SP3-64 Association between history of tuberculosis and vegetarianism from a nationally representative survey in India
Bibliographic record
Abstract
Introduction Infection with M tuberculosis is a necessary but not sufficient condition for development of clinical Tuberculosis (TB). The reasons why some tuberculosis infections progress to clinical TB while most remain latent is not clear. A vegetarian diet has been implicated as a risk factor for tuberculosis among South-Asians in the UK. Methods To explore whether this is the case in India we analysed data from the nationally representative National Family Health Survey-3 (2006) which collected information on TB and diet, and tested for HIV-1. Tuberculosis was reported by heads of households. Results Vegetarianism was not a risk factor for tuberculosis among HIV-1 negative married men and women between 15 and 49 (women) or 54 (men) years [OR 0.66 (95% CI 0.49 to 0.89)] while poverty and a history of blood transfusions were. Individuals reporting TB were slightly older than those who did not (31.8 vs 29.4 in women, 39.3 vs 37.2 in men). Vegetarians were also slightly older than non-vegetarians (29.5 vs 29.4 in women, and 37.9 vs 37.0 in men). Except for 11 men and 11 women all individuals with TB were reported to have received treatment for their condition. Urban residence, poverty, higher age, and blood transfusion were positively associated with TB. Conclusion Vegetarianism appeared to be protective against TB, perhaps due to confounding by unmeasured life-style factors. As it seems unlikely that confounding has masked a strong positive association between vegetarianism and TB, we conclude that vegetarianism is not a risk factor for TB in India.
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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 | 0.001 |
| 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) | 0.002 | 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".