Managing BMI and Emotional Distress Using mHealth: Nationally Representative Survey Study

Abstract

Abstract Background Mobile health (mHealth) technologies, including smartphone health apps and wearable trackers, are increasingly used to promote health behaviors. However, their impact on physical and mental well-being remains complex, with both benefits and potential unintended negative consequences. Objective This study aimed to examine the relationship between mHealth use (ie, health app and wearable tracker) and 2 health outcomes (BMI and emotional distress), as well as the mediating roles of healthy eating, sleep, and physical activity based on a representative sample. Methods We analyzed data from a nationally representative sample of US adults aged 33 to 43 years (N=1931). Chi-square tests and 1-way ANOVA were used to compare demographic differences between mHealth users and nonusers. A path model examined the relationship between mHealth use (ie, smartphone health apps and wearable trackers) and health outcomes (ie, BMI and emotional distress), with lifestyle factors (ie, healthy eating, physical activity, and sleep) as mediators. Mediation analyses tested indirect effects through these lifestyle factors. Results mHealth users were more likely to be female, married, have higher levels of education and income, and have health insurance. The primary use of mHealth was the management of physical activity. Smartphone health app use positively correlated with wearable tracker use (β=.394;<.001). Smartphone health app use predicted greater BMI (β=.068;=.006), whereas wearable tracker use did not significantly predict BMI. Smartphone health app use was unrelated to emotional distress, while wearable tracker use was associated with lower emotional distress (β=–.074;=.003). Mediation analyses showed that physical activity negatively mediated the relationships between both types of mHealth use and health outcomes, indicating that mHealth users were more physically active, which was linked to lower BMI and emotional distress. Sleep hours mediated only the association between wearable tracker use and health outcomes, such that greater tracker use was related to fewer sleep hours, predicting higher BMI and emotional distress. Finally, healthy eating mediated only the associations between mHealth use and emotional distress, suggesting that healthier dietary behaviors among mHealth users contributed to lower emotional distress. Conclusions mHealth technologies can potentially promote healthier behaviors, but their effectiveness depends on users taking the initiative to sustain lifestyle changes. While wearable trackers may aid in mental well-being, their association with reduced sleep warrants further investigation.