Abstract
BACKGROUND: Health indicators, such as mortality rates or life expectancy, need to be presented at the local level to improve the health of local residents and to reduce health inequality across geographic areas. The aim of this study was to estimate life expectancy at the district level in Korea through a spatio-temporal analysis. METHODS: Spatio-temporal models were applied to the National Health Information Database of the National Health Insurance Service to estimate the mortality rates for 19 age groups in 250 districts from 2004 to 2017 by gender in Korea. Annual district-level life tables by gender were constructed using the estimated mortality rates, and then annual district-level life expectancy by gender was estimated using the life table method and the Kannisto-Thatcher method. The annual district-level life expectancies based on the spatio-temporal models were compared to the life expectancies calculated under the assumption that the mortality rates in these 250 districts are independent from one another. RESULTS: In 2017, district-level life expectancy at birth ranged from 75.5 years (95% credible interval [CI], 74.0-77.0 years) to 84.2 years (95% CI, 83.4-85.0 years) for men and from 83.9 years (95% CI, 83.2-84.6 years) to 88.2 years (95% CI, 87.3-89.1 years) for women. Between 2004 and 2017, district-level life expectancy at birth increased by 4.57 years (95% CI, 4.49-4.65 years) for men and by 4.06 years (95% CI, 3.99-4.12 years) for women. To obtain stable annual life expectancy estimates at the district level, it is recommended to use the life expectancy based on spatio-temporal models instead of calculating life expectancy using observed mortality. CONCLUSION: In this study, we estimated the annual district-level life expectancy from 2004 to 2017 in Korea by gender using a spatio-temporal model. Local governments could use annual district-level life expectancy estimates as a performance indicator of health policies to improve the health of local residents. The approach to district-level analysis with spatio-temporal modeling employed in this study could be used in future analyses to produce district-level health-related indicators in Korea.