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Global association between atmospheric particulate matter and obesity: A systematic review and meta-analysis

期刊

ENVIRONMENTAL RESEARCH
卷 209, 期 -, 页码 -

出版社

ACADEMIC PRESS INC ELSEVIER SCIENCE
DOI: 10.1016/j.envres.2022.112785

关键词

Particulate matter; PM2.5; PM10; Obesity; Meta-analysis

资金

  1. National Natural Science Foundation of China [91943301, 92043301]

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Exposure to PM2.5 and PM10 with per 10 µg/m³ increment could increase the risk of obesity in the global population.
Background: Among various air pollutants, particulate matter (PM) is the most harmful and representative pollutant. Although several studies have shown a link between particulate pollution and obesity, the conclusions are still inconsistent. Methods: We conducted a systematic review and meta-analysis to pool the effect of PM exposure on obesity. Five databases (including PubMed, Web of Science, Scopus, Embase, and Cochrane) were searched for relevant studies up to Jan 2022. Adjusted risk ratio (RR) with corresponding 95% confidence interval (CI) were retrieved from individual studies and pooled with random effect models by STATA software. Besides, we tested the stability of results by Egger's test, Begg's test, funnel plot, and using the trim-and-fill method to modify the possible asymmetric funnel graph. The NTP-OHAT guidelines were followed to assess the risk of bias. Then the GRADE was used to evaluate the certainty of evidence. Results: 26 studies were included in this meta-analysis. 19 studies have shown that PM2.5 can increase the risk of obesity per 10 mu g/m(3) increment (RR: 1.159, 95% CI: 1.111-1.209), while 15 studies have indicated that PM10 increase the risk of obesity per 10 mu g/m(3) increment (RR: 1.092, 95% CI: 1.070-1.116). Besides, 5 other articles with maternal exposure showed that PM2.5 increases the risk of obesity in children (RR: 1.06, 95% CI: 1.02-1.11). And we explored the source of heterogeneity by subgroup analysis, which suggested associations between PM and obesity tended to vary by region, age group, participants number, etc. The analysis results showed publication bias and other biases are well controlled, but most certainties of the evidence were low, and more research is required to reduce these uncertainties. Conclusion: Exposure to PM2.5 and PM10 with per 10 mu g/m(3) increment could increase the risk of obesity in the global population.

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