Socioeconomic disparities of life expectancy: Analysis of 34 provinces in indonesia as of 2019
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Facullty of Public Health Universitas Indonesia Indonesian Public Health Assocition Facullty of Public Health Universitas Indonesia Kampus UI Depok Indonesia, 16424 Indonesia
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Facullty of Public Health Universitas Indonesia Indonesian Public Health Assocition (IPHA) Research and Community Service Center Faculty of Public Health Universitas Indonesia Kampus UI Depok, Indonesia 16424 Indonesia
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Department of Health Policy and Administration, Faculty of Public Health Universitas Indonesia Indonesian Public Health Assocition (IPHA) Kampus UI Depok, Indonesia 16424 Indonesia
Publication date: 2023-04-26
Popul. Med. 2023;5(Supplement):A805
ABSTRACT
Background:
Life expectancy at birth is one of the Human Development Index (HDI) that measure human development. More than half of Provinces in Indonesia have average of life expectancy at birth lower than the average of national life expectancy at birth (71,3 years). The range of gap is 10 years between Provinces with the lowest and highest life expectancy average at birth.
Objective:
To analyze the effect of socioeconomic disparities to Life expectancy at birth among provinces in Indonesia based on data 2019
Methods:
We used aggregate data of Province and Districts Government Budget Allocation for Health from Ministry of Finance and other socioeconomic data form the Central Bureau of Statistics. Dependent variables included average life expectancy of people in each Provinces. Independent variables included the socioeconomic aspect from each Province such as availability of healthcare and physicians, dependency ratio estimates, government budget allocation for health and proportion of people with income below half of the median. Pearson correlation test used to see the correlation between dependent and independent variables.
Results:
We found significant correlation between life expectancy average at birth with dependency ratio (r=-0,467, p-value=0,00), proportion of people with income below median (r=-0,386, p-value=0,02), and hospital ratio per 1.000 people (r=0,355, p-value=0,04). While there are no correlation between life expectancy average at birth with the other independent variable such as physician ratio per 100.000 people, public health center ratio per 100.000 people, poverty percentage and government budget allocation for health.
Conclusions:
There are significant disparities of life expectancy average at birth in socioeconomic aspect among Provinces in Indonesia. This study could be evidence-based input for the policymakers to reduce the disparities among Province or evermore to increase life expectancy average at birth.