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The Impact of Particulate Matter on Outdoor Activity and Mental Health: A Matching Approach

Author

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  • Miyeon Jung

    (College of Business, Korea Advanced Institute of Science and Technology, 85 Hoegiro Dongdaemoon-gu, Seoul 02455, Korea)

  • Daegon Cho

    (College of Business, Korea Advanced Institute of Science and Technology, 85 Hoegiro Dongdaemoon-gu, Seoul 02455, Korea)

  • Kwangsoo Shin

    (Department of Bio-Medical Convergence, College of Medicine, Chungbuk National University, 1 Chungdae-ro, Seowin-gu, Cheongju-si 28644, Korea)

Abstract

Exposure to air pollution affects human activity and health. Particularly, in Asian countries, the influence of particulate matter on humans has received wide attention. However, there is still a lack of research about the effects of particulate matter on human outdoor activities and mental health. Therefore, we aimed to explore the association between exposure to particulate matter with a diameter of less than 10 µm (PM10) and outdoor activity along with mental health in South Korea where issues caused by particulate matter increasingly have social and economic impacts. We examined this relationship by combining the physical and habitual factors of approximately 100,000 people in 2015 from the Korean National Health Survey. To measure each individual’s exposure to particulate matter, we computed the total hours exposed to a high PM10 concentration (>80 μg/m 3 ) in a given district one month before the survey was conducted. After dividing all districts into six groups according to the exposed level of the high PM10, we applied the propensity score-weighting method to control for observable background characteristics. We then estimated the impact of the high PM10 on outdoor activity and mental health between the weighted individuals in each group. Our main findings suggest that the impact of PM10 on outdoor activity and stress shows an inverted-U shaped function, which is counterintuitive. Specifically, both outdoor activity and stress levels tend to be worsened when the exposure time to a high PM10 (>80 μg/m 3 ) was more than 20 h. Related policy implications are discussed.

Suggested Citation

  • Miyeon Jung & Daegon Cho & Kwangsoo Shin, 2019. "The Impact of Particulate Matter on Outdoor Activity and Mental Health: A Matching Approach," IJERPH, MDPI, vol. 16(16), pages 1-17, August.
    • Handle: RePEc:gam:jijerp:v:16:y:2019:i:16:p:2983-:d:259041
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    References listed on IDEAS

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    1. Lavy, Victor & Ebenstein, Avraham & Roth, Sefi, 2014. "The Impact of Short Term Exposure to Ambient Air Pollution on Cognitive Performance and Human Capital Formation," CEPR Discussion Papers 10302, C.E.P.R. Discussion Papers.
    2. Neidell, Matthew J., 2004. "Air pollution, health, and socio-economic status: the effect of outdoor air quality on childhood asthma," Journal of Health Economics, Elsevier, vol. 23(6), pages 1209-1236, November.
    3. Joshua Graff Zivin & Matthew Neidell, 2012. "The Impact of Pollution on Worker Productivity," American Economic Review, American Economic Association, vol. 102(7), pages 3652-3673, December.
    4. Qingkun Song & David C. Christiani & XiaorongWang & Jun Ren, 2014. "The Global Contribution of Outdoor Air Pollution to the Incidence, Prevalence, Mortality and Hospital Admission for Chronic Obstructive Pulmonary Disease: A Systematic Review and Meta-Analysis," IJERPH, MDPI, vol. 11(11), pages 1-11, November.
    5. Jeffrey M. Wooldridge, 2002. "Inverse probability weighted M-estimators for sample selection, attrition, and stratification," Portuguese Economic Journal, Springer;Instituto Superior de Economia e Gestao, vol. 1(2), pages 117-139, August.
    6. Jeffrey M. Wooldridge, 2004. "Inverse probability weighted estimation for general missing data problems," CeMMAP working papers 05/04, Institute for Fiscal Studies.
    7. Wooldridge, Jeffrey M., 2007. "Inverse probability weighted estimation for general missing data problems," Journal of Econometrics, Elsevier, vol. 141(2), pages 1281-1301, December.
    8. Di Novi, Cinzia, 2013. "The indirect effect of fine particulate matter on health through individuals’ life-style," Journal of Behavioral and Experimental Economics (formerly The Journal of Socio-Economics), Elsevier, vol. 44(C), pages 27-36.
    9. Cohen, Barney, 2006. "Urbanization in developing countries: Current trends, future projections, and key challenges for sustainability," Technology in Society, Elsevier, vol. 28(1), pages 63-80.
    10. Jeffrey M. Wooldridge, 2002. "Inverse probability weighted M-estimators for sample selection, attrition and stratification," CeMMAP working papers 11/02, Institute for Fiscal Studies.
    11. Ok-Jin Kim & Sun-Young Kim & Ho Kim, 2017. "Association between Long-Term Exposure to Particulate Matter Air Pollution and Mortality in a South Korean National Cohort: Comparison across Different Exposure Assessment Approaches," IJERPH, MDPI, vol. 14(10), pages 1-14, September.
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    1. Kyungsoo Kim & Il-Youp Kwak & Hyunjin Min, 2021. "Particulate Matter 10 (PM 10 ) Is Associated with Epistaxis in Children and Adults," IJERPH, MDPI, vol. 18(9), pages 1-10, April.

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