Diabetes during pregnancy and perinatal outcomes among First Nations women in Ontario, 2002/03–2014/15: a population-based cohort study
Notice bibliographique
Résumé
BACKGROUND: In Canada, increasing numbers of women, especially First Nations women, are affected by diabetes during pregnancy, which is a major risk factor for adverse maternal and neonatal outcomes. The aim of this study was to examine temporal trends in pregnancy outcomes and use of health care services in a population-based cohort of First Nations women compared to other women in Ontario according to diabetes status during pregnancy. METHODS: Using health administrative databases, we created annual cohorts of pregnant women from 2002/03 to 2014/15 and identified those with preexisting diabetes and gestational diabetes. We used the Indian Register to identify First Nations women. We estimated rates of adverse maternal and infant outcomes, and measures of use of health care services in each population. RESULTS: There were 1 671 337 deliveries among 1 065 950 women during the study period; of these deliveries, 31 417 (1.9%) were in First Nations women, and 1 639 920 (98.1%) were in other women. First Nations women had a higher prevalence of preexisting diabetes and gestational diabetes than other women in Ontario. First Nations women with preexisting diabetes had higher rates of preeclampsia (3.2%-5.6%), labour induction (33.4%-42.9%) and cesarean delivery (47.8%-53.7%) than other women in Ontario, as did First Nations women with gestational diabetes (3.2%-4.7%, 38.5%-46.9% and 41.4%-43.4%, respectively). The rate of preterm birth was similar between First Nations women and other women in Ontario. Although First Nations women had a higher rate of babies who were large for gestational age than other women, regardless of diabetes status, obstructed labour rates were similar for the 2 cohorts. Almost all First Nations women, regardless of diabetes status, were seen by a primary care provider during their pregnancy, but rates of use of specialty care were lower for First Nations women than for other women. Fifteen percent of all pregnant women with preexisting diabetes visited an ophthalmologist during their pregnancy. INTERPRETATION: Our results confirm disparities in maternal and neonatal outcomes between First Nations women and other women in Ontario. Access to primary care for pregnant women seemed adequate, but access to specialized care, especially for women with preexisting diabetes, needs to improve.
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Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 0,000 |
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 tête enseignante, 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 ».