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.

Minhye Kim,Jong Heon Park,Seung-Yun Kim,Suzin You,Jong-Sung You

doi:10.3390/ijerph19010383

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.

Highlights

Use of administrative income data in social science and social epidemiology has been limited [1]
By accounting for spatial autocorrelation of the outcome, Slope Index of Inequality (SII) of men, we found that the effect of special occupational pension marginally increased
Higher SII for women was associated with higher proportion of female household head

Summary

Introduction

Use of administrative income data in social science and social epidemiology has been limited [1]. Population-based information on income from tax authorities has begun to be available for research starting from Scandinavian countries [2]. This provides an opportunity to make a breakthrough, as the improvement of the quality of individual income status and area-level factors such as Gini coefficient of income has been an important remaining task in health inequality research [3]. Reduction of health inequality is one of the main policy goals in the Health. Insufficient attention has been paid to the health inequality among older adults despite the country’s rapid aging.

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