Characterizing Physical Activity Trajectories Preceding Incident Major Depressive Disorder Diagnosis With Consumer Wearable Devices in the All of Us Research Program: Retrospective Nested Case-Control Study

Clinical Snapshot

Key Findings

• P Value: P<0.001 for global trajectory tests

• Effect Size: 428-step reduction (95% CI -531 to -326) and 5.61-minute MVPA reduction (95% CI -7.35 to -3.86) at diagnosis

• Primary Outcome: Physical activity trajectories (daily steps and MVPA) 12 months preceding MDD diagnosis

• Nnt Or Sensitivity: Significant changes emerged 4-5 months before diagnosis, suggesting potential early detection window

• Confidence Interval: 95% CI provided for all primary estimates

Clinical Application

Requires integration of wearable data with clinical systems and patient consent for monitoring Relevant to Australian primary care and mental health services; could complement RACGP depression screening guidelines and support early intervention strategies under Medicare mental health plans Adults at risk of depression with access to wearable technology

Abstract

BACKGROUND: Low physical activity (PA) is a well-established risk factor for major depressive disorder (MDD). However, the temporal dynamics of PA preceding an incident clinical diagnosis of MDD remain poorly characterized, particularly using long-term, objective measures collected in real-world settings. OBJECTIVE: This study aimed to characterize trajectories of wearable-measured PA during the year preceding incident MDD diagnosis and identify the timing of within-person changes. METHODS: We conducted a retrospective nested case-control study using linked electronic health record and wearable (Fitbit) data from the All of Us Research Program. Adults with at least 6 months of valid Fitbit PA data in the 12 months preceding diagnosis were included. Incident MDD cases were identified based on a first electronic health record-recorded diagnosis and matched to MDD-free controls on age, sex, BMI, and calendar time of diagnosis, with up to 4 controls per case. Daily steps and moderate to vigorous PA (MVPA) were aggregated into monthly averages. Linear mixed-effects models were used to compare prediagnostic PA trajectories between cases and controls over a retrospective time scale from -12 to 0 months. Among cases, within-person contrasts were used to identify when PA levels first showed statistically significant deviations relative to levels observed 12 months before diagnosis. Exploratory analyses assessed heterogeneity by demographic factors. RESULTS: The analytic cohort included 4104 participants (n=829, 20.2% incident MDD cases and n=3275, 79.8% matched controls; n=3355, 81.7% women; median age 48.4, IQR 36.3-61.3 years). Compared with controls, individuals who developed MDD exhibited consistently lower overall PA and significant downward trajectories in both daily steps and MVPA during the year preceding diagnosis (global trajectory tests; P<.001 for both outcomes). Differences widened progressively over time, indicating accelerating declines as diagnosis approached. Among cases, statistically significant changes in daily step counts emerged approximately 4 months before diagnosis (-145, 95% CI -253 to -37 steps vs month -12; P=.02) and reached -428 (95% CI -531 to -326) steps at diagnosis (P<.001). Declines in MVPA emerged approximately 5 months before diagnosis (-2.48, 95% CI -4.32 to -0.64 minutes; P=.02) and reached -5.61 (95% CI -7.35 to -3.86) minutes at diagnosis (P<.001). Furthermore, exploratory analyses suggested heterogeneity in prediagnostic trajectories across demographic subgroups, including steeper declines among men, more pronounced reductions in activity intensity at older ages, and persistently lower activity levels with flatter trajectories among individuals with obesity. CONCLUSIONS: Unlike prior studies lacking objective PA assessment before MDD diagnosis, this study linked wearable and clinical data to characterize long-term prediagnostic trajectories in real-world settings. We observed sustained within-person declines emerging 4 to 5 months before diagnosis, providing insights into temporal dynamics preceding clinical recognition. These findings suggest that wearable-based monitoring may offer scalable early signals for risk stratification, prevention, and intervention for MDD.

References

1. 1.Zhang, Y., Folarin, A. A., Ellis, H. L., Zhong, R., Stewart, C., Sankesara, H., Kim, H., Sun, S., Pratap, A., & Dobson, R. J. B. (2026). Characterizing Physical Activity Trajectories Preceding Incident Major Depressive Disorder Diagnosis With Consumer Wearable Devices in the All of Us Research Program: Retrospective Nested Case-Control Study. Journal of Medical Internet Research, 28(5), e93164. https://doi.org/10.2196/93164