Gestational diabetes (GDM) is a condition of carbohydrate intolerance that is diagnosed during the second or third trimester of pregnancy, making a distinction from overt diabetes in pregnancy [1,2]. GDM occurs when the activity of β cells is insufficient to overcome the insulin resistance induced by a series of hormones of placental origin and which is typical of the late stages of pregnancy [3]. Common risk factors for the development of GDM are maternal age >35 years, family history of diabetes, occurrence of GDM in previous pregnancies, overweight/obesity, belonging to ethnic groups at higher risk [4]. The prevalence of GDM reported in various studies is around 7%, with a wide range (1-25%) depending on the ethnic group analyzed and the diagnostic criteria used [5]. Recent studies indicate an increase in this prevalence over time, both in high- and low-to-middle-income countries; this is possibly linked to the increase in obesity among women of childbearing age [6-8]. Increased obstetric and neonatal risks are reported if GDM occurs, and affected pregnant women have a 50-65% risk of GDM recurrence in the next pregnancy compared to unaffected mothers. A pregnant woman with GDM presents, in addition to greater obstetric risks, a risk of up to sevenfold of developing type 2 diabetes mellitus within 5-10 years of delivery, compared to a woman with normoglycaemic pregnancy [4,6,9,10]. An accurate and timely identification of GDM, through a pregnancy screening is useful for the management of pregnancy itself, but also for planning of birth, containment of adverse effects for the newborn and planning of postpartum checks [11,12]. The HAPO study (Hyperglycemia and Adverse Pregnancy Outcome), as well as other studies have shown the relevant effects of even mild maternal hyperglycemia on maternal and fetal complications and that screening, diagnosis and treatment of GDM can be cost-effective[13-16]. The International Association of Diabetes and Pregnancy Study Group (IADPSG) in 2010 established in a consensus the indications for diagnosis of GDM which were subsequently implemented by several countries including Italy [17,18]. Furthermore, a debate is still open in the scientific community regarding the optimal management strategy of GDM and the acceptable duration of pregnancy even if labor induction is often a suggested option in order to mitigate possible adverse maternal and fetal outcomes [19-21]. In any case, maintaining metabolic control remains important to guarantee an optimal course of pregnancy and guarantee the best obstetric and neonatal outcomes. This retrospective observational study reports the prevalence of GDM in pregnant women assisted at maternity units in the Autonomous Province of Trento (North East Italy with 540,000 inhabitants as of 31 December 2018) in the years 2017-2019. The study also analyses the obstetric and neonatal outcomes on the basis of the data provided by the Birth Assistance Certificate (BAC).

The Italian Physiological Pregnancy guideline recommends a fasting plasma glucose check for all pregnant women at the first pregnancy visit (within 12 weeks of gestation) in order to identify women with pre-pregnancy diabetes. GDM screening using the 75 g oral glucose load tolerance test (OGTT) is performed later in pregnancy if certain risk factors are present and. In detail, this test is prescribed at 16-18 weeks of gestation in case of a previous diagnosis of GDM, pregravidic body mass index (BMI) ≥30 kg/m2, or plasma glucose values between 100 and 125 mg/dL before pregnancy or early in the pregnancy. It is performed at 24-28 weeks if the maternal age is ≥35 years, pregravidic BMI is ≥25 kg/m2, foetal macrosomia was diagnosed in a previous pregnancy, there is a first-degree family history of diabetes, or if the patient comes from an area with a high prevalence of diabetes, such as South Asia, the Caribbean, and the Middle East. The diagnosis is made for a single value ≥92 mg/dL fasting, 180 mg/dL at 60 min, and 153 mg/ dL at 120 min [18]. Upon identification of a GDM case, operators of obstetrics area contact the local diabetes care center who provide specialistic assistence to the mother until the birth. In the Province of Trento, data relating to glycaemic screening carried out during pregnancy are recorded in the personal obstetric guide of each pregnant woman, which is updated at each periodic obstetric check during pregnancy and, at the time of birth, in a dedicated electronic archive known as the Birth Assistance Certificate (BAC). The BAC information flow includes the national information document of reference for the registration of parental characteristics, the monitoring of assistance in pregnancy and childbirth, and the registration of the characteristics of the new-born [22]. The compilation of the BAC by health workers who assist the birth, usually midwives, is mandatory and operational in all maternity units in Trento. The provincial BAC archive is annually made available to the Clinical and Evaluation Epidemiology Service of the Provincial Health Services Agency of the Province of Trento. The GDM cases registered in the BAC were verified in the Hospital Information System (HIS) which is an electronic repository that collects the results of all of the diagnostic-therapeutic services carried out by users of the provincial health service. On the basis of the data recorded in the BAC and confirmed by the HIS, the birth cohorts from 2017 -2019 were retrospectively analyzed. The prevalence of GDM, with CI 95%, was calculated among all of the recorded pregnant women. The characteristics of pregnant women with GDM were evaluated compared to pregnant women with neither GDM nor overt diabetes (NGT group), considering the following variables: citizenship (Italian/foreign), age group and educational qualification. The significance of the differences between the categories under comparison was tested with the Chi-squared test. The evolution of pregnancy and obstetric outcomes were analyzed for the two subpopulations of pregnant women, considering the following variables: number of obstetric visits and ultrasounds, onset of hypertension/eclampsia/preeclampsia, premature rupture of membranes, type of labor, type of delivery, use of episiotomy in case of vaginal delivery, frequency of vaginal tears, primary postpartum haemorrhage. Statistical significance of the differences in the frequency of the variables of interest between the two subpopulations was tested with the chi-squared test. Neonatal outcomes between the two subpopulations were evaluated on the basis of the following variables: vital status at birth, gestational age, birth weight with estimate of the proportion of SGA cases and LGA cases, using the criteria provided by the WHO [23]. The other variables considered were: congenital malformations at birth, use of phototherapy, hospitalization at birth, admission to the neonatal intensive care unit, shoulder dystocia, frequency of the Apgar index at 5 minutes < of 7. The significance of the differences in the frequency of the variables of interest between the offspring of mothers with GDM versus those of NGT mothers was tested with the chi-squared test. The association between GDM and neonatal obstetric outcomes was analyzed through a multiple analysis according to the logistic model, considering, to minimize confounding, only singleton pregnancies. Finally, organizational characteristics (type of maternity units) and some maternal characteristics (age class, citizenship, pre-pregnancy weight) was evaluated as possible modifiers of the effect of GDM on neonatal-obstetric outcomes.

During the study period, 12,401 pregnant women were assisted at the maternity units in the Province of Trento. The average proportion of pregnant women with foreign citizenship was 25.8 %. The average age of the pregnant patients was 32 years, with that of Italians’ being 33 years and that of foreigners’, 30 years. A total of 841 cases of GDM were recorded (280 cases per year), 480 of whom were Italian and 361, foreigners. There were a total of 195 cases of overt diabetes recorded (65 per year on average). The agreement between the data on GDM recorded in the BAC and in the SIO is on average very high, around 98%. The average age of the patients with GDM was 34 years, with the Italians’ being 35 years and the foreigners’, 32.5 years. The average period prevalence of GDM among all of the pregnant women was 6.8 % (CI, 6.3-7.2), with the average prevalence among Italian women being 5,2 % (CI, 4.8–5.4) and among foreign women, 11.4 % (CI, 10.4–12.4). The prevalence of GDM among the foreigners was significantly higher than that among the Italians (p < 0.001). Among the foreigners, the prevalence was higher among Asians (15.7; CI, 12.7–18.7), followed by Africans (14.2; CI, 11.0–17.2). Pregnant women with GDM had, compared with those in the NGT group, an older age, a higher proportion of multiparous and less educated pregnant women, about twice the prevalence of foreign women and overweight women, and an approximately four-fold prevalence of obesity. The proportion of pregnant women who smoke during pregnancy substantially coincides between the two groups (table 1). 11.2% of pregnant women with GDM used insulin during pregnancy. Compared to NGT pregnant women pregnant women with GDM attended a higher average number of obstetric visits and ultrasound scans during pregnancy, even if the difference is not statistically significant. In the GDM group there is a double proportion of hypertension/eclampsia/preeclampsia, a more frequent recourse to induction of labor and cesarean delivery, especially elective, a greater frequency of vaginal tears, in the case of vaginal delivery, with a difference at the limits of statistical significance and a higher prevalence of primary postpartum hemorrhage, although not statistically significant (tab.2). Offspring of women with GDM, compared to those born to NGT mothers, showed an excess of preterm deliveries, low birth weight, LGA (above the 90th percentile for gestational age) and macrosomes (>4000 g). There was also an excess of newborns hospitalized at birth, admitted to intensive care unit and phototherapy. On the other hand, no differences emerged in the prevalence of congenital malformations and of live births with Apgar at 5 minutes lower than 7 (table 3). The multivariate analysis, conducted on 11,825 births, highlighted how the fundamental differences between infants of GDM mothers and those of NGT mothers essentially were the use of elective caesarean delivery and caesarean delivery in labor and hospitalization at birth (table 4). Regarding the evaluation of effect modifiers, we found that only age group and pre-pregnancy maternal weight modify the relationship between GDM status and the risk of elective caesarean section (figure 1,2).

Table 1: Socio-demographic characteristics of pregnant women with GDM vs. pregnant women with normal glucose tolerance. Percentages Values.

n.s.: not significant

Table 2: Frequency of clinical checks and pregnancy events. Comparison between pregnant women with GDM and pregnant women with normal glucose tolerance. Percentages Values.

Kg Kilo, n.s. Not significant

Table 3: Health Status of Newborns Comparison between pregnant women with GDM and pregnant women with normal glucose tolerance.

g grams, SGA small for gestational age, LGA large for gestational age.

Table 4: Odds Ratios Estimates with 95% CI. Neonatal outcomes: comparison between newborn to pregnant women with GDM and pregnant women with normal glucose tolerance.

SGA small for gestational age, LGA large for gestational age, NICU: neonatal intensive care unit

Figure 1: Odds ratio and 95% CI of elective caesarean section in GDM mothers by age classe of mothers.

Figure 2: Odds ratio and 95% CI of elective caesarean section in GDM mothers by pre pregnancy BMI.

The BAC, if properly used, can allow an epidemiological representation of GDM in the reference population. Moreover, since it is not a tool aimed at research activity, the completeness and accuracy of the recorded data have always to be taken into account. In our experience, also thanks to the comparison with other sources of information, we can count on reliable data concerning an overall and homogeneous series, referable to a well-specified reference population. In our study, GDM represents about 80% of cases of diabetes mellitus that occur in pregnancy. The present study confirms that pregnant women with GDM have different pre-pregnancy anthropometric characteristics compared to NGT pregnant women. Pregnant women with GDM have an older mean age that correlates well with a higher proportion of multiparous mothers. They also have a lower level of education, in particular the proportion of subjects with up to 8 years of study (elementary + lower middle school) is about double compared to NGT mothers. In pregnant women with GDM, foreign women are about double, as well as the proportion of overweight subjects while the proportion of subjects with obesity is about four times higher than in NGT pregnant women. Overall, the peculiarity of the characteristics of mothers affected by GDM is consistent with what has been reported by previous studies (24-26). A diagnosis of GDM implies more checkups during pregnancy and this is evident from the study, even if the differences in terms of obstetric visits and ultrasound checks do not appear to be statistically significant compared to the NGT mothers. We confirm what reported by previous studies [27-31] about an excess of cases of preeclampsia/eclampsia/hypertension in pregnant women with GDM which in our study is about double compared to the group of NGT pregnant women. All of these conditions are induced by the increased insulin resistance in pregnant women with GDM but also recognize an association with overweight/obesity [32,33]. It is also found, in pregnant women with GDM, an excess of induced labor and an excess of caesarean sections [27,28,31,34]. The frequency of induced labor is about double in pregnant women with GDM than in NGT pregnant women. This would have the aim of minimizing the obstetric risks for the mother and the newborn, even if in the case of good metabolic compensation there would be no need to induce delivery before the term [19,20]. It may be likely that the delivery room management criteria lead, almost automatically, to a more frequent use of labor induction in these subjects. The use of episiotomy, as well as the frequency of lacerations and intrapartum or postpartum blood loss did not substantially differ between the two groups of pregnant women. It may be likely that the methods of case management in the last stages of pregnancy, together with the selection criteria and timing of delivery contribute to minimizing the differences in obstetric outcomes between the two groups of pregnant women. With regard to neonatal outcomes, our study highlights an excess of preterm and underweight newborns as well as cases of LGA, aspects already reported in previous studies [31,34-36]. A higher frequency of hospitalization at birth for hyperbilirubinemia and respiratory distress is confirmed, as well as an excess of shoulder dystocia [30,34,37-41]. Moreover, this last event does not appear with a significantly different frequency compared to mothers with normal glucose tolerance, it can presumably be prevented by a greater use of elective caesarean section and caesarean section in labor [34,42]. Our study does not highlight, unlike what was reported by previous studies [43-45], a greater frequency of congenital malformations, also taking into account that some anomalies, especially non-severe ones, such as those in the cardiac or urinary area, can be overlooked to detection at birth. The multiple analysis, according to the logistic model, highlights, controlling for a series of variables, that the significantly more frequent obstetric events are represented by the greater use of elective caesarean delivery and caesarean delivery in labor, as reported by previous studies [31,34]. With specific regard to the newborn, a more frequent hospitalization at birth is confirmed [36,37] but not necessarily a more frequent hospitalization in the neonatal intensive care unit. Analysis of the effect modifiers does not show differences in the obstetric-neonatal outcomes in relation to maternity units (hub versus spoke centres) and citizenship (Italian versus foreign) of the pregnant women, aspects which indicate a homogeneity of management of cases in the territory and an absence of inequalities associated with nationality. However, certain maternal characteristics can modify the relationship between GDM and obstetric-neonatal outcomes, such as maternal age and pre-pregnancy BMI, so that as age/weight class increases, the risk of elective caesarean delivery increases [46-48].

The current information sources used, although unable to directly provide an estimate of metabolic control in the last stages of pregnancy, allow an efficient description of the management and outcomes in pregnant women affected by GDM. Overall, the extent of obstetric-neonatal adverse events in pregnant women with GDM is conditioned by the intrinsic characteristics of pregnant women and appear to be sufficiently contained, probably thanks to the adoption of a homogeneous and shared protocol for gestational diabetes among the various operating centers in the Province of Trento.

1. Metzger BE, Coustan DR for the Organizing Committee. Summary and recommendations of the Fourth International Workshop Conference on Gestational Diabetes Mellitus. Diabetes Care. 1998; 21: B161–B1671.
2. Reece EA, Leguizamon G, Wiznitzer A. Gestational diabetes: the need for a common ground. Lancet. 2009; 373: 1789-97.
3. Butte NF. Carbohydrate and lipid metabolism in pregnancy: normal compared with gestational diabetes mellitus. Am J Clin Nutr. 2000; 71: 1256S-1261S.
4. National Collaborating Centre for Women’s and Children’s Health. Diabetes in pregnancy. Management of diabetes and its complications from preconception to the postnatal period. RCOG Press, London. 2008.
5. Lapolla A, Dalfra MG, Ragazzi E, De Cata AP, Fedele D, et al. New International Association of the Diabetes and Pregnancy Study Groups (IADPSG) recommendations for diagnosing gestational diabetes compared with former criteria: a retrospective study on pregnancy outcome. Diabet Med. 2011; 28: 1074-1077.
6. Feig DS, Hwee J, Shah BR, Booth GL, Bierman AS, Lipscombe LL. Trends in incidence of Diabetes in Pregnancy and serious perinatal outcomes. A large population based study in Ontario, Canada, 1986-2010. Diabetes Care. 2014; 37: 1590-1596.
7. Guariguata L, Linnenkamp U, Beagley J, Whiting D, Cho N. Global estimates of the prevalence of hyperglycaemia in pregnancy. Diabetes Res Clin Pract. 2014; 103: 176-85.
8. Goldenberg RL, McClure EM, Harrison MS., Miodovnik M. Diabetes during Pregnancy in Low-and Middle-Income Countries. Amer J Perinatol. 2016; 33: 1227-1235.
9. Group HSCR. Hyperglycemia and adverse pregnancy outcomes. N Engl J Med. 2008; 358: 1991–2002.
10. Bellamy L, Casas JP et al. Type 2 diabetes mellitus after gestational diabetes: a systematic review and meta-analysis. Lancet. 2009; 373: 1773-1779.
11. Waugh N, Royle P et al. Screening for hyperglycaemia in pregnancy: a rapid update for the National Screening Committee. Health Technol Assess. 2010; 14: 1-183.
12. Royal College of Obstetricians and Gynaecologists (RCOG). Scientific Advisory Committee. Opinion Paper 23. Diagnosis and treatment of gestational diabetes. RCOG Press, London, 2011.
13. The HAPO Study Cooperative Research Group. Hyperglycemia and adverse pregnancy outcomes. N Engl J Med. 2008; 358: 1991-2002.
14. The HAPO Study Cooperative Research Group. Hyperglycaemia and adverse pregnancy outcome (HAPO) study: associations with maternal body mass index. BJOG. 2010; 117: 575-684.
15. Landon MB, Spong CY, Thom E, Carpenter MW, Ramin SM, Casey B, et al. A multicenter, randomized trial of treatment for mild gestational diabetes. N Engl J Med. 2009; 361:1339-1348.
16. Durnwald CP, Mele L, Carpenter MW, Ramin SM, Varner MW, Rouse DJ, et al. Glycemic characteristics and neonatal outcomes of women treated for mild gestational diabetes. Obstet Gynecol. 2011; 117: 819-827.
17. Weinert LS. International Association of Diabetes and Pregnancy Study Groups Consensus Panel. International Association of Diabetes and Pregnancy Study Groups recommendations on the diagnosis and classification of hyperglycemia in pregnancy. Diabetes Care. 2010; 33: 676-682.
18. Sistema Nazionale Linee Guida. La gravidanza Fisiologica: Ministero della Salute, Istituto Superiore di Sanità e CeVEAS. Rome 2011. Available from http://www.salute.gov.it/imgs/C17pubblicazioni1436 allegato.pdf), Last accessed January 2020.
19. Diabetes in pregnancy: management from preconception to the postnatal period. NICE guideline 2015.
20. Berger H, Gagnon R, Sermer M. Guideline No. 393-Diabetes in Pregnancy. Journal of Obstetrics and Gynaecology Canada. 2019; 41: 1814-1825 e.
21. ACOG Practice Bulletin No. 190. Gestational Diabetes Mellitus. Obstetrics and Gynecology. 2018; 131: pp. e49-e64.
22. Ministry of Health. Birth attendance certificate. Ministerial Decree no. 349 of 16 July 2001.
23. Child Growth Standards. Birth to six months. Available at https://www.who.int/health-topics/child-growth. Last accessed 2.18.2022
24. Martin KE, Grivell RM, Yelland LN, Dodd J. The influence of maternal BMI and gestational diabetes on pregnancy outcome. Diabetes Res. Clin. Pract. 2015; 108: 508-513.
25. Sugiyama, T, Nagao, K, Metoki, H et al. Pregnancy outcomes of gestational diabetes mellitus according to pre-gestational BMI in a retrospective multi-institutional study in Japan. Endocr. J. 2014; 61: 373-380.
26. Capobianco G, Gulotta A, Tupponi G, et al. Materno-Fetal and Neonatal Complications of Diabetes in Pregnancy: A Retrospective Study. J. Clin. Med. 2020; 9: 2707.
27. Schmidt CB, Voorhorst I, van de Gaar VHW, et al. Diabetes distress is associated with adverse pregnancy outcomes in women with gestational diabetes: a prospective cohort study. BMC Pregnancy Childbirth. 2019; 19: 223.
28. Dalfra MG, Nicolucci A, Bisson T, Bonsembiante B, Lapolla A. Quality of life in pregnancy and post-partum: a study in diabetic patients. Qual Life Res. 2012; 21: 291-298.
29. Yogev Y, Xenakis EM, Langer O. The association between preeclampsia and the severity of gestational diabetes: the impact of glycemic control. Am J Obstet Gynecol. 2004; 191: 1655-1660.
30. Yogev, Chen, Hod, Coustan, Oats, McIntyre, et al. Hyperglycemia and Adverse Pregnancy Outcome (HAPO) study: preeclampsia. Am J Obstet Gynecol. 2010; 202: 255.e1-255.e7.
31. Mistry SK, Gupta RD, Alam S, Kaur K, Shamim AA, Puthussery S. Gestational diabetes mellitus (GDM) and adverse pregnancy outcome in South Asia: A systematic review. Endocrinol Diab Metab. 2021; 4: e00285.
32. Montoro MN, Kjos SL, Chandler M, Peters RK, Xiang AH, Buchanan TA. Insulin resistance and preeclampsia in gestational diabetes mellitus. Diabetes Care. 2005; 28:1995-2000.
33. Ness RB, Roberts JM. Heterogeneous causes constituting the single syndrome of preeclampsia: a hypothesis and its implications. Am J Obstet Gynecol. 1996; 175: 1365-1370.
34. Shindo R, Aoki S, Nakanishi S et al. Impact of gestational diabetes mellitus diagnosed during the third trimester on pregnancy outcomes: a case-control study. BMC Pregnancy and Childbirth. 2021; 246.
35. Committee on Practice Bulletins—Obstetrics. Practice Bulletin No. 180: Gestational Diabetes Mellitus. Obstet. Gynecol. 2017; 130: e17-e37.
36. Kwik M, Seeho SK, Smith C, McElduff A, Morris JM. Outcomes of pregnancies affected by impaired glucose tolerance. Diabetes Res Clin Pract. 2007; 77: 263-268.
37. 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.
38. Crowther CA, Hiller JE, Moss JR, McPhee AJ, Jeffries WS, Robinson JS. Effect of treatment of gestational diabetes mellitus on pregnancy outcomes. N Engl J Med. 2005; 352: 2477-2486.
39. Hod M, Merlob P, Friedman S, Schoenfeld A, Ovadia J. Gestational diabetes mellitus. A survey of perinatal complications in the 1980s. Diabetes. 1991; 40:74-78.
40. Sandmire HF, O Halloin TJ. Shoulder dystocia: its incidence and associated risk factors. Int J Gynaecol Obstet. 1988; 26: 65-73.
41. Nesbitt TS, Gilbert WM, Herrchen B. Shoulder dystocia and associated risk factors with macrosomic infants born in California. Am J Obstet Gynecol. 1998; 179: 476-480.
42. Fonseca A, Lopes J, Clode N. Glucose intolerance in the third trimester is not predictive of adverse outcomes. Int J Gynaecol Obstet. 2019; 147: 108-114.
43. Garne, E, Loane M, Dolk, H, Calzolari E, Matias Dias C, Doray B, et al. Spectrum of congenital anomalies in pregnancies with pregestational Birth Defects Res. Part A Clin. Mol. Teratol. 2012; 94: 134-140.
44. Agha M.M, Glazier RH, Moineddin R, Booth G. Congenital abnormalities in newborns of women with prgestational diabetes: A time-trend analysis, 1994 to 2009. Birth Defects Res. 2016; 106: 831-839.
45. Parimi M, Nitsch DA. Systematic Review and Meta-Analysis of Diabetes during Pregnancy and Congenital Genitourinary Abnormalities. Kidney Int. Rep. 2020; 5: 678-693.
46. Wang T, Li L, Wu C, Cao R, Li Q, Yu L, et al. Body Mass Index and Gestational Weight Gain Are Associated with Maternal and Neonatal Outcomes Based on Chinese Women. J Diabetes Res. 2021; 2021: 4542367.
47. Kouhkan A, Najafi L, Malek M, Khamseh ME, Khajavi A, Hosseini R, et al. Gestational diabetes mellitus: Major risk factors and pregnancy-related outcomes: A cohort study. Int J Reprod Biomed. 2021; 19:827-836.
48. Castaneda C, Marsden K, Maxwell T, Kenne KA, Kuwaye D, Jackson JB, et al. Prevalence of maternal obesity at delivery and association with maternal and neonatal outcomes. J Matern Fetal Neonatal Med. 2021; 12:1-8.