ArticleBMC public health2022
Demographic and environmental factors associated with disability in India, Laos, and Tajikistan: a population-based cross-sectional study.
Article in BMC public health, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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Who cites it
4 citing papers in PubMed.
- Socioeconomic and national disparities in disability distribution among population in five East African countries: insights from the demographic and health surveys.International journal for equity in health · 2026Article
- Monitoring and evaluation of health disparities for people with disability in low- and middle-income countries: a scoping review.Epidemiologic reviews · 2026Article
- Socioeconomic and geographical disparities in disability distribution among Tanzanian population: insights from the 2022 demographic and health survey and malaria indicator survey.BMC public health · 2025Article
- Why Functioning Should Be Used as a Population Health Indicator? A Discussion of a Chilean Population Study.Healthcare (Basel, Switzerland) · 2025Article
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Authors and funding
5 authors.
Funding
Abstract
backgroundThe number of people experiencing functional limitations due to health conditions (capacity) is expected to increase in low and middle-income countries as populations age and rates of non-communicable disease rise. This trend could raise the prevalence and levels of disability worldwide. Understanding the demographic and environmental factors associated with disability can inform the design of policy interventions to make societies more accessible and inclusive for all.
methodsApproximately 2,500-3,000 participants in each of India, Laos, and Tajikistan responded to the Gallup World Poll and the World Health Organization's Brief Model Disability Survey through face-to-face interviews. For each country, random forest regression was performed to explore the associations of demographic and environmental factors with disability while controlling for capacity. Using the variable importance measures generated by the random forest models, linear regression models were built in a stepwise manner for each country to predict disability level based on these contextual factors.
resultsCapacity was strongly associated with disability in all three countries. Most of the variance in disability was explained by minimally adjusted linear models that included only capacity, sex, and age. Inclusion of additional demographic factors and environmental factors explained slightly more of the variance in disability score. Across all three countries, the level of basic infrastructure, public services, and financial stability were moderately associated with disability. Age, sex, employment status, the use of assistive technologies, and other factors had associations with disability that were highly variable across countries.
conclusionWhile capacity was the main determinant of disability, individual demographic and environmental factors were associated with disability in a country-specific manner while controlling for the effects of capacity.
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