Are weight and leisure physical activity associated with the onset or the chronicity of neck pain in adults with non specific neck pain? A systematic review
Bibliographic record
Abstract
Objective: To synthesize evidence from the past decade on the association between weight, leisure physical activity (PA), and the onset or chronicity of neck pain in adults with non-specific neck pain (NSNP). Literature search: Five databases (PubMed, Scopus, Embase, Cochrane Library, PsycINFO) were searched from January 2010 to November 2021. Study selection criteria: Case-control or cohort studies assessing the association between the onset or the chronicity of NSNP, weight and leisure PA in healthy adults or adults with NSNP at baseline. Data synthesis: Use of the “vote counting based on direction of effects” and narrative synthesis. Results: Nine articles were included (20,350 participants, range 86-11,391), four on the onset and five on the chronicity of NSNP. Methodological quality varied from poor to good according to the Newcastle-Ottawa Scale. For the onset and the chronicity of NSNP, studies showed modest associations suggesting a decreased risk with higher levels of leisure PA and an increased risk in overweight and obese people. However, certainty of evidence was judged to be very low for each association. Conclusion: The findings showed modest and sometimes inconsistent associations, but overall suggest that the risk of NSNP (onset and chronicity) may be decreased in more active people and increased in overweight and obese people. Results should be interpreted with caution and should not be generalized to populations other than white-collar workers. Future studies are needed to provide stronger evidence on these associations and to investigate the impact of combined factors (e.g., a healthy lifestyle) on NSNP.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.010 | 0.063 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.010 | 0.009 |
| Bibliometrics | 0.009 | 0.010 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.003 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".