Socioeconomic variation in incidence of primary and secondary major cardiovascular disease events: an Australian population-based prospective cohort study
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Korda, Rosemary
Soga, Kay
Joshy, Grace
Calabria, Bianca
Attia, John
Wong, Deborah
Banks, Emily
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BioMed Central
Abstract
BACKGROUND Cardiovascular disease (CVD) disproportionately affects disadvantaged people, but reliable quantitative evidence on socioeconomic variation in CVD incidence in Australia is lacking. This study aimed to quantify socioeconomic variation in rates of primary and secondary CVD events in mid-age and older Australians. METHODS Baseline data (2006-2009) from the 45 and Up Study, an Australian cohort involving 267,153 men and women aged ≥ 45, were linked to hospital and death data (to December 2013). Outcomes comprised first event - death or hospital admission - for major CVD combined, as well as myocardial infarction and stroke, in those with and without prior CVD (secondary and primary events, respectively). Cox regression estimated hazard ratios (HRs) for each outcome in relation to education (and income and area-level disadvantage), separately by age group (45-64, 65-79, and ≥ 80 years), adjusting for age and sex, and additional sociodemographic factors. RESULTS There were 18,207 primary major CVD events over 1,144,845 years of follow-up (15.9/1000 person-years), and 20,048 secondary events over 260,357 years (77.0/1000 person-years). For both primary and secondary events, incidence increased with decreasing education, with the absolute difference between education groups largest for secondary events. Age-sex adjusted hazard ratios were highest in the 45-64 years group: for major CVDs, HR (no qualifications vs university degree) = 1.62 (95% CI: 1.49-1.77) for primary events, and HR = 1.49 (1.34-1.65) for secondary events; myocardial infarction HR = 2.31 (1.87-2.85) and HR = 2.57 (1.90-3.47) respectively; stroke HR = 1.48 (1.16-1.87) and HR = 1.97 (1.42-2.74) respectively. Similar but attenuated results were seen in older age groups, and with income. For area-level disadvantage, CVD gradients were weak and non-significant in older people (> 64 years). CONCLUSIONS Individual-level data are important for quantifying socioeconomic variation in CVD incidence, which is shown to be substantial among both those with and without prior CVD. Findings reinforce the opportunity for, and importance of, primary and secondary prevention and treatment in reducing socioeconomic variation in CVD and consequently the overall burden of CVD morbidity and mortality in Australia.
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Keywords
Australia, cardiovascular diseases, cohort, disadvantage, education, health status disparities, incidence, income, inequalities, socioeconomic factors, aged, aged, 80 and over, cardiovascular diseases, female, humans, incidence, male, middle aged, myocardial infarction, proportional hazards models, prospective studies, risk factors, socioeconomic factors, stroke
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International journal for equity in health
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Open Access
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