Effects of Migration on Infant and Maternal Health in China
Bibliographic record
Abstract
We assess the association between maternal migrant status and health outcomes in China, which has one of the world’s largest migrant populations. Health records from the Shanghai First Maternity and Infant Hospital from January 1, 2013, to June 30, 2017, were used to analyze 104 681 live births for Shanghai native-born and migrant women based on International Classification of Diseases, Tenth Revision diagnosis codes and demographic data. Regression analysis including propensity score matching was conducted to investigate the association between maternal migrant status and adverse infant birth outcomes (fetal disease, congenital malformation, neonatal disease) and maternal health after controlling for pregnancy status and socioeconomic factors. The results demonstrate that migrant women had statistically significant increased odds (9.1%-10%, P < .001) of having infants with adverse health outcomes compared with their urban counterparts and that migrant mothers have less likelihood of pregnancy complications and gestational diabetes mellitus. Our results show the mixed effects of migration on infant and maternal health may be a possible outcome of China’s Hukou system that often represents an important barrier in accessing prenatal health care by migrant women. Current reforms that improve access to prenatal health care services for migrant women may enhance the health outcomes of their infants.
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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 | 0.001 | 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".