Journal of medical Internet research · 2026
Long-Term Associations of a Mobile-Based Chronic Disease Management Program With Employee Health: Four-Year Retrospective Cohort Study.
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Park Yujin, Kim Yoon Ji, Choi Boram, Noh Chang-Bo, Kim Su Hwan, Bang Jiseon, Lee Ji-Eun, Kang Jae-Heon, Bae Ye Seul
Аннотация
BACKGROUND: The burden of hypertension (HTN), type 2 diabetes mellitus (DM), and obesity is increasing among employees, driven by workplace-related factors such as sedentary behavior and unhealthy lifestyles, while follow-up management after health checkups remains inadequate. Mobile health (mHealth) interventions have emerged as promising tools to support self-management and sustain lifestyle changes; however, evidence regarding their long-term associations in real-world occupational settings remains limited.
OBJECTIVE: This study aimed to investigate whether a short-term mobile-based chronic disease management program was associated with sustained improvements in metabolic health outcomes among employees with metabolic risks over a 4-year period.
METHODS: The authors evaluated a 12-week mobile-based chronic disease management program delivered as part of an employee assistance program targeting workers with metabolic risk factors. Using propensity score-matched cohorts from the Kangbuk Samsung Health Study (HTN: N=90; DM: N=78; obesity: N=132), we analyzed longitudinal health examination data from 2019 (baseline) and 2023 (follow-up). Primary outcomes included blood pressure (BP), BMI, fasting glucose, glycated hemoglobin, triglycerides, and lipid profiles. Adjusted longitudinal changes were assessed using linear mixed effects models.
RESULTS: Among propensity score-matched cohorts, the intervention group showed more favorable changes compared to the controls. In the HTN cohort, systolic BP and diastolic BP showed no significant group × time interactions, although diastolic BP was lower in the intervention group at follow-up (P=.045). In the DM cohort, diastolic BP showed a significant group × time interaction (P=.02), with a decrease over time observed in the intervention group, while glycemic indicators did not differ significantly between groups. In the obesity cohort, triglycerides and high-density lipoprotein cholesterol showed significant group × time interactions (both P<.001), indicating more favorable longitudinal changes in the intervention group. Overall, the intervention groups demonstrated improved or stable cardiometabolic profiles compared to the control groups over the follow-up period.
CONCLUSIONS: A short-term, personalized mHealth intervention was associated with favorable long-term changes over a 4-year follow-up period among employees with chronic disease risk. This real-world evidence supports integrating digital health programs into routine workplace prevention strategies to bridge the postcheckup care gap.
OBJECTIVE: This study aimed to investigate whether a short-term mobile-based chronic disease management program was associated with sustained improvements in metabolic health outcomes among employees with metabolic risks over a 4-year period.
METHODS: The authors evaluated a 12-week mobile-based chronic disease management program delivered as part of an employee assistance program targeting workers with metabolic risk factors. Using propensity score-matched cohorts from the Kangbuk Samsung Health Study (HTN: N=90; DM: N=78; obesity: N=132), we analyzed longitudinal health examination data from 2019 (baseline) and 2023 (follow-up). Primary outcomes included blood pressure (BP), BMI, fasting glucose, glycated hemoglobin, triglycerides, and lipid profiles. Adjusted longitudinal changes were assessed using linear mixed effects models.
RESULTS: Among propensity score-matched cohorts, the intervention group showed more favorable changes compared to the controls. In the HTN cohort, systolic BP and diastolic BP showed no significant group × time interactions, although diastolic BP was lower in the intervention group at follow-up (P=.045). In the DM cohort, diastolic BP showed a significant group × time interaction (P=.02), with a decrease over time observed in the intervention group, while glycemic indicators did not differ significantly between groups. In the obesity cohort, triglycerides and high-density lipoprotein cholesterol showed significant group × time interactions (both P<.001), indicating more favorable longitudinal changes in the intervention group. Overall, the intervention groups demonstrated improved or stable cardiometabolic profiles compared to the control groups over the follow-up period.
CONCLUSIONS: A short-term, personalized mHealth intervention was associated with favorable long-term changes over a 4-year follow-up period among employees with chronic disease risk. This real-world evidence supports integrating digital health programs into routine workplace prevention strategies to bridge the postcheckup care gap.