[Factors of depression according to actigraphy in the fall season]

To evaluate the relationship between sleep parameters, physical activity, and illumination obtained by weekly actigraphy and depression symptoms measured by the Beck Depression Inventory (BDI-II) in young adults in the fall season.

The crossover study, conducted during one fall month, included 122 adults (mean age 24.40 years, 76.6% females) from Tyumen (Russia). Participants were monitored for seven days using actigraphy and completed the Russian version of the BDI-II questionnaire to assess depressive symptoms. Actigraphy data were analyzed for quantitative and qualitative sleep parameters, dynamic illumination, and circadian rhythm of motor activity. Both mean values and regularity indicators were recorded. Statistical analysis was performed using linear and multiple linear regression methods, using the Benjamini-Hochberg procedure to control the incidence of false correlations associated with multiple testing.

The analysis showed significant correlations between various actigraphic indicators and the level of depression according to BDI-II. In particular, the BDI-II integral score was significantly associated with a decrease in the amplitude of the circadian rhythm of physical activity (PIM A: -0.258; p=0.005), a high instability of sleep efficiency (SL_EFF SD: -0.323; p=0.0003), a high standard deviation of the moment of awakening (WT SD: -0.258; p=0.005), a decrease in the inter-day stability of the activity rhythm (IS: -0.260; p=0.004), and a lower circadian light hygiene index (NA_bl: -0.193; p=0.036). After multiple comparison adjustments, low PIM A, reduced inter-day stability (IS), increased WT SD, and high SL_EFF SD remained significant predictors of depressive symptoms. In age-, sex-, and body mass index (BMI)-adjusted multiple regression, WT SD (β=-0.258; p=0.006), SL_EFF SD (β=-0.302; p=0.0006), and IS (β=-0.225; p=0.013) were significant factors.

The data obtained indicate a complex relationship between sleep dynamics and mental health in the context of BDI-II. They emphasize the critical importance of using parameters that assess sleep regularity as one of the markers of biological clock synchrony to increase informative value and improve the interpretation of data obtained using wearable devices.