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Record W4401007557 · doi:10.1016/j.jocd.2024.101508

Team Sports Practice and Bone Health: A Systematic Review and Meta- Analysis

2024· review· en· W4401007557 on OpenAlexaff
Hassane Zouhal, Abdel-Jalil Berro, Elie Maliha, Nour Khalil, Gisèle El Khoury, Ayyappan Jayavel, Fatiha Laziri, Ayoub Saeidi, Ismail Laher, Rawad El Hage

Bibliographic record

VenueJournal of Clinical Densitometry · 2024
Typereview
Languageen
FieldMedicine
TopicSports injuries and prevention
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsBasketballMedicinePhysical therapyBone mineralBone mineral contentMeta-analysisBone healthOsteoporosisFootballTeam sportInternal medicineAthletes

Abstract

fetched live from OpenAlex

The primary aim of this study was to explore the effects of team sports practice on bone health indices in adults engaged in team sports. The secondary aim was to investigate the osteogenic effects of each type of team sport. This systematic literature search was conducted using common electronic databases from inception in June 2023, using key terms (and synonyms searched for by the MeSH database) that were combined using the operators "AND", "OR", "NOT": (``men'' OR ``man'' OR ``women'' OR ``woman'') AND (``bone mineral density'' OR ``BMD'' OR ``bone mineral content'' OR ``BMC'' OR ``peak bone mass'' OR ``mechanical loading'' OR ``osteoporosis'' OR ``bone geometry'' OR ``bone resistance'') AND (``team sport'' OR ``sport'' OR rugby OR basketball OR volleyball OR handball OR soccer OR football OR ``players''). After screening, 16 studies were included in the final analysis (5 continents, 2740 participants). The training duration lasted 1 to 13 years. Team sport training had a moderate impact on whole body bone mineral density (WB BMD) (1.07 SMD; 95 % [0.77, 1.37], p < 0.00) but a more significant impact on whole body bone mineral content (WB BMC) (1.3 SMD; 95 % [0.81, 1.79], p < 0.00). Subgroup analyses indicated that rugby training had a moderate but non-significant impact on WB BMD (1.19 SMD; 95 % [-0.13, 2.52], p = 0.08) but a greater impact on WB BMC (2.12 SMD; 95 % [0.84, 3.39], p < 0.00); basketball training had a moderate but significant impact on WB BMD (1 SMD; 95 % [0.35, 1.64], p < 0.00) and a trivial non-significant impact on WB BMC (0.18 SMD; 95 % [-1.09, 1.46], p = 0.78); volleyball training had a moderate but non-significant impact on WB BMD (0.63 SMD; 95 % [-0.22, 1.49], p = 0.15) and a significant impact on WB BMC (2.39 SMD; 95 % [1.45, 3.33], p < 0.00). Handball training produced a moderate significant impact on WB BMD (1.02 SMD; 95 % [0.33, 1.71], p < 0.00) and WB BMC (0.97 SMD; 95 % [0.47, 1.48], p < 0.00), and soccer training led to moderate but significant effects on WB BMD (1.16 SMD; 95 % [0.88, 1.44], p < 0.00) and a large effect on WB BMC (1.34 SMD; 95 % [0.92, 1.77], p < 0.00). Rugby training was associated with a higher WB BMC compared to basketball training (p = 0.03). Our systematic review and meta-analysis suggests that team sports, such as rugby, basketball, volleyball, handball and soccer have moderate to large effects on WB BMD and WB BMC. Specifically, our findings indicate that handball and soccer enhance WB BMD and WB BMC, whereas rugby only increases WB BMC. There is currently insufficient evidence indicating the superiority of any type of sport training that improves bone health in adults.

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)0.014
metaresearch head score (Gemma)0.035
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Meta-analysis · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.017
Threshold uncertainty score0.075

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0140.035
Meta-epidemiology (narrow)0.0030.002
Meta-epidemiology (broad)0.0170.031
Bibliometrics0.0080.011
Science and technology studies0.0010.001
Scholarly communication0.0030.002
Open science0.0020.002
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0040.000

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 head0.163
GPT teacher head0.556
Teacher spread0.392 · 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 designMeta-analysis
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

Citations7
Published2024
Admission routes1
Has abstractyes

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