背景:尽管有证据表明细颗粒物(PM2.5)与心脏代谢多重性(CMM)有关,其组成部分的影响尚不清楚。社会经济地位(SES)和地区差异可能会混淆它们的联系。我们旨在评估PM2.5成分与CMM之间的关联,并探讨社会经济地位和区域差异如何影响这些关系。
方法:我们从中国东部十个城市招募了108,941名35-76岁的参与者。使用跟踪中国空气污染(TAP)数据评估个人暴露,包括PM2.5和五种成分:铵(NH4+),黑碳(BC),硝酸盐(NO3-),有机质(OM),和硫酸盐(SO42-)。采用广义线性模型和分位数g计算模型来量化PM2.5成分对CMM的影响并识别关键成分。进行了分层分析,以研究SES和区域差异的修改效果。
结果:对于四分位数间距(IQR)的每增加,BC(赔率比[OR]1.37,95%CI1.29-1.47),OM(1.38,1.29-1.48),NH4+(1.31,1.21-1.40),NO3-(1.34,1.25-1.44),SO42-(1.28,1.20-1.38)与CMM呈正相关。5种成分的关节暴露与CMM呈显著正相关(OR:1.27,95%CI:1.21-1.33),SO42-具有最高的估计重量,其次是NO3-和BC。这些协会对来自低社会经济地位和贫困地区的参与者来说更加强大。
结论:总之,我们发现PM2.5及其成分对CMM的危害作用更强,与那些患有CMD的人相比,特别是在社会经济地位低和贫困地区的参与者中。SO42-可能是PM2.5成分与CMM之间关联的主要贡献者。这些发现强调了在卫生政策中优先考虑CMM和针对SO42相关污染源的重要性,特别是在中国人口老龄化的背景下,减少环境健康不平等至关重要。
BACKGROUND: Despite evidence linking fine particulate matter (PM2.5) to cardiometabolic multimorbidity (CMM), the impact of its components remains unclear. Socioeconomic status (SES) and regional disparities may confound their association. We aim to evaluate the associations between PM2.5 components and CMM and explore how socioeconomic status and regional disparities affect these relationships.
METHODS: We recruited 108,941 participants aged 35-76 years from ten cities in eastern
China. Individual exposure was assessed using Tracking Air Pollution in
China (TAP) data, including PM2.5 and five components: ammonium (NH4+), black carbon (BC), nitrates (NO3-), organic matter (OM), and sulfates (SO42-). Generalized linear models and quantile g-computation models were employed to quantify the effects of PM2.5 components on CMM and to identify key components. Stratified analyses were performed to investigate the modifying effect of SES and regional disparities.
RESULTS: For each increase in interquartile range (IQR), BC (odds ratio [OR] 1.37, 95 % CI 1.29-1.47), OM (1.38, 1.29-1.48), NH4+ (1.31, 1.21-1.40), NO3- (1.34, 1.25-1.44), and SO42- (1.28, 1.20-1.38) were positively associated with CMM. Joint exposure to five components was significantly positively associated with CMM (OR: 1.27, 95 % CI: 1.21-1.33), with SO42- having the highest estimated weight, followed by NO3- and BC. These associations were stronger for participants from low socio-economic status and poor regions.
CONCLUSIONS: In summary, we found a stronger hazard effect of PM2.5 and its components on CMM, compared to those suffering from CMDs, particularly among participants with low socioeconomic status and in poor regions. SO42- may be a primary contributor to the association between PM2.5 components and CMM. These findings underscore the importance of prioritizing CMM and targeting SO42-related pollution sources in health policies, particularly amid
China\'s aging population, reducing environmental health inequalities is critical.