Correlation of glycosylated hemoglobin and macrosomia in infants of diabetic mothers

Objective

Maternal diabetes mellitus has a significant impact on the neonatal outcome. Birth weight is related to the degree of glycemic control. Poor glycemic control in the mother causes somatic overgrowth and results in macrosomia. Maternal obesity is an independent risk factor for macrosomia. The study objective was to evaluate the correlation between glycosylated hemoglobin (HbA1c) level in diabetic mothers and macrosomia in their neonates.

Methods

A cross-sectional observational study was done on diabetic mothers and their neonates. Maternal body mass index, weight gain, duration of diabetes and type of treatment were recorded. Maternal HbA1c levels were measured within one hour of delivery and birth order, mode of delivery, gestational age and birth weight were recorded. The discrete variables were analyzed by chi-square test and continuous variables by independent t-test. Receiver operating characteristic (ROC) analysis was used to determine the optimum cut-off for predicting macrosomia with HbA1c. A p-value of <0.05 was considered significant.

Results

A total of 228 diabetic mothers and their neonates were studied and 18 neonates were macrosomic. Diabetes was pregestational in 56.6% of mothers and gestational in 43.4% of mothers. There was a significant difference in BMI, weight gain, and HbA1c in mothers of macrosomic and non-macrosomic neonates. There was no significant difference in mean values of maternal age, duration of diabetes and gestational age in the two groups.

Conclusion

This study suggests that diabetic women with elevated HbA1c>5.6% measured after delivery were likely to have macrosomic neonates.

Keywords

Gestational diabetes, macrosomia, glycosylated hemoglobin A.

Introduction

Maternal diabetes mellitus in both pre-gestational and gestational periods have a significant impact on the neonatal outcome. Outcome of pregnancy is related to the degree of glycemic control, and poor glycemic control in the mother causes somatic overgrowth and results in macrosomia. The term macrosomia denotes birth weight more than the 90th percentile or baby weighing >4000 g.[1] These infants have excess fat deposition on shoulders and trunk which predisposes to primary Cesarean section and birth trauma. Factors like increased insulin like growth factor-1, fibroblast growth factor, epidermal growth factor, platelet derived growth factor, leptin and also adiponectin are implicated in macrosomia.[2–4] Maternal obesity is an independent risk factor for macrosomia. Prevalence of gestational diabetes mellitus increases with increase in body mass index.[5] Excess weight gain during pregnancy is an additional risk factor for macrosomia. Excessive gestational weight gain was considered when it exceeded the total weight gain recommendations from the Institute of Medicine (IOM). As per the revised guidelines, the upper limit of recommended weight gain in pregnant women ranges from 9 kg to 11.5 kg for obese and overweight women, and 16 kg to 18 kg for normal and underweight women.[6,7]
This study was planned to find a correlation between glycosylated hemoglobin (HbA1c) level in the mother and macrosomia in the infant of diabetic mother. Emerging evidence indicates that abnormal fetal growth can occur before the routine biochemical diagnosis of gestational diabetes at 24–28 weeks of gestation.[8] This warrants measures to improve glycemic control early, more so in high risk obese population.[9]
The Hyperglycemia and Adverse Pregnancy Outcome (HAPO) study compared diabetic mothers with normal mothers and observed a strong association of higher maternal glucose levels with increased birth weight above the 90th percentile for gestational age.[10] Adverse pregnancy outcomes were higher in diabetic mothers if ideal glucose levels were not maintained.[11]
The cause of macrosomia in infants of diabetic mothers is considered to be the poor glycemic control. However, there are other studies where no significant correlation was found between the fetal body weight and the level of HbA1c in the mother. This study was planned to get a better understanding of the cause of macrosomia and investigate the ways to reduce its occurrence.

Methods

The study objective was to evaluate the correlation between HbA1c and macrosomia in infants of diabetic mothers. This was a cross-sectional study done between February and July 2016 at Department of Pediatrics of a tertiary care Medical College Hospital. The study protocol was approved by institutional ethics committee (protocol ID no 13/2016 meeting held on 4.4.2016). The study population included neonates born to diabetic mothers who delivered in a tertiary care Medical College hospital. Sample size was calculated using single population proportion formula by using the following statistical assumptions: 65% proportion (based on previous studies), 95% confidence interval, 5% marginal error (alpha) and expected response rate of 90%. For estimating the expected proportion with a 10% precision relative to the expected proportion which was 6.5%. The final sample size was 230.
Pregnant women who were diagnosed with pregestational diabetes or gestational diabetes fulfilling the inclusion criteria were enrolled into the study after obtaining their written informed consents (Fig. 1). Maternal blood samples were taken to measure HbA1c levels within one hour of delivery of baby. HemoCue HbA1c 501 Analyser (HemoCue AB, Ängelholm, Sweden) was used to estimate HbA1c level. The women were classified into two categories as having pre-gestational and gestational diabetes mellitus. Their body mass index, weight gain during pregnancy, duration of diabetes mellitus and type of treatment for diabetes were recorded. Neonates with congenital anomalies and neonates of mothers having any other co-morbid conditions apart from diabetes mellitus were excluded. Electronic weighing scale was used to measure birth weight. The newborn’s birth order, mode of delivery, gestational age and birth weight were recorded. The discrete variables were analyzed by chi-square test and continuous variables by t-test. The analysis was done by SPSS 17 software. The variables like maternal BMI, type of diabetes and treatment plan adopted were analyzed by chi-square test. The variables like maternal age, duration of diabetes, weight gain during pregnancy, HbA1c at the time of delivery and gestational age were analyzed by independent t-test. Receiver operating characteristic (ROC) analysis was used to determine the optimum cut-off for predicting macrosomia using the HbA1c levels at the time of delivery. A p-value <0.05 was considered significant.

Results

A total of 230 diabetic pregnant women and their neonates were enrolled for the study. As 2 patients had missing data, a total of 228 diabetic pregnant women and their neonates were analyzed. We observed that majority of the macrosomic neonates were born to mothers less than 25 years of age, and this constituted 55.6% of the macrosomic neonates. The prevalence of macrosomia in mothers above 31 years of age was only 11.1%. We observed that the occurrence of macrosomia decreased as maternal age increases. However, this was not statistically significant. Maternal anthropometric parameters had a significant impact on the birth weight of the babies and the BMI of the mother was significantly associated with macrosomia. In women with BMI >25, the majority of the babies (50%) were macrosomic. With increasing BMI, the occurrence of macrosomia increased and this was statistically significant (p-value 0.000). There was no difference in macrosomia between gestational diabetes mellitus and pre-gestational diabetes mellitus but this was not statistically significant. Macrosomia was more common in mothers who were on insulin (61.1%) as compared to those on meal plan but this was not statistically significant. The information about duration of insulin therapy was not obtained in our study and the impact of the duration of treatment on the outcome of macrosomia was not evaluated. Macrosomia was more common (38.9%) when the birth order was first or second. It was observed that all macrosomic babies were delivered by Cesarean section (Table 1).
The mean maternal age of mothers who had macrosomic neonates was 25.56 years (SD=3.382) and was similar to non-macrosomic neonates with no statistically significant difference. The mean BMI was higher (24.72; SD=2.461) in mothers who had macrosomic neonates than in non-macrosomic neonates, and this was found to be statistically significant. Mothers of macrosomic neonates had a mean weight gain of 13.72 kg (SD=0.895) which was higher than in those of non-macrosomic neonates and this was found to be statistically significant. Mean duration of diabetes was lower (14.89 months; SD=14.768) among mothers who had macrosomic neonates and it was 21.81 months (SD=25.463) in mothers who had non-macrosomic babies, and this was not statistically significant. Details about the duration of different types of treatment (insulin and meal plan) was not obtained in the study and hence not compared between the groups. The mean HbA1c at delivery was higher (5.978%; SD=0.2365) in mothers who had macrosomic neonates while in those who had non-macrosomic neonates the mean HbA1c at delivery was 4.853% (SD=0.4825) and was statistically significant. Mothers who had macrosomic neonates had HbA1c values above 5.6% than those who had non-macrosomic babies. There was no statistically significant difference between mean gestational age of macrosomic neonates (37.67 weeks) and non-macrosomic neonates (37.69 weeks) (Table 2).
Receiver operating characteristic (ROC) analysis was used to determine the optimum cut-off for predicting the occurrence of macrosomia using the HbA1c levels at the time of delivery (Fig. 2). The area under the ROC curve is 0.984656 which signifies that it is an excellent tool to predict macrosomia with a HbA1c value >5.6% (Table 3).

Discussion

In our study, we found that the majority of macrosomic neonates (55.6%) were born to young mothers below 25 years of age. The mean age of women having macrosomic neonates was 25.56 years (SD=3.382). This is in contrast to the study published by Stotland et al.[12] where they observed that macrosomia was more common in advanced maternal age between 30 to 40 years. However, we found that 61.1% of the macrosomic neonates were born in the group of women who were taking insulin implying that women requiring insulin to maintain a stable glucose control have a more deranged carbohydrate metabolism in the body with poor glycemic control which ultimately leads to fetal overgrowth. Women on meal plan offer a better intrauterine environment so as not to lead to fetal growth alterations. This is in confirmation of the study done by Suhonen et al.[13] in which they found that macrosomia occurred more often in women treated with insulin which supports the fact that the requirement for insulin is probably in those mothers with poor glycemic control.
In the present study, there was no difference in incidence of macrosomia in different types of diabetes mellitus. In our study, macrosomia occurred with equal frequency in women with gestational diabetes mellitus (50%) and pre-gestational diabetes mellitus (50%). However, Wahabi et al.[14] found in their study that women with gestational diabetes mellitus had increased odds of having a macrosomic baby (OR=1.65, 95% CI: 1.32–2.07).
In our study, there was a statistically significant correlation between HbA1c at delivery and occurrence of macrosomia in infants of diabetic mothers. Diabetic mothers with HbA1c>5.6% were more likely to have macrosomic babies. This had a sensitivity of 94.4 and specificity of 96.7. HbA1c value measured at the time of delivery was a good indicator of macrosomia. As the major weight gain in the fetus occurs in the last trimester of pregnancy, it is the period during which high glucose level in the maternal blood favors fetal overgrowth.[15] This was similar to the findings by Mikkelsen et al.[16] in their study that median HbA1c value was 5.9% before delivery which had a 3-fold increased risk of having large for gestational age babies. Gandhi et al.[17] evaluated in their study the impact of HbA1c levels and glycemic variability (assessed by mean home blood glucose levels) on the birth weight of neonates born to diabetic mothers and observed that the birth weight increased with HbA1c >6.5%. Bhavadharini et al.[18] found that in those patients who had HbA1c>5.0%, the adjusted OR for macrosomia was 1.92 (95% CI=1.24–2.97, p=0.003). The patients with HbA1c>5.0% were also significantly older, had higher body mass index, history of previous gestational diabetes mellitus and increased incidence of macrosomia. Bhavadharini et al.[18] found that pregnant women who had HbA1c≥5.0% had higher risk of macrosomia, majority of whom did not have gestational diabetes mellitus (GDM). This finding is of particular interest because it shows that HbA1c may be used as a marker for macrosomia, independent of the diagnosis of gestational diabetes mellitus.
However, studies by other researchers contradict this theory. Taylor et al.[19] found no relationship between mean HbA1c values and birth weight (R=0.02, p>0.1) in their study. Weissman-Brenner et al.[20] conducted a study on non-diabetic pregnant women and observed that the mean ± SD HbA1c level in women who delivered macrosomic neonates was 5.3±0.7% and those who had non-macrosomic neonates was 5.2±0.5% (p=0.27). The area under ROC curve for prediction of macrosomia by HbA1c levels was 0.53 (p=0.27) and ROC was a poor screening tool to predict macrosomia. Penny et al.[21] observed in their study that there was no statistically significant correlation between third trimester HbA1c levels and birth weight of the newborn. Binbir et al.[22] found that maternal HbA1c levels and macrosomia did not show any statistically significant relationship (p=0.701).
This study has its own limitations. Measuring the blood glucose level at the time of delivery gives us no time for interventions to modify pregnancy outcome. The timing of the test should be such that we can intervene to alter the perinatal outcome in the infants of diabetic mother. We did not study the impact of time of initiation of insulin treatment on the outcome of macrosomia. We conducted the study in a single center with limited sample size. However, the study was useful to understand the association between glycemic control and macrosomia.

Conclusion

Overall, this study suggests that HbA1c at delivery >5.6 % is statistically significantly related to the women giving birth to macrosomic neonates. Diabetic pregnant women who have a higher value of HbA1c are more likely to have macrosomic neonates. Other maternal characteristics related significantly to macrosomia are BMI, weight gain during pregnancy and delivery by Cesarean section. Diabetic women who had poor glycemic control and warranted treatment with insulin were at higher risk having macrosomia in their babies. Rest of the parameters i.e. age of the mother, type of diabetes mellitus, duration of diabetes mellitus, gestational age were not associated with macrosomia. Adequate control of blood sugar is important to normalize the internal milieu and improve perinatal outcome in the infants of diabetic mothers.

References

1. Cloherty JP, Eichenwald EC, Hansen AR, Stark AR (Eds.) Manual of neonatal care. 7th ed. Philadelphia, PA: Wolters Kluwer, Lippincott Williams & Wilkins; 2012.


2. Grissa O, Yessoufou A, Mrisak I, Hichami A, Amoussou-Guenou D, Grissa A, et al. Growth factor concentrations and their placental mRNA expression are modulated in gestational diabetes mellitus: possible interactions with macrosomia. BMC Pregnancy Childbirth 2010;10:7. [PubMed] [CrossRef] 


3. Loukovaara M, Leinonen P, Teramo K, Andersson S, Alfthan H, Stenman UH. Diabetic pregnancy associated with increased epidermal growth factor in cord serum at term. Obstet Gynecol 2004;103:240–4. [PubMed] [CrossRef] 


4. Mazaki-Tovi S, Kanety H, Pariente C, Hemi R, Schiff E, Sivan E. Cord blood adiponectin in large-for-gestational age newborns. Am J Obstet Gynecol 2005;193:1238–42. [PubMed] [CrossRef] 


5. Torloni MR, Betran AP, Horta BL, Nakamura MU, Atallah AN, Moron AF, et al. Prepregnancy BMI and the risk of gestational diabetes: a systematic review of the literature with meta-analysis. Obes Rev 2009;10:194–203. [PubMed] [CrossRef] 


6. American College of Obstetricians and Gynecologists. ACOG Committee opinion no. 548: weight gain during pregnancy. Obstet Gynecol 2013;121:210–2. [PubMed] [CrossRef] 


7. Pereda J, Bove I, Pineyro MM. Excessive maternal weight and diabetes are risk factors for macrosomia: a cross-sectional study of 42,663 pregnancies in Uruguay. Front Endocrinol (Lausanne) 2020;11:588443. [PubMed] [CrossRef] 


8. Venkataraman H, Ram U, Craik S, Arungunasekaran A, Seshadri S, Saravanan P. Increased fetal adiposity prior to diagnosis of gestational diabetes in South Asians: more evidence for the ‘thin-fat’ baby. Diabetologia 2017;60:399–405. [PubMed] [CrossRef] 


9. Sovio U, Murphy HR, Smith GCS. Accelerated fetal growth prior to diagnosis of gestational diabetes mellitus: a prospective cohort study of nulliparous women. Diabetes Care 2016;39:982–7. [PubMed] [CrossRef] 


10. HAPO Study Cooperative Research Group; Metzger BE, Lowe LP, Dyer AR, Trimble ER, Chaovarindr U, Coustan DR, et al. Hyperglycemia and adverse pregnancy outcomes. N Engl J Med 2008;358:1991–2002. [PubMed] [CrossRef] 


11. Buhary BM, Almohareb O, Aljohani N, Alzahrani SH, Elkaissi S, Sherbeeni S, et al. Glycemic control and pregnancy outcomes in patients with diabetes in pregnancy: a retrospective study. Indian J Endocrinol Metab 2016;20:481–90. [PubMed] [CrossRef] 


12. Stotland NE, Caughey AB, Breed EM, Escobar GJ. Risk factors and obstetric complications associated with macrosomia. Int J Gynaecol Obstet 2004;87:220–6. [PubMed] [CrossRef] 


13. Suhonen L, Hiilesmaa V, Kaaja R, Teramo K. Detection of pregnancies with high risk of fetal macrosomia among women with gestational diabetes mellitus. Acta Obstet Gynecol Scand 2008;87:940–5. [PubMed] [CrossRef] 


14. Wahabi H, Fayed A, Esmaeil S, Mamdouh H, Kotb R. Prevalence and complications of pregestational and gestational diabetes in Saudi women: analysis from Riyadh Mother and Baby Cohort Study (RAHMA). Biomed Res Int 2017;2017:6878263. [PubMed] [CrossRef] 


15. Konar H (Ed.). DC Dutta’s textbook of obstetrics. 7th ed. New Delhi: Jaypee Brothers Medical Publishers (P) Ltd.; 2013.


16. Mikkelsen MR, Nielsen SB, Stage E, Mathiesen ER, Damm P. High maternal HbA1c is associated with overweight in neonates. Dan Med Bull 2011;58:4309. [PubMed] 


17. Gandhi RA, Brown J, Simm A, Page RC, Idris I. HbA1c during pregnancy: its relationship to meal related glycaemia and neonatal birth weight in patients with diabetes. Eur J Obstet Gynecol Reprod Biol 2008;138:45–8. [PubMed] [CrossRef] 


18. Bhavadharini B, Mahalakshmi MM, Deepa M, Harish R, Malanda B, Kayal A, et al. Elevated glycated hemoglobin predicts macrosomia among Asian Indian pregnant women (WINGS-9). Indian J Endocrinol Metab 2017;21:184–9. [PubMed] [CrossRef] 


19. Taylor R, Lee C, Kyne-Grzebalski D, Marshall SM, Davison JM. Clinical outcomes of pregnancy in women with type 1 diabetes. Obstet Gynecol 2002;99:537–41. [PubMed] [CrossRef] 


20. Weissmann-Brenner A, O’Reilly-Green C, Ferber A, Divon MY. Does the availability of maternal HbA1c results improve the accuracy of sonographic diagnosis of macrosomia? Ultrasound Obstet Gynecol 2004;23:466–71. [PubMed] [CrossRef] 


21. Penney GC, Mair G, Pearson DW. The relationship between birth weight and maternal glycated haemoglobin (HbA1c) concentration in pregnancies complicated by Type 1 diabetes. Diabet Med 2003;20:162–6. [PubMed] [CrossRef] 


22. Binbir B, Yeniel AO, Ergenoglu AM, Kazandi M, Akercan F, Sagol S. The role of umbilical cord thickness and HbA1c levels for the prediction of fetal macrosomia in patients with gestational diabetes mellitus. Arch Gynecol Obstet 2012;285:635–9. [PubMed] [CrossRef] 

	File/Dsecription
	Correlation of Glycosylated Haemoglobin and Macrosomia in Infants of Diabetic Mothers ethics approval letter
	Fig. 1. Flow diagram of the study enrollment.
	Fig. 2. ROC curve.
	Table 1. Maternal factors and macrosomia.
	Table 2. Comparison of mean values of risk factors in macrosomic and non-macrosomic babies.
	Table 3. ROC curve’s results.