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Frequency and predictors of depression among the elderly population of Karachi

CONTEXT: Depression among the elderly is falsely considered as a normal part of aging and hence remains un-diagnosed in the majority. Elderly people are at a high risk of depression, which may produce a negative impact on their quality of life. Depression is a potentially treatable condition; hence,...

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Autores principales: Ali, Zaheer, Amin, Faridah, Saeed, Rabeeya, Durrani, Noureen, Pasha, Muhammad Saad, Ahmed, Iklhas
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Wolters Kluwer - Medknow 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10041233/
https://www.ncbi.nlm.nih.gov/pubmed/36993035
http://dx.doi.org/10.4103/jfmpc.jfmpc_947_22
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author Ali, Zaheer
Amin, Faridah
Saeed, Rabeeya
Durrani, Noureen
Pasha, Muhammad Saad
Ahmed, Iklhas
author_facet Ali, Zaheer
Amin, Faridah
Saeed, Rabeeya
Durrani, Noureen
Pasha, Muhammad Saad
Ahmed, Iklhas
author_sort Ali, Zaheer
collection PubMed
description CONTEXT: Depression among the elderly is falsely considered as a normal part of aging and hence remains un-diagnosed in the majority. Elderly people are at a high risk of depression, which may produce a negative impact on their quality of life. Depression is a potentially treatable condition; hence, it is worthwhile to explore its burden in order to ensure its timely evaluation and management. AIMS: To determine the frequency and predictors of depression among the elderly population of Karachi. SETTINGS AND DESIGN: The current study was a cross-sectional study, conducted in out-patient clinics of a tertiary care hospital and its out-reach centers located in different areas of Karachi. METHODS AND MATERIAL: Patients aged 60 years and above were enrolled in the study. Demographic profiles and physical health conditions were investigated. Depression was assessed using Geriatric Depression Scale-15. STATISTICAL ANALYSIS: Data were entered in SPSS version 21 for statistical analysis. RESULTS: A total of 232 participants were enrolled into the study with a median age of 65.8 [inter-quartile range = 61–69] years. Out of 232 participants, 186 (80.2%) were found to be depressed. In the multi-variable model, employment status, financial issues, and peer groups were left as independent predictors of depression. CONCLUSION: The current study found a significant burden of depression among elderly people in Karachi. Employment status, financial problems, and relationship with peers have been identified as risk factors of depression. There might be over-reporting of depression as the data collection was conducted during the coronavirus disease 2019 first wave. Hence, further community-based research is warranted to confirm the findings.
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spelling pubmed-100412332023-03-28 Frequency and predictors of depression among the elderly population of Karachi Ali, Zaheer Amin, Faridah Saeed, Rabeeya Durrani, Noureen Pasha, Muhammad Saad Ahmed, Iklhas J Family Med Prim Care Original Article CONTEXT: Depression among the elderly is falsely considered as a normal part of aging and hence remains un-diagnosed in the majority. Elderly people are at a high risk of depression, which may produce a negative impact on their quality of life. Depression is a potentially treatable condition; hence, it is worthwhile to explore its burden in order to ensure its timely evaluation and management. AIMS: To determine the frequency and predictors of depression among the elderly population of Karachi. SETTINGS AND DESIGN: The current study was a cross-sectional study, conducted in out-patient clinics of a tertiary care hospital and its out-reach centers located in different areas of Karachi. METHODS AND MATERIAL: Patients aged 60 years and above were enrolled in the study. Demographic profiles and physical health conditions were investigated. Depression was assessed using Geriatric Depression Scale-15. STATISTICAL ANALYSIS: Data were entered in SPSS version 21 for statistical analysis. RESULTS: A total of 232 participants were enrolled into the study with a median age of 65.8 [inter-quartile range = 61–69] years. Out of 232 participants, 186 (80.2%) were found to be depressed. In the multi-variable model, employment status, financial issues, and peer groups were left as independent predictors of depression. CONCLUSION: The current study found a significant burden of depression among elderly people in Karachi. Employment status, financial problems, and relationship with peers have been identified as risk factors of depression. There might be over-reporting of depression as the data collection was conducted during the coronavirus disease 2019 first wave. Hence, further community-based research is warranted to confirm the findings. Wolters Kluwer - Medknow 2022-11 2022-12-16 /pmc/articles/PMC10041233/ /pubmed/36993035 http://dx.doi.org/10.4103/jfmpc.jfmpc_947_22 Text en Copyright: © 2022 Journal of Family Medicine and Primary Care https://creativecommons.org/licenses/by-nc-sa/4.0/This is an open access journal, and articles are distributed under the terms of the Creative Commons Attribution-NonCommercial-ShareAlike 4.0 License, which allows others to remix, tweak, and build upon the work non-commercially, as long as appropriate credit is given and the new creations are licensed under the identical terms.
spellingShingle Original Article
Ali, Zaheer
Amin, Faridah
Saeed, Rabeeya
Durrani, Noureen
Pasha, Muhammad Saad
Ahmed, Iklhas
Frequency and predictors of depression among the elderly population of Karachi
title Frequency and predictors of depression among the elderly population of Karachi
title_full Frequency and predictors of depression among the elderly population of Karachi
title_fullStr Frequency and predictors of depression among the elderly population of Karachi
title_full_unstemmed Frequency and predictors of depression among the elderly population of Karachi
title_short Frequency and predictors of depression among the elderly population of Karachi
title_sort frequency and predictors of depression among the elderly population of karachi
topic Original Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10041233/
https://www.ncbi.nlm.nih.gov/pubmed/36993035
http://dx.doi.org/10.4103/jfmpc.jfmpc_947_22
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