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

Lisen Lin; Tianyu Li; Mengqi Sun; Qingqing Liang; Yuexiao Ma; Fenghong Wang; Junchao Duan; Zhiwei Sun

doi:10.1016/j.envres.2022.112785

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

Environ Res. 2022 Jun:209:112785. doi: 10.1016/j.envres.2022.112785. Epub 2022 Jan 22.

Authors

Lisen Lin¹, Tianyu Li¹, Mengqi Sun¹, Qingqing Liang¹, Yuexiao Ma¹, Fenghong Wang¹, Junchao Duan², Zhiwei Sun³

Affiliations

¹ Department of Toxicology and Sanitary Chemistry, School of Public Health, Capital Medical University, Beijing, 100069, PR China; Beijing Key Laboratory of Environmental Toxicology, Capital Medical University, Beijing, 100069, PR China.
² Department of Toxicology and Sanitary Chemistry, School of Public Health, Capital Medical University, Beijing, 100069, PR China; Beijing Key Laboratory of Environmental Toxicology, Capital Medical University, Beijing, 100069, PR China. Electronic address: jcduan@ccmu.edu.cn.
³ Department of Toxicology and Sanitary Chemistry, School of Public Health, Capital Medical University, Beijing, 100069, PR China; Beijing Key Laboratory of Environmental Toxicology, Capital Medical University, Beijing, 100069, PR China. Electronic address: zwsun@ccmu.edu.cn.

PMID: 35077718
DOI: 10.1016/j.envres.2022.112785

Abstract

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 PM_2.5 can increase the risk of obesity per 10 μg/m³ increment (RR: 1.159, 95% CI: 1.111-1.209), while 15 studies have indicated that PM₁₀ increase the risk of obesity per 10 μg/m³ increment (RR: 1.092, 95% CI: 1.070-1.116). Besides, 5 other articles with maternal exposure showed that PM_2.5 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 PM_2.5 and PM₁₀ with per 10 μg/m³ increment could increase the risk of obesity in the global population.

Keywords: Meta-analysis; Obesity; PM(10); PM(2.5); Particulate matter.

Publication types

Meta-Analysis
Review
Systematic Review

MeSH terms

Air Pollutants* / analysis
Air Pollutants* / toxicity
Air Pollution* / adverse effects
Air Pollution* / analysis
Child
Environmental Exposure / analysis
Humans
Obesity / etiology
Particulate Matter / analysis
Pediatric Obesity*

Substances

Air Pollutants
Particulate Matter