Adrian Angold and E. Jane Costello
Is conduct disorder a disorder?
Epidemiology is the study of the distribution of diseases and their causes and correlates in defined populations in time and space. It might be better to say that we study the distribution of ‘putative’ diseases (hereinafter referred to as
‘disorders’), because it often happens that what has been thought of as a single disease at one point in time is later recognized as a group of diseases with certain common clinical characteristics. On the other hand, some originally separate diseases come to be seen as being manifestations of a unitary underly-ing disease process. By a ‘disorder’ we mean a groupunderly-ing of symptoms, signs and pathological findings (a ‘syndrome’) that is deviant from some standard of
‘normality’. Disease status depends on the disorder being shown to have a distinctive genetic basis, etiology, physical pathology, particular prognosis or specific treatment response (Angold, 1988).
Many psychiatric disorders can be characterized as having a core group of key features around which other symptoms and impairments cluster. For instance, depressed mood is a key feature of depressive disorders. It may turn out that there are some individuals who ‘have’ a disorder but lack its key features, but such cases are anomalous. Conduct disorder (CD) is rather different, because it consists of a group of behaviours, none of which is conceptually central to our understanding of the disorder. The only require-ment is that individuals should manifest a lot of these behaviours if they are to be given the diagnosis. Even at the level of conceptual grouping, the items constituting conduct disorder are not immediately and self-evidently coherent.
Thus DSM–IV groups the items for Conduct Disorders into four categories: (1) aggressive conduct that causes or threatens physical harm to people or animals, (2) nonaggressive conduct that causes property loss or damage, (3) deceitful-ness or theft, and (4) serious violation of rules. To this we must add the four underlying constructs for DSM–IV Oppositional Defiant Disorder (ODD): (5)
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negativism, (6) defiance, (7) disobedience and (8) hostility. At best, we might say that conduct disorder consists of a group of behaviours that adults in legally constituted administrative authority do not like children to do. However, as we shall see, these different sorts of behaviour do tend to occur together in the same children, and there is evidence that such problems are associated with at least somewhat distinctive correlates and outcomes. Thus conduct disorder merits treatment as a disorder. The purpose of this chapter is to review the epidemiological evidence for its status as a disease (or group of diseases) and to identify problems that call for further research.
We identify four broad classes of research in the area: (1) early studies of individual behaviours, (2) factor analytic studies of problem behaviour, (3) studies of the diagnosis of conduct disorder or oppositional defiant disorder and (4) developmental studies of behavioural disturbance.
Studies of individual symptoms of behavioural disturbance
The earliest epidemiological studies of behavioural disturbance were simply surveys of the prevalence of individual types of disturbed behaviour. For instance, McFie (1934) questioned teachers about a range of problems in their 12–14-year-old pupils. She was surprised to find that 46.2% of children had at least one problem. The commonest ‘behaviour disorders’ were ‘lying, stealing, begging’ (3.4%), ‘bullying, quarrelling’ (2.4%), ‘shifty, unstable’ (2.4%), ‘rest-less, fidgety’ (2.1%), and ‘clowning, in limelight’ (2.0%). Cummings (1944) also used teachers as informants about 2–7-year-olds. Besides very high rates of symptoms of what we would now call attention deficit hyperactivity disorder (ADHD) symptoms, she found ‘aggressiveness’ in 10.9%, ‘lying’ in 8.4% and cruelty in ‘7.1%’ of these 2–7-year-olds. She also found that cruelty was more common in boys, and that the children of ‘parents constantly absent or neglectful’ were more likely to display antisocial symptoms. Thus, early on, it was established that individual ‘conduct problems’ were very common, that aggression was more common in boys than girls (see also Cullen & Boundy, 1966; Griffiths, 1952; Haggerty, 1925; Long, 1941; Olson, 1930; Young-Masten, 1938) and that these symptoms were associated with lax parenting. These two studies also illustrate a point that has perhaps been rather forgotten – that some conduct problems now associated with DSM–IV Conduct Disorder, like lying and some forms of aggression, actually have their peak prevalences by age 5 (not in adolescence), as shown in the California Guidance Study (Macfarlane et al., 1954) and by Griffiths (1952) (see Loeber & Stouthamer-Loeber, 1997 for a summary of more recent work on aggression in this regard). Even earlier work
(Wickman, 1928; Yourman, 1932) had indicated that teachers regarded overt behaviour disturbances as being more serious than withdrawn behaviour, and that such behaviour was associated with poor school performance (Haggerty, 1925; Yourman, 1932).
In the absence of clearly defined diagnostic categories, the authors of the studies considered above sometimes grouped symptoms on an ad hoc basis. In general, the presence of any one of a group resulted in the individual being classified as a member of that group. In effect a crude diagnosis was made on the basis of the presence of any one symptom. This was unsatisfactory, because it resulted in children who were obviously not really disturbed getting lumped in with children who gave their teachers, parents and themselves cause for considerable concern. In other words, this system failed to distinguish between naughty normal children and those with serious problems. One obvious solution to this problem was to count as ‘disturbed’ only those children who had a lot of problems (Haggerty, 1925; Olson, 1930). That required the use of some arbitrary cutpoints in the determination of how many children had conduct problems, but then so does any medical diagnostic system. However, it was also clear that different children had different kinds of problems, so just counting up the total number of symptoms of all types was also unsatisfactory.
But how to decide which symptoms to combine together for each ‘kind of problem’ scale (Olson, 1930)? The next section deals with factor analytic attempts to solve these problems of differentiating normal from abnormal and grouping symptoms for ‘diagnostic’ purposes.
Factor analytic studies of child behaviour problems
The factor analytic studies of clinical samples beginning in the 1940s (see Achenbach & Edelbrock, 1978 for a scholarly summary of the earlier work) started by focusing on adult (parent, teacher, case worker) reports of child problems, and were constrained by the requirements of the factor analytic methods usually employed – principal components or principal factor analysis with varimax rotation. Items were excluded from scales when they occurred rarely in the sample (in fewer than 5% of individuals for the Child Behavior Checklist (CBCL) for instance; Achenbach & Edelbrock, 1981), so instances of relatively uncommon, but highly problematic, behaviours (such as forced sex) were usually never asked about. We must also suppose that parents, teachers and case workers often did not know about their children’s covert antisocial activities, and so will have under-reported these aspects of behaviour.
The first notable finding is that there was a good deal of consistency in
findings across informants, measures and samples. The broad distinction be-tween ‘overcontrolled’, ‘internalizing’ or emotional disorders, and ‘undercon-trolled’, ‘externalizing’ or behavioural problems was identified everywhere, though other ‘broad band’ syndromes were also sometimes identified (Achen-bach & Edelbrock, 1978; Achen(Achen-bach et al., 1989; Crijnen et al., 1997; Verhulst, 1995; Verhulst & Achenbach, 1995). It was also clear that even though subscales were constructed so as to be statistically orthogonal (i.e. uncorrelated) as far as their item content was concerned, the dimensions represented by the factors are positively associated with one another in both clinically referred and nonreferred children (Garnefski & Diekstra, 1997; McConaughy & Achenbach, 1994; Verhulst & van der Ende, 1993).
Among the ‘narrow’ band factors that underlay the ‘broad band’ externaliz-ing factor two key syndromes often emerged, which we may call ‘aggressive conduct problems’ and ‘nonaggressive conduct problems’, although they have gone by many different names from study to study (Achenbach et al., 1989;
DeGroot et al., 1994). The important point is that there has long been evidence that physical aggression involves separate developmental pathways from those relating to nonaggressive behaviour problems, although these pathways are also clearly correlated. This literature, and extensions of it are also responsible for conduct disorder subtyping schemes that rely on patterns of peer relation-ships and social behaviour (Quay, 1986), such as the ICD–10 distinction between ‘unsocialized’ and ‘socialized’ conduct disorder. The former describes children with poor peer and adult relationships, who are also likely to be aggressive, while the latter included children who have good peer relationships and tend to engage in group oriented antisocial activities.
It is also important to note that the behaviour problem scales derived from this factor analytic work were all based on clinical or disturbed samples, rather than general population samples, so we can also expect them to have been biased by the nature of individuals referred to clinical services. For instance the scales of the CBCL were developed through factor analyses in clinical samples, and then nonclinical samples were used only to establish normalized distribu-tions of T scores for each scale (Achenbach, 1978; Achenbach & Edelbrock, 1979). It must also be remembered that the factors extracted depend on the items entered into the factor analysis, and that though different questionnaires often produce similar factors, there are also often notable differences. Consider for example Achenbach and colleagues’ conclusion that the CBCL did not produce a factor similar to the DSM category of Oppositional Defiant Disorder (Achenbach, 1980) in three large clinical samples from the USA and Holland. In contrast, the recent revisions of the Conners’ rating scale (CRS) found a factor
that very closely resembles operational defiant disorder (Conners, 1997), based on factors derived from relatively large nonclinical populations. Inspection of the two questionnaires reveals that the CBCL does not include many items relevant to the DSM construct of Operational Defiant Disorder, but that the CRS includes all the relevant items. On the other hand, the familiar ‘aggressive’
and ‘delinquent’ factors from the CBCL do not appear in the factor solutions from the CRS, but this is not surprising because a number of the relevant items are absent from the latter. The point here is that, just as whether a child receives an ICD–10 or DSM–IV diagnosis of Conduct Disorder is dependent on the definitions of Conduct Disorder given in the manuals of those nosologies, so the patterns of disturbance that emerge from factor analytic studies depend on the items included and the populations on which the subscales were developed. Neither method is purely ‘empirical’ since both depend on a priori conceptualizations of the phenomena that should be included in the original item pool from which either the questionnaire or the diagnostic category are eventually derived.
If the narrow band syndromes are correlated with one another, it is possible that the supposed underlying processes they represent are really just subsets of items that should properly be interpreted as being part of a single overarching process. It must be remembered that there is no unique best solution for a factor analysis – in fact such a solution is not even a theoretical possibility.
Rather each factor analyst presents what appears to him or her to be the best solution. Given that factor analytic attempts to parse psychopathology have been directed towards identifying coherent subsets of symptoms, they have emphasized descriptions of narrow band factors, rather than the associations among those factors.
As an example of what we mean here, consider the 48 items from the CBCL that we used as a screening tool in the Great Smoky Mountains Study (GSMS).
It was administered to a random sample of 3909 parents of 9-, 11- or 13-year-olds. Inspection of the item frequency tables indicated that 10 items occurred in fewer than 5% of the reports. These were Cruel to animals, Physically attacks people, Prefers older children, Runs away from home, Sets fires, Steals at home, Steals outside home, Truancy, Uses alcohol/drugs and Vandalism. If one adopts the usual factor analytic approach of excluding such relatively ‘rare’
items, it will not be surprising if a ‘conduct disorder’ factor fails to emerge – the key items that are involved in the construct will not have been included in the analysis! However, the statistical problem here is not determined by any particular percentage cutoff, but by having enough subjects with positive ratings to generate a reasonable estimate of the factor loadings of the items in
Fig. 6.1. Scree plot from PCA of GSMS screen.
question. We decided that we would only include items that were positively endorsed by at least 30 parents. This meant that four items were excluded:
Runs away from home, Uses alcohol or drugs, Vandalism and Truancy. Even so this means that we are still missing three important DSM–IV Conduct Disorder items. Be that as it may, we ran a principal components analysis (PCA), which resulted in the scree plot shown in Fig. 6.1 for the first ten factors for boys and girls separately. The scree plots suggest that a single factor solution may be the solution of choice, since the first factor has a much higher eigenvalue than any of the others and the others are all rather close together.
For neither boys nor girls did any factors other than the first explain more than 5% of the common variance. Examination of the factor loadings on this first unrotated factor showed that all but six of the items had loadings of at least 0.3, but each of these loaded positively on the first factor (the lowest loading was 0.17). One could well argue at this point that we are dealing with a unidimen-sional underlying problem scale involving all the items. However, the intention of previous factor analytic studies has been to identify separate dimensions underlying overall scores, so factor analysts have always gone on to rotate their solutions to produce multiple orthogonal factors. For illustrative purposes,
Fig. 6.2. Scree plot from ML FA of GSMS screen.
consider a three factor solution using varimax rotation. Our expectation from the clinical sample analyses from which the ‘official’ factor structure of the CBCL has been derived is that we should see clear ‘ADHD’, ‘aggressive’ and
‘delinquent’ factors. Items with factor loadings greater than 0.4 in boys are marked with an asterisk on the left hand side of Table 6.1. Factor 3 appears to be a clear ‘delinquency’ factor, but neither factor 1 nor factor 2 entirely fit the familiar clinical pattern. Factor 2 comes closest to unsocialized aggression, but includes several oppositional defiant disorder behaviours. Factor 1 represents a mixture of oppositional defiant disorder and ADHD behaviours.
Now compare these results with those from a maximal likelihood factor analysis (MLFA – a method that is statistically preferable with a large data set).
We note that in males the first unrotated factor accounts for 73% of the common variance (see Fig. 6.2), while in females it accounts for 76% of the common variance. The results of the three factor solutions for boys are given on the right hand side of Table 6.1. Factor 3 certainly appears to be an ‘ADHD’
factor. Factor 1 appears as an amalgam of ‘irritating and irritable behaviours’
that is reminiscent of some aspects of DSM–IV Oppositional Defiant Disorder.
Factor 2, however, is a clear mixture of both aggressive and delinquent behaviours, which is very reminiscent of DSM–IV Conduct Disorder.
However, in neither the PCA nor the MLFA do we see clear ‘hyperactivity’,
‘aggression’ and ‘delinquency’ factors. Note also that of the 64 component loadings greater than 0.4 only a minority are common to both three factor solutions, even when the factors most similar to each other are compared (rather than making comparisons between the pairs of first, second and third factors). For instance, the third factor emerges as a ‘pure’ ADHD dimension in the MLFA, while ADHD symptoms remain mixed in with a rag bag of other items in factor 1 in the PCA. On the other hand, the third component in the PCA is a relatively ‘pure’ ‘delinquency’ component, but no such component emerges in the MLFA.
So which is the ‘correct’ solution? The answer is that none is necessarily more correct than any other. Both one factor solutions are very similar, and we lean towards the MLFA analysis as far as the three factor solutions are concerned because it has some statistical advantages in large samples. How-ever, each analysis provides a particular view of the data. The single factor solutions remind us that all the items are correlated with one another. That we can extract what may be meaningful statistically orthogonal dimensions, which sometimes separate various components of ADHD, aggression and delin-quency means that we should take seriously the possibility that these may not be unitary components. But we should also recognize that the phenomena in the real world are not orthogonal. What the diagnostic literature calls comor-bidity is equally a phenomenon in the world of questionnaires. We need to realize that PCA and factor analysis are blunt tools for the development of a nosology. They can be very informative in the early stages of exploring the nature of psychopathological phenomena, and for the development of scales, but they will never lead to the identification of indisputable phenomenological dimensions. Much has been made of the advantages of ‘empirical’ classification based on PCA, but each of the solutions presented above could serve as the basis for such a classification, and in the end, the key factors in what that classification would look like would be (1) the initial choice of items to include in the analysis, (2) the choice of sample upon which to base the analysis, (3) subjective decisions as to which type of analysis produced the best results, and (4) subjective decisions as to what level of factor loading to use as a cutoff in deciding which items to include in each factor-based scale. There is nothing inherently more ‘empirical’ in this approach than in having a committee of experienced clinicians and researchers meet to decide on the content of the next DSM.
Table6.1.ThreefactorprincipalcomponentsanalysisandmaximumlikelihoodfactoranalysisoftheGSMSscreen PrincipalComponentsAnalysisMaximumLikelihoodFactorA Factor1Factor2Factor3Factor1Factor2F 52*1016Actstooyoung28134 48*39−1Arguesalot55*1322 312911Bragging,boasting332114 69*023Can’tconcentrate171277 67*916Can’tsitstill301160 03129Crueltoanimals1234 1261*28Cruelty,bullying,meanness3752* 52*344Demandsattention48*1731 312837Destroysownthings233828 1640*45*Destroysothers’things2152*19 42*45*16Disobedientathome53*2920 47*2830Disobedientatschool373234 2642*25Doesn’tgetalongwellwithothers2441*26 262223Doesn’tfeelguilty242318 3743*−4Easilyjealous45*1819 3350*4Feelsunloved42*2722 2753*14Othersouttogethim/her344023 1546*23Manyfights2441*16 331731Hangsoutwiththosewhogetintrouble222725 64*2121Impulsive42*2047 40*3045*Lyingorcheating3441*30
2182Bitesfingernails136 45*315Nervous,highlystrung,tense3619 193828Notlikedbyotherchildren1443* −452*34Physicallyattackspeople1453* 53*634Poorschoolwork1723 35169Poorlycoordinated,clumsy2015 19223Prefersolderchildren2112 2356*−3Screamsalot46*25 253113Secretive3320 21539Setsfires828 49*186Showingoff,clowning42*10 151362*Stealsathome1044* 6467*Stealsoutsidehome240 45*44*1Stubborn,sullen,irritable59*16 41*48*6Suddenmoodchanges53*24 3451*10Sulks51*28 1747*13Suspicious29341 183417Swearing3225 50*12−2Talkstoomuch344 35220Teases34101 3759*0Tempertantrums62*25 463*32Threatenspeople3257* 5−242*Truancy619 47*283Unusuallyloud42*15
Rates of conduct disorder using the ICD or DSM diagnostic systems
An alternative to factor analytic approaches to the diagnosis of conduct dis-order/oppositional defiant disorder is to predefine the disorder on the basis of current knowledge about the relationships among symptoms, and then to determine the prevalence of this ‘clinical syndrome’ in the general population.
The two principal diagnostic systems in use for the last 20 years have taken substantially different approaches to the diagnosis of disorders of conduct. In 1980 the Diagnostic and Statistical Manual of Mental Disorders, Third Edition (DSM–III) (American Psychiatric Association, 1980) introduced the diagnosis of oppositional disorder, requiring that two of five behaviours (violations of minor rules, temper tantrums, argumentativeness, provocative behaviour and stubbornness) be present for the diagnosis to be met (American Psychiatric Association, 1980, p. 35). The DSM–III criterion set included no indication of how often each of its constituent behaviours had to occur. The DSM–III–R (American Psychiatric Association, 1987) introduced such an indication by including the word ‘often’ in the specification of each criterion in an expanded group of nine criteria (of which five had to be present), and an important clarification in the statement ‘Consider a criterion met only if the behavior is considerably more frequent than that of most people of the same mental age’.
However, we know of only one study that has reported how often the individual criterion symptoms for oppositional defiant disorder occur in the general population (Angold & Costello, 1996). That study indicated that if
‘often’ was defined as being above the 90th general population percentile for the frequency of that behaviour, quite different frequency cutoffs were re-quired for different oppositional defiant disorder symptoms. DSM–IV (Ameri-can Psychiatric Association, 1994) continued to demand that the behaviours
‘often’ be present, but reduced the number of symptom criteria to eight (of which four must be present). The other criteria remain essentially unchanged except for minor differences in wording, as does the name oppositional defiant disorder introduced in the DSM–III–R. DSM–IV further states that the diag-nosis only applies if ‘The disturbance in behavior causes clinically significant impairment in social, academic, or occupational functioning’.
ICD–9 diagnoses (Rutter et al., 1979) were vaguely specified, but behaviours that constituted DSM Oppositional Defiant Disorder were included in the diagnosis of conduct disorder. This practice has continued in ICD–10, which, however, specified the diagnostic rules more precisely, so that ICD–10 Conduct Disorder is very similar to what would result from combining DSM–IV CD and ODD symptoms into a single criterion set. However, there is an important
difference hiding here. According to the ICD–10 scheme, the presence of any four (of 23) symptoms is sufficient for the diagnosis of the ICD–10 ODD subtype. Three more severe symptoms are required for the ICD–10 CD subtypes. Many ODD behaviours become less common between childhood and adolescence (Campbell, 1990; Loeber et al., 1991), while many CD behav-iours (especially covert behavbehav-iours) become more common (Farrington, 1986;
Farrington et al., 1990; Le Blanc & Fre´chette, 1989; Loeber, 1988). Given that the DSM–IV criteria for ODD and CD do not overlap in content, this means that it is possible for an individual who has previously met criteria for DSM–IV ODD, and who will later meet criteria for DSM–IV CD, to meet criteria for neither at an intermediate stage, despite having, say, three ODD symptoms and two CD symptoms at that point – a total of five relevant symptoms when ODD requires only four symptoms and CD only three. ICD–10 would allocate a diagnosis of the ODD subtype in such a case. To examine the effects of these classification rules, we categorized children in the Great Smoky Mountains Study into one of four exclusive categories – (1) those who met full DSM–IV for CD, (2) those who met full DSM–IV criteria for ODD, (3) those who met DSM–IV criteria for neither CD nor ODD, but met ICD–10 criteria for CD–
ODD subtype and (4) those who met none of these criteria. Across three waves of data covering ages 10–16 the rates of each of the CD groups was: DSM–IV CD – 2.2%, DSM–IV ODD – 1.6%, and ICD–10 only CD–ODD subtype – 2.8%.
Note that all of the individuals in the DSM–III–R CD and ODD groups would also have met criteria for ICD–10 CD. We may, therefore, suppose that other studies that have used the DSM–III, DSM–III–R or DSM–IV rules for diag-nosing disorders of conduct will have substantially underestimated (by around 40%) the numbers of individuals who have significant conduct problems according to the ICD–10 rules.
As if this were not sufficiently troublesome, the ICD-based studies also split disorders of conduct into pure conduct disorder and mixed disorders of conduct and emotions. The latter category roughly corresponds to DSM ODD or CD plus an emotional disorder diagnosis. So to arrive at an ICD-based estimate of CD we need to add the rates for pure CD and mixed disorders of conduct and emotions together. The rates for this combination were 3.4 in the Isle of Wight 10–11-year-olds (Rutter & Graham, 1966), and 4% in the Isle of Wight follow-up at ages 14–15. In these studies it was also found that the pure conduct disorders at age 10–11 were more likely to persist into adolescence than mixed disorders or pure emotional disorders (Graham & Rutter, 1973). A study from Mannheim found that 1.8% of 8-year-olds had a conduct disorder, compared with 8.4% at age 13 (Esser et al., 1990). Fombonne’s (1994) study in Chartres
Table6.2.Rateofdiagnosisandcomorbidityingeneralpopulationstudies Pop.Pop.RateofaRateofb StudyTimerateofarateofbRateofanotinbRateofbnotina (DSM)NAgeframe(%)(%)inb(%)(%)ina(%)(%)ORCI a=CD/ODDb=ADHD 1(III)792111yr9.16.747.27.134.74.411.66.3–21.5 2(III)943151yr9.02.120.08.84.71.92.60.85–8.0 5(III)2787–116mo9.82.354.68.713.01.212.63.6–44.1 6(III)27812–186mo13.912.246.99.441.07.58.63.8–48.7 10(III)2229–166mo10.51093.0—35.7—phi=0.47— 11(III–R)10159–133mo5.21.933.34.711.81.310.24.5–22.3 12(IV)97010–143mo4.81.035.54.57.50.6911.74.9–28.2 13(IV)92811–153mo3.30.922.13.15.80.78.72.0–37.9 14(IV)82012–163mo2.90.613.93.63.10.65.60.7–44.6 15(III–R)3239–133mo6.61.3256.34.81.04.90.49–49.6 16(IV)31710–143mo8.31.350.07.77.70.711.91.6–88.4 17(IV)30411–153mo5.01.0674.413.30.3543.73.7–513 18(IV)28912–163mo4.20.41003.98.30—— 19(III–R)986156mo10.84.8————26.813.7–52.4 20(III–R)27628–163mo4.31.4————3.20.9–8.7
a=CD/ODDb=Depression 1(III)792111yr9.11.878.68.715.30.4738.310.4–141 2(III)943151yr9.04.232.58.015.33.155.62.7–11. 3(III–R)930181yr5.518.07.25.123.517.61.40.74–2. 4(III)15014–161yr14.78.083.38.745.91.652.510.3–268 5(III)2787–111yr9.81.613.59.72.21.51.50.15–14 6(III–R)27812–186mo13.94.267.711.620.41.615.94.4–58. 7(III–R)7769–181yr7.13.423.76.610.92.84.31.6–11. 8(III–R)77611–201yr5.82.822.75.311.12.35.21.9–13. 9(III–R)171014–18curr1.82.98.01.612.92.75.31.8–15. 10(III)2229–166mo10.58.055.8—45.4—18.46.1–55. 11(III–R)10159–133mo5.21.528.94.88.41.18.012.8–22. 12(IV)97010–143mo4.93.125.74.316.02.47.82.6–23. 13(IV)92811–153mo3.43.242.92.041.41.936.211.1–118 14(IV)82012–163mo2.92.74.42.94.02.61.60.38–6. 15(III–R)3239–133mo6.50.3106.500.33—— 16(IV)31710–143mo8.21.660.07.411.50.718.83.0–118 17(IV)30411–153mo5.34.338.53.831.32.815.94.5–56. 18(IV)28912–163mo4.21.704.201.8—— 19(II–R)986156mo10.86.6————3.41.9–6.3 20(II–R)27628–163mo4.31.2————11.24.6–25.
Table6.2.(cont.) Pop.Pop.RateofaRateofb StudyTimerateofarateofbRateofanotinbRateofbnotina (DSM)NAgeFrame(%)(%)inb(%)(%)ina(%)(%)ORCI a=CD/ODDb=Anxiety 1(III)792111yr9.17.432.28.126.46.35.42.9–9.9 2(III)943151yr9.010.75.99.47.111.10.610.26–1.4 3(III–R)930181yr5.519.77.15.125.519.31.40.74–2.7 4(III)15014–161yr14.78.769.29.540.93.121.55.8–79.5 5(III)2787–111yr9.815.419.48.030.713.82.81.3–6.12 6(III–R)27812–186mo13.914.420.812.821.613.31.80.8–3.9 10(III)2229–161yr——62.4—55.3—phi=1.4— 11(III–R)10159–133mo5.25.518.34.419.24.74.812.13–10.9 12(IV)97010–143mo4.93.813.04.69.93.43.11.4–6.9 13(IV)92811–153mo3.42.87.93.26.62.72.60.85–7.7 14(IV)82012–163mo2.90.9816.22.85.50.96.81.6–29.6 15(III–R)3239–133mo6.55.35.96.54.85.30.890.11–7.1 16(IV)31710–143mo8.23.833.37.215.42.86.41.8–23.0 17(IV)30411–153mo5.32.033.34.712.51.410.11.7–60.2 18(IV)28912–163mo4.23.827.33.225.02.911.22.5–49.4 19(III–R)986156mo10.812.8————3.21.8–5.5 20(III–R)27628–163mo4.34.4————3.71.9–6.8 Study1.(Andersonetal.,1987). Study2.(McGeeetal.,1990)Afollow-upofstudy1. Study3.(Feehanetal.,1994)Afollow-upofstudies1 and2. Study4.(Kashanietal.,1987). Study5.(Costelloetal.,1988). Study6.Costello,unpublishedDISCDSM–III–R diagnosesfromafive-yearfollow-upofstudy5.
Study7.(Velezetal.,1989). Study8.(Velezetal.,1989)Afollow-upofstudy7. Study9.(Rhodeetal.,1991). Study10.(Lewinsohnetal.,1993). Study11.(Birdetal.,1993). Study12–15.(Angoldetal.,1998)Fourannualwaves ofdatacollection.
Study16–19.(Costelloetal.,1997)Fourannu wavesofdatacollection. Study20.(Fergussonetal.,1993a).Pvaluesre onlyasor0.05. Study21.(Simonoffetal.,1997).Pvaluesrep onlyasor0.05.
found that the rate of ‘conduct disorders’ was 9.3% in boys and 3.2% in girls, but included ‘hyperkinetic disorders’ in this classification, so we cannot tell how many met criteria for conduct disorder as we usually mean it today.
A number of studies from the mainland USA, Puerto Rico, Holland and New Zealand have reported rates of ODD and CD using one of the DSM nosologies, and Table 6.2 shows these rates for the combined category of ODD or CD, to provide a rough parallel with the ICD studies, from studies that reported rates of association among diagnoses. We should note, in addition, that Verhulst and colleagues (Verhulst et al., 1997) reported that DSM–III–R ODD was present in 1.2% of Dutch 13- to 18-year-olds, while the rate of CD was 2.0%. Across the age range from 8–16 rates vary from 1.8% to 14.7% (so the ICD estimates all fall within this range as well). However, half of the estimates fall between 5.9% and 9.1%, with a median of 5.8%. It seems reasonable to conclude, therefore, that the average rate of the combined category of CD or ODD is between 5% and 10% of the general population aged between 8 and 16 years. It is possible that overall rates will appear to be lower in the future with the adoption of the DSM–IV criteria. On the other hand, we have already seen that adopting ICD–10 type rules for defining CD led to a substantial increase in its apparent prevalence in the Great Smoky Mountains Study. So what is the ‘true’ preva-lence of CD? The answer is that this is a meaningless question at this point, because we have no agreement on what constitutes a ‘true’ case of CD. We can say, however, that, in general, across the industrialized Western world at any one time, probably between 5% and 10% of 8–16-year-olds have notable behavioural problems of the type commonly considered part of the spectrum of CD/ODD. In other words, CD/ODD represents a gigantic public health problem.
Age and gender effects on conduct disorder
As we have already noted, CD/ODD behaviours have usually been found to be more common in boys than girls for the last 70 years. However, less attention has been paid to the fact that there is probably wide variation in the gender-specific rates of CD/ODD individual symptoms. For instance, very few girls force boys to have sex with them, but we do not expect to see such an extreme gender differentiation in lying! It is also likely that the sex ratio is less for DSM ODD than it is for DSM CD. For instance, in the GSMS, the sex OR for DSM–IV ODD was 1.2, while that for DSM–IV CD was 2.9. It also seems likely that much of the gender difference lies in aggression rather than CD as a whole.
There is evidence that differences in rates of nonaggressive CD between males