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Record W2083231032 · doi:10.1002/ajhb.10081

Secular trend in the development of fatness during childhood and adolescence

2002· article· en· W2083231032 on OpenAlexaffabout
Angela Thompson, Adam Baxter‐Jones, Robert L. Mirwald, D. A. Bailey

Bibliographic record

VenueAmerican Journal of Human Biology · 2002
Typearticle
Languageen
FieldMedicine
TopicObesity, Physical Activity, Diet
Canadian institutionsUniversity of SaskatchewanSt. Francis Xavier University
Fundersnot available
KeywordsDemographySecular variationSkinfold thicknessHumBody mass indexLongitudinal studyMedicineMaturity (psychological)Body heightAnthropometryMultilevel modelEndocrinologyBody weightPsychologyInternal medicineDevelopmental psychologyMathematics

Abstract

fetched live from OpenAlex

This study examined the development of fatness, as indexed by skinfold thickness, in healthy Caucasian children and adolescents residing in the same location in Canada in the 1960s and the 1990s. The data comes from two longitudinal studies, conducted approximately 30 years apart, of children aged 8-16 years. The first study (1964-1973) annually measured 207 males and 140 females. The second investigation (1991-1997) repeatedly measured 113 males and 115 females. Identical measurement tools and protocols were used for height, body mass, and skinfolds. Maturational age was estimated as a measure in years from age of peak height velocity. Males from the second investigation matured significantly (P < 0.05) earlier. Multilevel regression modeling was utilized to determine developmental curves for the individuals within the two populations. When differences in height, body mass, and maturity were controlled, skinfold thicknesses of the males and females in the second study were significantly greater (P < 0.05) than age- and sex-matched peers in the first study. This was not seen in models of the BMI. The results suggest that when maturity and size were controlled, the fatness of children and adolescents increased over 30 years.

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 score0.082
Threshold uncertainty score0.222

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 head0.015
GPT teacher head0.269
Teacher spread0.254 · 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

Citations47
Published2002
Admission routes2
Has abstractyes

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