Psychosocial factors represent modifiable targets relevant to alleviate depression risk. While individual psychosocial risks are well-documented, their combined status across multiple life domains is underexplored. We aimed to construct a novel multidimensional composite score of psychosocial status and explore its association with incidence of depression.

A total of 336,922 individuals (mean age 56.21 years) without depression at baseline from the UK Biobank were included. Psychosocial status was assessed across four dimensions (recent stressful events, current psychiatric symptoms, social contact and socio-economic status) using 18 factors. A composite psychosocial score was constructed by weight effect of each factor, with higher values indicating lower level of psychosocial status. Using Cox proportional hazards models to evaluate the associations between individual psychosocial factor, psychosocial score and the risk of depression.

During a median follow-up of 13.60 years, 14,806 depression cases were identified. Low household income, recent depressive symptoms, loneliness and financial difficulties emerged as the most significant predictors of depression across four domains, with hazard ratios (HRs) of 3.82 (95% confidence intervals [CIs]: 3.43–4.26), 3.09 (2.99–3.19), 2.46 (2.37–2.54) and 1.96 (1.88–2.04), respectively. Each one-point increase in the psychosocial score was associated with a 42% higher depression risk. Compared to individuals with high psychosocial status, those in the medium- and low-level groups had an adjusted HR of 1.71 (95% CI: 1.62–1.81) and 4.36 (95% CI: 4.15–4.58), respectively.

These findings highlight that psychosocial factors collectively represent modifiable targets for preventing depression, with interventions addressing the combined status of these domains likely offering greater impact than focusing on isolated factors.