High-Frequency Functional Trajectories Predict Depressive Worsening in Singapore’s Community-Dwelling Older Adults

<b>Background/Objectives</b>: Functional difficulty and depression often coexist in older adults, yet local Singapore-based research often lacks detailed temporal resolution due to heterogeneity in ageing. This study employs non-parametric, data-driven longitudinal clustering to analyse functional trajectories and their association with depression, using high-frequency data to pinpoint key intervention periods. <b>Methods</b>: Data were drawn from 4273 community-dwelling older adults from Singapore Life Panel^® (2020-2024). Participants completed quarterly self-reported assessments of ADL, IADL and depressive symptoms (8-item CES-D). We employed k-means longitudinal clustering (kml) to identify functional trajectory groups and Cox regression to evaluate the hazard of increased depression (≥5-point increase in CES-D). <b>Results</b>: Three distinct trajectories emerged for both ADL and IADL (Stable, Medium increase in difficulty, High increase in difficulty). In fully adjusted Cox models, Medium and High clusters had higher hazard ratios for increased depression than Stable (ADL: HR 1.71 and 2.37; IADL: HR 1.60 and 2.20). Median time-to-event was not reached in the Stable group and occurred earlier in Medium/High clusters (ADL: 3.25 years and 1.75 years; IADL: 4.0 years and 2.1 years). The High cluster, comprising older and socioeconomically disadvantaged individuals, exhibited worse baseline health and psychosocial factor scores. Depression scores escalated in the Medium and High groups. <b>Conclusions</b>: Rapid functional difficulty acts as a precursor to worsening depressive symptoms. Routine monitoring of functional trajectories offers a strategic window for proactive mental health interventions in at-risk older adults.