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Record W2118380610 · doi:10.1136/bjsm.2008.057216

Does physical activity reduce seniors' need for healthcare?: a study of 24 281 Canadians

2009· article· en· W2118380610 on OpenAlexafffundabout
John Woolcott, Maureen C. Ashe, William C. Miller, Peilin Shi, Carlo A. Marra

Bibliographic record

VenueBritish Journal of Sports Medicine · 2009
Typearticle
Languageen
FieldMedicine
TopicPhysical Activity and Health
Canadian institutionsUniversity of British Columbia
FundersCanadian Institutes of Health ResearchUniversity of British ColumbiaMinistry of Health, British Columbia
KeywordsHealth careMedicineLogistic regressionEnvironmental healthPhysical activityGerontologyDemographyPhysical therapyInternal medicine

Abstract

fetched live from OpenAlex

OBJECTIVES: Physical inactivity has been associated with significant increases in disease morbidity and mortality. This study assessed the association between physical activity and (1) health resource use and (2) health resource use costs. DESIGN AND PARTICIPANTS: The responses from 24 281 respondents >65 years to the Canadian Community Health Survey Cycle 1.1 were used to find activity levels and determine health resource use and costs. Logistic regression models were used to assess risks of hospitalisation. RESULTS: Physical inactivity was associated with statistically significant increases to hospitalisations, lengths of stay and healthcare visits (p<0.01). Average healthcare costs (based on the 2007 value of the Canadian dollar) for the physically inactive were $C1214.15 higher than the healthcare costs of the physically active ($C2005.27 vs $C791.12, p<0.01). CONCLUSION: Among those >65 years, physical activity is strongly associated with reduced health resource use and costs.

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)0.001
metaresearch head score (Gemma)0.002
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 score0.022
Threshold uncertainty score0.077

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.003
Science and technology studies0.0050.001
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.001

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 head0.029
GPT teacher head0.338
Teacher spread0.309 · 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".

Quick stats

Citations53
Published2009
Admission routes3
Has abstractyes

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