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Record W4412515057 · doi:10.1186/s12889-025-23651-x

Estimates of the prevalence of autism spectrum disorder in the Middle East and North Africa region: A systematic review and Meta-Analysis

2025· review· en· W4412515057 on OpenAlexaboutno aff
Aishat F. Akomolafe, Bushra M. Abdallah, Fathima R. Mahmood, Amgad M. Elshoeibi, Aisha Abdulla Al-Khulaifi, Elhassan Mahmoud, Yara Dweidri, Nour Darwish, Duaa Yousif, Hafsa Khalid, Majed Al-Theyab, Muhammad Waqar Azeem, Durre Shahwar, Madeeha Kamal, Majid Alabdulla, Salma M. Khaled, Tawanda Chivese

Bibliographic record

VenueBMC Public Health · 2025
Typereview
Languageen
FieldNeuroscience
TopicAutism Spectrum Disorder Research
Canadian institutionsnot available
FundersQatar National Research FundFonds National de la Recherche LuxembourgUniversity of Washington
KeywordsBiostatisticsMedicineMeta-analysisPublic healthMiddle EastEpidemiologyAutism spectrum disorderAutismSystematic reviewEnvironmental healthDemographyMEDLINEPsychiatryPathologyGeography

Abstract

fetched live from OpenAlex

Prevalence estimates for autism spectrum disorder (ASD) in the Middle East and North Africa (MENA) region are not readily available, amid a lack of recent evidence. In this study, we estimated the prevalence of ASD in the MENA region by synthesising evidence from published studies. We conducted a systematic review and meta-analysis, searching PubMed, EMBASE, Scopus, and CINAHL for studies assessing ASD prevalence in the MENA region. Risk of bias was assessed using the Newcastle Ottawa scale. A bias-adjusted inverse variance heterogeneity meta-analysis model was used to synthesize prevalence estimates from included studies. Cochran’s Q statistic and the I 2 statistic were used to assess heterogeneity, and publication bias assessed using funnel and Doi plots. Of 3,739 studies identified, 19 met the inclusion criteria, published during the period 2007–2025, from Iran, Oman, Libya, Egypt, Saudi Arabia, Lebanon, United Arab Emirates, Bahrain, and Qatar, Iraq. Country specific prevalence estimates ranged from 0.01% in Oman in 2009 to 6.50% in one study from Iraq in 2024. The overall prevalence of ASD in the MENA region was 0.14% (95%CI 0.02– 0.36%), with significant heterogeneity (I 2 = 99.8%). Overall ASD prevalence was 0.04% (95%CI 0.00–0.13, I 2 = 99.4%) for studies done before 2015 and 0.45% (95%CI 0.17–0.87, I 2 = 99.4%) for studies after 2015. Overall ASD prevalence was high in studies that used the Modified Checklist for Autism in Toddlers (M-CHAT) only [1.66% (95%CI 0.15–4.33, I 2 = 97.5%)] while the overall ASD prevalence was 0.14% (95%CI 0.00-0.46, I 2 = 99.9%) for studies that used the Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition (DSM-IV) criteria for diagnosis. Estimates of the prevalence of ASD vary widely across the MENA region, with variability in ASD prevalence estimates by diagnostic methods and sampling approaches. While the data suggest a possible increase in prevalence during the study period, this observation warrants further investigation through more robust, longitudinal, and methodologically consistent studies. PROSPERO registration ID CRD42024499837.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.024
metaresearch head score (Gemma)0.054
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Meta-analysis · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.024
Threshold uncertainty score0.129

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0240.054
Meta-epidemiology (narrow)0.0040.002
Meta-epidemiology (broad)0.0190.047
Bibliometrics0.0130.011
Science and technology studies0.0010.001
Scholarly communication0.0050.003
Open science0.0020.002
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0030.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.313
GPT teacher head0.381
Teacher spread0.067 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designMeta-analysis
Domainnot available
GenreReview

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations14
Published2025
Admission routes1
Has abstractyes

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