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<p>An increasing number of epidemiological studies have suggested that ambient exposure to particular matter (PM) contributes to child obesity. However, whether variations in PM influence body mass index remains unknown. This study aimed to estimate the association between variability in ambient PM exposure and body mass index and the related urban-rural disparities, independent of air pollution exposure. This research utilized a cohort data set from the National School-aged Children and Adolescents Health Monitoring Project of China, encompassing over 1&#xa0;million school-aged children and adolescents aged 6 to 19 from 2013 to 2021. Pollution levels were defined by assigning each student the nearest grid according to the longitude and latitude of each student’s school. Subsequently, the monthly coefficients of variation in PM over 30 days preceding the physical examination date were calculated. Panel multilevel and panel quantile regression models were applied. In panel multilevel model, inverse probability weighting was introduced to adjust for bias in our study sample. After controlling for pollution concentration, a 1% increase in the monthly variability of PM<sub>2.5</sub> and PM<sub>10</sub> was associated with 0.0025 (95% CI: 0.22, 0.27) and 0.0034 (95% CI: 0.32, 0.36) increases in body mass index, respectively. The effect sizes of variability of PM<sub>2.5</sub> and PM<sub>10</sub> were 0.0022 (95% CI: 0.20, 0.25) and 0.0031 (95% CI: 0.29, 0.33) in urban areas, respectively. In contrast, in rural areas, the corresponding BMI increases were 0.0035 (95% CI: 0.30, 0.40) and 0.0043 (95% CI: 0.40, 0.47). Similar results were reported adjusting for weights and across quantile levels. Moreover, the effects were more pronounced for children and adolescents with a higher body mass index. The urban-rural disparities remained at different quantiles. To our knowledge, this is the first study revealing the positive relationship between air pollution variations and child obesity and the related urban-rural disparities. Environmental health policies accounting for variations in pollution exposure should be implemented, with particular focuses in rural areas.</p>

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Urban-rural disparities in the association between variability in particulate matter exposure and body mass index in school-aged children and adolescents: evidence from China

  • 期刊论文

  • 发表日期：

    2025年5月17日

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  • Xiaofeng Sun,
  • Fangying Liu,
  • Feng Cui,
  • Jingyi Zhao,
  • Qian Zhang,
  • Xiaowei Hao,
  • Meng Zhang,
  • Qing Wang

摘要

An increasing number of epidemiological studies have suggested that ambient exposure to particular matter (PM) contributes to child obesity. However, whether variations in PM influence body mass index remains unknown. This study aimed to estimate the association between variability in ambient PM exposure and body mass index and the related urban-rural disparities, independent of air pollution exposure. This research utilized a cohort data set from the National School-aged Children and Adolescents Health Monitoring Project of China, encompassing over 1 million school-aged children and adolescents aged 6 to 19 from 2013 to 2021. Pollution levels were defined by assigning each student the nearest grid according to the longitude and latitude of each student’s school. Subsequently, the monthly coefficients of variation in PM over 30 days preceding the physical examination date were calculated. Panel multilevel and panel quantile regression models were applied. In panel multilevel model, inverse probability weighting was introduced to adjust for bias in our study sample. After controlling for pollution concentration, a 1% increase in the monthly variability of PM2.5 and PM10 was associated with 0.0025 (95% CI: 0.22, 0.27) and 0.0034 (95% CI: 0.32, 0.36) increases in body mass index, respectively. The effect sizes of variability of PM2.5 and PM10 were 0.0022 (95% CI: 0.20, 0.25) and 0.0031 (95% CI: 0.29, 0.33) in urban areas, respectively. In contrast, in rural areas, the corresponding BMI increases were 0.0035 (95% CI: 0.30, 0.40) and 0.0043 (95% CI: 0.40, 0.47). Similar results were reported adjusting for weights and across quantile levels. Moreover, the effects were more pronounced for children and adolescents with a higher body mass index. The urban-rural disparities remained at different quantiles. To our knowledge, this is the first study revealing the positive relationship between air pollution variations and child obesity and the related urban-rural disparities. Environmental health policies accounting for variations in pollution exposure should be implemented, with particular focuses in rural areas.