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. Author manuscript; available in PMC: 2025 Feb 1.
Published in final edited form as: Expo Health. 2023 Mar 22;16(1):135–148. doi: 10.1007/s12403-023-00543-2

Associations of Perinatal Metal and Metalloid Exposures with Early Child Behavioral Development Over Time in the New Hampshire Birth Cohort Study

Julia A Bauer 1, Megan E Romano 1, Brian P Jackson 2, David Bellinger 3,4, Susan Korrick 5,6, Margaret R Karagas 1
PMCID: PMC11060719  NIHMSID: NIHMS1899058  PMID: 38694196

Abstract

Research on the neurodevelopmental effects of metal(loid)s has focused mainly on outcomes assessed at one time point, even though brain development progresses over time. We investigated biomarkers of perinatal exposure to metals and changes in child behavior over time. We followed 268 participants from the prospective New Hampshire Birth Cohort Study between birth and age 5 years. We measured arsenic (As), copper (Cu), manganese (Mn), lead (Pb), selenium (Se), and zinc (Zn) in toenails from 6-week-old infants. The Behavioral Symptoms Index (BSI), externalizing, and internalizing symptoms were assessed using the Behavior Assessment System for Children, 2nd edition (BASC-2) at ages 3 and 5 years. Multivariable linear regression was used to estimate associations of metals with behavior change, calculated as the difference in symptom raw scores between 3 and 5 years, in addition to the associations for symptom scores at 3 and 5 years separately. Sex-specific associations were also explored using stratified models and a sex-metal interaction term. Adjusted associations of metals and change in behavior varied by exposure and outcome. Each 1 μg/g increase in ln toenail Cu was associated with improved behavior between 3 and 5 years [BSI: β = − 3.88 (95%CI: − 7.12, − 0.64); Externalizing problems: β = − 2.20 (95%CI: − 4.07, − 0.33)]. Increasing Zn was associated with increased externalizing behavior over time (β = 3.42 (95%CI: 0.60, 6.25). Sex-stratified analyses suggested more pronounced associations among boys compared to girls. Perinatal exposure to metals may alter behavioral development between ages 3 and 5 years. Findings support the need for more research on associations between metals and neurodevelopment over longer time periods.

Keywords: Environment, Metals, Neurodevelopment, Children, Prenatal, Postnatal

Introduction

Brain development is a dynamic and tightly choreographed process especially during prenatal and early postnatal periods (Dubois et al. 2014; Rice & Barone 2000). During these periods, developmental processes are influenced by genetics as well as positive and negative environmental inputs that can change the course of future brain development (Bellinger et al. 2016; Debes et al. 2016; Rice & Barone 2000). Such environmental inputs include essential and neurotoxic metals and metalloids (hereafter referred to as metals) from anthropogenic and natural sources (Grandjean & Herz 2015; Grandjean & Landrigan 2014). While essential, yet neurotoxic in excess, metals such as manganese (Mn), copper (Cu), selenium (Se), and zinc (Zn) are required as part of a healthy diet, general populations can be over exposed to these ubiquitous metals and other toxic metals [e.g., arsenic (As) and lead (Pb)] by inhalation of contaminated air or dust, ingestion of contaminated drinking water or food, or less commonly, through dermal contact (Agency for Toxic Substances and Disease Registry (ATSDR), 2022; Agency for Toxic Substances and Disease Registry 2012; ATSDR 2004).

Although extensive research has assessed the relation of prenatal or early-life exposure to metals with subsequent neurodevelopment, there is sparse research investigating the influence of environmental metals on change in behavioral function, requiring multiple time points of neurobehavioral assessment (Amorós et al. 2019; Claus Henn et al. 2012; Coscia et al. 2010; Jedrychowski et al. 2009; Liu et al. 2018; Polanska et al. 2017; Tong et al. 1998; Wasserman et al. 2000). By investigating outcomes prospectively assessed at more than one time point, we can explore whether associations between prenatal and early-life exposure to metals and neurobehavior are persistent over time, appear at later time points (delayed) or are transient and resolve over time (Bellinger et al. 2016; Rice & Barone 2000).

Nearly all prior research associating prenatal or early-life metal exposure with neurodevelopment over multiple time points has focused on cognitive outcomes (Claus Henn et al. 2012; Coscia et al. 2010; Jedrychowski et al. 2009; Liu et al. 2018; Polanska et al. 2017). Findings of these works suggest that associations with early-life metal exposures can vary by timing of outcome measurement. However, other neurodevelopmental domains are also important to quality of life; one in five children living in western societies experiences emotional and behavioral difficulties (Bayer et al. 2008; C. A. Boyle et al. 2011; M. H. Boyle et al. 2019) that relate to enhanced risk of future mental health disorders, substance use disorders, suicidal behavior, and criminality(Babinski et al. 1999; Beesdo et al. 2009; Campbell 1995). Many emotional and behavioral difficulties can be characterized as externalizing behaviors (i.e., negative behaviors projected outward, such as aggression) or internalizing behaviors (i.e., negative behaviors projected inward, such as anxiety and depression). Symptoms of emotional and behavioral difficulties in children can be reliably measured beginning around 2 years of age, and in time, early symptoms may resolve or persist to become maladaptive behavioral disorders (e.g., ADHD, depression, and anxiety)(Poulou 2013; Wakschlag et al. 2010). Thus, examining trends in these symptoms, beginning at an early age, may help inform timely interventions that reduce the risk of adverse long-term outcomes (Bayer et al. 2008; Luby et al. 2019).

The aim of this study is to estimate the associations of perinatal exposure to trace elements (As, Cu, Mn, Pb, Se, and Zn) and change in behavior between ages 3 and 5 years in a birth cohort. Also, we further explored sex-specific associations and associations at each time point of the outcome. We examined data from 268 mother–infant participants in the New Hampshire Birth Cohort Study to estimate associations of perinatal exposure to metals and change in behavior between ages 3 and 5 years. We measured metal concentrations in infant toenails collected at age 6 weeks and estimated associations with the change in composite measures from the Behavioral Assessment System for Children, 2nd edition (BASC-2) including the overall behavioral symptoms index, internalizing problems, and externalizing problems scores.

Methods

Study Population

Participants for this analysis were part of the prospective New Hampshire Birth Cohort Study (NHBCS), in New Hampshire, USA, initially designed to investigate associations between contaminants in private water systems and health outcomes of pregnant women and their offspring as described previously (Gilbert-Diamond et al. 2016). Briefly, participants have been recruited through selected prenatal care clinics in New Hampshire. Pregnant women were eligible for the study if they were (1) aged 18–45 years; (2) pregnant with a singleton infant; (3) literate in English; (4) using a private drinking water system as their primary drinking water source at their residence; and (5) resided at the same address since their last menstrual period with intention to remain there throughout the pregnancy. At the time of this analysis, 1329 NHBCS participants had children born between 2010 and 2015 who were age eligible for 3- and 5-year behavioral assessments performed between 2014 and 2019.

Metals Assessment in Toenail Clippings

From two to eight weeks postpartum, each participant mother was instructed to collect their infant’s nail clippings from all toes and place them in a pre-labeled collection vial (Davis et al. 2014). Infant toenails were collected at a median age of 6 weeks. This time point reflects late pregnancy to early neonatal exposure (Doherty et al. 2020). Information regarding sample preparation and measurement have been detailed elsewhere (Davis et al. 2014; Punshon et al. 2016). Briefly, toenail samples were digested via low-pressure microwave (CEM, Microwave-Assisted Reaction System) and analyzed for trace element concentrations using inductively coupled plasma mass spectrometry (ICP-MS) on an Agilent 7700x (Agilent Technologies, Santa Clara, CA).

We selected six metals [arsenic (As), copper (Cu), manganese (Mn), lead (Pb), selenium (Se), and zinc (Zn)] measured in infant toenails a priori to include in our analyses based on the reliability of toenail biomarkers and previous evidence associating perinatal exposure to these metals with neurobehavioral outcomes in our cohort (Doherty et al. 2020). All values, including machine-reported concentrations below the limit of detection (LOD), were used (Whitcomb & Schisterman 2008). Undetectable concentrations were imputed with the element-specific LOD/sqrt(2) (See Table S1 for LOD information). Quality control procedures included digestion of fortified blanks, calibration verification, and inclusion of certified reference materials. Mean recovery of standard reference material [National Institute for Environmental Sciences (Japan) Certified Reference Material No. 13, hair] was 92% (± 7%), and the average coefficient of variation between duplicates was 5% (maximum CV = 7%). The Dartmouth Trace Elements Analysis Core (Hanover, NH) performed all chemical analyses.

Neurobehavioral Assessments

Participant neurobehavior was assessed during early childhood (around 3 and 5 years). For each participant, at approximately 3 years of age, a parent or other caregiver was mailed the preschool Parent Rating Scales of the Behavior Assessment System for Children, 2nd edition (BASC-2). At approximately 5 years of age, caregivers completed these same rating scales during an in-person study visit or remotely.

Participants’ behavior was assessed using the Behavior Assessment System for Children, Second Edition–Parent Rating Scale (BASC-2 PRS). The BASC-2 PRS for preschool-aged children (ages 2–5 years) is a standardized and validated behavioral check list used to characterize the frequency of both maladaptive and adaptive behaviors as observed and reported by the child’s parent. It contains 134 questions with the relative frequency of adaptive and problem behaviors ranked using a four-point Likert scale; the results are used to generate primary scales that are then used to create composite behavior measures (Kamphaus 2015). The twelve primary scales include either maladaptive (Aggression, Anxiety, Attention Problems, Atypicality, Depression, Hyperactivity, Somatization, Withdrawal), or adaptive (Activities of Daily Living, Adaptability, Functional Communication, Social Skills). Composite scores that we used in primary analyses included: the Behavioral Symptoms Index (BSI), internalizing problems, and externalizing problems. Higher scores on the maladaptive composite scores indicate more problematic behavior. The preschool BASC-2 PRS instrument has excellent internal reliability (median coefficient α values of 0.80–0.82 among normative samples), test–retest reliabilities (median 0.76), inter-rater reliability (median 0.77), and correlations with other measures of behavior in this age group (Kamphaus 2015). The BASC-2 includes three internal validity indices which help identify assessments that were inappropriately completed, either due to likely inattention to question content (Response Pattern Index), inconsistent responses to similar questions (Consistency Index), or excessively negative responses (F-Index). Participants were excluded from the analyses if any of the BASC-2 internal validity indices were scored as extreme caution (n = 17 out of 285 (6%)).

Statistical Analyses

We calculated univariate and bivariate descriptive statistics. Metal concentrations were natural log (ln) transformed to improve normality of residuals and reduce right skewed distributions. Bivariate correlations between transformed metals were examined using Pearson’s correlation coefficients. Regression diagnostics were examined for the computed outcomes (BASC score change for BSI, internalizing, and externalizing problems) to confirm normality and homoscedasticity of residuals. For each of the three BASC-2 measures, the difference in raw composite scores (BASC score at 5 years–BASC score at 3 years) was used as our primary outcome. Raw scores, instead of t-scores, were used to incorporate information on changes that occur over development and to optimize the variability of those changes over time. Regression diagnostics supported the use of untransformed outcome variables in our analyses.

Confounder Selection

Covariates, collected from maternal questionnaires at their child’s time of birth and follow ups, were selected based on a priori evidence of potential relationships with both exposure and outcome and included child sex, the number of years between the two assessments (continuous), mother finished college (yes, no), maternal marital status (married, other), maternal smoking status during pregnancy (smoker, never smoker), maternal IQ (continuous), and maternal pregnancy 2010 Alternative Healthy Eating Index score (continuous). Maternal IQ was measured during the 5-yr in-person assessments with the Kaufman Brief Intelligence Test, 2nd edition (KBIT2) (Kaufman & Kaufman 2004). The Alternative Maternal Healthy Eating Index (AHEI-2010) is based on a food frequency questionnaire administered upon enrollment and is a measure of diet quality set by the Dietary Guidelines for Americans for a nutritionally adequate diet. The measure has 11 components for different food groups that are either recommended (e.g., fruits or vegetables) or not recommended (e.g., saturated fats or added sugars) in the daily diet and scores range from 0 to 100 with a higher score indicating a better-quality diet (Emond et al. 2018).

Multiple Imputation

Maternal IQ is a well-known confounder for children’s IQ and has been associated with exposure to environmental toxicants (Bellinger 2008; Mink et al. 2004). In our study, maternal IQ was not assessed in all mothers (27% missing). We used multiple imputation to impute missing values for maternal IQ using chained equations with the MICE package in R. The variables included in the imputation were the covariates we adjusted for in main analyses. We assumed that data missingness was random and did not depend on unobserved data. We generated 40 imputed datasets and pooled across estimates and standard errors using Rubin’s Method (Rubin 2004).

Regression Models

Because evidence exists for potential nonlinear associations as well as interactions between several of the metals in our models and neurobehavior (ATSDR 2004; Brion et al. 2020; Hubbs-Tait et al. 2009; Peters et al. 2011; Vollet et al. 2016), we first explored nonlinearity and higher order interaction using Bayesian Kernel Machine Regression (BKMR) with multiple imputation (Bauer et al. 2020a). This method pools main effect estimates and 95% confidence intervals for each metal from the 40 datasets using Rubin’s method (Rubin 2004). BKMR analyses demonstrated little evidence for nonlinearity and interaction between metals and the change in each BASC composite score between 3 and 5 years of age. Given that metals were not strongly correlated (rho = 0.05 to 0.57 with most less than 0.35), we were able to additionally confirm linear associations and no metal–metal interactions by using multivariable linear regression. We (1) compared model fit between models with an additional quadratic term for each metal to a nested model with only linear metal terms using a likelihood ratio test in the MICE R package (Buuren & Groothuis-Oudshoorn 2011); and (2) statistically tested for interaction between ln-metals by including pairwise interactions between all metals in which statistical significance was indicated by a p value of < 0.10 for the interaction term. In the final three models (one final model per outcome), multivariable linear regression was used with simultaneous adjustment for all ln–metal measures but no ln–metal interaction or quadratic terms. From using 40 imputed datasets to impute maternal IQ for 27% of our sample, we obtained pooled estimates and 95% confidence intervals by combining information from the 40 mean and variance estimates for each metal using Rubin’s Method (Rubin 2004).

Secondary Analyses

We investigated if associations between metals and change in behavior over time were driven by a single time point by estimating associations at 3 or 5 years of age at assessment separately and comparing magnitudes of effect for each metal to results from primary analyses. Additionally, we explored whether associations between infant toenail metals and behavior differed between males and females given prior evidence of sex-specific metal effects on neurobehavior (Bauer et al. 2020b) by stratifying models by sex and including an interaction term for each metal (sex*metal) in regression models. Sex-metal interaction terms were considered statistically significant at p < 0.1.

Sensitivity Analyses

We assessed the robustness of our findings in several ways. To assess the impact of baseline behavioral score, we scaled each outcome by the baseline score to compute a proportional change in score from 3 to 5 years [(BASC score at 5 years–BASC score at 3 years)/(BASC score at 3 years)] and compared patterns of metal-behavior associations to the primary analyses. Because we used raw scores in our primary analysis, we repeated main analyses using BASC-2 composite t-scores to confirm the appropriateness of our use of raw scores. In addition, findings were compared between models where adjustment for age at each assessment was used in lieu of time between assessments. Finally, we used one dataset with maternal IQ imputed and removed 16 influential points with a Cook’s distance < (4/n) (n = 252) and compared to the results from all participants (n = 268).

All statistical analyses were conducted using R (version 3.6.0; R Development Core Team).

Results

A total of 268 participants had available and valid data for BASC-2 outcomes assessed at 3 (mean ± SD: 3.3 ± 0.4) and 5 (mean ± SD: 5.2 ± 0.4) years of age and infant toenail metal measures (Fig. 1). Mothers in the sample were slightly more likely to report a higher level of education, being married, white non-Hispanic race/ethnicity, a longer duration of breastfeeding, and no first- or second-hand smoking exposure (Doherty et al. 2020). Descriptive statistics of toenail metal concentrations were similar between included participants and non-included participants (see Doherty et al. 2020 for details). About half (49.3%) of participating children were male. Mothers of participants were mostly college educated (78%), married (91.8%), did not smoke during pregnancy (97%), and, on average, were 31.2 years of age upon enrollment (Table 1). Infant toenail Mn-Pb and Cu-Pb concentrations were moderately correlated (rho = 0.57 and 0.50, respectively) with the remainder ranging from rho = 0.05–0.41 (Figure S1). Maternal characteristics and metal concentrations did not differ by child sex (Table 1).

Fig. 1.

Fig. 1

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Adjusteda associations of a log unit increase in 6-week infant toenail metal concentrations with change in BASC-2 composite raw scores between 3 and 5 years of age among all participants, boys and girls from multivariable linear regression models. aAdjusted for child sex (only all participant models), maternal education, marital status, maternal smoking during pregnancy, maternal IQ, maternal healthy eating index during pregnancy, change in age at assessment, and metals. *p < 0.05 for sex-metal interaction term

Table 1.

Maternal and child characteristics of participants in the New Hampshire Birth Cohort Study who completed repeated BASC-2 assessmentsa at 3- and 5 years of age and had available metal concentrations from infant toenails collected at age 6 weeksb

All participants (n = 268)
N(%) or mean (SD)		 Boys (n = 132)
N(%) or mean (SD)		 Girls (n = 136)
N(%) or mean (SD)
Mother graduated college
 Yes 209 (78.0%) 102 (77.3%) 107 (78.7%)
 No 59 (22.0%) 30 (22.7%) 29 (21.3%)
Married at enrollment
 Yes 246 (91.8%) 121 (91.7%) 125 (91.9%)
 No 22 (8.2%) 11 (8.3%) 11 (8.1%)
Smoked during pregnancy
 Yes 8 (3.0%) 4 (3.0%) 4 (2.9%)
 No 260 (97.0%) 128 (97.0%) 132 (97.1%)
Maternal age at enrollment (years) 31.2 (4.1) 30.9 (4.2) 31.5 (4.0)
Maternal IQ 105.7 (13.2) 106.0 (13.3) 105.4 (12.9)
Maternal healthy eating index during pregnancy 54.9 (11.3) 54.8 (11.8) 55.1 (10.9)
Child sex male 49.3% – –
Child age at 3-year assessment (years) 3.3 (0.4) 3.4 (0.5) 3.3 (0.4)
Child age at 5-year assessment (years) 5.5 (0.4) 5.5 (0.4) 5.5 (0.4)
Age change between assessment (years) 2.2 (0.4) 2.2 (0.4) 2.2 (0.4)
Behavioral symptoms index score at 3 yearsa 283.5 (32.3) 287.7 (30.3) 279.5 (33.7)
Behavioral symptoms index score at 5 yearsa 286.4 (35.4) 289.5 (37.7) 283.4 (32.9)
Behavioral symptoms index score change 2.9 (29.4) 1.8 (32.0) 3.9 (26.8)
Internalizing problems score at 3 yearsa 144.5 (18.7) 143.8 (17.8) 145.1 (19.5)
Internalizing problems score at 5 yearsa 148.6 (21.2) 147.4 (20.6) 149.8 (21.8)
Internalizing problems score change 4.1 (18.1) 3.6 (18.6) 4.7 (17.7)
Externalizing problems score at 3 yearsa 94.3 (13.7) 96.5 (12.8) 92.1 (14.3)
Externalizing problems score at 5 yearsa 99.3 (20.6) 102.5 (21.8) 96.2 (19.0)
Externalizing problems score change 5.0 (17.7) 6.0 (19.0) 4.1 (16.5)
Infant toenail metals (median (IQR))
 Arsenic (μg/g) 0.05 (0.10) 0.05 (0.09) 0.05 (0.11)
 Copper (μg/g) 4.6 (6.2) 4.6 (6.3) 4.6 (6.0)
 Manganese (μg/g) 1.0 (1.8) 1.0 (1.8) 1.1 (1.7)
 Lead (μg/g) 0.3 (0.6) 0.3 (0.6) 0.3 (0.6)
 Selenium (μg/g) 1.2 (0.9) 1.1 (0.7) 1.2 (1.1)
 Zinc (μg/g) 128.1 (102.7) 127.1 (104.8) 129.1 (92.8)
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a

Raw scores from assessments used in analyses

b

Descriptive statistics averaged across 40 multiple imputed datasets

Adjusted associations between all infant toenail metals and the change from 3 to 5-year BASC-2 composite scores varied in direction depending on the element. In general, each ln increase in toenail Cu was associated with reduced maladaptive behaviors between 3 and 5 years of age across the three BASC-2 composite scores [BSI: β = − 3.88 (95%CI: − 7.12, − 0.64); Externalizing problems: β = − 2.20 (95%CI: − 4.07, − 0.33); Internalizing problems: β = − 1.24 (95%CI: − 3.24, 0.76)]; (Fig. 1; Table S2). Exploratory sex-stratified analyses suggested that these negative associations with Cu were in boys, not girls with BSI boys: β = − 6.39 (95%CI: − 10.85, − 1.93) vs. girls: β = 1.22 (95%CI: −3.83, 6.26); Externalizing problems boys: β = − 3.62 (95%CI: − 6.25, − 1.00) vs. girls: β = 1.00 (95%CI: − 1.77, 3.77); Internalizing problems boys: β = − 2.30 (95%CI: − 4.88, 0.29) vs. girls: β = 1.26 (95%CI: − 2.10, 4.62). P values for the sex*Cu term for each respective outcome were 0.03; 0.03; 0.11 (Fig. 1; Table S2). Associations of Pb and maladaptive behaviors from 3 to 5 years were generally null in models with all participants, but among boys, Pb was associated with increased changes in maladaptive behavior, while among girls Pb was associated with reduced maladaptive behavior, although sex-specific confidence intervals were imprecise: [BSI boys: β = 4.25 (95%CI: − 0.53, 9.02) vs. girls: β = − 3.86 (95%CI: − 7.90, 0.17); Externalizing problems boys: β = 1.81 (95%CI: − 1.00, 4.62) vs. girls: β = − 2.66 (95%CI: − 4.88, − 0.43); Internalizing problems boys: β = 1.06 (95%CI: − 1.71, 3.83) vs. girls: β = − 2.86 (95%CI: − 5.57, − 0.16)]. P values for the sex*Pb term for each respective outcome were 0.008; 0.007; 0.03. Zinc was associated with greater externalizing problems over time in models with all participants (β = 3.42, 95%CI: 0.60, 6.25), and especially among boys in sex-stratified models [β = 5.21 (95%CI: 0.24, 10.19) vs. girls β = 1.49 (95%CI: − 1.85, 4.84)], however, the p value for sex*Zn interaction term was not statistically significant (p = 0.33).

We performed several secondary analyses. To investigate if associations between metals and change in behavior over time were driven by a single time point, we estimated associations with behaviors at 3 or 5 years of age separately (Figure S2). In models with all participants, the perinatal metal exposure biomarkers were not associated with BASC-2 measures at 3 years. Consistent with Cu’s association with longitudinal changes in behavior, at 5 years, it was associated with fewer externalizing behaviors: β = − 1.98 (95%CI: − 3.91, − 0.05) vs. 3-year estimate: β = 0.92 (95%CI: − 0.61, 2.45). Sex differences were also explored for these secondary analyses. The pattern of negative associations of Cu with longitudinal changes in behavior in boys and of negative associations of Pb with longitudinal changes in behavior in girls was apparent in analyses of 5-year, but not 3-year, assessments (Fig. 1; Figure S3; Figure S4). In general, the magnitude of observed associations was stronger when the change in behavior over time was the outcome as compared to outcomes assessed at a single time (3 or 5 years) (Figure S2).

Results from sensitivity analyses including (1) using proportional change for the outcome [(BASC score at 5 years–BASC score at 3 years)/(BASC score at 3 years)] (Table S3 and Figure S5), (2) using BASC-2 t-scores for the outcomes (Figure S6) and (3) adjustment for age at each assessment in lieu of time between assessments (Figure S7) were all similar to results from the primary analyses. After removing influential points (n = 16) from our dataset, results were similar to our main analyses but associations between perinatal Cu or Zn and externalizing behavior was attenuated and no longer statistically significant (Table S4).

Discussion

In our study of U.S. of children from a general population sample of New Hampshire residents, we estimated associations between metals measured in infant toenails, a measure of perinatal metal exposure, and change in maladaptive behaviors from 3 to 5 year of age using repeated measures of children’s behavior. Overall, increasing toenail Cu concentrations were associated with improved behavior over time while Zn concentrations were associated with worse behavior over time, particularly externalizing behaviors. In secondary analyses both associations were more prominent among boys as compared to girls suggesting that boys may be more sensitive to metal-neurobehavior effects over time for this outcome and age range.

By using more than one time point for the outcome, our study contributes to the understanding of chemical exposures potential to alter expected neurodevelopmental trajectories, an area of sparse research (Braun et al. 2017). Neurodevelopmental trajectories reflect the progressive advancement of cognitive and behavioral skills that occurs over time as a child matures. Exposures during critical windows of development may change a trajectory’s course toward a more maladaptive or adaptive phenotype (Bellinger et al. 2016). Alterations in developmental trajectories, in turn, can be manifested as persistent or transient (Rice & Barone 2000). Problem behaviors assessed at 3–5 years of age are relatively stable in general populations as compared to earlier time points or outcomes (Bartels et al. 2004); consequently, investigating this time frame may reduce variability from factors other than perinatal metal exposure. Characterizing maladaptive behavioral trajectories in early childhood (e.g., increasing internalizing or externalizing symptoms over time) could help identify early indicators of risk for later psychopathology such as depression, anxiety, or Attention-Deficit/Hyperactivity Disorder (ADHD) (Luby et al. 2019), potentially allowing for earlier intervention, mental health screening, or other preventative or ameliorative efforts (Wakschlag et al. 2010, 2019).

In our study, infant toenails were used to estimate perinatal exposure to metals. Research is accumulating on the use of infant toenails as biomarkers of metal exposures (Davis et al. 2014; Di Ciaula et al. 2020; Doherty et al. 2020; Karatela et al. 2020, 2022; Laue et al. 2020; Nasser Eddine et al. 2022; Rodrigues et al. 2015; Salcedo-Bellido et al. 2021; Signes-Pastor et al. 2021; Zierold et al. 2021, 2022). Toenail clippings have been suggested to be a better biomarker than fingernails or hair, given their slower growth rate and reduced risk of external contamination (Esteban & Castaño, 2009; Yaemsiri et al. 2010). Like hair and fingernails, toenails are composed of keratinous material rich in sulfhydryl groups, which bind elements, allowing toenails to be good potential biomatrices for metals and metalloid exposure. They are easy to collect and store, and may reflect long-term metals exposure due to their slow growth rate (Goullé et al. 2009; Gutiérrez-González et al. 2019; He 2011). Infant toenails begin growing in utero and grow roughly 0.1 mm/day (Goullé et al. 2009). At birth, infant toenails are on average 5.7 mm in length (Davis et al. 2014); clippings will reflect exposure timing 6 to 7 weeks prior (Laue et al. 2020). As for validity, evidence exists on the correlation between environmental/biological media and toenail concentrations of As, Mn, Se, and Zn (Gutiérrez-González et al. 2019; Rodrigues et al. 2015; Signes-Pastor et al. 2021). Among occupationally exposed welders, toenail Pb concentrations reflected exposure from 7 to 12 months previously (Grashow et al. 2014). Toenail Pb correlates moderately with fingernail Pb (rho = 0.40) and blood Pb (rho = 0.49–0.65) (Dantzer et al. 2020; A. P. Sanders et al. 2014; T. Sanders et al. 2009). In addition, toenail Pb has correlated with Pb levels in environmental dust in Pakistani urban and industrial areas (Mohmand et al. 2015) and in Zambian children living near mining industry (Ndilila et al. 2014). Currently, there is no commonly accepted biomarker for Cu environmental exposure (ATSDR 2004; Bertinato & Zouzoulas 2009; Danzeisen et al. 2017). Among the few studies using toenail Cu as a biomarker of exposure (Gutiérrez-González et al. 2019), toenail Cu has been correlated with indoor dust levels in some populations living near to Cu-related industries (Berasaluce et al. 2019) but not all (Reis et al. 2015). In children, Cu concentrations in toenails have correlated with living near a contaminated site in Uganda (Mwesigye et al. 2016) and with exposed vs. unexposed children living near waste incineration sites in Italy (Di Ciaula et al. 2020).

Four recent cross-sectional studies of school-aged children have measured multiple metals in toenails (Karatela et al. 2020; Zierold et al. 2022; Nasser Eddine et al. 2022; Di Ciaula et al. 2020). As compared to these studies, our study participants had the highest toenail Zn and Se levels, the lowest toenail Pb levels, and mid-range levels for toenail As, Cu, and Mn. Specifically, a cross-sectional study of 9-year-old Pacific Island children living in New Zealand had higher toenail Cu and Pb than our study (Cu median: ~ 17 μg/g vs. 4.6 μg/g; Pb median: ~ 0.5 μg/g vs. 0.3 μg/g) (Karatela et al. 2020). Children ages 6–14 years old living near coal-burning power plants in the USA had similar median toenail Cu and Se concentrations as compared to our study (Cu: 4.9 μg/g vs. 4.6; Se: 1.7 vs. 1.2 μg/g), lower Zn concentrations (86.7 vs. 121.8 μg/g) and higher As (1.7 vs. 0.05 μg/g), Mn (3.9 vs. 1.0 μg/g), and Pb (4.3 vs. 0.3 μg/g) concentrations (Zierold et al. 2022). Compared with our study, a cross-sectional study of Lebanese child participants had lower metal(loid) concentrations in combined finger and toenail matrices for As (0.1 vs. 0.05 μg/g), Cu (2.5 vs. 4.6 μg/g), Se (0.6 vs. 1.2 μg/g), and Zn (89.3 vs. 121.8 μg/g) and slightly higher concentrations for Pb (0.8 vs. 0.3 μg/g) and Mn (0.7 vs. 1.0 μg/g) (Nasser Eddine et al. 2022). In an Italian study of children ages 6 to 9 year olds, the referent exposure group had similar toenail metal(loid) concentrations as the present study of Cu (4.7 vs. 4.6 μg/g), Pb (0.9 vs. 0.3 μg/g), and Se (0.01 vs. 1.2 μg/g) and lower concentrations of As (0.0 vs. 0.05 μg/g), Mn (1.0 vs. 2.5 μg/g), and Zn (95.3 vs. 121.8 μg/g) (Di Ciaula et al. 2020). A prospective study from Bangladesh with known water Mn and As contamination reported higher 1-month-old infant toenail metal concentrations than our U.S. rural general population cohort (median As: Rodrigues et al.: 0.5–0.7 μg/g vs. present study: 0.05 μg/g; Mn: Rodrigues et al.: 3.3–6.6 μg/g vs. present study: 1.0 μg/g) (Rodrigues et al. 2015). Another study of school-aged children (6–13 years) living in rural Canada with elevated Mn concentrations in their drinking water had twice the toenail Mn concentrations as our study (Ntihabose et al. 2018).

Comparisons from existing literature are more difficult to find in terms of associations between metals and changes in neurobehavioral outcomes over time, especially for child maladaptive behavior. We observed a protective association of perinatal Cu with change in maladaptive behavioral symptoms from 3 to 5 years of age, which is consistent with the properties of Cu as an essential nutrient that supports brain development and possibly promotes neuroprotection (Bica et al. 2014; Hung et al. 2012; Kaler 2011). Animal research has demonstrated that Cu has many essential roles in the nervous system as an antioxidant and neuromodulator (D’Ambrosi & Rossi 2015; Gaier et al. 2013) but in excess can be detrimental to a variety of neurobehavioral functions measured at one time point including learning, spatial memory, attention, and motor coordination (Behzadfar et al. 2017; Kalita et al. 2017; Kumar et al. 2015; Pujol et al. 2016). In concordance, findings remain mixed from previous epidemiologic studies in which Cu has been associated with enhanced (Jedynak et al. 2021; Liu et al. 2018), null (Karatela et al. 2020, 2022; Polanska et al. 2017) or poor (Amorós et al. 2019; Pujol et al. 2016) neurobehavioral skills in children. The only study estimating associations between metal mixtures, including Cu and neurodevelopmental trajectories, was a recent Mexican study which reported comparable findings to ours, wherein higher second trimester maternal blood Cu was associated with improved cognition between ages 6 and 24 months, assessed with repeated measures of the Bayley Scales of Infant Development, 3rd edition (BSID-III) (Liu et al. 2018). They observed an interaction between Cu and Pb, where the positive slope of the trajectory associated with Cu was lowest at high levels of Pb as compared to low levels of Pb. Our study did not observe interactions between metals. These differences may be due to use of different biomarkers of exposure (our study: infant toenails vs. second trimester blood (Liu et al.)) as well as assessment of different outcomes at different ages (maladaptive behavior from 3 to 5 years vs. cognition changes from 6 to 24 months).

All other epidemiologic literature investigating Cu and neurodevelopment did so with one time point for neurobehavioral assessment. A prospective study of Spanish children found that first trimester serum Cu was associated with reduced cognition at 12 months and a different test of verbal ability at 5 years, although beta estimates were small in magnitude and cognitive assessments were different for the two time points (Bayley Scales of Infant Development (BSID) vs. McCarthy Scales for Children) (Amorós et al. 2019). A Polish prospective birth cohort reported null associations between maternal plasma Cu measured at multiple perinatal time points and infant cognition assessed by the BSID at 12 or 24 months of age (Polanska et al. 2017). Two cross-sectional studies using subsets from a birth cohort of Pacific Island children (ages 6–14 years) found no associations between toenail Cu and internalizing behavior but did not adjust for confounders or use multivariable regression (Karatela et al. 2020, 2022). Collectively, the aforementioned research supports the need for more studies to investigate the protective and harmful effects of Cu over time using multiple time points of the outcome and identify which Cu biomarkers may be most informative for children’s neurodevelopment.

We found that Zn was associated with an increase in maladaptive behaviors between 3 and 5 years, especially for externalizing behaviors, although after removing influential points this association was weakened but the direction of the association remained. Zn is known for its beneficial effects on neurodevelopment (Adamo & Oteiza 2010; Boscarino et al. 2021; Georgieff 2007), in which it is involved in numerous metalloenzymatic processes and modulates synaptic activity (Agency for Toxic Substances and Disease Registry (ATSDR), 2005; Georgieff 2007; Wright & Baccarelli 2007). Less research exists on the neurotoxic effects of Zn; however, in vitro studies report that Zn neurotoxicity involves modulation of neurotransmitter receptors, destruction of mitochondria, and neuronal cell death (Anderson et al. 2015; Cai et al. 2006; Dineley et al. 2003). Prior prospective studies in children assessing Zn and neurobehavior have not measured neurodevelopment across multiple time points (Horton et al. 2018; Polanska et al. 2017; Yang et al. 2013; Yousef et al. 2011). A birth cohort study in Mexico City found that increased tooth Zn, reflecting exposures from birth to 11 months of age, was associated with more internalizing symptoms, but not with externalizing symptoms or BSI among children assessed with the BASC-2 at 8 years of age (Horton et al. 2018). In contrast, our results were null for associations of perinatal metal exposures, including Zn, with change in internalizing symptoms between 3 and 5 years of age. This may suggest that in the New Hampshire child population at 3–5 years, internalizing symptoms development may not be sensitive to perinatal metals exposure. Or it may be outcome related that metal-associated changes in internalizing symptoms are more easily ascertained at older ages (Horton et al., participants’ mean age was 8 years). In terms of exposure, differences between our study and Horton et. al include biomarkers and timing of exposure (infant 6-week toenails representing perinatal exposure in our study vs. deciduous teeth reflecting postnatal exposure for the first year of life in Horton et al. 2018). While these exposure time periods overlap around the neonatal period, they otherwise reflect different exposure time frames and potential routes of exposure; our perinatal metal toenail biomarker will additionally reflect maternal exposure, upregulation of nutrient absorption, and placental transport of nutrient metals, while the tooth metal biomarker reflects postnatal exposures from birth to 11 months (Horton et al. 2018) and thereby incorporates postnatal infant hand-to-mouth behavior, introduction of solid foods and more infant formula use (Cohen Hubal et al. 2000; Ljung et al. 2011; Zota et al. 2016). Not only do metal exposures vary over the course of late pregnancy through the first of life, but so do neurodevelopmental processes. As such, susceptible time points of neurodevelopmental insult vary between these exposure time periods and could explain differences in our study findings and Horton et al. 2018.

In exploratory sex-stratified analyses, associations of metals with longitudinal changes in behavior were typically more pronounced among boys as compared to girls. Among boys, perinatal Cu was associated with reduced problem behaviors over time, while Zn and Pb were associated with increased problem behaviors over time. It has been hypothesized that sex differences in metal-neurodevelopmental associations may be consequent to sex-specific anatomical and functional differences in brain development (Llop et al. 2013). For example, brain regions during development are sexually dimorphic and estrogens, which play a role in neuroprotection, are denser in some areas of developing female brains than in males (Rao & Kölsch 2003; Scallet & Meredith 2002; Vahter et al. 2002). In addition, male and female brains may rely on different neural pathways and information processing strategies to complete the same task (Cahill 2006; Gillies et al. 2014). A study of USA children living near coal-burning power plants found sex differences in associations between toenail and fingernail Cu or Zn and increased internalizing behavior measured at 9 years of age, in which associations were pronounced among boys only (Zierold et al. 2022). The few studies investigating sex as an effect modifier in the association between Cu and neurodevelopment reported more pronounced harmful associations between Cu and neurobehavior among boys (Amorós et al. 2019; Kicinski et al. 2015; Polanska et al. 2017; Zhou et al. 2015; Zierold et al. 2022), but there is one report of stronger Cu-associated decrements in visuospatial abilities in girls compared to boys (Rechtman et al. 2020). These findings generally support our observation that behavioral changes in boys were more sensitive to Cu than in girls (albeit a protective rather than harmful effect). A prospective study in Spain assessed prenatal Cu at multiple time points of cognitive development and reported an increase of 10 μg/L of 1st trimester maternal serum. Cu was associated with poorer cognition on the BSID mental developmental index at 1 year among boys compared to improved performance in girls. Likewise at 5 years, Cu-associated decrements in cognition (using the verbal scale of the McCarthy Scales of Children’s Abilities) were displayed in boys as compared to improved performance in girls; however, sex differences were not statistically significant (Amorós et al. 2019). Mixed findings have also been reported in multiple studies for sex differences in the association between Pb and children’s neurobehavior (Bauer et al. 2020b). Although the neurotoxicity of Pb is well documented (Bellinger 2013), we unexpectedly observed protective associations between perinatal Pb and maladaptive behavior among girls only, as did other studies in this cohort (Doherty et al. 2020). This finding may reflect residual confounding or other unidentified sources of bias that may impact stratified analyses. For example, one study using three time points (12, 24, and 36 month) of the BSID reported stronger inverse associations between cord blood Pb and 36-month mental development index (MDI) among boys while null results were found in girls (Jedrychowski et al. 2009).

There are limitations for this study. The sample size was relatively small and, therefore, had limited statistical power to detect associations in sex-stratified analyses. For this reason, we presented these analyses as exploratory. We used one exposure metric for metals collected at one time point. However, unmeasured exposures at other critical developmental time periods may be more or less potent for child maladaptive behavior (Bauer et al. 2020b). This may be important especially when considering sex-specific associations. For example, a prospective Korean study reported sex- and exposure time-specific associations between blood Pb and total, internalizing and externalizing problems in 2–5-year-old children. Boys were more susceptible to prenatal Pb exposure, while girls were more susceptible to postnatal exposure (Joo et al. 2018). Using a repeat outcomes design allowed for exploration of changes in behavior over time, an outcome with potentially important functional implications but for which prior research is limited. While estimating metal-behavioral associations in early childhood is important in terms of understanding later mental health etiology, it is also possible that environmental metals are differently associated with behavioral symptoms at later time points of development (Luby et al. 2019; Wakschlag et al. 2010, 2019). For example, a US study of 6–8-year-old children also reported negative associations between Pb (measured in maternal erythrocytes) and behavioral difficulties; however, Pb was more strongly associated with behavioral difficulties among girls as compared to boys (Fruh et al. 2019). Having access to only two time points for the outcome also hindered employment of new trajectory research methods (Liu et al. 2018). Other research studies examining associations of environmental metals on an outcome with more than two time points have used linear mixed models (Claus Henn et al. 2012; Coscia et al. 2010; Liu et al. 2018) or generalized estimating equations (Jedrychowski et al. 2009; Wasserman et al. 2000) to increase statistical power and allow for an overall estimate of the exposure effect across time and estimates at individual time points. Given that our data were only from two time points, using the change in BASC scores allowed us to investigate this trajectory question using both linear models as well as to initially explore metal mixture associations using BKMR with change in score as the outcome.

One of the strengths of the study was the use of more than one time point for the outcome. Our study contributes to understanding the potential role of metal exposures on neurodevelopmental trajectories, an area of sparse research (Braun et al. 2017). Our findings support the potential for changes in behavior over time in young children to be informative for chemical exposure effects. In this context, we were able to identify metals that may improve, and others that may impair, behavioral progression in young children. If replicable, such findings could help guide interventions. In addition, given the potential for maladaptive behavioral trajectories in early childhood (e.g., our study’s observation of metal-associated increasing externalizing symptoms over time) to be an early indicator of risk for later psychopathology such as ADHD (Luby et al. 2019), assessment of behavioral changes over time would allow for earlier intervention, mental health screening, or other preventative or ameliorative efforts (Wakschlag et al. 2010, 2019).

Conclusions

We used repeated measures of maladaptive behavior in a cohort of typically developing children to investigate whether perinatal exposure to metals may change behavior between the ages of 3 and 5 years. Overall, toenail Cu concentrations were associated with reduced maladaptive behaviors over time while toenail Zn concentrations were associated with increased maladaptive behaviors over time. In secondary analyses, both associations were more prominent among boys as compared to girls suggesting that boys were more sensitive to metal-neurobehavior effects over this time period, supporting the call for exploration of sex differences in these associations to protect children’s health. Our findings support the need for future research to investigate environmental influences on the progression of childhood neurobehavioral development.

Supplementary Material

Supplementary Material

Acknowledgements

The authors would like to acknowledge the New Hampshire Birth Cohort Study participants and research staff for their contributions to this research.

Funding

This work was supported in part by grants from the National Institute of Environmental Health Sciences (P01ES022832, P20ES018175, P42ES007373), the National Institute of General Medical Sciences (P20GM104416), and the U.S. Environmental Protection Agency (RD-83544201) and the National Cancer Institute T32CA134286.

Footnotes

Supplementary Information The online version contains supplementary material available at https://doi.org/10.1007/s12403-023-00543-2.

Competing interests The authors state they have no conflicts of interests.

Ethics Approval All participants provided written, informed consent and consent to publish on their results upon enrollment. All protocols were approved by the Dartmouth College Institutional Review Board (Dartmouth Committee for the Protection of Human Subjects Approval Reference #20844).

Data Availability

Use of the data may be possible under certain conditions by contacting the New Hampshire Birth Cohort Study Principal Investigator: Margaret Karagas, PhD, (margaret.r.karagas@dartmouth. edu).

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Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

Supplementary Material
NIHMS1899058-supplement-Supplementary_Material.docx (684.1KB, docx)

Data Availability Statement

Use of the data may be possible under certain conditions by contacting the New Hampshire Birth Cohort Study Principal Investigator: Margaret Karagas, PhD, (margaret.r.karagas@dartmouth. edu).

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