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Indian Journal of Community Medicine

A Study on Screening for Psychiatric Disorders in Adult Population

Author(s): A Barua, GP Jacob, SS Mahmood, S Udupa, M Naidu, PS Roopa, SJ Puthiyadam

Vol. 32, No. 1 (2007-01 - 2007-03)

A study on psychiatric morbidity in Kukundoor village of Karkala taluk, Karnataka by Ajay K.T. (1999)1, using the SCAN 2.1 version (WHO, 1998) questionnaire, determined a one-month point prevalence of 63.8% of mental disorders. This was the first study conducted using Patient Health Questionnaire (PHQ) for screening mental health problems in adult population of Karkala.

Material and Methods

Karkala taluk belongs to Udupi district of Southern Karnataka. It has a population of 1,80,453 residing in 50 villages. Majority of the population are Hindus (85.8%), followed by Christians (7.7%), Muslims (6.4%) and Jains (1%). Study Period: 1 month (1st to 31st March 2004). Setting: Dr. TMA Pai Rotary Hospital, Karkala, Karnataka. Study Design: Cross-sectional study. Study Population: 193 adult individuals in the age group of 18 years and above 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 psychiatrists and those admitted in any in-patient ward of the hospital were excluded from this study.

Screening for psychiatric disorders was determined using the instrument Patient Health Questionnaire. This instrument was translated into Kannada and Hindi and again back-translated into English. The back-translation was subsequently compared with the original version by a psychiatrist for conceptual equivalence of the items.

Validation and Utility of a Self-Report Version of PRIME-MD2: Primary Care Evaluation of Mental Disorders (PRIME-MD) is clinical evaluation guide for physicians to assess four groups of mental disorders (mood, anxiety, alcohol and somatoform) and eating disorders. Agreement between PHQ diagnoses and those made by mental health practitioners was highly satisfactory (kappa = 0.65; overall accuracy = 85%; sensitivity = 75%; specificity = 90%).

The study instrument was pre-tested on a small group of individuals (n=10) on accounts of feasibility and acceptability. After informed verbal consent was obtained, a designated respondent was administered a selected set of questionnaires by the investigators. The diagnoses generated by the screening instrument were reconfirmed by consulting a psychiatrist before arriving at a final ICD-10 diagnosis for data analysis. Confirmed cases were given 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.

The collected data was tabulated and analysed by using the statistical package SPSS (Statistical Package for Social Sciences) version 10.0 for Windows. Findings were described in terms of proportions. Chi-square test was applied to study the relationship between different socio-demographic variables and psychiatric morbidity. p value less than 0.05 was considered as significant.

Results and Discussion

The baseline characteristics of the study population revealed that there were 43.5% males and 56.5% females. Majority of respondents (40.4%) belonged to the age group below 30 years. However, the mean age was found to be 35.2 years (SD=10.8). 72.0% of respondents were married, 69.9% were literates and 23.8% belonged to low socio-economic status (below poverty level).

Among a total of 193 individuals interviewed, 77(39.9%) were screened positive for psychiatric disorders. This was consistent with the observations made by Carstairs and Kapur (1976)3, who reported a case rate of 370 per 1000 population. However; this was less than the study by Ajay KT (1999)1, who reported a 1month point prevalence of mental disorders as 63.8% in adult population of Kukundoor village of Karkala taluk.

Among those having psychiatric disorders, majority 27(35.1%) were suffering from somatoform disorders, while 26(33.8%) from Major Depressive Disorder, 9(11.7%) from other Depressive Syndromes, 22(28.6%) from Panic Syndrome, 23(29.9%) from other Anxiety Syndromes, 3(3.9%) from Bulaemia Nervosum (eating disorders) and 5(6.5%) from Alcohol Abuse. Ajay KT (1999)1 also observed a high proportion of Mood Disorders (32.6%) and Anxiety Disorders (20.8%) in adult population of Kukundoor village of Karkala taluk. More than one diagnoses (mean=1.5, SD=0.55) was attributed to many of these cases. These observations were also consistent with the findings by Kessler et al (1994)4 who also reported major depressive episode, alcohol dependence, social phobia and simple phobia as most common psychiatric morbidities in adult population. In his study, women had higher prevalence than men of affective disorders, anxiety disorders and non-affective psychosis. Men had higher rates of substance use disorders and anti-social personality disorders.

Table 1 Shows the distribution of psychiatric disorders according to various socio demographic correlates. In this study, the proportion of psychiatric disorders was higher among females (42.2%) than males (36.9%), but this difference was not found to be statistically significant. The 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 groups was found to be statistically significant (x2= 10.97, df=3, p=0.012*).

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

Socio
Demographic
Correlates (N)
Number of
Subjects
Interviewed
Morbidity
Individuals
With
Psychiatric (N)
Proportion of
Psychiatric
Morbidity (%)
x2, df, p
Sex
Male 84 31 36.9 x2= 0.55, df=1,
Female 109 46 42.2 p=0.456
Age Group (Years)
<30 78 24 30.8  
30-39 55 20 36.4 x2 for linear trend=10,
40-49 36 17 47.2 p = 0.001*
≥50 24 16 66.7  
Socio-Economic Status
Below poverty level 46 31 67.4 x2= 19.04, df=1,
Above poverty level 147 46 31.3 p= 0.0001*  
Marital Status
Unmarried/ 54 33 61.1 x2= 14.07, df=1,
Widowed/ Divorced       p= 0.0001*
Married 139 44 31.7  
Religion
Jain 1 0 0.0  
Christian 14 1 7.1 x2= 7.65, df=3,
Muslim 6 3 50.0 p= 0.054
Hindu 172 73 42.4  
Literacy Status
Illiterate 58 37 63.8 x2= 19.75, df=1,
Literate 135 40 29.6 p= 0.0001*
Present Occupation
Unemployed
/ Housewife
76 52 68.4  
Unskilled 32 13 40.6 x2= 49.38, df=3,
Skilled 52 7 13.5 p= 0.0001*
Professional 33 5 15.2  
Living arrangement in household
Living alone 41 30 73.2  
Living only with 62 25 40.3 x2= 27.90, df=2,
children & relatives p= 0.0001*
Living with spouse 90 22 24.4  
Family History of Psychiatric Illness
Present 11 8 72.7 x2= 5.24, df=1,
Absent 182 69 37.9 p= 0.022*
History of death in family within last 6 months
Present 35 10 28.6 x2= 2.29, df=1,
Absent 158 67 42.4 p= 0.130
* p value <0.05 is considered as significant The proportion of psychiatric disorders showed a positive linear trend of increase with the progression of age, which was also found to be statistically significant. Proportion of psychiatric disorders was significantly high (67.4%) among individuals belonging to low socio-economic status (below poverty level) and also among the unmarried, widowed or divorced individuals (61.1%) as compared to their married counterparts (31.7%). This is in contrast to the findings by Ajay KT (1999)1 who reported a high proportion of psychiatric morbidities among married individuals. Proportion of psychiatric disorders was significantly higher (63.8%) among illiterates.

Proportion of unemployed or housewives affected with psychiatric disorders was 68.4%. A significantly high 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.

Conclusion

In this study, the proportion of mental illnesses in adult population was determined to be 39.9%. Proportion of psychiatric morbidity among males and females were 36.2% and 42.2% respectively. A statistical significant difference for psychiatric disorders was observed among the groups of socio-demographic correlates like age group of 50 years and above, those below poverty level, single individuals, illiterates, unemployed and housewives; living alone and a history of psychiatric illness in the family.

Acknowledgements

The authors are indebted to Prof. Ian Philip, Head, Department of Health Care for Elderly people, University of Sheffield, UK for providing the Patient Health Questionnaire (PHQ) and its validity and reliability statistics. Authors also extend their heartfelt gratitude to Dr. N. Kar, Ex-associate Professor, Department of Psychiatry, Kasturba Medical College, Manipal and Consultant Psychiatrist, Corner House Resource Centre, Wolverhampton, UK for his technical guidance and valuable advice on various aspects of psychiatric evaluation.

References

  1. Ajay KT. Psychiatric morbidity in a rural low 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 Health Questionnaire Primary Care Study Group. Validation and Utility of a Self-Report Version of PRIME-MD, JAMA, 1999; 282:1737-1744.
  3. Carstairs GM, Kapur RL: The Great Universe of Kota; Stress, Change and Mental Disorders in an Indian Village. The Hogarth Press, London, 1976.
  4. Kessler CR, McGonagle KA, Zhao S, Welson CB, Hughes M, Erchleman S et al: Lifefime and 12-month prevalence of DSM-III-R psychiatric disorders in the United States. Archives of General Psychiatry, 1994; 51: 8-19.
  5. Ojen VR, Hooijer C, Bezeme D. late life depressive disorder in the community, early onset and the decrease of vulnerability with increasing age. Journal of Affective Disorders, 1995; 33:159-65.

Department of Community Medicine, Kasturba Medical College, Manipal
E-mail: [email protected]
Received: 11.10.04

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