Abstract
Currently, preventing and controlling air pollution and inhibiting the excessively rapid growth of medical expenditures to reduce the living burden of residents have become a focus of general concern of society as a whole. It is of great significance to conduct an in-depth study of the relationship between air pollution and public health expenditure and clarify to what extent air pollution affects health expenditure. Thus, this paper adopted spatial econometric methods to measure the impact of air pollution on residents’ health expenditure via panel data from 16 core cities in the Yangtze River Delta in China from 2005 to 2017. The results indicate that (1) at present, the air pollution in the Yangtze River Delta core urban agglomeration is still relatively prominent and has obvious spatial aggregation phenomena, and the particulate matter 2.5 (PM2.5) concentration shows the characteristic of decreasing gradually from northwest to southeast; (2) air pollution is the main factor that promotes the increase in residents’ health expenditure; (3) the spatial spillover effect of air pollution is obvious, accounting for half of the total effect; and (4) the impact of government public services on residents’ health expenditure varies. Finally, this paper proposes corresponding policy implications based on the findings.
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References
Balakrishnan K et al (2019) The impact of air pollution on deaths, disease burden, and life expectancy across the states of India: the Global Burden of Disease Study 2017. Lancet Planet Health 3:e26–e39. https://doi.org/10.1016/S2542-5196(18)30261-4
Bao J, Yang X, Zhao Z, Wang Z, Yu C, Li X (2015) The spatial-temporal characteristics of air pollution in China from 2001-2014. Int J Environ Res Public Health 12:15875–15887. https://doi.org/10.3390/ijerph121215029
Blázquez-Fernández C, Cantarero-Prieto D, Pascual-Sáez M (2019) On the nexus of air pollution and health expenditures: new empirical evidence. Gac Sanit 33:389–394. https://doi.org/10.1016/j.gaceta.2018.01.006
Bloemsma LD, Hoek G, Smit LAM (2016) Panel studies of air pollution in patients with COPD: Systematic review and meta-analysis. Environ Res 151:458–468. https://doi.org/10.1016/j.envres.2016.08.018
Cai Y, Shao Y, Wang C (2015) The association of air pollution with the patients' visits to the department of respiratory diseases. J Clin Med Res 7:551–555. https://doi.org/10.14740/jocmr2174e
Carvalho H (2019) Air pollution-related deaths in Europe - time for action. J Glob Health 9:020308. https://doi.org/10.7189/jogh.09.020308
Chen R et al (2012) Association of particulate air pollution with daily mortality: the China air pollution and health effects study. Am J Epidemiol 175:1173–1181. https://doi.org/10.1093/aje/kwr425
Chen H, Liu Y, Zhu Z, Li Z (2017a) Does where you live matter to your health? Investigating factors that influence the self-rated health of urban and rural Chinese residents: evidence drawn from Chinese General Social Survey data. Health Qual Life Outcomes 15:78–11. https://doi.org/10.1186/s12955-017-0658-0
Chen X, Shao S, Tian Z, Xie Z, Yin P (2017b) Impacts of air pollution and its spatial spillover effect on public health based on China’s big data sample. J Clean Prod 142:915–925. https://doi.org/10.1016/j.jclepro.2016.02.119
Chen J, Chen K, Wang G, Chen R, Liu X, Wei G (2019) Indirect economic impact incurred by haze pollution: an econometric and input–output joint model. Int J Environ Res Public Health 16:2328. https://doi.org/10.3390/ijerph16132328
Chen H, Zhang L, Zou W, Gao Q, Zhao H (2020) Regional differences of air pollution in China: comparison of clustering analysis and systematic clustering methods of panel data based on gray relational analysis. Air Qual Atmos Health. https://doi.org/10.1007/s11869-020-00880-0
Deng QZ, Yi YY, Yu KM (2020) Influencing factors and countermeasures of the health of residents in the city clusters along the middle reaches of the Yangtze River. Healthc 8:93. https://doi.org/10.3390/healthcare8020093
Du Y, Du Y, Li T, Li T (2016) Assessment of health-based economic costs linked to fine particulate (PM2.5) pollution: a case study of haze during January 2013 in Beijing, China. Air Qual Atmos Health 9:439–445. https://doi.org/10.1007/s11869-015-0387-7
Elhorst JP (2010) Specification and estimation of spatial panel data models. Int Reg Sci Rev 26:244–268
Enssle F, Kabisch N (2020) Urban green spaces for the social interaction, health and well-being of older people— An integrated view of urban ecosystem services and socio-environmental justice. Environ Sci Policy 109:36–44. https://doi.org/10.1016/j.envsci.2020.04.008
Fan F, Lei Y, Li L (2019) Health damage assessment of particulate matter pollution in Jing-Jin-Ji region of China. Environ Sci Pollut Res Int 26:7883–7895. https://doi.org/10.1007/s11356-018-04116-8
Garcia E, Hurley S, Nelson DO, Hertz A, Reynolds P (2015) Hazardous air pollutants and breast cancer risk in California teachers: a cohort study. Environ Health 14:14–14. https://doi.org/10.1186/1476-069X-14-14
Grossman M (1972) On the concept of health capital and the demand for health. J Polit Econ 80:223–255. https://doi.org/10.1086/259880
Hadian M, Raeissi P, Khalilabad TH (2020) The economic burden of mortality and morbidity due to air pollution in Tehran, Iran: a systematic review. Air Qual Atmos Health 13:1001–1011. https://doi.org/10.1007/s11869-020-00861-3
Han F, Lu X, Xiao C, Chang M, Huang K (2019) Estimation of Health Effects and Economic Losses from Ambient Air Pollution in Undeveloped Areas: Evidence from Guangxi, China. Int J Environ Res Public Health 16:2707. https://doi.org/10.3390/ijerph16152707
He L, Zhang L, Liu R (2019) Energy consumption, air quality, and air pollution spatial spillover effects: evidence from the Yangtze River Delta of China. Chin J Popul Resour Environ 17:329–340. https://doi.org/10.1080/10042857.2019.1650245
LeSage J, Pace RK (2009) Bayesian Spatial Econometric Models. In. Chapman and Hall/CRC, pp 145-176.
Li H, Li H, Song Y, Song Y, Zhang M, Zhang M (2018) Study on the gravity center evolution of air pollution in Yangtze River Delta of China. Nat Hazards (Dordr) 90:1447–1459. https://doi.org/10.1007/s11069-017-3110-1
Li H, Lu J, Li B (2020) Does pollution-intensive industrial agglomeration increase residents’ health expenditure? Sustain Cities Soc 56:102092. https://doi.org/10.1016/j.scs.2020.102092
Lu X, Yao T, Fung JCH, Lin C (2016) Estimation of health and economic costs of air pollution over the Pearl River Delta region in China. Sci Total Environ 566-567:134–143. https://doi.org/10.1016/j.scitotenv.2016.05.060
Raeissi P, Harati-Khalilabad T, Rezapour A, Hashemi SY, Mousavi A, Khodabakhshzadeh S (2018) Effects of air pollution on public and private health expenditures in Iran: a time series study (1972-2014). J Prev Med Public Health 51:140–147. https://doi.org/10.3961/jpmph.17.153
To T et al (2015) Chronic disease prevalence in women and air pollution — A 30-year longitudinal cohort study. Environ Int 80:26–32. https://doi.org/10.1016/j.envint.2015.03.017
Van Donkelaar A, Martin RV, Li C, Burnett RT (2019) Regional estimates of chemical composition of fine particulate matter using a combined geoscience-statistical method with information from satellites, models, and monitors. Environ Sci Technol 53:2595–2611. https://doi.org/10.1021/acs.est.8b06392
Wu Z, Zhang Y, Zhang L, Huang M, Zhong L, Chen D, Wang X (2019) Trends of outdoor air pollution and the impact on premature mortality in the Pearl River Delta region of southern China during 2006–2015. Sci Total Environ 690:248–260. https://doi.org/10.1016/j.scitotenv.2019.06.401
Xu X, Xu Z, Chen L, Li C (2019) How does industrial waste gas emission affect health care expenditure in different regions of China: an application of Bayesian quantile regression. Int J Environ Res Public Health 16:2748. https://doi.org/10.3390/ijerph16152748
Yang J, Zhang B (2018) Air pollution and healthcare expenditure: implication for the benefit of air pollution control in China. Environ Int 120:443–455. https://doi.org/10.1016/j.envint.2018.08.011
Zeng J, He Q (2019) Does industrial air pollution drive health care expenditures? Spatial evidence from China. J Clean Prod 218:400–408. https://doi.org/10.1016/j.jclepro.2019.01.288
Zeng, Du, Zhang (2019) Spatial-temporal effects of PM2.5 on health burden: evidence from China. Int J Environ Res Public Health 16:4695. https://doi.org/10.3390/ijerph16234695
Zhao X, Yu X, Wang Y, Fan C (2016) Economic evaluation of health losses from air pollution in Beijing, China. Environ Sci Pollut Res 23:11716–11728. https://doi.org/10.1007/s11356-016-6270-8
Zhao H, Cao X, Ma T (2020) A spatial econometric empirical research on the impact of industrial agglomeration on haze pollution in China. Air Qual Atmos Health. https://doi.org/10.1007/s11869-020-00884-w
Zhou M et al (2019) Mortality, morbidity, and risk factors in China and its provinces, 1990–2017: a systematic analysis for the Global Burden of Disease Study 2017. Lancet 394:1145–1158. https://doi.org/10.1016/S0140-6736(19)30427-1
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This research is supported by the Project of National Social Science Foundation of China (NSSFC): Study on the Spatial Effects and Governance Strategies of the Impact of Urban Haze Pollution on Public Health (No. 17BJY063).
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Sun, H., Leng, Z., Zhao, H. et al. The impact of air pollution on urban residents’ health expenditure: spatial evidence from Yangtze River Delta, China. Air Qual Atmos Health 14, 343–350 (2021). https://doi.org/10.1007/s11869-020-00939-y
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DOI: https://doi.org/10.1007/s11869-020-00939-y