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Life Expectancy and Inequalities Therein by Income From 2016 to 2018 Across the 253 Electoral Constituencies of the National Assembly of the Korea

  • Bahk, Jinwook (Department of Public Health, Keimyung University) ;
  • Kang, Hee-Yeon (Department of Health Policy and Management, Seoul National University College of Medicine) ;
  • Khang, Young-Ho (Department of Health Policy and Management, Seoul National University College of Medicine)
  • 투고 : 2020.02.20
  • 심사 : 2020.03.02
  • 발행 : 2020.03.31

초록

Objectives: We calculated life expectancy and inequalities therein by income for the period of 2016-2018 across the 253 electoral constituencies of the 20th National Assembly election in Korea. Methods: We obtained population and death data between 2016 and 2018 from the National Health Information Database and constructed abridged life tables using standard life table procedures according to gender and income quintiles for the electoral constituencies of the 20th National Assembly election held in 2016. Results: Life expectancy across the 253 constituencies ranged from 80.51 years to 87.05 years, corresponding to a gap of 6.54 years. The life expectancy difference by income across the 253 constituencies ranged from 2.94 years to 10.67 years. In each province, the difference in life expectancy by income across electoral constituencies was generally greater than the inter-constituency differences. Constituencies in capital and metropolitan areas showed a higher life expectancy and a lower life expectancy difference by income than constituencies in rural areas. Conclusions: Pro-rich inequalities in life expectancy by income existed in every electoral constituency in Korea. Both intra-constituency and inter-constituency socioeconomic inequalities in health should be highlighted in future policy-making in the National Assembly.

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참고문헌

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피인용 문헌

  1. 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 vol.19, pp.1, 2020, https://doi.org/10.3390/ijerph19010383