|Year : 2010 | Volume
| Issue : 2 | Page : 87-92
Socio-demographic factors of geriatric depression
Ankur Barua1, MK Ghosh2, N Kar3, MA Basilio4
1 Department of Community Medicine, Melaka-Manipal Medical College, Melaka, Malaysia
2 Department of Community Medicine, Sikkim-Manipal Institute of Medical Sciences, Sikkim, India
3 Department of Psychiatry, Corner House Resource Centre, Wolverhampton, United Kingdom
4 Department of Psychology, Saint Mary's University, Bayombong, Nueva Vizcaya, Philippines
|Date of Web Publication||1-Apr-2011|
Department of Community Medicine, Melaka-Manipal Medical College (MMMC), Jalan Batu Hampar, Bukit Baru, 75150 Melaka
Source of Support: None, Conflict of Interest: None
| Abstract|| |
Background: Depression is a common mental health problem in geriatric population and the overall prevalence rate of depression in this age group varies between 10 and 20%. Objective: To study the socio-demographic factors associated with depression in geriatric population. Materials and Methods: A systematic review was done on 74 community-based mental health surveys on depression in geriatric population, which were conducted in the continents of Asia, Europe, Australia, North America, and South America. All the studies were conducted between 1955 and 2005. The researchers had included only community-based cross-sectional surveys and some prospective studies that had not excluded depression on baseline. These studies were conducted on homogenous community of geriatric population in the world, who were selected by simple random sampling technique. A qualitative analysis was conducted to study the socio-demographic factors of depression. Results and Conclusion: The two non-modifiable risk factors found to be significantly associated with depression in geriatric population were "older age group" and "female gender". However, the potentially modifiable risk factors for depression in the geriatric population were identified as low socioeconomic status, loss of spouse, living alone, chronic co-morbidities, cognitive impairment, bereavement and restricted activities of daily living (ADL).
Keywords: Depression, factors, geriatric, prevalence, socio-demographic
|How to cite this article:|
Barua A, Ghosh M K, Kar N, Basilio M A. Socio-demographic factors of geriatric depression. Indian J Psychol Med 2010;32:87-92
|How to cite this URL:|
Barua A, Ghosh M K, Kar N, Basilio M A. Socio-demographic factors of geriatric depression. Indian J Psychol Med [serial online] 2010 [cited 2020 Feb 26];32:87-92. Available from: http://www.ijpm.info/text.asp?2010/32/2/87/78503
| Introduction|| |
The World Health Organization estimated that the overall prevalence rate of depression in geriatric population generally varies between 10% and 20% depending on cultural situations. , The community-based mental health studies in India have revealed that the point prevalence of depression in geriatric population Indian population varies between 13% and 25%. ,
According to the observations made by the World Health Organization, the factors of depression in old age are reported as genetic susceptibility, chronic disease and disability, pain, frustration with limitations in activities of daily living (ADL), personality trait (dependent, anxious or avoidant), adverse life events (widowhood, separation, divorce, bereavement, poverty, social isolation) and lack of adequate social support. ,
| Materials and Methods|| |
This was a retrospective study based on systematic review on prevalence of depression in geriatric population.
Community-based mental health surveys on depression in geriatric population, conducted in the continents of Asia, Europe, Australia, North America, and South America, were included in this analysis.
All the studies that were conducted and published in indexed journals between 1955 and 2005 (i.e., within the last 51 years) constituted the sample.
All published articles on prevalence of depression in geriatric population that were available, adequately analyzed and accessible from the Internet, the Central Library of Kasturba Medical College, Manipal, Karnataka, and the Central Library of Sikkim-Manipal Institute of Medical Sciences (SMIMS), Sikkim, constituted the study universe.
The search engines that were utilized for electronic data from the Internet were MEDLINE, PUBMED, GOOGLE, YAHOO, EMBASE, PsycINFO and the Cochrane Collaboration Database for original human research articles in the English literature published through 1 January 1955 and 31 December 2005, using the two sets of search items: "Prevalence of Depression in Geriatric Population" and "Prevalence of Geriatric Depression".
Only those studies that either covered the total population of study area or applied simple random sampling method to identify the study subjects in their corresponding research projects were included for this final systematic review.
To avoid undesired bias due to design effects from various epidemiological study designs, the researchers had included only community-based cross-sectional surveys on prevalence of depression and some prospective study designs that had not excluded depression on baseline. All these studies were conducted on homogenous community of geriatric population in the world, who were either selected by simple random sampling technique or covered under whole population of the study area. For determining the various factors of depression in geriatric population, only those articles in which at least one risk factor of depression was studied were included.
All the unpublished reports and unavailable or unanalyzed or inaccessible articles from the Internet as well as the Central Library of Kasturba Medical College, Manipal in Karnataka and Central Library of SMIMS, Sikkim, on studies regarding the prevalence of depression in geriatric population were excluded from this study.
Studies conducted on migrant populations, old age homes and health care institutions were also excluded from this systematic review in order to avoid biasness. High prevalence rate of depression was very common among isolated groups of individuals in the community, who had migrated to some other place either due to political force or to meet their physiological or financial needs.
Selection of articles
In the first step, while searching through all the selected databases, the key words "depression," "prevalence", "risk factor", "geriatric population", "elderly" and "aged" and the text word "community" were used. In the second step, after applying the inclusion and exclusion criteria, all relevant articles (judged on the basis of the title and abstract) were retrieved for more detailed evaluation. In the third step, the bibliographies of relevant articles were searched for additional references. Finally, all retrieved articles were screened to determine which one of these met the following six inclusion criteria: 1) original research published in English, 2) study group of community residents, 3) subjects age 60 years or older, 4) cross-sectional study design that included both old and new cases of depressed geriatric individuals in the community, 5) prospective or follow-up studies that have not excluded the depressed geriatric individuals at the baseline and 6) acceptable definition of depression (either recognized diagnostic criteria or cut-off on a depression rating scale).
Clinical Diagnoses by Psychiatrists were based on DSM-III-R, DSM-IV and ICD-10 criteria. Other standardized study instruments used were Geriatric Mental State Examination (GMS), AGECAT, Composite International Diagnostic Inventory (CIDI-SF), CES-D, BDI, HDS, Yesavage Geriatric Depression Scale, Centre for Epidemiologic Studies Depression Scale, Mini Mental Status Examination (MMSE), Hamilton Depression Scale (HDS/HAMD), Clinical Rating Scale for Depression, Mini Mental Status Examination and Geriatric Depression Screening Scale and Mastering Depression In Primary Care Version 1998.
Assessment of validity
The validity of each of these study instruments was verified with its individual validity and reliability reports and reconfirmed with the renowned psychiatrists. Some of the studies used the clinical assessment by the individual psychiatrists and the diagnostic criteria were never mentioned. In these cases, the impact factor of the journal where the research article got published was taken into consideration for assessing the quality and standard of research.
Data collection procedure
The investigators were trained by the renowned psychiatrists of Kasturba Medical College Manipal, Karnataka, and SMIMS on how to interpret the results from different community-based psychiatric evaluation studies. At the beginning, a Pilot study was conducted with randomly chosen data from 10 original research articles that surveyed geriatric individuals in the age group of 60 years and above, residing in various parts of the world. After applying the inclusion and exclusion criteria, some of these studies used in the Pilot study were included for statistical analysis in the final research project.
Abstraction of data
Information about the size of the study group, subjects' age, sampling method, criteria for depression, exclusion criteria at baseline, length of study period, number of prevalent cases of depression, and risk factors was abstracted from each report.
A qualitative analysis was conducted for studying the various socio-demographic factors associated with depression in geriatric population.
| Results and Discussion|| |
The search strategy yielded 896 potentially relevant studies; among these, 143 were retrieved for more detailed evaluation. Though 77 studies met the inclusion criteria, we could retrieve main article or structured abstract for only 74 studies which were included for the final analysis. So, only 3 (4%) potentially relevant studies could not be included due to their lack of inaccessibility and unavailability of relevant information elsewhere. Among these 74 selected articles, which formed the study universe for this systematic review of depression in geriatric population, 69 (93.2%) had cross-sectional study design and 5 (6.8%) had prospective study design that had not excluded depression on baseline.
Two meta-analysis reports, one by Chen et al. on 10 relevant studies and the other one by Copeland et al. on 14 relevant studies, and also, a systematic review report by Beekman et al. on 34 relevant studies were included in this meta-analysis project. So, this study had actually taken into consideration the prevalence rates of depression in geriatric population from [74+(10+14+34)=132] survey reports from various parts of the world.
Report from the selected 74 articles was used for estimation of median prevalence of depression in geriatric population; only 24 studies were shortlisted for analysis of factors of depression in geriatric population as they had focused on at least one risk factor in detail. All other studies were excluded for the following reasons: many did not meet the age criterion, many did not provide detailed information on criteria for confirmation of diagnosis and standard case definition, many were institution-based studies or conducted on migrant population, some study designs were not cross sectional, some had inadequate sample size or faulty sampling technique, some were prospective studies that had excluded depression at baseline, and some did not meet two or more of the inclusion criteria.
Assessment of factors of depression in geriatric population
Twenty different risk factors were studied by univariate analysis in 24 selected articles. Among these, 14 were in three or more positive studies and 6 were in two positive studies each. Older age group, female gender, chronic co-morbidities, less education, unemployed status in the past, low socioeconomic status, cognitive impairment, unmarried status, loss of spouse, living alone, bereavement, restricted ADL, and vision or hearing or functional impairment were identified as risk factors for depression in at least two studies each. Among these, only "older age group" and "female gender" were considered as non-modifiable risk factors, while the rest were considered as modifiable risk factors in this study.
Nine risk factors were studied by multivariate analysis in eight articles [Table 1]. Among these, four were in three or more positive studies and five in two positive studies each. Older age group, female gender, chronic co-morbidities, low socioeconomic status, cognitive impairment, loss of spouse, living alone, bereavement and restricted ADL were identified as independent risk factors for depression in at least two studies each. Risk factors identified by both univariate and multivariate analysis in at least two studies each included all of the above except unmarried status, low literacy level and unemployment.
Here, 20 different risk factors were studied by univariate analysis from 24 selected articles. Among these, older age group, female gender, chronic co-morbidities, less education, unemployed status in the past, low socioeconomic status, cognitive impairment, unmarried status, loss of spouse, living alone, bereavement, restricted ADL, and vision or hearing or functional impairment were identified as risk factors for depression in geriatric population. These findings are documented from some important studies mentioned below.
Studies conducted by Copeland et al.  Ramachandran et al.  Penninx Brenda et al.  Broadhead et al.  Kennedy Gary et al.  Schoevers et al.  Liu et al.  Steffens David et al.  Chong et al.  Kirby et al.  Beekman et al.  Copeland et al.  Braune  Ostbye  Mine Ekinci et al.  and Newman et al.  had documented a high prevalence of depression among the geriatric females.
Chong et al.  Liu et al.  Kennedy Gary et al.  Penninx Brenda et al.  Kay et al.  Schoevers et al.  Braune  Roberts et al.  Newman et al.  and Barua et al.  had reported a high prevalence of depression among the individuals aged above 74 years.
Studies conducted by Kennedy Gary et al.  Penninx Brenda et al.  Ramachandran et al.  Schoevers et al.  Liu et al.  Chong et al.  Mine Ekinci et al.  and Lobo et al.  had reported a significantly high prevalence of depression among individuals with lower level of education.
Studies conducted by Ramachandran et al.  Kennedy Gary et al.  Blazer et al.  Broadhead et al.  Beekman et al.  and Penninx Brenda et al.  reported a significantly higher prevalence of depression in geriatric population belonging to the low socioeconomic status group.
Studies conducted by Kennedy Gary et al.  Liu et al.  Ramachandran et al.  Broadhead et al.  and Chong et al.  had documented a significantly high prevalence of depression among the singles who were either unmarried or widowed.
Blazer Dan et al.  Kennedy Gary et al.  Ramachandran et al.  Liu et al.  Chen et al. , and Chong et al.  had observed a significantly high prevalence of depression among those living alone.
Broadhead et al.  Ramachandran et al.  and Kennedy Gary et al.  had reported a high prevalence of depression among the unemployed individuals.
Kennedy Gary et al.  Chen et al. and Barua et al.  had reported a significantly high prevalence of depression among those who had a history of death in their family within the last 6-12 months.
Kennedy Gary et al.  and Barua et al.  had observed a high prevalence of depression in individuals of geriatric population, who were suffering from four or more co-morbid chronic conditions that included diabetes, arthritis, bronchial asthma/chronic obstructive pulmonary disease (COPD), cerebro-vascular accidents (stroke), mental disorders and visual, hearing and functional impairments.
Presence of chronic co-morbidities associated with depression in geriatric population was also reported from studies conducted by Penninx Brenda et al.  Liu et al.  Braune  Ostbye  Mine Ekinci et al.  Roberts et al.  Chen et al. , and Pahkala et al. 
The univariate analysis from 11 studies on various chronic co-morbid conditions associated with depression in geriatric population revealed that arthritis, cognitive impairment, visual impairment, functional impairment and restricted ADL had significant association with depression in geriatric population. Majority of these findings were consistent with the observations by Penninx Brenda et al.  Iowa, East Boston, New Haven and Barua et al. 
The prevalence of depression often followed an increasing trend as the number of co-morbid chronic conditions increased and this trend was also found to be statistically significant in the studies conducted by Kennedy Gary et al.  and Barua et al.  where the prevalence of depression was highest among those with four or more co-morbid chronic conditions and this difference as compared with other groups was found to be statistically significant.
[Table 1] shows the major factors of depression in geriatric population from multivariate analysis using the Multiple Logistic Regression Model. Here, nine risk factors were studied by multivariate analysis in eight articles. Among these, older age group, female gender, chronic co-morbidities, low socioeconomic status, cognitive impairment, loss of spouse, living alone, bereavement and restricted ADL were identified as independent risk factors for depression in at least two studies each. The potential confounders were low literacy level, unmarried status, and unemployed status in the past. Majority of these findings were consistent with the observations made by Kennedy Gary et al.  and Barua et al. 
|Table 1: Prevalence of depression in geriatric population according to the major factors: Multivariate analysis |
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There was heterogeneity in the results for some risk factors (i.e., lower education level, functional impairment, cognitive impairment, chronic co-morbidities), perhaps related to different definitions of these variables in different studies and small study groups in some studies; consequently, the results of the systematic review for these risk factors must be interpreted cautiously. 
It was observed that a large proportion of depression in geriatric population people in the community was attributed to one of these risk factors. Since these risk factors are frequent in geriatric population age group, their modification could be expected to have an important public health impact. Geriatric population could be screened to identify individuals at high risk of depression. Subsequently, these individuals could be targeted for interventions to abate the three potentially modifiable risk factors and reduce the risk of depression. Such interventions might include education about the significance of the risk factors, bereavement counseling and support, new skills training, "maintenance of routines" protocols, enhancement of social supports, individual or group therapy to facilitate adjustment to loss of function, and sleep enhancement protocols. 
| Conclusions|| |
In this systematic review, the potentially modifiable risk factors for depression in geriatric population were identified as low socioeconomic status, loss of spouse, living alone, chronic co-morbidities, cognitive impairment, bereavement and restricted ADL. Despite the methodological limitations of individual studies, these findings might guide efforts to develop effective interventions for preventing geriatric depression.
| References|| |
|1.||Rangaswamy SM, editor. The World Health Organization. World Health Report: Mental Health: New understanding New Hope. Geneva: The institute; 2001. |
|2.||Wig NN. World Health Day, 2001. Indian J Psychiatry 2001;43:1-4. |
|3.||Nandi DN, Ajmany S, Ganguli H, Banerjee G, Boral GC, Ghosh A, et al. The Incidence of mental disorders in one year in a rural community in West Bengal. Indian J Psychiatry 1976;18:79-87. |
|4.||Ramachandran V, Menon Sarada M, Arunagiri S. Socio-cultural factors in late onset depression. Indian J Psychiatry 1982;24:268-73. |
|5.||Kennedy GJ, Kelman HR, Thomas C, Wisniewski W, Metz H, Bijur PE. Hierarchy of characteristics associated with depressive symptoms in an urban elderly sample. Am J Psychiatry 1989;146:220-5. |
|6.||Copeland JR, Beekman AT, Dewey ME, Hooijer C, Jordan A, Lawlor BA, et al. Depression in Europe. Br J Psychiatry 1999;174:312-21. |
|7.||Penninx Brenda WJ, Leveille S, Ferrucci L, Eijk JT, Guralnik JM. Exploring the effect of depression on Physical disability: Longitudinal evidence from the established populations for epidemiologic studies of the elderly. Am J Public Health 1999;89:1346-52. |
|8.||Broadhead WE, Blazer Dan G, George Linda K, Tse CT. Depression, disability days, and days lost from work in a prospective epidemiologic survey. J Am Med Assoc 1990;264:2524-8. |
|9.||Schoevers RA, Beekman AT, Tilburg WV, Deeg DJ, Jonker C, Geerlings MI, et al. Association of depression and gender with mortality in old age. Br J Psychiatry 2000;177:336-42. |
|10.||Liu CY, Wang SJ, Teng EL, Fuh JL, Lin CC, Lin KN, et al. Depressive disorders among older residents in a Chinese rural community. Psychol Med 1997;27:943-9. |
|11.||Steffens DC, Skoog I, Norton MC, Hart AD, Tschanz JA, Plassman BL, et al. Prevalence of depression and its treatment in an elderly population. Arch Gen Psychiatry 2000;57:601-7. |
|12.||Chong MY, Tsang HY, Chen CS, Tang TC, Chen CC, Yeh TL, et al. Community study of depression in old age in Taiwan. Br J Psychiatry 2001;178:29-35. |
|13.||Aisling D, Kirby M, Bruce I, Cunningham C, Coakley D, Lawlor BA. Three-year prognosis of depression in the community-dwelling elderly. Br J Psychiatry 2000;176:453-7. |
|14.||Beekman AT, Copeland JR, Prince MJ. Review of community prevalence of depression in later life. Br J Psychiatry 1999;174:307-11. |
|15.||Copeland JR, Beekman AT, Braam AW, Dewey ME, Delespaul P, Fuhrer R, et al. Depression among older people in Europe: The EURODEP studies. World Psychiatry 2004 February; 3(1):45-9. |
|16.||Braune BT, Berger K. The influence of depressive mood on activities of daily living and health care utilization in the elderly - The MEMO study on the KORA platform Augsburg. Gesundheitswesen 2005;67:S176-9. |
|17.||Ostbye T, Kristjansson B, Hill G, Newman SC, Brouwer RN, McDowell I. Prevalence and predictors of depression in elderly Canadians: The Canadian study of health and aging. Chronic Dis Can 2005;26:93-9. |
|18.||Ekinci M, Gulbu T, Ayse O, Serap S. The prevalence of depression in elderly living at home in Eastern Turkey: Erzurum. Int J Hum Sci 2004;1:1-10 |
|19.||Newman SC, Bland RC, Orn HT. The prevalence of mental disorders in the elderly in Edmonton: A community survey using GMS-AGECAT. Can J Psychiatry 1998;43:910-4. |
|20.||Kay DW, Henderson AS, Scott R, Wilson J, Rickwood D, Grayson DA. Dementia and depression among the elderly living in the Hobart community: The effect of the diagnostic criteria on the prevalence rates. Psychol Med 1985;15:771-88. |
|21.||Roberts RE, Kaplan GA, Shema SJ, Strawbridge WJ. Does growing old increase the risk for depression? Am J Psychiatry 1997;154:1384-90. |
|22.||Barua A, Acharya D, Nagaraj K, Bhat HV, Nair NS. Depression in elderly: A cross-sectional study in rural South India. J Int Med Sci Acad (JIMSA) 2007;20:259-61. |
|23.||Lobo A, Saz P, Marcos G, Día JL, De-la-Cámara C. The prevalence of dementia and depression in the elderly community in a Southern European population. The Zaragoza study. Arch Gen Psychiatry 1995;52:497-506. |
|24.||Blazer D, Williams CD. Epidemiology of dysphoria and depression in an elderly population. Am J Psychiatry 1980;137:439-44. |
|25.||Chen R, Copeland JR, Wei L. A meta-analysis of epidemiological studies in depression of older people in the People's Republic of China. Int J Geriatr Psychiatry 1999;14:821-30. |
|26.||Chen R, Wei L, Hu Z, Qin X, Copeland JR, Hemingway H. Depression in older people in rural China. Arch Intern Med 2005;165:2019-25. |
|27.||Pahkala K, Kesti E, Kongas-Saviaro P, Laippala P, Kivela SL. Prevalence of depression in an aged population in Finland. Soc Psychiatry Psychiatr Epidemiol 1995;30:99-106. |
|28.||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. |
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