Anthropometric Indices as Predictors of Coronary Heart Disease Risk: Joint Modeling of Longitudinal Measurements and Time to Event
AbstractBackground: The prevalence of overweight and obesity have increased dramatically worldwide and together they constitute a major risk factor for coronary heart disease (CHD). The aim of this study was to assess the repeated measurements of body mass index (BMI), waist circumference (WC), waist to hip ratio (WHR) and waist to height ratio (WHtR) in predicting CHD incidence.Methods: This longitudinal study was conducted within the framework of the Tehran Lipid and Glucose Study between 1999–2011, on 1959 women and 1371 men participants’ ages ≥30 yr, without a history of CVD. A joint modeling approach was utilized for data analysis using R software. The resulting joint model allowed measuring α (quantifies the association between anthropometric indices up to time t and the hazard for CHD event at the same time point).Results: About 9% of the participants (7.1% of the women and 11.7% of the men) experienced CHD event during follow-up. The results indicated a significant linear increasing trend in BMI, WC, WHR, and WHtR over time (P<0.001). The increased risk of CHD event in females increases with the values of BMI (α= 0.004, P=0.023), WC (α= 0.018, P=0.009), WHR (α= 0.067, P=0.014) and WHtR (α= 0.106, P=0.002). Furthermore, in males the risk of CHD risk increases by the values of BMI (α= 0.005, P=0.032), WC (α= 0.019, P=0.008), WHR (α= 0.043, P=0.015) and WHtR (α= 0.096, P=0.002).Conclusion: By jointly modeling longitudinal data with time-to-event outcomes, our study revealed that WHtR is superior to other indices in predicting CHD incidence.
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