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 Table of Contents 
ORIGINAL ARTICLE
Year : 2021  |  Volume : 12  |  Issue : 2  |  Page : 137-143  

A study on prevalence and factors associated with depression among elderly residing in tenements under resettlement scheme, Kancheepuram District, Tamil Nadu


1 Department of Community Medicine, Chettinad Hospital and Research Institute, Chettinad Academy of Research and Education, Udhagamandalam, T, he Nilgiris
2 Assistant Program Manager, National Health Mission, Deputy Directorate of Health Services, Udhagamandalam, T, he Nilgiris
3 Department of Community Medicine, Chettinad Hospital and Research Institute, Chettinad Academy of Research and Education, Kelambakkam, Chengalpattu, 3Department of Community Medicine, Shri Sathya Sai Medical College and Research Institute, Sri Balaji Vidyapeeth - Deemed to be University, Kancheepuram, Tamil Nadu, India

Date of Submission23-Mar-2020
Date of Decision26-Dec-2020
Date of Acceptance30-May-2021
Date of Web Publication27-Jul-2021

Correspondence Address:
Fasna Liaquathali
13/168, Kasimvayal, Gudalur, The Nilgiris-643212, Tamil Nadu
he Nilgiris
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Source of Support: None, Conflict of Interest: None


DOI: 10.4103/jmh.JMH_45_20

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   Abstract 


Background: Mental disorders have got high prevalence and low priority among the elderly in most of the countries worldwide, of which depression being the most common treatable condition. The causes for elderly depression are multifactorial and preventable. Objective: The aim of this study is to estimate the prevalence of depression and to assess the factors associated with depression among the elderly age. Materials and Methods: A cross-sectional study was conducted among participants more than 60 years of age residing in tenements under resettlement scheme in Semmenchery, Kancheepuram district, Tamil Nadu with a sample size of 184. Systematic sampling method was adopted to collect data at participants door step. A predesigned, pretested questionnaire was used to assess the factors associated with depression, and the Geriatric depression scale-30 was used to assess depression. The data were analyzed using SPSS and Chi-square <0.05 was considered significant. Results: The overall prevalence of depression was 35.3%. The factors such as female gender, educational status, occupation, type of family, financial dependency, history of depression, smoking and medical factors such as hypertension, cardiac disease, and chronic kidney disease and life events like conflict in family, unemployment, and financial problem were statistically significant (P < 0.05). Conclusion: Loss of spouse, financial dependency, neglected care, lack of awareness about the disease were found to be barriers in reaching basic mental health care for the elderly. Depression remains one of the main causes of DALY, especially among elders. National Program for Health care of elderly provides doorstep services, so incorporation of depression screening into that can impart the effects of depression on quality of life and DALY.

Keywords: DALY, depression, doorstep health services, elderly, mental health disorders


How to cite this article:
Kumar BM, Raja T K, Liaquathali F, Maruthupandian J, Raja PV. A study on prevalence and factors associated with depression among elderly residing in tenements under resettlement scheme, Kancheepuram District, Tamil Nadu. J Mid-life Health 2021;12:137-43

How to cite this URL:
Kumar BM, Raja T K, Liaquathali F, Maruthupandian J, Raja PV. A study on prevalence and factors associated with depression among elderly residing in tenements under resettlement scheme, Kancheepuram District, Tamil Nadu. J Mid-life Health [serial online] 2021 [cited 2021 Oct 24];12:137-43. Available from: https://www.jmidlifehealth.org/text.asp?2021/12/2/137/322436




   Introduction Top


Government of India adopted “National Policy on Older Persons” in January 1999 which defines “senior citizen” or “elderly” as a person who is of age 60 years or above.[1] There is steady increase in the elderly population from 5.3% in 1951 to 8% in 2011[2] due to epidemiologic transition and it is expected to increase by 12.17% in 2026.[3] With increase in the proportion of elders, they are more vulnerable for dual burden of disease–communicable and noncommunicable diseases.[4] The elderly who are in the unproductive age group are being neglected.[5] As a result, they are more prone for mental disorders, especially depression.

Mental disorders have got high prevalence and low priority among the elderly in most of the countries worldwide, of which depression being the most common treatable condition. The median prevalence of depression among the elderly in India is 21.9%.[6] The cause for depression among the elderly is multifactorial and preventable by addressing the risk factors such as living alone, stressful life events, lack of social support, loss of partner, lower socioeconomic status, and the presence of comorbid medical illness like diabetes, hypertension, cardiac disease, arthritis.[7]

Depression mostly manifests itself as somatic symptoms such as headache, hypertension, gastritis, heaviness among the elderly, most of them approach nonpsychiatric clinics seeking relief for their symptoms.[8] Hence its is equally important to create awareness among the health care workers along with family and community members to prevent the misdiagnosis of depression.

This study aims to explore the prevalence the depression and factors associated with depression among the elderly population.


   Materials and Methods Top


Study setting

The study was a cross-sectional study which was conducted among participants >60 years of age residing in tenements under resettlement scheme[9] in Semmenchery, Kancheepuram district, Tamil Nadu.

Study duration

The study was conducted from June 2018 to November 2018.

Sample size

The sample size was estimated using the formula n = 4pq/L2. The prevalence of depression, “p” among elderly persons was taken as 12%[10] where “L” was permissible error with 95% confidence limits and accounting 10% for nonresponse rate, the sample size was estimated to be 184.

Sampling method

The total population of the study area was obtained from the household register maintained in Urban Health and Training center, Karapakkam. A total of 392 participants above 60 years of age were enumerated. Systematic random sampling was adopted to select every 3rd participant until the required sample size was achieved.

Inclusion criteria

(i) Residents of age ≥60 years of age. (ii) Residents of the tenements who were staying more than 1 year in the study area were included.

Exclusion criteria

(i) The study participants with cognitive and hearing impairment. (ii) The participants who were not present in the house at the time survey even after 3 visits were excluded.

Study tool

The study tool consists of three sections.

Section I: A predesigned, pretested questionnaire was used to assess sociodemographic profiles such as age, gender, educational and occupational status, financial dependency socioeconomic classification (Modified BG Prasad classification 2018).

Section II: The depression was assessed using Geriatric Depression Scale-30 (GDS-30). A score of one or zero was given for each question depending upon the answer for 30 questions and the cut-off for normal was score of 0–9; for mild depression-10–19; and for severe depression-20–30.[11]

Section III: The factors associated with depression was assessed using questionnaire which comprises of the past history of depression, behavioral factors, medical risk factors, life events (past one 1).

Ethical consideration

The study was initiated after obtaining the Institutional Human Ethical committee (IHEC 126-06/18), Chettinad Hospital and Research Institute. The confidentiality of the collected data was maintained throughout the study.

Data collection procedure

The purpose and procedure of the study were explained to the participants in the local language. The data were collected at their doorsteps after obtaining the informed written consent from the participants.

Statistical analysis

he data were analyzed using the Statistical Package for the Social Sciences (SPSS IBM) 21 acquired by IBM corp., Armonk, United States of America. The data were expressed in mean and proportions and Chi-square test was applied (P < 0.05).


   Results Top


Distribution of depression among the study participants

The prevalence of depression was found to be 35.3% out of which 60 (32.6%) were mildly and 5 (2.7%) were severely depressed among the study participants. 35 (19%) had the previous history of depression and 12 (34.2%) had undergone treatment for depression. 3 (1.6%) study participants have family history of depression. 12 (6.5%) had a history of other psychiatric diseases.

[Table 1] shows the association between sociodemographic profile and depression among the study participants. Among the study participants, female sex, low educational status, unemployment, nuclear family, and financial dependency where statistically associated with depression.
Table 1: Association between sociodemographic profile and depression among the study participants

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[Table 2] shows the association between behavioral factors and depression among the study participants. Depression was significantly associated with the participants who sleeps <6 h in a night. Alcohol consumption, smoking, tobacco usage, and low or sedentary activity were statistically associated with depression among the study participants.
Table 2: Association between behavioral risk factors and depression among study participants

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[Table 3] shows the association between medical risk factors and depression among the study participants. There was a statistical association between hypertension and arthritis with depression among the participants. History of diabetes, chronic kidney disease, cardiac disease, visual and hearing impairment, constipation was not statistically associated with the depression.
Table 3: Association between medical risk factors and depression among the study participants

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In [Table 4], conflicts in the family and unemployment of self or children, financial problem or loss, accidental fall in the past 1 year were statistically associated with the depression among the study participants.
Table 4: Association between life events in the past 1 year and depression among the study participants

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   Discussion Top


The median age of the study participants in the present study was 65 ± 3.9 years which was similar to the study conducted by Pracheth et al.[12] 51.6% of participants were female and 48.4% were males which was almost similar to Goyal and Kajal.[13] Majority of the participants belong to the lower and middle class which was concurrent with the reports of Manjubhashini et al.[14] In this study, majority of participants were partially or totally financially dependent which corresponds with the reports of Sanjay et al.[15]

The prevalence of depression among the study participants residing in tenements was 35.3% which was almost similar to the results of Thirthahalli et al. and Buvneshkumar et al.[16],[17] and its less when compared with the prevalence of Arumugam et al.[18] A study conducted by Mohan et al. showed the prevalence of elderly depression 76% which was higher than the present study.[19]

The prevalence of depression was more among females which was found significant in the present study. Similar results were reported by Thirthahalli et al. and Arumugam et al. in their studies.[16],[18] This could be explained because women are the victims of more psychosocial stress compared to males, loss of support and increased life expectancy, and social isolation.[20] There is no significant association with socioeconomic class and depression which was similar to the study of Arumugam et al.[18]

The participants with lower education had a higher prevalence of depression which was significant in the present study, similar result was reported in Manjubhashini et al.[14] The depression was highly associated with the participants who are unemployed and unskilled work, Thirthahalli et al. exposed similar results. Financial dependency and low income to meet their daily needs and health care access could explain the above results.[16]

Sengupta and Benjamin study showed higher prevalence was seen among the participants in the nuclear family when compared to the joint family which was found coherent with the current study. Social isolation, negligence of the children, separation from the family is the major cause of depression in the residents of the nuclear family.[21]

The participants who sleep <6 h in a day were significantly associated with depression and similar results were reported in Sengupta and Benjamin study.[21] The lack of sleep in the night may lead to apathy, irritability, mood volatility leading to depression. The participants who smoke and consume alcohol were significantly associated with depression in the current study, Manjubhashini et al. reported similar results.[14] This could be explained by the longer duration of consumption of alcohol and smoking can lead to inhibition of neuron excitation in the brain leading to low mood, agitations unconcern about life leading to further consumption of alcohol and smoking.[22]

Pracheth et al., significant association with depression and low or sedentary activity which is coherent with the similar study.[12] Evidence suggests low or sedentary behavior not only leads to NCD but also causes negative emotions like depression by inhibiting serotonin pathways.[23]

Comorbidity like Hypertension has two times and chronic arthritis has four times higher risk of developing depression among the study participants which is almost similar to the results of Buvneshkumar et al. and Manjubhashini et al.[14],[17] Unemployment of self or children has three times higher risk of developing depression. This could be explained that considering themselves as financial burden to their families, anxiety of the future, financial and social neglect for basic health assess leading depression in the elderly.[17]

The severe life events that were more common in depressed subjects were the death of a spouse or child, serious physical illness, life-threatening illness to someone close, severe financial loss and enforced change of residence as a result of a demolition program. Major social difficulties lasting 2 or more years were also significantly associated with depression. One of the important factors associated with depression is “life-events” because the impact of life-events can be minimized by various methods including stress management techniques. Moreover, there is no such study from India, where the proportion and the number of elderly in the population are rising rapidly. Hence, it was decided to study the life events before the onset of depression in the elderly.[24]


   Conclusion Top


The overall prevalence of depression among the elderly in the study was 35.5% in which 32.6% had mild depression and 2.7% had severe depression. Female gender, low educational status, unemployment, nuclear family, tobacco and alcohol consumption, smoking, sedentary activity, conflicts in family, unemployment of self or children, comorbidities like hypertension and arthritis were significantly associated with the depression. Geriatric depression has emerged as public health problem due to epidemiological transition and trend leading toward urbanization and nucleation of families. Considering the high burden of the disease, more prioritization should be given for screening of depression at their doorsteps for early detection and treatment through the National program for health care of the elderly and creating awareness among their family members to help the needed senescence.

Financial support and sponsorship

Nil.

Conflicts of interest

There are no conflicts of interest.



 
   References Top

1.
Socialjustice.nic.in; 2018. Available from: http://socialjustice.nic.in/writereaddata/UploadFile/National%20Policy%20for%20Older%20Persons%20 Year%. [Last accessed on 2018 Mar 14].  Back to cited text no. 1
    
2.
Office of the Registrar General. Sample Registration System Population composition. New Delhi: Office of the Registrar General; 2010. Available from: http://www.censusindia.gov.in/vital_statistics/srs/Chap_2_-_2010.pdf. [Last accessed on 2018 Dec 03].  Back to cited text no. 2
    
3.
Central Statistics Office. Situation Analysis of the Elderly in India. New Delhi: Central Statistics Office; 2011. Available from: http://mospi.nic.in/mospi_new/upload/elderly_in_india.pdf. [Last accessed on 2018 Dec 03].  Back to cited text no. 3
    
4.
World Health Organization. Global Forum on Urbanization and Health. Japan: WHO; 2010. Available from: http://www.gfuh.org/docs/WHO_UrbanForumReport_web.pdf9. [Last accessed on 2018 Dec 03].  Back to cited text no. 4
    
5.
Kamble SV, Dhumale GB, Goyal RC, Phalke DB, Ghodke YD. Depression among elderly persons in a primary health centre area in Ahmednagar, Maharashtra. Indian J Public Health 2009;53:253-5.  Back to cited text no. 5
[PUBMED]  [Full text]  
6.
Depression in India Lets Talk; 2016. Available from: http://www.searo.who.int/india/depression_in_india.pdf. [Last accessed on 2018 Dec 03].  Back to cited text no. 6
    
7.
Rangaswamy SM. World Health Report. Mental Health: New Understanding New Hope. Geneva, Switzerland: World Health Organisation; 2001.  Back to cited text no. 7
    
8.
Dowrick C, Katona C, Peveler R, Lloyd H. Somatic symptoms and depression: Diagnostic confusion and clinical neglect. Br J Gen Pract 2005;55:829-30.  Back to cited text no. 8
    
9.
Resettlement and Rehabilitation Scheme (R&R Scheme) – TAMILNADU SLUM CLEARANCE BOARD; 2018. Available from: http://www.tnscb.org/resettlement-and-rehabilitation-scheme-rr-scheme/. [Last accessed on 2018 Jul 04].  Back to cited text no. 9
    
10.
Rajkumar AP, Thangadurai P, Senthilkumar P, Gayathri K, Prince M, Jacob KS. Nature, prevalence and factors associated with depression among the elderly in a rural south Indian community. Int Psychogeriatr 2009;21:372-8.  Back to cited text no. 10
    
11.
Yesavage JA, Brink TL, Rose TL, Lum O, Huang V, Adey M, et al. Development and validation of a geriatric depression screening scale: A preliminary report. J Psychiatr Res 1982;17:37-49.  Back to cited text no. 11
    
12.
Pracheth R, Mayur SS, Chowti JV. Geriatric Depression Scale: A tool to assess depression in elderly. Int J Med Sci Public Health 2013;2:31-5.  Back to cited text no. 12
    
13.
Goyal A, Kajal K. Prevalence of depression in elderly population in the southern part of Punjab. J Family Med Prim Care 2014;3:359-61.  Back to cited text no. 13
[PUBMED]  [Full text]  
14.
Manjubhashini S, Krishnababu G, Krishnaveni A. Epidemiological study of depression among population above 60 years in Visakhapatnam, India. Int J Med Sci Public Health 2013;2:695-703.  Back to cited text no. 14
    
15.
Sanjay T, 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;3:105-12.  Back to cited text no. 15
  [Full text]  
16.
Thirthahalli C, Suryanarayana SP, Sukumar GM, Bharath S, Rao GN, Murthy NS. Proportion and factors associated with depressive symptoms among elderly in an urban slum in Bangalore. J Urban Health 2014;91:1065-75.  Back to cited text no. 16
    
17.
Buvneshkumar M, John KR, Logaraj M. A study on prevalence of depression and associated risk factors among elderly in a rural block of Tamil Nadu. Indian J Public Health 2018;62:89-94.  Back to cited text no. 17
[PUBMED]  [Full text]  
18.
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;2:795-802.  Back to cited text no. 18
    
19.
Mohan Y, Jain T, Krishna S, Rajkumar A, Bonigi S. Elderly depression: Unnoticed public health problem in India-a study on prevalence of depression and its associated factors among people above 60 years in a semi urban area in Chennai. Int J Community Med Public Health 2017;4:3468-72.  Back to cited text no. 19
    
20.
Nakulan A, Sumesh TP, Kumar S, Rejani PP, Shaji KS. Prevalence and risk factors for depression among community resident older people in Kerala. Indian J Psychiatry 2015;57:262-6.  Back to cited text no. 20
[PUBMED]  [Full text]  
21.
Sengupta P, Benjamin AI. Prevalence of depression and associated risk factors among the elderly in urban and rural field practice areas of a tertiary care institution in Ludhiana. Indian J Public Health 2015;59:3-8.  Back to cited text no. 21
[PUBMED]  [Full text]  
22.
Jonas JB, Nangia V, Rietschel M, Paul T, Behere P, Panda-Jonas S. Prevalence of depression, suicidal ideation, alcohol intake and nicotine consumption in rural Central India. The Central India Eye and Medical Study. PLoS One 2014;9:e113550.  Back to cited text no. 22
    
23.
McAllister-Williams RH, Ferrier IN, Young AH. Mood and neuropsychological function in depression: The role of corticosteroids and serotonin. Psychol Med 1998;28:573-84.  Back to cited text no. 23
    
24.
Agrawal N, Jhingan HP. Life events and depression in elderly. Indian J Psychiatry 2002;44:34-40.  Back to cited text no. 24
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    Tables

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



 

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