Comparison of maternal mortality between migrating population and permanent residents in Shanghai, China, 1996–2005
Bibliographic record
Abstract
OBJECTIVE: Maternal mortality ratio (MMR) in Shanghai residents has been declining in the past two decades and has reached levels comparable to developed countries. The MMR in migrating population in Shanghai remains high, however. The objectives of this study were to compare the trends of MMR between residents and migrating population in Shanghai from 1996 to 2005 and to explore the reasons for the dramatic differences in MMR between the two groups living in the same city. DESIGN: Retrospective cohort study. SETTING: Shanghai, China. POPULATION: A total of 902,807 pregnancies with live births in Shanghai in the period of 1996-2005. METHODS: We first compared the overall MMR between migrating population and permanent residents in Shanghai and examined temporal trends of MMR in the two subpopulations. We then compared the causes and maternal characteristics of maternal deaths between the two subpopulations. MAIN OUTCOME MEASURES: Maternal mortality and cause of death. RESULTS: A total of 902,807 live births and 243 maternal deaths were recorded in Shanghai in the period of 1996 to 2005, with an average MMR of 26.66 per 100,000 live births. The MMR in Shanghai residents declined dramatically from 22.47 per 100,000 in 1996 to 1.64 per 100,000 live births in 2005 (P < 0.01), while the MMR in migrating population was reduced only moderately from 54.68 per 100,000 live births to 48.46 per 100,000 (P > 0.05). The main causes of maternal deaths in migrating population were postpartum haemorrhage (39.9%), pregnancy-induced hypertension (9.8%), and puerperal infection (9.3%), whereas the main causes of maternal death of Shanghai residents were chronic heart and liver diseases (20.0%), postpartum haemorrhage (12.9%), and amniotic fluid embolism (12.9%). Among the maternal death cases in migrating women, 60% had elementary education or less, 22% were unemployed, 65% had no prenatal visit, 44% gave a birth at home, and 12% of the deaths occurred at home. CONCLUSION: Lack of access to quality maternity care, especially for the effective management of postpartum haemorrhage, is the main reason for the high MMR in migrating population in Shanghai.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.001 | 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".