U.S. weight trends: a longitudinal analysis of an NIH-partnered dataset.

Abstract

Background: Obesity is a major public health challenge in the U.S. Existing datasets utilized for calculating obesity prevalence, such as the National Health and Nutrition Examination Survey (NHANES) and Behavioral Risk Factor Surveillance System (BRFSS), have limitations. Our objective was to analyze weight trends in the U.S. using a nationally representative dataset that incorporates longitudinal electronic health record data.

Methods: Using the National Institutes of Health All of Us Research Program (AoU) dataset, we identified patients aged 18-70 years old who had at least two height and weight measurements within a 5-year period from 2008 to 2021. Baseline and most recent BMI values were used to calculate total body weight (%TBW) changes. %TBW change predictors were determined using multivariable linear regression.

Results: We included 30,862 patients (mean age 48.9 [ ± 12.6] years; 60.5% female). At the 5-year follow-up, the prevalences of obesity and severe obesity were 37.4% and 20.7%, respectively. The frequency of patients with normal weight or overweight BMI who gained ≥5% TBW at follow-up was 37.8% and 33.1%, respectively. Nearly 24% of the cohort lost ≥ 5% TBW, and 6.5% with severe obesity lost weight to achieve a BMI < 30 kg/m². In adjusted analyses, male sex (-1.10%, 95% CI [-1.36, -0.85]), non-Hispanic Asian race/ethnicity (-1.69% [-2.44, -0.94]), and type 2 diabetes (-1.58% [-1.95, -1.22]) were associated with weight loss, while obstructive sleep apnea (1.80% [1.40, 2.19]) was associated with weight gain.

Conclusions: This evaluation of an NIH-partnered dataset suggests that patients are continuing to gain weight in the U.S. AoU represents a unique tool for obesity prediction, prevention, and treatment given its longitudinal nature and unique behavioral and genetic data.