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Your Environment. Your Health.

Publication Detail

Title: Early-Life Environmental Exposures and Childhood Obesity: An Exposome-Wide Approach.

Authors: Vrijheid, Martine; Fossati, Serena; Maitre, Léa; Márquez, Sandra; Roumeliotaki, Theano; Agier, Lydiane; Andrusaityte, Sandra; Cadiou, Solène; Casas, Maribel; de Castro, Montserrat; Dedele, Audrius; Donaire-Gonzalez, David; Grazuleviciene, Regina; Haug, Line S; McEachan, Rosemary; Meltzer, Helle Margrete; Papadopouplou, Eleni; Robinson, Oliver; Sakhi, Amrit K; Siroux, Valerie; Sunyer, Jordi; Schwarze, Per E; Tamayo-Uria, Ibon; Urquiza, Jose; Vafeiadi, Marina; Valentin, Antonia; Warembourg, Charline; Wright, John; Nieuwenhuijsen, Mark J; Thomsen, Cathrine; Basagaña, Xavier; Slama, Rémy; Chatzi, Leda

Published In Environ Health Perspect, (2020 06)

Abstract: BACKGROUND: Chemical and nonchemical environmental exposures are increasingly suspected to influence the development of obesity, especially during early life, but studies mostly consider single exposure groups. OBJECTIVES: Our study aimed to systematically assess the association between a wide array of early-life environmental exposures and childhood obesity, using an exposome-wide approach. METHODS: The HELIX (Human Early Life Exposome) study measured child body mass index (BMI), waist circumference, skinfold thickness, and body fat mass in 1,301 children from six European birth cohorts age 6-11 y. We estimated 77 prenatal exposures and 96 childhood exposures (cross-sectionally), including indoor and outdoor air pollutants, built environment, green spaces, tobacco smoking, and biomarkers of chemical pollutants (persistent organic pollutants, metals, phthalates, phenols, and pesticides). We used an exposure-wide association study (ExWAS) to screen all exposure-outcome associations independently and used the deletion-substitution-addition (DSA) variable selection algorithm to build a final multiexposure model. RESULTS: The prevalence of overweight and obesity combined was 28.8%. Maternal smoking was the only prenatal exposure variable associated with higher child BMI (z-score increase of 0.28, 95% confidence interval: 0.09, 0.48, for active vs. no smoking). For childhood exposures, the multiexposure model identified particulate and nitrogen dioxide air pollution inside the home, urine cotinine levels indicative of secondhand smoke exposure, and residence in more densely populated areas and in areas with fewer facilities to be associated with increased child BMI. Child blood levels of copper and cesium were associated with higher BMI, and levels of organochlorine pollutants, cobalt, and molybdenum were associated with lower BMI. Similar results were found for the other adiposity outcomes. DISCUSSION: This first comprehensive and systematic analysis of many suspected environmental obesogens strengthens evidence for an association of smoking, air pollution exposure, and characteristics of the built environment with childhood obesity risk. Cross-sectional biomarker results may suffer from reverse causality bias, whereby obesity status influenced the biomarker concentration. https://doi.org/10.1289/EHP5975.

PubMed ID: 32579081 Exiting the NIEHS site

MeSH Terms: Air Pollutants; Air Pollution/statistics & numerical data; Body Mass Index; Child; Environmental Exposure/statistics & numerical data*; Environmental Pollutants; Exposome; Female; Humans; Male; Nitrogen Dioxide; Obesity/epidemiology*; Phthalic Acids; Pregnancy; Skinfold Thickness; Smoking/epidemiology; Waist Circumference

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