Gestational diabetes in Korea: Temporal trends in prevalence, treatment, and short-term consequences from a national health insurance claims database between 2012 and 2016

Trends in the prevalence of gestational diabetes in Catalonia from 2010 to 2019

INTRODUCTION

Gestational diabetes mellitus (GDM) is globally increasing due to changes in risk factors such as gestational age, obesity, and socioeconomic status (SES). This study examined trends of GDM prevalence over ten years using a real-world Primary Health Care database from Catalonia (Spain).

METHODS

A retrospective analysis of pregnant women screened for GDM was conducted, using clinical and SES data from the SIDIAP database.

RESULTS

Among 221,806 women studied from 2010 to 2019,17,587 had GDM, equating to a 7.9% prevalence (95% CI 7.8-8.04). GDM subjects were older (33.5 ± 5.1 vs. 31.2 ± 5.6 years; p < 0.001) and had higher BMI (29.2 ± 5.1 vs .27.8 ± 4.8 kg/m²; p < 0.001) than non-GDM individuals. Overall GDM prevalence remained unchanged throughout the study, although an increase was observed in younger women (below 20 years: 1.28% [95% CI 0.59-2.42] in 2010 to 2.22% [95% CI 0.96-4.33] in 2019, p = 0.02; ages 20-25.9 years: 3.62% [95% CI 3.12-4.17] in 2010 to 4.63% [95% CI 3.88-5.48)] in 2019, p = 0.02). Age, BMI ≥ 25 kg/m2, deprived SES, and previous hypertension and dyslipidaemia were positively associated with GDM.

CONCLUSIONS

This study offers insights into GDM prevalence in Catalonia (Spain),showing overall stability except for a rising trend among younger women.

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

INTRODUCTION

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

METHODS

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

RESULTS

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

CONCLUSIONS

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

Recent progress in metabolic reprogramming in gestational diabetes mellitus: a review

Gestational diabetes mellitus is a prevalent metabolic disease that can impact the normal course of pregnancy and delivery, leading to adverse outcomes for both mother and child. Its pathogenesis is complex and involves various factors, such as insulin resistance and β-cell dysfunction. Metabolic reprogramming, which involves mitochondrial oxidative phosphorylation and glycolysis, is crucial for maintaining human metabolic balance and is involved in the pathogenesis and progression of gestational diabetes mellitus. However, research on the link and metabolic pathways between metabolic reprogramming and gestational diabetes mellitus is limited. Therefore, we reviewed the relationship between metabolic reprogramming and gestational diabetes mellitus to provide new therapeutic strategies for maternal health during pregnancy and reduce the risk of developing gestational diabetes mellitus.

Demand and Requirements for a Digital Healthcare System to Manage Gestational Diabetes in Patients and Healthcare Professionals: A Cross-sectional Survey

This study aimed to assess the current status of gestational diabetes mellitus (GDM) diagnosis and management, and the demand for a digital healthcare system, in order to develop an optimal digital-based management model for GDM. An anonymous online survey was conducted targeting pregnant/postpartum women (Group W), internal medicine physicians (Group P), and obstetricians (group O) from September 6, 2022 to December 31, 2022. The survey assessed the women's knowledge of GDM and gathered information about healthcare professionals' (HCPs) current GDM management practices. All groups were asked about their acceptance of and demands for a digital healthcare system for GDM. Statistical comparisons between groups were conducted using the chi-square test or Fisher's exact test where appropriate. A total of 168 participants were in Group W, 185 in Group P, and 256 in Group O. Participants from all groups recognized the need for a digital healthcare system for GDM (Group W: 95.8%, Group P: 85.9%, Group O: 60%). However, HCPs showed less willingness to integrate these systems into their clinics than pregnant/postpartum women. Essential features identified were recording blood glucose levels and insulin, along with automatic data linkage from self-monitoring devices. Group W showed a higher preference for lab test access, search functionality, and fetal weight assessment than groups P and O (all P < .0001), while Groups P and O had a greater preference for recording insulin and maternal body weight compared to Group W (P = .0141 and .0023, respectively). Both pregnant/postpartum women and HCPs acknowledged the benefits of utilizing a digital healthcare system for managing GDM. However, there were differences in perspectives among these groups.

Obesity Is Associated With Higher Risk of Adverse Maternal and Neonatal Outcomes Than Supervised Gestational Diabetes

BACKGROUND

Unlike gestational diabetic mellitus (GDM), which is strictly managed by most patients and physicians, obesity does not have proper management guidelines, and the importance of its management during pregnancy is often ignored. The aim of this study was to compare maternal and neonatal outcomes according to obesity and GDM, alone or in combination.

METHODS

This was a retrospective cohort study of 3,078 consecutive pregnant women who experienced prenatal care and delivery of a live singleton neonate between January 2016 and December 2020 at our institution. Study participants were categorized into 4 mutually exclusive groups, as follows: group 1, no GDM without obesity; group 2, GDM without obesity; group 3, no GDM with obesity; and group 4, GDM with obesity.

RESULTS

Compared to group 2, group 3 had higher rates of pre-eclampsia, cesarean section including emergent cesarean section rate. Also, neonates in group 3 were heavier and had lower glucose levels compared to those in group 2. Of note, there was no significant difference in maternal or neonatal outcomes except the rate of large-for-gestational-age (LGA) between group 1 and group 2. Among the GDM groups, group 4 had higher risks for pre-eclampsia, cesarean section, and LGA infant status than group 2.

CONCLUSION

Our data showed that obese women without GDM face higher risk of adverse pregnancy outcomes than women with supervised GDM and non-obese women. We also confirmed that adverse pregnancy outcomes associated with GDM were mainly attributable to obesity among women receiving GDM education.

Prediction of gestational diabetes mellitus in Asian women using machine learning algorithms

This study developed a machine learning algorithm to predict gestational diabetes mellitus (GDM) using retrospective data from 34,387 pregnancies in multi-centers of South Korea. Variables were collected at baseline, E0 (until 10 weeks' gestation), E1 (11-13 weeks' gestation) and M1 (14-24 weeks' gestation). The data set was randomly divided into training and test sets (7:3 ratio) to compare the performances of light gradient boosting machine (LGBM) and extreme gradient boosting (XGBoost) algorithms, with a full set of variables (original). A prediction model with the whole cohort achieved area under the receiver operating characteristics curve (AUC) and area under the precision-recall curve (AUPR) values of 0.711 and 0.246 at baseline, 0.720 and 0.256 at E0, 0.721 and 0.262 at E1, and 0.804 and 0.442 at M1, respectively. Then comparison of three models with different variable sets were performed: [a] variables from clinical guidelines; [b] selected variables from Shapley additive explanations (SHAP) values; and [c] Boruta algorithms. Based on model [c] with the least variables and similar or better performance than the other models, simple questionnaires were developed. The combined use of maternal factors and laboratory data could effectively predict individual risk of GDM using a machine learning model.

High maternal glucose exacerbates the association between prenatal per- and polyfluoroalkyl substance exposure and reduced birth weight

BACKGROUND

Per- and polyfluoroalkyl substances (PFAS) exposure has been associated with reduced birth weight. However, the association may be complicated by glucose status due to PFAS impact on fetal growth and placental transport.

OBJECTIVES

To examine whether maternal glucose status modifies the association between prenatal PFAS exposure and birth weight z-score.

METHODS

We analyzed data of 1405 mother-child pairs from the prospective Shanghai Birth Cohort. Plasma concentrations of six PFAS were quantified in the first trimester. Fasting plasma glucose (FPG) was collected at 24-28 gestation weeks. A range of FPG cutoffs (4.9-5.4 mmol/L) covering current recommendations for gestational diabetes mellitus were used to define high and low FPG groups. Association between PFAS concentration and birth weight z-score was evaluated using multivariate linear regression in two FPG groups respectively, and the dose-response relationship was estimated with cutoffs ranging from low to high. We then used propensity score to counterbalance the effects of different PFAS concentrations between the high and low FPG groups, and run the regression again.

RESULTS

A doubling increase in concentrations of several PFAS was inversely associated with birth weight z-score. The association was more evident in high FPG groups and the magnitudes intensified when FPG cutoff increased. The strongest association was observed for PFOA, with the magnitude increased from -0.34 (95 % CI: -0.66, -0.03) for 5.0 mmol/L cutoff, to -0.41 (95 % CI: -0.77, -0.05) for 5.1 mmol/L cutoff, and further to -0.51 (95 % CI: -0.98, -0.03) for 5.3 mmol/L. Propensity score matching yielded similar results.

CONCLUSIONS

High maternal glucose level may increase the risk of reduced birth weight z-score related to prenatal PFAS exposure. Moreover, exploring the effects with different FPG cutoffs may contribute to providing intervention strategies for pregnant women with high PFAS exposure.

Predicting the Risk of Insulin-Requiring Gestational Diabetes before Pregnancy: A Model Generated from a Nationwide Population-Based Cohort Study in Korea

BACKGRUOUND

The severity of gestational diabetes mellitus (GDM) is associated with adverse pregnancy outcomes. We aimed to generate a risk model for predicting insulin-requiring GDM before pregnancy in Korean women.

METHODS

A total of 417,210 women who received a health examination within 52 weeks before pregnancy and delivered between 2011 and 2015 were recruited from the Korean National Health Insurance database. The risk prediction model was created using a sample of 70% of the participants, while the remaining 30% were used for internal validation. Risk scores were assigned based on the hazard ratios for each risk factor in the multivariable Cox proportional hazards regression model. Six risk variables were selected, and a risk nomogram was created to estimate the risk of insulin-requiring GDM.

RESULTS

A total of 2,891 (0.69%) women developed insulin-requiring GDM. Age, body mass index (BMI), current smoking, fasting blood glucose (FBG), total cholesterol, and γ-glutamyl transferase were significant risk factors for insulin-requiring GDM and were incorporated into the risk model. Among the variables, old age, high BMI, and high FBG level were the main contributors to an increased risk of insulin-requiring GDM. The concordance index of the risk model for predicting insulin-requiring GDM was 0.783 (95% confidence interval, 0.766 to 0.799). The validation cohort's incidence rates for insulin-requiring GDM were consistent with the risk model's predictions.

CONCLUSION

A novel risk engine was generated to predict insulin-requiring GDM among Korean women. This model may provide helpful information for identifying high-risk women and enhancing prepregnancy care.

Trends in epidemiology of hyperglycemia in pregnancy in Taiwan, 2008-2017

Background

Hyperglycemia in pregnancy (HIP) increases the risk of adverse pregnancy outcomes. The increasing prevalence of overweight or obesity and the increasing proportion of pregnant women with advanced maternal age (AMA) in the recent decade may affect its prevalence. We analyzed the secular trend of HIP prevalence in 2008-2017 in Taiwan and investigated the impact of AMA in this study.

Methods

This cross-sectional study used data from Health and Welfare Data Science Center. Pregnant women who registered their data in the Birth Certificate Application in 2008-2017 were recruited. Diagnosis of HIP was defined by ICD-9-CM and ICD-10-CM codes.

Results

In 2008-2017, 151,306-211,768 pregnant women were recruited in different years. The proportion of women with AMA increased from 15.8% to 32.1%. Meanwhile, the prevalence increased from 0.5% to 0.9% for preexisting diabetes, 0.2% to 0.4% for undiagnosed diabetes, and 11.4% to 14.5% for GDM. Maternal age was significantly associated with the prevalence of HIP. For women aged <30 years, 30-34 years and ≥35 years, the prevalence of preexisting diabetes were 0.51%, 0.75% and 1.24%, respectively (p<0.05); the prevalence of undiagnosed diabetes were 0.18%, 0.24% and 0.37%, respectively (p<0.05); and the prevalence of GDM were 10.57%, 14.77% and 18.13%, respectively (p<0.05). In all age groups, the prevalence of HIP increased over time in 2008-2017.

Conclusion

The prevalence of HIP increased in Taiwan in 2008-2017, which may result from the increasing proportion of pregnant women with AMA and the change in the diagnostic criteria for GDM.

Evolution of Gestational Diabetes Mellitus across Continents in 21st Century

Over the last few decades, several definitions of gestational diabetes mellitus (GDM) have been described. There is currently not enough research to show which way is the best to diagnose GDM. Opinions differ in terms of the optimal screening and diagnostic measures, in part due to the differences in the population risks, the cost-effectiveness considerations, and the lack of an evidence base to support large national screening programs. The basic method for identifying the disease is the measurement of glucose plasma levels which may be determined when fasting, two hours after a meal, or simply at any random time. The currently increasing incidence of diabetes in the whole population, the altering demographics and the presence of lifestyle changes still require better methods of screening for hyperglycemia, especially during pregnancy. The main aim of this review is to focus on the prevalence and modifications to the screening criteria for GDM across all continents in the 21st century. We would like to show the differences in the above issues and correlate them with the geographical situation. Looking at the history of diabetes, we are sure that more than one evolution in GDM diagnosis will occur, due to the development of medicine, appearance of modern technologies, and the dynamic continuation of research.

Excessive gestational weight gain in early pregnancy and insufficient gestational weight gain in middle pregnancy increasing risk of gestational diabetes mellitus

Background:

Gestational weight gain (GWG) is associated with the risk of gestational diabetes mellitus (GDM). However, the effect of weight gain in different trimesters on the risk of GDM is unclear. This study aimed to evaluate the effect of GWG on GDM during different trimesters.

Methods:

A birth cohort study was conducted from 2017 to 2020 in Shenzhen, China. In total, 51,205 participants were included comprising two models (early pregnancy model and middle pregnancy model). Gestational weight (kg) was measured at each prenatal clinical visit using a standardized weight scale. Logistic regression analysis was used to assess the risk of GDM. Interaction analysis and mediation effect analysis were performed in the middle pregnancy model.

Results:

In the early pregnancy model, the risk of GDM was 0.858 times lower (95% confidence interval [CI]: 0.786, 0.937) with insufficient GWG (iGWG) and 1.201 times higher (95% CI: 1.097, 1.316) with excessive GWG after adjustment. In the middle pregnancy model, the risk of GDM associated with iGWG increased 1.595 times (95% CI: 1.418, 1.794) after adjustment; for excessive GWG, no significant difference was found (P = 0.223). Interaction analysis showed no interaction between GWG in early pregnancy (GWG-E) and GWG in middle pregnancy (GWG-M) (F = 1.268; P = 0.280). The mediation effect analysis indicated that GWG-M plays a partial mediating role, with an effect proportion of 14.9%.

Conclusions:

eGWG-E and iGWG-M are associated with an increased risk of GDM. Strict control of weight gain in early pregnancy is needed, and sufficient nutrition should be provided in middle pregnancy.

Obstetric and neonatal outcomes of gestational diabetes mellitus in twin pregnancies according to changes in its diagnostic criteria from National Diabetes Data Group criteria to Carpenter and Coustan criteria: a retrospective cohort study

BACKGROUND

To compare obstetric and neonatal outcomes in twin pregnancies with or without gestational diabetes mellitus (GDM) before and after changes in GDM diagnostic criteria.

METHODS

This was a retrospective cohort study of 1,764 twin pregnancies including 130 women with GDM (GDM group) and 1,634 women without GDM (non-GDM group). Patients with pregestational diabetes, unknown GDM status, and fetal death at < 24 gestational weeks were excluded. Obstetric and neonatal outcomes were compared between the two groups by two periods: period 1 (1995-2005) and period 2 (2005-2018) when National Diabetes Data Group criteria and Carpenter and Coustan criteria were used for diagnosis of GDM, respectively.

RESULTS

The incidence of GDM in twin pregnancies increased from 4.0% in period 1 to 9.3% in period 2. Composite obstetric complications rate was significantly higher in the GDM group than that in the non-GDM group during period 1 (72.0% vs. 45.5%, P = 0.009). However, it became comparable during period 2 (60.0% vs. 57.4%, P = 0.601). Interaction between GDM and period indicated a significant differential effect of GDM by period on the rate of composite obstetric complications. The rate of composite neonatal complications was similar between the two groups during both periods. The interaction between GDM and period was not significant.

CONCLUSION

After changes of GDM diagnostic criteria, the incidence of GDM increased more than twice, and the rate of composite obstetric complications decreased, but the rate of composite neonatal complications did not change significantly.

Experiences of Changes in Eating Habits and Eating Behaviors of Women First Diagnosed with Gestational Diabetes

As gestational diabetes, which is increasing steadily around the world, can cause complications in the mother and fetus, it is essential to change eating habits and eating behavior to prevent this. According to the 2020 American Diabetes Association recommendations, the food plan should be designed for the adequate calorie intake to achieve glycemic goals and consequently promote maternal and fetal health. Thus, the following study has used the qualitative theme analysis method to assess what it means for 28 South Korean women, who were diagnosed with gestational diabetes for the first time, to change their eating habits and behaviors. As a result, themes were derived related to reflection on daily life, formation of new relationships in the same group, efforts that must be made, rediscovery of couples, and lifestyles reborn as new roles. Based on the results of the study, it is shown that the study participants recovered the peace in their mental state after the crisis of gestational diabetes to pursue relaxation and ultimately higher quality of life by following the plan to fulfill healthy achievements, such as changing their eating habits and behaviors. Therefore, future research and support measures to help the healthy behaviors should be sought by comprehensively exploring the effects of women's experiences in changing their eating habits and behaviors.