Decomposition of gendered income-related inequalities in multiple biological cardiovascular risk factors in a middle-aged population.

backgroundSocioeconomic inequalities in cardiovascular disease seem to widen or endure in Sweden. However, research on inequalities in antecedent cardiovascular risk factors (CVRFs), and particularly what underpins them, is scarce. The present study aimed 1) to estimate income-related inequalities in eight biological cardiovascular risk factors in Swedish middle-aged women and men; and 2) to examine the contribution of demographic, socioeconomic, behavioural and psychosocial determinants to the observed inequalities.

methodsParticipants (N = 12,481) comprised all 40- and 50-years old women and men who participated in the regional Västerbotten Intervention Programme in Northern Sweden during 2008, 2009 and 2010. All participants completed a questionnaire on behavioural and psychosocial conditions, and underwent measurements with respect to eight CVRFs (body mass index; waist circumference; total cholesterol; high-density lipoprotein cholesterol; low-density lipoprotein cholesterol; triglycerides; systolic/diastolic blood pressure; glucose tolerance). Data on cardiovascular risk, psychosocial and health behaviours were linked to national register data on income and other socioeconomic and demographic factors. To estimate income inequalities in each CVRF concentration indexes were calculated, and to examine the contribution of the underlying determinants to the observed inequalities a Wagstaff-type decomposition analysis was performed separately for women and men.

resultsHealth inequalities ranged from small to substantial with generally greater magnitude in women. The highest inequalities among women were seen in BMI, triglycerides and HDL-cholesterol (Concentration index = - 0.1850; - 0.1683 and - 0.1479 respectively). Among men the largest inequalities were seen in glucose regulation, BMI and abdominal obesity (Concentration index = - 0.1661; - 0.1259 and - 0.1172). The main explanatory factors were, for both women and men socioeconomic conditions (contributions ranging from 54.8 to 76.7% in women and 34.0-72.6% in men) and health behaviours (contributions ranging from 6.9 to 20.5% in women and 9.2 to 26.9% in men). However, the patterns of specific dominant explanatory factors differed between CVRFs and genders.

conclusionTaken together, the results suggest that the magnitude of income-related inequalities in CVRFs and their determinants differ importantly between the risk factors and genders, a variation that should be taken into consideration in population interventions aiming to prevent inequalities in manifest cardiovascular disease.