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Heat-mortality relationship in North Carolina: Comparison using different exposure methods
BACKGROUND: Many studies have explored the heat-mortality relationship; however, comparability of results is hindered by the studies’ use of different exposure methods. OBJECTIVE: This study evaluated different methods for estimating exposure to temperature using individual-level data and examined t...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group US
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10403356/ https://www.ncbi.nlm.nih.gov/pubmed/37029251 http://dx.doi.org/10.1038/s41370-023-00544-y |
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author | Choi, Hayon Michelle Bell, Michelle L. |
author_facet | Choi, Hayon Michelle Bell, Michelle L. |
author_sort | Choi, Hayon Michelle |
collection | PubMed |
description | BACKGROUND: Many studies have explored the heat-mortality relationship; however, comparability of results is hindered by the studies’ use of different exposure methods. OBJECTIVE: This study evaluated different methods for estimating exposure to temperature using individual-level data and examined the impacts on the heat-mortality relationship. METHODS: We calculated different temperature exposures for each individual death by using a modeled, gridded temperature dataset and a monitoring station dataset in North Carolina for 2000–2016. We considered individual-level vs. county-level averages and measured vs. modeled temperature data. A case-crossover analysis was conducted to examine the heat-mortality risk under different exposure methods. RESULTS: The minimum mortality temperature (MMT) (i.e., the temperature with the lowest mortality rate) for the monitoring station dataset was 23.87 °C and 22.67 °C (individual monitor and county average, respectively), whereas for the modeled temperature dataset the MMT was 19.46 °C and 19.61 °C (individual and county, respectively). We found higher heat-mortality risk while using temperature exposure estimated from monitoring stations compared to risk based on exposure using the modeled temperature dataset. Individual-aggregated monitoring station temperature exposure resulted in higher heat mortality risk (odds ratio (95% CI): 2.24 (95% CI: 2.21, 2.27)) for a relative temperature change comparing the 99th and 90th temperature percentiles, while modeled temperature exposure resulted in lower odds ratio of 1.27 (95% CI: 1.25, 1.29). SIGNIFICANCE: Our findings indicate that using different temperature exposure methods can result in different temperature-mortality risk. The impact of using various exposure methods should be considered in planning health policies related to high temperatures, including under climate change. IMPACT STATEMENT: 1. We estimated the heat-mortality association using different methods to estimate exposure to temperature. 2. The mean temperature value among different exposure methods were similar although lower for the modeled data, however, use of the monitoring station temperature dataset resulted in higher heat-mortality risk than the modeled temperature dataset. 3. Differences in mortality risk from heat by urbanicity varies depending on the method used to estimate temperature exposure. |
format | Online Article Text |
id | pubmed-10403356 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Nature Publishing Group US |
record_format | MEDLINE/PubMed |
spelling | pubmed-104033562023-08-06 Heat-mortality relationship in North Carolina: Comparison using different exposure methods Choi, Hayon Michelle Bell, Michelle L. J Expo Sci Environ Epidemiol Article BACKGROUND: Many studies have explored the heat-mortality relationship; however, comparability of results is hindered by the studies’ use of different exposure methods. OBJECTIVE: This study evaluated different methods for estimating exposure to temperature using individual-level data and examined the impacts on the heat-mortality relationship. METHODS: We calculated different temperature exposures for each individual death by using a modeled, gridded temperature dataset and a monitoring station dataset in North Carolina for 2000–2016. We considered individual-level vs. county-level averages and measured vs. modeled temperature data. A case-crossover analysis was conducted to examine the heat-mortality risk under different exposure methods. RESULTS: The minimum mortality temperature (MMT) (i.e., the temperature with the lowest mortality rate) for the monitoring station dataset was 23.87 °C and 22.67 °C (individual monitor and county average, respectively), whereas for the modeled temperature dataset the MMT was 19.46 °C and 19.61 °C (individual and county, respectively). We found higher heat-mortality risk while using temperature exposure estimated from monitoring stations compared to risk based on exposure using the modeled temperature dataset. Individual-aggregated monitoring station temperature exposure resulted in higher heat mortality risk (odds ratio (95% CI): 2.24 (95% CI: 2.21, 2.27)) for a relative temperature change comparing the 99th and 90th temperature percentiles, while modeled temperature exposure resulted in lower odds ratio of 1.27 (95% CI: 1.25, 1.29). SIGNIFICANCE: Our findings indicate that using different temperature exposure methods can result in different temperature-mortality risk. The impact of using various exposure methods should be considered in planning health policies related to high temperatures, including under climate change. IMPACT STATEMENT: 1. We estimated the heat-mortality association using different methods to estimate exposure to temperature. 2. The mean temperature value among different exposure methods were similar although lower for the modeled data, however, use of the monitoring station temperature dataset resulted in higher heat-mortality risk than the modeled temperature dataset. 3. Differences in mortality risk from heat by urbanicity varies depending on the method used to estimate temperature exposure. Nature Publishing Group US 2023-04-07 2023 /pmc/articles/PMC10403356/ /pubmed/37029251 http://dx.doi.org/10.1038/s41370-023-00544-y Text en © This is a U.S. Government work and not under copyright protection in the US; foreign copyright protection may apply 2023 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Article Choi, Hayon Michelle Bell, Michelle L. Heat-mortality relationship in North Carolina: Comparison using different exposure methods |
title | Heat-mortality relationship in North Carolina: Comparison using different exposure methods |
title_full | Heat-mortality relationship in North Carolina: Comparison using different exposure methods |
title_fullStr | Heat-mortality relationship in North Carolina: Comparison using different exposure methods |
title_full_unstemmed | Heat-mortality relationship in North Carolina: Comparison using different exposure methods |
title_short | Heat-mortality relationship in North Carolina: Comparison using different exposure methods |
title_sort | heat-mortality relationship in north carolina: comparison using different exposure methods |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10403356/ https://www.ncbi.nlm.nih.gov/pubmed/37029251 http://dx.doi.org/10.1038/s41370-023-00544-y |
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