Hyperglycemia in pregnancy diagnosed using glycated hemoglobin (HbA_1c) in Uganda: a preliminary cross-sectional report

Abstract

Background: Hyperglycemia in pregnancy (HIP) is a common medical complication during pregnancy and is associated with several short and long-term maternal-fetal consequences. We aimed to determine the prevalence and factors associated with HIP among Ugandan women.

Methods: We consecutively enrolled eligible pregnant women attending antenatal care at Kawempe National Referral Hospital, Kampala, Uganda in September 2020. Mothers known to be living with diabetes mellitus or haemoglobinopathies and those with anemia (hemoglobin <11g/dl) were excluded. Random blood sugar (RBS) and glycated hemoglobin A1c (HbA_1c) were measured on peripheral venous blood samples. HIP was defined as an HbA1c ≥5.7% with its subsets of diabetes in pregnancy (DIP) and prediabetes defined as HbA1c_1c of ≥6.5% and 5.7–6.4% respectively. ROC curve analysis was performed to determine the optimum cutoff of RBS to screen for HIP.

Results: A total of 224 mothers with a mean (±SD) age 26±5 years were enrolled, most of whom were in the 2^nd or 3^rd trimester (94.6%, n=212) with a mean gestation age of 26.6±7.3 weeks. Prevalence of HIP was 11.2% (n=25) (95% CI: 7.7–16.0). Among the mothers with HIP, 2.2% (n=5) had DIP and 8.9% (n=20) prediabetes. Patients with HIP were older (28 years vs. 26 years, p=0.027), had previous tuberculosis (TB) contact (24% vs. 6.5%, p=0.003) and had a bigger hip circumference (107.8 (±10.4) vs. 103.3 (±9.7) cm, p=0.032). However only previous TB contact was predictive of HIP (odds ratio: 4.4, 95% CI: 1.2–14.0; p=0.022). Using HbA_1c as a reference variable, we derived an optimum RBS cutoff of 4.75 mmol/L as predictive of HIP with a sensitivity and specificity of 90.7% and 56.4% (area under the curve=0.75 (95% CI: 0.70–0.80, p<0.001)), respectively.

Conclusions: HIP is common among young Ugandan women, the majority of whom are without identifiable risk factors.

Citation

Bongomin, F., Kyazze, A.P., Ninsiima, S., Olum, R., Nattabi, G., Nabakka, W., Kukunda, R., Batte, C., Ssekamatte, P., Baruch Baluku, J., Kibirige, D., Cose, S. and Andia-Biraro, I. (2023), "Hyperglycemia in pregnancy diagnosed using glycated hemoglobin (HbA_1c) in Uganda: a preliminary cross-sectional report", Emerald Open Research, Vol. 1 No. 2. https://doi.org/10.1108/EOR-02-2023-0019

Introduction

Pregnancy is naturally characterized by insulin resistance and hyperinsulinemia leading to hyperglycemia, the most common endocrinopathy during the gestation period (Farrar, 2016; Saravanan et al., 2020). Previously, any hyperglycemia detected in pregnancy was termed gestational diabetes (GDM) (World Health Organization, 2013). However, recently, the term hyperglycemia in pregnancy (HIP) has been proposed by the World Health Organization (WHO) (Diabetes Canada Clinical Practice Guidelines Expert Committee et al., 2018; World Health Organization, 2018). HIP classifies hyperglycemia based on both onset and severity (Diabetes Canada Clinical Practice Guidelines Expert Committee et al., 2018; World Health Organization, 2018). It includes the more severe manifestations of total diabetes in pregnancy (comprising of known and previously undiagnosed diabetes in pregnancy; DIP), which may persist in the post-partum period and a more benign form, GDM (World Health Organization, 2013). DIP and GDM are together termed hyperglycemia first detected in pregnancy (World Health Organization, 2013).

HIP is a growing public health concern and adversely affects maternal and child health, and is likely to contribute to the growing global diabetes epidemic (Bianco and Josefson 2019; Guariguata et al., 2014). Depending on the diagnostic criteria used and the population of pregnant women studied, the resulting prevalence of HIP can vary widely. Results from a recent survey on HIP prevalence in 173 countries found country-specific prevalence estimates ranging from <1% in Germany up to 28% for a study in Nepal, using a variety of criteria (Jiwani et al., 2012). Globally, HIP has been estimated to affect nearly 16.9%, or 21.4 million, live births among women of reproductive age, with total diabetes in pregnancy accounting for an estimated 16.0% of these cases (Guariguata et al., 2014). In this report, more than 90% of cases of HIP were estimated to occur in low- and middle-income countries (LMICs), with South-East Asian and African regions having the highest number of live births affected with HIP at over 6.0 (23.2%) and 4.3 (16.0%) million cases, respectively (Guariguata et al., 2014).

Previous studies assessing the prevalence of HIP have mostly concentrated on high risk mothers, such as those with advanced age, high gravidity or in a specific period of gestation age, which may not reflect the true prevalence in the general population of pregnant women (Adefisan et al., 2020; Cosson et al., 2019; Mukuve et al., 2020). Moreover, screening and intervention on HIP during antenatal care (ANC) are not routine in most LMICs, making an accurate estimation of the burden of this treatable condition largely impossible. This could be due to the several caveats associated with current tests, which requires overnight fasts, multiple clinic visits and the oral glucose tolerance test (OGTT) which is labor intensive.

Despite the serious public health implications of HIP, there has been no universal definition and no universal standards for screening and diagnosis, and a wide variety of methods are applied (Guariguata et al., 2014). However, fasting plasma glucose (FPG), 1-hour, 2-hour or 3-hour plasma glucose following a 75g OGTT, interpreted according to the American Diabetes Association (ADA), WHO or the International Association of the Diabetes and Pregnancy Study Group (IADPSG) criteria are the most commonly used methods (Guariguata et al., 2014; Meek et al., 2020). Glycated hemoglobin (HbA_1c) can also be used to screen for and diagnose HIP, especially in early pregnancy (Goyal et al., 2020). Trimester specific cutoff values for HbA_1c have recently been proposed (Sánchez-González et al., 2018), though not widely validated or adopted by international guidelines (Sánchez-González et al., 2018).

The aim of this study was to determine the prevalence of HIP and its associated risk factors among pregnant women attending ANC in Uganda, irrespective of their gestation age, using HbA_1c. Secondarily, we sought to determine an appropriate random blood sugar (RBS) cutoff value for screening for HIP in our setting.

Methods

Study design and setting

We conducted a cross-sectional study in a large specialized obstetrics and gynecology national referral hospital in Kampala, Uganda in September 2020.

This study enrolled pregnant women attending the ANC clinic at the directorate of Obstetrics and Gynecology at Kawempe National Referral Hospital (KNRH), which also serves as the academic teaching hospital for Makerere University College of Health Sciences. KNRH was purposively selected due to its central location attracting a large number of patients from Kampala and its surrounding districts, thus representing the demographics of both urban and peri-urban patient populations. On average, about 50-60 mothers attend the ANC clinic at KNRH from Tuesday to Thursday every week.

Study population

Eligible participants were all pregnant women attending ANC (regardless of gestation age) during the study period who provided informed consent to participate in the study. Pregnant women known to be living with diabetes or haemoglobinopathies were excluded. In addition, patients with anemia (hemoglobin <11g/dl) were excluded at analysis.

Sample size and sampling procedure

With an estimated prevalence of HIP at 15.6% in Uganda (Kiiza et al., 2020), using the formula for the determination of sample size for prevalence studies (Kish-Leslie) (Kish, 1965), with an assumed non-response rate of 10%, precision of 5%, and a Z-score of 1.96 at 95% confidence interval, a sample size of 217 was anticipated. Eligible participants were identified, and consecutively sampled with the assistance of a senior nurse at the ANC clinic and two other trained study nurses.

Data collection

Study clinicians administered a semi-structured study questionnaire through a face-to-face interview to collect information regarding risk factors and symptoms for HIP and maternal characteristics: age, gravidity, education level, occupation, marital status, HIV status, tuberculosis contact, gestation age, history of abortion, smoking and alcohol usage, and the number of ANC visits in the current pregnancy. Gestation age was estimated using the date of the last normal menstrual period. Polyuria, polydipsia, and polyphagia were considered classic symptoms of diabetes.

Diagnosis of hyperglycemia in pregnancy. All consenting mothers were subjected to a RBS and HbA_1c tests. RBS was performed at the point of care on venous blood samples using the On-Call^TM Plus Glucometer (ACON Biotech, China) according to manufacturer’s instruction. HbA_1C was estimated using Cobas® 6000 analyzer series (Roche Diagnostics) at the Central Diagnostic Laboratory Services (CDLS), Medical Research Council/Uganda Virus Research Institute and London School of Hygiene and Tropical Medicine Uganda Research Unit laboratory within 24 hours of sample collection. Prediabetes was defined as HbA_1c of 5.7% to 6.4% and overt diabetes (diabetes in pregnancy, DIP) as HbA_1c of 6.5% or higher, according to the American Diabetes Association (Goyal et al., 2020) and consistent with guidelines of the IADPSG (Meek et al., 2020; Saravanan et al., 2020), and the WHO classification of hyperglycemia first diagnosed in pregnancy (World Health Organization, 2018). Patients with HIP were referred for the appropriate clinical care according to the national guidelines.

Complete blood count. A complete blood count was performed using the HumaCount 5D Hematology System (Wiesbaden, Germany) using 3 mL of blood samples collected in EDTA tubes within 12 hours from the time of sample collection. Patients with hemoglobin concentration of 11g/dl or lower were regarded as having anemia according to the WHO definition (World Health Organization, 2011) of anemia in pregnancy and were subsequently excluded from the study at analysis. Anemic patients were also referred for appropriate management by the clinical team.

Anthropometrical assessment. Weight was measured with minimal clothing and without shoes using a digital bathroom weighing scale (SECA-Germany), placed on a flat surface and recorded to the nearest 0.1kg. Height was measured using a calibrated stadiometer. Waist and hip circumferences were measured using a tailor’s measuring tape to the nearest 0.1 cm. Body mass index and Waist-Hip Ratios were calculated accordingly. Brachial blood pressure was measured from both arms while mothers were sitting down with their feet flat on the ground using an automated machine with an appropriate adult cuff size. The average of the two measurements was considered as the participant’s blood pressure. Women were classified as hypertensive if systolic and diastolic blood pressure were ≥140mmHg and ≥90mmHg, respectively, and normal if blood pressure is less than 140/90mmHg.

Statistical analysis

Statistical analyses were performed using STATA version 16 (StataCorp LLC, College Station, TX, USA) and GraphPad Prism version 8.0.4 (GraphPad Software, La Jolla, CA, USA). The data were expressed as absolute numbers and percentages for categorical variables, and as means and standard deviations (mean ± SDs) for continuous variables. Shapiro-Wilk normality test was applied to evaluate all quantitative variables to select the appropriate test. Welch’s One-Way ANOVA was used to compare continuous data across groups. Chi-square or Fisher’ Exact tests were used to assess associations between HIP across demographic and clinical characteristics of participants. Variables with a p value <0.2 were fitted into a multivariable logistic regression model to adjust for confounders. Receiver operating characteristics (ROC) curve analysis was performed to determine the optimum cutoff of RBS in those patients who met criteria for HIP in relation to HbA_1c test. Area under the ROC curve (AUC) was shown with 95% Wilson confidence intervals (CI). Optimal diagnostic cut-off value for RBS were calculated using Youden’s J statistic (sensitivity+specificity-1). For this analysis, the hypothesis was that at the optimal RBS cut off, the AUC = 0.7. In all analyses, P<0.05 was considered significant at 95% CI.

Ethical considerations

This study was approved by the Makerere University School of Medicine Ethics and Research Committee (reference number #REC REF 2020-113). All mothers provided informed written consent to participate after the study procedure, risks and benefits were explained to them.

Results

In September 2020, a total of 267 pregnant women participated in the study. However, 43 participants were excluded due to either incomplete data or presence of anemia Figure 1).

Baseline characteristics of study participants

Of the 224 eligible participants, most were married (91.1%, n=204), and attending ANC for the first time in the current pregnancy (63.4%, n=142). Over three quarters had attended post-primary education (77.7%, n=174) and were businesswomen (42.2%, n=99). The mean age of the women was 26 years (SD± 5), of which 138 (61.6%) were ≥25 years old. Just over one-third of the participants were primigravida (34.8%, n=78), and the majority of the mothers were in their 2^nd or 3^rd trimester of pregnancy (94.6%, n=212), with a mean gestation age of 26.6 weeks (SD ± 7.3) Table 1). In total, 43 (19.2%) women had at least one of the classic symptoms of diabetes.

Prevalence of HIP

RBS and HbA_1c was performed for all the 224 participants. The median (range) RBS was 4.6 (2.8-8.0) mmol/l. The median (range) of HbA_1c was 5.2 (3.6-14.9).

The overall prevalence of HIP was 11.2% (n=25) (95% CI: 7.7-16.0); 2.2% (n=5) (95% CI: 1.0-5.1) had DIP, and 8.9% (n=20) (95% CI: 5.9-13.4) prediabetes using the WHO criteria. Patients with HIP were slightly older than those without (28 years vs. 26 years, p=0.027), had previous tuberculosis contact (24% vs. 6.5%, p=0.003), had a bigger hip circumference (107.8 (±10.4) vs. 103.3 (±9.7) cm, p = 0.032) and a higher proportion of urban dwellers had HIP compared to their rural counterparts (88% vs.69.8%), though this was not statistically significant (p=0.062) Table 2). However, after accounting for important confounders in a multivariable logistic regression models, none of these factors showed a statistically significant association Table 3).

The mean RBS was slightly higher in those with HIP compared to those with normal HbA_1c; however this was not to statistical significance Figure 2).

Using HbA_1c as a reference variable, ROC curve and the AUC for RBS as a predictor of HIP was 0.75 (95% CI: 0.70-0.80, p<0.001) Figure 3). We derived optimum cutoffs for RBS of 4.75 mmol/L with a sensitivity and specificity of 90.7% and 56.4%, respectively. At a lower RBS cutoff of 4.0 mmol/L, the sensitivity and specificity was 99.5% and 23.6%, respectively, and at a higher RBS cutoff of 5.5 mmol/L, the sensitivity and specificity was 26.9% and 83.5%, respectively.

Discussion

The use of HbA_1c for screening, diagnosis and monitoring of diabetes and prediabetes in pregnancy remains a work in progress with several unanswered questions (Hughes et al., 2016). In the present study, we aimed to determine the prevalence and factors associated with HIP using HbA_1c in Uganda. To our knowledge, this is the first study to report on the use of HbA_1c to screen for HIP in Uganda. In our study, the prevalence of HIP ranged between 7.5 and 16.0%. This is consistent with the estimated prevalence of HIP of 16% reported in the Africa region (Guariguata et al., 2014). In two previously published studies from Uganda, the prevalence of HIP was 15.6% using FPG criteria (Kiiza et al., 2020) and 31.9% using OGTT criteria (Nakabuye et al., 2017). The observed differences in the prevalence of HIP across these studies could be due to the difference in the diagnostic criteria used. It is well established that due to physiological changes in pregnancy, HbA_1c level decreases as gestation age increases (Kumpatla et al., 2013; Rafat and Ahmad, 2012; Schaible et al., 2018). This could explain the low prevalence observed in our study.

HIP is typically diagnosed between 24^th and 28^th weeks of gestation (World Health Organization, 2018). However, evidence from the metacentric landmark trial, hyperglycemia and adverse pregnancy outcome (HAPO) showed that continued exposure to hyperglycemia non-diagnostic for diabetes was associated with adverse maternal and fetal outcomes (Catalano et al., 2012; HAPO Study Cooperative Research Group et al., 2008). Based on this finding, current guidelines recommend early screening and appropriate management of HIP to improve maternal and fetal outcomes (World Health Organization, 2018). OGTT is generally considered the gold standard for screening for HIP (Coetzee et al., 2020). However, FPG and HbA_1c can also be used. HbA_1c has been shown to correlate with poor maternal-fetal outcomes (Ho et al., 2017). Studies to establish normal HbA_1c reference ranges in pregnancy are scarce. Among healthy non-diabetic pregnant women, a recent study from Mexico has shown that the upper limit of HbA_1c increases with gestation age (Sánchez-González et al., 2018). In this population, the cutoff for the diagnosis of HIP was nearly identical to the American Diabetes Association criteria for the diagnosis of diabetes and prediabetes in non-pregnant population and in early pregnancy. However, given the ease of HbA_1c compared to OGTT, testing may improve follow-up rates and combining HbA_1c analysis with FPG or waist circumference may improve detection rates (Hughes et al., 2016).

Risk factors for HIP include advancing age; obesity; excessive weight gain during pregnancy; a family history of diabetes; HIP during a previous pregnancy; a history of stillbirth or infant with congenital abnormality; and glycosuria during pregnancy significantly overlap with those of type 2 diabetes mellitus (Diabetes Canada Clinical Practice Guidelines Expert Committee et al., 2018; Farrar, 2016; Saravanan et al., 2020). In our study, the majority of the patients were young, and family history of diabetes was only elicited in 20% of the patients. This is consistent with published studies in Uganda and elsewhere that have reported that over one-third to half of mothers do not have known risk factors (Nakabuye et al., 2017; Thacker and Petkewicz, 2009). This has implications for the selection of patients for screening. RBS has been studied as a possible screening tool. It is interesting that none of the patients with DIP in our study had RBS above 11.1 mmol/L. In one study conducted in Nigeria, using OGTT as a reference standard, the best threshold for screening was 5.4 mmol/L for RBS, which had a sensitivity of 45% and a specificity of 90.0% (Adefisan et al., 2020). In our study, with a cutoff of 4.75 mmol/L, we found the reverse, a higher sensitivity (90.7%) and a lower specificity (56.4%). However, at a cutoff of 5.5 mmol/L, we found a similar diagnostic performance (sensitivity of 27% and specificity of 84%). Given the high sensitivity of RBS at a relatively lower RBS cutoff and the cost of performing HbA_1c especially in LMICs, RBS – a cheap and readily available modality – may be used alongside HbA_1c for screening for HIP in our setting.

Our study is not without limitations. Firstly, we had a small sample size derived from a single center and thus our findings may not be generalizable to the general population of pregnant women in Uganda. Secondly, there is no established HbA_1c reference ranges among Ugandan women stratified by gestation age. It is therefore likely that we may have missed some cases of HIP since we used HbA_1c cutoff for non-/early pregnancy population. However, we excluded anemic patients by performing hemoglobin estimation for all mothers. Lastly, being a pilot study, we were unable to retrieve key risk factors, such as pre-pregnancy weight, and birth weights and perinatal outcomes of previous pregnancies. However, over 60% of the mothers were primigravida. However, the strength of this study lies in its inclusiveness of pregnant mothers of different gestation ages from both urban and peri-urban communities. We report for the first time the feasibility of screening for HIP using HbA_1c in a resource limited setting and the utility of RBS as an adjunct to HBA_1c to aid in identifying of mothers who are likely to have HIP.

Conclusions

In conclusion, we found a slightly over 10% prevalence of HIP among Uganda women all ages of gestation. The majority of those diagnosed with HIP were young without identifiable risk factors for hyperglycemia. RBS and HbA_1c may be used complementarily to diagnose HIP in resource constrained settings. We recommend a larger, multicenter study using different diagnostic modalities to confirm of findings.

Data availability

Underlying data

Figshare: Hyperglycemia in pregnancy diagnosed using glycated hemoglobin (HbA1c) in Uganda: a preliminary cross-sectional report dataset, https://doi.org/10.6084/m9.figshare.13292690.v1 (Bongomin, 2020).

Data are available under the terms of the Creative Commons Zero "No rights reserved" data waiver (CC0 1.0 Public domain dedication).

Publisher’s note

This article was originally published on the Emerald Open Research platform hosted by F1000, under the Healthier Lives gateway.

The original DOI of the article was 10.35241/emeraldopenres.14014.1

Author roles

Bongomin F: Conceptualization, Data Curation, Formal Analysis, Funding Acquisition, Investigation, Methodology, Project Administration, Resources, Supervision, Validation, Visualization, Writing - Original Draft Preparation, Writing - Review & Editing; Kyazze AP: Investigation, Project Administration, Resources, Validation, Visualization, Writing - Original Draft Preparation, Writing - Review & Editing; Ninsiima S: Investigation, Project Administration, Validation, Visualization, Writing - Original Draft Preparation, Writing - Review & Editing; Olum R: Data Curation, Formal Analysis, Investigation, Methodology, Validation, Visualization, Writing - Original Draft Preparation, Writing - Review & Editing; Nattabi G: Methodology, Validation, Visualization, Writing - Original Draft Preparation, Writing - Review & Editing; Nabakka W: Investigation, Methodology, Validation, Visualization, Writing - Original Draft Preparation, Writing - Review & Editing; Kukunda R: Investigation, Methodology, Validation, Visualization, Writing - Original Draft Preparation, Writing - Review & Editing; Batte C: Funding Acquisition, Project Administration, Validation, Visualization, Writing - Original Draft Preparation, Writing - Review & Editing; Ssekamatte P: Investigation, Methodology, Validation, Visualization, Writing - Original Draft Preparation, Writing - Review & Editing; Baruch Baluku J: Conceptualization, Investigation, Methodology, Supervision, Validation, Visualization, Writing - Original Draft Preparation, Writing - Review & Editing; Kibirige D: Investigation, Methodology, Project Administration, Validation, Visualization, Writing - Original Draft Preparation, Writing - Review & Editing; Cose S: Funding Acquisition, Validation, Visualization, Writing - Original Draft Preparation, Writing - Review & Editing; Andia-Biraro I: Conceptualization, Data Curation, Formal Analysis, Funding Acquisition, Investigation, Methodology, Project Administration, Resources, Supervision, Validation, Visualization, Writing - Original Draft Preparation, Writing - Review & Editing

Grant information:

Research reported in this publication was supported by the Forgarty International Centre of the National Institutes of Health under Award Number D43 TW0011401. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health. Also, this work was partially supported by the African Career Accelerator Award grant held by Dr. Irene Andia-Biraro, which is funded by the CRICK African Network and is hosted at the MRC/UVRI & LSHTM Uganda Research Unit in Entebbe, Uganda.

The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

Competing interests

No competing interests were disclosed.

Reviewer response for version 1

Ankia Coetzee, Division of Endocrinology, Stellenbosch University and Tygerberg Hospital, Stellenbosch, South Africa

Competing interests: No competing interests were disclosed.

This review was published on 07 June 2021.

This is an open access peer review report distributed under the terms of the Creative Commons Attribution Licence, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

recommendation approve

Thanks for the invitation to review the article entitled Hyperglycemia in pregnancy diagnosed using glycated hemoglobin in Uganda: a preliminary cross-sectional report.

The title is representative of the study and the abstract satisfactory. The introduction is scientifically accurate and meaningful. Study aims are clearly communicated and addressed appropriately with good quality methods. The authors use the HbA1c as the gold standard for the diagnosis of hyperglycemia in pregnancy and derive the RBS as a predictor of HIP with HbA1c as the reference. HIP is diagnosed in 20 pregnant women, using WHO criteria (validated for prediabetes outside of pregnancy). Five women have pre-existing/overt Diabetes Mellitus (HbA1c>6.5%) and the 20 "prediabetes" and 5 women with diabetes are categorized as HIP.

Comments:

It is unconventional to use HbA1c as the gold standard considering that, compared to an OGTT, HbA_1c has less evidence to support its use. This should be clearly stated and added to the limitations section.

The rationale for the inclusion of women in the first trimester in this context is also unclear. It has been suggested that RBS (plasma) performs surprisingly well as a first-trimester predictive tool for later GDM diagnosis, but this was not the aim of this study.

Diagnosis of hyperglycemia in pregnancy:

• The authors state that venous blood was used for the glucometer whereas capillary blood is usually used for point of care testing on a glucometer. There is a small but significant difference in the blood glucose results analyzed on a bedside glucometer when the samples are taken from capillary or venous sources. Can the authors please elaborate on the sampling and on the interchangeability of venous and capillary samples using this device?

Accuracy of RBS:

• How does the specific glucometer used, perform at the RBS levels obtained in this study? Has the glucometer method been standardized against isotope dilution mass spectrometry (ID/MS)? It has been proposed that a total error <5% with an imprecision [CV] <2% has to be achieved for a glucometer to be used in pregnancy, in view of this, is the glucometer used in this study fit for purpose?

Accuracy of HbA1c

• Was the HbA1C determination an approved International Federation of Clinical Chemistry and Laboratory Medicine method traceable to the DCCT trial?

Can the authors comment on the relationship between HbA1c and RBS in the "prediabetes" in pregnancy category (n=20) >24 weeks gestation? This would be a very worthwhile addition to the current study considering this is the group that one might forego OGTT on the basis of hbA1c and RBS in the future.

Is the argument information presented in such a way that it can be understood by a non-academic audience?

Yes

Could any solutions being offered be effectively implemented in practice?

Yes

Is the work clearly and accurately presented and does it cite the current literature?

Yes

If applicable, is the statistical analysis and its interpretation appropriate?

Yes

Is real-world evidence provided to support any conclusions made?

Yes

Are all the source data underlying the results available to ensure full reproducibility?

No source data required

Is the study design appropriate and is the work technically sound?

Yes

Are the conclusions drawn adequately supported by the results?

Yes

Does the piece present solutions to actual real world challenges?

Yes

Are sufficient details of methods and analysis provided to allow replication by others?

Yes

Reviewer Expertise:

Hyperglycemia first detected in pregnancy

I confirm that I have read this submission and believe that I have an appropriate level of expertise to confirm that it is of an acceptable scientific standard.

Figures

Figure 1.

Study flow diagram.

Figure 2.

Random blood sugar levels across different glycemic status.

Figure 3.

Receiver operating characteristic curve.

Table 1.

Sociodemographic and maternal characteristics of the study participants.

Participant variable	N (%) or Mean ± SD
Antenatal care visit at enrollment
First	142 (63.4)
Second	27 (12.1)
Third	19 (8.4)
Fourth and more	36 (16.1)
Age (years)	26 ± 5.0
<25 years	86 (38.4)
≥25 years	138 (61.6)
Marital status
Married	204 (91.1)
Single	12 (5.4)
Widowed	8 (3.6)
Education level
Informal	4 (1.8)
Primary	46 (20.5)
Secondary	117 (52.2)
Tertiary	57 (25.5)
Occupational status
Business	99 (42.2)
Professional	46 (20.5)
Unemployed	79 (35.3)
Smoking status
Former	2 (0.9)
Never	222 (99.1)
Alcohol usage
Current	12 (5.4)
Former	38 (17.0)
Never	174 (77.7)
Family history of diabetes
No	185 (82.6)
Yes	39 (17.4)
District of residence
Kampala	156 (69.6)
Wakiso	62 (27.7)
Mpigi	1 (0.5)
Mukono	4 (1.8)
Entebbe	1 (0.5)
Residence
Peri-Urban	63 (28.1)
Urban	161 (71.9)
HIV status
Positive	6 (2.7)
Negative	218 (97.3)
BCG scar
Yes	162 (72.3)
No	62 (27.7)
Family history of tuberculosis
Yes	22 (9.8)
No	202 (90.2)
Tuberculosis contact
Yes	19 (8.5)
No	205 (91.5)
Family size
≤4	177 (79.0)
≥5	47 (21.0)
Symptoms of diabetes
Yes	43 (19.2)
No	181 (80.8)
Gravidity
Primigravida	78 (34.8)
Multigravida	120 (53.6)
Grand multigravida	19 (8.5)
Great grand multigravida	7 (3.1)
Previous abortion
Yes	36 (16.1)
No	188 (83.9)
Gestation age at enrollment (weeks)	26.6 ±7.3
Trimester at enrollment
1	12 (5.4)
2	101 (45.1)
3	111 (49.6)
Anthropometry
Weight (kilograms)	68.9 ± 12.4
Height (meters)	1.6 ± 0.06
Body mass index (kg/m2)	27.3 ± 4.8
Waist circumference (centimeters)	95.2 ± 10.4
Hip circumference (centimeters)	103.8 ± 9.8
Waist-hip circumference	0.92 ± 0.08
Blood pressure at enrollment
Systolic blood pressure (mmHg)*	125 ± 18
Diastolic blood pressure (mmHg)*	78 ± 12.8
Normal	188 (91.5)
Hypertensive	19 (8.5)

*Average of two measurements taken.

Table 2.

Prevalence of hyperglycemia among pregnant women at Kawempe National Referral Hospital.

Participant variable	HIP (n=25)	No HIP (n=199)	P-value
	N (%)	N (%)
ANC visit at enrollment	2 (1)	2 (1)	0.857
First	16 (64.0)	126 (63.3)	0.277
Second	5 (20)	22 (11.1)
Third	0 (0)	19 (9.5)
Fourth and more	4 (16)	32 (16.1)
Age, mean (±SD)	28.4 ± 4.8	26.0 ± 5.0	0.027
<25 years	7 (28)	79 (39.7)	0.257
≥25 years	18 (72)	120 (60.3)
Marital status
Married	25 (100)	179 (89.9)	0.252
Single	0 (0)	12 (6.0)
Widowed	0 (0)	8 (4.0)
Education level
Informal	0 (0)	4 (2.0)	0.661
Primary	7 (28)	39 (19.6)
Secondary	13 (52)	104 (52.3)
Tertiary	5 (20)	52 (26.1)
Occupational status
Business	13 (52)	86 (43.2)	0.666
Professional	5 (20)	41 (20.6)
Unemployed	7 (28)	72 (36.2)
Smoking status
Former	0 (0)	2 (1.0)	>0.999
Never	25 (100)	197 (99.0)
Alcohol usage
Current	2 (8)	10 (5.0)	0.324
Former	6 (24)	32 (16.1)
Never	17 (68)	157 (78.9)
Family history of diabetes
No	20 (80)	165 (82.9)	0.717
Yes	5 (20)	34 (17.1)
District of residence
Kampala	17 (68)	139 (69.8)	0.061
Wakiso	6 (24)	56 (28.1)
Mpigi	1 (4)	3 (1.5)
Mukono	0 (0)	1 (0.5)
Entebbe	1 (4)	0 (0.0)
Residence
Peri-Urban	3 (12)	60 (30.2)	0.062
Urban	22 (88)	139 (69.8)
HIV status
Positive	1 (4)	5 (2.5)	0.513
Negative	24 (96)	194 (97.5)
BCG scar
Yes	10 (40)	52 (26.1)	0.144
No	15 (60)	147 (73.9)
Family history of tuberculosis
Yes	4 (16)	18 (9.0)	0.282
No	21 (84)	181 (91.0)
Tuberculosis contact
Yes	6 (24)	13 (6.5)	0.003
No	19 (76)	186 (93.5)
Family size
≤4	19 (76)	158 (79.4)	0.694
≥5	6 (24)	41 (20.6)
Symptoms of diabetes
Yes	4 (16)	39 (19.6)	0.793
No	21 (84)	160 (80.4)
Gravidity
Primigravida	4 (16)	74 (37.2)	0.112
Multigravida	16 (64)	104 (52.3)
Grand multigravida	3 (12)	16 (8.0)
Great grand multigravida	2 (8)	5 (2.5)
Previous abortion
Yes	7 (28)	29 (14.6)	0.085
No	18 (72)	170 (85.4)
Gestation age at enrollment (weeks; mean ± SD)	25.8 ± 7.7	26.7 ± 7.3	0.558
Trimester at enrollment
1	1 (4)	11 (5.5)	0.922
2	12 (48)	89 (44.7)
3	12 (48)	99 (49.7)
Anthropometry, mean ± SD
Weight (kilograms)	71.4 ± 15.0	68.6 ± 12.0	0.274
Height (meters)	1.6 ± 0.07	1.6 ± 0.06	0.408
BMI (kg/m2)	28.7 ± 5.9	27.1 ± 4.6	0.113
Waist circumference (centimeters)	97.5 ± 13.4	94.9 ± 10.0	0.227
Hip circumference (centimeters)	107.8 ± 10.4	103.3 ± 9.7	0.032
Waist-hip circumference	0.92 ± 0.08	0.92 ± 0.08	0.327
Blood pressure at enrollment, Mean ± (SD)
Systolic blood pressure (mmHg) *	122 ± 12	125 ± 18	0.394
Diastolic blood pressure (mmHg) *	77 ± 8	78 ± 13	0.759
Normal	23 (92)	165 (82.9)	0.386
Hypertension	2 (8)	34 (17.1)

HIP, hyperglycemia in pregnancy. *Average of two measurements taken.

Table 3.

A multivariable logistic regression model showing factors associated with hyperglycemia among pregnant women at Kawempe National Referral Hospital.

Demographic and clinical characteristics	Adjusted Odds Ratio	95% CI	P-value
Age	1.04	0.92 - 1.16	0.549
District of residence
Entebbe	1.00
Kampala	1.55	0.49 - 4.92	0.458
Mukono	9.36	0.6 - 146.93	0.112
Residence
Rural	1.00
Urban	3.80	0.92 - 15.63	0.064
BCG scar
Yes	1.00
No	1.72	0.64 - 4.58	0.280
Tuberculosis contact
No	1.00
Yes	4.14	1.23 - 13.98	0.022
Gravidity
Primigravida	1.00
Multigravida	1.67	0.43 - 6.43	0.458
Grand multigravida	2.08	0.3 - 14.55	0.462
Great grand multigravida	4.01	0.28 - 56.64	0.304
Previous abortion
No	1.00
Yes	1.24	0.37 - 4.21	0.728
Body mass index	0.98	0.84 - 1.15	0.826
Hip circumference	1.06	0.98 - 1.14	0.132

CI, confidence interval.