Effects of Smartphone-Based Remote Interventions on Dietary Intake, Physical Activity, Weight Control, and Related Health Benefits Among the Older Population With Overweight and Obesity in China: Randomized Controlled Trial

**Background:** The global aging population and rising rates of overweight and obesity pose major public health challenges. Traditional health management is resource-intensive and limited by time and space. Remote medical technology, particularly smartphone-based interventions, offers a scalable alternative, but evidence in older populations is limited. This study aimed to evaluate the effects of a smartphone-based remote management system on dietary intake, physical activity, weight control, and health benefits in older Chinese adults with overweight or obesity.

**Methods:** This was a 3-month randomized controlled trial conducted in China. A total of 750 participants aged 60–80 years with BMI ≥ 24 kg/m² were recruited via community posters and social media, and randomly assigned to three groups (250 each): a remote dietary and physical activity intervention group (group DPI), a remote physical activity intervention group (group PI), and a control group (group C). The intervention used a smartphone app (YIDO Health) connected to activity trackers and weighing scales, following a 'health information collection—health assessment—guidance and feedback—follow-up' model. Group DPI received personalized dietary and physical activity guidance from professionals via WeChat or phone 3–5 times per week, including low-energy diet recipes and encouragement for at least 20 minutes of resistance or aerobic activity or 6000 steps daily. Group PI received only the physical activity intervention. Group C received only a health education book. Data were collected at baseline (time 1), day 45 (time 2), and day 90 (time 3), including dietary intake (via food frequency questionnaire), physical activity (via International Physical Activity Questionnaire-based tool), anthropometrics (weight, height, BMI, waist and hip circumference), and blood biomarkers (fasting blood glucose, HbA1c, lipids, blood pressure). Statistical analysis used repeated measures ANOVA, Mann-Whitney U tests, and Kruskal-Wallis tests as appropriate.

**Key Results:** A total of 85.6% (642/750) of participants completed the 90-day follow-up (94.8% in group DPI, 81.2% in group PI, 80.8% in group C). At baseline, groups were similar in age (mean 70.1 years), sex (46.1% female), BMI (mean 27.67 kg/m²), and other characteristics. At time 3, group DPI showed significant reductions compared to group C in total energy intake (−581 vs −82 kcal; P<.05), protein (−17 vs −3 g; P<.05), fat (−8 vs 3 g; P<.05), and carbohydrate intake (−106.5 vs −4.7 g; P<.05). Cereal and potato intake decreased significantly in groups DPI and PI (P<.05). Physical activity levels related to transportation and housework/gardening improved in groups PI and C (P<.05), but overall physical activity levels did not differ significantly between groups. For weight control, group DPI showed significantly greater reductions than groups PI and C at time 2 in weight (−1.56 vs −0.86 and −0.66 kg; P<.05) and BMI (−0.61 vs −0.33 and −0.27 kg/m²; P<.05). At time 3, these differences were larger: weight change −4.11 vs −1.01 and −0.83 kg (P<.05), BMI change −1.61 vs −0.40 and −0.33 kg/m² (P<.05), and waist circumference change −2.76 vs −0.12 and 0.47 cm (P<.05). For health biomarkers at time 3, group DPI showed significantly greater improvements than group C in systolic blood pressure (−8.15 vs −3.80 mmHg; P<.05), triglycerides (−0.48 vs 0.18 mmol/L; P<.05), fasting blood glucose (−0.77 vs −0.14 mmol/L; P<.05), HDL-C (−0.00 vs −0.07 mmol/L; P<.05), and HbA1c (−0.19% vs −0.07%; P<.05). Group DPI also significantly outperformed group PI on several of these measures.

**Clinical Implications:** This study demonstrates that a smartphone-based remote intervention combining dietary and physical activity guidance is feasible and effective for improving weight control and metabolic health in older adults with overweight or obesity over 3 months. The combined intervention produced clinically meaningful weight loss (−4.11 kg), reductions in systolic blood pressure (−8.15 mmHg), and improvements in glycemic control and lipid profiles. The remote management model overcomes barriers of time, geography, and resource intensity associated with traditional programs. However, the study had a short duration (3 months) with no follow-up after intervention cessation, and lacked a traditional in-person management comparator group. Further research is needed to assess long-term sustainability and compare effectiveness with conventional approaches. The findings support broader implementation of smartphone-based remote health management for the aging population.