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Record W2993906317 · doi:10.1016/j.jshs.2019.11.004

Reflections on obesity, exercise, and musculoskeletal health

2019· editorial· en· W2993906317 on OpenAlexaff
Walter Herzog

Bibliographic record

VenueJournal of sport and health science/Journal of Sport and Health Science · 2019
Typeeditorial
Languageen
FieldMedicine
TopicObesity, Physical Activity, Diet
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsObesityPhysical therapyMedicinePhysical activityPhysical medicine and rehabilitationInternal medicine

Abstract

fetched live from OpenAlex

Reflections on obesity, exercise, and musculoskeletal healthObesity is a disease that has become an epidemic in economically developed countries, and manifests itself at increasing rates in economically developing countries.Obesity is associated with a variety of comorbidities, such as metabolic disease, diabetes, cardiovascular diseases, and musculoskeletal disorders, all resulting in tremendous costs to health care systems around the world, a reduced capacity for work, and reduced quality of life for people with obesity, coupled with physical inactivity, thereby producing a vicious circle of inactivity-induced diseases that enhances obesity.In this special topic of the Journal of Sport and Health Science (JSHS), 4 leading authorities and their collaborators provide insights into the complex issues associated with obesity, and how diet and exercise might contribute to offset some of the risk factors for diseases associated with obesity.Griffin and colleagues and Collins and colleagues present the most recent evidence of the effects of diet-induced obesity on musculoskeletal systems in a mouse and a rat model, respectively.Griffin et al. chose a high-fat diet to induce obesity in mice and, following obesity induction, added aerobic exercise (wheel running) to study the effects of diet and exercise on knee osteoarthritis.Collins et al. used a high-fat combined with a high-sucrose diet to study the effects of dietinduced obesity on knee osteoarthritis in rats exposed to this diet in childhood and in adulthood.Griffin et al. found little diet and exercise effects on knee osteoarthritis in their mouse model, but found distinct differences in the metabolic and inflammation profiles of mice exposed to a normal diet and a high-fat diet, and mice exposed to aerobic exercise and not exposed to exercise.They argue that there might be metabolic and inflammation profiles before osteoarthritis development, and that these pre-osteoarthritis profiles might be used as biomarkers and clinical indicators of risk for knee osteoarthritis development in populations with obesity.The results reported by Collins and colleagues were surprising in the fact that rats exposed to the high-fat/highsucrose diet following weaning (at age of 3 weeks) for 14 weeks, and rats exposed to the same diet starting at the age of 12 weeks for 4 weeks had distinctly different outcomes.Interestingly, the adult animals that were exposed to the diet for only 4 weeks had more severe knee osteoarthritis scores than the rats exposed to the high-fat/high-sucrose diet for 14 weeks that included the weeks of exposure of the adult rats.

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)0.007
metaresearch head score (Gemma)0.020
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Editorial · Consensus signal: Editorial
Teacher disagreement score0.019
Threshold uncertainty score0.036

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.020
Meta-epidemiology (narrow)0.0040.001
Meta-epidemiology (broad)0.0030.002
Bibliometrics0.0030.002
Science and technology studies0.0030.003
Scholarly communication0.0070.005
Open science0.0040.002
Research integrity0.0190.028
Insufficient payload (model declined to judge)0.0080.007

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 head0.043
GPT teacher head0.414
Teacher spread0.371 · 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 designNot applicable
Domainnot available
GenreEditorial

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

Citations16
Published2019
Admission routes1
Has abstractyes

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