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From Counting to Understanding: The Evolving Epidemiologic Approach to Dementia

Ian McDowell, PhD

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In Review
More Than the Epidemiology of Alzheimer’s Disease: Contributions of the Canadian Study of Health and Aging

Joan Lindsay, Elizabeth Sykes, Ian McDowell, René Verreault, Danielle Laurin

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Alzheimer’s Disease, Genes, and Environment: The Value of International Studies
Hugh C Hendrie, Kathleen S Hall, Adesola Ogunniyi, Sujuan Gao

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Original Research
Hidden Cardiac Lesions and Psychotropic Drugs as a Possible Cause of Sudden Death in Psychiatric Patients: A Report of 14 Cases and Review of the Literature

Dominique Frassati, Alain Tabib, Bernard Lachaux, Natalie Giloux, Jean Daléry, François Vittori, Dorothée Charvet, Cécile Barel, Bernard Bui-Xuan, Rachel Mégard, Louis Pierre Jenoudet, Jacques Descotes, Thierry Vial, Quadiri Timour

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The 5-Factor Model of Personality and Antidepressant Medication Compliance
Nicole L Cohen, Erin C Ross, R Michael Bagby, Peter Farvolden, Sidney H Kennedy

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Social, Demographic, and Clinical Factors Related to Disruptive Behaviour in Hospital
Andrea K Boggild, Marnin J Heisel, Paul S Links

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The Course of Depressive Illness in General Practice
Frédéric Limosin, PhD, Jean-Yves Loze, Myriam Zylberman-Bouhassira, Mark E Schmidt, Eléna Perrin, Frédéric Rouillon

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Review Paper
Prevalence and Incidence Studies of Mood Disorders: A Systematic Review of the Literature

Paul Waraich, Elliot M Goldner, Julian M Somers, Lorena Hsu

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Brief Communication
Bupropion Sustained Release Treatment Reduces Fatigue in Cancer Patients

Jodi L Cullum, Agnieszka E Wojciechowski, Guy Pelletier, J Steven A Simpson

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Patient Factors Associated With Missed Appointments in Persons With Schizophrenia
Shalom Coodin, Douglas Staley, Barb Cortens, Rob Desrochers, Sandy McLandress

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Book Reviews
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The Treatment of Anxiety Disorders: Clinical Guides and Patient Manuals. 2nd ed Reviewed by
Richard Swinson, MD


Cognitive-Behavioral Group Therapy for Social Phobia: Basic Mechanisms and Clinical Strategies
Reviewed by
Michael Van Ameringen, MD, FRCPC


Letters to the Editor
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Aripirazole–Olanzapine Combination for Treatment of Schizophrenia

Improvement of Torticollis With Quetiapine in a Schizophrenia Patient

Internalizing Antecedents of Conduct Disorder

Travel Time and the Use of Psychiatric Outpatient Clinic Services in Coastal Northern Norway

Respiratory Panic Disorder Treatment With Clonidine

Review Paper

Prevalence and Incidence Studies of Mood Disorders: A Systematic Review of the Literature

Paul Waraich, MHSc, MD1, Elliot M Goldner, MHSc, MD2, Julian M Somers, MSc, PhD1, Lorena Hsu, MSc3

 

This is the second in a series of papers that present systematic reviews of the prevalence and incidence of psychiatric disorders drawn from
studies published in English literature in the years 1980 to 2000. The series discusses the implications of these epidemiologic findings to mental health policy and practice. 

Objective: To present the results of a systematic review of literature published between January 1, 1980, and December 31, 2000, that reports findings on the prevalence and incidence of mood disorders in both general population and primary care settings.

Method: We conducted a literature search of epidemiologic studies of mood disorders, using Medline and HealthSTAR databases and canvassing English-language publications. Eligible publications were restricted to studies that examined subjects aged at least 15 years and over. We used a set of predetermined inclusion and exclusion criteria to identify relevant studies. We extracted and analyzed prevalence and incidence data for heterogeneity. 

Results: Of general population studies, a total of 18 prevalence and 5 incidence studies met eligibility criteria. We found heterogeneity across 1-year and lifetime prevalence of major depressive disorder (MDD), dysthymic disorder, and bipolar I disorder. The corresponding pooled rates for 1-year prevalence were 4.1 per 100, 2.0 per 100, and 0.72 per 100, respectively. For lifetime prevalence, the corresponding pooled rates were 6.7 per 100, 3.6 per 100, and 0.8 per 100, respectively. Significant variation was observed among 1-year incidence rates of MDD, with a corresponding pooled rate of 2.9 per 100. 

Conclusions: The prevalence of mood disorders reported in high-quality studies is generally lower than rates commonly reported in the general psychiatric literature. When controlled for common methodological confounds, variation in prevalence rates persists across studies and deserves continued study. Methodological variation among studies that have examined the prevalence of depression in primary health care services is so large that comparative analyses cannot be achieved. 

(Can J Psychiatry 2004;49:124–138) 

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Clinical Implications

  • If health planners, clinicians, and researchers have been using commonly reported prevalence rates to estimate the burden of disease as a result of mood disorders, they may need to revise these estimates downward. 

  • The prevalence of depression in primary care should be reexamined with standardized methodologies.

  • The persistent variation in the incidence and prevalence of mood disorders warrants further investigation. 

Limitations

  • The best-estimate rates reported in this study should not be reported without their confidence intervals, because significant heterogeneity exists among studies.

  • This study reviews English-only reports between 1980 and 2000 and may have missed some high-quality studies.

  • The preliminary analysis of variation in rates presented in this study should be seen as hypothesis-generating. Further analysis must be cautious of ecological fallacy.


Key Words
: mood disorders, major depression, dysthymia, bipolar disorders, prevalence, incidence, systematic review

Résumé :Études de la prévalence et de l’incidence des troubles de l’humeur : un examen méthodique de la documentation

The diagnostic category of mood disorders is among the most prevalent of all mental health diagnoses (1–3). (For a definition of prevalence and incidence, refer to Goldner and colleagues; 4). Conducting a review of this category of mental disorders is challenging for several reasons. One challenge is that the various conditions that comprise this grouping of disorders can be quite disparate: some are transient, others are chronic or recurrent. Therefore, it is difficult to speak in generalities about the characteristics of mood disorders. Although most mood disorders result in some degree of temporary cognitive difficulty and mild deficits in attention or concentration, some forms of mood disorders are associated with profound cognitive and perceptual disturbance with delusional and hallucinatory features. Another set of challenges to reviewing the epidemiology of mood disorders involves the nosological frameworks and systems of psychiatric nomenclature currently in use (5,6). Mood disorders are constructs (that is, entities that cannot be directly measured or observed) developed through inference, hypothesis, deduction, and conjecture (1). Although mood disorders are described as taxonic (that is, defined in categorical terms) in current diagnostic nosological systems, some of their features may be more usefully conceptualized in dimensional terms (7). Given the uncertainties of our diagnostic constructs for mood disorders, previous reviews unsurprisingly report highly variable rates for all mood disorders (3,8–12) (Table 1). In addition, individuals may alternate between various mood disorders during their lifetime (13), making it difficult to determine the onset and cessation of disease episodes.

Table 1  Variation of rates of mood disorders in selected review studies

Disorder 

Review study 

Prevalence rate (per 100) 

Incidence 

 

 

Point 

1-year 

Lifetime 

 

Depression 

Bland (3) 

— 

0.6 to 7.0 

0.9 to 16.1 

— 

 

Wittchen and others (8) 

1.5 to 4.0 

2.6 to 9.8 

4.4 to 18 

— 

 

Boyd and Weissman (9) 

— 

— 

— 

104 to 519 per 100 000 

Depression in primary care 

Lemelin and others (10) 

l Self-report 

l Interview-        based 

 

4.8 to 8.6 

9.0 to 30.0 

 

— 

— 

 

— 

— 

 

— 

— 

Dysthymia 

Wittchen and others (8) 

1.2 to 3.9 

2.3 to 4.6 

3.1 to 3.9 

— 

 

Bland (3) 

— 

— 

4.1 to 8.6 

— 

Bipolar I disorder 

Wittchen and others (8) 

0.1 to 2.3 

1.0 to 1.7 

0.6 to 3.3 

— 

 

Weissman and others (11) 

— 

0.3 to 1.5 

— 

 

Bebbington and Ramana (12) 

— 

— 

2.6 to 20.8 per 100 000 yearly 


This review addresses some of the challenges described above by presenting the results of a systematic review of literature published between January 1, 1980, and December 31, 2000, that reports findings of the prevalence and incidence of mood disorders in both general population and primary care settings. We examine the variability of the rates of disorders across studies and attempt to determine how much of this variance can be accounted for by various factors, using hetero- geneity analysis. This technique should decrease the variance associated with heterogeneous study methods and diagnostic constructs and subsequently provide a more robust estimate of the variation in rates of disorders.

We focus our discussion on the mood disorders that have been most extensively examined in epidemiologic studies: major depressive disorder (MDD), dysthymia, and bipolar I disorder (BD I). MDD has been found to be one of the most prevalent mood disorders in previous reviews (Table 1). It is important not only because of its prevalence but also because of its associated disability. The Global Burden of Disease study found that the disability associated with MDD is surpassed only by that associated with ischemic heart disease in industrialized countries (14). Previous reports have also highlighted recent trends toward an increasing prevalence of depression. This may mean that depression will be even more of a burden on society in future years (14,15). We selected the epidemiology of MDD in primary care as an additional topic of interest for this review. Several jurisdictions are currently attempting to address care gaps in the management of depression in primary care, such as the low detection rate by primary care physicians (16). Establishing robust estimates of the prevalence of depression in primary care will inform these policy initiatives.

Dysthymia is characterized by chronic low-grade depressive symptoms and can be particularly disabling when it is comorbid with other mood disorders, such as MDD. About 70% of those with dysthymia may eventually go on to develop MDD (13). Relative to other mood disorders, research on the epidemiology of dysthymia has been scarce (3); however, several recent studies have examined this disorder in more detail (17–19). BD I, also known as manic-depressive disorder, may be the most disabling of mood disorders (14). About 10% of people with MDD eventually develop BD, which makes studying the epidemiology of this disorder difficult (13).

Methods

The methods employed in this review have been presented in more detail elsewhere (4). We searched the Medline and HealthSTAR databases for relevant studies, using the key indexing terms epidemiology, prevalence, and incidence, combined with the search terms mental disorders, mood disorders, depressive disorders, major depression, dysthymia, and bipolar disorders. We limited the search to English-language studies published between January 1, 1980, and December 31, 2000. Reference lists of relevant primary and review articles identified were also searched.

General population prevalence and incidence studies were eligible for inclusion if they were community surveys using probability sampling techniques. For primary care studies, those that randomly or consecutively sampled a population of primary care attendees for a given period were included. Eligible publications were restricted to studies having sample sizes of 450 or over. We chose this number as the lower limit of sample size based on preliminary calculations (using the formula in Kelsey and colleagues; 20, p 282) that demonstrated adequate error rates for a range of expected prevalence rates. Studies were also eligible for inclusion if they examined age ranges covering the adult population. Only studies using operationalized diagnostic criteria and case identification based on either standardized instruments or clinician diagnosis were included. Prevalence data, including overall, sex-specific, and age-specific rates, were extracted from eligible studies.

We conducted qualitative analyses of variables related to methodology to summarize and elucidate any observed differences between rates. As well, we pooled each set of rates according to a Bayesian approach to metaanalysis, using the Fastpro software program. Readers interested in a more detailed discussion of this approach should refer to Eddy and colleagues (21). We analyzed each of the pooled rates for heterogeneity, using chi-square tests according to Fleiss’ method (22).

Results

Description of Studies
General Population Studies. From the citations and abstracts generated from the initial electronic search, we identified 38 prevalence and 12 incidence studies potentially meeting our inclusion criteria, in addition to 8 review papers. The full texts of these articles were retrieved. All reference lists of identified studies and reviews were searched, generating an additional 39 prevalence and 15 incidence studies, for which full-text articles were obtained.

Of the 77 prevalence studies for which full-text articles were reviewed, 42 studies were excluded: 30 studies did not meet eligibility criteria, and 12 presented duplicate data. Thus, 35 prevalence papers of mood disorders met eligibility criteria for the review (17–19,23–54); 18 unique primary investigations of prevalence were included. The reasons for excluding prevalence studies fulfilling all but 1 of the inclusion criteria are documented in Table 2 (55–66). Of the 27 incidence studies identified, 22 were excluded: 16 did not meet inclusion criteria, and 6 were based on duplicate data. Therefore, 5 general population incidence studies of mood disorders were included (17,44,46,67,68). Five of the excluded studies almost met inclusion criteria, and reasons for their exclusion are presented in Table 2 (61,69–72).

Table 2  Mood disorder studies excluded at article review stage 

Study reference 

Reason for exclusion 

Comments 

General population studies 

 

 

Prevalence studies 

 

 

Mumford and others (66) 

Does not report prevalence rates 

Rates cannot be determined from data presented 

Angst (55) 

Does not meet age criteria 

Assesses age range of 22 to 35 years 

Takeuchi and others (57) 

Population too specific 

Looks at population of Chinese Americans  

Angst and Merikangas (56) 

Does not meet age criteria 

Only looks at ages 18 to 19 years 

Angst (58) 

Does not meet age criteria 

Prospective 10-year cohort study; presents rates applicable to age 20 to 30 years  

Rumble and others (59) 

Diagnoses based on ICD-8 criteria 

Community sample 

Fournier and Kovess (64) 

Not clear whether operationalized criteria used 

Comparison of mail and telephone surveys 

Stefansson and others (63) 

Does not include entire adult age group 

Presents rates applicable to age 55 to 57 years 

Surtees and Sashidharan (60) 

Limited to population of women 

Comparison of 2 community samples 

Dilling and Weyerer (62) 

Uses ICD-8 diagnostic criteria 

Community sample 

Halldin (65) 

Uses ICD-8 diagnostic criteria 

Community sample 

Shen and others (61) 

Diagnostic criteria used unclear 

Large community sample 

Incidence studies 

 

 

Murphy and others  (69) 

Does not use operationalized criteria 

Follow-up of cohort from 1970 to 1992 

Eaton and others (70) 

Based on duplicate data 

Looks at Baltimore site of ECA study with 12-year follow-up   

Horwath and others (71) 

Based on duplicate data 

Looks at 4 sites of ECA study with 1-year follow-up 

Rorsman and others  (72) 

Does not use operationalized criteria 

Study carried out between 1957 and 1972 

Shen and others (61) 

Diagnostic criteria used unclear 

Large community sample 

Primary care studies 

 

 

Prevalence studies 

 

 

Zinbarg and others (89) 

Inadequate sample size 

Examines both primary care and outpatient psychiatry populations 

Barrett and others (83) 

Does not use operationalized criteria 

Presents rates based on screening scales 

Kessler and others (84) 

Rates not representative of primary care population 

Denominator used in rate is total household population 

Schulberg and others (85) 

Rate may not be representative 

Overall response rate < 50% 

Parker and others (85) 

Rate may not be representative 

1st-stage response rate not assessed; very low 2nd-stage response rate 

Zung and others (87) 

Does not use operationalized criteria 

Presents rates based on screening scales 

Nielsen and Williams (88) 

Diagnoses based on Feighner (1972) criteria 

Data collected in 1971 

Primary Care Studies. For MDD in primary care, 9 prevalence and 2 incidence studies as well as 4 review papers were identified and retrieved. An additional 34 prevalence studies and 1 incidence study resulted from the reference lists of identified articles. Of the 43 prevalence studies identified, 33 were excluded as they did not fulfill inclusion criteria. Thus, 10 primary care prevalence studies met eligibility criteria for the review (73–82). Excluded studies almost meeting eligibility criteria are presented in Table 2 (83–89). Of the 3 incidence studies identified, 2 met eligibility criteria (90,91).

Prevalence Studies. We present findings for the 24 papers reporting overall or sex-specific 1-year and lifetime prevalence rates and age-specific lifetime prevalence rates for mood disorders in general, for MDD, for dysthymic disorder, and for BD I (Table 3 to 5, Figure 1). The results of 2 studies reporting only 1-year age-specific rates are not reported here (35,44). The results of studies reporting only data for point prevalence or 6-month prevalence (23,30,38–40,45,46) or for mood disorder categories other than those stated above (23,42,92) are also not presented.

Table 3  One-year prevalence rates of mood disorders 

Study authors 

Study site 

Total number of subjects (n) 

Response rate
(%) 

Case-finding method 

Prevalence rate (per 100 persons) 

 

 

 

 

 

Any mood disorder 

Major depressive disorder 

Dysthymic disorder 

Bipolar I disorder 

Henderson and others (32) 

Australia - national 

10 600 

78.0 

Census; CIDI-A/ICD-10; lay interviewers 

 

5.1 

1.1 

 

Bijl and others (18) 

Netherlands - national 

7146 

69.7 

Census; CIDI/DSM-III-R; lay interviewers; algorithm diagnosis 

7.6 

5.8 

2.3 

1.1 

Pakriev and others (17) 

Udmurt Republic - region of Udmurtia (rural areas) 

855 

85.9 

Census; CIDI/ICD-10 & DSM-III-R; diagnosis made by clinician 

 

22.5c 

15.4b 

4.1c 

2.6b 

0.1c 

0.2b 

Szadoczky and others (17) 

Hungary - national 

2953 

85.0 

Census (GP lists for 5 different areas); DIS/DSM-III-R; lay interviewers; algorithm diagnosis 

 

7.1 

 

0.9 

Offord and others (19) 

Canada - province of Ontario 

8116 

76.5 

Census; UM-CIDI/DSM-III-R; lay interviewers; algorithm diagnosis 

4.5 

4.1 

0.8 

0.6 

Kessler and others (36) 

USA (NCS) - national 

8098 

82.4 

Census; UM-CIDI/DSM-III-R; lay interviewers; algorithm diagnosis 

11.3 

10.3 

2.5 

1.3 

Bourdon and others (26) 

USA (ECA) - 5 sites, mainly urban 

20291 

68 to 80 

Census; DIS/DSM-III; lay interviewers; algorithm diagnosis 

6.3 

3.5 

3.3 

0.6 

Faravelli and others (54) 

Italy - 3 local health units of Florence 

1000 

100.0 

Census (GP lists for 3 local health units); structured interview including items from SADS-L; DSM-III & DSM-III-R; interviews by GPs 

 

— 

6.3a 

6.2b 

3.0a 

2.6b 

1.3a 

1.5b 

Oakley-
Browne and others (43) 

New Zealand - area of Christchurch, mostly urban 

1498 

70.0 

Census; DIS/DSM-III; lay interviewers; algorithm diagnosis 

10.4 

6.7 

 

0.2 

Hwu and others (34) 

Taiwan - 

metropolitan 

Taipei 

small towns 

rural villages 

11 004 

5 005 

— 

3 004 

2 995 

95.0 

— 

— 

— 

— 

Census; DIS-CM/DSM-III; lay interviewers; method of diagnosis unclear 

 

— 

0.64 

— 

1.1 

0.81 

 

— 

— 

— 

— 

— 

1.2 

— 

0.3 

1.0 

Bland and others (24) 

Canada - metropolitan Edmonton 

3 258 

71.6 

Census; DIS-DSM-III; lay interviewers; algorithm diagnosis 

6.8 

4.6 

 

0.2 

 

 

 

 

Best-estimate 

(95%CI) 

7.5 

(5.7 to 9.7) 

4.1 

(2.4 to 6.2) 

2.0 

(1.3 to 2.8) 

0.72 

(0.5 to 1.0) 

— = Not reported; aDSM-III criteria; bDSM-III-R criteria; cICD-10 criteria. 

CIDI-A = Composite International Diagnostic Interview ; CIDI/ICD = Composite International Diagnostic Interview/International Classification of Diseases;
DIS = Diagnostic Interview Schedule; DISCM =  Diagnostic Interview Schedule Chinese Modified; UM-CIDI = University of Michigan Composite International Diagnostic Interview. 


Because the diagnostic nomenclature for mood disorders has undergone revisions from DSM-III to DSM-IV criteria, it was necessary to make assumptions with respect to the classification of various terms in these studies to be in accordance with DSM-IV criteria. These terms, along with the DSM-IV categories to which they are assumed to be equivalent, are in Table 6.


Table 4  Lifetime prevalence rates of mood disorders 

Study authors 

Study site 

Total number of subjects (n

Response rate
(%) 

Case-finding method 

Prevalence rate (per 100 persons) 

         

Any mood disorder 

Major depressive disorder 

Dysthymic disorder 

Bipolar I disorder 

Murphy and others  (42) 

Atlantic Canada - region of Stirling County 

1 396 

86.0 

Census; DIS/DSM-III; lay interviewers; method of diagnosis unclear 

— 

7.9 

— 

— 

Bijl and others (18) 

Netherlands - national 

7 146 

69.7 

Census; CIDI/DSM-III-R; lay interviewers; algorithm diagnosis 

19.0 

15.4 

6.3 

1.8 

Szadoczky and others  (48) 

Hungary - national 

2 953 

85.0 

Census (GP lists for 5 different areas); DIS/DSM-III-R; lay interviewers; algorithm diagnosis 

24.2 

15.1 

4.5 

1.5 

Fournier and others  (31) 

Canada - Montreal 

893 

63.6 

Telephone survey; CIDIS/DSM-III-R; lay interviewers; algorithm diagnosis 

31.4 

29.6 

14.0 

— 

Carta and others  (28) 

Italy - Cagliari and Scano Montiferro   

480 

87.0 

Census; CIDI/DSM-III-R; physician interviewers 

— 

13.3 

4.1 

 

— 

Kessler and others  (36) 

USA (NCS) - national 

8 098 

82.4 

Census; UM-CIDI/DSM-III-R; lay interviewers; algorithm diagnosis 

19.3 

17.1 

6.4 

1.6 

Chen and others (29) 

Hong Kong - national 

7 229 

77.8 

Census; DIS-III-CM/DSM-III; lay interviewers; algorithm diagnosis 

— 

1.9a 

2.0a 

0.15a 

Wacker and others  (49) 

Switzerland - city of Basel 

470 

52.2 

Census; CIDI/DSM-III-R & ICD-10; interviewers with training in psychiatry or psychology 

19.4b 

25.7c 

15.7b 

22.8c 

7.2b 

7.0c 

— 

Bourdon and others  (26) 

USA (ECA) - 5 sites, mainly urban 

20 291 

68-80 

Census; DIS/DSM-III; lay interviewers; algorithm diagnosis 

8.3 

5.9 

3.3 

0.8 

Wittchen and others  (53) 

Germany - former West Germany 

483 

73.5 

Census; DIS/DSM-III; clinical interview and diagnosis 

12.9 

9.0 

4.0 

0.24 

Oakley-Browne and others (43) 

New Zealand - area of Christchurch, mostly urban 

1 498 

70.0 

Census; DIS/DSM-III; lay interviewers; algorithm diagnosis 

14.7 

12.6 

6.4 

0.7 

Hwu and others  (34) 

Taiwan 

  Metropolitan 

  Taipei 

  Small towns 

  Rural villages 

11 004 

5 005 

 

3 004 

2 995 

95.0 

Census; DIS-CM/DSM-III; lay interviewers; method of diagnosis unclear 

— 

— 

— 

— 

— 

— 

0.88 

— 

1.7 

0.97 

— 

0.92 

— 

1.5 

0.94 

— 

1.6 

— 

0.7 

1.0 

Bland and others (93) 

Canada - metropolitan Edmonton 

3 258 

71.6 

Census; DIS/DSM-III; lay interviewers; algorithm diagnosis 

10.2 

8.6 

3.7 

0.6 

Lee and others  (37) 

Korea - Dong, Seoul (urban) and Eub, Myeon (rural) 

5 100 

81.8 

Census; DIS/DSM-III; lay interviewers; algorithm diagnosis 

5.4 

3.4 

2.2 

0.42 

Canino and others (27) 

Puerto Rico - entire island nation 

1 513 

91 

Census; DIS/DSM-III; lay interviewers; algorithm diagnosis 

7.9 

4.6 

4.7 

0.5 

       

Best-estimate 

(95%CI) 

14.1 

(10.2 to 18.7) 

6.7 

(4.2 to 10.1) 

3.6 

(2.5 to 

5.0) 

0.82 

(0.56 to  1.1) 

aOverall rate calculated from raw data (only sex and age-specific rates reported); bDSM-III-R criteria; cICD-10 criteria; CIDI-S = CIDI simplified 


All the studies presented are community surveys using samples ranging in size from approximately 500 (49) to 20 000 (26) subjects. For each study, the percentage confidence interval (CI) width or error rate for estimated prevalence at a 95% confidence level may be calculated using the formula provided by Kelsey and colleagues (20, p 282). Most studies used either the Diagnostic Interview Schedule (DIS) or the Composite International Diagnostic Interview (CIDI) administered by trained lay interviewers and applied algorithms to derive diagnoses.


Table 5  Sex-specific 1-year and lifetime prevalence rates of mood disorders  

Study authors 

Study site 

Prevalence rate (per 100 persons) 

   

Any mood disorder 

Major depressive
disorder 

Dysthymic
disorder 

Bipolar I
disorder 

   

Male 

Female 

Male 

Female 

Male 

Female 

Male 

Female 

                   

1-year prevalence 

               

Henderson and others (32) 

Australia 

— 

— 

3.4 

6.8 

1.0 

1.3 

— 

— 

Bijl and others (18) 

Netherlands 

5.7 

9.7 

4.1 

7.5 

1.4 

3.2 

1.1 

1.1 

Pakriev and others (17) 

Udmurt Republic 

— 

— 

13.1 

29.6 

2.7 

5.1 

— 

— 

Szadoczky and others (48) 

Hungary 

— 

— 

4.7 

9.0 

— 

— 

1.0 

0.9 

Offord and others (19) 

Ontario, Canada 

3.2 

5.9 

2.8 

5.4 

a 

0.8 

a 

0.6 

Kessler and others  (36) 

USA (NCS) 

8.5 

14.1 

7.7 

12.9 

2.1 

3.0 

1.4 

1.3 

Faravelli and others (54) 

Florence, Italy 

— 

— 

3.5 

8.8 

2.2 

3.7 

0.7 

1.9 

Weissman and others  (51) 

USA (ECA) 

— 

— 

— 

— 

— 

— 

0.9 

1.1 

 

Best-estimate 

(95%CI) 

5.5 

(3.0 to 

 8.6) 

9.5 

(5.5 to 14.2) 

4.9 

(3.3 to 7.1) 

10.0 

(6.4 to 14.6) 

1.7 

(1.2 to  2.3) 

2.4 

(1.3 to 3.8) 

1.1 

(0.93 to 1.3) 

1.1 

(0.87 to 1.3) 

Lifetime prevalence 

               

Murphy and others (41) 

Stirling County, Canada 

— 

— 

4.4 

11.5 

— 

— 

— 

— 

Bijl and others (18) 

Netherlands 

13.6 

24.5 

10.9 

20.1 

3.8 

8.9 

1.5 

2.1 

Szadoczky and others (48) 

Hungary 

17.9 

29.2 

9.2 

19.7 

2.8 

5.8 

1.3 

1.6 

Carta and others (28) 

Cagliari and Scano Montiferro, Italy 

— 

— 

11.6 

14.8 

3.0 

5.2 

— 

— 

Kessler and others  (36) 

USA (NCS) 

14.7 

23.9 

12.7 

21.3 

4.8 

8.0 

1.6 

1.7 

Weissman and others (50) 

USA (ECA) 

— 

— 

3.5 

8.0 

2.6 

5.4 

0.8 

1.0 

Chen and others  (29) 

Hong Kong 

— 

— 

1.3 

2.4 

1.1 

2.8 

0.15 

0.16 

Wittchen and others (53) 

Former West Germany 

6.4 

18.7 

4.0 

13.6 

2.5 

5.4 

0.0 

0.49 

Wells and others (53) 

Christchurch, New Zealand 

10.0 

19.4 

8.8 

16.3 

3.8 

9.0 

0.5 

0.9 

Hwu and others (34) 

Taiwan 

  Taipei 

  Small towns 

  Rural villages 

— 

— 

— 

— 

— 

— 

— 

— 

— 

0.7 

1.0 

0.6 

— 

1.0 

2.5 

1.4 

— 

0.7 

1.4 

0.6 

 

— 

1.1 

1.6 

1.4 

— 

1.6 

1.2 

1.2 

— 

1.6 

0.0 

0.7 

Bland and others (93) 

Edmonton, Canada 

7.1 

13.2 

5.9 

11.4 

2.2 

5.2 

0.7 

0.4 

Lee and others (37) 

Korea 

  Seoul 

  Rural Korea 

 

4.3 

4.2 

 

6.6 

6.0 

 

2.4 

2.9 

 

4.1 

4.1 

 

1.8 

1.3 

 

3.0 

2.5 

 

0.56 

0.78 

 

0.26 

0.1 

Canino and others (27) 

Puerto Rico 

4.7 

10.9 

3.5 

5.5 

1.6 

7.6 

0.7 

0.4 

 

Best-estimate 

(95%CI) 

9.0 

(6.1 to 12.7) 

17.0 

(12.0 to 23.1) 

3.8 

(2.4 to 5.8) 

7.5 

(4.5 to  11.3) 

2.1 

(1.5 to 

2.8) 

4.3 

(3.0 to 5.9) 

0.96 

(0.68 to 1.3) 

0.78 

(0.45 to 1.2) 

—Not reported; aNumbers were too small to be reported 


Qualitative Analysis
ne-Year Prevalence. For mood disorders in general, 1-year prevalence rates ranged from 4.5 per 100 in Ontario (19) to 11.3 per 100 in the US National Comorbidity Study (NCS) (36), which is a variation of 2.5-fold (Table 3). While the methodological characteristics of each study were similar, the studies differed with respect to the use of either CIDI–DSM-III-R or DIS–DSM-III. For MDD, 1-year prevalence varied from 0.64 per 100 in Taipei (34) to 22.5 per 100 in the region of Udmurtia (a sovereign republic within the Russian Federation) (17), a difference of approximately 35-fold. The rate in the latter study was based on ICD-10 criteria; for consistency, we use DSM-III-R criteria (here, and in further analyses) to obtain a 1-year prevalence rate of 15.4 per 100, reducing the variation to 24-fold. For the study conducted in Udmurtia, diagnoses were made by clinicians; most other studies used lay interviewers and computer algorithms to derive diagnoses.


Figure 1  Age-specific lifetime prevalence rates of mood disorders 

Frame4.JPG - 0 Bytes

For dysthymic disorder, 1-year prevalence ranged from 0.8 per 100 in Ontario (19) to 3.3 per 100 in the US Epidemiologic Catchment Area (ECA) study (26), a variation of slightly more than 4-fold. For BD I, 1-year prevalence rates ranged from 0.2 per 100 in Udmurtia (17), New Zealand (43), and Edmonton (24) to 1.5 per 100 in Florence, Italy (54), for a difference of 7.5-fold. (42).

Table 6  DSM-IV mood disorder category equivalents for diagnostic terms used across studies 

Diagnostic term used 

DSM-IV category 

Depressive disorders 

Major depressive disorder and dysthymic disorder 

Major depressive episode 

Major depressive disorder 

Bipolar disorder (in studies using DSM-III or DSM-III-R) 

Bipolar I disorder (unless made explicit that it included both bipolar I and bipolar II disorder) 

Manic episode, mania 

Bipolar I disorder 

Bipolar disorder not otherwise specified (in studies using DSM-III or DSM-III-R) 

Bipolar II disorder 

For dysthymic disorder, 1-year prevalence ranged from 0.8 per 100 in Ontario (19) to 3.3 per 100 in the US Epidemiologic Catchment Area (ECA) study (26), a variation of slightly more than 4-fold. For BD I, 1-year prevalence rates ranged from 0.2 per 100 in Udmurtia (17), New Zealand (43), and Edmonton (24) to 1.5 per 100 in Florence, Italy (54), for a difference of 7.5-fold. (42).

Lifetime Prevalence. The lifetime prevalence rates for mood disorders in general ranged from 5.4 per 100 in Korea (37) to 31.4 per 100 in Montreal (31), for a 5.8-fold difference. Studies with high rates were based on DSM-III-R or ICD-10 criteria, and lower rates were associated with studies using DSM-III criteria. For MDD, lifetime prevalence varied from 0.88 per 100 in Taipei (34) to 29.6 per 100 in Montreal (31). This is a difference of more than 33-fold. Studies reporting the highest rates employed DSM-III-R criteria, while studies reporting lower rates used DSM-III criteria, with the lowest of rates being reported in Asian countries. With respect to dysthymic disorder, lifetime prevalence ranged from 0.92 per 100 in Taipei (34) to 14.0 per 100 in Montreal (31), a variation of approximately 15-fold. Again, Asian studies reported the lowest rates. Lifetime prevalence rates for BD I ranged from 0.15 per 100 in Hong Kong (29) to 1.8 per 100 in the Netherlands (18), which is a variation of 12-fold. Examination of the studies does not reveal any regional patterns or relevant methodological differences that may help to explain the variation in rates of BD I.

Sex-Specific Prevalence. Table 5 presents findings from studies reporting sex-specific 1-year and lifetime prevalence rates for mood disorders. For mood disorders (in general), 1-year and lifetime prevalence rates were consistently found to be between 1.5 and 2 times higher for women than for men. Studies reporting 1-year and lifetime sex-specific rates for MDD also consistently demonstrated rates for women that were approximately 1.5- to 2.5-fold higher than for men. For dysthymic disorder, 1-year and lifetime prevalence rates were again generally between 1.5 and 2.5 times higher for women than men, with the exception of 1 study that reported a lifetime prevalence for women to be almost 5 times that for men (27). There was less consistency observed for sex-specific rates of BD I. While most 1-year and lifetime rates for BD I were found to be very similar for men and women, some studies demonstrated higher rates for women (18,52,54) and some for men (27,34,93).

Age-Specific Lifetime Prevalence. Results from each study reporting age-specific lifetime prevalence rates for mood disorders are presented in Figure 1. As shown, lifetime prevalence rates for MDD and BD I disorder seem fairly stable through ages 18 to 64 years. Dysthymic disorder slightly increases in prevalence with increasing age.

Estimation and Heterogeneity Analysis of Pooled Best-Estimate Rates.
Mood Disorders in General. The best-estimate rates for 1-year and lifetime prevalence of total mood disorders were 7.5 per 100 (95%CI, 5.7 to 9.7) and 14.1 per 100 (95%CI, 10.2 to 18.7), respectively (Tables 3, 4). The CI variations for the 1-year and lifetime prevalence estimates are 1.7-fold and 1.8-fold, respectively, which are lower than the respective 2.5-fold and 5.8-fold variations observed across individual rates. Heterogeneity analysis of 1-year and lifetime prevalence rates revealed significant differences across each set of proportions. For lifetime prevalence, variables that may have contributed to heterogeneity are study publication year, diagnostic criteria, and diagnostic instruments used (Table 7). Studies that employed CIDI (DSM-III-R) or those published after 1992 had pooled lifetime rates that were approximately twice the rates for studies that used other diagnostic instruments and criteria or that were published prior to 1992.

Table 7  Pooled 1-year and lifetime prevalence rates of mood disorders according to variables which may be causing heterogeneity 

 
Prevalence rate (per 100) (95%CI)

 
1-year

Lifetime

Variable 

Any mood
disorder 

Major
depressive disorder 

Dysthymic
disorder 

Bipolar I
disorder 

Any mood
disorder 

Major
depressive
disorder 

Dysthymic
disorder 

Bipolar I
disorder 

Country studied 

               

European 

 

8.0 

(5.0 to 11.9) 

           

Non-European 

 

3.0 

(1.5 to 4.9) 

           

Asian 

 

0.85 

(0.59 to 1.2) 

     

1.6 

(0.97 to 2.5) 

1.5 

(1.0 to 2.0) 

 

Non-Asian 

 

6.3 

(4.7 to 8.2) 

     

11.7 

(8.7 to 15.3) 

5.5 

(4.2 to 6.9) 

 

North
American 

6.9 

(4.7 to 9.7) 

             

Non-North American 

8.8 

(6.2 to 12.0) 

             

Diagnostic instrument 

               

CIDI 

       

21.2 

(16.0 to 27.3) 

 

6.2 

(5.3 to 7.2) 

1.7 

(1.4 to 2.0) 

Other 

       

10.9 

(7.4 to 15.3) 

 

2.7 

(1.8 to 3.7) 

0.83 

(0.6 to 1.1) 

Diagnostic criteria 

               

DSM-III-R 

 

7.5 

(5.1 to 10.5) 

   

21.8 

(17.4 to 26.7) 

15.8 

(14.6 to 16.9) 

6.7 

(4.7 to 9.2) 

1.7 

(1.4 to 1.9) 

Other 

 

2.4 

(1.1 to 4.1) 

   

9.4 

(7.0 to 12.3) 

3.9 

(2.2 to 5.9) 

2.5 

(1.7 to 3.6) 

0.64 

(0.43 to 0.92) 

Year study published 

               

£ 1994 

8.4 

(6.2 to 11.1) 

 

2.9 

(2.4 to 3.5) 

         

> 1994 

5.9 

(3.2 to 9.3) 

 

1.5 

(0.83 to 2.4) 

         

£ 1992 

       

10.5 

(7.5 to 14.0) 

     

> 1992 

       

22.4 

(17.0 to 28.5) 

     

Type of person administering interview 

               

Lay
interviewers 

     

0.71 

(0.48 to 1.0) 

       

Other 

     

0.82 

(0.02 to 2.6) 

       

Response rate 

               

< 75% 

       

14.2 

(9.6 to 19.8) 

     

³ 75% 

       

4.4 

(2.3 to 7.1) 

     

Major Depressive Disorder. The best-estimate rates for 1-year and lifetime prevalence were 4.1 per 100 (95%CI, 2.4 to 6.2 per 100) and 6.7 per 100 (95%CI, 4.2 to 10.1 per 100), respectively (Tables 3 and 4). The variations in the 1-year and lifetime prevalence rates, as shown by the CIs, are 2.6-fold and 2.4-fold, respectively, which are much lower than the respective 24-fold and over 30-fold differences observed across individual rates. Heterogeneity analysis demonstrated significant differences across 1-year and lifetime prevalence rates of MDD. For studies conducted in Europe, the pooled 1-year rates were found to be approximately 3 times higher than those of studies carried out in other parts of the world (Table 7). Conversely, for studies conducted in Asia, pooled 1-year and lifetime rates were approximately 7 times lower, compared with studies carried out in non-Asian countries. Studies using DSM-III-R criteria had pooled 1-year and lifetime rates that were around 3 to 4 times higher than those for studies using other diagnostic criteria. Finally, studies having response rates of under 75% had a pooled lifetime rate approximately 3 times greater than that of studies having response rates of 75% or over.

Dysthymic Disorder. The best-estimate rates for 1-year and lifetime prevalence were 2.0 per 100 (95%CI, 1.3 to 2.8 per 100) and 3.6 per 100 (95%CI, 2.5 to 5.0), respectively (Tables 3 and 4). The variations in the CIs for these 1-year and lifetime prevalence rates are 2.2-fold and 2.0-fold, respectively, which is much smaller than the respective variations of 4.1-fold and 15.2-fold observed across individual rates. Heterogeneity was demonstrated for 1-year and lifetime prevalence rates of dysthymic disorder. Studies conducted in Asian countries produced a pooled lifetime rate that was almost 4 times lower than that for studies carried out in non-Asian countries (Table 7). For studies using the CIDI (DSM-III-R), pooled lifetime rates were approximately twice as high, compared with studies using other instruments or criteria.

Bipolar I Disorder. The best-estimate rates for 1-year and lifetime prevalence were found to be 0.72 per 100 (95%CI, 0.5 to 1.0) and 0.82 per 100 (95%CI, 0.56 to 1.1), respectively (Tables 3 and 4). The CI variations for the 1-year and lifetime rates are 2.0-fold and 2.0-fold, respectively, which are much lower than the respective 7.5-fold and 12-fold differences observed across individual rates. Significant differences were found among 1-year and lifetime prevalence rates of BD I. For studies using the CIDI, the pooled lifetime prevalence was twice that of studies using other diagnostic instruments (Table 7). Similarly, for studies using DSM-III-R criteria, the pooled lifetime prevalence was 2.7 times that for studies using other diagnostic criteria.

Incidence Studies
Results are reported for 4 studies that provided data on overall and sex-specific 1-year incidence of MDD (Table 8). The results of a single incidence study are not presented here as only age-specific and sex-specific rates were reported (44).

Table 8  Annual incidence rates of major depressive disorder 

         

Incidence rate
(per 100) 

Study authors 

Study site 

Case-finding
method 

Period of study 

Total population (n

Total 

Men 

Women 

Sandanger and others (46) 

Norway - Oslo and islands of Lofoten 

Census; CIDI/ICD-10; interview given by health professionals; retrospective assessment 

1989 to 1991 

1-year before interview 

1 879 

  

1.8 

0.44 

3.0 

Pakriev and others (17) 

Udmurt Republic - region of Udmurtia 

Census; CIDI/ICD-10; diagnosis by clinician; retrospective assessment 

1995 

1-year period 

855 

7.5 

4.1 

10.1 

Newman and Bland (67) 

Canada - metropolitan Edmonton 

Census; DIS/DSM-III; lay interviewers; algorithm diagnosis; prospective follow-up of subjects for approx three years    

1984 to 1991 

approx 3 year follow-up 

1 964 

(4679 person-years at risk) 

2.8a 

2.0 

3.7 

Eaton and others (68) 

USA (ECA) - 4 sites, mainly urban 

Census; DIS/DSM-III; lay interviewers; algorithm diagnosis; prospective follow-up of subjects over  one year 

1980 - 1981 

1-year follow-up 

10 285 (persons at risk) 

(9250 person-years at risk) 

1.6 

1.1 

2.0 

       

Best-estimate 

(95%CI) 

2.9 

(1.3 to 4.8) 

 

 

aFigure obtained using raw data 

The incidence studies conducted in Edmonton, Alberta, (67) and in the US (68) were prospective follow-up studies of community-based samples with total populations of 1964 and 10 285, respectively. The studies conducted in Norway (46) and Udmurtia (17) were also based on community samples but involved retrospective assessments of incidence. The 2 prospective studies used the DIS and an algorithm to extract diagnoses, while the retrospective studies employed the CIDI and a clinician diagnosis.

Qualitative Analysis. The 1-year incidence for MDD ranged from 1.6 per 100 in the US ECA study (68) to 7.5 per 100 in Udmurtia (17). This represents a 4.7-fold variation. Excluding the outlying rate from the study conducted in Udmurtia, the rates vary up to 2.8 per 100, a difference of only 1.8-fold. With regard to sex-specific 1-year incidence rates, 3 of the studies reported rates for women that were approximately twice those for men, while the Norwegian study (46) found the rate for women to be more than 6 times that for men.

Estimation and Heterogeneity Analysis of Pooled Best-Estimate Rates. The best-estimate rate for 1-year incidence of MDD was 2.9 per 100 (Table 8). Heterogeneity analysis of the 1-year incidence rates for MDD revealed significant differences across rates. Pooled sex-specific rates were not calculated, as 1 study did not provide the required demographic data. Further analysis to determine the variables contributing to heterogeneity was not carried out because of the small number of rates.

Primary Care Studies
Findings are presented in Table 9 for the 10 studies reporting prevalence rates for MDD. Most studies involve the prospective recruitment and assessment of all patients seen at primary care practices over a specified period of time. Total sample sizes range from approximately 500 (73) to 7700 (76). Most studies followed a 2-stage sampling procedure in which recruited subjects were screened and then given a structured interview. Because an insufficient number of primary care incidence studies met our inclusion criteria, incidence data are not included in the analysis.

Table 9  Prevalence rates of major depressive disorder in primary care 

Study authors 

Location of primary care practice(s) 

Case-finding method 

Denominator population (n

Period of subject recruitment 

Prevalence rate
(per 100) 

Tiemens and others (78) 

   

All patients given GHQ screen; stratified random sample based screen scores given structured interview (CIDI/ICD-10) 

1271 

(unclear whether patients or visits) 

3 weeks (at each practice) 

13.5 

Rowe and others (77) 

USA - southern Wisconsin (88 primary care practices - urban/rural) 

Random sample of patients given self-report screen (HSS ) and extended form (using DIS questions and DSM-III-R); retrospective assessment of prevalence 

1865 

(unclear whether patients or visits) 

Unclear 

1-month:
21.7 (female)
12.7 (male) 

Lifetime:
36.1 (female)
23.3 (male) 

Schulberg and others (76) 

USA - city of Pittsburgh (4 primary care facilities) 

All patients given self-report screen (CES-D); all screen positive (cutoff score 22) given structured interview (DIS/DSM-III-R) 

7652 

(unclear whether patients or visits) 

21 months 

8.9a 

Simon and Von Korff (79) 

USA - city of Seattle (3 health maintenance organization clinics) 

All patients given GHQ screen; stratified random sample based screen scores given structured interview (CIDI/DSM-IV) 

1962 

unique patients 

unclear 

6.6 

Coyne  and others (75) 

USA - rural and suburban areas of southeastern Michigan (50 family physician practices) 

All patients given self-report screen (CES-D); sample of both screen positive and negative (cutoff score 16) given structured telephone interview (SCID/DSM-III-R) 

1928 

(unclear whether patients or visits) 

15 months 

13.5 

Barrett and others (74) 

USA - town of Hanover, New Hampshire (rural primary care practice for several towns) 

All patients given self-report screen (based on SCL and CES-D); all screen positive and random sample of remaining given interview by psychiatrist using SADS/RDC 

1055 

unique patients 

15 months 

2.2 

Blacker and Clare (80) 

UK - single inner-city health centre 

All patients given GHQ screen; all screen positive and sample of screen negative given structured interview (SADS+PSE-9/RDC) 

2308 

(unclear whether patients or visits) 

Unclear 

4.3 

Von Korff and others (81) 

USA - city of Baltimore (primary care group practice - surrounded by inner-city community) 

All patients given GHQ screen; all screen positive and sample of screen negative given structured interview (DIS/DSM-III) 

1242 

(unclear whether patients or visits) 

4 months 

5.0 

Kessler and others (82) 

USA - central Wisconsin (semirural multispecialty group practice) 

All patients given GHQ screen; stratified subsample given structured interview (SADS-L/RDC) at baseline and 6-months later (examines remitted, new, and continuing cases) 

1072 

(unclear whether patients or visits) 

3 months (with 6-month follow-up) 

9.1a 

Zung and others (73) 

USA - Durham, North Carolina (primary care physician’s office) 

All patients given self-report screen (SDS); all screen positivegiven structured interview based on DSM-III 

499 

(unclear whether patients or visits) 

9 months 

10.0 

aCalculated from raw data. 

CES-D = Centre for Epidemiologic Studies-Depression Scale; GHQ = General Health Questionnaire; HSS = Hangover Symptoms Scale; SCL = Symptom Checklist; SDS = Self-Rating Depression Scale; SADS/RDC = Schedule for Affective Disorders and Schizophrenia/Research Diagnostic Criteria; PSE = Present State Examination 

Qualitative Analysis. Prevalence rates of MDD in primary care ranged from 2.2 per 100 in New Hampshire (74) to 36.1 per 100 in female primary care attendees in Wisconsin (77) (Table 9). Although many studies attempted to determine point prevalence rates of MDD, studies used widely varying methods. For instance, the denominator value in this calculation at times used unique patients, and at other times no definition was provided at all. This is problematic as rates generated using unique visits in the denominator would likely be different from those using unique patients. Even assuming all studies used either unique patients or unique visits, there is variation in the period of subject recruitment or an absence of study-period description. Owing to this wide variation in even the basic definitions of prevalence rates in primary care, we did not attempt to perform any data analysis on the rates and only described them qualitatively.

Discussion

One intriguing finding of this review is the relatively low lifetime prevalence rate of MDD in similarly conducted, high-quality studies, compared with the typically reported rates of 5% to 12% for men and 10% to 25% for women (6). The finding of selective reporting of high rates for MDD warrants further examination in other domains of health care to determine whether this is specific to depression or whether it is a more generalized phenomenon.

With respect to the incidence findings, the rates seem implausibly large. If these incidence rates were applied to the calculation of morbidity risk (that is, cumulative annual incidence rates), over 100% of the population would suffer from depression over some period of time. Although 3 of the 4 incidence studies explicitly state that only first-onset cases of depression were sought, it is possible that, owing to recall bias, some recurrent or chronic cases were also included in the incidence figures, leading to overestimated rates.

Another important finding related to MDD is that rates in primary care were not comparable because of differing study methodologies. This is unfortunate, as robust estimates of point prevalence rates would allow for the estimate of pretest probabilities for screening tools used by primary care physicians (94), and 1-year prevalence rates in primary care would allow for comparison with rates in community studies.

The major flaw in primary care studies was the lack of standardized definitions for point and period prevalence. Many studies defined cases and the population at risk differently and measured these factors over differing time periods. In future studies, case definitions should be explicit and multiple rates should be provided, distinguishing cases and the population at risk over standard time periods, such as 6 months or 1 year.

Consistent with other studies (1–3), we found that women had a higher rate of MDD and dysthymia but that men and women were equally affected by BD I. This review, unlike earlier reviews, was able to incorporate the findings of several recent studies that examined the diagnosis of dysthymia. The inclusion of such studies confirmed that dysthymia is approximately one-half as common as MDD.

Similar to other mental disorders examined in this series (4), despite controlling for several methodological factors, there was persistent variation in the prevalence and incidence rates of mood disorders across studies. This was particularly noticeable when the range of rates was used as a measure of variation. When the CI was used as a measure of variation (a technique that reduces the effect of outliers and smaller studies), there was a lower, but still notable, 2-fold variation in rates. This may imply a degree of “real” variation in mood disorders, potentially related to variation in the distribution of risk factors for these conditions. Because of this persistence of variation across studies, the best-estimate rates in this review should not be reported without their CIs. This issue of unexplained variation warrants further study.

There are some important clinical implications of the findings from this review. When clinicians discuss the prevalence of mood disorders with consumers, they may need to revise the estimates provided in standard medical texts downward. The absence of consistently reported prevalence figures in primary care settings for MDD makes it difficult for clinicians to determine the pretest probability of this disorder in these settings. This may add uncertainty to accurately diagnosing MDD with brief diagnostic tools.

This review quantified several explanatory variables for the remaining variation in prevalence rates. The effects of diagnostic criteria were specifically examined, with studies using CIDI having approximately 2 times the rate of dysthymic disorder and BD I, compared with studies using DIS (DSM-III) criteria. Although interviewer effects are a significant matter (95), the type of person administering the interview (that is, layperson vs clinician) was not an important source of variation in the studies reviewed. Studies of lifetime prevalence of mood disorders reported significantly higher rates when published after 1992. Generally, there were higher rates in European studies and lower rates in Asian studies. All these findings regarding heterogeneity should be tempered by the fact that these are ecological comparisons rather than comparisons at the level of individuals; thus, the findings may be confounded by multiple variables. Although this review attempted to limit variation as a result of study methodology, further unexamined sources of potential variation could be important, such as differences in the measured concept of depression across cultures, differences in respondent reporting rates, differing age of onset, marital status and employment status, duration of illness, recovery and mortality rates between jurisdictions, and the effects of migration (3,15,96).


Funding and Support

All authors received salary support from the British Columbia Ministry of Health.

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Author(s)

Manuscript received August 2002, revised, and accepted May 2003.

1. Bioethicist, Centre for Addiction and Mental Health, Joint Centre for Bioethics and Faculty of Law, Department of Psychiatry, University of Toronto, Toronto, Ontario.

2. Associate Professor, Department of Psychiatry, Head, Mental Health Evaluation and Community Consultation Unit (MHECCU), University of British Columbia, Vancouver, British Columbia

3.Research Assistant, Mental Health Evaluation and Community Consultation Unit (MHECCU), University of British Columbia, Vancouver, British Columbia

Address for correspondence: Dr P Waraich, Mental Health Evaluation and Community Consultation Unit, St Paul’s Hospital, 306 A-1081 Burrard Street, Vancouver, BC V6Z 1Y6

e-mail: waraich@interchange.ubc.ca

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