Evidence map›Paper›PMID 41298836›Full record

ArticlePediatric research2026

Social epidemiology of gender diversity in early adolescents.

Jason M Nagata, Karen Li, Shirley S Sui, Patrick Low, Jonanne Talebloo, Christopher D Otmar, Iris Yuefan Shao, Kyle T Ganson, Alexander Testa, Jinbo He and 3 more

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In one paragraph

Article in Pediatric research, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Gender diversity and cholesterol in early adolescence: Findings from the Adolescent Brain Cognitive Development Study.International journal of cardiology. Cardiovascular risk and prevention · 2026
    Article
  2. Article
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

13 authors.

Jason M NagataDepartment of Pediatrics, University of California, San Francisco, San Francisco, CA, USA. jason.nagata@ucsf.edu.ORCID http://orcid.org/0000-0002-6541-0604
Karen LiDepartment of Pediatrics, University of California, San Francisco, San Francisco, CA, USA.
Shirley S SuiDepartment of Pediatrics, University of California, San Francisco, San Francisco, CA, USA.
Patrick LowDepartment of Pediatrics, University of California, San Francisco, San Francisco, CA, USA.
Jonanne TaleblooDepartment of Pediatrics, University of California, San Francisco, San Francisco, CA, USA.
Christopher D OtmarDepartment of Pediatrics, University of California, San Francisco, San Francisco, CA, USA.
Iris Yuefan ShaoDepartment of Pediatrics, University of California, San Francisco, San Francisco, CA, USA.
Kyle T GansonFactor-Inwentash Faculty of Social Work, University of Toronto, Toronto, ON, Canada.
Alexander TestaDepartment of Management, Policy and Community Health, University of Texas Health Science Center at Houston, Houston, TX, USA.
Jinbo HeSchool of Humanities and Social Science, The Chinese University of Hong Kong, Shenzhen, Guangdong, China.
Orsolya KissCenter for Health Sciences, SRI International, Menlo Park, CA, USA.
Claire D BrindisDepartment of Pediatrics, University of California, San Francisco, San Francisco, CA, USA.
Fiona C BakerCenter for Health Sciences, SRI International, Menlo Park, CA, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundFew large U.S. cohort studies have examined multidimensional measures of gender diversity; therefore, this study investigates their associations with sociodemographic factors in a national sample of 12- to 13-year-old adolescents.

methodsWe conducted a cross-sectional analysis of Adolescent Brain Cognitive Development (ABCD) Study data (2019-2021, Year 3 follow-up, N = 10,089). Associations between sociodemographic characteristics and gender were evaluated using ordinal logistic regression for ordinal measures (gender non-contentedness and gender expression), multinomial regression models for categorical measures (transgender identity and felt gender), and linear regression models for continuous measures (felt gender and gender spectrum).

resultsGender spectrum measures revealed the most diverse responses: 25.9% of sex-assigned females self-describing masculinity and 9.9% of sex-assigned males self-describing femininity. Female sex assigned at birth was associated with greater gender-diverse responses across all continuous and categorical gender measures compared to male sex assigned at birth. Higher household income was associated with less gender diversity relative to lower household income.

conclusionAssessment of gender across multiple measures beyond binary gender identity (e.g., transgender vs. cisgender) may yield more diversity of responses in early adolescents. Future research could explore explanations for the sociodemographic factors associated with greater gender diversity in early adolescents. IMPACT: Our study uses a large and diverse cohort to analyze sociodemographic associations with gender diversity using multidimensional measures. Across gender measures, female sex assigned at birth and lower household income were associated with greater gender diversity. Future research on gender diversity in early adolescents should use multidimensional gender measures to better understand the nuances of gender development.

Indexed as

Gender IdentityAdolescentAdolescent DevelopmentChildCross-Sectional StudiesFemaleGender-Nonconforming PersonsHumansMaleSocial GroupSociodemographic FactorsSocioeconomic FactorsUnited States

Identifiers

PMID41298836
PMCPMC13524781

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.