| Dietary information improves cardiovascular disease risk prediction models. | |
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MedLine Citation:
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PMID: 23149979 Owner: NLM Status: Publisher |
Abstract/OtherAbstract:
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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. |
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Authors:
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I Baik; N H Cho; S H Kim; C Shin |
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Publication Detail:
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Type: JOURNAL ARTICLE Date: 2012-11-14 |
Journal Detail:
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Title: European journal of clinical nutrition Volume: - ISSN: 1476-5640 ISO Abbreviation: Eur J Clin Nutr Publication Date: 2012 Nov |
Date Detail:
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Created Date: 2012-11-14 Completed Date: - Revised Date: - |
Medline Journal Info:
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Nlm Unique ID: 8804070 Medline TA: Eur J Clin Nutr Country: - |
Other Details:
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Languages: ENG Pagination: - Citation Subset: - |
Affiliation:
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Department of Foods and Nutrition, College of Natural Sciences, Kookmin University, Seoul, Republic of Korea. |
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From MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine
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