Are immigrants healthier than native-born Canadians? A systematic review of the healthy immigrant effect in Canada
Bibliographic record
Abstract
OBJECTIVES: Immigrants are typically healthier than the native-born population in the receiving country and also tend to be healthier than non-migrants in the countries of origin. This foreign-born health advantage has been referred to as the healthy immigrant effect (HIE). We examined evidence for the HIE in Canada. DESIGN: We employed a systematic search of the literature on immigration and health and identified 78 eligible studies. We used a narrative method to synthesize the HIE across different stages of the life-course and different health outcomes within each stage. We also examined the empirical evidence for positive selection and duration effects - two common explanations of migrants' health advantage and deterioration, respectively. RESULTS: We find that the HIE appears to be strongest during adulthood but less so during childhood/adolescence and late life. A foreign-born health advantage is also more robust for mortality but less so for morbidity. The HIE is also stronger for more recent immigrants but further research is needed to determine the critical threshold for when migrants' advantage disappears. Positive selection as an explanation for the HIE remains underdeveloped. CONCLUSIONS: There is an absence of a uniform foreign-born health advantage across different life-course stages and health outcomes in Canada. Nonetheless, it remains the case that the HIE characterizes the majority of contemporary migrants since Canada's foreign-born population consists mostly of core working age adults.
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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 | 0.006 | 0.026 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.004 |
| Bibliometrics | 0.010 | 0.015 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".