Engagement in a Multi-Feature Digital Health Lifestyle Change Program as a Predictor of Weight Loss

Background: Modern digital health interventions targeting weight loss employ multiple evidence-based strategies, including nutrition tracking, coaching, and activity monitoring, providing users with choice as they set and achieve their own goals. Still, limited research exists on the partial effects of each component of such interventions, and whether participants choose to use all of the features of a program. The objective of this study was to test the individual components of a fully-featured digital health lifestyle intervention as predictors of weight loss in a single statistical model. Methods: Participants in the study (N=25,273) were enrolled in the Livongo for Weight Loss program as part of their employee wellness benefit across 57 states/territories of the US from April, 2019 to January, 2021. Participants received a cellular-connected scale to use daily in the program; they were asked to track their eating via the app and physical activity via smartphones or wearables. Additionally, participants could engage with coaches voluntarily or by receiving feedback from coaches on their recorded food logs. A mixed-effects generalized linear model was used to test the effects of scale usage, physical activity, human telephonic coaching, and food logs without and without coaching feedback on the percent weight loss the following month. Predictors were disaggregated into between- and within-subject components to understand the impact of each component relative to one’s own mean. The month in the program and whether or not that month occurred during the COVID-19 pandemic were entered as time-varying covariates. Baseline age, gender, and BMI were entered as time-invariant covariates. Results: Participants were 45% male and had average age of 54.3 years old (SD =11.4), with an average BMI of 33.10 kg/m(2) (SD: 6.2). On average, participants were enrolled in the program for 10.4 months (SD: 5.1). Each additional use of the scale above one’s own average was associated with an overall 7.4% weight loss (z=21.06,p<0.001). Similarly, each additional minute of moderate-vigorous physical activity (MVPA) above one’s own average was associated with an overall 2.4% weight loss (z=3.14, p<0.01). Lastly, coaching and food logging with coaching feedback at a frequency above one’s own average were associated with approximately a 6% weight loss throughout the program (z=3.08 and 2.35, respectively; p<0.05 for both). Conclusion: We found that frequency of use of a scale in a weight loss intervention was most predictive of weight loss, followed by human coaching interaction and physical activity. However, food logging without feedback did not significantly impact weight loss among participants. Additional work is needed to understand drivers associated with increased utilization of beneficial program features, including optimizing the use of coaching, which offers great benefit, but may be costly to scale.