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Physical activity for obese individuals: a systematic review of effects on chronic disease risk factors

2011· review· en· W1814190303 on OpenAlexafffund
Peter T. Katzmarzyk, Scott A. Lear

Bibliographic record

VenueObesity Reviews · 2011
Typereview
Languageen
FieldMedicine
TopicPhysical Activity and Health
Canadian institutionsSimon Fraser University
FundersPublic Health Agency of Canada
KeywordsMedicineBody mass indexObesityRisk factorRandomized controlled trialWeight lossPhysical therapyDiseaseBlood pressureInternal medicine

Abstract

fetched live from OpenAlex

The purpose of this review was to determine the effectiveness of physical activity in improving chronic disease risk factors in obese individuals. A systematic review was conducted to identify randomized physical activity intervention studies reporting changes in risk factors among obese individuals published prior to March 2010. Studies included in the review were randomized trials of at least 10 weeks in duration, with a sample mean body mass index ≥ 30 kg/m(2) at baseline, and reporting a relevant risk factor (blood pressure, blood lipids, glucose/insulin or C-reactive protein). Forty-four studies met the inclusion criteria for this review. Overall, physical activity had no more than a modest effect on chronic disease risk factors in obese individuals. There was great heterogeneity in responses of risk factors across studies. In many studies it was difficult to determine the effect of physical activity, independent of changes in body mass consequent to the intervention. Obese individuals should be encouraged to undertake physical activity following general recommendations for weight loss and health. The degree to which physical activity is effective at lowering risk factor levels among high-risk obese individuals is not known.

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)0.004
metaresearch head score (Gemma)0.018
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.008
Threshold uncertainty score0.022

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.018
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0080.005
Bibliometrics0.0060.007
Science and technology studies0.0010.001
Scholarly communication0.0020.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0050.000

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 head0.120
GPT teacher head0.411
Teacher spread0.291 · 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 designSystematic review
Domainnot available
GenreReview

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

Citations73
Published2011
Admission routes2
Has abstractyes

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