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Socioeconomic and health-related inequalities in major depressive symptoms among older adults: a Wagstaff’s decomposition analysis of data from the LASI baseline survey, 2017–2018
OBJECTIVES: To find out the association between socioeconomic and health status and depression among older adults and explore the contributing factors in the socioeconomic and health-related inequalities in late-life depression. DESIGN: A cross-sectional study was conducted using large representativ...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BMJ Publishing Group
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9161106/ https://www.ncbi.nlm.nih.gov/pubmed/35649601 http://dx.doi.org/10.1136/bmjopen-2021-054730 |
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author | Muhammad, T. Skariah, Anjali Elsa Kumar, Manish Srivastava, Shobhit |
author_facet | Muhammad, T. Skariah, Anjali Elsa Kumar, Manish Srivastava, Shobhit |
author_sort | Muhammad, T. |
collection | PubMed |
description | OBJECTIVES: To find out the association between socioeconomic and health status and depression among older adults and explore the contributing factors in the socioeconomic and health-related inequalities in late-life depression. DESIGN: A cross-sectional study was conducted using large representative survey data. SETTING AND PARTICIPANTS: Data for this study were derived from the baseline wave of the Longitudinal Ageing Study in India conducted during 2017–2018. The effective sample size was 30 888 older adults aged 60 years and above. PRIMARY AND SECONDARY OUTCOME MEASURES: The outcome variable in this study was depression among older adults. Descriptive statistics along with bivariate analysis was conducted to report the preliminary results. Multivariable binary logistic regression analysis and Wagstaff’s decomposition were used to fulfil the objectives of the study. RESULTS: There was a significant difference for the prevalence of depression (4.3%; p<0.05) among older adults from poor (11.2%) and non-poor categories (6.8%). The value of the Concentration Index was −0.179 which also confirms that the major depression was more concentrated among poor older adults. About 38.4% of the socioeconomic and health-related inequality was explained by the wealth quintile for major depression among older adults. Moreover, about 26.6% of the inequality in major depression was explained by psychological distress. Self-rated health (SRH), difficulty in activities of daily living (ADL) and instrumental ADL (IADL) contributed 8.7%, 3.3% and 4.8% to the inequality, respectively. Additionally, region explained about 23.1% of inequality followed by life satisfaction (11.2) and working status (9.8%) for major depression among older adults. CONCLUSIONS: Findings revealed large socioeconomic and health-related inequalities in depression in older adults which were especially pronounced by poor household economy, widowhood, poor SRH, ADL and IADL difficulty, and psychological distress. In designing prevention programmes, detection and management of older adults with depression should be a high priority, especially for those who are more vulnerable. |
format | Online Article Text |
id | pubmed-9161106 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | BMJ Publishing Group |
record_format | MEDLINE/PubMed |
spelling | pubmed-91611062022-06-16 Socioeconomic and health-related inequalities in major depressive symptoms among older adults: a Wagstaff’s decomposition analysis of data from the LASI baseline survey, 2017–2018 Muhammad, T. Skariah, Anjali Elsa Kumar, Manish Srivastava, Shobhit BMJ Open Mental Health OBJECTIVES: To find out the association between socioeconomic and health status and depression among older adults and explore the contributing factors in the socioeconomic and health-related inequalities in late-life depression. DESIGN: A cross-sectional study was conducted using large representative survey data. SETTING AND PARTICIPANTS: Data for this study were derived from the baseline wave of the Longitudinal Ageing Study in India conducted during 2017–2018. The effective sample size was 30 888 older adults aged 60 years and above. PRIMARY AND SECONDARY OUTCOME MEASURES: The outcome variable in this study was depression among older adults. Descriptive statistics along with bivariate analysis was conducted to report the preliminary results. Multivariable binary logistic regression analysis and Wagstaff’s decomposition were used to fulfil the objectives of the study. RESULTS: There was a significant difference for the prevalence of depression (4.3%; p<0.05) among older adults from poor (11.2%) and non-poor categories (6.8%). The value of the Concentration Index was −0.179 which also confirms that the major depression was more concentrated among poor older adults. About 38.4% of the socioeconomic and health-related inequality was explained by the wealth quintile for major depression among older adults. Moreover, about 26.6% of the inequality in major depression was explained by psychological distress. Self-rated health (SRH), difficulty in activities of daily living (ADL) and instrumental ADL (IADL) contributed 8.7%, 3.3% and 4.8% to the inequality, respectively. Additionally, region explained about 23.1% of inequality followed by life satisfaction (11.2) and working status (9.8%) for major depression among older adults. CONCLUSIONS: Findings revealed large socioeconomic and health-related inequalities in depression in older adults which were especially pronounced by poor household economy, widowhood, poor SRH, ADL and IADL difficulty, and psychological distress. In designing prevention programmes, detection and management of older adults with depression should be a high priority, especially for those who are more vulnerable. BMJ Publishing Group 2022-06-01 /pmc/articles/PMC9161106/ /pubmed/35649601 http://dx.doi.org/10.1136/bmjopen-2021-054730 Text en © Author(s) (or their employer(s)) 2022. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ. https://creativecommons.org/licenses/by-nc/4.0/This is an open access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited, appropriate credit is given, any changes made indicated, and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/ (https://creativecommons.org/licenses/by-nc/4.0/) . |
spellingShingle | Mental Health Muhammad, T. Skariah, Anjali Elsa Kumar, Manish Srivastava, Shobhit Socioeconomic and health-related inequalities in major depressive symptoms among older adults: a Wagstaff’s decomposition analysis of data from the LASI baseline survey, 2017–2018 |
title | Socioeconomic and health-related inequalities in major depressive symptoms among older adults: a Wagstaff’s decomposition analysis of data from the LASI baseline survey, 2017–2018 |
title_full | Socioeconomic and health-related inequalities in major depressive symptoms among older adults: a Wagstaff’s decomposition analysis of data from the LASI baseline survey, 2017–2018 |
title_fullStr | Socioeconomic and health-related inequalities in major depressive symptoms among older adults: a Wagstaff’s decomposition analysis of data from the LASI baseline survey, 2017–2018 |
title_full_unstemmed | Socioeconomic and health-related inequalities in major depressive symptoms among older adults: a Wagstaff’s decomposition analysis of data from the LASI baseline survey, 2017–2018 |
title_short | Socioeconomic and health-related inequalities in major depressive symptoms among older adults: a Wagstaff’s decomposition analysis of data from the LASI baseline survey, 2017–2018 |
title_sort | socioeconomic and health-related inequalities in major depressive symptoms among older adults: a wagstaff’s decomposition analysis of data from the lasi baseline survey, 2017–2018 |
topic | Mental Health |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9161106/ https://www.ncbi.nlm.nih.gov/pubmed/35649601 http://dx.doi.org/10.1136/bmjopen-2021-054730 |
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