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Geographic, Demographic, and Temporal Variations in the Association between Heat Exposure and Hospitalization in Brazil: A Nationwide Study between 2000 and 2015

BACKGROUND: Limited evidence is available regarding the association between heat exposure and morbidity in Brazil and how the effect of heat exposure on health outcomes may change over time. OBJECTIVES: This study sought to quantify the geographic, demographic and temporal variations in the heat–hos...

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Autores principales: Zhao, Qi, Li, Shanshan, Coelho, Micheline S.Z.S., Saldiva, Paulo H.N., Hu, Kejia, Arblaster, Julie M., Nicholls, Neville, Huxley, Rachel R., Abramson, Michael J., Guo, Yuming
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Environmental Health Perspectives 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6371650/
https://www.ncbi.nlm.nih.gov/pubmed/30620212
http://dx.doi.org/10.1289/EHP3889
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author Zhao, Qi
Li, Shanshan
Coelho, Micheline S.Z.S.
Saldiva, Paulo H.N.
Hu, Kejia
Arblaster, Julie M.
Nicholls, Neville
Huxley, Rachel R.
Abramson, Michael J.
Guo, Yuming
author_facet Zhao, Qi
Li, Shanshan
Coelho, Micheline S.Z.S.
Saldiva, Paulo H.N.
Hu, Kejia
Arblaster, Julie M.
Nicholls, Neville
Huxley, Rachel R.
Abramson, Michael J.
Guo, Yuming
author_sort Zhao, Qi
collection PubMed
description BACKGROUND: Limited evidence is available regarding the association between heat exposure and morbidity in Brazil and how the effect of heat exposure on health outcomes may change over time. OBJECTIVES: This study sought to quantify the geographic, demographic and temporal variations in the heat–hospitalization association in Brazil from 2000–2015. METHODS: Data on hospitalization and meteorological conditions were collected from 1,814 cities during the 2000–2015 hot seasons. Quasi-Poisson regression with constrained lag model was applied to examine city-specific estimates, which were then pooled at the regional and national levels using random-effect meta-analyses. Stratified analyses were performed by sex, 10 age groups, and 11 cause categories. Meta-regression was used to examine the temporal change in estimates of heat effect from 2000 to 2015. RESULTS: For every 5°C increase in daily mean temperature during the 2000–2015 hot seasons, the estimated risk of hospitalization over lag 0–7 d rose by 4.0% [95% confidence interval (CI): 3.7%, 4.3%] nationwide. Estimated 6.2% [95% empirical CI (eCI): 3.3%, 9.1%] of hospitalizations were attributable to heat exposure, equating to 132 cases (95% eCI: 69%, 192%) per 100,000 residents. The attributable rate was greatest in children [Formula: see text] and was highest for hospitalizations due to infectious and parasitic diseases. Women of reproductive age and those [Formula: see text] had higher heat burden than men. The attributable burden was greatest for cities in the central west and the inland of the northeast; lowest in the north and eastern coast. Over the 16-y period, the estimated heat effects declined insignificantly at the national level. CONCLUSIONS: In Brazil’s hot seasons, 6% of hospitalizations were estimated to be attributed to heat exposure. As there was no evidence indicating that thermal adaptation had occurred at the national level, the burden of hospitalization associated with heat exposure in Brazil is likely to increase in the context of global warming. https://doi.org/10.1289/EHP3889
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spelling pubmed-63716502019-05-07 Geographic, Demographic, and Temporal Variations in the Association between Heat Exposure and Hospitalization in Brazil: A Nationwide Study between 2000 and 2015 Zhao, Qi Li, Shanshan Coelho, Micheline S.Z.S. Saldiva, Paulo H.N. Hu, Kejia Arblaster, Julie M. Nicholls, Neville Huxley, Rachel R. Abramson, Michael J. Guo, Yuming Environ Health Perspect Research BACKGROUND: Limited evidence is available regarding the association between heat exposure and morbidity in Brazil and how the effect of heat exposure on health outcomes may change over time. OBJECTIVES: This study sought to quantify the geographic, demographic and temporal variations in the heat–hospitalization association in Brazil from 2000–2015. METHODS: Data on hospitalization and meteorological conditions were collected from 1,814 cities during the 2000–2015 hot seasons. Quasi-Poisson regression with constrained lag model was applied to examine city-specific estimates, which were then pooled at the regional and national levels using random-effect meta-analyses. Stratified analyses were performed by sex, 10 age groups, and 11 cause categories. Meta-regression was used to examine the temporal change in estimates of heat effect from 2000 to 2015. RESULTS: For every 5°C increase in daily mean temperature during the 2000–2015 hot seasons, the estimated risk of hospitalization over lag 0–7 d rose by 4.0% [95% confidence interval (CI): 3.7%, 4.3%] nationwide. Estimated 6.2% [95% empirical CI (eCI): 3.3%, 9.1%] of hospitalizations were attributable to heat exposure, equating to 132 cases (95% eCI: 69%, 192%) per 100,000 residents. The attributable rate was greatest in children [Formula: see text] and was highest for hospitalizations due to infectious and parasitic diseases. Women of reproductive age and those [Formula: see text] had higher heat burden than men. The attributable burden was greatest for cities in the central west and the inland of the northeast; lowest in the north and eastern coast. Over the 16-y period, the estimated heat effects declined insignificantly at the national level. CONCLUSIONS: In Brazil’s hot seasons, 6% of hospitalizations were estimated to be attributed to heat exposure. As there was no evidence indicating that thermal adaptation had occurred at the national level, the burden of hospitalization associated with heat exposure in Brazil is likely to increase in the context of global warming. https://doi.org/10.1289/EHP3889 Environmental Health Perspectives 2019-01-08 /pmc/articles/PMC6371650/ /pubmed/30620212 http://dx.doi.org/10.1289/EHP3889 Text en EHP is an open-access journal published with support from the National Institute of Environmental Health Sciences, National Institutes of Health. All content is public domain unless otherwise noted.
spellingShingle Research
Zhao, Qi
Li, Shanshan
Coelho, Micheline S.Z.S.
Saldiva, Paulo H.N.
Hu, Kejia
Arblaster, Julie M.
Nicholls, Neville
Huxley, Rachel R.
Abramson, Michael J.
Guo, Yuming
Geographic, Demographic, and Temporal Variations in the Association between Heat Exposure and Hospitalization in Brazil: A Nationwide Study between 2000 and 2015
title Geographic, Demographic, and Temporal Variations in the Association between Heat Exposure and Hospitalization in Brazil: A Nationwide Study between 2000 and 2015
title_full Geographic, Demographic, and Temporal Variations in the Association between Heat Exposure and Hospitalization in Brazil: A Nationwide Study between 2000 and 2015
title_fullStr Geographic, Demographic, and Temporal Variations in the Association between Heat Exposure and Hospitalization in Brazil: A Nationwide Study between 2000 and 2015
title_full_unstemmed Geographic, Demographic, and Temporal Variations in the Association between Heat Exposure and Hospitalization in Brazil: A Nationwide Study between 2000 and 2015
title_short Geographic, Demographic, and Temporal Variations in the Association between Heat Exposure and Hospitalization in Brazil: A Nationwide Study between 2000 and 2015
title_sort geographic, demographic, and temporal variations in the association between heat exposure and hospitalization in brazil: a nationwide study between 2000 and 2015
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6371650/
https://www.ncbi.nlm.nih.gov/pubmed/30620212
http://dx.doi.org/10.1289/EHP3889
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