Weight Gain Prevention Outcomes From a Pragmatic Digital Health Intervention With Community Health Center Patients: Randomized Controlled Trial

Abstract

Background: The prevalence of obesity and its associated comorbidities continue to rise in the United States. Populations who are uninsured and from racial and ethnic minority groups continue to be disproportionately affected. These populations also experience fewer clinically meaningful outcomes in most weight loss trials. Weight gain prevention presents a useful strategy for individuals who experience barriers to weight loss. Given the often-limited weight management resources available to patients in primary care settings serving vulnerable patients, evaluating interventions with pragmatic designs may help inform the design of comprehensive obesity care delivered in primary care.

Objective: This study aims to evaluate the effectiveness of Balance, a 2-arm, 12-month pragmatic randomized controlled trial of a digital weight gain prevention intervention, delivered to patients receiving primary care within federally qualified community health centers.

Methods: Balance was a 2-arm, 12-month pragmatic randomized controlled trial of a digital weight gain prevention intervention delivered to individuals who had a BMI of 25-40 kg/m², spoke English or Spanish, and were receiving primary care within a network of federally qualified community health centers in North Carolina. The Balance intervention was designed to encourage behavioral changes that result in a slight energy deficit. Intervention participants received tailored goal setting and tracking, skills training, self-monitoring, and responsive health coaching from registered dietitians. Weight was measured at regular primary care visits and documented in the electronic health record. We compared the percentage of ≤3% weight gain in each arm at 24 months after randomization-our primary outcome-using individual empirical best linear unbiased predictors from the linear mixed-effects model. We used individual empirical best linear unbiased predictors from participants with at least 1 electronic health record weight documented within a 6-month window centered on the 24-month time point.

Results: We randomized 443 participants, of which 223 (50.3%) participants were allocated to the intervention arm. At baseline, participants had a mean BMI of 32.6 kg/m². Most participants were Latino or Hispanic (n=200, 45.1%) or non-Latino or Hispanic White (n=115, 26%). In total, 53% (n=235) of participants had at least 1 visit with weight measured in the primary time window. The intervention group had a higher proportion with ≤3% weight gain at 6 months (risk ratio=1.12, 95% CI 0.94-1.28; risk difference=9.5, 95% CI -4.5 to 16.4 percentage points). This difference attenuated to the null by 24 months (risk ratio=1.00, 95% CI 0.82-1.20; risk difference=0.2, 95% CI -12.1 to 11.0 percentage points).

Conclusions: In adults with overweight or obesity receiving primary care at a community health center, we did not find long-term evidence to support the dissemination of a digital health intervention for weight gain prevention.

Trial registration: ClinicalTrials.gov NCT03003403; https://clinicaltrials.gov/study/NCT03003403.

International registered report identifier (irrid): RR2-10.1186/s12889-019-6926-7.

Keywords: digital health; health disparities; intervention; obese; obesity; overweight; pragmatic clinical trial; prevalence; primary care; weight gain prevention; weight management.