Being a First Nations baby is not independently associated with low birthweight in a large metropolitan health service
Bibliographic record
Abstract
Aim To examine low birth weight (LBW) in First Nations babies born in a large metropolitan health service in Queensland, Australia. Materials and Methods A retrospective population‐based study using routinely collected data from administrative data sources. All singleton births in metropolitan health services, Queensland, Australia of ≥20 weeks gestation or at least 400 g birthweight and had information on First Nations status and born between 2019 and 2021 were included. The study measured birthweight and birthweight z‐score, and also identified the predictors of LBW. Multivariate regression models were adjusted by demographic, socioeconomic and perinatal factors. Results First Nations babies had higher rates of LBW (11.4% vs 6.9%, P < 0.001), with higher rates of preterm birth (13.9% vs 8.8%, P < 0.001). In all babies, the most important factors contributing to LBW were: maternal smoking after 20 weeks of gestation; maternal pre‐pregnancy underweight (body mass index <18.5 kg/m 2 ); nulliparity; socioeconomic disadvantage; geographical remoteness; less frequent antenatal care; history of cannabis use; pre‐existing cardiovascular disease; pre‐eclampsia; antepartum haemorrhage; and birth outcomes including prematurity and female baby. After adjusting for all contributing factors, no difference in odds of LBW was observed between First Nations and non‐First Nation babies. Conclusions First Nations status was not an independent factor influencing LBW in this cohort, after adjustment for identifiable factors. The disparity in LBW relates to modifiable risk factors, socioeconomic disadvantage, and prematurity. Upscaling culturally safe maternity care, focusing on modifiable risk factors is required to address LBW in Australian women.
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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 | 0.001 |
| 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) | 0.000 | 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".