Prevalence of Allergies and Food Intolerance: a Comparison Between the Persian Community and Canadians of European Descent
Bibliographic record
Abstract
Background: The prevalence of reported allergic diseases is higher in North-America than in other countries around the world. Further, certain types of allergies are more common in some geographic regions or amongst different ethnic populations. This phenomenon has not been well studied amongst the Persian population in the Canadian context; therefore, the current study aimed to compare the prevalence of perceived and diagnosed non-food and food allergies, and food intolerance between Canadians of Persian descent (CPD) and Canadians of European descent (CED), within a sample population of British Columbia residents, their family members and close friends. Methods: Participants were recruited via convenience and snowball sampling, and information about allergy history was collected through in-person and telephone interviews. The prevalence of perceived and diagnosed allergies and food intolerances were compared between CPD and CED. In total, data was reported about 4,404 individuals. Results: The prevalence of all perceived allergies was significantly higher amongst CED compared to CPD [RR (95%CI) = 2.33 (1.6, 3.3)]. A similar pattern was observed for diagnosed food and nut allergy. As well, no cases of perceived or diagnosed food intolerance were reported amongst Persians in the study population. Conclusion: In conclusion, these findings have clinical implications for the treatment and prevention of allergies and food intolerance in BC and Canada. The disproportionate effect of allergies and food intolerance on Canadians of European descent warrants the implementation of targeted public health prevention measures. The genitival and environmental reasons for lack of food intolerance in Canadians of Persian descent should also be investigated.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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".