Socioeconomic inequalities and dyslipidaemia in adult population of the Ravansar Non-Communicable Disease Cohort Study: the role of sex and age.

OBJECTIVES

This study represents a pioneering attempt to quantify the contribution of age, sex and socioeconomic status (SES) to the observed inequalities in lipid profile components.

DESIGN

Cross-sectional study.

SETTING

The data from the Ravansar Non-Communicable Disease (RaNCD) Cohort Study were used.

PARTICIPANTS

10 000 individuals aged 35-65 years.

MAIN OUTCOME MEASURES

Principal component analysis was used to determine the SES of individuals. Using the concentration index (C-index) and curves, the study assessed socioeconomic inequalities in dyslipidaemia in different age groups and genders. Decomposition analysis was used to determine the contribution of sex, age and SES to the observed inequality in the prevalence of dyslipidaemia components between the wealthiest and poorest groups.

RESULTS

The prevalence of dyslipidaemia was 72.39% of the population and was significantly higher in women than in men (excluding hypertriglyceridaemia). Overall, no significant SES-based inequality in dyslipidaemia was observed (C-index=-0.045, p=0.116), but after adjustment for age and sex, individuals with high SES had increased odds of dyslipidaemia (OR=1.16, 95% CI: 1.03 to 1.31). Hypercholesterolaemia and hyper-low-density lipoprotein (LDL) were more common in individuals with lower SES (C-index=-0.117 and -0.105), while hypo-high-density lipoprotein (HDL) was more prevalent in individuals with higher SES (C-index=0.029), regardless of adjustment for age, sex and confounding factors. SES played a significant role in hypercholesterolaemia and hyper-LDL (322.11% and 400.14%), while sex dominated in hypertriglyceridaemia and hypo-HDL (814.05% and -615.26%) and contributed to the existing inequalities.

CONCLUSION

The results highlight the existing inequalities in lipid profiles due to SES, sex and age. Consideration of these factors in interventions and policy decisions is critical to reduce abnormalities and inform future interventions.