Healthcare inequity arising from unequal response to need in the older (45+ years) population of India: Analysis of nationally representative data

Soc Sci Med. 2025 Jan:364:117535. doi: 10.1016/j.socscimed.2024.117535. Epub 2024 Nov 20.

Abstract

Given the large and growing number of older (45+ years) people in India, inequitable access to healthcare in this population would slow global progress toward universal health coverage. We used a 2017-18 nationally representative sample of this population (n = 53,687) to estimate healthcare inequality and inequity by economic status. We used an extensive battery of indicators in nine health domains, plus age and sex, to adjust for need. We measured economic status by monthly per capita consumption expenditure and used a concentration index to measure inequalities in probabilities of any doctor visit and any hospitalisation within 12 months. We decomposed inequality with a regression method that allowed for economic and urban/rural heterogeneity in partial associations between healthcare and both need and non-need covariates. We used the associations achieved by the richest fifth of urban dwellers to predict a need-justified distribution of healthcare and compared the actual distribution with that benchmark to identify inequity. We found pro-rich inequalities in doctor visits and hospitalisations, which were driven by use of private healthcare. Adjustment for the greater need of poorer individuals revealed pro-rich inequity that exceeded inequality by about 65% and 39% for doctor visits and hospitalisations, respectively. These adjustments would have been substantially smaller, and inequity underestimated, without allowing for use-need heterogeneity, which accounted for 11% of the inequity in doctor visits and was 373% of inequity in hospitalisations. Targeting service coverage on poorer and rural groups, and increasing their access to private providers, would both reduce inequity and raise average coverage in the older population of India.

Keywords: Ageing; Decomposition; Healthcare utilisation; Inequality; Universal health coverage.

MeSH terms

  • Aged
  • Aged, 80 and over
  • Female
  • Health Services Accessibility* / statistics & numerical data
  • Health Services Needs and Demand / statistics & numerical data
  • Healthcare Disparities* / statistics & numerical data
  • Hospitalization / statistics & numerical data
  • Humans
  • India
  • Male
  • Middle Aged
  • Rural Population / statistics & numerical data
  • Socioeconomic Factors