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Spatio-Temporal Variation and Prediction of Ischemic Heart Disease Hospitalizations in Shenzhen, China

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  • Yanxia Wang

    (School of Resource and Environmental Science, Wuhan University, 129 Luoyu Road, Wuhan 430079, China
    Key Laboratory of GIS, Ministry of Education, Wuhan University, 129 Luoyu Road, Wuhan 430079, China)

  • Qingyun Du

    (School of Resource and Environmental Science, Wuhan University, 129 Luoyu Road, Wuhan 430079, China
    Key Laboratory of GIS, Ministry of Education, Wuhan University, 129 Luoyu Road, Wuhan 430079, China)

  • Fu Ren

    (School of Resource and Environmental Science, Wuhan University, 129 Luoyu Road, Wuhan 430079, China
    Key Laboratory of GIS, Ministry of Education, Wuhan University, 129 Luoyu Road, Wuhan 430079, China)

  • Shi Liang

    (Shenzhen Center for Health Information, Renmin Road North 2210, Luohu District, Shenzhen 518001, China)

  • De-nan Lin

    (Shenzhen Center for Health Information, Renmin Road North 2210, Luohu District, Shenzhen 518001, China)

  • Qin Tian

    (School of Resource and Environmental Science, Wuhan University, 129 Luoyu Road, Wuhan 430079, China
    Key Laboratory of GIS, Ministry of Education, Wuhan University, 129 Luoyu Road, Wuhan 430079, China)

  • Yan Chen

    (Shenzhen Center for Health Information, Renmin Road North 2210, Luohu District, Shenzhen 518001, China)

  • Jia-jia Li

    (Shenzhen Center for Health Information, Renmin Road North 2210, Luohu District, Shenzhen 518001, China)

Abstract

Ischemic heart disease (IHD) is a leading cause of death worldwide. Urban public health and medical management in Shenzhen, an international city in the developing country of China, is challenged by an increasing burden of IHD. This study analyzed the spatio-temporal variation of IHD hospital admissions from 2003 to 2012 utilizing spatial statistics, spatial analysis, and space-time scan statistics. The spatial statistics and spatial analysis measured the incidence rate (hospital admissions per 1,000 residents) and the standardized rate (the observed cases standardized by the expected cases) of IHD at the district level to determine the spatio-temporal distribution and identify patterns of change. The space-time scan statistics was used to identify spatio-temporal clusters of IHD hospital admissions at the district level. The other objective of this study was to forecast the IHD hospital admissions over the next three years (2013–2015) to predict the IHD incidence rates and the varying burdens of IHD-related medical services among the districts in Shenzhen. The results show that the highest hospital admissions, incidence rates, and standardized rates of IHD are in Futian. From 2003 to 2012, the IHD hospital admissions exhibited similar mean centers and directional distributions, with a slight increase in admissions toward the north in accordance with the movement of the total population. The incidence rates of IHD exhibited a gradual increase from 2003 to 2012 for all districts in Shenzhen, which may be the result of the rapid development of the economy and the increasing traffic pollution. In addition, some neighboring areas exhibited similar temporal change patterns, which were also detected by the spatio-temporal cluster analysis. Futian and Dapeng would have the highest and the lowest hospital admissions, respectively, although these districts have the highest incidence rates among all of the districts from 2013 to 2015 based on the prediction using the GM (1,1). In addition, the combined analysis of the prediction of IHD hospital admissions and the general hospital distributions shows that Pingshan and Longgang might experience the most serious burden of IHD hospital services in the near future, although Futian would still have the greatest number and the highest incidence rate of hospital admissions for IHD.

Suggested Citation

  • Yanxia Wang & Qingyun Du & Fu Ren & Shi Liang & De-nan Lin & Qin Tian & Yan Chen & Jia-jia Li, 2014. "Spatio-Temporal Variation and Prediction of Ischemic Heart Disease Hospitalizations in Shenzhen, China," IJERPH, MDPI, vol. 11(5), pages 1-26, May.
    • Handle: RePEc:gam:jijerp:v:11:y:2014:i:5:p:4799-4824:d:35779
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    Cited by:

    1. Jinli Duan & Feng Jiao & Qishan Zhang & Zhibin Lin, 2017. "Predicting Urban Medical Services Demand in China: An Improved Grey Markov Chain Model by Taylor Approximation," IJERPH, MDPI, vol. 14(8), pages 1-12, August.
    2. Chengzhen Bao & Mamat Mayila & Zhenhua Ye & Jianbing Wang & Mingjuan Jin & Wenjiong He & Kun Chen, 2015. "Forecasting and Analyzing the Disease Burden of Aged Population in China, Based on the 2010 Global Burden of Disease Study," IJERPH, MDPI, vol. 12(7), pages 1-13, June.
    3. Qingyun Du & Mingxiao Zhang & Yayan Li & Hui Luan & Shi Liang & Fu Ren, 2016. "Spatial Patterns of Ischemic Heart Disease in Shenzhen, China: A Bayesian Multi-Disease Modelling Approach to Inform Health Planning Policies," IJERPH, MDPI, vol. 13(4), pages 1-14, April.
    4. Yuliang Xi & Fu Ren & Shi Liang & Jinghua Zhang & De-Nan Lin, 2014. "Spatial Analysis of the Distribution, Risk Factors and Access to Medical Resources of Patients with Hepatitis B in Shenzhen, China," IJERPH, MDPI, vol. 11(11), pages 1-23, November.

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