Do mother’s education and foreign born status interact to influence birth outcomes? Clarifying the epidemiological paradox and the healthy migrant effect
Bibliographic record
Abstract
INTRODUCTION: The unresolved "epidemiological paradox" concerns the association between low socioeconomic status and unexpectedly favourable birth outcomes in foreign born mothers. The "healthy migrant" effect concerns the association between foreign born status per se and birth outcomes. The epidemiological paradox and healthy migrant effect were analysed for newborns in a favourable sociopolitical environment. METHODS: 98,330 live births to mothers in Montreal, Canada from 1997 to 2001 were analysed. Mothers were categorised as foreign born versus Canadian born. Outcomes were: small for gestational age (SGA) birth; low birth weight (LBW) and preterm birth (PTB). Multilevel logistic regression was used to examine the interaction between maternal education and foreign born status, adjusting for covariates. RESULTS: Not having a high school diploma was associated with LBW in Canadian (odds ratio (OR) 3.20; 95% CI 2.61 to 3.91) but not foreign born (OR 1.14; 95% CI 0.99 to 2.10) mothers and was more strongly associated with SGA birth in Canadian (OR 2.03; 95% CI 1.84 to 2.22) than in foreign born (OR 1.26; 95% CI 1.07 to 1.49) mothers. Foreign born status was associated with SGA birth (OR 1.37; 95% CI 1.28 to 1.47), LBW (OR 1.51; 95% CI 1.27 to 1.79) and PTB (OR 1.12; 95% CI 1.03 to 1.22) in university-educated mothers only. CONCLUSIONS: The epidemiological paradox associated with low educational attainment was present for SGA birth and LBW but not PTB. Foreign born status was associated with adverse birth outcomes in university-educated mothers, the opposite of the healthy migrant effect.
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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 | 0.013 | 0.040 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.002 |
| 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".