Chemical constituents of ambient fine particulate matter and obesity among school-aged children: A representative national study in China.
Journal Article (Journal Article)
BackgroundStudies show that fine particulate matter (PM2.5 ) contributes to childhood obesity. However, evidence on the effects of its constituents on obesity has not been explored.
MethodsUsing multistage stratified cluster sampling, we enrolled 41,439 school-age children (aged 6-17 years) from a representative nationwide survey of 30 provinces in China (mean age ± standard deviation: 12.0 ± 3.3 years). Weight and height were measured using a physician beam scale with a height rod, and covariates were determined using a standard questionnaire. The concentration of PM2.5 chemical constituents was estimated by a chemical transport (GEOS-Chem) model using input satellite data and ground-based observations. The constituents included black carbon, ammonium, nitrate, organic matter, sulfate, and soil dust. Generalized linear models were used to estimate the association between the chemical constituents of PM2.5 and obesity.
ResultsA positive association between the constituents of PM2.5 and obesity were observed. Children were more susceptible to black carbon than other species. A 1-μg/m3 increase in black carbon led to a 0.079 (95 % confidence interval [CI]:0.028, 0.130)-kg/m2 increase in body mass index (BMI). This also increased the odds of being obese and overweight to 1.174 (95 % CI: 1.111, 1.240) and 1.165 (95 % CI: 1.116, 1.216), respectively. Stratified analyses showed that the effects were stronger in girls and older children, as well as in urban and Northeast regions. The effect of the PM2.5 constituents on obese and overweight children from urban areas significantly interacted with that of rural areas.
ConclusionsThe PM2.5 constituents were associated with an increased BMI and childhood obesity. Further studies are warranted to validate these results and clarify their potential mechanisms. We suggest focusing on black carbon and Northeast regions.
- Guo, Q; Zhang, K; Wang, B; Cao, S; Xue, T; Zhang, Q; Tian, H; Fu, P; Zhang, JJ; Duan, X
- November 2022
Volume / Issue
- 849 /
Start / End Page
- 157742 -
Electronic International Standard Serial Number (EISSN)
International Standard Serial Number (ISSN)
Digital Object Identifier (DOI)