Foodborne and waterborne illness among Canadian Indigenous populations: A scoping review
Bibliographic record
Abstract
BACKGROUND: Indigenous populations are often at higher risk for foodborne illness than the general Canadian population. OBJECTIVE: To investigate the extent of the literature on the link between food safety and the occurrence of foodborne and waterborne illness in Canadian Indigenous populations. METHODS: A scoping review was conducted using search strings in five databases and grey literature to identify all papers that studied a Canadian Indigenous population and referred to any potential associations between food safety (including consumption and preparation of traditional foods and retail foods) or water safety practices and food or waterborne illness. Two authors screened papers based on inclusion and exclusion criteria. Included documents were analyzed for emergent themes. RESULTS: From 1,718 unique records identified, 21 documents were selected. Foodborne illness was most common in children up to 14 years old. Walrus, seal, caribou and whale were the most common traditional foods tied to foodborne illness and were primarily associated with botulism and trichinosis. Aside from consuming the food raw, fermentation was the most common traditional preparation method linked to foodborne illness. There was concern about the safety of retail food but no clear link was identified with foodborne illness. Lastly, although there was concern about tap water, the use of alternate water sources, such as untreated brook water, and hygiene and cleaning practices in communities with boil water advisories were the most common risk behaviours associated with waterborne illness. CONCLUSION: Consumption of certain game meats, as well as the use of traditional fermentation practices may lead to an increased risk of foodborne illness among Indigenous populations. Concern about tap water may lead to use of unsafe alternate water sources. Further research is needed to examine potential culturally appropriate food and water safety opportunities.
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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 | 0.010 | 0.037 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.025 | 0.036 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| 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".