Distribution of depressive disorders in the elderly

Study design

A retrospective study based on the meta-analysis on the prevalence of depressive disorders in the elderly population.

Setting

Community-based mental health surveys on depressive disorders in the elderly, conducted in the continents of Asia, Europe, Australia, North America, and South America, were included in this analysis.

Study period

All the studies that were conducted and published in indexed journals between 1955 and 2005 (ie, within the last 51 years) would constitute the sample. This is decided on the observed fact that it normally took around 2-3 years time for a project report to get accepted and published in an indexed journal. So, a study conducted during 2005 was expected to get published in an indexed journal by the year 2008. The sample size for this project was finalized during the year 2008.

Sample size

All the published articles on the prevalence of depressive disorders in the elderly 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 sources. All the articles included for the final analysis were in the English language.

Databases

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 January 1, 1955 and December 31, 2005 using the two sets of search items: “Prevalence of Depression in Elderly” and “Prevalence of Geriatric Depression.”

Sampling procedures

Only 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 meta-analysis. Overlapping studies from the same geographic areas were also included for the analysis.

Inclusion criteria

To avoid undesired bias due to design effects from various epidemiologic study designs, the researchers had included only community-based cross-sectional surveys on the prevalence of depressive disorders and some prospective study designs that had not excluded depression on baseline. All these studies were conducted on homogenous community of elderly 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 correlates of depression in the elderly, only those articles were included that had studied at least one risk factor of depression.

Exclusion criteria

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, Karnataka, and the Central Library of Sikkim-Manipal Institute of Medical Sciences (SMIMS), Sikkim, on studies regarding the prevalence of depressive disorders in the elderly population were excluded from this study. But it was perceived by the researchers that the proportion of excluded reports on account of inaccessibility or unavailability would constitute less than 5% of the available articles on the relevant topic. Hence, this was expected to have a minimal impact on the final results. Studies in which the 95% Confidence Interval of the prevalence rate estimation exceeded more than 20 units were excluded on account of possible improper sample size estimation. Studies conducted on migrant populations, old age homes, and health care institutions were also excluded from this meta-analysis in order to avoid bias. 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 physiologic or financial needs.

Selection of articles

In the first step, while searching through all the selected databases, the key words “depression,” “prevalence,” “elderly,” “geriatric,” and “aged” and the text word “community” were used. In the second step, after applying the inclusion and exclusion criteria, all the 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 the retrieved articles were screened to determine which met the following six inclusion criteria: (1) original research published in English, (2) study group of community residents, (3) 60 years or older subjects, (4) cross-sectional study design that included both old and new cases of depressed elderly individuals in the community, (5) prospective or follow-up studies that have not excluded the depressed elderly individuals at baseline, and (6) acceptable definition of depression (either recognized diagnostic criteria or cutoff on a depression rating scale).

List of studies included in the meta-analysis

Essen-Moller (Sweden, 1956), Kay (Australia, 1964), Parsons (UK, 1965), Nandi D.N. et al. (India, 1972–73), Copeland J.R. et al. (UK, 1976), Ramachandran V. et al (India, 1979), Blazer D. et al. (North Carolina, 1979), Balzer (USA, 1980), Eaton (USA, 1981), Stanley A.M. (USA, 1981), Rao Venkoba A. et al. (India, 1982), Penninx Brenda W.J. et al. (New Haven, 1982–88), Broadhead W.E. et al. (USA, 1982–84), Murrel (USA, 1983), Gurland (USA, 1983), Kennedy G.J. et al. (USA, 1984–85), Kay (Australia, 1985), O’Hara (USA, 1985), Kay (Hobart, 1985), Kay D.W. et al. (Hobart, 1985), Berkman (USA, 1986), Copeland (UK, 1987), Copeland et al. (UK, 1987), Morgan (UK, 1987), Bland (Canada, 1988), Kivela (Finland, 1988), Weissman (USA, 1988), Kivela et al. (Finland, 1988), Kennedy (USA, 1989), Lindesay (UK, 1989), Cwikel (Israel, 1989), Bosma (Netherlands, 1990), Schoevers R.A et al. (Amsterdam, 1990–97), Geerlings M.I. et al. (Amsterdam, 1990–96), Blazer (USA, 1991), Fuhrer (France, 1992), Kua (Singapore, 1992), Madianos (Greece, 1992), Johnson J. et al. (USA, 1992), Henderson (Australia, 1993), Ihara (Japan, 1993), Saunders (UK, 1993), Liu C.Y. et al. (China, 1993), Woo (Hong Kong, 1994), Komahashi (Japan, 1994), Pahkala K et al. (Finland, 1994), Beekman (Netherlands, 1995), Hooijer (Netherlands, 1995), Lobo et al. (Southern Euro, 1995), Roberts R.E. et al. (USA, 1995), Ramin M. et al. (USA, 1996), Komer A. et al. (Denmark, 1996), Geraldine F.M. (USA, 1996), Lauritzen (Denmark, 1996), Chong M.Y. et al. (Taiwan, 1996–98), Nandi P.S. et al. (India, 1997), Prince M.J. et al. (UK, 1997–98),[5] McCracken C.F. (UK, 1997),[6] Kirby M. et al. (Dublin, 1997),[7] Braune B.T. et al. (Germany, 1997–98), Newman S.C. et al. (Canada, 1998), Newman S.C. et al. (Canada, 1998), Tiwari S.C. (India, 1999), Chen R. et al. (China, 1999), Beekman A.T. et al. (Netherlands, 1999), Deise A.A. (Brazil, 2001), Stella A. (Greece, 2001), Heun R. et al. (Germany, 2001), Mine E. et al. (Turkey, 2001–02), Barua A. (India, 2002), Daniel W.L. et al. (Canada, 2004), Copeland J.R. et al. (Berlin, 2004), Ostbye T. et al. (Canada, 2005), and Chen R. et al. (China, 2005).

Study instruments

Clinical Diagnoses by Psychiatrists were based on Diagnostic and Statistical Manual of Mental Disorders, editions DSM-III-R and DSM-IV, and ICD-10 criteria. Other standardized study instruments used were Geriatric Mental State Schedule (GMS), Automated Elderly Examination for Computer-Assisted Taxonomy (AGECAT), Composite International Diagnostic Inventory, Center for Epidemiologic Studies Depression Scale (CES-D), Beck's Depression Inventory, Hamilton Depression Scale (HDS/HAMD), Yesavage Geriatric Depression Scale, Mini-Mental Status Examination (MMSE), , Clinical Rating Scale for Depression, Elderly Depression Screening Scale, and Mastering Depression In Primary Care, Version 1998 [Table 1].

Table 1 Prevalence rates of depressive disorders in elderly population

Assessment of validity

The validity of each of these study instruments was verified with their individual validity and reliability reports and reconfirmed with renowned psychiatrists. Some of the studies used the clinical assessment by the individual psychiatrists where the diagnostic criteria were never mentioned. In these cases, the impact factor of the journals in which the research articles 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 the Kasturba Medical College, Manipal, Karnataka, and the Sikkim-Manipal Institute of Medical Sciences (SMIMS), Sikkim, on how to interpret the results from different community-based psychiatric evaluation studies. The diagnoses generated by the questionnaires used as study instruments were kept strictly confidential and reconfirmed by consulting the senior psychiatrists for confirmation of their acceptability, content validity, and reliability, before arriving at a final diagnosis for data analysis.

At the beginning, a pilot study was conducted with randomly chosen data from 25 original research articles that surveyed elderly 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.

Anytime a relevant article was found inaccessible on the Internet or in designated libraries, all attempts were made to contact the corresponding author(s) through postal letters, telephone, fax, or email requesting them to provide the investigators with a soft or hard copy of that article. In case the investigators failed to procure a relevant article even after five attempts, spread over 1 year, it was considered as unavailable and excluded from the final analysis.

Abstraction of data

Information about the size of the study group, subjects’ age, sampling method, criteria for depression, exclusion criteria at baseline, length of the study period, and the number of prevalent cases of depression was abstracted from each report.

Data analysis: The collected data were tabulated and analyzed by using the statistical package SPSS (Statistical Package for Social Sciences) version 10.0 is IBM Company in US for Windows and EPI INFO version windows 2000. The findings were described in terms of Median Prevalence Rates of depressive disorders in the elderly and their corresponding interquartile range (IQR). Proportions and their 95% confidence intervals (CI) were used for the same purpose. Chi-square test and Chi-square for Linear Trend were applied for studying prevalence rates of the depressive disorders of the elderly in the various countries of the world, including India. Here, a P value < 0.05 was considered as statistically significant.

Selection of articles

The search strategy yielded 896 potentially relevant studies; among these 143 were retrieved for more detailed evaluation. Although 77 studies met the inclusion criteria, we could retrieve the 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 inaccessibility and unavailability of relevant information elsewhere. Among these 74 selected articles, which formed the study material for this meta-analysis of depression in the elderly, 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[8] (1999, China) on 10 relevant studies and another by Copeland et al[9] (2004, Amsterdam) on 14 relevant studies, and also a systematic review report by Beekman et al[10] (1999, Netherlands) 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 the elderly from [74 + (10+14+34) = 132] the survey reports from various parts of the world.

The investigators could obtain full text versions of 44 (59.5%) articles and had retrieved structured abstracts with relevant data for this meta-analysis of 17 (23.0%) articles. Even though the investigators could not directly retrieve the reports of 13 (17.6%) important studies, the relevant information of these studies was obtained from the introduction and discussion sections of the full text versions of some of the retrieved articles.

Report from the selected 74 articles was used for estimation of median prevalence of depression in the elderly. 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.

Determination of median prevalence rate of depressive disorders in the elderly

The 74 included studies involved 4,87,275 elderly individuals from all parts of the world at baseline [Table 1]. Among these, 6 studies from India involved only 2499 (0.5%) elderly individuals at baseline for assessment of presence of depression. The mean ages of the study population were reported in 68 (85.1%) articles with mean ranging from 62 to 71 years. Here, 68 (91.9%) articles included gender distribution and 36%–64% of the participants were men (median = 46%). The length of the reported study period ranged from 3 to 84 months (median = 9).

Only 52 (70.3%) studies used some of the modern rating scales for diagnosis of depression in the elderly. Among these, 14 used AGECAT/GMS-AGECAT, 4 used Diagnostic Interview Schedule/HDS, 8 used GMS/Geriatric Depression Scale (GDS), 11 used CES-D, and 15 used DSM/ICD criteria for the diagnosis of geriatric depression. Although some studies had used more than one rating scale of depression, only the superior rating scale among these was included as the diagnostic instrument for each study. The prevalence rate of geriatric depression was found to be higher in studies using psychiatric examination and operational definitions and studies using the GDS or Geriatric Mental State Schedule (GMS) alone [Table 1].

The Median Prevalence Rate of depressive disorders in the world for the elderly population from 74 studies was determined to be 10.3% with Inter-Quartile Range varying between 4.7% and 16.0%. Similar findings were reported by Kirby et al[11] (1997, Dublin) and Kay et al[12] (1985, Hobart). Studies conducted by Geerlings et al[13] [(1990–1996), Amsterdam], Newman et al[14] (1998, Canada), and Liu et al[15] (1993, China) also reported the prevalence rate of depression among the elderly to be 10.5%, 11.2%, and 12.9%, respectively.

The comparison of median prevalence rates of depression in the elderly population of India and the rest of the world was also studied. It was found that the proportion of depressed elderly population in India (18.2%) was significantly higher than the rest of the world (5.4%) and this difference was found to be statistically highly significant (χ² = 770.4 and P = 0.000000001*). Although there is an alarming increase in the proportion of depressed elderly in India, we should also keep in mind that there were only 6 relevant studies available from India, covering only 0.5% of elderly participants of the world as compared with 68 studies from the rest of the world covering 99.5% of the participants.

The low prevalence of depression in the elderly during recent years could be due to the presence of better diagnostic instruments with optimum validity and reliability developed during the recent years to diagnose geriatric depression in the community and to rule out cases of dementia, which were often falsely diagnosed as depression in the past. The technologic advancements in recent years on health care delivery systems, including mental health, also provided adequate health support systems, improving the quality of life in the elderly.

However, a high prevalence in the past could be attributed to the fact that the study instruments that were applied during the years (1955–1984) were not specially devised to specifically detect depression in the community and they could have falsely identified more cases of dementia as depressive disorders and a majority of these studies relied on clinical diagnosis and operation definition where the cutoff level for identification of geriatric depression was lower.

Since there is population explosion recorded in many of the developing countries in the world, including India in recent years, we need also to keep in mind the number of depressed elderly individuals who would require adequate mental health care. Although a lower prevalence rate of geriatric depression was recorded in the recent years, there was an alarming increase in the number of elderly individuals suffering from depression, which had a booming 8-fold increase from the period of (1955–1984) to (1995–2005), and this trend was also found to be statistically highly significant. Although there was a significant decrease trend in the world prevalence of geriatric depression, it was significantly higher among Indians in recent years than the rest of the world.

The comparison of depressive disorders in the elderly population of various continents of the world was undertaken. Due to unavoidable circumstances, no study from the African continent was available for this meta-analysis. However, the findings suggested that the median prevalence rates of depression in the elderly were similar in Asia, Europe, and America, but it was significantly lower in Australia. Here, we should keep in mind that only 3 studies were available from Australia, which covered only 0.4% elderly population of the world. Although the proportion of elderly individuals affected with depression was significantly lower in Asia (4.2%) than Europe (10.9%) and America (8.4%), the number of depressed elderly individuals was significantly higher in Asia, which was evident from 14 studies conducted in various Asian countries covering 74.5% population of the world. Studies from the developing countries, such as India, had reported a very high prevalence rate of 21.9% with IQR ranging from 11.6 to 31.1. Care and bonding from family support systems, lesser competitive life styles, and improved mental health facilities with their integration with primary health care could account for lesser prevalence rates in some of the developed Asian countries.[124]