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

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.

Changes in prevalence and causes of visual impairment and cataract surgical coverage in Nampula, Mozambique between 2011 and 2018: findings from two cross-sectional surveys

“…(8,9) In addition to measuring these indicators in the population as a whole, it is important to understand how such measures differ between different sub-groups, men and women, rich and poor, urban and rural and those with and without disabilities (8,10,11). Evidence exists to suggest that health needs and access to health services varies between different population sub-groups but often to different extents in different locations (10,12,13).…”

Changes in prevalence and causes of visual impairment and cataract surgical coverage in Nampula, Mozambique between 2011 and 2018: findings from two cross-sectional surveys

“…(8,9) In addition to measuring these indicators in the population as a whole, it is important to understand how such measures differ between different sub-groups, men and women, rich and poor, urban and rural and those with and without disabilities (8,10,11). Evidence exists to suggest that health needs and access to health services varies between different population sub-groups but often to different extents in different locations (10,12,13).…”

Geo-mapping of government healthcare facilities providing diagnostic laboratory services in Delhi, India: a pilot study

“…Another study 35 in Vellore (Tamil Nadu, India), while characterising the CTX-M strain of E. coli using PCR were able to identify clustering among patients, healthy individuals and contaminated environmental points using spatial presentation of GIS mapping. While geospatial data analysis for healthcare in India was used in limited studies, many studies have assessed the effectiveness and variations in healthcare service delivery 36 40 and studied disease trends or outcomes 3641 47 and the impact of intervention systems 3848 52 for improved healthcare delivery by geomapping. GIS has been used in 17 studies 3953 68 for the evaluation of health-related aspects or health facilities in India.…”

Applying intersectionality in vision impairment research: A scoping review

“…Importantly, in the vision impairment literature, differences in social identities have been linked to the prevalence of vision impairment. For example, previous studies have shown that females have a higher prevalence of vision impairment (i.e., 55% of people with vision impairment are females), while socio-economic status, ethnicity and race, and geographical inequalities were associated with differences in the prevalence of vision impairment (Lyu & Kim, 2018; Mohanty et al, 2019; Mullings & Schulz, 2006; Rius Ulldemolins et al, 2019; Shickle & Farragher, 2015). In support of this, Liew (2019) argued that an intersectional perspective adds value in vision impairment research, where he examined the impact of race/ethnicity and sex differences in transitioning across different visual-functioning states among older adults with vision impairment.…”

Changes in prevalence and causes of visual impairment and cataract surgical coverage in Nampula, Mozambique between 2011 and 2018: findings from two cross-sectional surveys

“…(8,9) In addition to measuring these indicators in the population as a whole, it is important to understand how such measures differ between different sub-groups, men and women, rich and poor, urban and rural and those with and without disabilities (8,10,11). Evidence exists to suggest that health needs and access to health services varies between different population sub-groups but often to different extents in different locations (10,12,13).…”

Geo-mapping of government healthcare facilities providing diagnostic laboratory services in Delhi, India: a pilot study

“…Another study 35 in Vellore (Tamil Nadu, India), while characterising the CTX-M strain of E. coli using PCR were able to identify clustering among patients, healthy individuals and contaminated environmental points using spatial presentation of GIS mapping. While geospatial data analysis for healthcare in India was used in limited studies, many studies have assessed the effectiveness and variations in healthcare service delivery 36 40 and studied disease trends or outcomes 3641 47 and the impact of intervention systems 3848 52 for improved healthcare delivery by geomapping. GIS has been used in 17 studies 3953 68 for the evaluation of health-related aspects or health facilities in India.…”

Applying intersectionality in vision impairment research: A scoping review

“…Importantly, in the vision impairment literature, differences in social identities have been linked to the prevalence of vision impairment. For example, previous studies have shown that females have a higher prevalence of vision impairment (i.e., 55% of people with vision impairment are females), while socio-economic status, ethnicity and race, and geographical inequalities were associated with differences in the prevalence of vision impairment (Lyu & Kim, 2018; Mohanty et al, 2019; Mullings & Schulz, 2006; Rius Ulldemolins et al, 2019; Shickle & Farragher, 2015). In support of this, Liew (2019) argued that an intersectional perspective adds value in vision impairment research, where he examined the impact of race/ethnicity and sex differences in transitioning across different visual-functioning states among older adults with vision impairment.…”

Changes in prevalence and causes of visual impairment and cataract surgical coverage in Nampula, Mozambique between 2011 and 2018: findings from two cross-sectional surveys

“…(8,9) In addition to measuring these indicators in the population as a whole, it is important to understand how such measures differ between different sub-groups, men and women, rich and poor, urban and rural and those with and without disabilities (8,10,11). Evidence exists to suggest that health needs and access to health services varies between different population sub-groups but often to different extents in different locations (10,12,13).…”

Geo-mapping of government healthcare facilities providing diagnostic laboratory services in Delhi, India: a pilot study

“…Another study 35 in Vellore (Tamil Nadu, India), while characterising the CTX-M strain of E. coli using PCR were able to identify clustering among patients, healthy individuals and contaminated environmental points using spatial presentation of GIS mapping. While geospatial data analysis for healthcare in India was used in limited studies, many studies have assessed the effectiveness and variations in healthcare service delivery 36 40 and studied disease trends or outcomes 3641 47 and the impact of intervention systems 3848 52 for improved healthcare delivery by geomapping. GIS has been used in 17 studies 3953 68 for the evaluation of health-related aspects or health facilities in India.…”

Applying intersectionality in vision impairment research: A scoping review

“…Importantly, in the vision impairment literature, differences in social identities have been linked to the prevalence of vision impairment. For example, previous studies have shown that females have a higher prevalence of vision impairment (i.e., 55% of people with vision impairment are females), while socio-economic status, ethnicity and race, and geographical inequalities were associated with differences in the prevalence of vision impairment (Lyu & Kim, 2018; Mohanty et al, 2019; Mullings & Schulz, 2006; Rius Ulldemolins et al, 2019; Shickle & Farragher, 2015). In support of this, Liew (2019) argued that an intersectional perspective adds value in vision impairment research, where he examined the impact of race/ethnicity and sex differences in transitioning across different visual-functioning states among older adults with vision impairment.…”