Assessment of diet quality improves the classification ability of cardiovascular risk score in predicting future events: The 10-year follow-up of the ATTICA study (2002–2012)
Restricted accessResearch articleFirst published online November, 2015
Assessment of diet quality improves the classification ability of cardiovascular risk score in predicting future events: The 10-year follow-up of the ATTICA study (2002–2012)
In past years the prediction of cardiovascular disease (CVD) risk has received special attention; however, the presented risk models have so far not been very successful or appreciated.
Design
The aim of the present work was to examine whether the inclusion of a diet quality evaluation in a CVD risk prediction model is associated with the accuracy of estimating future events.
Methods
The working sample consisted of the 2009 ATTICA study participants (aged 18–89 years). The HellenicSCORE (a calibration of the European Society of Cardiology SCORE, based on age, gender, smoking habits, systolic blood pressure and total cholesterol) was calculated as a proxy of heart disease risk, while assessment of diet quality was based on the MedDietScore, which evaluates adherence to a Mediterranean diet. Fatal or non-fatal incidence of CVD (i.e., development of acute coronary syndromes, stroke or other CVD according to WHO-ICD-10 criteria) was calculated using the 10-year follow-up (2002–2012) data of the ATTICA study participants.
Results
The MedDietScore and the HellenicSCORE were significant predictors of CVD events (p < 0.05). The estimating bias (i.e., misclassification rate of cases) of the model that included only the HellenicSCORE was significantly reduced by the inclusion of MedDietScore in the risk model (Harrell’s C = 0.027, p = 0.012), improving the classification ability of the risk model by 56%.
Conclusion
The inclusion of dietary evaluation increased the accuracy of HellenicSCORE risk estimation and, thus, its incorporation into CVD risk prediction scores might help clinicians and public health professionals to better allocate future CVD candidates.
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