Peri-conception hyperglycaemia and nephropathy are associated with risk of congenital anomaly in women with pre-existing diabetes: a population-based cohort study

Abstract

AIMS: The aim of this study was to quantify the risk of major congenital anomaly, and to assess the influence of peri-conception HbA(1c) and other clinical and socio-demographic factors on the risk of congenital anomaly occurrence in offspring of women with type 1 and type 2 diabetes diagnosed before pregnancy. METHODS: This was a population-based cohort study using linked data from registers of congenital anomaly and diabetes in pregnancy. A total of 401,149 singleton pregnancies (1,677 in women with diabetes) between 1996 and 2008 resulting in live birth, fetal death at ≥20 weeks' gestation or termination of pregnancy for fetal anomaly were included. RESULTS: The rate of non-chromosomal major congenital anomaly in women with diabetes was 71.6 per 1,000 pregnancies (95% CI 59.6, 84.9), a relative risk of 3.8 (95% CI 3.2, 4.5) compared with women without diabetes. There was a three- to sixfold increased risk across all common anomaly groups. In a multivariate analysis, peri-conception glycaemic control (adjusted OR [aOR] 1.3 [95% CI 1.2, 1.4] per 1% [11 mmol/mol] linear increase in HbA(1c) above 6.3% [45 mmol/mol]) and pre-existing nephropathy (aOR 2.5 [95% CI 1.1, 5.3]) were significant independent predictors of congenital anomaly. Associations with gestation at booking (aOR 1.1 [95% CI 1.0, 1.1]) and parity (aOR 1.6 [95% CI 1.0, 2. 5]) were not significant. Unadjusted risk was higher for women from deprived areas or who did not take folate. Type and duration of diabetes, ethnicity, age, BMI, preconception care, smoking and fetal sex were not associated with congenital anomaly risk. CONCLUSIONS: Peri-conception glycaemia is the most important modifiable risk factor for congenital anomaly in women with diabetes. The association with nephropathy merits further study.

HbA1c and birthweight in women with pre-conception type 1 and type 2 diabetes: a population-based cohort study

“…We also used data from two other linked regional surveys, NorCAS and PMMS, which allowed us to create a complete dataset of normally formed singleton pregnancies in women with diabetes. By excluding pregnancies affected by a major congenital anomaly (over 7% in this population [3]) and antepartum stillbirths, known to be associated with low birthweight, we avoided a potential bias of over-representation of SGA fetuses, which other similar studies might not have. The birthweight distribution of the North of England birth population, both overall and among women with diabetes, is almost identical to the equivalent distribution in England and Wales [8] (ESM Fig.…”

“…Gestational age (centred to reduce collinearity) was modelled as a three-term polynomial, i.e. b 1 (gestational age − x)+b 2 (gestational age − x) 2 + b 3 (gestational age − x) 3 (see electronic supplementary material [ESM] Fig. 1).…”

“…Women with type 1 and type 2 diabetes have a much higher risk of serious adverse pregnancy outcomes, such as stillbirth, major congenital anomalies, neonatal morbidity and mortality [1][2][3][4]. Maternal diabetes is also associated with a higher risk of aberrant fetal growth.…”

Congenital anomalies in diabetic pregnancy: an important confirmation

“…The paper in this issue of Diabetologia by Bell et al is important [2]. It is the first time that epidemiologists with particular knowledge of congenital fetal anomalies, and of diabetes management before and during pregnancy, have come together to observe-albeit retrospectively-all of the actual outcomes of pregnancy in a defined region.…”

The North of England Survey of Twin and Multiple Pregnancy

“…The records are maintained and held at the RMSO on a single database linked through the mother's details to the Perinatal Morbidity and Mortality Survey (PMMS; Hey et al, 1984), the Northern Congenital Abnormality Survey (NorCAS;Richmond & Atkins, 2005), the Northern Diabetes in Pregnancy Survey (NorDIP; Bell et al, 2012), and the North of England Collaborative Cerebral Palsy Survey (NECCPS; Glinianaia et al, 2011b). Beaumont Colson Ltd, database designers, developed the RMSO database using Bespoke software.…”