Serum vitamin C and spinal pain: a nationwide study
Bibliographic record
Abstract
Back pain brings about one of the heaviest burden of disease. Despite much research, this condition remains poorly understood, and effective treatments are frustratingly elusive. Thus, researchers in the field need to consider new hypotheses. Vitamin C (ascorbic acid) is an essential cofactor for collagen crosslinks, a key determinant of ligament, tendon, and bone quality. Recent studies have reported high frequency of hypovitaminosis C in the general population. We hypothesized that lack of vitamin C contributes to poor collagen properties and back pain. We conducted this study to examine the associations between serum concentration of vitamin C and the prevalence of spinal pain and related functional limitations in the adult general population. This study used nationwide cross-sectional data from the U.S. National Health and Nutrition Examination Survey (NHANES) 2003-2004. Data were available for 4742 individuals aged ≥20 years. Suboptimal serum vitamin C concentrations were associated with the prevalence of neck pain (adjusted odds ratio [aOR]: 1.5; 95% confidence interval [CI]: 1.2-2.0), low back pain (aOR: 1.3; 95% CI: 1.0-1.6), and low back pain with pain below knee (aOR: 1.3; 95% CI: 1.0-1.9) in the past 3 months, self-reported diagnosis of arthritis/rheumatism (aOR: 1.4; 95% CI: 1.2-1.7), and related functional limitations' score (adjusted difference of means [aB]: 0.03; 95% CI: 0.00-0.05). The prevalence of hypovitaminosis C in the general population is high. Our study shows associations between vitamin C and spinal pain that warrant further investigation to determine the possible importance of vitamin C in the treatment of back pain patients.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.007 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".