Environmental toxins, a potential risk factor for diabetes among canadian aborginals
Bibliographic record
Abstract
OBJECTIVES: To review the current literature to determine if there is a case for examining the presence of toxins in traditional foods and the environment as a possible risk factor for type 2 diabetes in Canadian Aboriginal populations. STUDY DESIGN: Literature review. METHODS. The scientific literature on possible causes of type 2 diabetes in Aboriginal populations in Canada was reviewed. Potential exposure through food and water to environmental toxins such as methylmercury, arsenic, persistent organic pollutants (POPs), including bisphenol A and phthalates, as well as Aboriginal lifestyle and composition of the traditional diet is discussed. RESULTS. There is growing evidence to suggest that environmental toxins may be associated with noninsulin-dependent diabetes mellitus (type 2 diabetes), which many consider to be endemic worldwide. In Canada, diabetes has reached epidemic proportions, especially among Aboriginal populations. Based on both molecular and pathological findings, some toxins found in the environment interfere with the functioning of the pancreas' islets of Langerhans cells, and consequently they affect insulin production. In addition, there is new evidence suggesting that obesity may be linked to endocrine disruptors, thus increasing the likelihood that obesity in itself may not be a chief risk factor for diabetes. CONCLUSIONS: Diabetes prevalence rates among First Nations, Inuit and Métis populations are 3-5 times higher than the general population. Accepted risk factors such as diet, lifestyle and genetics do not fully explain this phenomenon. However, as many environmental toxins bioaccumulate in the food chain and are found in wild game and fish traditionally harvested and consumed by Aboriginal peoples, these chemicals could present health risks not yet fully explored. As there is not enough evidence to rule out this possibility, further studies are suggested. If correct, such environmental risk factors, especially if they are encountered early in life, would have implications on Aboriginal public health.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.006 | 0.008 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".