Obesity has been identified as a risk factor for heart failure. The importance of a measure of central adiposity (waist-hip ratio) as compared to BMI has not been extensively studied. The increasing prevalence of both obesity and heart failure (HF) make this association an important topic for prevention. The Atherosclerosis Risk in Communities (ARIC) study is an ongoing bi-racial population-based cohort (45-65 years) from 4 U.S. communities with 14 years median follow-up for incident hospitalized or fatal heart failure. Waist-hip ratio (WHR), waist circumference and BMI were measured at the baseline visit (1987-1989). After exclusion of prevalent HF, missing anthropometry measures, and poorly represented race groups, there were N=8,031 women and N=6,659 men at baseline. BMI was categorized as normal weight (BMI <25 kg/m2), overweight (BMI 25-30 kg/m2), and obese (BMI [greater than or equal to] 30 kg/m2). WHR and waist circumference were divided into gender-specific tertiles. Models were adjusted for demographics, alcohol use, smoking, age, and educational level using Cox proportional hazards modeling. Because HF is a syndrome without clear objective diagnostic criteria, we evaluated the effect of outcome misclassification with Monte Carlo sensitivity analysis. The impact of a hypothetical reduction in obesity and overweight on heart failure incidence was estimated by calculation of the generalized impact fraction. With stratification by race and gender, the adjusted hazard ratios for the comparison of the highest category of each anthropometric measure (obese) to the lowest were similar and [greater than or equal to] 1.0. Results from the sensitivity analysis estimated the effect of outcome misclassification was to bias our findings toward the null. Calculation of the generalized impact fraction estimated that a hypothetical 30 % reduction in the prevalence of obesity would reduce incident HF by 6.7 % in the population. Our findings do not support the superiority of a measure of central adiposity (WHR) over BMI for the prediction of incident HF. A 6.7 % reduction in heart failure, the estimated impact of a 30 % reduction in obesity, would result in 44,220 fewer incident heart failure cases per year. Such evaluations are vital to prioritize and inform future prevention programs regarding the possible impact of their efforts
