Ingesting Self-Grown Produce and Seropositivity for Hepatitis E in the United States
Bibliographic record
Abstract
Background . Hepatitis E virus (HEV) is a major cause of hepatitis in developing and industrialized countries worldwide. The modes of HEV transmission in industrialized countries, including the United States, remain largely unknown. This study is aimed at evaluating the association between HEV seropositivity and consumption of self-grown foods in the United States. Methods . Cross-sectional data was extracted from the 2009–2012 National Health and Nutrition Examination Survey (NHANES). Data from the dietary interview and the serum HEV IgG and IgM enzyme immunoassay test results were linked and examined. Univariate and multivariable logistic regression models were used to evaluate the significance and effect size of an association between self-grown food consumption and hepatitis E seropositivity. Results . The estimated HEV seroprevalence in the civilian, noninstitutionalized US population was 6.6% in 2009–2012, which corresponds to an estimated hepatitis E national seroprevalence of 17,196,457 people. Overall, 10.9% of participants who ingested self-grown foods had positive HEV antibodies versus 6.1% of participants who did not consume self-grown foods (<mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" id="M1"><mml:mi>P</mml:mi><mml:mo><</mml:mo><mml:mn>0.001</mml:mn></mml:math>; odds ratio (OR) 1.87; 95% CI 1.41–2.48). In the age-stratified multivariable analysis, the correlation between ingesting self-grown foods and HEV seropositivity was significant for participants 40–59 years old, but not overall, or for those < 40 years or ≥60 years. Conclusions . Ingesting self-grown food, or simply the process of gardening/farming, may be a source of zoonotic HEV transmission.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.006 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".