Prediction of body mass index using concurrently self-reported or previously measured height and weight

Objective: To compare alternative models for the imputation of BMI_M (measured weight in kilograms/ measured height in meters squared) in a longitudinal study. Methods: We used data from 11,008 adults examined at wave III (2001-2002) and wave IV (2007-2008) in the National Longitudinal Study of Adolescent to Adult Health. Participants were asked their height and weight before being measured. Equations to predict wave IV BMI_M were developed in an 80% random subsample and evaluated in the remaining participants. The validity of models that included BMI constructed from previously measured height and weight (BMI_PM) was compared to the validity of models that used BMI calculated from concurrently self-reported height and weight (BMI_SR). The usefulness of including demographics and perceived weight category in those models was also examined. Results: The model that used BMI_SR, compared to BMI_PM, as the only variable produced a larger R² (0.913 vs. 0.693), a smaller root mean square error (2.07 vs. 3.90 kg/m²) and a lower bias between normal-weight participants and those with obesity (0.98 vs. 4.24 kg/m²). The performance of the model containing BMI_SR alone was not substantially improved by the addition of demographics, perceived weight category or BMI_PM. Conclusions Our work is the first to show that concurrent self-reports of height and weight may be more useful than previously measured height and weight for imputation of missing BMI_M when the time interval between measures is relatively long. Other time frames and alternatives to inperson collection of self-reported data need to be examined.