Epidemiology of Mental Disorders: The Current Agenda
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1 Epidemiologic Reviews Copyright 2000 by The Johns Hopkins University School of Hygiene and Public Health All rights reserved Vol. 22, No. 1 Printed in U.S.A. Epidemiology of Mental Disorders: The Current Agenda Scott Henderson INTRODUCTION A great deal is now known about the prevalence of the major types of mental disorders among different age groups in the general populations of many countries, and a considerable amount is known about their likely causes (1, 2). In both domains the measurement of psychiatric morbidity in communities and the identification of etiologic factors the advances achieved internationally have exposed some deeply troubling problems in methodology. These problems must now be confronted. Meanwhile, there have been some promising new developments resulting from etiologic research on mental disorders and from largescale population interventions. THE MEASUREMENT OF PSYCHIATRIC MORBIDITY: EMERGING PROBLEMS There could have been little progress in psychiatric epidemiology during the 20th century without the development of two basic tools. The first was a clear specification of the clinical features that have to be present to justify a diagnosis of each mental disorder, irrespective of whether the person has received mental health services. Work on this nomenclature has progressed over approximately five decades (3), yielding the Classification of Mental and Behavioral Disorders in the International Classification of Diseases, Tenth Revision (ICD-10) (4) and its US counterpart, the American Psychiatric Association's Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition (DSM-IV) (5). These two tools provide a reasonably unambiguous specification of the necessary diagnostic features. Creation of these coding systems was a major methodological advance, because they Received for publication May 14,1999, and accepted for publication December 6, Abbreviations: CIDI, Composite International Diagnostic Interview; DSM-III-R, Diagnostic and Statistical Manual of Mental Disorders, Third Edition, Revised; DSM-IV, Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition; ICD-10, International Classification of Diseases, Tenth Revision. From the Centre for Mental Health Research, The Australian National University, Canberra ACT 0200, Australia. (Reprint requests to Dr. Scott Henderson at this address). provided the building bricks for the next stage construction of standardized interviews for the clinical assessment of large community samples. Examples of two contrasting types of assessment are 1) the Composite International Diagnostic Interview (CIDI) (6) and the automated computer-administered version of the CIDI (CIDI-Auto) (7), both designed for use by lay interviewers, and 2) the Schedules for Clinical Assessment in Neuropsychiatry (SCAN) (8), designed for use by clinicians. Laypersons' versus clinicians' assessments Instruments such as these have made it possible to assemble estimates of the national prevalence of mental disorders in a number of countries, using consistent diagnostic criteria. Examples include the large survey carried out in Finland by Lehtinen et al. (9); the National Comorbidity Survey, conducted in the United States (10); the National Survey of Psychiatric Morbidity, carried out in the United Kingdom (11); and the National Survey of Mental Health and Weil- Being, conducted in Australia (12, 13). In the course of these studies, two very interesting problems have come to light: poor agreement between lay and clinician-based assessments in community samples and unrealistically high prevalence rates in the general population. Standardized interviews conducted by laypersons, albeit after careful training, generate quite different results from standardized assessments made by clinicians. The first person to question the validity of the Epidemiologic Catchment Area studies was Parker (14), in an editorial entitled, "Are the lifetime prevalence estimates in the ECA Study accurate?" The issues he raised still await resolution. Brugha et al. (15) recently reported poor concordance between fully structured interviews (such as the CIDI) given by laypersons and semistructured assessments made by research clinicians in general population samples. In an editorial, they concluded, "A fundamental promise [sic] of the application of epidemiologic methods to psychiatry is the collection of reliable information about the burden of psychiatric morbidity in whole populations. Two generations of attempts to achieve 24
2 Epidemiology of Mental Disorders 25 this have led to limited progress. Future approaches are unlikely to be any more successful unless basic clinical judgements can be incorporated successfully in large-scale surveys by professional lay interviewers" (15, p. 1019). Wittchen et al. (16) had a different perspective on the CIDI and were unable to agree with the UK group. However, the poor agreement between instruments cannot be disputed. Even in situations where information has been obtained by one instrument (the CIDI-Auto) and then assembled into diagnoses according to the algorithms specified in the DSM-IV and ICD-10, the two diagnostic systems generate different prevalence rates for the same population sample, and they often identify different individuals as cases. In a sample deliberately enriched to contain approximately twice the expected number of cases usually found in general populations, Andrews et al. (17) reported that concordance between the two systems ranged from 83 percent for major depression to 33 percent for substance abuse. The overall agreement for any mental disorder was only 68 percent. In short, valid measurement of psychiatric disorders, as categorical entities, in community samples has proven to be a very difficult task. It has not been made easier by the existence of two classification systems that have been found to differ in their performance rather more than their creators would have intended. Much of this discordance is due to the use of arbitrary cutoffs, deceptively called diagnostic criteria, on what is typically a continuum of symptoms and signs. Many researchers are justifiably skeptical about the value, and indeed the validity, of diagnostic categories (2, 3, 18, 19). The "exaggerated estimate" problem The second issue to be resolved is that estimates of 1-year or 1-month prevalence of the major mental disorders, as found in several large population samples in industrialized countries, produce values that far exceed a realistic estimate of the numbers of persons needing mental health care (20-23). The 1-year prevalence of any mental disorder was just under 30 percent for DSM-III-R disorders in the National Comorbidity Survey, and prevalence was 18 percent for ICD-10 disorders in the Australian national survey; both studies used the CIDI. In the UK survey, which used a different instrument, the 1-week prevalence of ICD-10 nonpsychotic disorders was 15.6 percent. Despite the differing methodologies, including different age ranges, it is highly improbable that such high proportions of the adult public require mental health services. This is the "exaggerated estimate" problem noted by Henderson (23). As they stand, the prevalence rates are technically likely to be underestimates because of nonresponse in psychiatric surveys, a topic that is often discreetly neglected (24,25). Most of the large surveys have had response rates of approximately 80 percent or less; response rates are never higher than that. Thus, typically nothing is known about the 20 percent of the sample who were not examined, yet they are likely to have had a higher level of psychiatric morbidity than those who agreed to be examined and with whom an interview was completed. When Kessler et al. (25) used special incentives to increase the response rate in the National Comorbidity Survey, they found that prevalence estimates had to be increased by approximately 10 percent. The scientific challenge is to identify persons who are both unwell and disabled within the larger group of persons who may have enough symptoms to qualify as cases by international criteria but are less significant in terms of planning and funding services. On the other hand, there may be an administratively significant number of persons whose symptoms do not take them to the case level by the international criteria but are nevertheless significantly disabled by their symptoms in daily life. This is particularly likely in primary care settings. The current diagnostic criteria are ill-suited to the diagnosis of morbidity in primary care, having their provenance in the experience of psychiatrists in teaching hospitals or outpatient practice. There are at least three possible reasons for the "exaggerated estimate" problem: 1) The case-finding instruments may have too low a threshold, especially in the hands of nonclinician interviewers. 2) Some people may have many symptoms but the symptoms are largely manageable, either by the self or by others, in daily life; Foulds once proposed this (26) but was not taken seriously by epidemiologists. Too little is known about these noncomplaining patients. 3) Symptoms may be nonlinearly related to disablement, a possibility that deserves much more attention. Investigation of these three propositions is urgently needed. In ministries of health across the world and in influential international bodies such as the World Bank and the World Health Organization, it is now accepted that mental disorders are important in terms of human health and well-being, and that they are economically far from trivial. Therefore, epidemiologists are now being asked to produce believable estimates of unmet need. When epidemiologists have these estimates, stripped of exaggeration, they will have data that may reasonably be used to inform service administration and policy. The "exaggerated estimate" problem is causing difficulties in another area of epidemiologic research. If the standardized interviews currently being used in
3 26 Henderson general population studies incorrectly identify some persons as cases, etiologic research conducted in these studies is likely to be seriously disadvantaged. This applies whether the candidate causal factors are exposures from the person's social environment or genetic polymorphisms in the complex web of etiology. If phenotypes are incorrectly established, the search for causes will be jeopardized. The above discussion refers to a binary world of psychiatric morbidity in which the population is divided sharply but artificially into cases and noncases. That is not how mental disorders occur, either cross-sectionally or over time. Therefore, in both research and administrative contexts it may be useful to have continuous measures of symptoms and of disablement in daily functioning, in addition to categorical diagnoses. ETIOLOGY Ideas about the causes of mental disorders have changed strikingly in the last 100 years (27). They have swung from a strong emphasis on "hereditary taints" to a predominantly social paradigm that has prevailed during much of the 20th century. The dominance of the idea that exposures to the social environment are causal becomes clear when the variables typically used in psychiatric epidemiology are enumerated. First, there are the sociodemographic variables (age, race, sex, etc.). The expectation has been that the individual's experience will be influenced by each of these factors. Then there are exposures that have been favorite etiologic candidates: childhood separation from the mother or maternal loss, parental style, adverse life events, unemployment, migration, and extreme experiences. Progress in understanding the consequences of this whole range of exposures has been impressive (1, 2, 27-31). However, in retrospect, it seems that many investigators must have assumed that a human being is initially a tabula rasa on which the environment becomes progressively imprinted. A significant advance came through epidemiologic studies of large series of adult twins by Kendler and colleagues (32-34). They showed how genetic factors interact with environmental exposures in subtle ways to influence vulnerability. It is not simply that heredity is a causal factor in, for example, depressive disorder. There is also "genetic control of exposure to the environment," through which genes alter the probability that an individual will be exposed to a harmful environment, increasing the likelihood of a depressive disorder (32). Then there is "genetic control of sensitivity to the environment," in which many genes, each having only a small effect, influence how sensitive the individual will be to environmental stressors. Allelic association studies conducted collaboratively by psychiatric epidemiologists and molecular geneticists are now an area of burgeoning activity, recently summarized by Henderson and Blackwood (35). These studies stand in marked contrast to clinically based studies of genes with mendelian inheritance and a strong effect, where progress in the etiology of psychoses has been elusive. However, the allelic association/interactionist model has opened up, in Plomin's words, "a new wave of research that goes beyond nature versus nurture... to explore the developmental duet by which genotypes become phenotypes" (36, p. 161). From a population health perspective, the common mental disorders of anxiety, depression, and substance abuse are those of the greatest significance. For epidemiologic research on these disorders, a new wave of activity is developing in which our technical resources for clinical assessment albeit imperfect and for measuring environmental exposures in childhood and adult life can now be coupled with molecular genetics. This is a matter of profound significance for etiologic research, and probably for prevention. Henderson and Blackwood (35) have suggested directions in which future developments in psychiatric epidemiology are likely to lead us as a consequence of the rapid progress being made in molecular genetics. Completion of the Human Genome Project will lead to identification of the many genetic polymorphisms that confer vulnerability (or resistance) to common mental disorders. To the molecular geneticist, such disorders are quantitative traits, reflecting the concerted action of many genes. Using molecular genetics, epidemiologists will at last have an opportunity to include biologic variables in studies of the etiology of anxiety, depression, and alcohol abuse. The brain itself is not accessible to epidemiologists, but DNA can now be obtained from large population samples by means of a simple noninvasive cheek-swab. Henderson and Blackwood acknowledge the technical and methodological problems that are being confronted in this new field of epidemiology (35), but they also argue that bringing molecular genetics into psychiatric epidemiology will allow us to study the interaction between genetic polymorphisms and environmental exposures in determining phenotypes. The same prospect has been discussed by Heninger (37). LARGE-SCALE POPULATION INTERVENTIONS Health officials in many countries are now asking psychiatric epidemiologists to advise them on methods of reducing the prevalence of mental disorders. Some, much influenced by the work of Mrazek and Haggerty (38), go further by seeking to reduce incidence at the
4 Epidemiology of Mental Disorders 27 general population level and in primary care. Although such intentions are noble, they set the scene for applying what is already known in psychiatric epidemiology to the promotion of population health. In the design of such interventions, a recurrent issue is competition between the traditional strategy of targeting individuals or groups known to be at high risk and the population health approach described by Rose (39, 40), in which an attempt is made to alter the health or behavior of the entire population, regardless of individual risk. The former strategy carries both public and political appeal, but the latter is probably far more effective at a national level, as in the introduction of seat belts in preventing trauma from road accidents. The coming decades will bring new challenges to psychiatric epidemiologists to provide the scientific basis for these emerging national programs in mental health promotion and disease prevention. ACKNOWLEDGMENTS The author conveys his appreciation for critical reading of this paper by his colleagues at the Centre for Mental Health Research and by Gavin Andrews in Sydney, Australia. REFERENCES 1. Regier D, Burke JD. Epidemiology. In: Sadock BJ, Sadock VA, eds. Kaplan and Sadock's comprehensive textbook of psychiatry. 7th ed. New York, NY: Lippincott Williams and Wilkins, 2000: Henderson AS. The contribution of epidemiology to psychiatric aetiology. In: Gelder M, Andreasen N, L6pez-Ibor J, eds. The new Oxford textbook of psychiatry. New York, NY: Oxford University Press (in press). 3. Jablensky A. The nature of psychiatric classification: issues beyond ICD-10 and DSM-IV. Aust N Z J Psychiatr 1999;33: 137^4. 4. World Health Organization. The ICD-10 classification of mental and behavioural disorders: clinical descriptions and diagnostic guidelines. Geneva, Switzerland: World Health Organization, American Psychiatric Association. Diagnostic and statistical manual of mental disorders. Fourth Edition. Washington, DC: American Psychiatric Association, Robins LN, Wing J, Wittchen HU, 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: Peters L, Andrews G. Procedural validity of the computerized version of the Composite International Diagnostic Interview (CIDI-Auto) in the anxiety disorders. Psychol Med 1995;25: Wing JK, Babor T, Brugha T, et al. SCAN: Schedules for Clinical Assessment in Neuropsychiatry. Arch Gen Psychiatry 1990;47: Lehtinen V, Joukamaa M, Lahtela K, et al. Prevalence of mental disorders among adults in Finland: basic results from the Mini Finland Health Survey. Acta Psychiatr Scand 1990;81: Kessler RC, McGonagle KA, Zhao S, et al. Lifetime and 12- month prevalence of DSM-HJ-R psychiatric disorders in the United States: results from the National Comorbidity Survey. Arch Gen Psychiatry 1994;51: Jenkins R, Lewis G, Bebbington P, et al. The national psychiatric morbidity surveys of Great Britain initial findings from the household survey. Psychol Med 1997;27: Andrews G, Hall W, Teesson M, et al. The mental health of Australians. Canberra, Australia: Commonwealth Department of Health and Aged Care, Henderson S, Andrews G, Hall W. Australia's mental health: an overview of the population survey. Aust N Z J Psychiatr (in press). 14. Parker G. Are the lifetime prevalence estimates in the ECA Study accurate? (Editorial). Psychol Med 1987;17: Brugha TS, Bebbington PE, Jenkins R. A difference that matters: comparisons of structured and semi-structured psychiatric diagnostic interviews in the general population. (Editorial). Psychol Med 1999;29: Wittchen H-U, Ustiin TB, Kessler RC. 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Unmet need in psychiatry: problems, resources, responses. Cambridge, United Kingdom: Cambridge University Press, Gove WR, McCorkel J, Fain T, et al. Response bias in community surveys of mental health: systematic bias or random noise? Soc Sci Med 1976; 10: Kessler RC, Little RJ, Groves RM. Advances in strategies for minimizing and adjusting for survey nonresponse. Epidemiol Rev 1995;17: Foulds GA. The hierarchical nature of personal illness. New York, NY: Academic Press, Inc, 1976: Dohrenwend BR A psychosocial perspective on the past and future of psychiatric epidemiology. Am J Epidemiol 1998; 147: Parker G. Parental overprotection: a risk factor in psychosocial development. New York, NY: Grune and Stratton, Paykel ES, ed. Handbook of affective disorders. 2nd ed. New York, NY: The Guilford Press, Kessler RC. The effects of stressful life events on depression. Annu Rev Psychol 1997;48: Dohrenwend BR Adversity, stress, and psychopathology. 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5 28 Henderson events, genetic liability, and onset of an episode of major depression in women. Am J Psychiatry 1995;152: Henderson AS, Blackwood DH. Molecular genetics in psychiatric epidemiology: the promise and challenge. Psychol Med 1999;29: Plomin R. Beyond nature versus nurture. (Editorial). Int J Methods Psychiatr Res 1995;5: Heninger GR. Psychiatric research in the 21st century: opportunities and limitations. Mol Psychiatry 1999;4: Mrazek PJ, Haggerty RJ. Reducing risks for mental disorders: frontiers for preventive intervention research. Washington, DC: National Academy Press, Rose G. The strategy of preventive medicine. New York, NY: Oxford University Press, Rose G. Mental disorder and the strategies of prevention. (Editorial). Psychol Med 1993,23:553-5.
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