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Record W4408997032 · doi:10.1080/03014460.2025.2482972

The effect of birth month on body height of Austrian conscripts varies according to educational level

2025· article· en· W4408997032 on OpenAlexaff
Thomas Waldhoer, Sylvia Kirchengast, Lin Yang

Bibliographic record

VenueAnnals of Human Biology · 2025
Typearticle
Languageen
FieldEnvironmental Science
TopicClimate Change and Health Impacts
Canadian institutionsUniversity of CalgaryAlberta Health Services
Fundersnot available
KeywordsDemographySocioeconomic statusBody heightBody mass indexPopulationGeographyMedicineBody weight

Abstract

fetched live from OpenAlex

An association between birth month and height has been repeatedly described, but no consistent seasonal patterns can be observed. In this study, the significance of educational level as a modulating cofactor for the association between body height and birth month was analysed using an anonymous data set from 1,179,600 male conscripts born in Austria between 1971 and 2002. A distinct seasonal trend was observed. Conscripts born from June to December had shorter final body height than their counterparts born between January and May. In general, the effect of month of birth on final body height is very small. Considering socioeconomic co-factors, however, this effect was particularly noticeable for the highest and middle education classes, while the observed effect was small among the lowest education class. A low educational level seems to reduce the seasonal effect on growth and finally body height. Consequently, a clear seasonal effect in body height was observed in this Austrian population-based sample, socioeconomic stress factors, such as a low level of education, can reduce the seasonal effects.

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 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)0.000
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 score0.077
Threshold uncertainty score0.314

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 head0.134
GPT teacher head0.420
Teacher spread0.286 · 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
Published2025
Admission routes1
Has abstractyes

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