Birthweight of babies born to migrant mothers - What role do integration policies play?
Bibliographic record
Abstract
Birthweights of babies born to migrant women are generally lower than those of babies born to native-born women. Favourable integration policies may improve migrants' living conditions and contribute to higher birthweights. We aimed to explore associations between integration policies, captured by the Migrant Integration Policy Index (MIPEX), with offspring birthweight among migrants from various world regions. In this cross-country study we pooled 31 million term birth records between 1998 and 2014 from ten high-income countries: Australia, Belgium, Canada, Denmark, Finland, Japan, Norway, Spain, Sweden and United Kingdom (Scotland). Birthweight differences in grams (g) were analysed with regression analysis for aggregate data and random effects models. Proportion of births to migrant women varied from 2% in Japan to 28% in Australia. The MIPEX score was not associated with birthweight in most migrant groups, but was positively associated among native-born (mean birthweight difference associated with a 10-unit increase in MIPEX: 105 g; 95% CI: 24, 186). Birthweight among migrants was highest in the Nordic countries and lowest in Japan and Belgium. Migrants from a given origin had heavier newborns in countries where the mean birthweight of native-born was higher and vice versa. Mean birthweight differences between migrants from the same origin and the native-born varied substantially across destinations (70 g-285 g). Birthweight among migrants does not correlate with MIPEX scores. However, birthweight of migrant groups aligned better with that of the native-born in destination counties. Further studies may clarify which broader social policies support migrant women and have impacts on perinatal outcomes.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".