Body mass index estimates using a categorical body weight variable: a cross-sectional secondary data analysis

Self-reported weight data have been considered questionable because of under- or over-reporting trends and stigma, especially among females.

This study aimed to evaluate the quality of self-reported categorical weight information used to determine body mass index (BMI) groups among females.

Cross-sectional secondary data analysis.

This study used two datasets: a nurse survey of the Nurses Worklife and Health Study (NWHS) in the 2 US states, and the 2003-2004 National Health and Nutrition Examination Survey (NHANES).

This analysis included 2203 female nurses in the NWHS and 606 female participants in the NHANES, all of whom aged 22-83 years and were currently employed with at least a college education.

BMI groups created using self-reported categorical weight data were compared to those derived from continuous weight responses and to the gold standard: scale measured weight data.

When using the median values of each weight category, similar distributions of BMI groups were found to those obtained from continuous self-reported responses and direct scaled measures of weight. The groupings derived from the BMI median estimates demonstrated good agreement with those obtained from the directly scaled BMI data and good criterion/construct validity.

BMI-based weight groups derived from self-reported categorical weight responses demonstrated good psychometric properties when the median value was used to calculate the BMI, and may promote more complete responding, especially among women.