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Income-Related Mortality Inequalities and Its Social Factors among Middle-Aged and Older Adults at the District Level in Aging Seoul: An Ecological Study Using Administrative Big Data

Author

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  • Minhye Kim

    (Department of Sociology, College of Social Science, Changwon National University, Changwon-si 51140, Korea)

  • Suzin You

    (Inequality and Social Policy Institute, Gachon University, Seongnam-si 13120, Korea)

  • Jong-sung You

    (Inequality and Social Policy Institute, Gachon University, Seongnam-si 13120, Korea)

  • Seung-Yun Kim

    (Department of Urban Society Research, Seoul Institute, Seoul 06756, Korea)

  • Jong Heon Park

    (Big Data Steering Department, National Health Insurance Service, Wonju-si 26464, Korea)

Abstract

This study investigated income-related health inequality at sub-national level, focusing on mortality inequality among middle-aged and older adults (MOAs). Specifically, we examined income-related mortality inequality and its social factors among MOAs across 25 districts in Seoul using administrative big data from the National Health Insurance Service (NHIS). We obtained access to the NHIS’s full-population micro-data on both incomes and demographic variables for the entire residents of Seoul. Slope Index of Inequality (SII) and Relative Index of Inequality (RII) were calculated. The effects of social attributes of districts on SIIs and RIIs were examined through ordinary least squares and spatial regressions. There were clear income-related mortality gradients. Cross-district variance of mortality rates was greater among the lowest income group. SIIs were smaller in wealthier districts. Weak spatial correlation was found in SIIs among men. Lower RIIs were linked to lower Gini coefficients of income for both genders. SIIs (men) were associated with higher proportions of special occupational pensioners and working population. Lower SIIs and RIIs (women) were associated with higher proportions of female household heads. The results suggest that increasing economic activities, targeting households with female heads, reforming public pensions, and reducing income inequality among MOAs can be good policy directions.

Suggested Citation

  • Minhye Kim & Suzin You & Jong-sung You & Seung-Yun Kim & Jong Heon Park, 2021. "Income-Related Mortality Inequalities and Its Social Factors among Middle-Aged and Older Adults at the District Level in Aging Seoul: An Ecological Study Using Administrative Big Data," IJERPH, MDPI, vol. 19(1), pages 1-17, December.
    • Handle: RePEc:gam:jijerp:v:19:y:2021:i:1:p:383-:d:714581
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    References listed on IDEAS

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    1. André Decoster & Thomas Minten & Johannes Spinnewijn, 2021. "The Income Gradient in Mortality during the Covid-19 Crisis: Evidence from Belgium," The Journal of Economic Inequality, Springer;Society for the Study of Economic Inequality, vol. 19(3), pages 551-570, September.
    2. Mosquera, Paola A. & San Sebastian, Miguel & Waenerlund, Anna-Karin & Ivarsson, Anneli & Weinehall, Lars & Gustafsson, Per E., 2016. "Income-related inequalities in cardiovascular disease from mid-life to old age in a Northern Swedish cohort: A decomposition analysis," Social Science & Medicine, Elsevier, vol. 149(C), pages 135-144.
    3. Anselin, Luc & Bera, Anil K. & Florax, Raymond & Yoon, Mann J., 1996. "Simple diagnostic tests for spatial dependence," Regional Science and Urban Economics, Elsevier, vol. 26(1), pages 77-104, February.
    4. Randall S. Jones, 2010. "Health-Care Reform in Korea," OECD Economics Department Working Papers 797, OECD Publishing.
    5. Young-Eun Kim & Yoon-Sun Jung & Minsu Ock & Hyesook Park & Ki-Beom Kim & Dun-Sol Go & Seok-Jun Yoon, 2021. "The Gaps in Health-Adjusted Life Years (HALE) by Income and Region in Korea: A National Representative Bigdata Analysis," IJERPH, MDPI, vol. 18(7), pages 1-8, March.
    6. Lei Yang & Zhenbo Wang, 2020. "Early-Life Conditions and Cognitive Function in Middle-and Old-Aged Chinese Adults: A Longitudinal Study," IJERPH, MDPI, vol. 17(10), pages 1-13, May.
    7. Kinge, Jonas Minet & Vallejo-Torres, Laura & Morris, Stephen, 2015. "Income related inequalities in avoidable mortality in Norway: A population-based study using data from 1994–2011," Health Policy, Elsevier, vol. 119(7), pages 889-898.
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