People often wonder how many Autistic people there are in Aotearoa New Zealand. This is a difficult question to answer, as we do not have a single national system for recording autism diagnoses. Over the past few years, Nick Bowden and colleagues have been working to address this problem using administrative data from Stats NZ’s Integrated Data Infrastructure. This article explains what they have learned so far.

Introduction: Why autism prevalence is changing

Around the world, reported autism rates have increased substantially over the past two decades (Zeidan et al., 2022). This pattern has been observed across high income countries such as the United States, the United Kingdom and Australia (Nielsen et al., 2024; Russell et al., 2022; Shaw, 2025). Most researchers now agree that these increases do not reflect a sudden rise in the number of Autistic people. Instead, they can be explained by improved awareness of autism among families, educators and health professionals, broader diagnostic criteria, better access to assessment services in some communities, and changes in how autism diagnoses are recorded in data systems (Fombonne, 2025).

Alongside these overall increases, international evidence shows that historical differences in autism identification by gender and ethnicity are also changing. Although boys are still more likely to be identified as Autistic than girls, the ratio has narrowed over time as clinicians have become more aware of how autism can present differently in girls and women (Grosvenor et al., 2024; Shaw, 2025). Similarly, autism identification rates among Indigenous and minoritised ethnic groups have increased in many countries. In some settings, rates among these groups now match or exceed those of majority populations  (Shaw, 2025). These changes are widely understood to reflect improved identification and reduced barriers to diagnosis rather than true biological differences in autism prevalence.

In Aotearoa New Zealand (henceforth Aotearoa), understanding autism prevalence has been more challenging. Unlike some other countries (e.g., the USA, Canada and Denmark), Aotearoa does not have a national autism surveillance programme or a population-based autism registry. This means there is no single system that records everyone who has received an autism diagnosis. At present, the only routine national estimate of autism prevalence comes from the New Zealand Health Survey, which asks parents whether they have ever been told that their child, aged between 2 and 14 years, ‘has autism spectrum disorder’ (Ministry of Health, 2025). While this provides valuable information, it relies on parent report rather than clinical records, is restricted to a narrow age band and, as it is based on a small percentage of the population, it is not possible to reliably examine autism prevalence among demographic sub-groups.

Because of these limitations, researchers have increasingly used the Integrated Data Infrastructure (IDI) to better understand autism in Aotearoa. The IDI is a large, secure research database managed by Stats NZ that links de-identified information from a wide range of government services, including health, education and disability support (Milne et al., 2019). Approved researchers can use the IDI for projects that serve the public good, while strict privacy and confidentiality protections are maintained.

Over the past decade, several studies have used the IDI to examine autism identification in Aotearoa. These include population-focused research developing an IDI-based autism case identification method (Bowden, Thabrew, Kokaua, Audas, et al., 2020), Pacific-focused studies conducted in partnership with Pacific community stakeholders examining autism rates and case complexity (Kokaua et al., 2023; Ruhe et al., 2022), and a Māori-focused study developed in partnership with Autistic Māori that explored autism rates and support needs (Tupou et al., 2025). Together, this body of work provides a strong foundation for understanding autism prevalence in Aotearoa using administrative data. This article synthesises that existing literature and builds on it by presenting, for the first time, national IDI-based trends in autism identification over a ten-year period.

What we already know from IDI-based autism research

Bowden and colleagues undertook the first major IDI-based autism study in Aotearoa in 2020 (Bowden, Thabrew, Kokaua, Audas, et al., 2020). This work developed a method to identify Autistic children and young people aged 0 to 24 years (henceforth children) using three national health and disability datasets: specialist mental health service records, public hospital admissions data and disability support needs assessment information. Using this approach, the study identified almost 10,000 Autistic children in the population, based on the 2015/16 fiscal year. Among eight-year-olds, the identification rate was one in 102, which represented approximately a 40% undercount compared to US-based estimates at the time. Importantly, the authors emphasised that the IDI-based method undercounts autism: it does not include individuals who have not been diagnosed as Autistic, nor those who do have a diagnosis but have not interacted with the publicly funded specialist services whose data are captured with the case identification method.

Subsequent IDI research using 2017/18 data focused specifically on Pacific children to explore why autism rates were significantly lower (53 per 10,000 0-24 year olds) compared with non-Māori, non-Pacific children (83 per 10,000) (Ruhe et al., 2022). Ruhe and colleagues found that when Pacific children were identified as Autistic, they were more likely to have indicators of higher support needs, such as learning disability or high-needs education funding, suggesting that Autistic Pacific children with lower support needs might be missing out on a diagnosis. Further work by Kokaua and colleagues explored one potential explanation for this pattern by examining parental education (Kokaua et al., 2023). They found that higher levels of formal parental education were associated with a greater likelihood of autism being identified among Pacific children. This finding highlighted the role of structural and systemic barriers in navigating diagnostic pathways and accessing services.

Tupou and colleagues also undertook a national study examining autism identification among Māori children using a Māori-centred, Autistic-led research approach (Tupou et al., 2025). This study found that autism identification rates in 2017/18 were lower for Māori (70.9 per 10,000 0-24 year olds) than for non-Māori (78.3 per 10,000). It also found that Autistic Māori were more likely to have a learning disability recorded and more likely to receive high-needs education funding. As with the Pacific-focused research, these findings were interpreted as reflecting inequities in access to diagnosis and support, particularly for Māori with lower formal support needs, rather than genuine differences in autism prevalence.

New national autism trends from the IDI

Building on this earlier work, Cure Kids funded new analyses using the IDI but with increased time coverage of data. This made it possible to examine autism identification trends in Aotearoa over the past decade. Over 10 years (2014/15 to 2023/24 fiscal year), the number of Autistic children aged 0 to 24 years identified in the IDI increased steadily, from around 11,500 individuals in 2014/15 to more than 27,500 in 2023/24 (see Figure 1). This reflects an increase in identified prevalence of 131% (0.74 to 1.71 per 100 people), a substantial increase that closely mirrors international trends (Zeidan et al., 2022).

Figure 1: Counts of children and young people aged 0-24 identified as Autistic in Aotearoa New Zealand administrative data, 2014/15 to 2023/24

Across all years, the majority of identified Autistic individuals were boys. However, the proportion of girls increased consistently over time (see Figure 2). In 2014/15, the male to female ratio was approximately 4:1. However, by 2023/24, this had reduced to 2.8:1. This pattern aligns with changed diagnostic practices and growing recognition that autism in girls has historically been under-identified (Grosvenor et al., 2024).

Figure 2: Male to female ratio of children and young people aged 0-24 identified as Autistic in Aotearoa New Zealand administrative data, 2014/15 to 2023/34

Important changes were also observed in identification patterns by ethnicity. Over the 10-year period, autism rates among Māori and Pacific children increased substantially compared to European & Other children (see Figure 3). Māori rates rose nearly 200% and Pacific over 250% compared to about 125% for European & Other. These trends are consistent with U.S. evidence showing that ethnic gaps in autism identification can narrow as awareness improves and barriers to diagnosis are reduced (Shaw, 2025). At the same time, they reinforce findings that inequities persist.

It is important to be clear about what these trends do and do not represent. The IDI does not capture all Autistic people in Aotearoa, and the figures reflect identified autism in the IDI rather than true prevalence. Increases over time are therefore best understood as reflecting improved recognition, access and recording rather than a sudden rise in autism itself. An additional limitation is that gender is recorded using a binary male/female classification, which does not reflect the full diversity of gender identities and experiences. This reflects the statistical standards in use at the time the data were collected, which largely capture sex assigned at birth rather than self-identified gender. Emerging Aotearoa research drawing on 2023 Census gender data has demonstrated that autism rates are significantly higher among those who identify outside of the male/female binary (3.7%) compared with males (2.3%) and females (0.7%) (Fraser et al., 2025). Together, these considerations highlight that observed trends and sex differences in administrative data are shaped not only by underlying neurodevelopmental variation, but also by diagnostic practices, service access and the way demographic information is captured. Despite these limitations, the IDI currently provides the most comprehensive national picture of autism identification available in Aotearoa.

Figure 3: Autism rates among children and young people aged 0-24 by ethnicity, 2014/15 to 2023/34

Where to next? Future priorities for autism data in Aotearoa

National autism trends derived from the IDI highlight both significant progress and important gaps in current knowledge. One clear priority for future work is ongoing monitoring of autism rates. Regularly updating IDI-based autism analyses would allow researchers, policymakers and communities to track changes over time, assess any changes in inequities, and respond more quickly to emerging needs.

Another important area for development is validation of the autism case identification method used within the IDI. While the current approach provides valuable population-level insights, the extent to which some Autistic people remain missing from administrative data is unknown. Further research is needed to better understand who is not being captured.

Improving data coverage is also critical. Expanding the range of data sources used to identify autism could substantially improve the completeness and accuracy of future estimates. In particular, improved access to primary care and outpatient health data would be valuable. Incorporating information from the Child Disability Allowance administered by the Ministry of Social Development and from Oranga Tamariki could also help identify children who may not appear in health datasets.

Building on this case identification method, subsequent IDI-based research could examine other aspects of the lives of Autistic children and their whānau. This could build on the substantial body of work already undertaken, including into patterns of health outcomes and health service use (Bowden, Schluter, et al., 2025; Bowden, Thabrew, Kokaua, & Braund, 2020; McLay et al., 2022; McLay et al., 2021; McLay et al., 2024; Schluter et al., 2024; Vu et al., 2024), education resourcing, experiences and outcomes (Bowden, Anns, et al., 2025; Bowden, Gibb, et al., 2022), interactions with the criminal justice system (Bowden, Milne, et al., 2022), and more generally, outcomes across the lifecourse (Bowden et al., 2024), including for parents and whānau (Gibb et al., 2025; O’Flaherty et al., 2025).

Finally, future autism prevalence research in Aotearoa should continue to be developed in partnership with Autistic people, whānau and communities. Māori-led, Pacific-led and Autistic-led research approaches are especially important for ensuring that findings are interpreted appropriately and used in ways that support equity, self-determination and improved access to services. Strengthening these partnerships alongside better data will be essential for building a more accurate, inclusive and useful national evidence base on autism in Aotearoa.

A note on language

There is no universal consensus on preferred language when describing autism, and preferences vary across individuals, communities, cultures and contexts. Drawing on guidance from recent scholarship, including Monk (2022), we recognise the importance of respecting this diversity of views and the limitations of any single linguistic approach.

In this article, we use identity-first language (e.g. Autistic person), reflecting evidence that this is commonly preferred within Autistic communities and is frequently used in contemporary autism research and advocacy in Aotearoa New Zealand.

We also acknowledge Māori concepts and terminology relating to autism, including takiwātanga, which emphasises autism as a person having their own time and space, and te kura urupare, which has been used in some contexts to describe autism. We recognise the cultural significance of these terms. However, given the absence of consensus on a single Māori term being widely preferred or consistently used, we have not adopted these terms within the body of this article.

Disclaimer

These results are not official statistics. They have been created for research purposes from the Integrated Data Infrastructure (IDI), which is carefully managed by Statistics New Zealand. For more information about the IDI please visit https://www.stats.govt.nz/integrated-data/.

Author bios

	Dr Nick Bowden is a Senior Research Fellow at the University of Otago who leads population-level autism research using Aotearoa New Zealand’s Integrated Data Infrastructure (IDI). His work focuses on understanding autism prevalence, inequities in identification and access to support, and long-term outcomes for autistic people, with a strong emphasis on partnership with autistic communities, Māori, and Pacific researchers.
	Joanne Dacombe is a researcher with the University of Otago. She is Autistic with an Autistic adult son and an Autistic grandson. She is passionate about Autism research that improves life outcomes for Autistics. She is active in governance and disability advocacy.
	Dr Troy Ruhe (Ngāpuhi, Ngāti Tūwharetoa, Ngāti Raukawa, Ma’uke) is a Research Fellow at the Va’a o Tautai – Centre for Pacific Health at the University of Otago. His primary research involves Pacific and Māori informed and nuanced interpretations of population-based health data that reflects the lived realities of Pacific and Māori communities.
	Dr Sujata Saha is a researcher with the University of Otago. She is a mathematician, with research experience in epidemiology and quantitative analysis. More recently, she has specialised in the use of the IDI for research focused on neurodevelopmental conditions.
	Dr Jessica Tupou (Kāti Māmoe, Kāi Tahu) is a senior lecturer in educational psychology at Te Herenga Waka, Victoria University of Wellington. Her research investigates autism through a Māori-centred lens, prioritising mātauranga Māori and the perspectives of Autistic Māori and their whānau. Working in close collaboration with communities, Jessica’s research explores early supports, whānau and educator experiences, and population-level data using inclusive, culturally responsive methodologies.
	Professor Laurie McLay is the Associate Dean of Research in Te Kaupeka Oranga | Faculty of Health at Te Whare Wānanga o Waitaha | University of Canterbury and is Director of the Autism Research Centre Aotearoa. Her primary research focus includes the co-design, development and evaluation of digitally-delivered supports that promote the health and well-being of Autistic children and those in their support network.

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