Gestational diabetes mellitus per different diagnostic criteria, risk factors, obstetric outcomes and postpartum glycemia: A prospective study in Ghana

The surge in gestational diabetes mellitus (GDM) globally requires a health system tailored approach towards prevention, detection and management. We estimated the prevalence of GDM using diverse recommended tests and diagnostic thresholds, and also assessed the risk factors and obstetric outcomes, including postpartum glycemia. Using a prospective cohort design, 446 singleton pregnant women without pre-existing diabetes did GDM tests in five hospitals in Ghana from 20–34 weeks using fasting plasma glucose (FPG), one-hour and 2-h oral glucose tolerance test (OGTT). Birth outcomes of 403 were assessed. GDM was diagnosed using six international diagnostic criteria. At 12 weeks postpartum, impaired fasting glucose (6.1–6.9 mmol/L) and diabetes (FPG ≥7.0 mmol/L) were measured for 100 women. Per FPG and 2-h OGTT cut-offs, GDM prevalence ranged between 8.3–23.8% and 4.4–14.3%, respectively. Risk factors included overweight (OR = 2.13, 95% CI: 1.13–4.03), previous miscarriage (OR = 4.01, 95% CI: 1.09–14.76) and high caloric intake (OR = 2.91, 95% CI: 1.05–8.07). Perineal tear (RR = 2.91, 95% CI: 1.08–5.57) and birth asphyxia (RR = 3.24, 95% CI: 1.01–10.45) were the associated perinatal outcomes. At 12 weeks postpartum, 15% had impaired fasting glucose, and 5% had diabetes. Tackling modifiable risk factors is crucial for prevention. Glycemic monitoring needs to be integral in postpartum and well-child reviews. This observational study was conducted as a prospective longitudinal study and reported in line with the STROBE (strengthening the reporting of observational studies in epidemiology) statement for cohort studies. In Ghana, universal testing of all pregnant women using the ‘one-step’ screening approach is the current guideline for GDM detection [22]. The blue shaded area in Figure 2 illustrates the recommended screening and testing modalities. Essentially, at every ANC visit, urine glucose of all pregnant women is checked. If the urine glucose is 1+/2+ on two occasions or 3+/4+ on any single visit, 2-h OGTT is performed. Between 24–32 gestational weeks, all pregnant women should perform both fasting blood glucose and 2-h OGTT. When the fasting blood glucose is 6.1–7.0 mmol/L or the 2-h OGTT >8.5 mmol/L, GDM is diagnosed. Diet and exercise therapy, which is the first-line management strategy, is initiated, but where glycemic control is unsatisfactory, insulin is administered. Recommended standard of care for GDM detection in Ghana vis-à-vis the actual clinical practice. Note: Author designed. ANC, antenatal care clinic; 2-h OGTT, two-hour oral glucose tolerance test; GDM, gestational diabetes mellitus; CHPS, Community Health-Based Planning Services. Although the use of oral anti-diabetic medications is contraindicated during pregnancy in Ghana [22], some clinicians administer metformin as a monotherapy or in combination with insulin based on evidence that metformin significantly lowers post-prandial blood glucose than insulin [23]. However, the guideline is silent on the exact glycemic values at which administration of hypoglycemic agent is utterly necessary in situations where diet therapy does not lead to satisfactory glycemic control. Regarding actual clinical implementation, there exist discrepancies at the various levels of healthcare. The screening and management practice in primary, secondary, and tertiary levels of care is shown in the orange shaded area in Figure 2. Despite the national target of 85% pregnant women receiving at least four ANC visits, in 2016, only 72% achieved this target in the study region. ANC booking in the first trimester and skilled delivery were approximately 45% [24]. The study sites have been described elsewhere [25]. Participants were recruited in the first trimester of pregnancy and the cohort followed-up until 12 weeks postpartum. In line with ANC delivery in Ghana, participants were proportionately allocated to one clinic, three municipal hospitals and one teaching hospital representing primary, secondary and tertiary levels of care respectively, which serve rural and urban communities in the Volta Region, Ghana. The sample size of 416 was determined using GDM prevalence of 9.3% [21], a population of 516,461 women in their reproductive age in the region, a 95% confidence level corresponding to 1.96 Z-score, a 5% error margin and a design effect of 3.2 accounting for variability in the different levels of ANC [25]. Based on 43.7% access to a skilled attendant at birth in Ghana [24], the sample size was increased to 800 to account for any attrition. Singleton pregnant women without pre-existing diabetes who registered for ANC in the first trimester of pregnancy were eligible. At ANC booking, random blood glucose and glycated hemoglobin (HbA1c) were checked. Participants whose random blood glucose values (≥11.1 mmol/L) and HbA1c (≥6.5%, 7.8 mmol/L) were suggestive of pre-existing diabetes were excluded (n = 10). Women who did not intend to deliver in any of the study facilities were also excluded. All women (n = 3093) who registered for ANC in the first trimester in the five study facilities from June 2016 to April 2017 constituted the sampling frame. Eligible participants were consecutively selected until the required sample size was obtained. Overall, 807 participants were booked for GDM testing, of which 490 reported but about 5% (n = 44) arrived in a non-fasting state and were thus excluded. Reasons for dropout from the study are shown in Figure 3. Overall, 446 performed the diagnostic tests, 403 were traced at delivery and 100 were followed-up at 12 weeks postpartum. Number of participants followed-up at each stage of the study. Note: n, number of participants; GDM, gestational diabetes mellitus; CS, cesarean section; LGA, large-for-gestational-age. At the first ANC booking, which was typically before the 16th week of gestation, we conducted one-on-one interviews to obtain data on socio-demographic variables. We measured body weight, height and mid-upper arm circumference (MUAC) following standard procedures and derived the body mass index (BMI) from the anthropometric indices. We extracted information from the maternal health record booklet on participants’ obstetric (gravida, parity, previous macrosomic births, cesarean section [CS], miscarriages, perinatal and neonatal deaths) and medical histories (first-degree relations with diabetes and/or hypertension). We assessed habitual dietary patterns using a food frequency questionnaire (FFQ). The FFQ had a frequency of consumption categories ranging from daily, weekly, fortnightly, monthly, rarely to never. Designed a priori based on frequently consumed foods in Ghana, the FFQ provided qualitative data on food intake, including snacks and beverages. To minimize recall biases, we checked the plausibility of the reported dietary intakes by collecting a non-quantitative 24-h recall data. Daily consumption of any carbohydrate-dense foods that contributed over 70% of the glycemic index (GI) value was assigned a score of one. Based on the cumulative scores, daily intake of five or more foods that contributed over 70% GI value was rated as high caloric intake; daily intake of three to four high GI value foods was considered to be moderate caloric intake, and daily consumption of two or less high GI value foods was considered to be low caloric intake. During the monthly ANC visits, we took blood pressure, gestational weight gain and urine glucose/protein measurements. MUAC was measured once in each trimester and the cut-off determined using the population median value. Per recommendations from the Institute of Medicine on ideal pregnancy weight gain, a woman was considered to be at high risk for GDM if her body weight for gestational age was above the threshold for her BMI group. The BMI groups and the corresponding pregnancy weight gain categories are underweight (<18.5 kg/m2), 12.5–18.0 kg; normal weight (18.5–24.9 kg/m2), 11.5–16.0 kg; overweight (25.0–29.9 kg/m2), 7.0–11.5 kg; and obese (≥30 kg/m2), 5.0–9.0 kg. Testing was scheduled between 20–28 gestational weeks using the one-step universal screening approach. Participants who were unable to report at the designated period were rescheduled between 30–34 weeks (n = 178, 36.3%). After 12 h overnight fast, pre-prandial venous blood was drawn from the antecubital fossa to measure the fasting venous plasma glucose (FPG) and lipid profile (total cholesterol, triglycerides; high, low and very-low-density lipoproteins). Thereafter, participants were given 75-g anhydrous glucose dissolved in 300 mL of water at ambient temperature to drink under direct observation. One milliliter blood was collected at one and two hours postprandial following standard operating procedures. Laboratory analysis was done on the fully automated Selectra ProM (Elitech Group, Puteaux, France) clinical chemistry analyzer operating on the kinetic enzymatic peroxidase-antiperoxidase principle. We estimated the prevalence of GDM by applying some major thresholds for GDM diagnosis based on fasting plasma glucose, 1-h and 2-h OGTT values. We followed the criteria of the IADPSG [3] officially adopted by the World Health Organization [19], the International Federation of Gynecology and Obstetrics [8] and the American Diabetes Association [5], as well as cut-offs by the National Institute for Health and Care Excellence [26], the Canadian Diabetes Association [27], the American Congress of Obstetricians and Gynecologists [28] and the protocol employed in Ghana [22]. Since one abnormal value is sufficient to make a diagnosis [3,19], participants without the full GDM test results were included in the analysis and reporting. As this study design was observational, all GDM cases received the usual routine care. The primary outcome was GDM. At peripartum, obstetric outcomes assessed included CS, perineal tear, postpartum hemorrhage (defined as estimated blood loss above 500 mL), newborn adiposity and survival. We estimated adiposity using three indicators: (1) macrosomia defined as birth weight ≥4 kg regardless of gestational age at birth; (2) large-for-gestational-age (LGA) defined as birth weight >90th percentile per the InterGrowth study standards accounting for gestational age at birth and sex of the newborn; and (3) Ponderal Index (PI) calculated as the birth weight (g)/length (cm3) × 100. PI was classified as small-for-gestational-age (<2.0), marginal (2.0–2.5), normal (2.5–3.0.) and large-for-gestational-age (≥3.0). Survival of the newborn was assessed using four indicators: (1) Apgar score at one and five minutes; (2) resuscitation, (3) admission to neonatal intensive care unit (NICU) and (4) perinatal death. Secondary outcomes were gestational age at birth and random glucose of the newborn determined from the capillary blood collected at the heel between one to two hours after birth. At 12 weeks postpartum, we measured FPG of the GDM cases to diagnose impaired fasting glucose (6.1–6.9 mmol/L), and diabetes (FPG ≥7.0 mmol/L) using the International Federation of Gynecology and Obstetrics’ diagnostic criteria for non-pregnant women [8,29]. Descriptive analysis was conducted using unpaired t-test and Chi-square test. Differences between the GDM present or absent groups was tested using a dichotomous outcome tabulated in a two-by-two table with the dichotomous input variables. Inferential analysis was conducted using unconditional logistic regression to generate crude estimates of association. Variables that had theoretical evidence of association with GDM or recorded p < 0.10 in the crude estimates were included in the adjusted model. To control for confounding variables, multivariate binary logistic regression was modeled and the adjusted odds ratios (aOR) obtained through the Cochran -Mantel-Haenszel statistic. We conducted a simple linear regression to estimate the coefficient of a unit rise in blood glucose on individual pregnancy outcomes assessed. A correlation matrix was computed to identify collinearity and possible confounders, in addition to interaction terms considered in the final model selection. Adjusting for confounding variables in a multivariate analysis, binary logistic regression model was run to estimate the relative risk for an adverse obstetric outcome. Missing values were deleted pairwise. As multiple birth outcomes were tested simultaneously, the effect of multiple comparisons was adjusted for using the Bonferroni correction. A corrected p < 0.05 (two-sided) and confidence intervals (CI) excluding one were considered to be associated with the outcome measures. Analysis was done in Stata software (version 14.2). The Ghana Health Service Ethics Review Committee (GHS-ERC-GM 04/02/16) and the Institutional Review Board of Heidelberg University Medical Faculty (S-042/2016) approved the study. We obtained written informed consent from all study participants, including participants below 18 years who were ethically regarded as emancipated adults.