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Record W2789782366 · doi:10.1093/ageing/afy025

Longitudinal changes in physical function and physical activity in older adults

2018· article· en· W2789782366 on OpenAlexaff
Andrea L. Metti, John R. Best, C. Elizabeth Shaaban, Mary Ganguli, Caterina Rosano

Bibliographic record

VenueAge and Ageing · 2018
Typearticle
Languageen
FieldMedicine
TopicPhysical Activity and Health
Canadian institutionsVancouver Coastal Health Research InstituteUniversity of British ColumbiaVancouver Coastal Health
FundersNational Institute on Aging
KeywordsMedicineGerontologyPhysical activityPhysical medicine and rehabilitation

Abstract

fetched live from OpenAlex

BACKGROUND: physical function (PF) and physical activity (PA) both decline as adults age and have been linked to negative outcomes, including dementia, depression and cardiovascular diseases. Although declines in each are associated with numerous negative outcomes, the longitudinal relationship between these two measures is unclear. OBJECTIVE: to examine the dynamic, bidirectional associations between declines in PF and PA. DESIGN: prospective cohort. SETTING: the Monongahela-Youghiogheny Healthy Aging Team (MYHAT) study. SUBJECTS: about 1,404 men and women, 76.96 ± 7.2 years, 62.4% female and 95.2% white. METHODS: over nine annual assessment cycles, PF was evaluated via the timed Up-and-Go task and PA via a self-reported questionnaire. Piecewise latent growth models examined bidirectional associations between PA and PF to determine whether the initial values (intercept) or early slope (cycles 1-5) (in either PF or PA) predicted later slope (cycles 5-9) (in either PF or PA). RESULTS: initial PF significantly predicted early (standardised β= -0.10, P < 0.001) and later (standardised β= -0.09, P = 0.01) PA slopes. Initial PA significantly predicted later (standardised β = -0.09, P = 0.04) but not early PF slope. Associations were independent of baseline memory test scores, baseline cognitive status, later cognitive status and age. Early physical function slope neither predicts later PA slope nor did early PA slope predict later PF slope (both P values >0.10). CONCLUSIONS: the relationship between PF and PA is bidirectional, with PF more consistently predicting declines of PA, both in the short- and long-term. Intervening on PF impairments may improve PA engagement, which could in turn promote PF and translate to beneficial effects on cognitive function, cardiovascular health and mood.

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)0.000
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.919
Threshold uncertainty score0.299

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
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 head0.034
GPT teacher head0.312
Teacher spread0.278 · 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

Citations58
Published2018
Admission routes1
Has abstractyes

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