Dataset Information

Spatio-temporal Analysis of District-level Life Expectancy from 2004 to 2017 in Korea.

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.

SUBMITTER: Lim HK

PROVIDER: S-EPMC7801148 | biostudies-literature | 2021 Jan

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Spatio-temporal Analysis of District-level Life Expectancy from 2004 to 2017 in Korea.

Lim Hwa Kyung HK Kang Hee Yeon HY Kim Ikhan I Khang Young Ho YH

Journal of Korean medical science 20210111 2

<h4>Background</h4>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.<h4>Methods</h4>Spatio-temporal models were applied to the National Health Information Database of the National Health Insurance Service to estimate the mortali ...[more]

PMID: 33429472

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Project description:BACKGROUND:Malaria transmission is influenced by a complex interplay of factors including climate, socio-economic, environmental factors and interventions. Malaria control efforts across Africa have shown a mixed impact. Climate driven factors may play an increasing role with climate change. Efforts to strengthen routine facility-based monthly malaria data collection across Africa create an increasingly valuable data source to interpret burden trends and monitor control programme progress. A better understanding of the association with other climatic and non-climatic drivers of malaria incidence over time and space may help guide and interpret the impact of interventions. METHODS:Routine monthly paediatric outpatient clinical malaria case data were compiled from 27 districts in Malawi between 2004 and 2017, and analysed in combination with data on climatic, environmental, socio-economic and interventional factors and district level population estimates. A spatio-temporal generalized linear mixed model was fitted using Bayesian inference, in order to quantify the strength of association of the various risk factors with district-level variation in clinical malaria rates in Malawi, and visualized using maps. RESULTS:Between 2004 and 2017 reported childhood clinical malaria case rates showed a slight increase, from 50 to 53 cases per 1000 population, with considerable variation across the country between climatic zones. Climatic and environmental factors, including average monthly air temperature and rainfall anomalies, normalized difference vegetative index (NDVI) and RDT use for diagnosis showed a significant relationship with malaria incidence. Temperature in the current month and in each of the 3 months prior showed a significant relationship with the disease incidence unlike rainfall anomaly which was associated with malaria incidence at only three months prior. Estimated risk maps show relatively high risk along the lake and Shire valley regions of Malawi. CONCLUSION:The modelling approach can identify locations likely to have unusually high or low risk of malaria incidence across Malawi, and distinguishes between contributions to risk that can be explained by measured risk-factors and unexplained residual spatial variation. Also, spatial statistical methods applied to readily available routine data provides an alternative information source that can supplement survey data in policy development and implementation to direct surveillance and intervention efforts.

Dataset Information

Spatio-temporal Analysis of District-level Life Expectancy from 2004 to 2017 in Korea.

Background

Methods

Results

Conclusion

Publications

Spatio-temporal Analysis of District-level Life Expectancy from 2004 to 2017 in Korea.

Similar Datasets

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