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Record W2972609593 · doi:10.1016/j.gloepi.2019.100009

Decomposing the effects of physical activity and cardiorespiratory fitness on mortality

2019· article· en· W2972609593 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueGlobal Epidemiology · 2019
Typearticle
Languageen
FieldMedicine
TopicPhysical Activity and Health
Canadian institutionsMcGill UniversityJewish General Hospital
FundersSixth Framework ProgrammeNational Institutes of HealthMinisterio de Educación, Cultura y Deporte
KeywordsCardiorespiratory fitnessMediationLongitudinal studyPhysical activityInteractionMedicineCausal modelInternal medicinePhysical fitnessDemographyPsychologyGerontologyPhysical therapyBiology

Abstract

fetched live from OpenAlex

Characterizing the effects of physical activity (PA) and cardiorespiratory fitness (CRF) on mortality is challenging because the causal relationship between PA, CRF, and other cardiovascular risk factors is unclear. To better understand the effects of PA and CRF on mortality, we re-analyzed data from 42,373 participants in the Aerobics Center Longitudinal Study (ACLS) using a modified version of VanderWeele's four-way causal effect decomposition method. The method was applied to decompose the causal effects of PA and CRF on median time to death into parts reflecting mediation, interaction, mediated interaction, and neither interaction nor mediation. We found that 67% of the effect of PA on mortality was mediated by CRF, while the effect of CRF was not significantly mediated by PA. The effects of both PA and CRF were mediated to a small extent by hypertension and diabetes. There were no meaningful interactions. Our findings strengthen the evidence that the benefit on mortality from PA is largely mediated by its effect on CRF, and support efforts to increase longevity by encouraging PA.

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.

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)0.001
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 score0.104
Threshold uncertainty score0.290

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.054
GPT teacher head0.403
Teacher spread0.349 · 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