The prevalence of obesity and underweight in celiac patients at the time of diagnosis: a systematic review and meta-analysis
Bibliographic record
Abstract
BACKGROUND: This study aimed to estimate the prevalence of obesity, overweight, and underweight in celiac disease (CD) at diagnosis before starting the Gluten-free diet (GFD). METHODS: A comprehensive search was conducted in PubMed, Embase, Scopus, and Web of Science until July 2024 to find the cross-sectional and longitudinal studies that measured the body mass index (BMI) in CD patients at diagnosis. The risk of bias assessment was conducted using the Newcastle-Ottawa Quality Assessment scale. Meta-regression analyses were applied to understand whether weight status is associated with CD. RESULTS: A total of 23 studies involving 15,299 CD patients and 815,167 healthy individuals were included in this study. In newly diagnosed CD patients, pooled estimates of the prevalence of obesity, overweight, and underweight before GFD were 11.78%, 18.42%, and 11.04%, respectively. The prevalence of overweight and obesity in newly diagnosed CD patients increased from 22.15% in 2003-2009 to 32.51% in 2016-2021. Meta-regression analyses indicated that the CD patients with higher BMI had a higher mean age (p = 0.001), and female gender had a marginally significant (p = 0.055) association with higher BMI. Only a few CD patients were underweight at the time of diagnosis, and more patients were overweight/obese. CONCLUSIONS: our meta-analysis demonstrated that only a few CD patients were underweight at the time of diagnosis, and almost 37% were overweight or obese. Meta-regression showed a significant association between higher BMI and higher mean age and female gender. A delay or failure for diagnosis of CD is more common in overweight/obese patients, resulting in more progression of the disease and counteracting any advantages of diagnosis.
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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 | 0.014 | 0.033 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.018 | 0.044 |
| Bibliometrics | 0.011 | 0.010 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".