Digital health interventions for promoting adults lifestyle behaviors: who is being left behind? An evidence synthesis of social inequality

Background: Digital health interventions have gained increasing prominence worldwide and demonstrate substantial potential for promoting healthy lifestyle behaviors. However, accumulating evidence suggests that not all population groups benefit equally from these interventions, raising concerns about persistent social inequalities in access, engagement, and outcomes. Methods: This study conducted an umbrella review to systematically synthesize evidence from review-level studies that examined social inequality indicators in digital health interventions targeting lifestyle behaviors among adults. Comprehensive searches were performed across seven electronic databases, identifying 41 eligible reviews published between January 2000 and June 2025. Data were extracted on targeted behavioral domains, intervention outcomes, and reported social inequality indicators. Results: The included reviews primarily focused on interventions targeting physical activity and diet, followed by sedentary behavior and sleep, with behavioral outcomes serving as the main evaluation metrics. Among social inequality indicators, age, gender, and place of residence were most frequently reported. In contrast, indicators such as income, race/ethnicity, socioeconomic status, education, digital health literacy, and employment were substantially underrepresented. This uneven distribution indicates significant gaps in the current evidence base and suggests that the differential effects of digital health interventions across social groups may be underestimated or overlooked. Conclusions: Current review-level evidence on digital health interventions insufficiently captures the full spectrum of social inequalities shaping intervention access, engagement, and benefits. To support more equitable and inclusive health promotion strategies, future research should systematically incorporate a broader range of social inequality indicators and conduct in-depth analyses of the mechanisms underlying unequal intervention effects across diverse demographic and socioeconomic groups.