Quantifying links between stroke and risk factors: a study on individual health risk appraisal of stroke in a community of Chongqing.
The objective of this study is to investigate the risk factors of stroke in a community in Chongqing by setting quantitative criteria for determining the risk factors of stroke. Thus, high-risk individuals can be identified and laid a foundation for predicting individual risk of stroke. 1,034 cases with 1:2 matched controls (2,068) were chosen from five communities in Chongqing including Shapingba, Xiaolongkan, Tianxingqiao, Yubei Road and Ciqikou. Participants were interviewed with a uniform questionnaire. The risk factors of stroke and the odds ratios of risk factors were analyzed with a logistic regression model, and risk exposure factors of different levels were converted into risk scores using statistical models. For men, ten risk factors including hypertension (5.728), family history of stroke (4.599), and coronary heart disease (5.404), among others, were entered into the main effect model. For women, 11 risk factors included hypertension (5.270), family history of stroke (4.866), hyperlipidemia (4.346), among others. The related risk scores were added to obtain a combined risk score to predict the individual's risk of stoke in the future. An individual health risk appraisal model of stroke, which was applicable to individuals of different gender, age, health behavior, disease and family history, was established. In conclusion, personal diseases including hypertension, diabetes mellitus, etc., were very important to the prevalence of stoke. The prevalence of stroke can be effectively reduced by changing unhealthy lifestyles and curing the positive individual disease. The study lays a foundation for health education to persuade people to change their unhealthy lifestyles or behaviors, and could be used in community health services.
Wu
Yazhou
Y
Department of Health Statistics, Third Military Medical University, Chongqing, 400038, People's Republic of China.
Zhang
Ling
L
Yuan
Xiaoyan
X
Wu
Yamin
Y
Yi
Dong
D
D017677:Age Distribution; D000367:Age Factors; D002681:China / Q000453:epidemiology; D005260:Female; D006305:Health Status Indicators; D006801:Humans; D016015:Logistic Models; D008297:Male; D015995:Prevalence; D012111:Residence Characteristics; D012307:Risk Factors; D012737:Sex Factors; D020521:Stroke / Q000453:epidemiology* / Q000209:etiology*; D011795:Surveys and Questionnaires