Soc Psychiatry Psychiatr Epidemiol (2002) 37: 316–325 10.1007/s00127-002-0551-x

■ Abstract Background The prevalence (lifetime, 12-month, 1-month) of mental disorders, their relationshipwith sociodemographic features, and the use of serviceswere investigated in the population aged 18 years orolder living in the catchment area of a large hospitalcomplex in the city of São Paulo, Brazil. Methods A com-munity survey was conducted in two boroughs of SãoPaulo, on 1,464 residents aged 18 years or older. The as-sessment of psychopathology was made by CIDI 1.1,yielding diagnoses according to ICD-10 for mood disor-ders, anxiety disorders, non-affective psychosis, sub-stance use disorders, dissociative and somatoform dis-orders, and cognitive impairment. Results Of the totalsample, 45.9 % had at least one lifetime diagnosis ofmental disorder, 26.8 % in the year, and 22.2 % in themonth prior to interview. The most prevalent disorders(lifetime, 12-month, and 1-month, respectively) were:nicotine dependence (25 %, 11.4 %, 9.3 %), any mooddisorder (18.5 %, 7.6 %, 5 %) with depressive episode themost prevalent mood disorder (16.8 %, 7.1 %, 4.5 %), anyanxiety disorder (12.5 %, 7.7 %, 6 %), somatoform disor-der (6 %, 4.2 %, 3.2 %), and alcohol abuse/dependence(5.5 %, 4.5 %, 4 %). No gender differences were found inoverall morbidity. Excluding substance use disorders,women had a higher risk for non-psychotic disorders.The presence of psychiatric diagnosis increased the use

of services, with a low proportion of subjects seekingspecialty mental care. Conclusion Our results confirmthe high prevalence of mental disorders in the commu-nity, similar to findings in other countries. A compari-son with findings from other studies with similarmethodology is made.

■ Key words mental disorders – epidemiology – Brazil– use of services – demographic correlates – prevalences

Introduction

Population-based studies of psychiatric morbidity inBrazil are uncommon. Many studies have been con-ducted in primary health care settings (Mari 1987; Vil-lano et al. 1995), or for specific populations and disor-ders (Lopes et al. 1996), but these studies did not allowestimation of population rates. The main reason for thepaucity of population-based studies is that the countryis very large, with a diversity of cultural and socioeco-nomic aspects represented in its 8.5 million square kilo-meters territorial extension and 160 million inhabitants(Almeida-Filho and Santana 1998).

The currently available estimates come from a multi-site population-based survey conducted on three metro-politan areas of Brazil (Almeida-Filho et al. 1997;n = 6,470), using a 44-item screening instrument de-signed to assess psychiatric morbidity in adults inBrazilian urban areas (Questionário de MorbidadePsiquiátrica do Adulto–QMPA; Santana 1982). Sub-sam-ples of probable cases and non-cases (n = 836) were in-terviewed by psychiatrists using the DSM-III SymptomChecklist. The lifetime prevalence rate for any disordervaries from 30 to 50 % in the three sites. Anxiety andphobic disorders were the most common, with lifetimeprevalence between 10 and 18 %, and particularly affect-ing women. Alcohol abuse/dependence was the secondmost important mental health problem, affecting 8 % ofthe sample, with higher rates in men. As reported by theauthors, methodological problems such as low stability

ORIGINAL PAPER

Laura Andrade · Ellen E. Walters · Valentim Gentil · Ruy Laurenti

Prevalence of ICD-10 mental disorders in a catchment area in the city of São Paulo, Brazil

Accepted: 9 January 2002

SPPE

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Dr. L. Andrade (�) · V. GentilInstituto de PsiquiatriaHospital das ClínicasFaculdade de MedicinaUniversidade de São PauloRUA Dr. Ovidio Pires de Campos, s/n. CEP 05403–010São Paulo, SP, BrazilE-Mail: lhsgandr@usp.br

E. E. WaltersDepartment of Health Care PolicyHarvard Medical School, USA

R. LaurentiDepartamento de EpidemiologiaFaculdade de Saúde PúblicaUniversidade de São Paulo, Brazil

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of the screening instrument and the distinct samplingdesigns in the three research sites may have biased thecomparability of these data.

The present study is an important step in psychiatricepidemiology in Brazil. It is, as far as we know, the firstsurvey to collect data on prevalence and risk factors cov-ering a range of disorders (anxiety,mood disorders,psy-chosis, and substance use disorders) by systematic ad-ministration of a structured psychiatric interview thatallows comparisons with data from other countries. Theaim of the study is to obtain data on prevalence of men-tal disorders in the population aged 18 years or older liv-ing in the catchment area of a large hospital complex,and to investigate their relationship with sociodemo-graphic features in order to provide data on health ser-vice use and needs.

Subjects and methods

The survey site consists of two boroughs of São Paulo, a highly in-dustrialized city located in the Southeast of Brazil.With 12 million in-habitants, São Paulo is the largest city in South America and the sec-ond largest in the world.

The population in this study lives in the catchment area of a pri-mary care unit of the University of São Paulo Medical Center, thelargest hospital complex in South America. The catchment area, con-sisting of the boroughs Jardim America and Vila Madalena, is 412blocks in a geographic area of 10.5 km2. At the time of the 1991 Cen-sus (Fundaçao IBGE 1995), this region contained 28,169 householdswith 91,276 inhabitants. Eligible respondents for this study includeonly people 18 years old or older, i. e., 70,743 inhabitants (77.1 %) withapproximately 2.5 inhabitants per household. The area consists pre-dominantly of families from middle and upper socioeconomic levels,although it does contain some slums and shanty towns.

■ Sample design

The sample is a household survey using an area probability designwith stratification on age and multiple respondents per household.The sample size for this study was calculated using a 0.05 level two-sided test to obtain a precision of plus or minus two standard errors(half a percent) for a rare outcome, such as mania, which is estimatedto have a lifetime population prevalence of 0.8 %. This results in 1,220units. This sample size was then adjusted assuming a non-responserate of 33 %, for a final sample size of 1,626 households.

Since the most current Census data are from 1991, field workerswere sent to the catchment area to compile a complete household list-ing. This process identified 32,136 households. Households were sys-tematically ordered by block and every twentieth house selected, re-sulting in a household probability of selection of 5.1 % to obtain thesample size of 1,626 households.

A list of all individuals living in each selected household was thencreated. In order to improve the probability of observing young psy-chotics and old age psychiatric morbidity, all persons aged 18–24years and 60 years or older living in each selected household were in-terviewed.Of the remaining individuals aged 25–59 years living in theselected household, one was chosen for interview based on the Kish(1965) selection table. In this way, it was possible to have more thanone person interviewed in each selected household.

■ Household response rate

Of the 1,626 households selected,168 (10.3 %) were not eligible for thestudy because they were not households or were empty houses. Of the1,458 households eligible for interview, the residents could not be

contacted or refused to participate in 508 cases (34.8 %), resulting ina household response rate of 65.2 % (950 households).

■ Individual response rate

From these 950 households, 1,906 people were selected to participatein the study, based on the three age strata described above. Of these,442 refused to participate, resulting in a final sample of 1,464 subjects,with an individual response rate of 76.8 %.

It should be emphasized that more than one person may havebeen interviewed in a single household. The distribution of numberof respondents per household is as follows: 574 houses with one re-spondent, 262 houses with two respondents, 93 houses with three re-spondents, and 21 houses with four or more respondents.

■ Statistical analysis

Since the data in this report were obtained from a complex stratifiedsample design, they were weighted to adjust for differential probabil-ities of selection and non-response. The following factors were in-cluded in the analysis weight: 1) the probability of household selec-tion, which is constant for each household unit as the selection ofhousehold was systematic; 2) the probability of selection of each in-dividual in the household. The probability of selection of a subject tobe interviewed varies according to age strata. For stratum 1 and 3 theprobability is 1, because everyone aged 18–24 years and aged 60 yearsor more living in the household was selected for the study. For stra-tum 2, the probability is 1/n2i, where n2i is the number of people aged25–59 years living in household i.

Post-stratification to known population characteristics of sex andregional geographic groupings in the sample age range was also madeto compensate for discrepancies between the sample and the originalcensus population data. For this process, 16 classes were constructedfor each geographic region taking into account eight age groups andgender.

A matrix with the following factors was constructed in order tocalculate the final weight: age, sex, age strata, number of persons ineach strata by household, and a post-stratification factor.

Logistic regression analysis was used to examine the associationbetween demographic factors and diagnostic outcomes.As a result ofthe complex sample design and weighting, estimates of standard er-rors based on the usual assumption of equal-probability simple ran-dom sampling are biased. Thus, standard errors of prevalence esti-mates and of logistic regression coefficients were computed using themethod of Jackknife Repeated Replications (JRR) to adjust for the de-sign effects introduced by clustering and weighting of observations(Kish and Frankel 1970). All evaluations of significance are based ontwo-sided tests using the 0.05 level of significance.

■ Diagnostic assessment

The psychiatric diagnoses were based on face-to-face interviews. Theinstrument used was the Brazilian version of the Composite Interna-tional Diagnostic Interview (CIDI; Miranda et al. 1990; Wittchen et al.1991), version 1.1. CIDI is a structured psychiatric interview (Robinset al.1988) designed for use by lay interviewers.The interviewers weretrained to use the instrument in the CIDI training Center in SãoPaulo, Brazil, in a 7-day study-specific training program. A reliabilitystudy of the Brazilian version of the CIDI is detailed elsewhere (Lopes1994).

The instrument provides lifetime, 12-month, and 1-month preva-lence estimates for ICD-10 diagnoses (International Statistical Classi-fication of Diseases and Related Heath Problems, 10th revision, WHO1992): mood disorders (depressive episode, dysthymia, bipolar disor-der); anxiety disorders (panic disorder, agoraphobia, social phobia,simple phobia, obsessive-compulsive disorder); substance use disor-ders (alcohol, nicotine, other drugs); non-affective psychosis; disso-ciative disorders; somatoform disorders; eating disorders (bulimia,anorexia); and cognitive impairment. Cognitive impairment at the

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time of interview was assessed by the Mini-Mental State Examination(Folstein et al. 1975), and the 1-month prevalence estimate reported.

■ Sociodemographic measures

We considered the effects of several sociodemographic variables: age,gender, marital status, employment status, level of education (years ofeducation),annual family income (in US dollars),and social class.Agewas coded categorically in the ranges 18–24, 25–34, 35–44, 45–54,55–64, and 65 plus. Gender was coded dichotomously (male, female).Marital status was coded categorically as married, never married, andpreviously married (separated, divorced, or widowed). Employmentstatus was coded categorically as employed, unemployed, student,homemaker, and retired/other. Years of education were coded cate-gorically in the ranges 0–8, 9–11, 12–15 and 16 plus. Income was cal-culated as the average annual net income per family. The sample is di-vided into three income categories: the 25 % with the highest income,a 50 % middle bracket, and the 25 % with the lowest income. Socialclass categories are based on the informant occupational situation(not determined where the subject had never worked, or is a full-timestudent, unemployed, or retired). The definition of the categories is asfollows: I: professional; II: employers and managers; III: intermediateand junior non-manual, skilled manual, and self-employed non-pro-fessional; IV: semi-skilled manual and personal service; V: unskilledmanual (OPCS 1991).

■ Use of services assessment

The rate of past month service-use for any purpose was assessed in allrespondents. Respondents’ answers were grouped into two main ser-vice categories: (i) general medical care contact, i. e., seeing a physi-cian other than a psychiatrist, regardless of place, specialty and gen-eral medical service; (ii) Specialty mental care visits to a psychiatristor psychologist, social worker, or counselor, from public or privatesystems.

The frequency of 1-month use of services is examined in relationto the presence of past year CIDI/ICD-10 disorders. Need for servicesis defined as the presence of any 12-month disorder.

Multiple logistic regression was used to determine the relation-ship between use of general medical or specialty mental care forglobal diagnostic categories, and sociodemographic variables.

■ Editing of data

Data entry was carried out using software specifically developed forthe CIDI 1.1.The software has consistency checking for all entries andproduces psychiatric diagnoses according to DSM-IIIR and ICD-10criteria. We closely monitored fieldwork throughout the data collec-tion period, with detection of missing or unclear data. In this paperwe will report lifetime, 12-month, and 1-month disorder prevalencesaccording to ICD-10 criteria.

Results

One thousand four hundred and sixty-four subjectswere interviewed. Men represent 32.9 % of the sample.Table 1 shows the demographic features of the sample(unweighted and weighted) compared to the populationcensus statistics of age and gender. It is a relativelyyoung sample, with more than 60 % of the subjects be-tween 18 and 45 years old.Almost half of the subjects aremarried (47 %).

Of the sample, 52.5 % are originally from other partsof the country. Of these, 83 % moved to São Paulo fromother urban areas. More than 50 % of those not origi-

nally from urban areas have lived in São Paulo for morethan 20 years. Thus, the respondents are predominantlyfrom urban areas or have lived in an urban area for manyyears.

The lifetime, 12-month, and 1-month prevalencerates according to ICD-10 for the total sample and bygender are shown in Table 2. Nearly 46 % of the samplehad at least one lifetime mental disorder, i. e., almost onein two respondents reported a given disorder at sometime in their lives. Of the sample, 26.8 % had an episodein the year preceding the interview and 22.2 % in themonth prior to the interview. The most common disor-der was nicotine dependence. Excluding nicotine de-pendence, 33 % of the sample experienced at least onelifetime disorder, depressive episode being the most

Table 1 Characteristics of the respondents (unweighted and weighted) com-pared with those of the population in study (percent)

Population Sample Samplein study weighted unweighted% % %

SexMale 42.5 42.6 32.9Female 57.5 57.4 67.1

Age, years18–25 15.6 15.5 22.826–45 45.9 45.8 34.346–59 20.2 20.3 17.360 or more 18.3 18.3 25.5

Marital statusMarried/cohabitation n.a. 47.0 39.3Separated/divorced n.a. 10.2 11.1Widowed n.a. 6.4 8.9Never married n.a. 36.3 40.6

Education, yearsIlliterate n.a. 2.04 2.041–7 n.a. 16.9 20.18 n.a. 6.3 6.79–10 n.a. 4.2 4.411 n.a. 9.7 10.212–15 n.a. 24.8 25.1≥ 16 n.a. 35.8 31.3

Occupational statusEmployed n.a. 68.1 62.6Unemployed n.a. 2.1 1.6Homemaker n.a. 11.9 13.9Student n.a. 5.4 7.2Retired/ others n.a. 11.2 13.5

Annual family income**Top 25 % (> 70 000) n.a. 19.1 17.0Next 50 % (13 800–69 000) n.a. 35.4 33.5Low 25 % (0–13 500) n.a. 45.5 49.5

Social class*I n.a. 25.2 23.0II n.a. 37.9 36.7III n.a. 25.9 26.1IV n.a. 3.8 4.5V n.a. 7.2 9.7

Total N 70,743 1,464 1,464

n.a. Information not available* I: Professional; II: Employers and managers; III: Intermediate and junior non-man-ual, skilled manual and self-employed non-professional; IV: Semi-skilled manualand personal service; V: Unskilled manual. Homemaker, student, unemployed, re-tired/others are excluded from the five social class categories** US dollars

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common disorder in any period assessed. The next mostcommon lifetime disorders were somatoform disorder(6 %), alcohol dependence (5.5 %), and simple phobia(4.8 %).

The prevalence of more global categories is alsoshown in Table 2. For these summary categories, sub-stance use disorder was the most prevalent (27.3 %), dueto the high frequency of nicotine dependence. Overall,24 % of the sample fulfilled ICD-10 criteria for at leastone lifetime anxiety or depressive disorder. About 10 %met criteria for those disorders in the year and monthbefore the interview. Over the course of the lifespan,mood disorders were more prevalent than anxiety dis-orders (18.4 % and 12.5 %, respectively), but the 12-month prevalence was the same for both disorders, withthe tendency for anxiety disorders to be more frequentin the 30 days before the interview.

Non-affective psychosis had an overall lifetime rateof 1.9 %, and almost half of the cases were still present inthe year prior to interview. The prevalences in men andwomen did not differ.We found 1.5 % of the sample withlifetime bulimia nervosa, but no cases of anorexia ner-vosa were detected by the CIDI 1.1 interview.

■ Demographic correlates of psychiatric morbidity

Gender

Table 3 presents odds ratios for gender, age groups, andother demographic correlates. There was no differencebetween genders for having at least one lifetime mentaldisorder according to ICD-10. When we excluded nico-tine dependence,women were 1.5 times more likely thanmen to suffer any lifetime mental disorder (95 % CI:1.2–1.9). Women were more likely than men to havemood disorders (with the exception of bipolar disorderand dysthymia, for which there were no gender differ-ences), anxiety disorders (except for obsessive-compul-sive disorder, social phobia, and generalized anxiety dis-order), and bulimia nervosa (OR = 9.4; 95 % CI:2.7–32.4).

Regarding substance use disorders, men had higherlifetime rates of harmful use or dependence of any drug,including nicotine and alcohol.

There were no gender differences in the rates of non-affective psychosis, somatoform disorders, and currentcognitive impairment,or for the presence of two or morecomorbid disorders.

Age

People 65 years or older consistently had the lowestprevalence for all the diagnosis groups, except for cur-

Table 2 Lifetime, 12-month and 1-month prevalence of CIDI 1.1/ICD-10 disorders for the total sample, male and female (weighted data; N = 1,464)

ICD-10 Diagnosis Male Female Total

% (SE) % (SE) % (SE) % (SE) % (SE) % (SE) % (SE) % (SE) % (SE)Lifetime 12-month 1-month Lifetime 12-month 1-month Lifetime 12-month 1-month

Any disorder 45.3 (2.8) 24.8 (1.8) 20.6 (1.8) 46.3 (1.7) 28.2 (1.7) 23.3 (1.5) 45.9 (1.6) 26.8 (1.3) 22.2 (1.2)Any disorder but nicotine dependence 28.3 (2.4) 15.0 (1.9) 13.2 (1.9) 36.6 (1.4) 21.6 (1.3) 17.1 (1.1) 33.1 (1.3) 18.8 (1.1) 15.4 (1.1)Anxiety/depressive disorder 18.3 (1.9) 7.6 (1.1) 5.9 (1.0) 28.2 (1.3) 16.1 (1.2) 11.5 (0.9) 24.0 (1.2) 12.5 (0.9) 9.1 (0.7)Any mood disorder 15.0 (1.6) 4.8 (0.8) 3.6 (0.9) 21.0 (1.4) 10.1 (1.1) 6.0 (0.7) 18.4 (1.2) 7.8 (0.8) 5.0 (0.5)Depressive episode (DE) 13.5 (1.6) 4.3 (0.9) 3.2 (0.9) 19.2 (0.3) 9.2 (1.1) 5.4 (0.6) 16.8 (1.1) 7.1 (0.8) 4.5 (0.6)Dysthymia 3.7 (0.8) 1.1 (0.4) 1.0 (0.4) 4.7 (0.7) 1.6 (0.3) 1.1 (0.3) 4.3 (0.5) 1.4 (0.3) 1.1 (0.2)Any depression (DE and/or dysthymia) 14.6 (1.7) 4.8 (0.8) 3.6 (0.9) 20.7 (1.4) 9.7 (1.1) 5.9 (0.6) 18.1 (1.2) 7.6 (0.8) 4.9 (0.5)Bipolar disorder 1.1 (0.6) 0.3 (0.3) 0.3 (0.3) 0.9 (0.3) 0.6 (0.2) 0.4 (0.1) 1.0 (0.3) 0.5 (0.2) 0.4 (0.2)Any anxiety disorder* 8.2 (1.6) 4.0 (0.8) 3.5 (0.8) 15.6 (1.1) 10.4 (0.9) 7.8 (0.7) 12.5 (1.0) 7.7 (0.7) 6.0 (0.5)Generalized anxiety disorder 3.3 (0.9) 1.1 (0.7) 1.0 (0.7) 4.9 (0.8) 2.1 (0.4) 1.5 (0.4) 4.2 (0.6) 1.7 (0.4) 1.3 (0.4)Panic disorder 0.7 (0.4) 0.2 (0.1) 0.0 2.3 (0.4) 1.7 (0.4) 0.8 (0.2) 1.6 (0.3) 1.0 (0.2) 0.4 (0.1)Agoraphobia 0.8 (0.4) 0.4 (0.1) 0.4 (0.1) 3.0 (0.6) 1.7 (0.4) 1.2 (0.3) 2.1 (0.4) 1.2 (0.2) 0.8 (0.1)Simple phobia 2.2 (0.5) 1.7 (0.4) 1.4 (0.4) 6.7 (0.7) 4.7 (0.6) 3.9 (0.5) 4.8 (0.5) 3.5 (0.3) 2.9 (0.3)Social phobia 2.6 (0.6) 1.5 (0.6) 1.3 (0.6) 4.1 (0.5) 2.7 (0.5) 2.0 (0.4) 3.5 (0.4) 2.2 (0.4) 1.7 (0.3)Any phobia** 4.4 (0.6) 2.4 (0.4) 2.1 (0.3) 11.4 (1.0) 7.9 (0.8) 6.1 (0.6) 8.4 (0.6) 5.6 (0.5) 4.4 (0.4)Obsessive-compulsive disorder 0.4 (0.3) 0.4 (0.3) 0.4 (0.3) 0.1 (0.1) 0.1 (0.1) 0.1 (0.1) 0.3 (0.1) 0.3 (0.1) 0.3 (0.1)Any substance use disorder 33.1 (2.1) 18.1 (1.6) 14.5 (1.8) 23.0 (1.6) 12.8 (1.1) 11.0 (1.1) 27.3 (1.5) 15.1 (1.0) 12.5 (1.1)Alcohol dependence 7.8 (1.5) 6.5 (1.5) 6.3 (1.5) 3.8 (0.4) 3.1 (0.4) 2.2 (0.5) 5.5 (0.7) 4.5 (0.7) 4.0 (0.7)Drug dependence 1.9 (0.6) 1.1 (0.4) 0.9 (0.4) 0.6 (0.3) 0.2 (0.1) 0.2 (0.1) 1.1 (0.3) 0.6 (0.2) 0.5 (0.2)Nicotine dependence 30.0 (2.0) 12.0 (1.6) 8.4 (1.3) 21.3 (0.7) 10.8 (1.3) 9.7 (1.3) 25 (1.5) 11.3 (1.0) 9.2 (0.9)Non-affective psychosis 1.7 (0.6) 0.8 (0.4) 0.5 (0.3) 2.0 (0.4) 0.8 (0.4) 0.8 (0.4) 1.9 (0.3) 0.8 (0.2) 0.7 (0.2)Dissociative disorder 0.5 (0.4) 0.3 (0.3) 0.3 (0.3) 3.4 (0.6) 0.6 (0.3) 0.3 (0.2) 2.2 (0.4) 0.5 (0.2) 0.3 (0.2)Somatoform disorder 4.7 (1.2) 3.0 (1.1) 2.2 (1.1) 6.9 (0.7) 5.0 (0.6) 4.0 (0.6) 6.0 (0.7) 4.2 (0.6) 3.2 (0.6)Bulimia nervosa 0.3 (0.2) 0.1 (0.1) 0.0 2.4 (0.5) 1.7 (0.4) 1.3 (0.4) 1.5 (0.3) 1.0 (0.3) 0.7 (0.3)Cognitive impairment – – 1.3 (0.6) – – 1.1 (0.3) – – 1.2 (0.3)

* Includes panic disorder, agoraphobia, social phobia, simple phobia, obsessive-compulsive disorder** Includes agoraphobia, social phobia, simple phobia

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rent cognitive impairment (OR = 11; 95 % CI: 1.8–66.7).It was possible, because of the oversampling of the el-derly in this survey, to divide the 60 years and over groupinto three categories.Persons aged 60 years and over hadhigher rates of cognitive impairment (4.8 %) than otherage groups in which rates varied between 0.8 and 1.5 %.The rates increased with the advancing of age, from 1 %for people aged 60–69 years, to 3 % for those 70–79 years,and to 15.5 % for those persons aged 80 years or more,and were not different for males and females.

Age was not associated with anxiety disorders as asummary category.For mood disorders the highest rateswere among people 25–54 years old, whereas for sub-stance use disorders the highest rates were among peo-ple 35–54 years old. These two age groups were morelikely to have any lifetime disorders and two or more dis-orders when compared with the age group of 18–24years.

Marital status

Those who were divorced/separated or widowed weremore likely to have any mood disorder and two or moredisorders in their lifetime, showing that disrupted mar-ital status is associated with an increased lifetime riskfor any depression (OR: 2.2; 95 % CI: 1.5–3.3) and life-time comorbidity. Excluding widowed people from thiscategory, separated or divorced respondents were twofold more likely to have alcohol, nicotine, and drugabuse/dependence (OR = 2.2–95 % CI: 1.1–4.6;OR = 1.6–95 % CI: 1.1–2.4; OR = 1.8–95 % CI: 1.2–2.6, re-spectively), although this significance disappearedwhen all substance use disorders were pooled together.

Socioeconomic status

As reflected by years of education and social class, thesocioeconomic status of this sample was far above theBrazilian average. More than 60 % of the sample had 12or more years of education.For those 68 % currently em-ployed,63 % had an occupational status of professionals,

Table 3 Demographic multivariate correlates of lifetime ICD-10 diagnosis groups

Lifetime mood Lifetime anxiety Lifetime substance Any lifetime Two or moredisorders disorders use disorders disorder lifetime disordersOR (95% CI) OR (95% CI) OR (95% CI) OR (95% CI) OR (95% CI)

SexMale 1.0 1.0 1.0 1.0 1.0Female 1.6 (1.2–2.1)* 2.3 (1.5–3.4)* 0.6 (0.5–0.8)* 1.1 (0.8–1.5) 1.3 (0.9–1.7)

Age18–24 1.0 1.0 1.0 1.0 1.025–34 2.0 (1.2–3.4)* 1.3 (0.8–2.0) 1.6 (0.1–2.6) 1.6 (1.1–2.3)* 2.1 (1.2–3.4)*35–44 2.2 (1.3–3.9)* 1.2 (0.7–2.0) 2.6 (1.6–4.3)* 2.1 (1.4–3.1)* 2.3 (1.3–3.8)*45–54 2.3 (1.4–3.8)* 1.3 (0.7–2.3) 2.2 (1.3–3.6)* 2.0 (1.4–3.1)* 1.8 (1.1–3.1)*55–64 1.5 (0.7–3.4) 1.2 (0.7–2.3) 1.7 (0.9–2.9) 1.6 (1.0–2.5)* 1.7 (0.8–3.3)65 or more 0.8 (0.4–1.6) 0.6 (0.3–1.1) 0.8 (0.5–1.4) 0.8 (0.5–1.2) 0.7 (0.4–1.3)

Marital status**Married/cohabitation 1.0 1.0 1.0 1.0 1.0Divorced/separated/widowed 1.5 (0.9–2.3)* 0.8 (0.5–1.4) 1.3 (0.9–1.8) 1.1 (0.8–1.5) 1.5 (1.0–2.3)*Never married 0.9 (0.6–1.3) 1.0 (0.6–1.5) 0.9 (0.7–1.2) 0.8 (0.6–1.1) 1.0 (0.7–1.4)

Education (years)**0–8 0.5 (0.4–0.8)* 0.8 (0.5–1.3) 0.8 (0.5–1.2) 0.9 (0.6–1.3) 0.9 (0.6–1.4)9–11 0.7 (0.5–1.2) 0.6 (0.3–1.2) 0.9 (0.7–1.4) 0.9 (0.6–1.2) 0.9 (0.6–1.5)12–15 1.1 (0.7–1.6) 0.9 (0.5–1.5) 0.8 (0.5–1.1) 1.0 (0.7–1.4) 0.9 (0.6–1.4)≥ 16 1.0 1.0 1.0 1.0 1.0

Employment**Employed 1.0 1.0 1.0 1.0 1.0Unemployed 3.1 (1.2–7.8)* 1.0 (0.2–4.5) 2.3 (1.0–6.0)* 2.3 (0.8–7.1) 2.9 (1.2–6.7)*Homemaker 0.6 (0.4–1.0) 0.7 (0.4–1.2) 0.5 (0.3–0.8) 0.6 (0.5–0.9)* 0.6 (0.3–0.9)*Student 0.6 (0.3–1.3) 0.6 (0.2–1.3) 0.6 (0.3–1.0) 0.7 (0.4–1.2) 0.5 (0.2–1.1)Retired/others 0.7 (0.4–1.2) 0.7 (0.4–1.1) 0.8 (0.5–1.3) 0.9 (0.7–1.3) 0.7 (0.4–1.1)

Family income**Top 25 % (> 70 000) 1.0 1.0 1.0 1.0 1.0Next 50 % (13 800–69 000) 1.0 (0.7–1.7) 1.1 (0.7–1.8) 0.9 (0.6–1.5) 0.8 (0.5–1.3) 0.8 (0.5–1.3)Low 25 % (0–13 500) 0.7 (0.5–1.2) 0.8 (0.4–1.5) 1.0 (0.7–1.5) 0.8 (0.6–1.3) 0.7 (0.5–1.2)

Social class**I 1.0 1.0 1.0 1.0 1.0II 1.3 (0.9–1.9) 0.9 (0.5–1.5) 1.4 (1.0–1.9)* 1.3 (0.9–1.7) 1.1 (0.8–1.6)III 1.1 (0.7–1.7) 1.2 (0.7–2.1) 1.4 (1.0–2.1)* 1.2 (0.8–1.7) 1.5 (1.0–2.5)*IV 0.6 (0.2–1.9) 1.3 (0.6–3.0) 1.1 (0.5–2.6) 1.1 (0.5–2.6) 1.7 (0.8–3.5)V 0.7 (0.3–1.5) 1.4 (0.7–2.7) 0.5 (0.2–1.0) 0.6 (0.3–1.0) 1.0 (0.5–2.1)

* significant for p < 0.05** controlled by age groups and gender

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employers, and managers. Compared to city patterns,the socioeconomic status of this sample is skewed to-ward higher education and higher income level (Fun-daçao IBGE 1995).

Years of education

Respondents with low education (0–8 years of educa-tion) were less likely than those with a college degree toreceive a diagnosis of mood disorders, particularly ofany depression (OR = 0.5; 95 % CI: 0.3–0.8). They had in-creased rates of alcohol abuse/dependence (OR = 2.1;95 % CI: 1–4.9), but when the substance use disorderswere grouped together, there were no differences amongthe educational levels. Level of education was inverselyassociated with dissociative disorder (OR = 3.8; 95 % CI1.1–15.1 for people with 0–8 years of education). The12–15 years of education group was twice as likely tohave somatoform disorder compared to those with 16 ormore years of education (OR = 2.3; 95 % CI 1.3–4.1). Thepresence of any anxiety disorder, overall morbidity andcomorbidity was not related to level of education.

Employment status

Except for anxiety disorders, unemployed respondentswere more likely to have any lifetime disorder, particu-larly substance use disorders, and comorbidity thanthose who were employed. Compared with the em-ployed, students, homemakers, and retired persons were all less likely to have any psychiatric morbidity,particularly substance use disorders.

Social class

Regarding social classes, the results show that the inter-mediate social classes had a higher rate of substance usedisorders. Social Classes II (employers and managers)and III (intermediate and junior non-manual, skilledmanual and self-employed non-professional) were morelikely to have substance abuse or dependence whencompared with Social Class I (professionals). Class V(unskilled manual) had less substance use disorders(OR = 0.5; 95 % CI 0.2–1.0; p < 0.04) and Class III hadmore comorbidity than Class I.

Annual family income

There were no significant differences in prevalence ofany disorder among the income groups.

■ Comorbidity

A total of 25.3 % of respondents in the sample had onedisorder, 11.5 % of respondents had two psychiatric dis-orders, and 9.2 % of the sample had three or more life-time disorders. In other words, one in every two personswith any lifetime disorder had two or more disorders. A

greater proportion of those with a disorder in the yearor in the month before the interview (around 60 %) hadtwo or more psychiatric disorders in their lifetime.These results show that comorbidity is quite a commonphenomenon and psychopathology is concentrated inapproximately the 9.2 % of the total sample that hadthree or more lifetime disorders and accounted fornearly one-third of all 12-month disorders.

There were no gender differences in the comorbidityrates, but people younger than 45 years, unemployed, orfrom a disrupted family were more likely to have morethan one mental disorder in any period of their lives.

■ Use of services

The percentage of people utilizing a health service forany purpose in the month prior to the interview was ex-amined according to summary 12-month diagnosticcategories (Table 4).Considering the total sample,one inevery three respondents obtained general medical ser-vice in the month before the interview. People with nopsychiatric disorder at any time in their lives had thelowest rates of use of general medical services. However,the percentage of people using a general health servicewas higher in the presence of any of the12-month psy-chiatric diagnoses assessed, particularly mood and anx-iety disorders.

There was an increased rate of use of general medicalservice in those who presented with a 12-month so-matoform disorder, compared with the total sample(44.8 % vs 29 %). However, the rate for seeking help frommental health professionals was similar (8.7 % vs 7.7 %).Whether these findings might be indicative of excessiveuse of the health care system by these persons who donot have their disorder recognized as a mental healthproblem will be analyzed in detail in a further article.

Regarding psychiatric/psychological treatment, notmuch more than 10–20 % of psychiatric cases visited aspecialty mental health professional in the previousmonth. People presenting mood and anxiety disordersstill showed the highest rate of attendance. However, anappreciable proportion, particularly those with sub-stance use disorders, did not have any type of health

Table 4 Percentage of people who seek treatment: pattern of last month serviceuse for any purpose by summary 12-month CIDI 1.1/ICD-10 diagnostic categories(weighted data; N = 1,464)

General Specialtymedical care mental care% (SE) % (SE)

Any 12-month disorder 38.3 (2.8) 13.0 (1.8)Any 12-month mood disorder 46.7 (4.1) 23.2 (4.4)Any 12-month anxiety disorder 36.4 (3.7) 19.7 (3.6)Any 12-month substance use disorder 32.1 (3.7) 10.0 (1.9)12-month somatoform disorder 44.8 (7.4) 8.7 (3.1)No psychiatric disorder ever 23.7 (1.6) 5.2 (0.9)Total sample 29.0 (1.3) 7.7 (0.7)

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care. It is worthwhile noting that more than 5 % of peo-ple who have never had a psychiatric diagnosis had vis-ited a mental health professional in the last month(n = 41). This number is very close to the 51 people witha 12-month mental disorder who had a specialist con-sultation in the month prior to the interview.

Focusing on particular sociodemographic groups(Table 5), patterns in care-seeking were observed.Whilewomen were two times more likely than men to seekgeneral medical care, no gender differences were foundin the use of specialty mental care.Considering age,peo-ple 60 years old or more were more likely to visit a gen-eral medical professional, but have a low likelihood ofhaving specialty mental care, compared to other agegroups. Those with disrupted marital status are 1.4times more likely to seek psychiatric/psychological carethan those who are married. Those more socioeconom-ically deprived (taking into account education, socialclass, and income) are the group of people less likely tohave a specialty mental health care visit in the month be-fore the interview.

Discussion

This is the first study in Brazil with an instrument thatallows comparisons with studies from other countries ina sample of adults aged 18 years or older. The resultsshow that mental disorders are highly prevalent in thepopulation studied, with one in two persons having atleast one CIDI/ICD-10 lifetime mental disorder, 27 % inthe year prior to interview, and 22 % in the month priorto interview.Even though these rates could be inflated bythe inclusion of nicotine dependence, the remainingrates are still a matter of concern (33.1 %, 18.8 %, and15.4 %, respectively). These figures attest that mentaldisorders are,similar to findings in developed countries,a major public health problem in Brazil. Comparisons ofthese results with previous Brazilian studies should bemade keeping in mind the differences in samplingstrategies, in socioeconomic status (this is an affluentcatchment area), and case ascertainment. However,these results are consistent with the high prevalence ofoverall mental disorders reported in the Brazilian Mul-ticentric Study (Almeida-Filho et al. 1997), varying from30 to 51 % in the three sites, and in a sample of womenfrom a squatter settlement (36 % probable cases; Rei-chenheim and Harpham 1991).

Substance use disorders are the most prevalent groupof disorders, and this rate is raised by the inclusion ofnicotine dependence. This was the most frequent disor-der, presented in 25 % of the sample followed by depres-sive episode (16.8 %). As reported in the study “TheGlobal Burden of Disease” (Murray and Lopez 1996), de-pressive episode is one of the leading causes of disabil-ity and premature death. Tobacco is expected to killmore people in the next century than any single disease.Thus, these findings should be taken into account byBrazilian health authorities when planning services.

The current official diagnostic criteria in Brazil isICD-10, thus the results of this study are presented usingthis classification. Comparing our finding with studiesdone in other countries using CIDI as the diagnostic in-strument and DSM III-R as the diagnostic classificationsystem (National Comorbidity Survey, NCS, Kessler etal. 1994; the Netherlands Mental Health Survey and In-cidence Study, NEMESIS, Bijl et al. 1998; and the Mexi-can American Prevalence and Services Survey,Vega et al.1998), some similarities were found in overall estimates.Since ICD-10 identifies more cases of depression in ageneral population than DSM III-R and fewer anxietydisorders, the morbidity detected by each criteriashould be compared with caution (Wacker et al. 1992).

The overall estimate of 46 % lifetime prevalence ofmental disorder is close to the 48 % of NCS, the 41.2 % inNEMESIS, and the 48.7 % of Native-born MexicanAmericans. The lifetime rates of mood disorders in theNCS (19.3 %) and NEMESIS (19 %) are very similar tothe rate in this study (18.4 %). Our rate of lifetime anxi-ety disorders (12.5 %) is half the rate in the United States(24.9 %) and lower than the rate for the Netherlands

Table 5 Demographic multivariate correlates of last month service use

General Specialtymedical care mental care

SexMale 1.0 1.0Female 2.2 (1.6–3.0)* 1.4 (0.9–2.2)

Age, years18–25 1.0 1.026–45 1.1 (0.7–1.6) 1.0 (0.5–1.7)46–59 1.2 (0.9–1.8) 0.8 (0.4–1.5)60 or more 1.7 (1.2–2.3)* 0.3 (0.2–0.6)*

Marital statusMarried/cohabitation 1.0 1.0Separated/divorced 1.3 (0.9–2.1) 3.9 (1.9–8.0)*Widowed 1.4 (0.8–2.2) 1.3 (0.4–3.6)Never married 0.8 (0.6–1.1) 1.7 (1.1–2.9)*

Education, years0–8 0.9 (0.6–1.4) 0.2 (0.1–0.3)*9–11 0.9 (0.6–1.4) 0.5 (0.3–1.0)12–15 1.0 (0.7–1.4) 0.9 (0.5–1.4)≥ 16 1.0 1.0

Occupational statusEmployed 1.0 1.0Unemployed 0.7 (0.3–1.9) 0.8 (0.2–3.9)Homemaker 1.7 (1.3–2.4)* 0.5 (0.3–1.2)Student 0.8 (0.5–1.2) 1.4 (0.7–2.8)Retired/others 1.6 (1.1–2.2)* 0.9 (0.4–2.1)

Annual family income**Top 25 % (> 70 000) 1.0 1.0Next 50 % (13 800–69 000) 1.1 (0.7–1.6) 0.9 (0.5–1.7)Low 25 % (0–13 500) 0.9 (0.6–1.2) 0.4 (0.2–0.8)*

Social class I 1.0 1.0II 1.0 (0.7–1.3) 1.1 (0.7–1.8)III 0.8 (0.6–1.2) 0.8 (0.5–1.6)IV 0.6 (0.3–1.4) 0.3 (0.1–1.2)V 0.5 (0.3–0.8)* 0.1 (0.02–0.3)*

*p < 0.05** US dollars

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(19.3 %), and Mexican Americans (16.8 %). Compar-isons in prevalence of any substance use disorder aredifficult because our rate is increased with the inclusionof nicotine dependence. Considering alcohol and druguse disorders only, we report lower rates than any ofthose other three studies. Whether these are true differ-ences or equalities will be examined in future analysiscomparing our results using DSM III-R criteria withthese and a series of other studies coordinated by the In-ternational Consortium of Psychiatric Epidemiology(ICPE; Kessler 1999).

The figures for other drug abuse/dependence asidefrom alcohol or nicotine may represent a rather conser-vative estimate for drug consumption in this sample(1.1 % lifetime prevalence). In a previous study designedto assess use of illegal drugs in a Brazilian urban area insubjects 14 years old or more, Carvalho-Neto et al.(1987) reported a rate of 2.2 %. In a study done in tenmajor cities in Brazil, Galduroz et al. (1997) showed thatone in every four students (95 % of the sample aged10–18 years) had experienced psychotropic drugs, ex-cluding alcohol and tobacco. For alcohol abuse and de-pendence, the rates in former Brazilian studies rangefrom 3 to 9 % (de Almeida e Coutinho 1993). Differencesin sampling methods and instruments compromise thecomparability of these data.

A striking finding is the high rate of somatoform dis-order found in our sample (6 % lifetime prevalence, ac-counted for mainly by chronic pain disorder). This isconsistent, however, with the Brazilian MulticentricStudy (Almeida-Filho et al. 1997) which reported life-time prevalences of somato-dissociative disorders from2.8 to 8 % in the three sites.

Certain cultural or religious experiences may resultin positive scores in the CIDI 1.1 section of schizophre-nia, with low validity when compared with the clinicalreappraisals.For this reason, the lifetime rate of 1.9 % fornon-affective psychosis may be overestimated. The bu-limia nervosa lifetime prevalence rate of 2.5 % in womenis within the Sullivan et al. (1998) estimated range of1–3 % of lifetime prevalence of bulimia in this genderfrom different Western cultures.

It seems important to stress the chronicity or relaps-ing nature of more frequent disorders shown by the highratios between the 1-month and lifetime rates. Half ofthe lifetime cases of more prevalent disorders are stillpresent in the month prior to interview (ratio of 0.5 forany disorder, any anxiety, and somatoform; around 0.45for any substance use disorders, increasing to 0.7 for al-cohol-related disorders).The finding of the chronicity ofsomatoform disorder has significant clinical and epi-demiological relevance, as it is known that these caseshave repeated help-seeking behavior.The co-occurrenceof physical symptoms with other psychiatric disorders,risk factors and use of services will be explored in a fu-ture paper.

In addition to chronicity, comorbidity is also a com-mon occurrence in our study. There is a heavy burdenexperienced by those with three or more disorders in a

lifetime. These results are similar to previous studies inother countries that have shown high rates of comor-bidity of psychiatric disorders in the community(Robins and Regier 1991; Kessler et al. 1994; Bijl et al.1998). This must be taken into account when planningservices and prevention strategies.

In order to address questions regarding the validityof population-based studies using structured lay inter-views, 391 cases and non-cases were evaluated by clini-cal psychiatrists using SCAN 2.0. A comparison of thetwo assessment methods is under way, and will be re-ported in a subsequent paper.

■ Demographic factors

As documented in several epidemiological studies(Canino et al. 1987; Regier et al. 1988; Kessler et al. 1994;Mason and Wilkinson 1996; Bijl et al. 1998), as well as inthe Brazilian Multicentric Study (Almeida-Filho et al.1997), our findings confirm that women experiencemore mood disorders (particularly depressive episode)and anxiety disorders, and men more substance use dis-orders. In addition, women are about nine times morelikely to have bulimia than men. Somatoform disordersdid not show differences by gender, similar to findingsin Puerto Rico (Canino et al. 1987) and primary caresamples (Piccinelli and Simon 1997).

Cognitive impairment is the only disorder in thisstudy with higher rates in people 60 years or older.Theserates and the variation across age groups are similar tothe rates of the ECA study (Regier et al. 1988). It shouldbe emphasized that each case of cognitive impairmentassessed through the CIDI was clinically evaluated andthe false positives (usually people with low educationallevel) were excluded from the calculation of the rates.

Overall morbidity and comorbidity decreased at theextreme age groups with a peak in the 35–44 year agegroup.There was no trend in the age distribution of anx-iety disorders.A disrupted marital status is substantiallyassociated with any mood or substance use disorder,and comorbidity. Whether it is a casual risk factor or aconsequence of the disorder could not be determinedbecause of lack of information on the time of maritaldisruption.

Socioeconomic status as a risk factor for mental dis-orders showed a complex relation and the results mustbe viewed with some caution. Findings such as the lowerprevalence of mood disorder in people with less educa-tion and decreased rates of substance use in SocialClasses IV and V might be related to a special feature ofthis sample. Since this is a sample with high socioeco-nomic status, most of those with less education havesemi-skilled or unskilled occupations or work in per-sonal services (porters, housemaids) in this middle-class highly educated environment, and could not keeptheir jobs if they had severe mental problems. The asso-ciation of alcohol abuse/dependence with low educationis consistent with that reported in the Brazilian Multi-

324

centric Study (1997). Future studies in low-income andlow-educated population should be done to explorethese findings.The classic association of unemploymentand mental morbidity, particularly substance use disor-ders, was confirmed in this study.

■ Use of services

An important issue should be kept in mind to better un-derstand the pattern of service use in this sample. Thisis a wealthy community and the health facilities avail-able to persons in this catchment area are some of thebest in the country, not representing the services avail-able to the nation as a whole.

Our findings show considerably higher rates of use ofspecialty services, when comparing other studies withsimilar methodology (Alegria et al. 2000). However, itshould be considered that the rates reported there arefor consultation for a mental problem, whereas ours arefor any purpose.We have no way of knowing in our datawhether people are seeking general medical care for so-matic presentations associated with a primary psychi-atric disorder or for a physical disorder.Our higher ratesfor specialty mental care might be due to the pattern ofour service system that is still centralized in specialtycare with a lack of family doctors or primary care units.

Nevertheless, we still noticed some sub-utilization ofmental health care services,with many people with emo-tional problems seeking help in the general medical sec-tor. The increased rates of general medical visits foundin people with mood, anxiety, and somatoform disor-ders might indicate a considerable proportion of hiddentreatment of emotional problems. Unnecessary exami-nations and visits to general clinicians by those withmental disorders probably occur.

The 5 % rate of people without any detectable psychi-atric disorder visiting a mental health service in themonth before the interview is nearly the same for thosewith last-year disorder having the same kind of care.This might be understood as an index of psychothera-peutic seeking by this highly educated sample for dis-tress or life problems, or still people with sub-thresholddiagnosis seeking help at an early stage. Again, thismight be related to particularities of our health system,as lack of priority planning and delivery.

Another thing worth noting is the effect of sociode-mographic variables in the use of services. Better edu-cated people had a higher utilization of mental care ser-vices. This may be due to having a more positive attitudeto psychological intervention. Age group differencesmay be due to cohort effects and geriatric services plac-ing a greater emphasis on mental disorders.Future stud-ies in more deprived populations should be done to ad-dress this issue.

We must use caution in interpreting the results of thepresent study. The findings in this sample cannot be ex-tended to the whole country. Brazil is a very large coun-try,with an array of cultural and socioeconomic aspects.

The lack of influence of some socioeconomic variablesin the risk for mental disorders might be due to a certainhomogeneity of this sample which diminished thepower to detect these influences.Other issues of concernare related to sampling strategies. Although we wereaware that in the survey site some people lived on thestreets, we could not reach those persons who did nothave a fixed address. Homeless people usually have highprevalence of mental disorders and this is true in Brazilas shown in a recent study done in an urban area of aBrazilian city (Heckert et al. 1999). However, we are notable to estimate the amount of influence this omissionmight have on the prevalence rates found here.

Despite the variations in methods of assessment anddiagnostic criteria, the similarities in risk factors andprevalence in comparison with other studies might in-dicate that there is some validity in what we have mea-sured.

■ Acknowledgements We would like to thank all the respondents;Prof. Cecilia Amaro de Lolio* for all her commitment to make possi-ble the CIDI data collection; Prof. Ronald Kessler for his comments ina previous version; Prof. Paulo Rossi Menezes and Jenny Hochstadtfor their help in data management; Maria de Lourdes Larrea for sta-tistical help in calculating the weights; Pro-Reitoria de Pesquisa daUniversidade de São Paulo, Fundaçao Faculdade de Medicina, andSmith Klein Beecham for funding the license of SAS Software. MaryF. Gonçalves and Carla Juliana Monteiro provided all clerical and ad-ministrative work. This study was supported by FAPESP (ProjetoTemático 93/0501–4).

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