Visual acuity in fish consumers of the Brazilian Amazon: risks and benefits from local diet
Bibliographic record
Abstract
OBJECTIVE: To examine the associations between near and distant visual acuity and biomarkers of Hg, Pb, n-3 fatty acids and Se from the local diet of fish-eating communities of the Tapajós River in the Brazilian Amazon. DESIGN: Visuo-ocular health and biomarkers of Hg (hair, whole blood, plasma), Pb (whole blood), Se (whole blood and plasma) and n-3 fatty acids (plasma total phospholipids) were assessed in a cross-sectional study. SETTING: Lower Tapajós River Basin (State of Pará, Brazil), May to July 2006. SUBJECTS: Two hundred and forty-three adults (≥15 years) without diagnosed age-related cataracts or ocular pathologies. RESULTS: Near visual acuity was negatively associated with hair Hg and positively associated with %DHA, with a highly significant Log Hg × age interaction term. Stratifying for age showed that while young people presented good acuity, for those aged ≥40 years, clinical presbyopia was associated with hair Hg ≥ 15 μg/g (OR = 3·93, 95% CI 1·25, 14·18) and %DHA (OR = 0·37, 95% CI 0·11, 1·11). A similar age-related pattern was observed for distant visual acuity in relation to blood Pb, but the evidence was weaker. CONCLUSIONS: These findings suggest that Hg and Pb may affect visual acuity in older persons, while DHA appears to be protective for near visual acuity loss. In this population, with little access to eye care, diet may have an important influence on visuo-ocular ageing.
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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 | 0.000 | 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) | 0.001 | 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".