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The impact of potentially modifiable risk factors for stroke in a middle-income area of China: A case-control study

AIMS: To reveal the impact of eleven risk factors on stroke and provide estimates of the prevention potential. METHODS: We completed a multicenter case-control study in Jiangxi, China, a middle-income area. Neuroimaging examination was performed in all cases. Controls were stroke-free adults recruit...

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Autores principales: Wu, Yuhang, Chen, Xiaoyun, Hu, Songbo, Zheng, Huilie, Chen, Yiying, Liu, Jie, Xu, Yan, Chen, Xiaona, Zhu, Liping, Yan, Wei
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9437343/
https://www.ncbi.nlm.nih.gov/pubmed/36062135
http://dx.doi.org/10.3389/fpubh.2022.815579
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author Wu, Yuhang
Chen, Xiaoyun
Hu, Songbo
Zheng, Huilie
Chen, Yiying
Liu, Jie
Xu, Yan
Chen, Xiaona
Zhu, Liping
Yan, Wei
author_facet Wu, Yuhang
Chen, Xiaoyun
Hu, Songbo
Zheng, Huilie
Chen, Yiying
Liu, Jie
Xu, Yan
Chen, Xiaona
Zhu, Liping
Yan, Wei
author_sort Wu, Yuhang
collection PubMed
description AIMS: To reveal the impact of eleven risk factors on stroke and provide estimates of the prevention potential. METHODS: We completed a multicenter case-control study in Jiangxi, China, a middle-income area. Neuroimaging examination was performed in all cases. Controls were stroke-free adults recruited from the community in the case concentration area. Conditional logistic regression and unconditional logistic regression were used for subgroup analysis of stroke type, and other groups (sex, age and urban-rural area), respectively. Odds ratios (ORs) and their population attributable risks (PARs) were calculated, with 95% confidence intervals. RESULTS: A total of 43,615 participants (11,735 cases and 31,880 controls) were recruited from February to September 2018, of whom we enrolled 11,729 case-control pairs. Physical inactivity [PAR 69.5% (66.9–71.9%)] and hypertension [53.4% (49.8–56.8%)] were two major risk factors for stroke, followed by high salt intake [23.9% (20.5–27.3%)], dyslipidemia [20.5% (17.1–24.0%)], meat-based diet [17.5% (14.9–20.4%)], diabetes [7.7% (5.9–9.7%)], cardiac causes [5.3% (4.0–6.7%)], alcohol intake [4.7% (0.2–10.0%)], and high homocysteine [4.3% (1.4–7.4%)]. Nine of these factors were associated with ischemic stroke, and five were associated with intracerebral hemorrhage. Collectively, eleven risk factors accounted for 59.9% of the PAR for all stroke (ischemic stroke: 61.0%; intracerebral hemorrhage: 46.5%), and were consistent across sex (men: 65.5%; women: 62.3%), age (≤55: 65.2%; >55: 63.5%), and urban-rural areas (city: 62.2%; county: 65.7%). CONCLUSION: The 11 risk factors associated with stroke identified will provide an important reference for evidence-based planning for stroke prevention in middle-income areas. There is an urgent need to improve awareness, management and control of behavioral and metabolic risk factors, particularly to promote physical activity and reduce blood pressure.
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spelling pubmed-94373432022-09-03 The impact of potentially modifiable risk factors for stroke in a middle-income area of China: A case-control study Wu, Yuhang Chen, Xiaoyun Hu, Songbo Zheng, Huilie Chen, Yiying Liu, Jie Xu, Yan Chen, Xiaona Zhu, Liping Yan, Wei Front Public Health Public Health AIMS: To reveal the impact of eleven risk factors on stroke and provide estimates of the prevention potential. METHODS: We completed a multicenter case-control study in Jiangxi, China, a middle-income area. Neuroimaging examination was performed in all cases. Controls were stroke-free adults recruited from the community in the case concentration area. Conditional logistic regression and unconditional logistic regression were used for subgroup analysis of stroke type, and other groups (sex, age and urban-rural area), respectively. Odds ratios (ORs) and their population attributable risks (PARs) were calculated, with 95% confidence intervals. RESULTS: A total of 43,615 participants (11,735 cases and 31,880 controls) were recruited from February to September 2018, of whom we enrolled 11,729 case-control pairs. Physical inactivity [PAR 69.5% (66.9–71.9%)] and hypertension [53.4% (49.8–56.8%)] were two major risk factors for stroke, followed by high salt intake [23.9% (20.5–27.3%)], dyslipidemia [20.5% (17.1–24.0%)], meat-based diet [17.5% (14.9–20.4%)], diabetes [7.7% (5.9–9.7%)], cardiac causes [5.3% (4.0–6.7%)], alcohol intake [4.7% (0.2–10.0%)], and high homocysteine [4.3% (1.4–7.4%)]. Nine of these factors were associated with ischemic stroke, and five were associated with intracerebral hemorrhage. Collectively, eleven risk factors accounted for 59.9% of the PAR for all stroke (ischemic stroke: 61.0%; intracerebral hemorrhage: 46.5%), and were consistent across sex (men: 65.5%; women: 62.3%), age (≤55: 65.2%; >55: 63.5%), and urban-rural areas (city: 62.2%; county: 65.7%). CONCLUSION: The 11 risk factors associated with stroke identified will provide an important reference for evidence-based planning for stroke prevention in middle-income areas. There is an urgent need to improve awareness, management and control of behavioral and metabolic risk factors, particularly to promote physical activity and reduce blood pressure. Frontiers Media S.A. 2022-08-19 /pmc/articles/PMC9437343/ /pubmed/36062135 http://dx.doi.org/10.3389/fpubh.2022.815579 Text en Copyright © 2022 Wu, Chen, Hu, Zheng, Chen, Liu, Xu, Chen, Zhu and Yan. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Public Health
Wu, Yuhang
Chen, Xiaoyun
Hu, Songbo
Zheng, Huilie
Chen, Yiying
Liu, Jie
Xu, Yan
Chen, Xiaona
Zhu, Liping
Yan, Wei
The impact of potentially modifiable risk factors for stroke in a middle-income area of China: A case-control study
title The impact of potentially modifiable risk factors for stroke in a middle-income area of China: A case-control study
title_full The impact of potentially modifiable risk factors for stroke in a middle-income area of China: A case-control study
title_fullStr The impact of potentially modifiable risk factors for stroke in a middle-income area of China: A case-control study
title_full_unstemmed The impact of potentially modifiable risk factors for stroke in a middle-income area of China: A case-control study
title_short The impact of potentially modifiable risk factors for stroke in a middle-income area of China: A case-control study
title_sort impact of potentially modifiable risk factors for stroke in a middle-income area of china: a case-control study
topic Public Health
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9437343/
https://www.ncbi.nlm.nih.gov/pubmed/36062135
http://dx.doi.org/10.3389/fpubh.2022.815579
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