Adult Psychiatric Morbidity Survey: Survey of Mental Health and Wellbeing, England, 2023/4

Autism spectrum disorders (ASDs), also referred to as autism, are characterised by persistent difficulties in social interaction and communication, as well as restricted, repetitive, and inflexible patterns of behaviour, interests or activities (World Health Organization (WHO) 2023).

In the phase one interview, autism was screened for using an adapted version of the 20-item Autism Spectrum Quotient (AQ-20). In the phase two interview, full examinations were carried out with a subset of participants by clinically trained interviewers using the Autism Diagnostic Observation Schedule, 2nd edition (ADOS). The ADOS results were weighted to generate a prevalence estimate for the general population.

This chapter presents data on the profile of ADOS-examined autism among adults living in private households.

• Prevalence of autism in adults remained stable at about one adult in a hundred: ADOS-examined autism was present in 1.0% of adults in 2007 (95% confidence interval (CI) 0.5, 2.0), 0.7% in 2014 (CI 0.3, 1.3), and 0.9% in 2023/4 (CI 0.5, 1.7).
• Autism was more common in males (1.5%, CI 1.0, 2.3) than females (0.2%, CI 0.1, 0.5), and may be higher in White (0.9%, CI 0.6, 1.3) and Asian (1.0%, CI 0.2, 4.9) adults than in those from Mixed/multiple or other (0.1%, CI 0.0, 0.5) ethnic backgrounds. No autistic adults from a Black ethnic background were identified in the survey sample.
• Living in more deprived neighbourhoods was associated with autism. 1.8% of those in the most deprived areas were identified as autistic compared with 0.2% of those in the least deprived areas.
• Few adults had an autism diagnosis. Overall, 3.4% of adults thought that they were autistic and 1.2% reported that this had been diagnosed by a professional.
• Autistic adults were no more likely to use health services for a mental health reason or receive mental health treatment than the rest of the population.

Being autistic can have an impact on learning, and, among those most profoundly affected, on the ability to live independently in adulthood (Howlin et al. 2004). Autistic adults often experience isolation and adverse experiences such as being bullied and socially excluded (Brugha et al. 2016b). Furthermore, diagnosed autistic people have been found to have higher rates of a wide range of common mental and physical illnesses compared with the general population (Croen et al. 2015; Lai et al. 2019).

The lifetime cost of supporting an individual diagnosed as autistic without intellectual disability was estimated in 2014 as £0.92 million in the United Kingdom and higher for those with intellectual disability. Residential care, supportive living accommodation and individual productivity loss contribute the highest costs for autistic adults with intellectual disability (Buescher et al. 2014). However, people based in these care settings, as well as, for example, those in prison or homeless, are not included in the APMS. Quantifying such costs requires reliable estimates of the number of adults with the condition, and the proportion who have a diagnosis. APMS 2007 was the first general population probability sample survey to produce such estimates using an examination for autism in a large representative sample of adults living in private households (Brugha et al. 2009). The 2007 and 2014 APMS estimated the prevalence of autism in England to be about one in a hundred. The 2021 Global Burden of Disease study found a similar prevalence of about one in every 127 people, with an estimated 61.8 million autistic people globally in 2021 (Santomauro et al. 2025).

Data from the APMS series is consistent with prevalence being higher in men than women, in adults without educational qualifications (Brugha et al. 2016a) or living in rented social housing (Brugha et al. 2011), and in those with epilepsy (Rai et al. 2012). Autism is also known to be strongly associated with intellectual disability (Cooper et al. 2007), particularly among those with moderate to profound intellectual disability (Brugha et al. 2016b). The 2007 APMS was extended to cover a sample of people with intellectual disability, including some living in residential settings, and found the prevalence of autism to be substantially higher (7.5%) in this group (Brugha et al. 2016b). While circumstances for autistic adults continue to be under-researched (Tromans et al. 2024), including research involving older autistic people (Mason et al. 2022), the condition clearly has a significant impact across the life course, with adults with autistic traits experiencing barriers to accessing healthcare (Tromans et al. 2024) and found to be significantly over-represented in those who die by suicide (Cassidy et al. 2022). Among diagnosed autistic people, higher rates of a range of common mental and physical health conditions have been reported (Croen et al. 2015; Lai et al. 2019), however the burden of these conditions among undiagnosed autistic people is largely unknown outside of the present work.

Autism was also assessed, using the Development and Wellbeing Assessment (DAWBA), in the 2004 and 2017 Mental Health of Children and Young People Surveys (MHCYP). Similar to the APMS estimate of prevalence in adults, MHCYP identified autism in 1.2% of 5 to 19 year olds and found it to be more common in boys (1.9%) than girls (0.4%) (Marcheselli et al. 2018). It is often easier to involve autistic children in research, in part because the diagnosis of autism should include presence of autistic features in childhood and parent and teacher observations of this are more likely to be accurate and available for this group. Both parent and teacher observations were collected in MHCYP.

There is a widespread consensus that the proportion of people who are diagnosed with autism is increasing (O’Nions et al. 2023; Russell et al. 2022). However, evidence suggests that the prevalence of autism has remained stable. In England, the prevalence of autism on the survey of Mental Health of Children and Young People was 1.2% in 5 to 19 year olds (Marcheselli et al. 2018) and was similar to one in a hundred identified in APMS 2007 and 2014 for adults of all ages and both studies noted stability in prevalence over time. These findings were also comparable with rates found by the Avon Longitudinal Study of Parents and Children and the Millennium Cohort Study (Brugha et al. 2016b). It is likely that increases in diagnosed cases are due to changes in public and professional awareness of the condition, different diagnostic definitions and practices, availability of services and referrals, and earlier age at diagnosis (Fombonne 2009; Russell et al. 2015; Brugha et al. 2018). Additionally, increased autism diagnosis in women and adults could be a contributing factor (Russell et al. 2022). Although increased autism prevalence cannot be ruled out (Rutter 2005; Lord et al. 2020), Lundström and colleagues concluded that this is unlikely to be a driving factor in the increase of diagnosed cases in children (Lundström et al. 2015). Evidence suggests that most autistic adults in England are undiagnosed, particularly among women and in older age groups, with one population-based cohort study concluding that over 90% of autistic people aged 50 years or older were undiagnosed (O’Nions et al. 2023).

Under the 2009 Autism Act, local authorities and NHS organisations gained new responsibilities to develop services to support autistic people, and their families and carers. Since then, the National Institute for Health and Care Excellence (NICE) published guidelines on diagnosis and management of autism in adults (NICE 2012, updated 2021). The Autism Self-Assessment Framework survey of local authorities throughout England reported that autism assessment services were available in all areas, but that waiting times were increasing beyond the NICE recommended limit of three months (Public Health England 2017, updated 2019). New government funding for autistic children, young people and adults was announced for the period 2021-2026 with almost £75 million allocated in the first year in England (Department of Health and Social Care and Department for Education 2021).

Psychosocial interventions and autism psychoeducation are recommended for core features of autism and for developing life skills, but evidence for their benefits is needed (Lord et al. 2020). Large scale randomised controlled trials of treatment of anxiety (STRATA) (Rai et al. 2024) and of depression (ADEPT-2) in autistic adults are due to report soon (McKeon et al. 2024). For autistic adults without a learning disability or with a mild learning disability and who are having difficulty obtaining or maintaining employment, NICE recommends considering an individual supported employment programme (NICE 2012, updated 2021).

Autism

The concept of autism gained recognition in the mid-20th century and is still evolving (Frith 1991; Silberman 2015; Lord et al. 2020). It remains unclear whether autism comprises one condition or a range of similar inter-related neurodevelopmental conditions, with separate subtypes. Experts have achieved a broad consensus on what constitutes the category of autism, and diagnostic guidance set out in the fourth and fifth Diagnostic and Statistical Manual (DSM-IV and -5) (APA 1994; 2013) and the World Health Organization (WHO) International Classification of Diseases (ICD-10 and ICD-11) (WHO 1993, 2019, 2024) are similar. Both systems require information on early childhood development and significant impact on functioning for diagnosis.

Assessment of autism

Case assessment of autism

In surveys of autism in childhood, information on behaviour and development is collected from parents and teachers. For adults, the ideal scenario would involve assessments of directly observed current behaviour and information on both early development and on current day to day functioning over an extended period. This is not a practical option for a large general population survey of adults. Therefore, the assessment process used on APMS 2007, and replicated on APMS 2014 and APMS 2023/4, was based on a combination of self-report screening data collected at the phase one interview and a semi-structured examination carried out by a clinically trained research interviewer at the phase two interview (Brugha et al. 2009). This multi-stage case assessment for autism is similar in structure to that used in the APMS series since 1993 for the assessment of psychotic disorders.

The process used in APMS since 2007 involves a detailed validation assessment (Brugha et al. 2011). It included the following stages:

A. Phase one AQ-20 self-completion questionnaire

B. Selection of cases for phase two assessment

C. Phase two ADOS examination of a subset of selected adults

D. Weighting to adjust for selection probabilities and non-response.

This approach has undergone an extensive programme of validation work at the University of Leicester supported by the NHS and Department of Health and Social Care (Brugha et al. 2009; 2011; 2012; 2016a). The validation programme involved calibration of the ADOS with other research instruments for autism assessment; interviews with participants’ parents and other family members; comparison with further data collected from community, learning impairment, and patient samples; consensus ratings of participant vignettes with autism practitioners; and engagement with psychiatrists and epidemiologists with expertise in this field. The validation of the APMS process for identifying autism has been more extensive than that of other conditions covered on the survey.

A. Phase one screening: Autism Spectrum Quotient

The full Autism Spectrum Quotient (AQ-50) is one of few fully structured questionnaires designed to fulfill the aim of screening for possible autism in adult participants (Baron-Cohen et al. 2001). The AQ-50 was reported in clinical populations to have good correspondence with a full autism diagnosis (Baron-Cohen et al. 2001). Other available validated questionnaires tend to be longer (Constantino et al. 2003; Ritvo et al. 2008). A clinical diagnosis cannot be derived from the AQ-50 - it is a test designed to identify potential underlying autistic traits.

The full AQ consists of 50 items. To minimise participant burden on the already long APMS 2007 questionnaire, a shorter 20 item version was derived using data collected by two of the AQ authors in the development of the full schedule. Details of the modelling undertaken to select the best subset of items are given in a separate technical report (Brugha et al. 2011). The AQ-50 questionnaire is composed of items designed to assess five broad dimensions: social functioning, imagination, communication, attention switching and attention to detail. The 20 adopted items selected by the modelling procedure as the best predictors of a positive autism assessment spread quite evenly across these categories: six were social functioning items; four, communication; four, attention to detail; three, attention switching; and three, imagination. The AQ-20 was discussed by an expert panel and tested in the cognitive pilot conducted as part of the APMS 2007 development work. Further modelling took place using a random sample of adults in contact with mental health services. This identified the 17 most predictive AQ items used in the 2007 survey, these were retained and three (which had performed poorly in the 2007 data) were replaced with items with improved prediction selected from the original AQ-50 (Tyrer et al. 2013). The revised 20 item version of the AQ is reproduced in full in the questionnaire in Appendix D of the APMS 2023/4 Methods documentation.

A score was generated for each participant based on their responses to the 17 AQ items included in both the 2007 and 2014 surveys. Each response indicative of autism was given one point, so that a higher score indicated greater likelihood that the person may be autistic. The AQ-20 is a self-completion questionnaire, and it was administered via a laptop in the phase one interview. Because AQ-20 is a brief test and not a diagnostic measure, a clinical examination was included in the phase two interview. On APMS, the AQ was used only to exclude participants with an extremely low likelihood of being autistic (those with an AQ-20 score of between zero and three) and to inform the selection probabilities for phase two. It was not used to positively identify autism.

B. Selection of cases for phase two assessment

To produce estimates of the prevalence of autism amongst adults living in private households in England, a two-phase approach was adopted consisting of a phase one screen followed by a phase two clinical examination for a subset of participants, described in the APMS 2023/4 Methods chapter.

Participants were selected for phase two based on their phase one responses and agreement to be contacted by the University of Leicester, who conducted the phase two examination. Those with a higher AQ score had a higher chance of being selected. In APMS 2014 the selection probabilities were based on participants’ AQ score and whether they were male or female. In APMS 2023/4 the same autism sampling fractions were applied to both male and female participants, to ensure that a sufficient number of women were examined.

In summary:

• No participants with an AQ score of 0 to 3 were selected for a phase two ADOS examination.
• A subsample of participants (16%) with an AQ score between 4 and 7 were selected for phase two.

All participants with an AQ score of 8 or more were selected for phase two. It was not feasible for all phase one participants to have a phase two assessment, and this approach was designed so that those predicted to have the highest likelihood of being autistic had the highest likelihood of being assessed, combined with having a large enough sample size to be able to generate estimated rates of autism for the population as a whole.

C. Phase 2 assessment: Autism Diagnostic Observation Schedule (ADOS) 4

The second phase examinations were carried out by clinically trained research interviewers from the University of Leicester. The assessment of conditions such as autism required a more flexible interview than was possible at the first phase, and the use of judgement in rating clinical criteria for diagnostic classification. The Autism Diagnostic Observation Schedule (ADOS), Module 4, was completed with 884 participants at the APMS 2023/4 phase two; 628 in APMS 2014 and 618 in 2007). The ADOS is a semi-structured clinical examination of whether current behaviour is consistent with a diagnosis of autism. It is a widely recommended ‘gold standard’ clinical research examination instrument for autism that is used to rate information on adult functioning, which does not require involvement of an informant, which would have been impractical in an adult household survey (Lord et al. 2002).

Because the ADOS does not offer sufficient opportunity to measure restricted and repetitive behaviours, which are emphasised in DSM-5 and ICD-11, additional questions on restricted, repetitive patterns of behaviour and sensory differences were included in the phase two interview.

The ADOS and its algorithm have been validated in previous clinic-based testing, but prior to APMS 2007 they had rarely been used with older adults or in a general population setting (Gotham et al. 2008). The methods and results of a quality assurance and validation study made use of clinician ratings and developmental interviews with parents and other informants to guide severity and clinical significance thresholds (Brugha et al. 2009). That study found that the ADOS performed well, and its results have informed the case threshold used in this report. The ADOS consists of a series of tasks that evaluate communication, reciprocal social interaction (social functioning), creativity, imagination and stereotyped interests and restricted interests. These tasks are rated by a trained examiner. The ADOS ratings that correspond to autism criteria are summed to produce an overall score. The recommended threshold of 10 or more is applied in this report to indicate a case of autism, validated in the same population (Brugha et al. 2012). It is possible that using the threshold of 10, rather than 7, could potentially lead to missing some cases with less observable autism features, as discussed more fully by Brugha et al. (Brugha et al. 2011).

D. Weighting to adjust for selection probabilities and non-response

For the designation of an autism outcome the following approach was used:

• Adults with a phase one AQ score of 4 or more who had an ADOS examination, the results of the ADOS were used.
• Adults with a phase one AQ score of 3 or less were designated autism-negative, regardless of whether an ADOS examination was completed.
• Adults with a phase one AQ score of 4 or more who did not have an ADOS examination (e.g. due to non-selection, refusal or non-contact) were excluded from the analysis, and a weighting strategy was applied to take account of their absence and to address non-response biases.

For analysis of estimated prevalence of disorders assessed at phase two (autism, psychosis and eating disorders), the weighted phase two participants were added to the set of phase one participants who were not eligible for phase two, the prevalence being assumed to be zero for the not eligible group. Those not eligible were given their phase one weights. The sampling and weighting strategy is described in more detail in Section 4 Weighting the data in the APMS 2023/4 Methods documentation.

For the analyses presented in this report, the 2007, 2014 and 2023/4 samples were combined to increase the sample size available for subgroup analysis. The survey series has been designed with the intention that samples can be combined, especially for analyses of low prevalence disorders or subgroups. This approach is also taken in the chapter on psychotic disorder.

Autism prevalence in 2007, 2014 and 2023/4, by age and sex

The estimated prevalence of autism in 2023/4, as indicated by a score of 10 or more on the ADOS, was 0.9% of the adult population in England (equivalent to 9 per thousand adults). Prevalence in the wider adult population is likely to be between 0.5% and 1.7%, referred to as the 95% confidence interval (95% CI). This equates to about 430 thousand adults in England. There was no indication that there has been any change in prevalence over time. The prevalence of autism in the 2023/4 survey was similar to that for the 2007 (1.0%, 95% CI 0.5, 2.0) and 2014 (0.7%, CI 0.3, 1.3) surveys, with largely overlapping confidence intervals.

A total of 30 probable cases were identified in the 2023/4 sample, because a sub-sample of respondents was selected for a phase two interview. This small base means that great caution is required in interpreting the population distribution of autism. To improve how robust the estimates are, the 2007, 2014 and 2023/4 samples have been combined, yielding 61 participants identified with autism. Estimates based on the combined sample are more robust than those based on the separate 2007, 2014 and 2023/4 samples.

For more information: Table 10.1

Where data on demographic and socio-economic characteristics were collected consistently since 2007, the results in this chapter draw on a dataset that combines the 2007, 2014 and 2023/4 samples and are analysed by sex (male and female) rather than gender (men and women). See How to interpret the findings for information on how changes over time were assessed.

The overall prevalence of autism using this combined data was 0.8% (CI 0.6, 1.2). The size of this confidence interval is similar to that of some of the other low prevalence disorders considered on APMS.

Autism prevalence varied by sex with males (1.5%, CI 1.0, 2.3) more likely than females (0.2%, CI 0.1, 0.5) to be assessed as autistic. Prevalence of a positive autism assessment varied by age, although there was no clear pattern.

For more information: Table 10.2 and Table A1 for confidence intervals

Variation by other characteristics in combined 2007, 2014 and 2023/4 sample

Ethnic group

In age-standardised analyses, prevalence of autism varied between ethnic groups. It was higher among White adults (0.9%, CI 0.6, 1.3) and Asian/Asian British adults (1.0%, CI 0.2, 4.9) and lowest in those identifying to a Mixed/multiple or other ethnic group (0.1%, CI 0.0, 0.5). No Black/Black British participants in the sample were assessed as autistic. It should be noted that the number of participants in some ethnic groups was small and the confidence intervals around estimates were wide.

For more information: Table 10.3 and Table A2 for confidence intervals.

Employment status

In age-standardised analysis based on working age adults (aged 16 to 64), there were no statistically significant differences in adults assessed as autistic by employment status.

For more information: Table 10.4

Problem debt

Problem debt was defined as being seriously behind with debt repayments or having one’s utilities cut off. In age-standardised analysis, using the 2023/4 sample only, no statistically significant variation in autism prevalence was found by experiences of problem debt. See the APMS 2023/4 Methods documentation for more information on how problem debt was derived.

For more information: Table 10.5

Area-level deprivation

In age-standardised analyses, autism prevalence was highest among those living in the two most deprived quintiles, compared with those living in less deprived areas. 1.8% of those living in areas in the most deprived quintile and 1.6% of those living in the second most deprived quintile were assessed as autistic, compared with between 0.2% of those living in areas in the least deprived quintile.

For more information: Table 10.6

Region

Due to small base sizes, regions were grouped into four areas (North, Midlands and East, South, and London) for this analysis due to the low number of cases of adults assessed as autistic in APMS. In age-standardised analyses, the proportion of adults assessed with autism was highest in the North (1.3%) of England and lowest in among adults in London (0.4%).

For more information: Table 10.7

Co-occurring conditions

Physical health conditions

In age-standardised analysis of APMS 2023/4 data, those without a limiting health condition (1.2%) were more likely to be autistic than those with a physical health condition (0.4%).

For more information: Table 10.8

Common mental health conditions

In age-standardised analysis, there was no statistically significant variation by common mental health condition.

For more information: Table 10.8

Self-diagnosis and professional diagnosis of autism

Participants were shown a list of mental health conditions and asked whether they thought that they had ever had any of them. In APMS 2023/4 the list was expanded to include ‘autism spectrum disorder’. Those who reported that they thought that they were autistic were asked if this had been diagnosed by a professional, and if so, whether this condition had been present in the past 12 months.

Overall, 165 adults (3.4%) thought that they were autistic and 59 adults (1.2%) reported that this had been diagnosed by a professional.

Due to small sample sizes, the presentation of results was constrained. However, initial analysis identified little correspondence between professionally diagnosed autism and ADOS-identified autism.

For more information: Table 10.9

Treatment and service use

Participants were asked about use of different types of mental health treatment and services. Two types of mental health treatment were asked about: current medication and psychological therapy for a mental or emotional problem. The use of a range of health, community and day care services over the past year were also asked about. This treatment and service use could have been for any condition and was not necessarily related to autism.

In combined data from 2007, 2014, and 2023/4, people identified as autistic were no more likely than non-autistic people to report currently receiving treatment for a mental or emotional problem, including medication, psychological therapy, or a combination of these two types of treatment. One in ten autistic adults (10.4%) reported current receipt of any mental health treatment.

Adults identified as autistic were less likely than non-autistic adults to have used health services for a mental health reason. 6.7% of adults identified as autistic reported using any health care service for a mental or emotional problem, compared with 12.9% of those who were non-autistic. Those who were autistic were no more or less likely to report having used community care or day care services in the past year.

For more information: Table 10.10

APMS is one of the best available sources of data on the prevalence of autism in the general population. The combined autism prevalence in adults in private households in England based on the 2007, 2014 and 2023/4 APMS surveys was about one adult in a hundred (0.8%, CI 0.6, 1.2). In these surveys, adults were interviewed if they were able to participate fully in a general population survey. Adults who would be unable to participate in the APMS because of intellectual disability were represented in an extension to the 2007 APMS (Brugha et al. 2016b). Taking account of the higher prevalence of autism in the intellectual disability population only raised the overall prevalence slightly, given the low proportion of the population living in such settings (from 1.0% in private households in 2007 to 1.1% including those living in group residential settings (Brugha et al. 2012)).

In the discussion that follows, comparisons with other studies are almost entirely based on research on people with identified (recorded, diagnosed) autism or on people who self-identify as being autistic.

Prevalence has remained stable over time. There was no significant difference between the prevalence of autism identified in 2007, 2014 and 2023/4. Two previous studies in children have shown that rates of independently assessed autism remain stable over multiple time points. The prevalence of autism in 5 to 15 year old children remained stable in general population surveys in England conducted in 2004 and 2017 (Marcheselli et al. 2018). The annual prevalence of the autism symptom phenotype in children assessed by a validated parental telephone interview was found to be stable during a 10-year period in Sweden during which registered diagnoses rose significantly (Lundström et al. 2015). NHS England figures, which analyses patient GP records, found that the percentage of patients with a diagnosis of autism increased from 0.6% in 2017-18 to 1.2% in 2022-23 and 1.3% in 2023-24 (NHS England 2024). Unlike APMS, these figures do not cover adults who are not in touch with NHS services and the APMS results show that autistic adults are less likely to use NHS services than the non-autistic population.

A higher prevalence of autism in men than women was found in all three APMS surveys. This is consistent with most research on autism (Brugha et al. 2011, Tromans et al. 2024). It is likely that while autism is more common in men than women, the difference between males and females may have been overstated and there has been a greater level of underdiagnosis in women. A meta-analysis in 2017 by Loomes and colleagues reported that males had closer to three times higher prevalence than females, rather than four times higher as previously reported (Loomes et al. 2017). In a survey extending the coverage of the 2007 APMS, no difference in autism prevalence was found between adult males and females with moderate, severe or profound intellectual disability (Brugha et al. 2016b). Autism assessments, including ADOS, focus on observable features. This may insufficiently consider less clearly manifested autistic traits (Cook et al. 2024), which may be more likely among women than men (Hull et al. 2020). Additionally, assessments for autism may draw more on how the condition manifests in men, leading to further under identification of autism in women (Trubanova et al. 2014). For example, Rynkiewicz et al. (2016) report that autistic females present with more vivid and energetic gestures on ADOS-2 examination and thus may be at risk of underdiagnosis.

There was variation in autism prevalence among adults of Asian and White ethnicity. Combined data from 2007, 2014 and 2023/4 allowed analysis of autism prevalence by ethnic group for the first time in the series. Autism prevalence was higher among White adults (0.9%) and Asian/Asian British adults (1.0%) and lowest in those identifying to a Mixed/multiple or other ethnic group (0.1%) although the causal relationship is unclear. Secondary analysis of a survey of adults registered with NHS GP surgeries in England showed higher rates of self-identified autism among White adults, but a lower prevalence in Asian or Asian British participants (Tromans et al. 2024). In contrast, national experimental statistics (NHS England 2024) report a high percentage of registered patients with a diagnosis of autism who are of mixed/multiple ethnic groups (1.87%; 95% CI 1.85, 1.90), compared to White patients (1.49%, CI 1.48, 1.49), Asian or Asian British patients (0.67, CI 0.66, 0.68), and those classified as Other ethnic group (0.71%, CI 0.70, 0.73), though this data reflects clinically identified autistic cases, in contrast to the research-identified autistic cases reported in the APMS. In general, autism prevalence studies across different countries tend to identify the highest autism prevalence in the majority ethnic group of the population in which the prevalence study took place, with lower estimates for minority ethnic groups (Tromans et al. 2021).

People living in deprived areas were more likely to be autistic. 1.8% of those living in areas in the most deprived quintile and 1.6% of those living in the second most deprived quintile were assessed as autistic, compared with between 0.2% of those living in areas in the least deprived quintile. This is consistent with existing evidence finding that higher levels of socioeconomic deprivation are associated with higher rates of diagnosed autism (O’Nions et al. 2023). This has also been shown in children in a national school census in England (Roman-Urrestarazu et al. 2021).

Few autistic adults had an autism diagnosis. Adults interviewed in the APMS in 2007 and 2014 were not asked if they were autistic. However, it was reported that none of the participants identified as having autism in the 2007 APMS had previously been given a formal autism assessment or diagnosis (Brugha et al. 2011). In primary care in England, autism identification and diagnosis rates have been rising exponentially between 1998 and 2018, with relative rises in new diagnoses in adults (Russell et al. 2022). Further year on year rises have been observed in NHS England analyses of GP records, with 1.3% of adults diagnosed with autism in 2023-4 (NHS England 2024). These data are in line with APMS autism prevalence in 2007, 2014 and 2023/4. Lundström and colleagues (2015) also found diagnosis rates in children to be rising during the 10-year period from 1993 to 2002 during which parent reported autism traits in the population remained stable.

Autistic adults were no more likely to have a co-occurring common mental health condition or to report using health services. Autistic adults in the survey were no more likely than non-autistic adults to be identified with a physical or common mental health condition. This result was surprising and might reflect a lack of insight and disclosure in autistic adults, or that the tool used to identify common mental health conditions in the survey did not work as well with autistic adults. They were also no more likely to use treatment or services for a mental health reason than non-autistic adults. In contrast, every other condition examined in this and previous APMS has been shown to be associated with increased use of treatment and health services (Brugha et al. 2016a). This finding appears at odds with a prior systematic review on healthcare service use among autistic adults (Gilmore et al. 2022), which reported that most eligible articles described ‘autistic adults had equal or higher use of healthcare services than non-autistic adults.’ However, this may be a reflection on group differences that may exist between research-identified autistic adults (as reported in the APMS), and autism surveillance work that reports on autistic people identified through the educational system and/or clinical practice. It may also reflect barriers to accessing health services faced by autistic people (Tromans et al. 2024), and the possibility that the lack of a formal diagnosis may exacerbate such barriers.

Autism is a life-long condition, and autistic adults may need life-long support. Autistic adults have enduring difficulties with communication and social understanding, though they can also have additional capabilities such as special memory skills and pitch perception (Meilleur et al., 2015). There are no effective medication-based interventions for core autistic features in autistic adults (NICE 2012, updated 2021). NHS specialist autism teams have been developed throughout England to improve identification of autism and to support people through extra provision of psychology, speech and language, and occupational therapy. Care services for identifying and supporting autistic people have been developed throughout England. Training in autism (and in learning disability) is now mandatory for all health and social care staff. These public services are based on the principle that carers and health and social care staff can recognise autism and learn how to understand and communicate with autistic people. Providing informed health and social care to autistic adults could lead to real improvements in their quality of life.

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Please cite this chapter as:

Tromans, S., Clery, E., Randall, E., Morris, S., Gullon-Scott, F., Morgan, Z., McManus, S., Brugha, T. (2025). Autism spectrum disorder. In Morris, S., Hill, S., Brugha, T., McManus, S. (Eds.), Adult Psychiatric Morbidity Survey: Survey of Mental Health and Wellbeing, England, 2023/4. NHS England.