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Evaluating the Sensitivity of Heat Wave Definitions among North Carolina Physiographic Regions
Exposure to extreme heat is a known risk factor that is associated with increased heat-related illness (HRI) outcomes. The relevance of heat wave definitions (HWDs) could change across health conditions and geographies due to the heterogenous climate profile. This study compared the sensitivity of 2...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9408726/ https://www.ncbi.nlm.nih.gov/pubmed/36011743 http://dx.doi.org/10.3390/ijerph191610108 |
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author | Puvvula, Jagadeesh Abadi, Azar M. Conlon, Kathryn C. Rennie, Jared J. Jones, Hunter Bell, Jesse E. |
author_facet | Puvvula, Jagadeesh Abadi, Azar M. Conlon, Kathryn C. Rennie, Jared J. Jones, Hunter Bell, Jesse E. |
author_sort | Puvvula, Jagadeesh |
collection | PubMed |
description | Exposure to extreme heat is a known risk factor that is associated with increased heat-related illness (HRI) outcomes. The relevance of heat wave definitions (HWDs) could change across health conditions and geographies due to the heterogenous climate profile. This study compared the sensitivity of 28 HWDs associated with HRI emergency department visits over five summer seasons (2011–2016), stratified by two physiographic regions (Coastal and Piedmont) in North Carolina. The HRI rate ratios associated with heat waves were estimated using the generalized linear regression framework assuming a negative binomial distribution. We compared the Akaike Information Criterion (AIC) values across the HWDs to identify an optimal HWD. In the Coastal region, HWDs based on daily maximum temperature with a threshold > 90th percentile for two or more consecutive days had the optimal model fit. In the Piedmont region, HWD based on the daily minimum temperature with a threshold value > 90th percentile for two or more consecutive days was optimal. The HWDs with optimal model performance included in this study captured moderate and frequent heat episodes compared to the National Weather Service (NWS) heat products. This study compared the HRI morbidity risk associated with epidemiologic-based HWDs and with NWS heat products. Our findings could be used for public health education and suggest recalibrating NWS heat products. |
format | Online Article Text |
id | pubmed-9408726 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-94087262022-08-26 Evaluating the Sensitivity of Heat Wave Definitions among North Carolina Physiographic Regions Puvvula, Jagadeesh Abadi, Azar M. Conlon, Kathryn C. Rennie, Jared J. Jones, Hunter Bell, Jesse E. Int J Environ Res Public Health Article Exposure to extreme heat is a known risk factor that is associated with increased heat-related illness (HRI) outcomes. The relevance of heat wave definitions (HWDs) could change across health conditions and geographies due to the heterogenous climate profile. This study compared the sensitivity of 28 HWDs associated with HRI emergency department visits over five summer seasons (2011–2016), stratified by two physiographic regions (Coastal and Piedmont) in North Carolina. The HRI rate ratios associated with heat waves were estimated using the generalized linear regression framework assuming a negative binomial distribution. We compared the Akaike Information Criterion (AIC) values across the HWDs to identify an optimal HWD. In the Coastal region, HWDs based on daily maximum temperature with a threshold > 90th percentile for two or more consecutive days had the optimal model fit. In the Piedmont region, HWD based on the daily minimum temperature with a threshold value > 90th percentile for two or more consecutive days was optimal. The HWDs with optimal model performance included in this study captured moderate and frequent heat episodes compared to the National Weather Service (NWS) heat products. This study compared the HRI morbidity risk associated with epidemiologic-based HWDs and with NWS heat products. Our findings could be used for public health education and suggest recalibrating NWS heat products. MDPI 2022-08-16 /pmc/articles/PMC9408726/ /pubmed/36011743 http://dx.doi.org/10.3390/ijerph191610108 Text en © 2022 by the authors. https://creativecommons.org/licenses/by/4.0/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 (https://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Puvvula, Jagadeesh Abadi, Azar M. Conlon, Kathryn C. Rennie, Jared J. Jones, Hunter Bell, Jesse E. Evaluating the Sensitivity of Heat Wave Definitions among North Carolina Physiographic Regions |
title | Evaluating the Sensitivity of Heat Wave Definitions among North Carolina Physiographic Regions |
title_full | Evaluating the Sensitivity of Heat Wave Definitions among North Carolina Physiographic Regions |
title_fullStr | Evaluating the Sensitivity of Heat Wave Definitions among North Carolina Physiographic Regions |
title_full_unstemmed | Evaluating the Sensitivity of Heat Wave Definitions among North Carolina Physiographic Regions |
title_short | Evaluating the Sensitivity of Heat Wave Definitions among North Carolina Physiographic Regions |
title_sort | evaluating the sensitivity of heat wave definitions among north carolina physiographic regions |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9408726/ https://www.ncbi.nlm.nih.gov/pubmed/36011743 http://dx.doi.org/10.3390/ijerph191610108 |
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