Re-evaluation of link between interpregnancy interval and adverse birth outcomes: Retrospective cohort study matching 2 intervals per mother
Notice bibliographique
Résumé
The time interval between pregnancies is a modifiable risk factor of adverse birth outcomes, including preterm birth, small for gestational age (SGA), and low birth weight. Variations in birth outcomes might be explained by risk factors that vary greatly among women but tend to persist between pregnancies (eg, genetics, lifestyle, or social conditions). Among women who have had 3 births, each mother can be her own control for risk factors that affect outcomes. This retrospective cohort study was performed to examine the effect of interpregnancy interval after adjusting for maternal factors by using within-mother analyses. The association between interpregnancy interval and the incidence of preterm birth, SGA, and low birth weight among the second and third births was determined using data from a population-wide database. Among 84,151 mothers, 40,441 all had their first 3 births as live singletons during 1980 to 2010. Outcome variables were preterm birth (<37 weeks), SGA, and low birth weight (<2500 g). Interpregnancy intervals (in months) were 0 to 5, 6 to 11, 12 to 17, 18 to 23 (reference category), 24 to 59, 60 to 119, and 120 or longer. A maternally matched design was used to model the odds of preterm birth, SGA, and low birth weight as a function of interpregnancy interval. Conditional logistic regression was used to measure this association for an individual woman, which allowed inferences based only on within-mother effects. Confounding factors that can vary between births and affect interpregnancy interval were maternal age, parity, birth year, ethnicity, socioeconomic status, and outcome of the previous birth. The terms matched and unmatched referred to the within-mother design based on conditional and unconditional logistic regression, respectively. Among the 40,441 pairs of second and third births, matched by mother, the mean incidence rates for preterm birth, SGA, and low birth weight for second births were 5.3%, 7.4%, and 3.5%, respectively. For third births, the rates were 5.8%, 6.3%, and 3.6%, respectively. Unconditional logistic regression suggested a strong effect of short interpregnancy interval on the incidence of preterm birth and low birth weight but not SGA, after adjustment for confounders. Among interpregnancy intervals of less than 18 to 23 months, the highest odds ratios (ORs) for preterm birth (adjusted OR [aOR], 1.41; 95% confidence interval [CI], 1.31–1.51) and low birth weight (aOR, 1.26; 95% CI, 1.15–1.37) were for intervals of 0 to 5 months. The incidence of SGA birth was similar across 0 to 23 months, with ORs ranging from 0.98 to 1.03. Among interpregnancy intervals of more than 18 to 23 months, the highest OR of preterm birth (aOR, 1.35; 95% CI, 1.26–1.45) was 60 to 119 months; the highest ORs of low birth weight (aOR, 1.67; 95% CI, 1.42–1.97) and SGA (aOR, 1.98; 95% CI, 1.74–2.24) were for intervals of more than 119 months. In the matched model, among intervals of less than 18 to 23 months, the highest ORs of preterm birth (aOR, 1.07; 95% CI, 0.86–1.34) and low birth weight (aOR, 1.03; 95% CI, 0.79–1.34) were for 0 to 5 months. The OR for SGA was estimated at 1.08 for all 3 categories of interpregnancy intervals of less than 18 months. For preterm birth at intervals of more than 23 months, ORs ranged from 1.01 (0.86–1.18) for 24 to 59 months to 0.88 (0.54–1.46) for more than 119 months. For intervals of more than 23 months, ORs for low birth weight ranged from 1.07 (0.88–1.30) for 24 to 59 months to 1.58 (0.82–3.06) for more than 119 months. Odds ratios for SGA ranged from 1.11 (0.96–1.28) for 24 to 59 months to 1.72 (1.04–2.85) for intervals of more than 119 months. These results do not support the concept of a causal effect of short interpregnancy interval on adverse birth outcomes. However, short interpregnancy interval remains a strong predictor of the risk for adverse birth outcomes, but correlated maternal risk factors must be considered. Clinicians should treat a short interpregnancy interval as a possible risk of adverse birth outcomes but remain aware of other maternal risk factors.
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Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,008 | 0,027 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,001 | 0,002 |
| Bibliométrie | 0,002 | 0,004 |
| Études des sciences et des technologies | 0,001 | 0,000 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,002 | 0,001 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,005 | 0,001 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».