Evidence map›Paper›PMID 42078229›Full record

ReviewCureus2026

Global Autism Spectrum Disorder Prevalence Estimates and Associated Covariates: A Systematic Review and Meta-Regression Analysis.

John K Muthuka, Chrisphine Onyango, Japheth M Nzioki, Lucy K Chebungei, Ruvimbo Zimunya, Andrina Simengwa, Sara Kim, Desire A Nshimirimana, Rosemary Nabaweesi

Abstract readReview
In one paragraph

Review in Cureus, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Trial
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

9 authors.

John K MuthukaCommunity Health and Health Promotion, Kenya Medical Training College, Nairobi, KEN.
Chrisphine OnyangoChildren Behavior Services, Anderson Center for Autism, New York, USA.
Japheth M NziokiSchool of Nursing, Andrews University, Berrien Springs, USA.
Lucy K ChebungeiDepartment of Nursing, Kenya Medical Training College, Nairobi, KEN.
Ruvimbo ZimunyaChildren Behavior Services, Anderson Center for Autism, New York, USA.
Andrina SimengwaChildren Behavior Services, Anderson Center for Autism, New York, USA.
Sara KimSchool of Nursing, Andrews University, Berrien Springs, USA.
Desire A NshimirimanaCollege of Doctoral Studies, Grand Canyon University, Phoenix, USA.
Rosemary NabaweesiSchool of Global Health, Meharry Medical College, Nashville, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This review aimed to estimate the global prevalence of autism spectrum disorder (ASD) and identify methodological and contextual covariates influencing prevalence estimates. Despite increasing research, the true global burden of ASD remains unclear due to substantial variability in reported prevalence across studies. The specific methodological and contextual factors driving this heterogeneity have not been fully quantified. Electronic databases, including PubMed, Scopus, Web of Science, Embase, and Google Scholar, were systematically searched from 2004 to 2025. All human population-based studies were included, irrespective of region or diagnostic framework. Nineteen studies, comprising approximately 20.6 million participants, met the inclusion criteria and reported ASD prevalence. To estimate pooled prevalence, a random-effects model (REML) was used, and Bayesian hierarchical modeling was conducted to provide posterior estimates. Publication bias and sensitivity analyses were conducted, followed by meta-regression to account for covariates such as diagnostic framework, study setting, and region. The frequentist pooled prevalence of ASD was 0.8% (95% CI: 0.4%-1.7%), with substantial heterogeneity (I² ≈ 100%) and a wide prediction interval (0.03%-17.3%). Bayesian hierarchical modeling produced a posterior mean prevalence of 1.55% (95% CrI: 0.75%-4.1%), and a Bayesian sensitivity analysis excluding an extreme outlier study yielded a posterior mean prevalence of 0.9% (95% CrI: 0.6%-1.8%) with substantial heterogeneity (τ = 1.14, I² = 99.98%) and a prediction interval of 0.09%-9.5%, indicating strong consistency between frequentist and Bayesian estimates. Regional prevalence varied: North America (1.9%), Africa (6.3%) (wide confidence intervals reflecting limited data), Europe (0.4%), Latin America (0.2%), and the Middle East (0.6%). Meta-regression analysis demonstrated that ASD prevalence was influenced by diagnostic framework, study setting, and region (R² ≈ 0.78), and the combined impact of all covariates explained a substantial proportion of the variance in effect sizes. Our updated meta-analysis indicated that global ASD prevalence varies widely across regions, largely due to methodological and contextual differences rather than demographics alone. Standardized diagnostic practices, enhanced surveillance, and targeted investment in underrepresented regions are critical for improving the accuracy and comparability of prevalence estimates. This updated synthesis provides a more robust and context-sensitive estimate of global ASD prevalence and supports the interpretation of variability observed in prior studies.

Indexed as

autism spectrum disorder (asd)bayesian hierarchical modelingglobal epidemiologyglobal mental healthprevalencerisk predictorssystematic review and metaanalysis

Identifiers

PMID42078229
PMCPMC13134363

What OpenQuestion holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.