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Abstract A14: Infancy and childhood infections and pubertal timing in the LEGACY Girls’ Study

2020· article· en· W3094041423 on OpenAlexaff
Yun Huang, Irene L. Andrulis, Angela R. Bradbury, Saundra S. Buys, Mary B. Daly, Esther M. John, Lisa A. Schwartz, Mary Beth Terry, Jasmine A. McDonald

Bibliographic record

VenueCancer Prevention Research · 2020
Typearticle
Languageen
FieldMedicine
TopicGestational Diabetes Research and Management
Canadian institutionsSinai Health SystemLunenfeld-Tanenbaum Research Institute
Fundersnot available
KeywordsMedicineMenarcheBreast developmentProspective cohort studyHazard ratioDemographyPediatricsPubic hairEarly childhoodCohort studyInternal medicineHormoneConfidence interval

Abstract

fetched live from OpenAlex

Abstract An earlier age at pubertal development is associated with increased breast cancer risk, and Westernized countries are observing earlier ages of pubertal timing in girls. While increased rates of childhood obesity are associated with earlier ages of pubertal development, earlier ages of puberty are also observed in countries that are not experiencing high rates of childhood obesity. Prior evidence from a birth cohort in Hong Kong suggests that early life infections, as measured by hospitalizations, is associated with pubertal onset. Emerging evidence suggests that early life and childhood exposures to infection may impact pubertal development. Therefore, we aimed to assess whether indirect measures of infections in infancy (birth-12 months) and early childhood (1-5 years) are associated with the age of onset of puberty (menarche and breast and pubic hair development). We used data from the Infection Questionnaire from the multisite prospective LEGACY Girls Study where mothers/guardians reported on daughters’ indirect exposure to infection (daycare attendance, antibiotic use, physician visit due to fever, hospitalization due to infection) and specific exposure to infections (e.g., tonsillitis, cold sores). Mothers/guardians reported on daughters’ age at first menses and the onset of breast and pubic hair development using Tanner Staging (as defined as Tanner Stage 2 or higher). We used Cox Proportional Hazard Ratio (HR) models to examine the prospective association between infection history and pubertal timing. We considered site, race/ethnicity, and maternal education as possible confounders. In 615 girls (average age (SD) 9.5 (2.4) years) whose mother/guardians completed the Infection Questionnaire, 65% were white non-Hispanic, 18% were Hispanic, 5% were Black non-Hispanic, and 9% were Asian. Sixty-nine percent of mothers/guardians had a college degree or higher. We assessed frequency of infectious exposures across infancy and early childhood where 73% of girls ever used antibiotics, 59% of girls ever had an ear infection, 59% of girls ever attended daycare over 10 hours per week, 29% of girls visited a physician due to fever (measured in childhood only), 36% of mothers reported girls having 2 or more infections, and 6% of girls were ever hospitalized due to infection. In multivariable models controlled for socioeconomic and maternal factors, earlier age of pubic hair development was associated with hospitalization due to infection compared to never hospitalized (HR=1.53, 95% CI=1.07-2.21) and ever antibiotic use compared to never antibiotic use (HR=1.31, 95% CI=1.03-1.68). Compared to never, multivariable models suggested that earlier age at menarche was associated with physician visit due to fever (HR=1.30, 95% CI=1.04-1.63). We observed no association between infectious exposures and earlier breast development. These results suggest that infancy and childhood infectious exposures may be related to earlier pubertal development, but more studies are needed to confirm these findings. Citation Format: Yun Huang, Irene L. Andrulis, Angela R. Bradbury, Saundra S. Buys, Mary B. Daly, Esther M. John, Lisa A. Schwartz, Mary Beth Terry, Jasmine A. McDonald. Infancy and childhood infections and pubertal timing in the LEGACY Girls’ Study [abstract]. In: Proceedings of the AACR Special Conference on Environmental Carcinogenesis: Potential Pathway to Cancer Prevention; 2019 Jun 22-24; Charlotte, NC. Philadelphia (PA): AACR; Can Prev Res 2020;13(7 Suppl): Abstract nr A14.

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How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.176
Threshold uncertainty score0.294

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.125
GPT teacher head0.451
Teacher spread0.326 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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

Citations0
Published2020
Admission routes1
Has abstractyes

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