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Neighbourhood Social Determinants of Health and Geographical Inequalities in Premature Mortality in Taiwan: A Spatiotemporal Approach

Author

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  • Shiue-Shan Weng

    (Institute of Public Health, National Yang Ming Chiao Tung University, Taipei 112, Taiwan
    Department of Nursing, College of Nursing, National Yang Ming Chiao Tung University, Taipei 112, Taiwan)

  • Ta-Chien Chan

    (Institute of Public Health, National Yang Ming Chiao Tung University, Taipei 112, Taiwan
    Research Center for Humanities and Social Sciences, Academia Sinica, Taipei 115, Taiwan)

  • Pei-Ying Hsu

    (Department of Health Care Management, National Taipei University of Nursing and Health Sciences, Taipei 112, Taiwan)

  • Shu-Fen Niu

    (Department of Nursing, Shin Kong Wu Ho-Su Memorial Hospital, Taipei 111, Taiwan
    Department of Nursing, Fu Jen Catholic University, Taipei 242, Taiwan)

Abstract

Geographical inequalities in premature mortality and the role of neighbourhood social determinants of health (SDOH) have been less explored. This study aims to assess the geographical inequalities in premature mortality in Taiwan and how neighbourhood SDOH contribute to them and to examine the place-specific associations between neighbourhood SDOH and premature mortality. We used township-level nationwide data for the years 2015 to 2019, including age-standardized premature mortality rates and three upstream SDOH (ethnicity, education, and income). Space-time scan statistics were used to assess the geographical inequality in premature mortality. A geographical and temporal weighted regression was applied to assess spatial heterogeneity and how neighbourhood SDOH contribute to geographic variation in premature mortality. We found geographical inequality in premature mortality to be clearly clustered around mountainous rural and indigenous areas. The association between neighbourhood SDOH and premature mortality was shown to be area-specific. Ethnicity and education could explain nearly 84% variation in premature mortality. After adjusting for neighbourhood SDOH, only a handful of hotspots for premature mortality remained, mainly consisting of rural and indigenous areas in the central-south region of Taiwan. These findings provide empirical evidence for developing locally tailored public health programs for geographical priority areas.

Suggested Citation

  • Shiue-Shan Weng & Ta-Chien Chan & Pei-Ying Hsu & Shu-Fen Niu, 2021. "Neighbourhood Social Determinants of Health and Geographical Inequalities in Premature Mortality in Taiwan: A Spatiotemporal Approach," IJERPH, MDPI, vol. 18(13), pages 1-14, July.
    • Handle: RePEc:gam:jijerp:v:18:y:2021:i:13:p:7091-:d:587428
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    References listed on IDEAS

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    1. Michelle Del Rio & William L. Hargrove & Joe Tomaka & Marcelo Korc, 2017. "Transportation Matters: A Health Impact Assessment in Rural New Mexico," IJERPH, MDPI, vol. 14(6), pages 1-19, June.
    2. Manfred M. Fischer & Arthur Getis (ed.), 2010. "Handbook of Applied Spatial Analysis," Springer Books, Springer, number 978-3-642-03647-7, April.
    3. Peter James & Jaime E. Hart & Mariana C. Arcaya & Diane Feskanich & Francine Laden & S.V. Subramanian, 2015. "Neighborhood Self-Selection: The Role of Pre-Move Health Factors on the Built and Socioeconomic Environment," IJERPH, MDPI, vol. 12(10), pages 1-16, October.
    4. Tse-Chuan Yang & Leif Jensen, 2015. "Exploring the Inequality-Mortality Relationship in the US with Bayesian Spatial Modeling," Population Research and Policy Review, Springer;Southern Demographic Association (SDA), vol. 34(3), pages 437-460, June.
    5. Bernard, Paul & Charafeddine, Rana & Frohlich, Katherine L. & Daniel, Mark & Kestens, Yan & Potvin, Louise, 2007. "Health inequalities and place: A theoretical conception of neighbourhood," Social Science & Medicine, Elsevier, vol. 65(9), pages 1839-1852, November.
    6. Inhwan Lee & Shinuk Kim & Hyunsik Kang, 2019. "Lifestyle Risk Factors and All-Cause and Cardiovascular Disease Mortality: Data from the Korean Longitudinal Study of Aging," IJERPH, MDPI, vol. 16(17), pages 1-11, August.
    7. Jiemin Ma & Jiaquan Xu & Robert N Anderson & Ahmedin Jemal, 2012. "Widening Educational Disparities in Premature Death Rates in Twenty Six States in the United States, 1993–2007," PLOS ONE, Public Library of Science, vol. 7(7), pages 1-10, July.
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    Cited by:

    1. Peter Akioyamen & Mehmet A. Begen, 2023. "A Spatio-Temporal Analysis of OECD Member Countries’ Health Care Systems: Effects of Data Missingness and Geographically and Temporally Weighted Regression on Inference," IJERPH, MDPI, vol. 20(13), pages 1-18, June.
    2. Laura A. Rodriguez-Villamizar & Diana Marín & Juan Gabriel Piñeros-Jiménez & Oscar Alberto Rojas-Sánchez & Jesus Serrano-Lomelin & Victor Herrera, 2023. "Intraurban Geographic and Socioeconomic Inequalities of Mortality in Four Cities in Colombia," IJERPH, MDPI, vol. 20(2), pages 1-19, January.

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