Indian Journal of Psychiatric Nursing

ORIGINAL ARTICLE
Year
: 2018  |  Volume : 15  |  Issue : 2  |  Page : 42--45

Prevalence of depression among geriatric population


Sindhu Gopal1, Meena Chacko2, Punita A Sharma1, D Mitra2,  
1 Faculty, College of Nursing, AFMC, Pune, India
2 Faculty, College of Nursing, CH(EC), Kolkata, India

Correspondence Address:

Abstract

Background:Life expectancy has increased in India, elderly population is currently the second largest in the world and 20% of illness in the elderly is due to mental or a neurological illness and the most common being dementia and depression. Aim of the study was to assess the prevalence of depression among geriatric population attending OPD of selected tertiary hospitals. Methods: A cross sectional descriptive study was conducted on 120 geriatric population attending Out Patient Departments of selected tertiary care hospital selected by stratified simple random sampling method. Tools: The questionnaire included section I, socio demographic data and section II Geriatric Depression Scale Short Form(GDS-SF). Ethical clearance obtained from institutional research ethical committee. Permission was obtained from tertiary hospital and informed consent was taken. Results: Prevalence of depression was 24.2%. Conclusion: with the gradual greying of population expected in India over the coming time, maintaining a good quality of life for the senior citizens is the need of the hour.



How to cite this article:
Gopal S, Chacko M, Sharma PA, Mitra D. Prevalence of depression among geriatric population.Indian J Psy Nsg 2018;15:42-45


How to cite this URL:
Gopal S, Chacko M, Sharma PA, Mitra D. Prevalence of depression among geriatric population. Indian J Psy Nsg [serial online] 2018 [cited 2022 Nov 26 ];15:42-45
Available from: https://www.ijpn.in/text.asp?2018/15/2/42/262450


Full Text



 Introduction



Life expectancy has increased in India over the last 70 years. In 1951, life expectancy at birth was 36.7 years and as per the recent data of 2012, it is reported to be about 67 years.[1] Resultantly, the proportion of the elderly population in India has risen from 5.6% in 1961 to 8.5% in 2011.[2] According to 2016 report by the ministry for statistics and programme implementation, India has 103.9 million elderly people above age 60,about 8.5 percent population.[3] The Indian aged population is currently the second largest in the world and is projected to rise from 70 million, according to the National Census of 2011, to almost 324 million by the year 2050, with serious social, economic and public health consequences.[4] Elderly will form 19% of the total population.[5]

Geriatric psychiatry is concerned with preventing, diagnosing and treating psychological disorders in older adults. Persons with a healthy mental adaptation to life are likely to live longer than those stressed with emotional problems. Studies have shown that 5% of people seeking help in a tertiary care or general hospital setting happen to be older than 60 years. A recent study using Geriatric Depression Scale[6] reported a prevalence of 45.9%. Similar rates were reported from West Bengal[7] and Uttar Pradesh [8]. A study from a rural community near Vellore in Tamil Nadu9 reported a prevalence of 12.7% for depression.

 Materials And Methods



This was a cross sectional descriptive study that was conducted in the OPDs of selected tertiary hospitals of Pune for a period of 6 weeks. Stratified simple random sampling was used.

Inclusion criteria

  • □ Age more than 60 yrs, attending OPD
  • □ Willing to participate


Exclusion criteria

  • □ Person suffering from Acute Delirium , HIV infection, head injury, Post stroke, SOL/CNS infections
  • □ major mental illness, oncological conditions and recent bereavement .


Sample Size : Sample size was 120 (calculated from the previous studies using the formula (n = 117))

Tools:

  • The Section- I data sheet consisted of demograpgic and selected variables such as age, gender, education, marital status, mobility, living arrangements, medic al illness, family income,individual income.
  • Section- II is the Geriatric Depression scale which has 15 items and is a standardized scale.


Analysis of data: Fischer’s exact test is used for inferential statistics and SPSS 19 version is used for statistical analysis.

Ethical aspects

Permission was taken from the head of the institutions where the study was conducted. Ethical clearance from institutional committee was obtained. Written Consent from participants taken.

 Results



{Table 1}{Table 2}

 Discussion



Description of the Socio demographic variables

In the present study 76.7% were males and 23.3% were females, in contrast with a study by Anita Bhaskar et al (2014)10.There were 43% males and 57% females among the subjects.Males accounted for 63.7% in a study by Bodhare et al(2013)11 which is similar to the present study.

In the present study the age group was divided into three class intervals. The majority of the subjects were in the age group 60-70 yrs (61.7%), and minimum were in the age group of >80 (8.3%). Mean age of the population was 65.75 ± 5.78 years, with male having mean age of 66 ± 5.9 years and female 65 ± 5.7 years,in a study by Inderjeet Gambhir (2014)12 which is similar to the present study. Majority had education up to secondary(66%). Postgraduates were 5%. A study by Anita Bhaskar 10 reported primary level of education >50%. Married were 82.5% and 11.7%widow/widower. Widowed (22.54%) were there in a study by Swapnil Yadav(2015)13. Most were 80.8% ambulatory and 18% were ambulatory with support.

23.9% had family income>Rs.20000 and 17.9% had no family income, 28.9% had no individual income whereas 27.2% had individual income >Rs.10000.

Assessing the prevalence of Depression among geriatric population

Out of 120 subjects 03(2.5%) had severe depression, 04 (3,3%) had moderate depression 22(18.3%) had mild depression, and 91(75.8%) had no depression,. The total prevalence of depression was 24%.In a study by Sankar etal(2011)14 41.2% were normal, 37.8% were having mild depression and 21% were severely depressed. Similar prevalence was reported by the study done by Barua A and Kar N(2002)15 as the prevalence of depression in elderly population was determined to be 21.7% (95% CI = 18.4 - 24.9).

Prevalence of depression was found to be 36% in urban poor locality of Bengaluru as per a study by Sanjay TV et al(2012)16, which is higher than the present study.

The overall prevalence of depression in elderly Chinese people was found to be 24.3% (95% CI: 20.8%–28.3%)(Giri M,Chen T 2016)17.

Association of depression with the Socio demographic variables

In the study done by by Naveen Kumar D, Sudhakar TP (2013)18 prevalence of depression was 44.8% (51.0% women, 39.6% men); with relation to age, gender, literacy and economic status, there were significant differences observed.

In terms of socio-demographic variables, female gender, widowed state, unemployed condition, low social class, nuclear family, living alone, physical illness and sensory deficits were significantly associated with depression in old age as per the study by Ramachandran(1982)19.Other studies by Seby K et al, Javed S et al and Kamble SV et al20 showed high level of depression among females as compared to males and this difference was statistically significant in their studies showing sex as a risk factor associated with depression.

In the present study 18% married, 40% unmarried, 57% widows and 50% divorcees had depression. (p value - 0.003(<0.05)). Hance there is significant association exists between depression and marital status. It is found that marital status, increasing age, and cognitive impairment were associated with high risk of late-life depression.(Giri M.2016).17 Similar findings have been reported among the geriatric population in Pakistan..(Taqui AM 2007).21. On the contrary, a study by Prasanth AK et al (2015)22 the major factors influencing depression based on probability were financial fear and income insufficiency. The prevalence was 58.5%.Similarly, Socio-demographic correlates like age, living arrangement, working status, chronic illness were significantly associated with depression(P<0.05) among elderly in the study by Swapnil Yadav(2013).13 Almost 34% respondents were suffering from depression who were living alone as compared to 11.52% found among those who were living with their family.

In the present study the 50% of study subjects were staying alone, 20% with family and 80% stay by other means had depression. (p value - 0.006(<0.05)).So there is significant association exists between depression and living arrangement. In the present study 24% had depression along with hypertension, 29% had mild depression with heart disease,20%had depression along with diabetes,18%had mild-moderate depression in renal illness,33% had depression with orthopaedic problems,67% had mild depression with gynaecological problems. p value - >0.05 .There is no significant association between depression and medical illness.

A study by Swapnil Yadav(2013)13 shows out of total 141 (52.22%) respondents who were suffering from different types of chronic morbidities like diabetes, hypertension, visual impairment, loco motor disabilities etc, 21.28% respondents showed presence of depression.

 Conclusion



All health care professionals who deal with older people should be able to administer a short depression screening test suitable for their workplace, and be aware of its limitations. They should also be aware of the longer tests available and their potential for a more in depth assessment.The present study found a significant proportion of the elderly population having depressive symptoms. Several important risk factors were found to be associated with depression. Identification of these risk factors among the elderly population and their use to identify the individuals at higher risk for them can help the health care providers to plan for better care of the geriatric population and reduce the severity of the occurrence of these diseases among them. Knowing the prevalence rate of depression in elderly, together with the associated factors may inform policy makers and aid in designing better geriatric friendly health services.

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