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Health Risks of Temperature Variability on Hospital Admissions in Cape Town, 2011–2016

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  • Malebo Sephule Makunyane

    (School of Health Systems and Public Health, Faculty of Health Sciences, University of Pretoria, Pretoria 0002, South Africa
    South African Weather Service, Pretoria 0001, South Africa)

  • Hannes Rautenbach

    (School of Health Systems and Public Health, Faculty of Health Sciences, University of Pretoria, Pretoria 0002, South Africa
    Faculty of Natural Sciences, Akademia, Pretoria 0002, South Africa)

  • Neville Sweijd

    (Applied Centre for Climate and Earth Systems Science, Council for Scientific and Industrial Research, Cape Town 7700, South Africa)

  • Joel Botai

    (South African Weather Service, Pretoria 0001, South Africa
    Department of Geography, Geoinformatics and Meteorology, University of Pretoria, Pretoria 0002, South Africa)

  • Janine Wichmann

    (School of Health Systems and Public Health, Faculty of Health Sciences, University of Pretoria, Pretoria 0002, South Africa)

Abstract

Epidemiological studies have provided compelling evidence of associations between temperature variability (TV) and health outcomes. However, such studies are limited in developing countries. This study aimed to investigate the relationship between TV and hospital admissions for cause-specific diseases in South Africa. Hospital admission data for cardiovascular diseases (CVD) and respiratory diseases (RD) were obtained from seven private hospitals in Cape Town from 1 January 2011 to 31 October 2016. Meteorological data were obtained from the South African Weather Service (SAWS). A quasi-Poisson regression model was used to investigate the association between TV and health outcomes after controlling for potential effect modifiers. A positive and statistically significant association between TV and hospital admissions for both diseases was observed, even after controlling for the non-linear and delayed effects of daily mean temperature and relative humidity. TV showed the greatest effect on the entire study group when using short lags, 0–2 days for CVD and 0–1 days for RD hospitalisations. However, the elderly were more sensitive to RD hospitalisation and the 15–64 year age group was more sensitive to CVD hospitalisations. Men were more susceptible to hospitalisation than females. The results indicate that more attention should be paid to the effects of temperature variability and change on human health. Furthermore, different weather and climate metrics, such as TV, should be considered in understanding the climate component of the epidemiology of these (and other diseases), especially in light of climate change, where a wider range and extreme climate events are expected to occur in future.

Suggested Citation

  • Malebo Sephule Makunyane & Hannes Rautenbach & Neville Sweijd & Joel Botai & Janine Wichmann, 2023. "Health Risks of Temperature Variability on Hospital Admissions in Cape Town, 2011–2016," IJERPH, MDPI, vol. 20(2), pages 1-18, January.
    • Handle: RePEc:gam:jijerp:v:20:y:2023:i:2:p:1159-:d:1029581
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    References listed on IDEAS

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    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. Hugo Pedder & Thandi Kapwata & Guy Howard & Rajen N. Naidoo & Zamantimande Kunene & Richard W. Morris & Angela Mathee & Caradee Y. Wright, 2021. "Lagged Association between Climate Variables and Hospital Admissions for Pneumonia in South Africa," IJERPH, MDPI, vol. 18(12), pages 1-16, June.
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