.552

-0.009 0.015 0.529

0.025 0.026 0.338

-0.033 0.066 0.615

-0.017 0.009 0.069

-0.007 0.008 0.384

-0.024 0.014 0.090

0.054 0.092 0.556

0.009 0.131 0.943

0.014 0.026 0.592

0.041 0.033 0.221

0.015 0.030 0.629

0.004 0.043 0.924

0.035 0.055 0.518

0.009 0.070 0.897

-0.014 0.021 0.516

0.000 0.025 0.999

-0.008 0.020 0.703

-0.011 0.018 0.537

-0.068 0.065 0.299

0.014 0.074 0.852

-0.046 0.067 0.491

>.05, <.10

P reN atAllM erc X Exp07 m os

E st S .E . P E st S .E . P Est S.E. P Est S .E. P

Speech and Language

Boston N am ing Test 0.430 0.276 0.119 0.051 0.030 0.090 1.103 0.655 0.093 0.113 0.063 0.071

N EP SY: S peeded N am ing 1.675 0.588 0.004+ 0.012 0.038 0.753 1.392 0.963 0.149 -0.014 0.079 0.863

N EP SY: C om prehension of Instructions 0.211 0.210 0.315 -0.014 0.014 0.301 0.344 0.343 0.317 -0.002 0.028 0.947

C ELF: Form ulated S entences -0.060 0.207 0.772 -0.034 0.030 0.248 0.691 0.612 0.259 0.036 0.062 0.560

C ELF: R ecalling Sentences 0.244 0.482 0.612 0.001 0.062 0.982 1.008 1.290 0.435 0.073 0.128 0.569

G FTA: A rticulation (lower = better) -0.034 0.067 0.611 0.011 0.010 0.254 -0.173 0.197 0.381 -0.002 0.020 0.919

Stuttering: Assessor R ating (lower = better) -0.116 0.208 0.579 0.025 0.033 0.438 0.402 0.633 0.525 0.071 0.062 0.254

Stuttering: Parent R ating (low er = better) -0.188 0.265 0.478 0.020 0.043 0.631 -1.263 0.887 0.154 -0.069 0.082 0.397

Stuttering: Teacher R ating (low er = better) -0.132 0.180 0.465 0.008 0.025 0.754 0.575 0.552 0.297 0.068 0.051 0.183

Verbal M em ory

C VLT-C : Free R ecall, N o D elay 0.364 0.476 0.444 -0.001 0.046 0.991 0.584 1.019 0.567 0.020 0.097 0.835

C VLT-C : Free R ecall, Short D elay 0.183 0.115 0.113 -0.024 0.013 0.070 0.219 0.282 0.438 -0.020 0.027 0.455

C VLT-C : C ued R ecall, S hort D elay 0.029 0.084 0.734 -0.005 0.011 0.637 0.009 0.237 0.970 -0.007 0.024 0.760

C VLT-C : Free R ecall, Long D elay 0.102 0.122 0.401 -0.019 0.012 0.111 0.294 0.265 0.268 -0.001 0.025 0.957

C VLT-C : C ued R ecall, Long D elay 0.211 0.183 0.249 0.001 0.012 0.924 0.210 0.300 0.484 0.001 0.025 0.966

C M S S tories 1: Im m ediate R ecall 0.353 0.416 0.396 -0.029 0.059 0.630 2.766 1.224 0.024+ 0.198 0.123 0.109

C M S S tories 2: D elayed R ecall 0.401 0.476 0.400 0.004 0.059 0.948 2.823 1.216 0.020+ 0.234 0.121 0.054

Achievem ent

W JIII: Letter- W ord Identification -0.350 0.300 0.243 0.063 0.037 0.090 0.819 0.764 0.284 0.173 0.076 0.023+

Fine M otor C oordination

G rooved Pegboard: D om inant H and (low er = better) -0.688 0.737 0.351 -0.085 0.089 0.339 0.418 1.880 0.824 0.019 0.185 0.920

G rooved Pegboard: N on-dom H and (lower = better) -1.191 1.393 0.393 -0.278 0.109 0.011+ -0.165 2.594 0.949 -0.185 0.227 0.415

Finger Tapping: D om inant H and -0.186 0.216 0.389 0.033 0.031 0.288 -0.046 0.639 0.942 0.046 0.064 0.473

Finger Tapping: N on-dom inant H and -0.136 0.269 0.612 0.017 0.028 0.539 0.191 0.613 0.755 0.048 0.058 0.414

Visual S patial Ability

Stanford Binet: C opying 0.093 0.185 0.613 0.007 0.015 0.655 0.287 0.358 0.424 0.024 0.032 0.443

Attention/Executive Functioning

G D S V igilance Task: C orrect R esponses 0.049 0.328 0.881 0.032 0.026 0.220 -0.443 0.610 0.467 -0.014 0.054 0.799

G D S V igilance Task: E rrors (lower = better) 0.275 0.624 0.660 -0.020 0.067 0.766 0.927 1.440 0.520 0.041 0.139 0.766

W IS C III: D igit S pan, Forw ard R ecall -0.057 0.077 0.462 -0.002 0.010 0.819 0.277 0.199 0.164 0.029 0.020 0.138

W IS C III: D igit S pan, B ackward R ecall -0.027 0.058 0.647 0.017 0.008 0.035+ 0.113 0.171 0.508 0.030 0.017 0.075

W IS C III: D igit Span, C om bined -0.083 0.113 0.463 0.016 0.015 0.259 0.394 0.303 0.193 0.061 0.030 0.042+

BR IE F Parent R ating: M etacognition (lower = better) -0.890 0.927 0.338 -0.052 0.092 0.573 -1.950 2.024 0.336 -0.151 0.191 0.431

BR IE F Teacher R ating: M etacognition (lower = better) -1.105 1.631 0.498 -0.145 0.132 0.275 -1.300 3.158 0.681 -0.162 0.274 0.554

B ehavior R egu lation (low er = better)

C R S-R : P arent R ating: H yperactive/Im pulsive -0.078 0.191 0.684 0.019 0.026 0.464 -0.348 0.539 0.519 -0.006 0.053 0.909

C R S-R : Teacher R ating: H yperactive/Im pulsive 0.241 0.313 0.442 -0.046 0.034 0.171 -0.580 0.740 0.433 -0.121 0.069 0.083

C R S-R : P arent R ating: Inattentive -0.122 0.295 0.678 -0.023 0.030 0.439 -0.411 0.665 0.537 -0.050 0.063 0.427

C R S-R : Teacher R ating: Inattentive -0.127 0.481 0.791 -0.034 0.043 0.433 -0.212 1.012 0.834 -0.041 0.089 0.642

BR IE F Parent R ating: B ehavior R egulation -0.974 0.518 0.060 0.073 0.055 0.184 -1.679 1.208 0.165 0.009 0.114 0.939

BR IE F Teacher R ating: B ehavior R egulation -0.014 0.526 0.978 -0.042 0.072 0.557 -0.196 1.491 0.896 -0.059 0.148 0.689

Tics (low er = better)

M otor tics (current): Assessor R ating 0.086 0.197 0.662 0.033 0.022 0.133 0.376 0.489 0.441 0.058 0.045 0.194

Phonics tics (current): A ssessor R ating 0.189 0.213 0.375 0.038 0.023 0.095 0.188 0.540 0.727 0.038 0.049 0.431

M otor tics (current): Parent R ating 0.087 0.219 0.693 -0.001 0.021 0.971 0.235 0.447 0.600 0.013 0.042 0.753

Phonics tics (current): P arent R ating 0.140 0.163 0.391 0.007 0.019 0.693 0.359 0.390 0.357 0.028 0.038 0.465

G eneral In tellectual Fun ction in g

W A S I V erbal IQ 0.366 0.513 0.475 -0.040 0.066 0.538 1.696 1.378 0.219 0.084 0.136 0.539

W A S I P erform ance IQ 0.903 0.583 0.122 0.130 0.074 0.080 0.634 1.558 0.684 0.105 0.154 0.496

W A S I Full Scale IQ 0.721 0.523 0.168 0.061 0.068 0.370 1.616 1.401 0.249 0.145 0.140 0.300

< .05 >.05, <.10 < .05 >.05, <.10

K ey: M ercury effect = B etter O utcom e p-value+ p-value M ercury effect =W orse O utcom e p-value* p-value

P-values show n are rounded to 3 decim al places. Therefore, a value show n as 0.050 m ay satisify p<0.05 criterion if the original value was rounded up, or m ay not satisify the criterion if the value was rounded dow n.

PreN atA llM erc Exp07m os

Interactio n M odel

Exp07m os

Test

M ain Effects M od el

PreN atAllM erc
Abt Associates Inc. Chapter 9 157

9.2.6. Concurrent Antibiotics-by-Exposure Interaction

Models

9.2.6.1. Introduction

Several studies of the rates of excretion of methylmercuric chloride in rodents have

indicated that oral antibiotics taken concurrently with oral ingestion of methylmercuric

chloride is associated with slower excretion (Rowland et. al., 1977, 1980,1984). The

results of these studies suggest that antibiotics may interact with mercury in a way that

may alter the effects of mercury. These finding motivate the hypothesis that, in children,

antibiotics may interact with exposure to ethylmercury from thimerosal in vaccines, to

have an effect that is different from exposure to ethylmercury from vaccines absent

antibiotics use.

The models summarized in this section were fit to the data in order to explore the

concurrent antibiotics hypothesis. Exposure to ethylmercury from thimerosal was

defined as “concurrent with antibiotic receipt” if the thimerosal-containing vaccine was

received during the course of antibiotic treatment, or was received up to 14 days prior to

initiation of antibiotic treatment, or was received up to 14 days after the last day of

antibiotic treatment. This definition of “concurrent with antibiotics” was the subject of

much discussion and debate among the study’s external consultants and principal

investigators, and after consultation with the literature and several experts in toxicology,

the current definition was considered to be the best available option. The rationale for

this definition is as follows.

If we operate on the theory that the loss of normal flora by antibiotic treatment causes the

thimerosal to be excreted more slowly from the body, we must include a period of time

after antibiotic usage stops during which the normal flora returns to normal. Pediatric

experts advised that E. coli (the most common gut bacteria) typically returns to normal

levels within two weeks of antibiotic use.

The rational for the window prior to antibiotic use is based on the notion that it takes time

for the mercury to be excreted, and if antibiotic treatment starts after receipt of a

thimerosal containing vaccine, the antibiotic could slow the excretion rate of the

previously received, but unexcreted mercury. A consulting toxicologist advised that both

animal and human data indicate demethylation and fecal excretion of the inorganic

species is the predominant route of elimination of ethylmercury from the body.

Unfortunately there are no precise numbers for the rate or biological half time of this

process. Data from human infants (Pichichero et al, 2002), and infant monkeys

(Burbacher et al., 2005) suggested that 14 days would be a reasonable guess at the length

of one half-life for excretion.

9.2.6.2. Model Specifications
Abt Associates Inc. Chapter 9 158

The following two models were fit to each outcome variable18:

Model (1): Concurrent Antibiotics from Birth to 7 Months

   

    

  

     

     

l

j k l l

k

j k k

j

j j

oe cf St

Y preNatThimer Exp07mos AbDays07mos AbExp07mos 0 1 2 3 4

: 0 : 0

: 0 : 0

0 2 4 2 4

0 4 4

   

 

   

 

a

a

H vs H

H vs H

where

AbDays07mos = a count of the number of days that child received antibiotics, during the

age range of 1 to 214 days,

and

AbExp07mos = a cumulative measure of ethylmercury exposure from thimerosal in

vaccines received concurrent with antibiotics during the age range from birth through

seven months (1 – 214 days), expressed in microgram units per kilograms of body weight

at the time of vaccine receipt.

The parameter estimates have the following interpretations:

2

ˆ is an estimate of the effect of exposure without concurrent antibiotic use.

3

ˆ is an estimate of the effect of antibiotic use (note: not concurrent antibiotics, but

antibiotics in and of themselves).

4

ˆ is an estimate of the difference between exposure effects with concurrent antibiotic

use and exposure effects without antibiotic use.

2 4

ˆ ˆ    is an estimate of the effect of exposure with concurrent antibiotic use (assuming

the number of days on antibiotics is held constant).

Model (2): Concurrent Antibiotics from Birth to 1 Month, and 1 to 7 Months

   

 

     

  

 

     

     

l

j k l l

k

j k k

j

j j

oe cf St

AbExp mos AbExp mos

Y preNatThimer HepB Exp mos AbDays mos AbDays mos

01 17

17 01 17

6 7

0 1 2 3 4 5

18 The models shown here are OLS regression models for continuous outcome variables. For dichotomous

outcome measures (tics and stuttering) logistic regression models of a similar form were fit to the data.
Abt Associates Inc. Chapter 9 159

: 0 : 0

: 0 : 0

: 0 : 0

: 0 : 0

0 3 7 3 7

0 2 6 2 6

0 7 7

0 6 6

   

   

 

 

   

   

 

 

a

a

a

a

H vs H

H vs H

H vs H

H vs H

where

AbDays01mos = a count of the number of days that child received antibiotics, during the

first month of life (age range of 1 to 28 days),

AbDays17mos = a count of the number of days that child received antibiotics, during the

during the age range of 1 to 7 months (age range of 29 to 214 days),

and

AbExp01mos = a cumulative measure of ethylmercury exposure from thimerosal in

vaccines received concurrent with antibiotics during the age ranges from birth through

one month1 (1 – 28 days), expressed in microgram units per kilograms of body weight at

the time of vaccine receipt,

AbExp17mos = a cumulative measure of ethylmercury exposure from thimerosal in

vaccines received concurrent with antibiotics during the age ranges from one through

seven months (29 – 214 days), expressed in microgram units per kilograms of body

weight at the time of vaccine receipt, and all other terms are as defined in the analysis

plan.

The parameter estimates have the following interpretations:

2

ˆ is an estimate of the effect of exposure without concurrent antibiotic use (during the

age range spanning birth to 28 days).

3

ˆ is an estimate of the effect of exposure without concurrent antibiotic use (during the

age range spanning 29 days to seven months).

4

ˆ is an estimate of the effect of antibiotic use during the age range spanning birth to 28

days. (note: not concurrent antibiotics, but antibiotics in and of themselves).

5

ˆ is an estimate of the effect of antibiotic use during the age range spanning 29 days to

seven months. (note: not concurrent antibiotics, but antibiotics in and of themselves).

6

ˆ is an estimate of the difference between exposure effects with concurrent antibiotic

use and exposure effects without antibiotic use, for the age range spanning birth to 28

days.

6

ˆ is an estimate of the difference between exposure effects with concurrent antibiotic

use and exposure effects without antibiotic use, for the age range spanning 29 days to

seven months.

2 6

ˆ ˆ    is an estimate of the effect of exposure with concurrent antibiotic use, for the age

range spanning birth to 28 days (assuming the number of days on antibiotics is held

constant).
Abt Associates Inc. Chapter 9 160

3 7

ˆ ˆ    is an estimate of the effect of exposure with concurrent antibiotic use, for the age

range spanning 29 days to seven months.

9.2.6.3. Results

The results offer little support for the hypothesis that mercury from vaccines is more

harmful if received concurrent with antibiotics. Of the 42 outcomes analyzed in the birth

to seven months exposure model (Model 1), one, CRS-R Teacher Rating Hyperactive /

Impulsive, had a significant exposure by antibiotics interaction effect19. For this outcome

the model estimated a statistically non-significant beneficial effect of cumulative

exposure during the age range from birth to seven months, when the exposures were not

concurrent with antibiotics20. For exposures that were concurrent with antibiotics, the

model estimates a harmful effect that was not statistically significant, but was

approximately similar in magnitude to the beneficial effect of non-concurrent exposure21.

Furthermore, the estimated effects of the antibiotics themselves, were significant in the

direction of benefit.

For the Assessor Rated Motor Tics outcome measure, the results indicate a significant

effect of concurrent exposure during the age range from birth to seven months. Holding

the number of days on antibiotics constant, the model predicts increasing risk of tics with

increasing concurrent exposure. However, the coefficient for the effect of the number of

days on antibiotics (AbDays07mos) is negative. This means that the model predicts that

an increase in the number of days on antibiotics results in lower risk for this outcome.

The predictions from this model are such that a combination of high levels concurrent

exposure with a high number of days on antibiotics, produces a lower estimated risk than

is estimated for a combination of low concurrent exposure and few days on antibiotics.

The Model 2 estimates regarding exposure during the age range from 1 to 7 months on

the same outcome, CRS-R Teacher Rating Hyperactive / Impulsive, mirror the previously

described results from Model 1 regarding exposure from birth to 7 months. (See columns

labeled “Exp17mos”, “AbExp17mos”, and “Concur Exp17mos effect” in Exhibit

9.2.6.2). There was also a significant interaction effect (exposure 1 to 7 months by

antibiotics) for the Finger Tapping Non-Dominant Hand outcome measures. For this

outcome, estimates for non-concurrent exposure are in the direction of benefit, while

estimates for concurrent exposure are in the direction of harm. However, for this same

outcome, concurrent exposure in the earlier age range (birth to 28 days) is in the direction

of benefit. For Finger Tapping: Dominant Hand, the interaction effect for birth to 28

days is significant, and the beneficial effect of concurrent exposure during the age range

spanning birth to 28 days is statistically significant.

19 See the column labeled “AbExp07mos” in Exhibit 9.2.6.1.

20 See the column labeled “Exp07mos” in Exhibit 9.2.6.1.

21 See the column labeled “ Concur Exp07mos Effect” in Exhibit 9.2.6.1.
Abt Associates Inc. Chapter 9 161

.

Exhibit 9.2.6.1. Summary of Models for Concurrent Antibiotics Effect –Birth to Seven Months (n=1,047)

Est S.E. P StCf Est S.E. P StCf Est S.E. P StCf Est S.E. P StCf

Speech and Language

Boston Naming Test 0.032 0.022 0.143 0.033 0.049 0.031 0.111 0.044 -0.008 0.014 0.544 0.006 0.058 0.911

NEPSY: Speeded Naming 0.058 0.027 0.031 + 0.060 0.017 0.039 0.670 0.015 -0.001 0.017 0.969 -0.066 0.073 0.368

NEPSY: Comprehension of Instructions -0.002 0.010 0.867 -0.005 -0.013 0.014 0.356 -0.032 0.004 0.006 0.517 -0.008 0.026 0.759

CELF: Formulated Sentences 0.020 0.021 0.341 0.025 -0.035 0.030 0.247 -0.037 0.016 0.013 0.231 0.008 0.056 0.893

CELF: Recalling Sentences 0.057 0.044 0.201 0.033 -0.012 0.063 0.846 -0.006 -0.014 0.028 0.616 0.102 0.118 0.389

GFTA: Articulation (lower = better) -0.002 0.007 0.800 -0.008 0.010 0.010 0.284 0.040 -0.004 0.004 0.313 0.003 0.018 0.859

Stuttering: Assessor Rating (lower = better) -0.002 0.021 0.941 0.974 0.031 0.033 0.355 1.556 0.015 0.011 0.170 -0.048 0.062 0.437

Stuttering: Parent Rating (lower = better) -0.022 0.049 0.651 0.694 0.034 0.045 0.452 1.620 0.001 0.026 0.974 -0.188 0.114 0.100

Stuttering: Teacher Rating (lower = better) -0.039 0.029 0.176 0.519 0.009 0.026 0.721 1.140 0.010 0.008 0.187 -0.002 0.041 0.959

Verbal M em ory

CVLT-C: Free Recall, No Delay 0.030 0.033 0.356 0.026 0.010 0.047 0.826 0.008 0.022 0.021 0.299 -0.112 0.088 0.205

CVLT-C: Free Recall, Short Delay -0.001 0.009 0.895 -0.004 -0.023 0.013 0.085 -0.060 0.006 0.006 0.350 -0.007 0.025 0.795

CVLT-C: Cued Recall, Short Delay -0.001 0.008 0.916 -0.003 -0.005 0.012 0.672 -0.015 0.001 0.005 0.919 -0.004 0.022 0.864

CVLT-C: Free Recall, Long Delay 0.001 0.009 0.926 0.003 -0.020 0.012 0.111 -0.055 0.001 0.006 0.837 0.003 0.023 0.880

CVLT-C: Cued Recall, Long Delay 0.005 0.008 0.563 0.016 0.002 0.012 0.900 0.004 0.001 0.005 0.904 -0.004 0.023 0.844

CMS Stories 1: Im mediate Recall 0.025 0.042 0.555 0.013 -0.028 0.061 0.650 -0.013 -0.014 0.027 0.600 -0.032 0.113 0.781

CMS Stories 2: Delayed Recall -0.009 0.041 0.826 -0.005 0.006 0.060 0.925 0.003 -0.010 0.027 0.711 -0.014 0.111 0.903

Achievem ent

W JIII: Letter- W ord Identification 0.013 0.026 0.633 0.011 0.072 0.038 0.055 0.055 0.026 0.017 0.122 -0.094 0.070 0.182

Fine Motor Coordination

Grooved Pegboard: Dominant Hand (lower = better) -0.111 0.064 0.084 -0.033 -0.081 0.091 0.370 -0.021 0.069 0.041 0.095 0.058 0.171 0.736

Grooved Pegboard: Non-dom Hand (lower = better) -0.086 0.077 0.263 -0.023 -0.281 0.111 0.012 + -0.063 0.078 0.050 0.118 0.118 0.207 0.569

Finger Tapping: Dominant Hand -0.013 0.022 0.561 -0.016 0.044 0.032 0.167 0.046 0.004 0.014 0.764 -0.096 0.059 0.105

Finger Tapping: Non-dominant Hand -0.013 0.020 0.511 -0.017 0.029 0.029 0.315 0.033 0.011 0.013 0.393 -0.103 0.054 0.055

Visual Spatial Ability

Stanford Binet: Copying 0.006 0.011 0.595 0.016 0.009 0.016 0.545 0.022 -0.001 0.007 0.874 -0.029 0.029 0.307

Attention/Executive Functioning

GDS Vigilance Task: Correct Responses -0.012 0.018 0.505 -0.020 0.039 0.026 0.138 0.054 0.010 0.012 0.392 -0.063 0.049 0.198

GDS Vigilance Task: Errors (lower = better) 0.035 0.047 0.461 0.022 -0.005 0.068 0.947 -0.002 0.070 0.030 0.020* -0.152 0.126 0.227

W ISC III: Digit Span, Forward Recall 0.000 0.007 0.968 0.001 -0.002 0.010 0.859 -0.007 -0.002 0.004 0.687 -0.006 0.018 0.755

W ISC III: Digit Span, Backward Recall -0.013 0.006 0.030 * -0.065 0.019 0.008 0.022 + 0.084 0.001 0.004 0.710 -0.012 0.016 0.447

W ISC III: Digit Span, Com bined -0.012 0.010 0.258 -0.033 0.019 0.015 0.205 0.046 0.000 0.007 0.951 -0.019 0.028 0.498

BRIEF Parent Rating: Metacognition (lower = better) 0.019 0.066 0.770 0.009 -0.066 0.094 0.479 -0.026 -0.028 0.042 0.506 0.134 0.176 0.449

BRIEF Teacher Rating: Metacognition (lower = better) 0.022 0.088 0.800 0.008 -0.174 0.135 0.198 -0.055 -0.033 0.057 0.564 0.275 0.244 0.260

Behavior Regulation (low er = better)

CRS-R: Parent Rating: Hyperactive/Impulsive 0.005 0.019 0.776 0.009 0.009 0.026 0.727 0.013 -0.026 0.012 0.028+ 0.082 0.050 0.098

CRS-R: Teacher Rating: Hyperactive/Im pulsive 0.021 0.022 0.349 0.030 -0.065 0.034 0.057 -0.080 -0.029 0.015 0.049+ 0.177 0.062 0.005*

CRS-R: Parent Rating: Inattentive 0.011 0.022 0.609 0.015 -0.024 0.031 0.440 -0.029 0.001 0.014 0.934 0.002 0.058 0.967

CRS-R: Teacher Rating: Inattentive 0.001 0.029 0.967 0.001 -0.039 0.044 0.372 -0.038 -0.002 0.019 0.927 0.060 0.080 0.458

BRIEF Parent Rating: Behavior Regulation -0.023 0.040 0.556 -0.018 0.060 0.057 0.287 0.040 -0.037 0.026 0.151 0.144 0.106 0.176

BRIEF Teacher Rating: Behavior Regulation 0.033 0.048 0.488 0.023 -0.061 0.073 0.402 -0.036 -0.019 0.031 0.529 0.174 0.132 0.187

Tics (low er = better)

Motor tics (current): Assessor Rating 0.017 0.011 0.119 1.320 0.025 0.022 0.265 1.429 -0.027 0.015 0.078 0.059 0.039 0.130

Phonics tics (current): Assessor Rating -0.011 0.018 0.538 0.829 0.034 0.023 0.151 1.618 -0.002 0.009 0.839 0.024 0.038 0.522

Motor tics (current): Parent Rating 0.003 0.012 0.834 1.043 -0.003 0.021 0.876 0.955 -0.013 0.010 0.185 -0.005 0.041 0.893

Phonics tics (current): Parent Rating -0.013 0.017 0.443 0.810 0.012 0.019 0.538 1.183 0.007 0.007 0.344 -0.041 0.036 0.260

General Intellectual Functioning

W ASI Verbal IQ 0.052 0.047 0.270 0.029 -0.055 0.067 0.414 -0.027 -0.014 0.030 0.651 0.104 0.126 0.409

W ASI Perform ance IQ -0.008 0.054 0.887 -0.004 0.130 0.076 0.086 0.061 -0.023 0.034 0.496 -0.016 0.144 0.910

W ASI Full Scale IQ 0.026 0.048 0.595 0.015 0.057 0.069 0.412 0.028 -0.016 0.031 0.600 0.019 0.129 0.884

< .05 >.05, <.10 < .05 >.05, <.10

Key: Mercury effect = Better Outcome p-value+ p-value Mercury effect =W orse Outcome p-value* p-value

P-values shown are rounded to 3 decimal places. Therefore, a value shown as 0.050 m ay satisify p<0.05 criterion if the original value was rounded up, or m ay not satisify the criterion if the value was rounded down.

Exp07m os AbDays07m os AbExp07mos

Test

PreNatThim er

Est S.E. P StCf

0.056 0.060 0.352 0.050

-0.049 0.076 0.518 -0.043

-0.021 0.027 0.440 -0.053

-0.028 0.059 0.637 -0.029

0.090 0.122 0.464 0.045

0.014 0.019 0.469 0.052

-0.017 0.065 0.788 0.779

-0.154 0.114 0.174 0.110

0.007 0.044 0.874 1.106

-0.101 0.091 0.268 -0.074

-0.029 0.026 0.256 -0.077

-0.009 0.023 0.701 -0.026

-0.016 0.024 0.502 -0.045

-0.003 0.024 0.901 -0.008

-0.059 0.117 0.614 -0.027

-0.008 0.116 0.946 -0.004

-0.022 0.073 0.766 -0.017

-0.024 0.177 0.894 -0.006

-0.163 0.215 0.449 -0.037

-0.052 0.061 0.397 -0.054

-0.074 0.055 0.181 -0.085

-0.020 0.030 0.502 -0.048

-0.024 0.051 0.638 -0.033

-0.157 0.131 0.232 -0.084

-0.007 0.019 0.695 -0.028

0.007 0.016 0.658 0.032

0.000 0.029 1.000 0.000

0.067 0.182 0.713 0.026

0.102 0.257 0.692 0.032

0.091 0.051 0.075 0.128

0.112 0.065 0.088 0.138

-0.021 0.060 0.720 -0.026

0.020 0.085 0.812 0.020

0.204 0.110 0.063 0.134

0.113 0.139 0.417 0.067

0.084 0.040 0.037* 3.310

0.058 0.040 0.142 2.291

-0.009 0.042 0.834 0.883

-0.029 0.037 0.439 0.661

0.049 0.130 0.705 0.024

0.114 0.149 0.445 0.053

0.076 0.134 0.573 0.037

>.05, <.10

Concur Exp07m os Effect
Abt Associates Inc. Chapter 9 162

.

Exhibit 9.2.6.2. Summary of Models for Concurrent Antibiotics Effect –Birth to 28 Days, and 29 Days to Seven Months (n=1,047)

Est S.E. P StCf Est S.E. P StCf Est S.E. P StCf Est S.E. P StCf

SpeechandLanguage

BostonNamingTest 0.033 0.022 0.129 0.034 -0.047 0.102 0.643 -0.011 0.063 0.033 0.056 0.052 -0.173 0.109 0.112

NEPSY:SpeededNaming 0.057 0.027 0.033+ 0.059 -0.034 0.127 0.788 -0.008 0.024 0.042 0.573 0.019 -0.019 0.135 0.889

NEPSY:Comprehensionof Instructions -0.002 0.010 0.842 -0.006 -0.023 0.045 0.610 -0.016 -0.012 0.015 0.421 -0.028 0.028 0.049 0.566

CELF:FormulatedSentences 0.020 0.021 0.340 0.025 -0.064 0.099 0.518 -0.018 -0.030 0.032 0.356 -0.030 -0.089 0.106 0.399

CELF:RecallingSentences 0.054 0.044 0.224 0.031 -0.035 0.207 0.866 -0.005 -0.007 0.067 0.914 -0.003 -0.082 0.222 0.711

GFTA: Articulation(lower= better) -0.002 0.007 0.715 -0.011 0.076 0.032 0.017* 0.077 0.003 0.010 0.794 0.010 0.008 0.034 0.821

Stuttering:AssessorRating(lower=better) -0.002 0.021 0.925 0.967 0.067 0.104 0.523 1.290 0.024 0.036 0.495 1.381 0.066 0.081 0.416

Stuttering:ParentRating (lower=better) -0.021 0.048 0.663 0.705 -0.095 0.125 0.447 0.696 0.046 0.046 0.324 1.840 -6.373 50.547 0.900

Stuttering:TeacherRating (lower=better) -0.038 0.029 0.183 0.529 0.030 0.075 0.689 1.122 0.010 0.028 0.726 1.137 -0.044 0.074 0.554

VerbalMemory

CVLT-C:FreeRecall,NoDelay 0.031 0.033 0.356 0.026 0.020 0.154 0.897 0.004 0.011 0.050 0.833 0.007 -0.065 0.166 0.694

CVLT-C:FreeRecall,ShortDelay -0.001 0.009 0.896 -0.004 -0.017 0.044 0.695 -0.012 -0.023 0.014 0.103 -0.056 -0.024 0.047 0.617

CVLT-C:CuedRecall,ShortDelay -0.001 0.008 0.870 -0.005 0.030 0.038 0.432 0.024 -0.009 0.012 0.488 -0.024 -0.021 0.041 0.602

CVLT-C:FreeRecall,LongDelay 0.001 0.009 0.943 0.002 -0.020 0.041 0.618 -0.015 -0.019 0.013 0.144 -0.050 -0.020 0.043 0.645

CVLT-C:CuedRecall,LongDelay 0.005 0.008 0.565 0.016 0.008 0.040 0.835 0.006 0.001 0.013 0.918 0.004 -0.036 0.042 0.396

CMSStories1:ImmediateRecall 0.024 0.042 0.572 0.013 -0.068 0.198 0.731 -0.008 -0.023 0.065 0.721 -0.010 0.029 0.212 0.891

CMSStories2:DelayedRecall -0.011 0.041 0.791 -0.006 -0.037 0.195 0.847 -0.005 0.011 0.064 0.859 0.005 -0.002 0.209 0.994

Achievement

WJIII:Letter-WordIdentification 0.013 0.026 0.609 0.012 -0.072 0.123 0.559 -0.015 0.090 0.040 0.024+ 0.064 -0.059 0.132 0.656

FineMotorCoordination

GroovedPegboard:DominantHand(lower=better) -0.108 0.064 0.092 -0.033 -0.278 0.301 0.355 -0.019 -0.061 0.096 0.527 -0.015 0.133 0.323 0.680

GroovedPegboard:Non-domHand(lower=better) -0.090 0.077 0.244 -0.024 -0.165 0.364 0.651 -0.010 -0.296 0.119 0.013+ -0.062 0.252 0.388 0.517

FingerTapping:DominantHand -0.012 0.022 0.573 -0.015 0.197 0.104 0.057 0.055 0.028 0.034 0.404 0.028 -0.152 0.110 0.168

FingerTapping:Non-dominantHand -0.012 0.020 0.560 -0.015 0.025 0.094 0.791 0.008 0.032 0.031 0.303 0.034 -0.127 0.100 0.207

VisualSpatialAbility

StanfordBinet:Copying 0.006 0.011 0.560 0.017 -0.025 0.051 0.621 -0.016 0.014 0.017 0.408 0.031 -0.021 0.054 0.693

Attention/ExecutiveFunctioning

GDSVigilanceTask:CorrectResponses -0.011 0.018 0.540 -0.018 -0.014 0.086 0.875 -0.005 0.045 0.028 0.110 0.058 0.018 0.092 0.846

GDSVigilanceTask:Errors(lower=better) 0.033 0.047 0.489 0.020 0.051 0.221 0.817 0.007 -0.009 0.072 0.905 -0.004 -0.040 0.236 0.866

WISCIII:DigitSpan,ForwardRecall 0.000 0.007 0.953 0.002 -0.014 0.032 0.649 -0.015 0.001 0.010 0.934 0.003 -0.063 0.034 0.065

WISCIII:DigitSpan,BackwardRecall -0.013 0.006 0.028* -0.066 0.038 0.028 0.168 0.045 0.018 0.009 0.049+ 0.071 -0.021 0.030 0.478

WISCIII: DigitSpan,Combined -0.012 0.010 0.255 -0.033 0.017 0.049 0.732 0.011 0.021 0.016 0.195 0.046 -0.086 0.052 0.099

BRIEFParentRating: Metacognition(lower=better) 0.019 0.066 0.778 0.008 0.004 0.309 0.990 0.000 -0.072 0.100 0.474 -0.026 -0.167 0.332 0.616

BRIEFTeacherRating:Metacognition(lower=better) 0.019 0.089 0.832 0.007 0.014 0.436 0.974 0.001 -0.198 0.144 0.169 -0.058 0.070 0.441 0.873

BehaviorRegulation(lower=better)

CRS-R:ParentRating:Hyperactive/Impulsive 0.003 0.019 0.853 0.006 0.079 0.087 0.364 0.030 0.000 0.028 0.998 0.000 0.065 0.093 0.488

CRS-R:TeacherRating:Hyperactive/Impulsive 0.020 0.022 0.367 0.029 -0.019 0.111 0.867 -0.006 -0.069 0.036 0.058 -0.079 -0.070 0.112 0.535

CRS-R:ParentRating:Inattentive 0.010 0.022 0.638 0.014 0.025 0.101 0.807 0.008 -0.030 0.033 0.365 -0.033 0.040 0.109 0.713

CRS-R:TeacherRating:Inattentive 0.001 0.029 0.984 0.001 0.009 0.142 0.950 0.002 -0.046 0.047 0.326 -0.042 0.026 0.144 0.858

BRIEFParentRating: BehaviorRegulation -0.023 0.040 0.559 -0.018 -0.061 0.186 0.745 -0.011 0.075 0.060 0.214 0.046 -0.066 0.200 0.742

BRIEFTeacherRating:BehaviorRegulation 0.029 0.048 0.540 0.020 0.186 0.234 0.426 0.029 -0.089 0.078 0.252 -0.049 -0.050 0.237 0.832

Tics(lower=better)

Motortics(current):AssessorRating 0.018 0.011 0.099 1.345 -0.038 0.069 0.580 0.864 0.031 0.024 0.190 1.510 0.047 0.066 0.478

Phonicstics(current):AssessorRating -0.012 0.019 0.533 0.825 0.032 0.074 0.661 1.132 0.032 0.024 0.187 1.534 0.026 0.062 0.673

Motortics(current):ParentRating 0.003 0.012 0.795 1.055 -0.106 0.070 0.129 0.666 0.009 0.022 0.681 1.130 -0.040 0.103 0.700

Phonicstics(current):ParentRating -0.013 0.017 0.437 0.807 0.030 0.065 0.638 1.123 0.011 0.020 0.605 1.150 -0.101 0.102 0.323

General IntellectualFunctioning

WASIVerbal IQ 0.054 0.047 0.247 0.031 -0.399 0.220 0.071 -0.052 -0.014 0.071 0.840 -0.007 -0.128 0.236 0.587

WASIPerformanceIQ -0.009 0.054 0.875 -0.005 0.304 0.254 0.231 0.038 0.114 0.080 0.158 0.050 -0.167 0.269 0.534

WASIFullScaleIQ 0.027 0.049 0.580 0.015 -0.082 0.227 0.717 -0.011 0.075 0.074 0.310 0.034 -0.137 0.240 0.570

<.05 >.05,<.10 <.05 >.05,<.10

Key: Mercuryeffect=BetterOutcome p-value+ p-value Mercuryeffect=WorseOutcome p-value* p-value

P-valuesshownareroundedto3decimal places.Therefore,avalueshownas0.050maysatisifyp<0.05criterioniftheoriginalvaluewasroundedup,ormaynotsatisifythecriterionifthevaluewasroundeddown.

HepB Exp17mos AbDays01mos

Test

PreNatThimer

Est S.E. P StCf Est S.E. P StCf Est S.E. P StCf Est S.E. P StCf Est S.E. P StCf

0.001 0.015 0.942 0.101 0.342 0.767 -0.003 0.059 0.958 0.054 0.346 0.876 0.013 0.060 0.061 0.327 0.050

0.003 0.019 0.862 -0.801 0.424 0.059 -0.052 0.074 0.483 -0.835 0.429 0.052 -0.196 -0.028 0.077 0.713 -0.023

0.003 0.007 0.681 -0.189 0.155 0.225 -0.003 0.027 0.918 -0.212 0.157 0.179 -0.143 -0.015 0.028 0.594 -0.035

0.023 0.015 0.116 -0.143 0.332 0.667 0.007 0.057 0.905 -0.207 0.336 0.538 -0.059 -0.023 0.060 0.698 -0.023

-0.005 0.031 0.877 -1.282 0.701 0.068 0.126 0.120 0.293 -1.317 0.708 0.063 -0.176 0.119 0.124 0.341 0.055

-0.005 0.005 0.288 -0.040 0.108 0.715 0.006 0.019 0.755 0.036 0.109 0.740 0.037 0.008 0.019 0.659 0.030

0.011 0.013 0.404 -0.068 0.295 0.818 -0.048 0.064 0.455 -0.001 0.299 0.997 0.996 -0.024 0.067 0.724 0.729

0.002 0.027 0.950 -0.839 69.395 0.990 -0.173 0.115 0.131 -0.934 69.395 0.989 0.028 -0.127 0.115 0.267 0.184

0.015 0.010 0.118 0.013 0.234 0.957 -0.006 0.041 0.878 0.043 0.237 0.857 1.178 0.003 0.045 0.940 1.046

0.027 0.023 0.238 -0.080 0.522 0.879 -0.115 0.089 0.198 -0.060 0.529 0.910 -0.012 -0.105 0.093 0.263 -0.072

0.007 0.007 0.260 -0.004 0.148 0.980 -0.008 0.025 0.768 -0.021 0.150 0.889 -0.015 -0.031 0.026 0.247 -0.075

0.002 0.006 0.691 -0.107 0.131 0.415 -0.002 0.022 0.926 -0.077 0.132 0.561 -0.061 -0.011 0.023 0.643 -0.030

0.003 0.006 0.655 -0.067 0.137 0.627 0.004 0.024 0.863 -0.087 0.139 0.532 -0.065 -0.015 0.024 0.538 -0.040

0.003 0.006 0.622 -0.003 0.135 0.984 -0.006 0.023 0.802 0.006 0.137 0.968 0.004 -0.004 0.024 0.854 -0.012

-0.015 0.029 0.619 -0.642 0.667 0.336 -0.018 0.115 0.877 -0.711 0.675 0.293 -0.087 -0.041 0.120 0.733 -0.018

-0.007 0.029 0.814 -0.980 0.654 0.134 0.006 0.113 0.956 -1.018 0.662 0.125 -0.128 0.018 0.118 0.881 0.008

0.032 0.018 0.078 -0.356 0.415 0.392 -0.096 0.071 0.179 -0.428 0.420 0.309 -0.087 -0.006 0.074 0.940 -0.004

0.063 0.045 0.159 0.518 1.011 0.608 0.047 0.174 0.787 0.240 1.023 0.815 0.017 -0.014 0.181 0.938 -0.003

0.072 0.054 0.185 -1.117 1.224 0.362 0.152 0.211 0.471 -1.281 1.237 0.301 -0.077 -0.144 0.220 0.511 -0.030

0.011 0.015 0.493 0.719 0.351 0.041+ -0.115 0.060 0.055 0.916 0.355 0.010+ 0.257 -0.086 0.062 0.164 -0.084

0.017 0.014 0.221 0.490 0.318 0.124 -0.120 0.054 0.027* 0.515 0.322 0.110 0.157 -0.089 0.056 0.116 -0.095

0.000 0.008 0.980 0.063 0.171 0.713 -0.033 0.029 0.264 0.038 0.172 0.828 0.024 -0.019 0.030 0.534 -0.042

0.009 0.013 0.493 0.146 0.289 0.614 -0.068 0.050 0.172 0.132 0.292 0.651 0.049 -0.023 0.052 0.658 -0.030

0.080 0.033 0.015* -0.992 0.744 0.183 -0.138 0.127 0.278 -0.941 0.752 0.211 -0.135 -0.147 0.134 0.271 -0.074

0.002 0.005 0.646 -0.066 0.107 0.539 -0.007 0.018 0.705 -0.080 0.108 0.459 -0.081 -0.006 0.019 0.750 -0.022

0.003 0.004 0.509 -0.002 0.093 0.979 -0.013 0.016 0.431 0.036 0.095 0.704 0.042 0.005 0.017 0.769 0.020

0.005 0.007 0.493 -0.060 0.165 0.715 -0.021 0.028 0.449 -0.044 0.167 0.794 -0.028 -0.001 0.029 0.978 -0.002

-0.019 0.046 0.675 0.033 1.047 0.975 0.131 0.179 0.464 0.037 1.058 0.972 0.004 0.060 0.186 0.749 0.022

-0.040 0.064 0.527 0.173 1.390 0.901 0.289 0.248 0.245 0.187 1.405 0.894 0.016 0.090 0.261 0.729 0.027

-0.030 0.013 0.020+ -0.402 0.292 0.169 0.097 0.050 0.054 -0.323 0.296 0.275 -0.121 0.097 0.052 0.063 0.127

-0.025 0.016 0.113 0.124 0.355 0.726 0.177 0.063 0.005* 0.106 0.358 0.768 0.035 0.108 0.066 0.106 0.124

-0.001 0.015 0.964 -0.165 0.341 0.628 0.008 0.059 0.888 -0.140 0.345 0.684 -0.045 -0.021 0.061 0.725 -0.024

-0.005 0.021 0.824 0.227 0.451 0.615 0.060 0.081 0.462 0.236 0.456 0.606 0.061 0.014 0.086 0.872 0.013

-0.033 0.028 0.237 -0.422 0.627 0.501 0.153 0.108 0.158 -0.483 0.634 0.446 -0.085 0.227 0.112 0.042* 0.139

-0.017 0.034 0.621 0.063 0.749 0.933 0.180 0.133 0.178 0.249 0.756 0.742 0.039 0.091 0.141 0.521 0.050

-0.031 0.015 0.042+ 0.047 0.195 0.810 0.064 0.040 0.110 0.009 0.199 0.966 1.033 0.095 0.042 0.025* 3.529

-0.005 0.011 0.651 0.131 0.188 0.486 0.023 0.040 0.566 0.163 0.194 0.400 1.867 0.055 0.041 0.184 2.078

-0.013 0.010 0.213 -0.086 0.289 0.765 -0.004 0.041 0.931 -0.192 0.290 0.508 0.479 0.006 0.043 0.895 1.078

0.010 0.008 0.209 0.104 0.219 0.633 -0.045 0.037 0.220 0.135 0.223 0.545 1.674 -0.035 0.039 0.370 0.630

-0.006 0.033 0.859 -0.242 0.755 0.749 0.102 0.128 0.426 -0.641 0.763 0.401 -0.084 0.087 0.132 0.510 0.040

-0.016 0.037 0.668 0.328 0.844 0.697 -0.024 0.147 0.870 0.632 0.855 0.460 0.079 0.090 0.152 0.554 0.039

-0.008 0.033 0.804 -0.135 0.766 0.861 0.015 0.131 0.908 -0.217 0.774 0.779 -0.028 0.090 0.137 0.510 0.041

>.05,<.10

AbDays17mos AbExp01mos AbExp17mos ConcurHepBEffect ConcurExp17mosEffect
Abt Associates Inc. Chapter 10 163

10. References

Ambrose, N. G.; Cox, N. J.; Yairi, E. (1997, June). The genetic basis of the persistence

and recovery in stuttering. Journal of Speech, Language, and Hearing Research, 40(3),

567-580.

Andrews N, Miller E, Grant A, Stowe J, Osborne V, Taylor B (2004). Thimerosal

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