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Demographic and environmental factors associated with disability in India, Laos, and Tajikistan: a population-based cross-sectional study
BACKGROUND: The 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....
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8962048/ https://www.ncbi.nlm.nih.gov/pubmed/35351052 http://dx.doi.org/10.1186/s12889-022-12846-1 |
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author | Chen, Michael Zhu Lee, Lindsay Fellinghauer, Carolina Cieza, Alarcos Chatterji, Somnath |
author_facet | Chen, Michael Zhu Lee, Lindsay Fellinghauer, Carolina Cieza, Alarcos Chatterji, Somnath |
author_sort | Chen, Michael Zhu |
collection | PubMed |
description | BACKGROUND: The 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. METHODS: Approximately 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. RESULTS: Capacity 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. CONCLUSION: While 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. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12889-022-12846-1. |
format | Online Article Text |
id | pubmed-8962048 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-89620482022-03-30 Demographic and environmental factors associated with disability in India, Laos, and Tajikistan: a population-based cross-sectional study Chen, Michael Zhu Lee, Lindsay Fellinghauer, Carolina Cieza, Alarcos Chatterji, Somnath BMC Public Health Research Article BACKGROUND: The 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. METHODS: Approximately 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. RESULTS: Capacity 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. CONCLUSION: While 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. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12889-022-12846-1. BioMed Central 2022-03-29 /pmc/articles/PMC8962048/ /pubmed/35351052 http://dx.doi.org/10.1186/s12889-022-12846-1 Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data. |
spellingShingle | Research Article Chen, Michael Zhu Lee, Lindsay Fellinghauer, Carolina Cieza, Alarcos Chatterji, Somnath Demographic and environmental factors associated with disability in India, Laos, and Tajikistan: a population-based cross-sectional study |
title | Demographic and environmental factors associated with disability in India, Laos, and Tajikistan: a population-based cross-sectional study |
title_full | Demographic and environmental factors associated with disability in India, Laos, and Tajikistan: a population-based cross-sectional study |
title_fullStr | Demographic and environmental factors associated with disability in India, Laos, and Tajikistan: a population-based cross-sectional study |
title_full_unstemmed | Demographic and environmental factors associated with disability in India, Laos, and Tajikistan: a population-based cross-sectional study |
title_short | Demographic and environmental factors associated with disability in India, Laos, and Tajikistan: a population-based cross-sectional study |
title_sort | demographic and environmental factors associated with disability in india, laos, and tajikistan: a population-based cross-sectional study |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8962048/ https://www.ncbi.nlm.nih.gov/pubmed/35351052 http://dx.doi.org/10.1186/s12889-022-12846-1 |
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