Impact of lifestyle and mobile application engagement patterns on weight reduction in digital health intervention for obesity

Abstract Background Metabolic disorder progression can be prevented by adopting appropriate lifestyle habits. Previous reports indicate that the effectiveness of digital health interventions for lifestyle modification is influenced by pre-programmed lifestyle patterns and mobile application usage 1). However, their impact on intervention effectiveness remains unclear. Objective In this study, we identified the distinct clusters based on lifestyle behaviors and mobile application usage and examined their relationship with weight reduction in individuals with obesity participating in a lifestyle modification programme. Methods We analysed data obtained from a 6-month lifestyle modification programme that involved individuals with obesity undergoing treatment for metabolic disorders, including hypertension and diabetes. Pre-programme health check-up questionnaires were administered to assess their baseline lifestyle habits, including smoking history, alcohol consumption, exercise habits (regular exercise and brisk walking), dietary habits (skipping breakfast, eating before bedtime and eating speed) and sleep habits. Mobile application usage data, such as application launch frequency, usage duration, entry rate of lifestyle data and chat frequency, were extracted from the first two weeks of the programme. The participants were classified into distinct subgroups through latent class analysis (LCA). The programme incorporated lifestyle monitoring via a mobile application, alongside behaviour change support provided by healthcare professionals through phone calls and chat interactions. The weight change rates before and after the programme were compared across the identified clusters, using analysis of variance. Results Data of 1,924 participants were analysed. LCA identified three distinct clusters: Group 1 (44.5%), high application engagement; Group 2 (15.8%), low application engagement but with healthy lifestyle habits, and Group 3 (39.6%), low application engagement with unhealthy lifestyle habits. The weight change rates significantly differed across the three groups (P < 0.001). Group 1 exhibited the greatest weight reduction (−3.42%), which was significantly greater than that observed in Group 2 (−2.34%, P < 0.001) and Group 3 (−2.33%, P < 0.001). Conclusion Participants in the lifestyle modification programme were classified into three distinct groups according to their baseline lifestyle behaviour and mobile application usage patterns. Weight reduction outcomes were strongly associated with initial mobile application engagement, suggesting that early usage of the mobile application is a critical determinant of intervention effectiveness. Therefore, mobile application engagement may be a key predictor of successful weight management in digital health interventions.Table1.Characteristics of participants  Fig1.Weight change rate for six month