DEPRESSIVE SYMPTOMS AMONG THE ELDERLY IN KERALA- PREVALENCE, DETERMINANTS AND VALIDATION OF GERIATRIC DEPRESSION SCALE (GDS-15) DR. ARAVIND P.

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1 DEPRESSIVE SYMPTOMS AMONG THE ELDERLY IN KERALA- PREVALENCE, DETERMINANTS AND VALIDATION OF GERIATRIC DEPRESSION SCALE (GDS-15) DR. ARAVIND P. Dissertation submitted in partial fulfillment of the requirement for the award of the degree of Master of Public Health. Achutha Menon Centre for Health Science Studies (AMCHSS) Sree Chitra Tirunal Institute for Medical Sciences and Technology (SCTIMST) Thiruvananthapuram Kerala (India) June 2004

2 Declaration I hereby certify that, the work embodied in this dissertation entitled Depressive symptoms among the elderly in Kerala: Prevalence, determinants and validation of Geriatric Depression Scale (GDS-15) is the result of original research and hasn t been submitted for the award of any degree in any other University or Institution. Place: Date: Dr. Aravind P 1

3 Acknowledgments I am highly indebted to my teacher and guide Dr.Mala Ramanathan, without whose support and encouragement this work would have been impossible. I sincerely extend my gratitude to Dr. KS Shaji, who was the resource person in designing the study. I am thankful to Dr.John Copeland and Ms Caroline Walsh of GMS Resource Center at the University of Liverpool for donating the GMS and AGECAT for this study. I would like to thank Dr Vikram Patel for his valuable inputs and comments. The study would not have taken place without the valuable help and assistance from Mr Sreekantan, Grameena Padana Kendram at Karakulam Panchayth and I extend my sincere gratitude towards him and other staff at the center. I am thankful to all the faculties of AMCHSS, especially Dr.Sankara Sarma who helped me with the analysis of the data; Dr.Biju Soman whose valuable suggestions and constructive criticism helped me in writing the dissertation and Dr.Sundari Raveendran who gave important comments. I would like to thank Dr. Sailesh Mohan, my senior who helped me with the abstract. I am also thankful to all my batch mates for their encouragement and inputs received during the course. I thank the study participants, and all others who were directly or indirectly involved in this study. Finally, I am thankful to my family especially my wife who is a constant source of support and motivation. 2

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5 Table of Contents Page No Chapter I Introduction and review of literature 1-18 Background 2 Epidemiology of depression 2 Sub threshold depressions 4 Indian scenario 7 Assessment of depression in the elderly 9 Screening for depression 11 Determinants of Geriatric depression 12 Objectives 18 Chapter II Methodology Methodology 19 Analysis of data 23 Ethical concerns 25 Chapter III Results Sample characteristics 26 Prevalence of depression 31 Validating the Geriatric Depression Scale (GDS ) 32 Epidemiological features 34 Chapter IV Discussion and policy implications Discussion 44 Limitation of the study 52 Strengths of the study 52 Policy Implications 53 References Annexures GMS B3 (English) GMS B3 (Malayalam) GDS-15 (English) GDS-15 (Malayalam) Questionnaire III 4

6 DEPRESSIVE SYMPTOMS AMONG THE ELDERLY IN KERALA- PREVALENCE, DETERMINANTS AND VALIDATION OF GERIATRIC DEPRESSION SCALE (GDS-15) Abstract Among the various chronic morbidities that afflict the elderly, depression requires special attention due to high prevalence (8-24%), its debilitating effect on the quality of life and substantial impact on other chronic diseases. Recent studies highlight the importance of recognizing depressive symptoms not amounting to clinical depression in elderly in addition to depressive illness. Timely detection and treatment appreciably reduces the disease burden. The absence of a validated screening instrument, in developing country settings often impedes effective screening for depressive symptoms at the primary care level. These issues need to be looked into for the Indian State of Kerala, which is undergoing a demographic transition towards an ageing population. Objective To estimate the prevalence and correlates of depressive symptoms among the population aged 60 years and above in a community in Kerala and validate the Geriatric Depression Scale (GDS) for this population. Methodology By systematic sampling, 259 elderly ( 60) were selected from the electoral rolls of two wards in a village. They were interviewed with the semi structured interview schedule The Geriatric Mental Status Schedule (GMS) and an independently translated Malayalam version of the screening instrument Geriatric Depression Scale (GDS). Case level depression as well as undifferentiated depression diagnosed by the GMS was considered as depressive symptoms. GDS score was validated against the GMS diagnosis of depressive symptoms. Reliability was tested using test retest method for 30 randomly selected subjects. Various socio demographic factors were examined to find the correlates of depressive symptoms. Results The prevalence of depressive symptoms among the elderly was found to be 24.7%. The cut off score arrived at by plotting an ROC curve with sensitivity and specificity for each score against the GMS diagnosis was 5 (sensitivity= 96.9% Specificity= 86%) for depressive symptoms. Spearman s coefficient between GMS diagnosis and GDS screening using the new cut off was The test retest reliability, coefficient kappa was 0.76 and internal consistency calculated by standardized Cronbach s alpha was 0.73 Depressive symptoms were found to be significantly associated with increasing age, female gender, illiteracy, chronic disease, disability, being single, significant adverse life events, and non-participation in any work. In the multivariate analysis depressive symptoms were found to be associated with being single (OR 1.9), non-participation in any work (OR 3.5) and clustering of significant life events (OR 4.1). Conclusion Depressive symptoms among the elderly population were quite high and were associated with being single, non-participation in any work and adverse significant life events. The Malayalam version of GDS-15 validated in this study is an effective tool for screening depression in the community. It can be routinely used as a screening tool for high-risk elderly population. 5

7 Chapter I INTRODUCTION AND REVIEW OF LITERATURE Advances in medicine and improvements in living conditions over the past century have resulted in numerically greater number of persons reaching old age. With this increasing life expectancy is the health concern of a greying world. Among the numerous chronic morbidities that afflict the elderly, depression requires special attention due to high prevalence (8-24%) and its effect on other morbidities. Yet, depression in old age remains as an under recognised public health problem. It results in suffering among many who go undiagnosed, and burdens families and institutions providing care for the elderly. What makes depression in the elderly so insidious is that neither the victim nor the health care provider may recognize its symptoms in the context of the multiple physical problems that they experience. On the other hand, studies from different settings have clearly established the surplus disability, morbidity and mortality associated with old age depression. Without treatment, depression in old age becomes a chronic disease that produces high level of morbidity and mortality. Copeland et al. 1 found that two third of those diagnosed with depression were either dead or psychiatrically ill after three years. Unlike many other chronic conditions that affect the elderly, depression is amenable to treatment. Thus, there is great potential and opportunity for detecting depression in older people. In addition to relieving great suffering, there is preliminary evidence that recovery from depression reduces health service usage by older people. 2 6

8 Background Epidemiology of depression Until the middle of the last century our knowledge about the mental illness in elderly was limited. Studies from 1950's and 1960's proved that the nature of mental illness was not significantly different from that of younger adults except for their extend. 3 But earlier studies were mostly hospital based and they underestimated the magnitude of the problem. The iceberg phenomenon that is, 2/3 rd of the diseased population lying submerged (under recognized) is true with regard to geriatric psychiatric morbidity also. Considerable impediments to professional recognition of the disorder and their treatment also resulted in widespread underestimation. Many societies and families accept some amount of gloom and desolation among the elderly as natural, and defer from addressing the problem. Nevertheless, studies have shown that depression is not age related and there is no reason to believe it to be part of normal aging. It s the knowledge from the various epidemiological studies involving both treated and untreated cases which provides a more complete picture of main categories of the disorder. 4 Quantifying and comparing the extent of geriatric depression from various studies have been a problem due to the methodological issue of differences in defining depression. The diagnostic and statistical manual fourth edition (DSM IV American psychiatric association 1994), classifies depression within the mood disorders (Affective disorder) because mood disturbance is the most salient characteristic. According to these criteria, patients must experience 5 of the following symptoms for at least 2 weeks: depressed mood, diminished interest or pleasure in daily activities, significant changes in weight or 7

9 appetite, insomnia or hypersomnia, psychomotor agitation or retardation, fatigue, feelings of guilt or worthlessness, impaired concentration, or suicidal ideation. It includes a spectrum of mood disorders from milder dysthymia to major depression. The most intense depression is classified as major depressive disorders while the most chronic are termed dysthymia. The Epidemiological Catchments Area Study 5 documented that major depressive disorder is less frequent in elderly when compared to young adults. Thus, the prevalence of major depressive disorder among persons aged 65 years or older was estimated to be 1.4% in women and 4% in men with an overall prevalence of 1%. 5 But high rates of depression occur in medically ill, disabled or institutionalised elderly persons. With the increase of elderly population and the aging of birth cohorts of the post war period who appear to be particularly prone to depression, a significantly greater number of elderly are expected to be in need of psychiatric attention. Furthermore, failure to detect major depression may lead to over utilization of physical and laboratory examinations, unnecessary consultations with medical specialists, frequent office visits, and costly medication or other treatments. 6, 7 Finally, approximately 15% of untreated depressed patients eventually commit suicide, and up to 70% of suicide victims suffer from depression. The suicide rate for elderly patients is 26.5 out of 100,000 compared to a rate of 12.4 out of 100,000 for the general population, with elderly white men at highest risk. 8 In addition to major depression, approximately 2% of elderly population suffers from dysthymic disorder and 4 % have an adjustment disorder with depressed mood. A rather large percentage of elderly i.e. more than 15%, have depressive symptomatology that does not meet criteria for a specific depressive symptom. 5 8

10 Sub threshold depressions While the prevalence of major depression in geriatric population in the community is similar to other age groups, recent epidemiological studies consistently find higher rates of depressive symptoms in older adults who do not meet the criteria for one of the depressive disorders in Diagnostic and Statistical Manual (DSM). Many of the earlier studies, which reported relative low prevalence of depressive symptoms identified in elderly population, may be in part due to methodological problems, including tendency of elderly persons to express psychiatric symptoms in somatic terms. Problems in case identification are especially prevalent in late life since many of the symptoms and signs of psychiatric disorders in late life may be ubiquitous with the aging process. As a result older adults do not really fit into an appropriate psychiatric diagnosis. 9 Therefore, they are less likely to be diagnosed of depression. In addition to depressive disorders recognized by Diagnostic and Statistical Manual (DSM), sub threshold or sub syndromal depression is currently being espoused as a major clinical concern for older adults that may warrant its own diagnostic code. These minor or sub threshold depressions are receiving increasing attention because of their clinical importance to physical as well as mental health. Disability from milder depressive syndromes appears comparable to that associated with major depression They are also associated with increased risk of disability, increased mortality, and impaired 10, psychosocial functioning. Blazer and colleagues 16 analysed symptom clusters in an effort to identify variant forms of depression in elderly. One symptom cluster that emerged from their analysis was found almost exclusively in older adults. The symptoms included depressed mood, 9

11 psychomotor retardation, difficulty in concentrating and problems performing on the mental status examination. In addition these individuals described themselves as in poor health. Although they would not meet the criteria for diagnosis of depression based on DSM IV, these older adults were obviously struggling with depression that was associated with physical illness and cognitive impairment. Some studies which explored geriatric depression with standardized screening questionnaires (like the GDS) captured all subjects with significant depressive symptoms in addition to major depression showing prevalence from 8 to 28% from different parts of the world. Table 1.1 Community prevalence of geriatric depression from various studies Study Year Methodology (instrument) Study Outcome Eurodep Programme Multi centric study in Europe 17 G Rait et.al. 18 African Caribbean 1999 people in Manchester Bhatnagar and Frank 20 South east London Bradford UK Hybels et al. Duke s university (1999) 19 The Sunny Brooke Stroke Study 21 GMS- AGECAT Case level depression GMS- AGECAT Case level depression 1997 GMS- AGECAT Centre for Epidemiologic Studies Depression scale (CES D) Montgomery Asberg Depression Rating Scale (MADRS) Depression Overall prevalence of 12.3%, 14.1% for women and 8.6% for men 10% Depression 20% depressive symptoms (CES D) 9.1% and sub-threshold depression 9.9%, 27% Depressive symptoms 10

12 Study Stephenson et al Canadian community sample Year 1992 Madianos et al. et al. Athens Livingstone et al. The Gospel Oak 1990 Study inner London 70 Methodology (instrument) Centre for Epidemiologic Studies Depression scale (CES D) Centre for Epidemiologic Studies Depression scale (CES D) Short care comprehensive assessment for referral and evaluation Study Outcome 8% Depression (4.3%) men and 10.4% women 27.1% depressive symptoms, 15.9% depression Amsterdam Study of the Elderly 1990 GMS- AGECAT (AMSTEL) 71 Depression 12.9% overall. 6.9% depression in men and 16.5% in women Lindesay et al. Home sample south-east London 1989 Blazer et al CARE structured interview Mild to moderate depressive symptoms 4.3% Major depression and 13.5% pervasive depression. 24% Depressive symptoms. Geriatric morbidity poses an important problem for both the developed and developing countries. Compared to developed countries where most of the researches in these subjects are carried out, there is a dearth of information from the developing world where a majority of world s elderly live. Previously it was assumed that old age depression has a low prevalence in the South East Asian Countries explained by the good family support system with the tradition of giving respect to the elderly. But recent studies from some of these countries shows that though the incidence of major depression is low compared with western societies; they have high rates of minor psychiatric morbidity including dysthymia and other variants of depressive 11

13 disorder. A recent study using GMS AGECAT shows a prevalence of 21.2% for any form of depression in elderly Taiwanese population 23 and the WHO SEARO reports a prevalence of 20% for geriatric depressive symptoms in South East Asian countries. Indian scenario India has one of the largest geriatric population with 7.6% of the population above the age of sixty and is expected to reach to 8.14% by the year There have been few attempts to study the prevalence of mental disorders in the elderly. The mental morbidity among those aged sixty years and above in India has been estimated at 89 per 1000 by Venkoba Rao and Madhavan in a morbidity survey in a semi urban area near Madurai and the same study also found depression as the commonest psychiatric problem (67% of total psychiatric morbidity) in this age group. 25 The occurrence of affective disorder in elderly has been found to vary from 21% to 39% among the patients attending 26, 27 Geropsychiatric Clinic in Madurai. Depression was the commonest diagnosis in the random sampling survey carried out by Ramachandran and Saradha Menon near Madras. 28 Their prevalence rate was 241 per Out of 98 cases of depression they noted 12 to be endogenous and 86 as neurotic type. The depressive illness in communities is often invisible because of community tolerance, attributing the withdrawal feature of the old person to the process of aging itself, and failure to perceive depression as an illness by family members and the society. A study done at Raipur in India 29 drew attention to the failure of perception of depressive illness by the rural population. 12

14 In view of the paucity of information in this area, the Indian Council of Medical Research considered it appropriate to initiate a task force project on mental health research in the aged on a priority basis. This was started in Madurai and its first phase was hospital based. Out of the 150 subjects studied, 43% suffered from depressive illness. A study by Age Care India showed that about 80% of all the aged person in India both men and women are lonely, shelter less and financial handicapped. Table 1.2 Community prevalence of depression Studies in India Year Age group Prevalence Ganguly et al 24 (Northern India) 1999 >55 years 23% (symptoms) Ramachandran et al 28 (Madras) 1979 > % (symptoms) Venkoba Rao 25 (Madurai) 1982 >60 6% (cases) Parmjeet Kaur et al > % Old age problems require special emphasize in the state of Kerala with its highest life expectancy in India. The state is undergoing a demographic transition and the traditional social structures that supported the older population are becoming non-existent. Thus the elderly may now remain neglected and abused with low access to much needed care. All these factors contribute to the increased psychiatry morbidity in old age. Though caregivers in different settings are now recognizing geriatric depression, there is lack of information about the magnitude of the problem. This has been an obstacle in setting up a public health programme since no previous community based study on 13

15 prevalence of old age depression using a standardized instrument is available from Kerala. Assessment of depression in the elderly Mental and behavioural disorders are identified and diagnosed using clinical methods that are similar to those used for physical disorders. Earlier methods of unstructured clinician interviews used for diagnosis in epidemiological studies were over-optimistic on standardization in clinical training and practice. 31 Currently, interview schedules tend to be either semi structured or completely structured. This has made it possible to attain a high degree of validity and reliability in diagnosis of mental disorder. Assessment of depression includes determining the presence, frequency and severity of typical symptoms. In recent years various standardised assessment tools have been used in different epidemiological studies. Some of these instruments assess depression using: 1. Self-rating scale 2. Observer rating scales and 3. Standardized diagnostic interviews. While the first two are routinely used for screening purpose, the diagnostic interviews represent the gold standard of psychiatric diagnosis. The psychiatric diagnostic scales are assessment tools that identify specific mental disorders. The commonly used tools are CIDI (Composite International Diagnostic Interview) developed by WHO and Structured Clinical Interviews for Axis 1 disorders. These diagnostic interviews rely on the widely accepted DSM and the ICD- the internationally accepted standardized diagnostic criteria. 14

16 The Geriatric Mental Status Schedule (GMS) is another semi structured diagnostic clinical interview designed to assess the mental status of the elderly in the community. The computerised diagnostic schedule that process the GMS data, the Automated Geriatric Examination for Computer Assisted Taxonomy (AGECAT) reduces unreliability and support a wide range of disorders, and has been shown to accord with the diagnosis made by an experienced psychiatrist. The diagnostic agreement between the research psychiatrist and AGECAT was good with generalized K score of 0.87 for depressive disorders and 0.73 for organic brain syndromes. 23 Cases of organic disorder and depression diagnosed by GMS-AGECAT correlate well with DSM III diagnosis of dementia and combined major depression dysthymia and adjustment disorder respectively Four studies on randomly selected community samples have used the Geriatric Mental Status state schedule (GMS) and have reported the prevalence rate for depression in subjects aged 65 years and over in New York, London, Liverpool and Hobart in Tasmania. Prevalence rate in studies using the AGECAT computer based diagnostic syndrome case level for depression are summarized as below. Table 1.3 Prevalence rates for depression from studies using GMS-AGECAT New York 35 London 35 Liverpool 36 Hobart 37 Male Female Total

17 Screening for depression In developing countries with scarce resources it is nearly not feasible to have psychiatric service at primary care level to identify and diagnose cases. A solution to bridge this gap in manpower is to train multipurpose health workers and other field staff, to identify suspected cases and refer them to a secondary care facility with psychiatric services. Though psychiatric diagnosis is more complicated and subjective, there are many standardized screening instruments widely used around the world to identify suspected cases with psychiatric morbidity and refer them to a specialist. Thus, the levels of detection can be increased by the use of validated screening instruments. But the difficulty in using many of these scales is their lack of validation for use in different cultural and language settings. Therefore, cross culturally validating an instrument is crucial before using it in a new setting. A review of literature and consultation with researchers working in this field in South India failed to locate a validated screening instrument for geriatric depression, which could be effectively used by a multipurpose health worker with minimum training. The best general-purpose instrument is probably the Geriatric Depression Scale (GDS). The 30-item Geriatric Depression Scale (GDS-30) has been developed to screen elderly subjects for depression 38 and the GDS-30 has given acceptable sensitivity and specificity. 39 One of the advantages of the GDS-30 is that it relies less on the somatic symptoms of depression and has been proven valid for use in patients with a chronic physical disease. 38 Because the GDS-30 is relatively time-consuming, a shortened version consisting of 15 questions (GDS-15) has been developed. 40 Sensitivity and specificity of the GDS-15 has 16

18 been assessed in a general elderly population, 40 geriatric inpatients, 41 primary care outpatients. 42 The GDS is recommended for screening in the geriatric setting by the Royal College of Physicians and the British Geriatric Society. 43 It has been translated into many languages (Chinese, Dutch, French, German, Hebrew, Italian, Japanese, Rumanian, Russian, Spanish, and Yiddish.). The Malayalam translation of 15-item version used in this study was done at the Department of Psychology, University of Kerala. But till now the scale has not been validated in any population in South India. A shortened version that takes only five minutes to complete is acceptable by primary care attendees. A Hindi version of GDS (GDS-H) validated in Northern India took approximately 6-7 minutes for administration. 24 Determinants of Geriatric depression The determinants of late life depression are definitely multiple. The major factors associated with depression are: Genetic factors Biological factors Physical factors Psycho social factors Economic factors 17

19 Genetic factors Twin family studies along with recent studies of molecular genetics provide strong evidence for a heritable contribution to aetiology of major depression and bipolar disorder. Associated with the genetic predisposition for depression is the observation that depression is more common in women. 44 Most of the studies on distribution of depression across the life span confirm the persistence of 2:1 ratio in women to men into late life. Even in the best-controlled studies, the sex difference in the prevalence of the more severe depression persists, and the factors that are operable persist into later life. 16 Biological factors It has been postulated that cerebral ageing plays a part in the aetiology of depression arising for the first time in old age especially severe depression. 45 The biological changes includes 1 Neurotransmitter changes 2 Neuroendocrine changes 3 Neuroradiological changes 4 Neurophysiological changes 5 Changes of circadian rhythm Physical factors The primary sign of aging is loss of physical health, manifesting as physical illness, physical disability, and increased vulnerability to disease, infection, accidents, malnutrition, debilitation, discomfort and malaise. With the onset of physical illness there develops a greater dependency followed by the preoccupation with physical symptoms, which is very often encountered as hypochondrias and clinically dismissed as insignificant. 46 In a community study Kay et al. demonstrated a significant relationship 18

20 between physical and psychiatric disorders. 47 Elderly people with functional psychiatric disorder showed higher morbidity and mortality rates than the average value for their age and greater use of institutional facilities including non psychiatric hospital beds. There is evidence of specific relationship between physical illness and depression in at least three areas, 1. Depression presenting as physical illness 2. Physical illness presenting as depression 3. Influence of physical disease on the course and outcome of depression Depression can be physically disabling. Fatigue, sleep disturbance and loss of appetite may be compounded by self-neglect, inactivity, and a reduction in patient s motivation to take treatment for physical illness. 45 Greater difficulty arises when elderly depressed patient presents with a persistent and well-defined physical symptom, and with those who deny any other feature suggesting a primary depressive illness. The commonest presenting symptom is pain. A typical facial pain, particularly in women is well known as a possible depressive symptom. Other symptoms include tinnitus, myokymia and pruritis. 48 Depression is a common reaction to a physical disability. The fact that depression is apparently reactive does not mean that the patient may not benefit from appropriate antidepressant therapy in addition to treatment for physical disorder. The five possible reasons leading to presence of depression in physical illness can be: 1. Depression as a consequence to treatment 2. As a consequence of organic brain diseases 3. Psychological reaction to physical illness 19

21 4. Depression may predispose to onset of physical disease 5. The behavioural consequences of depressed mood may cause or complicates physical ill health through starvation, self neglect and self harm Moreover, the physical disorder and disability may increase the individual s vulnerability to other adverse life events that predispose to depression and also inhibit recovery from depression. Many physical diseases have specific association with depression. The latest being explored is the vascular origin of depression hypothesis. Robinson et al 49 reported a rate of sixty percent for major affective disorder in the first six months after a stroke. Depression is a recognized symptom of Parkinson's Disease, also seen associated with malignancies of pancreas, stomach and bronchus. Studies have shown that patients suffering from other chronic morbidities like cardiac diseases, chronic obstructive pulmonary diseases, and arthritis are also vulnerable for depression. 72 Psychosocial factors The most realistic conclusion at present regarding the factors associated with depression is that depression is in part a social phenomenon and depressive conditions are as a result of complex transactions between the individual and his or her social environment. The importance of psychosocial and economic factors is due to the fact that they can be modified to a greater extent compared to other factors. Some of the factors currently established as important for geriatric depression are feminine gender, remaining unmarried and living alone. Studies from many parts of the world have also shown life events as a predictor of depression. The two major factors that have been demonstrated repeatedly from studies in industrialized countries affecting 20

22 depression are life events and chronic diseases. But there is lack of community-based study on the determinants of geriatric depression from India. A hospital-based study from Delhi has shown clear association between life events including death spouse and chronic diseases and depression in elderly. 50 Life events and depression Old age is a time of losses. It is the stage of life when an individual gradually or suddenly loses his physical vigour, physiological resources of body functions, occupation, friends, and spouse and may be, independence. These life events keep on occurring continuously in the life of an old person. If and when these stresses become too severe or too numerous, they might affect the physical and/or psychic equilibrium producing maladaptive patterns of adjustment including physical and mental disorders especially depression. A number of studies have revealed clustering of adverse life events during the period preceding the onset of depression in depressive patients compared with controls Given a pause between the events, the individuals may adapt to the event; but a quick succession of events prevents coping. 54 Nanko & Demura 55 investigated the relationship of life events to the onset of depression. They indicated that life stress in general played an important role among women in the onset of depression and those undesirable events and problems of work specifically play a role in the onset of depression. However, critics of life events research have pointed out that the magnitude of the effect of events on the causation of depression may be quite small

23 The extent to which stressful life events precipitate depression in old age is uncertain; clinically a loss of some kind seems a frequent precedent but research findings are ambiguous. Murphy 56 (1982) found that 48% of depressed patients in the hospital setting and 68% of depressed subjects in the community experienced a severe life event in the year preceding onset, compared with 23% of the normal group from the community. The severe life events that were more common in depressed subjects were the death of a spouse or child, serious physical illness, life threatening illness to some one close, severe financial loss and enforced changed of residence as a result of a demolition programme. Major social difficulties lasting for two or more years were also significantly associated with depression. Barnes and Wise 57 (1991), in a study of three generations, found that there was an interaction between life events and depression for young adults but not for either of the older groups consisting of parents and grand parents. To sum up, our present understanding of depression points to a multifactorial origin. It can be endogenous (biological) or exogenous. Endogenous factors are frequently associated with severe and chronic depressive illness while psychosocial factors more often contribute to sub threshold depression. The plan for a public health intervention starts with estimating the magnitude of the problem and identifying the modifiable risk factors associated with depression. 22

24 Objectives The objectives of this study are: To estimate the prevalence of depressive symptoms among the population above 60 years of age in a community in Kerala and examine its determinants. To validate the Geriatric Depression Scale (GDS) for geriatric population of Kerala and fix the cut-off point for screening depressive symptoms. 23

25 Chapter II METHODOLOGY Study design The study is a community based cross sectional survey. Study Setting The study was conducted at the Karakulam Panchayath (village) under the Nedumangadu Taluk in the Trivandrum district. The data for the study was collected from January 1 st to 31 st March Selection of subjects The Karakulam Panchayath had a population of about fifty thousand and comprised of 22 wards, with each ward having a population size ranging from 2000 to 5000.The sampling frame comprised of all residents of the Panchayath above the age of sixty (as of January 2004) from the electoral rolls. A total of 275 subjects above the age of 60 were selected by systematic sampling from two wards (135 from one ward and 140 from the other). From the electoral roll every alternate person above the age of sixty was approached at their place of residence. All persons who consented to participate after having been explained the aims of the study, procedure involved, and time required for participation were included. In cases where the alternate eligible person could not be traced due to death, change of residents, or errors in the electoral rolls the next person above the age of sixty was approached. Appointments for the interview were fixed with the help of a social worker at least one day prior to the interview. Informed verbal consent was obtained by the investigator just before the interview from the subject and care givers (if present). 24

26 Sample size estimation The sample size for the study was calculated as 256. A total of 275 subjects were approached for the study of which 259 subjects participated and 8 were unwilling to participate. After fixing the appointments, two subjects could not be interviewed as they were hospitalized and six others were not available due to other reasons. Diagnosing a case and finding the prevalence Depression was measured using the Geriatric Mental Status Schedule (GMS) in conjunction with its computerised diagnostic system AGECAT. The prevalence of depressive symptoms in elderly adults is high yet, the criteria to identify depressive disorder may leave many elders undiagnosed and untreated. Hence this study focused on depressive symptoms, which included sub threshold depression in addition to clinical cases. The GMS enabled patients to be classified by the symptom profile and type of depressive disorders by means of a computer-assisted system- The Automated Geriatric Examination for Computer Assisted Taxonomy (AGECAT). All subjects were first interviewed with the paper version of GMS, which took an average of 40 minutes. The The sample size was calculated as (Z) 2 P Q 2 Z is the confidence limit function which is 1.96 for 95% confidence interval P is the prevalence; Q = 1- P; the Precision factor A review of literature failed to find any previous published study from Kerala on geriatric depression using a valid and standardized instrument. So the assumed prevalence of depressive symptoms (20%) was based on unpublished studies and consultation with researchers working in this field. A similar study done in Northern India validating the Hindi version of a GDS 24 found a prevalence of 23%. Assuming a 20% prevalence of depressive symptoms in 60 + age group and a of 5 the sample size calculated for this study was

27 computer algorithm generated the diagnosis later during the data analysis stage. AGECAT consists of the application of hierarchical rules to the items of the GMS in order to reach a diagnosis for various psychiatric disorders (e.g. depression and dementia syndromes) with different levels of confidence. Level zero represents no syndrome, levels one and two are regarded as sub threshold syndromes, and level three and above correspond to clinical cases. In this study, all those above level zero were considered as having significant depressive symptom. The current community version GMS B3 is extensively used in dementia research in developing countries. The Malayalam translation used in the study is a modified one of a previous Malayalam version used in a 10/66 (Organization working for improving dementia research in developing countries) dementia study in the state. It has 182 questions with filter questions and branching points, and required about minutes for each subject. All the interviews were conducted by a single interviewer trained in using the GMS. Validating the Geriatric Depression Scale (GDS) The Geriatric Depression Scale short version 40 (GDS-15) was selected as a tool for regular use in the community for screening geriatric depression. The study aimed at validating the GDS against the diagnostic instrument Geriatric mental status schedule (GMS). A Malayalam translation of the GDS-15 was available from The Department of Psychology, University of Kerala, which was not validated. The questionnaire was back translated to English and the newly translated English version was again translated to Malayalam independently. Appropriate changes were made to make the tool suitable for GMS Resource Centre at the University of Liverpool holds copyright for both the GMS and AGECAT. The instruments were donated by the GMS Resource Centre, University of Liverpool for this study after approving the training given to the investigator for using GMS. 26

28 Malayalam speaking population. The questionnaire was pilot tested before the study. Though the GDS is a self-administered questionnaire bearing in mind the limitations of the study population with regard to visual problems and their lack of familiarity with the pencil and paper forms and questionnaires, the GDS was used as an interviewer administered questionnaire in this study. A single interviewer read out the Malayalam questions to each of the subjects and recorded their oral response. Both GMS and the GDS were simultaneously administered to all the study subjects at their home. After completing the data collection, the diagnosis and symptom profile generated from the GMS of each patient using the AGECAT were compared with the corresponding GDS score. The possible bias due to a single investigator administering both diagnostic schedule and screening instrument to be validated is limited as the GMS diagnosis was generated only at a later stage after completing both the questionnaires for a subject. To determine the accuracy of the GDS-15 in detecting depression, sensitivity and specificity were calculated at various cut off points against the GMS diagnosis. And the suitable cut off point for the community was settled using an ROC curve. Spearman s Rank correlation was calculated between the GMS diagnosis and the GDS based on the new cut off score to find the agreement between diagnostic instrument and screening questionnaire. Reliability of the GDS To find the stability of a measurement over time, test retest reliability of GDS was established. Thirty randomly selected subjects were retested with GDS within two weeks (mean= 8 Days) of the original interview at their residence. 27

29 The internal consistency of a measure indicates the extent to which its component parts; in the case of a scale, the individual items address a common underlying construct. The internal consistency of GDS was also tested for 30 randomly selected study subjects. Determinants of Depression This study used a separate questionnaire to collect data regarding socio demographic factors and probable determinants of depression from all subjects. The questionnaire contained two parts. The first section contained the following independent variables: Demographic factors Age, Sex and Marital status Living arrangement Occupation (Past and Current) Source of independent income (Money regularly received from any source; not necessarily earned) Education Disability Significant life events in the past one year History of mental illness in the family The second section was on chronic diseases based on reported morbidity. It included questions on the duration of diseases, type of health care, family support for care, and impediments to treatment. Analysis of data Diagnoses for individual subjects were generated using the GMS-AGECAT package. Those subjects who had case level depression (level 3-5 in AGECAT) and sub threshold 28

30 depression (Level 1-2) were grouped together into a single category to include all subjects with depressive symptoms. Point prevalence of depressive symptom among the elderly was calculated with 95% confidence interval. The validity of the screening instrument GDS was tested against the Gold standard diagnostic interview the GMS. A receiver operator characteristic curve (ROC) was plotted allowing for the choice of most appropriate cut off for the GDS. Spearman s correlation coefficient was calculated between the GDS score and GMS diagnosis to find their agreement. For test retest reliability coefficient Kappa was calculated between the test and retest score of GDS for 30 randomly selected the respondents. Internal consistency of GDS was measured using Cronbachs`s alpha. An examination of the various factors associated with depression was done by cross tabulation of determinants against the groups with and without depressive symptoms. Statistical significance of such associations was tested by the Chi-Square Test. All the statistical analysis of the data was done using the Statistical Package for Social Scientists (SPSS) version

31 Ethical concerns Informed verbal consent of all the participants were obtained prior to the interview stating the purpose of the study. Whenever a caretaker was available his\her consent was also taken as a gatekeeper but the respondents consent was the requirement. All subjects with psychological illness identified during the study were referred to the Consultant Psychiatrist at the Nedumangadu Taluk Hospital or to Department of Psychiatry, Medical College, Trivandrum as preferred by the patients and their family for further evaluation and management. 30

32 Chapter III RESULTS Out of the 275 elderly persons selected for the study, 259 were interviewed to elicit the information, giving a response rate of 94.18%. This is a good response rate for any community based study. Sample characteristics Table 3.1 Age sex distribution of the study population Age category Men (%) Women (%) Total (37.8) 52(37.1) 97 (37.5) (26.1) 43(30.7) 74 (28.6) (17.6) 24(17.1) 45 (17.4) (8.4) 11(7.9) 21 (8.1) (10.1) 10(7.1) 22 (8.5) Total 119(100.0) 140(100.0) 259 (100.0) Age and sex: The study group consists of 119 men and 140 women, thus including more women (54.1%) than men. Nearly two-thirds of the elderly are in their sixties. Women outnumber men in all age groups except in the above 80 age category. Table 3.2 Marital status of the elderly in the study population Marital status Men (%) Women (%) Total (%) Married 89 (74.8) 60 (42.9) 149 (57.5) Widowed 25 (21.0) 65 (46.4) 90 (34.7) Separated 2 (1.7) 10 (7.1) 12 (4.6) Never married 3 (2.5) 5 (3.6) 8 (3.1) 31

33 Total 119 (100.0) 140 (100.0) 259 (100.0) Marital status: In the study sample majority of men are married (74.8%) while more number of women (46.4%) are widowed. Compared to men more women are separated or unmarried. Staying with Men (%) Women (%) Total (%) Spouse 12 (10.1) 15(10.7) 27(10.4) Spouse and children 74 (62.2) 46(32.9) 120(46.3) Son or daughter 23 (19.3) 66(47.2) 89(34.4) Living alone 4 (3.4) 3 (2.1) 7 (2.7) Others 6 (5.0) 10(7.1) 16 (6.2) Total 119(100.0) 140(100.0) 259(100.0) Table 3.3 Living arrangements of the elderly in the study population Living arrangements: As majority of elderly women are widows, they live with son or daughter compared to very less number of men who live so. Only 42% of women live with spouse while 82% of men live with their spouse. Religion: Among the 259 subjects 155 (59.8%) are Hindus, 75 (29%) Christians and 29 (11.2%) Muslims. 32

34 Table 3.4 Literacy rate of the elderly in the study population Education Men (%) Women (%) Total (%) Illiterate 24 (20.2) 61 (43.6) 85(32.8) Literate 95 (79.8) 79 (56.4) 154(67.2) Total 119 (100.0) 140 (100.0) 259(100.0) Literacy: In the study population 43% of elderly women are illiterate compared to 20% of men. The illiterate group also includes elderly who had attended schools but no longer knows to read or write. Almost equal number of elderly women and men had higher education, and this is a characteristic of Kerala, where both men and women receive education. Table 3.5 Present occupations and income of the elderly in the study population Occupation Men (%) Women (%) Total No work 64 (53.8) 49 (35) 113 (43.6) Agriculture 11 (9.2) 0 (0.0) 11(4.2) Service 4 (3.4) 3 (2.1) 7(2.7) Business 3 (2.5) 2 (1.4) 5(1.9) Manual labour 6 (5.0) 4 (2.9) 10(3.9) Household work 31(26.1) 82 (58.6) 113(43.6) Total 119(100.0) 140(100.0) 259(100.0) Income Men (%) Women (%) Total (%) Income 60 (50.4) 30 (21.4) 90(34.7) No Income 59 (49.6) 110 (78.6) 169(65.3) Total 119(100.0) 140(100.0) 259(100.0) Occupation and income: More number of elderly women participates in work compared to men. Most of the elderly women participate in household work, which is often unaccounted. As a result, though 65% of women participate in some form of work, only 33

35 21% have independent income while 50% of men have some form of independent income. Table 3.6 Significant Life events in the past one year Significant Life Events in the past Men (%) Women (%) Total one year Nil 64 (53.8) 70(50.0) 134(51.7) One 31(26.0) 37(26.4) 68(26.3) Two or more 24(20.2) 33(23.6) 57(22.0) Total 119(100.0) 140(100.0) 259(100.0) Significant life event: Nearly half of the elderly (49%) who participated in the study encountered at least one significant adverse life event in the past one year and some of them faced cluster of events (two or more). Women perceived more significant life events (55.1%) compared to men. Clustering of life events was also more for women (57.9%) when compared to men. The commonest problem elderly experienced were related to finance, interpersonal problems, and illness in the family. While men are more concerned with financial problems, women faced problems related to illness and interpersonal problems. 34

36 Table 3.7 Disability and chronic illness in the study population Levels of Disability Men (%) Women (%) Total No Disability 31 (26.1) 61(43.6) 92(35.5) Mild- Moderate disability 76 (63.9) 66 (47.1) 142(54.8) Severe disability 12 (10.0) 13 (9.3) 25(9.7) Total 119(100.0) 140(100.0) 259(100.0) Disease (reported morbidity) Men (%) Women (%) Prevalence (%) Hypertension 31(26.1) 39(28.7) 70 (27) Diabetes 15(12.6) 13(9.6) 28 (10.8) Musculo skeletal problems 5(4.2) 5(3.7) 10(4) Cerebro vascular accidents (strokes) 10(8.4) 5(3.7) 15(5.8) Cardiovascular disease 34(28.6) 52(38.2) 86(32) TB/Asthma 27(22.7) 19(14.0) 46 (17.9) Cancer 1(.8) 3(2.2) 4(1.6) Disability and chronic illness: Disability was measured in relation to three routine activities-taking food, self-care (using the toilet, bathing and dressing), and moving inside the house. Around 10% of the elderly had severe disability, as they are dependent on others or bedridden. About 54% have mild to moderate disability, as they are not able to perform the regular activities as they used to. The commonest reported chronic morbidity in the elderly is musculoskeletal and joint complaints including arthritis. The reported morbidity due to hypertension, cancer and musculoskeletal complaints are more in women while diabetes, asthma, cardiovascular diseases and strokes are more among men. 35

37 Prevalence of depression Of the 259 subjects surveyed, 15 (5.8%) were diagnosed as having depressive illness (AGECAT Diagnosis level 3-5) by GMS- AGECAT warranting immediate medical attention. In addition 49 (18.9%) subjects were identified with significant depressive symptoms classified as sub threshold depression (AGECAT Diagnosis level 1-2). Table 3.8 Depressive symptoms among the elderly Diagnosis Men Women Total Depressive symptoms-absent 97(81.5) 98(70.0) 195(75.3) Sub threshold depression 6(5.0) 13(9.3) (level 1) 19(7.3) Sub threshold depression 2(1.7) 3(2.5) (level 1) 5(1.9) With symptoms of anxiety Sub threshold depression 8(6.7) 13(9.3) (level 2) 21(8.1) Sub threshold depression 2(1.7) 2(1.4) (level 2) 4(1.5) With symptoms of anxiety Depressive neurosis (Level 3) 3(2.5) 7(5.0) 10(3.9) Depressive psychosis (Level 3) 1(0.8) 2(1.4) 3(1.2) Depressive neurosis (Level 4) 0(0.0) 2(1.4) 2(0.8) Prevalence(%) Sub threshold depression 49 (18.9) Case level depression 15 (5.8) 119(100.0) 140(100.0) 259(100.0) Any Depressive symptom 64 (24.7) The point prevalence of depressive symptoms (Subthreshold and Case level depression) among the elderly is 24.7%. (95% Confidence Interval = ). Point prevalence of depressive symptoms (men) 18.49% (95%CI ) Point prevalence of depressive symptoms (women) 30.0% (95% CI ) 36