作者
Si-Tian Zang,Jie Luan,Ling Li,Qi‐Jun Wu,Qing Chang,Huixu Dai,Yuhong Zhao
摘要
Globally, the number of metabolic syndrome (MetS) cases has increased substantially over time. However, the association between air pollution (AP) and MetS risk has been contradictory in observational studies. This is the first reported meta-analysis quantitatively exploring the aforementioned association. We searched PubMed, Embase, and Web of Science database entries up to September 14, 2020, and searches were updated up to December 6, 2020 to identify eligible articles on the AP-MetS risk association. No language restriction was imposed. Random-effects models were applied to estimate summary and subgroup effect sizes with 95% confidence intervals (CIs). PROSPERO registration number: CRD42020210431. Eight articles (nine studies) were eligible for the meta-analysis. Increased MetS prevalence was not found to be associated with particulate matter less than 1 μm (PM1), 2.5 μm (PM2.5), and 10 μm (PM10) in diameter or nitrogen dioxide (NO2), and the summary effect sizes were 1.33 (95% CI: 0.95–1.85), 1.34 (95% CI: 0.96–1.89), 1.18 (95% CI: 0.98–1.19), and 1.28 (95% CI: 0.89–1.82), respectively, based on cross-sectional studies. The summary results indicated no association between each 10 μg/m3 increase in PM2.5 and MetS incidence (effect size 2.78 [95% CI: 0.70–11.02]), based on cohort studies. Subgroup analysis demonstrated that MetS incidence in older men increased dramatically by 992% with each 10 μg/m3 increase in PM2.5. The evidence presented here suggests that although exposure to PM1, PM2.5, PM10, or NO2 was not found to have a significant association with the occurrence of MetS, the statistical significance of the relationship between exposure to PM1, PM2.5, or PM10 and MetS prevalence was approximately borderline. More studies on AP-MetS risk association in low-/middle-income countries, as well as on the association between other air pollutants and MetS risk, are warranted. A sufficient number of high-quality studies is required to perform a meaningful meta-analysis of the relationship between air pollutants and MetS.