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Record W2755286891 · doi:10.1002/ajhb.23056

Longitudinal patterns in BMI and percent total body fat from peak height velocity through emerging adulthood into young adulthood

2017· article· en· W2755286891 on OpenAlexafffund
Erin Barbour‐Tuck, Marta Erlandson, Nazeem Muhajarine, Heather J.A. Foulds, Adam Baxter‐Jones

Bibliographic record

VenueAmerican Journal of Human Biology · 2017
Typearticle
Languageen
FieldMedicine
TopicObesity, Physical Activity, Diet
Canadian institutionsUniversity of Saskatchewan
FundersCanadian Institutes of Health ResearchSaskatchewan Health Research Foundation
KeywordsLongitudinal studyEarly adulthoodYoung adultDemographyBody mass indexLongitudinal dataMedicineBiologyGerontologyInternal medicinePathology

Abstract

fetched live from OpenAlex

OBJECTIVES: Emerging adulthood, a potential critical period, is an understudied period of fat mass accrual. The aim of this study was to describe patterns of fat mass accrual, and weight status, from adolescence, through emerging adulthood, into young adulthood. METHODS: One-hundred-eighteen participants (59 male) were measured repeatedly for 20 years. Annual measures of height, weight, and body composition (DXA) were taken. Calculated measures included: peak height velocity (PHV), biological age (BA; years from PHV), body mass index (BMI), and percent total body fat (%TBF). Weight status groupings (normal NW, and overweight/obese OWO) were created using age and sex specific BMI and %TBF cut-offs. Analysis included t-tests and logistic regression. RESULTS: BMI and %TBF increased significantly until 8 years post PHV (P < .05), plateaued for 7 years (P > .05), and then began increasing again (P < .05). At PHV, 9% of males and 14% of females were OWO rising to 65% and 32% respectively 15 years post PHV. OWO status at PHV did not predict OWO status in early adulthood (P > .05). CONCLUSIONS: During emerging adulthood, the prevalence of OWO increased. Being NW at PHV was not protective against being overweight in young adulthood. Emerging adulthood appears to be a potential critical period for fat accrual and warrants further attention.

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 score0.011
Threshold uncertainty score0.916

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.018
GPT teacher head0.318
Teacher spread0.300 · 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

Citations17
Published2017
Admission routes2
Has abstractyes

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