Obesity Represents a Persisting Health Issue in Axial Spondyloarthritis, Particularly Affecting Socially Disadvantaged Patients
Bibliographic record
Abstract
Objective Obesity is an important comorbidity in axial spondyloarthritis (axSpA); however, the prevalence of obesity in axSpA compared with the general population and associated socioeconomic factors remain unknown. Methods This repeated cross-sectional study compared BMI (kg/m2) groups of patients with axSpA to the Swiss population at 3 timepoints (2007, 2012, and 2017). BMI categories were compared by different age, sex, and education categories using the chi-square goodness of fit test. Unpaired, 1-sidedttests were used to compare the BMI in patients with axSpA between the different timepoints. Results Compared to the general population, patients with axSpA had a higher proportion of overweight and obesity: 18.9% of all patients with axSpA were obese, compared to 11.3% of the Swiss population in 2017. Comparison of BMI groups within sex, age, and education groups consistently showed a trend toward higher rates of overweight and obesity in axSpA. Further, patients with axSpA, especially females, showed a trend of increasing BMI over the studied 10 years. At every time point, overweight and obese patients were significantly more likely to be male, were older, and had higher disease activity than patients with normal weight. Obesity was associated with a deprived socioeconomic status as indicated by a higher proportion of patients with manual labor jobs and lower levels of education. Conclusion The prevalence of obesity was significantly higher among patients with axSpA compared to the Swiss population, with socially disadvantaged individuals being the most affected. There is an urgent need to initiate prevention strategies for obesity in patients with axSpA.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 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) | 0.002 | 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".