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Cardiorespiratory Fitness within an Obesity Risk Classification Model Identifies Men at Increased Risk of Mortality

2016· article· en· W2473186152 on OpenAlexaff
Taryn Davidson, Alex Ricketts, Xuemei Sui, Carl J. Lavie, Steven N. Blair, Robert Ross

Bibliographic record

VenueMedicine & Science in Sports & Exercise · 2016
Typearticle
Languageen
FieldMedicine
TopicCardiovascular and exercise physiology
Canadian institutionsQueen's University
Fundersnot available
KeywordsCardiorespiratory fitnessMedicineBody mass indexOverweightWaistHazard ratioPopulationInternal medicineObesityDemographyPhysical therapyConfidence intervalEnvironmental health

Abstract

fetched live from OpenAlex

Guidelines for identification of obesity-related risk stratify disease risk using specific combinations of body mass index (BMI) and waist circumference (WC). Whether the addition of cardiorespiratory fitness (CRF), an independent predictor of disease risk, provides better risk prediction of all-cause mortality within current BMI and WC categories is unknown. PURPOSE: To determine whether the addition of CRF improves prediction of all-cause mortality risk classified by established categorization of BMI and WC. METHODS: Prospective observational data from the Aerobics Center Longitudinal Study (ACLS). A total of 31,267 men (mean (SD) age 43.9 (9.4) years completed a baseline medical examination during 1974-2002. Participants were grouped according to the following BMI- and WC-specific threshold combinations: Normal BMI of 18.5-24.9 kg/m2, WC threshold of 90 cm; overweight BMI of 25.0-29.9 kg/m2, WC threshold of 100 cm, and obese BMI of 30.0-34.9 kg/m2, WC threshold of 110 cm. Participants were classified by CRF as unfit or fit. Unfit was defined as the lowest fifth of the age-specified distribution of maximal exercise test time on treadmill among the entire ACLS population. The main outcome measure was all-cause mortality. RESULTS: 1,399 deaths occurred over an average length of follow-up of 14.1 ± 7.4 years, for a total of 439, 991 person-years of observation. Males who were unfit and normal BMI with WC<90 cm and ≥90 cm had 95% (1.95, 1.34-2.83) [Hazard ratio, 95% confidence interval] and 163% (2.63, 1.58-4.40) higher mortality risk than males who were fit, respectively (p<.05). Males who were unfit and overweight had 41% (1.41, 1.04-1.90) higher mortality risk with a WC <100 cm (p<.05), but were at no greater risk (1.30, 0.92-1.84) if their WC was ≥100 cm (p=.14). Males who were unfit and obese were not at increased mortality risk (1.37, 0.90-2.09) with a WC <110 cm (p=.14), but were at 111% (2.11, 1.31-3.42) increased risk with a WC ≥110 cm (p<.05). CONCLUSIONS: For most of the BMI and WC categories, inclusion of CRF allowed for improved identification of males at increased mortality risk.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.004
metaresearch head score (Gemma)0.005
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.014
Threshold uncertainty score0.028

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.005
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.001

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 head0.027
GPT teacher head0.293
Teacher spread0.266 · 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 source (direct Gemma or distilled Codex), 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".

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Citations0
Published2016
Admission routes1
Has abstractyes

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