Why the study?
There is limited understanding of how socioeconomic status and cardiometabolic burden collectively influence long-term mortality in real-world HF populations compared to community controls. Previous studies have seldom accounted for disparities between these groups, restricting insights into the independent contribution of non-clinical risk factors.
Cohort (n=2,156)
Yes
Socioeconomic disadvantage and cardiometabolic comorbidities significantly impact 20-year mortality in heart failure patients, with heart failure carrying a substantial independent mortality risk even after adjusting for baseline differences.
Background While heart failure (HF) is recognized for significantly worsening prognosis, there is a limited understanding of how socioeconomic status and cardiometabolic burden collectively influence long-term mortality in real-world HF populations compared to community controls. Previous studies have seldom accounted for disparities between these groups, thereby restricting insights into the independent contribution of non-clinical risk factors. This study investigates the impact of demographic, socioeconomic, and cardiometabolic determinants on 20-year mortality. Methods Data were obtained from two parallel national cohorts (2004–2005): HF patients included from primary care physician from different country region and participants from general population surveys based on random inclusion based on administrative data. Variables common to both cohorts were harmonized, and age/sex matching (1:3) was implemented. Cox regressions models were utilized to quantify independent associations between predictors and long-term survival. Kaplan Meier was used to asses long-term survival pattern. Results After matching, 2,156 participants (539 HF;1,617 controls) demonstrated substantial heterogeneity in socioeconomic status and comorbidity burden. All HF patients had much higher prevalence of all analyzed comorbidities. Likewise socioeconomic disadvantages were more frequent in HF (Table 1). In multivariable mortality models, when the two populations were analyzed separately, comorbidities such as diabetes and lipid disorders, as well as sociodemographic factors including age, sex, and unemployment, demonstrated consistent directions of prognostic influence across both cohorts, whereas hypertension (HT) showed an opposite effect (Figure 1). Some other variables like higher education, living alone were predictive only in general population, while peripheral vascular disease only in HF. Cox regression model, adjusted for all mentioned above variables showed, significantly higher mortality risk in HF patients compared to general population. Due to opposite effect in both cohorts, we analyzed HF*HT interaction showing that HF patients without HT had higher risk of mortality (HR=4.27), whereas HF×HT interaction indicated attenuation of this excess risk in those with coexisting HT (HR=2.49). Kaplan-Meier survival analysis revealed a significant difference between the groups (log-rank test: p<0.001). Conclusions Socioeconomic disadvantage and cardiometabolic comorbidities significantly impact long-term mortality risk in HF beyond traditional clinical predictors. Even after adjustment for baseline differences, HF carried a substantial independent mortality risk, highlighting the necessity for integrated care strategies that includes medical, lifestyle, and socioeconomic interventions.
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Rywik et al. (2026) conducted a cohort in Heart failure (n=2,156). Heart failure and socioeconomic/cardiometabolic determinants vs. Age- and sex-matched general population controls was evaluated on 20-year mortality (HR 4.27, p=<0.001).
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