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Use of Data to Understand the Social Determinants of Depression in Two Middle‐Income Countries: the 3‐D Commission
Depression accounts for a large share of the global disease burden, with an estimated 264 million people globally suffering from depression. Despite being one of the most common kinds of mental health (MH) disorders, much about depression remains unknown. There are limited data about depression, in...
Autores principales: | , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer US
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8373292/ https://www.ncbi.nlm.nih.gov/pubmed/34409557 http://dx.doi.org/10.1007/s11524-021-00559-6 |
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author | Thapa, Bishnu Torres, Irene Koya, Shaffi Fazaludeen Robbins, Grace Abdalla, Salma M. Arah, Onyebuchi A. Weeks, William B. Zhang, Luxia Asma, Samira Morales, Jeanette Vega Galea, Sandro Rhee, Kyu Larson, Heidi J. |
author_facet | Thapa, Bishnu Torres, Irene Koya, Shaffi Fazaludeen Robbins, Grace Abdalla, Salma M. Arah, Onyebuchi A. Weeks, William B. Zhang, Luxia Asma, Samira Morales, Jeanette Vega Galea, Sandro Rhee, Kyu Larson, Heidi J. |
author_sort | Thapa, Bishnu |
collection | PubMed |
description | Depression accounts for a large share of the global disease burden, with an estimated 264 million people globally suffering from depression. Despite being one of the most common kinds of mental health (MH) disorders, much about depression remains unknown. There are limited data about depression, in terms of its occurrence, distribution, and wider social determinants. This work examined the use of novel data sources for assessing the scope and social determinants of depression, with a view to informing the reduction of the global burden of depression. This study focused on new and traditional sources of data on depression and its social determinants in two middle-income countries (LMICs), namely, Brazil and India. We identified data sources using a combination of a targeted PubMed search, Google search, expert consultations, and snowball sampling of the relevant literature published between October 2010 and September 2020. Our search focused on data sources on the following HEALTHY subset of determinants: healthcare (H), education (E), access to healthy choices (A), labor/employment (L), transportation (T), housing (H), and income (Y). Despite the emergence of a variety of data sources, their use in the study of depression and its HEALTHY determinants in India and Brazil are still limited. Survey-based data are still the most widely used source. In instances where new data sources are used, the most commonly used data sources include social media (twitter data in particular), geographic information systems/global positioning systems (GIS/GPS), mobile phone, and satellite imagery. Often, the new data sources are used in conjunction with traditional sources of data. In Brazil, the limited use of new data sources to study depression and its HEALTHY determinants may be linked to (a) the government’s outsized role in coordinating healthcare delivery and controlling the data system, thus limiting innovation that may be expected from the private sector; (b) the government routinely collecting data on depression and other MH disorders (and therefore, does not see the need for other data sources); and (c) insufficient prioritization of MH as a whole. In India, the limited use of new data sources to study depression and its HEALTHY determinants could be a function of (a) the lack of appropriate regulation and incentives to encourage data sharing by and within the private sector, (b) absence of purposeful data collection at subnational levels, and (c) inadequate prioritization of MH. There is a continuing gap in the collection and analysis of data on depression, possibly reflecting the limited priority accorded to mental health as a whole. The relatively limited use of data to inform our understanding of the HEALTHY determinants of depression suggests a substantial need for support of independent research using new data sources. Finally, there is a need to revisit the universal health coverage (UHC) frameworks, as these frameworks currently do not include depression and other mental health-related indicators so as to enable tracking of progress (or lack thereof) on such indicators. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s11524-021-00559-6. |
format | Online Article Text |
id | pubmed-8373292 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Springer US |
record_format | MEDLINE/PubMed |
spelling | pubmed-83732922021-08-19 Use of Data to Understand the Social Determinants of Depression in Two Middle‐Income Countries: the 3‐D Commission Thapa, Bishnu Torres, Irene Koya, Shaffi Fazaludeen Robbins, Grace Abdalla, Salma M. Arah, Onyebuchi A. Weeks, William B. Zhang, Luxia Asma, Samira Morales, Jeanette Vega Galea, Sandro Rhee, Kyu Larson, Heidi J. J Urban Health Article Depression accounts for a large share of the global disease burden, with an estimated 264 million people globally suffering from depression. Despite being one of the most common kinds of mental health (MH) disorders, much about depression remains unknown. There are limited data about depression, in terms of its occurrence, distribution, and wider social determinants. This work examined the use of novel data sources for assessing the scope and social determinants of depression, with a view to informing the reduction of the global burden of depression. This study focused on new and traditional sources of data on depression and its social determinants in two middle-income countries (LMICs), namely, Brazil and India. We identified data sources using a combination of a targeted PubMed search, Google search, expert consultations, and snowball sampling of the relevant literature published between October 2010 and September 2020. Our search focused on data sources on the following HEALTHY subset of determinants: healthcare (H), education (E), access to healthy choices (A), labor/employment (L), transportation (T), housing (H), and income (Y). Despite the emergence of a variety of data sources, their use in the study of depression and its HEALTHY determinants in India and Brazil are still limited. Survey-based data are still the most widely used source. In instances where new data sources are used, the most commonly used data sources include social media (twitter data in particular), geographic information systems/global positioning systems (GIS/GPS), mobile phone, and satellite imagery. Often, the new data sources are used in conjunction with traditional sources of data. In Brazil, the limited use of new data sources to study depression and its HEALTHY determinants may be linked to (a) the government’s outsized role in coordinating healthcare delivery and controlling the data system, thus limiting innovation that may be expected from the private sector; (b) the government routinely collecting data on depression and other MH disorders (and therefore, does not see the need for other data sources); and (c) insufficient prioritization of MH as a whole. In India, the limited use of new data sources to study depression and its HEALTHY determinants could be a function of (a) the lack of appropriate regulation and incentives to encourage data sharing by and within the private sector, (b) absence of purposeful data collection at subnational levels, and (c) inadequate prioritization of MH. There is a continuing gap in the collection and analysis of data on depression, possibly reflecting the limited priority accorded to mental health as a whole. The relatively limited use of data to inform our understanding of the HEALTHY determinants of depression suggests a substantial need for support of independent research using new data sources. Finally, there is a need to revisit the universal health coverage (UHC) frameworks, as these frameworks currently do not include depression and other mental health-related indicators so as to enable tracking of progress (or lack thereof) on such indicators. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s11524-021-00559-6. Springer US 2021-08-18 2021-08 /pmc/articles/PMC8373292/ /pubmed/34409557 http://dx.doi.org/10.1007/s11524-021-00559-6 Text en © The New York Academy of Medicine 2021 |
spellingShingle | Article Thapa, Bishnu Torres, Irene Koya, Shaffi Fazaludeen Robbins, Grace Abdalla, Salma M. Arah, Onyebuchi A. Weeks, William B. Zhang, Luxia Asma, Samira Morales, Jeanette Vega Galea, Sandro Rhee, Kyu Larson, Heidi J. Use of Data to Understand the Social Determinants of Depression in Two Middle‐Income Countries: the 3‐D Commission |
title | Use of Data to Understand the Social Determinants of Depression in Two Middle‐Income Countries: the 3‐D Commission |
title_full | Use of Data to Understand the Social Determinants of Depression in Two Middle‐Income Countries: the 3‐D Commission |
title_fullStr | Use of Data to Understand the Social Determinants of Depression in Two Middle‐Income Countries: the 3‐D Commission |
title_full_unstemmed | Use of Data to Understand the Social Determinants of Depression in Two Middle‐Income Countries: the 3‐D Commission |
title_short | Use of Data to Understand the Social Determinants of Depression in Two Middle‐Income Countries: the 3‐D Commission |
title_sort | use of data to understand the social determinants of depression in two middle‐income countries: the 3‐d commission |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8373292/ https://www.ncbi.nlm.nih.gov/pubmed/34409557 http://dx.doi.org/10.1007/s11524-021-00559-6 |
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