Factors Associated with Gestational Diabetes Mellitus: A Meta-Analysis

Women's perspectives on mHealth behavior change interventions for the management of overweight, obesity, or gestational diabetes: A qualitative meta-synthesis

mHealth interventions play an increasingly important role in health behavior change for gestational diabetes or peripartum obesity management. This qualitative systematic review and meta-synthesis aims to explore women's perceptions of mHealth behavior change interventions for gestational diabetes and/or overweight/obesity management during pregnancy and the postpartum period. Cumulative Index of Nursing and Allied Health Literature (CINAHL), Cochrane, Excerpta Medica Database (EMBASE), Medical Literature Analysis and Retrieval System Online (MEDLINE), and Psychological Information Database (PsycINFO) databases were searched using a Sample, Phenomenon of Interest, Design, Evaluation and Research type (SPIDER) concept framework through to February 2024. Included studies were quality assessed using the Critical Appraisal Skills Programme checklist. Study findings were evaluated using reflexive thematic analysis and GRADE-Confidence in the Evidence from Reviews of Qualitative Research (CERQual) checklist. We identified 29 studies, representing 604 women's views from one upper middle-income and nine high-income countries. Two themes were generated: mHealth as a supportive tool; and mHealth as a personalizable tool. Women highlighted the importance of self-monitoring, information trustworthiness, peer support, motivational tools (goal setting, risk awareness, and problem solving) and convenience in achieving behavior change using mHealth technology. They suggest mHealth programs incorporate these elements to support user engagement and improved health outcomes. Understanding what women want as mHealth users is particularly important for effective interventions in gestational diabetes, weight management, and chronic disease prevention. Creating a better, more woman-centered experience by addressing central engagement issues should result in improved maternal health outcomes.

Epidemiology and management of gestational diabetes

Gestational diabetes is defined as hyperglycaemia first detected during pregnancy at glucose concentrations that are less than those of overt diabetes. Around 14% of pregnancies globally are affected by gestational diabetes; its prevalence varies with differences in risk factors and approaches to screening and diagnosis; and it is increasing in parallel with obesity and type 2 diabetes. Gestational diabetes direct costs are US$1·6 billion in the USA alone, largely due to complications including hypertensive disorders, preterm delivery, and neonatal metabolic and respiratory consequences. Between 30% and 70% of gestational diabetes is diagnosed in early pregnancy (ie, early gestational diabetes defined by hyperglycaemia before 20 weeks of gestation). Early gestational diabetes is associated with worse pregnancy outcomes compared with women diagnosed with late gestational diabetes (hyperglycaemia from 24 weeks to 28 weeks of gestation). Randomised controlled trials show benefits of treating gestational diabetes from 24 weeks to 28 weeks of gestation. The WHO 2013 recommendations for diagnosing gestational diabetes (one-step 75 gm 2-h oral glucose tolerance test at 24-28 weeks of gestation) are largely based on the Hyperglycemia and Adverse Pregnancy Outcomes Study, which confirmed the linear association between pregnancy complications and late-pregnancy maternal glycaemia: a phenomenon that has now also been shown in early pregnancy. Recently, the Treatment of Booking Gestational Diabetes Mellitus (TOBOGM) trial showed benefit in diagnosis and treatment of early gestational diabetes for women with risk factors. Given the diabesity epidemic, evidence for gestational diabetes heterogeneity by timing and subtype, and advances in technology, a life course precision medicine approach is urgently needed, using evidence-based prevention, diagnostic, and treatment strategies.

The role of machine learning algorithms in detection of gestational diabetes; a narrative review of current evidence

Gestational Diabetes Mellitus (GDM) poses significant health risks to mothers and infants. Early prediction and effective management are crucial to improving outcomes. Machine learning techniques have emerged as powerful tools for GDM prediction. This review compiles and analyses the available studies to highlight key findings and trends in the application of machine learning for GDM prediction. A comprehensive search of relevant studies published between 2000 and September 2023 was conducted. Fourteen studies were selected based on their focus on machine learning for GDM prediction. These studies were subjected to rigorous analysis to identify common themes and trends. The review revealed several key themes. Models capable of predicting GDM risk during the early stages of pregnancy were identified from the studies reviewed. Several studies underscored the necessity of tailoring predictive models to specific populations and demographic groups. These findings highlighted the limitations of uniform guidelines for diverse populations. Moreover, studies emphasised the value of integrating clinical data into GDM prediction models. This integration improved the treatment and care delivery for individuals diagnosed with GDM. While different machine learning models showed promise, selecting and weighing variables remains complex. The reviewed studies offer valuable insights into the complexities and potential solutions in GDM prediction using machine learning. The pursuit of accurate, early prediction models, the consideration of diverse populations, clinical data, and emerging data sources underscore the commitment of researchers to improve healthcare outcomes for pregnant individuals at risk of GDM.

Gestational Diabetes Mellitus Risk Factors in Pregnant Women Attending Public Health Institutions in Ethiopia's Sidama Region: An Unmatched Case-Control Study

Background

Gestational diabetes mellitus (GDM), a chronic condition leading to glucose intolerance during pregnancy, is common in low- and middle-income countries, posing health risks to both the mother and fetus. Limited studies have been done in Ethiopia, especially using WHO's 2013 universal screening criteria. Therefore, this study aimed to evaluate the risk factors linked to GDM in women attending antenatal (ANC) clinics in Hawassa town public health institutions, located in the Sidama regional state of Ethiopia.

Methods

An Unmatched case-control study was carried out in Ethiopia's Sidama Region from April 1st to June 10th, 2023, involving 510 pregnant women. The Oral Glucose Tolerance Test (OGTT) was utilized for universal screening and diagnosing GDM based on the updated 2013 WHO diagnostic criteria. Data analysis included descriptive and analytical statistics, with variables having p-values below 0.1 deemed suitable for bivariate analysis. Statistical significance was assessed using the adjusted odds ratio (AOR) with a 95% confidence interval and a p-value < 0.05.

Results

The study involved 633 participants (255 cases and 378 controls), resulting in a 100% response rate, with women having an average age of 29.03 years.Variables such as: age at first conception (AOR=0.97, P=0.01, 95% CI (0.95,0.99)), urban residency (AOR=1.66, P<0.01, 95% CI(01.14,2.40)), widowed marital status (AOR=0.30, P=0.02, 95% CI (0.30,0.90)), parity (AOR=1.10, P<0.01, 95% CI (1.03,1.17)), history of stillbirth (AOR=1.15, P=0.03, 95% CI(1.04,2.30)), and previous cesarean section (AOR=1.86, P=0.01, 95% CI (1.13,2.66)) were identified as independent factors associated with GDM.

Conclusion

The study concluded that factors like age at first conception, place of residence, marital status, parity, history of Caesarian section, and stillbirth were independently associated with GDM. Surprisingly, upper arm circumference (MUAC), a proxy for pre-gestational BMI, was not identified as a risk factor for GDM. It is recommended that healthcare providers conduct comprehensive GDM risk assessments in pregnant women to identify and address risk factors, and propose specific screening and intervention strategies.

Temporal Trends in Gestational Diabetes Mellitus and Associated Risk Factors in Ontario, Canada, 2012-2020: A Population-Based Cohort Study

OBJECTIVES

The prevalence of gestational diabetes mellitus (GDM) has been increasing globally over recent decades; however, underlying reasons for the increase remain unclear. We analyzed trends in GDM rates and evaluated risk factors associated with the observed trends in Ontario, Canada.

METHODS

We conducted a retrospective population-based cohort study using the Better Outcomes Registry and Network Ontario, linked with the Canadian Institute for Health Information Discharge Abstract Database. All pregnant individuals who had a singleton hospital delivery from 1 April 2012 to 31 March 2020 were included. We calculated rates and 95% CIs for GDM by year of delivery and contrasted fiscal year 2019/20 with 2012/13. Temporal trends in GDM were quantified using crude and adjusted risk ratios by modified Poisson regression. We further quantified the temporal increase attributable to changes in maternal characteristics by decomposition analysis.

RESULTS

Among 1 044 258 pregnant individuals, 82 896 (7.9%) were diagnosed with GDM over the 8 years. GDM rate rose from 6.1 to 10.4 per 100 deliveries between fiscal years 2012/13 and 2019/20. The risk of GDM in 2019/20 was 1.53 times (95% CI 1.50-1.56) higher compared with 2012/13. 27% of the increase in GDM was due to changes in maternal age, 8 BMI, and Asian ethnicity.

CONCLUSIONS

The GDM rate has been consistently increasing in Ontario, Canada. The contribution of increasing maternal age, pre-pregnancy obesity, and Asian ethnicity to the recent increase in GDM is notable. Further investigation is required to better understand the contributors to increasing GDM.

Effect of different nutrients on blood glucose, inflammatory response and oxidative stress in gestational diabetes mellitus: a network meta-analysis

We searched PubMed, Web of Science, Embase, The Cochrane Library, China Biomedical Literature Database and other databases from inception to June 2023. The included studies were randomised controlled trials (RCT). The studies were screened by four authors, divided into two independent pairs. A total of eighteen studies were included, including 1362 patients, involving twelve intervention measures. The different nutrients had a significant effect on improving blood glucose, reducing inflammation levels and reducing oxidative stress compared with placebo (P < 0.05). Cumulative probability ranking showed that vitamin A + vitamin D + vitamin E ranked first in lowering fasting blood glucose (standardised mean difference (SMD) = 41.30, 95 % CI (2.07, 825.60)) and postprandial 2-h blood glucose (SMD = 15.19, 95 % CI (4.16, 55.53)). In terms of insulin resistance index, the first highest probability ranking is vitamin D (SMD = 5.12, 95 % CI (0.76, 34.54)). In terms of reducing the high-sensitivity C-reactive protein level, the first in probability ranking is VE (SMD = 2.58, 95 % CI (1.87,3.55)). The results of cumulative probability ranking showed that Mg + Zn + Ca + VD ranked first in reducing TNF-α (SMD = 1.90, 95% CI (0.40, 9.08)) and IL-6 (SMD = 1.83, 95 % CI (0.37, 9.12)). In terms of reducing malondialdehyde levels, the first ranked probability is VB1 (SMD = 4.99, 95 % CI (1.85, 13.46)). Cumulative probability ranking results showed that Ca + VD ranked first in reducing total antioxidant capacity (SMD = 0.66,95 % CI (0.38, 1.15)) and glutathione (SMD = 1.39, 95 % CI (0.43, 4.56)). In conclusion, nutritional interventions have significant effects on improving blood glucose, inflammatory levels and oxidative stress in patients with gestational diabetes. Due to the high uncertainty in the results and differences in the number and quality of studies included, the reliability of the conclusions still needs to be validated by conducting large-sample, high-quality RCT studies.

Diabetic and hypertensive disorders following early pregnancy loss: a systematic review and meta-analysis

Background

Spontaneous and induced abortions are common outcomes of pregnancy. There is inconsistent evidence of an association between early pregnancy loss and subsequent diabetic and hypertensive disorders in women. This systematic review and meta-analysis evaluated evidence on the risk of the subsequent development of pregnancy and non-pregnancy related diabetic and hypertensive disorders in women who experienced an early pregnancy loss.

Methods

Systematic searches were conducted in seven electronic databases (CINAHL Plus, Ovid/EMBASE, Ovid/MEDLINE, ProQuest, PubMed, Scopus, and Web of Science) from inception to 22nd December 2023. Studies were included if they reported an exposure of spontaneous abortion (SAB), induced abortion (IA) or recurrent pregnancy loss (RPL) with an outcome of gestational diabetes mellitus, pre-eclampsia, gestational hypertension, and non-pregnancy related diabetic and hypertensive disorders. Risk of bias was assessed using Risk of Bias Instrument for Non-Randomized Studies of Exposures (ROBINS-E). Random effects meta-analysis was used to pool odds of developing diabetic and hypertensive disorders following an early pregnancy loss. This study is registered with PROSPERO (CRD42022327689).

Findings

Of 20,176 records, 60 unique articles were identified for full-text review and 52 met the inclusion criteria, representing a total population of 4,132,895 women from 22 countries. Thirty-five studies were suitable for meta-analysis, resulting in a pooled odds ratio (OR) of 1.44 (95% confidence interval (CI) 1.23-1.68) for gestational diabetes mellitus following a prior SAB and a pooled OR of 1.06 (95% CI 0.90-1.26) for pre-eclampsia following a prior SAB. RPL increased the odds of developing pre-eclampsia (OR 1.37 95% CI 1.05-1.79). There was no association between IA and diabetic and hypertensive disorders.

Interpretation

A prior SAB was associated with increased odds of gestational diabetes mellitus, but not pre-eclampsia. However, women who experienced RPL had an increased risk of subsequent pre-eclampsia. Future research is required to establish evidence for an association between early pregnancy loss with non-pregnancy related diabetic and hypertensive disorders.

Funding

National Health and Medical Research Council.

Epidemiology of hyperglycemia during pregnancy in Ethiopia: prevalence, associated factors, and feto-maternal outcomes: systematic review and meta-analysis

BACKGROUND

Hyperglycemia in pregnancy (HIP) is a significant medical complication affecting pregnant women globally and is considered a public health burden due to the negative outcomes it can cause for both mother and infant. The aim of this systematic review and meta-analysis was to examine the prevalence, risk factors, and feto-maternal outcomes of HIP in Ethiopia.

METHODS

To gather relevant information for this study, both published and unpublished studies were searched for in several major databases, including PubMed, Embase, HINARI, Web of Science direct, and Google Scholar, as well as other sources. The Joanna Briggs Institute (JBI) tool was used to evaluate the methodological quality of the findings from these studies. Data was then extracted and summarized using a template in Microsoft Excel software, and the extracted data was analyzed using Stata software version 16.0. If significant heterogeneity was found between studies, subgroup analyses were conducted to further examine the data.

RESULT

Eighteen studies were included in this systematic review and meta-analysis, involving a total sample size of 50,816 pregnant women in Ethiopia. The prevalence of HIP among pregnant women varied considerably across the primary studies, ranging from 0.4 to 26.2%. The pooled prevalence of HIP among pregnant women in Ethiopia was found to be 6.9% (95% C 2.2-11.6). Pregnant women with a family history of diabetes had 2.5 times higher odds of developing HIP compared to those without a family history of diabetes (OR = 2.49; 95% CI = 2.02, 2.96). However, there was no significant association found between HIP and maternal obesity (OR 2.31, 95% CI = 0.85, 3.78) or previous history of abortion (OR 3.89; 95% CI 0.85, 6.94). The common fetal outcomes associated with HIP were admission to the intensive care unit (46.2; 95% CI 27.4, 65.1), macrosomia (27.3%; 95% CI 9.4%, 45.1%), and preterm birth (16.9; 95% CI 12.5, 21.3). Additionally, hypertensive disorders of pregnancy (28.0%; 95% CI 15.2, 40.8) and operative delivery (51.4%; 95% CI 35.9, 66.8) were more common among women with HIP in Ethiopia.

CONCLUSION

Although there was some variation between studies, the meta-analysis revealed that approximately seven out of 100 pregnant women in Ethiopia had HIP. A family history of diabetes was found to be a significant predictor of HIP in Ethiopia. Additionally, HIP was associated with various serious adverse outcomes for both mothers and infants in Ethiopia. These findings highlight the need for national guidelines to ensure that pregnant women are uniformly screened for HIP.

Genetic and inflammatory factors underlying gestational diabetes mellitus: a review

Gestational diabetes mellitus (GDM) poses a significant global health concern, impacting both maternal and fetal well-being. Early detection and treatment are imperative to mitigate adverse outcomes during pregnancy. This review delves into the pivotal role of insulin function and the influence of genetic variants, including SLC30A8, CDKAL1, TCF7L2, IRS1, and GCK, in GDM development. These genetic variations affect beta-cell function and insulin activity in crucial tissues, such as muscle, disrupting glucose regulation during pregnancy. We propose a hypothesis that this variation may disrupt zinc transport, consequently impairing insulin production and secretion, thereby contributing to GDM onset. Furthermore, we discussed the involvement of inflammatory pathways, such as TNF-alpha and IL-6, in predisposing individuals to GDM. Genetic modulation of these pathways may exacerbate glucose metabolism dysregulation observed in GDM patients. We also discussed how GDM affects cardiovascular disease (CVD) through a direct correlation between pregnancy and cardiometabolic function, increasing atherosclerosis, decreased vascular function, dyslipidemia, and hypertension in women with GDM history. However, further research is imperative to unravel the intricate interplay between inflammatory pathways, genetics, and GDM. This understanding is pivotal for devising targeted gene therapies and pharmacological interventions to rectify genetic variations in SLC30A8, CDKAL1, TCF7L2, IRS1, GCK, and other pertinent genes. Ultimately, this review offers insights into the pathophysiological mechanisms of GDM, providing a foundation for developing strategies to mitigate its impact.

Non-hypertensive gestational diabetes mellitus: Placental histomorphology and its association with perinatal outcomes

INTRODUCTION

Gestational diabetes mellitus (GDM) exerts a great impact on the placenta and reflects changes on placentas both morphological and functionally. The aims of this study are to evaluate the prevalence of placental histopathological lesions in pregnancies complicated by GDM compared to gestational age-matched controls, and their association with maternal and fetal complications.

METHODS

Fifty-four singleton GDM-complicated pregnancies were recruited and compared to 33 consecutive normal pregnancies. Two pathologists, blinded to all clinical data, reviewed and evaluated all histological samples of the placentas in accordance with Amsterdam criteria. Relevant demographic, clinical data and primary birth outcomes were recorded.

RESULTS

A myriad of histomorphological abnormalities, including chronic inflammation (n = 9/54, p = 0.031), histological chorioamnionitis (n = 23/54, p < 0.001), umbilical/chorionic vasculitis (n = 9/54, p = 0.031), changes related to maternal vascular malperfusion (n = 22/54, p = 0.003), chorangiosis (n = 10/54, p = 0.046) and villous dysmaturity (n = 9/54, p = 0.012) were observed more frequently in the GDM placentas compared to the controls. Additionally, GDM significantly increased the risk of fetal complications, including macrosomia/fetal growth restriction (n = 13/54, p = 0.004).

DISCUSSION

Histoarchitectural abnormalities were observed more frequently in placentas of GDM pregnancies compared to the controls. Our findings support the hypothesis that diabetic-induced damage in the placental function may be associated with the increased in fetal growth disorders in GDM-complicated pregnancies.

Synergistic effect between pre-pregnancy smoking and assisted reproductive technology on gestational diabetes mellitus in twin pregnancies

AIM

Women with twin pregnancies have an increased risk of gestational diabetes mellitus (GDM). Assisted reproductive technology (ART) and pre-pregnancy smoking were both associated with GDM. However, the relationships between pre-pregnancy smoking and ART and GDM in twin pregnancies were unclear. Herein, this study aims to explore the roles of pre-pregnancy smoking and ART in GDM among women with twin pregnancies.

METHODS

Data of women with twin pregnancies were extracted from the National Vital Statistics System (NVSS) database in 2016-2020 in this retrospective cohort study. Univariate and multivariate logistic regression analyses were used to explore the associations between pre-pregnancy smoking and ART and GDM in women with twin pregnancies. The evaluation index was odds ratios (ORs) with 95% confidence intervals (CIs). Subgroup analysis of age and BMI was also performed.

RESULTS

A total of 19,860 (9.15%) women had GDM in our study. After adjusting for covariates, we found that receiving ART was associated with high odds of GDM [OR = 1.41, 95% CI (1.34-1.48)], while pre-pregnancy smoking combined with ART was associated with higher odds of GDM [OR = 1.66, 95% CI (1.14-2.42)]. In addition, these relationships were also found in women who aged ≥ 35 years old [OR = 1.98, 95% CI (1.14-3.44)] and with BMI ≥ 25 kg/m2 [OR = 1.69, 95% CI (1.11-2.55)].

CONCLUSION

Pre-pregnancy smoking may further increase the risk of GDM from ART in women with twin pregnancies. In clinical, women who are ready to receive ART treatment are recommend to quit smoking, which may reduce the risk of GDM and prevent adverse pregnancy outcomes.

Association of MST1 in the First Trimester of Pregnancy with Gestational Diabetes Mellitus and Adverse Pregnancy Outcomes

Aim

We investigate the association of mammalian sterile line 20-like kinase 1 (MST1) in the first trimester with the risks of gestational diabetes mellitus (GDM) and adverse pregnancy outcomes.

Methods

Pregnancies were recruited during their first antenatal care visit between 8 and 12 gestational weeks. These pregnancies underwent an oral glucose tolerance test between 24 and 28 gestational weeks and were followed up until delivery. Serum MST1 levels at 8-12 gestational weeks and 24-28 gestational weeks were measured using an enzyme-linked immunosorbent assay (ELISA) kit. Logistic regression models were used to evaluate the association between MST1 levels in the first trimester and the risks of GDM and adverse pregnancy outcomes.

Results

This cohort study enrolled a total of 231 pregnancies. GDM was present in 42 (18.18%) women. Compared to the normal glucose tolerance (NGT) group, the GDM group had higher levels of FPG, HOMA-IR, and MST1 both in the first and second trimesters, but had lower HOMA-β levels only in the second trimester. Then participants were classified according to the median MST1 value in the first trimester. Incidences of GDM, composite adverse pregnancy outcomes, preterm birth, and macrosomia increased in women with higher MST1 values. Serum MST1 in the first trimester was correlated with FPG, 1hr PG, 2hr PG, and HOMA-IR, while inversely correlated with HOMA-β in the second trimester. Furthermore, after adjusting for traditional risk factors, women with higher first-trimester MST1 values had greater odds of GDM, composite adverse pregnancy outcomes, preterm birth, and macrosomia (aOR 2.276, P=0.030; aOR 2.690, P=0.003; aOR 3.210, P=0.048; aOR 5.488, P=0.010).

Conclusion

Elevated levels of MST1 in the first trimester of pregnancies are associated with increased risks of GDM and adverse pregnancy outcomes.

Blood manganese level and gestational diabetes mellitus: a systematic review and meta-analysis

BACKGROUND

Previous studies evaluating the relationship between blood manganese (Mn) level and gestational diabetes mellitus (GDM) in pregnant women showed inconsistent results. A systematic review and meta-analysis was therefore performed to investigate the above association.

METHODS

Relevant observational studies were obtained by search of electronic databases including Medline, Embase, Cochrane Library and Web of Science from database inception to 10 March 2023. Two authors independently performed database search, literature identification and data extraction. A randomised-effects model was selected to pool the data by incorporating the influence of potential heterogeneity. Subgroup analysis was performed to evaluate the influence of study characteristics on the results of the meta-analysis.

RESULTS

Six datasets from five observational studies, involving 91,249 pregnant women were included in the meta-analysis. Among the participants, 3597 (3.9%) were diagnosed as GDM. Overall, pooled results showed that a high blood level of Mn was associated with a higher risk of GDM (compared between women with highest versus lowest category blood Mn, odds ratio: 1.31, 95% confidence interval: 1.19-1.44, p < .001) with no significant heterogeneity (p for Cochrane Q-test = 0.93, I2 = 0%). Subgroup analyses according to study design, mean maternal age, matrix or methods for measuring blood Mn, and the incidence of GDM also showed consistent results (p for subgroup difference all >.05).

CONCLUSIONS

Results of the meta-analysis suggest that a high blood Mn level may be a risk factor of GDM in pregnant women. Studies are needed to determine the underlying mechanisms, and to investigate if the relationship between blood Mn level and GDM is dose-dependent.

Smoking during pregnancy and gestational diabetes mellitus: a systematic review and meta-analysis

PURPOSE

To investigate whether maternal cigarette smoking during pregnancy is a risk factor for developing GDM.

METHODS

MEDLINE, Scopus, CENTRAL and Google Scholar databases were searched from inception to December 2022 to identify eligible original articles. A systematic review and meta-analysis (weighted data, random-effects model) were performed. The primary outcome was the development of GDM in pregnant women. The results were expressed as odds ratios (OR) with 95% confidence interval (CI) (inverse variance method). Subgroup analysis was planned according to the maternal smoking status and GDM diagnostic criteria. Statistical heterogeneity was checked with the Chi-squared (Chi2) test and the I2 index was used to quantify it. The studies were evaluated for publication bias.

RESULTS

Thirty-five studies, including 23,849,696 pregnant women, met the inclusion criteria. The pooled OR of smoking during pregnancy compared with non-smoking (never smokers and former smokers) was 1.06 (95% CI 0.95-1.19), p = 0.30; I2 = 90%; Chi2 = 344; df=34; p < 0.001. Subgroup analysis was performed according to the two-step Carpenter-Coustan diagnostic criteria, due to the high heterogeneity among the other applied methods. The pooled OR for the Carpenter-Coustan subgroup was 1.19 (95% CI 0.95-1.49), p = 0.12; I2 = 63%; Chi2 = 27; df=10; p < 0.002. Further subgroup analysis according to maternal smoking status was not performed due to missing data.

CONCLUSION

There is no evidence to support an association between maternal cigarette smoking during pregnancy and the risk for GDM. Universally accepted diagnostic criteria for GDM must be adopted to reduce heterogeneity and clarify the association between smoking and GDM.

Association of triglyceride-glucose index levels with gestational diabetes mellitus in the US pregnant women: a cross-sectional study

Objective

This investigation aimed to assess the correlation between the triglyceride-glucose (TyG) index and gestational diabetes mellitus (GDM) in pregnant women in the United States.

Methods

We calculated the TyG index utilizing data from pregnant women who participated in the National Health and Nutrition Examination Survey (NHANES) through 1999 to March 2020, and then employed multivariate logistic regression, smoothed curve fitting, and subgroup analysis to investigate the association between the TyG index and gestational diabetes during pregnancy.

Results

Logistic regression models revealed a positive association between the TyG index and GDM, remaining significant even after adjusting for all confounding variables (OR=3.43, 95% CI: 1.20-9.85, P = 0.0216). Subgroup analysis demonstrated consistent correlations and showed that there is no difference in the TyG index among first trimester subgroup. The TyG index had limited diagnostic efficacy for GDM (AUC=0.57, 95% CI: 0.50-0.63).

Conclusion

The TyG index correlates positively with the GDM, however its diagnostic efficacy is limited. Further research on the TyG index as an early predictor of GDM is required.

Previous traumatic brain injury is associated with an increased odds for gestational diabetes: a nationwide register-based cohort study in finland

AIMS

Despite recent findings that traumatic brain injury (TBI) is a possible risk factor for type 2 diabetes (DM2) and that a strong association exists between gestational diabetes (GDM) and the risk for the development of DM2, no previous studies have investigated the effects of TBI on the risk for the development of GDM. Therefore, this study aims to determine the possible association between a previous traumatic brain injury and later gestational diabetes.

METHODS

In this retrospective register-based cohort study, data from the National Medical Birth Register were combined with data from the Care Register for Health Care. Women who had sustained a TBI before pregnancy were included in the patient group. Women who had sustained previous fractures of the upper extremity, pelvis, or lower extremity were included in the control group. A logistic regression model was used to assess the risk for the development of GDM during pregnancy. Adjusted odds ratios (aOR) with 95% confidence intervals between the groups were compared. The model was adjusted by prepregnancy body mass index (BMI) and maternal age during pregnancy, the use of in vitro fertilization (IVF), maternal smoking status, and multiple pregnancies. The risk for the development of GDM during different periods following the injury (0-3 years, 3-6 years, 6-9 years, and 9+ years) was calculated.

RESULTS

In total, a 75 g 2-h oral glucose tolerance test (OGTT) was performed on 6802 pregnancies of women who had sustained a TBI and on 11 717 pregnancies of women who sustained fractures of the upper extremity, pelvis, or lower extremity. Of these, 1889 (27.8%) pregnancies were diagnosed with GDM in the patient group and 3117 (26.6%) in the control group. The total odds for GDM were higher after TBI compared to the other traumas (aOR 1.14, CI 1.06-1.22). The odds were highest at 9 + years after the injury (aOR 1.22, CI 1.07-1.39).

CONCLUSION

The total odds for the development of GDM after TBI were higher when compared to the control group. Based on our findings, more research on this topic is warranted. Moreover, a history of TBI should be considered a possible risk factor for the development of GDM.

Passive smoking and risk of gestational diabetes mellitus: A systematic review and meta-analysis

INTRODUCTION

Pregestational smoking increases the risk of gestational diabetes mellitus (GDM) and is a common health problem during pregnancy, with its incidence on the rise worldwide, especially in China. This study is a meta-analysis of passive smoking as a risk factor associated with GDM.

METHODS

Two independent reviewers searched passive smoking and the risk of GDM in PubMed, Medline, Web of Knowledge, Science Direct, China National Knowledge Internet (CNKI) and Wanfang databases (up to May 2023). The authors extracted the study data independently and used the Newcastle-Ottawa scale (NOS) to evaluate the quality of the included articles. A meta-analysis was conducted using a random effects model depending on the size of the heterogeneity. Begg's and Egger's tests were performed to assess publication bias.

RESULTS

The overall relative risk for GDM caused by passive smoking was 1.47 (95% CI: 1.31-1.64), with moderate heterogeneity between studies (I2=41.7%, p=0.079). Subgroup and sensitivity analyses were stable, and no evidence of publication bias was found.

CONCLUSIONS

Passive smoking is a risk factor for GDM, even in those who are not active smokers. To eliminate the effects of other confounding factors, larger prospective cohort studies are required to clarify the relationship between passive smoking and the occurrence of GDM.

The Effect of Timing and Methods for the Diagnosis of Gestational Diabetes Mellitus on Obstetric Complications

Aim. To compare the impact of the time and method of diagnosis on gestational diabetes mellitus (GDM) in women who gave birth at the Hospital of the Lithuanian University of Health Sciences (LUHS) Kauno klinikos. Methods. A retrospective study was performed using data from the Department of Obstetrics and Gynecology of the LUHS Birth Registry to analyze the data of women who gave birth and had GDM in 2020-2021. The subjects were divided based on the type of diagnosis: GDM was diagnosed either at the first antenatal visit when fasting plasma glycemia (FPG) was ≥5.1 mmol/L (early diagnosis group) or after OGTT at 24 + 0 - 28 + 6 weeks of gestation when at least one pathological glycemic index was observed: fasting glycemia 5.1-6.9 mmol/L or 1-h glycemia ≥10.0 mmol/L or 2 h glycemia 8.5-11.0 mmol/L (late diagnosis group). The results were processed using IBM SPSS. Results. The early diagnosis group had 1254 (65.7%) women, the late diagnosis group had 654 (34.3%). More primigravida women were in the late diagnosis group (p = 0.017) while more multigravida were in the early diagnosis group (p = 0.033). The early diagnosis group had more obese women (p = 0.001), including those with a BMI > 40 (p = 0.001). In the early diagnosis group, GDM was more frequently diagnosed in women who gained <11 kg (p = 0.005), while in the late diagnosis group->16 kg (p = 0.001). FPG was higher in the early diagnosis group (p = 0.001). Glycemia was more commonly corrected with lifestyle changes in the late diagnosis group (p = 0.001), and with additional insulin therapy in the early diagnosis group (p = 0.001). Polyhydramnios and preeclampsia were more common in the late diagnosis group (p = 0.027 and p = 0.009). There were more large-for-gestational-age neonates in the late diagnosis group (p = 0.005). Macrosomia was more common in the late diagnosis group (p = 0.008). Conclusions. GDM is more commonly diagnosed with OGTT in primigravida women. Higher pregestational weight and BMI has an impact on the early diagnosis of GDM and need for insulin therapy with lifestyle changes. Late diagnosis of GDM is connected with obstetric complications.

A systematic review and meta-analysis of participant characteristics in the prevention of gestational diabetes: a summary of evidence for precision medicine

Background and aims

Precision prevention involves using the unique characteristics of a particular group to determine their responses to preventive interventions. This study aimed to systematically evaluate the participant characteristics associated with interventions in gestational diabetes mellitus (GDM) prevention.

Methods

We searched MEDLINE, EMBASE, and Pubmed to identify lifestyle (diet, physical activity, or both), metformin, myoinositol/inositol and probiotics interventions of GDM prevention published up to May 24, 2022.

Results

From 10347 studies, 116 studies (n=40940 women) were included. Physical activity resulted in greater GDM reduction in participants with a normal body mass index (BMI) at baseline compared to obese BMI (risk ratio, 95% confidence interval: 0.06 [0.03, 0.14] vs 0.68 [0.26, 1.60]). Diet and physical activity interventions resulted in greater GDM reduction in participants without polycystic ovary syndrome (PCOS) than those with PCOS (0.62 [0.47, 0.82] vs 1.12 [0.78-1.61]) and in those without a history of GDM than those with unspecified history (0.62 [0.47, 0.81] vs 0.85 [0.76, 0.95]). Metformin interventions were more effective in participants with PCOS than those with unspecified status (0.38 [0.19, 0.74] vs 0.59 [0.25, 1.43]), or when commenced preconception than during pregnancy (0.22 [0.11, 0.45] vs 1.15 [0.86-1.55]). Parity, history of having a large-for-gestational-age infant or family history of diabetes had no effect.

Conclusions

GDM prevention through metformin or lifestyle differs according to some individual characteristics. Future research should include trials commencing preconception and provide results stratified by participant characteristics including social and environmental factors, clinical traits, and other novel risk factors to predict GDM prevention through interventions.

Plain language summary

Precision prevention involves using a group’s unique context to determine their responses to preventive interventions. This study aimed to evaluate the participant characteristics associated with interventions in GDM prevention. We searched medical literature databases to identify lifestyle (diet, physical activity), metformin, myoinositol/inositol and probiotics interventions. A total of 116 studies (n=40903 women) were included. Diet and physical activity interventions resulted in greater GDM reduction in participants without polycystic ovary syndrome (PCOS) and those without a history of GDM. Metformin interventions resulted in greater GDM reduction in participants with PCOS or when started during the preconception period. Future research should include trials starting in the preconception period, and provide results stratified by participant characteristics to predict GDM prevention through interventions.

Association between the history of abortion and gestational diabetes mellitus: A meta-analysis

PURPOSE

Gestational diabetes mellitus (GDM) is a common metabolic disease in pregnant women. The purpose of this study was to determine whether a history of abortion increases the risk of GDM by meta-analysis.

METHODS

A comprehensive literature search was conducted in nine databases of studies on the association between abortion history and GDM up to April 12, 2022. Fixed- or random-effects models were used to estimate the pooled odds ratio (OR) and 95% CI. The I square value (I²) was used to assess heterogeneity. Possible sources of heterogeneity were explored by conducting subgroup analysis and meta-regression. A sensitivity analysis was also performed for this meta-analysis. Publication bias was assessed by funnel plots and Egger's tests.

RESULTS

Thirty-one studies enrolling 311,900 subjects were included in this meta-analysis. The risk of GDM was higher in women who experienced abortion than in those who did not (OR = 1.41 95% CI: 1.28-1.55, I² = 66.8%). The risk of GDM increased with an increasing number of abortions (1 time: OR = 1.67, 95% CI = 1.26-2.22; 2 times: OR = 2.10, 95% CI = 1.26-3.49; ≥3 times: OR = 2.49, 95% CI = 1.24-5.01). Both spontaneous abortion (OR = 1.52, 95% CI = 1.30-1.78) and induced abortion (OR = 1.07, 95% CI = 1.03-1.11) were associated with an increased risk of GDM.

CONCLUSIONS

A history of abortion was associated with an increased risk of GDM in pregnant women, which may be a risk factor for predicting GDM.

Exploring psychosocial adaptation to pregnancy in women with gestational diabetes

Background: Gestational diabetes mellitus (GDM) is one of the most common medical complications of pregnancy. Diagnosis of GDM, that could be unexpected, may cause women to feel negative emotions such as fear, guilt, sadness, and loss of control and experience difficulties adapting to pregnancy.Objective: This study aimed to explore psychosocial adaptation to pregnancy in women with GDM.Methods: This observational cross-sectional study was conducted with women with GDM and healthy pregnant women who applied to the pregnancy and perinatology outpatient clinic of a university hospital. Groups were matched according to age, education level, and gestational week. The Prenatal Self-Evaluation Questionnaire (PSEQ) was used to collect data. Simple linear regression was performed to determine factors influenced psychosocial adaptation to pregnancy using average scores from the PSEQ.Results: Regression analysis indicated, GDM status (beta = -48.8, p ≤ 0.001) and smoking status during pregnancy (beta = 11.0, p = 0.032) influenced the total score of the PSEQ.Conclusions: Nurses are encouraged to develop a multifaceted nursing care model that considers the physical and psychosocial problems and to provide care to increase the psychosocial adaptation of women with GDM to pregnancy.

The effect of diet quality on the risk of developing gestational diabetes mellitus: A systematic review and meta-analysis

Objective

To examine the effect of diet quality on the risk of gestational diabetes mellitus.

Methods

This review included cohort and case-control studies reporting an association between diet quality and gestational diabetes mellitus. We searched PubMed, Cochrane Library, Web of Science, Embase, PsycINFO, CINAHL Complete, Chinese Periodical Full-text Database, China National Knowledge Infrastructure, Chinese Biomedical Literature Database, and China Wanfang Database for studies published from inception to November 18, 2022. The Newcastle-Ottawa Scale was used for quality assessment, and the overall quality of evidence was assessed using the GRADEpro GDT.

Results

A total of 19 studies (15 cohort, four case-control) with 108,084 participants were included. We found that better higher diet quality before or during pregnancy reduced the risk of developing gestational diabetes mellitus, including a higher Mediterranean diet (OR: 0.51; 95% CI: 0.30-0.86), dietary approaches to stop hypertension (OR: 0.66; 95% CI: 0.44-0.97), Alternate Healthy Eating Index (OR: 0.61; 95% CI: 0.44-0.83), overall plant-based diet index (OR: 0.57; 95% CI: 0.41-0.78), and adherence to national dietary guidelines (OR: 0.39; 95% CI:0.31-0.48). However, poorer diet quality increased the risk of gestational diabetes mellitus, including a higher dietary inflammatory index (OR: 1.37; 95% CI: 1.21-1.57) and overall low-carbohydrate diets (OR: 1.41; 95% CI: 1.22-1.64). After meta-regression, subgroup, and sensitivity analyses, the results remained statistically significant.

Conclusions

Before and during pregnancy, higher diet quality reduced the risk of developing gestational diabetes mellitus, whereas poorer diet quality increased this risk.

Systematic review registration

https://www.crd.york.ac.uk/PROSPERO/, identifier: CRD42022372488.

Prediction model for gestational diabetes mellitus using the XG Boost machine learning algorithm

OBJECTIVE

To develop the extreme gradient boosting (XG Boost) machine learning (ML) model for predicting gestational diabetes mellitus (GDM) compared with a model using the traditional logistic regression (LR) method.

METHODS

A case-control study was carried out among pregnant women, who were assigned to either the training set (these women were recruited from August 2019 to November 2019) or the testing set (these women were recruited in August 2020). We applied the XG Boost ML model approach to identify the best set of predictors out of a set of 33 variables. The performance of the prediction model was determined by using the area under the receiver operating characteristic (ROC) curve (AUC) to assess discrimination, and the Hosmer-Lemeshow (HL) test and calibration plots to assess calibration. Decision curve analysis (DCA) was introduced to evaluate the clinical use of each of the models.

RESULTS

A total of 735 and 190 pregnant women were included in the training and testing sets, respectively. The XG Boost ML model, which included 20 predictors, resulted in an AUC of 0.946 and yielded a predictive accuracy of 0.875, whereas the model using a traditional LR included four predictors and presented an AUC of 0.752 and yielded a predictive accuracy of 0.786. The HL test and calibration plots show that the two models have good calibration. DCA indicated that treating only those women whom the XG Boost ML model predicts are at risk of GDM confers a net benefit compared with treating all women or treating none.

CONCLUSIONS

The established model using XG Boost ML showed better predictive ability than the traditional LR model in terms of discrimination. The calibration performance of both models was good.

Miscarriage, stillbirth and the risk of diabetes in women: A systematic review and meta-analysis

AIMS

Whether women with a history of miscarriage or stillbirth have an increased risk of diabetes is inconclusive. We aimed to systematically assess the association between them.

METHODS

We searched PubMed, Web of Science and Scopus through November 2022. Random-effect model for meta-analysis was applied to calculate pooled odds ratios and corresponding 95 % confidence intervals (CIs) when heterogeneity was > 40 %.

RESULTS

Thirteen cohort studies and eight case-control studies with a total of 529,990 participants were included. Women ever experiencing a miscarriage had a 1.15-fold risk of non-gestational diabetes (95% CI: 1.02-1.28) and a 1.62-fold risk of gestational diabetes (95% CI: 1.32-1.98) compared to those never experiencing a miscarriage. Of them, women with three or more miscarriages had a 1.99-fold risk of non-gestational diabetes (95% CI: 1.36-2.91). The risk of non-gestational diabetes among women ever experiencing a stillbirth was 1.21 times compared with those never experiencing a stillbirth (95% CI: 1.03-1.41). Pooled results did not support a stable association between stillbirth and gestational diabetes risk (odds ratio:1.91, 95% CI: 1.00-3.64).

CONCLUSIONS

A history of miscarriage or stillbirth was associated with an increased risk of diabetes in women. Future studies are needed to explore whether prediabetic metabolic conditions contribute to this association.

Plasma Manganese Levels and Risk of Gestational Diabetes Mellitus: A Prospective Cohort Study

Manganese (Mn) intake has been found to be linked with risk of type 2 diabetes. However, the role of Mn in the development of gestational diabetes mellitus (GDM) remains to be investigated. This prospective study included pregnant women from the Tongji Maternal and Child Health Cohort. A total of 2327 participants with plasma specimens before 20 weeks were included. Among the pregnant women, 9.7% (225/2327) were diagnosed with GDM. After adjustment, pregnant women with the third and highest quartile of plasma Mn levels had 1.31-fold (RR, 2.31 [1.48, 3.61]) and 2.35-fold (RR, 3.35 [2.17, 5.17]) increased risk of GDM compared with those with the lowest quartile. A 1 standard deviation increment of ln-transformed plasma Mn levels (0.53 μg/L) was related to elevated risks of GDM with RRs of 1.28 [1.17, 1.40]. The positive associations between Mn and GDM remained consistent in all the subgroups. The weighted quantile sum index was significantly related to GDM (RR, 1.60 [1.37, 1.86]). The contribution of Mn (58.69%) to the metal mixture index was the highest related to GDM. Higher plasma Mn levels were found to be linked with elevated fasting and 2 h post-load blood glucose. This study revealed relationships of higher plasma Mn levels in early pregnancy and increased risk of GDM, suggesting that though essential, excess Mn in the body might be a potential important risk factor for GDM.

Effects of Probiotic Supplementation during Pregnancy on the Future Maternal Risk of Metabolic Syndrome

Probiotics are live microorganisms that induce health benefits in the host. Taking probiotics is generally safe and well tolerated by pregnant women and their children. Consumption of probiotics can result in both prophylactic and therapeutic effects. In healthy adult humans, the gut microbiome is stable at the level of the dominant taxa: Bacteroidetes, Firmicutes and Actinobacteria, and has a higher presence of Verrucomicrobia. During pregnancy, an increase in the number of Proteobacteria and Actinobacteria phyla and a decrease in the beneficial species Roseburia intestinalis and Faecalibacterium prausnitzii are observed. Pregnancy is a "window" to the mother's future health. The aim of this paper is to review studies assessing the potentially beneficial effects of probiotics in preventing the development of diseases that appear during pregnancy, which are currently considered as risk factors for the development of metabolic syndrome, and consequently, reducing the risk of developing maternal metabolic syndrome in the future. The use of probiotics in gestational diabetes mellitus, preeclampsia and excessive gestational weight gain is reviewed. Probiotics are a relatively new intervention that can prevent the development of these disorders during pregnancy, and thus, would reduce the risk of metabolic syndrome resulting from these disorders in the mother's future.

Novel Biomolecules in the Pathogenesis of Gestational Diabetes Mellitus 2.0

Gestational diabetes mellitus (GDM) has become a major public health problem and one of the most discussed issues in modern obstetrics. GDM is associated with serious adverse perinatal outcomes and long-term health consequences for both the mother and child. Currently, the importance and purposefulness of finding a biopredictor that will enable the identification of women with an increased risk of developing GDM as early as the beginning of pregnancy are highly emphasized. Both “older” molecules, such as adiponectin and leptin, and “newer” adipokines, including fatty acid-binding protein 4 (FABP4), have proven to be of pathophysiological importance in GDM. Therefore, in our previous review, we presented 13 novel biomolecules, i.e., galectins, growth differentiation factor-15, chemerin, omentin-1, osteocalcin, resistin, visfatin, vaspin, irisin, apelin, FABP4, fibroblast growth factor 21, and lipocalin-2. The purpose of this review is to present the potential and importance of another nine lesser known molecules in the pathogenesis of GDM, i.e., 3-carboxy-4-methyl-5-propyl-2-furanpropanoic acid (CMPF), angiopoietin-like protein-8 (ANGPTL-8), nesfatin-1, afamin, adropin, fetuin-A, zonulin, secreted frizzled-related proteins (SFRPs), and amylin. It seems that two of them, fetuin-A and zonulin in high serum levels, may be applied as biopredictors of GDM.