Cargando…

Geographical specific association between lifestyles and multimorbidity among adults in China

The relationship between lifestyles and multimorbidity is well established, but previous studies have often neglected the role of spatial heterogeneity. Thus, this study is the first to explore this association in Chinese adults from a spatial perspective using a geographically weighted logistic reg...

Descripción completa

Detalles Bibliográficos
Autores principales: Rong, Peixi, Chen, Yukui, Dang, Yusong, Duan, Xinyu, Yan, Mingxin, Zhao, Yaling, Chen, Fangyao, Zhou, Jing, Wang, Duolao, Pei, Leilei
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10246811/
https://www.ncbi.nlm.nih.gov/pubmed/37285342
http://dx.doi.org/10.1371/journal.pone.0286401
_version_ 1785055107518300160
author Rong, Peixi
Chen, Yukui
Dang, Yusong
Duan, Xinyu
Yan, Mingxin
Zhao, Yaling
Chen, Fangyao
Zhou, Jing
Wang, Duolao
Pei, Leilei
author_facet Rong, Peixi
Chen, Yukui
Dang, Yusong
Duan, Xinyu
Yan, Mingxin
Zhao, Yaling
Chen, Fangyao
Zhou, Jing
Wang, Duolao
Pei, Leilei
author_sort Rong, Peixi
collection PubMed
description The relationship between lifestyles and multimorbidity is well established, but previous studies have often neglected the role of spatial heterogeneity. Thus, this study is the first to explore this association in Chinese adults from a spatial perspective using a geographically weighted logistic regression (GWLR) model and describe the geographical characteristics across different regions. According to 2018 China Health and Retirement Longitudinal Study (CHARLS) database, a total of 7101 subjects were finally included, with 124 prefecture-level administrative regions in China. Non-spatial and GWLR model were used for analysis, and gender stratification analysis was also performed. Data were visualized through ArcGIS 10.7. The results showed that a total prevalence of approximately 5.13% of multimorbidity, and among participants with multimorbidity, the separate prevalence of hypertension, diabetes or high blood sugar, heart disease, and stroke were 4.45%, 2.32%, 3.02%, and 1.41%, respectively. The GWLR model indicated that current (OR: 1.202–1.220) and former smokers (OR: 1.168–1.206) may be important risk factors for multimorbidity in adults, especially in north and west among male. Past drinkers (OR: 1.233–1.240), especially in eastern China, contribute to the development of the multimorbidity in men but not in women. Vigorous-intensity activities (OR: 0.761–0.799) were negatively associated with multimorbidity in the west, with no gender difference. Depression (OR: 1.266–1.293) appeared to increase the risk for multimorbidity, with the weakest effects in central China and no gender difference. There was an interaction between light activities and gender (P = 0.024). The prevalence of multimorbidity differed across various areas of the province. The role of geographical variations in lifestyles and multimorbidity may provide valuable information for developing site-specific intervention strategies.
format Online
Article
Text
id pubmed-10246811
institution National Center for Biotechnology Information
language English
publishDate 2023
publisher Public Library of Science
record_format MEDLINE/PubMed
spelling pubmed-102468112023-06-08 Geographical specific association between lifestyles and multimorbidity among adults in China Rong, Peixi Chen, Yukui Dang, Yusong Duan, Xinyu Yan, Mingxin Zhao, Yaling Chen, Fangyao Zhou, Jing Wang, Duolao Pei, Leilei PLoS One Research Article The relationship between lifestyles and multimorbidity is well established, but previous studies have often neglected the role of spatial heterogeneity. Thus, this study is the first to explore this association in Chinese adults from a spatial perspective using a geographically weighted logistic regression (GWLR) model and describe the geographical characteristics across different regions. According to 2018 China Health and Retirement Longitudinal Study (CHARLS) database, a total of 7101 subjects were finally included, with 124 prefecture-level administrative regions in China. Non-spatial and GWLR model were used for analysis, and gender stratification analysis was also performed. Data were visualized through ArcGIS 10.7. The results showed that a total prevalence of approximately 5.13% of multimorbidity, and among participants with multimorbidity, the separate prevalence of hypertension, diabetes or high blood sugar, heart disease, and stroke were 4.45%, 2.32%, 3.02%, and 1.41%, respectively. The GWLR model indicated that current (OR: 1.202–1.220) and former smokers (OR: 1.168–1.206) may be important risk factors for multimorbidity in adults, especially in north and west among male. Past drinkers (OR: 1.233–1.240), especially in eastern China, contribute to the development of the multimorbidity in men but not in women. Vigorous-intensity activities (OR: 0.761–0.799) were negatively associated with multimorbidity in the west, with no gender difference. Depression (OR: 1.266–1.293) appeared to increase the risk for multimorbidity, with the weakest effects in central China and no gender difference. There was an interaction between light activities and gender (P = 0.024). The prevalence of multimorbidity differed across various areas of the province. The role of geographical variations in lifestyles and multimorbidity may provide valuable information for developing site-specific intervention strategies. Public Library of Science 2023-06-07 /pmc/articles/PMC10246811/ /pubmed/37285342 http://dx.doi.org/10.1371/journal.pone.0286401 Text en © 2023 Rong et al https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Rong, Peixi
Chen, Yukui
Dang, Yusong
Duan, Xinyu
Yan, Mingxin
Zhao, Yaling
Chen, Fangyao
Zhou, Jing
Wang, Duolao
Pei, Leilei
Geographical specific association between lifestyles and multimorbidity among adults in China
title Geographical specific association between lifestyles and multimorbidity among adults in China
title_full Geographical specific association between lifestyles and multimorbidity among adults in China
title_fullStr Geographical specific association between lifestyles and multimorbidity among adults in China
title_full_unstemmed Geographical specific association between lifestyles and multimorbidity among adults in China
title_short Geographical specific association between lifestyles and multimorbidity among adults in China
title_sort geographical specific association between lifestyles and multimorbidity among adults in china
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10246811/
https://www.ncbi.nlm.nih.gov/pubmed/37285342
http://dx.doi.org/10.1371/journal.pone.0286401
work_keys_str_mv AT rongpeixi geographicalspecificassociationbetweenlifestylesandmultimorbidityamongadultsinchina
AT chenyukui geographicalspecificassociationbetweenlifestylesandmultimorbidityamongadultsinchina
AT dangyusong geographicalspecificassociationbetweenlifestylesandmultimorbidityamongadultsinchina
AT duanxinyu geographicalspecificassociationbetweenlifestylesandmultimorbidityamongadultsinchina
AT yanmingxin geographicalspecificassociationbetweenlifestylesandmultimorbidityamongadultsinchina
AT zhaoyaling geographicalspecificassociationbetweenlifestylesandmultimorbidityamongadultsinchina
AT chenfangyao geographicalspecificassociationbetweenlifestylesandmultimorbidityamongadultsinchina
AT zhoujing geographicalspecificassociationbetweenlifestylesandmultimorbidityamongadultsinchina
AT wangduolao geographicalspecificassociationbetweenlifestylesandmultimorbidityamongadultsinchina
AT peileilei geographicalspecificassociationbetweenlifestylesandmultimorbidityamongadultsinchina