Pregnancy complications and risk of preterm birth according to maternal age: A population‐based study of delivery hospitalizations in Alberta
Bibliographic record
Abstract
INTRODUCTION: Pregnancy-related medical complications are associated with a 2- to 5-fold increased risk of preterm birth (PTB), but the nature of this etiologic relation in context with maternal factors remains poorly understood. Previous studies have generally treated maternal age as a confounder but overlooked its potential as an effect modifier, whereby the magnitude of the effect of complications on PTB could differ significantly across age groups. We investigated whether advanced maternal age (≥35 years) modified the association between pregnancy complications and PTB, and compared population-attributable fractions of PTB from complications in women older vs younger than 35 years. MATERIAL AND METHODS: We analyzed population-based, cross-sectional data from the Alberta Discharge Abstract Database for women aged 18-50 years with singleton live births in hospital between 2014 and 2017 (n = 152 246). Complications were preeclampsia, gestational diabetes, and placental disorders identified using diagnostic codes. Outcomes were spontaneous (sPTB) or iatrogenic (iPTB) PTB before 37 weeks of gestation. We estimated risk ratios and risk differences using modified Poisson and log binomial regression, respectively, adjusting for confounders (pregnancy history, comorbidities). Population-attributable fractions estimates were calculated from risk ratios. Age modification was tested using interaction terms and Z-tests. RESULTS: Prevalence of advanced maternal age was 19.2%. Pregnancy complications and s/iPTB were more common among women aged ≥35 years. Age modified the risk of PTB from preeclampsia only, with risk differences of 9.9% (95% CI 7.2%-12.6%) in older women vs 6.1% (95% CI 4.8%-7.4%) in younger women (P-interaction = 0.012) for sPTB, and 29.5% (95% CI 26.0%-33.1%) vs 20.8% (95% CI 18.9%-22.6%, P-interaction <0.001) for iPTB. Population-attributable fractions of s/iPTB types for all complications were consistently 2%-5% larger in women aged ≥35 years, and significantly larger for preeclampsia (sPTB: 5.1% vs 2.7%, P = 0.002; iPTB: 18.8% vs 14.0%, P < 0.001) and placental disorders (sPTB: 12.5% vs 8.7%, P < 0.001; iPTB: 13.2% vs 8.9%, P < 0.001). CONCLUSIONS: Of the pregnancy complications studied, advanced maternal age only modified the association between PTB and preeclampsia, such that older women with preeclampsia have a higher risk for s/iPTB than younger counterparts. Pregnancy complications contribute to a sizable proportion of PTBs in Alberta, especially among women aged ≥35 years. Findings may inform clinical risk assessment and population-level policy targeting PTB.
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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 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| 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".