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 Table of Contents  
ORIGINAL ARTICLE
Year : 2014  |  Volume : 3  |  Issue : 2  |  Page : 105-109

Prevalence and factors influencing depression among elderly living in the urban poor locality of Bengaluru city


1 Department of Community Medicine, KIMS, Mandya, Bengaluru, Karnataka, India
2 Department of Community Medicine, MIMS, Mandya, Bengaluru, Karnataka, India
3 Department of Psychiatry, KIMS, Mandya, Bengaluru, Karnataka, India

Date of Web Publication19-May-2014

Correspondence Address:
R Jahnavi
Department of Community Medicine, Mandya Institute of Medical Sciences, Mandya, Karnataka
India
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Source of Support: None, Conflict of Interest: None


DOI: 10.4103/2278-344X.132695

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  Abstract 

Background: The Indian elderly population is currently the second largest in the world. Mental disorders have got high prevalence and low priority among elderly in most of the countries around the world, of which depression being the most common treatable condition. In India, there is scarcity of research on prevalence and factors influencing depression among elderly from urban poor locality by adopting a geriatric depression scale-15 (GDS-15) scale. Objectives: (1) To find out the prevalence of geriatric depression, (2) to find out the factors associated with depression. Methodology: A cross-sectional study was conducted at urban poor locality of Bengaluru on 100 elderly people by applying GDS-15 Kannada version to assess the prevalence of depression and information regarding the sociodemographic characteristics, financial status, and comorbid conditions were collected. Results: The prevalence of depression assessed by using GDS-15 Kannada version was found to be 36%. Depression was more among 12 (70.6%) from medium standard of living index (SLI) group compared to 24 (28.9%) from high SLI group, which was shown to be statistically significant. Among the elderly with depression, 31 (86.1%) had some medical comorbidities when compared with 33 (51.6%) elderly without depression, which was found to be statistically significant. Conclusions: The current research has shown prevalence of depression according to GDS-15 (Kannada version) as 36% and influenced by SLI, hold on assets, insomnia and comorbidities, which needs to be confirmed by undertaking further studies.

Keywords: Comorbidities, depression among elderly, prevalence, urban poor locality


How to cite this article:
Sanjay T V, Jahnavi R, Gangaboraiah B, Lakshmi P, Jayanthi S. Prevalence and factors influencing depression among elderly living in the urban poor locality of Bengaluru city. Int J Health Allied Sci 2014;3:105-9

How to cite this URL:
Sanjay T V, Jahnavi R, Gangaboraiah B, Lakshmi P, Jayanthi S. Prevalence and factors influencing depression among elderly living in the urban poor locality of Bengaluru city. Int J Health Allied Sci [serial online] 2014 [cited 2019 Aug 17];3:105-9. Available from: http://www.ijhas.in/text.asp?2014/3/2/105/132695


  Introduction Top


Ageing is a natural phenomenon and has its own dynamics, which is beyond human control. The elderly population is growing faster than the total population throughout the world. The proportion of the elderly population in India rose from 5.6% in 1961 to 7.5% in 2001 and it will rise to 9% by 2016. [1] The Indian elderly population is currently the second largest in the world. [2]

Mental disorders has got high prevalence and low priority in most of the countries around the world, of which depression among the elderly population being the most common treatable medical condition and is the most frequent cause of emotional distress. In India, community-based studies on mental disorder have revealed that the prevalence of depression varies between 13% and 46% among the elderly population and assuming epidemic form. [3]

Depression among the elderly population further complicates the existing morbidity conditions such as diabetes, hypertension, and cerebrovascular accidents. It decreases the quality-of-life, functional ability, increases the mortality, and health care utilization. [4] Majority of depressive disorders remains undiagnosed and untreated because of a wrong belief that it is a part of ageing and a social stigma.

The geriatric depression scale (GDS)-15 is designed specifically to screen depression among elderly. It can be used as a valid public health instrument, which can be easily acceptable for detecting and managing depression in nonspecialized settings.

In India, there is scarcity of research on prevalence and factors influencing depression among elderly from urban poor locality by adopting a GDS-15 scale, which has been linguistically validated in Indian language. In this regard, the present study was undertaken.


  Methodology Top


This cross-sectional study was conducted in Parvathipura, urban poor locality of Bengaluru after getting approval from Institutional Ethical Committee. The sample size was estimated using the formula n = 4 pq/L 2 . The prevalence of depression, "p" among elderly persons was taken as 46%. [5] With precision of 10%, using the above mentioned statistical formula which considers 95% confidence limits, the sample size was estimated to be 99.36-100.

House to house survey was conducted to enumerate total number of elderly. The elderly were residing in the area were 347, among them 151 were males and 196 were females. All the males and females were line listed separately according to the alphabetic order of their name. Among them, 100 elderly (44 males and 56 females were selected based on probability proportion to size) were randomly selected using a random number table.

The original validated English version given by Sheikh and Yesavage. [6] The construct and content validation of all the items in the questionnaire were performed by subject experts in both languages (Kannada and English). The final Kannada version was having excellent internal consistency.

Elderly were interviewed separately in their residence and GDS 15 Kannada version was applied to assess the prevalence of depression and information regarding the sociodemographic characteristics, financial status, and comorbid conditions were collected using a pretested structured proforma and data were analyzed using Open -Epi version 2.3.1 Copyright (c) 2003, 2008 Andrew G. Dean and Kevin M. Sullivan, Atlanta, GA, USA.


  Results Top


The prevalence of depression assessed by using Kannada version of GDS-15 among 100 elderly was found to be 36 (36%). Among those who were depressed, 21 (58.3%) were in moderate and 15 (41.7%) were in severe depression.

When sociodemographic characteristics and depression was assessed, 13 (32.9%) elderly aged more than 70 years and 23 (41.1%) of the females were having depression. Regarding education status, 10 (41.7%) illiterates were depressed compared with 26 (34.2%) literates. Depression was more among 12 (70.6%) from medium standard of living index (SLI) group compared to 24 (28.9%) from high SLI group, which was shown to be statistically significant (P < 0.001). The depression was more common among 15 (50%) elderly from joint/three generation family compared to 21 (30%) from the nuclear family [Table 1].
Table 1: Prevalence of depression according to sociodemographic characteristics


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When the financial status and depression was studied, it was observed that the depression was found among 26 (41.3%) financially dependent elderly compared to 10 (27%) who were financially independent. Among the elderly receiving financial assistance, 13 (46.4%) had depression compared to 13 (18.1%) who were not receiving assistance, which was found to be statistically significant.

Regarding the hold on the asset, 21 (49.1%) elderly who do not have hold on asset were more depressed compared to 9 (20%) having hold on the asset, which was found to be statistically significant [Table 2].
Table 2: Prevalence of depression according to financial status


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In the current study, association of anorexia and insomnia with depression was analyzed, Insomnia was more among 31 (86.1%) elderly with depression when compared to 5 (13.9%) elderly without depression, which was found to be statistically significant. The odd of having depression is 15.8 times more among elderly who have insomnia when compared to those who do not have insomnia.

Among the elderly suffering from depression 9 (25.0%) had anorexia compared to 27 (75%) without anorexia, which was found to be statistically significant. The odds of not suffering from anorexia are 3.2 times more among elderly who have depression when compared to those who do not have depression [Table 3].
Table 3: Prevalence of depression according to insomnia and anorexia


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When the association between medical comorbidities and depression was analyzed, it was observed that among the elderly with depression, 31 (86.1%) had medical comorbidities in them when compared to 33 (51.6%) elderly without depression. There was a significant association between comorbidities and depression. The odds of having depression was 5.8 times more among elderly who have comorbidities when compared to those who do not have comorbidities [Table 4]. Among the elderly with depression, majority had hypertension (74.2%) followed by diabetes mellitus (35.5%).
Table 4: Distribution of depression status according to comorbidities


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  Discussion Top


The prevalence of depression assessed by using Kannada version of GDS-15 was found to be 36%.

In a study conducted by Nair et al. in Dharwad observed the prevalence of 32.4% [7] and a study conducted by Vishal et al. in the urban poor locality of Surat observed the prevalence of 39%. [8] When compared with these studies, the present study documented moderately high prevalence of depression.

The World Health Organization estimated overall prevalence rate of depressive disorders among the elderly varies between 10% and 20%, depending on the cultural situations. [9]

All these evidence strengthen the fact that depression in elderly is emerging as an important public health concern due to age-related decline in the physical and physiological functioning, urbanization, changing family structure leading to poor quality-of-life, increased disability, and morbidity.

In this study, the medium SLI group had more number of elderly with depression and all the household in the study area were belonging to either medium or high SLI. This could be due to the fact that the study population may be in the phase of economic transition. Many studies have observed that depression was associated with poor socioeconomic status. [5],[10] These studies have taken income into account, the major drawback of this information is majority of the elderly are economically dependent and unaware of gross family income, whereas SLI is the asset-based indicator, which takes into account possession of durables and housing facilities and extensive review literature at that point in time revealed paucity of research involving SLI in depression.

The depression was significantly associated with elderly who were on financial assistance such as old age and retirement pension. In a study conducted by Gupta et al. shown that depression was less pronounced in those receiving pension. [11] This difference could be due to the fact that the majority of elderly in the current study were on old age pension given to destitute.

The study found that depression was significantly associated with elderly not holding any assets. The hold on assets in their name found to be a protective factor against depression because assets will provide financial security and sense of mental well-being.

In this study, there was a significant association between insomnia and depression. Many studies observed that insomnia was consistently associated with depression. [7],[12],[13] The diagnostic and statistical manual (DSM-VI) criteria states insomnia as a fourth symptom for the diagnosis of depression. [14] In depression, sleep architecture will be altered with reduced total sleep time, longer latency and frequent awakening. [15]

Interestingly, study found, majority of the depressed elderly were not having anorexia, which was statistically significant. Even though, DSM-VI criteria states anorexia as a third symptom for the diagnosis of depression. These difference needs to be investigated further.

Significant association was found between comorbidities and depression. The comorbidities were considered as an important risk factor for depression and vice versa. [16],[17] These comorbidities along with depression increases physical disability, poor compliance and increased health care utilization leading to poor quality-of-life and further complicating the treatment of depression. Majority of depressed subjects were suffering from hypertension and diabetes mellitus. This observation was supported by a study conducted elsewhere. [5]

The study included small sample size. This could be regarded as a limitation in reducing generalizability.

This study revealed moderately high prevalence of depression in elderly and associated with medium SLI, financial assistance and not having hold on assets, insomnia and comorbidities. This indicates that depression is becoming a silent killer and assuming an epidemic form and compromising the quality of life of the elderly. These finding should be confirmed by further undertaking multicentric, large representative sample studies in different settings such as hospital out-patients, in-patients, community, and old age home inmates and information should be utilized for policy making and incorporating screening and management of depression for elderly in nonspecialized settings in a cost-effective manner.


  Conclusions Top


The current research has shown prevalence of depression according to GDS-15 (Kannada version) as 36% and influenced by standard of living index, hold on assets, insomnia and comorbidities, which needs to be confirmed by undertaking further studies.

 
  References Top

1.Kandpal SD, Kakkar R, Aggarwal P. Mental and social dimensions in geriatric population: Need of the hour. Indian J Community Health 2012;24: 71-2.  Back to cited text no. 1
    
2.The World Health Organization. Mental Health. Available from: http://www.who.org. [Last cited on 2013 Aug 12].  Back to cited text no. 2
    
3.Barua A, Kar N. Screening for depression in elderly Indian population. Indian J Psychiatry 2010;52:150-3.  Back to cited text no. 3
[PUBMED]  Medknow Journal  
4.National Health Care Disparities Report, 2011. Available from: http://www.ahrq.gov/research/findings/nhqrdr/nhdr11/nhdr11.pdf. [Last cited on 2013 Sep 07].  Back to cited text no. 4
    
5.Jain RK, Aras RY. Depression in geriatric population in urban slums of Mumbai. Indian J Public Health 2007;51:112-3.  Back to cited text no. 5
[PUBMED]  Medknow Journal  
6.Sheikh JI, Yesavage JA. Geriatric depression scale (GDS) recent evidence and development of a shorter version. In: Brink TL, editor. Clinical Gerontology: A Guide to Assessment and Intervention. New York: The Haworth Press; 1986. p. 165-73.  Back to cited text no. 6
    
7.Nair SS, Hiremath SG, Ramesh, Pooja, Nair SS. Depression among geriatrics: Prevalence and associated factors. Int J Curr Res Rev 2013;5:110-2.  Back to cited text no. 7
    
8.Vishal J, Bansal RK, Swati P, Bimal T. A study of depression among aged in Surat city. Natl J Community Med 2010;1:47-9.  Back to cited text no. 8
    
9.Arumugam B, Nagalingam S, Nivetha R. Geriatric depression among rural and urban slum community in Chennai: A cross sectional study. J Evol Med Dent Sci 2013;3:795-801.  Back to cited text no. 9
    
10.Pracheth R, Mayur SS, Chowri JV. Geriatric depression scale: A tool to assess depression in elderly. Int J Med Sci Public Health 2013;3:31-5.  Back to cited text no. 10
    
11.Gupta M, Lehl SS, Boparoy NS, Katyal R, Sachdev A. A study of prevalence of depression in elderly with medical disorders. J Indian Acad Geriatr 2010;6:18-23.  Back to cited text no. 11
    
12.Grover S, Dutt A, Avasthi A. An overview of Indian research in depression. Indian J Psychiatry 2010;52:S178-88.  Back to cited text no. 12
    
13.Bharatwaj RS, Vijaya K, Rajaram P. Prevalence of urban geriatric depression: A cross sectional study in Pondicherry. Int J Med Health Sci 2013;2:286-91.  Back to cited text no. 13
    
14.Baldwin R. Depression in Late Life.  United States: Oxford Psychiatry Library; 2009. p. 3-9.  Back to cited text no. 14
    
15.Gupta R, Dahiya S, Bhatia MS. Effect of depression on sleep: Qualitative or quantitative? Indian J Psychiatry 2009;51:117-21.  Back to cited text no. 15
[PUBMED]  Medknow Journal  
16.Kaneko Y, Motohashi Y, Sasaki H, Yamaji M. Prevalence of depressive symptoms and related risk factors for depressive symptoms among elderly persons living in a rural Japanese community: A cross-sectional study. Community Ment Health J 2007;43:583-90.  Back to cited text no. 16
    
17.Wong SY, Mercer SW, Woo J, Leung J. The influence of multi-morbidity and self-reported socio-economic standing on the prevalence of depression in an elderly Hong Kong population. BMC Public Health 2008;8:119.  Back to cited text no. 17
    



 
 
    Tables

  [Table 1], [Table 2], [Table 3], [Table 4]


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