Users Online: 249 Home Print this page Email this page Small font sizeDefault font sizeIncrease font size


Home About us Editorial board Search Ahead of print Current issue Archives Submit article Instructions Subscribe Contacts Login 

 Table of Contents  
Year : 2015  |  Volume : 59  |  Issue : 1  |  Page : 3-8  

Prevalence of depression and associated risk factors among the elderly in urban and rural field practice areas of a tertiary care institution in Ludhiana

Professor, Department of Community Medicine, Christian Medical College, Ludhiana, Punjab, India

Date of Web Publication9-Mar-2015

Correspondence Address:
Paramita Sengupta
Professor, Department of Community Medicine, Christian Medical College, Ludhiana - 141 008, Punjab
Login to access the Email id

Source of Support: None, Conflict of Interest: None

DOI: 10.4103/0019-557X.152845

Rights and Permissions

Background: Depression, the most common psychiatric disorder among the elderly, is not yet perceived as an important health problem in India, where few population-based studies have addressed this problem. Objectives: To estimate the prevalence of depression and identify the associated risk factors in the elderly population. Materials and Methods: 3038 consenting elderly (>60 years old) rural and urban residents of both sexes from the field practice areas were interviewed and examined in a cross-sectional study. Physical impairment in the subjects was assessed with the Everyday Abilities Scale for India (EASI), depression by the 15-item Geriatric Depression Scale (GDS-15), and cognitive impairment by the Mini-Mental State Examination (MMSE). Data were analyzed using Epi Info version-6 software. Statistical analysis included proportions, χ[2] -test, odds ratio, and its 95% confidence interval. Multiple logistic regression was done using SPSS version 21. Results: The prevalence of depression in the study population was 8.9%. It was significantly higher in urban residents, females, older elderly, nuclear families, in those living alone, those not working, illiterates, poor, functionally impaired, and cognitively impaired. In the multivariate analysis, unmarried/widowed status, unemployment, and illiteracy did not emerge as risk factors. Conclusions: Urban residence, female gender, higher age, nuclear family, poverty, and functional and cognitive impairment were found to be associated with depression even after controlling for other factors.

Keywords: Cognitive impairment, Depression, Elderly, Functional impairment, Prevalence

How to cite this article:
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

How to cite this URL:
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 [serial online] 2015 [cited 2023 Mar 30];59:3-8. Available from:

   Introduction Top

The Global Burden of Disease (GBD) study projections show that depression will be the single leading cause of Disability Adjusted Life Years by 2020 in the developing world. [1] The GBD 2000 estimates the point prevalence of unipolar depressive episodes to be 1.9% for men and 3.2% for women, and that 5.8% of men and 9.5% of women will experience a depressive episode in a 12-month period. These prevalence figures vary across populations and may be higher in some populations. In a meta-analysis of various study reports of community -based mental health surveys on geriatric depressive disorders in those aged 60 years and above, conducted in the continents of Asia, Europe, Australia, North America, and South America between 1955 and 2005, the median prevalence rate of depressive disorders in the world for the elderly population was determined to be 10.3%, while among the elderly Indian population, it was determined to be 21.9% [interquartile range (IQR) 11.6-31.1)]. Depression is the most common psychiatric disorder among the elderly, [4] and although India is the second-most populous country in the world in terms of elderly population > 60 years of age, depression in the elderly is not yet perceived as an important health problem in the country. Few community-based studies have been conducted in India so far to address this issue. Hence, this study was conducted to estimate the prevalence of depression in the elderly ( > 60 years old) in Ludhiana and to identify the major risk factors for depression in the study population.

   Materials and Methods Top

Study design

Cross-sectional study.

Study period

Six months (from 1 June 2011 to 30 November, 2011).

Study participants

The study participants consisted of consenting elderly ( > 60 years old) residents of the field practice areas of the Department of Community Medicine, covering a population of about 45,000 (30,000 urban and 15,000 rural), identified through house-to-house survey. All the elderly, of both sexes, in the study population were included in the study.

Sample size estimation

In the absence of epidemiological information on depression among the elderly in this area, for the purpose of calculating the minimum sample size required for our study, we considered the lower value of 11.6% of the IQR for the prevalence of depression reported in the Indian elderly in the meta-analysis of six community-based studies. [3] With the allowable error of 10% of the prevalence, within 95% confidence limits, the minimum sample size required was 2842. A total of 3054 elderly were found in the population under study, of which 3038 eligible respondents participated in the investigation.

Ethics approval

Approval of the Institutional Ethics Committee was obtained prior to commencement of the study.

Consenting procedure

The respondents were explained the purpose of the study, and their signed consent was obtained. Consent was obtained from the caregiver in the event of the subject being unable to give informed consent.

Assessment tools

Information was obtained from consenting respondents using a pre-tested questionnaire containing various socio-demographic parameters. The interview was conducted in the language with which the subject was familiar (Hindi/Punjabi), for which purpose the consent form and assessment tools were translated into both the languages and back-translated by an independent coworker proficient in both languages to ensure validity of the translation. Functioning for daily living of the subjects was assessed in the presence of the primary caregiver with the help of Everyday Abilities Scale for India (EASI) and subjects with EASI score of > 3 were classified as functionally impaired. [5] Depression was assessed using the 15-item Geriatric Depression Scale (GDS), [6] which is a 15-item self-report assessment used as a basic screening measure of depression in the elderly. Accuracy of the GDS-15 is not influenced by the severity of medical burden, age, or other socio-demographic characteristics and even the "very old" and ill can be screened appropriately. [7] Moreover, the presence of a major depressive episode among elderly home-bound adults can be reliably detected. In a validation study comparing the long and short forms of the GDS for self-rating of symptoms of depression, both were successful in differentiating depressed from non-depressed adults with a high correlation (r = 0.84, P < 0.001). Hence, this scale is better suited in identifying depression in the elderly. [8] Those with a GDS score > 5 were categorized as depressed. Using this cut-off, a high sensitivity and specificity of the 15-item GDS has been reported. [9] Cognitive impairment was assessed using the Mini-Mental State Examination (MMSE), and respondents with MMSE score < 25 were considered as cognitively impaired. [10] The Hindi translation of MMSE (used for the rural illiterate elderly, validated in a previous study) was suitably modified and used in this study. [11]

Exclusion criteria

The deaf/dumb/blind, those with diagnosed psychiatric illness (schizophrenia, mental retardation) or neurological disorders ( Parkinsonism More Details, severe head injury, or brain neoplasm), and those who were ill at the time of the study were excluded, as there was no way to obtain reliable information from them.

Statistical analysis

Data were analyzed using Epi Info version-6 software. Data analysis included proportions. Odds ratio and its 95% confidence intervals were calculated. Chi-square test was used to determine statistical significance of the observed differences. Multiple logistic regression analysis was carried out using SPSS software version 21 (IBM Corp., Armonk, NY, USA).

   Results Top

[Table 1] shows that the prevalence of depression (GDS score > 5) in the elderly population under study was found to be 8.9%. The prevalence was significantly higher in the urban residents, females, older elderly ( > 80 years old), those living alone without a spouse, i.e., unmarried/widowed, nuclear families, illiterates, those not working, and in the poor with monthly per capita income (MPCI) of < Rs. 1000. The prevalence of functional impairment (EASI score > 3) in the elderly was 7.0% and of cognitive impairment (MMSE score < 25) was 8.8%. The prevalence of depression was found to be significantly higher both in those with functional impairment as well as in those with cognitive impairment.
Table 1: Risk factors for depression in the elderly

Click here to view

[Table 2] shows that on applying multiple logistic regression model, urban residence, female sex, age > 80 years, nuclear family, MPCI < Rs. 1000, and functional as well as cognitive impairment were found to be strong predictors of depression. Marital status, educational status, or occupational status was not found to have a significant effect on depression in the multivariate analysis.
Table 2: Multivariate analysis of the association of risk factors with depression

Click here to view

   Discussion Top

The prevalence of depression, based on GDS scores > 5, was found to be 8.9% in the present study. Studies have revealed that the prevalence rates for depression in community samples of elderly in India vary from 6 to 50%. [12] The prevalence has been reported to be 45.9% in the urban slums of Mumbai, [13] 29.36% in the urban slums of Dharwad district, Karnataka, [14] 31.4% in a rural population of Ahmednagar, Maharashtra, [15] and 12.7% in a cross-sectional study of 1000 elderly in Vellore, Tamil Nadu. [16] An increased median prevalence of 21.9% (IQR 11.6-31.1) of the depressed elderly in India in a meta-analysis of 74 studies across the world [3] may be explained by the fact that the meta-analysis consisted of six relevant studies from India, covering only 2499 (0.5%) elderly participants, as compared to 68 studies from the rest of the world covering 487,275 (99.5%) of the participants. A cross-sectional study in a tertiary care hospital in Karachi found the prevalence of depression to be 19.5% in the elderly aged 65 years and above. [17]

Significant predictors for depression found among the elderly in our study were urban residence, female sex, increasing age, nuclear family, illiteracy, and poverty. A meta-analysis of the risk factors of depression in the elderly [18] found bereavement, sleep disturbance, disability, prior depression, and female gender to be significant risk factors for depression. A study in Pakistan also reported female gender, elderly without a spouse, low level of education, and unemployment to be independent predictors of depression. [17] Similar findings have been reported among the geriatric population in the urban slums of Mumbai [13] and Dharwad, [14] as well as in the rural elderly of district Ahmednagar, Maharashtra. [15] However, a study on community-dwelling elderly in Tamil Nadu [16] found that age, female gender, cognitive impairment, and disability status were not significantly associated with geriatric depression. In the present study, marital status, educational status, and occupational status were not found to be predictors of depression in the multivariate analysis.

Nuclear family was found to be an independent risk factor for depression in the present study. The elderly living in a nuclear family were more than 3 times likely to suffer from depression than those living in a joint family. Similar findings have been reported by other researchers. [17],[19] Urbanization leads to households becoming less extended and more nuclear. Data from household surveys conducted in 43 developing countries in the 1990s suggest a trend toward convergence to predominantly nuclear households. [20] Nucleation of the family leads to a decrease in coresidence of the elderly with adult children and, therefore, a decrease in their care and support. [17],[20],[21]

Those not working/retired subjects in our study were 3 times more likely to suffer from depression than those who were employed, although it was not found to be an independent risk factor for depression. Other studies [14],[17] have also reported depression to be more in those not working.

Functional impairment was found to be a strong predictor for depression, with those functionally impaired having more than 11 times a risk of depression. Lenze et al. [22] observed that though depressive symptoms in late life may predict functional disability in older persons, persistent depression is thought to be associated with a greater linear increase in functional disability than remitted depression. Payne et al. [23] observed that patients with Alzheimer's disease who are less severely demented but more functionally impaired are more likely to be depressed. One explanation for this finding is that since patients with less severe cognitive impairment are usually less functionally impaired, greater functional impairment in a mildly demented patient might indicate that a process other than dementia leads to the functional impairment. This might be a physical disability such as blindness or difficulty in walking, but it could also be the coexisting depressive features. Alternatively, difficulties with activities of daily living might be more likely to cause early dementia patients to feel depressed. Treatment of depression has been associated with improved functional status.

Those cognitively impaired were also found to be more than 3 times at risk of depression in the present study. Depression is associated with cognitive impairment in older adults, [24] and a meta-analysis of case-control and prospective studies of the association between depression and dementia conducted in 2001 concluded that history of depression approximately doubled the risk for dementia. [25] The prevalence of depression in dementias has been reported to be between 9% and 68%, and it has been proposed to be both a risk factor for as well as a prodrome of dementia. [26] People with mild cognitive impairment and dementia exhibit greater rates of depression than age-matched cognitively intact individuals. [27]

Among the Ballabgarh elderly also, higher depressive symptom scores were independently and significantly associated both with lower cognitive function scores and with greater levels of functional impairment. [6] A consensus opinion from the National Institute of Mental Health is that late life depression may represent an independent risk factor predisposing to dementing disorders, even when depressive symptoms occur more than 10 years before the onset of dementia. [28] The correct diagnosis of depression in the elderly suffering from Alzheimer's disease is important because, in most cases, it can be treated successfully. [29]

   Conclusions Top

The prevalence of symptoms of depression in the elderly population under study was 8.9%. Urban residence, female gender, higher age, nuclear family, poverty, functional and cognitive impairment were found to be associated with depression, even after controlling for other factors. With increasing longevity and proportion of the elderly population in India, and the trend toward urbanization and nucleation of the families, depression among the elderly is likely to become a disease demanding "public health problem" status in the near future. The care of the elderly, including their mental health care, requires to be brought on the national health care agenda.

   Acknowledgment Top

The authors wish to acknowledge the contribution of Dr. Paramdeep Kaur for the multivariate analysis.

   References Top

Murray CJ, Lopez AD. Alternative projections of mortality and disability by cause 1990-2020: Global Burden of Disease Study. Lancet 1997;349:1498-504.  Back to cited text no. 1
World Health Organization (WHO). The World Health Report 2001 - Mental Health: New Understanding, New Hope. Geneva: World Health Organization; 2001. p. 30.  Back to cited text no. 2
Barua A, Ghosh MK, Kar N, Basilio MA. Depressive disorders in Elderly: An estimation of this public health problem. J Int Med Sci Acad 2011;24:193-4.  Back to cited text no. 3
Satcher D. Mental Health: A report of the surgeon general- executive summary. Prof Psychol Res Pr 2000;31:5-13.  Back to cited text no. 4
Fillenbaum GG, Chandra V, Ganguli M, Pandav R, Gilby JE, Seaberg EC, et al. Development of an activities of daily living scale to screen for dementia in an illiterate rural older population in India. Age Ageing 1999;28:161-8  Back to cited text no. 5
Ganguly M, Dubey S, Johnston JM, Pandav R, Chandra V, Dodge HH. Depressive symptoms, cognitive impairment and functional impairment in a rural elderly population in India: A Hindi version of the Geriatric Depression Scale (GDS-H). Int J Geriatr Psychiatry 1999;14:807-20  Back to cited text no. 6
Marc LG, Raue PJ, Bruce ML. Screening Performance of the 15-item Geriatric Depression Scale in a diverse elderly home care population. Am J Geriatr Psychiatry 2008;16:914-21.  Back to cited text no. 7
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. 8
Lyness JM, Noel TK, Cox C, King DA, Conwell Y, Caine ED. Screening for depression in elderly primary care patients. A comparison of the Center for Epidemiologic Studies-Depression Scale and the Geriatric Depression Scale. Arch Intern Med 1997;157:449-54.  Back to cited text no. 9
Folstein MF, Folstein SE, McHugh PR. "Mini Mental State". A practical method for grading the cognitive state of patients for the clinician. J Psychiatr Res 1975;12:189-98.  Back to cited text no. 10
Ganguli M, Ratcliff G, Chandra V, Sharma S, Gilby J, Pandav R. A Hindi version of the MMSE: The development of a cognitive screening instrument for a largely illiterate rural elderly population in India. Int J Geriatr Psychiatry 1995;10:367-77.  Back to cited text no. 11
Venkoba RA. Psychiatry of old age in India. Int Rev Psychiatry 1993;5:165-70.  Back to cited text no. 12
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. 13
[PUBMED]  Medknow Journal  
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. 14
Kamble SV, Dhumale GB, Goyal RC, Phalke DB, Ghodke YD. Depression among elderly persons in a Primary Health Centre area in Ahmednagar, Maharastra. Indian J Public Health 2009;53:253-5.  Back to cited text no. 15
[PUBMED]  Medknow Journal  
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. 16
Taqui AM, Itrat A, Qidwai W, Qadri Z. Depression in the elderly: Does family system play a role? A cross-sectional study. BMC Psychiatry 2007;7:57.  Back to cited text no. 17
Cole MG, Dendukuri N. Risk factors for depression among elderly community subjects: A systematic review and meta-analysis. Am J Psychiatry 2003;160:1147-56.  Back to cited text no. 18
Jhingan HP, Sagar R, Pandey RM. Prognosis of late-onset depression in the elderly: A study from India. Int Psychogeriatr 2001;13:51-61.  Back to cited text no. 19
Bongaarts J. Household size and composition in the developing world in the 1990s. Popul Stud (Camb) 2001;55:263-79.  Back to cited text no. 20
Mason KO. Family change and support of the elderly in Asia: What do we know? Asia Pac Popul J 1992;7:13-32.  Back to cited text no. 21
Lenze EJ, Schulz R, Martire LM, Zdaniuk B, Glass T, Kop WJ, et al. The course of functional decline in older people with persistently elevated depressive symptoms: Longitudinal findings from the Cardiovascular Health Study. J Am Geriatr Soc 2005;53:569-75.  Back to cited text no. 22
Payne JL, Lyketsos CG, Steele C, Baker L, Galik E, Kopunek S, et al. Relationship of Cognitive and Functional Impairment to Depressive Features in Alzheimer's Disease and Other Dementias. J Neuropsychiatry Clin Neurosci 1998;10:440-7.   Back to cited text no. 23
Barnes DE, Alexopoulos GS, Lopez OL, Williamson JD, Yaffe K. Depressive symptoms, vascular disease, and mild cognitive impairment: Findings from the Cardiovascular Health Study. Arch Gen Psychiatry 2006;63:273-9.  Back to cited text no. 24
Jorm AF. History of depression as a risk factor for dementia: An updated review. Aust N Z J Psychiatry 2001;35:776-81.  Back to cited text no. 25
Muliyala KP, Varghese M. The complex relationship between depression and dementia. Ann Indian Acad Neurol 2010;13(Suppl 2):S69-73.   Back to cited text no. 26
Modrego PJ, Ferrández J. Depression in patients with mild cognitive impairment increases the risk of developing dementia of Alzheimer's type: A prospective cohort study. Arch Neurol 2004;61:1290-3.  Back to cited text no. 27
Steffens DC, Otey E, Alexopoulos GS, Butters MA, Cuthbert B, Ganguli M, et al. Perspectives on depression, mild cognitive impairment, and cognitive decline. Arch Gen Psychiatry 2006;63:130-8.  Back to cited text no. 28
Lyketsos CG, Olin J. Depression in Alzheimer's disease: Overview and treatment. Biol Psychiatry 2002;52:243-52.  Back to cited text no. 29


  [Table 1], [Table 2]

This article has been cited by
1 Urban-rural and gender differential in depressive symptoms among elderly in India
Shubham Kumar, Shekhar Chauhan, Ratna Patel, Manish Kumar, David Jean Simon
Dialogues in Health. 2023; 2: 100114
[Pubmed] | [DOI]
2 Impact of the COVID 19 pandemic on the mental health and quality of life among older adults in India
Steve Manjaly, Anu Francis, Siju Jose Koonen, Deepthi Thekkinath, Sangeetha Dhruvan
Southeast Asian Journal of Case Report and Review. 2023; 10(1): 5
[Pubmed] | [DOI]
3 Extent, spectrum, and predictors of cognitive impairment in urban geriatric population in a district of North India
Priya Keshari, Hari Shankar
Indian Journal of Public Health. 2022; 66(4): 504
[Pubmed] | [DOI]
4 Depression and quality of life among elderly: Comparative cross-sectional study between elderly in community and old age homes in Eastern India
SoumyaS Sahoo, Vazinder Kaur, UditK Panda, Bhola Nath, PragyanP Parija, DineshP Sahu
Journal of Education and Health Promotion. 2022; 11(1): 301
[Pubmed] | [DOI]
5 A comparative review of the epidemiology of mental disorders in Australia and India
Nagesh Pai, Shae-Leigh Vella, David Castle
Asia-Pacific Psychiatry. 2022;
[Pubmed] | [DOI]
6 Does clean cooking energy improve mental health? Evidence from China
Pihui Liu, Chuanfeng Han, Minmin Teng
Energy Policy. 2022; 166: 113011
[Pubmed] | [DOI]
7 Association between quality of life, sleep quality and mental disorders in Iranian older adults
Ali Khorshidi, Marzieh Rostamkhani, Roya Farokhi, Abbas Abbasi-Ghahramanloo
Scientific Reports. 2022; 12(1)
[Pubmed] | [DOI]
8 Living and eating alone on depressive symptoms by physical frailty status: A cross-sectional study based on the Korean Frailty and Aging Cohort Study
Ji Hyun Moon, Jung Sik Huh, Chang Won Won, Hyeon Ju Kim
Archives of Gerontology and Geriatrics. 2022; 98: 104570
[Pubmed] | [DOI]
9 Spectrum of cardiovascular diseases with increasing age and its association with geriatric syndromes
Pramod Kumar, Bhrigu Jain, Nidhi Soni, SN Dwivedi, AparajitBallav Dey, Prashun Chatterjee, Avinash Chakrawarty
Journal of the Indian Academy of Geriatrics. 2022; 18(2): 68
[Pubmed] | [DOI]
10 A study on prevalence and factors associated with depression among elderly residing in tenements under resettlement scheme, Kancheepuram District, Tamil Nadu
BuvneshM Kumar,TK Raja,Fasna Liaquathali,Jasmine Maruthupandian,PragadeeshV Raja
Journal of Mid-life Health. 2021; 12(2): 137
[Pubmed] | [DOI]
11 Prevalence of depression amongst the Elderly population in old age homes of Mangalore city
Saurabh Kumar,Sharon Joseph,Athul Abraham
Journal of Family Medicine and Primary Care. 2021; 10(5): 1868
[Pubmed] | [DOI]
12 Prevalence of Common mental disorders in older adults: Results from the National Mental Health Survey of India
Preeti Sinha,Tajamul Hussain,Naveen Kumar Boora,Girish N Rao,Mathew Varghese,G. Gururaj,Vivek Benegal
Asian Journal of Psychiatry. 2021; 55: 102463
[Pubmed] | [DOI]
13 Prevalence and association of depressive symptoms with spiritual intelligence among older adults: A community-based study in rural Puducherry, South India
Pritam Kumar Roy,Ganesh Kumar Saya,Revathi Ulaganeethi,Suganya Jayaram,Swetha S Kumar
Asian Journal of Psychiatry. 2021; 55: 102510
[Pubmed] | [DOI]
14 Factors associated with depression among the elderly living in rural Vietnam 2019: Recommendations to remove barriers of psychological service accessibility
Van Nguyen Hang Nguyet,Huyen Nguyen Thi Khanh,Luong Nguyen Thanh,Duc Duong Minh,Thanh Pham Quoc
International Journal of Mental Health. 2021; 50(2): 136
[Pubmed] | [DOI]
15 Depression among older adults: a systematic review of South Asian countries
Anil R. Assariparambil,Judith A. Noronha,Asha Kamath,Prabha Adhikari,Baby S. Nayak,Ravi Shankar,Anice George
Psychogeriatrics. 2021; 21(2): 201
[Pubmed] | [DOI]
16 Prevalence, Structure, and Risk Factors for Mental Disorders in Older People
N. N. Petrova, D. A. Khvostikova
Advances in Gerontology. 2021; 11(4): 409
[Pubmed] | [DOI]
17 Health care need and health disparities: Findings from the Regional South Australia Health (RESONATE) survey
Matthew J. Leach,Marianne Gillam,David A. Gonzalez-Chica,Sandra Walsh,Kuda Muyambi,Martin Jones
Health & Social Care in the Community. 2021; 29(4): 905
[Pubmed] | [DOI]
18 Sex hormone levels in females of different ages suffering from depression
Rong Lei, Yan Sun, Jiawen Liao, Yuan Yuan, Linlin Sun, Yugeng Liu, Xinyu Yang, Wenyou Ma, Zhenjian Yu
BMC Women's Health. 2021; 21(1)
[Pubmed] | [DOI]
19 Differences in depressive symptoms by rurality in Japan: a cross-sectional multilevel study using different aggregation units of municipalities and neighborhoods (JAGES)
Mariko Kanamori,Masamichi Hanazato,Daisuke Takagi,Katsunori Kondo,Toshiyuki Ojima,Airi Amemiya,Naoki Kondo
International Journal of Health Geographics. 2021; 20(1)
[Pubmed] | [DOI]
20 Prevalence and determinants of depression among old age: a systematic review and meta-analysis
Yosef Zenebe, Baye Akele, Mulugeta W/Selassie, Mogesie Necho
Annals of General Psychiatry. 2021; 20(1)
[Pubmed] | [DOI]
21 Dissatisfaction with life and absence of leisure time activity: clues to overt depression and occult suicide risk in elderly individuals without significant disabling disease
Nuryil Yilmaz,Sanem Nemmezi Karaca
Psychogeriatrics. 2020; 20(3): 337
[Pubmed] | [DOI]
22 Prevalence of psychiatric disorders among older adults in Jodhpur and stakeholders perspective on responsive health system
Mamta Patel,Pankaj Bhardwaj,Naresh Nebhinani,AkhilDhanesh Goel,Kamlesh Patel
Journal of Family Medicine and Primary Care. 2020; 9(2): 714
[Pubmed] | [DOI]
23 Adding life to years: Role of gender and social and family engagement in geriatric depression in rural areas of Northern India
KikkeriHanumantha Setty Naveen,AkhilDhanesh Goel,Shraddha Dwivedi,MohdAmirul Hassan
Journal of Family Medicine and Primary Care. 2020; 9(2): 721
[Pubmed] | [DOI]
24 Impacts of Urbanization and ICT Use on Loneliness Among the Elderly in Israel
Shiri Pearlman-Avnion,Yael Goldschmidt,Neli Shamis
Education and Urban Society. 2020; 52(6): 962
[Pubmed] | [DOI]
25 Prevalence and determinants of geriatric depression in North India: A cross-sectional study
Bhavna Sahni,Kiran Bala,Tejinder Kumar,Akash Narangyal
Journal of Family Medicine and Primary Care. 2020; 9(5): 2332
[Pubmed] | [DOI]
26 Geriatric Mental Health Challenges in India- A Review
Reeta Verma Katiyar,Sharique Ahmad,Maha Waqar Beg,Tanish Baqar
Journal of Evolution of Medical and Dental Sciences. 2020; 9(23): 1787
[Pubmed] | [DOI]
27 Depressão em idosos de uma região rural do Sul do Brasil
Mariana Lima Corrêa,Marina Xavier Carpena,Rodrigo Dalke Meucci,Lucas Neiva-Silva
Ciência & Saúde Coletiva. 2020; 25(6): 2083
[Pubmed] | [DOI]
28 Comparison of depression among the elderly in a selected semiurban and rural community of Haryana, North India: A cross-sectional survey
Sudesh Kumari,Jaison Joseph
Journal of Geriatric Mental Health. 2020; 7(1): 33
[Pubmed] | [DOI]
29 Comparative assessment of psychosocial status of elderly in urban and rural areas, Karnataka, India
GovindarajanVenguidesvarane Akila,BanavaramAnniappan Arvind,Arjunan Isaac
Journal of Family Medicine and Primary Care. 2019; 8(9): 2870
[Pubmed] | [DOI]
30 Urban–Rural Differences in Older Adult Depression: A Systematic Review and Meta-analysis of Comparative Studies
Jonathan Purtle,Katherine L. Nelson,Yong Yang,Brent Langellier,Ivana Stankov,Ana V. Diez Roux
American Journal of Preventive Medicine. 2019; 56(4): 603
[Pubmed] | [DOI]
31 Prevalence, associated risk factors of depression and mental health needs among geriatric population of an urban slum, Cuttack, Odisha
Swetaleena Ashe,Dipanweeta Routray
International Journal of Geriatric Psychiatry. 2019; 34(12): 1799
[Pubmed] | [DOI]
32 Association between health behaviors and mood disorders among the elderly: a community-based cohort study
Tzu-Jung Tseng,Yi-Syuan Wu,Jia-Hong Tang,Yen-Hui Chiu,Yu-Ting Lee,I-Chun Fan,Ta-Chien Chan
BMC Geriatrics. 2019; 19(1)
[Pubmed] | [DOI]
33 Prevalence of depression among the elderly (60?years and above) population in India, 1997–2016: a systematic review and meta-analysis
Manju Pilania,Vikas Yadav,Mohan Bairwa,Priyamadhaba Behera,Shiv Dutt Gupta,Hitesh Khurana,Viswanathan Mohan,Girish Baniya,S. Poongothai
BMC Public Health. 2019; 19(1)
[Pubmed] | [DOI]
Muniswamy Sundar,Rajani Urs H.S
Journal of Evidence Based Medicine and Healthcare. 2018; 5(5): 453
[Pubmed] | [DOI]
35 The Prevalence of Depression and its Associated Demographic Factors in the Elderly with Electronic Health Records in Zanjan
Akbar Pourrahimi,Aida sheykhlar,Mahnaz Keshvarz Afshar,Mohammad Abdi,Ali Aghajanloo,Sana Mohammadi,Fatemeh Bayat
Preventive Care In Nursing and Midwifery Journal. 2018; 8(2): 18
[Pubmed] | [DOI]
36 Depression and its associated factors among elderly: A community-based study in Egypt
Abdel-Hady El-Gilany,Ghada O. Elkhawaga,Bernadet B. Sarraf
Archives of Gerontology and Geriatrics. 2018; 77: 103
[Pubmed] | [DOI]
37 Prevalence of geriatric depression in a community sample in Ghana: Analysis of associated risk and protective factors
Nuworza Kugbey,Theodore Atsu Nortu,Bright Akpalu,Martin Amogre Ayanore,Francis Bruno Zotor
Archives of Gerontology and Geriatrics. 2018; 78: 171
[Pubmed] | [DOI]
38 Prevalence of and Factors Contributing to Anxiety, Depression and Cognitive Disorders among Urban Elderly in Odisha – A Study through the Health Systems’ Lens
Sudharani Nayak,Mrinal Kar Mohapatra,Bhuputra Panda
Archives of Gerontology and Geriatrics. 2018;
[Pubmed] | [DOI]
39 The association between somatic and psychological discomfort and health-related quality of life according to the elderly and non-elderly
Hyeon-Sook Lee,Siwoo Lee,Sohee Park,Younghwa Baek,Ji-Hye Youn,Dan Bee Cho,Jung-Hyun Jin,Aesun Shin,Sue K. Park,Keon Wook Kang,Young-Khi Lim,Chul Hwan Kang,Keun-Young Yoo,Kwang-Pil Ko
Quality of Life Research. 2017;
[Pubmed] | [DOI]
40 Incidence, risk, and associated factors of depression in adults with physical and sensory disabilities: A nationwide population-based study
Szu-Ching Shen,Kuang-Hua Huang,Pei-Tseng Kung,Li-Ting Chiu,Wen-Chen Tsai,Dongmei Li
PLOS ONE. 2017; 12(3): e0175141
[Pubmed] | [DOI]
41 Huzurevinde, Evde Ailesiyle ve Yalniz Yasayan Yasli Bireylerde Depresyon, Yalnizlik Hissi Düzeylerinin Karsilastirilmasi
Ege Agirman,Mehmet Ziya Gençer
Journal of Contemporary Medicine. 2017; : 234
[Pubmed] | [DOI]
42 A Comparative Study on Mental Health between Elderly Living Alone and Elderly Couples - Focus on Gender and Demographic Characteristics -
Bo-Young Park,Ho-Jang Kwon,Mi-Na Ha,Eun-Ae Burm
Journal of Korean Public Health Nursing. 2016; 30(2): 195
[Pubmed] | [DOI]
43 A Community-Based Study of Quality of Life and Depression among Older Adults
Wenjun Cao,Chongzheng Guo,Weiwei Ping,Zhijun Tan,Ying Guo,Jianzhong Zheng
International Journal of Environmental Research and Public Health. 2016; 13(7): 693
[Pubmed] | [DOI]
44 Social Network and Mental Health Among Older Adults in Rural Uttar Pradesh, India: A Cross-Sectional Study
Lucky Singh,Prashant Kumar Singh,Perianayagam Arokiasamy
Journal of Cross-Cultural Gerontology. 2016;
[Pubmed] | [DOI]
45 Association between eating alone and depressive symptom in elders: a cross-sectional study
Xinyi Wang,Wei Shen,Chunmei Wang,Xiaoyi Zhang,Yuanyuan Xiao,Fan He,Yujia Zhai,Fudong Li,Xiaopeng Shang,Junfen Lin
BMC Geriatrics. 2016; 16(1)
[Pubmed] | [DOI]
46 Association between asthma and depression in Korean adults
Yeo Jin Kim,Jeoung Eun Kim,Ju Suk Lee
Allergy, Asthma & Respiratory Disease. 2015; 3(3): 173
[Pubmed] | [DOI]


    Similar in PUBMED
   Search Pubmed for
   Search in Google Scholar for
 Related articles
    Access Statistics
    Email Alert *
    Add to My List *
* Registration required (free)  

  In this article
    Materials and Me...
    Materials and Me...
    Article Tables

 Article Access Statistics
    PDF Downloaded2174    
    Comments [Add]    
    Cited by others 46    

Recommend this journal