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Estimating Temperature-Mortality Exposure-Response Relationships and Optimum Ambient Temperature at the Multi-City Level of China

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Listed:
  • Qiang Zeng

    (Tianjin Centers for Disease Control and Prevention, Huayue Road, Hedong District, Tianjin 300011, China)

  • Guoxing Li

    (Department of Occupational and Environmental Health, School of Public Health, Peking University, Xueyuan Road, Haidian District, Beijing 100191, China)

  • Yushan Cui

    (Tianjin Centers for Disease Control and Prevention, Huayue Road, Hedong District, Tianjin 300011, China)

  • Guohong Jiang

    (Tianjin Centers for Disease Control and Prevention, Huayue Road, Hedong District, Tianjin 300011, China)

  • Xiaochuan Pan

    (Department of Occupational and Environmental Health, School of Public Health, Peking University, Xueyuan Road, Haidian District, Beijing 100191, China)

Abstract

Few studies have explored temperature–mortality relationships in China, especially at the multi-large city level. This study was based on the data of seven typical, large Chinese cities to examine temperature-mortality relationships and optimum temperature of China. A generalized additive model (GAM) was applied to analyze the acute-effect of temperature on non-accidental mortality, and meta-analysis was used to merge data. Furthermore, the lagged effects of temperature up to 40 days on mortality and optimum temperature were analyzed using the distributed lag non-linear model (DLNM). We found that for all non-accidental mortality, high temperature could significantly increase the excess risk (ER) of death by 0.33% (95% confidence interval: 0.11%, 0.56%) with the temperature increase of 1 °C. Similar but non-significant ER of death was observed when temperature decreased. The lagged effect of temperature showed that the relative risk of non-accidental mortality was lowest at 21 °C. Our research suggests that high temperatures are more likely to cause an acute increase in mortality. There was a lagged effect of temperature on mortality, with an optimum temperature of 21 °C. Our results could provide a theoretical basis for climate-related public health policy.

Suggested Citation

  • Qiang Zeng & Guoxing Li & Yushan Cui & Guohong Jiang & Xiaochuan Pan, 2016. "Estimating Temperature-Mortality Exposure-Response Relationships and Optimum Ambient Temperature at the Multi-City Level of China," IJERPH, MDPI, vol. 13(3), pages 1-12, March.
    • Handle: RePEc:gam:jijerp:v:13:y:2016:i:3:p:279-:d:65022
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    References listed on IDEAS

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    1. Jonathan A. Patz & Diarmid Campbell-Lendrum & Tracey Holloway & Jonathan A. Foley, 2005. "Impact of regional climate change on human health," Nature, Nature, vol. 438(7066), pages 310-317, November.
    2. Vandentorren, S. & Suzan, F. & Medina, S. & Pascal, M. & Maulpoix, A. & Cohen, J.-C. & Ledrans, M., 2004. "Mortality in 13 French cities during the August 2003 heat wave," American Journal of Public Health, American Public Health Association, vol. 94(9), pages 1518-1520.
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    Cited by:

    1. Xerxes T. Seposo & Tran Ngoc Dang & Yasushi Honda, 2017. "How Does Ambient Air Temperature Affect Diabetes Mortality in Tropical Cities?," IJERPH, MDPI, vol. 14(4), pages 1-10, April.
    2. Ru Cao & Yuxin Wang & Jing Huang & Jie He & Pitakchon Ponsawansong & Jianbo Jin & Zhihu Xu & Teng Yang & Xiaochuan Pan & Tippawan Prapamontol & Guoxing Li, 2021. "The Mortality Effect of Apparent Temperature: A Multi-City Study in Asia," IJERPH, MDPI, vol. 18(9), pages 1-12, April.
    3. Wentan Dong & Qiang Zeng & Yue Ma & Guoxing Li & Xiaochuan Pan, 2016. "Impact of Heat Wave Definitions on the Added Effect of Heat Waves on Cardiovascular Mortality in Beijing, China," IJERPH, MDPI, vol. 13(9), pages 1-12, September.

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