Prevalence and predictors of gestational diabetes mellitus: a nationwide multicentre prospective study

The association of inflammatory markers in early pregnancy with the development of gestational diabetes: Qazvin maternal and neonatal metabolic study (QMNS)

BACKGROUND

This study investigates the association of blood cell components and blood cell-derived inflammatory indices in early pregnancy with the development of gestational diabetes mellitus (GDM).

METHODS

This research is part of the Qazvin maternal and neonatal metabolic study (QMNMS) conducted in Iran from 2018 to 2021. Pregnant women with gestational age ≤ 14 weeks were enrolled in the study. The association of blood cells and inflammatory indices, including neutrophil-to-lymphocyte ratio (NLR), systemic inflammatory response index (SIRI), systemic immune inflammation index (SII), and aggregate systemic inflammatory response index (AISI), in early pregnancy with subsequent GDM development was examined using multivariate logistic regression. This analysis was adjusted for age, pre-pregnancy body mass index (BMI), weight gain, and GDM history in previous pregnancies (Model 1), as well as for these factors in addition to the homeostatic model assessment for insulin resistance (HOMA-IR) (Model 2). The correlation of blood cells and inflammatory indices with insulin resistance was assessed through Spearman partial correlation, adjusted for the same risk factors.

RESULTS

The final analysis included 612 participants, among whom GDM developed in 96 participants (15.7%). Neutrophil, platelet, and lymphocyte counts showed significant correlations with HOMA-IR (r = 0.14, r = 0.22, and r = 0.17, respectively; P < 0.01 for all). In univariate analysis, the highest quartile of neutrophil count was associated with a 5.9 times higher risk of GDM development (95% CI 2.6-13.2, P < 0.001). In multivariate logistic regression, neutrophil count quartiles remained significant predictors of GDM development, with relative risks of 3.7, 4.4, and 8.2 for the 2nd, 3rd, and 4th neutrophil quartiles compared to the 1st quartile (P < 0.001). While platelet count was initially associated with GDM development (RR = 2.6, 95% CI 1.3-5.1, P = 0.028), this association was no longer significant after adjusting for HOMA-IR. Neither lymphocyte nor monocyte counts were linked to GDM development. Additionally, inflammatory indices, such as NLR, SIRI, SII, and AISI, did not provide additional predictive value for GDM development.

CONCLUSION

Neutrophil count is an independent predictor of GDM development, and its role in GDM development is not influenced by early pregnancy insulin resistance. Moreover, novel inflammatory indices offer no additional predictive benefit for GDM.

Association of iron homeostasis-related gene polymorphisms with pregnancy and neonatal outcomes in patients with gestational diabetes mellitus

OBJECTIVE

The purpose of this study was to assess associations between iron homeostasis-related gene polymorphisms and gestational diabetes mellitus (GDM), adverse pregnancy outcomes, and neonatal outcomes.

METHODS

In total, 138 patients with GDM and 74 normal pregnancy controls were recruited. Time-of-flight mass spectrometry was used to genotype single-nucleotide polymorphisms (H63D rs1799945, TMPRSS6 rs855791, GDF15 rs1059369, rs4808793, BMP2 rs173107, C282Y rs3811647, rs1800562, rs269853, TF rs8177240, TFR2 rs7385804, FADS2 rs174577, and CUBN rs10904850) in 12 candidate genes related to iron homeostasis. Adverse pregnancy outcomes and neonatal health data were collected. Differences in genotype distributions and allele frequencies between patients and controls as well as their correlations with clinical factors were assessed. Additionally, associations between genotype, haemoglobin levels, and ferritin levels were evaluated.

RESULTS

Pregnant women carrying the GDF15 rs4808793 allele (C) or TMPRSS6 rs855791 homozygous mutation (GG) had a significantly higher risk of GDM than that in the control group (p < 0.05). In patients with GDM, the BMP2 rs173107 heterozygous mutation (AC) was associated with significantly higher haemoglobin levels in late pregnancy compared with those for wild-type (AA) BMP2 (p < 0.05). Furthermore, in patients with GDM, the FADS2 rs174577 heterozygous mutation (AC) was associated with a significantly reduced risk of preterm birth (p < 0.05), the H63D rs1799945 heterozygous mutation (CG) was associated with a significantly increased risk of adverse neonatal outcomes (p < 0.05), TFR2 rs7385804 was associated a significantly reduced probability of caesarean section (p < 0.05), and the G mutation in TMPRSS6 rs855791 was related to a significantly increased probability of caesarean section (p < 0.05).

CONCLUSIONS

These results suggest that polymorphisms in genes related to iron metabolism could potentially impact pregnancy and neonatal outcomes in patients with GDM. Large-scale studies are needed to further clarify the relationship between these polymorphisms and susceptibility to GDM.

The association of plasma pancreastatin levels with insulin resistance in patients with gestational diabetes mellitus

Introduction

Gestational diabetes mellitus (GDM) occurs on the background of increased insulin resistance. We aimed to investigate the levels of plasma pancreastatin (PST) levels and its association with metabolic, demographic, and anthropometric parameters in gestational diabetic and normal glucose-tolerant pregnant women.

Materials and methods

A total of 165 pregnant women in the 24th-28th week of pregnancy were enrolled in this cross-sectional study. PST levels were measured using ELISA method.

Results

Median PST levels were similar between GDM (n = 62, 37.6%) and normal glucose-tolerant control group (n = 103, 62.4%). In the GDM group, PST level showed a significant positive correlation with fasting insulin and the homeostasis model assessment of insulin resistance (HOMA-IR). In binary logistic regression analysis, PST levels did not predict the presence of GDM significantly.

Conclusion

Positive correlation of PST with fasting insulin and HOMA-IR suggests that PST could be associated with insulin resistance. Further studies are needed as regards to the role of PST in GDM pathogenesis.

Development and validation of a clinical model to predict preconception risk of gestational diabetes mellitus in nulliparous women: A retrospective cohort study

OBJECTIVE

To develop and validate a model to predict the preconception risk of gestational diabetes mellitus (GDM) in nulliparous women.

METHODS

This was a retrospective cohort study. A total of 1565 women in early pregnancy who underwent preconception health examinations in the Women and Children's Hospital of Chongqing Medical University between January 2020 and June 2021 were invited to participate in a questionnaire survey. Logistic regression analysis was performed to determine the preconception risk factors for GDM. These factors were used to construct a model to predict GDM risk in nulliparous women. Then, the model was used to assess the preconception risk of GDM in 1060 nulliparous women.

RESULTS

Independent preconception risk factors for GDM included the following: age 35 years or greater, diastolic blood pressure 80 mm Hg or greater, fasting plasma glucose 5.1 mmol/L or greater, body mass index (BMI, calculated as weight in kilograms divided by the square of height in meters) 24 or greater, weight gain 10 kg or greater in the year before pregnancy, age of menarche 15 years or greater, three or more previous pregnancies, daily staple food intake 300 g or greater, fondness for sweets, and family history of diabetes. BMI less than 18.5, daily physical activity duration 1 h or greater, and high-intensity physical activity were protective factors. These factors were used to construct a model to predict GDM risk in nulliparous women, and the incidence of GDM significantly increased as the risk score increased. The area under the curve of the prediction model was 0.82 (95% confidence interval 0.80-0.85).

CONCLUSION

The preconception GDM risk prediction model demonstrated good predictive efficacy and can be used to identify populations at high risk of GDM before pregnancy, which provides the possibility for preconception intervention.

Environmental tobacco smoke increased risk of gestational diabetes mellitus: A birth cohort study in Sichuan, China

INTRODUCTION

Studies on the relationship between environmental tobacco smoke (ETS) and gestational diabetes mellitus (GDM) are limited. In this study, we aimed to clarify the association between ETS at different trimesters of pregnancy and the risk of GDM among non-smoking pregnant women.

METHODS

A total of 16,893 non-smoking mothers from the Southwest Birth Cohort, China, were included in the final analyses. Exposure and outcome measures included self-reported ETS status at different trimesters of pregnancy and GDM diagnosis. Multivariable logistic regression models were constructed to estimate the association between ETS and GDM.

RESULTS

The prevalence of ETS exposure was 25.7%. Compared with no ETS, ever ETS had an increased risk of GDM, with an adjusted odds ratio (95% confidence intervals) of 1.21 (1.09, 1.33). The association remained consistent at different trimesters of pregnancy ETS exposure. In the last trimester and with continuous ETS exposure, the risk of GDM increased significantly with the increase in the duration of the exposure. The risk of GDM associated with ever ETS during pregnancy significantly increased in mothers over 30 years old and pre-pregnancy overweight (P for interaction <0.05).

CONCLUSIONS

ETS exposure at different trimesters of pregnancy was associated with an increased risk of GDM among non-smoking pregnant women. These findings emphasise the importance of preventing ETS exposure during pregnancy.

Increased Circulating IL-32 Is Associated With Placenta Macrophage-derived IL-32 and Gestational Diabetes Mellitus

OBJECTIVE

Placenta-derived inflammation plays a vital role in the pathophysiology of gestational diabetes mellitus (GDM). IL-32 is a novel pro-inflammatory cytokine and metabolic regulator involved in the development of metabolic disease. We investigated the effect of IL-32 in GDM.

MATERIALS AND METHODS

First-trimester C-reactive protein (CRP) level was monitored in a case-control study of 186 women with GDM and 186 women without. Placental tissue was lysed and analyzed by high-resolution liquid chromatography-tandem mass spectrometry. Circulating level of inflammatory cytokines IL-32, IL-6, and TNF-α were measured by ELISA kits. The expression of placenta-derived macrophages, inflammatory cytokines, and related pathway proteins were assessed by reverse transcriptase-quantitative PCR, western blot, immunohistochemistry, or immunofluorescence.

RESULTS

First-trimester CRP level in peripheral blood was closely associated with glucose and insulin resistance index and was an independent correlation with the development of GDM. High-resolution liquid chromatography-tandem mass spectrometry revealed that placenta-derived CRP expression was dramatically elevated in women with GDM. Interestingly, the expression of placenta-derived IL-32 was also increased and located in the macrophages of placental tissue. Meanwhile, the expression of IL-6, TNF-α, and p-p38 were up-regulated in the placental tissues with GDM. Either IL-6 or TNF-α was colocated with IL-32 in the placental tissue. Importantly, circulating IL-32 throughout pregnancy was increased in GDM and was related to placental-derived IL-32 expression, circulating IL-6, and TNF-α, glucose and insulin resistance index.

CONCLUSION

Increased circulating IL-32 throughout pregnancy was closely associated with placenta macrophage-derived IL-32 expression and GDM. First trimester IL-32 level in peripheral blood may serve to predict the development of GDM.

The yield of early-pregnancy homeostasis of model assessment -insulin resistance (HOMA-IR) for predicting gestational diabetes mellitus in different body mass index and age groups

BACKGROUND

Early prediction of gestational diabetes mellitus(GDM) can be beneficial for lifestyle modifications to prevent GDM. The aim of this study was to investigate the predictive values of Homeostasis of Model Assessment -Insulin Resistance (HOMA-IR) in early pregnancy to predict GDM development in different body mass index (BMI) and age risk categories.

MATERIALS AND METHODS

This study is part of the Qazvin Maternal and Neonatal Metabolic Study (QMNMS) in Iran (2018-2021). In this prospective longitudinal study, pregnant women with a gestational age ≤ 14 weeks were enrolled in the study using convenience sampling method and were followed up until delivery to investigate risk factors for maternal and neonatal complications. Data collection was done using questionnaires. Serum sampling was done at a gestational age ≤ 14 weeks and sera were frozen until the end of study. GDM was diagnosed at 24-28 weeks of pregnancy using 75gr oral glucose tolerance test. Fasting blood glucose and insulin were measured in sera taken during early pregnancy in 583 participants. The Mann-Whitney U test, independent t-test, and Chi-square test were used for comparing variables between groups. The logistic regression analysis was used to examine the independent association of HOMA-IR with GDM development and receiver operating characteristic analysis was used for finding the best cut-off of HOMA-IR for predicting GDM.

RESULTS

GDM was developed in 90 (15.4%) of the participants. The third HOMA-IR tertile was independently associated with 3.2 times higher GDM occurrence (95% CI:1.6-6.2, P = 0.001). Despite the high prevalence of GDM in advanced maternal age (GDM rate = 28.4%), HOMA-IR had no association with GDM occurrence in this high-risk group. In both normal BMI and overweight/obese groups, HOMA-IR was a moderate predictor of GDM development (AUC = 0.638, P = 0.005 and AUC = 0.622, P = 0.008, respectively). However, the best cut-off for predicting GDM was 2.06 (sensitivity 67.5%, specificity 61.1%) in normal BMI and 3.13 (sensitivity 64.6%, specificity61.8%) in overweight/obese BMI.

CONCLUSION

The present study revealed the necessity of considering the BMI and age risk groups when using the HOMA-IR index to predict GDM. Using lower cut-offs is more accurate for women with a normal BMI. In the advanced maternal age, there is no yield of HOMA-IR for predicting GDM.

Development and validation of a multivariable genotype-informed gestational diabetes prediction algorithm for clinical use in the Mexican population: insights into susceptibility mechanisms

INTRODUCTION

Gestational diabetes mellitus (GDM) is underdiagnosed in Mexico. Early GDM risk stratification through prediction modeling is expected to improve preventative care. We developed a GDM risk assessment model that integrates both genetic and clinical variables.

RESEARCH DESIGN AND METHODS

Data from pregnant Mexican women enrolled in the 'Cuido mi Embarazo' (CME) cohort were used for development (107 cases, 469 controls) and data from the 'Mónica Pretelini Sáenz' Maternal Perinatal Hospital (HMPMPS) cohort were used for external validation (32 cases, 199 controls). A 2-hour oral glucose tolerance test (OGTT) with 75 g glucose performed at 24-28 gestational weeks was used to diagnose GDM. A total of 114 single-nucleotide polymorphisms (SNPs) with reported predictive power were selected for evaluation. Blood samples collected during the OGTT were used for SNP analysis. The CME cohort was randomly divided into training (70% of the cohort) and testing datasets (30% of the cohort). The training dataset was divided into 10 groups, 9 to build the predictive model and 1 for validation. The model was further validated using the testing dataset and the HMPMPS cohort.

RESULTS

Nineteen attributes (14 SNPs and 5 clinical variables) were significantly associated with the outcome; 11 SNPs and 4 clinical variables were included in the GDM prediction regression model and applied to the training dataset. The algorithm was highly predictive, with an area under the curve (AUC) of 0.7507, 79% sensitivity, and 71% specificity and adequately powered to discriminate between cases and controls. On further validation, the training dataset and HMPMPS cohort had AUCs of 0.8256 and 0.8001, respectively.

CONCLUSIONS

We developed a predictive model using both genetic and clinical factors to identify Mexican women at risk of developing GDM. These findings may contribute to a greater understanding of metabolic functions that underlie elevated GDM risk and support personalized patient recommendations.

Regional divergence and time trends in the prevalence of gestational diabetes mellitus: a national Danish cohort study

AIMS

To evaluate the prevalence and time trends of gestational diabetes mellitus (GDM) across the five regions of Denmark with uniform national guidelines for screening and diagnosing GDM.

METHODS

This register-based national cohort study included 287,684 births from 2013 to 2017. Trends in GDM prevalence over time and differences between the five regions were evaluated. Crude and adjusted odd ratios (ORs) for GDM were calculated including potential confounding clinical risk factors as age, BMI, educational level, marital status, parity, country of origin and assisted reproduction.

RESULTS

From 2013 to 2017, GDM prevalence in Denmark increased by 7% per year (OR 1.07, 95% CI 1.06-1.09, P < 0.001). GDM prevalence varied considerably between regions and ranged from 3.0 to 5.9% in 2017, corresponding to a maximal regional difference of 97%. In crude analyses, the risk of GDM in 2017 was significantly different in four of five regions compared to the remaining regions (OR ranging from 0.60 to 1.55), and these differences persisted after adjusting for confounding clinical risk factors (adjusted OR: 0.59-1.45).

CONCLUSION

The prevalence of GDM increased over time in all Danish regions with substantial regional divergence. Up to a 97%, difference in GDM prevalence was observed between Danish regions, which was not explained by available clinical risk factors. This occurred despite national guidelines and raises the question of whether regional variations in screening efficacy, diagnostic procedures or inequality in clinical health care access may explain the observed differences.

Predictors of postpartum glucose metabolism disorders in women with gestational diabetes mellitus

BACKGROUND AND AIMS

Postpartum glucose metabolism disorders are a common problem in women with gestational diabetes mellitus (GDM). They are often underdiagnosed since many patients do not attend the postpartum screening. This study aims to assess predictors of postpartum glucose metabolism disorders and type 2 diabetes mellitus (T2DM) after GDM.

MATERIAL AND METHODS

Retrospective study in women with GMD who underwent postpartum screening for glucose metabolism disorders (n = 2688). Logistic regression was used in the statistical analysis.

RESULTS

24.6% of women had postpartum glucose metabolism disorder. In multivariate analysis, pre-pregnancy body mass index (BMI) 25-30 kg/m² (OR 1.46, 95%CI 1.05 to 2.02) or BMI ≥30 kg/m² (OR 2.62, 95%CI 1.72 to 3.96), diagnosis of GDM before 20 weeks of pregnancy (OR 2.33, 95%CI 1.57 to 3.46), fasting plasma glucose after diagnosis of GDM ≥90 mg/dl (OR 2.12, 95%CI 1.50 to 2.98), postprandial glucose ≥100 mg/dl (OR 1.47, 95%CI 1.09 to 2.99), and HbA1c in the third trimester of pregnancy ≥5.3% (2.04, 95%CI, 1.52 to 2.75) were independent predictors for any postpartum glucose metabolism disorder.

CONCLUSION

postpartum screening for T2DM should be performed in all women with GDM, and it is especially important not to lose follow-up in those with one or more predictive factors.

The association of interleukin-6, interleukin-27, and body roundness index with gestational diabetes mellitus

We aimed to investigate the relationship between GDM and IL-27, IL-6, and body roundness index (BRI), a new anthropometric measurement more sensitive than BMI in identifying obesity and predicting cardiometabolic outcomes. We enrolled 80 patients, 40 pregnant women with GDM and 40 healthy pregnant women at midgestation. The women's anthropometric measurements were recorded and serum markers and IL-6, IL-27 were analysed. At the time of delivery maternal, neonatal results were recorded. Women with GDM had significantly higher pregestational, midgestational and prepartum BMI and midgestational BRI; HOMA-IR; HbA1c; and IL-6 values and lower HDL values (p < .05). There was no statistically significant difference in IL-27 values between the groups (p = .939). In multivariate logistic regression analysis, HbA1c, IL-6 (>4.886 pg/mL), and BRI (>6.708) were found as independent risk factors associated with GDM (p < .05). Mean BRI was significantly associated with obesity (p < .001) and BRI higher than 6.708 was found to have 67.5% sensitivity and 80% specificity in the prediction of GDM. Women with GDM had elevated IL-6 levels, but no relationship was detected between IL-27 and GDM. BRI is a new anthropometric index that strongly correlated with BMI and seems to be a reliable alternative to BMI for the evaluation of obesity in GDM patients.IMPACT STATEMENTWhat's already known on this subject? Gestational diabetes mellitus (GDM) is the most common systemic disease in pregnancy. The risk of GDM was 3 times higher in obese pregnant women compared to normal weighted patients. IL-6 is an adipose-derived cytokine that was found to be associated with GDM. The body roundness index (BRI) is a new sensitive anthropometric index for detecting obesity and its secondary cardiometabolic results.What do the results of this study add? Our results showed that BRI was strongly correlated with obesity in GDM patients. HbA1c, IL-6 and BRI were found as independent risk factors associated with GDM. IL 27, a cytokine associated with inflammatory diseases, was not associated with GDM.What are the implications of these findings for clinical practice and/or further research? BRI could be a reliable alternative to BMI for the evaluation of obesity in pregnant women and predicting cardiometabolic outcomes.

Decreased Monocyte Count Is Associated With Gestational Diabetes Mellitus Development, Macrosomia, and Inflammation

CONTEXT

The immune system plays a central role in the pathophysiology of gestational diabetes mellitus (GDM). Monocytes, the main innate immune cells, are especially important in the maintenance of a normal pregnancy.

OBJECTIVE

Here, we investigated the potential effect of monocytes in GDM.

METHODS

Monocyte count was monitored throughout pregnancy in 214 women with GDM and 926 women without in a case-control and cohort study. Circulating levels of inflammatory cytokines, placenta-derived macrophages, and their products were measured.

RESULTS

Throughout pregnancy, monocyte count was significantly decreased in women with GDM, and was closely associated with glucose level, insulin resistance, and newborn weight. First-trimester monocyte count outperformed that of the second and third trimester as a risk factor and diagnostic predictor of GDM and macrosomia both in the case-control and cohort study. In addition, our cohort study showed that as first-trimester monocyte count decreased, GDM and macrosomia incidence, glucose level, and newborn weight increased in a stepwise manner. Risk of GDM started to decrease rapidly when first-trimester monocyte count exceeded 0.48 × 109/L. Notably, CD206 and interleukin 10 (IL-10) were significantly lower, whereas CD80, CD86, tumor necrosis factor α (TNF-α), and interleukin 6 (IL-6) were higher both in GDM placental tissue and peripheral blood. First-trimester monocyte count was positively related to IL-10 and CD206, but negatively related to CD80, CD86, TNF-α, and IL-6.

CONCLUSION

Decreased monocyte count throughout pregnancy was closely associated with the development of GDM, macrosomia, and the chronic inflammatory state of GDM. First-trimester monocyte count has great potential as an early diagnostic marker of GDM.

Association of COVID-19 Lockdown With Gestational Diabetes Mellitus

IMPORTANCE

The ongoing pandemic of COVID-19 is still affecting our life, but the effects of lockdown measures on gestational diabetes mellitus (GDM) in pregnant women remain unclear.

AIM

To investigate the association between COVID-19 lockdown and GDM.

SUBJECTS AND METHODS

Medical records of 140844 pregnant women during 2015-2020 were extracted from 5 hospitals in Guangdong Province, China. Pregnant women who underwent the COVID-19 Level I lockdown (1/23 - 2/24/2020) during pregnancy were defined as the exposed group (N=20472) and pregnant women who underwent the same calendar months during 2015-2019 (1/23 - 2/24) were defined as the unexposed group (N=120372). Subgroup analyses were used to explore the potential susceptible exposure window of COVID-19 lockdown on GDM. Cumulative exposure is quantitatively estimated by assigning different weights to response periods with different exposure intensities. A logistic regression model was used to estimate the association between COVID-19 lockdown exposure and GDM.

RESULTS

The rates of GDM in the exposed and unexposed groups were 15.2% and 12.4%, respectively. The overall analyses showed positive associations (odds ratio, OR=1.22, 95%CI: 1.17, 1.27) between lockdown exposure and GDM risk in all pregnant women. More pronounced associations were found in women who underwent the COVID-19 lockdown in their first four months of pregnancy, and the adjusted OR values ranged from 1.24 (95%CI: 1.10, 1.39) in women with 5-8 gestational weeks (GWs) to 1.35 (95%CI: 1.20, 1.52) with < 5 GWs. In addition, we found a positive exposure-response association of cumulative lockdown exposure with the risk of GDM.

CONCLUSIONS

The COVID-19 lockdown was associated with an increased risk of GDM, and the first four months of pregnancy may be the window for sensitive exposure.

Trends in maternal body mass index in Northern Ireland: a cross-sectional and longitudinal study

Objectives

Explore (1) associations between maternal body mass index (BMI), demographic and clinical characteristics, (2) longitudinal trends in BMI, (3) geographical distributions in prevalence of maternal overweight and obesity.

Design

Retrospective population-based study.

Setting

Linked, anonymised, routinely collected healthcare data and official statistics from Northern Ireland.

Participants

All pregnancies in Northern Ireland (2011–2017) with BMI measured at ≤16 weeks gestation.

Methods

Analysis of variance and χ² tests were used to explore associations. Multiple linear regression was used to explore longitudinal trends and spatial visualisation illustrated geographical distribution. Main outcomes are prevalence of overweight (BMI ≥25 kg/m²) and obesity (BMI ≥30 kg/m²).

Results

152 961 singleton and 2362 multiple pregnancies were included. A high prevalence of maternal overweight and obesity in Northern Ireland is apparent (singleton: 52.4%; multiple: 48.3%) and is increasing. Obesity was positively associated with older age, larger numbers of previous pregnancies and unplanned pregnancy (p<0.001). BMI category was also positively associated with unemployment (35% in obese class III vs 22% in normal BMI category) (p<0.001). Higher BMI categories were associated with increased rate of comorbidities, including hypertension (normal BMI: 1.8% vs obese III: 12.4%), diabetes mellitus (normal BMI: 0.04% vs obese III: 1.29%) and mental ill-health (normal BMI: 5.0% vs obese III: 11.8%) (p<0.001). Prevalence of maternal obesity varied with deprivation (most deprived: 22.8% vs least deprived: 15.7%) (p<0.001). Low BMI was associated with age <20 years, nulliparity, unemployment and mental ill-health (p<0.001).

Conclusions

The prevalence of maternal BMI >25 kg/m² is increasing over time in Northern Ireland. Women are entering pregnancy with additional comorbidities likely to impact their life course beyond pregnancy. This highlights the need for prioritisation of preconception and inter-pregnancy support for management of weight and chronic conditions.

An early model to predict the risk of gestational diabetes mellitus in the absence of blood examination indexes: application in primary health care centres

Background

Gestational diabetes mellitus (GDM) is one of the critical causes of adverse perinatal outcomes. A reliable estimate of GDM in early pregnancy would facilitate intervention plans for maternal and infant health care to prevent the risk of adverse perinatal outcomes. This study aims to build an early model to predict GDM in the first trimester for the primary health care centre.

Methods

Characteristics of pregnant women in the first trimester were collected from eastern China from 2017 to 2019. The univariate analysis was performed using SPSS 23.0 statistical software. Characteristics comparison was applied with Mann-Whitney U test for continuous variables and chi-square test for categorical variables. All analyses were two-sided with p < 0.05 indicating statistical significance. The train_test_split function in Python was used to split the data set into 70% for training and 30% for test. The Random Forest model and Logistic Regression model in Python were applied to model the training data set. The 10-fold cross-validation was used to assess the model’s performance by the areas under the ROC Curve, diagnostic accuracy, sensitivity, and specificity.

Results

A total of 1,139 pregnant women (186 with GDM) were included in the final data analysis. Significant differences were observed in age (Z=−2.693, p=0.007), pre-pregnancy BMI (Z=−5.502, p<0.001), abdomen circumference in the first trimester (Z=−6.069, p<0.001), gravidity (Z=−3.210, p=0.001), PCOS (χ²=101.024, p<0.001), irregular menstruation (χ²=6.578, p=0.010), and family history of diabetes (χ²=15.266, p<0.001) between participants with GDM or without GDM. The Random Forest model achieved a higher AUC than the Logistic Regression model (0.777±0.034 vs 0.755±0.032), and had a better discrimination ability of GDM from Non-GDMs (Sensitivity: 0.651±0.087 vs 0.683±0.084, Specificity: 0.813±0.075 vs 0.736±0.087).

Conclusions

This research developed a simple model to predict the risk of GDM using machine learning algorithm based on pre-pregnancy BMI, abdomen circumference in the first trimester, age, PCOS, gravidity, irregular menstruation, and family history of diabetes. The model was easy in operation, and all predictors were easily obtained in the first trimester in primary health care centres.

Behaviors of Turkish pregnant women towards gestational diabetes screening

OBJECTIVES

Although gestational diabetes is the most common metabolic disease in pregnancy some pregnant women still refuse to undergo oral glucose tolerance test (OGTT). The purpose of this study was to evaluate the behavior of pregnant women undergoing OGTT, and to compare perinatal results between women who undergo and refuse OGTT.

METHODS

This retrospective cohort study was performed by evaluating the data of Izmir Katip Celebi University Gynecology and Obstetrics outpatient clinic between 2012-2017. Data of 2079 pregnant were evaluated retrospectively. Among 373 women who refused OGTT were evaluated as the study group, while remaining 1706 women who underwent OGTT were considered as the control group. The groups were compared with regard to perinatal results.

RESULTS

Sixty-two point four percent of the group who refused OGTT had a C-section, while 56.3% of the control group had a C-section (p<0.05). Intrauterine growth retardation, fetal distress, amniotic fluid pathologies, macrosomia, gestational hypertension and perinatal death were slightly higher in pregnant women who did not undergo OGTT compared to the control group, however, the difference was not statistically significant.

CONCLUSION

Maternal complications and poor pregnancy results were found slightly higher in pregnant women who refused OGTT. These results might be explained by assuring glycemic control in pregnant women who refused OGTT by a series of fasting and postprandial blood sugar measurements in our center.

Gestational Diabetes Mellitus: The Genetic Susceptibility Behind the Disease

Gestational diabetes mellitus (GDM), a type of pregnancy-specific glucose intolerance or hyperglycemia, is one of the most common metabolic disorders in pregnant women with 16.9% of the global prevalence of gestational hyperglycemia. Not only are women with GDM likely to develop T2DM, but their children are also at risk for birth complications or metabolic disease in adulthood. Therefore, identifying the potential risk factors for GDM is very important in the prevention and treatment of GDM. Previous studies have shown that genetic predisposition is an essential component in the occurrence of GDM. In this narrative review, we describe the role of polymorphisms in different functional genes associated with increased risk for GDM, and available evidence on genetic factors in the risk of GDM is summarized and discussed.

Association Between Neutrophil-Lymphocyte Ratio and Gestational Diabetes-A Systematic Review and Meta-Analysis

A growing body of evidence shows that the neutrophil-lymphocyte ratio (NLR) is a surrogate index of systemic inflammation in several chronic diseases. Conflicting associations between NLR and gestational diabetes mellitus (GDM) have been reported in individual studies. This meta-analysis sought to investigate the association between NLR and GDM. The PubMed, EMBASE, and Google Scholar databases were searched to identify relevant articles. The pooled standardized mean difference with 95% CI was calculated using a random-effects model. Subgroup and meta-regression analysis were carried out to control for the effects of GDM diagnostic criteria, ethnicity, body mass index (BMI), and age. Eleven eligible articles were included, containing 1271 participants with GDM and 1504 controls. Pooled outcomes indicated a higher NLR in GDM pregnancies than in normoglycemic controls (SMD = 0.584; 95% CI, 0.339-0.830; P < .001), although extensive heterogeneity between studies was noted. Subgroup analysis revealed that the higher pooled estimate in GDM was not affected by diagnostic criteria, ethnicity, or BMI, although matching for BMI reduced heterogeneity between studies. This meta-analysis supports the higher NLR in GDM described by some individual studies.

Decreased serum human leukocyte antigen-G levels are associated with gestational diabetes mellitus

AIM

This study was designed to determine serum human leukocyte antigen-G (HLA-G) levels and establish whether serum HLA-G level is related with gestational diabetes mellitus (GDM).

METHODS

Twenty-five GDM patients aged between 24 and 34 years and 24 healthy pregnant women aged between 22 and 33 years were included in this study. Health status of subjects was determined by medical history, physical, and obstetric examinations. Absence of family history for Type 2 diabetes mellitus, absence of diagnosis or clinical evidence of any major disease, and absence of medication use altering glucose metabolism constituted the inclusion criteria. GDM cases who are at their 24-28 weeks of pregnancy and who have not been using any oral hypoglycemic agents were included in GDM group. Control group consisted of healthy pregnant women at their 24-28 weeks of pregnancy.

RESULTS

Women with GDM had significantly lower levels of serum HLA-G than controls. HLA-G levels were negatively correlated with all parameters of glucose metabolism including insulin (r = - 0.14; p = 0.338), fasting blood glucose (r = - 0.220; p = 0.129), 1-h oral glucose tolerance test (OGTT) blood glucose (r = - 0.18; p = 0.271), 2-h OGTT blood glucose (r = - 0.314; p = 0.172), homeostasis model assessment (r = - 0.226; p = 0.119), HbA1C (r = -0.342; p = 0.108), and WBC (r = -0.149; p = 0.307). There was a negative correlation between HLA-G and BMI (r = -0.341; p = 0.016).

CONCLUSION

Decreased circulating HLA-G level is found to be associated with insulin resistance and GDM, in this study.

The possible role of visceral fat in early pregnancy as a predictor of gestational diabetes mellitus by regulating adipose-derived exosomes miRNA-148 family: protocol for a nested case-control study in a cohort study

Background

Gestational diabetes mellitus (GDM) has become alarming public health concern. It is associated with adverse pregnancy outcomes and increased risk of postpartum type 2 diabetes. Pre-pregnant body mass index (BMI), waist circumference and other anthropometric parameters have been proposed to predict GDM. However, visceral fat thickness can better reflect the distribution of body fat, and may more accurately predict the risk of GDM. Visceral fat thickness may lead to insulin resistance by regulating the adipose-derived exosomes miRNA-148 family, which affect the development of GDM. Evidence from prospective cohort studies on visceral fat thickness as a predictor of GDM and the possible mechanisms is still insufficient.

Methods

In this prospective cohort study, we will recruit 3000 women at first antenatal visit between 4 and 12 weeks of gestation. Baseline socio-demographic factors and visceral fat thickness will be assessed by questionnaire form and the ultrasonic measurement, respectively. At 20 weeks of gestation, 10 ml blood samples will be drawn and we will extract adipose-derived exosomes miRNA on the basis of nested case-control study. GDM will be screened at 24–28 weeks’ gestation and the expression of miRNA-148 family between pregnant women with GDM and without GDM will be analyzed. Intermediary analysis will be used to investigate whether visceral fat thickness can predict GDM by regulating adipose-derived exosomes miRNA-148 family.

Discussion

We hypothesized that visceral fat thickness may predict GDM by regulating the miRNA-148 family of adipose-derived exosomes. The findings of the study will assist in further clarifying the pathophysiological mechanism of GDM, it will also provide technical support for effective screening of high-risk pregnant women with GDM.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12884-021-03737-1.

Higher Parity, Pre-Pregnancy BMI and Rate of Gestational Weight Gain Are Associated with Gestational Diabetes Mellitus in Food Insecure Women

Food insecurity may exacerbate adverse maternal health outcomes during pregnancy, however, this association has not been well established, particularly in the context of developing countries. This study aimed to identify the associations between household food insecurity and gestational diabetes mellitus (GDM) risk among urban pregnant women. Household food insecurity was assessed using the translated 10-item Radimer/Cornell hunger scale. Logistic regression models were used to estimate the associations between food insecurity status and GDM risk. About 35.6% of women experienced food insecurity, with 25.2% reported household food insecurity, 8.0% individual food insecurity, and 2.4% child hunger. Food insecure women were at significantly higher risk of developing GDM compared to food secure women (AOR = 16.65, 95% CI = 6.17–24.98). The significant association between food insecurity and GDM risk was influenced by pre-pregnancy BMI, parity and rate of GWG at second trimester. Food insecure women with parity ≥ 2 (AOR = 4.21, 95% CI = 1.98–8.92), overweight/obese BMI prior to pregnancy (AOR = 12.11, 95% CI = 6.09–24.10) and excessive rate of GWG in the second trimester (AOR = 9.66, 95% CI = 4.27–21.83) were significantly more likely to develop GDM compared to food secure women. Food insecurity showed strong association with GDM risk in that the association was influenced by maternal biological and physical characteristics. Multipronged interventions may be necessary for food insecure pregnant women who are not only at risk of overweight/obesity prior to pregnancy but also may have excessive gestational weight gain, in order to effectively reduce GDM risk.

Trends in prevalence of gestational diabetes mellitus in Zhejiang Province, China, 2016-2018

Background

Limited population-based studies have investigated the secular trend of prevalence of gestational diabetes mellitus (GDM) in mainland China. Therefore, this study aimed to estimate the prevalence of GDM and time trends in Chinese female population.

Methods

Based on Diabetes Surveillance System of Zhejiang Province, 97,063 diagnosed GDM cases aged 20–50 years were identified from January 1, 2016 to December 31, 2018. Annual prevalence, prevalence rate ratios (PRRs) and average annual percentage change with their 95% confidence intervals (CIs) were reported.

Results

The age-standardized overall prevalence of GDM was reported to be 7.30% (95% CI 7.27–7.33%); 9.13% (95% CI 9.07–9.19%) in urban areas and 6.24% (95% CI 6.21–6.27%) in rural areas. Compared with 20–24 years age group, women in advanced age groups (25–50 years) were at higher risk for GDM (PRRs ranged from 1.37 to 8.95 and the 95% CIs did not include the null). Compared with rural areas, the risk for GDM was higher in urban areas (PRR: 1.69, 95% CI 1.67–1.72). The standardized annual prevalence increased from 6.02% in 2016 to 7.94% in 2018, with an average annual increase of 5.48%, and grew more rapidly in rural than urban areas (11.28% vs. 0.00%).

Conclusions

This study suggested a significant increase in the prevalence of GDM among Chinese female population in Zhejiang province during 2016–2018, especially in women characterized by advanced age and rural areas.

Maternal and umbilical cord blood subfatin and spexin levels in patients with gestational diabetes mellitus

Subfatin and spexin are two novel adipokines implicated in glucose homeostasis. This study was designed to investigate changes in blood subfatin and spexin levels during gestational diabetes mellitus (GDM) and childbirth, and define the mechanisms of these hormones in the physiopathology of GDM. A total of 60 pregnant women, comprising 30 diagnosed with GDM and 30 with normal gestation, were included in the study. The diagnosis of GDM was made through a 75-g oral glucose tolerance test (OGTT) administered between 24 and 28 weeks of pregnancy. The amounts of subfatin, spexin, and insulin were measured in blood samples by enzyme-linked immunosorbent assays; lipid profiles, glucose, and other biochemical parameters were measured by using an autoanalyzer. Levels of subfatin and spexin were significantly higher in blood samples drawn at baseline (before OGTT) in mothers with GDM compared to those with normal gestation. Similar observations were made in maternal and cord blood sampled at the end of pregnancy. However, at delivery, the increase in subfatin and spexin concentrations observed at baseline was abrogated in both groups of pregnant women, although levels in mothers with GDM were comparatively higher. These results show that levels of subfatin and spexin increased because of GDM and suggest that these hormones could be potential biomarkers for the diagnosis and management of GDM.

Trends and predictors of gestational diabetes mellitus in Chile

OBJECTIVE

To examine the temporal trends in gestational diabetes mellitus (GDM) prevalence in Chile, and to determine the main predictors of GDM.

METHODS

A secondary analysis was conducted of all birth records at Hospital Dr. Sótero del Río, Chile, from January 1, 2002, to December 31, 2015. We excluded those women with pre-existing type 2 diabetes, those with missing data, and those with unlikely data. GDM was defined as fasting glucose levels >5.55 mmol/L [>100 mg/dL] or >7.77 mmol/L [>140 mg/dL] 2 hours after glucose load in the oral glucose tolerance test. Potential predictors were selected based on prior research and ease of evaluation.

RESULTS

From the original database of 100 758 records, 86 362 women were included in the final cohort. The mean GDM prevalence was 7.6% (95% CI [confidence interval] 7.5%-7.8%), increasing from 4.4% (95% CI 4.0%-4.9%) in 2002 to 13.0% (95% CI 12.0%-13.9%) in 2015. Age, education, marital status, parity, family history of type 2 diabetes, personal history of GDM, hypertension and pre-eclampsia, alcohol consumption, smoking, and pre-gestational nutritional status performed well in the prediction of GDM.

CONCLUSION

One out of eight Chilean pregnant women of medium- to low socio-economic status were found to develop GDM. We identified a set of easy-to-capture predictors in the primary health care system that may allow for the early identification of women at high-risk for the development of GDM.