The impact of socioeconomic status on secondary prevention of the acute coronary syndrome

Abstract

Abstract Background Although socioeconomic status (SES) has been reported to be associated with health inequities, there are limited studies exploring the association between SES and secondary prevention of acute coronary syndrome (ACS) in countries with universal health cover. Purpose The aim is to examine whether SES has an impact on the secondary prevention of ACS in Australia. Methods Australian SNAPSHOT ACS data (2012) and its 18-month follow-up data were linked to admissions data from 6 jurisdictions covering all states and territories, national death index and Medicare Pharmaceutical Benefits Scheme data covering up to 3 years post-discharge. The five SES groups (lowest in Group 1 and highest in Group 5) were derived from the Australian Bureau of Statistics Socio-Economic Indexes for Areas (SEIFA) using the residential postcode at baseline. Outcomes were cardiac rehabilitation (CR) participation and smoking rate at 18 months post discharge as well as the use of ≥3 of the 4 indicated medications, all-cause death and cardiovascular disease (CVD) rates by 36 months of discharge. Outcomes were compared between the groups using the multilevel logistic regression with covariates of SES (5 groups), sex, GRACE risk score (4 groups), ACS diagnosis (STEMI/NSTEMI/UA) and the jurisdictions where the admissions data were linked. Results Of 1655 patients with ACS (mean age 68±13.5 yrs, 65% were male), who were discharged from hospital alive and had linked data available, 353 (21%) were in SES Group 1 (lowest SES), 369 (22%) in Group 2, 382 (23%) in Group 3, 296 (18%) in Group 4 and 255 (15%) in Group 5 (highest SES). Baseline clinical characteristics were comparable across the five SES groups. At 18-month after discharge, 1014 (61%) patients were followed-up with comparable loss to follow-up in each group. After adjustment, fewer patients in the lower SES groups (Groups 1 and 2) had participated in CR than those in the highest SES group (Group 5) (OR (95% CI): 0.60 (0.36, 0.99) and 0.56 (0.35, 0.91), respectively). Moreover, the odds of smoking was greater in Group 3 than Group 5 (2.60 (1.15, 5.89)) but no trend was found across the groups. By 36 months of discharge after adjustment, there was no difference in the odds of using ≥3 out of 4 medications between the SES groups. Despite this, patients in Groups 1 and 2 were significantly more likely to die than those in the highest SES group (1.96 (1.19, 3.21) and 1.91 (1.19, 3.07), respectively). The odds of CVD readmission did not differ across SES groups. Conclusion This study suggests that patients with low SES were less likely to participate in CR programs and more likely to die than those with high SES. Smoking rates varied between patients with intermediate and high SES but no trend was found across the groups. Despite the universal health cover available, inequity between the SES groups still exist. Future research is needed to further explore strategies to help close the evidence-practice gaps. Funding Acknowledgement Type of funding source: Public grant(s) – National budget only. Main funding source(s): Australian National Heart Foundation Postdoctoral Fellowship