Association of Metabolic Markers with self-reported osteoarthritis among middle-aged BMI-defined non-obese individuals: a cross-sectional study
Bibliographic record
Abstract
BACKGROUND: , is less known. Our goal was to evaluate the association of metabolic markers including body fat percentage (BF%), waist circumference, maximum weight gain during adulthood and serum creatinine with self-reported OA to establish if such measures offer additional information over BMI among the non-obese population between 40 and 65 years of age. METHODS: Cross-sectional data from two cycles of the Canadian Health Measures Survey (CHMS) in 2007-2009 and 2009-2011 were analyzed. Sex-specific logistic regression models were developed to evaluate the association of self-reported OA with metabolic markers. Models were separately adjusted for age, BMI categories and serum creatinine, and a stratified analysis across BM categories was performed. In a secondary analysis, we evaluated the association of self-reported OA, cardiovascular diseases and hypertension across BF% categories. RESULTS: Of 2462 individuals, 217 (8.8%) self-reported OA. After adjusting for age and BMI, those within BF%-defined overweight/obese category had 2.67 (95% CI: 1.32-3.51) and 2.11(95% CI: 1.38-3.21) times higher odds of reporting self-reported OA compared to those within BF%-defined athletic/acceptable category for females and males, respectively. BF% was also significantly associated with self-reported OA after adjusting for age and serum creatinine only among females (OR: 1.47, 95%CI: 1.12-1.84). Furthermore, among the BMI-defined overweight group, the age-adjusted odds of self-reported OA was significantly higher for overweight/obese BF% compared to athletic/acceptable BF% in both females and males. In a secondary analysis, we showed that the association of self-reported OA and hypertension/cardiovascular diseases is significantly higher among BF% overweight/obese (OR: 1.37, 95%CI: 1.19-3.09) compared to BF% athletic/acceptable (OR: 1.13, 95%CI: 0.87-2.82). CONCLUSION: Our results provide corroborating evidence for a relationship between body fat and OA in a population-based study, while no significant independent correlates were found between other metabolic markers and OA prevalence. Future investigation on the longitudinal relationship between BF and OA among this sub-population may inform targeted prevention opportunities.
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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 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".