International Journal of Mental Health & PsychiatryISSN: 2471-4372

All submissions of the EM system will be redirected to Online Manuscript Submission System. Authors are requested to submit articles directly to Online Manuscript Submission System of respective journal.

Research Article, Int J Ment Health Psychiatry Vol: 2 Issue: 2

Mean Scores on Geriatric Depression Scale (GDS) as Indicator of Prevalence of Depression in a Rural Elderly Population in North-West India

Raina SK1*, Chander V1, Bhardwaj A1 and Parasher CL2
1Department of Community Medicine, DR. RPGMC, Tanda, Kangra (Himachal Pradesh) India
2PhD Scholar, Shri Jagdishprasad Jhabarmal Tibrewala University, Rajasthan, India
Corresponding author : Dr. Sunil Kumar Raina
Associate Professor, Department of Community Medicine,DR. RPGMC, Tanda, Kangra, Himachal Pradesh, India
Tel: 09418061066
E-mail: [email protected]
Received: November 05, 2015 Accepted: March 17, 2016 Published: March 21, 2016
Citation: Raina SK, Chander V, Bhardwaj A, Parasher CL (2015) Mean scores on Geriatric Depression Scale (GDS) as Indicator of Prevalence of Depression in a Rural Elderly Population in North-West India. Int J Ment Health Psychiatry 2:2. doi:10.4172/2471-4372.1000117

Abstract

Introduction: Depression constitutes the most prominent of affective disorders encountered in old age. Major depression, found in some 5% of older persons in the community, and minor depression, found in some 10- 20%, is associated with increased risk of physical disability.

Material and Methods: The study was conducted as a survey of all residents aged 60 years and older. A house-to-house survey was conducted to identify individuals eligible for inclusion in the study. All eligible individuals present in their homes on the day of survey and who gave their consent to participate were included in the study.

Results: The mean score on Geriatric Depression Scale (GDS) for the study population was 0.39+1.54 with females scoring slightly higher (0.41+2.25) as compared to males (0.38+1.19). Importantly the GDS scores were found to be highest for the age group 80-89 at 2.14+5.34. The GDS scores showed a significant upward trend as the age advanced.

Conclusions: The mean GDS scores among elderly in Himachal Pradesh is lower indicating a lower prevalence of depression as compared to studies conducted across different parts of world. This could be because joint family norm is still the predominant form of family setting in Himachal Pradesh which helps prevent loneliness and compensates for economic insecurity among elders.

Keywords: Geriatric depression scale; Psychological disability; Elders

Keywords

Geriatric depression scale; Psychological disability; Elders

Introduction

Demographic aging is a global phenomenon. According to the 2011 census, India is home to more than 103 million people aged 60 years and above [1]. This age group, currently comprising only 8.6% of the population, is expected to grow dramatically in the next few decades [2]. A report jointly brought out by United Nations Population Fund (UNFPA) and Help Age International says the following: India’s population is likely to increase by 60 per cent between 2000 and 2050 but the number of elders, who have attained 60 years of age, will shoot up by 360 per cent. India has around 103 million elderly at present and the number is expected to increase to 323 million, constituting 20 per cent of the total population, by 2050 [3]. Further the demographics in India is not uniform with Himachal Pradesh (where this study was conducted) being home to 10.2% of elderly in a total population of 68.65 lakh which is much higher than the national average [4].
Mental and psychological disability among the elderly is a major societal concern. Amongst mental and psychological disabilities, depression is the most prominent of affective disorders encountered in old age. Major depression, found in some 5% of older persons in the community, and minor depression, found in some 10-20%, is associated with increased risk of physical disability [5]. The long term prognosis of geriatric depression is bleak with incomplete recovery and higher relapse rate. In addition to the physiological and psychological changes associated with aging, changes in the associated risk factors also modify the prevalence and prognosis of geriatric depression [6]. According to World Health Organisation (WHO), in 2004 there were 0.5 million adults (age 60 years and above) with moderate or severe depression in high income countries and 4.8 million in low- and middle income countries [7]. Studies across nations have reported on varied prevalence with 5.1% in Mexico, 3.6% in the United States and 19.8-33.5% in Japanese communities reporting depression [7]. Studies conducted across India have also reflected on this variation in prevalence of depression among geriatric population [7-9].
The current study was planned with the aim to evaluate mean scores on Geriatric Depression Scale (GDS) among elderly as indication of prevalence of depression among rural elderly in Himachal Pradesh. It is important to estimate the prevalence in Himachal Pradesh as the proportion of elderly (individual aged more than 60 years) is higher than the proportion of elderly at national level [4]. Added to this is the fact that Himachal Pradesh is a predominantly rural state with less than 10% of its population living in urban areas [4].

Methods

The study was conducted in a rural area of Himachal Pradesh state in India. The state of Himachal Pradesh situated in the north western Himalayas extends between 32°22’-33°12’N, and 75°45’- 79°04’E covering an area of 56,090 km2. Topography of the state is dominantly mountainous with the altitude ranging between 350 and 6,975 m. The state has a total population of 6,856,509 and 90.2% people live in rural setup [4].
Tehsil Palampur and its adjoining area, covering a population of 10,000 individuals was included in the study [4]. The study was conducted as a survey of all residents aged 60 years and older. A house-to-house survey was conducted from July 2013 through October 2014 to identify individuals eligible for inclusion in the study. All eligible individuals present in their homes on the day of survey and who gave their consent to participate were included in the study. A total of 710 consecutive individuals from a total population of 10,000 were identified for the purpose of this study from already defined geographical area (Palampur). Out of 710 elderly individuals approached, only 697 consented to participate in the study giving us a response rate of 98%. The interviews were conducted by a social scientist (CLP) in participants homes with participants asked to provide informed written consent. Next of kin was asked to provide written agreement in the event of lack of capacity to consent. A detailed history of the sociodemographic profile of the study population including details on demography, occupation, was enquired. A Short Form geriatric depression scale (GDS) consisting of 15 questions was used as a primary screen [10]. The Short Form is more easily used by physically ill and mildly to moderately demented patients who have short attention spans and/or feel easily fatigued.The GDS was been found to have a 92% sensitivity and a 89% specificity when evaluated against diagnostic criteria. The validity and reliability of the tool have been supported through both clinical practice and research. There are many instruments available to measure depression, the Geriatric Depression Scale (GDS), first created by Yesavage, et al., has been tested and used extensively with the older population [10]. A GDS- 15 score of 5-9 was taken as possible depression; above 9 usually indicates depression.
Statistical analysis
Depression was the dependent variable while sociodemographic factors were the independent variables. The data entry and analysis was performed by using SPSS version 17. Frequency distribution was calculated for all variables and “Kendall’s tau” test was used to test the significance of association.

Results

As part of the field survey, a total of 697 individuals irrespective of the sex of the individuals were included in the study. The baseline characteristics of the population surveyed revealed that majority (512/697; 73.5%) of them were male (Table 1). A higher percentage (66.7%) of individuals belonged to the age group 60-69 years with a mean age of 64+2.72 years. A total of 13 (13/697; 1.8%) individuals above 60 years of age reported with a score above 5 indicating possible depression.
Table 1: Showing the age profile of the study sample.
The mean GDS score for the study population was 0.39+1.54 with females scoring slightly higher (0.41+2.25) as compared to males (0.38+1.19)(Table 2). Importantly the GDS scores were found to be highest for the age group 80-89 at 2.14+5.34. The GDS scores showed an upward trend as the age advanced (Table 3). However the result was not statistically significant. As a subgroup females in the age group of 80-89 had the highest GDS scores (7.50+8.02). An analysis of mean GDS scores among different education levels did not reveal a uniform trend with illiterate population scoring the highest (2.50+5.71). An analysis of GDS scores among different occupations reveals that the score was higher among unskilled workers as compared to other occupations (Table 4). A similar analysis of family income and mean GDS scores also revealed a non-uniform trend. However, interestingly the middle income population (with family income/month of 5050-6749) scored highest (0.96+3.17). Important to note however thatanalysis of the role of socio-demographic variables on depression using regression equation reveals that income is significantly associated with depression (Table 5).
Table 2: Showing the mean GDS scores in different age and sex groups.
Table 3: Showing the increase in GDS scores as the age increases.
Table 4: Showing the mean GDS scores in different education, occupation and income groups.
Table 5: Showing Regression analysis to check the influence of socio-demographic variables on depression (GDS as dependent variable).

Discussion

The increase in the proportion of the ageing population over last few decades represents a significant shift in the demographics of India. With an increase predicted for coming decades, this may become more significant. The number of older people living in resource poor settings like Africa, Asia and Latin America is much higher at 59% than developed countries [11]. The developing world has the largest absolute number of older adults and is experiencing the largest percentage increase. Within these numbers are also certain vital factors. Women outlive men; only 15% of centenarians are men. Men also remarry more frequently than do women; consequently, older women are frequently single and live alone. Women are more likely to have inadequate financial resources. Women also spend a greater proportion of their surviving years being disabled than do men [11]. The prevalence of depression reported by our study is much lower than earlier studies conducted by other authors among geriatric populations in India with studies reporting prevalence as high as 60% [6-9].
A systematic review by Ankur Barua et al., on 74 community-based mental health surveys on depression in geriatric population found it significantly associated with age and potentially some modifiable risk factors like low socioeconomic status, loss of spouse, living alone, chronic co-morbidities were also had a significant association with depression [8]. In our study we made use of mean GDS scores to establish an association between various socio-demographic factors and depression. Increasing age was a factor which led to increase in the GDS scores which may be linked to inadequate financial resources with increase in age. Study conducted in Tamil Nadu, India has also identified advanced age as significantly associated with depression [8]. In addition the study had also identified sex, education, monthly income among other factors as significantly associated with depression [8]. Economy was also identified as a factor for increased levels of depression among elderly according to a study conducted in a rural south Indian community [6]. The study identified; low income, experiencing hunger within the previous one month, having diabetes, cardiac illness, transient ischemic attacks and head injury as correlates of geriatric depression [6]. Further older females in our study had a significantly higher GDS score probably because women in our study sample lived longer than their male counterparts. Older women are frequently single and live alone. Although the results indicate that the GDS scores differ on different levels of education, there is no linear pattern for this relationship. GDS score was highest for lower education and is in line with the systematic review conducted by Ankur Barua et al. [8]. Again GDS scores differ on different levels of occupation; there is no linear pattern for this relationship too, with unskilled workers showing highest scores. Trends with regard to income are similar to education and occupation with no linear pattern found. Interestingly middle income groups score the highest.
It is very important to assess the magnitude of depression in elderly population because depression in later life is not just costly but because of its influence on reduction of life satisfaction and quality. It also leads to social deprivation, loneliness and increased use of homecare services which puts a huge burden on our health care setup.

Conclusion

The mean GDS scores among elderly in Himachal Pradesh is lower indicating a lower prevalence of depression as compared to studies conducted across different parts of world. There is a scarcity of data on depression from the rural areas of less developed regions of sub-Saharan Africa and South Asia. Studies such as the one conducted by us in a predominantly rural population may help identify potential preventive factors responsible for differential distribution of depression across populations. For our study population the factor favouring low prevalence of depression could be the joint family norm. Joint family norm is still the predominant form of family setting in Himachal Pradesh which helps prevent loneliness and compensates for economic insecurity among elders.

Limitations

The study primarily focussed on screening for prevalence of depression using GDS and therefore may have missed on the actual prevalence of depression. Conducting the study in a two phase survey design mode with second phase involving clinical examination of all individuals scoring above 5 on GDS and a random subsample of those scoring less than 5, would be increased the validity of the tool and the study.

References












Track Your Manuscript