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 Table of Contents  
ORIGINAL ARTICLE
Year : 2020  |  Volume : 7  |  Issue : 1  |  Page : 33-37

Comparison of depression among the elderly in a selected semiurban and rural community of Haryana, North India: A cross-sectional survey


Department of Psychiatric Nursing, College of Nursing, Pt. B.D. Sharma University of Health Sciences, Rohtak, Haryana, India

Date of Submission21-Feb-2020
Date of Decision21-Mar-2020
Date of Acceptance10-Apr-2020
Date of Web Publication29-Jun-2020

Correspondence Address:
Mr. Jaison Joseph
College of Nursing, Pt. B.D. Sharma University of Health Sciences, Rohtak - 124 001, Haryana
India
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Source of Support: None, Conflict of Interest: None


DOI: 10.4103/jgmh.jgmh_5_20

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  Abstract 


Background: Depression in the elderly is one of the most common rising mental health problems worldwide. The prevalence of geriatric depression is relatively sparse as per the epidemiological studies conducted in the Indian setting. Aim: The present study compares the depression among the elderly in a selected semiurban and rural community of North India. Materials and Methods: The present study was conducted among 400 elderly in a selected semiurban and rural community setting of North India. The participants were included as per the predetermined criteria using a convenient sampling method. Geriatric depression scale 15 Hindi version (GDS-15) was used for the assessment of depression. Results: The overall prevalence of geriatric depression (GDS-15 score >5) was found to be 10.5% (95% confidence interval [CI]: 7.8–13.8). Of the 400 individuals, the proportion of the elderly who were at risk of developing depression was higher in the rural area (46.19%; 95% CI: 39.5–52.9) as compared to the semiurban area (22.1%; 95% CI: 16.79–28.53). The presence of chronic illness had an independent association with depression in the elderly residing in the rural setup (adjusted OR: 3.584; 95% CI: 1.399–9.178). Conclusion: The study showed a significantly higher burden of depression in rural geriatric population as compared to the semiurban setting. Considering the rapidly increasing population of older aged people in India, epidemiological data regarding the prevalence of depression form the mainstay for proper health planning.

Keywords: Depression, elderly, rural area, semiurban area


How to cite this article:
Kumari S, Joseph J. Comparison of depression among the elderly in a selected semiurban and rural community of Haryana, North India: A cross-sectional survey. J Geriatr Ment Health 2020;7:33-7

How to cite this URL:
Kumari S, Joseph J. Comparison of depression among the elderly in a selected semiurban and rural community of Haryana, North India: A cross-sectional survey. J Geriatr Ment Health [serial online] 2020 [cited 2020 Nov 23];7:33-7. Available from: https://www.jgmh.org/text.asp?2020/7/1/33/288241




  Introduction Top


Depression is a common illness and the burden of depression is on the rise globally. The World Health Organization projects depression as one of the most common mental illnesses with more than 264 million people affected worldwide.[1] The world mental health survey reported that people in low- and middle-income countries often not receive treatment for their illness due to various barriers such as lack of resources, social stigma, and inaccurate assessment.[2] Aging is a universal phenomenon and the experience of aging is largely influenced by various factors such as physical, psychological, social, cultural, and economic factors.[3] The elderly population is highly vulnerable to medical and psychiatric morbidities and the related symptoms often ignored by considering it as a part of the aging process.[4]

Elderly depression is an emerging public health challenge in India.[5] Depression is often undertreated in this age group though they have multiple coexisting medical and psychological problems.[6] Early recognition and initiation of treatment for depression are of at most importance as it significantly reduces the mortality due to suicide and other medical illnesses.[7] Numerous studies have been conducted in India to study the magnitude of depression among the elderly. The Indian Association for Geriatric Mental Health's Multicentric Study on depression reported that somatic and anxiety symptoms were highly prevalent among elderly patients with depression.[8] However, the prevalence of geriatric depression is relatively sparse varying from 8.9% to 62.16% as per the community-based studies and 42.4%–72% as per the clinic-based studies. The available studies also suggest a regional variation in the prevalence rate across India.[9] A recent systematic review identified a wide variation in the estimated prevalence of depression depending on various factors such as screening tools and area of residence.[10] There is limited empirical-based evidence on the depression in the elderly from Haryana.[11],[12]

We attempted to explore the previously unidentified burden of depression in semiurban areas and to compare its significance with the elderly residing in the rural Haryana setting.


  Materials and Methods Top


The present study was conducted among 400 elderly in a selected semiurban and rural community setting of Haryana, North India. The semiurban study participants were recruited from selected ward areas of Kalanaur, a city under Rohtak district administration with population of about 23,000 as per 2011 census.[13] Elderly residing in the selected panchayats of Dobh village in the rural block of Rohtak district, Haryana, were contacted through house-to-house visit. The participants were included as per the predetermined criteria using a convenient sampling method. Apparently, healthy men and women aged 60 years and more residing in a semiurban and rural residential area, having the ability to understand the Hindi language, were included in the study. Those who did not give consent had speech and communication problems were excluded.

The study participants were initially interviewed using a semistructured questionnaire and collected information regarding sociodemographic profile, chronic illness, physical activeness, social activeness, and sleep problems. The presence chronic illness was considered for those with known cases of hypertension, diabetes mellitus, or any illness of more than 6 months' duration. The regular involvement of any occupation or household work and attending to community gatherings were operationally labeled as “physical activeness” and “social activeness,” respectively. The experience of a significant disturbance in the sleep–wake cycle for the last 2 weeks was considered as sleep problems.

Geriatric depression scale 15 Hindi version (GDS-15) was used for the assessment of depression. GDS is one of the most commonly used instruments for screening depression in specialized and nonspecialized settings. The 15-item GDS is a short attractive instrument in terms of brevity with a sensitivity of 92% and a specificity of 81% at a cutoff of 5. A score of 5 or more indicated the presence of depression; scores 9–11 were described as moderate and 12–15 were described as severe depression.[14]

Ethics approval was taken from the Institutional Ethics Committee, Pt. BDS UHS, Rohtak, and written informed consent was taken from the study participants. We compared the characteristics of various categorical data using Pearson's Chi-square test. Variables that showed statistical significance (P < 0.05) in the univariate analysis were considered for multivariate analysis for adjustment. Multiple logistic regression was used to find out an independent association of various factors with depression. The results were expressed in adjusted odds ratios (OR) and 95% confidence intervals (95% CI).


  Results Top


The overall prevalence of geriatric depression (GDS score >5) was found to be 10.5% (95% CI: 7.8–13.8). Of the 400 participants, the proportion of elderly who were at risk of developing depression was higher in the rural area (46.2%) as compared to semiurban area (22.1%). The mean age of study participants was 66.5 years (standard deviation = 6.46). The comparison based on the presence or absence of depression revealed a statistically significant association of depression in the following with sociodemographic variables: female sex, living in a nuclear family and rural setup, having a widowed marital status, the presence of any chronic illness and sleep problems, decreased societal participation, and inactive way of living [P < 0.05; [Table 1].
Table 1: Association of depression with sociodemographic variables

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The severity of the at-risk symptoms of depression in the rural population is as follows: mild (GDS score of 5–8) and moderate-to-severe depression (GDS score of 9–15) in the rural setting were 21.4% and 24.8%, respectively. In the urban population, 17.4% of the elderly reported moderate-to-severe depression and 4.7% reported mild depression. The comparison of the severity of “at-risk symptoms of depression” based on semiurban and rural settings revealed the following findings. Participants with severe at-risk symptoms of depression were having sleep problems, decreased societal participation, and had a physically inactive way of living regardless of their area of residence. The presence of chronic illness and living in a nuclear family setup was more reported in participants with at-risk symptoms of severe depression in the rural setting. The association was statistically significant [Table 2]. After controlling for various factors, the overall model of logistic regression showed that the presence of chronic illness had an independent association with depression in elderly residing in the rural setup (adjusted OR: 3.584; 95% CI: 1.399–9.178). The variables included in the logistic regression analyses are shown in [Table 3].
Table 2: Comparison of the severity of depression as per study setting

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Table 3: Predictors of depression as per logistic regression analysis

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  Discussion Top


We found an overall prevalence of 10.5% depression in a selected geriatric population of Haryana, North India. Previous studies conducted in North India reported a nearly prevalence rate of 9.5% in Himachal Pradesh [15] and Uttar Pradesh [16] and 8.9% in Punjab.[17] However, a community-based study from southern Haryana reported the geriatric prevalence rate as 22%.[12] A recent systematic review analyzed 51 studies conducted from the 16 states of India reported a prevalence of 34.4% depression among Indian elderly population.[10] This wide variation in prevalence could be attributed to sampling strategies, sample sizes, study setting, and instruments used in different studies.

The index study identified a higher prevalence of geriatric depression in the rural (46.19%; 95% CI: 39.5–52.9) than the semiurban area (22.1%; 95% CI: 16.79–28.53). A review on the epidemiology of depression among Indian elderly population also reported a higher prevalence of depression in the rural area (37.8%; 95% CI: 29.9–45.9) as compared to urban areas (32.1%; 95% CI: 26.1–38.5).[10] A previous study reported the prevalence of geriatric depression as 41.1% and 45.8% in urban and rural south Indian community setting, respectively.[18] Furthermore, a recent study from Karnataka reported that the proportion of elderly who were at risk of developing depression was higher in rural area (32.6%) when compared to urban area (30.4%).[19] Our study results revealed a significant higher burden of depression in rural geriatric population (46.1%) and it was moderately high in our sample of semiurban community-dwelling elderly (22.1%).

We used the Hindi version of GDS-15 with a cutoff of 5 to screen geriatric depression and found a prevalence of 46.19% in the rural setting. Previous community-based studies conducted in the rural Indian setting with GDS-15 as a screening instrument reported the prevalence ranging from 31% to 57% in South India [20],[21],[22],[23],[24] to 62.16% in Northern India.[25] Analyses of the severity of depression in the present study revealed that 21.4% of mild depression (GDS score of 5–8) and 24.8% of moderate-to-severe depression (GDS score of 9–15) in the rural study setting. A study conducted in the older adult rural population of South India using GDS-15 reported 22.3% and 20.4% of mild and moderate-to-severe depression, respectively.[26] The prevalence of depression in the semiurban study population was 22.1%. A recent study conducted among urban elderly in South India reported a prevalence of 23% as per GDS-15.[27] Hence, the results of the present study corroborate the findings of previous studies that evaluated geriatric depression using GDS-15.

Although several factors were associated with depression among the elderly, our study found that depression was 3.4 times more prevalent in the presence of chronic illness among the rural elderly population. The “Lucknow Elderly” study also noted similar findings.[28] In a study conducted in rural Haryana, the population identified that female gender, increasing age, marital status, illiteracy, lower socioeconomic state, and presence of morbidity were significant predictors of depression.[11] A study conducted in North India in nonpsychiatric geriatric patients reported that depression was more common in geriatric patients who had more than one medical illness.[29] In our study, there was a statistically significant association of depression with physical activity, sleep problems, and social participation. However, none of these were identified as an independent risk factor for depression on regression analysis.

The present study has certain limitations. The study sample was recruited by a convenient sampling method and included those elderly available during the time of home visit. No measure was undertaken to identify the cognitive status of the study population and we excluded those elderly who were affected by cognitive impairment. Furthermore, the results of the study relied on self-reported standard measurement and screening with GDS may not tap all the symptoms of depression among elderly in the Indian context.[30] No efforts were carried out to confirm the diagnosis due to logistic reasons.

Despite the limitation, the study gives insights about the epidemiological outlook of geriatric depression that proposes future prospective researches for studying correlates of elderly depression with various geriatric attributes. In light of detecting a moderate-to-high prevalence of depression among semiurban and rural elders in this study, we suggest to routinely screen for elderly depression to initiate timely intervention for its prevention. The identification of chronic illness as an independent predictor of depression may be considered when planning community-based awareness campaigns so that comorbid physical and mental illness-related complications can be prevented at early stages.[31]


  Conclusion Top


The study showed a significantly higher burden of depression in the rural geriatric population. The symptoms of depression were more among women and associated with the presence of chronic illness. The magnitude of depression was moderately high in our sample of semiurban community-dwelling elderly. Considering the rapidly increasing population of older aged people in India, epidemiological data regarding the prevalence of depression form the mainstay for proper health planning.

Financial support and sponsorship

Nil.

Conflicts of interest

There are no conflicts of interest.



 
  References Top

1.
James SL, Abate D, Abate KH, Abay SM, Abbafati C, Abbasi N, et al. Global, regional, and national incidence, prevalence, and years lived with disability for 354 diseases and injuries for 195 countries and territories, 1990–2017: A systematic analysis for the global burden of disease study 2017. Lancet 2018;392:1789-858.  Back to cited text no. 1
    
2.
Wang PS, Aguilar-Gaxiola S, Alonso J, Angermeyer MC, Borges G, Bromet EJ, et al. Use of mental health services for anxiety, mood, and substance disorders in 17 countries in the WHO World Mental Health Surveys. Lancet 2007;370:841-50.  Back to cited text no. 2
    
3.
Franzese AT, Rurka MM. Theories of Aging. Encyclopedia of Family Studies. [e-book] 1st ed. New York: John Wiley & Sons; 2016; 23:1-9. Available from: https://onlinelibrary.wiley.com/doi/abs/10.1002/9781119085621.wbefs206. [Last cited on 2020 Mar 03].  Back to cited text no. 3
    
4.
Verghese A, Beig A, Senseman LA, Rao SS, Benjamin V. A social and psychiatric study of a representative group of families in Vellore town. Indian J Med Res 1973;61:608-20.  Back to cited text no. 4
    
5.
Lodha P, De Sousa A. Geriatric mental health: The challenges for India. J Geriatr Ment Health 2018;5:16-29.  Back to cited text no. 5
  [Full text]  
6.
Grover S. Multimorbidity in elderly: Are we prepared for it! J Geriatr Ment Health 2019;6:35-7.  Back to cited text no. 6
    
7.
Pilania M, Bairwa M, Kumar N, Khanna P, Kurana H. Elderly depression in India: An emerging public health challenge. Australas Med J 2013;6:107-11.  Back to cited text no. 7
    
8.
Grover S, Avasthi A, Sahoo S, Lakdawala B, Nebhinani N, Dan A, et al. Indian Association for geriatric mental health's multicentric study on depression in elderly: Symptom profile and influence of gender, age of onset, age at presentation, and number of episodes on symptom profile. J Geriatr Ment Health 2018;5:35-48.  Back to cited text no. 8
  [Full text]  
9.
Grover S, Malhotra N. Depression in elderly: A review of Indian research. J Geriatr Ment Health 2015;2:4-15.  Back to cited text no. 9
  [Full text]  
10.
Pilania M, Yadav V, Bairwa M, Behera P, Gupta SD, Khurana H, et al. Prevalence of depression among the elderly (60 years and above) population in India, 1997-2016: A systematic review and meta-analysis. BMC Public Health 2019;19:832.  Back to cited text no. 10
    
11.
Pilania M, Bairwa M, Khurana H, Kumar N. Prevalence and predictors of depression in community-dwelling elderly in rural Haryana, India. Indian J Community Med 2017;42:13-8.  Back to cited text no. 11
[PUBMED]  [Full text]  
12.
Chawla S, Gour N, Goel PK, Rohilla R. Depression and its correlates among geriatric people: A community based study from Southern Haryana, India. Indian J Community Fam Med 2018;4:49.  Back to cited text no. 12
  [Full text]  
13.
The Census of India. In: District Census Hand Book. Rohtak, Haryana: The Census of India; 2011. Available from: https://censusindia.gov.in/2011census/dc hb/0614_PART_B_DCHB_ROHTAK.pdf. [Last accessed on 2020 Mar 04].  Back to cited text no. 13
    
14.
Paz SH, Jones L, Calderón JL, Hays RD. Readability and comprehension of the geriatric depression scale and PROMIS ® Physical function items in older African Americans and Latinos. Patient 2017;10:117-31.  Back to cited text no. 14
    
15.
Sharma K, Gupta A, Sharma RC, Mahajan N, Mahajan A, Sharma D, et al. Prevalence and risk factors for depression in elderly North Indians. J Geriatr Ment Health 2016;3:158-63.  Back to cited text no. 15
  [Full text]  
16.
Goel PK, Muzammil K, Kumar S, Singh JV, Raghav SK. Sociodemographic correlates of depression among elderly slum dwellers of North India. Nepal J Epidemiol 2014;4:317-22.  Back to cited text no. 16
    
17.
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. 17
[PUBMED]  [Full text]  
18.
Arumugam B, Nagalingam S, Nivetha R, Balaji A. Geriatric depression among rural and urban slum community in Chennai: A cross-sectional study. J Evol Med Dent Sci 2013;3:795-80.  Back to cited text no. 18
    
19.
Akila GV, Arvind BA, Isaac A. Comparative assessment of psychosocial status of elderly in urban and rural areas, Karnataka, India. J Family Med Prim Care 2019;8:2870-6.  Back to cited text no. 19
[PUBMED]  [Full text]  
20.
Reddy NB, Pallavi M, Reddy NN, Reddy CS, Singh RK, Pirabu RA. Psychological morbidity status among the rural geriatric population of Tamil Nadu, India: A cross-sectional Study. Indian J Psychol Med 2012;34:227-31.  Back to cited text no. 20
[PUBMED]  [Full text]  
21.
Swarnalatha N. The prevalence of depression among the rural elderly in Chittoor District, Andhra Pradesh. J Clin Diagn Res 2013;7:1356-60.  Back to cited text no. 21
    
22.
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. 22
    
23.
Sanjay TV, 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.  Back to cited text no. 23
  [Full text]  
24.
D'souza L, Ranganath T, Thangara S. Prevalence of depression among the elderly in an urban slum of Bangalore, a cross-sectional study. Int J Interdiscip Multidiscip Stud 2015;2:1-4.  Back to cited text no. 24
    
25.
Sekhon H, Minhas S, Ahmed S, Garg R. A study of depression in geriatric population in a rural area of north India. Sch Acad J Biosci 2015;3:26-9.  Back to cited text no. 25
    
26.
Sinha SP, Shrivastava SR, Ramasamy J. Depression in an older adult rural population in India. MEDICC Rev 2013;15:41-4.  Back to cited text no. 26
    
27.
Konda PR, Sharma PK, Gandhi AR, Ganguly E. Geriatric depression, and its correlates among South Indian Urban. J Depress Anxiety 2018;7:314.  Back to cited text no. 27
    
28.
Tiwari SC, Tripathi RK, Kumar A, Kar AM, Singh R, Kohli VK, et al. Prevalence of psychiatric morbidity among urban elderlies: Lucknow elderly study. Indian J Psychiatry 2014;56:154-60.  Back to cited text no. 28
[PUBMED]  [Full text]  
29.
Lall A, Goyal SK. Depression in non-psychiatric geriatric outpatients. J Geriatr Ment Health 2015;2:38-41.  Back to cited text no. 29
  [Full text]  
30.
Mehra A, Grover S, Chakrabarti S, Avasthi A. Symptom profile of depression in elderly: Is assessment with geriatric depression rating scale enough? J Geriatr Ment Health 2017;4:18-25.  Back to cited text no. 30
  [Full text]  
31.
Grover S. Future of psychiatry in India: Geriatric psychiatry, a speciality to watch out. J Geriatr Ment Health 2014;1:1-5.  Back to cited text no. 31
  [Full text]  



 
 
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