Evidence map›Paper›PMID 41041384›Full record

ArticleFrontiers in public health2025

Real-world evidence from a multi-center pediatric network: greenness exposure and autism spectrum disorder in urban China.

Wenxu Yang, Shiwen He, Sophia Zuoqiu

Abstract readMulticenter Study
In one paragraph

Article in Frontiers in public health, 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

3 authors.

Wenxu YangDepartment of Child Healthcare, Chengdu Women and Children's Hospital, School of Medicine, University of Electronic Science and Technology of China, Chengdu, China.
Shiwen HeDepartment of Environmental Science and Engineering, College of Architecture and Environment, Sichuan University, Chengdu, China.
Sophia ZuoqiuDepartment of Industrial Engineering, Pittsburg Institute, Sichuan University, Chengdu, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: Childhood autism spectrum disorder (ASD) is a global public health concern and its prevalence is increasing rapidly in developing countries such as China. The mechanism behind ASD development remains unclear. Greenness exposure is reportedly associated with various health outcomes, however, the connection between greenness exposure and ASD is relatively unexplored. Methods: We designed a two-stage screening process and conducted city-wide screening for early childhood ASD to investigate the association between greenness exposure and ASD prevalence in a megacity in southwest China. Results: We screened 13,458 children from 0-52 months through 20 local primary care hospitals and the estimated ASD prevalence was 0.55%. We matched greenness exposure, air pollution exposure, and weather condition with ASD diagnosis outcomes based on the study subject's geographic information. Gender (male) and age (older) were significantly associated with higher odds of being diagnosed with ASD. Discussion: Although the association between ASD diagnosis and greenness was not statistically significant, real-world data may help improve ASD screening methods and guide future studies. Our findings highlight the potential role of real-world environmental and health data in informing sustainable urban and pediatric health policies.

Indexed as

Autism Spectrum DisorderEnvironmental ExposureUrban PopulationAir PollutionChild, PreschoolChinaFemaleHumansInfantInfant, NewbornMalePrevalencechild developmentchildhood ASD prevalencegreenness exposureNDVIreal-world data

Identifiers

PMID41041384
PMCPMC12484007

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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.