Evidence map›Paper›PMID 40075145›Full record

ArticleScientific reports2025

Female reproductive health trends and autism spectrum disorder prevalence between 2000 and 2024.

Adil Abdul-Rehman Siddiq Al-Salihy

Abstract read
In one paragraph

Article in Scientific reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing 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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

1 author.

Adil Abdul-Rehman Siddiq Al-SalihyConsultant in Clinical Psychology\Neuro- & Psycho-Therapy Science, Head of the Mental Health Department, Psychological Research Center, Ministry of Higher Education & Scientific Research, Baghdad, Iraq. adil_alsalihy@yahoo.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This study investigates the correlation between female reproductive health parameters and Autism Spectrum Disorder (ASD) prevalence from 2000 to 2024. The analysis used advanced statistical and machine learning models to identify trends in key reproductive indicators and their association with ASD prevalence. Significant positive correlations were observed between ASD prevalence and maternal age, while negative correlations were found with antral follicle count, Anti-Müllerian Hormone (AMH) levels, and fertility rate. The Random Forest model emerged as the most accurate predictive tool, explaining 96.9% of the variance in ASD prevalence. Maternal age was the dominant predictor of the variables analyzed, contributing approximately 75% of the model's predictive power, while estradiol levels and Follicle Stimulating Hormone (FSH) contributed significantly less. These findings highlight potential statistical associations but do not establish causality. Further research is necessary to validate these associations and explore underlying biological mechanisms.

Indexed as

Autism Spectrum DisorderReproductive HealthAdolescentAdultAnti-Mullerian HormoneEstradiolFemaleFollicle Stimulating HormoneHumansMachine LearningMaternal AgeMiddle AgedPrevalenceYoung AdultAnti-Mullerian HormoneEstradiolFollicle Stimulating HormoneAnti-Müllerian hormone (AMH)Autism spectrum disorder (ASD)Female Reproductive HealthFollicle stimulating hormone (FSH)Machine learningMaternal agePredictive models

Identifiers

PMID40075145
PMCPMC11904183

What Socratic holds

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LicenceCC BY-NC-ND
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Registered trials

None linked

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 Socratic graph.