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Original article

The burden of mental disorders in primary care

G. Grandes *, I. Montoya, M.S. Arietaleanizbeaskoa, V. Arce, A. Sanchez

on behalf of the MAS group1

Primary Care Research Unit of Bizkaia, Basque Healthcare Service - Osakidetza, Luis Power, 18-4a Planta, 48014 Bilbao, Spain

A R T I C L E I N F O

Article history:

Received 27 May 2010

Received in revised form 8 November 2010

Accepted 13 November 2010

Keywords:

Mood disorders

Anxiety disorders

Health-related quality of life

Prevalence

Comorbidity

Primary health care

A B S T R A C T

Objectives: To describe and compare the prevalence of mental disorders across primary care populations,

and estimate their impact on quality of life.

Methods: Cross-sectional multilevel analysis of a systematic sample of 2539 attendees to eight primary

care centres in different regions of Spain, assessed with the WHO Composite International Diagnostic

Interview (CIDI 1.1), the Short Form Health Survey (SF-36) quality of life questionnaire and the SF-6D

utility index.

Results: The 12-month prevalence of any mental disorder was 23% (95% confidence interval: 21–24%),

10% had mood, 9% anxiety, 5% organic, 4% somatoform, and 1% alcohol use disorders, with a significant

between-centre variability (P < 0.001). People with mental disorders had one standard deviation lower

mental quality of life than the general population. We estimated that 1831 quality-adjusted life-years

(QALYs) are lost annually per 100,000 patients due to mental disorders, without considering mortality.

Mood disorders have the worst impact with an annual loss of 1124 QALYs per 100,000 patients, excluding

mortality (95% confidence interval: 912–1351).

Conclusions: Prevalence rates were similar to those obtained in international studies using the same

diagnostic instrument and, given the significant between-centre variability found, it is recommended

that mental health statistics be considered at small area level. Mental disorders, and especially mood

disorders, are associated with very poor quality of life and higher scores on disability indexes than other

common chronic conditions.

� 2011 Published by Elsevier Masson SAS.

1. Introduction

Mental disorders are a growing public health problem, affectinghundreds of millions of people, and creating an enormous toll ofsuffering, disability and economic loss [1]. The World HealthOrganization (WHO) attributed 31% of all years lived-with-disabilityto neuropsychiatric disorders (11% to unipolar depression, 3.7% to

* Corresponding author. Tel.: +34 94 600 66 38; fax: +34 94 600 66 39.

E-mail address: gonzalo.grandes@osakidetza.net (G. Grandes).1 Director team: Primary Care Research Unit of Bizkaia, Basque Healthcare

Service-Osakidetza (principal investigator: Gonzalo Grandes; co-investigators:

Alvaro Sanchez, Imanol Montoya, Ricardo Ortega Sanchez-Pinilla). Research team:

Basque Healthcare Service-Osakidetza: Basauri-Arız Health Center (Jesus Torcal,-

Veronica Arce), Galdakao Health Center (Pilar Echevarria, Marisol Arietaleaniz-

beaskoa), Algorta Health Center (Irene Toquero, Janire Payo). Catalonian Healthcare

Service: Serraparera Health Center, Barcelona (Agusti Guiu, Ana Cascos). Castilla y

Leon Healthcare Service: Casa Barco Health Center, Valladolid (Carmen Fernandez,

Jose Ignacio Recio), La Alamedilla Health Center, Salamanca (Luis Garcıa, Manuel

Gomez, Yolanda Castano). Castilla – la Mancha Healthcare Service: San Fernando

Cuenca III Health Center, Cuenca (Vicente Martinez, Patricia Lopez). Galicia Health

Service: Sardoma Health Center, Vigo (Francisco J Soidan, Marisa Enrıquez).

Please cite this article in press as: Grandes G, et al. The burden ofdoi:10.1016/j.eurpsy.2010.11.002

0924-9338/$ – see front matter � 2011 Published by Elsevier Masson SAS.

doi:10.1016/j.eurpsy.2010.11.002

alcohol use disorder, 2.7% to schizophrenia, and 2.4% to bipolaraffective disorder) and predicts unipolar depressive disorder to bethe leading cause of the total disease burden in 2030 [2,3].

Integrating mental health services into primary care is the mostviable way of ensuring that people receive the mental health carethey need [3]. Most people suffering mental disorders will visittheir general practitioner, complaining either of psychological orsomatic symptoms [4,5]. Medically unexplained symptoms, socommon in general practice, are strongly associated with commonmental disorders and are a challenge for general practitioners [6,7].In addition, mental disorders interact with other non-communi-cable and communicable diseases and also contribute to accidentaland non-accidental injuries [8]. Nevertheless, primary careservices prioritize the control of diseases and risk factors thatcause early death, such as cardiovascular disease, diabetes or highblood pressure, above those that cause disability. As a conse-quence, the real need for the promotion of mental health, as well asthe management of mental health problems, in primary care isunderestimated [1], and for the particular case of Spain theproportion of patients receiving minimally adequate treatment hasbeen reported to be low [9].

mental disorders in primary care. European Psychiatry (2011),

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A change in priorities and reallocation of health resources isrequired and a basic indicator to appropriately scale up theseservices is the prevalence of mental disorders among primary careattendees. However, available estimates vary widely with char-acteristics of participants and measurement instruments in differentstudies, as well as across different geographic areas and healthservices. Two recent studies in Spain exemplify this. King et al.reported that mental disorders in people attending their generalpractitioners vary significantly between European countries andfound the highest prevalence of mood disorders in Spain, this being18% and 11% for women and men respectively [10]. On the otherhand, Roca et al. produced figures more than two times higher, 41%and 27%, also for the Spanish primary care population [11].

Another basic indicator to assess the comparative importance ofdiseases is disability-adjusted life years (DALYs), calculated as thesum of the years of life lost due to premature mortality and theyears lost due to disability [3]. This measure has been criticised forusing disability weights derived from the opinion of experts on theconsequences of specific diseases [12]. Alternatively, there areutility indexes that reflect social preferences and the value thatsociety gives to different states of health, from 0 (death or theworst situation) to 1 (perfect health). These indexes are used tocalculate quality-adjusted life-years (QALYs) weighting each yearof life by a utility score associated with the corresponding healthstatus [13]. The objectives of this study were to describe theprevalence of the most common mental disorders, psychiatriccomorbidity, and the variability across different primary carepopulations found within one country, Spain; as well as to estimatethe burden of disease based on the decrease in quality of life andthe annual loss in QALYs associated with these disorders withoutconsidering mortality.

2. Subjects and methods

2.1. Participants

This was a cross-sectional study carried out in 2006–2007 infive Spanish autonomous regions. The study population comesfrom a clinical trial of physical activity promotion in which allgeneral practice attendees at eight urban primary health carecentres from October 2003 to May 2004 were eligible to participate[14]. These centres served urban populations of 11,000–30,000people. At the beginning of the clinical trial, a systematic samplewas taken from among the patients aged 18–80 years oldscheduled for appointments with their general practitioner.Patients were excluded from the trial if they were physicallyactive, there were difficulties with follow-up or they hadconditions that could preclude exercising safely:

� specifically, cardiovascular or cerebrovascular diseases (e.g.,coronary heart disease, uncontrolled arrhythmia, heart failure,cardiomyopathy, pericarditis, severe or uncontrolled valvular,arterial-venous or embolic disease);� neuromusculoskeletal disorders that are exacerbated by exer-

cise;� chronic diseases with a marked organ or system impairment

(e.g., severe chronic lung, kidney or liver disease);� uncontrolled metabolic diseases (e.g., diabetes, thyrotoxicosis or

myxedema);� chronic active infectious diseases (e.g., hepatitis or AIDS);� severe emotional distress;� complicated pregnancies.

A detailed description of the recruitment process in the originalclinical trial is given elsewhere [15]. Two years after finishing theclinical trial, research nurses contacted those who had collaborated

Please cite this article in press as: Grandes G, et al. The burden ofdoi:10.1016/j.eurpsy.2010.11.002

in the final follow-up visit and also those who had been initiallyexcluded from the trial because they were physically active, toinvite them to participate in this cross-sectional study. Thesenurses informed participants of the objectives and procedures ofthe study, reviewed once again exclusion criteria and invited themto participate. Those who agreed to collaborate signed a consentform before measurements were taken. The study protocol wasapproved by the institutional ethical research committees of allparticipating centres.

2.2. Measurements

Participants’ psychiatric disorders were evaluated using theComposite International Diagnostic Interview (CIDI), Spanishversion 1.1 [16]. This instrument was designed by the WHO foruse by trained interviewers who are not clinicians. It has been usedin seminal epidemiological studies and has been accredited withhigh reliability and validity, with the exception of the psychoticsymptoms module, not used in this study [17–21]. The CIDI wasadministered by research nurses who received three days(equivalent to 24 h) of intensive official training provided by theSpanish representatives of the WHO centre for research andtraining, devoted to reviewing the interviewers’ instruction guideand its practical administration using role playing techniques. Apilot study was subsequently conducted in each of the collaborat-ing centres during which the nurses received advice on problemsand concerns regarding administration of the interviews. In thisarticle, we codify diagnoses according to DSM-III-R Axis I criteriabased on symptoms detected in the previous 12 months andthroughout life.

Health-related quality of life scores were obtained using theSpanish version of the Medical Outcomes Trust SF-36 question-naire (version 1) [22,23]. Standardised scores were calculatedfor the Spanish population (norm-based mean for each sex = 50,standard deviation = 10) [22]. A utility index (SF-6D), based onthe method developed by Brazier et al., was calculated as aunique quality of life state for each individual [13]. The SF-6Dutility index reflects the value, between 0 (death or worsthealth state) and 1 (perfect health), which society gives to oneyear of life with a specific heath status, and it is used to calculateQALYs.

Age, sex, social class, occupation, and educational level wererecorded and classified in accordance with the recommendationsof the Spanish Society of Epidemiology [24].

2.3. Analysis

We calculated the proportion of people with different diagnosesof mental disorders, prevalence odds ratios (PORs) for the socio-demographic characteristics associated with them and 95%confidence intervals (95% CI), taking into account the clusteredstructure of data of this multicenter study (SAS1 PROC SURVEY-FREQ and SURVEYMEANS, SAS Institute Inc., Cary, NC, USA, 2002).Multilevel logistic regression analysis was undertaken to identifycharacteristics associated with each diagnosis group, takingaccount of the hierarchical structure of the data, with patients(level 1) nested within centres (level 2), and with centres asintercept random effects to compare between-centre prevalence ofmental disorders (SAS1 PROC GLIMMIX). We used multivariatelinear mixed models with the SF-6D utility index as the dependentvariable to estimate the loss of utility (without consideringmortality) associated with each mental disorder group, simulta-neously adjusted for the socio-demographic characteristics listedin Table 1 and other diagnosis groups listed in Table 2 (SAS1 PROCMIXED). The contribution of variables included in each of thesemodels was determined using likelihood ratio tests (significance

mental disorders in primary care. European Psychiatry (2011),

Table 1Characteristics of participants.

Study population General population

18–80 years olda,b

Primary care population

18–80 years oldb

n % % %

Total 2539 100

Sexa

Male 1033 40.69 49.26 41.65

Female 1506 59.31 50.74 58.35

Agea

18 to 29 146 5.75 16.96 14.44

30 to 39 331 13.04 22.97 15.35

40 to 49 506 19.93 20.73 17.48

50 to 59 578 22.76 16.37 15.69

60 to 69 607 23.91 12.95 18.09

70 to 80 371 14.61 10.02 18.96

Level of educationa

None or elementary school 890 35.05 38.41 Not available

Middle or high school 1139 44.86 48.03

University 510 20.09 13.56

Social classb

I, Manager large company 207 8.15 10.56 7.09

II, Manager small company 289 11.38 10.21 8.60

III, Intermediate employee 806 31.74 23.71 22.88

IV–V, Manual worker 1237 48.72 55.52 61.43

Work statusb

Works out of home 1225 48.25 51.57 41.99

Student 49 1.93 6.54 2.37

Homemaker 627 24.69 13.10 17.42

Unemployed 88 3.47 7.17 7.17

Retired 485 19.10 20.56 29.63

Others 65 2.56 1.06 1.42

Health centre

Algorta 335 13.19

Basauri - Arız 497 19.57

Cerdanyola del Valles 157 6.18

Cuenca 343 13.51

Galdakao 473 18.63

Salamanca 265 10.44

Valladolid 292 11.50

Vigo 177 6.97

a Spanish National Statistics Institute: current population estimates for Spain, 2001 population and housing census, http://www.ine.es/.b Ministry of Health and Social Policy. 2006 National Health Survey of Spain, http://www.msps.es/estadEstudios/estadisticas/encuestaNacional/encuesta2006.htm

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criterion P < 0.05), and non-significant terms were removedfollowing a backward step-wise procedure.

Markov Chain Monte Carlo techniques were used to simulatethe distribution of the QALY losses in the population excludingmortality, associated with each disorder by multiplying thedistributions of the estimated effect on utility for each disorderby the prevalence of the condition [25]. For each disorder, the meanannual loss in QALYs without considering mortality and the 95%credibility interval were estimated from the posterior distributionof the 100,000 simulated values. This is interpreted as the burdenresulting from the disorder, excluding mortality [26].

3. Results

There were 5504 primary care patients eligible for this study,but due to discontinuation of funding, research nurses were onlyable to contact the first 3427 patients, of whom 446 (13.0%) met atleast one of the exclusion criteria, 297 (8.7%) refused to collaborate,110 (3.2%) did not attend the appointment, and 35 (1.0%) had aninvalid measurement. The following analyses correspond to the2539 patients with complete data, 74% of those contacted. Age andsex distributions of people who participated and who declinedwere similar (P > 0.09).

Please cite this article in press as: Grandes G, et al. The burden ofdoi:10.1016/j.eurpsy.2010.11.002

Characteristics of participants and those of the Spanish generaland primary care populations are listed in Table 1. In our sample,the mean age was 53.58 (S.D. = 14.20) and 59.3% were women.Indeed, the socio-demographic structure of the study sample iscloser to that of the primary care population than to that of thegeneral population: there are more women, people over their 50s,and homemakers, as well as an under-representation of peopleyounger than 40, students and unemployed people. On the otherhand, the educational level, social class, and work statusdistributions of the study population lie between general andprimary care populations (e.g., social class I: 8.1% in the studysample, 10.6% in general population, and 7.1% in primary carepopulation).

The overall lifetime prevalence of one or more mental disorderswas 37.8% (95% CI, 35.9 to 39.6%) and the 12-month prevalence,22.8% (95% CI, 21.2 to 24.4%). Mood disorders were the mostcommon disorders with 23.2% lifetime prevalence (95% CI, 21.6 to24.9%) and 10.0% 12-month prevalence (95% CI, 8.8 to 11.4%).Anxiety disorders were next, with 15.4% lifetime prevalence (95%CI, 13.9 to 16.8%) and 9.1% 12-month prevalence (95% CI, 8.0 to10.3%), followed by somatoform, organic, and then alcohol usedisorders (Table 2). Since prevalence of mental disorders is two ormore times higher in women than in men, except for alcohol usedisorders, Table 2 is stratified by sex. Prevalence varies widely

mental disorders in primary care. European Psychiatry (2011),

Table 2Lifetime and 12-month prevalence of mental disorders: total and stratified by sex.

Total Female Male

Life 12-month Life 12-month Life 12-month

Diagnosis groups % 95% CI % 95% CI % 95% CI % 95% CI % 95% CI % 95% CI

Mood disordersa 23.2 (21.6–24.9) 10.0 (8.8–11.1) 30.3 (27.9–32.7) 13.3 (11.5–15.1) 13.2 (11.1–15.3) 5.2 (3.8–6.6)

Major depressiona 20.7 (19.1–22.3) 8.4 (7.3–9.5) 27.5 (25.2–29.8) 11.3 (9.7–13.0) 11.1 (9.2–13.0) 4.3 (3.0–5.6)

Dysthymiaa 10.7 (9.5–12.0) 5.0 (4.2–5.9) 14.7 (12.9–16.6) 6.8 (5.5–8.1) 5.1 (3.7–6.5) 2.5 (1.5–3.5)

Bipolar disordersa 0.5 (0.2–0.8) 0.2 (0.0–0.4) 0.5 (0.1–0.9) 0.3 (0.0–0.6) 0.5 (0.1–0.9) 0.2 (0.0–0.5)

Anxiety disordersa 15.4 (13.9–16.8) 9.1 (8.0–10.3) 19.8 (17.7–21.8) 11.8 (10.1–13.4) 9.1 (7.3–10.9) 5.4 (4.0–6.8)

Panic disordera 2.8 (2.1–3.4) 1.3 (0.9–1.8) 3.5 (2.5–4.4) 1.8 (1.1–2.4) 1.7 (0.9–2.5) 0.7 (0.2–1.2)

Agoraphobia (without panic)a 4.2 (3.4–5.0) 2.4 (1.8–2.9) 5.7 (4.5–6.9) 3.1 (2.2–4.0) 2.0 (1.1–2.9) 1.3 (0.6–2.0)

Simple phobiaa 4.4 (3.6–5.2) 3.5 (2.7–4.2) 5.6 (4.4–6.8) 4.4 (3.3–5.4) 2.6 (1.6–3.6) 2.2 (1.3–3.1)

Social phobiaa 3.6 (2.8–4.3) 2.2 (1.6–2.8) 4.4 (3.4–5.5) 2.7 (1.9–3.6) 2.3 (1.4–3.2) 1.5 (0.8–2.2)

Generalized anxiety disordera 6.9 (5.9–7.9) 3.0 (2.3–3.7) 8.9 (7.4–10.3) 3.9 (2.9–4.9) 4.0 (2.8–5.2) 1.7 (0.9–2.5)

Somatoform disordersa 7.6 (6.6–8.6) 4.3 (3.5–5.1) 10.0 (8.5–11.5) 5.7 (4.5–6.9) 4.2 (3.0–5.4) 2.2 (1.3–3.1)

Somatization disordera 0.1 (0.0–0.3) 0.0 (0.0–0.1) 0.1 (0.0–0.3) 0.1 (0.0–0.2) 0.1 (0.0–0.3) 0.0

Somatoform pain disordera 6.2 (5.3–7.2) 3.8 (3.1–4.6) 8.5 (7.1–10) 5.1 (4.0–6.3) 3.0 (1.9–4.1) 2.0 (1.1–2.9)

Conversion disordera 1.1 (0.7–1.5) 0.2 (0.0–0.3) 1.2 (0.6–1.8) 0.3 (0.0–0.6) 0.9 (0.3–1.5) 0.0

Hypochondriasisa 0.4 (0.1–0.6) 0.3 (0.1–0.5) 0.5 (0.1–0.9) 0.4 (0.0–0.7) 0.2 (0.0–0.5) 0.2 (0.0–0.5)

Somatoform disorder not

otherwise specifieda

0.0 (0.0–0.1) 0.0 (0.0–0.1) 0.0 0.0 0.1 (0.0–0.3) 0.1 (0.0–0.3)

Alcohol use disordersa 2.5 (1.9–3.1) 0.7 (0.3–1.0) 0.4 (0.1–0.8) 0.1 (0.0–0.2) 5.5 (4.1–6.9) 1.7 (0.7–2.3)

Alcohol abusea 2.1 (1.6–2.7) 0.4 (0.2–0.7) 0.4 (0.0–0.7) 0.0 4.7 (3.4–6.0) 1.0 (0.4–1.6)

Alcohol dependencea 0.6 (0.3–0.9) 0.3 (0.1–0.6) 0.1 (0.0–0.2) 0.1 (0.0–0.2) 1.4 (0.7–2.1) 0.7 (0.2–1.2)

Organic disorders 4.8 (3.9–5.6) 4.7 (3.9–5.5) 5.8 (4.6–6.9) 5.7 (4.6–6.9) 3.3 (2.2–4.4) 3.2 (2.1–4.3)

Dementia 4.7 (3.9–5.5) 4.7 (3.9–5.5) 5.7 (4.6–6.9) 5.7 (4.6–6.9) 3.2 (2.1–4.3) 3.2 (2.1–4.3)

Deliriuma 0.1 (0.0–0.2) 0.0 0.1 (0.0–0.2) 0.0 0.1 (0.0–0.3) 0.0

One or more disorders 37.8 (35.9–39.6) 22.8 (21.2–24.4) 45.7 (43.2–48.2) 28.3 (26.1–30.5) 26.2 (23.6–28.9) 14.7 (12.6–16.9)

n = 2539.a n = 2420 (excluding those participants with dementia).

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between collaborating centres (P < 0.001), from 34.2 to 9.6% for12-month prevalence of any mental disorder, 18.5 to 4.0% foranxiety disorders, and 12.8 to 3.9% for mood disorders (Table 3).Lifetime psychiatric comorbidity was found in 11.0% of the primarycare patients, and the most common combination was that ofanxiety and depressive disorders (8.1%) (Fig. 1).

With regard to the socio-demographic characteristics shown inTable 3, there is a clear association between female sex andprevalence of mental disorders, with adjusted odds ratios in therange of 2 to 3 for different mental disorders. Age is associated withthe prevalence of mood, anxiety, and somatoform disorders.People in their 40s have the highest odds of having mood orsomatoform disorders, while patients in their 30s have the highestodds of having anxiety disorders. There is a dose-responserelationship between level of education and prevalence of mood,somatoform and one or more mental disorders. When comparedwith people with university level education, those with noeducation or only elementary school level show odds ratios withinthe range of 2 to 3.5 for these disorders. After adjusting for thesecharacteristics of individuals there was a statistically significantvariability between centres (P < 0.001) and differences in the oddsof prevalence were relevant, being two times higher or lower thanthe overall average for several centres (Table 3).

People with mental disorders show worse quality of life scoresthan the general population (reference mean value = 50, S.D. = 10)(Table 4). This occurs in all health dimensions and in both physicaland mental component summary scores, although it is in themental component in which this reduction in quality of life is moreevident. Individuals with one or more mental disorders in theprevious 12-month have a mental component summary score of42.4 (95% CI, 41.1–43.7), those with a mood disorder a score of37.17 (95% CI, 35.33–39.01), with an anxiety disorder 42.11 (95%CI, 40.26–43.96) and with a somatoform disorder 41.98 (95% CI,39.19–44.77).

Please cite this article in press as: Grandes G, et al. The burden ofdoi:10.1016/j.eurpsy.2010.11.002

The summary SF-6D utility index is more than 10% lower forpeople with mental disorders than for those without (Table 5). Themean utility varied from 0.66 for patients with any mood disorderto 0.74 for alcohol use disorders. Mood disorders had the greatestimpact on utility, with a negative effect of �0.11 points, onceadjusted for the comorbidity shown in Fig. 1 and socio-demographic characteristics associated with the presence of thecondition. The annual loss in QALYs without considering mortalityassociated to any mental disorder per 100,000 primary carepatients was 1831 (95% credibility interval: 1547–2128). Mooddisorders were associated with the greatest annual QALY lossexcluding mortality, followed by anxiety, somatoform, and alcoholuse disorders (1124, 488, 244 and 38, respectively) (Table 5).

4. Discussion

This study confirms the high prevalence of mental disordersamong primary care attendees, specifically a one-year prevalenceof 23%. Mood and anxiety disorders are the most common, withone-year prevalences of 10% and 9%, respectively. These figures areclose to the average values previously reported by the WHO’stranscultural study performed in the primary care populations of14 different countries using the same diagnostic instrument: theCIDI. It is found that around 24% of all the patients had a mentaldisorder, ranging from 7% in China to 52% in Chile; overall 10% haddepression, ranging from 3% in Japan to 29% in Chile, andapproximately 8% had anxiety, ranging from 1% in Turkey to23% in Brazil [18].

The prevalences estimated in our study are higher than those ofthe general population for depressive disorder but consistent withthe results for other disorders obtained in studies with generalpopulation samples and using the CIDI as diagnostic instrument[17,19,27]. It is important to highlight that the population

mental disorders in primary care. European Psychiatry (2011),

Table 3Factors associated with the presence of mental disorders in the last 12 months and between-centre variability.

Mood disordersa,b Anxiety disordersa Somatoform disordersa,b One or more disorders

AOR 95% CI AOR 95% CI AOR 95% CI AOR 95% CI

Fixed effects at individual level

Gender

Female 2.73 (1.95–3.75) 2.39 (1.73–3.31) 2.34 (1.43–3.82) 2.23 (1.81–2.75)

Male 1.00 1.00 1.00 1.00

Age

18 0.89 (0.38–2.08) 2.39 (1.17–4.86) 1.92 (0.55–6.69)

25 1.24 (0.64–2.40) 2.98 (1.68–5.26) 2.78 (1.02–7.52)

35 1.71 (0.98–3.00) 3.49 (2.03–5.98) 3.78 (1.55–9.18)

45 1.97 (1.15–3.38) 3.38 (1.94–5.90) 3.98 (1.67–9.47)

55 1.88 (1.17–3.02) 2.72 (1.65–4.46) 3.24 (1.52–6.91)

65 1.50 (1.11–2.03) 1.81 (1.32–2.48) 2.05 (1.27–3.30)

75 1.00 1.00 1.00

Level of education

None or elementary school 1.93 (1.13–3.30) 3.42 (1.56–7.52) 1.99 (1.48–2.67)

Middle or high school 1.71 (1.10–2.67) 1.88 (0.97–3.67) 1.40 (1.05–1.86)

University 1.00 1.00 1.00

Random effects at centre level

Centre – Empirical Bayes estimators

Algorta 1.34 (0.87–2.06) 1.98 (1.16–3.39) 2.47 (1.19–5.14) 1.75 (1.11–2.75)

Basauri - Ariz 0.77 (0.50–1.19) 1.09 (0.63–1.89) 2.07 (1.02–4.20) 1.27 (0.82–1.97)

Cerdanyola del Valles 0.77 (0.46–1.30) 0.70 (0.35–1.40) 0.49 (0.17–1.37) 0.42 (0.24–0.74)

Cuenca 0.49 (0.30–0.80) 0.56 (0.30–1.04) 1.10 (0.50–2.43) 0.63 (0.39–1.02)

Galdakao 1.30 (0.88–1.94) 0.75 (0.43–1.31) 0.25 (0.09–0.65) 0.87 (0.56–1.37)

Salamanca 1.26 (0.81–1.95) 0.98 (0.54–1.78) 1.61 (0.74–3.50) 1.19 (0.74–1.89)

Valladolid 1.38 (0.88–2.17) 2.91 (1.68–5.02) 1.12 (0.48–2.60) 2.12 (1.34–3.33)

Vigo 1.12 (0.69–1.82) 0.55 (0.27–1.11) 0.83 (0.33–2.09) 0.77 (0.46–1.29)

Overall population 1.00 1.00 1.00 1.00

s2 (s.e.) P-valuec s2 (s.e.) P-valuec s2 (s.e.) P-valuec s2 (s.e.) P-valuec

Between centre variability (logit scale) 0.17 (0.12) <0.001 0.41 (0.25) <0.001 0.70 (0.48) <0.001 0.31 (0.19) <0.001

n = 2539; AOR: adjusted odds ratio.a n = 2420 (excluding those participants with dementia).b Adjusted by social class due to partial confounding.c Hypothesis test for between centre variability

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attending Spanish public primary care centres is very similar to thegeneral population as the Spanish health service providesuniversal coverage with free access to publicly funded healthcare. As a consequence, primary care services in Spain are readilyaccessible and have a very high rate of use by the population.

By contrast, our estimates are slightly below those recentlyreported for major depression in the Spanish primary carepopulation by King et al. using the CIDI [10]. They found an 18%six-month prevalence of major depression for Spanish women, 11%for men, and 14% for women and 8% for men for the wholepopulation of the six European countries participating in the study,while our estimates are 13% for women and 5% for men. As the

Table 4SF-36 norm-based scores and SF-36 summaries of people with and without mental dis

No mental disorders,

n = 1961a,b

Mood disorders,

n = 241a,b

Mean 95% CI Mean 95% CI

Physical functioning 51.28 (51.00–51.57) 47.75 (46.67–48.84)

Role – physical 51.05 (50.64–51.46) 45.57 (43.94–47.20)

Bodily pain 47.88 (47.46–48.31) 42.17 (40.80–43.55)

General health 50.41 (50.01–50.81) 43.94 (42.54–45.34)

Vitality 50.04 (49.62–50.46) 41.09 (39.75–42.44)

Social functioning 50.84 (50.43–51.24) 39.56 (37.62–41.51)

Role – emotional 51.12 (50.73–51.51) 39.16 (37.14–41.17)

Mental health 51.36 (50.96–51.76) 39.57 (38.15–40.98)

Physical component summary 49.84 (49.49–50.18) 47.77 (46.47–49.07)

Mental component summary 51.23 (50.83–51.63) 37.17 (35.33–39.01)

a Excluding those participants with dementia.b Missing values range from 10.7 to 20.8%

Please cite this article in press as: Grandes G, et al. The burden ofdoi:10.1016/j.eurpsy.2010.11.002

objective of that study was to develop a risk algorithm for the onsetof major depression, it is possible that they tended to recruit ahigh-risk population. In fact, two thirds of their Spanishparticipants were women and had no or only primary education,known risk factors for depression, and the cumulative 12-monthincidence of major depression was almost two times greater thanthe incidence in the other five European countries [28]. Our resultsare also considerably lower than those reported for the Spanishprimary care population by Roca et al. and by Baca Baldomero et al[11,29]. In both studies, 53% of the sample presented mentaldisorders diagnosed by general practitioners with the PRIME-MD,an instrument specifically designed for the detection of mental

orders in the previous 12 months.

Anxiety disorders,

n = 221a,b

Somatoform disorders,

n = 103a,b

One or more disor-

ders, n = 459a,b

Mean 95% CI Mean 95% CI Mean 95% CI

49.90 (48.81–51.00) 48.13 (46.49–49.77) 49.13 (48.39–49.87)

47.18 (45.63–48.72) 47.20 (44.82–49.58) 47.44 (46.36–48.51)

43.46 (42.10–44.81) 41.56 (39.43–43.69) 43.53 (42.56–44.49)

46.68 (45.28–48.08) 44.60 (42.32–46.89) 46.10 (45.12–47.09)

44.52 (43.06–45.99) 42.78 (40.28–45.28) 44.15 (43.13–45.18)

42.77 (40.86–44.67) 43.27 (39.98–46.55) 43.66 (42.34–44.98)

43.61 (41.70–45.53) 43.21 (40.24–46.17) 43.90 (42.55–45.24)

44.07 (42.59–45.54) 43.14 (40.86–45.42) 43.64 (42.59–44.68)

48.56 (47.32–49.80) 46.81 (45.16–48.47) 48.17 (47.31–49.03)

42.11 (40.26–43.96) 41.98 (39.19–44.77) 42.40 (41.11–43.68)

mental disorders in primary care. European Psychiatry (2011),

Lifetime prevalence

Twelve-month prevalence

Mood Disorders

Anxietydisorders

Somatoform disorders

13.22%

6.20%

2.81%

6.24%

1.86%

1.03%

1.90%

Mood Disorders

Anxietydisorders

Somatoform disorders

6.36%

5.32%

2.31%

2.27%

0.70%

0.62%

0.62%

Fig. 1. Lifetime and 12-month psychiatric comorbidity in primary care patients.

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disorders in primary care [30]. Such a great disparity with all theaforementioned studies is possibly due to the low specificity of theSpanish version of the PRIME-MD (66%) [31], and to differencesbetween study populations. Further, a recent meta-analysissuggests that general practitioners may overdiagnose commonmental disorders such as depression [32].

Estimation of the true burden that psychiatric disorders placeon health related quality of life is essential for setting priorities and

Table 5Annual losses in quality-adjusted life-years (QALYs) without considering mortality ass

Mean SF-6D utility index

(95% CI), n = 1961a

Adjusted effect of men

disorders on utility (95

No mental disorder 0.8114 (0.8058–0.8171)

Diagnosis groups

Mood disorders 0.6617 (0.6429–0.6805) �0.1128 (�0.1303–�0.

Anxiety disorders 0.7125 (0.6924–0.7325) �0.0534 (�0.0712–�0.

Alcohol use disorders 0.7362 (0.6393–0.8332) �0.0583 (�0.1142–�0.

Somatoform disorders 0.6973 (0.6675–0.7271) �0.0574 (�0.0822–�0.

Any mental disorder 0.7100 (0.6961–0.7240) �0.0966 (�0.1097–�0.

a Excluding those participants with dementia.

Please cite this article in press as: Grandes G, et al. The burden ofdoi:10.1016/j.eurpsy.2010.11.002

rationally assigning healthcare resources. Our data describe aremarkable impact of mental disorders on quality of life, which isconsistent with previous studies showing that psychiatric dis-orders have a significant negative effect on health even strongerthan that of other common chronic conditions such as diabetes,arthritis, heart or lung disease [27,33–35]. In accordance withprevious studies that have measured the decrease in quality of lifeassociated with mental disorders, mood disorders had the worstimpact on utility [26,36]. The utility estimated for mood disordersin our study (0.64–0.68) is in line with reported utilities fordepression derived from the same instrument used in our study,the SF-36, which varied from 0.55 to 0.63 for moderate depressionand 0.64–0.73 for mild depression to 0.72–0.83 for people onmaintenance antidepressant therapy [37]. The impact of psychiat-ric conditions on health related quality of life in our study wasclearly worse than that of other somatic conditions, reported inprevious studies with similar primary care populations and usingthe same utility index [36]. Fernandez et al. estimated 353 QALYslost annually without considering mortality per 100,000 primarycare attendees associated with cardiovascular diseases, 250 withdiabetes and 641 with high blood pressure, all lower than the QALYlosses, also excluding mortality, associated with mood disorders inour data [36]. Years lost due to disability (YLD) estimates for WHOEuropean region ‘‘A’’ in 14- to 79-year-old population arecomparable to the variable our study has investigated (QALYlosses without considering mortality) [3]. The figures in the WHOdata for malignant neoplasms (243 YLD per 100,000), cardiovas-cular diseases (427 YLD per 100,000), diabetes (247 YLD per100,000), and respiratory diseases (518 YLD per 100,000) are lowerthan those estimated for unipolar depressive disorders, also in theWHO data, (1085 YLD per 100,000) and for mood disorders in ourstudy (1124 QALYs lost per 100,000 excluding mortality).

With regard to age, gender, and education, our findings of apeak prevalence in the 30s and 40s, more than twice as high inwomen as in men (except for alcohol use disorders), and in peoplewith a low educational level, are in keeping with previouslongitudinal studies [28].

4.1. Limitations

Apart from the cross-sectional design, that precludes any causalconclusion, the main limitation of this study is the possibleselection bias that could have led to a tendency to underestimatethe prevalence of mental disorders. The group of individualsexcluded from the original clinical trial, due to cardiovascular orother severe diseases, and those not attending the interview mostlikely includes a high proportion of individuals with mentaldisorders. Accordingly, participants do not closely represent theoverall primary care population but rather a healthier subgroup inwhich prevalence of mental disorders may be lower. Additionally,it is not unlikely that the observed impact of mental disorders on

ociated with mental disorders per 100,000 primary care patients.

tal

% CI)

12-month prevalence of mental

disorders (95% CI), n = 1961a

Annual loss of QALYs

without considering mortality

(95% credibility interval)

0954) 10.0% (8.8%–11.1%) 1124.0 (911.6–1351.0)

0356) 9.1% (8.0%–10.3%) 487.8 (319.2–666.0)

0023) 0.7% (0.3%–1.0%) 38.5 (1.4–86.2)

0326) 4.3% (3.5%–4.6%) 244.3 (133.9–365.0)

0834) 19.0% (17.4%–20.5%) 1831.0 (1547.0–2128.0)

mental disorders in primary care. European Psychiatry (2011),

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quality of life also underestimates the true level due to the four-week time frame of the SF-36. Many episodes of mental disorder inthe previous 12 months may have gone into remission earlier thanthe recall period to which the questionnaire refers. This leads us toconsider our results as conservative estimates of the actualprevalence and burden of mental disorders in primary care, whichmay well be even higher than our data reflects.

4.2. Conclusions

Our results describe the high burden of disease associated withmental disorders in primary care and one of the most relevantfindings is the significant variability in their prevalence across theparticipating centres in Spain, i.e., within the same country andhealth system, once socio-demographic differences have beentaken into account. This is in contrast with previous studies carriedout in other countries showing a lack of significant area-levelvariance [38]. It is unlikely that the variability found in our studybe due to differences between centre measurement procedures, aswe used a validated standardized diagnostic instrument applied inexactly the same conditions by nurses receiving the same commonand centralized intensive training and quality control. Between-country variability has been reported previously [10,17–19], andthe within-country variability described in this study indicates theneed for valid mental health epidemiological statistics at smallarea level, which reflect genuine variations in morbidity, to informplanning decisions and help in the process of clinical detection ofmental disorders in primary care. Mood disorders are responsiblefor a large proportion of QALYs lost without considering mortalityamong primary care patients and this justifies new priorities,strategies, and greater efforts to improve the detection and care ofpeople with these disorders.

Conflict of interest statement

None.

Funding

The project was supported by the Carlos III Health Institute ofthe Spanish Ministry of Health, and co-financed by ERDF funding ofthe European Union (FIS PI051934, RETICS G03/170 and RD06/0018/0018), and by the Health Department of the BasqueGovernment. The authors are totally independent of the sponsors,and have full responsibility for the implementation of the studyand the publication.

Acknowledgements

The authors would like to thank all patients, collaboratingnurses, and family physicians; and John Brazier, PhD, Professorof Health Economics, University of Sheffield, for the provisionof the algorithm to calculate the utility index based on the SF-36questionnaire.

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