DIETARY INFLAMMATORY INDEX AND KNEE STRUCTURES ON MRI AND PAIN: A PROSPECTIVE COHORT STUDY
Bibliographic record
Abstract
BackgroundWhile some individual dietary nutrients/components have been shown to be associated with knee osteoarthritis (OA) progression, the associations of the dietary inflammatory index (DII), which reflects the overall inflammatory potential of a diet, with MRI-detected structural changes and pain have not been investigated.ObjectivesThis longitudinal study aimed to determine whether DII scores are associated with knee structural changes and pain over a 10.7-year follow-up in community-dwelling older adults.MethodsThis study utilised the data from a prospective population-based cohort study (mean age 63 years, 51% women) in which 1,099, 875, 768 and 563 participants completed assessments at baseline, 2.6, 5.1 and 10.7 years, respectively. T1-weighted or T2-weighted MRI of the right knee was performed to measure cartilage volume (CV) and bone marrow lesions (BMLs) at baseline and 10.7 years. The Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC) pain questionnaire was used to measure knee pain at all assessments. Baseline energy-adjusted DII (E-DII) scores were calculated using a validated Food Frequency Questionnaire. X-ray was performed to assess radiographic knee osteoarthritis (ROA). Linear, log-binomial regression and linear mixed-effects modelling with adjustments for covariates were used to examine the associations of E-DII with CV loss, BML size increase and knee pain, respectively. Pain trajectories (i.e., ‘Minimal Pain’, ‘Mild Pain’, and ‘Moderate Pain’) were previously identified in this cohort using group-based trajectory modelling [1]. Multi-nominal logistic regression was used to examine the association between E-DII and pain trajectory groups.ResultsThe mean E-DII at baseline was -0.48±1.39. In multivariable analyses, E-DII score was not associated with tibial CV loss and BML size increase [CV loss: β=0.03% per annum, 95%CI -0.01–0.06; BML size increase: relative risk (RR)=0.94, 95%CI 0.84–1.05;]. Higher E-DII was associated with greater pain score over 10.7 years (β=0.21, 95%CI 0.004-0.43) and an increased risk of belonging to ‘Moderate pain’ as compared to ‘Minimal Pain’ trajectory group [relative risk ratio (RRR): 1.19, 95%CI 1.02-1.39] after adjustment for age, body mass index, physical activity, education level, employment, emotional problems, comorbidities, and ROA.ConclusionHigher DII was associated with greater pain score and higher risk of more severe pain trajectory, but not structural changes, suggesting discordance between effects of diet on structural damage and pain, and that targeting pro-inflammatory diets may be beneficial to reduce pain.References[1]Pan F, Tian J, Aitken D, Cicuttini F, Jones G. Predictors of pain severity trajectory in older adults: a 10.7-year follow-up study. Osteoarthritis Cartilage. 2018;26(12):1619-26.Disclosure of InterestsNone declared
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".