Improved risk communications with a Bayesian multipollutant Air Quality Health Index

Huan Xu; Wei Zeng; Bing Guo; Philip K Hopke; Xue Qiao; Hyunok Choi; Bin Luo; Wei Zhang; Xing Zhao

doi:10.1016/j.scitotenv.2020.137892

Improved risk communications with a Bayesian multipollutant Air Quality Health Index

Sci Total Environ. 2020 Jun 20:722:137892. doi: 10.1016/j.scitotenv.2020.137892. Epub 2020 Mar 13.

Authors

Huan Xu¹, Wei Zeng², Bing Guo¹, Philip K Hopke³, Xue Qiao⁴, Hyunok Choi⁵, Bin Luo⁶, Wei Zhang⁷, Xing Zhao⁸

Affiliations

¹ Department of Epidemiology and Biostatistics, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu 610041, China.
² Chengdu Center for Diseases Control and Prevention, Chengdu 610041, China.
³ Department of Public Health Sciences, School of Medicine and Dentistry, University of Rochester, Rochester, NY 14642, USA; Center for Air Resources Engineering and Science, Clarkson University, Potsdam, NY 13699, USA.
⁴ Institute of New Energy and Low-Carbon Technology, Sichuan University, Chengdu 610065, China.
⁵ Department of Environmental Health Sciences, School of Public Health, University at Albany, 1 University Place, Rensselaer, NY 12144, USA.
⁶ Sichuan Academy of Environmental policy and planning, Chengdu 610041, Sichuan Province, China.
⁷ Sichuan Environmental Monitoring Center, Chengdu 610041, Sichuan Province, China.
⁸ Department of Epidemiology and Biostatistics, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu 610041, China. Electronic address: zhaoxing731@foxmail.com.

PMID: 32199385
DOI: 10.1016/j.scitotenv.2020.137892

Abstract

Establishing an optimal indicator to communicate health risks of multiple air pollutants to public is much important. The Air Quality Health Index (AQHI) has been developed in many countries as a communication tool of multiple air pollutants related health risks. However, the current AQHI is based on the sum of the excess health risks which are typically derived from the single-pollutant statistical models. Such a strategy may overestimate the joint effect of multiple pollutants. We proposed an improved strategy to construct the AQHI based on a Bayesian multipollutant weighted model. Using this strategy, two improved indices - Bayesian multipollutant AQHI (BMP-AQHI) and Bayesian multipollutant AQHI with seasonal specificity (SBMP-AQHI) were calculated to present the multiple pollutants related health risks to the cardiovascular system based on data collected in Chengdu, China during 2013 to 2018. The two improved indices were compared to current Air Quality Index (AQI) and AQHI to evaluate the effectiveness of the improved indices in characterizing multipollutant health risks. The AQI risk classification suggested much smaller health risks than AQHIs. Among three AQHI types, the BMP-AQHI and SBMP-AQHI suggested slightly lower health risks to the cardiovascular system than the current AQHI. In the evaluation analysis, the SBMP-AQHI had the strongest association with the mortality of cardiovascular disease (CVD) (2.66%; 95%CI, 1.57%, 3.76%). In the subgroup analysis, an interquartile increase (IQR) of the SBMP-AQHI was associated with 3.21% (95%CI, 2.06%, 4.38%), 1.34% (95%CI, -0.13%, 2.82%), and 4.20% (95%CI, 2.59%, 5.84%) increases for CVD mortality in the elderly, male, and female subgroups, respectively. The study shows that the improved AQHIs can communicate the health information of multiple air pollutants more efficiently. The study also indicates the necessity to consider seasonal specificity in the construction of the AQHI.

Keywords: Air Quality Health Index; Air Quality Index; Air pollution; Evaluation; Health risks.

MeSH terms

Air Pollutants
Air Pollution*
Bayes Theorem
China
Communication
Environmental Exposure
Female
Humans
Male
Particulate Matter

Substances

Air Pollutants
Particulate Matter