FREQUENCY OF DEPRESSION WITH ASSOCIATED RISK FACTORS AMONG ELDERLY IN TWO TERTIARY CARE HOSPITALS IN RAWALPINDI.
Keywords: Depression, Elderly, Frequency, Geriatric Depression Scale (GDS).
Depression is a disease which has assumed immense public health importance with fast changing life styles and increasing life spans. It is the 2nd leading cause of disability worldwide and the WHO global burden of disease study projections show that depression will be leading Disability Adjusted Life Years (DALYs) by 2020 in developing nations1,2. Although usually depression is under diagnosed and under treated, yet around 350 million people live with depression globally.
Elderly are more susceptible to depression3. It is the most common psychiatric disorder among elderly in Pakistan that cannot be neglected4. Unfortunately, it is not yet perceived as the priority public health problem in this part of the world5. It increases the risk of cardiac disease and suicidal tendency in elderly. Depression reduces elderly's ability to rehabilitate. It is also interesting to note that elderly populations above 55 years with depression have four times higher death rate than those without depression6,7. Due to scientific development and public health awareness life expectancy is increased over the years with more people in elderly phase than before. There is a simultaneous fall in fertility rate. This resulted into a shift leading to increased number of geriatric population. Pakistan with 200 million population and dependency ratio 0.7510 has chronic disease burden attributing 42% of all deaths.
The fate of elderly depression is incomplete recovery with higher relapse3. The elderly having depression show overall poorer social participation than those with heart disease, hypertension or diabetes3. Weaker health system with no specific elderly clinics, declining social moral standards, lack of old age benefits, mechanical life, decreased harmony with nature, competitive life style, disposable culture and injustice all throw the individuals into valley of depression, sometimes for all the life years to follow3. As geriatric depression is under diagnosed so the magnitude of the problem is much greater than what is being reported5.
Table-I: Shows descriptive analysis.
Frequency of Depression###51.6% (n=179)
Gender distribution###Females 58% (n=104)
Median Age (Range)###71 years (61-92)
Most affected Age Group###61-70 years (57%)
Table-II: Shows association of depression with various risk factors along with p-value.
###Yes (%)###No (%)
###Urban###109 (56.4%)###84 (43.6%)
###Rural###70 (45.5%)###84 (54.5%)
###Un Married###5 (83%)###1 (7%)
###Divorced###8 (100%)###0 (0%)###0.00
###Widowed###13 (72%)###5 (28%)
Very few studies on geriatric depression have been conducted so far in Pakistan to address this issue. 34% was the mean prevalence of anxiety and depression in community setup and not among elderly8. A quantitative study was conducted in Karachi, Pakistan and it identified 22.9% prevalence of depression among elderly9. In Pakistan, female gender has been closely correlated with high prevalence of depression as compared to men. A study done in 2006 found that rate of depression among female is double i.e. 30% to that of male which is 15.7%10. Elderly females are more likely to suffer from depression than the males because of intergenerational gap and lack of physical and emotional support in a traditional family system by the younger generation. Besides, death of spouse can break the family system leaving elderly without support.
An empirical study conducted in Karachi reported 33% of prevalence of depression which was double in females than males which was 15.7%11,5. This study is conducted with the objectives to determine frequency of depression among elderly, assess its predictors and to suggest recommendations for prevention.
MATERIAL AND METHODS
This cross sectional analytical study was conducted at Outpatient department of Pak Emirates Military Hospital (PEMH) and Benazir Bhutto Hospital (BBH) from January to March 2018. Taking mean prevalence of 34% from literature review with 95% confidence interval, sample of 347 was selected. Non-Probability Consecutive Sampling was used in which every subject fulfilling the inclusion criteria were included. Data collection tool was Interviewbased structured questionnaire which include age, sex, education, marital status, relation with spouse, having children and financial support. A 15 questioned Geriatric Depression Scale (GDS) was used in the study12. Every desired answer was assigned single score. A score of more than 5 out of 15 was suggestive of depression.
Consenting elderly >60 years of age attending OPD of PEMH and BBH were included while deaf/dumb, blind, terminally ill, having known malignancy and known psychiatric patients other than depression were excluded from the study. Frequencies and percentages were assessed for descriptive analysis while Chisquare was used to determine association among various risk factors.
Table-III: Shows association of depression with various risk factors along with p-value.
###Yes (%)###No (%)
Having Child###130 (46.6%)###149 (53.4%)
No Child###49 (72%)###19 (28%)
Illiterate###41 (59.4%)###28 (40.6%)
Middle###58 (56.3%)###45 (43.7%)
Matric###35 (59.3%)###24 (40.7%)
Intermediate###24 (45%)###29 (55%)
Graduation###7 (41%)###10 (59%)
Masters and above###14 (30.4%)###32 (69.6)
Table-IV: Shows association of depression with various risk factors along with p-value.
Employed###86 (48%)###76 (45.2%)
Un employed###93 (52%)###92 (54.8%)
Yes###89 (49.7%)###71 (42%)
No###90 (50.3%)###97 (58%)
Yes###92 (51%)###82 (49%)
No###87 (49%)###86 (51%)
Out of 347 subjects, 51.6% (n=179) were found to be depressed according to GDS.
Descriptive analysis is shown in table-I.
Females were more depressed than males and male to female ratio was 1:1.4 while median age was 71 years with range of 61-92 years. Most affected age group was 61-70 years (57%).
The bar graph showed the age and gender distribution of depression in elderly. Here we estimate that 61-70 years' age group is more effected and females were more effected than males.
Urban residence, marital status, having no child and educational status came out to be significant factors which is shown in table-II and III.
Out of 193 urban residents, 56% (n=109) were depressed while 43.6% (n=84) were non depressed (p-value=0.03). In marital status, 83, 100 and 72% of the unmarried, divorced and widowed were found to be depressed respectively (p-value=0.00) according to GDS.
Out of total of 68 persons with no child, 72% (n=49) were depressed (p-value=0.01) while educational status also came out to be significant predictor for depression (p-value=0.04) as depression status seemed to be reduced with increase in educational level.
Employment status, ethnicity, known metabolic disorder and nuclear family were not significantly associated with depression as shown in table-IV.
Although depression is usually taken as normal response of aging but it has huge impact on elderly's health13. Elderly depression may become the biggest cause of disease burden among developing nations by 202014. This study was carried out to determine frequency and risk factors of depression among elderly. In our study frequency of depression came out to be 51.6%. There is wide range of prevalence of depression in various studies according to the racial, sociopolitical and cultural factors.
In a previously conducted study, prevalence of depression was 29% of which 6.88% were of major depression13. Studies have revealed that the prevalence rates for depression in community samples of elderly in India vary from 6 to 50%15. The global median prevalence of depression for the elderly was 11.7%16. In our study, females were more effected (58%) than males. Various other studies showed same results. Depression was high in females in multiple studies as 37.5% and 57.1% as compared to males which came out to be 35.3% and 46%17,18. In previous studies, education level and income were main risk factors for depression among elderly. In a study conducted previously depression was high in low socioeconomic group 34%17. In ourstudy, living in urban areas, marital status, educational status and having no children were associated with elderly depression.
A study in Pakistan also reported female gender, elderly without a spouse, low level of education, and unemployment to be independent predictors of depression11. Similar ndings have been reported among the geriatric population in the urban slums of Mumbai19. In a study conducted previously the rate of depression washigher among illiterate/ semiliterate 66.7% than those having secondary/ university education 24.5%20. In another previous study, depression among elderly was significantly associated with illiteracy 0.01521. In our study, having no child was significantly associated with depression (72%) compared to those having children 28%. Similar results were seen in various other studies21,22. Opposite results were found in other studies20. In this study, poor marital relationship (72% and 100%) was significant predictor of depression which is supported by various other studies.
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 above11. A different finding was observed in a study where scores on GDS indicated elevated level of depression symptomology with 67.1% scoring above cut off for depression23.
More than 50% of the elderly patients attending hospital OPD were found to be depressed according to GDS. 71% of the depressed were diagnosed for the first time. Marital status, education, urban residence and having no children were significantly associated with depression while good relation with spouse was having protective effect towards depression.
It is recommended that in case of depression, must seek professional help as it is a treatable condition. Do not take depression as stigma because stigma fades away the confidence that depression is a treatable health issue. Planning to address depressive disorder at primary care level is required. Screening programs for early diagnosis/detection of depression must be initiated not only for effective treatment and recovery but also to avoid long DALYs. Pre marriage counselling of eligible couples must be done to avoid post marital depression syndrome. Awareness raising programs in the form of lectures, seminars and workshops highlighting the importance of this treatable public health issue must be organized even from school level.
The author gratefully acknowledges the help and assistance of the Head of Departments and management staff of the hospitals (PEMH and BBH) in facilitating this study.
CONFLICT OF INTEREST
This study has no conflict of interest to be declared by any author.
1. Tomlinson M, Lund C. Why does mental health not get the attention it deserves? An application of the Shiffman and Smith framework. PLoS medicine 2012; 9(2): e1001178.
2. 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(1): 3-8.
3. Hussain A, Azad SH. Frequency and predictors of depression among elderly of rawalpindi. Pakistan J Postgrad Med Inst 2016; 30(1): 35-40.
4. Cassum LA. Elderly depression in Pakistan: An emerging public health challenge. Intl J Innovative Res Develop 2014; 3(5): 698.
5. Cassum LA. Elderly depression in PakistanAn emerging pub health challenge.pdf. Intl J innovative res development 2014; 3(5): .
6. Fiske A, Wetherell JL, Gatz M. Depression in older adults. Annual review of clinical psychology 2013; 5: 363-89.
7. Organization WH. Global tuberculosis control: WHO report 2001. Global tuberculosis control: WHO report 2001: WHO; 2001.
8. Mirza I, Jenkins R. Risk factors, prevalence, and treatment of anxiety and depressive disorders in Pakistan: Systematic review. BMJ 2004; 328(7443): 794.
9. Alam A, Ibrar M, Khan P. Socio-Economic and psychological problems of the senior citizens of Pakistan. Peshawar J Psychol Behav Sci 2016; 2(2): 249-62.
10. Djernes JK. Prevalence and predictors of depression in populations of elderly: A review. Acta Psychiatrica Scandinavica 2014; 113(5): 372-87.
11. Taqui AM, Itrat A, Qidwai W, Qadri Z. Depression in the elderly: Does family system play a role? A cross-sectional study. BMC psychiatry 2015; 7(1): 57.
12. Ganguli M, Dube 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 (GDSH). Intl J Geriatric Psychiatry 1999; 14(10): 807-20.
13. Pracheth R, Mayur S, Chowti J. Geriatric depression scale: A tool to assess depression in elderly. Intl J Med Science Public Health 2015; 2(1): 31-6.
14. Organization WH. World Organization of Family Doctors Integrating mental health into primary care: A global perspective 2009; 197.
15. Udayar SE, Prasad DV. Epidemiological study of socio demographic factors in relation to depression among the elderly people in a rural area of Chittoor district of Andhra Pradesh, India. Intl J Community Med Public Health 2017; 3(1): 161-5.
16. Barua A, Ghosh M, Kar N, Basilio M. Distribution of depressive disorders in the elderly. J neurosciences rural practice 2010; 1(2): 67.
17. Manjubhashini S, Krishnababu G, Krishnaveni A. Epidemiological study of depression among population above 60 years in Visakhapatnam, India. Intl J Med Science Public Health 2014; 2(3): 695-703.
18. Assil S, Zeidan Z. Prevalence of depression and associated factors among elderly Sudanese: A household survey in Khartoum State 2013.
19. Jain R, Aras R. Depression in geriatric population in urban slums of Mumbai. Ind J Pub Health 2014; 51(2).
20. El Kady H, Ibrahim H. Depression among a group of elders in Alexandria, Egypt. 2016.
21. Arumugam B, Nagalingam S, Nivetha R. Geriatric depression among rural and urban slum community in Chennai - A cross sectional study. J evolution Medical Dental sciences 2015; 2(7): 795-802.
22. Yadav SP, Doibale MK, Aswar N, Inamdar I, Sonkar V, Gadekar R. Assessment of Socio-demographic correlates of depression among the elderly in an urban area in Maharashtra. J Evolution Med Den Sci 2013; 2(51): 9895-901.
23. Cummings S, Sull L, Davis C. Correlates of depres-sion among older Kurdish refugees. Social work 2011; 56(2): 159-68.
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|Publication:||Pakistan Armed Forces Medical Journal|
|Date:||Apr 30, 2019|
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