Integrating Geospatial Data and Measures of Disability and Wealth to Assess Inequalities in an Eye Health Survey: An Example from the Indian Sunderbans

Int J Environ Res Public Health. 2019 Dec 3;16(23):4869. doi: 10.3390/ijerph16234869.

Abstract

The Sunderbans are a group of delta islands that straddle the border between India and Bangladesh. For people living on the Indian side, health services are scarce and the terrain makes access to what is available difficult. In 2018, the international non-governmental organisation Sightsavers and their partners conducted a population-based survey of visual impairment and coverage of cataract and spectacle services, supplemented with tools to measure equity in eye health by wealth, disability, and geographical location. Two-stage cluster sampling was undertaken to randomly select 3868 individuals aged 40+ years, of whom 3410 were examined. Results were calculated using standard statistical processes and geospatial approaches were used to visualise the data. The age-sex adjusted prevalence of blindness was 0.8%, with higher prevalence among women (1.1%). Cataract Surgical Coverage for eyes at visual acuity (VA) 3/60 was 86.3%. The study did not find any association between visual impairment and wealth, however there were significant differences by additional (non-visual) disabilities at all levels of visual impairment. Geospatial mapping highlighted blocks where higher prevalence of visual impairment was identified. Integrating additional tools in population-based surveys is critical for measuring eye health inequalities and identifying population groups and locations that are at risk of being left behind.

Keywords: Blindness; GIS and spatial analysis; cataract surgical coverage; visual impairment.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Adult
  • Aged
  • Disability Evaluation*
  • Female
  • Geographic Information Systems*
  • Health Surveys*
  • Healthcare Disparities / statistics & numerical data*
  • Humans
  • India / epidemiology
  • Male
  • Middle Aged
  • Spatial Analysis
  • Vision Disorders / epidemiology*