Correcting for BMI Self-Reporting Bias

Headshot of Zach Ward.

CHDS faculty Zachary Ward and colleagues developed a novel method for correcting self-reporting bias of body-mass index (BMI) to estimate state-specific prevalence of severe obesity in US adults.

Accurate estimates of the prevalence of obesity help state health officials develop and implement effective preventive policies and treatment programs. Data from the Behavioral Risk Factor Surveillance System (BRFSS) is used to create the Centers for Disease Control and Prevention (CDC)’s annual obesity prevalence maps. However, because BRFSS relies on self-reporting of height and weight to calculate BMI, it is subject to self-reporting bias affecting the calculations. The smaller National Health and Nutrition Examination Survey (NHANES) uses actual measures of height and weight to calculate BMI. By adjusting the BMI in BRFSS using the NHANES measured data using a validated bias-correction method, Ward and colleagues were able to estimate the quantile-specific differences between self-reported BMI in BRFSS and measured BMI in NHANES and then estimate self-report bias across the entire BMI distribution. They found that in all sociodemographic subgroups self-reporting of data resulted in underestimation of severe obesity prevalence.

Learn more: Read the press release, Improving Accuracy of State-level Obesity Estimates to Better Inform Prevention, Treatment
Learn more: Read the full article, State-Specific Prevalence of Severe Obesity Among Adults in the US Using Bias Correction of Self-Reported Body Mass Index
Learn more: Resource Pack: Decision Analysis & Childhood Obesity

Related news: Zachary Ward Appointed Assistant Professor