Optimal anthropometric measures to predict incidence of coronary heart disease in adults

Samenvatting

Background: Anthropometric measures play a significant role in predicting the incidence of coronary heart disease (CHD) in adults. Identifying the most optimal anthropometric measures can enhance early detection and preventive strategies for CHD.
Materials and Methods: A prospective cohort study was conducted involving 2000 adults aged 40-65 years without prior history of CHD. Anthropometric measures including waist circumference (WC), body mass index (BMI), waist-to-hip ratio (WHR), and waist-to-height ratio (WHtR) were recorded at baseline. Participants were followed up for 10 years to track the incidence of CHD. Cox proportional hazards regression analysis was performed to determine the association between anthropometric measures and CHD incidence, adjusting for potential confounders.
Results: Over the 10-year follow-up period, 150 cases of CHD were diagnosed. The mean baseline values for WC, BMI, WHR, and WHtR were 95 cm, 28 kg/m², 0.90, and 0.55, respectively. Cox regression analysis revealed that each standard deviation increase in WC (HR=1.35, 95% CI: 1.20-1.52), BMI (HR=1.27, 95% CI: 1.15-1.41), WHR (HR=1.18, 95% CI: 1.06-1.32), and WHtR (HR=1.42, 95% CI: 1.26-1.60) was associated with a significantly higher risk of developing CHD (p < 0.001 for all).
Conclusion: Waist circumference and waist-to-height ratio emerged as the most robust predictors of CHD incidence in adults. Incorporating these simple anthropometric measures into routine clinical assessments can aid in identifying individuals at higher risk of CHD and implementing timely preventive interventions.