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Musculoskeletal fitness and risk of mortality

2002· article· en· W1983325345 on OpenAlexaffabout
Peter T. Katzmarzyk, Cora L. Craig

Bibliographic record

VenueMedicine & Science in Sports & Exercise · 2002
Typearticle
Languageen
FieldMedicine
TopicPhysical Activity and Health
Canadian institutionsYork University
Fundersnot available
KeywordsQuartileMedicineGrip strengthDemographyTrunkPhysical fitnessPopulationPhysical therapyRelative riskConfidence intervalLower riskFlexibility (engineering)GerontologyInternal medicineEnvironmental healthStatisticsBiology

Abstract

fetched live from OpenAlex

PURPOSE: To quantify the relationship between musculoskeletal fitness and all-cause mortality in the Canadian population. METHODS: The sample consisted of 8116 people (3933 men and 4183 women), aged 20-69 yr, who participated in the 1981 Canada Fitness Survey. Measures of musculoskeletal fitness included sit-ups, push-ups, grip strength, and sit-and-reach trunk flexibility. In the 13 yr after the Canada Fitness Survey, there were 238 deaths and a total of 101,685 person-years. Proportional hazards regression was used to estimate the risk of mortality across baseline age- and sex-specific quartiles of the musculoskeletal fitness measures. All models included the effects of age, smoking status, body mass, and estimated VO2max as covariates, and the upper quartile was set as the reference group. RESULTS: There was no pattern of increased risk of mortality across quartiles of trunk flexibility or push-ups; however, there was a significantly higher risk in the lower quartile of sit-ups in both men (relative risk (RR) = 2.72, 95% CI 1.56-4.64) and women (RR = 2.26, 95% CI 1.15-4.43). Grip strength was not predictive of mortality in women, although there was a 49% increased risk of death in the lower quartile of grip strength in males (RR = 1.49, 95% CI 0.86-2.59). CONCLUSION: The results suggest that some components of musculoskeletal fitness, particularly sit-ups (abdominal muscular endurance), are predictive of mortality in the Canadian population.

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)0.001
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 score0.087
Threshold uncertainty score0.713

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.002
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 head0.033
GPT teacher head0.332
Teacher spread0.299 · 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

Citations202
Published2002
Admission routes2
Has abstractyes

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