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Risk factors of direct heat-related hospital admissions during the 2009 heatwave in Adelaide, Australia: a matched case–control study
OBJECTIVE: The extreme heatwave of 2009 in South Australia dramatically increased morbidity, with a 14-fold increase in direct heat-related hospitalisation in metropolitan Adelaide. Our study aimed to identify risk factors for the excess morbidity. DESIGN: A matched case–control study of risk factor...
Autores principales: | , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BMJ Publishing Group
2016
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4893849/ https://www.ncbi.nlm.nih.gov/pubmed/27256088 http://dx.doi.org/10.1136/bmjopen-2015-010666 |
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author | Zhang, Ying Nitschke, Monika Krackowizer, Antoinette Dear, Keith Pisaniello, Dino Weinstein, Philip Tucker, Graeme Shakib, Sepehr Bi, Peng |
author_facet | Zhang, Ying Nitschke, Monika Krackowizer, Antoinette Dear, Keith Pisaniello, Dino Weinstein, Philip Tucker, Graeme Shakib, Sepehr Bi, Peng |
author_sort | Zhang, Ying |
collection | PubMed |
description | OBJECTIVE: The extreme heatwave of 2009 in South Australia dramatically increased morbidity, with a 14-fold increase in direct heat-related hospitalisation in metropolitan Adelaide. Our study aimed to identify risk factors for the excess morbidity. DESIGN: A matched case–control study of risk factors was conducted. SETTING: Patients and matched community controls were interviewed to gather data on demographics, living environment, social support, health status and behaviour changes during the heatwave. PARTICIPANTS: Cases were all hospital admissions with heat-related diagnoses during the 5-day heatwave in 2009. Controls were randomly selected from communities. OUTCOME MEASURES: Descriptive analyses, simple and multiple conditional logistic regressions were performed. Adjusted ORs (AORs) were estimated. RESULTS: In total, 143 hospital patients and 143 matched community controls were interviewed, with a mean age of 73 years (SD 21), 96% European ethnicity, 63% retired, 36% with high school or higher education, and 8% institutional living. The regression model indicated that compared with the controls, cases were more likely to have heart disease (AOR=13.56, 95% CI 1.27 to 144.86) and dementia (AOR=26.43, 95% CI 1.99 to 350.73). The protective factors included higher education level (AOR=0.48, 95% CI 0.23 to 0.99), having air-conditioner in the bedroom (AOR=0.12, 95% CI 0.02 to 0.74), having an emergency button (AOR=0.09, 95% CI 0.01 to 0.96), using refreshment (AOR=0.10, 95% CI 0.01 to 0.84), and having more social activities (AOR=0.11, 95% CI 0.02 to 0.57). CONCLUSIONS: Pre-existing heart disease and dementia significantly increase the risk of direct heat-related hospitalisations during heatwaves. The presence of an air-conditioner in the bedroom, more social activities, a higher education level, use of emergency buttons and refreshments reduce the risk during heatwaves. |
format | Online Article Text |
id | pubmed-4893849 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2016 |
publisher | BMJ Publishing Group |
record_format | MEDLINE/PubMed |
spelling | pubmed-48938492016-06-09 Risk factors of direct heat-related hospital admissions during the 2009 heatwave in Adelaide, Australia: a matched case–control study Zhang, Ying Nitschke, Monika Krackowizer, Antoinette Dear, Keith Pisaniello, Dino Weinstein, Philip Tucker, Graeme Shakib, Sepehr Bi, Peng BMJ Open Public Health OBJECTIVE: The extreme heatwave of 2009 in South Australia dramatically increased morbidity, with a 14-fold increase in direct heat-related hospitalisation in metropolitan Adelaide. Our study aimed to identify risk factors for the excess morbidity. DESIGN: A matched case–control study of risk factors was conducted. SETTING: Patients and matched community controls were interviewed to gather data on demographics, living environment, social support, health status and behaviour changes during the heatwave. PARTICIPANTS: Cases were all hospital admissions with heat-related diagnoses during the 5-day heatwave in 2009. Controls were randomly selected from communities. OUTCOME MEASURES: Descriptive analyses, simple and multiple conditional logistic regressions were performed. Adjusted ORs (AORs) were estimated. RESULTS: In total, 143 hospital patients and 143 matched community controls were interviewed, with a mean age of 73 years (SD 21), 96% European ethnicity, 63% retired, 36% with high school or higher education, and 8% institutional living. The regression model indicated that compared with the controls, cases were more likely to have heart disease (AOR=13.56, 95% CI 1.27 to 144.86) and dementia (AOR=26.43, 95% CI 1.99 to 350.73). The protective factors included higher education level (AOR=0.48, 95% CI 0.23 to 0.99), having air-conditioner in the bedroom (AOR=0.12, 95% CI 0.02 to 0.74), having an emergency button (AOR=0.09, 95% CI 0.01 to 0.96), using refreshment (AOR=0.10, 95% CI 0.01 to 0.84), and having more social activities (AOR=0.11, 95% CI 0.02 to 0.57). CONCLUSIONS: Pre-existing heart disease and dementia significantly increase the risk of direct heat-related hospitalisations during heatwaves. The presence of an air-conditioner in the bedroom, more social activities, a higher education level, use of emergency buttons and refreshments reduce the risk during heatwaves. BMJ Publishing Group 2016-06-02 /pmc/articles/PMC4893849/ /pubmed/27256088 http://dx.doi.org/10.1136/bmjopen-2015-010666 Text en Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing/ This is an Open Access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/ |
spellingShingle | Public Health Zhang, Ying Nitschke, Monika Krackowizer, Antoinette Dear, Keith Pisaniello, Dino Weinstein, Philip Tucker, Graeme Shakib, Sepehr Bi, Peng Risk factors of direct heat-related hospital admissions during the 2009 heatwave in Adelaide, Australia: a matched case–control study |
title | Risk factors of direct heat-related hospital admissions during the 2009 heatwave in Adelaide, Australia: a matched case–control study |
title_full | Risk factors of direct heat-related hospital admissions during the 2009 heatwave in Adelaide, Australia: a matched case–control study |
title_fullStr | Risk factors of direct heat-related hospital admissions during the 2009 heatwave in Adelaide, Australia: a matched case–control study |
title_full_unstemmed | Risk factors of direct heat-related hospital admissions during the 2009 heatwave in Adelaide, Australia: a matched case–control study |
title_short | Risk factors of direct heat-related hospital admissions during the 2009 heatwave in Adelaide, Australia: a matched case–control study |
title_sort | risk factors of direct heat-related hospital admissions during the 2009 heatwave in adelaide, australia: a matched case–control study |
topic | Public Health |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4893849/ https://www.ncbi.nlm.nih.gov/pubmed/27256088 http://dx.doi.org/10.1136/bmjopen-2015-010666 |
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