Long-Term Implications of Socioeconomic Status on Major Adverse Cardiovascular, Cerebrovascular Events (MACCE), and All-Cause Mortality

Abstract

Background

Socio-economic status (SES) has a large impact on health through a complex interplay of upstream, midstream and downstream factors. However, little is known about the predictive role of SES on long-term major adverse cardiovascular, cerebrovascular events, and mortality (MACCE).

Aim

To determine the long-term relationship between SES and MACCE for men and women. The secondary endpoint was to determine the relationship between SES and all-cause mortality.

Method

A total of 3,034 participants (1,494 women and 1,540 men) were assessed at baseline in the Geelong Osteoporosis Study, a large regional Australian population cohort study. Area-based SES was assessed, utilising the Index of Relative Socio-Economic Disadvantage (IRSD) and grouped into quintiles. The primary endpoint, MACCE, was defined as a composite of myocardial infarction, heart failure hospitalisation, malignant arrhythmias, stroke, and all-cause mortality. The secondary endpoint was all-cause mortality. Baseline data including age, sex, smoking status and alcohol use, and comorbidities were collected between 1993–1997 for women, and 2001–2006 for men, with follow-up over 30 and 22 years, respectively. Logistic regression was utilised to assess MACCE and all-cause mortality outcomes across the SES quintiles.

Results

Participants lost to follow-up or with incomplete data collection were excluded leaving 2,173 participants eligible for analysis. SES was associated with MACCE outcomes. Compared with Quintile I (lowest SES stratum), the odds of MACCE for each IRSD stratum were: Quintile II, odds ratio (OR) 0.85 (95% confidence interval [CI] 0.65–1.13); Quintile III, OR 0.69 (95% CI 0.51–0.91); Quintile IV, OR 0.66 (95% CI 0.50–0.88); and, Quintile V, OR 0.55 (95% CI 0.41–0.72). In the adjusted model, an inverse trend was noted, with reducing MACCE outcomes with an increasing SES status; IRSD Quintile II, OR 0.85 (95% CI 0.62–1.17); Quintile III, OR 0.70 (95% CI 0.50–0.97); Quintile IV, OR 0.73 (95% CI 0.52–1.02); and, Quintile V, OR 0.54 (95% CI 0.39–0.74). SES was inversely associated with all-cause mortality; IRSD Quintile II (OR 0.87, 95% CI 0.66–1.16) failed to achieve significance however IRSD Quintile III (OR 0.65, 95% CI 0.48–0.88), Quintile IV (OR 0.59, 95% CI 0.44–0.80) and Quintile V (OR 0.46, 95% CI 0.34–0.62) had a lower risk of mortality compared with Quintile I. In the adjusted model, an inversely proportional trend was noted between SES and all-cause mortality; IRSD Quintile II (OR 0.82, 95% CI 0.59–1.15), IRSD Quintile III (OR 0.63, 95% CI 0.49–0.95), Quintile IV (OR 0.59, 95% CI 0.45–0.90) and Quintile V (OR 0.44, 95% CI 0.31–0.61) had fewer mortality events compared with IRSD Quintile I.

Conclusions

Our research indicates that being part of a lower socio-economic stratum is linked to a higher likelihood of experiencing negative cardiovascular and cerebrovascular events, along with an increased risk of overall mortality. SES is an important risk stratification marker for long-term prognosis of cardiovascular diseases and stroke, and warrants further investigation.