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Record W2099628256 · doi:10.1123/jpah.2012-0268

Physical Activity Matters: Associations Among Body Mass Index, Physical Activity, and Health-Related Quality of Life Trajectories Over 10 Years

2014· article· en· W2099628256 on OpenAlexafffundabout
David Feeny, Rochelle Garner, Julie Bernier, Amanda Thompson, Bentson H. McFarland, Nathalie Huguet, Mark S. Kaplan, Nancy A. Ross, Chris M. Blanchard

Bibliographic record

VenueJournal of Physical Activity and Health · 2014
Typearticle
Languageen
FieldMedicine
TopicPhysical Activity and Health
Canadian institutionsDalhousie UniversityMcGill UniversityStatistics CanadaMcMaster University
FundersNational Institute of Diabetes and Digestive and Kidney DiseasesNational Institute on AgingObesity CanadaNational Institutes of HealthIndiana University-Purdue University Indianapolis
KeywordsBody mass indexMedicineQuality of life (healthcare)GerontologyPhysical activityDemographyLeisure timeHealth related quality of lifePhysical therapyDisease

Abstract

fetched live from OpenAlex

BACKGROUND: The objective of this study was to assess the associations among body mass index (BMI), leisure time physical activity (LTPA) and health-related quality of life (HRQL) trajectories among adults. METHODS: Self-reported data were drawn from the Canadian National Population Health Survey, with respondents being interviewed every 2 years between 1996-97 and 2006-07. Using growth curve modeling, HRQL trajectories for individuals aged 18 and over were associated with measures of BMI and LTPA. Growth models were constructed separately for males and females. RESULTS: Findings suggested that, for males, BMI categories had little impact on baseline HRQL, and no impact on the rate of change in HRQL. Among women, higher BMI categories were associated with significantly lower baseline HRQL. However, BMI had no impact on the rate of change of HRQL. Conversely, for both men and women and regardless of BMI category, LTPA had significant impacts on baseline HRQL, as well as the rate of change in HRQL. Individuals who were inactive or sedentary had much steeper declines in HRQL as they aged, as compared with individuals who were active in their leisure time. CONCLUSIONS: The results underscore the importance of LTPA in shaping trajectories of HRQL.

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.705
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0030.001
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.002
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 head0.065
GPT teacher head0.387
Teacher spread0.322 · 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.

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

Citations31
Published2014
Admission routes3
Has abstractyes

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