Citation: | GAO Jinghua, ZHOU Chunliang, HU Jianxiong, MENG Ruilin, ZHOU Maigeng, HOU Zhulin, XIAO Yize, YU Min, HUANG Biao, XU Xiaojun, LIU Tao, GONG Weiwei, JIN Donghui, QIN Mingfang, YIN Peng, XU Yiqing, HE Guanhao, WU Xianbo, ZENG Weilin, MA Wenjun. Construction of AQHI based on joint effects of multi-pollutants in 5 provinces of China[J]. Journal of Environmental and Occupational Medicine, 2023, 40(3): 281-288. DOI: 10.11836/JEOM22425 |
Air pollution is a major public health concern. Air Quality Health Index (AQHI) is a very important air quality risk communication tool. However, AQHI is usually constructed by single-pollutant model, which has obvious disadvantages.
To construct an AQHI based on the joint effects of multiple air pollutants (J-AQHI), and to provide a scientific tool for health risk warning and risk communication of air pollution.
Data on non-accidental deaths in Yunnan, Guangdong, Hunan, Zhejiang, and Jilin provinces from January 1, 2013 to December 31, 2018 were obtained from the corresponding provincial disease surveillance points systems (DSPS), including date of death, age, gender, and cause of death. Daily meteorological (temperature and relative humidity) and air pollution data (SO2, NO2, CO, PM2.5, PM10, and maximum 8 h O3 concentrations) at the same period were respectively derived from China Meteorological Data Sharing Service System and National Urban Air Quality Real-time Publishing Platform. Lasso regression was first applied to select air pollutants, then a time-stratified case-crossover design was applied. Each case was matched to 3 or 4 control days which were selected on the same days of the week in the same calendar month. Then a distributed lag nonlinear model (DLNM) was used to estimate the exposure-response relationship between selected air pollutants and mortality, which was used to construct the AQHI. Finally, AQHI was classified into four levels according to the air pollutant guidance limit values from World Health Organization Global Air Quality Guidelines (AQG 2021), and the excess risks (ERs) were calculated to compare the AQHI based on single-pollutant model and the J-AQHI based on multi-pollutant model.
PM2.5, NO2, SO2, and O3 were selected by Lasso regression to establish DLNM model. The ERs for an interquartile range (IQR) increase and 95% confidence intervals (CI) for PM2.5, NO2, SO2 and O3 were 0.71% (0.34%–1.09%), 2.46% (1.78%–3.15%), 1.25% (0.9%–1.6%), and 0.27% (−0.11%–0.65%) respectively. The distribution of J-AQHI was right-skewed, and it was divided into four levels, with ranges of 0-1 for low risk, 2-3 for moderate risk, 4-5 for high health risk, and ≥6 for severe risk, and the corresponding proportions were 11.25%, 64.61%, 19.33%, and 4.81%, respectively. The ER (95%CI) of mortality risk increased by 3.61% (2.93–4.29) for each IQR increase of the multi-pollutant based J-AQHI , while it was 3.39% (2.68–4.11) for the single-pollutant based AQHI .
The J-AQHI generated by multi-pollutant model demonstrates the actual exposure health risk of air pollution in the population and provides new ideas for further improvement of AQHI calculation methods.
[1] |
World Health Organization. Global health observatory[EB/OL]. [2015-03-18]. http://www.who.int/gho/phe/en/.
|
[2] |
World Health Organization. World Health Statistics 2022[R]. Geneva: WHO, 2020.
|
[3] |
GORAI A K, TCHOUNWOU P B, BISWAL S S, et al. Spatio-temporal variation of particulate matter(PM2.5) concentrations and its health impacts in a Mega City, Delhi in India[J]. Environ Health Insights, 2018, 12: 1178630218792861.
|
[4] |
WONG C M, MA S, HEDLEY A J, et al. Effect of air pollution on daily mortality in Hong Kong[J]. Environ Health Perspect, 2001, 109(4): 335-340. doi: 10.1289/ehp.01109335
|
[5] |
STIEB D M, BURNETT R T, SMITH-DOIRON M, et al. A new multipollutant, no-threshold air quality health index based on short-term associations observed in daily time-series analyses[J]. J Air Waste Manag Assoc, 2008, 58(3): 435-450. doi: 10.3155/1047-3289.58.3.435
|
[6] |
Environment Canada. Air quality health index[EB/OL]. [2012-06-10]. http://www.airqualityontario.com/aqhi/.
|
[7] |
DU X, CHEN R, MENG X, et al. The establishment of national air quality health index in China[J]. Environ Int, 2020, 138: 105594. doi: 10.1016/j.envint.2020.105594
|
[8] |
CHEN R, WANG X, MENG X, et al. Communicating air pollution-related health risks to the public: an application of the Air Quality Health Index in Shanghai, China[J]. Environ Int, 2013, 51: 168-173. doi: 10.1016/j.envint.2012.11.008
|
[9] |
MASON T G, SCHOOLING C M, RAN J, et al. Does the AQHI reduce cardiovascular hospitalization in Hong Kong's elderly population?[J]. Environ Int, 2020, 135: 105344. doi: 10.1016/j.envint.2019.105344
|
[10] |
LI X, XIAO J, LIN H, et al. The construction and validity analysis of AQHI based on mortality risk: a case study in Guangzhou, China[J]. Environ Pollut, 2017, 220: 487-494. doi: 10.1016/j.envpol.2016.09.091
|
[11] |
CAO R, WANG Y, HUANG J, et al. The construction of the air quality health index (AQHI) and a validity comparison based on three different methods[J]. Environ Res, 2021, 197: 110987. doi: 10.1016/j.envres.2021.110987
|
[12] |
XU H, ZENG W, GUO B, et al. Improved risk communications with a Bayesian multipollutant air quality health index[J]. Sci Total Environ, 2020, 722: 137892. doi: 10.1016/j.scitotenv.2020.137892
|
[13] |
WINQUIST A, KIRRANE E, KLEIN M, et al. Joint effects of ambient air pollutants on pediatric asthma emergency department visits in Atlanta, 1998-2004[J]. Epidemiology, 2014, 25(5): 666-673. doi: 10.1097/EDE.0000000000000146
|
[14] |
BILLIONNET C, SHERRILL D, ANNESI-MAESANO I. Estimating the health effects of exposure to multi-pollutant mixture[J]. Ann Epidemiol, 2012, 22(2): 126-141. doi: 10.1016/j.annepidem.2011.11.004
|
[15] |
HU J, HOU Z, XU Y, et al. Life loss of cardiovascular diseases per death attributable to ambient temperature: a national time series analysis based on 364 locations in China[J]. Sci Total Environ, 2021, 756: 142614. doi: 10.1016/j.scitotenv.2020.142614
|
[16] |
LIU X, YE Y, CHEN Y, et al. Effects of prenatal exposure to air particulate matter on the risk of preterm birth and roles of maternal and cord blood LINE-1 methylation: a birth cohort study in Guangzhou, China[J]. Environ Int, 2019, 133: 105177. doi: 10.1016/j.envint.2019.105177
|
[17] |
LIU T, CHEN X, XU Y, et al. Gut microbiota partially mediates the effects of fine particulate matter on type 2 diabetes: evidence from a population-based epidemiological study[J]. Environ Int, 2019, 130: 104882. doi: 10.1016/j.envint.2019.05.076
|
[18] |
LIU T, MENG H, YU M, et al. Urban-rural disparity of the short-term association of PM2.5 with mortality and its attributable burden[J]. Innovation (Camb), 2021, 2(4): 100171.
|
[19] |
WAKABAYASHI I, SOTODA Y, EGUCHI R. Contribution of platelet-derived microRNAs to serum microRNAs in healthy men[J]. Platelets, 2021, 32(7): 984-987. doi: 10.1080/09537104.2020.1810223
|
[20] |
TIBSHIRANI R. Regression shrinkage and selection via the lasso[J]. J R Stat Soc Series B Methodol, 1996, 58(1): 267-288.
|
[21] |
VERSÜMER S, STEFFENS J, BLÄTTERMANN P, et al. Modeling evaluations of low-level sounds in everyday situations using linear machine learning for variable selection[J]. Front Psychol, 2020, 11: 570761. doi: 10.3389/fpsyg.2020.570761
|
[22] |
LIU Y, PAN J, FAN C, et al. Short-term exposure to ambient air pollution and mortality from myocardial infarction[J]. J Am Coll Cardiol, 2021, 77(3): 271-281. doi: 10.1016/j.jacc.2020.11.033
|
[23] |
GASPARRINI A, LEONE M. Attributable risk from distributed lag models[J]. BMC Med Res Methodol, 2014, 14: 55. doi: 10.1186/1471-2288-14-55
|
[24] |
胡建雄, 陈思齐, 刘涛, 等. R语言在公共卫生领域的应用: 基本数据处理[J]. 华南预防医学, 2020, 46(2): 183-184,188.
HU J X, CHEN S Q, LIU T, et al. Application of R language in public health: basic data processing[J]. South China J Prev Med, 2020, 46(2): 183-184,188.
|
[25] |
ROBERTS S. A new model for investigating the mortality effects of multiple air pollutants in air pollution mortality time-series studies[J]. J Toxicol Environ Health A, 2006, 69(6): 417-435. doi: 10.1080/15287390500246761
|
[26] |
ZOU H, HASTIE T. Regularization and variable selection via the elastic net[J]. J R Stat Soc:Series B (Stat Methodol), 2005, 67(2): 301-320. doi: 10.1111/j.1467-9868.2005.00503.x
|
[27] |
DOMINICI F, PENG R D, BARR C D, et al. Protecting human health from air pollution: shifting from a single-pollutant to a multipollutant approach[J]. Epidemiology, 2010, 21(2): 187-194. doi: 10.1097/EDE.0b013e3181cc86e8
|
[28] |
CARRACEDO-MARTÍNEZ E, TARACIDO M, TOBIAS A, et al. Case-crossover analysis of air pollution health effects: a systematic review of methodology and application[J]. Environ Health Perspect, 2010, 118(8): 1173-1182. doi: 10.1289/ehp.0901485
|
[29] |
WONG T W, TAM W W S, YU I T S, et al. Developing a risk-based air quality health index[J]. Atmos Environ, 2013, 76: 52-58. doi: 10.1016/j.atmosenv.2012.06.071
|
[30] |
VEDAL S, BRAUER M, WHITE R, et al. Air pollution and daily mortality in a city with low levels of pollution[J]. Environ Health Perspect, 2003, 111(1): 45-52. doi: 10.1289/ehp.5276
|
[31] |
KLEPEIS N E, NELSON W C, OTT W R, et al. The national human activity pattern survey (NHAPS): a resource for assessing exposure to environmental pollutants[J]. J Expo Anal Environ Epidemiol, 2001, 11(3): 231-252. doi: 10.1038/sj.jea.7500165
|
[32] |
LEECH J A, NELSON W C, BURNETT R T, et al. It's about time: a comparison of Canadian and American time-activity patterns[J]. J Expo Anal Environ Epidemiol, 2002, 12(6): 427-432. doi: 10.1038/sj.jea.7500244
|
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