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Record W4391187736 · doi:10.1093/jbmr/zjae004

Sedentary behavior does not predict low BMD nor fracture—population-based Canadian Multicentre Osteoporosis Study

2024· article· en· W4391187736 on OpenAlexafffundabout
Sigríður Lára Guðmundsdóttir, Claudie Berger, Heather Macdonald, Jonathan D. Adachi, Wilma M. Hopman, Stéphanie Kaiser, Christopher S. Kovács, K. Shawn Davison, Suzanne N. Morin, David Goltzman, Nancy Kreiger, Alan Tenenhouse, Elham Rahme, J. Brent Richards, Carol Joyce, Susan Kirkland, Jacques P. Brown, Louis Bessette, Tassos Anastassiades, Tanveer Towheed, Angela M. Cheung, Robert G. Josse, Andy Kin On Wong, Αλεξάνδρα Παπαϊωάννου, Wojciech P. Olszynski, Kelly Davison, David A. Hanley, Steven K. Boyd, Jerilynn C. Prior, Shirin Kalyan, Brian C. Lentle, Millan S. Patel, Stuart Jackson, William D. Leslie

Bibliographic record

VenueJournal of Bone and Mineral Research · 2024
Typearticle
Languageen
FieldMedicine
TopicPhysical Activity and Health
Canadian institutionsMcGill UniversitySt. John’s Health Sciences CentreMemorial University of NewfoundlandDalhousie UniversityMcMaster UniversityQueen's UniversityPrioris.ai (Canada)Kingston Health Sciences CentreUniversity of British ColumbiaKingston General HospitalMcGill University Health Centre
FundersPfizer CanadaNovartis Pharmaceuticals CanadaArthritis SocietyDairy Farmers of CanadaMcGill UniversityCanadian Institutes of Health ResearchDanoneAmgen CanadaSanofiEli Lilly and CompanyEli Lilly CanadaServierAmgenPfizerUniversity of TorontoServier Canada
KeywordsMedicineQuartileOsteoporosisPopulationSittingBone mineralFemoral neckPhysical therapyHip fractureBone densityInternal medicineConfidence interval

Abstract

fetched live from OpenAlex

Sedentary behavior (SB) or sitting is associated with multiple unfavorable health outcomes. Bone tissue responds to imposed gravitational and muscular strain with there being some evidence suggesting a causal link between SB and poor bone health. However, there are no population-based data on the longitudinal relationship between SB, bone change, and incidence of fragility fractures. This study aimed to examine the associations of sitting/SB (defined as daily sitting time), areal BMD (by DXA), and incident low trauma (fragility) osteoporotic fractures (excluding hands, feet, face, and head). We measured baseline (1995-7) and 10-yr self-reported SB, femoral neck (FN), total hip (TH), and lumbar spine (L1-L4) BMD in 5708 women and 2564 men aged 25 to 80+ yr from the population-based, nationwide, 9-center Canadian Multicentre Osteoporosis Study. Incident 10-yr fragility fracture data were obtained from 4624 participants; >80% of fractures were objectively confirmed by medical records or radiology reports. Vertebral fractures were confirmed by qualitative morphological methods. All analyses were stratified by sex. Multivariable regression models assessed SB-BMD relationships; Cox proportional models were fit for fracture risk. Models were adjusted for age, height, BMI, physical activity, and sex-specific covariates. Women in third/fourth quartiles had lower adjusted FN BMD versus women with the least SB (first quartile); women in the SB third quartile had lower adjusted TH BMD. Men in the SB third quartile had lower adjusted FN BMD than those in SB first quartile. Neither baseline nor stable 10-yr SB was related to BMD change nor to incident fragility fractures. Increased sitting (SB) in this large, population-based cohort was associated with lower baseline FN BMD. Stable SB was not associated with 10-yr BMD loss nor increased fragility fracture. In conclusion, habitual adult SB was not associated with subsequent loss of BMD nor increased risk of fracture.

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)0.003
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 score0.083
Threshold uncertainty score0.168

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.003
Science and technology studies0.0030.000
Scholarly communication0.0010.000
Open science0.0020.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.400
Teacher spread0.346 · 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

Citations5
Published2024
Admission routes3
Has abstractyes

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