Cut-off values of obesity indices to predict coronary heart disease incidence by time-dependent receiver operating characteristic curve analysis in ۱۰-year follow-up in study of Yazd Healthy Heart Cohort, Iran

BACKGROUND: The current study aimed to determine the optimal cut-off of obesity indices for detecting coronary heart disease (CHD) in ۱۰-year study of Yazd Healthy Heart Cohort (YHHC) in Iran.METHODS: A total of ۲۰۰۰ individuals aged ۲۰-۷۴ years were enrolled. All participants without cardiovascular disease (CVD) had a full medical check-up at the start of the study. At the start of the study, a variety of obesity indices were assessed and calculated, including body mass index (BMI), waist circumference (WC), waist-to-hip ratio (WHpR), waist-to-height ratio (WHtR), A Body Shape Index (ABSI), abdominal volume index (AVI), body adiposity index (BAI), and body roundness index (BRI). Coronary artery bypass graft (CABG), percutaneous coronary intervention (PCI), myocardial infarction (MI), Rose Angina Questionnaire (RAQ) (chest pain) greater than ۳, and electrocardiographic (ECG) changes in favour of the coronary artery disease (CAD) were considered as the CVD risks. A time-dependent receiver operating characteristic (ROC) curve with right-censored data and naive estimator was used to estimate the time-dependent sensitivity and specificity and the best cut-off of the anthropometric indices for CHD risk.RESULTS: Overall, ۱۶۲۳ participants (۸۱۸ men and ۸۰۵ women) with mean and standard deviation (SD) of weight of ۷۱.۲۱ ± ۱۲.۹۴ kg were included. In a ۱۰-year follow-up, ۱۰۱ [۵۹ (۵۸.۴۲%) men and ۴۲ (۴۱.۵۸%) women] developed CVD event. WHpR demonstrated the largest area under the time-dependent ROC curve (AUC) of ۰.۶۵ and ۰.۶۳ as well as ۹۵% confidence interval (CI) of ۵۸.۶۴-۷۲.۶۶ and ۵۰.۷۴-۷۵.۵۵ for men and women, respectively, in predicting CVD. Optimal WHpR cut-off was ۰.۹۳ and ۰.۹۲, respectively, for men and women.CONCLUSION: WHpR index was superior to other obesity indices in predicting CHD.

Keywords:

Cardiovascular Diseases , Anthropometry , ROC Curve