From the Department of Public Health, Environments and Society, London School of Hygiene and Tropical Medicine (LSHTM), 15-17 Tavistock Place, London, WC1H 9SH, United Kingdom.
Department of Statistics, Computer Science and Applications "G. Parenti", University of Florence, Florence, Italy.
Epidemiology. 2022 Mar 1;33(2):167-175. doi: 10.1097/EDE.0000000000001455.
The association between fine particulate matter (PM2.5) and mortality widely differs between as well as within countries. Differences in PM2.5 composition can play a role in modifying the effect estimates, but there is little evidence about which components have higher impacts on mortality.
We applied a 2-stage analysis on data collected from 210 locations in 16 countries. In the first stage, we estimated location-specific relative risks (RR) for mortality associated with daily total PM2.5 through time series regression analysis. We then pooled these estimates in a meta-regression model that included city-specific logratio-transformed proportions of seven PM2.5 components as well as meta-predictors derived from city-specific socio-economic and environmental indicators.
We found associations between RR and several PM2.5 components. Increasing the ammonium (NH4+) proportion from 1% to 22%, while keeping a relative average proportion of other components, increased the RR from 1.0063 (95% confidence interval [95% CI] = 1.0030, 1.0097) to 1.0102 (95% CI = 1.0070, 1.0135). Conversely, an increase in nitrate (NO3-) from 1% to 71% resulted in a reduced RR, from 1.0100 (95% CI = 1.0067, 1.0133) to 1.0037 (95% CI = 0.9998, 1.0077). Differences in composition explained a substantial part of the heterogeneity in PM2.5 risk.
These findings contribute to the identification of more hazardous emission sources. Further work is needed to understand the health impacts of PM2.5 components and sources given the overlapping sources and correlations among many components.
细颗粒物(PM2.5)与死亡率之间的关联在国家之间以及国家内部存在广泛差异。PM2.5 成分的差异可能在改变效应估计方面发挥作用,但关于哪些成分对死亡率的影响更高,证据很少。
我们对来自 16 个国家的 210 个地点收集的数据进行了 2 阶段分析。在第一阶段,我们通过时间序列回归分析估计了与每日总 PM2.5 相关的死亡率的特定地点相对风险(RR)。然后,我们将这些估计值纳入一个包含七个 PM2.5 成分的城市特定对数比转换比例以及源自城市特定社会经济和环境指标的元预测因子的元回归模型中进行汇总。
我们发现 RR 与几种 PM2.5 成分之间存在关联。在保持其他成分的相对平均比例的情况下,将铵(NH4+)的比例从 1%增加到 22%,RR 从 1.0063(95%置信区间[95%CI] = 1.0030,1.0097)增加到 1.0102(95%CI = 1.0070,1.0135)。相反,硝酸盐(NO3-)从 1%增加到 71%导致 RR 降低,从 1.0100(95%CI = 1.0067,1.0133)降低到 1.0037(95%CI = 0.9998,1.0077)。成分的差异解释了 PM2.5 风险异质性的很大一部分。
这些发现有助于确定更危险的排放源。需要进一步的工作来了解 PM2.5 成分和来源对健康的影响,因为许多成分之间存在重叠的来源和相关性。