PMCCPMCCPMCC

Search tips
Search criteria 

Advanced

 
Logo of nihpaAbout Author manuscriptsSubmit a manuscriptNIH Public Access; Author Manuscript; Accepted for publication in peer reviewed journal;
 
J Clin Psychiatry. Author manuscript; available in PMC Apr 17, 2007.
Published in final edited form as:
PMCID: PMC1852440
NIHMSID: NIHMS19603
The global burden of anxiety and mood disorders: Putting ESEMeD findings into perspective
Ronald C. Kessler, PhD
Ronald C. Kessler, Department of Health Care Policy, Harvard Medical School, Boston, USA;
Correspondence: RC Kessler, Department of Health Care Policy, Harvard Medical School, 180 Longwood Avenue, Boston, MA, 02115, USA, Tel: 617-432-3587 (Voice), Fax: 617-432-3588 (Fax), Email: kessler/at/hcp.med.harvard.edu
Background
This paper compares the preliminary descriptive ESEMeD findings reported in this issue with eight broad patterns of results found in previous psychiatric epidemiological surveys.
Method
Systematic review of the literature on community epidemiological surveys of anxiety and mood disorders.
Results
The review concludes that the ESEMeD findings are broadly consistent with the patterns found in previous surveys, but faults the preliminary ESEMeD analyses for failing to distinguish cases by severity and to consider the effects of severity on need for treatment.
Conclusion
The fact that the ESEMeD surveys collected much richer data than previous psychiatric epidemiological surveys on role impairment, symptom severity, and episode duration makes it possible to develop more useful classifications of clinical severity in future analyses. Elaborations that feature such distinctions have the potential substantially to increase the relevance of the ESEMeD findings for European health care policy.
Although community epidemiological surveys of mental disorders have been carried out in many parts of the world since shortly after World War II,13 the absence of common standards and operational procedures for diagnostic interviews has hampered efforts to make cross-national comparisons. This situation changed in the early 1980s with the development of the Diagnostic Interview Schedule (DIS),4 the first fully structured psychiatric diagnostic interview designed for use by trained interviewers who are not clinicians. The DIS made it possible for the first time for trained lay interviewers to carry out assessments of clinically significant mental disorders. In addition, computerized algorithms created in conjunction with the DIS made it possible to generate accurate diagnoses. The DIS was first used in the Epidemiologic Catchment Area Study (ECA),5 a large survey of the prevalence and correlates of mental disorders in the United States, and soon became the standard instrument for community epidemiological surveys of mental disorders.
A number of surveys modeled on the ECA were carried out in other countries during the 1980s.612 These surveys were subsequently brought together in a series of cross-national comparative analyses of specific disorders.1315 All of these surveys focused on DSM-III criteria, the system on which the DIS was based. However, the World Health Organization (WHO) International Classification of Diseases (ICD) system was used by the health care systems in a number of these countries, limiting the usefulness of the DIS findings. WHO, recognizing this problem, developed a second fully structured research diagnostic interview, the WHO Composite International Diagnostic Interview (CIDI),16 that expanded the DIS to include the questions needed to make diagnoses according to the definitions and criteria of the ICD-10 system.16 In addition, WHO coordinated the translation of the CIDI into many different languages and carried out extensive cross-national CIDI field trials to guarantee that the CIDI translations yielded results of comparable reliability and validity across countries.17
Version 1.0 of the CIDI was released in 1990.18 Diagnoses were made based on both the DSM-III-R and the ICD-10 criteria. The CIDI was subsequently revised to include DSM-IV criteria.19 In the decade since it first became available, the CIDI was used in a number of large-scale community epidemiological surveys throughout the world.2026 In recognition of this wide use, WHO created a research consortium, the WHO International Consortium in Psychiatric Epidemiology (ICPE), to coordinate comparative analyses. The ICPE has subsequently generated a large body of comparative cross-national data on the epidemiology of mental disorders.2731
The ESEMeD surveys are part of the generation of surveys using an expanded version of the CIDI that was built on the ICPE experience. The motivation for this CIDI expansion was the realization that the cross-national comparative analyses in the ICPE surveys were severely limited by the fact that the original version of the CIDI consisted exclusively of diagnostic questions and basic demographic questions. No questions were included about risk factors, consequences, treatment, or barriers to seeking treatment. Although some of the ICPE surveys collected information about these other factors, the assessments were not comparable, making it impossible to carry out systematic cross-national comparisons. As additional investigators began to contact the ICPE about carrying out new CIDI surveys, a decision was made to expand the CIDI to resolve this problem by developing CIDI sections on correlates and treatment.
In addition to including entirely new sections on risk factors, consequences, treatment, and barriers to treatment, this new version of the CIDI added questions to the diagnostic sections to update the DSM assessment from version III-R to version IV. It added a number of impulse-control disorders to the diagnostic assessment (e.g., Intermittent Explosive Disorder, Pathological Gambling, Bulimia, Borderline Personality Disorder). It added retrospective assessments of several important childhood disorders (Attention-Deficit Hyperactivity Disorder, Conduct Disorder, Oppositional-Defiant Disorder, and Separation Anxiety Disorder). Finally, it made a number of important changes in the diagnostic sections of the CIDI to improve completeness and accuracy of reporting. These changes were based on the cognitive interviewing methodology strategies used in the US National Comorbidity Survey (NCS)32, 33 and were guided by the empirical findings in the clinical calibrations of the NCS34 and of the Munich version of the CIDI.35 These changes substantially improved the clinical validity of the CIDI, but also reduced the comparability of this new version of the CIDI with the DIS and the original CIDI. A more detailed discussion of these changes is presented elsewhere.36 This new version of the CIDI was completed in 1999, at which time WHO established a World Mental Health (WMH) survey initiative aimed at carrying out surveys with the new CIDI (WMH-CIDI) in a representative set of countries in all major regions of the world.37 WMH collaborations were established in 28 different countries. The six ESEMeD surveys are the WMH collaborating surveys in Western Europe. Additional European surveys that joined the WMH collaboration after ESEMeD have either been completed or are currently being carried out in Bulgaria, Israel, Northern Ireland, Rumania, Scotland, Turkey, and Ukraine. Results from these surveys will soon be available to provide additional comparisons with the ESEMeD results. In addition, clinical calibration studies are currently underway to validate the WMH-CIDI in a number of countries. Three ESEMeD countries are participating in this calibration exercise (France, Italy, and Spain) along with countries in all other major regions of the world, including China, Colombia, India, Mexico, Nigeria, Panama, South Africa, and the US.
Comparison of the preliminary ESEMeD results with the findings from the larger set of WMH surveys will be the most valuable comparisons in the future. However, only preliminary results from a small number of the other WMH surveys are currently available. As a result, it is necessary to turn to the published results from the early DIS surveys and the more recent ICPE surveys for comparative data. Eight broad patterns of results can be detected in the basic descriptive epidemiological findings from these earlier surveys.
First, wide variation has been found in these previous surveys in both lifetime and recent prevalence estimates of anxiety disorders (Figure 1) and mood disorders (Figure 2). The ESEMeD lifetime prevalence estimates were in the middle of this range for lifetime prevalence estimates and somewhat lower than the average for recent (6–12 month) prevalence.38
Figure 1
Figure 1
Lifetime and recent (6-month or 12-month) prevalence of anxiety disorders in previous surveys
Figure 2
Figure 2
Lifetime and recent (6-month or 12-month) prevalence of mood disorders in previous surveys
Second, an examination of the implicit slopes in Figures 1 and and22 shows that anxiety and mood disorders are consistently found to be highly persistent, as indirectly indicated by the ratio of 12-month to lifetime prevalence. Roughly 60–70% of survey respondents with a lifetime anxiety disorder in these surveys report that their anxiety has been active in the 6–12 months before the interview. The comparable percentages for mood disorders are 40–50%. The same general pattern holds in the ESEMeD data, with the persistence of anxiety disorders somewhat higher than that of mood disorders, although the persistence ratios for both anxiety and mood disorders are lower in ESEMeD than in most of the earlier surveys.38
Third, retrospective reports in earlier surveys have consistently shown that anxiety and mood disorders typically have early ages of onset. Figures 3 (anxiety) and 4 (mood), which are based on the ICPE surveys, demonstrate substantial cross-national consistency in these patterns, with estimated medians of 15 years for anxiety disorders and 26 years for mood disorders. The ESEMeD data on age of onset have not yet been reported.
Figure 3
Figure 3
Age of onset distributions for any anxiety disorders in the International Consortium in Psychiatric Epidemiology surveys
Fourth, anxiety and mood disorders have consistently been found in earlier surveys to be highly comorbid.39, 40 The vast majority of people who have a history of one anxiety disorder have typically been found also to meet criteria for a second anxiety disorder. More than half the people with a history of either anxiety or mood disorder have typically been found to have both types of disorder. Anxiety has usually been the temporally primary disorder among people with a history of anxious-depression. Similar patterns have been shown in epidemiological studies of primary care samples41 and in clinical samples of psychiatric patients.42 The preliminary ESEMeD results have been strikingly similar to these earlier findings.43
Fifth, analysis of retrospective age-of-onset reports in earlier surveys has shown patterns that are consistent with the possibility that the lifetime prevalence of anxiety and mood disorders has increased in recent cohorts.30 This increase is more pronounced for mood than for anxiety disorders and, among people with mood disorders, more for those with comorbid anxious-depression than for those with pure depression. No data have yet been reported on whether similar patterns exist in the ESEMeD surveys.
Sixth, anxiety and mood disorders have consistently been found in earlier surveys to be associated with substantial impairments in both productive roles (e.g., work absenteeism, work performance, unemployment, under-employment) and social roles (e.g., social isolation, interpersonal tensions, marital disruption).44, 45 Other evidence on this issue has come into existence over the past decade based on primary care surveys, employer disability claims data, and clinical trials. These studies, which have been reviewed elsewhere for the anxiety disorders46, 47 and the mood disorders,31, 48 consistently document extensive role impairments associated with anxiety and mood disorders. The preliminary ESEMeD data reported in this issue are broadly consistent with these results.
Seventh, in addition to being associated with the indicators of disadvantaged achieved status that follow from impairments in productive roles (e.g., low income and education), anxiety and mood disorders have also consistently been associated with disadvantaged ascribed social status (e.g., racial-ethnic minority status, female gender). Indeed, these patterns of association have been consistently found in epidemiological surveys of psychological distress and mental disorders since the early 1950s.49, 50 The ESEMeD data are consistent with these previous results with regard to gender, but are weaker than previous results regarding socioeconomic status. No ESEMeD data have yet been reported on minority status.
Eighth, there is consistent evidence in the ICPE surveys that delays in seeking professional treatment are widespread after first onset of an anxiety or mood disorder, especially among early-onset cases and that only a minority of people with prevalent disorders receive any formal treatment.30 We are aware of only one study on this issue other than in the ICPE surveys. A recent report from a survey carried out by ICPE investigators among members of the Global Alliance of Mental Illness Advocacy Network (GAMIAN) asked respondents about age of disorder onset in relation to age of first receiving treatment.51 The results were consistent with those in the ICPE surveys in finding both pervasive delays in initial help seeking and strong positive associations between speed of initial treatment contact and age of onset. The ESEMeD surveys collected data that will allow the same patterns to be studied, but these results have not yet been reported.
Before turning to a discussion of proposed future directions of ESEMeD analyses, it is important to comment on the validity of the ESEMeD assessment of mental disorders. There are two key issues in comparing results of the ESEMeD surveys with those of previous surveys. The first is the issue of diagnostic validity: whether the instruments used to operationalize DSM or ICD diagnoses in these surveys are valid. The second is the issue of practical validity: whether these diagnoses, even if valid in a narrow technical sense of operationalizing the intended DSM or ICD criteria, are more broadly valid in identifying the range of people in need of treatment for mental disorders.
Diagnostic validity has been the focus of methodological research since the early 1980s.5254 As of the early 1990s, Wittchen reviewed the literature in this area,17 while a number of related reports have subsequently been published that focus largely on the reliability or validity of revised versions of the CIDI.34, 35, 5557 Three results emerge consistently from this literature. The first is that the concordance between diagnoses based on the DIS or CIDI compared to diagnoses based on blind clinical re-interviews is far from perfect, with concordance for most diagnoses in the adequate-to-good range using conventional standards to define these characterizations.58 This lack of concordance if often due to one or two criteria for a particular diagnosis that are inaccurately assessed in the DIS or CIDI,55 resulting in substantially improved concordance if these criteria are suppressed.
The second consistent result is that substantial downward bias exists in the DIS and early versions of the CIDI. For example, a comparison of results collected at baseline and one-year follow-up of the ECA study showed that a substantial number of early-onset lifetime disorders reported in the follow-up were not reported at baseline.59 If we accept the well-known finding that embarrassing behaviors are much more likely to be under-reported than over-reported, this result is most plausibly interpreted as evidence of under-reporting in the baseline interview. This bias was substantial, with up to 40% of true lifetime cases in the combined two-wave study missed in the baseline interview. At least two plausible causes exist for this under-reporting: the tendency for people to have an easier time recalling past experiences when they are in a mood that is consistent with the mood that existed in the situation they are being asked to recall; and the tendency for respondents to vary in the effort they put into active memory search in response to recall questions depending on their engagement with the interviewer and the interview. An extensive experimental literature shows that these two processes have substantial effects on the accuracy of responses to recall questions.60, 61
The third consistent result is that the under-reporting biases described in the last paragraph can be at least partially overcome by the use of strategies developed by survey methodologists to increase motivation for active memory search and to facilitate this sort of active memory search when motivation exists.32, 34, 62 Six such strategies were used in developing the WMH-CIDI. First, the CIDI diagnostic stem questions for all disorders were moved up to the front of the interview in a separate lifetime review section rather than appearing at the beginning of each separate diagnostic section. This consolidation of diagnostic stem questions allowed memory motivation and facilitation strategies to be focused on these critical entry questions to each diagnostic section and to be administered at a point in the interview when respondents were still cognitively fresh. It also allowed all stem questions to be administered before respondents became aware that endorsement of a stem question would result in the administration of many follow-up questions.
Second, an explanation was included at the beginning of the WMH-CIDI lifetime review section aimed at increasing respondent understanding that serious memory search was required to answer the lifetime stem questions. Third, motivational components were included in this introduction to encourage active memory search. Specifically, respondents were told “it is very important for the research to get complete and accurate answers to this next set of questions, so please take your time and think carefully before answering.” Respondents were then administered a commitment probe that asked them, with this injunction as a background, that they are ready to begin. Methodological research has shown that commitment probes of this sort that require respondents to acknowledge their understanding that active memory search is needed and their willingness to engage in this type of active memory search, significantly improves the accuracy of responses to survey questions that require recall.63
Fourth, interviewers were trained to read the stem questions slowly and deliberately. The aims here were to make sure respondents heard all the elements of the questions, to convey to respondents the importance of the questions, and to give respondents time to begin their memory search before the questions were finished. Fifth, interviewers were trained to use feedback probes aimed at encouraging active memory search. A nondirective reinforcing feedback probe such as “thanks, that’s very useful,” for example, was periodically used when the respondent appeared to be taking his or her time to think before answering. This sort of probe was used regardless of whether the respondent answered yes or no to the question. A corrective probe such as “You answered that one awfully quickly. Are you sure there’s not something you forgot?” was used if the respondent appeared to be giving a superficial answer. Sixth, the stem questions were presented to respondents as a set on a card as a visual aid aimed at improving question comprehension and focus.
A field experiment carried out in conjunction with the NCS showed that this set of six strategies, when combined, leads to a dramatic decrease in diagnostic under-reporting bias as well as to an associated increase in concordance with diagnoses based on clinical reappraisal interviews.34 Indeed, there were no statistically significant differences in this experiment between prevalence estimates based on the version of the CIDI that used these methodological strategies and prevalence estimates based on blind clinical interviews for twelve of fourteen DSM-III-R diagnoses. Furthermore, an independent investigation showed that the prevalence estimates obtained in a single interview that used these methodological strategies very closely reproduced prevalence estimates obtained by combining data over two waves of a similar fully structured interview that did not use these strategies.59
Based on these results, one would expect, all else equal, that the ESEMeD prevalence estimates would be more strongly concordant with independent clinical diagnoses and higher than the estimates in previous surveys based on the DIS and CIDI. An ESEMeD clinical reappraisal sub-study will eventually allow us to make a definitive evaluation of the first of these two expectations. However, the data from this sub-study are still being cleaned and coded and probably will not be thoroughly analyzed for another year.
The second expectation, that the ESEMeD prevalence estimates should be higher than in previous surveys, all else being equal, can be evaluated now based on the results in Figure 1 and and2.2. Prevalence estimates in the ESEMeD surveys are roughly comparable with those of earlier surveys. In considering this result, we must recognize that the ESEMeD prevalence estimates differ in at least one important respect from those obtained in earlier surveys: the ESEMeD surveys, as a component of the larger WHO World Mental Health Survey Initiative, are among the first large-scale international community epidemiological surveys to base prevalence estimates on DSM-IV criteria. Previous DIS and CIDI surveys primarily used DSM-II and DSM-III-R criteria. This is important because DSM-IV criteria are more strict than those in previous versions of the DSM as a result of the more prominent emphasis on the requirement that a syndrome must be associated with clinically significant distress or impairment to qualify as a disorder. Controversy exists as to the wisdom of this requirement, based on the observation that many serious medical conditions such as hypertension and hypercholesterolemia do not cause meaningful impairment until many years after they begin.64 In any event, this difference means that we would expect a downward drift in ESEMeD prevalence estimates compared with earlier surveys.
Another methodological issue that may also have played an important part in creating under-estimation of prevalence in the ESEMeD surveys involves fundamental survey conditions. Four fundamental survey conditions of the ESEMeD surveys are especially relevant here. First, the ESEMeD interviews were both longer (an average administration time of about two hours) and much more variable in length (ranging between forty-five minutes for a respondent who denied all diagnostic stem questions to as much as four hours for a respondent who endorsed all the stem questions and had a complex psychiatric history) than the typical market research interviews that the professional interviewers who conducted the ESEMeD surveys were used to carrying out. Second, the interviewers were paid by the interview rather than by the hour and generally did not receive any additional compensation for a long interview. Third, the stem-branch structure of the CIDI creates an opportunity for interviewers to guarantee that the interview will be short merely by entering negative responses to the small number of diagnostic stem questions that guide the interview skip logic. Bias of this sort can occur either by interviewers consciously entering negative responses even when respondents answer the stem questions affirmatively or by more subtle methods that involve using voice tone or speed of reading the questions or incorrect use of the feedback probes to induce negative responses to the stem questions. Fourth, the interviewer quality control procedures used in the ESEMeD surveys did not adequately guard against this type of downward recording bias. The required controls include supervisor monitoring of the clock in the computerized software used to administer the ESEMeD interviews to make sure that diagnostic stem questions were not rushed through and supervisor telephone recontact of a high proportion of respondents shortly after the completion of their interviews to repeat diagnostic stem questions and make sure that positive responses were correctly elicited and accurately recorded. It should be noted that the ESEMeD investigators specifically contracted survey firms that had carried out surveys with similar quality control requirements, but the firms did not implement these procedures with the rigor required to prevent bias.
Preliminary data files only became available to the ESEMeD coordinating center in Spain midway through the completion of the data collection. Staff of the coordinating center immediately detected problems of the sort described in the last paragraph when they were able to inspect the data. The ESEMeD committee made truly heroic efforts to correct the most egregious of these problems, including discarding a nearly complete survey in one country, based on evidence that an interviewer was cheating, and conducting the survey afresh with new fundamental survey conditions designed to prevent a repeat of the same problems. However, it must be acknowledged that there is no foolproof method of guarding against subtle forms of these problems when interviewers have financial disincentives for long interviews. The only truly foolproof method to deal with this problem is to pay interviewers in a way that removes any incentive to decrease the duration of the interview. Paying interviewers by the hour or providing a financial bonus for long interviews over and above a per-interview payment are the two most reasonable approaches of this sort. ESEMeD used the second of these methods in some countries once it became clear that downward bias was a serious problem. It is almost certainly the case, though, that some residual downward bias remains in the data, although we have no way of knowing how large this bias might be.
The considerations raised in the last section suggest that the ESEMeD prevalence estimates might reasonably be interpreted as valid lower bounds on the true prevalence of DSM-IV disorders. Even if this tentative conclusion is accepted, though, it remains important to confront the issue of practical validity: whether these estimates define the people in need of treatment for mental disorders. Ever since the ECA study two decades ago estimated that one-third of people in the general population of the US meet criteria for a DSM-III mental disorder at some time in their lives, critics have argued that these estimates are of little value for policy planning purposes because they encompass a much higher proportion of the population than could possibly be helped with available treatment resources.65 As reported in the last section, we now know from numerous methodological studies that the prevalence estimates in these lay interview surveys either under-estimate or are consistent with those obtained in blind clinical interviews. However, this is irrelevant to the question of practical validity, as critics who focus on practical validity call into question the over-inclusiveness of the DSM and ICD systems more than the surveys that attempt to operationalize the diagnoses in these systems. In recognition of the problem that the number of people meeting criteria for mental disorders exceeds currently available treatment resources, several more restrictive definitions have been proposed that can be used to reduce the number of people qualifying for treatment. In the US, for example, the National Institute for Mental Health’s National Advisory Mental Health Council distinguished people with Severe and Persistent Mental Illness (SPMI) from other mentally ill people and suggested that SPMI be the focus of efforts to provide universal mental health insurance coverage regardless of ability to pay.66 Many health plans in the US have followed suit by restricting payment of mental health treatment to people with a subset of DSM disorders that they consider to be either very serious or “biologically-based.”
This is a complex issue in at least two ways. First, it is not obvious how to define severity. Multiple dimensions of functioning are affected by mental disorders and no clear rules exist for calibrating levels across these dimensions. In addition, current distress and functioning are not the only considerations, as patients who are currently functioning quite well, might nonetheless be at extremely high risk of serious future problems based on their risk profile. Second, severity should not be the only criterion for deciding whether a person with a mental disorder needs treatment, as it is often possible to treat mild conditions with simple short-term treatments (e.g., behavioral treatment of specific phobia). Instead, the problem of unmet need for treatment should be addressed by developing comprehensive triage rules that allocate available resources based on evidence-based assessments of the cost-effectiveness of available treatments across the severity threshold of the disorder. Severity gradients are widely used in this way in other branches of medicine.67 In the absence if such rules, which currently do not exist, ad hoc decision-making is inevitable.
In light of these considerations, it would be very useful for policy planning purposes if epidemiological surveys distinguished cases that vary in severity. Consider, for example, the finding in the US WMH survey that only 21.7% of the US citizens who met criteria for DSM-IV Major Depressive Disorder (MDD) in the 12 months before the interview received adequate 12-month health care treatment for that illness.68 This might be seen as a source of considerable concern by policy-makers in light of evidence that MDD is a seriously impairing disorder31 that usually responds quite well to treatment.69 However, this result is seen in a somewhat different light when we examine the effects of severity [as assessed by a fully structured version of a standard clinical severity scale70] on probability of obtaining adequate treatment (Table 1). This shows that 39.1% of people with very severe MDD received adequate treatment, while adequate treatment was successively less common at lower levels of severity. Based on even a superficial consideration of these results, one quickly comes to the conclusion that the summary measure of 21.7% is of little value.
Table 1
Table 1
The proportion of respondents with 12-month MDD who received adequate treatment as a function of symptom severity,1 US WMH Survey (n=514)
A great strength of the ESEMeD surveys is that they, like all the WMH surveys, contain very detailed assessments of symptom severity and role impairment. Some ESEMeD data on role impairment were presented in this special issue. However, no results have yet been reported regarding the structured screening versions of standard symptom severity measures that were embedded in the ESEMeD surveys. Included here, for example, are structured screens that are able to assign approximate scores on the Hamilton Rating Scale for Depression71 and the Panic Disorder Severity Test.72
Furthermore, we await the use of information about role impairment and symptom severity to classify cases in terms of overall clinical severity. This is of most importance in the examination of treatment. While the ESEMeD results show clearly that only a minority of respondents with recent anxiety or mood disorders received treatment, we do not yet know whether this is true among people with serious or severe disorders. This kind of disaggregated analysis of treatment as a function of clinical severity should be a high priority for future ESEMeD analyses.
Although the last few paragraphs focused on the importance of distinguishing between mild and more serious cases, it is important for the ESEMeD analyses to retain information about mild cases even though treatment guidelines, once they are developed, will probably define treatment of mild cases as currently not being cost-effective. It is important to keep these mild cases in analyses both to acknowledge that mental disorders, like physical disorders, vary in severity and also to remind us that the development of cost-effective treatments for mild disorders might prevent a substantial proportion of future serious disorders.
This last point is nicely illustrated in a recently completed investigation that was carried out in the longitudinal component of the US National Comorbidity Survey follow-up (NCS-2).73 This component used the WMH-CIDI to re-interview a nationally representative sample of 4375 respondents who participated a decade earlier in the baseline NCS. For purposes of this analysis, overall baseline 12-month prevalence was classified in terms of clinical severity: mild, moderate, serious, and severe cases. Over half of all cases were found to be mild. The researchers then went on to examine clinical outcomes indicative of serious mental illness over the subsequent decade, such as hospitalization for an emotional problem and a suicide attempt. Summary results are presented in Table 2. There is a clear gradient in risk of serious outcomes associated with baseline clinical severity. However, risk of the outcomes is consistently elevated among baseline mild cases compared with non-cases. Furthermore, because of the much larger number of baseline mild cases than either moderate or serious cases, the Population Attributable Risk Proportions (PARP) of these outcomes due to mild cases (10.8–12.9%) are very similar in magnitude to those associated with baseline moderate (7.8–13.7%) and serious (10.7–12.2%) cases.
Table 2
Table 2
The Associations (Odds-Ratios) of Baseline (1990–92) Illness Severity with Serious Outcomes a Decade Later (2000–02), National Comorbidity Survey Follow-up, (n=4375)1
As mentioned previously, formal cost-effectiveness analysis will presumably find that currently available treatments are not cost-effective for the treatment of mild cases. This is true both because many forms of psychiatric treatment are more effective in reducing serious symptoms than in resolving mild symptoms and because the fact that mild cases cause only a small reduction in quality of life means that the cost savings of successful treatment will be calculated as being low. The results in Table 2 remind us, though, that we need to include risk of future serious outcomes in addition to current quality of life in cost-effectiveness calculations. Furthermore, as new treatments that might be more effective and less expensive become available, cost-effectiveness results can change dramatically. The WMH-CIDI was designed with this thought in mind, recognizing that cost-effectiveness thresholds can change over time and, with them, definitions of unmet need for treatment. This was an important reason for including extensive disorder-specific data on symptom severity and role impairment in the instrument. The policy relevance of ESEMeD will be increased substantially if these data are used to refine the characterization of the descriptive epidemiology of mental disorders in Europe.
The brief overview presented in this paper of previous psychiatric epidemiological surveys in the same tradition as the ESEMeD surveys shows that the preliminary ESEMeD findings are generally quite consistent with previous research. There remains great potential for the ESEMeD surveys, as part of the larger WHO WMH Survey Initiative, to go beyond previous epidemiological findings and increase the policy relevance of results. Early work of this sort has already been completed74 and additional work is underway. A number of key analyses still need to be carried out, especially basic comparisons of descriptive pooled cross-national data (e.g. analysis of age of onset distributions and trends in prevalence over successive cohorts) to other survey results.
Completion of the ESEMeD clinical reappraisal analyses to compare prevalence estimates based on the fully structured WMH-CIDI with blind clinical diagnoses obtained in re-interviews with selected ESEMeD respondents would also be useful. Ultimately the richness of the data captured by ESEMeD using WMH-CIDI with respect to pathways and characteristics of treatment had the potential to provide important guidance regarding public health interventions that could increase treatment by influencing demand or removing barriers to treatment.
Figure 4
Figure 4
Age of onset distributions for any mood disorders in the International Consortium in Psychiatric Epidemiology surveys
Acknowledgments
The author thanks Kathleen Merikangas and Bedirhan Ustun for commenting on an earlier version of this paper.
Footnotes
The material published in this supplement is derived from the proceedings of the meeting “ESEMeD – Benefit to the Community in Depression and Anxiety”, held on September 5, 2003 in Cliveden, Berkshire, UK. The meeting was supported by an unrestricted educational grant from GlaxoSmithKline Pharmaceuticals.
Preparation of this paper was carried out in conjunction with the author’s work as the Co-Director, with Bedirhan Ustun, of the World Health Organization’s World Mental Health (WMH) survey initiative. We thank the staff of the WMH Data Collection and Data Analysis Coordination Centres for assistance with instrumentation, fieldwork, and consultation on data analysis. These activities were supported by the 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 DA016558), 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. A complete list of WMH publications can be found at http://www.hcp.med.harvard.edu/wmh/.
1. Comstock GW, Helsing KJ. Symptoms of depression in two communities. Psychol Med. 1976;6:551–563. [PubMed]
2. Helgason T. Epidemiology of mental disorders in Iceland. Acta Psychiatr Scand Suppl. 1964;173:115–132.
3. Lin TY. A study of incidence of mental disorders in Chinese and other cultures. Psychiatry. 1953;16:315–335.
4. Robins LN, Helzer JE, Croughan JL, Ratcliff KS. National Institute of Mental Health Diagnostic Interview Schedule: Its history, characteristics and validity. Arch Gen Psychiatry. 1981;38:381–389. [PubMed]
5. Robins LN, Regier DA. Psychiatric Disorders in America: the Epidemiologic Catchment Area Study. New York, NY: Free Press; 1991.
6. Bland RC, Orn H, Newman SC. Lifetime prevalence of psychiatric disorders in Edmonton. Acta Psychiatr Scand Suppl. 1988;338:24–32. [PubMed]
7. Canino GJ, Bird HR, Shrout PE, et al. The prevalence of specific psychiatric disorders in Puerto Rico. Arch Gen Psychiatry. 1987;44:727–735. [PubMed]
8. Hwu HG, Yeh EK, Cheng LY. Prevalence of psychiatric disorders in Taiwan defined by the Chinese diagnostic interview schedule. Acta Psychiatr Scand. 1989;79:136–147. [PubMed]
9. Lee CK, Kwak YS, Yamamoto J, et al. Psychiatric epidemiology in Korea: Part I. Gender and age differences in Seoul. J Nerv Ment Dis. 1990;178:242–246. [PubMed]
10. Lépine JP, Lellouch J, Lovell A, et al. Anxiety and depressive disorders in a french population: Methodology and preliminary results. Psychiatr Psychobiol. 1989;4:267–274.
11. Wells JE, Bushnell JA, Hornblow AR, Joyce PR, Oakley-Browne MA. Christchurch Psychiatric Epidemiology Study, part I: methodology and lifetime prevalence for specific psychiatric disorders. Aust N Z J Psychiatry. 1989;23:315–326. [PubMed]
12. Wittchen H-U, Essau CA, von Zerssen D, Krieg CJ, Zaudig M. Lifetime and six-month prevalence of mental disorders in the Munich Follow-up Study. Eur Arch Psychiatry Clin Neurosci. 1992;241:247–258. [PubMed]
13. Cross-National Collaborative Group. The changing rate of major depression: cross-national comparisons. JAMA. 1992;268:3098–3105. [PubMed]
14. Weissman MM, Bland RC, Canino GJ, et al. Cross-national epidemiology of major depression and bipolar disorder. JAMA. 1996;276:293–299. [PubMed]
15. Weissman MM, Bland RC, Canino GJ, et al. The cross-national epidemiology of panic disorder. Arch Gen Psychiatry. 1997;54:305–309. [PubMed]
16. Robins LN, Wing J, Wittchen H-U, et al. The Composite International Diagnostic Interview: An epidemiologic instrument suitable for use in conjunction with different diagnostic systems and in different cultures. Arch Gen Psychiatry. 1988;45:1069–1077. [PubMed]
17. Wittchen H-U. Reliability and validity studies of the WHO Composite International Diagnostic Interview (CIDI): A critical review. J Psychiatr Res. 1994;28:57–84. [PubMed]
18. World Health Organization. Composite International Diagnostic Interview (CIDI) Version 1.0. Geneva: World Health Organization; 1990.
19. World Health Organization. Composite International Diagnostic Interview (CIDI) Version 2.1. Geneva: World Health Organization; 1997.
20. Wittchen H-U. Early developmental stages of psychopathology study (EDSP): objectives and design. Eur Add Res. 1998;4:18–27.
21. Vega WA, Kolody B, Aguilar-Gaxiola S, Alderete E, Catalano R, Caraveo-Anduaga JJ. Lifetime prevalence of DSM-III-R psychiatric disorders among urban and rural Mexican Americans in California. Arch Gen Psychiatry. 1998;55:771–778. [PubMed]
22. Kýlýç C. Mental Health Profile of Turkey: Main report. Ankara: Ministry of Health Publications; 1998.
23. Kessler RC, McGonagle KA, Zhao S, et al. Lifetime and 12-month prevalence of DSM-III-R psychiatric disorders in the United States: Results from the National Comorbidity Survey. Arch Gen Psychiatry. 1994;51:8–19. [PubMed]
24. Caraveo J, Martinez J, Rivera B. A model for epidemiological studies on mental health and psychiatric morbidity. Salud Mental. 1998;21:48–57.
25. Bijl RV, van Zessen G, Ravelli A, de Rijk C, Langendoen Y. The Netherlands Mental Health Survey and Incidence Study (NEMESIS): objectives and design. Soc Psychiatry Psychiatr Epidemiol. 1998;33:581–586. [PubMed]
26. Andrade L, de Lolio C, Gentil V, Laurenti R, Werebe D. Lifetime prevalence of mental disorders in a catchment area in Sao Paulo, Brazil. Paper presented at: VII Congress of the International Federation of Psychiatric Epidemiology; August, 1996; Santiago, Chile.
27. Alegria M, Bijl RV, Lin E, Walters EE, Kessler RC. Income differences in persons seeking outpatient treatment for mental disorders: A comparison of the US with Ontario and the Netherlands. Arch Gen Psychiatry. 2000;57:383–391. [PubMed]
28. Andrade L, Caraveo-Anduaga JJ, Berglund P, et al. The epidemiology of major depressive episodes: results from the International Consortium of Psychiatric Epidemiology (ICPE) Surveys. Int J Methods Psychiatr Res. 2003;12:3–21. [PubMed]
29. Bijl RV, de Graaf R, Hiripi E, et al. The prevalence of treated and untreated mental disorders in five countries. Health Aff (Millwood) 2003;22:122–133. [PubMed]
30. International Consortium of Psychiatric Epidemiology. Cross-national comparisons of the prevalences and correlates of mental disorders: an ICPE study. Bull World Health Organ. 2000;78:413–426. [PubMed]
31. Wang PS, Simon GE, Kessler RC. The economic burden of depression and the cost-effectiveness of treatment. Int J Methods Psychiatr Res. 2003;12:22–33. [PubMed]
32. Kessler RC, Mroczek DK, Belli RF. Retrospective adult assessment of childhood psychopathology. In: Shaffer D, Lucas CP, Richters JE, editors. Diagnostic Assessment in Child and Adolescent Psychopathology. New York, NY: Guilford Press; 1999. pp. 256–284.
33. Kessler RC, Wittchen H-U, Abelson J, Zhao S. Methodological issues in assessing psychiatric disorder with self-reports. In: Stone AA, Turrkan JS, Bachrach CA, Jobe JB, Kurtzman HS, Cain VS, editors. The Science of Self-Report: Implications for Research and Practice. Mahwah, NJ: Lawrence Erlbaum Associates; 2000. pp. 229–255.
34. Kessler RC, Wittchen H-U, Abelson J, et al. Methodological Studies of the Composite International Diagnostic Interview (CIDI) in the US National Comorbidity Survey. Int J Methods Psychiatr Res. 1998;7:33–55.
35. Wittchen H-U, Lachner G, Wunderlich U, Pfister H. Test-retest reliability of the DSM-IV version of the M-CIDI. Soc Psychiatry Psychiatr Epidemiol. 1998;33:568–578. [PubMed]
36. Kessler RC, Ustun TB. The World Mental Health (WMH) Survey Initiative Version of the World Health Organization (WHO) Composite International Diagnostic Interview (CIDI) Int J Methods Psychiatr Res. 2004;13:93–121. [PubMed]
37. Kessler RC, Ustun TB. The World Health Organization World Mental Health 2000 Initiative. Hospital Management International. 2000:195–196.
38. Alonso J, Angermeyer MC, Bernert S, et al. Prevalence of mental disorders in Europe: results from the European Study of the Epidemiology of Mental Disorders (ESEMeD) project. Acta Psychiatr Scand Suppl. 2004:21–27. [PubMed]
39. Kessler RC. The prevalence of psychiatric comorbidity. In: Wetzler S, Sanderson WC, editors. Treatment Strategies for Patients with Psychiatric Comorbidity. New York, NY: John Wiley & Sons, Inc; 1997. pp. 23–48.
40. Merikangas KR, Angst J, Eaton WW, et al. Comorbidity and boundaries of affective disorders with anxiety disorders and substance misuse: results of an international task force. Br J Psychiatry. 1996;168:58–67.
41. Sartorius N, Ustun TB, Lecrubier YH-UW. Depression comorbid with anxiety: results from the WHO study on psychological disorders in primary health care. Br J Psychiatry. 1996;168:38–43. [PubMed]
42. Maser JD, Cloninger CR. Comorbidity of mood and anxiety disorders. Washington, DC: American Psychiatric Press; 1990.
43. Alonso J, Angermeyer MC, Bernert S, et al. 12-Month comorbidity patterns and associated factors in Europe: results from the European Study of the Epidemiology of Mental Disorders (ESEMeD) project. Acta Psychiatr Scand Suppl. 2004:28–37. [PubMed]
44. Kessler RC, Frank RG. The impact of psychiatric disorders on work loss days. Psychol Med. 1997;27:861–873. [PubMed]
45. Kouzis AC, Eaton WW. Emotional disability days: Prevalence and predictors. Am J Public Health. 1994;84:1304–1307. [PubMed]
46. DuPont RL, Rice DP, Miller LS, Shiraki SS, Rowland CR, Harwood HJ. Economic costs of anxiety. Anxiety. 1996;2:167–172. [PubMed]
47. Greenberg PE, Sistisky T, Kessler RC. The economic burden of anxiety disorders in the 1990's. J Clin Psychiatry. 1999;60:427–435. [PubMed]
48. Simon GE, Barber C, Birnbaum HG, et al. Depression and work productivity: The comparative costs of treatment versus nontreatment. J Occup Environ Med. 2001;43:2–9. [PubMed]
49. Hollingshead AB, Redlich FC. Social Class and Mental Illness: A Community Study. New York, NY: John Wiley & Sons, Inc; 1958.
50. Srole L, Langner TS, Michael ST, Opler MK, Rennie TA. Mental Health in the Metropolis: The Midtown Manhattan Study. New York, NY: McGraw-Hill; 1962.
51. Christiana JM, Gilman SE, Guardino M, et al. Duration between onset and time of obtaining initial treatment among people with anxiety and mood disorders: an international survey of members of mental health patient advocate groups. Psychol Med. 2000;30:693–703. [PubMed]
52. Anthony JC, Folstein M, Romanoski AJ, et al. Comparison of the lay Diagnostic Interview Schedule and a standardized psychiatric diagnosis. Experience in Eastern Baltimore. Arch Gen Psychiatry. 1985;42:667–675. [PubMed]
53. Helzer JE, Spitznagel EL, McEvoy L. The predictive validity of lay Diagnostic Interview schedule diagnoses in the general population: A comparison with physician examiners. Arch Gen Psychiatry. 1987;44:1069–1077. [PubMed]
54. Robins LN, Helzer JE, Ratcliff KS, Seyfried W. Validity of the Diagnostic Interview Schedule, Version II: DSM- III diagnoses. Psychol Med. 1982;12:855–870. [PubMed]
55. Wittchen H-U, Kessler RC, Zhao S, Abelson J. Reliability and clinical validity of UM-CIDI DSM-III-R generalized anxiety disorder. J Psychiatr Res. 1995;29:95–110. [PubMed]
56. Wittchen HU, Kessler RC. The UM-CIDI: Rationale, Options, Modifications, and Technical Equivalence to the CIDI. Max Planck Institute of Psychiatry (Munich) 1996
57. Wittchen HU, Zhao S, Abelson JM, Abelson JL, Kessler RC. Reliability and procedural validity of UM-CIDI DSM-III-R phobic disorders. Psychol Med. 1996;26:1169–1177. [PubMed]
58. Landis JR, Koch GG. The measurement of observer agreement for categorical data. Biometrics. 1977;33:159–174. [PubMed]
59. Regier DA, Kaelber CT, Rae DS, et al. Limitations of diagnostic criteria and assessment instruments for mental disorders: Implications for research and policy. Arch Gen Psychiatry. 1998;55:109–115. [PubMed]
60. Cannell CF, Marquis KH, Laurent A. A summary of studies of interviewing methodology. Vital Health Stat 1: Programs & Collection Procedures. 1977;Series 2:i–viii. 1–78.
61. McFarland C, Buehler R. The impact of negative affect on autobiographical memory: the role of self-focused attention to moods. J Pers Soc Psychol. 1998;75:1424–1440. [PubMed]
62. Knauper B, Cannell CF, Schwarz N, Bruce ML, Kessler RC. Improving the accuracy of major depression age of onset reports in the US National Comorbidity Survey. Int J Methods Psychiatr Res. 1999;8:39–48.
63. Cannell CF, Miller PV, Oksenberg L. Research on interviewing techniques. In: Leinhardt S, editor. Sociological Methodology 1981. San Francisco, CA: Jossey-Bass; 1981. pp. 389–437.
64. Wakefield JC, Spitzer RL. Lowered estimates-but of what? Arch Gen Psychiatry. 2002;59:129–130. [PubMed]
65. Narrow WE, Rae DS, Robins LN, Regier DA. Revised prevalence estimates of mental disorders in the United States: using a clinical significance criterion to reconcile 2 surveys' estimates. Arch Gen Psychiatry. 2002;59:115–123. [PubMed]
66. National Advisory Mental Health Council. Health care reform for Americans with severe mental illnesses: report of the National Advisory Mental Health Council. Am J Psychiatry. 1993;150:1447–1465. [PubMed]
67. Anonymous Summary of the second report of the National Cholesterol Education Program (NCEP) Expert Panel on Detection, Evaluation, and Treatment of High Blood Cholesterol in Adults (Adult Treatment Panel II)[comment] JAMA. 1993;269:3015–3023. [PubMed]
68. Kessler RC, Berglund P, Demler O, et al. The epidemiology of major depressive disorder: results from the National Comorbidity Survey Replication (NCS-R) JAMA. 2003;289:3095–3105. [PubMed]
69. Esposito K, Goodnick P. Predictors of response in depression. Psychiatr Clin North Am. 2003;26:353–365. [PubMed]
70. Rush AJ, Trivedi MH, Ibrahim HM, et al. The 16-Item Quick Inventory of Depressive Symptomatology (QIDS), clinician rating (QIDS-C), and self-report (QIDS-SR): a psychometric evaluation in patients with chronic major depression. Biol Psychiatry. 2003;54:573–583. [PubMed]
71. Hamilton M. Development of a rating scale for primary depressive illness. Br J Soc Clin Psychol. 1967;6:278–296. [PubMed]
72. Houck PR, Spiegel DA, Shear MK, Rucci P. Reliability of the self-report version of the panic disorder severity scale. Depress Anxiety. 2002;15:183–185. [PubMed]
73. Kessler RC, Merikangas KR, Berglund PA, Eaton WW, Koretz DS, Walters EE. Mild disorders should not be eliminated from the DSM-V. Arch Gen Psychiatry. 2003;60:1117–1122. [PubMed]
74. Demyttenaere K, Bruffaerts R, Posada-Villa J, et al. Prevalence, severity and unmet need for treatment of mental disorders in the World Health Organization World Mental Health surveys. JAMA. 2004;291:2581–2590. [PubMed]