Department of Occupational and Environmental Health Sciences, Peking University School of Public Health, 38 Xueyuan Road, 100191, Beijing, China.
National Center for Chronic and Noncommunicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, 27 Nanwei Road, Xicheng District, Beijing, 100050, China.
Environ Res. 2022 Dec;215(Pt 2):114264. doi: 10.1016/j.envres.2022.114264. Epub 2022 Sep 6.
The Air Quality Index (AQI) has been criticized because it does not adequately account for the health effect of multi-pollutants. Although the developed Air Quality Health Index (AQHI) is a more effective communication tool, little is known about the best method to construct AQHI on long time and large spatial scales.
To further evaluate the validity of existing approaches to the establishment of AQHI on both long time and larger spatial scales.
By introducing 3 approaches addressing multi-pollutant exposures: cumulative risk index (CRI), supervised principal component analysis (SPCA), and Bayesian multi-pollutants weighted model (BMP), we constructed CRI-AQHI, SPCA-AQHI, BMP-AQHI and standard-AQHI on cardiovascular mortality in China from 2015 to 2019 at both the national and geographic regional levels. We further assessed the performance of the four methods in estimating the joint effect of multi-pollutants by simulations under various scenarios of pollution effect.
The results of national China showed that the BMP-AQHI improved the goodness of fit of the standard-AQHI by 108.24%, followed by CRI-AQHI (5.02%), and all AQHIs performed better than AQI, consistent with 6 geographic regional results. In addition, the simulation result showed that the BMP method provided stable and relatively accurate estimations of the short-term combined effect of exposure to multi-pollutants.
AQHI based on BMP could communicate the air pollution risk to the public more effectively than the current AQHI and AQI.
空气质量指数 (AQI) 受到了批评，因为它没有充分考虑到多种污染物对健康的影响。尽管发达的空气质量健康指数 (AQHI) 是一种更有效的沟通工具，但对于在长时间和大空间尺度上构建 AQHI 的最佳方法知之甚少。
进一步评估在长时间和大空间尺度上建立 AQHI 的现有方法的有效性。
通过引入 3 种多污染物暴露评估方法：累积风险指数 (CRI)、有监督主成分分析 (SPCA) 和贝叶斯多污染物加权模型 (BMP)，我们构建了 2015 年至 2019 年中国心血管死亡率的 CRI-AQHI、SPCA-AQHI、BMP-AQHI 和标准-AQHI，分别在全国和地理区域层面。我们还通过在各种污染效应情景下的模拟，评估了这四种方法在估计多污染物联合效应方面的性能。
中国全国范围内的结果表明，BMP-AQHI 使标准-AQHI 的拟合优度提高了 108.24%，其次是 CRI-AQHI（5.02%），所有 AQHIs 的表现均优于 AQI，与 6 个地理区域的结果一致。此外，模拟结果表明，BMP 方法提供了多污染物暴露短期联合效应的稳定且相对准确的估计。
基于 BMP 的 AQHI 可以比当前的 AQHI 和 AQI 更有效地向公众传达空气污染风险。
