Participation in physical activity and back pain among an elderly population in South Asia
Bibliographic record
Abstract
INTRODUCTION: Globally, chronic back pain is one of the most commonly encountered medical conditions among an elderly population with significant bearings on health, functional mobility and general well-being. OBJECTIVE: To estimate the burden of chronic back pain and its association with physical activity (PA) among population aged 50 years and above in Bangladesh, India, Nepal, Pakistan and Sri Lanka. METHODS: Cross-sectional data on 8502 men and women aged 50 years and above were collected from the World Health Survey (2002). Three forms of PA were considered - vigorous physical activity (VPA), moderate physical activity (MPA) and walking. Odds ratios (ORs) of the association between self-reported back pain and VPA, MPA and walking were calculated by using generalized estimating equations. RESULTS: The prevalence of back pain was, respectively, 64.8%, 19.8%, 69.5%, 40.6% and 36.2% in Bangladesh, India, Nepal, Pakistan and Sri Lanka. No significant association between back pain and VPA was observed among men in any of the countries. In India, Pakistan and Sri Lanka, the odds of suffering from back pain were, respectively, 29%, 2.5 times and 59% higher among women who almost never took MPA. In India, taking MPA for few days a week and almost never was associated with, respectively, 38% (OR=1.38; 95% confidence interval [CI]=1.017-1.876) and 56% (OR=1.564; 95% CI=1.003-2.438) higher odds of reporting back pain. Walking almost never was also associated with, respectively, 83% (OR=1.829; 95% CI=1.14-2.934) and 2.9 times (OR=2.854; 95% CI=1.419-5.738) higher odds of reporting back pain among men in Nepal and Pakistan, respectively. CONCLUSION: Though the relationship was not consistent across sex and countries, results indicate that inadequate or nonparticipation can substantially increase the likelihood of suffering from back pain among an elderly population in this region. Further research is needed to better understand this relationship and the potential of exercised-based strategies to prevent and treat back pain among elderly persons.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".