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Joint and independent neurotoxic effects of early life exposures to a chemical mixture: A multi-pollutant approach combining ensemble learning and g-computation.

ABSTRACT: Background:Exposure to mercury (Hg) is associated with adverse developmental effects. However, Hg occurs with a multitude of chemicals. We assessed the associations of developmental exposure to multiple pollutants with children's neurodevelopment using a novel approach. Methods:Hg, polychlorinated biphenyls (PCBs), and perfluoroalkyl substances were measured in maternal and children's blood at 5-years (n=449 and 419). At 7-years, children were administered Boston Naming Test (BNT) and the Strengths and Difficulties Questionnaire (SDQ). We used the G-formula combined with SuperLearner to estimate independent and joint effects of chemicals at both ages. We constructed flexible exposure-response relationships and assessed interactions. Results:Most chemicals showed negative relationships with BNT scores. An inter-quartile range (IQR) increase in maternal Hg and perfluorooctanoic acid (PFOA) was associated with 0.15 standard deviation [SD] (95% Confidence Interval [CI]: -0.29,-0.03) and 0.14 SD (95%CI: -0.26,-0.05) lower scores in BNT, whereas a joint IQR increase in the mixture of chemicals was associated with 0.48 SD (95%CI: -0.69,-0.25) lower scores in BNT. An IQR increase in PFOA was associated with 0.11 SD (95%CI: 0.02,0.26) higher total SDQ difficulties scores. Maternal ?PCBs concentrations were associated with lower SDQ scores (?=-0.09 SD; 95%CI: -0.19,0), whereas 5-years ?PCBs showed a negative association (?=-0.09 SD; 95%CI: -0.21,0). Finally, a joint IQR increase in the mixture was associated with 0.22 SD (95%CI: 0.04,0.4) higher SDQ scores. Conclusions:Using a novel statistical approach, we confirmed associations between prenatal mercury exposure and lower cognitive function. The potential developmental effects of PFASs need additional attention.

SUBMITTER: Oulhote Y

PROVIDER: S-EPMC7015154 | biostudies-literature | 2019 Oct

REPOSITORIES: biostudies-literature

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Joint and independent neurotoxic effects of early life exposures to a chemical mixture: A multi-pollutant approach combining ensemble learning and g-computation.

Oulhote Youssef Y Coull Brent B Bind Marie-Abele MA Debes Frodi F Nielsen Flemming F Tamayo Ibon I Weihe Pal P Grandjean Philippe P

Environmental epidemiology (Philadelphia, Pa.) 20191001 5

<h4>Background</h4>Exposure to mercury (Hg) is associated with adverse developmental effects. However, Hg occurs with a multitude of chemicals. We assessed the associations of developmental exposure to multiple pollutants with children's neurodevelopment using a novel approach.<h4>Methods</h4>Hg, polychlorinated biphenyls (PCBs), and perfluoroalkyl substances were measured in maternal and children's blood at 5-years (n=449 and 419). At 7-years, children were administered Boston Naming Test (BNT) ...[more]

PMID: 32051926

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Project description:BACKGROUND:Gestational diabetes mellitus (GDM) is associated with increased availability of glucose and macronutrients in fetal circulation and macrosomia. Therefore, the role of GDM in the association between metabolism-disrupting chemicals and birth size deserves attention. OBJECTIVE:We examined whether GDM may mediate or modify the associations between maternal environmental pollutant exposures and offspring birth size measures. METHODS:We analyzed 604 Faroese pregnant women and their offsprings born in 1997-2000. Maternal pregnancy serum concentrations of organochlorine compounds (OCs: polychlorinated biphenyl (PCB) congeners and dichlorodiphenyldichloroethylene (DDE)), and five perfluoroalkyl substances (PFASs), and hair and cord blood mercury concentrations were measured. We used regression (single-pollutants) and structural equation models (SEMs) (multiple-pollutant analyses using latent constructs of OCs, PFASs and mercury) to estimate the associations with GDM and birth size measures, accounting for mediation and/or effect modification by GDM. RESULTS:Serum-DDE and hair-mercury concentrations were associated with GDM (adjusted OR per concentration doubling: 1.29; 95% CI: 0.94, 1.77 for DDE, and 0.79; 95% CI: 0.62, 0.99 for mercury), but in multiple pollutant-adjusted SEMs only a positive association between OC exposure and GDM remained significant (change in GDM odds per OC doubling: 0.45; 95% CI: 0.05, 0.86). PCB and overall OC exposure were positively associated with head circumference (SEM; mean change per OC doubling: 0.13cm; 95% CI, 0.01. 0.25). Overall PFAS exposure was inversely associated with birth weight (SEM; mean change per PFAS doubling: -169g; 95% CI: -359, 21), and for many single-PFASs we found a pattern of inverse associations with birth weight and head circumference in boys, and positive or null associations in girls. None of the environmental pollutants was associated with offspring length. GDM neither modified nor mediated the associations with birth size measures. CONCLUSIONS:We found associations with GDM and offspring birth size to be specific to the environmental pollutant or pollutant group. Associations with birth size measures appear to be independent of GDM occurrence.

Project description:BACKGROUND:Volatile organic compounds (VOC), which include many hazardous chemicals, have been used extensively in personal, commercial and industrial products. Due to the variation in source emissions, differences in the settings and environmental conditions where exposures occur, and measurement issues, distributions of VOC concentrations can have multiple modes, heavy tails, and significant portions of data below the method detection limit (MDL). These issues challenge standard parametric distribution models needed to estimate the exposures, even after log-transformation of the data. METHODS:This paper considers mixture of distributions that can be directly applied to concentration and exposure data. Two types of mixture distributions are considered: the traditional finite mixture of normal distributions, and a semi-parametric Dirichlet process mixture (DPM) of normal distributions. Both methods are implemented for a sample data set obtained from the Relationship between Indoor, Outdoor and Personal Air (RIOPA) study. Performance is assessed based on goodness-of-fit criteria that compare the closeness of the density estimates with the empirical density based on data. The goodness-of-fit for the proposed density estimation methods are evaluated by a comprehensive simulation study. RESULTS:The finite mixture of normals and DPM of normals have superior performance when compared to the single normal distribution fitted to log-transformed exposure data. The advantages of using these mixture distributions are more pronounced when exposure data have heavy tails or a large fraction of data below the MDL. Distributions from the DPM provided slightly better fits than the finite mixture of normals. Additionally, the DPM method avoids certain convergence issues associated with the finite mixture of normals, and adaptively selects the number of components. CONCLUSIONS:Compared to the finite mixture of normals, DPM of normals has advantages by characterizing uncertainty around the number of components, and by providing a formal assessment of uncertainty for all model parameters through the posterior distribution. The method adapts to a spectrum of departures from standard model assumptions and provides robust estimates of the exposure density even under censoring due to MDL.

Project description:BackgroundResidential natural gas cooking burners (NGCBs) can emit substantial quantities of pollutants, and they are typically used without venting range hoods.ObjectiveWe quantified pollutant concentrations and occupant exposures resulting from NGCB use in California homes.MethodsA mass-balance model was applied to estimate time-dependent pollutant concentrations throughout homes in Southern California and the exposure concentrations experienced by individual occupants. We estimated nitrogen dioxide (NO2), carbon monoxide (CO), and formaldehyde (HCHO) concentrations for 1 week each in summer and winter for a representative sample of Southern California homes. The model simulated pollutant emissions from NGCBs as well as NO2 and CO entry from outdoors, dilution throughout the home, and removal by ventilation and deposition. Residence characteristics and outdoor concentrations of NO2 and CO were obtained from available databases. We inferred ventilation rates, occupancy patterns, and burner use from household characteristics. We also explored proximity to the burner(s) and the benefits of using venting range hoods. Replicate model executions using independently generated sets of stochastic variable values yielded estimated pollutant concentration distributions with geometric means varying by <10%.ResultsThe simulation model estimated that-in homes using NGCBs without coincident use of venting range hoods-62%, 9%, and 53% of occupants are routinely exposed to NO2, CO, and HCHO levels that exceed acute health-based standards and guidelines. NGCB use increased the sample median of the highest simulated 1-hr indoor concentrations by 100, 3,000, and 20 ppb for NO2, CO, and HCHO, respectively.ConclusionsReducing pollutant exposures from NGCBs should be a public health priority. Simulation results suggest that regular use of even moderately effective venting range hoods would dramatically reduce the percentage of homes in which concentrations exceed health-based standards.

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Joint and independent neurotoxic effects of early life exposures to a chemical mixture: A multi-pollutant approach combining ensemble learning and g-computation.

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Joint and independent neurotoxic effects of early life exposures to a chemical mixture: A multi-pollutant approach combining ensemble learning and g-computation.

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