Background
Evolving animal studies and limited epidemiological data show that prenatal air pollution exposure is associated with childhood obesity. Timing of exposure and child sex may play an important role in these associations. We applied an innovative method to examine sex-specific sensitive prenatal windows of exposure to PM2.5 on anthropometric measures in preschool-aged children.
Methods
Analyses included 239 children born ≥37 weeks gestation in an ethnically-mixed lower-income urban birth cohort. Prenatal daily PM2.5 exposure was estimated using a validated satellite-based spatio-temporal model. Body mass index z-score (BMI-z), fat mass, % body fat, subscapular and triceps skinfold thickness, waist and hip circumferences and waist-to-hip ratio (WHR) were assessed at age 4.0±0.7 years. Using Bayesian distributed lag interaction models (BDLIMs), we examined sex differences in sensitive windows of weekly averaged PM2.5 levels on these measures, adjusting for child age, maternal age, education, race/ethnicity, and pre-pregnancy BMI.
Results
Mothers were primarily Hispanic (55%) or Black (26%), had ≤12 years of education (66%) and never smoked (80%). Increased PM2.5 exposure from 8–17 and 15–22 weeks gestation was significantly associated with increased BMI z-scores and fat mass in boys, but not in girls. Higher PM2.5 exposure from 10–29 weeks gestation was significantly associated with increased WHR in girls, but not in boys. Prenatal PM2.5 was not significantly associated with other measures of body composition. Estimated cumulative effects across pregnancy, accounting for sensitive windows and within-window effects, were 0.21 (95%CI=0.01–0.37) for BMI-z and 0.36 (95%CI=0.12–0.68) for fat mass (kg) in boys, and 0.02 (95%CI=0.01–0.03) for WHR in girls, all per μg/m3 increase in PM2.5.
Conclusions
Increased prenatal PM2.5 exposure was more strongly associated with indices of increased whole body size in boys and with an indicator of body shape in girls. Methods to better characterize vulnerable windows may provide insight into underlying mechanisms contributing to sex-specific associations.