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

暴露的 环境卫生 可替宁 医学 肥胖 超重 体质指数 儿童肥胖 尼古丁 内科学
作者
Martine Vrijheid,Serena Fossati,Léa Maitre,Sandra Marquez,Theano Roumeliotaki,Lydiane Agier,Regina Grazuleviciene,Solène Cadiou,Maribel Casas,Montserrat de Castro,Audrius Dedele,David Donaire-Gonzalez,Line Småstuen Haug,Rosemary R. C. McEachan,Helle Margrete Meltzer,Eleni Papadopouplou,Oliver J. Robinson,Anne Lise Brantsæter,Valérie Siroux,Jordi Sunyer,Per E. Schwarze,Ibon Tamayo-Uria,Jose Urquiza,Marina Vafeiadi,Antònia Valentín,Charline Warembourg,John Wright,Mark J. Nieuwenhuijsen,Cathrine Thomsen,Xavier Basagaña,Rémy Slama,Leda Chatzi
出处
期刊:Environmental Health Perspectives [National Institute of Environmental Health Sciences]
卷期号:128 (6) 被引量:96
标识
DOI:10.1289/ehp5975
摘要

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.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.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.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.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.
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