Understanding economic disparities in elderly health outcomes: a decomposition analysis in Bankura district.

BACKGROUND

Economic inequality negatively affects population health by increasing social violence, discrimination, and reduced social trust, while also limiting equitable access to healthcare services. Given these challenges, the present study aims to measure socioeconomic inequality in health outcomes among the elderly population in the Bankura district.

METHODS

The present study was conducted using a cross-sectional survey with a multi-stage random sampling design among elderly individuals in the Bankura district of West Bengal. The total sample size for the study was 480. To measure socioeconomic inequality in health outcomes, the Concentration Index (CI) and Concentration Curve (CC) were applied. Additionally, the regression-based Wagstaff decomposition method of the Concentration Index was used to identify factors associated with health inequality and their relative contributions.

RESULTS

The study findings indicate that 91% of elderly individuals suffer from at least one chronic disease. The Concentration Index values suggest that cholesterol (CI = 0.40), diabetes (CI = 0.29), and hypertension (CI = 0.04) were more concentrated among the wealthier population, whereas bone diseases (CI = -0.11), lung diseases (CI = -0.24), and heart diseases (CI = -0.04) were more prevalent among the poorer population. The decomposition analysis revealed that non-vegetarian food preference (64.5%), being poor (15.4%), smoking (13.2%), alcohol consumption (26.2%), and older age (60 years and above, 3.8%) were the major contributing factors to pro-rich inequality in chronic disease prevalence. Furthermore, the probit regression model indicated that the likelihood of chronic disease increased with age (coefficient = 0.82), being alone (coefficient = 0.32), alcohol consumption (coefficient = 0.37), and smoking (coefficient = 0.21).

CONCLUSION

The study reveals that health inequality was more pronounced among economically disadvantaged individuals due to low levels of education and engagement in unhealthy, risky behaviors. Policymakers should focus on improving health-related infrastructure in rural areas, particularly for the oldest-old population.