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Dietary information improves cardiovascular disease risk prediction models.
MedLine Citation:
PMID:  23149979     Owner:  NLM     Status:  Publisher    
Abstract/OtherAbstract:
Background/objectives:Data are limited on cardiovascular disease (CVD) risk prediction models that include dietary predictors. Using known risk factors and dietary information, we constructed and evaluated CVD risk prediction models.Subjects/methods:Data for modeling were from population-based prospective cohort studies comprised of 9026 men and women aged 40-69 years. At baseline, all were free of known CVD and cancer, and were followed up for CVD incidence during an 8-year period. We used Cox proportional hazard regression analysis to construct a traditional risk factor model, an office-based model, and two diet-containing models and evaluated these models by calculating Akaike information criterion (AIC), C-statistics, integrated discrimination improvement (IDI), net reclassification improvement (NRI) and calibration statistic.Results:We constructed diet-containing models with significant dietary predictors such as poultry, legumes, carbonated soft drinks or green tea consumption. Adding dietary predictors to the traditional model yielded a decrease in AIC (delta AIC=15), a 53% increase in relative IDI (P-value for IDI <0.001) and an increase in NRI (category-free NRI=0.14, P <0.001). The simplified diet-containing model also showed a decrease in AIC (delta AIC=14), a 38% increase in relative IDI (P-value for IDI <0.001) and an increase in NRI (category-free NRI=0.08, P<0.01) compared with the office-based model. The calibration plots for risk prediction demonstrated that the inclusion of dietary predictors contributes to better agreement in persons at high risk for CVD. C-statistics for the four models were acceptable and comparable.Conclusions:We suggest that dietary information may be useful in constructing CVD risk prediction models.European Journal of Clinical Nutrition advance online publication, 14 November 2012; doi:10.1038/ejcn.2012.175.
Authors:
I Baik; N H Cho; S H Kim; C Shin
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Publication Detail:
Type:  JOURNAL ARTICLE     Date:  2012-11-14
Journal Detail:
Title:  European journal of clinical nutrition     Volume:  -     ISSN:  1476-5640     ISO Abbreviation:  Eur J Clin Nutr     Publication Date:  2012 Nov 
Date Detail:
Created Date:  2012-11-14     Completed Date:  -     Revised Date:  -    
Medline Journal Info:
Nlm Unique ID:  8804070     Medline TA:  Eur J Clin Nutr     Country:  -    
Other Details:
Languages:  ENG     Pagination:  -     Citation Subset:  -    
Affiliation:
Department of Foods and Nutrition, College of Natural Sciences, Kookmin University, Seoul, Republic of Korea.
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