AN EPIDEMOLOGICAL STUDY OF PSYCHIATRIC DISORDERS IN RURAL POPULATION: USING GLOBAL MENTAL HEALTH ASSESSMENT TOOL   Dr Anil Kumar M N Dr Karthik K N Dr T S Satyanarayana Rao (Presented for S S Jayaram Award on the occasion of IPSOCON 2013 at Kerala on 19/10/2013)

Introduction Objective Materials Methodology Results Discussion Conclusion Future Directions Limitations

Introduction Mental Health Advisory Committee of the Government of India suggested a probable prevalence of mental illness of 20 per 1000 population in general, 18 per 1000 for semi-rural and 14 per 1000 for rural areas. However many epidemiological studies in India on mental and behavioral disorders report varying prevalence rates ranging from 9.5 to 370 per1000 population, owing to methodological factors.

Introduction The World Bank report (1993) revealed that the Disability Adjusted Life Year (DALY) loss due to neuro-psychiatric disorders is much higher than diarrhoea, malaria, worm infestations and tuberculosis if taken individually. According to the estimates DALY’s loss due to mental disorders are expected to represent 15% of the global burden of diseases by 2020

Introduction The WHO (& NMHP in India) advocates the need to integrate mental health into Primary health care as the optimal strategy for addressing the global burden of mental diseases. Also due to the overlap between mental and physical health, people with mental disorders frequently present to PHC settings.

Introduction PHC staffs lack the skills required to make an appropriate psychiatric diagnosis. Effective training programs are required to develop the mental health skills of generalist PHC staff. A simple computerised tool can be introduced into the primary health centres to help those staff diagnose a psychiatric problem reliably, manage some simple ones and refer them to specialized centers for further care.

Objectives To estimate the prevalence of psychiatric disorders in rural population using computerized Global Mental Health Assessment Tool (GMHAT). To help the health workers in primary care setting in identifying psychiatric problems and referring them to higher centers. To assess the quality of life of those patients with a psychiatric diagnosis as given by GMHAT using ‘WHO QOL- bref’.

Computerized GMHAT Computer assisted clinical interview, can be easily used in routine clinical practice. Generates a computer diagnosis, a symptom rating, a self-harm risk assessment, and a referral letter. Takes about 15 minutes for patients who have psychiatric symptoms. Primary care version can be easily used by health workers, who are not well versed with psychiatry.

GMHAT It consists of a series of questions leading to a comprehensive yet quick mental state assessment focusing sequentially on the following symptoms or problems: worries; anxiety and panic attacks; concentration; depressed mood, including suicidal risk; sleep; appetite; eating disorders; hypochondriasis; obsessions and compulsions; phobia; mania/hypomania; thought disorder; psychotic symptoms (delusions and hallucinations); disorientation; memory impairment; alcohol misuse; drug misuse; personality problems & stressors.

GMHAT The questions proceed in clinical order along a tree-branch structure. For each of the major clinical disorders there are one or two screening questions. If the patient does not have symptoms based on the first one or two items of a subsection, the interview moves on to the next subsection, thus saving much valuable time.

WHO QOL- bref This is a quality of life questionnaire containing 26 questions divided over 4 domains of health- physical, psychological, social and environmental. It was administered to all those patients having a psychiatric diagnosis as per GMHAT except those having MR, Mania, psychosis and organic mental disorders.

Method Study conducted in suttur , 27 km from mysore. Data collected b/n Nov 12- Feb 13, thrice a week. Systematic random sampling, every third house. N=1000 from 300 houses. All permanent residents of suttur were considered eligible for study. Children below 6 yrs were not included. Head of the family was interviewed first and then other members; if any member was not present that day, we would interview him in next visit.

Analysis The data collected was analyzed using SPSS version 16.0. Previous studies show that prevalence rate of psychiatric morbidity ranges from 4.6 to 88%, hence if we assume the prevalence here to be around 25%. By keeping a confidence level of 95% we would get a confidence interval of 3. Descriptive statistics was applied to the data.

Results Out of the total sample of 1000, GMHAT gave a psychiatric diagnosis for 285 subjects (28.5%). Depression- 169 (M 59, F 110) Alcohol abuse- 43 (M 43, F 0) Anxiety- 41 (M 23, F 18) Stress- 14 (M 6, F 8) Epilepsy- 4 (M 2, F 2) Organic psy disorder- 4 (M 4, F 0) Mental retardation- 5 (M 2, F 3) Other drug use- 3 (M 3, F 0) Psychosis, Mania- 1 each (both F)

Marital status and psychiatric illness 57.4% of study subjects were married. 1.2% were widowed. 41.8% were unmarried. 76.84% of psychiatrically ill belonged to married group. 23.16% of those mentally ill were unmarried.

Socio-economic status (modified kuppuswamy) 3%- lower class 36.8%- upper lower class 44.4%- lower middle class 14.9%- upper middle class 0.9%- upper class Among mentally ill 50.9% - upper lower class 34.4%- lower middle class 11.2%- upper middle class Thus prevalence in psy disorders increase with decline in socio-economic status.

Study population - 61.1% - in nuclear families - 38.9% - in joint families - 0.2% - stayed alone Among psychiatrically ill - 62.4% belonged to nuclear families. - 36.5% belonged to joint families. This implies higher risk of psychiatric disorders in nuclear families

Scores on WHO QOL- bref Physical health: 41.5 Psychological health: 40.7 Social relationships: 42.24 Environmental: 44.38 Overall: 43.3 Depression: 39.62 Alcohol use: 41.48 Anxiety: 46.44 Epilepsy: 48.1 Stress: 53.48

Discussion Varying prevalence rates have been reported in international studies like the Epidemiological Catchment Area program (32.2%) and the National Co morbidity Survey (48.7 %). Psychiatric disorders are known to vary across time within the same population and also vary across population at the same time. This dynamic nature of the psychiatric illness will impact planning, funding and healthcare delivery.

Discussion The study was undertaken in Suttur, a small village with a population of 4018 and total number of families 986. In our present study, 1000 (504 males, 496 females) subjects were interviewed. The overall prevalence rate of 28.5% is in accordance with the other studies. Further, it was found to be 14.3 % in females and 14.2 % in males.

Discussion Depression was significantly higher in females than males, which again follows the literature. Certain socio-demographic variables such as age, education and marital status were found to influence the occurrence of mental illness. Patients suffering from depression had the lowest average QOL score followed by people with alcohol use disorders, anxiety, epilepsy and stress. This indicates that depression is the psychiatric disorder which affects the quality of life to a significant extent.

Conclusion The prevalence of psychiatric disorders in suttur village clearly indicates that mental illness is an important problem there. The quality of life is adversely affected by the presence of psychiatric illness. The computerized GMHAT has proved to be handy in conducting such an epidemiological study.

Conclusion GMHAT trains the PHC staff reg mental health. GMHAT gives practical diagnosis by evaluating sub clinical psychiatric problems. GMHAT assists in referral to higher centers.

Future directions Staff members in primary care settings need to strengthen their knowledge in identifying common psychiatric disorders. A simple computerized tool like GMHAT which helps in identifying common psychiatric problems is the need of the hour, owing to increased use of computers in government settings nowadays. GMHAT can be used in effective implementation of National Mental Health Program.

Limitations This study being a descriptive one, we did not attempt interpreting how the socio-demographic factors affect the mental health of an individual. GMHAT does not give longitudinal and specific diagnosis. e.g., BPAD, schizophrenia. Child and Adolescent disorders such as ADHD etc were not evaluated.

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