Abstract
<jats:p>Circadian biology has long been implicated in mood and depressive disorders. While longer, infradian rhythms are increasingly recognised across diverse physiological processes, their relevance to mood remains poorly understood. Using long-term wearable heart rate data, this study mapped depressive symptom severity onto person-specific multiday physiological phase. Individual-specific cycles were estimated from 413 young adult participants (Notre Dame NetHealth project) alongside up to four repeated Beck Depression Inventory (BDI) assessments (955 observations). Individual's dominant infradian rhythm (2-60 days) was estimated from heart rate using wavelet analysis, and BDI scores were indexed according to whether surveys occurred during the cycle peak or trough. Mixed-effects linear modelling examined the relationship of cycle phase with mood symptoms, and whether this relationship differed by exercise level. In those with significant cycles (360 participants, 864 observations), depressive symptom severity varied across multiday physiological phase as a function of exercise level: Cycle Phase X Exercise Group interaction, F(1,712.21)=5.13, p=0.024. BDI scores were higher at the peak than trough in the Low-exercise group, Δ = 1.69, 95% CI [0.11, 3.28], p=0.037, with no peak-trough difference in the Higher-exercise group. Higher daily heart rate, lower exercise, female sex, and winter season were associated with higher BDI scores. Notably, this study introduces a "when" dimension to depressive symptom variation and provides the groundwork for clinical studies testing whether wearable-derived cycles can characterise temporal patterns of symptom vulnerability and support personalised tracking of mood dynamics.</jats:p>