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Prediction of physical activity and physical work capacity (PWC150) in young adulthood from childhood and adolescence with consideration of parental measures

2001· article· en· W2054340387 on OpenAlexaffabout
Peter T. Campbell, Peter T. Katzmarzyk, Robert M. Malina, D. C. Rao, Louis P�russe, Claude Bouchard

Bibliographic record

VenueAmerican Journal of Human Biology · 2001
Typearticle
Languageen
FieldMedicine
TopicObesity, Physical Activity, Diet
Canadian institutionsUniversité LavalYork University
Fundersnot available
KeywordsPhysical activityYoung adultDemographyPhysical fitnessEnergy expenditureAnalysis of varianceMedicineEarly adulthoodHeart ratePsychologyGerontologyPhysical therapyBlood pressureInternal medicine

Abstract

fetched live from OpenAlex

The 12-year prediction of physical activity level and submaximal aerobic fitness observed during young adulthood was quantified from childhood and parental measures. The sample consisted of 153 children and adolescents of the Quebec Family Study who were evaluated at baseline and reassessed 12 years later, as young adults. Physical work capacity at a heart rate of 150 beats x min(-1) (PWC150) was measured using cycle ergometry. A 3-day activity record was used to estimate daily energy expenditure (DEE), inactive time (IA), and time spent in moderate-to-vigorous activity (MVPA). Spearman partial inter-age correlations, controlling for length of follow-up and age at baseline, indicated better tracking for PWC150 (0.24 and 0.46, males and females, respectively) than for indicators of physical activity (0.07 < or = r < or = 0.25, males; 0.06 < or = r < or = 0.22, females). Multiple regression analyses indicated that parental measurements of activity and PWC150 did not add any predictive value, with the exception of paternal DEE, which accounted for 8% of the variance in males. There is moderately high stability of submaximal work capacity and lower tracking of physical activity from childhood and adolescence into young adulthood.

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 score0.092
Threshold uncertainty score0.431

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 integrity0.0000.000
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 head0.019
GPT teacher head0.262
Teacher spread0.242 · 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

Citations75
Published2001
Admission routes2
Has abstractyes

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