Previous studies linking prenatal air pollution to adverse birth outcomes may be confounded by unmeasured familial factors, potentially leading to biased effect estimates and misleading public health recommendations. This sibling-matched case-control study re-examined associations between six criteria air pollutants and preterm birth (PTB), low birth weight (LBW), and small-for-gestational-age (SGA). Associations were assessed using both a sibling-matched generalized linear mixed model (estimating subject-specific conditional effects) and conventional unmatched logistic regression (estimating population-averaged marginal effects) for comparison. We analyzed 194 284 mother-infant pairs (97 142 sibling pairs) from Nanning, China (2016–2022). Pollutant data were sourced from the high-resolution CHAP dataset. In sibling-matched analyses, first-trimester NO2 exposure increased PTB risk (OR = 1.004), while exposures to SO₂ (ORfirst=1.009, ORsecond=1.009, ORthird=1.010) and CO (ORsecond=1.163, ORthird=1.157) in specific trimesters were associated with elevated SGA risk. Some significant associations observed in unmatched designs (e.g., CO exposure across trimesters and PTB) were attenuated to non-significance after sibling matching. Furthermore, unmatched designs generally overestimated pollutant-PTB associations while underestimating pollutant-SGA links, with the largest between-model differences in effect estimates for CO. Prenatal exposure to NO₂, SO₂, and CO is associated with increased risks of PTB and SGA. Conventional unmatched study may lead to divergent effect estimates due to both unmeasured familial confounding and inherent mathematical differences between statistical models, underscoring the critical need to control for familial confounders in environmental epidemiological studies. Our findings highlight the importance of methodological refinement in environmental risk assessment to inform evidence-based air quality policies.
The relationship between long-term exposure to air pollution and the risk of neurodegenerative diseases has drawn increasing attention. However, the relative effects of various pollutants and the potential role of systemic inflammation remain unclear. This study aims to explore the association between various air pollutants and the comprehensive risk score of neurodegenerative diseases in the middle-aged and elderly population in China, and to examine the effect modification of baseline high-sensitivity C-reactive protein (hs-CRP) and white blood cell count (WBC). The data were sourced from the China Longitudinal Study of Health and Retirement (CHARLS) and the National Earth System Science Data Center. The average concentrations of fine particulate matter (PM2.5), inhalable particulate matter (PM10), nitrogen dioxide (NO2), and ozone (O3 ) from 2012 to 2015 were obtained through processing by the ArcGIS platform. The outcome was the comprehensive risk score and its ternary scale constructed by grip strength, the Central Depression Scale (CES-D-10), the Mini-Mental State Examination (MMSE), and instrumental activities of daily living (IADL) at the follow-up in 2015. A two-stage analysis was adopted: Firstly, multiple linear regression (OLS) was used to analyze the association between pollutants and continuous scores; Then, ordered Logistic regression was applied. After adjusting for the baseline score in 2011, age, gender, education, urban and rural residence, and the number of chronic diseases, the association between pollutants and risk levels was analyzed, and age stratification analysis of pollutants was conducted (30-59 years old, 60-74 years old, ≥75 years old). The effect modification effect was examined by incorporating the interaction term between pollutants and baseline inflammatory markers into the model. OLS regression analysis showed that long-term PM2.5 exposure was significantly associated with an elevated comprehensive neurodegenerative risk score (adjusted β = 0.010, 95
Human biomonitoring studies of per- and polyfluoroalkyl substances (PFAS) have typically focused on legacy PFAS. Data for alternative and precursor PFAS are emerging, but are still scarce. These data are critical for assessing exposure and human health risk. We measured serum concentrations of 40 PFAS among 2,775 premenopausal participants from the CARTaGENE cohort (Phase A: 2009–2010; Phase B: 2013–2014). We examined differences in geometric mean serum concentrations of PFAS with > 60
Prenatal and postnatal exposure to air pollution has been associated in multiple epidemiological studies with adverse neurodevelopmental outcomes in children, including in New York City cohorts. Studies are lacking on changes in associations between air quality and neurodevelopmental outcomes over recent decades that have been marked by improvement in air quality. Here we investigated whether decreased prenatal exposure to air pollution, previously linked to clean air and climate policies in New York City, benefited cognitive development in children participating in cohort studies of the Columbia Center for Children’s Environmental Health between 1998 and 2020. Information from such studies can benefit public health policy. We utilized data on prenatal exposure to fine particulate matter (PM2.5), nitrogen dioxide (NO2) and polycyclic aromatic hydrocarbons (PAH) in successive longitudinal cohort studies. PM2.5 and NO2 were available in the first two cohorts (1998–2016); PAH were monitored in three cohorts (1998–2020). Children were assessed for cognitive development at ages 1, 2, and 3 using the Bayley Scales of Infant and Toddler Development (BSID-II), which provided Mental Development Index (MDI) scores. To test associations between air pollutant exposures and MDI, we used linear regression, adjusting for demographic and other factors that contribute to neurodevelopment and/or changed over time. Across the cohorts, levels of prenatal exposure to PM2.5, NO2, and PAH decreased significantly; and there was a significant upward trend in MDI scores (N = 1109). Overall, when combining samples from cohorts, the pollutants were significantly and inversely associated with MDI at 1, 2, and 3 years. In the cohort-specific analyses, significant inverse associations between prenatal exposure to PM2.5, NO2, PAH and 3-year MDI were seen in the larger initial cohort (N > 700, enrolled between 1998 and 2006) that experienced the highest exposure and the greatest decrease in levels of air pollutants. Weaker, albeit inverse, associations were observed between PM2.5 and cognitive development of children in the later cohort (2008–2016) who experienced lower exposure. These results indicate that, during the period of the largest reduction in air pollution levels, previously associated with air pollution and climate policies enacted in NYC, children’s scores on cognitive tests improved, providing new evidence that such policies are beneficial to children’s neurodevelopment.
Prenatal exposure to per- and polyfluoroalkyl substances (PFAS) may be associated with child neurodevelopment, but evidence based on fetal-proximal exposure biomarkers, mixture effects, and domain-specific outcomes remains limited. In the Shanghai Birth Cohort (n = 1,668 mother-child pairs), we quantified 32 PFAS compounds in umbilical cord blood and assessed neurodevelopment at 24 months using the Bayley Scales of Infant and Toddler Development, Third Edition (BSID-III). Associations were evaluated using adjusted single-pollutant regression models as the primary analyses. Developmental risk defined as BSID-III composite score < 90 was evaluated as a complementary outcome, and weighted quantile sum (WQS) regression was used to evaluate PFAS mixture associations. Nineteen PFAS compounds had detection rates greater than 65
Dietary exposure to mycotoxins—including aflatoxins (AFs), ochratoxin A (OTA), and citrinin (CIT)—represents an important health risk, particularly in low-resource settings with widespread food contamination. This study investigates mycotoxin exposure among 719 participants (433 women and 286 children) of a cluster-randomized trial in rural Bangladesh, using residual blood samples collected during the 2019 endline survey. A total of 712 whole blood and 578 serum samples were analyzed by ultra-high-performance liquid chromatography-tandem mass spectrometry (UHPLC-MS/MS). Serum aflatoxin B1 (AFB1)-lysine adducts were quantified following enzymatic digestion and solid-phase extraction. To evaluate potential health risks, we estimated probable daily intake (PDI) from blood concentrations of frequently detected mycotoxins. All whole blood samples contained at least two mycotoxins, and 84
Wildland fires are a significant source of pollution that can cause sudden changes in ground-level ambient fine particulate matter (PM2.5), an exposure that has been associated with gestational blood pressure increases. However, estimating the health risks specific to wildland fire smoke PM2.5 is often encumbered by limitations to smoke plume modeling. We utilized a novel approach to estimate and characterize wildland fire smoke PM2.5 in Reno, Nevada, USA, an area prone to seasonal smoke from wildland fires. Daily, 24-h averaged, plume-specific wildland fire smoke PM2.5 concentrations were estimated at two air quality monitoring stations, and each plume was categorized by both the intensity of the source fire (high vs. low intensity) and the primary fuel type (forest, shrub/scrub, grassland, and other). Using electronic medical records (2012–2019), we identified a set of healthcare encounters of pregnant individuals, assigned these encounters to the air quality monitor closest to the maternal residential address at the time of the encounter and estimated the acute effects (0 to 3 day lag periods) of wildland fire smoke PM2.5 on maternal systolic and diastolic blood pressure measures across gestational periods using a multi-level linear regression model. We evaluated 132,570 clinical encounters with a blood pressure measurement over 22,399 pregnancies (median 4.0 measures per pregnancy). Overall, we found null associations between wildland fire smoke PM2.5 and maternal blood pressure, regardless of the lag period. However, there was evidence that suggested associations could differ between gestational exposure periods, as positive associations not meeting statistical significance criteria were observed for almost all first trimester exposures. Associations did not differ by fire intensity or fuel type. We did not find evidence for short-term associations between wildland fire smoke PM2.5 and maternal blood pressure. Similar to other studies in the field, challenges to modeling smoke plumes and subjects altering their behavior during smoke events may be impacting the analyses.
Plasma per- and polyfluoroalkyl substances (PFAS) are associated with immune dysfunction, including childhood antibody response. We evaluated whether first trimester maternal plasma PFAS concentrations are associated with mid-childhood MMR (measles, mumps, rubella) and DTaP (diphtheria, tetanus, pertussis) antibody titers. We measured six PFAS (EtFOSSA, MeFOSSA, PFHxS, PFNA, PFOA, PFOS) in first trimester plasma from participants in the longitudinal Project Viva cohort, recruited 1999–2002 in eastern Massachusetts. We measured mid-childhood plasma MMR and DTaP antibody titers. We restricted the analytical sample to children fully vaccinated, according to 2007 United States Center for Disease Control guidelines and used covariate-adjusted quantile g-computation and regression analyses to estimate associations (n = 333–416). Median [interquartile range (IQR)] age at antibody titer blood draw was 7.7 years (7.4, 8.4), and children received their most recent MMR or DTaP dose at median (IQR) 4.3 years (4.1, 5.0). The PFAS mixture was associated with lower antibody titers, except for measles, although none of the associations reached statistical significance. A one unit (ng/mL) increase in EtFOSSA was associated with higher measles antibody titers [β = 0.02, 95
Bisphenol A (BPA) is a high production volume chemical that has been used for decades in numerous consumer and industrial applications. Daily exposure to BPA is likely; it is readily detected in >90
Childhood lead exposure remains a significant public health concern, particularly in urban settings with persistent socioeconomic disadvantage. Although prior studies have linked lead exposure to adverse neurodevelopmental outcomes, evidence using clinically diagnosed neurobehavioral disorders at contemporary low blood lead levels (BLLs) is limited. We conducted a retrospective cohort study of children aged 11 years or younger who received care through the Temple University Health System in Philadelphia, Pennsylvania, between 2010 and 2020. BLLs were obtained from electronic health records and analyzed as continuous measures and dichotomized at 3.5 µg/dL. Attention-deficit/hyperactivity disorder (ADHD) and conduct disorders were identified using international classification diagnoses (ICD) codes, and only incident diagnoses occurring after blood lead measurement were considered. Multivariable logistic regression models were fit adjusted for individual- and neighborhood-level sociodemographic factors selected using a directed acyclic graph framework. Sex-stratified analyses were conducted to assess effect modification. Among 13,989 children included in the ADHD analysis, 751 (5.4
Abstract Background Gulf War Illness (GWI) has been identified in more than 20% of Veterans following military service in the 1990–1991 Gulf War (GW). Unfortunately, after several decades, GWI pathogenesis remains unclear and the patterns of GWI symptom co-occurrence are still poorly understood. Methods This population-based case–control study included 34,179 (16% females; 34% GW deployed; mean age 61 years) Veterans enrolled in the Million Veteran Program (MVP) who were active-duty military personnel in 1990–1991. We analyzed 14 GWI symptoms in GW-deployed and non-deployed GW-Era Veterans. Multivariable generalized linear models were used to estimate GWI symptom associations with demographic factors and deployment status. Correlation, factor, and network analyses were performed to examine the underlying structure of GWI symptoms. In addition, polygenic risk score and one-sample Mendelian randomization analyses were conducted to evaluate the genetically inferred effects of health-related traits on symptom factors. Results Among 14 GWI symptoms, joint pain had the highest prevalence in both GW deployed (86%) and non-deployed GW-Era Veterans (79%). The median age of symptom onset ranged from 38 to 46 years among deployed Veterans and from 45 to 54 years among non-deployed Veterans. Factor analysis identified a five-factor latent structure as the best-fit model for GWI symptoms, and latent class analysis classified Veterans into seven symptom classes. The network of GWI symptoms showed that fatigue had the largest closeness and betweenness and had more edges in deployed Veterans. Younger age, female sex, non-European descent, lower educational attainment, enlisted rank, and GW deployment, as well as multiple GW-related exposures in deployed Veterans, were associated with increased GWI symptom burden. Genetic liability to multiple health-related outcomes, including type 2 diabetes (T2D) and posttraumatic stress disorder (PTSD), showed putative causal effects on GWI-symptom factors, with the T2D effect being larger in deployed Veterans and the PTSD effect being larger in non-deployed Veterans. Conclusions The present findings demonstrate differences in symptom onset between deployed and non-deployed GW Veterans. They also reinforce the importance of symptom clusters of relevance to GWI, associations between deployment-specific exposures and symptom burden, and different genetic linkages underlying symptoms for deployed and non-deployed groups. Trial registration Not applicable.
Air pollution is increasingly recognized as a risk factor for progression of kidney disease; however, few studies have examined its impact among patients with primary glomerular disorders. To address this knowledge gap, we previously reported positive associations between fine particulate matter ≤ 2.5μm in aerodynamic diameter (PM2.5) and black carbon with kidney disease progression in an observational cohort of children and adults (n = 925) with primary glomerular diseases, namely minimal change disease, focal segmental glomerulosclerosis, membranous nephropathy, and IgA nephropathy. In the current study, we leverage the same cohort to (1) identify additional air pollutants that may be associated with kidney disease progression using data from the National Center for Atmospheric Research (NCAR); (2) determine whether the association between baseline air pollution exposure and kidney disease progression is maintained over a longer follow-up period; and (3) assess whether associations identified in our previously published findings remain when using NCAR pollutant data. In this retrospective cohort study, we obtained air pollutant concentration data from NCAR based on participant residential census tract at enrollment. For each census tract and pollutant, we aggregated daily pollutant concentrations to annual averages. We used Cox proportional hazards models to estimate associations between average baseline pollutant exposure and time to kidney disease progression, defined as a 40
Humans encounter a wide range of natural and synthetic chemicals throughout their lifespan and these exposures have a complex impact on health outcomes. Epidemiological studies provide compelling evidence linking chemical exposure to neurological disorders and various cancers. However, establishing causality between specific pollutants, or their mixtures, and health outcomes is challenging due to long disease latencies. Functional biomarkers in exposed subjects provide rapid predictions of the impact of environmental exposures. Notably, genome alterations, including DNA breaks and epigenetic modifications, are hallmark features of cancers, premature aging, and neurological diseases. Biomonitoring studies show that individual chemical exposures are specific. These differences highlight disparities across socioeconomic groups. They also present opportunities to associate specific environmental factors and disease development, as well as socioeconomic determinants of exposures and their consequences. This review focuses on biomonitoring environmental chemical exposures and their effects with hair and hair follicles. Pollutants detected in the hair matrix reflect cumulative internal exposures over specific time periods, while biomarkers can be analyzed in plucked hair follicles. These mini organs contain proliferating and stem/progenitor cells, which are critical to understanding the onset of various diseases. We propose an integrated approach that combines socioeconomic indicators, chemical analyses in hair, and biological assessments of matching hair follicles to evaluate the exposome and its effects on the genome. We discuss the state of the art of these approaches, their current limitations, and the perspectives they offer.
Prenatal depression shows diverse patterns in severity and progression. While air pollution has been linked to depression risk, its impact on the course of prenatal depression remains understudied. The study objectives were to (1) identify distinct trajectories of depressive symptoms across pregnancy, and (2) to evaluate whether preconception and early-pregnancy air pollution exposure impacts membership in trajectory groups. This study followed 542 predominantly low-income Hispanic/Latina participants in the MADRES cohort. We assessed depressive symptoms using the Center for Epidemiologic Studies-Depression (CES-D) scale at 1st, 2nd, and 3rd trimester visits. Daily residential concentrations of PM2.5, PM10, NO2, and O3 were estimated using inverse-distance squared spatial interpolation from monitoring data. We used latent growth mixture modeling (LGMM) to identify trajectory classes and multinomial logistic regression to estimate adjusted relative risk ratios (RRRs) of membership in each class relative to the lowest group with averaged air pollution levels over preconception and early pregnancy. We identified four distinct trajectories: moderate-to-high symptoms (7.4
Maternal per- and polyfluoroalkyl substances (PFAS) exposure has been linked to adverse health effects on offspring, but the mechanisms remain unclear. The present study investigates the relationship between maternal PFAS exposure and the expression of placental cytochrome P450 enzymes (CYP19A1, CYP2J2, and CYP2E1), and explores the potential role of these enzymes in linking maternal PFAS exposure to offspring development. We included 350 mother-infant pairs from the Jiashan birth cohort. Thirteen PFAS compounds were measured in maternal plasma collected at 8–16 weeks of gestation, while the expression levels of the three CYP genes were quantified in placental tissues collected at delivery. Offspring weight and length were measured at birth and at 1, 3, 6, 8, 12, and 24 months of age, and their ponderal index (PI) was computed. Multivariable linear regression was used to examine associations between plasma concentrations of individual PFAS and placental CYP gene expression. Quantile-based g-computation was used to examine the association of the PFAS mixture with placental CYP gene expression. A linear mixed model was used to examine the associations of maternal PFAS and placental CYP expression levels with repeated PI measurements from birth to 24 months. Multilevel mediation analysis was conducted to explore the potential mediating role of CYP genes. Consistent inverse associations between maternal PFAS exposure and the three placental CYP genes expression in female placentas were observed. Specifically, statistically significant decreases were observed in the associations between all PFAS compounds and CYP2J2 expression with β- estimates for the highest exposure versus the lowest from -0.255 to -0.174, as well as between the highest exposure of perfluorotridecanoic acid (PFTrDA) and CYP19A1 expression (β = -0.279, 95
Longitudinal biomonitoring studies during preconception, pregnancy and early childhood are highly valuable tools for assessing environmental chemical exposures during sensitive windows and their effects on health and development. For the past 15 years, the Maternal-Infant Research on Environmental Chemicals (MIREC) Research Platform has been Canada's flagship study of the long-term effects of early life exposure to environmental chemicals. In light of the evolving scientific and legislative landscapes and need to address emerging research questions, MIREC Platform researchers at Health Canada consulted with scientific investigators of other cohort studies to inform the development of a future preconception or pregnancy longitudinal biomonitoring study. This effort included 1) hybrid consultation meetings on Dec 6, 2024 (Toronto, ON) and Jan 21, 2025 (Ottawa, ON) and 2) a virtual seminar series from October 2024 to June 2025 hosted by the Health Canada MIREC team. Our objective here is to share lessons learned from this consultation. We report on key lessons learned related to the themes of: 1) participant engagement, recruitment and retention, 2) validity and causal inference, and 3) study longevity. While the ultimate goal of this consultation was to inform future longitudinal biomonitoring studies in Canada, the content is largely generalizable and relevant to others planning, modifying, or evaluating observational research in reproductive and environmental epidemiology.
The exposome encompasses all environmental exposures humans undergo from conception. We frame exposome studies according to four broad aims essential for environmental health research. First, a descriptive aim, consisting in assessing exposure patterns, including correlations between exposures and their within-subject variability. This descriptive aim includes “environmental justice” studies of associations between the exposome and sociodemographic factors. A second – etiologic – aim is to describe the subclinical and clinical effects of the exposome (hazard identification). A third aim is the quantification of the exposome health impact (e.g., in life years lost at the population level) and the ranking of exposures in terms of population disease burden (exposome disease burden or risk assessment). A fourth (intervention) aim corresponds to the identification of approaches to modify the exposome, as a way to improve health. With the large increase in the number of chemicals quantifiable in a small volume of a biospecimen, the main challenge of descriptive exposome studies is population representativeness. Regarding the etiologic aim, by simultaneously showing associations of a given biological parameter with hundreds of exposures, exposome studies effectively limit publication bias and selective reporting of results, which are a strong concern in single-exposure studies. They nonetheless face several challenges, related to the curse of dimensionality, the correlation between exposures, the breadth vs. depth tension… Increasing the number of exposures considered implies to simultaneously increase study population sizes, aiming for cohorts of 100,000 subjects or more. The accuracy of exposure assessment should simultaneously be improved, e.g., by collecting repeated biospecimens within each subject, assessing exposures at various ages and decreasing limits of quantification. Classical exposome statistical designs such as ExWAS (exposome-wide association studies) are subject to a high false positive rate. Models adapted to sparse data allowing to control for confounding by co-exposures appear more efficient. The results from exposome descriptive and etiologic studies can be combined to feed exposome disease burden assessments. These can in turn help prioritize exposures for which efficient interventions need to be identified. The approaches outlined in this work could help exposome research contribute more strongly to environmental health research and to the associated risk management decisions.
Radon is a known environmental carcinogen associated with thousands of lung cancers each year. Understanding characteristics associated with testing is critical to design interventions to increase acceptance and promote mitigation. The objective of this study was to evaluate socioeconomic factors and cancer beliefs associated with previous home air radon testing, mitigation, and—for those who had not yet tested—acceptance of a free test. A population-based survey was administered to adults residing in New Hampshire and Vermont to understand previous home air radon testing and mitigation patterns, and among those who had not previously tested, acceptance of information on how to request a free test. The proportions of test kits requested and returned are reported. Of 1,717 survey respondents, 513 (29.7
Taiwan is one of the fastest-warming regions globally. As climate change intensifies, understanding how vulnerability influences health outcomes critical. This study aimed to identify regional vulnerability factors for temperature-related respiratory mortality and effective region-specific adaptation policies. A two-stage time-series study was conducted using daily respiratory mortality counts aggregated by county and day. This study employed a distributed lag non-linear model to estimate the temperature-attributable mortality burden from respiratory diseases across all counties and cities in Taiwan. A two-stage meta-analysis was conducted to estimate temperature–mortality associations and quantify cold- and heat-related mortality burdens by county. Meta-regression was used to identify regional vulnerability factors modifying temperature-related mortality risk, and geographically weighted regression (GWR) was applied to characterize the spatial heterogeneity of these effects across counties. Cold exposure was linked to a higher burden of respiratory disease mortality (attributable fraction [AF]: 2.03
Abstract Fetal growth is a critical health outcome influenced by prenatal exposure to environmental chemicals, particularly endocrine-disrupting chemicals (EDCs). Studies have shown that pregnant women are simultaneously exposed to multiple chemicals, illustrating the need for methods that can examine the health effects of cumulative exposures. We compared four statistical methods—Principal Component Analysis (PCA), k-means clustering, Weighted Quantile Sum Regression (WQSR), and Bayesian Kernel Machine Regression (BKMR), —to identify associations between the mixture of chemicals and birth weight z-scores, including phthalate metabolites, bisphenol A, bisphenol A alternatives, triclosan, organophosphate pesticides, arsenic species, glyphosate and its breakdown product aminomethylphosphonic acid (AMPA), solvent metabolites, organophosphate flame retardants, fluoride, polybrominated diphenyl ethers, polychlorinated biphenyls (PCBs), organochlorine pesticides (OCs), cotinine, per- and polyfluoroalkyl substances (PFAS), and five metals. Our complete case analysis investigated the potential effects of a mixture of 46 chemicals on birth weight z-score, using 1127 mother-infant pairs from the Maternal-Infant Research on Environmental Chemicals (MIREC) study. PCA showed a significant inverse association between birth weight z-score and a component with loadings highest for PCBs (-0.035, 95%CI: (-0.068, -0.002)) using multivariable linear regression. The k-means analysis revealed distinct clusters of chemical profiles associated with lower birth weight z-score (-0.17, 95% CI: (-0.34, -0.01)) using multivariable linear regression, and primarily composed of arsenic (As), mercury (Hg), lead(Pb), ΣOC Chlordane and the PCBs, WQSR showed an inverse association with the overall mixture index (-0.065; CI: (-0.171, 0.04) driven mostly by Aroclor 1260, ΣOC Chlordane, glyphosate, and PCB180. BKMR highlighted that the birth weight z-score was 0.054 (-0.100, 0.209)when all chemicals in the 25thpercentile were compared to their medians, which decreased to -0.04 (-0.219, 0.14)when all chemicals in the 75th percentile were compared to their median values. After stratification by infant sex, associations tended to be larger in magnitude in females. We observed, according to all four approaches, that ΣOC Chlordane, ΣOC Insecticides, Aroclor 1260, dimethylarsinic acid, Pb, PCB170 and PCB180 were most often associated with decreased birth weight. These findings underscore the potential adverse effects of chemical mixtures on birth weight, the usefulness of using multiple methods, and suggest the need for continued research for evaluating cumulative environmental exposures in prenatal health outcomes.
