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World Psychiatry. Oct 2007; 6(3): 168–176.
PMCID: PMC2174588

Lifetime prevalence and age-of-onset distributions of mental disorders in the World Health Organization's World Mental Health Survey Initiative

Abstract

Data are presented on the lifetime prevalence, projected lifetime risk, and age-of-onset distributions of mental disorders in the World Health Organization (WHO)'s World Mental Health (WMH) Surveys. Face-to-face community surveys were conducted in seventeen countries in Africa, Asia, the Americas, Europe, and the Middle East. The combined numbers of respondents were 85,052. Lifetime prevalence, projected lifetime risk, and age of onset of DSM-IV disorders were assessed with the WHO Composite International Diagnostic Interview (CIDI), a fully-structured lay administered diagnostic interview. Survival analysis was used to estimate lifetime risk. Median and inter-quartile range (IQR) of age of onset is very early for some anxiety disorders (7-14, IQR: 8-11) and impulse control disorders (7-15, IQR: 11-12). The age-of-onset distribution is later for mood disorders (29-43, IQR: 35-40), other anxiety disorders (24-50, IQR: 31-41), and substance use disorders (18-29, IQR: 21-26). Median and IQR lifetime prevalence estimates are: anxiety disorders 4.8-31.0% (IQR: 9.9-16.7%), mood disorders 3.3-21.4% (IQR: 9.8-15.8%), impulse control disorders 0.3-25.0% (IQR: 3.1-5.7%), substance use disorders 1.3-15.0% (IQR: 4.8-9.6%), and any disorder 12.0-47.4% (IQR: 18.1-36.1%). Projected lifetime risk is proportionally between 17% and 69% higher than estimated lifetime prevalence (IQR: 28-44%), with the highest ratios in countries exposed to sectarian violence (Israel, Nigeria, and South Africa), and a general tendency for projected risk to be highest in recent cohorts in all countries. These results document clearly that mental disorders are commonly occurring. As many mental disorders begin in childhood or adolescents, interventions aimed at early detection and treatment might help reduce the persistence or severity of primary disorders and prevent the subsequent onset of secondary disorders.

Keywords: Mental disorders, lifetime prevalence, projected lifetime risk, age-of-onset distribution

Although psychiatric epidemiological surveys have been carried out since after World War II (1), absence of a common format for diagnosis hampered cross-national syntheses. This situation changed in the early 1980s, with the development of fully structured research diagnostic interviews (2) and the implementation of large-scale psychiatric epidemiological surveys in many countries (3-5). The World Health Organization (WHO) developed a diagnostic instrument, the WHO Composite International Diagnostic Interview (CIDI) (6,7), based on extensive cross-national field trials, for use in cross-national epidemiological surveys (8-14). In 1998, the WHO created the WHO International Consortium in Psychiatric Epidemiology (ICPE) to coordinate comparative analyses of these surveys. The ICPE launched the WHO World Mental Health (WMH) Survey Initiative shortly thereafter to conduct coordinated CIDI surveys in all parts of the world. The current report presents the first cross-national results regarding age of onset, lifetime prevalence, and projected lifetime risk of mental disorders from the 17 WMH surveys so far completed.

Data of this sort are sorely needed by policy planners to assess the societal burden of mental disorders, unmet need for treatment, and barriers to treatment. These data are especially important given evidence from the WHO Global Burden of Disease Study that mental disorders impose enormous burdens worldwide, due to their combination of high prevalence and high disability (15), and evidence that, despite efficacious treatments, substantial unmet need for treatment exists throughout the world (16). While earlier studies found high lifetime prevalence and generally early age-of-onset distributions of mental disorders, they did not make systematic disorder-specific age-of-onset comparisons. The latter are important for targeting early interventions, which are coming to be seen as critical for an effective public health response to mental disorders (17-19). Previous studies also focused on lifetime prevalence (the proportion of the population with a lifetime disorder up to age at interview) rather than projected lifetime risk (the estimated proportion of the population who will have the disorder by the end of their life), even though the latter is more important for policy planning purposes. We consider both prevalence and risk in this report.

METHODS

Samples

WMH surveys were administered in Africa (Nigeria, South Africa); the Americas (Colombia, Mexico, United States), Asia and the Pacific (Japan, New Zealand, Beijing and Shanghai in the People's Republic of China, henceforth referred to as Metropolitan PRC), Europe (Belgium, France, Germany, Italy, the Netherlands, Spain, Ukraine) (20); and the Middle East (Israel, Lebanon). Seven of these countries are classified by the World Bank as less developed (China, Colombia, Lebanon, Mexico, Nigeria, South Africa, Ukraine), while the others are classified as developed (21).

Most WMH surveys were based on stratified multistage clustered area probability household samples. Samples of areas equivalent to counties or municipalities in the US were selected in the first stage, followed by one or more subsequent stages of geographic sampling (e.g., towns within counties, blocks within towns, households within blocks) to arrive at a sample of households. In each of them, a listing of household members was created and one or two people were selected to be interviewed. No substitution was allowed when the originally sampled household resident could not be interviewed. The household samples were selected from census area data in all countries other than France (where telephone directories were used) and the Netherlands (where postal registries were used). Several WMH surveys (Belgium, Germany, Italy) used municipal resident registries to select respondents without listing households. The Japanese sample is the only totally unclustered sample, with households randomly selected in each of the four sample areas and one random respondent selected in each sample household. Nine of the 17 surveys were based on nationally representative household samples, while two others were based on nationally representative household samples in urbanized areas (Colombia, Mexico).

All surveys were conducted face-to-face by trained lay interviewers in multi-stage household probability samples, with 85,052 respondents. Country-level samples ranged from 2372 (Netherlands) to 12,992 (New Zealand). The weighted average cross-national response rate was 71.1%, with a 45.9-87.7% range (Table (Table11).

Table 1
Sample characteristics of the World Mental Health Surveys

The Part I interview schedule, completed by all respondents, assessed core diagnoses. All respondents who met criteria for any diagnosis plus a probability sub-sample of other Part I respondents were administered Part II, which assessed disorders of secondary interest and a wide range of correlates. Part I data were weighted to adjust for differential probabilities of selection and to match population distributions on socio-demographic and geographic data. The Part II sample was additionally weighted for the oversampling of Part I respondents with core disorders. The interview schedule and other study materials were translated using standardized WHO translation and back-translation protocols. Consistent interviewer training procedures and quality control monitoring were used in all surveys (22,23). Informed consent was obtained in all countries using procedures approved by local Institutional Review Boards.

Measures

Diagnoses were based on CIDI Version 3.0 (24), which generates both ICD-10 (25) and DSM-IV (26) diagnoses. DSM-IV criteria are used here to facilitate comparison with previous epidemiological surveys. Core diagnoses included anxiety disorders (panic disorder, agoraphobia without panic disorder, specific phobia, social phobia, generalized anxiety disorder, post-traumatic stress disorder, and separation anxiety disorder), mood disorders (major depressive disorder, dysthymic disorder, bipolar disorder I or II or subthreshold bipolar disorder), impulse control disorders (intermittent explosive disorder, oppositionaldefiant disorder, conduct disorder, attention-deficit/hyperactivity disorder), and substance use disorders (alcohol and drug abuse with or without dependence). Not all disorders were assessed in all countries. The Western European countries did not assess bipolar disorders and drug dependence. Only three countries (Colombia, Mexico, United States) assessed all impulse control disorders.

The disorders that require childhood onset (oppositional defiant disorder, conduct disorder, and attention-deficit/hyperactivity disorder) were included in Part II and limited to respondents in the age range 18-39/44, because of concerns about recall bias among older respondents. All other disorders were assessed for the full sample age range. Organic exclusion rules and hierarchy rules were used to make all diagnoses other than substance use disorders, which were diagnosed without hierarchy, because abuse often is a stage in the progression to dependence. Clinical calibration studies (27) found CIDI to assess these disorders with generally good validity in comparison to blinded clinical reappraisal interviews using the Structured Clinical Interview for DSM-IV (SCID) (28). CIDI prevalence estimates were not higher than SCID prevalence estimates. Retrospective age-of-onset reports were based on a question series designed to avoid the implausible response patterns obtained in using the standard CIDI age-of-onset question (29). Experimental research has shown that this question sequence yields responses with a much more plausible age-of-onset distribution than the standard CIDI age-of-onset question (30). Predictor variables included cohort (defined by ages at interview 18-34, 35-49, 50-64, 65+), sex, and education (students versus non-students with low, low-average, average-high, and high education categories based on country-specific distributions). Education was coded as a time-varying predictor by assuming an orderly educational history.

Analysis procedures

Age of onset and projected lifetime risk as of age 75 were estimated using the two-part actuarial method implemented in SAS 8.2 (31). Predictors were examined using discrete- time survival analysis with person-year as the unit of analysis (32). Standard errors were estimated using the Taylor series linearization method (33) implemented in the SUDAAN software system (34). Multivariate significance tests were made with Wald ?2 tests, using Taylor series design- based coefficient variance-covariance matrices. Standard errors of lifetime risk were estimated using the jackknife repeated replication method (35) implemented in a SAS macro (31). Significance tests were all evaluated at the .05 level with two-sided tests. (TABLE (TABLE11)

RESULTS

Lifetime prevalence

The estimated lifetime prevalence of having one or more of the disorders considered here varies widely across the WMH surveys, from 47.4% in the United States to 12.0% in Nigeria. The inter-quartile range (IQR; 25th-75th percentiles across countries) is 18.1-36.1%. Symptoms consistent with the existence of one or more lifetime mental disorders were reported by more than one-third of respondents in five countries (Colombia, France, New Zealand, Ukraine, United States), more than one-fourth in six (Belgium, Germany, Lebanon, Mexico, The Netherlands, South Africa), and more than one-sixth in four (Israel, Italy, Japan, Spain). The remaining two countries, Metropolitan PRC (13.2%) and Nigeria (12.0%), had considerably lower prevalence estimates, that are likely to be downwardly biased (36, 37). Prevalence estimates for other developing countries were all above the lower bound of the inter-quartile range (Table (Table22).

Table 2
Lifetime prevalence and projected lifetime risk as of age 75 of DSM-IV disorders

All four classes of disorder were important components of overall prevalence. Anxiety disorders were the most prevalent in ten countries (4.8-31.0%, IQR 9.9-16.7%) and mood disorders in all but one other country (3.3-21.4%, IQR 9.8-15.8%). Impulse control disorders were the least prevalent in most countries that included a relatively full assessment of these disorders (0.3-25.0%, IQR 3.1-5.7%). Substance use disorders were generally the least prevalent elsewhere (1.3-15.0%, IQR 4.8-9.6). The Western European countries did not assess illicit drug abuse-dependence, though, leading to artificially low prevalence estimates (1.3-8.9%) compared to other countries (2.2- 15.0%). Substance dependence was also assessed only in the presence of abuse, possibly further reducing estimated prevalence (38). Lifetime disorder co-occurrence was quite common, as seen by noting that the sum of prevalence across the four disorder types was generally between 30% and 50% higher than the prevalence of any disorder. Within- class co-occurrence cannot be seen in the reported results, but is even stronger than between-class co-occurrence (results available on request).

Age-of-onset distributions

Despite the wide cross-national variation in estimated lifetime prevalence, considerable cross-national consistency exists in standardized age-of-onset distributions (detailed results are not reported here, but are available on request).

Impulse control disorders have the earliest age-of-onset distributions, both in terms of early median ages of onset (7-9 years of age for attention-deficit/hyperactivity disorder, 7-15 for oppositional-defiant disorder, 9-14 for conduct disorder, and 13-21 for intermittent explosive disorder) and an extremely narrow age range of onset risk, with 80% of all lifetime attention-deficit/hyperactivity disorder beginning in the age range 4-11 and the vast majority of oppositional- defiant disorder and conduct disorder beginning between ages 5 and 15. Although the age-of-onset distribution is less concentrated for intermittent explosive disorder, fully half of all lifetime cases have onsets in childhood and adolescence.

The situation is more complex with anxiety disorders, as the age-of-onset distributions fall into two distinct sets. The phobias and separation anxiety disorder all have very early ages of onset (medians in the range 7-14, IQR 8-11). Generalized anxiety disorder, panic disorder, and posttraumatic stress disorder, in comparison, have much later age-of-onset distributions (median 24-50, IQR 31-41), with much wider cross-national variation than for the impulse control disorders or the phobias or separation anxiety disorder.

The age-of-onset distributions for mood disorders are similar to those for generalized anxiety disorder, panic disorder, and post-traumatic stress disorder. Prevalence is consistently low until the early teens, at which time a roughly linear increase begins that continues through late middle age, with a more gradual increase thereafter. The median age of onset of mood disorders ranges between the late 20s and the early 40s (29-43, IQR 35-40).

The age-of-onset distribution of substance use disorders is consistent across countries, in that few onsets occur prior to the mid teens and cumulative increase in onset is rapid in adolescence and early adulthood. Considerable crossnational variation exists, though, in the sharpness of the change in the slope as well as in the age range of this change. This cross-national variation leads to wider crossnational variation in both the median and the inter-quartile range of the age-of-onset distributions than for impulse control disorders or phobias or separation anxiety disorder, but lower variation than for mood disorders or other anxiety disorders.

Projected lifetime risk

Projected lifetime risk of any disorder as of age 75 is between 17% (United States) and 69% (Israel) higher than estimated lifetime prevalence (IQR 28-44%) (Table (Table2).2). The highest risk-to-prevalence ratios (57-69%) are in countries exposed to sectarian violence (Israel, Nigeria, and South Africa). Excluding these three, there is no strong difference in ratios of less developed (28-41%) versus developed (17- 49%) countries. The highest class-specific proportional increase in projected risk is for mood disorders (45-170%, IQR 61-98%) and the lowest for impulse control disorders (0-14%, IQR 0-2%), consistent with the former having the latest and the latter having the earliest age-of-onset distribution. The projected lifetime risk estimates suggest that approximately half the population (47-55%) will eventually have a mental disorder in six countries (Colombia, France, New Zealand, South Africa, Ukraine, United States), approximately one-third (30-43%) in six other countries (Belgium, Germany, Israel, Lebanon, Mexico, the Netherlands), approximately one-fourth (24-29%) in three others (Italy, Japan, Spain), and approximately one-fifth (18-19%) in the remaining countries (Metropolitan PRC, Nigeria).

Cohort effects

Previous research has suggested that projected lifetime risk might be increasing in recent cohorts (39). Prospective tracking studies are required to monitor cohort effects directly. However, indirect approximations can be obtained in cross-sectional data using retrospective age-of-onset reports. This was done in the WMH data using discrete-time survival analysis to predict onset of disorders across age groups 18-34, 35-49, 50-64, and 65+. As these surveys were completed between 2002 and 2005, the most recent cohorts (aged 18-34 at interview) roughly correspond to those born in the years from 1968+. Respondents aged 35-49 at interview correspond roughly to cohorts born in 1953-1970, while those aged 50-64 were born in 1938-1955, and those aged 65+ were born before 1938. Survival analysis finds that the odds ratios for anxiety, mood, and substance use disorders are generally higher in recent compared to older cohorts, while not for impulse control disorders (Tables (Tables33--5). No5). No meaningful difference exists between less developed and developed countries, although cross-national variation exceeds chance expectations. (TABLE 2)

Table 3
Inter-cohort differences in lifetime risk of any DSM-IV anxiety disorder a
Table 5
Inter-cohort differences in lifetime risk of any DSM-IV substance use disorder a

DISCUSSION

Three possible biases could have led to under-estimating prevalence. First, people with mental illness have been found to be less likely than others to participate in surveys, because of sample frame exclusions (e.g., excluding homeless people), differential mortality, or greater reluctance to participate (40). Variation in the magnitude of such under-representation across countries could help account for the wide betweencountry variation in prevalence-risk estimates. Second, previous research suggests that lifetime prevalence is sometimes under-reported because of respondent reluctance to admit mental illness (41). This bias might be especially strong in less developed countries with no strong tradition of independent public opinion research, which could help account for the especially low prevalence-risk estimates in Nigeria and Metropolitan PRC. Third, interviewer error might have led to under- reporting, especially in countries where there was an indirect incentive to rush through interviews, because interviewers were paid by the interview rather than by the hour. The most plausible bias that could have led to over-estimating prevalence, in comparison, is that the interview thresholds for defining disorders might have been too liberal. However, as noted in the section on measures, clinical reappraisal studies carried out in some of the countries with the highest prevalence estimates found no evidence of such bias (27).

Two possible biases of other sorts are also noteworthy. First, the method used to estimate lifetime risk was based on the assumption of constant conditional risk of first onset in a given year of life across cohorts. The existence of an apparent cohort effect means that this assumption is incorrect, probably causing an under-estimation of lifetime risk in younger cohorts. Second, age of onset might have been recalled with error related to age at interview, which could produce the data pattern found here as indirect evidence for a cohort effect (42). Evidence for age-related bias has been documented in previous epidemiological research (29), although the novel probing strategy used in the WMH surveys has been shown to minimize this problem (30).

Based on these considerations, the wide cross-national variation in WMH prevalence and risk estimates should be interpreted with caution, because it is likely over-estimated due to between-country differences in some of the biases enumerated above. The overall prevalence-risk estimates, which are consistent with previous cross-national research (8-14,39), are likely to be conservative, as the most plausible biases lead to under-estimation. The evidence for cohort effects is more difficult to judge, as both substantive and methodological interpretations are plausible. The options are either that the prevalence of mental disorders is on the rise or that prevalence is stable but under-estimated among older respondents.

Given the high prevalence-risk estimates even with the possibility of conservative bias, a question can be raised about the meaningfulness of these estimates. Our clinical reappraisal studies, consistent with comparable studies carried out in conjunction with previous community psychiatric epidemiological surveys (43), show that the high prevalence estimates are genuine (i.e., consistent with expert clinician judgments) rather than due to CIDI errors. It is important to recognize, though, that not all mental disorders are severe. WMH measures of disorder severity were applied only to 12-month cases, so we have no way to estimate severity of lifetime cases. Analysis of 12-month cases, though, finds the majority rated mild on a clinical rating scale with categories mild, moderate, and severe (22). These cases are nonetheless meaningful, because even mild cases can be impairing and often evolve into more serious disorders over time (44).

The age-of-onset distributions reported here are consistent with those in previous epidemiological surveys (39,45). Given the enormous personal and societal burdens of mental disorders, the finding that many cases have early ages of onset suggests that public health interventions might profitably begin in childhood. Importantly, studies of initial contact with the treatment system (46-48) show that people with these early-onset disorders often wait more than a decade before seeking treatment, and present with seriously impairing disorders that might have been easier to treat if they had sought treatment earlier in the course of illness. Interventions aimed at early detection and treatment might help reduce the persistence or severity of these largely primary anxiety and impulse control disorders and prevent the onset of secondary disorders. More preclinical and clinical research is needed on treatments of early cases, though, to determine whether this is true. Epidemiological research is also needed on the long-term consequences of early interventions for long-term secondary prevention.

Table 4
Inter-cohort differences in lifetime risk of any DSM-IV mood disorder a

Acknowledgements

The surveys discussed in this article were carried out in conjunction with the World Health Organization's World Mental Health (WMH) Survey Initiative. We thank the WMH staff for assistance with instrumentation, fieldwork, and data analysis. These activities were supported by the United States National Institute of Mental Health (R01-MH070884), the John D. and Catherine T. MacArthur Foundation, the Pfizer Foundation, the US Public Health Service (R13-MH066849, R01-MH069864, and R01-DA016 558), the Fogarty International Center (FIRCA R01- TW006481), the Pan American Health Organization, Eli Lilly and Company, Ortho-McNeil Pharmaceutical, Inc., GlaxoSmithKline, and Bristol-Myers Squibb. The Chinese World Mental Health Survey Initiative is supported by the Pfizer Foundation. The Colombian National Study of Mental Health (NSMH) is supported by the Ministry of Social Protection, with supplemental support from the Saldarriaga Concha Foundation. The ESEMeD project is funded by the European Commission (Contracts QLG5- 1999-01042; SANCO 2004123), the Piedmont Region (Italy), Fondo de Investigaciòn Sanitaria, Instituto de Salud Carlos III, Spain (FIS 00/0028), Ministerio de Ciencia y Tecnología, Spain (SAF 2000-158-CE), Departament de Salut, Generalitat de Catalunya, Spain, and other local agencies, and by an unrestricted educational grant from GlaxoSmithKline. The Israel National Health Survey is funded by the Ministry of Health, with support from the Israel National Institute for Health Policy and Health Services Research and the National Insurance Institute of Israel. The World Mental Health Japan (WMHJ) Survey is supported by the Grant for Research on Psychiatric and Neurological Diseases and Mental Health (H13-SHOGAI- 023, H14-TOKUBETSU-026, H16-KOKORO-013) from the Japan Ministry of Health, Labour and Welfare. The Lebanese National Mental Health Survey (LEBANON) is supported by the Lebanese Ministry of Public Health, the WHO (Lebanon), anonymous private donations to IDRAAC, Lebanon, and unrestricted grants from Janssen Cilag, Eli Lilly, GlaxoSmithKline, Roche, and Novartis. The Mexican National Comorbidity Survey (MNCS) is supported by the National Institute of Psychiatry Ramon de la Fuente (INPRFMDIES 4280) and by the National Council on Science and Technology (CONACyT-G30544- H), with supplemental support from the Pan American Health Organization. Te Rau Hinengaro: The New Zealand Mental Health Survey (NZMHS) is supported by the New Zealand Ministry of Health, Alcohol Advisory Council, and the Health Research Council. The Nigerian Survey of Mental Health and Wellbeing (NSMHW) is supported by the World Health Organization (Geneva), the World Health Organization (Nigeria), and the Federal Ministry of Health, Abuja, Nigeria. The South Africa and Health Study (SASH) is supported by the US National Institute of Mental Health (R01-MH059575) and National Institute of Drug Abuse, with supplemental funding from the South African Department of Health and the University of Michigan. The Ukraine Comorbid Mental Disorders during Periods of Social Disruption (CMDPSD) study is funded by the US National Institute of Mental Health (R01- MH61905). The US National Comorbidity Survey Replication (NCS-R) is supported by the National Institute of Mental Health (U01-MH60220), with supplemental support from the National Institute of Drug Abuse, the Substance Abuse and Mental Health Services Administration (SAMHSA), the Robert Wood Johnson Foundation (Grant 044780), and the John W. Alden Trust.

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