Risk factors for gestational diabetes: An umbrella review of meta-analyses of observational studies

Trends in gestational diabetes in Iceland before and after guideline changes in 2012: a nationwide study from 1997 to 2020

Internationally accepted diagnostic criteria recommendations for gestational diabetes (GDM) in 2010 resulted in a rise in global prevalence of GDM. Our aim was to describe the trends in GDM before and after Icelandic guideline changes in 2012 and the trends in pregestational diabetes (PGDM). The study included all singleton births (N = 101 093) in Iceland during 1997-2020. Modified Poisson regression models were used to estimate prevalence ratios (PRs) with 95% confidence intervals (CIs) for risk of GDM overall and by maternal age group, as well as overall risk of PGDM, according to time period of birth. The overall prevalence of GDM by time period of birth ranged from 0.6% (N = 101) in 1997-2000 to 16.2% (N = 2720) in 2017-2020, and the prevalence of PGDM ranged from 0.4% (N = 57) in 1997-2000 to 0.7% (N = 120) in 2017-2020. The overall relative GDM prevalence rate difference before and after 2012 was 380%, and the largest difference was found among women aged <25 years at 473%. Risk of GDM increased in 2017-2020 (PR 14.21, CI 11.45, 17.64) compared to 1997-2000 and was highest among women aged >34 years with PR 19.46 (CI 12.36, 30.63) in 2017-2020. Prevalence rates of GDM and PGDM increased during the study period. An accelerated rate of increase in GDM was found after 2012, overall, and among all maternal age groups. Women aged >34 years had the greatest risk of GDM throughout all time periods, while women aged <25 years appear to have a higher relative rate difference after 2012.

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.

Serum Levels of Adipolin and Adiponectin and Their Correlation with Perinatal Outcomes in Gestational Diabetes Mellitus

Objectives: This study aimed to investigate the serum level of adipolin and adiponectin in healthy pregnant women and pregnant women with gestational diabetes mellitus (GDM) during the second trimester, the prepartum period, and in the newborns of these patients. Methods: A total of 55 women diagnosed with GDM and 110 healthy pregnant women were included in this study. Pearson's and Spearman's correlation coefficients were calculated to determine the association of adipolin and adiponectin with anthropometric markers of obesity (body mass index (BMI), mid-upper arm circumference (MUAC), tricipital skinfold thickness (TST)), inflammation markers (neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), C-reactive protein (CRP)), and maternal glucose homeostasis parameters (fasting glucose, insulin, C peptide, glycosylated hemoglobin A1c (HbA1c), Insulin Resistance-Homeostatic Model Assessment (IR HOMA)). Results: There were no statistical differences between the adipolin value in patients with GDM compared to healthy patients (p = 0.65 at diagnosis and p = 0.50 prepartum) and in newborns from mothers with GDM compared to healthy mothers (p = 0.24). Adipolin levels are significantly higher in patients with GDM who gave birth via cesarean section (p = 0.01). In patients with GDM, the adipolin level correlates positively with HgA1c in the prepartum period. We found a positive correlation between the maternal adipolin values at diagnosis and prepartum and neonatal adipolin (respectively: r = 0.556, p = 0.001; r = 0.332, p = 0.013). Adiponectin levels were significantly lower in patients with GDM at diagnosis and prepartum (p = 0.0009 and p = 0.02), but their levels increased prepartum (5267 ± 2114 ng/mL vs. 6312 ± 3150 ng/mL p = 0.0006). Newborns of mothers with GDM had lower adiponectin levels than newborns of healthy mothers (p < 0.0001). The maternal adiponectin value correlates negatively with maternal BMI, MUAC, and IR HOMA in both groups at diagnosis and prepartum. There were no differences between the groups in terms of cesarean rate (p > 0.99). The relative risk of occurrence of adverse events in patients with GDM compared to healthy ones was 2.15 (95% CI 1.416 to 3.182), and the odds ratio for macrosomia was 4.66 (95% CI 1.591 to 12.69). Conclusions: There was no difference in adipolin levels between mothers with GDM and healthy mothers during the second trimester and the prepartum period. Adipolin is known to enhance insulin sensitivity and reduce inflammation, but unlike adiponectin, it does not appear to contribute to the development of GDM.

The association of red and processed meat with gestational diabetes mellitus: Results from 2 Canadian birth cohort studies

OBJECTIVE

Red and processed meat is considered risk factors of gestational diabetes mellitus (GDM), but the evidence is inconclusive. We aimed to examine the association between red and processed meat intake and odds of GDM among South Asian and White European women living in Canada.

METHODS

This is a cross-sectional analysis of pregnant women from two birth cohorts: SouTh Asian biRth cohorT (START; n = 976) and Family Atherosclerosis Monitoring In earLY life (FAMILY; n = 581). Dietary intake was assessed using a validated 169-item semi-quantitative food-frequency questionnaire (FFQ). Multivariate logistic regression models were used to examine the associations between gestational diabetes and: 1) total red and processed meat; 2) unprocessed red meat; 3) processed meat and GDM after adjustment for potential confounders.

RESULTS

There were 241 GDM cases in START and 91 in FAMILY. The median total red and processed meat intake were 1.5 g/d (START) and 52.8 g/d (FAMILY). In START, the multivariable-adjusted odds ratio (OR) showed neither lower nor higher intakes of unprocessed red meat (p-trend = 0.68), processed meat (p-trend = 0.90), or total red and processed meat (p-trend = 0.44), were associated with increased odds of GDM, when compared with medium intake. Similar results were observed in FAMILY except for processed meat intake [OR = 0.94 (95% CI 0.47-1.91), for medium versus low and OR = 1.51 (95% CI 0.77-2.29) for medium versus high; p-trend = 0.18] after adjusting for additional dietary factors such as the diet quality score, total fiber, saturated fat and glycemic load.

CONCLUSION

Medium compared with low or high red and processed meat intake is not associated with GDM in White Europeans and South Asians living in Canada.

A first trimester prediction model and nomogram for gestational diabetes mellitus based on maternal clinical risk factors in a resource-poor setting

BACKGROUND

The implementation of universal screening for Gestational Diabetes Mellitus (GDM) is challenged by several factors key amongst which is limited resources, hence the continued reliance on risk factor-based screening. Effective identification of high-risk women early in pregnancy may enable preventive intervention. This study aimed at developing a GDM prediction model based on maternal clinical risk factors that are easily assessable in the first trimester of pregnancy in a population of Nigerian women.

METHODS

This was a multi-hospital prospective observational cohort study of 253 consecutively selected pregnant women from which maternal clinical data was collected at 8-12 weeks gestational age. Diagnosis of GDM was made via a one-step 75-gram Oral Glucose Tolerance Test (OGTT) at 24-28 weeks of gestation. A GDM prediction model and nomogram based on selected maternal clinical risk factors was developed using multiple logistic regression analysis, and its performance was assessed by Receiver Operator Curve (ROC) analysis. Data analysis was carried out using Statistical Package for Social Sciences (SPSS) version 25 and Python programming language (version 3.0).

RESULTS

Increasing maternal age, higher body mass index (BMI), a family history of diabetes mellitus in first-degree relative and previous history of foetal macrosomia were the major predictors of GDM. The model equation was: LogitP = 6.358 - 0.066 × Age - 0.075 × First trimester BMI - 1.879 × First-degree relative with diabetes mellitus - 0.522 × History of foetal macrosomia. It had an area under the receiver operator characteristic (ROC) curve (AUC) of 0.814 (95% CI: 0.751-0.877; p-value < 0.001), and at a predicted probability threshold of 0.745, it had a sensitivity of 79.2% and specificity of 74.5%.

CONCLUSION

This first trimester prediction model reliably identifies women at high risk for GDM development in the first trimester, and the nomogram enhances its practical applicability, contributing to improved clinical outcomes in the study population.

Effect of arsenic on the risk of gestational diabetes mellitus: a systematic review and meta-analysis

BACKGROUND

Gestational diabetes mellitus (GDM) is a complication of pregnancy associated with numerous adverse outcomes. There may be a potential link between GDM and arsenic (As) exposure, but this hypothesis remains controversial. This meta-analysis summarizes the latest studies evaluating the association between As and GDM.

METHODS

A comprehensive search of the PubMed, Embase, and Scopus databases up to September 2023 was performed. The pooled estimates with 95% CIs were presented using forest plots. Estimates were calculated with random effects models, and subgroup and sensitivity analyses were conducted to address heterogeneity.

RESULTS

A total of 13 eligible studies involving 2575 patients with GDM were included in this meta-analysis. The results showed that women exposed to As had a significantly increased risk of GDM (OR 1.47, 95% CI: 1.11 to 1.95, P = 0.007). Subgroup analyses suggested that the heterogeneity might be attributed to the years of publication. In addition, sensitivity analysis confirmed the robust and reliable results.

CONCLUSIONS

This analysis suggested that women exposed to As have a greater risk of GDM. However, the significant heterogeneity across studies requires careful interpretation.

REGISTRATION

The PROSPERO registration ID is CRD42023461820.

Assessment of the Level of Knowledge About Risk Factors, Prevention, and Treatment of Gestational Diabetes Mellitus in a Community Sample From Saudi Arabia

Introduction Gestational diabetes mellitus (GDM) is a common disease affecting pregnant females, and it carries a major risk of short and long-term health problems for both mothers and their offspring. Multiple factors like advanced maternal age, obesity, and unhealthy lifestyle can increase the risk of GDM. The current guidelines recommend screening all pregnant females for risk factors during the first trimester with subsequent testing of the blood glucose level at 24 weeks gestation. Lack of awareness about GDM is a main contributing factor in the delay in screening and diagnosis of GDM with subsequent fetal and maternal complications. This study aims to identify the level of knowledge about GDM among the adult population in the Kingdom of Saudi Arabia (KSA). Material and methods A descriptive cross-sectional questionnaire-based study was conducted to identify the level of knowledge about risk factors, prevention, and treatment of GDM in a community sample from Saudi Arabia. A self-administered electronic questionnaire was designed, tested for validity and reliability, and distributed through social media platforms. It consisted of 18 questions asking about the socio-demographic characteristics, the type of hospital in which the participant receives their medical care, whether the participant heard about GDM or not, and if they know someone with GDM, in addition to questions to assess the level of knowledge about risk factors, complications, prevention, and treatment of GDM. The total score of knowledge was calculated. The multivariate regression analysis test was employed to analyze the relationship between various demographic variables and the level of knowledge about GDM among the study population. A p-value of 0.05 or less was considered statistically significant. Results A total of 539 (100%) participants completed the questionnaire: 263 (48.8%) of them were in the age category (18-25 years), 440 (81.6%) of them were females, 307 (57%) had a bachelor's degree, 275 (51%) were single, 454 (84.2%) had heard about GDM, and 258 (47.9%) of them have or know someone with GDM. The total score of knowledge revealed excellent, good, fair, and poor levels among 334 (62%), 140 (26%), 49 (9%), and 16 (3%) of participants, respectively. The multivariable linear regression model revealed that participants who received health care from governmental hospitals heard about GDM and had or knew someone with GDM were positively associated with a higher level of knowledge. Conclusions The findings revealed that among participants, 62% showed excellent knowledge about GDM, although, the other 38% had non-optimal levels of knowledge. Awareness campaigns are recommended to improve the level of knowledge about this disease, its risk factors, treatment, and complications.

Understanding the role of childhood nurture, abuse, and stability on gestational diabetes in the Coronary Artery Risk Development in Young Adults study (CARDIA)

BACKGROUND

To estimate associations between facets of the maternal childhood family environment with gestational diabetes (GDM) and to test mediation by pre-pregnancy waist circumference.

METHODS

We used data from CARDIA, a cohort of individuals aged 18-30 years at baseline (1985-86), followed over 30 years (2016). We included participants with one or more pregnancies ≥ 20 weeks after baseline, without pre-pregnancy diabetes. The primary exposure was the Childhood Family Environment Scale (assessed year 15), including the total score and abuse, nurture, and stability subscales as continuous, separate exposures. The outcome was GDM (self-reported at each visit for each pregnancy). We fit log binomial models with generalized estimating equations to calculate risk ratios (RR) and 95% confidence intervals (CI), adjusting for age at delivery, parity, race (Black or White), and parental education. We used regression models with bootstrapped CIs to test mediation and effect modification by excess abdominal adiposity at the last preconception CARDIA visit (waist circumference ≥ 88 cm).

RESULTS

We included 1033 individuals (46% Black) with 1836 pregnancies. 130 pregnancies (7.1%) were complicated by GDM. For each 1 point increase on the abuse subscale (e.g., from "rarely or never" to "some or little of the time") there was a 30% increased risk of GDM (RR: 1.3, 95% CI: 1.0, 1.7). There was evidence of effect modification but not mediation by preconception abdominal adiposity.

CONCLUSIONS

A more adverse childhood family environment was associated with increased risk of GDM, with a stronger association among individuals with preconception waist circumference ≥ 88 cm.

The influence of Chinese culture and customs on the beliefs and health-related behaviours of Chinese women with gestational diabetes mellitus: A qualitative study

OBJECTIVE

The study aimed to explore the influence of Chinese culture and customs on the beliefs and health-related behaviours of Chinese women with gestational diabetes mellitus (GDM).

METHODS

This descriptive qualitative study conducted semi-structured interviews with 15 Chinese women between November 2022 and January 2023. The interview data were analysed using thematic analysis.

RESULTS

Three major themes are found: (1) beliefs in health, (2) beliefs in illness and GDM and (3) beliefs in health-related behaviours. They worried about the negative effects of GDM on the infant and family, so they actively sought medical advice to maintain health. However, it is challenging for them to balance adhering to healthcare professionals' advice and avoiding practical difficulties in the impact of the Chinese sociocultural context.

CONCLUSION

This study emphasizes the influence of Chinese culture and customs on the beliefs and health-related behaviours of women with GDM. Healthcare providers should recognize the influence of Chinese culture, customs and beliefs on women with GDM and their families, in order to provide individualized education to help them maintain health-related behaviours.

Gestational diabetes mellitus and adverse maternal and perinatal outcomes in twin and singleton pregnancies: a systematic review and meta-analysis

OBJECTIVE

This study aimed to assess the risk of adverse maternal and perinatal complications between twin and singleton pregnancies affected by gestational diabetes mellitus and the respective group without gestational diabetes mellitus (controls).

DATA SOURCES

A literature search was performed using MEDLINE, Embase, and Cochrane from January 1980 to May 2023.

STUDY ELIGIBILITY CRITERIA

Observational studies reporting maternal and perinatal outcomes in singleton and/or twin pregnancies with gestational diabetes mellitus vs controls were included.

METHODS

This was a systematic review and meta-analysis. Pooled estimate risk ratios with 95% confidence intervals were generated to determine the likelihood of adverse pregnancy outcomes between twin and singleton pregnancies with and without gestational diabetes mellitus. Heterogeneity among studies was evaluated in the model and expressed using the I2 statistic. A P value of <.05 was considered statistically significant. The meta-analyses were performed using Review Manager (RevMan Web). Version 5.4. The Cochrane Collaboration, 2020. Meta-regression was used to compare relative risks between singleton and twin pregnancies. The addition of multiple covariates into the models was used to address the lack of adjustments.

RESULTS

Overall, 85 studies in singleton pregnancies and 27 in twin pregnancies were included. In singleton pregnancies with gestational diabetes mellitus, compared with controls, there were increased risks of hypertensive disorders of pregnancy (relative risk, 1.85; 95% confidence interval, 1.69-2.01), induction of labor (relative risk, 1.36; 95% confidence interval, 1.05-1.77), cesarean delivery (relative risk, 1.31; 95% confidence interval, 1.24-1.38), large-for-gestational-age neonate (relative risk, 1.61; 95% confidence interval, 1.46-1.77), preterm birth (relative risk, 1.36; 95% confidence interval, 1.27-1.46), and admission to the neonatal intensive care unit (relative risk, 1.43; 95% confidence interval, 1.38-1.49). In twin pregnancies with gestational diabetes mellitus, compared with controls, there were increased risks of hypertensive disorders of pregnancy (relative risk, 1.69; 95% confidence interval, 1.51-1.90), cesarean delivery (relative risk, 1.10; 95% confidence interval, 1.06-1.13), large-for-gestational-age neonate (relative risk, 1.29; 95% confidence interval, 1.03-1.60), preterm birth (relative risk, 1.19; 95% confidence interval, 1.07-1.32), and admission to the neonatal intensive care unit (relative risk, 1.20; 95% confidence interval, 1.09-1.32) and reduced risks of small-for-gestational-age neonate (relative risk, 0.89; 95% confidence interval, 0.81-0.97) and neonatal death (relative risk, 0.50; 95% confidence interval, 0.39-0.65). When comparing relative risks in singleton vs twin pregnancies, there was sufficient evidence to suggest that twin pregnancies have a lower relative risk of cesarean delivery (P=.003), have sufficient adjustment for confounders, and have lower relative risks of admission to the neonatal intensive care unit (P=.005), stillbirths (P=.002), and neonatal death (P=.001) than singleton pregnancies.

CONCLUSION

In both singleton and twin pregnancies, gestational diabetes mellitus was associated with an increased risk of adverse maternal and perinatal outcomes. In twin pregnancies, gestational diabetes mellitus may have a milder effect on some adverse perinatal outcomes and may be associated with a lower risk of neonatal death.

Influence of gestational diabetes mellitus on subclinical myocardial dysfunction during pregnancy: A systematic review and meta-analysis

OBJECTIVE

The correlation between gestational diabetes mellitus (GDM) and subclinical myocardial dysfunction has been poorly investigated. Accordingly, we performed a meta-analysis to examine the influence of GDM on left ventricular (LV) global longitudinal strain (GLS), assessed by speckle tracking echocardiography (STE), during pregnancy.

STUDY DESIGN

All echocardiographic studies assessing conventional echoDoppler parameters and LV-GLS in GDM women vs. healthy controls, selected from PubMed and EMBASE databases, were included. The risk of bias was assessed by using the National Institutes of Health (NIH) Quality Assessment of Case-Control Studies. The subtotal and overall standardized mean differences (SMDs) of LV-GLS were calculated using the random-effect model.

RESULTS

The full-texts of 10 studies with 1147 women with GDM and 7706 pregnant women without diabetes were analyzed. GDM women enrolled in the included studies were diagnosed with a small reduction in LV-GLS in comparison to controls (average value -19.4 ± 2.5 vs -21.8 ± 2.5 %, P < 0.001) and to the accepted reference values (more negative than -20 %). Substantial heterogeneity was detected for the included studies, with an overall statistic value I2 of 94.4 % (P < 0.001). Large SMDs were obtained for the included studies, with an overall SMD of -0.97 (95 %CI -1.32, -0.63, P < 0.001). Egger's test for a regression intercept gave a P-value of 0.99, indicating no publication bias. On meta-regression analysis, all moderators and/or potential confounders (age at pregnancy, BMI, systolic blood pressure and ethnicity) were not significantly associated with effect modification (all P < 0.05).

CONCLUSIONS

GDM is independently associated with subclinical myocardial dysfunction in pregnancy. STE analysis allows to identify, among GDM women, those who might benefit of targeted non-pharmacological and/or pharmacological interventions, aimed at reducing the risk of developing type 2 diabetes and cardiovascular complications later in life.

Smoking, dietary factors and major age-related eye disorders: an umbrella review of systematic reviews and meta-analyses

BACKGROUND

There is accumulating evidence of the associations between age-related eye diseases (AREDs) and smoking or dietary factors. We aimed to provide an umbrella review of the published literature pertaining to smoking or dietary intake as risk factors for major AREDs including cataract, glaucoma, age-related macular degeneration (AMD) and diabetic retinopathy.

METHODS

We searched for pertinent systematic reviews or meta-analyses in PubMed and Web of Science until 16 April 2022. We reperformed the meta-analysis of each association using random effects models. The heterogeneity and 95% prediction interval were calculated. The presence of small-study effect or excess significance bias was also assessed.

RESULTS

In total, 64 associations from 25 meta-analyses and 41 associations from 10 qualitative systematic reviews were evaluated. There was convincing (class I) evidence for only one association, namely current smoking and cataract. Two factors had highly suggestive (class II) evidence, namely ever smoking associated with cataract and fish consumption associated with AMD. We also found suggestive (class III) evidence for associations between the dietary intake of omega-3 polyunsaturated fatty acid, lutein, zeaxanthin, vitamin C and the risk of cataract.

CONCLUSIONS

Smoking as a risk factor for cataract was the most robust association we identified. We also identified several dietary elements associated with AREDs. Large prospective studies are warranted to further examine the associations discussed in this review.

PROSPERO REGISTRATION NUMBER

CRD42022339082.

Effectiveness of mobile health interventions for pregnant women with gestational diabetes mellitus: a systematic review and meta-analysis

Gestational diabetes mellitus is a growing global health problem. Inadequate management during pregnancy can lead to maternal and foetal complications. Currently, mobile health (mHealth) delivers healthcare services, playing an increasingly important role in the management of blood glucose in GDM. This study aimed to systematically evaluate the effectiveness of mHealth intervention in pregnant women with GDM. Based on randomised controlled trials of mHealth application in GDM patients searched from the database, literature screening, data extraction, and quality evaluation were conducted independently by two researchers. Statistical analysis was performed using Review Manager 5.4 software. The review included 27 studies with a total of 3483 patients. The results showed a significant improvement in glycemic control. In addition, mHealth interventions could reduce the occurrence of adverse pregnancy outcomes and improve self-management ability. In a subgroup analysis, recording of delivery mode and WeChat combined phone call indicated significant differences with mHealth interventions. It was suggested that mHealth interventions imposed a positive effect on glycemic control and reduction of adverse pregnancy outcomes in GDM patients. Our results demonstrated that the application of mHealth interventions can act as an effective and feasible approach to self-management to promote the self-management level and awareness of GDM patients.

Cellular and molecular overview of gestational diabetes mellitus: Is it predictable and preventable?

BACKGROUND

In contrast to overt diabetes mellitus (DM), gestational DM (GDM) is defined as impaired glucose tolerance induced by pregnancy, which may arise from exaggerated physiologic changes in glucose metabolism. GDM prevalence is reported to be as high as 20% among pregnancies depending on the screening method, gestational age, and the population studied. Maternal and fetal effects of uncontrolled GDM include stillbirth, macrosomia, neonatal diabetes, birth trauma, and subsequent postpartum hemorrhage. Therefore, it is essential to find the potential target population and associated predictive and preventive measures for future intensive peripartum care.

AIM

To review studies that explored the cellular and molecular mechanisms of GDM as well as predictive measures and prevention strategies.

METHODS

The search was performed in the Medline and PubMed databases using the terms “gestational diabetes mellitus,” “overt diabetes mellitus,” and “insulin resistance.” In the literature, only full-text articles were considered for inclusion (237 articles). Furthermore, articles published before 1997 and duplicate articles were excluded. After a final review by two experts, all studies (1997-2023) included in the review met the search terms and search strategy (identification from the database, screening of the studies, selection of potential articles, and final inclusion).

RESULTS

Finally, a total of 79 articles were collected for review. Reported risk factors for GDM included maternal obesity or overweight, pre-existing DM, and polycystic ovary syndrome. The pathophysiology of GDM involves genetic variants responsible for insulin secretion and glycemic control, pancreatic β cell depletion or dysfunction, aggravated insulin resistance due to failure in the plasma membrane translocation of glucose transporter 4, and the effects of chronic, low-grade inflammation. Currently, many antepartum measurements including adipokines (leptin), body mass ratio (waist circumference and waist-to-hip ratio], and biomarkers (microRNA in extracellular vesicles) have been studied and confirmed to be useful markers for predicting GDM. For preventing GDM, physical activity and dietary approaches are effective interventions to control body weight, improve glycemic control, and reduce insulin resistance.

CONCLUSION

This review explored the possible factors that influence GDM and the underlying molecular and cellular mechanisms of GDM and provided predictive measures and prevention strategies based on results of clinical studies.

The Maternal Microbiome and Gestational Diabetes Mellitus: Cause and Effect

Gestational diabetes mellitus (GDM) is a growing public health concern that affects many pregnancies globally. The condition is associated with adverse maternal and neonatal outcomes including gestational hypertension, preeclampsia, placental abruption, preterm birth, stillbirth, and fetal growth restriction. In the long-term, mothers and children have an increased risk of developing metabolic diseases such as type 2 diabetes and cardiovascular disease. Accumulating evidence suggest that alterations in the maternal microbiome may play a role in the pathogenesis of GDM and adverse pregnancy outcomes. This review describes changes in the maternal microbiome during the physiological adaptations of pregnancy, GDM and adverse maternal and neonatal outcomes. Findings from this review highlight the importance of understanding the link between the maternal microbiome and GDM. Furthermore, new therapeutic approaches to prevent or better manage GDM are discussed. Further research and clinical trials are necessary to fully realize the therapeutic potential of the maternal microbiome and translate these findings into clinical practice.

Knowledge domain and research trends for Gestational Diabetes Mellitus and nutrition from 2011 to 2021: a bibliometric analysis

Objective

Nutrient management and lifestyle changes are the frontlines of treatment for all pregnant women diagnosed with Gestational Diabetes Mellitus (GDM). This study aimed to identify the global research architecture, trends, and hotpots of GDM and nutrition.

Methods

We obtained publications from the sub-databases of Science Citation Index Expanded and Social Science Citation Index sourced from the Web of Science Core Collection database on January 4, 2022, using publication years between 2011 and 2021. CiteSpace software, VOSviewer, and Microsoft Excel 2019 were used to conduct the bibliometric analyses.

Results

A growing publication trend was observed for GDM and nutrition, and this field has great potential. More GDM and nutrition research has been conducted in developed countries than developing countries. The top three authors with a high publication frequency, co-citations, and a good h-index were from the United States. There were the four studies of randomized controlled trials (RCTs) or meta-analyses of RCTs, as well as one review in the top five items of cited literature. Keywords were categorized into four clusters based on the keywords visualization.

Conclusion

It is important to strengthen the collaboration between nations of different economies to produce more high-quality research on GDM and nutrition. It may be beneficial to further study the etiology, diagnosis, and treatment of GDM based on current results to provide a new perspective on GDM and nutrition.

A culturally tailored personaliseD nutrition intErvention in South ASIan women at risk of Gestational Diabetes Mellitus (DESI-GDM): a randomised controlled trial protocol

INTRODUCTION

South Asians are more likely to develop gestational diabetes mellitus (GDM) than white Europeans. Diet and lifestyle modifications may prevent GDM and reduce undesirable outcomes in both the mother and offspring. Our study seeks to evaluate the effectiveness and participant acceptability of a culturally tailored, personalised nutrition intervention on the glucose area under the curve (AUC) after a 2-hour 75 g oral glucose tolerance test (OGTT) in pregnant women of South Asian ancestry with GDM risk factors.

METHODS AND ANALYSIS

A total of 190 South Asian pregnant women with at least 2 of the following GDM risk factors-prepregnancy body mass index>23, age>29, poor-quality diet, family history of type 2 diabetes in a first-degree relative or GDM in a previous pregnancy will be enrolled during gestational weeks 12-18, and randomly assigned in a 1:1 ratio to: (1) usual care, plus weekly text messages to encourage walking and paper handouts or (2) a personalised nutrition plan developed and delivered by a culturally congruent dietitian and health coach; and FitBit to track steps. The intervention lasts 6-16 weeks, depending on week of recruitment. The primary outcome is the glucose AUC from a three-sample 75 g OGTT 24-28 weeks' gestation. The secondary outcome is GDM diagnosis, based on Born-in-Bradford criteria (fasting glucose>5.2 mmol/L or 2 hours post load>7.2 mmol/L).

ETHICS AND DISSEMINATION

The study has been approved by the Hamilton Integrated Research Ethics Board (HiREB #10942). Findings will be disseminated among academics and policy-makers through scientific publications along with community-orientated strategies.

TRIAL REGISTRATION NUMBER

NCT03607799.

Thyroid dysfunction during gestation and gestational diabetes mellitus: a complex relationship

PURPOSE

Gestational diabetes mellitus (GDM) and thyroid dysfunction during gestation (GTD) are the two most prevalent endocrinopathies during pregnancy. The aim of the present review is to provide an overview of the peculiar aspects of GDM and GTD, to highlight the potential interactions and clinical consequences of these two frequent clinical conditions.

METHODS

A literature review regarding GDM and GTD was carried out with particular interest on meta-analyses and human studies dealing with the (i) shared risk factors between GDM and GTD, (ii) the epidemiological link between GTD and GDM, (iii) physiopathologic link between GTD and GDM, (iv) clinical consequences of GDM and GTD, and (v) post-partum implications of GDM and GTD.

RESULTS

The association between GDM and GTD is common and may be explained by the insulin-resistance state due to maternal GTD, to alterations in the placentation process or to the many shared risk factors. Discrepant results of epidemiologic studies can be explained, at least in part, by the changes in diagnostic criteria and screening strategies throughout the years for both conditions. GDM and GTD impact pregnancy outcome and have post-partum long-term consequences, but more studies are needed to prove an additional adverse effect.

CONCLUSIONS

Based on the epidemiological and physio-pathological link between GDM and GTD, it could be suggested that a diagnosis of GTD could lead to screen GDM and the other way round.

In utero metabolomic signatures of refined grain intake and risk of gestational diabetes: A metabolome-wide association study

BACKGROUND

Epidemiologic evidence has linked refined grain intake to a higher risk of gestational diabetes (GDM), but the biological underpinnings remain unclear.

OBJECTIVES

We aimed to identify and validate refined grain-related metabolomic biomarkers for GDM risk.

METHODS

In a metabolome-wide association study of 91 cases with GDM and 180 matched controls without GDM (discovery set) nested in the prospective Pregnancy Environment and Lifestyle Study (PETALS), refined grain intake during preconception and early pregnancy and serum untargeted metabolomics were assessed at gestational weeks 10-13. We identified refined grain-related metabolites using multivariable linear regression and examined their prospective associations with GDM risk using conditional logistic regression. We further examined the predictivity of refined grain-related metabolites selected by least absolute shrinkage and selection operator regression in the discovery set and validation set (a random PETALS subsample of 38 individuals with and 336 without GDM).

RESULTS

Among 821 annotated serum (87.4% fasting) metabolites, 42 were associated with refined grain intake, of which 17 (70.6% in glycerolipids, glycerophospholipids, and sphingolipids clusters) were associated with subsequent GDM risk (all false discovery rate-adjusted P values <0.05). Adding 7 of 17 metabolites to a conventional risk factor-based prediction model increased the C-statistic for GDM risk in the discovery set from 0.71 (95% CI: 0.64, 0.77) to 0.77 (95% CI: 0.71, 0.83) and in the validation set from 0.77 (95% CI: 0.69, 0.86) to 0.81 (95% CI: 0.74, 0.89), both with P-for-difference <0.05.

CONCLUSIONS

Clusters of glycerolipids, glycerophospholipids, and sphingolipids may be implicated in the association between refined grain intake and GDM risk, as demonstrated by the significant associations of these metabolites with both refined grains and GDM risk and the incremental predictive value of these metabolites for GDM risk beyond the conventional risk factors. These findings provide evidence on the potential biological underpinnings linking refined grain intake to the risk of GDM and help identify novel disease-related dietary biomarkers to inform diet-related preventive strategies for GDM.

Clinical First-Trimester Prediction Models for Gestational Diabetes Mellitus: A Systematic Review and Meta-Analysis

BACKGROUND

Gestational diabetes mellitus (GDM) is a common pregnancy complication that negatively impacts the health of both the mother and child. Early prediction of the risk of GDM may permit prompt and effective interventions. This systematic review and meta-analysis aimed to summarize the study characteristics, methodological quality, and model performance of first-trimester prediction model studies for GDM.

METHODS

Five electronic databases, one clinical trial register, and gray literature were searched from the inception date to March 19, 2022. Studies developing or validating a first-trimester prediction model for GDM were included. Two reviewers independently extracted data according to an established checklist and assessed the risk of bias by the Prediction Model Risk of Bias Assessment Tool (PROBAST). We used a random-effects model to perform a quantitative meta-analysis of the predictive power of models that were externally validated at least three times.

RESULTS

We identified 43 model development studies, six model development and external validation studies, and five external validation-only studies. Body mass index, maternal age, and fasting plasma glucose were the most commonly included predictors across all models. Multiple estimates of performance measures were available for eight of the models. Summary estimates range from 0.68 to 0.78 (I² ranged from 0% to 97%).

CONCLUSION

Most studies were assessed as having a high overall risk of bias. Only eight prediction models for GDM have been externally validated at least three times. Future research needs to focus on updating and externally validating existing models.

Ethnic Disparities and Obesity Risk Factors in Pregnant Women: A Retrospective Observational Cohort Study

(1) Background: This article focuses on the prevalence of overweight and obesity in pregnancy in different ethnic groups and assesses the existence of associated comorbidities. (2) Materials and Methods: A retrospective observational cohort study of 16803 pregnant women was carried out between 2012 and 2018 in the health region of Lleida (72% of the total). The relationship between overweight and obesity and different variables was analyzed by calculating the adjusted odds ratio (aOR) and 95% confidence intervals with multivariate logistic regression models. (3) Results: The prevalence of obesity in pregnant women rose from 11.1% in 2012 to 13.4% in 2018, and there was an age-related weight gain. A high incidence of overweight and obesity was recorded in pregnant women from ethnic groups: Maghrebi, sub-Saharan African and Latin America populations presented ORs of 4.08, 3.18 and 1.59, respectively. Hypertension was the variable most affected by body mass index (BMI) > 25 (OR = 3.39) followed by gestational diabetes mellitus (OR = 2.35). Depression was also associated with obesity. (4) Conclusions: The BMI of pregnant women is influenced by individual, ethnic and clinical factors. Mental health conditions such as depression are associated with BMI.

Rate of Spontaneous Preterm Delivery Between Pregnant Women With and Without Gestational Diabetes

Objective The aim of this study is to compare the rate of spontaneous preterm delivery between gestational diabetes mellitus (GDM) and normal pregnancy. Pregnancy outcomes and associated risk factors for spontaneous preterm delivery were evaluated. Methods A retrospective cohort study was conducted on 120 GDM and 480 normal pregnant women. All women received GDM screening with 50-g glucose challenge test and 100-g oral glucose tolerance test at the first visit and repeated at 24-28 weeks. Data were retrieved from medical records and included baseline and obstetric characteristics, preterm risks, GDM risks, and pregnancy outcomes. Spontaneous preterm birth was defined as delivery before 37 completed weeks of gestation that had been preceded by spontaneous labor. Results GDM women were more likely to be ≥30 years (p=0.032) and have previous GDM (p=0.013). Incidence of overall preterm delivery was significantly higher in GDM women (17.5% vs. 8.5%, p=0.004), as well as the incidence of spontaneous preterm delivery (15.8% vs. 7.1%, p=0.004). GDM women had less gestational weight gain (p<0.001) and were less likely to have excessive weight gain (p=0.002). GDM women were more likely to deliver large for gestational age (LGA) (p=0.02) and macrosomic infants (p=0.027). Neonatal hypoglycemia was significantly more common among GDM women (p=0.013). Multivariate analysis showed that previous preterm birth and GDM independently increased the risk of spontaneous preterm delivery (adjusted OR: 2.56, 95% CI: 1.13-5.79, p=0.024, and adjusted OR: 2.15, 95% CI: 1.2-3.84, p = 0.010, respectively). Conclusion GDM and previous preterm birth significantly increased the risk of spontaneous preterm delivery. GDM also increased the risk of LGA, macrosomia, and neonatal hypoglycemia.

Interpretable machine learning analysis to identify risk factors for diabetes using the anonymous living census data of Japan

Purpose

Diabetes mellitus causes various problems in our life. With the big data boom in our society, some risk factors for Diabetes must still exist. To identify new risk factors for diabetes in the big data society and explore further efficient use of big data, the non-objective-oriented census data about the Japanese Citizen's Survey of Living Conditions were analyzed using interpretable machine learning methods.

Methods

Seven interpretable machine learning methods were used to analysis Japan citizens' census data. Firstly, logistic analysis was used to analyze the risk factors of diabetes from 19 selected initial elements. Then, the linear analysis, linear discriminate analysis, Hayashi's quantification analysis method 2, random forest, XGBoost, and SHAP methods were used to re-check and find the different factor contributions. Finally, the relationship among the factors was analyzed to understand the relationship among factors.

Results

Four new risk factors: the number of family members, insurance type, public pension type, and health awareness level, were found as risk factors for diabetes mellitus for the first time, while another 11 risk factors were reconfirmed in this analysis. Especially the insurance type factor and health awareness level factor make more contributions to diabetes than factors: hypertension, hyperlipidemia, and stress in some interpretable models. We also found that work years were identified as a risk factor for diabetes because it has a high coefficient with the risk factor of age.

Conclusions

New risk factors for diabetes mellitus were identified based on Japan's non-objective-oriented anonymous census data using interpretable machine learning models. The newly identified risk factors inspire new possible policies for preventing diabetes. Moreover, our analysis certifies that big data can help us find helpful knowledge in today's prosperous society. Our study also paves the way for identifying more risk factors and promoting the efficiency of using big data.

Construction and validation of risk prediction model for gestational diabetes based on a nomogram

OBJECTIVE

To construct a model to predict the risk of gestational diabetes mellitus (GDM) based on a nomogram and verify it.

METHODS

Data from 182 patients with GDM treated in Xi'an International Medical Center Hospital from January 2018 to May 2021 were retrospectively analyzed. A total of 491 normal parturients who underwent physical examination in Xi'an International Medical Center Hospital during the same period were selected as controls. With a ratio of 7:3, patients with GDM were divided into a training group (n=128) and a verification (n=54) group, and 491 normal parturients were divided into a training control group (n=344) and a verification control group (n=147). Clinical data were collected, and risk factors for GDM were analyzed by logistic regression. R language was used to construct a prognostic prediction nomogram model for GDM, and a receiver operating characteristic curve was employed to evaluate the accuracy of this nomogram model in predicting the prognosis of GDM.

RESULTS

Univariate analysis revealed that age, body mass index (BMI), family history of diabetes, hemoglobin, triglycerides, serum ferritin, and fasting blood glucose in the first trimester were different between the training group and the training control group (P<0.05). Multivariate analysis revealed that age, BMI, hemoglobin, triglycerides, serum ferritin, and fasting blood glucose in the first trimester were independent risk factors for GDM (P<0.05). Based on a logistic regression equation, the risk formula was -5.971 + 1.054 * age + 1.133 * BMI + 1.763 * hemoglobin + 1.260 * triglycerides + 3.041 * serum ferritin + 1.756 * fasting blood glucose in the first trimester. The area under the curve for predicting the risk of GDM in the training group was 0.920, and that of the validation group was 0.753.

CONCLUSION

Age, BMI, hemoglobin, serum ferritin, and fasting blood glucose in the first trimester are risk factors for GDM.

Revealing the impact of lifestyle stressors on the risk of adverse pregnancy outcomes with multitask machine learning

Psychosocial and stress-related factors (PSFs), defined as internal or external stimuli that induce biological changes, are potentially modifiable factors and accessible targets for interventions that are associated with adverse pregnancy outcomes (APOs). Although individual APOs have been shown to be connected to PSFs, they are biologically interconnected, relatively infrequent, and therefore challenging to model. In this context, multi-task machine learning (MML) is an ideal tool for exploring the interconnectedness of APOs on the one hand and building on joint combinatorial outcomes to increase predictive power on the other hand. Additionally, by integrating single cell immunological profiling of underlying biological processes, the effects of stress-based therapeutics may be measurable, facilitating the development of precision medicine approaches.

Objectives

The primary objectives were to jointly model multiple APOs and their connection to stress early in pregnancy, and to explore the underlying biology to guide development of accessible and measurable interventions.

Materials and Methods

In a prospective cohort study, PSFs were assessed during the first trimester with an extensive self-filled questionnaire for 200 women. We used MML to simultaneously model, and predict APOs (severe preeclampsia, superimposed preeclampsia, gestational diabetes and early gestational age) as well as several risk factors (BMI, diabetes, hypertension) for these patients based on PSFs. Strongly interrelated stressors were categorized to identify potential therapeutic targets. Furthermore, for a subset of 14 women, we modeled the connection of PSFs to the maternal immune system to APOs by building corresponding ML models based on an extensive single cell immune dataset generated by mass cytometry time of flight (CyTOF).

Results

Jointly modeling APOs in a MML setting significantly increased modeling capabilities and yielded a highly predictive integrated model of APOs underscoring their interconnectedness. Most APOs were associated with mental health, life stress, and perceived health risks. Biologically, stressors were associated with specific immune characteristics revolving around CD4/CD8 T cells. Immune characteristics predicted based on stress were in turn found to be associated with APOs.

Conclusions

Elucidating connections among stress, multiple APOs simultaneously, and immune characteristics has the potential to facilitate the implementation of ML-based, individualized, integrative models of pregnancy in clinical decision making. The modifiable nature of stressors may enable the development of accessible interventions, with success tracked through immune characteristics.

Gut Microbiota Associated with Gestational Health Conditions in a Sample of Mexican Women

Gestational diabetes (GD), pre-gestational diabetes (PD), and pre-eclampsia (PE) are morbidities affecting gestational health which have been associated with dysbiosis of the mother's gut microbiota. This study aimed to assess the extent of change in the gut microbiota diversity, short-chain fatty acids (SCFA) production, and fecal metabolites profile in a sample of Mexican women affected by these disorders. Fecal samples were collected from women with GD, PD, or PE in the third trimester of pregnancy, along with clinical and biochemical data. Gut microbiota was characterized by high-throughput DNA sequencing of V3-16S rRNA gene libraries; SCFA and metabolites were measured by High-Pressure Liquid Chromatography (HPLC) and (Fourier Transform Ion Cyclotron Mass Spectrometry (FT-ICR MS), respectively, in extracts prepared from feces. Although the results for fecal microbiota did not show statistically significant differences in alfa diversity for GD, PD, and PE concerning controls, there was a difference in beta diversity for GD versus CO, and a high abundance of Proteobacteria, followed by Firmicutes and Bacteroidota among gestational health conditions. DESeq2 analysis revealed bacterial genera associated with each health condition; the Spearman's correlation analyses showed selected anthropometric, biochemical, dietary, and SCFA metadata associated with specific bacterial abundances, and although the HPLC did not show relevant differences in SCFA content among the studied groups, FT-ICR MS disclosed the presence of interesting metabolites of complex phenolic, valeric, arachidic, and caprylic acid nature. The major conclusion of our work is that GD, PD, and PE are associated with fecal bacterial microbiota profiles, with distinct predictive metagenomes.

Gestational diabetes mellitus and hypertensive disorder of pregnancy play as spouse-pair risk factors of diabetes and hypertension: Insights from Tehran Lipid and Glucose Study

BACKGROUND

Complicated pregnancies by gestational diabetes mellitus (GDM) and hypertensive disorder of pregnancy (HDP) are relatively common worldwide. The evidence is still inconclusive regarding the role of GDM and HDP as spousal risk factor of diabetes (DM) and hypertension (HTN). This study aimed to determine the spousal risk of development of DM and/or HTN in the context of GDM and/or HDP.

METHODS

This population-based cohort study involved couples who participated in Tehran Lipid and Glucose Study. A total of 3650 pairs of spouses were identified, and among them, 2820 met the inclusion criteria. Included participants, followed up 3-year intervals visits from 1999 to 2018. All pairs underwent standard data collection. GDM and HDP were the main exposure of interest in females, and DM and HTN were the main outcomes in both females and their spouses. Cox proportional hazard regression models were used for both females and their spouses, adjusting for age, consanguinity, waist-to-height ratio, physical activity, smoking, and parity.

RESULTS

Of 2820 females, 558 (19.79 %) had histories of GDM or HDP, and 72 (2.55 %) experienced both. Among females who experienced GDM and HDP, 24 (33 %) and 31 (33 %) developed DM and HTN during the follow-up. The corresponding numbers were 89 (16 %) and 191 (34 %) for those who experienced GDM or HPD, and 274 (13 %) and 623 (28 %) for the non-risk factors group. The incidences of DM were 9 (12 %), 100 (18 %), and 373 (17 %) for males whose spouses experienced both GDM and HDP, either one or none of them, respectively. Among males in these groups, 20 (28 %), 150 (27 %), and 630 (29 %) developed HTN, respectively. Females who never had history of GDM and HDP have 34 % (95 % CI: 21, 45) less hazard of being diabetic than their spouses if they have the same age and waist to hip ratio. In cases with histories of both GDM and HDP, the risk of females increases to 3.05 (95 % CI: 1.43, 6.52) times of their spouses. Also, females who had experienced GDM (HR: 3.51, 95 % CI: 2.23, 5.53), or HDP (HR: 2.80, 95 % CI: 1.72, 4.56) were at higher risk of developing DM compared with females who never had GDM or HDP. We found that females with neither GDM nor HDP were more likely than males to be hypertensive in the future by the hazard ratio of 1.21 (95 % CI: 1.06, 1.39).

CONCLUSIONS

Complicated pregnancies by GDM and/or HDP were associated with increased risk of development DM and HTN in later life of females and their spouses. Further studies are required to confirm these results. Preventive care programs should be considered pregnancy complications as couple-based risk factors for subsequent DM and HTN.

The effect of maternal gestational diabetes on maternal and neonatal outcomes in twin pregnancies: a systematic review and meta-analysis

Diabetes and twin pregnancies are known risk factors for poor perinatal and neonatal outcomes. However, the effects of these two entities occurring together are still unclear. PubMed, Scopus and Google Scholar databases were searched in a systematic manner to identify observational studies among twin pregnancies, which documented the association of gestational diabetes with maternal and neonatal outcomes. All the analysis was done using STATA software. The meta-analysis included 21 studies, of which majority were retrospective data based. Mothers with gestational diabetes had higher risks of hypertensive disorder in pregnancy, caesarean section, large for gestational age baby, NICU admission and neonatal hypoglycaemia compared to mothers without gestational diabetes. Diabetic mothers were at reduced risk of small for gestational age baby and low APGAR score. No statistically significant differences in the risk of low birth weight, mean birth weight, prematurity and neonatal death were noted. This meta-analysis observed increased risks of detrimental maternal, neonatal and perinatal outcomes in twin pregnancies complicated by gestational diabetes, underscoring the need for the early detection and management of gestational diabetes.

High Folate, Perturbed One-Carbon Metabolism and Gestational Diabetes Mellitus

Folate is a dietary micronutrient essential to one-carbon metabolism. The World Health Organisation recommends folic acid (FA) supplementation pre-conception and in early pregnancy to reduce the risk of fetal neural tube defects (NTDs). Subsequently, many countries (~92) have mandatory FA fortification policies, as well as recommendations for periconceptional FA supplementation. Mandatory fortification initiatives have been largely successful in reducing the incidence of NTDs. However, humans have limited capacity to incorporate FA into the one-carbon metabolic pathway, resulting in the increasingly ubiquitous presence of circulating unmetabolised folic acid (uFA). Excess FA intake has emerged as a risk factor in gestational diabetes mellitus (GDM). Several other one-carbon metabolism components (vitamin B12, homocysteine and choline-derived betaine) are also closely entwined with GDM risk, suggesting a role for one-carbon metabolism in GDM pathogenesis. There is growing evidence from in vitro and animal studies suggesting a role for excess FA in dysregulation of one-carbon metabolism. Specifically, high levels of FA reduce methylenetetrahydrofolate reductase (MTHFR) activity, dysregulate the balance of thymidylate synthase (TS) and methionine synthase (MTR) activity, and elevate homocysteine. High homocysteine is associated with increased oxidative stress and trophoblast apoptosis and reduced human chorionic gonadotrophin (hCG) secretion and pancreatic β-cell function. While the relationship between high FA, perturbed one-carbon metabolism and GDM pathogenesis is not yet fully understood, here we summarise the current state of knowledge. Given rising rates of GDM, now estimated to be 14% globally, and widespread FA food fortification, further research is urgently needed to elucidate the mechanisms which underpin GDM pathogenesis.

Maternal Early-Life Risk Factors and Later Gestational Diabetes Mellitus: A Cross-Sectional Analysis of the UAE Healthy Future Study (UAEHFS)

Limited studies have focused on maternal early-life risk factors and the later development of gestational diabetes mellitus (GDM). We aimed to estimate the GDM prevalence and examine the associations of maternal early-life risk factors, namely: maternal birthweight, parental smoking at birth, childhood urbanicity, ever-breastfed, parental education attainment, parental history of diabetes, childhood overall health, childhood body size, and childhood height, with later GDM. This was a retrospective cross-sectional study using the UAE Healthy Future Study (UAEHFS) baseline data (February 2016 to April 2022) on 702 ever-married women aged 18 to 67 years. We fitted a Poisson regression to estimate the risk ratio (RR) for later GDM and its 95% confidence interval (CI). The GDM prevalence was 5.1%. In the fully adjusted model, females with low birthweight were four times more likely (RR 4.04, 95% CI 1.36-12.0) and females with a parental history of diabetes were nearly three times more likely (RR 2.86, 95% CI 1.10-7.43) to report later GDM. In conclusion, maternal birthweight and parental history of diabetes were significantly associated with later GDM. Close glucose monitoring during pregnancy among females with either a low birth weight and/or parental history of diabetes might help to prevent GDM among this high-risk group.

Scoping Review of the Relationship Between Gestational Diabetes Mellitus and the Neonatal and Infant Gut Microbiome

OBJECTIVE

To conduct a scoping review to examine the relationship between a diagnosis of gestational diabetes mellitus (GDM) and the neonatal and infant gut microbiome from 0 to 1 year of age.

DATA SOURCES

We searched PubMed, Scopus, Embase, and CINAHL for articles with key terms "microbiome" and "gestational diabetes mellitus."

STUDY SELECTION

We included articles published in English in peer-reviewed journals between 2012 and 2021 that were reports of original research studies in which researchers used next-generation sequencing for analysis of the fecal microbiome and collected meconium or transitional stool from neonates and infants.

DATA EXTRACTION

We identified nine studies with a combined sample size of 1,279 neonates and infants. We extracted data, including title, authors, sample size, study design, methods, findings, significance, and limitations. We extracted and charted confounding variables such as treatment of GDM, body mass index, gestational age at birth, antibiotic use, mode of birth, and feeding method.

DATA SYNTHESIS

Gestational diabetes mellitus may alter the neonatal and infant gut microbiome because neonates and infants of women with GDM had altered composition and diversity compared to neonates and infants of women without GDM.

CONCLUSION

Mechanisms by which the neonatal and infant microbiome changes in response to GDM are poorly understood and need to be evaluated in future research. Further study of how GDM plays a role in the initial seeding of the microbiome, how the maternal microbiome may affect fetal metabolic programming, and how the neonatal microbiome leads to the future development of obesity and glucose intolerance is critical. Future studies should include larger sample sizes, appropriate collection of potential confounding variables, assessment of maternal interventions for GDM, and longitudinal designs to further understand potential associations with long-term detrimental outcomes such as obesity and impaired glucose tolerance.

Can Thyroid Screening in the First Trimester Improve the Prediction of Gestational Diabetes Mellitus?

This study aimed to evaluate the clinical utility of the subclinical hypothyroidism (SCH) marker, elevated thyroid-stimulating hormone (TSH) and thyroid antibodies in their ability to predict subsequent gestational diabetes mellitus (GDM). In a prospective clinical trial, 230 pregnant women were screened for thyroid function during the first trimester of pregnancy. Increased TSH levels with normal free thyroxine (fT4) were considered SCH. The titers of thyroid peroxidase antibody (anti TPO Ab) at >35 IU/mL and thyroglobulin antibody (anti Tg Ab) at >115 IU/mL were considered as antibodies present. According to the OGTT results, the number of pregnant women with GDM showed the expected growth trend, which was 19%. Two groups of pregnant women were compared, one with GDM and the other without. Increased TSH levels and the presence of thyroid antibodies showed a positive correlation with the risk of GDM. TSH levels were significantly higher in pregnant women with GDM, p = 0.027. In this study, 25.6% of pregnant women met the diagnostic criteria for autoimmune thyroiditis. Hashimoto’s thyroiditis was significantly more common in GDM patients, p < 0.001. Through multivariate logistic regression, it was demonstrated that patient age, TSH 4 IU/mL, and anti TPO Ab > 35 IU/mL are significant predictors of gestational diabetes mellitus that may improve first-trimester pregnancy screening performance, AUC: 0.711; 95% CI: 0.629−0.793.

Risk factors for depression in the elderly: An umbrella review of published meta-analyses and systematic reviews

BACKGROUND

Depression has been identified as one of the leading causes of the disease burden worldwide. Identification of the potential factors that increased or decreased the risk of depression could be important to provide prevention strategies. We aimed to conduct an umbrella review of risk factors for depression in the elderly and assessed the credibility of evidence of the association between each factor and depression.

METHODS

We searched PubMed and Web of Science from 1990 to April 11, 2021 for articles investigating associations between potential factors and depression. For each association, we recalculated the summary effect size and 95% confidence intervals using random effects models. The 95% prediction interval and between-heterogeneity were also reported. For publication bias, small-study effect and excess of significance bias were assessed.

RESULTS

Twenty-five publications met the inclusion criteria, including twenty-two meta-analyses and three qualitative systematic reviews. Approximately 1,199,927 participants and 82 unique factors were reported. Two factors were rated as convincing evidence and four factors showed highly suggestive evidence. These risk factors were aspirin use, individuals aged 80 years and above, sleep disturbances and persistent sleep disturbances, hearing problem, poor vision, and cardiac disease.

LIMITATIONS

Most studies that we included were of low quality.

CONCLUSIONS

We found several risk factors for depression with different levels of evidence, in which aspirin use and individuals aged 80 years and above presented the strongest evidence. Further research is warranted to support other findings from this umbrella review using a large, well-designed cohort study.

Methodological approaches for assessing certainty of the evidence in umbrella reviews: A scoping review

Introduction

The number of umbrella reviews (URs) that compiled systematic reviews and meta-analysis (SR-MAs) has increased dramatically over recent years. No formal guidance for assessing the certainty of evidence in URs of meta-analyses exists nowadays. URs of non-interventional studies help establish evidence linking exposure to certain health outcomes in a population. This study aims to identify and describe the methodological approaches for assessing the certainty of the evidence in published URs of non-interventions.

Methods

We searched from 3 databases including PubMed, Embase, and The Cochrane Library from May 2010 to September 2021. We included URs that included SR-MAs of studies with non-interventions. Two independent reviewers screened and extracted data. We compared URs characteristics stratified by publication year, journal ranking, journal impact factor using Chi-square test.

Results

Ninety-nine URs have been included. Most were SR-MAs of observational studies evaluating association of non-modifiable risk factors with some outcomes. Only half (56.6%) of the included URs assessed the certainty of the evidence. The most frequently used criteria is credibility assessment (80.4%), followed by GRADE approach (14.3%). URs published in journals with higher journal impact factor assessed certainty of evidence than URs published in lower impact group (77.1 versus 37.2% respectively, p < 0.05). However, criteria for credibility assessment used in four of the seven URs that were published in top ranking journals were slightly varied.

Conclusions

Half of URs of MAs of non-interventional studies have assessed the certainty of the evidence, in which criteria for credibility assessment was the commonly used method. Guidance and standards are required to ensure the methodological rigor and consistency of certainty of evidence assessment for URs.

A self-efficacy-enhancing physical activity intervention in women with high-risk factors for gestational diabetes mellitus: study protocol for a randomized clinical trial

BACKGROUND

Gestational diabetes mellitus (GDM) is one of the most common medical disorders in pregnancy. Evidence has demonstrated that moderate-intensity physical activity may reduce the risk of gestational diabetes. However, women at risk of GDM spend most of their time performing sedentary behaviors. Although researchers identified self-efficacy as a mediator to overcome physical activity barriers, exercise intervention during pregnancy based on self-efficacy theory has not been discussed so far. Furthermore, there is conflicting evidence regarding the effects of a physical exercise intervention on the incidence of GDM and other maternal or neonatal outcomes in women at higher risk for GDM.

METHODS/DESIGN

A single-center, parallel, randomized controlled trial will be conducted in a maternal-child health care center. A total of 244 pregnant women at high risk for GDM will be randomized into a study group receiving a self-efficacy-enhancing physical activity intervention or a control group receiving the usual care. The intervention will consist of four group sessions and everyday reminders by WeChat (Tencent, Shenzhen, China). The program will begin at approximately 13-14+6 gestational weeks and end at 36+6 gestational weeks. The primary outcomes will include the incidence of GDM, blood sugar values, and physical activity. The secondary outcomes will include physical activity self-efficacy, gestational weight gain, maternal outcomes, and neonatal outcomes.

DISCUSSION

The findings of this research will contribute toward understanding the effects of a self-efficacy theory-oriented physical activity program on the incidence of GDM, blood sugar values, physical activity level, gestational weight gain, physical activity self-efficacy, maternal outcomes, and neonatal outcomes.

TRIAL REGISTRATION

Chinese Clinical Trial Registry (CHiCTR) ChiCTR2200056355 . Registered on February 4, 2022.

Equal Weighting of the Healthy Eating Index-2010 Components May Not be Appropriate for Pregnancy

BACKGROUND

Adherence to the Dietary Guidelines for Americans is often assessed using the Healthy Eating Index (HEI). The HEI total score reflects overall diet quality, with all aspects equally important. Using the traditional weighting scheme for the HEI, all components are generally weighted equally in the total score. However, there is limited empirical basis for applying the traditional weighting for pregnancy specifically.

OBJECTIVES

We aimed to assess associations between the 12 HEI-2010 component scores and select pregnancy outcomes.

METHODS

The Nulliparous Pregnancy Outcomes Study: Monitoring Mothers-to-Be was a prospective pregnancy cohort (US multicenter, 2010-2013). Participants enrolled in the study between 6 and 13 weeks of gestation. An FFQ assessed usual dietary intake 3 months prior to pregnancy (n = 7880). Scores for the HEI-2010 components were assigned using prespecified standards based on densities (standard units per 1000 kcal) of relevant food groups for most components, a ratio (PUFAs and MUFAs to SFAs) for fatty acids, and the contribution to total energy for empty calories. Using binomial regression, we estimated risk differences between each component score and cases of small-for-gestational age (SGA) birth, preterm birth, preeclampsia, and gestational diabetes, controlling for total energy and scores for the other HEI-2010 components.

RESULTS

Higher scores for greens and beans and total vegetables were associated with fewer cases of SGA birth, preterm birth, and preeclampsia. For instance, every 1-unit increase in the greens and beans score was associated with 1.2 fewer SGA infants (95% CI, 0.7-1.7), 0.7 fewer preterm births (95% CI, 0.3-1.1), and 0.7 fewer preeclampsia cases (95% CI, 0.2-1.1) per 100 deliveries. For gestational diabetes, the associations were null.

CONCLUSIONS

Vegetable-rich diets were associated with fewer cases of SGA birth, preterm birth, and preeclampsia, controlling for overall diet quality. Examination of the equal weighting of the HEI components (and underlying guidance) is needed for pregnancy.

Vitamin D Status and Gestational Diabetes in Russian Pregnant Women in the Period between 2012 and 2021: A Nested Case-Control Study

Several meta-analyses found an association between low maternal serum 25-hydroxyvitamin D (25(OH)D) level and gestational diabetes mellitus (GDM). However, some of them reported significant heterogeneity. We examined the association of serum 25(OH)D concentration measured in the first and in the second halves of pregnancy with the development of GDM in Russian women surveyed in the periods of 2012−2014 and 2018−2021. We conducted a case−control study (including 318 pregnant women) nested on two previous studies. In 2012−2014, a total of 214 women (83 GDM and 131 controls) were enrolled before 15 weeks of gestation and maternal serum 25(OH)D concentrations were measured twice: at 8th−14th week of gestation and simultaneously with two-hour 75 g oral glucose tolerance test (OGTT) at 24th−32nd week of gestation. In the period of 2018−2021, 104 women (56 GDM and 48 controls) were included after OGTT and 25(OH)D concentrations were measured at 24th−32nd week of gestation. Median 25(OH)D levels were 20.0 [15.1−25.7] vs. 20.5 [14.5−27.5] ng/mL (p = 0.565) in GDM and control group in the first half of pregnancy and 25.3 [19.8−33.0] vs. 26.7 [20.8−36.8] ng/mL (p = 0.471) in the second half of pregnancy, respectively. The prevalence rates for vitamin D deficiency (25(OH)D levels < 20 ng/mL) were 49.4% and 45.8% (p = 0.608) in the first half of pregnancy and 26.2% vs. 22.1% (p = 0.516) in the second half of pregnancy in women who developed GDM and in women without GDM, respectively. The frequency of vitamin D supplements intake during pregnancy increased in 2018−2021 compared to 2012−2014 (p = 0.001). However, the third trimester 25(OH)D levels and prevalence of vitamin D deficiency (25.5 vs. 23.1, p = 0.744) did not differ in women examined in the periods of 2012−2014 and 2018−2021. To conclude, there was no association between gestational diabetes risk and maternal 25(OH)D measured both in the first and in the second halves of pregnancy. The increased prevalence of vitamin D supplements intake during pregnancy by 2018−2021 did not lead to higher levels of 25(OH)D.

Predictors for insulin use in gestational diabetes mellitus

OBJECTIVES

Gestational diabetes mellitus (GDM) affects about 15% of pregnancies in Australia, with approximately 30% of those diagnosed with GDM requiring insulin therapy. There are several established risk factors for developing GDM, however limited studies show how these can be used to predict need for insulin treatment. The aim of this study is to identify predictors of insulin therapy in women diagnosed with GDM once an oral glucose tolerance test (OGTT) is performed during pregnancy.

STUDY DESIGN

This is a retrospective cohort study of women with singleton pregnancies complicated by GDM between 2016 and 2017 at a single, large health network in Melbourne, Australia. Data were obtained from hospital record and pathology result systems. Univariable and multivariable logistic regression models were fit to the data to obtain crude and adjusted odds ratios.

RESULTS

Of 2,048 women diagnosed with GDM, 647 (31.6%) required insulin therapy. Positive predictors included in the final multivariable model after backwards, stepwise elimination were an elevated fasting result on an OGTT (adjusted odds ratio (AOR) 2.93 [95% CI 2.34-3.66]), previous birth weight greater than 90th% (AOR 2.04 [95% CI 1.412.94]), previous diagnosis of GDM (AOR 1.68 [95% CI 1.28-2.21]), being born in the South Asian region (AOR 1.58 [95% CI 1.27-1.98]), the 2hr OGTT result (AOR 1.14 [95% CI 1.05-1.24]), body mass index (BMI; AOR 1.13 [95% CI 1.04-1.23]) and age (AOR 1.03 [95% CI 1.00-1.05]) The final predictive model had an area under the receiver-operating characteristics (ROC) curve of 0.744 (95% CI 0.720-0.767).

CONCLUSIONS

This study highlights the possible predictors of insulin use, informing counselling for women who are newly diagnosed with gestational diabetes.

Prediction of gestational diabetes mellitus by different obesity indices

Background

The incidence rates of obesity and gestational diabetes mellitus (GDM) are increasing in parallel. This study aimed to evaluate the relationship between different obesity indices, including prepregnancy body mass index (preBMI), the first-trimester abdominal circumference (AC), and first-trimester abdominal circumference/height ratio (ACHtR), and GDM, and the efficacy of these three indices in predicting GDM was assessed.

Methods

A total of 15,472 pregnant women gave birth to a singleton at the Obstetrics and Gynecology Hospital of Fudan University, Shanghai, China. Prepregnancy weight was self-reported by study participants, body height and AC were measured by nurses at the first prenatal visit during weeks 11 to 13⁺⁶ of pregnancy. GDM was diagnosed through a 75-g oral glucose tolerance test at 24–28 gestational weeks. Using receiver operator characteristic (ROC) curve analysis, we evaluated the association between obesity indices and GDM.

Results

A total of 1912 women (12.4%) were diagnosed with GDM. Logistic regression analysis showed that AC, ACHtR, and preBMI (P < 0.001) were all independent risk factors for the development of GDM. In the normal BMI population, the higher the AC or ACHtR was, the more likely the pregnant woman was to develop GDM. The area under the ROC curve (AUC) was 0.63 (95% CI: 0.62–0.64) for the AC, 0.64 (95% CI: 0.62–0.65) for the ACHtR and 0.63 (95% CI: 0.62–0.64) for the preBMI. An AC ≥ 80.3 cm (sensitivity: 61.6%; specificity: 57.9%), an ACHtR of ≥ 0.49 (sensitivity: 67.3%; specificity: 54.0%), and a preBMI ≥ 22.7 (sensitivity: 48.4%; specificity: 71.8%) were determined to be the best cut-off levels for identifying subjects with GDM.

Conclusions

An increase in ACHtR may be an independent risk factor for GDM in the first trimester of pregnancy. Even in the normal BMI population, the higher the AC and ACHtR are, the more likely a pregnant woman is to develop GDM. AC, ACHtR in the first trimester and preBMI might be anthropometric indices for predicting GDM, but a single obesity index had limited predictive value for GDM.

Subsequent perinatal outcomes of pregnancy with two consecutive pregnancies with gestational diabetes mellitus: A population-based cohort study

BACKGROUND

Gestational diabetes mellitus (GDM) is glucose intolerance diagnosed during pregnancy. We aimed to explore the different outcomes of women with two consecutive pregnancies with GDM.

METHODS

This study included 861 women with recurrent GDM who had two consecutive singleton deliveries at Fujian Maternity and Child Health Hospital between May 2012 and September 2020. Data on pregnancy complications and neonatal and delivery outcomes were collected and analyzed.

RESULTS

Among those women with recurrent GDM, there was no difference in pregnancy complications in index pregnancy vs subsequent pregnancy. Our data revealed there was a significantly higher incidence of thyroid disease in the subsequent pregnancies than in the index pregnancy. (6% vs 10%, p = .003)In subsequent pregnancies, the birth weight was greater than that of the index pregnancy (3296.63 ± 16.85 vs 3348.99 ± 16.05, p = .025); and the incidence of large for gestational age (LGA) was higher than that of the index pregnancy (16.3% vs 20.6%, p = .021). More cesarean sections occurred in the subsequent pregnancy. (32.9% vs 6.6%, p = .039). Postpartum hemorrhage, premature birth, and placental abruption were not significantly different between the two pregnancies.

CONCLUSIONS

The results suggest the effect of GDM on thyroid dysfunction may be persistent. Recurrent gestational diabetes results in a higher rate of cesarean delivery, incidence of LGA, and neonatal admission to the neonatal intensive care unit (NICU) in subsequent pregnancies. We need to pay attention to the postpartum thyroid function of pregnant women with GDM. Further studies are still needed on recurrent GDM to reduce this occurrence of admission to NICU.

Association between thyroid autoimmunity and gestational diabetes mellitus in euthyroid women

OBJECTIVE

Pregnant women with autoimmune (subclinical) hypothyroidism have an increased risk of developing gestational diabetes mellitus (GDM). However, this association remains controversial in euthyroid women with thyroid autoimmunity (TAI). Therefore, the aim of the study was to determine the association between TAI and GDM in euthyroid women in a logistic regression analysis with adjustments for baseline/demographic parameters.

METHODS

Cross-sectional study in 1447 euthyroid women who performed their entire clinical/biological workup and oral glucose tolerance test (OGTT) in our center. At median 13 (11-17) weeks of gestation, thyroid-stimulating hormone, free T4, and thyroid peroxidase antibodies (TPOAb) were measured, baseline characteristics were recorded, and an OGTT was performed between 24 and 28 weeks of pregnancy. Exclusion criteria were pre-pregnancy diabetes, assisted pregnancies, and women with (treated) thyroid dysfunction before or after screening. The diagnosis of GDM was based on 2013 World Health Organization criteria, and TAI was defined as TPOAb levels ≥60 kIU/L.

RESULTS

Two hundred eighty women were diagnosed with GDM (19.4%), 26.1% in women with TAI, and 18.9% in women without TAI (P = 0.096). In the logistic regression analysis, TAI was associated with GDM in women older than 30 years (adjusted odds ratio 1.68 (95% CI, 1.01-2.78); P = 0.048). Maternal age >30 years, pre-pregnancy BMI ≥30 kg/m2, and other than Caucasian background were also associated with GDM; aOR 1.93 (95% CI, 1.46-2.56); P < 0.001, 2.03 (95% CI, 1.46-2.81); P < 0.001 and 1.46 (95% CI, 1.03-2.06); P = 0.034, respectively.

CONCLUSIONS

In older pregnant women, the presence of TAI in euthyroid women was associated with GDM. In line with the literature data, (higher) age and BMI were strongly associated with GDM. Future investigations should focus on treatments that might prevent the development of GDM in euthyroid women with TAI.

Prevalence and Risk Factors of Gestational Diabetes Mellitus in Bangladesh: Findings from Demographic Health Survey 2017-2018

Gestational diabetes mellitus (GDM) has serious consequences for both maternal and neonatal health. The growing number of noncommunicable diseases and related risk factors as well as the introduction of new World Health Organization (WHO) diagnostic criteria for GDM are likely to impact the GDM prevalence in Bangladesh. Our study aimed to assess the national prevalence and identify the risk factors using the most recent WHO criteria. We used the secondary data of 272 pregnant women (weighted for sampling strategy) from the Bangladesh Demographic and Health Survey 2017–2018. Multivariate logistic regression was performed to determine the risk factors of GDM. The overall prevalence of GDM in Bangladesh was 35% (95/272). Increased odds of GDM were observed among women living in the urban areas (adjusted odds ratio (aOR) 2.74, 95% confidence interval (CI) 1.43–5.27) compared to rural areas and those aged ≥25 years (aOR 2.03, 95% CI 1.13–3.65). GDM rates were less prevalent in the later weeks of pregnancy compared to early weeks. Our study demonstrates that the national prevalence of GDM in Bangladesh is very high, which warrants immediate attention of policy makers, health practitioners, public health researchers, and the community. Context-specific and properly tailored interventions are needed for the prevention and early diagnosis of GDM.

Racial and ethnic disparities in pregnancy complications and the protective role of greenspace: A retrospective birth cohort study

Greenspace may positively impact pregnancy health for racially and economically minoritized populations; few studies have examined local availability and accessibility of green/park space in reducing maternal morbidity. The objective of this retrospective birth cohort study was to examine the association between residential exposure to greenspace and adverse pregnancy health outcomes in a Southern US state characterized by high poverty and racial disparities in maternal health (2013-2017). National data from the Protected Area database - United States (PAD-US) and ParkServe estimated three publicly available and accessible residential greenspace measures-a more direct proxy than using remotely-sensed greenness indicators (e.g., normalized difference vegetation index (NDVI))-(a) percent area of greenspace (M1), (b) area of available greenspace per person (M2), (c) total population within a 10-minute walk (M3). Generalized Estimating Equations with logistic regression were used to examine the association between individual greenspace metrics and South Carolina hospital deliveries (n = 238,922 deliveries) for women with correlated maternal health outcomes for gestational hypertension (GHTN), gestational diabetes (GD), severe maternal morbidity (SMM), preeclampsia (PRE), mental disorders (MD), depressive disorders (DD), and preterm birth (PTB). Lowest compared to highest tertiles of all three metrics were associated with increased risk for MD, DD, and a monotonic increase in GD, particularly for black women. Women with the lowest access to M2 and M3 were more at risk for PRE, PTB, and MD. We observed that women in low-income, majority-black communities in the lowest versus highest tertile of M2 were more likely to experience a DD, MD, SMM, or PTB compared to primarily high-income majority-white communities. Available and accessible green/park space may present as an effective nature-based intervention to reduce maternal complications, particularly for gestational diabetes and other pregnancy health risks for which there are currently few known evidence-based primary prevention strategies.

Differing risk factors for new onset and recurrent gestational diabetes mellitus in multipara women: a cohort study

OBJECTIVES

To assess whether recurrent gestational diabetes mellitus (GDM) and newly diagnosed GDM share similar risk factors.

METHODS

The study recruited a cohort of 10,151 multipara women with singleton pregnancy who delivered between 2016 and 2019 in Beijing, China. The prevalence of recurrent GDM and associated risk factors were analyzed between women with and without prior GDM history.

RESULTS

Eight hundred and seventy-five (8.6%) multipara women had a diagnosis of GDM during previous pregnancies. The prevalence of GDM and pre-gestational diabetes mellitus were 48.34% (423/875) and 7.89% (69/875) if the women were diagnosed with GDM during previous pregnancies, as compared to 16.00% (1484/9276) and 0.50% (46/9276) if the women were never diagnosed with GDM before. In women without a history of GDM, a variety of factors including older maternal age, higher pre-pregnancy body mass index (PPBMI), prolonged interval between the two pregnancies, higher early pregnancy weight gain, family history of type 2 diabetes mellitus (T2DM), maternal low birth weight, and higher early pregnancy glycemic and lipid indexes were generally associated with an increased risk of GDM at subsequent pregnancy. In women with a history of GDM, higher PPBMI, higher fasting glucose level and maternal birthweight ≥4000 g were independent risk factors for recurrent GDM.

CONCLUSIONS

GDM reoccurred in nearly half of women with a history of GDM. Risk factors for recurrent GDM and newly diagnosed GDM were different. Identifying additional factors for GDM recurrence can help guide clinical management for future pregnancies to prevent GDM recurrence.

Higher maternal thyroid resistance indices were associated with increased neonatal thyroid-stimulating hormone- analyses based on the Huizhou mother-infant cohort

OBJECTIVES

This study aimed to explore the relationship of maternal thyroid function and thyroid resistance parameters with neonatal thyroid-stimulating hormone (TSH).

METHODS

This work was a longitudinal study. Singleton pregnant women without a history of thyroid disorders were recruited in their first prenatal visit from October 2018 to June 2020. Maternal thyroid markers including TSH, free triiodothyronine (FT3), free thyroxine (FT4), and neonatal TSH were tested in the clinical laboratory of the hospital by electrochemiluminescence immunoassay. Thyroid resistance indices including Thyroid Feedback Quantile-based Index (TFQI), TSH index (TSHI), and thyrotroph T4 resistance index (TT4RI) were estimated in accordance with maternal FT4 and TSH levels. Multivariable linear and logistic regression was applied to explore the associations of maternal thyroid indices with infantile TSH level.

RESULTS

A total of 3,210 mothers and 2,991 newborns with valid TSH data were included for analysis. Multivariable linear regression indicated that maternal thyroid variables were significantly and positively associated with neonatal TSH levels with standardized coefficients of 0.085 for TSH, 0.102 for FT3, 0.100 for FT4, 0.076 for TSHI, 0.087 for TFQI, and 0.089 for TT4RI (all P < 0.001). Compared with the lowest quartile, the highest quartile of TSHI [odds ratio (OR) = 1.590, 95% CI: 0.928-2.724; P_trend = 0.025], TFQI (OR = 1.746, 95% CI: 1.005-3.034; P_trend = 0.016), and TT4RI (OR = 1.730, 95% CI: 1.021-2.934; P_trend = 0.030) were significantly associated with an increased risk of elevated neonatal TSH (>5 mIU/L) in a dose-response manner.

CONCLUSION

The longitudinal data demonstrated that maternal thyroid resistance indices and thyroid hormones in the first half of gestation were positively associated with neonatal TSH levels. The findings offered an additionally practical recommendation to improve the current screening algorithms for congenital hypothyroidism.

miRNAs as Predictive Factors in Early Diagnosis of Gestational Diabetes Mellitus

INTRODUCTION

Circulating miRNAs are important mediators in epigenetic changes. These non-coding molecules regulate post-transcriptional gene expression by binding to mRNA. As a result, they influence the development of many diseases, such as gestational diabetes mellitus (GDM). Therefore, this study investigates the changes in the miRNA profile in GDM patients before hyperglycemia appears.

MATERIALS AND METHODS

The study group consisted of 24 patients with GDM, and the control group was 24 normoglycemic pregnant women who were matched for body mass index (BMI), age, and gestational age. GDM was diagnosed with an oral glucose tolerance test between the 24th and 26th weeks of pregnancy. The study had a prospective design, and serum for analysis was obtained in the first trimester of pregnancy. Circulating miRNAs were measured using the NanoString quantitative assay platform. Validation with real time-polymerase chain reaction (RT-PCR) was performed on the same group of patients. Mann-Whitney U-test and Spearman correlation were done to assess the significance of the results.

RESULTS

Among the 800 miRNAs, 221 miRNAs were not detected, and 439 were close to background noise. The remaining miRNAs were carefully investigated for their average counts, fold changes, p-values, and false discovery rate (FDR) scores. We selected four miRNAs for further validation: miR-16-5p, miR-142-3p, miR-144-3p, and miR-320e, which showed the most prominent changes between the studied groups. The validation showed up-regulation of miR-16-5p (p<0.0001), miR-142-3p (p=0.001), and miR-144-3p (p=0.003).

CONCLUSION

We present changes in miRNA profile in the serum of GDM women, which may indicate significance in the pathophysiology of GDM. These findings emphasize the role of miRNAs as a predictive factor that could potentially be useful in early diagnosis.

Increased Central and Peripheral Thyroid Resistance Indices During the First Half of Gestation Were Associated With Lowered Risk of Gestational Diabetes-Analyses Based on Huizhou Birth Cohort in South China

OBJECTIVES

The study aimed to explore the relationship of thyroid function and resistance indices with subsequent risk of gestational diabetes (GDM).

DESIGN

This was a longitudinal study embedded in the Huizhou Birth Cohort.

METHODS

A total of 2,927 women of singleton pregnancy were recruited from January to October of 2019. Thyroid central resistance indices were evaluated by Thyroid Feedback Quartile-Based index (TFQI), Thyrotrophy T4 Resistance Index (TT4RI), and TSH Index (TSHI) based on plasma-free thyroxine (FT4) and thyroid-stimulating hormone (TSH) levels during the first half of pregnancy. Thyroid peripheral sensitivity was assessed by free triiodothyronine (FT3) to FT4 ratio (FT3/FT4), a proxy of deiodinase activity. GDM was diagnosed between 24 and 28 weeks of gestation by a standardized 75 g oral glucose tolerance test. Multivariable linear and logistic regression was applied to examine the associations of thyroid markers with GDM risk.

RESULTS

FT3 and FT3/FT4 were positively associated with both fasting and post-load glucose levels, while TSH, TSHI, TT4RI, and TFQI were negatively associated with 1 and 2 h post-load glucose levels. Compared with the lowest quartile, GDM risk in the highest quartile increased by 44% [odds ratio (OR) = 1.44; 95%CI, 1.08-1.92; p_trend = 0.027] for FT3 and 81% (OR = 1.81; 95%CI, 1.33-2.46; p_trend < 0.001) for FT3/FT4, while it lowered by 37% (OR = 0.63; 95%CI, 0.47-0.86; p_trend = 0.002] for TSHI, 28% for TT4RI (OR = 0.72; 95%CI, 0.54-0.97; p_trend = 0.06), and 37% for TFQI (OR = 0.63; 95%CI, 0.46-0.85; p_trend < 0.001).

CONCLUSIONS

This longitudinal study indicated that higher FT3 and FT3/FT4 and lower central thyroid resistance indices were associated with increased risk of GDM.

Dynamic changes and early predictive value of branched-chain amino acids in gestational diabetes mellitus during pregnancy

OBJECTIVE

Branched-chain amino acids (BCAAs) are closely associated with type 2 diabetes mellitus, but their roles in gestational diabetes mellitus (GDM) are still controversial. This study aims to explore the dynamic changes of BCAAs during pregnancy and identify potential early biomarkers for GDM.

METHODS

This study is a nested case-control study involved 49 women with GDM and 50 age- and body mass index (BMI)-matched healthy pregnant women. The dynamic changes of valine (Val), isoleucine (Ile), and leucine (Leu) were detected in the first (8-12 weeks) and second trimesters (24-28 weeks) by liquid chromatography-mass spectrometry.

RESULTS

Serum Val, Ile, and Leu were higher in GDM patients than in controls in the first trimester. Compared with the first trimester, the serum Val, Ile, and Leu in GDM patients were decreased in the second trimester. In addition, Val, Ile, and Leu in the first trimester were the risk factors for GDM, and Ile presented a high predictive value for GDM. Ile + age (≥ 35) + BMI (≥ 24) exhibited the highest predictive value for GDM (AUC = 0.902, sensitivity = 93.9%, specificity = 80%).

CONCLUSION

Maternal serum Ile in the first trimester was a valuable biomarker for GDM. Ile combined with advanced maternal age and overweight may be used for the early prediction of GDM.

Long-Term Metabolic Outcomes after Gestational Diabetes Mellitus (GDM): Results from the Odense GDM Follow-Up Study (OGFUS)

AIMS

To compare metabolic profiles and the long-term risk of metabolic dysfunction between women with previous gestational diabetes mellitus (pGDM) and women without pGDM (non-GDM) matched on age, prepregnancy body mass index (BMI), and parity.

METHODS

In total, 128 women with pGDM (median follow-up: 7.8 years) and 70 non-GDM controls (median follow-up: 10.0 years) completed a 2 h oral glucose tolerance test (OGTT) with assessment of glucose, C-peptide, insulin, and other metabolic measures. Additionally, anthropometrics, fat mass, and blood pressure were assessed and indices of insulin sensitivity and beta cell function were calculated.

RESULTS

The prevalence of type 2 diabetes mellitus (T2DM) was significantly higher in the pGDM group compared to the non-GDM group (26% vs. 0%). For women with pGDM, the prevalence of prediabetes (38%) and the metabolic syndrome (MetS) (59%) were approximately 3-fold higher than in non-GDM women (p's < 0.001). Both insulin sensitivity and beta cell function were significantly reduced in pGDM women compared to non-GDM women.

CONCLUSION

Despite similar BMI, women with pGDM had a substantially higher risk of developing T2DM, prediabetes, and the MetS compared to controls. Both beta cell dysfunction and reduced insulin sensitivity seem to contribute to this increased risk.

Gestational weight gain and the risk of gestational diabetes mellitus: A latent class trajectory analysis using birth cohort data

AIMS

To explore trajectories of gestational weight gain (GWG) before diagnosis and its association with risk of gestational diabetes mellitus (GDM).

METHODS

A population-based retrospective cohort study including 37,060 women with live singleton was conducted between 2013 and 2019 in China. Latent class trajectory model (LCTM) was used to identify GWG trajectories, and Poisson regression with robust error estimates was used to estimate risk ratio (RR) of GDM.

RESULTS

Among total 37,060 participants, 25.47% of women were developed with GDM. Two trajectories of GWG were identified as non-excessive weight gain (94.31%) and excessive weight gain (5.69%) before diagnosis of GDM. Women with excessive GWG trajectory before diagnosis had significantly 32.8% (aRR = 1.328, 95 %CI: 1.252 ∼ 1.409, P < 0.001) increased risk of developing GDM compared with non-excessive GWG trajectory. Women with excessive GWG trajectory also had higher risk of macrosomia (aRR = 1.476, 95 %CI: 1.307 ∼ 1.666, P < 0.001) and cesarean delivery (aRR = 1.126, 95 %CI: 1.081 ∼ 1.174, P < 0.001). The impact of excessive GWG trajectory on GDM was greater among pre-pregnancy normal weight women compared with overweight/obese or underweight women.

CONCLUSION

Women with excessive GWG trajectory before diagnosis had significantly higher risk of GDM and GDM-related adverse outcomes, and pre-pregnancy normal weight women with excessive GWG trajectory should also be concerned.