Wearable actigraphy-indexed sleep disturbances, including longer total sleep time and lower sleep efficiency, predicted MDD severity 9 years later beyond baseline severity.
Cohort (n=1,054)
Do baseline physiological ECG and sleep actigraphy wearable assessments predict major depressive disorder severity 9 years later in community adults?
Wearable actigraphy-indexed sleep disturbances predict long-term MDD symptoms beyond baseline severity, whereas ECG-derived autonomic indices offer limited incremental predictive value.
BACKGROUND: Major depressive disorder (MDD) is prevalent and poses major public health implications. Autonomic nervous system (ANS) dysregulation and sleep disturbances are theorized to be distal risk factors. However, previous research has depended on cross-sectional designs, small predictor sets, and suboptimal methods, limiting temporal inference and predictive accuracy. We thus capitalized on machine learning to identify physiology and sleep predictors of nine-year MDD symptoms. METHOD: Community adults (N = 1054) participated in a study that included baseline physiological electrocardiogram (ECG) and sleep actigraphy wearable assessments. Clinical interviews were administered to assess for psychiatric symptoms at baseline and nine-year follow-up. Eight ML models were trained to predict MDD severity using 80 baseline variables via a 70-30 train-test split with 5-fold cross-validation with 81 baseline variables to predict MDD severity. RESULTS: = 19.8%). Baseline MDD, generalized anxiety, and panic disorder symptoms strongly predicted nine-year MDD severity. Longer total sleep time, lower sleep efficiency, and higher average wake time during sleep phases were key correlates of higher nine-year MDD severity. Other correlates included fewer average sleep bouts and shorter wake times during active phases, as well as nonlinear patterns of wake time length and percentage during rest phases. Physiology ECG variables had limited incremental predictive value. CONCLUSIONS: Wearable actigraphy-indexed sleep disturbances predicted long-term MDD symptoms beyond baseline severity and ANS dysregulation indices. Combining passive sleep sensors into routine assessments might optimize MDD prevention and treatment.
Zainal et al. (Wed,) conducted a cohort in Major depressive disorder (MDD) (n=1,054). Wearable actigraphy and ECG assessments was evaluated on MDD severity at 9 years. Wearable actigraphy-indexed sleep disturbances, including longer total sleep time and lower sleep efficiency, predicted MDD severity 9 years later beyond baseline severity.