P2512Association between income and control of cardiovascular risk factors after acute coronary syndrome

Abstract

Background: New preventive strategies recommended after acute coronary syndrome (ACS) such as the prescription PCSK9 inhibitors drugs are expensive, and may be limited to people with high socio-economic status. However, in countries with universal health insurance coverage like in Switzerland, income shouldn't influence optimal control of cardiovascular risk factors (CVRF). Purpose: We aim to assess the association between income and control of CVRF one-year after ACS in Switzerland. Methods: Between January 2013 and August 2014, we studied 244 patients from a prospective cohort of patients hospitalized with ACS in one academic center in Switzerland. We assessed household income at baseline and at one-year followup with a validated self-reported questionnaire, and stratified patients in 3 income categories (1) high defined as more than 9000 CHF per month, (2) medium, defined as between 4500 and 9000 CHF per month, (3) and low defined as less than 4500 CHF per month. We used age-sex adjusted logistic regression models to assess the association between income and one-year control of CVRF such as 1) ideal cholesterol management, defined as LDL-cholesterol below 1.8 mmol/l or 50% decrease; 2) ideal blood pressure control, defined as below 140/90 mmHg; 3) smoking cessation; 4) reporting using drugs according to guidelines, defined as the concomitant use of aspirin, statin and either angiotensin converting enzyme inhibitors, angiotensin-receptor blockers, or beta-blockers. Results: Overall, 31% (n=75) of patients with ACS were in the high income category, 53% (n=129) in the middle and 16% (n=40) in the low income category. In the high income category, there were more men than in the low income category (90% vs 65%, p<0.001), patients were more likely to have achieved high school (65% vs 19%, p<0.001) and were also more likely to be married (75% vs 40%, p=0.002). At one year, rates of ideal cholesterol management were not significantly increased between all three categories of income, reaching 47% for the high, 39% for the medium and 30% for the low income category (age-sex odds ratio (OR) high vs low category 2.33, 95% CI 0.93-5.85, p=0.071). Similar rate of ideal blood pressure control and adherence to recommended drugs were found for the 3 categories of income. However, more patients in the high income category stopped smoking one-year after hospital discharge compared to the low income category, (56% vs 24%, age-sex adjusted OR 4.13, 95% CI 1.27-13.46, p=0.019). This association was slightly modified after adjustment for education and marital status (multivariate adjusted OR 3.12, 95% CI 0.90-10.86, p=0.07). Conclusion: A low houshold income decreased rate of smoking cessation compared to high household income but doesn't seem to influence rates of recommended medication use after an ACS. Universal health insurance coverage may limit the impact of income inequalities regarding drug availability but not regarding the change of smoking behavior.