Jing Wang1, Xin Wen1, Wen Li2, Xin Li3, Yuan Wang4, Wenli Lu1. 1. Department of Epidemiology and Health Statistics, School of Public Health, Tianjin Medical University, Tianjin, China; Collaborative Innovation Center of Chronic Disease Prevention and Control, Tianjin Medical University, Tianjin, China. 2. Collaborative Innovation Center of Chronic Disease Prevention and Control, Tianjin Medical University, Tianjin, China. 3. Department of Neurology, The Second Hospital of Tianjin Medical University, Tianjin, China. 4. Department of Epidemiology and Health Statistics, School of Public Health, Tianjin Medical University, Tianjin, China; Collaborative Innovation Center of Chronic Disease Prevention and Control, Tianjin Medical University, Tianjin, China. Electronic address: wangyuan@tmu.edu.cn.
Abstract
BACKGROUND: Stroke is the leading cause of death in China. According to the Chinese Stroke Screening and Prevention Project, 8 main risk factors were assessed and individuals with 3 or more risk factors were identified as high-risk population of stroke. To explore the potential impropriety of counting the risk factors but ignoring the different strength of association of each risk factor, we performed this study. METHODS: Relevant databases were searched for case-control and cohort studies focusing on the risk factors of stroke. We systematically identified studies conducted between 1990 and 2015 that included data on the frequency of risk factors in Chinese Han populations. Pooled relative risks and odds ratios, with their 95% confidence intervals, were calculated for the cohort and case-control studies, respectively. RESULTS: Fifteen cohort studies and 178 case-control studies were identified. Hypertension was the strongest independent risk factor for stroke (pooled odds ratio, 3.50; pooled relative risk, 2.68). Diabetes mellitus, heart disease, family history of stroke, hyperlipidemia, overweight, and smoking were also mildly predictive (pooled odd ratios, 1.82-2.68; pooled relative risks, 1.27-2.47). By contrast, physical exercise was a protective factor against stroke (pooled odd ratio, .49). CONCLUSIONS: There was a measurable difference in the strength of association of the 8 risk factors with stroke; hypertension and diabetes were associated with the highest risks, indicating a need to focus resources on patients with these conditions. Giving risk factors equal weighting may not be an appropriate screening methodology.
BACKGROUND:Stroke is the leading cause of death in China. According to the Chinese Stroke Screening and Prevention Project, 8 main risk factors were assessed and individuals with 3 or more risk factors were identified as high-risk population of stroke. To explore the potential impropriety of counting the risk factors but ignoring the different strength of association of each risk factor, we performed this study. METHODS: Relevant databases were searched for case-control and cohort studies focusing on the risk factors of stroke. We systematically identified studies conducted between 1990 and 2015 that included data on the frequency of risk factors in Chinese Han populations. Pooled relative risks and odds ratios, with their 95% confidence intervals, were calculated for the cohort and case-control studies, respectively. RESULTS: Fifteen cohort studies and 178 case-control studies were identified. Hypertension was the strongest independent risk factor for stroke (pooled odds ratio, 3.50; pooled relative risk, 2.68). Diabetes mellitus, heart disease, family history of stroke, hyperlipidemia, overweight, and smoking were also mildly predictive (pooled odd ratios, 1.82-2.68; pooled relative risks, 1.27-2.47). By contrast, physical exercise was a protective factor against stroke (pooled odd ratio, .49). CONCLUSIONS: There was a measurable difference in the strength of association of the 8 risk factors with stroke; hypertension and diabetes were associated with the highest risks, indicating a need to focus resources on patients with these conditions. Giving risk factors equal weighting may not be an appropriate screening methodology.
Authors: Allan I Pack; Ulysses J Magalang; Bhajan Singh; Samuel T Kuna; Brendan T Keenan; Greg Maislin Journal: Sleep Date: 2021-02-12 Impact factor: 5.849