A Study on Screening for Psychiatric Disorders in Adult Population

Indian Journal of Community Medicine Vol. 32, No. 1 (2007-01 - 2007-03)

A Barua, GP Jacob, SS Mahmood, S Udupa, M Naidu, PS Roopa, SJ Puthiyadam

Department of Community Medicine, Kasturba Medical College, Manipal

Introduction acceptability. After informed verbal consent was obtained, A study on psychiatric morbidity in Kukundoor village of a designated respondent was administered a selected set 1, Karkala taluk, Karnataka by Ajay K.T. (1999) using the of questionnaires by the investigators. The diagnoses SCAN 2.1 version (WHO, 1998) questionnaire, determined generated by the screening instrument were reconfirmed a one-month point prevalence of 63.8% of mental disorders. This was the first study conducted using Patient by consulting a psychiatrist before arriving at a final ICD- Health Questionnaire (PHQ) for screening mental health 10 diagnosis for data analysis. Confirmed cases were given problems in adult population of Karkala. a referral slip and confidentially requested to visit the Psychiatry OPD of Dr. TMA Pai Rotary Hospital, Karkala at the earliest for a free consultancy. Material and Methods Karkala taluk belongs to Udupi district of Southern The collected data was tabulated and analyzed by using Karnataka. It has a population of 1,80,453 residing in 50 the statistical package SPSS (Statistical Package for Social villages. Majority of the population are Hindus (85.8%), Sciences) version 10.0 for Windows. Findings were followed by Christians (7.7%), Muslims (6.4%) and Jains (1%). Study Period: 1 month (1st to 31st March 2004). described in terms of proportions. Chi-square test was Setting: Dr. TMA Pai Rotary Hospital, Karkala, Karnataka. applied to study the relationship between different socio- Study Design: Cross-sectional study. Study Population: 193 demographic variables and psychiatric morbidity. p value adult individuals in the age group of 18 years and above less than 0.05 was considered as significant. participated in this study. Sampling Method: Purposive sampling method using the snowball technique was applied. Exclusion Criteria: All individuals, who were previously diagnosed as mentally challenged by the Results and Discussion psychiatrists and those admitted in any in-patient ward of The baseline characteristics of the study population the hospital were excluded from this study. revealed that there were 43.5% males and 56.5% females. Screening for psychiatric disorders was determined using Majority of respondents (40.4%) belonged to the age the instrument Patient Health Questionnaire. This group below 30 years. However, the mean age was found instrument was translated into Kannada and Hindi and to be 35.2 years (SD=10.8). 72.0% of respondents were again back-translated into English. The back-translation married, 69.9% were literates and 23.8% belonged to low was subsequently compared with the original version by a socio-economic status (below poverty level). Among a total of 193 individuals interviewed, 77(39.9%) psychiatrist for conceptual equivalence of the items. were screened positive for psychiatric disorders. This was Validation and Utility of a Self-Report Version of PRIME- consistent with the observations made by Carstairs and 3 MD2: Primary Care Evaluation of Mental Disorders (PRIME- Kapur (1976) , who reported a case rate of 370 per 1000 MD) is clinical evaluation guide for physicians to assess population. However; this was less than the study by Ajay 1 four groups of mental disorders (mood, anxiety, alcohol KT (1999) , who reported a 1month point prevalence of and somatoform) and eating disorders. Agreement mental disorders as 63.8% in adult population of between PHQ diagnoses and those made by mental health Kukundoor village of Karkala taluk. practitioners was highly satisfactory (kappa = 0.65; overall Among those having psychiatric disorders, majority accuracy = 85%; sensitivity = 75%; specificity = 90%). 27(35.1%) were suffering from somatoform disorders, The study instrument was pre-tested on a small group of while 26(33.8%) from Major Depressive Disorder, 9(11.7%) individuals (n=10) on accounts of feasibility and from other Depressive Syndromes, 22(28.6%) from Panic

65 Syndrome, 23(29.9%) from other Anxiety Syndromes, Conclusion 3(3.9%) from Bulaemia Nervosum (eating disorders) and In this study, the proportion of mental illnesses in adult 5(6.5%) from Alcohol Abuse. Ajay KT (1999)1 also observed population was determined to be 39.9%. Proportion of psychiatric morbidity among males and females were a high proportion of Mood Disorders (32.6%) and Anxiety 36.2% and 42.2% respectively. A statistical significant Disorders (20.8%) in adult population of Kukundoor village difference for psychiatric disorders was observed among of Karkala taluk. More than one diagnoses (mean=1.5, the groups of socio-demographic correlates like age group SD=0.55) was attributed to many of these cases. These of 50 years and above, those below poverty level, single observations were also consistent with the findings by individuals, illiterates, unemployed and housewives; living Kessler et al (1994)4 who also reported major depressive alone and a history of psychiatric illness in the family. episode, alcohol dependence, social phobia and simple phobia as most common psychiatric morbidities in adult Acknowledgements population. In his study, women had higher prevalence The authors are indebted to Prof. Ian Philip, Head, than men of affective disorders, anxiety disorders and non- Department of Health Care for Elderly people, University of affective psychosis. Men had higher rates of substance use Sheffield, UK for providing the Patient Health disorders and anti-social personality disorders. Questionnaire (PHQ) and its validity and reliability statistics. Authors also extend their heartfelt gratitude to Table 1 Shows the distribution of psychiatric disorders Dr. N. Kar, Ex-associate Professor, Department of according to various socio demographic correlates. In this Psychiatry, Kasturba Medical College, Manipal and study, the proportion of psychiatric disorders was higher Consultant Psychiatrist, Corner House Resource Centre, Wolverhampton, UK for his technical guidance and among females (42.2%) than males (36.9%), but this valuable advice on various aspects of psychiatric difference was not found to be statistically significant. The evaluation. proportion of psychiatric disorders was highest (66.7%) in the age group of 50 years and above. The difference in proportion of psychiatric morbidity between different age References groups was found to be statistically significant (x2= 10.97, 1. Ajay KT. Psychiatric morbidity in a rural low df=3, p=0.012*). socioeconomic status population: An epidemiological field survey Kasturba Medical College, Manipal: Manipal Academy of Higher Education; July 2000. 2. Spitzer RL, Kroenke K, Williams JBW, and the Patient The proportion of psychiatric disorders showed a positive Health Questionnaire Primary Care Study Group. linear trend of increase with the progression of age, which Validation and Utility of a Self-Report Version of PRIME- was also found to be statistically significant. Proportion of MD, JAMA, 1999; 282:1737-1744. psychiatric disorders was significantly high (67.4%) among individuals belonging to low socio-economic status (below 3. Carstairs GM, Kapur RL: The Great Universe of Kota; poverty level) and also among the unmarried, widowed or Stress, Change and Mental Disorders in an Indian Village. The Hogarth Press, London, 1976. divorced individuals (61.1%) as compared to their married counterparts (31.7%). This is in contrast to the findings by 4. Kessler CR, McGonagle KA, Zhao S, Welson CB, Hughes 1 Ajay KT (1999) who reported a high proportion of M, Erchleman S et al: Lifefime and 12-month prevalence psychiatric morbidities among married individuals. of DSM-III-R psychiatric disorders in the United States. Proportion of psychiatric disorders was significantly higher Archives of General Psychiatry, 1994; 51: 8-19. (63.8%) among illiterates. 5. Ojen VR, Hooijer C, Bezeme D. late life depressive disorder in the community, early onset and the decrease Proportion of unemployed or housewives affected with of vulnerability with increasing age. Journal of Affective psychiatric disorders was 68.4%. A significantly high Disorders, 1995; 33:159-65. proportion (72.7%) of psychiatric morbidities was observed among those who gave a positive family history of psychiatric illness and among those who lived alone (73.2%). Our findings were similar to the observations by Ojen Van et al (1995)5.

66 Table 1: Distribution of Psychiatric Disorders According to the Socio Demographic Correlates

Number Of Individuals With Proportion of Subjects Psychiatric Psychiatric x2, df, p Socio Demographic Correlates Interviewed Morbidity morbidity (N) (N) (%) 1. Sex Male 84 31 36.9 x2= 0.55, df=1, p=0.456 Female 109 46 42.2 2. Age Group (Years) <30 78 24 30.8 30-39 55 20 36.4 x2 for linear trend=10.11, 40-49 36 17 47.2 p = 0.001* ≥50 24 16 66.7

3. Socio-Economic Status Below poverty level 46 31 67.4 x2= 19.04, df=1, p= 0.0001* Above poverty level 147 46 31.3 4. Marital Status Unmarried/ Widowed/ Divorced 54 33 61.1 x2= 14.07, df=1, p= 0.0001* Married 139 44 31.7 5. Religion Jain 1 0 0.0 Christian 14 1 7.1 x2= 7.65, df=3, p= 0.054 Muslim 6 3 50.0 Hindu 172 73 42.4 6. Literacy Status Illiterate 58 37 63.8 x2= 19.75, df=1, p= 0.0001* Literate 135 40 29.6 7. Present Occupation Unemployed / Housewife 76 52 68.4 Unskilled 32 13 40.6 x2= 49.38, df=3, p= 0.0001* Skilled 52 7 13.5 Professional 33 5 15.2 8. Living arrangement in household Living alone 41 30 73.2 Living only with children & relatives 62 25 40.3 x2= 27.90, df=2, p= 0.0001* Living with spouse 90 22 24.4 9. Family History of Psychiatric Illness Present 11 8 72.7 x2= 5.24, df=1, p= 0.022* Absent 182 69 37.9 10. History of death in family within last 6 months Present 35 10 28.6 x2= 2.29, df=1, p= 0.130 Absent 158 67 42.4 * p value <0.05 is considered as significant