Abstract MP033: Socioeconomic Disparities in the Risk of Developing Heart Failure: Prospective Findings from the Moli-Sani Study

Introduction: The association between socioeconomic status (SES) and the risk of cardiovascular disease and all-cause mortality is well-established, while the impact of SES on heart failure (HF) incidence is less explored. Hypothesis: We tested the hypothesis of a SES gradient in the risk of HF. Methods: Population-based cohort study on 22,395 individuals (mean age 55.3±11.7, 47.7% men) free from HF at baseline randomly recruited from the general population included in the Moli-sani study (Italy). The cohort was followed up for a median of 7.6 years (168,031 person-years). Annual household income (Euros) and educational level were used as SES indicators. Presence of risk factors at baseline and a panel of health behaviours were tested as possible mediators of the association between SES and incident HF. Incident HF at follow-up was defined by HF hospitalization or HF death, according to the International Classification of Diseases-Ninth Revision (ICD-9). Hazard ratios (HR) with 95% confidence intervals were calculated by Cox-proportional hazard models. Results: We identified 757 first HF events. Both lowest education (middle and secondary schools) and household income (<60,000 Euros/y) were separately associated with increased risk of HF as compared with the highest category (Table). After simultaneous adjustment, the association of income appeared to be largely explained by education. The inclusion of traditional risk factors, biomarkers of heart failure and health-behaviors into the model attenuated the association of low education with HF incidence by 12%, 3.8% and 11.5%, respectively. Overall, the full explanatory model accounted for 23.8% of the educational gradient in the risk of HF (Table). Conclusions: Educational level, rather than income, is an independent predictor of HF development. Excess risk associated with low education was partially explained by traditional health risk factors, biomarkers of subclinical damage and health-behaviors. ![][1] [1]: /embed/graphic-1.gif