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Early-Life Environmental Exposures and Childhood Obesity: An Exposome-Wide Approach
Martine Vrijheid1,2,3, Serena Fossati1,2,3, Léa Maitre1,2,3
1ISGlobal, Barcelona, Spain.
Environmental Health Perspectives
|June 25, 2020
Summary
This study linked early-life environmental exposures to childhood obesity. Key factors included smoking, air pollution, and urban environment characteristics, highlighting the impact of multiple exposures on child weight.
Area of Science:
- Environmental health science
- Pediatric epidemiology
- Obesity research
Background:
- Environmental exposures are increasingly implicated in childhood obesity development.
- Previous studies often focused on single exposure groups, limiting comprehensive understanding.
- Early life is a critical window for environmental influences on adiposity.
Purpose of the Study:
- To systematically assess associations between a wide range of early-life environmental exposures and childhood obesity.
- To utilize an exposome-wide approach for a comprehensive analysis.
- To identify key environmental factors contributing to childhood obesity risk.
Main Methods:
- The Human Early Life Exposome (HELIX) study involved 1,301 children aged 6-11 years across six European cohorts.
- Measured 77 prenatal and 96 childhood exposures, including air pollutants, built environment, and chemical biomarkers.
- Employed an exposure-wide association study (ExWAS) and deletion-substitution-addition (DSA) algorithm for multiexposure modeling.
Main Results:
- Maternal smoking was linked to higher child Body Mass Index (BMI).
- Childhood exposures associated with increased BMI included indoor air pollution (particulate matter, nitrogen dioxide), secondhand smoke, and less favorable built environments.
- Specific chemical biomarkers showed varied associations with BMI, with some metals linked to higher BMI and others to lower BMI.
Conclusions:
- This study provides comprehensive evidence linking smoking, air pollution, and built environment characteristics to childhood obesity.
- The findings emphasize the importance of considering multiple environmental exposures in early life.
- Acknowledges potential reverse causality bias in cross-sectional biomarker analyses.
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