IDEAS home Printed from https://ideas.repec.org/a/gam/jijerp/v12y2015i12p15042-16156d60926.html
   My bibliography  Save this article

Effects of Extreme Temperatures on Cause-Specific Cardiovascular Mortality in China

Author

Listed:
  • Xuying Wang

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

  • Guoxing Li

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

  • Liqun Liu

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

  • Dane Westerdahl

    (Sibley School of Mechanical and Aerospace Engineering, Cornell University, Ithaca, NY 14850, USA)

  • Xiaobin Jin

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

  • Xiaochuan Pan

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

Abstract

Objective : Limited evidence is available for the effects of extreme temperatures on cause-specific cardiovascular mortality in China. Methods : We collected data from Beijing and Shanghai, China, during 2007–2009, including the daily mortality of cardiovascular disease, cerebrovascular disease, ischemic heart disease and hypertensive disease, as well as air pollution concentrations and weather conditions. We used Poisson regression with a distributed lag non-linear model to examine the effects of extremely high and low ambient temperatures on cause-specific cardiovascular mortality. Results : For all cause-specific cardiovascular mortality, Beijing had stronger cold and hot effects than those in Shanghai. The cold effects on cause-specific cardiovascular mortality reached the strongest at lag 0–27, while the hot effects reached the strongest at lag 0–14. The effects of extremely low and high temperatures differed by mortality types in the two cities. Hypertensive disease in Beijing was particularly susceptible to both extremely high and low temperatures; while for Shanghai, people with ischemic heart disease showed the greatest relative risk (RRs = 1.16, 95% CI: 1.03, 1.34) to extremely low temperature. Conclusion : People with hypertensive disease were particularly susceptible to extremely low and high temperatures in Beijing. People with ischemic heart disease in Shanghai showed greater susceptibility to extremely cold days.

Suggested Citation

  • Xuying Wang & Guoxing Li & Liqun Liu & Dane Westerdahl & Xiaobin Jin & Xiaochuan Pan, 2015. "Effects of Extreme Temperatures on Cause-Specific Cardiovascular Mortality in China," IJERPH, MDPI, vol. 12(12), pages 1-21, December.
  • Handle: RePEc:gam:jijerp:v:12:y:2015:i:12:p:15042-16156:d:60926
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1660-4601/12/12/15042/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/1660-4601/12/12/15042/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Gasparrini, Antonio, 2011. "Distributed Lag Linear and Non-Linear Models in R: The Package dlnm," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 43(i08).
    2. Hirotugu Akaike, 1987. "Factor analysis and AIC," Psychometrika, Springer;The Psychometric Society, vol. 52(3), pages 317-332, September.
    3. Yu-Kai Lin & Chin-Kuo Chang & Yu-Chun Wang & Tsung-Jung Ho, 2013. "Acute and Prolonged Adverse Effects of Temperature on Mortality from Cardiovascular Diseases," PLOS ONE, Public Library of Science, vol. 8(12), pages 1-8, December.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Mengxuan Li & Benjamin A. Shaw & Wangjian Zhang & Elizabeth Vásquez & Shao Lin, 2019. "Impact of Extremely Hot Days on Emergency Department Visits for Cardiovascular Disease among Older Adults in New York State," IJERPH, MDPI, vol. 16(12), pages 1-13, June.
    2. Sida Liu & Emily Yang Ying Chan & William Bernard Goggins & Zhe Huang, 2020. "The Mortality Risk and Socioeconomic Vulnerability Associated with High and Low Temperature in Hong Kong," IJERPH, MDPI, vol. 17(19), pages 1-14, October.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Jiwon Lee & Midam An & Yongku Kim & Jung-In Seo, 2021. "Optimal Allocation for Electric Vehicle Charging Stations," Energies, MDPI, vol. 14(18), pages 1-10, September.
    2. Benjamin G Schultz & Catherine J Stevens & Peter E Keller & Barbara Tillmann, 2013. "A Sequence Identification Measurement Model to Investigate the Implicit Learning of Metrical Temporal Patterns," PLOS ONE, Public Library of Science, vol. 8(9), pages 1-1, September.
    3. Daniela Andreini & Diego Rinallo & Giuseppe Pedeliento & Mara Bergamaschi, 2017. "Brands and Religion in the Secularized Marketplace and Workplace: Insights from the Case of an Italian Hospital Renamed After a Roman Catholic Pope," Journal of Business Ethics, Springer, vol. 141(3), pages 529-550, March.
    4. Martina S. Ragettli & Apolline Saucy & Benjamin Flückiger & Danielle Vienneau & Kees de Hoogh & Ana M. Vicedo-Cabrera & Christian Schindler & Martin Röösli, 2023. "Explorative Assessment of the Temperature–Mortality Association to Support Health-Based Heat-Warning Thresholds: A National Case-Crossover Study in Switzerland," IJERPH, MDPI, vol. 20(6), pages 1-16, March.
    5. Yunquan Zhang & Chuanhua Yu & Jin Yang & Lan Zhang & Fangfang Cui, 2017. "Diurnal Temperature Range in Relation to Daily Mortality and Years of Life Lost in Wuhan, China," IJERPH, MDPI, vol. 14(8), pages 1-11, August.
    6. Andreas Wienke & Anne M. Herskind & Kaare Christensen & Axel Skytthe & Anatoli I. Yashin, 2002. "The influence of smoking and BMI on heritability in susceptibility to coronary heart disease," MPIDR Working Papers WP-2002-003, Max Planck Institute for Demographic Research, Rostock, Germany.
    7. Iara da Silva & Caroline Fernanda Hei Wikuats & Elizabeth Mie Hashimoto & Leila Droprinchinski Martins, 2022. "Effects of Environmental and Socioeconomic Inequalities on Health Outcomes: A Multi-Region Time-Series Study," IJERPH, MDPI, vol. 19(24), pages 1-22, December.
    8. Byrd, T. A. & Marshall, T. E., 1997. "Relating information technology investment to organizational performance: a causal model analysis," Omega, Elsevier, vol. 25(1), pages 43-56, February.
    9. Berry, Brian J.L. & Okulicz-Kozaryn, Adam, 2008. "Are there ENSO signals in the macroeconomy," Ecological Economics, Elsevier, vol. 64(3), pages 625-633, January.
    10. Nicos Nicolaou & Scott Shane, 2019. "Common genetic effects on risk-taking preferences and choices," Journal of Risk and Uncertainty, Springer, vol. 59(3), pages 261-279, December.
    11. Stephen Richards, 2010. "Author's response," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 173(4), pages 920-924, October.
    12. Michael Tong & Berhanu Wondmagegn & Jianjun Xiang & Alana Hansen & Keith Dear & Dino Pisaniello & Blesson Varghese & Jianguo Xiao & Le Jian & Benjamin Scalley & Monika Nitschke & John Nairn & Hilary B, 2022. "Hospitalization Costs of Respiratory Diseases Attributable to Temperature in Australia and Projections for Future Costs in the 2030s and 2050s under Climate Change," IJERPH, MDPI, vol. 19(15), pages 1-16, August.
    13. Ken B Hanscombe & Maciej Trzaskowski & Claire M A Haworth & Oliver S P Davis & Philip S Dale & Robert Plomin, 2012. "Socioeconomic Status (SES) and Children's Intelligence (IQ): In a UK-Representative Sample SES Moderates the Environmental, Not Genetic, Effect on IQ," PLOS ONE, Public Library of Science, vol. 7(2), pages 1-16, February.
    14. Zhang, Quanzhong & Wei, Haiyan & Liu, Jing & Zhao, Zefang & Ran, Qiao & Gu, Wei, 2021. "A Bayesian network with fuzzy mathematics for species habitat suitability analysis: A case with limited Angelica sinensis (Oliv.) Diels data," Ecological Modelling, Elsevier, vol. 450(C).
    15. Oh, Man-Suk, 2014. "Bayesian comparison of models with inequality and equality constraints," Statistics & Probability Letters, Elsevier, vol. 84(C), pages 176-182.
    16. Kai Luo & Wenjing Li & Ruiming Zhang & Runkui Li & Qun Xu & Yang Cao, 2016. "Ambient Fine Particulate Matter Exposure and Risk of Cardiovascular Mortality: Adjustment of the Meteorological Factors," IJERPH, MDPI, vol. 13(11), pages 1-17, November.
    17. Miller, Reid & Golab, Lukasz & Rosenberg, Catherine, 2017. "Modelling weather effects for impact analysis of residential time-of-use electricity pricing," Energy Policy, Elsevier, vol. 105(C), pages 534-546.
    18. Satonori Nasu & Yu Ishibashi & Junichi Ikuta & Shingo Yamane & Ryuji Kobayashi, 2022. "Reliability and Validity of the Japanese Version of the Assessment of Readiness for Mobility Transition (ARMT-J) for Japanese Elderly," IJERPH, MDPI, vol. 19(21), pages 1-14, October.
    19. Bonaiuto, M. & Mosca, O. & Milani, A. & Ariccio, S. & Dessi, F. & Fornara, F., 2024. "Beliefs about technological and contextual features drive biofuels’ social acceptance," Renewable and Sustainable Energy Reviews, Elsevier, vol. 189(PA).
    20. Yunfei Cheng & Tatiana Ermolieva & Gui-Ying Cao & Xiaoying Zheng, 2018. "Health Impacts of Exposure to Gaseous Pollutants and Particulate Matter in Beijing—A Non-Linear Analysis Based on the New Evidence," IJERPH, MDPI, vol. 15(9), pages 1-12, September.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jijerp:v:12:y:2015:i:12:p:15042-16156:d:60926. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.