Prevalence of hyperthyroidism according to type of vegetarian diet
Bibliographic record
Abstract
OBJECTIVE: Vegetarian diets may be associated with low prevalence of autoimmune disease, as observed in rural sub-Saharan Africans. Graves' disease, an autoimmune disorder, is the most common cause of hyperthyroidism. We studied prevalence of hyperthyroidism according to dietary pattern in a population with a high proportion of vegetarians. DESIGN: Cross-sectional prevalence study. The association between diet and prevalence of hyperthyroidism was examined using multivariate logistic regression analyses controlling for sociodemographic characteristics and salt use. SETTING: The Adventist Health Study-2 conducted in the USA and Canada. SUBJECTS: Church members (n 65 981) provided demographic, dietary, lifestyle and medical history data by questionnaire. RESULTS: The prevalence of self-reported hyperthyroidism was 0·9 %. Male gender (OR=0·32; 95 % CI 0·26, 0·41) and moderate or high income (OR=0·67; 95 % CI 0·52, 0·88 and OR=0·73; 95 % CI 0·58, 0·91, respectively) protected against hyperthyroidism, while obesity and prevalent CVD were associated with increased risk (OR=1·25; 95 % CI 1·02, 1·54 and OR=1·92; 95 % CI 1·53, 2·42, respectively). Vegan, lacto-ovo and pesco vegetarian diets were associated with lower risk compared with omnivorous diets (OR=0·49; 95 % CI 0·33, OR=0·72, 0·65; 95 % CI 0·53, 0·81 and OR=0·74; 95 % CI 0·56, 1·00, respectively). CONCLUSIONS: Exclusion of all animal foods was associated with half the prevalence of hyperthyroidism compared with omnivorous diets. Lacto-ovo and pesco vegetarian diets were associated with intermediate protection. Further study of potential mechanisms is warranted.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 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".