Seasonal variations in incidence and maternal-fetal outcomes of gestational diabetes

Abstract

Aims: To determine whether the neonatal and delivery outcomes of gestational diabetes vary seasonally in the context of a relatively cool temperate climate.

Methods: A retrospect cohort of 23 735 women consecutively delivering singleton, live-born term infants in a single tertiary obstetrics centre in the UK (2004-2008) was identified. A total of 985 (4.1%) met the diagnostic criteria for gestational diabetes. Additive dynamic regression models, adjusted for maternal age, BMI, parity and ethnicity, were used to compare gestational diabetes incidence and outcomes over annual cycles. Outcomes included: random plasma glucose at booking; gestational diabetes diagnosis; birth weight centile; and delivery mode.

Results: The incidence of gestational diabetes varied by 30% from peak incidence (October births) to lowest incidence (March births; P=0.031). Ambient temperature at time of testing (28 weeks) was strongly positively associated with diagnosis (P<0.001). Significant seasonal variation was evident in birth weight in gestational diabetes-affected pregnancies (average 54^th centile June to September; average 60^th centile December to March; P=0.027). Emergency Caesarean rates also showed significant seasonal variation of up to 50% (P=0.038), which was closely temporally correlated with increased birth weights.

Conclusions: There is substantial seasonal variation in gestational diabetes incidence and maternal-fetal outcomes, even in a relatively cool temperate climate. The highest average birth weight and greatest risk of emergency Caesarean delivery occurs in women delivering during the spring months. Recognizing seasonal variation in neonatal and delivery outcomes provides new opportunity for individualizing approaches to managing gestational diabetes.

Figure 1

(a) Result of booking random plasma glucose dependent on day of screening (P<0.001). (b) Risk of diagnosis of gestational diabetes (GDM) dependent on day of delivery (P=0.031). P values refer to the significance of the non‐parametric trend in the relevant dependent variable across the annual cycle, derived from dynamic additive logistic regression models. x‐axis tick marks correspond in dates to 1 January (day 1), 30 April (day 120), 28 August (day 240) and 26 December (day 360), respectively. Vertical marks along the x‐axis represent individual observations. Horizontal line represents the mean risk level for the outcome; risks that are negative with respect to this line are therefore less likely than average, and those that are positive are more likely than average. Dashed lines represent the area within two standard errors of the mean for numeric variables only. Models are adjusted for maternal age, maternal BMI at booking, ethnicity, and parity.

Figure 2

(a) Average birth weight centile dependent on day of delivery (P=0.027). (b) Likelihood of delivery by emergency Caesarean section dependent on day of delivery (P=0.038). P values refer to the significance of the non‐parametric trend in the relevant dependent variable across the annual cycle, derived from dynamic additive logistic regression models. x‐axis tick marks correspond in dates to 1 January (day 1), 30 April (day 120), 28 August (day 240) and 26 December (day 360), respectively. Vertical marks along the x‐axis represent individual observations. Horizontal line represents the mean risk level for the outcome; risks that are negative with respect to this line are therefore less likely than average, and those that are positive are more likely than average. Dashed lines represent the area within two standard errors of the mean for numeric variables only. Models are adjusted for maternal age, maternal BMI at booking, ethnicity and parity.