Ultra-processed food consumption is associated with knee osteoarthritis: Data from the Osteoarthritis Initiative
Bibliographic record
Abstract
OBJECTIVE: To explore the relationship between ultra-processed food (UPF) intake and knee osteoarthritis (KOA)-related imaging and clinical outcomes in men and women. DESIGN: Osteoarthritis Initiative participants with sufficient dietary and sociodemographic data (n = 4403) were included in this cross-sectional study. UPF was assessed by food frequency questionnaire-based NOVA Classification, categorizing diet according to processing level, with NOVA-4 indicating UPF. The exposure variable was standardized UPF proportion/day (%)-the proportion of NOVA-4 servings in the daily diet. The outcomes were Western Ontario and McMaster University OA Index (WOMAC) pain, activities of daily living (ADL), stiffness, total scores, average cartilage thickness (quantified using 3D-dual echo steady-state sequences on 3T MRI), Chair Stand Test (CST) and gait speed. Mixed effects and linear regression models were used for knee-level and participant-level outcomes, respectively. Models were adjusted for age, race, BMI, daily calories, physical activity, and medical insurance availability. Sex differences were tested by interactions between UPF and sex. RESULTS: Sex interactions were significant for WOMAC-pain, ADL, total, gait speed, cartilage thickness (p-interaction-range < 0.001-0.006). Greater UPF was associated with significantly worse pain (β = 0.17 [0.093, 0.242], p < 0.001), ADL (β = 0.59 [0.365, 0.832], p < 0.001), total scores (β = 0.81 [0.483, 1.13], p < 0.001), thinner cartilage (β = -0.013 [-0.02, -0.006], p < 0.001), slower gait (β = -0.035 [-0.042, -0.027], p < 0.001) in women. Sex interactions were non-significant for CST and WOMAC-stiffness (p-interaction = 0.319, 0.573, respectively). With greater UPF, CST and WOMAC-stiffness showed significant poor outcomes (β = -0.008 [-0.013, -0.004], p < 0.001, β = 0.04 [0.008, 0.064], p = 0.011, respectively). WOMAC-stiffness results were not significant after Bonferroni corrections. CONCLUSIONS: UPF-rich diet is linked to worse KOA outcomes disproportionately more in women.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".