Research on gestational diabetes mellitus (GDM) dates back to 1882 [1
]. However, the Hyperglycemia and Adverse Pregnancy Outcomes (HAPO) study conducted at 15 centers in nine countries to assess the association between varying degrees of maternal glucose and adverse outcomes [2
] sparked interest in GDM research and its clinical practice. It formed the foundation for the diagnostic criteria currently recommended by the International Association of Diabetes and Pregnancy Study Group (IADPSG) [3
]. GDM accounts for 86.4% of all cases of hyperglycemia in pregnancy [4
]. According to the HAPO study, 18–26% of pregnancies are affected by GDM [2
], but globally, prevalence is estimated to be between 1–14% [5
]. In sub-Saharan Africa, there has been an upward trajectory in prevalence between 2015 [6
] and 2019 (8.5%) [7
Attributed to the rising prevalence are modifiable and non-modifiable risk factors [2
] driven primarily by the demographic, epidemiological, nutrition, obstetric and technological transitions. GDM is linked to adverse maternal and fetal outcomes [2
] as well as long-term cardiometabolic complications [8
]. It is argued that the use of different screening algorithms and lower diagnostic criteria may increase the rates, thereby masking the true prevalence [13
]; generating concerns of overdiagnosis [14
] and unnecessary medicalization of pregnancy [17
]. Overdiagnosis could complicate treatment outcomes [13
], cause emotional, physical and financial distress to women diagnosed, increase care providers’ workload as well as healthcare expenditure [19
Despite the widened interest in GDM research, studies from low-income settings are sparse and generally narrowed to prevalence and risk factors (Figure 1
). Adverse pregnancy outcomes are not well established in these settings, and often, retrospective data from tertiary hospitals are used which do not reflect population-based prevalence. Additionally, there is little focus on diet and pharmacological treatment, obstetric outcomes and future health impacts. Meanwhile, because these health systems are traditionally designed to cater for infectious diseases, their readiness towards managing the surge is weak. Further, many studies fail to indicate the diagnostic approach used (be it universal ‘one-step’ versus selective ‘two-step screening), and the resulting prevalence according to the ‘gold standard’ 2-h oral glucose tolerance test (OGTT) and fasting plasma glucose (FPG) tests.
In Ghana, GDM prevalence per 2-h OGTT ≥8.5 mmol/L (153 mg/dL) is 9.3% [21
]. Given that this study was conducted in the largest referral hospital, where 92.5% of the study participants are urban dwellers, findings might not reflect the general population where lower prevalence is expected. Estimating the prevalence per different diagnostic tests and cut-offs and identifying the obstetric outcomes could enhance screening, diagnosis and management modalities. This is especially important at primary and secondary levels of antenatal care (ANC) where specialist care and essential medical supplies are often lacking. Therefore, this study aimed to (1) estimate the prevalence of GDM in lower-level facilities using some common diagnostic cut-offs; (2) assess the risk factors; (3) influence of GDM on perinatal outcomes and (4) maternal glycemic status at 12 weeks postpartum.
Depending on the test tool and diagnostic criteria, 4–24% had at least one abnormal blood glucose value. Findings reaffirmed some established risk factors for GDM, such as advanced maternal age and obesity. Meanwhile, it revealed some emerging risks such as partner’s level of education, ANC in primary facilities and intake of high glycemic index foods. Perineal trauma and birth asphyxia were key obstetric outcomes. At 12 weeks postpartum, a fifth of the GDM cases remained hyperglycemic, of which 5% was suggestive of diabetes.
Although the majority of GDM cases occur in low- and middle-income countries, the prevalence in Africa is relatively lower (9.5%) [4
] as seen in Ghana (9.3%) [21
], South African (9.1%) [30
] and Nigeria (8.6%) [31
]. Yet, isolated higher rates have been reported in Tanzania (19.5%) [32
], South Africa (25.8%) [33
] and Morocco (23.7%) [34
]. However, the use of diverse diagnostic tests and screening algorithms coupled with differences in study populations and healthcare settings pose a challenge in comparing rates, exposures, treatment effects, pregnancy outcomes and harmonizing clinical practice [13
]. Another difficulty is that many of these studies do not indicate whether the reported prevalence is derived from FPG or 2-h OGTT, which are slightly variant [2
]. In Tanzania, a considerable variation (14%) was found between GDM prevalence per FPG (18.3%) and 2-h OGTT (4.3%) using the IADPSG criteria [32
]. Interestingly, we found a similar variation in our study (≈14.0%). In fact, from the dietary data collected, the frequency of consumption of sugar-sweetened foods (35.7%) and beverages (21.1%) during both day and night, was relatively high. Therefore, we suspect that sub-optimum adherence to test preparations, particularly the overnight fast, could account for the high prevalence from FPG test, but this is inconclusive and needs further investigation. It also affirms the importance of nutrition education in all health promotion interventions. The lowering of GDM diagnostic thresholds has generated concerns of over-diagnosing [14
], unnecessary medical interventions during pregnancy [17
] and the associated emotional stress to the woman [35
]. It is envisaged that lower-level health systems in many developing countries will be unable to manage the high number of diagnosed cases. Recommendations by the WHO for health systems to contextualize the diagnostic criteria by the IADPSG to suit the needs of individual healthcare settings [19
] is worth considering.
For instance, in Ghana, a higher threshold for fasting blood glucose (above 6.0 mmol/L) is used to diagnose GDM [22
]. A study in Ghana found that fasting plasma glucose ≥5.6 mmol/L yielded an optimized and clinically relevant sensitivity (80%) and specificity (74%) using the IADPSG/WHO threshold for 2-h OGTT as the gold standard [25
]. Furthermore, the positive predictive value was higher (35.6%) when compared to ≥5.1 mmol/L cut-off (25.2%) [25
]. Women with GDM tend to have macrosomic babies, thus requiring CS [2
] but vaginal delivery of macrosomic babies prolongs labor, traumatizes the perineum and asphyxiates the newborn [2
]. However, we found a few variations in the birth outcomes depending on the test and diagnostic criteria. In comparing the groups of GDM confirmed by different criteria, 2-h OGTT ≥8.5 mmol/L was associated with large-for-gestational-age while fasting plasma glucose ≥6.1 mmol/L was associated with birth asphyxia. The physiologic interactions between fasting glucose and 2-h OGTT during pregnancy should be further explored. A stricter diagnostic threshold could be used as is done in many centers in India where 2-h OGTT is done irrespective of the women’s fasting state and GDM diagnosed if 2-h OGTT value is ≥7.8 mmol/L [36
We found a higher risk among primary facility users. Rural dwellers in Ghana often receive ANC in primary facilities where emergency obstetric and newborn care services are limited while medical specialists are not within reach. Meanwhile, rural dwellers experience more multiparity, poverty and illiteracy [37
]. The implications are longer reproductive years, more unwanted pregnancies and poor health-seeking behaviors [38
]. Improving access to basic healthcare amenities for GDM screening and management in rural facilities and sensitizing the need for optimum ANC seeking behaviors is crucial. Additionally, there is a need to ensure effective monitoring, surveillance and implementation of the GDM policy in developing countries. Rather than adopt guidelines that might pose challenges to already fragile healthcare systems, it should be adapted reference to contextual circumstances.
Intake of high glycemic index foods such as roots, tubers, plantain, rice, bread, pasta and sugar-sweetened beverages, associated with high GDM risk, is typical in Ghana, [39
] contributing to the obesity epidemic. Socio-culturally acceptable lifestyle interventions focused on diet and weight control are crucial [8
]. Firstline medical nutrition therapy could be a feasible option for many primary healthcare systems since pharmacotherapy is provided only at a higher level of healthcare. Having observed a lower risk for GDM among women whose partners have attained higher levels of formal education goes to emphasize the importance of male involvement in maternal healthcare. Males are decision-makers and financiers of many indigenous households and when involved, tend to support the women in making healthy decisions [38
4.1. Strengths and Limitations of This Study
In determining participants’ body mass index, first-trimester weight was used instead of pre-pregnancy weight and was complemented by mid-upper arm circumference measurement, a reliable indicator for assessing adiposity when pregnancy is advanced. Although we validated the plausibility of dietary data obtained from the food frequency questionnaire with a 24-h recall, we did not exclude any participant based on non-plausible self-reported dietary intake. A third of the pregnant women booked for GDM testing failed to attend the appointment, but that did not affect our estimates as we accounted for 50% attrition rate in the design. However, only 29% of the GDM cases could be traced at 12 weeks postpartum. Although a very low turnout, it is not entirely surprising as in many developing countries, coverage for postnatal care tends to be relatively poor compared with other maternal and child health services. Attrition bias is a major challenge in cohort studies. Where the follow-up rate is below the acceptable thresholds (60–80%), it can threaten the validity of the results. In typical social settings similar to where our study was conducted, possible reasons that could account for the low postpartum turnout are maternal feeling of being out of danger after childbirth, being occupied with newborn care, difficulty adjusting to the new caregiver role and moving in to stay with relations who are capable of supporting with the newborn’s care. It is possible that participants who did not return for testing are significantly different from those who reported. Since not all the women scheduled for the follow-up assessments returned, the findings should be interpreted only in the context of this study and not extrapolated to the entire population. In lieu of random allocation to the different GDM test, each pregnant woman had the opportunity to do all the recommended tests. Hence, any within-individual differences are likely to be random deviations which seldom affects the true results. Although not an intervention study, we had an intention to treat yet we did not obtain data on the form of treatment administered or its effectiveness on reducing basal or prandial insulin sensitivity. Women who had abnormal glycemic results were simply referred to their obstetricians meaning that where GDM was present, it was not managed according to a unified study protocol primarily as treatment was not an objective of the study. We are therefore oblivious of the kind of therapeutic support each diagnosed woman received, the glycemic control achieved and the consequent effect of management on pregnancy outcome and postpartum glycemia.
4.2. Implications for Clinical and Public Health Practice
Considering that the disease burden varied widely (a 20% range) according to the type of test and diagnostic criteria used and health systems vary in the package of services they are capable of providing, the choice to use one screening procedure or diagnostic criteria over another should be established in relation to a country’s health infrastructure, health policies and services. As health systems in many low- and middle-income settings are traditionally designed to treat infections, strategies for non-communicable diseases, including GDM, are limited. We support universal testing, but depending on the health setting, lower thresholds could be used for GDM classification. Strengthening GDM detection at primary healthcare levels, where basic amenities for screening are often lacking, is vital. The use of stricter diagnostic cut-offs might favor low-income contexts where health financing and access to essential drugs and other health interventions are challenging. Nonetheless, pregnancy complicated by diabetes should be considered as an opportunity to improve metabolic and cardiovascular risk besides changing unhealthy lifestyles. Health promotion interventions that tackle modifiable risk factors such as poor dietary habits and obesity are paramount. A coordinated transition of care after regular postpartum care ceases, and the integration of post-delivery glycemic monitoring into routine health care services will facilitate the detection of persistently hyperglycemic cases after delivery.