REVIEW ARTICLE |
Department of Psychiatry and Psychotherapy, Semmelweis University Budapest, Hungary
Department of Psychiatry and Psychotherapy, Semmelweis University Budapest, Hungary, and Nathan Kline Institute for Psychiatric Research, Orangeburg, New York, USA
Department of Psychiatry and Psychotherapy, Semmelweis University Budapest, Hungary
Correspondence: Dr Viktória Simon, Semmelweis University Budapest, Department of Psychiatry and Psychotherapy, Balassa u. 6, Budapest H-1083, Hungary. Email: simonviktoria{at}psych.sote.hu
None.
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In spite of the growing literature about adult attention-deficit hyperactivity disorder (ADHD), relatively little is known about the prevalence and correlates of this disorder.
Aims
To estimate the prevalence of adult ADHD and to identify its demographic correlates using meta-regression analysis.
Method
We used the MEDLINE, PsycLit and EMBASE databases as well as hand-searching to find relevant publications.
Results
The pooled prevalence of adult ADHD was 2.5% (95% CI 2.1–3.1). Gender and mean age, interacting with each other, were significantly related to prevalence of ADHD. Meta-regression analysis indicated that the proportion of participants with ADHD decreased with age when men and women were equally represented in the sample.
Conclusions
Prevalence of ADHD in adults declines with age in the general population. We think, however, that the unclear validity of DSM–IV diagnostic criteria for this condition can lead to reduced prevalence rates by underestimation of the prevalence of adult ADHD.
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In spite of the growing literature dealing with adult ADHD, relatively little is known about the prevalence of the disorder among adults and its correlates. To our knowledge no meta-analysis of the epidemiological data on adult ADHD has been published. The aim of our study was to estimate the prevalence of ADHD in adulthood using a meta-regression approach and to identify demographic factors that might influence the prevalence of ADHD in a given population.
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For our meta-regression analyses six studies were omitted. Three of these studies (Kessler et al,32 Medina-Mora et al33 and Fayyad et al31) were not included because they did not provide raw data for the prevalence and demographic variables necessary for the computations. The study by Barbaresi et al24 was not included because it dealt only with the cumulative incidence of ADHD between the ages of 5 and 19 years and accordingly provided information about ADHD in adolescents rather than in adults. The study by Weyandt et al26 was not included because it measured only the prevalence of attention-deficit symptoms and not the prevalence of adult ADHD. Finally, we omitted the study by Gadow et al30 because these authors did not use DSM–IV35 criteria for the diagnosis of adult ADHD. The modified diagnostic criteria used by Gadow et al did not include age at onset or functional impairment criteria, and applied a threshold of five rather than six symptoms.30 Lowering the diagnostic threshold concerning symptom counts has a dramatic effect on prevalence estimates; inclusion of data based on a lower symptoms threshold would therefore have introduced substantial heterogeneity in the meta-analysis.
Variables
For the purpose of the meta-analysis we extracted the following domains or
variables from the articles that were finally included:
Statistical analysis
A mixed-effect (with fixed and random effects) meta-regression–a
meta-analytic technique of multivariate linear regression across
studies–was applied to estimate the prevalence of ADHD across various
study samples and in order to evaluate the impact of potential demographic
variables of interest including age and gender on the prevalence estimates.
The meta-regression analysis that we adopted in this investigation was based
on van Houwelingen et al's general linear mixed-model technique based
on the approximate likelihood
approach.36 In
particular, the log-odds of the observed prevalence in each study were
regressed using intercept and basic study-level demographic covariates that
included average age and gender composition from each of the individual
studies. Interaction between the two covariates (age, gender composition) was
also included in the model. In addition, a random-effect intercept term
representing systematic between-study variation (heterogeneity) was also
incorporated in the meta-regression model. A common weighted prevalence
estimate for ADHD was calculated as a DerSimonian & Laird estimator, based
on the random effects component of the mixed model that incorporated both
fixed and random
effects.37
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Table 1 Demographic data of samples included in the meta-analysis
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Table 2 Descriptive data for studies included in the meta-analysis
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Age
In most of the studies, the sample's mean age was low compared with the
mean age of a typical adult population. Specifically, although the mean ages
were 19.4–44.9 years for all samples in the analysis (the mean age,
weighted by the number of participants in each study, was 34 years), for the
majority of samples the mean age ranged between 19.4 and 28.5 years. Only one
study had a mean age of 44.9
years,19 whereas
two studies had a mean age of around 35
years.25,34
(Of these two studies, Faraone & Biederman provided estimates for mean age
based on weighting using the US census
data;34
Table 1).
Gender
With the exception of one study sample (the USA arm of the study by DuPaul
et al),27
the gender proportions were neither balanced nor representative of the target
population. There were extreme differences in the male: female ratio across
the groups in the study by DuPaul et
al,27 with a
substantial departure from the population gender distribution in two arms of
this study, possibly as a result of the above-mentioned convenience sampling
(Table 1).
Diagnosis
The studies included in our meta-analysis applied different methodology and
design with regard to sampling and diagnosing adults with ADHD
(Table 2). All studies employed
DSM–IV diagnostic criteria, even though all–except for Faraone
& Biederman34
and Almeida Montes et
al29–questioned
the validity of DSM–IV criteria for ADHD when applied to
adults.35 In terms
of association between symptoms that underlie the DSM–IV diagnosis of
adult ADHD and functional impairment (used as an external validator of the
disorder), Kooij et al found the strongest association from four
symptoms being present (as opposed to the threshold of six symptoms according
to the DSM–IV diagnostic
system).19 DuPaul
et al27
and Heiligenstein et
al28 applied
alternative diagnostic criteria with a lower threshold, besides the original
DSM–IV criteria. Although Murphy & Barkley used only DSM–IV
diagnostic criteria in their study, they suggested the possibility of
modifying these criteria for adult ADHD in
future.25 Faraone
& Biederman considered two types of diagnoses for adult ADHD: a `broad'
diagnosis for screening purposes, which followed the DSM–IV criteria but
was more inclusive concerning symptom severity; and a `narrow' diagnosis based
solely on DSM–IV
criteria.34
Estimated prevalence and correlates of adult ADHD
Mixed-effect meta-regression analysis was applied to estimate the
prevalence across samples and to investigate prevalence as a function of
gender composition and mean age in the respective samples. Results of the
meta-regression analysis indicated that the pooled prevalence of ADHD across
samples was 2.5% (95% CI 2.1–3.1; t=42.3, P<0.0001)
(Fig. 1).
![]() View larger version (7K): [in a new window] [as a PowerPoint slide] |
Fig. 1 Prevalence estimates and 95% confidence intervals of adult
attention-deficit hyperactivity disorder in individual investigations and
pooled prevalence estimated across studies using meta-regression analysis.
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2=65.2, d.f.=1,
P<0.0001), which (as shown by subsequent analyses) was due, at
least in part, to the principal demographic variables that we examined in our
study. In particular, our results showed that the prevalence of ADHD was
significantly related to the gender composition in the sample
(t=4.34, P=0.012, standardised beta for log-odds of observed
prevalence 15.19 x 10–2) and to the mean age
(t=3.03, P=0.039, standardised beta for log-odds of observed
prevalence 20.98 x 10–2). Furthermore, the interaction
between the two covariates also reached statistical significance
(t=–3.42, P=0.027, standardised beta for log-odds of
observed prevalence 0.50 x 10–2). The association
between the proportion of participants with ADHD and gender composition and
mean age is shown in Fig. 2.
Owing to the statistically significant interaction reported above, for
illustrative purposes the association of prevalence with gender composition is
displayed at various ages (20, 30 and 40 years;
Fig. 2(a)); for younger age
groups the prevalence increases, whereas for the older age group prevalence
decreases with higher proportion of males in the sample. Analogously, for
illustrative purposes the association of prevalence with mean age was broken
down by male percentage of the sample (a third, a half, two-thirds;
Fig. 2(b)); the prevalence
decreases with age when men are represented at 50% or more in the sample, but
increases with age when women are predominantly represented in the sample
(male proportion, 33.3%).
![]() View larger version (12K): [in a new window] [as a PowerPoint slide] |
Fig. 2 Relationship between gender composition (% male) and prevalence (%) of
adult attention-deficit hyperactivity disorder (ADHD). Meta-regression
analysis indicated that gender and mean age, interacting with each other, were
statistically significantly related to the prevalence of ADHD in the sample.
(a) Relationship between gender composition and prevalence at ages 20, 30 and
40 years. (b) Relationship between age and prevalence as a function of gender
composition (a third, a half, two-thirds males).
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Table 3 Results of the studies included in the meta-analysis
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Follow-up studies are long-term prospective studies designed to determine the persistence of ADHD among adolescents and adults by following an index ADHD group of school-aged children and a matched control group. Follow-up studies show that ADHD persists in 4–66% of the cases into adulthood.1–8 Such variability in the persistence of the disorder into adulthood can be explained–at least in part–by methodological differences such as small sample sizes; non-representative, predominantly clinical samples; different diagnostic criteria among and across studies; and changing the source of information during the follow-up from parent report to self-report only. These methodological differences imply that follow-up studies are difficult to compare and the results of those studies can neither be generalised nor used for estimating prevalence of ADHD in adulthood.
Population-based studies estimated prevalence rates of adult ADHD at 1–7.3% applying DSM–IV criteria.19,24,25,27–29,31–35 Most of these studies were designed for direct estimation of the prevalence of adult ADHD in a target population such as a community, university students, prisoners or a special population of patients. These studies typically used a large sample and therefore were usually appropriate for estimating prevalence with sufficient precision. However, they did not assure representativeness, since they were based on a sample of convenience. In general, the mean age of the participants was low compared with a typical adult population, and there were several studies in which the gender proportion of the sample was significantly unbalanced. In addition, the diagnostic tools and the approach for the identification of cases usually varied from study to study.
Gadow et al provided estimates of the prevalence of adult ADHD using a large, representative sample of the general population.30 Nevertheless, because these authors applied only modified diagnostic criteria, their prevalence data are difficult to compare with the prevalence estimates from other studies that relied on the original DSM–IV classification. Two studies, being parts of large-scale epidemiological surveys–the National Comorbidity Survey39 and the World Health Organization (WHO) World Mental Health Surveys40–did not provide crude estimates for the prevalence of adult ADHD in their sample; they used indirect estimation in order to assess the prevalence of adult ADHD in the general population. The first of these studies (Kessler et al32) examined an US sample, whereas the second (Fayyad et al31) estimated cross-national prevalence in ten countries. We note that despite these two studies applying the same general approach, the first estimated prevalence at 4.4%,32 whereas the second estimated the prevalence in the US sample at 5.2%.31 Based on the authors' comments, this discrepancy is attributable to the fact that certain predictors for the prevalence estimation that were used in the first (USA only) study were not available in the second (multinational) study. In the second study, the prevalence estimates of adult ADHD across samples showed a substantial variation: they were between 1.2% and 7.3%, with an estimated general cross-national prevalence of 3.4%.31 In both studies, prevalence estimates were based on multiple imputation using a combination of directly interviewed cases and multiply imputed cases from the remainder of the sample. In all cases (directly interviewed and multiply imputed) in both samples the individuals were aged 18–44 years; prevalence estimates for higher age ranges were based on weighting data.31,32 The aforementioned indirect estimations (applied in both studies) of the prevalence of adult ADHD in the general population hinge on prediction equations that were obtained in a relatively small sample (n=154). It is not clear how reliably these equations can predict the occurrence of ADHD, and what the exact predictors are. With regard to the multinational study, it must be noted that the prediction equation of the US sample was extrapolated to other countries, a potential limitation pointed out by the authors. A third study, conducted as part of the WHO survey, estimated the 12-month prevalence of ADHD in Mexico;33 however, like the parent study it did not provide a crude prevalence estimate for the targeted sample and therefore was not included in our meta-analysis.
In summary, published estimates of the prevalence of adult ADHD vary greatly.19,25,27–29,31–34 After reviewing the pertinent publications, we attributed this variability to methodological and diagnostic differences between the studies. In addition, only self-reports were used as a source of information and in some studies there was a lack of information about the relevant childhood symptoms that would be necessary for the proper diagnosis of adult ADHD.26–28
Correlation of prevalence with gender and age
Our finding of a pooled prevalence rate for adult ADHD of 2.5% (95% CI
2.1–3.1) seems to be conservative in the context of the research
discussed above. Our pooled prevalence estimates were derived from studies
that provided data for crude prevalence based on strict DSM–IV criteria
for diagnosing ADHD. In two of these studies, however, indirect estimates were
derived by assessing ADHD symptoms in childhood and asking only a single
question about the persistence of problems with ADHD into
adulthood.31,32
Polanczyk et al recently estimated the worldwide prevalence of ADHD in a meta-regression analysis of 102 articles regarding child and adolescent ADHD.41 Although the pooled prevalence of ADHD in children and adolescents according to these authors was 5.29%, they also reported that the prevalence in adolescents was around 3%.41 This estimate is consistent with our pooled prevalence data, especially in light of the finding about the relationship between age and prevalence of ADHD.
A growing number of studies indicate that biased samples might underlie extreme gender effects on the prevalence of ADHD in clinically referred paediatric study samples. Specifically, some of these studies suggest that a weaker association with conduct disorder and disruptive behaviour in girls compared with boys might result in lower numbers of female referrals.42–44 In contrast to the clinical samples, in which male: female ratios as high as 10: 1 have been observed,45,46 community samples showed a less extreme gender ratio (male: female risk 3: 1) in the prevalence of ADHD in childhood.43,44 Compared with paediatric and adolescent studies, adult ADHD studies have generally shown a more balanced distribution of prevalence in men and women. This may be attributable to the fact that whereas childhood referrals are usually initiated by parents or teachers, in adulthood self-referrals are common. The observation that women with ADHD have more internalising problems than men, which leads to a higher rate of self-referrals in adulthood,47 may underlie the more balanced gender ratio in adult samples.
In the studies that were included in our analysis, samples were community-based and the authors found heterogeneous gender ratios but no significant gender effect on prevalence in their samples when applying DSM–IV diagnostic criteria.19,25,27–29,34 In two studies that were not included in our meta-analysis owing to the lack of crude prevalence data,31,32 the authors found modest gender effects on prevalence, with a significantly higher proportion of men in their ADHD group. In spite of the findings of the studied articles that supported no significant gender effect on prevalence, using the raw data of the individual studies we identified gender as another factor that has an impact on the prevalence of adult ADHD. In this case – as in the case of effect of age – we presume that methodological differences and questions concerning sample selection and case identification underlie the absence of or modest appearance of gender effects in community-based samples.
Our findings indicate that the prevalence of adult ADHD has a significant negative association with age, although this association is moderated by the gender composition of the sample. The explanation and the potential practical use of this finding are complex. Specifically, available literature and clinical experience indicate a modulation of the presentation of symptoms of ADHD by adulthood.48–50 Conceptualisation of ADHD as a developmental disorder entails that, although the disabling feature of the disorder remains, both the quality and the severity of symptoms may change over time. Thus, applying the diagnostic criteria created for children may not be appropriate in adulthood. The developmental nature of the disorder also means that although new cases do not emerge in adulthood, there might be a certain number of children who `outgrow' the disorder. This concept predicts reduced prevalence in adulthood because of the nature of the disorder. In view of our finding of a significant age–gender interaction, this concept might be mainly true for male ADHD cases with more hyperactive symptoms and linked disruptive behavioural problems than female ADHD cases in general.
Several studies reported that symptoms of ADHD declined with age.25,28,31,32,34,51 At the same time, functional impairment and low socio-economic outcome can be detected even with a reduced number of symptoms19,23,31,41,48 These observations lead us to another possible conclusion, that some children with ADHD do not outgrow the disorder but `outgrow the diagnostic criteria',1 meaning that reduced prevalence among adults results from an underestimation of the true prevalence of adult ADHD. Our finding that prevalence increases with age when women are predominantly represented in the sample might relate to the previously mentioned possibility of `pseudo-new' cases of ADHD, when women with this disorder who were not referred for treatment in childhood owing to the absence of disruptive behavioural problems refer themselves in adulthood because of emerging comorbid psychiatric disease.
Two other factors concerning the diagnosis of adult ADHD should be mentioned, since either of them may result in underestimation of the prevalence of the disorder. First, based on the finding of the Milwaukee study,1 – relevant also to clinical experience – it seems that the source of information might have a great impact on diagnosing ADHD: the persistence of ADHD was five to nine times higher when based on parent's report than when based on self-report, and parent's reports also showed higher potential to predict functional impairment than did self-report.1 The second factor is the problem of symptom recall. Several authors pointed out that collecting data with retrospective self-report would underestimate the prevalence of adult ADHD, since adults do not remember their childhood symptoms properly. Empirical findings are inconsistent concerning this issue.1,52–60 In the Milwaukee follow-up study, at the adult follow-up only 47% of the participants recalled having ADHD in childhood from the original ADHD index group.1 Their self-report showed only 20% concordance with their parents' report concerning their childhood symptoms.1 Manuzza et al on the other hand, in the results of the New York follow-up study, reported good symptom recall (the sensitivity of retrospective diagnosis of ADHD was 0.78 and the specificity was 0.89) based on self-reports in the index group at the adult follow-up.52 These authors noted that this might result from the fact that participants in the index group were from a clinically referred sample. Moreover, they suggested that adults who were not hospitalised in their childhood might have had poorer symptom recall.52 The fact that in the New York study there was a high rate of false positive cases in the control group, according to Manuzza et al,52 raises the possibility of problematic symptom recall among people who do not have ADHD.
In summary, we think that our finding is consistent with the suggestion that the prevalence of ADHD declines with age; however, the background of this phenomenon remains unclear and a caveat is needed in this regard. Specifically, the validity of DSM–IV diagnostic criteria for diagnosing adult ADHD is an important issue, emerging both from the interpretation of our findings and also from the relevant literature. It seems that diagnosing adult ADHD on the basis of strict DSM–IV criteria – as well as the above-mentioned methodological difficulties – may lead to underestimation of the prevalence of the disorder in this age group. Thus, further investigations are necessary to find out in what proportion methodological questions or natural developmental features are responsible for the observed decline in the prevalence of ADHD with age. Future well-designed, community-based epidemiological studies critically depend on an improved understanding of the aetiology and pathophysiology of the disorder, which in turn would help to improve the current diagnostic criteria and would thereby facilitate more reliable identification of people with ADHD. We must note that the small number of studies included in the meta-regression analysis and the above-detailed methodological difficulties of the reviewed and analysed studies are also potential limitations of our findings.
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