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Two-level analysis of risk factors for ischemic cardiovascular disease-A community-based study from Henan, China
Yuehua Zhang1, Xiaoqin Cao2, Fujiao Duan3
1Department of Epidemiology and Health Statistics, College of Public Health, Zhengzhou University, Zhengzhou, Henan, China; Key Laboratory of Tumor Epidemiology of Henan Province, Zhengzhou, China.
Background:
Ischemic cardiovascular disease (ICVD) has high incidence and high mortality worldwide. The studies of its risk factors were mostly concentrated on an individual level, and there are scarce studies on the two levels of risk factors which include individual and regional levels.
Methods:
The data were obtained from a community-based study in 4 cities and 6 counties of Henan, China. Risk factors were initially screened by one-way analysis of variance or chi-square test. Then, they were re-analyzed using a two-level logistic regression model to construct a personal disease risk prediction model.
Results:
A two-level ICVD risk prediction model comprised 11 variables: age, body mass index (BMI), family history of hypertension, marital status, salt intake, smoking, moderate recreational physical activities, alcohol intake, and education at the individual level. Among the unalterable risk factors, for each additional unit of age and family history of hypertension, the risk of ICVD increased by 1.08 and 1.07 units [β95% confidence interval (95%CI): 0.99-1.16, 0.97-1.17, both p < 0.0001], respectively. Among the modifiable risk factors, the ICVD risk increases by 0.67, 0.27, and 0.28 units for each additional unit of BMI, marital status, and education (β95%CI: 0.60-0.74, p < 0.0001; β95%CI: 0.14-0.40, p = 0.0012, 0.18-0.37, p = 0.0001).
Conclusions:
The two-level ICVD risk model can predict that the risk of one person for ICVD will be lower if one is younger, thinner, and well-educated without a family history of hypertension. Overall, the two-level ICVD risk prediction model gets a better fitting effect than the single-level model.
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