Li Na,Wu Yazhou,Yi Dong.An algorithm based on Disease Risk Index for predicting individual stroke risk in community residents in Chongqing[J].J Amry Med Univ (J Third Mil Med Univ),2010,32(20):2216-2219.
Li Na,Wu Yazhou,Yi Dong.An algorithm based on Disease Risk Index for predicting individual stroke risk in community residents in Chongqing[J].J Amry Med Univ (J Third Mil Med Univ),2010,32(20):2216-2219.DOI:
An algorithm based on Disease Risk Index for predicting individual stroke risk in community residents in Chongqing
Objective To establish a prediction method for individual stroke risk in Chongqing
and serve it as a theoretical basis of stroke prevention. Methods Based on the community residents health census of Chongqing Shapingba Center for Disease Control and Prevention
logistic regression analysis on the original data was carried out to screen the main risk factors of stroke. We translated the relative risk associated with an exposure into a number of disease risk points. The prevalence of risk factor was taken from the China National Nutrition and Health Survey documents in 2002. An individual’s risk of a given or total cardiovascular disease relative to those in the general population of the same gender as the individual was estimated and then expressed qualitatively and quantitatively. Results A risk score and population average score table (quantitative criteria for assessment) of main risk factors for stoke was developed for men at different age groups
including education
high salt consumption
physical exercise
family history of hypertension and stroke
diabetes
hypertension and hyperlipidemia. The similar table was developed for women
including education
drinking
high salt consumption
overweight and obesity
family history of hypertension and stroke
diabetes
hypertension and hyperlipidemia. Conclusion The Disease Risk Index offers an effective classification and estimation for personal risk of health and disease. It may help to inform individuals of the risk factors and identify changes in lifestyle that will reduce their risk. It lays a foundation for personalized health education and health promotion.
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