The risk of falling into poverty after developing heart disease: A survival analysis

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Abstract

Background: Those with a low income are known to have a higher risk of developing heart disease. However, the inverse relationship - falling into income poverty after developing heart disease has not been explored with longitudinal data. This paper aims to determine if those with heart disease have an elevated risk of falling into poverty. Methods: Survival analysis was conducted using the longitudinal Household Income and Labour Dynamics in Australia survey, between the years 2007 and 2012. The study focused on the Australian population aged 21 years and over in 2007 who were not already in poverty and did not already have heart disease, who were followed from 2007 to 2012. Cox regression models adjusting for age, sex and time-varying co-variates (marital status, home ownership and remoteness of area of residence) were constructed to assess the risk of falling into poverty. Results: For those aged 20 who developed heart disease, the hazard ratio for falling into income poverty was 9.24 (95 % CI: 8.97-9.51) and for falling into multidimensional poverty the hazard ratio was 14.21 (95 % CI: 13.76-14.68); for those aged 40 the hazard ratio for falling into income poverty was 3.45 (95 % CI: 3.39-3.51) and for multidimensional poverty, 5.20 (95 % CI: 5.11-5.29); and for those aged 60 the hazard ratio for falling into income poverty was 1.29 (95 % CI: 1.28-1.30) and for multidimensional poverty, 1.52 (95 % CI: 1.51-1.54), relative those who never developed heart disease. The risk for both income and multidimensional poverty decreases with age up to the age of 70, over which, those who developed heart disease had a reduced risk of poverty. Conclusion: For those under the age of 70, developing heart disease is associated with an increased risk of falling into both income poverty and multidimensional poverty.

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APA

Callander, E. J., & Schofield, D. J. (2016). The risk of falling into poverty after developing heart disease: A survival analysis. BMC Public Health, 16(1). https://doi.org/10.1186/s12889-016-3240-5

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