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dc.contributor.author | Pedder, Hugo![]() |
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dc.contributor.author | Kapwata, Thandi![]() |
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dc.contributor.author | Howard, Guy![]() |
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dc.contributor.author | Naidoo, Rajen N.![]() |
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dc.contributor.author | Kunene, Zamantimande![]() |
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dc.contributor.author | Morris, Richard W.![]() |
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dc.contributor.author | Mathee, Angela![]() |
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dc.contributor.author | Wright, Caradee Yael![]() |
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dc.date.accessioned | 2022-04-07T14:33:45Z | |
dc.date.available | 2022-04-07T14:33:45Z | |
dc.date.issued | 2021-06 | |
dc.description | SUPPLEMENTARY MATERIAL: Supplementary Figures S1–S11. Figure S1: Daily pneumonia hospital admissions with model fitted values; Figure S2: The association between mean daily temperature and pneumonia hospital admissions across different lag durations at 12 and 28 C; Figure S3: The association between relative humidity and pneumonia hospital admissions across different lag durations at 24 and 92% relative humidity; Figure S4: Model residual deviances plotted by date of admission; Figure S5: Model residual deviances plotted against model predictors for mean daily temperature, relative humidity, daily temperature range, and day of the week; Figure S6: Partial autocorrelation of model residuals between neighboring days separated by different lags; Figure S7: Cumulative association between minimum daily temperature and pneumonia hospital admissions across a 21-day lag period; Figure S8: Cumulative association between maximum daily temperature and pneumonia hospital admissions across a 21-day lag period; Figure S9: Cumulative associations between mean daily temperature and pneumonia hospital admissions across a 21-day lag for models with different degrees of freedom used to fit the natural cubic spline function exposure and lag components; Figure S10: Cumulative associations between relative humidity and pneumonia hospital admissions across a 21-day lag for models with different degrees of freedom used to fit the natural cubic spline function exposure and lag components; Figure S11: Cumulative associations between Daily Temperature Range (DTR) and pneumonia hospital admissions across a 21-day lag for models with different degrees of freedom used to fit the natural cubic spline function exposure component. | en_ZA |
dc.description.abstract | Pneumonia is a leading cause of hospitalization in South Africa. Climate change could potentially affect its incidence via changes in meteorological conditions. We investigated the delayed effects of temperature and relative humidity on pneumonia hospital admissions at two large public hospitals in Limpopo province, South Africa. Using 4062 pneumonia hospital admission records from 2007 to 2015, a time-varying distributed lag non-linear model was used to estimate temperature-lag and relative humidity-lag pneumonia relationships. Mean temperature, relative humidity and diurnal temperature range were all significantly associated with pneumonia admissions. Cumulatively across the 21-day period, higher mean daily temperature (30 C relative to 21 C) was most strongly associated with a decreased rate of hospital admissions (relative rate ratios (RR): 0.34, 95% confidence interval (CI): 0.14–0.82), whereas results were suggestive of lower mean daily temperature (12 C relative to 21 C) being associated with an increased rate of admissions (RR: 1.27, 95%CI: 0.75–2.16). Higher relative humidity (>80%) was associated with fewer hospital admissions while low relative humidity (<30%) was associated with increased admissions. A proportion of pneumonia admissions were attributable to changes in meteorological variables, and our results indicate that even small shifts in their distributions (e.g., due to climate change) could lead to substantial changes in their burden. These findings can inform a better understanding of the health implications of climate change and the burden of hospital admissions for pneumonia now and in the future. | en_ZA |
dc.description.department | Geography, Geoinformatics and Meteorology | en_ZA |
dc.description.librarian | am2022 | en_ZA |
dc.description.sponsorship | The iDEWS (infectious Diseases Early-Warning System) project supported by SATREPS (Science and Technology Research Partnership for Sustainable Development) Program of JICA (JAPAN International Cooperation Agency)/AMED (Japan Agency for Medical Research and Development) in Japan, the ACCESS (Applied Centre for Climate and Earth Systems Science) program of NRF (National Research Foundation), DST (Department of Science and Technology in South Africa) and from the Quality Related Global Challenges Research Fund of the University of Bristol as well as the South African Medical Research Council. | en_ZA |
dc.description.uri | https://www.mdpi.com/journal/ijerph | en_ZA |
dc.identifier.citation | Pedder, H.; Kapwata, T.; Howard, G.; Naidoo, R.N.; Kunene, Z.; Morris, R.W.; Mathee, A.;Wright, C.Y. Lagged Association between Climate Variables and Hospital Admissions for Pneumonia in South Africa. International Journal of Environmental Research and Public Health 2021, 18, 6191. https://DOI.org/10.3390/ijerph18126191. | en_ZA |
dc.identifier.issn | 1660-4601 (online) | |
dc.identifier.other | 10.3390/ijerph18126191 | |
dc.identifier.uri | http://hdl.handle.net/2263/84825 | |
dc.language.iso | en | en_ZA |
dc.publisher | MDPI Publishing | en_ZA |
dc.rights | © 2021 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license. | en_ZA |
dc.subject | Climate change | en_ZA |
dc.subject | Distributed non-linear lag model | en_ZA |
dc.subject | Environmental health | en_ZA |
dc.subject | Public health | en_ZA |
dc.subject | Respiratory disease | en_ZA |
dc.subject | Pneumonia | en_ZA |
dc.subject | Meteorology | en_ZA |
dc.subject | South Africa (SA) | en_ZA |
dc.title | Lagged association between climate variables and hospital admissions for pneumonia in South Africa | en_ZA |
dc.type | Article | en_ZA |