TY - JOUR
T1 - Socioeconomic variation in incidence of primary and secondary major cardiovascular disease events
T2 - an Australian population-based prospective cohort study
AU - Korda, Rosemary J.
AU - Soga, Kay
AU - Joshy, Grace
AU - Calabria, Bianca
AU - Attia, John
AU - Wong, Deborah
AU - Banks, Emily
N1 - Publisher Copyright:
© 2016 The Author(s).
PY - 2016/11/21
Y1 - 2016/11/21
N2 - 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.
AB - 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.
KW - Australia
KW - Cardiovascular diseases
KW - Cohort
KW - Disadvantage
KW - Education
KW - Health status disparities
KW - Incidence
KW - Income
KW - Inequalities
KW - Socioeconomic factors
UR - http://www.scopus.com/inward/record.url?scp=84995803018&partnerID=8YFLogxK
U2 - 10.1186/s12939-016-0471-0
DO - 10.1186/s12939-016-0471-0
M3 - Article
SN - 1475-9276
VL - 15
SP - 1
EP - 10
JO - International Journal for Equity in Health
JF - International Journal for Equity in Health
IS - 1
ER -