Review Article: Trend of the prevalence of geriatric
depression: a modern silent epidemic

Ankur Barua

Review Article: Trend of the prevalence of geriatric depression: a modern silent epidemic

Ankur Barua

Ankur Barua^1,2

Department of Community Medicine, Sikkim-Manipal Institute of Medical Sciences (SMIMS), India
International Medical University (IMU), Malaysia

Corresponding Author: Dr. ANKUR BARUA Senior Lecturer; Department of Community Medicine, International Medical University (IMU), No. 126, Jalan Jalil Perkasa 19, Bukit Jalil, 57000 Kuala Lampur, Malaysia, Email: ankurbarua26@yahoo.com | Mobile: +60122569902, +60105354023

Related article at Pubmed, Scholar Google

Visit for more related articles at International Journal of Collaborative Research on Internal Medicine & Public Health

Abstract

Introduction: Unipolar Major Depression is predicted to become the second-most important cause of morbidity throughout the world by the year 2020 by the World Health Organization (WHO). This systematic review on the prevalence rates of geriatric depression was conducted to draw the attention of all health care personnel for focussing their intense endeavours in addressing this burning issue.

Objectives:

(1) To determine the Median Prevalence Rates of geriatric depression of the world and in India.

(2) To conduct a Time-Trend Analysis on prevalence of geriatric depression in the world.

Materials & Methods: This Retrospective study based on Systematic review on prevalence of geriatric depression was conducted on the community based mental health surveys on geriatric depression conducted in continents of Asia, Europe, Australia, North America, and South America. All the studies that constituted the sample were conducted between 1956 and 2005. After applying the inclusion and exclusion criteria, 65 original research studies that surveyed a total of 99,297 elderly individuals in the age group of 60 years and above, residing in various parts of the world were included for the final analysis. Statistical procedures applied were the median prevalence rate and its corresponding inter-quartile range as well as the Chi-square for Linear Trend. P value <0.05 was considered as statistically significant.

Results: The Median Prevalence Rate of geriatric depression in the world was determined to be 10.3% with Interquartile Range varying between 4.6% and 16.0%. The Median Prevalence Rate of geriatric depression in Indian population was determined to be 21.9% with Interquartile Range varying between 11.6% and 31.1%.

Conclusion: The high prevalence rate of geriatric depression could be attributed to the fact that better diagnostic instruments with optimum validity and reliability had been developed during the recent years to diagnose geriatric depression at an early stage in the community.

Keywords

Elderly, Unipolar, Major, Depression, Time-Trend Analysis, Chi-square

Introduction

Depression is a silent killer of modern era. According to the future projection of Disability Adjusted Life Years (DALY), it has been predicted by the WHO that, Unipolar Major Depression, would become the second-most important cause of morbidity throughout the world by the year 2020.1 A significant number of the elderly people today are likely to have physical and mental morbidity besides having psychosocial problems1. Among the various mental disorders of old age, depression was the commonest problem observed in the community. According to the estimates of the World Health Organization, the overall prevalence rate of geriatric depression generally varies between 10% and 20% depending on cultural situations.2 A recent study in Edmonton by Newman et al. (1998) on a community sample of people over 65 years of age, found the rate of depression as 11.2%.3,4

In India, the principal mental disorders of later life were mood disorders (predominantly depressions) and dementias.1 The community-based mental health studies have revealed that the point prevalence of depression among the geriatric population in India varies between 13 and 25 per cent.1,5,6,7

According to the observations made by the World Health Organization, the correlates of depression in old age were reported as: (1) Genetic susceptibility, (2) chronic disease and disability, (3) pain, frustration with limitations in activities of daily living, (4) personality trait (dependent, anxious or avoidant), (5) adverse life-events (widowhood, separation, divorce, bereavement, poverty, social isolation) and (6) lack of adequate social support.2,4,8,9,10

Though the suicidal tendencies among the aged, occur frequently as a result of major depression, 4,11 studies show that only 8–20% of the elderly, suffering from depression, were being cared for in the community.11,12

Currently, India was entering the grey revolution. The proportion of those, who were aged 60 years and above, were estimated to be 7.7% for the year 2000, and this proportion were expected to reach 12.6% in 2025. The Indian aged population was currently the second largest in the world.13

However, in India, due importance was not given to determine the magnitude of geriatric mental health problems and to assess their long-term effects on general health. This was evident from the fact that only a few studies were available that have explored geriatric health problems, particularly the mental health problems.5,6,7,14,15

Though India was the second-most populated country in the world in terms of elderly population of sixty years and above, yet geriatric depression was not yet perceived as a public health problem in India. So, there was a need to conduct a systematic review and compare the prevalence rates of geriatric depression in India and the rest of the world, in order to draw the attention of all health care personnel for focussing their intense endeavours to address this issue.

Materials and Methods

Study Design: Retrospective study based on Systematic review on prevalence of geriatric depression.

Setting: Community based mental health surveys on geriatric depression conducted in continents of Asia, Europe, Australia, North America, and South America.

Study Period: All the studies that were conducted and published in indexed journals between 1956 and 2005 (i.e., within the last fifty years) constituted the sample.

Sample Size: All published articles on prevalence of geriatric depression that were available, adequately analyzed and accessible from the internet, the Central Library of Kasturba Medical College Manipal in Karnataka and the Central Library of Sikkim- Manipal Institute of Medical Sciences (SMIMS) in Sikkim, constituted the study universe of sixty five articles which are enlisted in Table A.

Sampling Procedures: Simple Random Sampling Method was applied to identify the study subjects in all the individual and independent surveys conducted in the constituent studies.

Inclusion Criteria: To avoid undesired bias due to design effects from various epidemiological study designs, the researchers had included only community based crosssectional surveys on prevalence of depression that were conducted on homogenous community of elderly population in the world, who were selected by simple random sampling technique.

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 in Karnataka and Central Library of Sikkim-Manipal Institute of Medical Sciences (SMIMS), Sikkim on studies regarding the prevalence of geriatric depression were excluded from the study.

Any study, where the 95% Confidence Interval for the prevalence rate estimation exceeded 20 units; the study was excluded from analysis on accounts of probable inappropriate sample size calculation. But it was perceived by the researchers that the proportion of excluded reports would constitute less than 5% of the available articles on relevant topic. Hence, it was expected to have minimal impact on the final results.

Study Instruments: Clinical Diagnoses by Psychiatrists was based on Diagnostic Statistical Manual version III (DSM-III-R), Diagnostic Statistical Manual version IV (DSM IV) and International Codes for Diseases (ICD-10) criteria. Other standardized study instruments used were Geriatric Mental State Examination (GMS), Automated Geriatric Examination for Computer Assisted Taxonomy (AGECAT), Composite International Diagnostic Inventory (CIDI-SF), Centre for Epidemiological studies Depression scale (CES-D), Beck’s Depression Inventory (BDI), HDS, Yesavage Geriatric Depression Scale, Centre for Epidemiologic Studies Depression Scale, Mini Mental Status Examination (MMSE), Clinical Rating Scale for Depression and Geriatric Depression Screening Scale and Mastering Depression In Primary Care Version 1998.

Data Collection Procedure

The investigators were trained by the renowned psychiatrists of Kasturba Medical College Manipal, Karnataka and Sikkim-Manipal Institute of Medical Sciences (SMIMS) on how to interpret the results form different community based psychiatric evaluation studies. The diagnoses generated by the questionnaires used as study instruments were strictly kept confidential and were reconfirmed by consulting the senior psychiatrists for confirmation of their acceptability, content validity and reliability, before arriving at a final ICD-10 diagnosis for data analysis.

After applying the inclusion and exclusion criteria, a Pilot study was conducted at the initial stage with data from 20 randomly chosen original research studies that surveyed a total of 3800 elderly individuals in the age group of 60 years and above, residing in various parts of the world. The data from the pilot study were later included in the statistical analysis of the final research project.

Anytime a relevant article was found inaccessible on internet, all attempts were made to contact the corresponding author(s) through postal letters, telephone, fax or email and sincerely requested to provide us with a soft or hard copy of that article. In case after repeated five attempts, spread over three months, if the investigators fail to procure a relevant article, then that article was considered as unavailable and it was excluded from the analysis.

Data Analysis

The collected data was tabulated and analysed by using the statistical package SPSS (Statistical Package for Social Sciences) version 10.0 for Windows. The Median prevalence of geriatric depression was estimated along with its corresponding interquartile range. Chi-square for Linear Trend was applied to conduct the time-trend analysis of geriatric depression in India and major continents in the world. P value <0.05 was considered as statistically significant.

Results and Discussions

From Table 1, the Median Prevalence Rate of geriatric depression in the world was determined to be 10.3% with Interquartile Range varying between 4.6% and 16.0%.

From Table 2, the Median Prevalence Rate of geriatric depression in Indian population was determined to be 21.9% with Interquartile Range varying between 11.6% and 31.1%. This finding is similar to the observations from the community-based mental health studies conducted in various parts of India which had revealed that the point prevalence of geriatric depression in India varied between 13 and 25 per cent. 1,5,6,7

Apart from an increase in stress related injuries of brain due to fast-paced modernization and industrial development, there was also an element of social isolation due to the failure of social support and network systems for elderly population in India.

The high prevalence rate of geriatric depression could also be attributed to the fact that better diagnostic instruments with optimum validity and reliability had been developed during the recent years to diagnose geriatric depression at an early stage in the community.

Though the Time-Trend Analysis on prevalence of geriatric depression from Table3, revealed that the prevalence of geriatric depression was significantly on decrease from 1956-2005 (x2 for linear trend = 10.2 and p= 0.00144*), but the number of individuals affected in recent years was more. This could also be attributed to the fact that the study instruments that were applied during the year 1956-1983 were not specially devised to specifically detect depression in the community and they could have falsely identified more cases of dementia as depressive disorders.

Conclusion

A high prevalence rate of geriatric depression was observed in this study. This could be due to the use of better diagnostic instruments with optimum validity and reliability that had been developed during the recent years to diagnose geriatric depression at an early stage in the community. Though the Time-Trend Analysis revealed that the prevalence of geriatric depression significantly decreased from 1956-2005, but the number of individuals affected in recent years was comparatively higher.

Competing interests

NIL

Authors' contributions

Ankur Barua had conceptualized this project, formed the protocol, collected the data, did the statistical analysis and composed the final report.

References

The World Health Organization. World Health Report: Mental Health: New understanding New Hope. Geneva: The institute; 2001.
Dey AB, editor. Handbook on Health Care of the Elderly: A manual for physicians and in Primary and Secondary Health Care Facilities. New Delhi: The World Health Organization: Regional Office for Southeast Asia, Ministry of Health and Family Welfare, All India Institute of Medical Sciences (India); 1999.
Newman SC, Bland RC, Orn HT. The prevalence of mental disorders in the elderly in Edmonton: a community survey using GMS-AGECAT. Canadian Journal of Psychiatry. 1998; 43: 910–14.
The World Health Organization. Mental Health Around the World: Stop Exclusion – Dare to Care: World Health Day. Geneva: The institute; 2001.
Tiwari SC. Geriatric psychiatric morbidity in rural northern India: Implications for the future. International Psychogeriatrics. 2000 March; 12(1): 35-48.
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 Journal of Psychiatry. 1976; 18: 79-87.
Ramachandran V, Menon Sarada M, Arunagiri S. Socio-cultural factors in late onset Depression. Indian Journal of Psychiatry. 1982; 24(3), 268-73.
Cleaveland clinic health system. Depression in the elderly, Health information home. Ohio: The institute; 2002.
Katona C, Livingston G. Impact of screening old people with physical illness for depression. Lancet. 2000 July; 356(9224): 91.
Kennedy Gary J, Kelman R Howard, Thomas Cynthia, Wisniewski Wendy, Metz Helen, Bijur E Polly. Hierarchy of characteristics associated with Depressive Symptoms in an urban elderly sample. American Journal of Psychiatry. 1989 February; 146(2): 220-25.
The World Health Organization. Well-being Measures in Primary Health Care/ The DEPCARE Project: Report on a WHO Meeting. Regional Office for Europe: The institute; 1998.
Johansen Kirsten Staehr, Philip Ian, Skovlund Søren, Bech Per. DepCare: A European Approach to the Challenge of Depression. Regional Office for Europe. The World Health Organization; 1998.
Prakash Indira J. Ageing in India. Geneva: The World Health Organization; 1999.
Nandi PS, Banerjee G, Mukherjee SP, Nandi S, Nandi DN. A study of Psychiatric morbidity of the elderly population of a rural community in West Bengal. Indian Journal of Psychiatry. 1997; 39(2): 122-9.
Rao Venkoba A, Madhavan T. Geropsychiatric morbidity survey in a semi-urban area near Madurai. Indian Journal of Psychiatry. 1982; 24(3): 258-67.