Methods: Using the Health and Retirement Study (HRS), a nationally representative longitudinal survey of Americans aged 50 and older, this study analyzed 1,520 cancer survivors diagnosed prior to baseline who completed the Leave-Behind Psychosocial Questionnaire. A three-timepoint design was employed: SES and baseline depression at T1 (2012/2014), financial hardship at T2 (2014/2016 Leave-Behind survey), and depressive symptoms at T3 (2016/2018). SES was constructed as income, education years, and wealth. A latent financial hardship variable was constructed from seven indicators (financial satisfaction, difficulty making ends meet, financial strain, perceived social status, food insecurity, medication nonadherence, perceived financial control). Factor analyses supported a one factor structure. Structural equation modeling with weighted least squares estimation and complex survey design tested the mediation model, controlling for insurance, partnership, sex, race/ethnicity, age at diagnosis, and time since diagnosis.
Results: The model demonstrated good fit (RMSEA = .031, CFI = .997, TLI = 0.995). Financial hardship significantly predicted subsequent depression (β = .209, p < .001), controlling for baseline depression. Income demonstrated full mediation, i.e., the indirect effect through financial hardship was significant (β = -.079, p < .001), while the direct effect was not (β = -.015, p = .686). Education showed partial mediation, with both the indirect (β = -.017, p = .043) and direct effects (β = -.056, p = .015) remaining significant. Compared to private insurance, public insurance was associated with greater financial hardship, which in turn increased depression (indirect β = .018, p = .002). Younger age at diagnosis (β = -.358) and more recent diagnosis (β = -.270) were among the strongest predictors of financial hardship, and their effects on depression were fully mediated through financial hardship. Baseline depression also indirectly worsened future depression through increased financial hardship (indirect β = .053, p < .001), suggesting a depression-hardship vicious cycle.
Conclusions: Financial hardship is a key mechanism linking SES to depression among older cancer survivors. Income showed a significant indirect association with depression through financial hardship, while its direct association was not significant, suggesting that financial hardship may be an important pathway through which economic disadvantage relates to depression in this population. Younger and recently diagnosed survivors face disproportionate hardship, indicating that financial screening should begin at diagnosis. The depression-hardship vicious cycle underscores the need for integrated approaches addressing both mental health and financial wellbeing in survivorship care.
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