Income-related inequalities in cardiovascular disease from mid-life to old age in a Northern Swedish cohort: A decomposition analysis

• Published in: Social science & medicine (1982) 2016-01, Vol.149, p.135-144
• Main Authors: Mosquera, Paola A., San Sebastian, Miguel, Waenerlund, Anna-Karin, Ivarsson, Anneli, Weinehall, Lars, Gustafsson, Per E.
• Format: Article
• Language: English
• Subjects: Adult; Age Distribution; Aged; Cardiovascular disease; Cardiovascular diseases; Cardiovascular Diseases - epidemiology; Cohort design; Cohort Studies; Concentration index; Decomposition; Decomposition. Life course; Employment; Equity; Health Status Disparities; Heart disease; Hospitalization; Humans; Income - statistics & numerical data; Income inequality; Inequality; Intervention; Life course; Middle Aged; Older people; Sociodemographics; Socioeconomic Factors; Sweden; Sweden - epidemiology
• ISSN: 0277-9536; 1873-5347; 1873-5347
• DOI: 10.1016/j.socscimed.2015.12.017

While the social determinants of cardiovascular disease (CVD) are fairly well-known, the determinants of socioeconomic inequalities in CVD are scarcely studied and almost completely based on cross-sectional designs in which the changing circumstances across the life course are not taken into account. The present study seeks to incorporate a life course approach to the social determinants of socioeconomic inequalities in CVD. The specific aims were to 1) examine how income-related inequalities in CVD change over two decades of the mid-late life course, and 2) identify the key social determinants of the inequalities at each time period. The cohort (N = 44,039) comprised all individuals aged 40–60 years in 1990 who during 1990–2010 were enrolled in the county-wide preventive effort :“Västerbotten Intervention Program” (VIP). The cohort was followed over these two decades by Swedish population register data linked within the Umeå SIMSAM Lab micro data infrastructure. First-time hospitalization for CVD and mean earned income were used to calculate the concentration index (C) during four periods of 5–6 years. The C for each period was decomposed by sociodemographic factors, using Wagstaff-type decomposition analysis. Results suggest that inequalities in CVD increase gradually from mid-life to old age; from initially non-significant to particularly marked among the elderly. The decomposition showed that, from middle to old age, educational and employment inequalities underwent a transition from initially dominant to a moderate role in explaining the health inequalities, coupled with an increasing importance of age and a stable role of income. In conclusion, the study illustrates the need for incorporating a dynamic life course perspective into research, policy and practice concerned with equity in health. •Income inequalities in CVD increased gradually from mid-life to old age.•The key factors explaining CVD inequalities underwent life-course transitions.•Labour market factors successively gave way to age as a central determinant.•Income inequalities remained a persistently key determinant across aging.•A joint equity lens and life course approach may be needed to tackle inequities.