disorders in the
Emma Williams MSc PhD, Centre for Child and
Kate Thomas MSc, Avon Longitudinal Study of Parents
and Children (ALSPAC);
Helen Sidebotham MSc;
Alan Emond* MB MD FRCPCH, Centre for Child and
Adolescent Health, University of Bristol, Bristol, UK.
The aim of this study was to determine the prevalence of
autistic spectrum disorder (ASD) within a large
representative population sample: the Avon Longitudinal
Study of Parents and Children (ALSPAC). Cases of ASD were
identified from the clinical notes of children in the ALSPAC
with a suspected developmental disorder and from the Pupil
Level Annual Schools Census (PLASC) for England in 2003.
Seventy-one cases of ASD diagnosed after a multidisciplinary
assessment were identified from health records. There were
an additional 15 cases from PLASC data in which ASD was
mentioned as a principal difficulty, thus giving a total of 86
children diagnosed by the age of 11 years. Prevalence of
ASD per 10 000 population at 11 years was 51.1 for those
with a multi-professional diagnosis, and 61.9 if cases from
education were included, made up of 21.6 for childhood
autism, 10.8 for atypical autism, 16.6 for Asperger syndrome,
and 13.0 for unspecified ASD. The male:female ratio was
6.8:1. Median age at diagnosis ranged from 45 months in
childhood autism to 116 months in Asperger syndrome. A
comorbid developmental disorder was recorded in 33.8% of
cases, including learning disability*in 14.7%, epilepsy in
10.3%, and mixed developmental disorder in 4.4%. We
conclude that the prevalence of ASD diagnosed at 11 years in
a UK representative population-based sample is at least
Autistic spectrum disorder (ASD) is a pervasive developmen-
tal disorder characterized by abnormal development of social
interaction, communication, and behaviour. In recent years,
estimates of prevalence have ranged from 12.2 to 67.4 cases
per 10 000 population.1A large population-based study from
South Thames, UK,2has recently reported a prevalence of
ASD of 116 per 10 000, and another study3has estimated the
prevalence of the wider autistic spectrum to be up to 2.7% of
children. Other developmental disorders and medical condi-
tions are recognized to co-occur in individuals with a diagno-
sis of ASD, although precise comorbidities and prevalence
rates vary widely in the literature. A review of studies investi-
gating disorders co-existing with ASD concluded that studies
of large general population samples where comorbidity pat-
terns can be analyzed without bias should receive high prior-
ity because this information can be used to increase
understanding of the possible subtypes of childhood autism
and the genetic links.4
The Avon Longitudinal Study of Parents and Children (AL-
SPAC),5a large population-based birth cohort study, specifi-
cally designed to investigate how an individual’s genotype
interacts with environmental pressures to influence health
and development, is an ideal sample to use for this research.
The aim of this study was to report on the prevalence of ASD
in the ALSPAC cohort, and to describe comorbid develop-
mental impairments. We also report on the median age at
diagnosis for each of the ASDs found in the ALSPAC cohort,
and the social and demographic characteristics of children
diagnosed with ASD. This information is vital not only so that
we can better understand and provide services for children
with ASD, but also as a basis for elucidating the contribution
of environmental and genetic influences to autistic disorders.
ALSPAC is a longitudinal cohort study following the health
and development of children who had an expected date of
delivery between April 1991 and December 1992, and who
were resident in the Avon area of southwest England at the
time of their birth. The initial ALSPAC sample consisted of
14 541 pregnancies, which resulted in 14 062 live births. This
study population had social and demographic characteristics
in common with the 1991 UK national census.6
Ethical permission was granted for this study by the local
research ethics committees, and Caldicott Guardian approval
was gained for linkage of UK National Health Service (NHS)
data for this investigation. All research was within the guide-
lines set out by these bodies, and the study was monitored by
the ALSPAC Law and Ethics Committee. The ALSPAC ethical
framework does not allow researchers to use information
from ALSPAC to make contact with individual study members
or their families. It was, therefore, not possible to use ALSPAC
questionnaires to screen for autism, and cases had to be iden-
tified through health and education records. Permission to
search their child’s medical records for research purposes
was granted by the children’s mothers at the time of
enrolment to the ALSPAC study.
IDENTIFYING CASES OF ASD
Information on which children in the ALSPAC may have been
diagnosed with an ASD was gathered both from NHS and
Developmental Medicine & Child Neurology 2008, 50: 672–677
education sources. First, we requested data on all individuals
with a date of birth in the ALSPAC cohort who had a diagno-
sis relating to any form of developmental delay for the period
1991 to 2003 inclusive (the diagnosis being based on the
World Health Organization’s International Statistical Classifi-
cation of Diseases and Related Health Problems, Tenth Revi-
sion [ICD-10]) from the computer systems of local NHS
trusts (North Bristol Trust, United Bristol Healthcare Trust,
Weston Area Health Trust and Royal United Hospital, Bath).
Second, we requested information from the Child Health
computer system in Bristol (shared across all the NHS trusts
in the area) about all children who were identified as having
special educational needs between 1993 and 2003 inclusive.
These two lists were then matched against the ALSPAC cohort
to confirm that the child was a member of the study and that
permission had been given to search their health records. A
team of three experienced researchers then searched hospi-
tal medical records (in-patient and outpatient) and commu-
nity child-health records (including child development team
records) to identify children who had a diagnosis of ASD
made after a multidisciplinary assessment. No direct contact
was made with any of the children, parents, or clinicians. The
researchers searched for ICD-10 diagnoses according to a
structured proforma, based on information that was available
in the records written by the multiprofessional team involved
in the care of the child. The date a diagnosis was confirmed
by a multidisciplinary assessment was also recorded from the
notes. The project’s principal investigator (AE), a consultant
paediatrician with 30 years of clinical experience, reviewed
all information collected from the notes and confirmed
that the diagnostic information was consistent with ICD-10
The data collected from NHS sources (both hospital and
community notes) formed the core NHS dataset for this
study. All the NHS Trusts in the ALSPAC area have specialist
autism teams in children’s services, trained to use standard-
ized assessment tools such as the Diagnostic Interview for
Social and Communication Disorders,7the Autism Diagnos-
tic Observation Schedule,8and the Asperger Syndrome Diag-
nostic Interview.9Only cases diagnosed by multidisciplinary
teams were included. Cases where a lone consultant or
speech therapist applied a label of ASD were excluded. All
personal identifiers were stripped from the NHS dataset and
further work was performed by an ALSPAC statistician (KT),
not by the researchers who had collected the data from the
The second source of data on children with developmen-
tal disabilities came from national education records. ALSPAC
supplied information on all study children from the Pupil
Level Annual Schools Census (PLASC) dataset for 2003⁄4,
supplied by the Department of Education for England. These
data included children attending state schools (both main-
stream and special schools) in England who were recorded
as having some form of special educational needs (SEN)
within that academic year. For each child, the PLASC data
provided information on the level of extra help being pro-
vided at school (School Action, School Action Plus, or State-
ment of Special Educational Needs), and one of two principal
difficulties for children at School Action Plus and Statement
of Special Needs level. Wesearchedthecomplete PLASC data-
set for children with ASD listed as either a primary or a
secondary concern. However, it was not possible to link this
dataset with the children’s health records (hospital or com-
munity) because the ethical framework of ALSPAC does not
allow data to be given to a researcher that identify individual
children as having specific problems.6Therefore, health
records for those children whose ASD label was obtained
from the PLASC database could not be searched to confirm
these diagnoses, or to gain information on comorbidities.
All data manipulation and statistical analyses were performed
using SPSS (version 12.0.1). Approximation to the normal
distribution was used to calculate 95% confidence intervals
(CI) for the prevalence rates. Between-group comparisons of
ages and dates used the non-parametric Mann–Whitney U
and Kruskal–Wallis tests, because the data were not normally
distributed. Fisher’s exact test was used to test for an associa-
tion in a two-by-two contingency table when expected counts
CASES OF ASD
A total of 86 children in the ALSPAC were diagnosed with
ASD by 11 years of age, from an original cohort of 14 062
births. Searches of NHS notes produced 71 cases of a con-
firmed ASD diagnosis, and there were 51 children on the
PLASC database who had a diagnosis of ASD listed as one of
the two principal difficulties. There were 31 children that
were only identified from the NHS data, 15 that were identi-
fied only from the PLASC data, and 40 that were common to
both sources (Fig. 1).
The estimated prevalence of ASD at age 11 years in the
ALSPAC cohort was 51.1 per 10 000 (95% confidence interval
[CI] CI 39.2–62.9) for those diagnosed after multidisciplinary
assessment, and 61.9 per 10 000 (CI 48.8–74.9) if the extra
cases identified by education were included.
We also calculated an estimated prevalence for different
autism diagnoses. The 15 cases identified only by the PLASC
data were assigned the ‘unspecified ASD’ code, as we were
not able to check their health records. The prevalence of
childhood autism was estimated as 21.6 per 10 000 (CI 13.9–
29.3; n=30), atypical autism as 10.8 per 10 000 (CI 5.3–16.3;
Grand total = 86
Total = 57
Total = 71
Figure 1: The frequency of autism spectrum disorder in the
Avon Longituden Study of Parents and Children cohort, illus-
trating the number of cases identified by searches of NHS
notes, the number of cases identified from Pupil Level Annual
Schools Census (PLASC), and the agreement between these
ASD in ALSPAC Emma Williams et al.
n=15), Asperger syndrome as 16.6 per 10 000 (CI 9.8–23.3;
n=23), and other or unspecified ASD as 13.0 per 10 000 (CI
4.8–15.3; n=18). There was no case of Rett syndrome or of
‘other childhood disintegrative disorder’.
AGE AT DIAGNOSIS
Age at diagnosis was only known for the 71 cases of ASD
found by researchers through examination of the health
records. Median age at diagnosis of ASD was 81.9 months (in-
terquartile range [IQR] 42.7–116.6), or 6 years 7 months. Age
at diagnosis was lowest for children with childhood autism,
at a median age of 44.9 months (IQR 36.5–85.6), followed by
atypical autism at 75.5 months (IQR 42.7–117.9), then Asper-
ger syndrome at 115.9 months (IQR 93.4 to 130.6). Age at
diagnosis for children with Asperger syndrome was signifi-
cantly later than for children diagnosed with other forms of
ASD (Kruskal–Wallis test, p<0.001).
Of the 86 cases of ASD in the ALSPAC cohort, 75 (87.2%)
were males, and 11 (12.8%) females, a male:female ratio of
6.8:1 (Table I). Of the cases where the specific ASD diagnosis
was known (childhood autism, atypical autism, or Asperger
syndrome), there appeared to be a trend towards females
being over-represented at the more severe end of the spec-
trum (childhood autism) compared with males (Table II).
However, the total numbers of females with each ASD diag-
nosis were too low for statistical comparisons.
Across all ASD diagnoses derived from NHS data, the med-
ian age at diagnosis for females was 81.9 months (IQR 40.4–
119.5), and for males 83.8 months (IQR 43.0–116.5). This dif-
ference between the sexes for age at diagnosis was not statis-
tically significant (Mann–Whitney U test, p=0.923).
There was no difference in the proportion of children with
ASD who came from a non-white background compared with
the rest of the cohort. Mean age of the mothers of children
with ASD was slightly higher than the rest of the cohort, with
more mothers of children with ASD aged 30 to 34 years;
there was no association with paternal age. No difference
was apparent in the educational background of the parents
of children with ASD compared with the rest of the parents
in the cohort. No consistent trend was found with maternal
occupational social class, but fathers of children with ASD
were more likely to have a non-manual occupation (Table I).
Median age at diagnosis for the children identified from
NHS data was 89.2 months for children of mothers educated
to less than Ordinary Level (O-level; high school) standard,
68.9 months for children with mothers educated to O-level,
and 92.9 months for children with mother educated to
greater than O-level. There was no statistical evidence of a
difference (Kruskal–Wallis test, p=0.866).
The children with ASD did not differ from the rest of the
cohort at birth for birthweight, gestation, or whether they
had been in a multiple pregnancy.
SPECIAL EDUCATIONAL NEEDS STATUS
Of all the ASD cases, 94.4% had a statement of SEN, 4.2%
were on School Action Plus, and 1.4% (one child with Asper-
ger syndrome) had no special provision. Data on special
needs support were missing for 10 children with ASD: these
children attended a private school, were home educated, or
attended a school outside England.
COMORBID DEVELOPMENTAL IMPAIRMENTS
Some children had other developmental impairments, as
well as having a diagnosis of ASD. Data were available on
Table I: Comparison of demographic and other factors between
children with ASD and the rest of the ALSPAC cohort
Maternal age, y <2512 (14.0)
Paternal age, y0.186
Characteristics at birth
78 (92.9) 12846 (94.6)
80 (93)12754 (94.4)
Birthweight, g 0.481
Sex of child7111 (51.5)
Highest educational attainment
Non-manual 51 (82.3)
Non-manual 55 (75.3)
Sample sizes vary because of missing data. Variable with the most
missing data is maternal occupation (n=10 088).aOrdinary level
pass at national assessments at 16 years. ALSPAC, Avon Longitudi-
nal Study of Parents and Children, ASD, autism spectrum disorder.
Table II: Frequency of females and males having each subtype
ASD diagnosis Male, n (%)Female, n (%)
Other and unspecified ASD
ASD, autism spectrum disorder.
Developmental Medicine & Child Neurology 2008, 50: 672–677
specific conditions for the children who had a diagnosis of
ASD confirmed by a multidisciplinary assessment (n=71):
33.8% had at least one associated developmental disorder.
The figure was 36.7% for cases of childhood autism, 26.7%
for atypical autism, and 34.8% for Asperger syndrome.
Table III summarizes the frequency and percentage of
cases of comorbid developmental impairments that were
found in association with diagnoses of ASD. Because children
had between one and four developmental impairments each,
the total number of developmental impairments does not
relate to the number of children.
As there were few comorbid developmental impairment
conditions associated with specific ASD diagnoses, no firm
statistical conclusions can be drawn from these data. How-
ever, learning disability did appear to be more strongly asso-
ciated with atypical autism (26.7% of cases) compared with
Asperger syndrome and childhood autism (8.7% and 13.3%
of cases respectively). Epilepsy was more strongly associated
with childhood autism (16.7% of cases) than either atypical
autism (no cases) or Asperger syndrome (8.7% of cases).
Although classifications according to ICD-1010and the DSM-
IV11do not allow the simultaneous labelling of autism and
attention-deficit–hyperactivity disorder, it is well recognized
in clinical practice that there is an overlap. In the ALSPAC
sample, hyperkinetic disorders appeared to be more associ-
ated with Asperger syndrome (13% of cases), than either
childhood autism or atypical autism (3.3% and 6.7% of cases
Although we have used a large population-based sample, our
case-finding methods were biased towards children with a
statement of SEN who were attending English state schools
in 2003. We are likely to have under-reported children at the
higher-functioning end of the autistic spectrum (Asperger
syndrome), who, typically, may not have a statement of SEN,
and who may be diagnosed after 11 years of age. We also
potentially missed children with diagnoses of ASD who
attended private or independent schools, schools outside
England, or children who were educated at home.
Although most cases had a good diagnostic assessment by
a specialist multidisciplinary team, different tools were used
by different teams, and the ASD label was applied by clinical
consensus and not after a research evaluation. This may have
biased our results in either direction: the lack of a rigorously
applied research diagnostic scale may have resulted in an
overestimate of the true prevalence by including children
with autistic traits who do not fulfil strict diagnostic criteria.
Alternatively, the reliance on a clinically referred population
may have underestimated the true prevalence by not includ-
ing milder cases on the spectrum that were never referred.
For this reason, we included the education data, but these
presented their own difficulties such as, most importantly,
the lack of detailed diagnostic information. The PLASC data-
base only records a primary and a secondary educational dif-
ficulty, so unless an ASD has been identified as one of the
two major concerns in a child’s ability to access the national
curriculum, it will not be listed. Interestingly, the 17% of
cases identified only by educational sources in the present
study is small compared with the 40% of ASD cases identified
only by educational and not medical sources in a US-based
study.12These results highlight the importance of searching
for ASD cases using multiple methods,13to ensure as
complete an ascertainment as possible.
The most secure estimate of ASD prevalence in the ALSPAC
cohort of 51 per 10 000 is within the range of estimates from
other population-based studies. The wide range of estimates
in the literature is likely to be a result of different methods
used to find cases, rather than genuine differences in preva-
lence in different populations.1,14Chakrabarti and Fo-
highlight that four UK surveys on similar
paediatric populations reported a fourfold difference in prev-
alence, which suggests that the rigorousness of the methods
used to find cases is likely to have the strongest influence
on the result, rather than the characteristics of the study
The prevalence estimate for childhood autism reported in
the present study (21.6 per 10 000) is high compared with
figures quoted in 23 studies before 1999,14and figures
quoted in more recent studies15,16which ranged from 0.7 to
21.1 cases per 10 000. However, it is similar to the Special
Needs and Autism Project,2which calculated a prevalence of
24.8 per 10 000 for a narrow definition of childhood autism,
and 38.9 per 10 000 for a prevalence of childhood autism
estimated using a sample weighting procedure.
For atypical autism, the prevalence of 10.8 cases per
10 000 in this study is comparable to that published by
Table III: Frequency of other developmental conditions in children with a diagnosis of ASD
Developmental impairment Childhood autism
(n=30) n (%)
(n=15) n (%)
(n=23) n (%)
Specific motor function disorder
and mixed developmental disorder
aMental retardation on ICD-10. ASD, autism spectrum disorder.
ASD in ALSPAC Emma Williams et al.
Lingam et al.16of 10.5 per 10 000 cases. The prevalence of As-
perger syndrome in the present study of 16.6 cases per 10
000 was two to three times that reported previously.15,17
Identification of Asperger syndrome is often made later in
childhood or adolescence, so the point prevalence would be
expected to increase with age after 11 years.14,17In addition,
the prevalence rate will depend on which diagnostic classifi-
cation is used. A recent study of 8-year-olds from Finland
reported prevalence rates of Asperger syndrome to range
from 16 to 29 per 10 000 with different diagnostic criteria
used on the same sample of children.18
In addition, all 15 cases identified only by the PLASC data
were labelled as ‘unspecified ASD’ by this study. It is likely
that some of these cases belong to a more specific ASD diag-
nosis. Therefore, although the prevalence of individual ASD
diagnoses in the present study appears high, in reality these
are likely to be underestimates.
The predominance (87.2%) of male children having a
diagnosis of ASD was similar to figures for five recently pub-
lished UK studies,2,13,15,16,19which calculated the percent-
ages of males with ASD to be between 79.2 and 87.4%.
Although there was no evidence of a difference in age at diag-
nosis between males and females in ALSPAC, Yeargin-Allsop
et al. reported that males were being diagnosed significantly
earlier than females (3.6 years and 4.1 years respectively).12
The lack of association of ASD with maternal education is
consistent with previous studies,14,19although Baird et al.
found that the rate of identification of ASD by local services
was lowest for children of less educated parents.2
In the present study, 98.6% of children with ASD were
known to have special educational needs, with 94.4% of chil-
dren having a full statement of SEN. These figures are in line
with those quoted in the Mental Health of Children and
Young People in Great Britain report,21which stated that
97% of children with a diagnosis of ASD have special educa-
COMORBID DEVELOPMENTAL IMPAIRMENTS
In this study, 33.8% of ASD cases had an identified comor-
bid developmental disorder: previous studies14,21,22have
quoted figures of between 9% and 37% for the co-existence
of developmental and⁄or neurological disorders, although
Yeargin-Allsop et al.12reported a much higher figure of
62%. This suggests we achieved relatively good rates of
despite this research being based on health records rather
than systematic assessment of children with a diagnosis of
ASD to find possible comorbidities. However, the percent-
age of children (14.7%) labelled as having learning disabil-
ity in this study may be an underestimate. An early study23
quoted a prevalence of learning disability in childhood aut-
ism to be as high as 80%, although more recently, better
diagnostic services have meant that more higher-function-
ing cases of ASD are now being diagnosed, and the esti-
mates of ASD cases with learning disability now range from
25.8 to 30%.12,16,21,22One reason why the figure for a diag-
nosis of learning disability may be low in our study is that
researchers only coded this diagnosis if a child had under-
gone IQ testing and the results were filed in the clinical
records. When a child has severe autism and is diagnosed
very young, they may go straight into a special school, and
their IQ may never be measured. This may explain why
our results show a higher proportion of learning disability
in atypical autism, rather than classical childhood autism as
would be expected from the literature.
Epilepsy is a commonly reported comorbidity in children
with ASD. It was found in 16.7% of cases of childhood autism
and 8.7% of children with Asperger syndrome, similar to pre-
vious estimates of epilepsy in ASD in the literature ranging
from 5.6% to 29% of cases.12,17,21,22,24Although Gillberg and
Billstedt4report that Tourette syndrome and other tic dis-
orders, blindness, deafness, and chromosomal abnormalities
also show high rates of comorbidity with ASD, there were too
few cases of these disorders found in ALSPAC. We did find
hyperactivity to be a relatively common comorbidity, espe-
cially in children with a diagnosis of Asperger syndrome
(13% of cases). Many authors4,17,21,22,24have commented that
symptoms of attention-deficit–hyperactivity and conduct dis-
orders are over-represented in children with ASD, despite
the diagnostic limitations of the classification systems of
ICD-10 and DSM-IV. It is also important to recognize that
there is significant overlap between different subtypes of ASD
and that the developmental difficulties associated with
autism may change as a child gets older.
The prevalence of ASD in this representative sample is consis-
tent with recent reports and probably reflects improved
ascertainment by multidisciplinary teams in health and edu-
cation. The identification of cases of ASD in the ALSPAC study
will facilitate further studies using this cohort to elucidate the
genetic and environmental causes of ASD, and these children
will be followed up into adolescence and adult life.
Accepted for publication 17th March 2008.
We are grateful to all the families who took part in this study,
the midwives for help in recruiting them, and the whole ALSPAC
team, which includes interviewers, computer and laboratory
technicians, clerical workers, research scientists, volunteers,
managers, receptionists, and nurses. The UK Medical Research
Council, the Wellcome Trust, and the University of Bristol
provide core support for ALSPAC. This study was supported
by a steering group consisting of the authors and Dr Jon Pollock,
Ms Sue Bonnell, Ms Karen Birmingham, and Professor Jean
Golding. We thank Andy Boyd and Mike Crawford for their help
with data management and linkage, and Debbie Johnson for her
help with data extraction from notes. This study was funded by
the Wellcome Trust, (grant 59579).
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