A cohort study on the relationship between different hip circumference levels and the events of cerebrovascular diseases and deaths in Mongolian peasants and herdsmen
Objective To learn the relationship between different hip circumference levels and the events of cerebrovascular diseases and deaths in Mongolians.Methods Prospective cohort study was used.A total of 2 586 peasants and herdsmen was followed in Tongliao,Inner Mongolia,who had the age over 20.Follow-up outcome events were cardiovascular and cerebrovascular disease (including stroke and coronary heart disease) and death in 2008,2009,2010.We calculated cumulative incidence and incidence density to describe the occurrence of cardiovascular diseases and death in outcome events,to analyze the baseline of outcome occurred.Multivariate Cox proportional hazards model was used,multioutcome events (cardiovascular and cerebrovascular diseases and deaths) were defined as stroke,coronary heart disease and death,HR value and its 95％ CI of hip circumference levels and other risk factors were calculated.Results During the follow-up period,stroke and coronary heart disease cumulative incidence was 5.64％,the incidence density was 787.4/ 100 thousands per year,and the cumulative mortality was 4.44％,the death density was 620.2/100 thousands per year.Multivariate multiple Cox proportional hazards model showed that,after adjusted the three traditional risk factors of age,gender and family history of hypertension,different hip circumference levels were related with the outcome events,compared to the first level,the second,third and fourth levels related with the ending events (cardio-cerebrovascular disease and death events),HR (95％ CI) value was 0.64(0.45-0.91),0.75 (0.53-1.04),0.65 (0.46-0.92),respectively (all P ＜ O.05).Conclusions Hip circumference levels negatively related with cardiovascular disease and death,and may have independent predictor for cardiovascular and cerebrovascular diseases and death.
Hip circumference levelsMongolianCardiovascular and cerebrovascular diseasesCohort study
NETL
NSTL
维普
万方数据
