Cross-sectional analysis finds distinct financial toxicity profiles linked to elevated anxiety and depression in cardiovascular multimorbidity, suggesting targeted interventions may be beneficial.
Background Cardiovascular disease with multimorbidity imposes substantial long-term financial burdens. Financial toxicity, the financial burden associated with healthcare, is increasingly recognized as a psychosocial stressor affecting health outcomes among chronically ill populations. However, its psychological heterogeneity in non-cancer patients is understudied. We aimed to identify financial toxicity profiles, their determinants, and associations with anxiety/depression in cardiovascular non-cancer multimorbidity. Methods This study used a cross-sectional design. Utilizing latent profile analysis to identify distinct financial toxicity subgroups. Univariate and multivariate logistic regression analyses were employed to explore factors associated with subgroup membership. Inverse probability of treatment weighting based on covariate balancing propensity scores was applied to assess the associations between financial toxicity profiles and psychological distress. Doubly robust regression models were utilized to validate the robustness of the observed associations. Results Financial toxicity was categorized into three latent profiles: mild (63.8%), moderate (11.0%), and none (25.2%). Demographic, economic, social support, and coping variables significantly differed across profiles. In weighted regression models using inverse probability of treatment weighting based on covariate balancing propensity scores, both mild and moderate toxicity were associated with elevated anxiety ( β = 1.88 and 8.68, respectively) and depression scores ( β = 4.21 and 11.92; all p < 0.01) compared to the no-toxicity group. These associations remained robust in doubly robust models adjusting for covariates (GAD-7: β = 1.72 and 8.31; PHQ-9: β = 4.08 and 11.48). Conclusion Financial toxicity is prevalent and heterogeneous in cardiovascular multimorbidity. Its distinct profiles predict elevated psychological distress, supporting targeted interventions to alleviate financial burden and enhance mental health resilience.
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Wu et al. (2025) studied this question.
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