Is the socioeconomic status of immigrant mothers in Brussels relevant to predict their risk of adverse pregnancy outcomes?
Bibliographic record
Abstract
BACKGROUND: Understanding and tackling perinatal health inequities in industrialized countries requires analysing the socioeconomic determinants of adverse pregnancy outcomes among immigrant populations. Studies show that among certain migrant groups, education is not associated with adverse pregnancy outcomes. We aim to extend this analysis to further dimensions of socioeconomic status (SES) and to other settings. The objective of this study is to identify sociodemographic characteristics associated with adverse pregnancy outcomes, according to the origin of mothers residing in Brussels. METHODS: We analysed all singleton live births in Brussels between 2005 and 2010 (n = 97,844). The data arise from the linkage between three administrative databases. Four groups of women were included according to their place of birth: Belgium, EU, North Africa, and Sub-Saharan Africa. For each group, logistic regression was carried out to estimate the odds ratios of low birthweight (LBW) and small for gestational age (SGA) according to SES indicators (household income, maternal employment status, maternal education) and single parenthood. RESULTS: Three key findings emerge from this study: 1) 25% of children were born into a household under the poverty threshold. This proportion was much higher for mothers born outside of the EU. 2) For North African immigrants, SES indicators didn't influence the pregnancy outcomes, whereas their risk of LBW increased with single parenthood. 3) For Sub-Saharan Africans the risk of LBW increased with low household income. CONCLUSION: In a region where immigrant mothers are at high poverty risk, we observe a classic social gradient in perinatal outcomes only for mothers born in Belgium or the EU. In the other groups, SES influences perinatal outcomes less systematically. To develop interventions to reduce inequities from birth, it's important to identify the determinants of perinatal health among immigrants and to understand the underlying mechanisms in different contexts.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".