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Dietary information improves cardiovascular disease risk prediction models.

Authors
Baik, I; Cho, NH; Kim, SH; Shin, C
Citation
European journal of clinical nutrition, 67(1):25-30, 2013
Journal Title
European journal of clinical nutrition
ISSN
0954-30071476-5640
Abstract
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.
MeSH terms
AdultAgedCalibrationCardiovascular Diseases/epidemiology/ethnology/*etiology/prevention & controlCohort StudiesDiet/*adverse effects/ethnologyFemaleFollow-Up StudiesHumansIncidenceMaleMiddle Aged*Models, BiologicalProportional Hazards ModelsProspective StudiesQuestionnairesRepublic of Korea/epidemiologyRisk Factors
DOI
10.1038/ejcn.2012.175
PMID
23149979
Appears in Collections:
Journal Papers > School of Medicine / Graduate School of Medicine > Preventive Medicine & Public Health
AJOU Authors
조, 남한
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