Intergenerational risk of preterm birth in First Nations Australians: a population-based cohort study from the Northern Territory, Australia
Bibliographic record
Abstract
BACKGROUND: PTB increases the risk of health problems such as chronic renal disease and diabetes in later life and adverse impacts are inversely correlated with gestational age at birth. Rates of PTB in the Northern Territory (NT) of Australia are amongst the highest nationally and globally, with First Nations babies most affected. This study assessed the magnitude and potential drivers of intergenerational PTB recurrence in the NT. METHODS: A retrospective intergenerational cohort study (1986-2017) was conducted amongst 5,366 mothers born singleton who had 9,571 singleton live births (7,673 First Nations, and 1,898 non-First Nations babies). Maternal and offspring PTB was categorised as early (< 34 weeks) and late (34-36 gestational weeks). Modified Poisson regression was used to estimate the relative risk (RR) of PTB associated with maternal PTB, adjusting for moderators such as receipt of antenatal care prior to the offspring PTB. Secondary analyses assessed the impact of additional adjustment for conditions with a familial component, or that PTB predisposes to, on the risk estimate. Mediation analysis assessed the degree of mediation of maternal-offspring PTB relationships by these conditions. RESULTS: Overall, First Nations women born preterm (< 37 weeks) had an increased risk of delivering before 37 gestational weeks (aRR 1.28; 95%CI 1.08, 1.51). Women born preterm had a higher risk of delivering early (< 34 gestational weeks) but not late preterm (34-36 weeks): the risk of early offspring PTB was increased amongst women themselves born early preterm (aRR 1.95, 95%CI 1.17, 3.24) or late preterm (aRR 1.41, 95%CI 1.01, 1.97). Adjustment for pre-eclampsia, intrauterine growth restriction, and hypertensive renal disease attenuated the observed intergenerational PTB associations. Mediation analysis suggested these conditions may mediate up to 26% of the observed intergenerational PTB recurrence. Similar trends were observed when first-time mothers were considered only. Maternal PTB status was not associated with PTB amongst non-First Nations women. CONCLUSIONS: First Nations women born preterm have an increased risk of early PTB. This association is in part driven by pre-eclampsia and hypertensive renal disease. Routine inquiry of maternal birth status may be a useful tool to identify NT First Nations women who may benefit from preventative measures.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".