Prevalence of psychiatric morbidity at Mobile Health Clinic in an urban community in North India

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General Hospital Psychiatry 34 (2012) 121 – 126

Prevalence of psychiatric morbidity at Mobile Health Clinic in an urban community in North India☆,☆☆ Harshal Salve, M.D. a,⁎, Kiran Goswami, M.D. a , Baridalyne Nongkynrih, M.D. a , Rajesh Sagar, M.D. b , V. Sreenivas, Ph.D. c a

Centre for Community Medicine, All India Institute of Medical Sciences, New Delhi, India b Department of Psychiatry, All India Institute of Medical Sciences, New Delhi, India c Department of Biostatistics, All India Institute of Medical Sciences, New Delhi, India Received 4 July 2011; accepted 13 September 2011

Abstract Objective: The objective was to estimate the prevalence of psychiatric morbidity amongst patients attending Mobile Health Clinic (MHC) in an urban community in South Delhi. Methods: Adult subjects were recruited by systematic random sampling at outpatient MHC. Primary Care Evaluation of Mental Disorder Patient Health Questionnaire (PHQ) was used for screening, and Mini International Neuropsychiatric Interview (M.I.N.I.) was used for the confirmation of diagnosis of psychiatric disorder of all PHQ-positive and 20% of PHQ-negative patients. Association of selected sociodemographic factors with psychiatric morbidity was also assessed. Results: In total, 350 subjects were recruited, out of which 92 (26.3%) [95% confidence interval (CI) 21.7–31.0] were found to be PHQ positive. M.I.N.I. was administered to 141 subjects (92 PHQ positives and 52 PHQ negatives). Total estimated magnitude of psychiatric morbidity by M.I.N.I. was 25.4% (95% CI 20.9–29.9). Depression (15.7%) was observed to be the most common psychiatric disorder followed by generalized anxiety disorder (11.1%) and phobic disorders (10.1%). Suicidal ideation was reported by 37 (10.6%) patients. Literate status [odds ratio (OR)=0.43] and duration of migration N20 years to study area (OR=1.27) were found to be significantly associated with psychiatric morbidity. Conclusion: In resource-poor country like India, high psychiatric morbidity at MHC justifies the use of MHC for providing outreach mental health services in difficult areas. © 2012 Elsevier Inc. All rights reserved. Keywords: Psychiatric morbidity; Primary care; Mobile Health Clinic; India

1. Introduction Globally, psychiatric morbidity contributes to 12% of the disease burden and is projected to increase to 15% by the year 2020 [1]. In India, meta-analysis of epidemiological studies has reported prevalence of psychiatric morbidity from 58.2 [2] to 73 [3] per 1000 people. Prevalence of ☆

Source of funding: none. Conflicts of interest: none declared. ⁎ Corresponding author. Tel.: +91 011 26593233 (O): +91 99111253846 (M); fax: +91 011 2658 8522, +91 011 2649 2692. E-mail addresses: [email protected], [email protected] (H. Salve). ☆☆

0163-8343/$ – see front matter © 2012 Elsevier Inc. All rights reserved. doi:10.1016/j.genhosppsych.2011.09.009

psychiatry morbidity in the urban region was found to be 3.5% higher compared to that in rural India [4]. Pothen et al. reported that psychiatric disorders contribute to substantial amount of morbidity at primary care setting, and thus, there is need to treat these disorders at the primary care level [5]. Assessment of extent and pattern of disorders at the primary care level is important due to the potential of identifying individuals with disorders and providing needed care at this level itself. Most often, the psychiatric disorders at primary care remain undiagnosed because patients present with physical disorders or somatic complaints [6,7]. Psychiatric disorders commonly presenting at primary care are grouped as common mental disorders [8], including mood disorders and “Neurotic, Stress related and

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Somatoform disorders” as per the International Classification of Diseases, 10th Revision (ICD-10) [9]. Two-stage screening procedure, i.e., utilizing a validated screening technique followed by a standardized psychiatric interview, is a useful strategy for detecting psychiatric disorders at primary care [10]. With reference to National Mental Health Programme of India, the 11th Five-Year Plan (2007–2012) also recommends the integration of mental health services in primary care so that these can be easily accessible and affordable to the population [11]. Also, management of psychiatric disorders at primary care with affordable drugs is proven to be a cost-effective strategy [12]. Most of the published studies on psychiatric disorders at the primary care level have been conducted either in rural setting [5,6,8,13–15] or in general hospitals [16–19]. The present study deals with the estimation of magnitude of psychiatric morbidity by using the Primary Care Evaluation of Mental Disorder Patient Health Questionnaire (PRIME-MD PHQ) as a screening tool and the Mini International Neuropsychiatric Interview (M.I.N.I.) as a diagnostic tool at Mobile Health Clinic (MHC). Association of selected sociodemographic factors with psychiatric morbidity was also assessed.

2. Methods The present study was conducted at MHC in Dr. Ambedkar Nagar, South Delhi. This MHC is part of the Urban Health Programme of Centre for Community Medicine, All India Institute of Medical Sciences, New Delhi. Through MHC, health care services like general health care, immunization and antenatal care are being provided to approximately 40,000 to 50,000 people, with an average daily outpatient attendance ranging from 70 to 100 patients. Sample size of 350 was calculated by taking estimated prevalence of 24% [19] with 4.8% precision, 10% loss to follow-up and 95% confidence interval (CI). In MHC outpatient clinic (OPD), new adult patients (≥18 years) were recruited by systematic random sampling over a period of 6 months. Patients not able to communicate or who refused to participate were excluded from the study. Study subjects were screened using PRIME-MD PHQ, developed and validated against clinical diagnosis by Spitzer et al. [20,21] for use in primary care settings to diagnose specific psychiatric disorders using Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition (DSM-IV) diagnostic criteria. Diagnosis of psychiatric disorders was done by using M.I.N.I. (6.0.0) at household after tracing subject's address. M.I.N.I. is a validated instrument used globally, which gives DSM-IV-Text Revision (TR) and ICD-10 diagnosis [22–25]. English versions of PRIME-MD PHQ and M.I.N.I. were translated into Hindi in two steps. In the first step, English version was translated into Hindi by two nonmedical experts. In the second step, the Hindi-translated version was back

translated into English by a medical person not involved in study and compared with the original version. The finalized Hindi version was applied on 10 local Hindi-speaking people. Any difficulty observed was resolved with the help of a psychiatrist (R.S.) before preparing the final Hindi translation. Information about age, sex, residential address and present complaint for which patient attended the OPD was recorded on interview schedule from study subjects. Any recruited subject fulfilling criteria for diagnosis of any of the psychiatric disorders which are covered under PRIME-MD PHQ like somatoform disorders, severe depression, other depression syndrome, panic disorders, generalized anxiety disorders, alcohol abuse and eating disorders was categorized into PHQ positive, while those who did not fulfil any criteria were categorized as PHQ negative. M.I.N.I. was administered to all PHQ-positive and 20% randomly selected PHQ-negative subjects. Any subject fulfilling diagnostic criteria of any of the disease module of M.I.N.I. was labeled as M.I.N.I. positive, and those not fulfilling any criteria were labeled as M.I.N.I. negative. All subjects with diagnosed psychiatric morbidity were provided with appropriate counseling and treatment. 2.1. Training and quality assurance Training of the investigator in M.I.N.I. administration was done by a psychiatrist (R.S.) for a period of 3 months. Quality assurance by the psychiatrist was performed for 5% of M.I.N.I.-positive and the same number of M.I.N.I.negative subjects in a double-blinded manner. One hundred percent agreement between M.I.N.I. diagnosis and diagnosis by psychiatrist was observed. 2.2. Data analysis Data were analyzed in SPSS version 13 for Windows. The χ 2 statistical test was used to study association of selected sociodemographic factors with psychiatric morbidity, and it was expressed with odds ratio (OR) and 95% CI. P value b.05 was considered statistically significant. All factors were analyzed by multivariate logistic regression analysis, and adjusted ORs and 95% CIs were calculated. 2.3. Ethical issues Written informed consent was obtained from the study subject before participation. Ethical clearance for the study was obtained from the Institute's Ethical Committee of All India Institute of Medical Sciences, New Delhi. 3. Results A total 350 new adult (≥18 years) subjects were recruited at MHC. Profile of the patients recruited for screening by PRIME-MD PHQ is given in Table 1. Most (80%) of the 350 study subjects were younger than 50 years. Most of them were female (84.6%). Health care at MHC was sought most

H. Salve et al. / General Hospital Psychiatry 34 (2012) 121–126 Table 1 Profile of recruited patients for screening by PRIME-MD PHQ (N=350) Age group (years)

Male

Female

Total (%)

18–29 30–49 ≥50 Total

14 19 21 54 (15.4)

148 98 50 296 (84.6)

162 (46.3) 117 (33.4) 71 (20.3) 350

frequently for generalized body ache (27%) and antenatal care (21%), followed by chest symptoms (13%). Mean duration required for PHQ administration was 6.2 (S.D.: 0.9) min at MHC. Out of 350 subjects, 92 (26.3%) (95% CI 21.7–31.0) subjects were identified as PHQ positive and 258 (73.7%) as PHQ negatives. Out of 258 PHQ-negative subjects, 52 (20.2%) were selected randomly for M.I.N.I. administration (Fig. 1). Out of 141 subjects administered M.I.N.I. (89 PHQ positive and 52 PHQ negative), 69 (49.4%) were MINI positive and 72 (50.6%) were MINI negative (Table 2). Of 89 PHQ-positive subjects, 64 were M.I.N.I. positive and 25 were M.I.N.I. negative. Out of 52 PHQ-negative subjects, 5 (10%) were found to be positive for M.I.N.I. Extrapolating this result to all 258 PHQ-negative subjects, total M.I.N.I.positive out of PHQ-negative subjects could be estimated to be 25. Hence, total estimated magnitude of psychiatric morbidity by M.I.N.I. amongst study subjects could be estimated as 89 out of 350, i.e., 25.4% (95% CI 20.9–29.9). Agreement analysis of diagnosis by PRIME MD PHQ and MINI observed moderate (k=0.6) level of agreement. 3.1. Diagnosis (DSM-IV-TR and ICD-10) of psychiatric morbidity by M.I.N.I. Out of 52 PHQ-negative subjects, five were diagnosed with psychiatric disorder by M.I.N.I. for depression (two), generalized anxiety disorder (two), posttraumatic stress disorder (one) and agoraphobia (four). Estimated prevalence of all psychiatric disorders was calculated for total sample of

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Table 2 Distribution of M.I.N.I.-positive patients amongst PRIME-MD PHQscreened patients

PHQ positive PHQ negative Total

M.I.N.I. positive

M.I.N.I. negative

Total

64 5 69

25 47 72

89 52 141

350. The most common psychiatric disorder in patients attending MHC was depression (15.7%) followed by generalized anxiety disorders (11.1%) and phobic disorder (10.0%). Both depression and anxiety disorder were reported in 37 (10.6%) patients. Other diagnosed psychiatric disorders included panic disorders (2.2%), obsessive–compulsive disorders (2.2%) and manic disorder (1.4%). Alcohol dependence was reported in four (1.1%) of the patients. Thirty-seven (10.6%) patients reported suicidal ideation in the preceding 1 month (Table 3). According to ICD-10, majority of the diagnosed psychiatric disorders were mood disorders (17.1%) followed by anxiety and stress-related disorders (13.4%). Other neurotic disorders reported were phobic disorders (10.6%) and obsessive–compulsive disorders (2.2%) (Fig. 2). Conversion from DSM-IV to ICD-10 classification is not always exact though. M.I.N.I. does not diagnose somatoform disorders that are picked up by PRIME-MD PHQ. Magnitude of somatoform disorders amongst patients attending MHC was observed to be 12% by PRIME-MD PHQ. Out of 42 subjects positive for somatoform disorder by PHQ, 29 were also positive for other disorders by PRIME-MD PHQ. Thus, only 13 subjects were there who had PHQ positivity for somatoform disorder only. Out of 13 subjects, only five were positive for depression with M.I.N.I. 3.2. Association of psychiatric morbidity with sociodemographic factors Association of psychiatric morbidity with selected sociodemographic factors was assessed (Table 4). Literate status was found to be protective for psychiatric morbidity Table 3 Estimated prevalence of psychiatric disorders (DSM-IV-TR) by M.I.N.I. (N=350)

Fig. 1. Flow of the study subjects for screening and diagnosis of psychiatric disorders.

Diagnosis of psychiatric disorder

n (%)

Major depression (past/current/recurrent) Generalized anxiety disorders Agoraphobia/social phobia Posttraumatic stress disorder Panic disorder (current/lifetime) Obsessive–compulsive disorders Manic episode/hypomania episode Alcohol abuse/dependence Other disorders a

55 (15.7) 39 (11.1) 36 (10.1) 7 (2.0) 8 (2.2) 8 (2.2) 5 (1.4) 4 (1.1) 3 (0.8)

Seventy-four patients had more than one psychiatric disorder. a Other disorders include: one case of posttraumatic stress disorder, psychotic disorder, bulimia nervosa and antisocial personality disorder.

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Fig. 2. Magnitude of psychiatric disorders (ICD-10) amongst adult patients attending MHC. Other neurosis disorders include phobic disorders and obsessive–compulsive disorders. Anxiety disorders include generalized anxiety disorders and panic disorder. Diagnosis of somatoform disorders was by PRIME-MD PHQ. Other psychiatric disorders include alcohol dependence disorders, psychotic disorders, and eating disorders.

(OR=0.43, 95% CI 0.22–0.85) (P=.01). Longer duration since migration to the study area (N20 years) was found to be associated with psychiatric morbidity (OR 1.27, 95% CI 1.01–1.60) (P=.04). On multivariate logistic regression analysis, being illiterate (P=.04) and having migrated to area for at least N20 years (P=.04) remained statistically significant with coefficient of regression (β) of −0.88 and 2.06, respectively. But OR for both factors remained the same. In multivariate analysis, variables like age, sex, marital status, current alcohol use, working status, socioeconomic condition, stressful event in life, mental illness in family and type of family were adjusted.

4. Discussion One fourth (25.4%) of the adult patients attending MHC in an urban region in South Delhi were diagnosed with psychiatric morbidity by M.I.N.I. Reported psychiatric morbidity in the present study is comparable to that in the study by Channabasavnna et al. [19] (23.9%) and Murthy

Table 4 Association of sociodemographic factors with psychiatric morbidity Sociodemographic factor

Adjusted OR (95% CI)

P value

Age N50 years Female sex Duration since migration N20 years Currently married Literate status Working status Lower socioeconomic status Extended family Current alcohol use Current chronic illness Mental illness in family Stressful event in last 6 months in life

1.14 (0.53–2.46) 0.86 (0.35–2.09) 1.27 (1.01–1.26) 0.53 (0.22–1.27) 0.43 (0.22-0.85) 0.25 (0.05–1.20) 1.56 (0.79–3.06) 1.28 (0.66–2.49) 4.59 (0.94–22.4) 1.72 (0.77–3.83) 1.46 (0.24–8.90) 0.66 (0.19–2.19)

.29 .73 .04 .16 .01 .07 .19 .46 .05 .18 .68 .49

Chronic illness: hypertension, diabetes mellitus, chronic obstructive pulmonary illness. Bold: statistically significant.

et al. [16] (27.0%) at primary care setting. Various studies in India like those by Chatterjee et al. [26] (33.7%), Pothen et al. [5] (33.9%), Shamsundar et al. [18] (35.9%), Krishnamurthy et al. [17] (36.1%), Kishore et al. [15] (41.7%), Nambi et al. [6] (44.0%) and Patel et al. [8] (46.5%) reported higher prevalence, whereas Harding et al. [13] (17.7%) and Seshadri et al. [14] (11.8%) reported lower prevalence of psychiatric morbidity compared to the present study. These differences in prevalence in these studies could be attributed to difference in diagnostic instruments, study population and study settings. Globally, PRIME-MD PHQ is widely used at the primary care level for screening of psychiatry morbidity [27–30]. The Hindi version of PRIME-MD PHQ was used in a secondary care setting by Avasthi et al. [31] and Barua et al. [32] as a self-administered questionnaire, whereas in the present study, the instrument was used as an interview schedule. As PRIME-MD PHQ showed good level of agreement (k=0.6) with diagnosis of psychiatric disorder by M.I.N.I. and also because the time required for its administration was less (6.2 min), it can be used for screening of psychiatric disorders in the primary care setting in India. Depression (15.7%) is observed to be the most common psychiatric disorder followed by anxiety and stress-related disorders (11.1%) and somatoform disorders (12%). Pothen et al. [5] and Patel et al. [8] also reported similar findings at the primary care level. Only five patients with somatoform disorder (only) were captured as depression by M.I.N.I. Most of the patients attend primary care setting for physical complaint either due to unawareness of symptoms of psychiatric disorders or due to stigma attached with it. Diagnosis of somatoform disorder by PRIME-MD PHQ is done by identifying physical complaint which is not explained by any other illness. This could be the reason for the high prevalence of somatoform disorder in various studies at primary care setting [15,26]. Alcohol abuse is reported in 1.1% of the patients in the present study, which is comparable to that in the study by Avasthi et al. [31] but less than that reported by Barua et al. [32] (6.5%). In the present study, 84.6% of the participants were female as MHC provides services in morning hours during which most men are likely to be at work. Higher female participation might explain lower prevalence of alcohol abuse. The present study reports suicidal ideation in 10.6% of patients, which is lower than patients at other primary care settings (18%) [8]. The present study observes lower prevalence of psychiatric morbidity amongst literates (P=.04). A relationship of illiteracy and psychiatric morbidity at primary care has been documented in a previous study at primary care [5]. Area served by MHC has slum population and a resettlement colony. Majority of study population had migrated from the surrounding poorer area of Delhi. Any migrated population brings culture, beliefs, practices and expectations that are often very different from the ones they encounter in their new location. According to theory of

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“social drift,” rapid urbanization creates the “fringe population” mostly living hand to mouth, adding to the poverty and ultimately into mental and behavioral disorders [33]. The longer the duration of exposure to this social stress, higher the chances of development of psychiatric disorders, and this could be the reason for statistically significant association of psychiatric morbidity with longer duration of migration to the study area. Duration between administration of PRIME-MD PHQ and M.I.N.I. was more than 3 weeks in some cases, which could have affected diagnosis of psychiatric disorder and underestimated the psychiatric morbidity. PRIME-MD PHQ and M.I.N.I. were administered by the same person (H.S.), so the possibility of bias in psychiatric diagnosis needs to be considered. Relationship of poverty, female gender, unemployment, unmarried or separated status, and family history of psychiatric illness with psychiatric morbidity is well documented in the literature [5,8,18,34,35]. As the basis of sample size calculation was to estimate the prevalence of psychiatric morbidity, the present study did not have adequate power to detect statistically significant association of all these factors with psychiatric morbidity. The present study observes association of risk factor with psychiatric morbidity amongst adults who sought health care at MHC and hence cannot be generalized to the community. Concept of illness and related health-seeking behavior amongst local population could also affect presentation of psychiatric morbidity and consequently the strength of their association with risk factors [5]. Also, help-seeking behavior of the local population determines the sample population in the studies at the primary care level.

5. Conclusion The study reports high prevalence (25.4%) of undiagnosed psychiatric morbidity amongst patients attending primary care in an urban region in north India, the majority contributed by common mental disorders. As per the mandate of National Mental Health Programme of India, there is a need to provide mental health care services at the primary care level [11]. This has been supported by high burden of psychiatric morbidity in the present study. Given the paucity of psychiatrists in the country [36], the gap of workforce can only be filled by training primary care physicians in diagnosis and management of psychiatric morbidity as evident in the present study. Two staged screening of psychiatric morbidity by using PRIME-MD PHQ as screening tool can be done at the primary care setting. Rural areas in India have a three-tiered primary health care system. This is lacking in urban areas, because of which the cost of availing treatment for mental illness increases [37]. Currently, 1031 Mobile Medical Units and several Urban Health Centre and Dispensaries provide outreach

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services in underprivileged areas like urban slums [36]. These facilities can be utilized to deliver outreach mental health services that will increase the reach of the mental health services and decrease the cost of treatment of mental illness in the community. References [1] The World Health Report 2001. Mental health: new understanding, new hope. World Health Organ 2001. [2] Math SB, Chandrashekar CR, Bhugra D. Psychiatric epidemiology in India. Indian J Med Res 2007;126(3):183–92. [3] Reddy MV, Chandrasekar CR. Prevalence of mental and behavioural disorders in India: a meta-analysis. Indian J Psychiatry 1998;40:149–57. [4] Ganguli HC. Epidemiological finding on prevalence of mental disorders in India. Indian J Psychiatry 2000;42:14–20. [5] Pothen M, Kuruvilla A, Philip K, Joseph A, Jacob KS. Common mental disorders among primary care attendees in Vellore, South India: nature, prevalence and risk factors. Int J Soc Psychiatry 2003;49(2): 119–25. [6] Nambi SK, Prasad J, Singh D, Abraham V, Kuruvilla A, Jacob KS. Explanatory models and common mental disorders among patients with unexplained somatic symptoms attending a primary care facility in Tamil Nadu. Natl Med J India 2002;15(6):331–5. [7] Kisely SR Goldberg DP. Physical and psychiatric co-morbidity in general practice. Br J Psychiatry 1996;169(2):236–42. [8] Patel V, Pereira J, Coutinho L, Fernandes R, Fernandes J, Mann A. Poverty, psychological disorder and disability in primary care attainders in Goa, India. Br J Psychiatry 1998;172:533–6. [9] World Health Organization. The ICD-10 classification of mental & behavioural disorders: diagnostic criteria for research. Geneva: WHO; 1993. [10] Sen B, Wilkinson G, Mari JJ. Psychiatric morbidity in primary health care. A two-stage screening procedure in developing countries: choice of instruments and cost-effectiveness. Br J Psychiatry 1987; 151:33–8. [11] Planning Commission. Towards a faster and more inclusive growth — an approach to the 11th Five-Year Plan. New Delhi: Government of India, Yojana Bhavan; 2006. [12] Patel V, Chisholm D, Rabe-Hesketh S, Dias-Saxena F, Andrew G, Mann A. Efficacy and cost-effectiveness of drug and psychological treatments for common mental disorders in general health care in Goa, India: a randomised, controlled trial. Lancet 2003;361(9351): 33–9. [13] Harding TV, Arango MV, Baltazar J, Climent CE, Ibrahim HHA, Ladrino-Ignacio I. Mental disorders in primary health care: a study of their frequency and diagnosis in four developing countries. Psychol Med 1980;10:231–41. [14] Seshadri S, Kumar KVK, Moily S, Gangadhar V. Patients presenting with multiple somatic complaints to rural health clinic (Sakalwara); preliminary report. NIMHANS J 1988;6:13–7. [15] Kishore J, Reddaiah VP, Kapoor V, Gill JS. Characteristics of mental morbidity in a rural primary health centre of Haryana. Indian J Psychiatry 1997;39(3):187–9. [16] Murthy RS, Kuruvilla K, Vergese A, Pullimood BM. Psychiatric illness in general hospital medical clinic. J Indian Med Assoc 1976; 66:6–8. [17] Krishnamurthy S, Shamasundar C, Prakash O, Prabhakar N. Psychiatric morbidity in general practice — a preliminary report. Indian J Psychiatry 1981;23:40–3. [18] Shamasundar C, Krishnamurthy S, Prakash O, Prabhakar N, Subbakrishna D. Psychiatric morbidity in general practice in an Indian city. Br Med J 1986;292:1713–5. [19] Channabasavanna SM, Sriram T, Kumar K. Results from the Bangalore centre. In: Ustun TB, & Sartorious N, editors. Mental

126

[20]

[21]

[22]

[23]

[24]

[25]

[26]

[27]

H. Salve et al. / General Hospital Psychiatry 34 (2012) 121–126 illness in general health care: an international study. Chichester: John Wiley & Sons; 1995. p. 79–97. Spitzer RL, Williams JBW, Kroenke K, Linzer M, deGruy FVIII, Hahn SR, et al. Utility of a new procedure for diagnosing mental disorders in primary care. JAMA 1994;272:1749–56. Spitzer RL, Kroenke K, Williams JBW. Validation and utility of a self report version of PRIME-MD: the PHQ Primary Care Study. JAMA 1999;282:1737–44. Sheehan DV, Lecrubier Y, Sheehan KH, et al. The Mini-International Neuropsychiatric Interview (M.I.N.I.): the development and validation of a structured diagnostic psychiatric interview for DSM-IV and ICD10. J Clin Psychiatry 1998;59(Suppl 20):22–33. de Azevedo Marques JM, Zuardi AW. Validity and applicability of the Mini International Neuropsychiatric Interview (MINI). Gen Hosp Psychiatry 2008;30(4):303–10. Narsimha RP, Madison H, Musser E, Rissmiller D. MINI International Neuropsychiatric Schedule: clinical utility and patient acceptance. Eur Psychiatry 2003;18(7):361–4. Otsubo T, Tanaka K, Koda R, et al. Reliability and validity of Japanese version of the Mini-International Neuropsychiatric Interview. Psychiatry Clin Neurosci 2005;59(5):517–26. Chatterjee S, Chowdhary N, Pednekar S, Cohen A, Andrew G. Integrating evidence-based treatments for common mental disorders in routine primary care: feasibility and acceptability of the MANAS intervention. World Psychiatry 2008;7(1):39–46. Daradkeh T, Eapen V, Ghubash R. Mental morbidity in primary care in Al Ain (UAE): application of the Arabic translation of the PRIME-MD (PHQ) version German. J Psychiatry 2005;8: 32–5.

[28] ZamZam R, Thambu M, Midin M, Omar K, Kaur P. Psychiatric morbidity among adult patients in a semi-urban primary care setting in Malaysia. Int J Ment Health Sys 2009;3:13–8. [29] Broers T, Hodgetts G, Bcatić-Mujanović O, Petrović V, Hasanagić M, Godwin M. Prevalence of mental and social disorders in adults attending primary care centres in Bosnia and Herzegovina. Croat Med J 2006;47(3):478–84. [30] Norton De Roquefeuil G, Boulenger JP, Ritchie K, Mann A, Tylee A. Use of the PRIME-MD Patient Health Questionnaire for estimating the prevalence of psychiatric disorders in French primary care: comparison with family practitioner estimates and relationship to psychotropic medication use. Gen Hosp Psychiatry 2007;29(4):285–93. [31] Avasthi A, Varma SC, Kulhara P, Nehra R, Grover S, Sharma S. Diagnosis of common mental disorders by using PRIME-MD Patient Health Questionnaire. Indian J Med Res 2008;127:159–64. [32] Barua A, Jacob GP, Mahmood SS, et al. A study on screening for psychiatric disorders in adult population. Indian J Community Med 2007;32(1):1–3. [33] Trivedi JK, Sareen H, Dhyani M. Rapid urbanization — its impact on mental health: a South Asian perspective. Indian J Psychiatry 2008;50(3):161–5. [34] Patel V, Kleinman A. Poverty and common mental disorders in developing countries. Bull World Health Organ 2003;81:609–15. [35] Kuruvilla, Jacob KS. Poverty, social stress & mental health. Indian J Med Res 2007;126:273–8. [36] Ministry of Health and Family Welfare. Annual report 2009–10. Available at www.mohfw.nic.in. [37] Planning Commission, Government of India, State plans, trends, concern and strategies, tenth five year plan (Volume III) 2002-2007, Government of India, New Delhi. Available at http://planning commission.gov.in/ plans/planrel/fiveyr/10th/volume3/10th_vol3.pdf