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Research on the relationship between common metabolic syndrome and meteorological factors in Wuhu, a subtropical humid city of China
As climate conditions deteriorate, human health faces a broader range of threats. This study aimed to determine the risk of death from metabolic syndrome (MetS) due to meteorological factors. We collected daily data from 2014 to 2020 in Wuhu City, including meteorological factors, environmental poll...
Autores principales: | , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10685562/ https://www.ncbi.nlm.nih.gov/pubmed/38031031 http://dx.doi.org/10.1186/s12889-023-17299-8 |
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author | Zhang, Tao Ni, Man Jia, Juan Deng, Yujie Sun, Xiaoya Wang, Xinqi Chen, Yuting Fang, Lanlan Zhao, Hui Xu, Shanshan Ma, Yubo Zhu, Jiansheng Pan, Faming |
author_facet | Zhang, Tao Ni, Man Jia, Juan Deng, Yujie Sun, Xiaoya Wang, Xinqi Chen, Yuting Fang, Lanlan Zhao, Hui Xu, Shanshan Ma, Yubo Zhu, Jiansheng Pan, Faming |
author_sort | Zhang, Tao |
collection | PubMed |
description | As climate conditions deteriorate, human health faces a broader range of threats. This study aimed to determine the risk of death from metabolic syndrome (MetS) due to meteorological factors. We collected daily data from 2014 to 2020 in Wuhu City, including meteorological factors, environmental pollutants and death data of common MetS (hypertension, hyperlipidemia and diabetes), as well as a total number of 15,272 MetS deaths. To examine the relationship between meteorological factors, air pollutants, and MetS mortality, we used a generalized additive model (GAM) combined with a distributed delay nonlinear model (DLNM) for time series analysis. The relationship between the above factors and death outcomes was preliminarily evaluated using Spearman analysis and structural equation modeling (SEM). As per out discovery, diurnal temperature range (DTR) and daily mean temperature (T mean) increased the MetS mortality risk notably. The ultra low DTR raised the MetS mortality risk upon the general people, with the highest RR value of 1.033 (95% CI: 1.002, 1.065) at lag day 14. In addition, T mean was also significantly associated with MetS death. The highest risk of ultra low and ultra high T mean occured on the same day (lag 14), RR values were 1.043 (95% CI: 1.010, 1.077) and 1.032 (95% CI: 1.003, 1.061) respectively. Stratified analysis’s result showed lower DTR had a more pronounced effect on women and the elderly, and ultra low and high T mean was a risk factor for MetS mortality in women and men. The elderly need to take extra note of temperature changes, and different levels of T mean will increase the risk of death. In warm seasons, ultra high RH and T mean can increase the mortality rate of MetS patients. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12889-023-17299-8. |
format | Online Article Text |
id | pubmed-10685562 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-106855622023-11-30 Research on the relationship between common metabolic syndrome and meteorological factors in Wuhu, a subtropical humid city of China Zhang, Tao Ni, Man Jia, Juan Deng, Yujie Sun, Xiaoya Wang, Xinqi Chen, Yuting Fang, Lanlan Zhao, Hui Xu, Shanshan Ma, Yubo Zhu, Jiansheng Pan, Faming BMC Public Health Research As climate conditions deteriorate, human health faces a broader range of threats. This study aimed to determine the risk of death from metabolic syndrome (MetS) due to meteorological factors. We collected daily data from 2014 to 2020 in Wuhu City, including meteorological factors, environmental pollutants and death data of common MetS (hypertension, hyperlipidemia and diabetes), as well as a total number of 15,272 MetS deaths. To examine the relationship between meteorological factors, air pollutants, and MetS mortality, we used a generalized additive model (GAM) combined with a distributed delay nonlinear model (DLNM) for time series analysis. The relationship between the above factors and death outcomes was preliminarily evaluated using Spearman analysis and structural equation modeling (SEM). As per out discovery, diurnal temperature range (DTR) and daily mean temperature (T mean) increased the MetS mortality risk notably. The ultra low DTR raised the MetS mortality risk upon the general people, with the highest RR value of 1.033 (95% CI: 1.002, 1.065) at lag day 14. In addition, T mean was also significantly associated with MetS death. The highest risk of ultra low and ultra high T mean occured on the same day (lag 14), RR values were 1.043 (95% CI: 1.010, 1.077) and 1.032 (95% CI: 1.003, 1.061) respectively. Stratified analysis’s result showed lower DTR had a more pronounced effect on women and the elderly, and ultra low and high T mean was a risk factor for MetS mortality in women and men. The elderly need to take extra note of temperature changes, and different levels of T mean will increase the risk of death. In warm seasons, ultra high RH and T mean can increase the mortality rate of MetS patients. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12889-023-17299-8. BioMed Central 2023-11-29 /pmc/articles/PMC10685562/ /pubmed/38031031 http://dx.doi.org/10.1186/s12889-023-17299-8 Text en © The Author(s) 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 licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence 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 licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data. |
spellingShingle | Research Zhang, Tao Ni, Man Jia, Juan Deng, Yujie Sun, Xiaoya Wang, Xinqi Chen, Yuting Fang, Lanlan Zhao, Hui Xu, Shanshan Ma, Yubo Zhu, Jiansheng Pan, Faming Research on the relationship between common metabolic syndrome and meteorological factors in Wuhu, a subtropical humid city of China |
title | Research on the relationship between common metabolic syndrome and meteorological factors in Wuhu, a subtropical humid city of China |
title_full | Research on the relationship between common metabolic syndrome and meteorological factors in Wuhu, a subtropical humid city of China |
title_fullStr | Research on the relationship between common metabolic syndrome and meteorological factors in Wuhu, a subtropical humid city of China |
title_full_unstemmed | Research on the relationship between common metabolic syndrome and meteorological factors in Wuhu, a subtropical humid city of China |
title_short | Research on the relationship between common metabolic syndrome and meteorological factors in Wuhu, a subtropical humid city of China |
title_sort | research on the relationship between common metabolic syndrome and meteorological factors in wuhu, a subtropical humid city of china |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10685562/ https://www.ncbi.nlm.nih.gov/pubmed/38031031 http://dx.doi.org/10.1186/s12889-023-17299-8 |
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