|Year : 2022 | Volume
| Issue : 4 | Page : 162-167
Depression in the elderly: Prevalence and associated factors in urban population
Rupali Verma Bagga1, Anamika Prashant2
1 Department of Community Medicine, Gian Sagar Medical College and Hospital, Ramnagar, Rajpura, Punjab, India
2 Medical student, MIMER Medical College and Dr. BSTR Hospital, Talegaon Dabhade, Pune, Maharashtra, India
|Date of Submission||07-Oct-2022|
|Date of Decision||16-Nov-2022|
|Date of Acceptance||17-Nov-2022|
|Date of Web Publication||27-Dec-2022|
Dr. Rupali Verma Bagga
Department of Community Medicine, Gian Sagar Medical College and Hospital, Ramnagar, Rajpura - 140601, Punjab
Source of Support: None, Conflict of Interest: None
Introduction: Depression in elderly population is a serious public health concern but is often undetected and ignored as a medical problem, leading to poor quality of life. Aim and Objectives: The objectives of this study were to estimate the prevalence and degree of depression among the elderly population using a Geriatric Depression Scale (GDS-15) Short Form and to study some correlates associated with depression in them. Materials and Methods: A community-based cross-sectional study was conducted with a sample size of 100 elderly subjects using systematic random sampling technique. After getting informed consent, information was collected using GDS-15 Marathi version. Results: Of 100 respondents interviewed, 52 were 70 years and above and 54 were male. The prevalence of depression among the elderly was 84.0%. Sixteen (8 males and 8 females) were suffering from severe depression. Age, sex, death of spouse, education, occupation, and morbidity status were found to be significantly associated with depression. Conclusions: The prevalence of depression among the urban elderly was very high. By identifying risk factors for depression among the elderly population and screening them on time, we can go a long way in adding life to their years instead of years to life of the elderly.
Keywords: Depression, elderly, Geriatric Depression Scale, prevalence, urban
|How to cite this article:|
Bagga RV, Prashant A. Depression in the elderly: Prevalence and associated factors in urban population. J Indian Acad Geriatr 2022;18:162-7
|How to cite this URL:|
Bagga RV, Prashant A. Depression in the elderly: Prevalence and associated factors in urban population. J Indian Acad Geriatr [serial online] 2022 [cited 2023 Jan 29];18:162-7. Available from: http://www.jiag.com/text.asp?2022/18/4/162/365780
| Introduction|| |
Population aging is one of the distinctive phenomena of the twentieth century and will surely remain an important challenge throughout the 21st century. Population aging – a process of progressive increase in the number of older people relative to the rest of the population – was long thought of as primarily an issue for the developed world. However, in recent years, many countries in the developing world are also beginning to experience population aging. This demographic trend poses new challenges, including for the developing world. India is no exception to the process of population aging.
The elderly population is defined as people aged 60 and above. India is going through a rapid demographic aging. Between 1961 and 2011, the population aged 60 and above nearly quadrupled. The share of the population aged 70 and above also increased from 2.0 to 3.6 per cent from 1961 to 2011, and the population share of persons 70 and above is projected to increase by about 1 per cent by 2031, and then 1 per cent every 10 years up to 2051. India also recorded an improvement in life expectancy at birth, which was 47 years in 1969, growing to 60 years in 1994 and 69 years in 2019. The population of the elderly in Maharashtra has also increased rapidly from 5.3% in 1961 to 9.9% in 2019.
These trends clearly point to population aging as a major challenge, and indicate that considerable resources will need to be directed toward the support, care, and medical treatment of older persons. Population aging may be seen as a human success story – a triumph of public health programs, medical advancements, and economic development over diseases and injuries that have limited human life expectancy for years. At the same time, however, it has a profound impact on socioeconomic issues such as economic growth, savings, investment, retirement, pensions, labor markets, and intergenerational transfers. Population aging also increases the health needs of societies as the older population forms a larger proportion of a country's population. When populations age rapidly, governments are often caught unprepared to face and mitigate the consequences; this has implications for the socioeconomic and health status of the elderly.
With the aging of the population, the physical, mental, and social aspects of health start to deteriorate. Depression is one of the most common psychiatric problems among the elderly which presents with depressed mood, loss of interest or pleasure, decreased energy, feelings of guilt or low self-worth, disturbed sleep or appetite, and poor concentration. Due to this, the physical and social aspects of health are also affected. The World Health Organization predicts depression will be a second leading cause of disability in the world by the year 2020 with negative impact on human well-being and overtaking ischemic heart disease, cancers, and cerebrovascular disease.
Depression in the elderly is yet to receive its due recognition in India. Many studies conducted in India have estimated the varied prevalence of depression among the elderly in community samples. Methodological differences may account for this variability. Studies to assess the depression among the elderly population have not been done in this region. Keeping in mind the different problems of the elderly, the need was strongly felt to assess the prevalence of depression and its determinants among the elderly so as to plan regionally sensitive intervention strategies for engaging and empowering the elderly against depression. In this context, this research was undertaken.
| Materials and Methods|| |
Study design and setting
The present study was cross-sectional in nature and was conducted in field practice area of Urban Health and Training Centre of Maharashtra Institute of Medical Education and Research, Talegaon Dabhade, Maharashtra, India. The study was undertaken in months of July 2018 to September 2018 among people aged 60 years and above.
After getting clearance from the Institutional Ethical Committee, the study population of the elderly aged 60 years and above residing in that area for at least 1 year was included in this study. The exclusion criterion was elderly persons with poor cognition screened through Mini-Cog and those not willing and not consenting to participate in the study for their own reasons.
Previous studies have reported prevalence of depression in elderly to be around 49.52%. Considering allowable error=20% of prevalence, i.e power of test is 80%, allowable error is 9.8. Considering 95% confidence interval (α=0.05) sample size can be calculated as follows-
Formula for sample size:
n = sample size
Z = level of significance
p = positive prevalence
q = nonprevalence
d = allowable error
= 99.96 ~ 100
Hence, sample size is 100.
The sampling technique used was Systematic random sampling.
Out of all families registered under Urban Health Centre, every third family was selected and all elderly people in that family were interviewed and data were collected during the home visit by the researcher with the help of social worker. Screening for dementia using Mini-Cog assessment was done individually. Those who were positive for dementia using Mini-Cog (score <3) were excluded from the study. Informed written consent was obtained from the participants. A predesigned questionnaire in local language was administered to each elderly to collect data on sociodemographic profile such as age, sex, religion, marital status, education, income, and socioeconomic status. Completion of data was ensured by revisiting the houses.
The Geriatric Depression Scale (GDS-15) Short Form was used to measure the level of depression in geriatric population. It is a preprepared, prevalidated scale for assessing depression in elderly people, which has 15 questions, was administered individually through face-to-face interview in local language, and depression levels were thus assessed for the elderly who screened negative for dementia. GDS-15 is not a substitute for a diagnostic interview but is a useful screening tool which facilitates the assessment of depression in older adults. GDS-15 has been extensively used in the community. We have used its Marathi version in this study as the study participants were mostly Marathi speaking and were comfortable in answering to the Marathi questionnaire.
The 15-item Geriatric Depression Scale (GDS-15) was used to assess depressive symptoms. The instrument focuses on psychological symptoms: 10 questions indicated the presence of depression when answered positively while the rest 5 questions indicated depression when answered negatively. The GDS-15 questions were read out to the study participants and they were asked how they felt over the past week using a yes and no response format. A score of 0–4 is considered normal, 5–8 is suggestive of mild depression, 9–11 is suggestive of moderate depression, and 12–15 is indicative of severe depression.
Ethical clearance of the Institutional Ethics Committee was taken before conducting research. Informed consent was obtained from each of the study participants before administration of questionnaire. We took all possible precautions to maintain the anonymity of each study participant. Confidentiality was assured in collection of personal data.
Data were collected in local language and were analyzed using Statistical Package for the Social Sciences (SPSS) version 20 (trial version) IBM Corp. Armonk, NY. Results were tabulated in percentages and proportions. To calculate the differences between the groups, appropriate statistical tests including Chi-square test was applied. Significance was checked at P = 0.05. Yates correction was applied whenever it was required. P < 0.05 was considered statistically significant.
| Results|| |
In the present study, 100 elderly people, aged 60 years and above, were assessed for depression. About half of the elderly (48%) were between the age group of 60 and 70 years and around the other half 52% were above 70 years. The mean age group of the population was 69.4 years. Among them, 54 were male and 46 were female. All of the participants were married and 64% of the study subjects reported that their partner was alive. Sixteen percent (16%) of subjects were illiterate and 30% were not doing any job, so they were dependent on other family members for monetary needs. Majority of the elderly (69%) belonged to upper- and upper-middle-class socioeconomic status according to modified Kuppuswamy classification. Seventy-nine percent (79%) were suffering from various diseases such as diabetes, hypertension, and chronic renal failure. The sociodemographic details of the study population are explained in [Table 1].
|Table 1: Sociodemographic characteristics of the study population (n=100)|
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Prevalence of depression
The overall prevalence of depression was found to be 84%. Among the depressed elderly, 61% had mild depression, 20% had moderate depression, and 19% were suffering from severe depression [Figure 1].
|Figure 1: Distribution of the depressed elderly according to severity of depression|
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The proportion of the elderly with depression was higher in the age group of 70 years and above (98%), female gender (98%), widow/widower (97%), living in nuclear family (90%), literates (89%), unemployed (90%), both socioeconomic status groups (84%), and with morbidities (90%). Age group, gender, death of spouse, educational qualification, occupation, and presence of morbidity were significantly associated with the presence of depression among study participants (P < 0.05) [Table 2].
|Table 2: Association of depression with different characteristics of study population (n=100)|
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| Discussion|| |
In the present study, 84% of the elderly were found to have depression. Various community-based studies across the country have reported depression from as low as 32.4%–77%.,,,, This may be due to differences in the sociodemographic characteristics of people, different sample size, and different scales used in the measurement of depression. 16% of the elderly were found to have severe depression; a similarly high proportion of severe depression (17%) was also reported by Goyal and Kajal in their study on depression in the elderly in South Punjab. In the present study, there was a significant association of depression with the increasing age of geriatric persons. The age group of 70 years and above was found to be more under depression (98%) than 60–69 years' age group. Advancing age is often accompanied by various events in life such as the death of a spouse, retirement, financial dependence, and relocation of residence. Similar findings were observed by certain other studies.,, In the present study, depression was found to be associated more with females as compared to males. Similar observation was made by Ankur Barua et al. in Manipal. and Mullick et al., but few results were contrary to this finding such as Nautiyal et al. and Mandolikar et al. which found that males were more depressed than females. The current study showed that gender was significantly associated with the prevalence of depression.
Everyone needs social connections to survive and thrive. However, as people age, they often find themselves spending more time alone. Loneliness and social isolation are associated with higher rates of depression. Death of spouse had a significant association with the prevalence of depression in our study. In the present study, the widowed had a higher prevalence of depression, compared to those whose spouse was alive. This was in concordance with the findings of studies conducted by Gupta et al. and Naveen et al.
We found that there was a significant association between educational qualification and prevalence of depression among the respondents, surprisingly with literate persons being more depressed. Opposite results were noted from different studies such as Goyal et al. Rathod et al. and Paul et al. Similar result was found in a study by Jayshree et al. where positive correlation was found between educational status and depression. A greater protective effect against mental disorders may be linked to higher education. Those from educated backgrounds are more likely to have healthy lifestyles and the resources to intellectually support them that promote mental health. Higher education can also be considered helpful in attaining more fulfilling careers and higher wages, thus leading to lower risk of depression. Education can be linked to better economic resources and a work environment that can mitigate financial stress, support healthy lifestyles, and hence promote mental health. But in the present study, surprisingly all these factors couldn't help, rather those who were educated were more depressed.
This study showed that financial dependency was significantly associated with the prevalence of depression. Similar findings were noted from studies such as Mullick et al. and Pilania et al. With the loss of a job or retirement, older people often feel the loss of dignity and self-respect. This can result in feelings of loneliness or psychological distress. Socioeconomic status had a significant association with the prevalence of depression in our study and it was the highest in the lower class. Similar findings have been noted from studies conducted in other settings., In the present study, there was a significant association observed between morbidity and prevalence of depression, having the presence of morbidities more commonly associated with depression. Several other studies supported the fact., These comorbidities along with depression increase physical disability, poor compliance, and increased health-care utilization leading to poor quality of life and further complicating the treatment of depression.
The high prevalence of depression observed among older adults emphasizes the need of increased community support and availability of health-care services for better care of the elderly. There is also an urgent need for greater awareness of depression among family members and community at large. At the same time, it is important to increase community support and create networks for better geriatric care, in accordance with the WHO findings. This type of study is important to persuade community-based medical personnel like family physician of the importance of diagnosing and treating depression. When dealing with older adults, health personnel must always keep in mind the possibility of depression; it frequently manifests with somatic symptoms (headache, tension, body ache, etc.) for which patients visit outpatient departments other than psychiatry, seeking relief for their symptoms.
The cross-sectional nature of this study is a limitation, in that causal relationships cannot be inferred. Furthermore, the small sample size limits generalizability, so large-scale studies are needed to find out the importance of other factors such as substance abuse and adverse life events as predictors of depression in elderly population in India. Even the diagnosis of comorbidities was based on history and medical records. Hence, it has limitations over diagnostic criteria as well.
| Conclusions|| |
This study showed that the prevalence of depression among older adults was high; moreover, none of the elderly were diagnosed to be depressed. Increasing age, lack of family support, economic dependence, and comorbid conditions were the major determinants of depression. Hence, depression in the elderly should be taken as a serious issue. Steps such as screening for depression among the elderly should be undertaken to diagnose the cases of depression, and they should be treated and also be given proper counseling sessions to reduce their levels of depression.
The authors would like to thank the study subjects, who enthusiastically participated in the study. The authors also acknowledge faculty members for their motivation and support.
Financial support and sponsorship
Conflicts of interest
There are no conflicts of interest.
| References|| |
Arokiasamy P, Parasuraman S, Sekher TV, Lhungdim H. Study on Global Ageing and Adult Health (SAGE) Wave 1, India National Report. WHO Geneva: International Institute for Population Sciences; 2013.
Ashok BT, Ali R. Aging research in India. Exp Gerontol 2003;38:597-603.
ORGI. Census of India, 2011, Office of the Registrar General and the Census Commissioner of India, Ministry of Home Affairs, Government of India; 2011. Available from: www.censusindia.gov.in. [Last accessed on 2022 Jul 18].
UNFPA (United Nations Population Fund). State of World Population 2019: Worlds Apart. New York: UNFPA; 2019.
ORGI (Various Years), Census of India, Various Years, Office of the Registrar General and the Census Commissioner of India, Ministry of Home Affairs, Government of India. Available from: www.censusindia.gov.in. [Last accessed on 2022 Jul 20].
Miller KE, Zylstra RG, Standridge JB. The geriatric patient: A systematic approach to maintaining health. Am Fam Physician 2000;61:1089-104.
Tasci G, Baykara S, Gurok MG, Atmaca M. Effect of exercise on therapeutic response in depression treatment. Psychiatry Clin Psychopharmacol 2019;29:137-43.
Borson S, Scanlan J, Brush M, Vitaliano P, Dokmak A. The minicog: A cognitive 'vital signs' measure for dementia screening in multilingual elderly. Int J Geriatr Psychiatry 2000;15:1021-7.
Yesavage JA. Geriatric depression scale (GDS). Psychopharmacol Bull 1988;24:709-11.
Sharma R. Revised Kuppuswamy's socioeconomic status scale: Explained and updated. Indian Pediatr 2017;54:867-70.
Nair S, Hiremath SG, Ramesh. Depression among geriatrics: Prevalence and associated factors. Int J Curr Res Rev 2013;5:109-12.
Jain RK, Aras RY. Depression in geriatric population in urban slums of Mumbai. Indian J Public Health 2007;51:112-3.
] [Full text]
Sati P, Sinha MD, Saurabh R. Depression in an older adult rural population in India. MEDICC Rev 2013;15:40-2.
Ranjan S, Bhattarai A, Dutta M. Prevalence of depression among elderly people living in old age home in the capital city Kathmandu. Health Renaiss 2013;11:213-8.
D'souza L, Ranganath TS, Thangaraj S. Prevalence of depression among elderly in an urban slum of Bangalore, a cross sectional study. Int J Interdiscip Multidiscip Stud 2015;2:1-4.
Goyal A, Kajal KS. Prevalence of depression in elderly population in the Southern part of Punjab. J Family Med Prim Care 2014;3:359-61.
] [Full text]
Swarnalatha N. The prevalence of depression among the rural elderly in Chittoor District, Andhra Pradesh. J Clin Diagn Res 2013;7:1356-60.
Rathod MS, Dixit JV, Goel AD, Yadav V. Prevalence of depression in an Urban geriatric population in Marathwada Region of Western India. Indian J Psychol Med 2019;41:32-7.
] [Full text]
Gupta A, Mohan U, Singh SK, Manar MK, Tiwari SC, Singh VK. Screening depression among elderly in a city of Southeast Asia. J Clin Diagn Res 2015;9:LC01-5.
Barua A, Ghosh MK, Kar N, Basilio MA. Depressive disorders in elderly: An estimation of this public health problem. JIMSA 2011;24:193-4.
Mullick TH, Samanta S, Maji B, Sarangi L. Pattern of morbidity and depression among the urban geriatric population: A community-based survey in Bhubaneswar, Orissa, India. Int J Health Allied Sci 2018;7:233-9. [Full text]
Nautiyal A, Satheesh Madhav NV, Ojha A, Sharma RK, Bhargava S, Kothiyal P, et al.
Prevalence of depression among geriatric people in Dehradun City of Uttarakhand, India. J Depress Anxiety 2015;4:208.
Mandolikar RY, Naik P, Akram MD, Nirgude AS. Depression among the elderly: A cross-sectional study in an urban community. Int J Med Sci Public Health 2017;6:318-22.
Naveen KH, Goel AD, Dwivedi S, Hassan MA. Adding life to years: Role of gender and social and family engagement in geriatric depression in rural areas of Northern India. J Family Med Prim Care 2020;9:721-8. [Full text]
Paul NS, Ramamurthy PH, Paul B, Saravanan M, Santosh SR, Fernandes D, et al.
Depression among geriatric population; the need for community awareness. Clin Epidemiol 2019;7:107-10.
Dawane J, Pandit V, Rajopadhye B. Functional assessment of elderly in Pune, India: Preliminary study. Journal of Gerontol Geriatric Research. 2014;3:155-6.
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.
] [Full text]
Konda PR, Sharma PK, Gandhi AR, Ganguly E. Geriatric depression and its correlates among South Indian Urbans. J Depress Anxiety 2018;7:314.
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;3:105-9. [Full text]
[Table 1], [Table 2]