首页|期刊导航|环境与职业医学|大气污染物复合暴露对呼吸系统疾病死亡效应的空气质量健康指数构建:基于加权分位数和回归模型

大气污染物复合暴露对呼吸系统疾病死亡效应的空气质量健康指数构建:基于加权分位数和回归模型OA

Development of an air quality health index for respiratory disease mortality associated with air pollutant mixtures using weighted quantile sum regression

中文摘要英文摘要

[背景]基于单一大气污染物的空气质量指数(AQI)和基于不同大气污染物的空气质量健康指数(AQHI)均难以准确量化复合大气污染对健康的协同效应,且无法识别高贡献污染物.大气污染复合暴露情况存在地域差异,有必要针对不同区域的不同疾病群体构建AQHI. [目的]基于加权分位数和回归(WQS)模型构建大气污染物复合暴露下表征大气质量对呼吸系统疾病死亡风险的天津市AQHI,明确指示污染物的贡献. [方法]收集天津市中心城区 2014-2019年 6种大气污染物及 AQI、气象因素和呼吸系统疾病死亡的逐日数据,合并整理为时间序列数据库.首先采用广义相加模型(GAM)筛选大气污染复合暴露的指示污染物;然后采用 WQS模型分析不同指示污染物的权重贡献并提取大气混合污染物与呼吸系统疾病死亡的暴露-反应关系系数,进而构建 AQHI;最后构建并对比AQHI和AQI与不同特征人群和季节呼吸系统疾病死亡风险的暴露反应关系. [结果]细颗粒物(PM2.5)、可吸入颗粒物(PM10)、二氧化硫(SO2)和臭氧(O3)为大气污染复合暴露的指示污染物.其中颗粒物(PM2.5 和 PM10)和 O3 贡献较大,其次为 SO2.采用 WQS模型构建的 AQHI值每升高 1个四分位数间距(IQR)对全人群、男性、老年、非老年人群和暖季的呼吸系统疾病死亡的暴露-反应关系均具有统计学意义,效应值分别为 3.79%(95%CI:1.24%~6.27%)、4.37%(95%CI:0.96%~7.67%)、3.16%(95%CI:0.47%~5.77%)、9.36%(95%CI:2.01%~16.15%)和7.13%(95%CI:1.31%~13.30%),且与AQI相比,风险效应值更高. [结论]在天津地区,颗粒物(PM2.5 和 PM10)和 O3 在大气混合污染物对呼吸系统疾病死亡的影响中贡献较大;与 AQI相比,采用 WQS模型构建的 AQHI能够更好地反映空气质量与不同特征人群呼吸系统疾病死亡风险的关联.

[Background]The air quality index(AQI),which is based on the concentration of a dominant pol-lutant,and the air quality health index(AQHI),which is constructed using excess risk estimates for individual pollutants,may not fully capture the health risks associated with combined exposure to air pollutants.These approaches also provide limited information on the relative contributions of different pollutants.Given the geographical heterogeneity in the composition and health effects of air pollutant mixtures,it is necessary to develop region-and disease-specific AQHIs for different population groups. [Objective]To develop and evaluate a health risk-based AQHI for respiratory disease mortality associated with air pollutant mixtures using the weighted quantile sum(WQS)regression model and to quantify the relative weight contributions of selected pollutants. [Methods]Daily data on six air pollutants,the AQI,meteorological factors,and deaths from res-piratory diseases in the central urban districts of Tianjin from 2014 to 2019 were collected and integrated into a time-series database.First,generalized additive models(GAMs)were applied to identify indicator pollutants associated with respiratory disease mortality.Second,the WQS regression model was then applied to estimate the relative weight contributions of selected pollutants and to establish the exposure-response relationship between air pollutant mixtures and respiratory disease mortality for AQHI development.Finally,the exposure-response relationships of the AQHI and AQI with respiratory disease mortality were evaluated and compared across population subgroups and seasons. [Results]Fine particulate matter(PM2.5),inhalable particulate matter(PM10),sulfur dioxide(SO2),and ozone(O3)were identified as indicator pollutants for combined air pollution exposure.Particulate matter,including PM2.5 and PM10,and O3 contributed the most to the mixture index,followed by SO2.Each interquartile range(IQR)increase in the WQS-based AQHI was significantly associated with respiratory disease mortality in the total population,males,elderly individuals,non-elderly individuals,and during the warm season.The corresponding excess risks(ER)were 3.79%(95%CI:1.24%,6.27%),4.37%(95%CI:0.96%,7.67%),3.16%(95%CI:0.47%,5.77%),9.36%(95%CI:2.01%,16.15%),and 7.13%(95%CI:1.31%,13.30%),respectively.Compared with the AQI,the AQHI showed stronger associations with respiratory disease mortality across different population subgroups and seasons. [Conclusion]PM2.5,PM10,and O3 contribute substantially to the association between air pollutant mixtures and respiratory disease mortality in Tianjin.Compared with the AQI,the WQS-based AQHI better characterizes the association between air quality and respiratory disease mortality across population subgroups.

倪洋;张继勉;曾强

天津市疾病预防控制中心职业健康所,天津 300011天津市疾病预防控制中心职业健康所,天津 300011天津市疾病预防控制中心职业健康所,天津 300011

医药卫生

大气污染加权分位数和回归空气质量指数空气质量健康指数呼吸系统疾病

air pollutionweighted quantile sum regressionair quality indexair quality health indexrespiratory disease

《环境与职业医学》 2026 (8)

944-950,7

天津市医学重点建设学科项目(TJYXZDXK-3-020B)

10.11836/JEOM26086

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