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COMMON MENTAL DISORDERS IN WOMEN ATTENDING OUTPATIENT CLINIC OF AN URBAN
LOW COST UNIT
A CROSS-SECTIONAL STUDY ON PREVALENCE, PROFILE AND ASSOCIATED FACTORS
Dissertation submitted to
The Tamil Nadu Dr. M.G.R. Medical University In part fulfilment of the requirement for
M.D. branch XVIII - Psychiatry Final Examination
May 2018
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CERTIFICATE
This is to certify that the dissertation titled “Common mental disorders in women attending outpatient clinic of an urban low cost unit - A cross-sectional study on prevalence, profile and associated factors” is the bona fide work of Dr. Aiswarya R Nair towards the MD Psychiatry Degree Examination of the Tamil Nadu Dr.
M.G.R Medical University to be conducted in May 2018. This work has not been submitted to any university in part or full.
Dr. Anna Benjamin Pulimood, MD. Pathology, PhD Principal
Christian Medical College Vellore, 632 002.
[3]
CERTIFICATE
This is to certify that the dissertation titled “Common mental disorders in women attending outpatient clinic of an urban low cost unit - A cross-sectional study on prevalence, profile and associated factors” is the bona fide work of Dr. Aiswarya R Nair towards the MD Psychiatry Degree Examination of the Tamil Nadu Dr M.G.R Medical University to be conducted in May 2018. This work has not been submitted to any university in part or full.
Dr. Mary Anju Kuruvilla, MD Professor and Head
Department of Psychiatry Christian Medical College Vellore, 632 002.
[4]
CERTIFICATE
This is to certify that the dissertation titled “Common mental disorders in women attending outpatient clinic of an urban low cost unit - A cross-sectional study on prevalence, profile and associated factors” is the bona fide work of Dr. Aiswarya R Nair towards the MD Psychiatry Degree Examination of the Tamil Nadu Dr M.G.R Medical University to be conducted in May 2018 and that this study has been done under my guidance. This work has not been submitted to any university in part or full.
Dr. Suja Kurian, DPM, MD Professor
Department of Psychiatry Christian Medical College Vellore, 632 002.
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DECLARATION
I hereby declare that this dissertation titled “Common mental disorders in women attending outpatient clinic of an urban low cost unit - A cross-sectional study on prevalence, profile and associated factors” is the bona fide work by me under the guidance of Dr. Suja Kurian, Professor, Department of Psychiatry, Christian Medical College, Vellore. This work has not been submitted to any university in part or full.
Dr. Aiswarya R Nair, DPM Post Graduate Registrar (MD) Department of Psychiatry Christian Medical College Vellore - 632 002.
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[7]
[8]
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PLAGIRISM CERTIFICATE
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ABSTRACT
Title of the abstract: Common mental disorders (CMD) in women attending outpatient clinic of an urban low cost unit - A cross-sectional study on prevalence, profile and associated factors
Department: Psychiatry
Name of the candidate: Dr. Aiswarya R Nair Degree and subject: MD, Psychiatry
Name of the guide: Dr. Suja Kurian
Objectives: To determine the prevalence of common mental disorders amongst women attending the out-patient services in a secondary care hospital, to study their profile and to determine any associations.
Methods: Consecutive, consenting women (N=172) satisfying the inclusion and exclusion criteria and attending the out-patient services in the secondary care general medical setting was evaluated for presence of common mental disorders.
Their profiles were studied and associations were determined. The tools used were, the CIS-R, sexual history questionnaire and a specially designed proforma. The people with CMD were classified according to ICD-10 diagnosis. Chi square test and independent T – test were used to compare the factors associated with CMD depending on variable type and logistic regression was done to look for adjusted effects of factors.
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Results: A prevalence of 44.78% (37.26 - 57.27%) with a confidence interval of 95% was determined. Significant associations with common mental disorders on the basis of univariate analysis was found in the domains of socio demographic variables, variables related to family structure and health (physical and psychological), sexual factors and factors related to abuse. Factors in all the aforesaid domains except abuse were found to be significant in multivariate analysis. The study urges an assessment and understanding of psychosocial factors contributing to common mental disorders, in the management of women attending primary and secondary care medical setting.
Key Words – common mental disorder, women, urban, poor
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ACKNOWLEDGEMENTS
I would like to express my gratitude to:
God,for this opportunity and his grace.
Dr. Suja Kurian, Professor of Psychiatry and my dear guide for sharing her insights on this amazing topic and for the constant help, support and encouragement throughout this study.
Dr. Sunil Abraham, my co-guide, for being a ready source of advice and giving me the permission to conduct this study in the department of Family Medicine.
All my teachers for sharing their perspectives and knowledge, for their encouragement and the wonderful years throughout the course.
Mrs. Mahasampath Gowri S., for her patient help in statistical analysis.
Dr Rajesh G for the encouragement and feedbacks.
Mrs Nandini Kathale for all the support.
Dr Arun R and Dr Jibi Achamma for all their help, and time during the enumerable instances they were instrumental in the completion of this study.
Mr. James, Mr. Suresh, Mr. Jayapal and all the administrative staff in the department who helped me at need.
The staff in LCECU for their warmth and help in identifying the study participants.
Sai and Aswin for just being there . Our parents for their love and blessings.
All my friends and colleagues for their constant encouragement and for keeping me going.
And finally, to the brave and wonderful women, my study participants, for the warriors they are, for sharing their stories, for being instrumental in my learning of psychiatry and much more.
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INDEX
S.NO. CONTENTS PAGE
NUMBER
1. Introduction 17
2. Review of Literature
Evolution of The Concept And Definition
Classificatory Systems and Common Mental Disorders Common Mental Disorders And Disability
Prevalence of Common Mental Disorders Risk Factors for Common Mental Disorders Assessment of Common Mental Disorders
Primary Care, Mental Health and Common Mental Disorders
22 24 25
26 31 39 42
3. Rationale of the study 45
4. Materials and Methods 46
5. Results 56
6. Discussion 84
7. Strengths and Limitations of the study 100
8. Conclusion 101
9. Future Direction 103
10. Appendix 104
11. Bibliography 124
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LIST OF TABLES
Table Number
Table Label Page
Number Table 1 Socio - Demographic and economic details of married
women attending the urban low cost unit and participated
in the study 58
Table 2 Factors related to family 59
Table 3 Chronic Medical Problems in women who attended the
low cost urban centre and participated in the study 60
Table 4 Obstetric and Gynaecological Factors 61
Table 5 Factors related to psychological well-being 68 Table 6 Association between Common Mental Disorders and
Socio-Demographic, and economic variables 73 Table 7 Association of Common Mental Disorders with factors
related to family structure 74
Table 8 Association between common mental disorders and
chronic physical illness 76
Table 9 Association between common mental disorders and
participant’s Obstetric and Gynaecological history 76
Table 10 Psychological Factors 78
Table 11 Association of common mental disorders with factors
related to sexual history 79
Table 12 Association between abuse and common mental disorders 79 Table 13 Association between Common Mental Disorders and
Socio-Demographic and Economic variables 80 Table 14 Association of Common Mental Disorders with factors
related to family 81
Table 15 Association of Common Mental Disorders with factors related to health (physical and psychological), sexual history and abuse
83
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LIST OF FIGURES
Table Number Label of Figure Page
Number Figure 1 Source of first knowledge about sex among
participants
63
Figure 2 Attitude towards sex among participants 64 Figure 3 Methods of Contraception practiced by participants 64 Figure 4
Satisfaction regarding sexual life 65
Figure 5 Availability of privacy at home as revealed by the participants
65
Figure 6 Satisfaction regarding sexual functioning 65 Figure 7 Prevalence of Physical and Sexual Abuse 67 Figure 8 Prevalence of Symptoms in different domains
according to CIS-R
70
Figure 9 Common Mental Disorders classified according to ICD-10
71
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INTRODUCTION
Common mental disorders (CMDs) are conditions reflecting distress states which are manifested commonly as depressive and unexplained somatic symptoms. They are by and large encountered in community and primary care settings. The term Common mental disorders were proposed by Goldberg and Huxley in 1992 in their book on Common mental disorders: a biosocial model. The significance of the group of illnesses is increasing by day with more and more research showing them to be the leading cause for disability related to mental health in the global burden of disease.
A multicenter, cross-national collaborative study conducted by WHO concluded that, in major cultures around the world, psychiatric disorder in primary care is common and associated with substantial levels of disability which was most strongly related to major depression, panic disorder, generalized anxiety, and neurasthenia, which remain within the domain of common mental disorders (1).
These disorders might occur alone or with other physical co morbidities. There have also been significant research and findings on the intricacies and challenges related to diagnosis, and management especially at a primary and secondary care level. The significance of sub-threshold symptoms of mental illness and missing them in an outpatient clinic adds to the conundrum. Impact of CMD has been studied and is seen to negatively influence a extensive range of health, social and economic outcomes (2).
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Common Mental Disorders in Women
Studies leave as with no doubts to the fact that gender is a very critical determinant of mental well being. Sex predetermines the differential control women and men have over the social and economic determinants of their lives and therefore mental health. It also influences, their social status and treatment in society and thereby their exposure and vulnerability to specific mental health risks. Studies show that about 80% of people who are affected by wars and displacement are women and children. Lifetime prevalence of violence against women is between 16% to 50%. One in five women goes through an attempt rape or falls victim to rape (3).
There are unique factors which are pertinent to women in terms of their social and cultural roles, reproductive physiological cycles and stages (4). There is great relevance for the problems and mental health issues in women during gestation and post partum as it has profound and long term significance on the mother’s and child’s health and safety (3). Gender disadvantage and societal discrimination also plays an important role in the women’s health. This makes it important to understand the context and ensure safe and protecting environment in addition to providing treatment and overall management (4).
WHO report states distinctly that prevalence of gender differences or rather gender disadvantage is reflected particularly in the prevalence rates of common mental disorders (3). Plummeting the over-representation of females with common mental disorders will contribute extensively to decreasing the global
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burden of disease and disability due to mental illness/ ill health. Common mental disorders are significantly related to co-occurring risk factors such as stressors, negative life experience and gender based roles. Gender explicit risks for common mental disorders that affect women include gender based violence, income inequality, low income and, low or inferior social rank and the unrelenting accountability for being the care giver for others (3). There is also the concept that restructuring of policies causing economic and social principal that is sudden and severe changes which are drastic, disruptive and out of one’s control significantly increase gender inequality and the prevalence of common mental disorder (3). Gender related risks, social and financial pressures, pressures related to handling multiple roles and responsibilities increase their vulnerability for common mental disorders. The effect of chronic, cumulative stress in woman is a domain that needs further research (3).
The difference in symptom presentation and the practical difficulties in distinguishing anxiety and depressive symptoms in a general medical setting or primary care has been cited by many researchers and clinicians (5,6).This is relevant as this presentation is seen most frequently in primary or secondary care setting.
One of the main differences is the differing conceptual models amongst practioners employed in psychiatric and general settings. Psychiatrists often employ a medical model while general practioners give emphasis on stress, personality ,the psycho- social context, and coping (6). Another important difference is the variance in patient profile. The patients who visit psychiatric facilities frequently have chronic
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and severe illness and are motivated to receive specialist treatment in comparison to those who visit GPs who may have milder or less discrete forms of illness often associated with concomitant psychosocial stress (6). In terms of presentation in primary care commonly seen are mixed presentations of anxiety and depression.
Sub threshold symptoms are common and many who cross the cut offs do not have the complete syndromal cluster of depression or anxiety. One of the commonest presentation of psychiatric problems in primary care is that of medically unexplained somatic symptoms (6). A significant fraction of the presentation also gives history of associated distress or psychological stress (6). Many of these patients do not fulfill the full syndromal criteria attributes of corresponding diagnosis in ICD and show spontaneous remission or earlier remission (6). In the International Classification of Disease 10 (ICD 10) for primary care, the several categories of depression in the ICD-10 have been clubbed into a single category of depression. This will technically amount to patients with features of biological depression being clubbed with normal people who cannot cope with the demands of life because of poor coping skills and those with adjustment reactions due to stress (6). Some of the other clinical tools used like on standardized interview schedules (e.g. Revised Clinical Interview Schedules (CISR)) are continuously distributed with no point of rarity between cases and non cases. This is yet another limitation in the primary setting making dichotomous clinical decision making difficult (6).
Urbanization may be described as the increase in population in towns and cities (7).
Its significance also lies in the aspect of it being inclusive of the economic,
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psychological and social aspects of the demographic shift (7). UN World Urbanization Prospects 2008 states that by the year 2020 the urban population growth is expected to reach 41% as compared to 28% in 2008 (7). Multiple studies support that urbanization is associated with an increase in prevalence of mental disorders, globally. The prevalence of mental illnesses in Urban India was found to be 80.6% as compared to 48.9% in Rural India according to a meta analysis by Chandrasekhar and Reddy (8). Some of the theories supported being lack of social support (9) a slow or poor growth in infrastructure not keeping up with the pace of increase in urban population (7). Transition from joint to nuclear families, environmental adversities and poverty adding to the equation (7). There are also studies which support a biological basis. There are studies assessing increased contact to non-natural physical elements typical of urban settings in animal models and those studying exposure to artificial source of illumination. The results have showed more biomarkers of mental illnesses like major depression in the same (10).
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REVIEW OF LITERATURE
EVOLUTION OF THE CONCEPT AND DEFINITION
During 1960s-70s the World Health Organization brought forward the concept of Severe Mental Illness (SMIs). Disorders which fell into that category were mainly epilepsy, schizophrenia and manic depressive psychosis (MDP). Later in early 90s depression, Anxiety and Unexplained somatic illnesses were regarded as Minor mental disorders. Since operationalising the diagnosis of major and the minor mental disorders, there has been manifold increase in large scale population based studies in both. But the studies and researches consistently showed that those so called minor mental disorders were more common and had significant impact on the burden of health care delivery systems. Thus, corrections were made and these three groups of disorders were called collectively as common mental disorders (CMDs) (11). Thereafter there has been better focus on the group of illnesses presently regarded as common mental disorders.
The concept of common disorder was an attempt in the part of the authors Huxley and Goldberg, one a physician and the other trained in social sciences to combine insights from social psychiatry and biological psychiatry to define a model for common mental disorders. The concept was defined by them in their book, Common mental disorders: A bio-social model, 1992. They defined it as a group of distress states manifesting with anxiety, depressive and unexplained somatic
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symptoms and as the contemporary equivalent of neurotic disorders typically encountered in community and primary care settings.
This model was unique in that it gave equal emphasis in determining susceptibility of mental disorder to psychological and social events and to factors affecting physical health. It surveys primarily three factors in a given individual. The factors are vulnerability, destabilization and restitution. Vulnerability is defined as factors which make some individuals more susceptible than others to episodes of mental disorder, destabilization is defined as the process of beginning to experience symptoms and restitution is defined as factors which determine how long an episode of illness will last in a particular individual (12). This model explores the physical processes which mark states of depression and anxiety, and attempts to show the ways in which environmental factors can influence upon these processes.
The two major symptom dimensions constituting common mental disorders are seen to be depression and anxiety symptoms. Over the years the concept has evolved and presently it is seen more as dimensional or as lying in a spectrum as compared to a categorical one. This is so as the former is seen as more apt to understand or conceptualize the correlation between social and biological factors (13).
Common mental disorders are seen to be accompanied with substantial disease burden and highly prevalent across the world. Recent advances and studies into the area of epidemiology pertaining to psychiatry highlights the relevance of common
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mental disorders based on its impact upon global burden of diseases (1). It is also seen to have an effect on individual distress and dysfunctionality (14).
The data suggests evidence for a disparity between the association of psychiatric co morbidity with major mental illness and subsequent disability. The reasons cited for this being the initial focus on major mental illnesses and thereby probably missing out on the impact of sub threshold symptoms (15). Initially the sub threshold symptoms contributing to disease burden were thought to be part of depressive syndrome. Latest evidence supports them to be also part of anxiety spectrum and related disorders (15). It has also been studied and shown that the overall cost in society of psychiatric symptoms might be underestimated when looking at only specific syndromes or psychiatric diagnoses.
CLASSIFICATORY SYSTEMS AND COMMON MENTAL DISRODERS The prevalent systems of classification including the ICD-10 and DSM 5 can be used to describe common mental disorders. However they are often criticized as being tailored to a secondary or tertiary psychiatric setting and that they may not readily pick up the subtle sub syndromal symptoms or the distress states which are quite common presentations especially in a primary care. The difficulties in separating anxiety and depression pictures in primary care setting have been documented time and again. These presentations have been shown as highly prevalent and also having huge impacts on Quality of life and DALY. ICD-10 primary care version which was meant for use by primary health center (PHC)
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practitioners may be quite appropriately used for the diagnosis of common mental disorders in primary care (16,17).
The ICD10-PHC (Primary Care version) is a basic version of the WHO’s International Classification of Diseases (ICD-10) meant for use in primary health care settings and general practice. This condensed classification system is a rough equivalence but not the exact equivalent of ICD-10 classification (18). For instance, the chapter on mental and behavioral disorders enlists and describes 25 disorders which are commonly managed within primary care as compare to about 450 described in Chapter V of ICD-10 (18). The ICD10-PHC also serves as a useful and important tool for in translating, transmitting and presenting applications of global mental health knowledge to public health, health systems contexts and populations’ health. ICD11-PHC, the revision of ICD10-PHC, is currently under development.
COMMON MENTAL DISORDERS AND DISABILITY
Analysis by Global Burden of Diseases 2000 bought out the finding that unipolar depressive disorders causes a vast burden on the world and they are ranked as the fourth leading cause of burden among all diseases. This accounts for 4.4% of the total DALYs (Disability adjusted life years) and 11.9% of total YLDs (Years lived with disabilities) (19). If current epidemiological and demographic trends continue, it is estimated that the burden of depression will increase to constitute about 5.7%
of the total burden of disease, and thereby will become the second leading cause of
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DALYs lost (2). It will be second only to ischemic heart disease for DALYs lost for both sexes, worldwide. In the developed countries, it is estimated that depression will become the first ranking cause of burden of disease. There is a need for programmes targeting management of Common Mental Disorders and therefore more research on the presentation and the population to be targeted.
PREVALENCE OF COMMON MENTAL DISORDERS
In the past nearly thirty years following the introduction of the concept of common mental disorder, we have witnessed a burgeoning of research in the field of epidemiology of psychiatric illnesses, globally.
These studies have found out significant, inter-survey heterogeneity in the different studied populations. They have also reported substantial variability in period and lifetime prevalence estimates of common mental disorder even after removal of possible confounders. However there was no significant difference between point and period prevalence in sub-group analysis and therefore it seems like we can retain focus on 12 month prevalence.
The prevalence supported by most studies are obtained from populations with potentially varying age structures especially between high income countries (HIC) and low and middle income countries (LMIC), this factor may be causing variation in prevalence of common mental disorder. These studies have also featured the high prevalence of physical co morbidity along with common mental disorders. It
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was observed that there were higher estimates of prevalence of common mental disorders in those studies where sample sizes were smaller i.e. less than 1000 in comparison with studies with larger sample sizes.
A significant body of research has been dedicated to the patterns and variations in expressions of idioms of distress across contexts and cultures. There is also evidence for common mental disorders as being expressions of distress. This has again emphasized the need for using culture specific and sensitive tools for an accurate estimation.
The key results of all the studies are that common mental disorders, often showing co morbid patterns, are highly prevalent, affecting substantial sections of all the populations surveyed and there is evidence for significant regional differences in the prevalence of common mental disorder. One of the strongest findings from research across the continents have been the robust gender effect persistent in the prevalence of common mental disorder that was apparent for both period and lifetime prevalence estimates (20). There is clear evidence for substantial disability due to the same across borders and time.
There is a lack of studies to estimate differences in prevalence across time and about the nature of changes across time despite some evidence that prevalence rates varied across decades and also for assessment of national /international policies which have been implemented for improving mental health (21).
Global Prevalence of Common Mental Disorder
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Research shows that studies done during the 1990s showed a higher pooled prevalence rates as compared to surveys undertaken during other decades. A Meta analysis by Steel Z reflected the same particularly considering period prevalence (21). A meta analysis reviewing the data from 1980–2013 picked up a prevalence of one in five respondents (17.6%;16.3–18.9%) for a common mental disorder during the 1 year and 29.2% (25.9–32.6%) had lifetime prevalence (21). The studies also picked up regional variation consistently when estimating its prevalence. An ongoing challenge in psychiatric epidemiology seems to be recognizing the reasons for variability in the prevalence of common mental disorder globally (21). This focuses the need for encouraging regional studies even if in limited population.
Global prevalence of common mental disorder based on clinical sub- domain and gender
Some of the most recent meta-analysis (4) on the pooled period prevalence of mood disorder across 148 surveys was 5.4% (4.9–6.0%) with a pooled lifetime prevalence of 9.6% (8.5–10.7%) across 83 surveys. For anxiety disorders, the pooled period prevalence was 6.7% (6.0–7.6%) from 122 surveys with a lifetime prevalence of 12.9% (11.3–14.7%) from 70 surveys. Based on 104 surveys disorders due to substance use showed a pooled period prevalence coming to 3.8% (3.4–4.3%). Lifetime prevalence estimated was about 10.7% (9.2–12.4%) based on 74 surveys after reasons of unwarranted influence was removed (21).
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A higher aggregated estimate of period prevalence of common mental disorder (19.8%; 18.3–21.3%) was found in females as compared to males (15.2%, 14.1–
16.3%). When exploring clinical sub-domains, a consistent pattern of results however emerged for gender in the sub domains of mood and anxiety. The prevalence rates for mood was found to be (period 7.3%, 6.5–8.1%; lifetime 14.0%, 12.4–15.9%) and in anxiety disorders (period 8.7%, 7.6–9.8%; lifetime 18.2%, 16.2–20.4%) .This is in comparison to men with the following rates of mood period, 4.0%, (3.5–4.6%) and lifetime 7.3%,( 6.3–8.5%) and anxiety period being 4.3% (3.7–4.9%) and lifetime of 10.1% (8.8–11.6%) (21, 22).
In contrast, men had higher pooled prevalence rates for substance disorders (period 7.5%, 6.7–8.4%; lifetime 17.1%, 14.4–20.3%) compared with women (period 2.0%,1.6–2.5%; lifetime 5.0%, 3.9–8%) (21).
Regional Studies
A study done in Vellore among outpatients showed a high prevalence of (111/327;
33%) of common mental disorder. The study was done in people attending the base hospital of a community health of a tertiary care hospital in Vellore. The patients were seen to satisfying the criteria for ICD-10 Primary care version (ICD-10 PHC) (23).
There is a limitation in terms of number of studies on the prevalence of common mental disorders targeting women exclusively in low-income country. There is a longitudinal study, in Goa studying the incidence in women. It also looks at the
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determinants of common mental disorders which have scarcely been attempted in longitudinal studies. A study with a sample size of 2494 women, showed incident cases of 39 amongst 2166 participants (5). The target population was aged; 18 to 50 years. It helped to identify significant risk factors which were considered pertinent and important in our population. These will be discussed under the section on risk factors. The study concludes that mental health programmes in our region should be considerate of women. They should target to allay the burden of mental disorder in women. With special consideration to women with chronic physical illness, those with gynecological symptoms, women belonging to LSES, and tobacco users (20).
In a study examining the association of common mental disorders in primary health clinic attendees with indicators of poverty and disability in Goa, India, the prevalence was found to be 46.5% (8).
Another study attempted to delineate categories and causes of common mental disorders (CMD) and their management as understood by traditional healers practicing in rural South India (25). It had a sample of 72 patients who were interviewed with the Short Explanatory Model Interview (SEMI) and the clinical Interview Schedule-Revised (CIS-R). Thirty patients (42.3%) satisfied the ICD-10 Primary Care Version diagnostic criteria also. The most prevalent diagnosis was Mixed anxiety depression was (40%) (25).This study emphasized that the understanding of the perspectives of local patient with common mental disorders is
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essential for modern medicine to be culturally sensitive and also to provide locally acceptable health care.
However there was limited information on the prevalence of CMD in women, which is the population identified globally to have a gender disadvantage and therefore a higher prevalence of common mental disorders in our population. There was also limited information about the profile or probable associations which might be significant in the local population.
RISK FACTORS FOR COMMON MENTAL DISORDERS 1. Poverty
One of the most consistent finding is that common mental disorder is most common amongst people with poor standards of living .(26).This was found to be free of factors of occupational and social class (26, 27, 28). Multiple studies have recorded association between mental disorders and indicators of poverty. One of the most consistent association picked up was low levels of education and unemployment which are powerful indicators of poverty (29). Financial strain was an influential independent predictor of common mental disorders with respect to the onset and maintenance of illness. Poverty and unemployment were associated with the mainly maintenance of episodes of most common mental disorders but not significantly so with their onset (28). Evidence also show that the effect of poverty increased with the level of baseline morbidity (28).
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Experience of hopelessness and insecurity, the risks of violence and physical ill- health effects and susceptibility to rapid social change may explain the greater vulnerability of the poor to common mental disorders (29). Studies done on primary care attenders in Harare in Zimbabwe, Goa in India and Santiago in Chile brought out that gender disadvantage, poverty and low education were significantly associated with common mental disorders (30). This was also reported by 2 studies based on community samples in Pelotasin and Olinda Brazil (31). Studies in inequalities related to health also reveals vulnerability to common mental disorder for female gender, inability to buy food due to financial constraints and also being in debt (32). The said cases with the aforesaid mentioned associations scored appreciably higher on measures of disability (32).
Socio-economic factors which were by far and large found as most frequently and strongly associated with common mental disorders were those related to deprivation and poverty. They are indicated by low educational status, household income, not having access to running water at home, experiencing hunger and having difficulties in making ends meet (20). The association between poverty and common mental disorders has been replicated in countries extremely diverse in their economic strength. This finding suggests that relative poverty might be the key factor (9).
2. Social disadvantage
'Psychotic' psychiatric illnesses and multiple physical conditions are known to be distributed unfairly by social position (33). Psychotic illnesses are considered to be
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severe and exerting a profound consequence on the persons social standing are however relatively rare in comparison to common mental disorders with relatively more (22) prevalence. Common mental disorders are also found as more prevalent in socially disadvantaged populace (34). The plausible mechanisms mediating this association is said to be multiple and diverse. The direct and indirect expenses of mental ill-being is said to worsen the financial condition, thereby producing a brutal cycle of poverty and mental disorder (29). Some other precise markers of social disadvantage according to literature are indicators of employment, education and material circumstances (35). Occupational class seems to be a less consistent marker (35). WHO report of 2014 calls forth countries to take steps to improve conditions and quality of daily life prior to birth, during early childhood, during school age, throughout family forming and working ages and through old age. It also urges nations to provide opportunities to perk up mental well being of population and to lessen the menace of mental disorders linked with social inequalities (34).
3. Gender and common mental disorders
Gender-based differences in the prevalence of common mental disorders may be arising due to psychosocial, epidemiological, biomedical and may be even due to a global perspective (36). These include genetic factors, physiological factors, anatomical factors, hormonal factors those related to personality and coping, related to gender roles, social adversities and symptom reporting (36). Population- based risk factors along with social determinants act together with each other and
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aggravate biological vulnerabilities (36). Amongst the profile of mental illness the sex difference seems to be most significant for common mental disorders (36).
In clinical assessment of CMD in women , studies support the exploration of factors like violence and gender disadvantage (37). Some examples cited for gender disadvantage are deficiency of autonomy in decision making ,the experience of intimate partner violence, lack of support for daily activities and being married and bearing children during adolescence (37). Reproductive health is a major priorities in public health, and is a fundamental and unchallengeable part of women's health (38). Reproductive tract infections (RTIs) are widely prevalent and creates a heavy burden on physical ill health on women which in turn may directly or indirectly affect mental health (37). The unique social role woman experiences in relation to menstruation, childbearing, and infertility (37) needs further studying. Gender being a social construct will be influenced by cultural and ethnicity. Studies have stressed the importance of understanding the ethnic and cultural relevance of the same (39).
Women between the age 18 and 50 years was found to be the demographic group at maximum risk (20), being divorced or married or widowed and gynecological morbidity (experiencing abnormal vaginal discharge) were seen as pertinent factors in the group (9). The evidence for high prevalence in the widowed, divorced or married was strong, and independent with an increased risk for common mental disorder (9). Literature review shows gender disadvantage being an important risk factor for common mental disorder and that women are being disproportionately affected by common mental disorder.
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All these evidence based on studies and meta analysis points towards the fact that efficient strategies reduction in for risk factors’ related to mental illnesses must not be gender-neutral (36). This is relevant as the risks in particular are gender- specific, and the status of women’s health and life opportunities remain low globally (36). The pervasive violation of women’s rights, including their reproductive rights, contributes directly to the growing burden of disability caused by poor mental health (36). Therefore, multi-disciplinary actions at the level of policy making and implementation in favour of women’s autonomy and mental health is crucial (36). Attention and studies focusing on factors that facilitate coping with stress or distress and interventional programmes at the community and primary care level are the need of the hour (36).
4. Urbanization and common mental disorders
One of the areas which has been said to be affected the most due to urbanization is South Asia. This region is the most heavily populated and one of the areas where there is multitudes living below the poverty line (40). The disease burden and range of disorders associated with urbanization is enormous and broad. It includes diseases and deviances ranging from severe depression, substance abuse, dementia, crime, PTSD (10) and family disintegration (7). The other important factor being lack of carers for people with mental and physical illnesses, especially the geriatric population, with the shift of the young towards the cities. There has also been suggestions that social deviance might be due to many of the social
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processes associated with urbanization, including accommodation, assimilation, class conflict competition (41).
There is enough evidence to state that urbanization has lead to an increase in mental illness and there is evidence to support multimodal association including biological and environmental factors.
5. Gynecological morbidity and common mental disorders
For a long time clinical observations and suspicions have shown significant correlation between mental illnesses and gynecological co morbidity(42,43). There are also attempts to correlate psychiatric co morbidity in women to their age and status of menstruation and thereby classifying into groups as menstruating, perimenopausal and menopausal groups. The reasons are suggested to be multi factorial. Studies have also considered the reason for correlation to be also due to gynecological illness causing the CMD (37). Recent studies have not picked up any association between biological indicators signifying reproductive health and CMDs and therefore they have postulated that the association might be explained better by the relation that the seemingly “physical complaints” are due to the result of CMDs (37). For instance a study exploring the risk factors in a patient complaining of vaginal discharge found no association with reproductive tract infection and high association with psychosocial factors (44). Studies have shown that gynecological complaints may be idioms of distress in a women facing emotional distress and social disadvantage (45).
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Nearly all studies that reflect the propose psychosocial factors as the main association and urge for syndromal approach to gynaecological symptoms (44).
Some studies suggest the variety of etiologies for the symptoms might lie along the continuum between longstanding social difficulties and common mental disorder (9). All studies agree that the world wide association of psychological distress in gynecology patients merits attention and further study (46–48).
6. Domestic violence and common mental disorders
Violence in the form of sexual and physical violence is seen to be associated with psychiatric illness and physical illness (49–53). Studies have also reported that the said associations could not be explained by differences in socio demographic factors like age, marital status or education (50). Existing research shows that psychological and physical illnesses are endemic to people subjected to intimate partner violence (51). The presentation and prevention of the same is also seen to be culture specific (51).
In a household survey of rural, urban non-slum and urban slum areas from seven sites in India, the population of women aged 15-49 years was sampled and findings indicate a strong association between domestic spousal violence and poor mental health (54). However after adjusting poverty and other factors, this was not replicated to be an independent factor in a recent study (9). There is evidence supporting that domestic violence is emerging as a significant determinant of mental health as well as a global issue causing preventable mortality and morbidity in women (51).
[38]
7. Others
a) Physical co morbidity
Multiple studies have confirmed that there is significant co-morbidity between physical and mental health problems (12). This association has been studied by many and is seen to be bidirectional (12). There are various mechanisms explaining the same including biological pathways connecting physical illnesses especially chronic illnesses and common mental disorder (9). Other mechanisms suggested are the side effects of treatments for chronic illnesses, the effects of disability and disability associated with chronic diseases and their impacts on mental health (9). Studies on structure examination of common mental disorders also supports evidence for co-morbidity on the basis of, fundamental core psychopathological processes (55).
b) Substance use
Six reasons are mentioned by Armstrong and Costello for exploring co-morbidity between psychopathology and substance use (56). This includes hypothesis that the co morbid disorders are mutually precipitating, perpetuating and maintaining each other. Also that treatment seeking varies with the presenting symptom, pattern of temporality and the treatment setting (56). There are implications for the interaction between the aforesaid patterns and also with socio demographic features especially SES (56).
[39]
Western literature has supported evidence for association with emotional distress and the use of tobacco since many decades (57). This result has been replicated in an Indian study in women (9). There may be several mechanisms which can explain this but the relevance of the study lies in the fact that this could be proved in our population where tobacco use in women is quite rare.
Studies have also bought about the effects of substance use in the mental health of the family and that an early intervention in substance use disorders is associated with better outcome for the entire family (58).
c) Underprivileged
There have been enumerable studies proving that mental ill health is more prevalent in the underprivileged, immigrants, the vulnerable, uninsured etc. There is evidence for increased occurrence of the same in population / where utilization of health facility is less for any reason (59). Evidence shows a plethora of untreated or poorly treated mental illnesses existing in the affluent United States, particularly among groups such as African Americans and the underinsured (14).
ASSESSMENT OF COMMON MENTAL DISORDERS
Screening Tools
Concise screening instruments are vital for developing mental health in (LMIC) low and middle income countries. Adopting appropriate screening instruments is
[40]
therefore an important first step to integrate care for CMDs into existing primary health care (PHC) services and also for enhancing research and training in LMIC (60). Screening tools can also be used as part of a mental health training package for PHC workers (61).
The Importance of Cultural Validation
There is a lot of importance given for cultural sensitivity as this in turn is supposed to increase overall sensitivity of the instrument in diagnosing CMD. For instance, distress is believed to be more commonly expressed through somatic symptoms and local idioms. This is also taking into account that although CMDs are prevalent in all regions worldwide, clinical presentation does differ between settings (62).
For cross-cultural application of a screening tool, it is most important to assess criterion validity (63). This involves comparing the results of a screening tool to those of a recognized gold standard, defined as ‘a relatively irrefutable standard that constitutes recognized and accepted evidence that a certain disease exists (64).
The most reliable gold standards employed in cross-cultural mental health research are diagnostic interviews conducted by qualified mental health professionals (20).
Choosing a Screening Tool
It is recommended to choose a screening tool, taking into account all the factors mentioned regarding cultural sensitivity and validity preferably following a pilot
[41]
study .If applicable using the tool locally adapted is considered practical. Some of the recommended screening tools are GHQ-5/12 and SRQ-20 as they demonstrate the strongest psychometric properties.
CIS-R AND CMD
The clinical Interview Schedule-Revised is a fully structured diagnostic instrument that was developed from an existing instrument, the Clinical Interview Schedule (CIS), which was designed for the use of clinically experienced interviewers such as psychiatrists (65). It was revised in order to increase standardization and to make it suitable to be used by trained lay interviewers in assessing minor psychiatric morbidity in the community, general hospital, occupational and primary care research (66).
The CIS-R has been validated previously in multiple languages and the results are widely known (67). The CIS-R has also been used to validate other scales in regional languages. Kuruvilla et al has used the CIS-R to validate the 12-item GHQ in Tamil (68). The ICD-10 diagnoses could be derived for the data from an algorithm, based on the Published Diagnostic Criteria for Research (3). A computer based algorithm has also been developed and is presently in use to allow production of ICD-10 diagnosis using a program called PROQSY or Programmable Questionnaire System (4). This program enables the automatic generation of diagnoses without psychiatric consultation.
Diagnosis
Common mental disorders are typically encountered in community and primary care settings and therefore focus has been rightly placed on its management at
[42]
primary care level. ICD-10 primary care version meant for the use by primary health centre (PHC) practitioners can be most appropriately used in primary care for the diagnosis of common mental disorders (69,26).
PRIMARY CARE, MENTAL HEALTH AND COMMON MENTAL DISORDERS
Definition
Mental health in primary care can be defined as providing basic or crucial curative and preventive mental health care at the first contact or point of entry of the patient into the health care system (73).
Relevance
Primary care doctors are the keystone for identification, diagnosis, management and specialist referral for all types of illnesses, irrespective of whether they are psychological, physical or both. The last two decades have seen an additional emphasis of this role, predominantly with respect to the treatment of mental disorders in primary care. WHO has recommended that treatment of all these disorders should be based in primary care to be more effective and accessible to all the community people (11). The reasons for the same are manifold. At least one third of their consultations have a direct and explicit psychological component (70).
International epidemiological evidence suggests that, of all the people with mental disorder who receive treatment, a large proportion obtain at least minimal intervention through their primary care doctor (71,72). Also the continuing trend of
[43]
reducing psychiatric hospital beds and also probably the unequal allocation of National funds contributes to a larger burden of psychiatric patients in outpatient and, particularly, primary care settings. Finally, the rapidly accumulating knowledge in clinical neuroscience and clinical psychology has resulted in various new treatment options for a wide range of neuropsychiatric conditions and disorders, and many of these can be applied in primary care.
Structure
The structure of mental health care in primary care is generally understood in terms of the “pathways to care” model. Accessing mental health care involves passing through five levels and three filters between the community and specialist care (74). The model highlights the decreasing proportion of the total population who access higher levels and the important role of the primary care clinician, whose ability to detect disorder in presenting patients (filter 2) and propensity to refer (filter 3), represent key barriers to care. Hence a wide range of mental health problems present in primary care (74).
Management of Common Mental Disorders in Primary Care
This includes recognition, further assessment deciding on the type and level of care for each presentation. The management would also depend on the model of care chosen which can be by training primary care staff (75), Consultation-liaison model (76), Collaborative care (77) or by Replacement / Referral.
A ‘stepped care’ approach has been advocated in mild to moderate depressive illnesses in younger population which principally involves choosing the least
[44]
intrusive intervention required to achieve clinical change for an individual.
Progression through levels of care is determined on the basis of patient response.
Support for self-care is additional feature in this approach. Affordable antidepressants such as fluoxetine are considered the treatment of choice as they are associated with improved clinical and economic outcomes, especially in the short term (78).
The most effective management policy is an ongoing, interactive, contextually relevant continuing education which focuses not only on knowledge, but also on skills and attitudes of primary care physicians (79).
Challenges
There are multiple challenges in primary care management. The challenge can be at the policy level like the extent of the problem being disproportionate to the limited mental health budget. It can be an absent or inadequate mental health policy or legislation or health insurance. It can also be benefits which discriminate against persons with mental and behavioral disorders. It can be at the level of Primary health care due to lack of awareness, skills, training and supervision for mental health. It may be a poorly developed infra structure. It can also be due to a lack of resources in terms of human resources or psychotropic drugs. We also have to take into consideration factors like stigma and discrimination, urbanization, war and conflicts, disaster and of course poverty.
[45]
RATIONALE FOR THE STUDY
The evidence base for risk factors of common mental disorders being high in LMIC is significant. Gender disadvantage has also been decidedly seen as a risk factor for CMD. There is also increasing evidence that systematic, small-area studies are needed to determine the prevalence of disorders as areas differ in levels of absolute and relative poverty. The significance of small area studies lies in identifying the social issues and cultural contexts locally as well as identifying the prevalent patterns of probable associations based on large area studies and, conversely, the factors that help reduce the risk in persons who face severe economic or social adversity.
This study aims to look for prevalence of CMD in the high risk population, i.e women in the age group 18-50 years, in an attempt to find the probable associations, which will benefit our knowledge, approach, further research and might potentially benefit in policy making which is the need of the hour for this vulnerable population.
Newly emerging social, medical, educational and legal strategies, offer new local models which are culturally sensitive to promote social transformations beginning with raising the status and standards of living in women . The ubiquity, depth and variability of domestic violence in different cultures require added research to encourage the acknowledgment, awareness, intervention and avoidance of domestic violence that are both locally specific, culturally sensitive and internationally instructive (51).
[46]
MATERIALS AND METHODS
Study Design
A cross-sectional study design was adopted for this study. Patients were screened on the basis of the inclusion and exclusion criteria and after obtaining informed consent. Questionnaires and instruments used were applied cross-sectionally to assess the prevalence of common mental disorder and associated factors in women who are attending the outpatient services in this urban medical setting.
Site and Setting for the study
Low Cost Effective Care Unit (LCECU) Kosapet, Vellore, Tamil Nadu, managed by the Department of Family Medicine, Christian Medical College, Vellore, is located in Vellore town. Established in 1983, this unit caters to people belonging to the catchment area, Kosapet area with a population between 65000 and 75000 belonging to Vellore Corporation. It caters to about 5 neighborhoods in the area which houses multiple urban slums. This hospital aims to meet out effective care at the lowest possible cost and serves the people belonging to low socio economic status. This hospital also runs multiple outreach programmes to the community with a team consisting of doctors and other health workers. Besides giving care at the door step, these programmes also aim to bridge the gap between illness and care. It acts as an interface between community and the unit enabling referrals to the hospital when deemed necessary.
[47]
The outpatient turn out to the hospital on any day is roughly about 200 per day.
Patients are managed by the family physician looks out for psychosocial issues and management also includes psychosocial interventions which is the holistic philosophy of family medicine. There are also liaison clinics run by multiple specialties including psychiatry in this hospital.
This study was approved by the institutional review board (IRB Number: 10302) and was carried out as a collaborative study between the department of Psychiatry and department of Family Medicine, CMC, Vellore
Sample size calculation
Estimates of prevalence of common mental disorders among women were not available from Tamil Nadu. The study sample size was calculated based on the findings of a previous study, the validation of the Tamil version of the 12 item general health questionnaire which revealed a 33% prevalence of common mental disorders (23).
A minimum sample size of 139 was calculated for finding the prevalence of common mental disorders with a precision of 8 and confidence interval of 95%.
Following formula was used N= 4 x p x q / d x d where p = prevalence of CMD q =1- p
d = precision
[48]
On applying the formula (N= 4 x 33 x 67 / 8 x 8), the sample size of 139 was estimated.
Consecutive women, aged between 18-50 years, attending the out-patient department of LCECU Hospital, Kosapet, were screened during the months of January to May 2017.
Women attending the outpatient department for their medical problems were recruited following the screening and evaluated for presence of common mental disorders. Women who could communicate in Tamil/English and gave informed consent for the study were included. Following recruitment, they were interviewed at a single point of time. Data collection was done using the clinical research form.
Proposed scales were also applied at a single point of time. A total of 172 women were recruited during 5 months of data collection.
Inclusion and Exclusion Criteria Inclusion criteria
1) Women who are married aged 18- 50yrs attending outpatient department 2) Tamil speaking women
Exclusion criteria
1. Women attending outpatient department who are on treatment for psychiatric disorders
2. Women with intellectual disability or cognitive impairment 3. Women who are unmarried
[49]
4. Women who are pregnant
The inclusion and exclusion criteria was so determined to maintain homogeneity in the sample as the study also attempts to study the associations in the particular group and it was considered culturally inappropriate to administer the sexual history questionnaire to unmarried women.
Procedure
Statistical analysis: Data was summarized using mean (SD) and median for continuous variables depending on normality and frequency along with percentage for categorical variables. Prevalence of the disease was presented along with 95%
confidence interval (CI). Data was summarized using mean (SD). Chi square test and independent T –test were used to compare the factors associated with CMD depending on variable type. The estimate of effect size was given as odds ratio (95%) confidence interval.
A logistic regression was performed to look for adjusted effects of factors. Three models were constructed based on the factors as described below:-
1. The socio demographic variables – Here the variables pertinent to socio demographic profile like age, marital status, schooling and indicators of economic status / poverty is described and analyzed.
2. The second model looks at the structure of a family unit, with reference to its type, no of children, habits in spouse, and integration within the family and the society regarding religiosity.
[50]
3. The third model looks at the factors of health and abuse. Women’s health is studied under the headings of physical and psychological health. Physical health looks into chronic physical illnesses, obstetric and gynecological history, and factors pertinent to sexual health. Psychological health is determined by the interview with questions covering perceived stressors and protective factors in the domains of occupation, family, marital and sexual relationship, society and religion.
The estimate of effect size was given as odds ratio (95%) confidence interval for multivariate analysis also. The model of fit was assessed using Hosmer lemshow fit. All the analysis was done using STATA/1C 13.1 software.
The relationship between variables was analysed using Independent t test, ANOVA or Chi square based on the nature of variable.
Variables
Socio-demographic details, obstetric history, details of family and social supports, family history of psychiatric disorder and history of violence and abuse were collected. In addition, the answers obtained from the sexual history questionnaire and the Clinical Interview Schedule- Revised was documented in the provided domains.
[51]
Flow Chart
Tools
Following tools were administered and interview was carried out for assessment of psychological and social factors.
1. The CIS-R (Lewis et al 1992)
2. Sexual history questionnaire (Viswanathan et al. sexual function in women in rural Tamil Nadu ,the national medical journal of India vol. 27, no. 1, 2014)
3. Specially designed Proforma to collect socio demographic, economic details, psychological factors and health related concerns.
Identification of potential cases - Screening done by the primary investigator
Written informed consent obtained from the participants
INTERVIEW, ADMINISTRATION OF SCALES/INSTRUMENTS Interpretation/Classification according to ICD -10
STATISTICAL ANALYSIS AND RESULTS
[52]
Data Sources / Measurement
After getting consent from patient, information was collected from the patient’s record and clinical interview with the patient. Following scales were used for assessment.
1. CIS-R
The Clinical Interview Schedule- Revised (CIS-R) is a standardized semi- structured interview to assess the mental state of subjects with common mental disorders. This is a gold standard instrument to assess common mental disorders, anxiety and depression (79). The CIS-R has been translated into multiple languages and has been used across cultures and in different countries(80).
Multiple studies have used it in India and there are versions in Tamil, Hindi and Konkani (23,80,81) .
The scale gives specifications on almost all aspects of the interviewing style .It mentions the exact phrasing of the questions and detailed guidelines for coding symptoms. The interview includes 14 sub-sections on somatic symptoms, fatigue, concentration, sleep problems, irritability, and worry about physical health, depression, depressive ideas, worry, anxiety, phobia, panic, obsessions and compulsions. Each section has a set of screening questions. If screened positive, the further questions in the domain should be asked. Scores for sub-sections range from 0 to 4. Each section score has to be summed to get a total score. A cut-off score of 12 has been validated to determine caseness (82).
[53]
It has been widely adopted across cultures to assess common mental disorders (83).
The CISR-R has minimal observer bias, as the precise word of questions is given and this helps to avoid clinician’s judgement. It empowers the lay health workers as the reliability of diagnosis made based on CIS R is compared favourably with that of other standardized interviews. Studies show that interviews by lay interviewers came out as reliable as by the professional and lay users did not show any bias in the use of the CIS-R (84).
Algorithms have been developed to lead to an ICD-10 diagnosis, from the CIS-R scores.
The CIS-R with a high inter rater reliability has been translated, validated and found to be culturally sensitive in our population and was therefore chosen as the gold-standard.
2. Sexual history questionnaire
This scale was used in a study, by Viswanathan et al looking at sexual functioning in women in rural Tamil Nadu(86).This questionnaire was used in a community population of women who lived in Kaniyambadi block. This questionnaire was translated in Tamil and was seen to be culture sensitive. The questionnaire explores multiple domains related to sexuality including first knowledge about sex, opinion about sex, sexual concerns, satisfaction about sex, reason for dissatisfaction, privacy at home for sex, contraceptive use and protection against sexually transmitted disorders.
