Prevalence and Determinants of Gestational Diabetes Mellitus: A Cross-Sectional Study in China

Establishing causal relationships between insomnia and gestational diabetes mellitus using Mendelian randomization

Background

Gestational diabetes mellitus (GDM) is a common condition observed globally, and previous studies have suggested a link between GDM and insomnia. The objective of this study was to elucidate the causative relationship between insomnia and GDM, and to investigate the influence of factors related to insomnia on GDM.

Methods

We performed bidirectional Mendelian randomization (MR) analyses using single nucleotide polymorphisms (SNPs) as genetic instruments for exposure and mediators, thereby minimizing bias due to confounding and reverse causation. The Cochran Q test was utilized for heterogeneity analysis, MR-Egger regression for pleiotropy assessment, and the leave-one-out method for evaluating the robustness of the results. Additionally, we determined the causal relationships between GDM and other factors such as coffee consumption, alcohol intake, and household income.

Results

Insomnia was positively associated with GDM, as indicated by 39 SNPs (OR = 1.27, 95 % CI 1.12-1.439, P-value = 0.008). Conversely, the MR analysis did not reveal any causal relationship between GDM and insomnia (OR = 1.032, 95 % CI 0.994-1.071, P-value = 0.99). Additionally, no causal relationship was observed between coffee consumption, alcohol intake, household income, and GDM (all P-values >0.05).

Conclusion

Our study indicates that insomnia elevates the risk of GDM, thereby establishing a causal link with GDM, independent of coffee consumption, alcohol intake, and household income.

Association between nighttime sleep duration, midday napping, and sleep quality during early pregnancy and risk of gestational diabetes mellitus: A prospective cohort study in China

AIM

To evaluate the prospective associations of nighttime sleep duration, midday napping, and sleep quality during early pregnancy with gestational diabetes mellitus (GDM) risk among Chinese pregnant women.

METHODS

Sleep-related information was assessed by the Pittsburgh Sleep Quality Index in baseline surveys during the 6-15 (mean 10.3) gestational weeks. GDM was diagnosed during 24-28 gestational weeks according to the Chinese Guidelines on Diagnosis and Management of Hyperglycemia in Pregnancy (2022). Multivariable logistic regression models with adjustments for socio-demographic and lifestyle factors were used to estimate odds ratios (ORs) and 95 % confidence intervals (CIs) for the associations of sleep traits with GDM risk.

RESULTS

We identified 503 incident GDM cases among 6993 participants. Compared with women who slept for 7-9 hours/night in early pregnancy, those who slept <7 hours/night showed a higher risk of GDM (OR, 1.75; 95 % CI: 1.20-2.54), whereas those who slept >9 hours/night showed no significant association for GDM risk (OR, 1.01; 95 % CI: 0.78-1.30). Compared with women with absolutely no napping, those with ≤60 and > 60 min/day midday napping showed no significant association for GDM risk (OR, 0.82; 95 % CI: 0.64-1.05 for ≤60 min/day midday napping; OR, 0.87; 95 % CI: 0.66-1.15 for >60 min/day midday napping). Poor sleep quality was not associated with GDM risk compared with good quality (OR, 0.90; 95 % CI: 0.72-1.12).

CONCLUSION

A short nighttime sleep duration during early pregnancy was associated with a higher risk of GDM, which was independent of midday napping, sleep quality and lifestyle factors.

Sleep health predicted glucose metabolism among pregnant women: A prospective cohort study

AIMS

To examine whether sleep health in the first trimester could predict glucose metabolism in the second trimester.

METHODS

Pregnant women (N = 127) during the first trimester were recruited (August 2022 to March 2023). Overall sleep health was assessed by the Sleep Health Index. Various dimensions of sleep health were measured using a 7-day sleep diary and questionnaires. The outcomes, including diagnosis of gestational diabetes mellitus (GDM) and HbA1c, were obtained from the medical records in the second trimester. Poisson regression analysis and multiple linear regression were used for data analysis.

RESULTS

The average age of the participants was 32.6 years. The incidence of GDM was 28.3 % and the mean HbA1c was 5.2 % (33 mmol/mol). Sleep duration regularity (RR = 1.808; 95 %CI 1.023, 3.196) was associated with GDM after controlling for confounders. SHI total score (β = -0.278; 95 %CI -0.022, -0.005) and sleep duration regularity (β = 0.243; 95 %CI 0.057, 0.372) were associated with HbA1c.

CONCLUSIONS

Worse sleep health, particularly lower sleep regularity, predicted worse glucose metabolism among pregnant women. Healthcare professional may consider adding sleep-related assessment to prenatal care. Maintaining regular sleep should be encouraged. Studies examining the impact of sleep intervention on glucose metabolism among pregnant women are warranted.

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

PURPOSE

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

METHODS

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

RESULTS

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

CONCLUSION

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

Lifestyle interventions to prevent adverse pregnancy outcomes in women at high risk for gestational diabetes mellitus: a randomized controlled trial

Objective

To examine the effects of lifestyle interventions, including dietary guidance, health education and weight management, on pregnancy outcomes in women at high risk of gestational diabetes mellitus (GDM).

Methods

Our study included 251 women at high risk of GDM and 128 randomized to lifestyle interventions (dietary guidance, health education, and weight management); One hundred and twenty-three people were randomly assigned to a control group (regular pregnancy check-ups). Counts between groups were compared using either chi-square test or Fisher's exact test.

Results

Compared with the control group, the risk of GDM was reduced by 46.9% (16.4% vs 30.9%, P = 0.007) and the risk of pregnancy induced hypertension (PIH) was reduced by 74.2% (2.3% vs 8.9%, P = 0.034) in the intervention group. There were no significant differences in macrosomia, cesarean section, or preterm birth (P >0.05).

Conclusion

The lifestyle intervention in this study helped pregnant women to better understand knowledge related to pregnancy, reduce stress and anxiety, and increase intake of adequate prenatal nutrition. This intervention prevented metabolic abnormalities that may occur due to inadequate nutrient intake during pregnancy. In addition, it helped women to control weight gain, maintain appropriate weight gain during pregnancy, and reduce the risk of excessive or insufficient weight gain, ultimately lowering the incidence of GDM and PIH. This highlights the importance of early screening and intervention for high-risk pregnant women.

Clinical Trial Registration

https://www.chictr.org.cn, identifier ChiCTR2300073766.

Prevalence of abnormal glucose values and gestational diabetes mellitus among pregnant women in Xi'an from 2015 to 2021

BACKGROUND

Pregnant women with gestational diabetes mellitus (GDM) often have an increased risk of adverse pregnancy outcomes. The purpose of this study was to explore the prevalence and characteristics of GDM in Xi'an from 2015 to 2021 since the implementation of China's "Two-Child policy" and to provide a clinical basis for the management of GDM.

METHODS

We analyzed the oral glucose tolerance test (OGTT) results of 152,836 pregnant women who underwent routine prenatal examination at the Northwest Women and Children's Hospital from 2015 to 2021. Additionally, we analyzed the GDM prevalence and characteristics.

RESULTS

The prevalence of GDM in the Xi'an urban area was 24.66% and exhibited an increasing trend annually (χ2 for trend = 43.922, p < 0.001) and with age (χ2 for trend = 2527.000, p < 0.001). Consistent with this, the proportion of pregnant women aged 18-25 and 26-30 years decreased significantly with the annual growth (χ2 for trend = 183.279, p < 0.001 and χ2 for trend = 33.192, p < 0.001, respectively). The proportion of pregnant women aged 31-35 and 36-42 years increased gradually annually (χ2 for trend = 134.436, p < 0.001and χ2 for trend = 44.403, p < 0.001, respectively). Of the pregnant women diagnosed with GDM, 71.15% (65.05-74.95%) had abnormal fasting plasma glucose (FPG) values. The highest percentage of patients had a single abnormal OGTT value (68.31%; 65.77-70.61%), followed by two (20.52%; 18.79-22.55%) and three (11.17%; 10.11-11.85%) abnormal values (FPG and 1-h and 2-h plasma glucose (PG).

CONCLUSION

The prevalence of GDM among pregnant women in Xi'an region was high, and it had a increasing trend over the period from 2015 to 2021. Notably, the proportion of elder pregnant women, aged 31-42 years, presented a significant rise after the implementation of the universal two-child policy. On the basis of the high incidence of GDM among elder pregnant women and the high rate of abnormal OGTT values (numbe ≥ 2) in pregnant women diagnosed with GDM, the management of GDM should be intensified, and relevant departments should pay more attention to pregnant women of advanced age.

Prevalence and Associated Risk Factors of Urinary Tract Infection among Diabetic Patients: A Cross-Sectional Study

Urinary tract infections (UTIs) are one of the most common long-term complications of diabetes mellitus (DM). Additionally, various factors, such as socio-demographics, type of DM, fasting blood glucose, regular diabetes monitoring, comorbid chronic diseases, HbA1c, body mass index (BMI), and duration of DM, are also thought to predispose individuals to developing UTIs more frequently when they have DM. This research aims to evaluate the risk factors for UTIs and their prevalence among people with DM in Saudi Arabia (KSA). This cross-sectional study was conducted among 440 adults with type 1, type 2, and gestational DM. The participants had to be at least 18 years old, of both genders, and had been suffering from DM for any period of time. A self-administered questionnaire was utilized to collect data on demographic characteristics, such as sex, age, height, weight, material state, education level, income, and clinical profiles of DM and UTI. The crude (COR) and adjusted odds ratios (AOR) were calculated using logistic regression in the IBM SPSS software. The incidence of types 1 and 2 DM and gestational diabetes reached 34.1, 60.9, and 5%, respectively. Most of the participants had first-degree relatives with DM (65.9%). UTI was common in 39.3% of participants. A chi-squared statistical analysis revealed that the frequency of UTI varied depending (χ2 = 5.176, P = 0.023) on the type of DM. Burning urination and abdominal pain were the most common symptoms. The CORs for sex, marital status, hypertension, and BMI were significant (P < 0.05) and had values of 2.68 (95% CI = 1.78–4.02), 0.57 (95% CI = 0.36–0.92), 1.97 (95% CI = 1.14–3.43), and 2.83 (95% CI = 1.19–2.99), respectively. According to the adjusted model, only sex influenced the occurrence of UTIs. The AOR for sex was 3.45 (95% CI = 2.08–5.69). Based on this study, the authorities related to the health of DM patients can use its findings to guide awareness programs and clinical preparedness.

Efficacy and safety of metformin compared to insulin in gestational diabetes: a systemic review and meta-analysis of Chinese randomized controlled trials

BACKGROUND

Metformin is widely used for the treatment of gestational diabetes. Although some meta-analyses are conducted on the efficacy and safety of metformin, none of them are focused on the Chinese population. The efficacy and safety of metformin in the Chinese GDM population are unknown.

AIM

The study aimed to compare metformin to insulin regarding the safety and efficacy in Chinese GDM patients using randomized controlled trials (RCTs) conducted in China.

METHOD

Chinese databases (Wanfang, CNKI, VIP, and CBM), PubMed, Embase, Cochrane library, and Scopus were searched for RCTs. The last search date was October 18, 2021.

RESULTS

Fifty RCTs (4663 patients) were included in this study after screening. Six outcomes were analyzed. In the main analysis, metformin had lower risk of respiratory distress syndrome (RDS, OR, 0.28; 95% CI 0.16-0.51; P < 0.0001), premature birth (OR, 0.42; 95% CI 0.21-0.85, P = 0.02), and neonatal hypoglycemia (OR, 0.34; 95% CI 0.24-0.48; P < 0.00001) compared to insulin. Moreover, the metformin group is better than the insulin group concerning all other outcomes such as maternal glycemic control and glycated hemoglobin. Subgroup analysis confirmed that metformin has better outcomes than all types of insulin except for RDS, premature birth, 2 h postprandial blood glucose, and glycated hemoglobin.

CONCLUSION

Metformin is considered to be a safe and effective alternative to insulin for the management of GDM if patients refuse insulin due to any reasons in China.

Preventing Gestational Diabetes Mellitus by Improving Healthy Diet and/or Physical Activity during Pregnancy: An Umbrella Review

Several epidemiological studies have analyzed the effects of lifestyle modification on reducing the risk of gestational diabetes mellitus (GDM); however, their results remain inconsistent. This umbrella review aims to evaluate the effects of diet and/or physical activity interventions during pregnancy on preventing GDM. Systematic reviews and meta-analysis of randomized clinical trials reporting preventive effects of diet and/or physical activity in reducing the incidence of GDM were included from PubMed, Web of Science, Scopus and Cochrane library. Two authors independently assessed the overlapping and quality of the 35 selected reviews using AMSTAR 2. The results, although variable, tend to defend the protective role of diet and physical activity interventions separately and independently of each other in the prevention of GDM. However, the results for the combined interventions show a possible protective effect; however, it is not entirely clear because most of the analyzed meta-analyses tend to approach 1, and heterogeneity cannot be ruled out. Establishing conclusions about the most efficient type of intervention and a dose–effect relationship was not feasible given the low quality of systematic reviews (83% low to critically low) and the variability in reporting interventions. Therefore, more studies with better quality and definition of the interventions are required. The protocol was previously registered in PROSPERO as CRD42021237895.

Passive Smoking and Risk of Gestational Diabetes Mellitus among Nonsmoking Women: A Prospective Cohort Study in China

Background: Increasing evidence has shown that active smoking can increase the risk of gestational diabetes mellitus (GDM), but the effect of passive smoking is still unknown. Women in pregnancy are vulnerable to secondhand smoke. This study explored the association of passive smoking with GDM in China. Method: A total of 3083 nonsmoking pregnant women living in Beijing were recruited into a prospective cohort study. Sociodemographic and passive smoking data were collected with structured questionnaires during face-to-face interviews. Glucose levels were measured by physicians according to standard protocols. Multivariate logistic regression was performed for the association estimation after accounting for potential confounders. Result: In total, 562 of the 3083 participants developed GDM (18.23%); 779 participants (25.27%) reported exposure to passive smoking. After adjusting for age, BMI, ethnicity, education, occupation, and parity, passive smoking conferred an approximately 1.4-fold risk increase in GDM (adjusted odds ratio (OR) = 1.37, 95% confidence interval (CI): (1.11, 1.70)). The adjusted ORs with 95% CIs for passive smoking levels of <1, 1−6, and ≥7 times per week were 1.21 (0.94, 1.55), 1.81 (1.22, 2.69), and 1.70 (1.02, 2.84), respectively. An obvious passive-smoking−GDM association was observed among only nulliparous women (adjusted OR = 1.45, 95% CI: (1.14, 1.85)). Conclusion: Frequent exposure to secondhand smoke could increase the risk of GDM among nonsmoking pregnant women. Parity status might modify their association. Public policies should be advocated to prevent passive smoking among this population.

Knowledge of Gestational Diabetes Mellitus Among Saudi Women in a Primary Health Care Center of Almadinah Almunawarah, Kingdom of Saudi Arabia

Background

Gestational diabetes mellitus (GDM) is a type of diabetes mellitus known as any stage of glucose intolerance with onset or first recognition during pregnancy. Awareness of GDM is the first step toward its screening in pregnancy. This study was designed to assess knowledge of GDM, its screening, and risk factors among Saudi women attending primary healthcare center in Almadinah Almunawarah, Kingdom of Saudi Arabia.

Methods

This was an observational cross-sectional study conducted on Saudi women who attended the primary healthcare centers in Almadinah Almunawarah during the study period from January 2021 to June 2021. The sampling technique used was the stratification of primary healthcare centers in Madinah. According to the Epi-Info, version 3.5.1, the minimum sample size was 292. Data collection was done using a valid, Arabic self-administered questionnaire, which was composed of two main parts: general sociodemographic data and a questionnaire to assess GDM knowledge and awareness (12 questions). Data was recorded and analyzed using SPSS version 26.

Results

In this study, 333 women were enrolled with an age range between 18 and 60 years, with a mean of 34.31±9.21 years. Overall, more than half of the women (53.45%) had a poor level of knowledge related to GDM, whereas only 7.80% had a good level of knowledge. Results of multivariate logistic regression analysis revealed that women living in rural areas were at almost four-fold higher risk of having a poor level of knowledge (adjusted odds ratio (aOR): 3.97; 95% confidence interval (CI): 1.44-41.98, p=0.0031). With a one-year increase in women’s age, the risk of poor knowledge increased by 4% (aOR: 1.38; 95% CI: 1.08-1.48, p=0.001). In comparison to illiterate women, university-graduated and postgraduate women had a significantly lower risk of poor knowledge (aOR: 0.03; 95% CI: 0.01-0.31, p=0.001 and aOR: 0.19; 95% CI: 0.06-0.66, p = 0.011, respectively).

Conclusion

The GDM knowledge of Saudi adult women was poor, particularly regarding risk factors, diagnosis, and treatment with insulin. However, their knowledge regarding treatment by lifestyle and diet modifications was quite acceptable.

Maternal sleep during pregnancy and adverse pregnancy outcomes: a systematic review and meta-analysis

AIM/INTRODUCTION

Sleep problem is an important public health concern worldwide. We conducted a meta-analysis to quantitatively evaluate whether sleep duration associated with pregnancy outcomes, and the associations were modified by important characteristics of studies.

MATERIALS AND METHODS

Basing on PubMed, Embase, the Cochrane Central Register of Controlled Trials (CENTRAL) databases, we searched for the published literature related to maternal sleep duration and adverse pregnancy outcomes before 30 June, 2021. We conducted risk of bias assessment, subgroup analyses and sensitivity analysis. The relative risks (RR) or odds ratios (OR) with 95% confidence intervals (CI) were used to estimate the pooled effects.

RESULTS

5246 references were identified through databases searching, 41 studies were included in the study. Pregnant with short sleep duration had 1.81 times (95% CI 1.35-2.44, P < 0.001) risk of gestational diabetes mellitus (GDM). The association between short sleep duration and the risk of gestational hypertension (GH), cesarean section (CS), low birthweight (LBW), preterm birth (PTB) and small for gestational age (SGA) were not significant (P > 0.05). Furthermore, long sleep duration was significantly correlated with GDM (OR 1.24. 95% CI 1.12-1.36, P < 0.001) and CS (OR 1.13. 95% CI 1.04-1.22, P = 0.004), while long sleep duration was not linked with GH, LBW, PTB and SGA (P > 0.05).

CONCLUSIONS

Short / long sleep duration appeared to be associated with adverse pregnancy outcome, specifically with an increased risk of GDM. Sleep should be systematically screened in the obstetric population.

Sleep Quality is an Independent Predictor of Blood Glucose and Gestational Diabetes Mellitus: A Longitudinal Study of 4550 Chinese Women

PURPOSE

To investigate whether pregnant women's subjective sleep quality during the first trimester independently predicted blood glucose and gestational diabetes mellitus (GDM).

METHODS

A total of 4550 pregnant women in the first trimester were enrolled in Chongqing Health Center for Women and Children, China, from January to October 2020.The Pittsburgh Sleep Quality Index (PSQI) was used to measure subjective sleep quality. Depression symptoms and anxiety were measured with the Patient Health Questionnaire-9 (PHQ-9) and General Anxiety Disorder-7 (GAD-7). Oral glucose tolerance tests (OGTT) and blood glucose area under the curve (AUC) were used for estimation of blood glucose and diagnosis of GDM during the second trimester. Linear, mixed model, and logistic regression were used to analyze the association between PSQI and blood glucose as well as GDM.

RESULTS

946/4550 were diagnosed with GDM (20.8%). In the mixed model analysis, the blood glucose level of the highest-scoring group (PSQI score = 18) was 1.94 (95% CI: 0.45~3.43, P = 0.011) mmol/L higher than that of the lowest-scoring group (PSQI score = 0). After adjusting for potential confounders, a one-point PSQI score increase was associated with a 0.014 (95% CI: 0.001~0.027, P = 0.039) mmol/L increase in blood glucose level. Blood glucose AUC was also positively associated with PSQI scores (β = 0.034, 95% CI: 0.003~0.064, P = 0.030). The results for the logistic regression model showed that PSQI was marginal positively correlated with GDM (OR = 1.146, 95% CI: 0.995~1.321, P = 0.059) when age and BMI were not controlled for. When investigating the association between PSQI and the GDM-diagnosed time window, the 1-h diagnosed GDM had a borderline positive correlation with PSQI (OR = 1.182, 95% CI: 0.993~1.405, P = 0.060).

CONCLUSION

Sleep quality during the first trimester may be a risk factor for elevated blood glucose and GDM later in gestation.

Hsa_circRNA_102682 is closely related to lipid metabolism in gestational diabetes mellitus

OBJECTIVE

To explore the relationship between circular RNA (circRNA) in gestational diabetes mellitus (GDM) and the metabolic profile at the molecular level, and find a biological marker that can predict GDM early.

METHODS

A retrospective case-control study was conducted using data and samples from women treated at a hospital in China between January 10 2018 and February 20 2019. Reverse transcription polymerase chain reaction (qRT-PCR) was used to evaluate the expression level of hsa_circRNA_102682 in serum and analyze its correlation with lipid metabolism parameters.

RESULTS

Advanced age and higher pre-pregnancy body mass index (BMI) during pregnancy are risk factors for GDM. The expression level of hsa_circ_102682 was lower among the cases than the controls (p=.000). The levels of triglyceride, apolipoprotein A1 (APOA1), APOB, and high-density lipoprotein cholesterol (HDL-C) were different between the controls and cases (p<.05). Hsa_circRNA_102682 was significantly correlated with triglycerides, APOA1, APOB, 1-h blood glucose in the serum of GDM patients, and the correlation coefficients were 0.319, 0.314, 0.286, and 0.311, respectively (p<.05). The area under the receiver operating characteristic curve is 0.684 (95% confidence interval 0.611-0.756, p=.0001).

CONCLUSIONS

Hsa_circRNA_102682 may regulate lipid metabolism, participate in the pathogenesis of GDM. It can be used as a marker to predict GDM.

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

Background

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

Methods

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

Results

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

Conclusions

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

Relationship of Circulating Copper Level with Gestational Diabetes Mellitus: a Meta-Analysis and Systemic Review

BACKGROUND AND PURPOSE

Gestational diabetes mellitus (GDM) represents the frequently occurring medical disorder beginning in the process of pregnancy. No consensus has been reached about the relationship of circulating copper content with the risk of GDM. Therefore, the present work carried out a meta-analysis for summarizing epidemiological research regarding the copper level with the GDM risk. Furthermore, studies using categories of copper concentration as exposure were combined by dose-response meta-analysis.

METHODS

Related studies were retrieved against the PubMed, Web of Science, and Scopus databases from inception till August 2020. The overall effects were expressed as standard mean difference (SMD). A dose-response meta-analysis was conducted to assess whether the higher copper concentration was associated with higher risks of GDM. Stata 16.0 and Review Manager 5.3 were utilized for data analysis.

RESULTS

A total of fourteen articles involving were retrieved for meta-analysis; in the meantime, 2670 pregnant subjects including 910 GDM cases were enrolled for quantitative analysis. Based on the integrated findings, GDM cases showed increased circulating copper contents relative to those in normal pregnant subjects (SMD = 0.65, 95% CI 0.19 to 1.11; P = 0.005). There was no obvious evidence of publication bias among the studies enrolled. Subgroup analysis showed that such trend was consistent in the third trimester (SMD = 1.21, 95% CI 0.35 to 2.08; P = 0.006) but not second trimester. Meanwhile, circulating copper concentration was significantly higher in women with GDM than those without GDM within the Asian population but not within the Caucasian population (Asia: SMD = 0.73; 95% CI 0.12 to 1.34, P = 0.02; Europe: SMD = 0.49; 95% CI: - 0.23 to 1.20, P = 0.18). Further, serum copper analysis together with subgroup analysis was conducted, and the same result was obtained. For dose-response analysis, the linear associations between circulating copper and risks of GDM were revealed, that higher circulating copper concentration during pregnancy is closely associated with GDM.

CONCLUSION

According to existing evidence, the serum copper concentration increased among GDM cases compared with subjects with normality in glucose tolerance pregnant subject, in particular among the Asians and during the third trimester. The finding from dose-response analysis suggested that increased copper level is associated with an increased risk of GDM. Nonetheless, more specially designed prospective articles should be carried out for understanding the dynamic relationship of copper concentration with the GDM risk.

A systematic review and meta-analysis of the prevalence and determinants of gestational diabetes mellitus in Nigeria

BACKGROUND

Gestational diabetes mellitus (GDM) is any degree of glucose intolerance with onset or first diagnosis in pregnancy. GDM has numerous potential complications and it is important to estimate its burden and risk factors. The objective of the meta-analysis was to determine the pooled prevalence of GDM in Nigeria and identify its determinants.

METHODS

The study design was a meta-analysis; therefore the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines were followed. Electronic databases (African Journal Online, PubMed, SCOPUS, and Google Scholar) and the gray literature were systematically searched. Statistical analysis was done with MetaXL using the random effect model. Heterogeneity was determined using the I2 statistic and the publication bias was checked with the Doi plot.

RESULTS

The total sample size was 46 210. The prevalence of GDM in Nigeria was 0.5 - 38% and the pooled prevalence was 11.0% (95% CI 8-13). The I2 statistic was 99%. The Doi plot suggested some degree of bias. The most frequently reported determinants of GDM were previous macrosomic babies, maternal obesity, family history of diabetes, previous miscarriage, and advanced maternal age.

CONCLUSION

The prevalence of GDM in Nigeria is high and efforts should be geared at modifying its risk factors so as to reduce its prevalence and prevent the associated complications.

Mediterranean Diet for the Prevention of Gestational Diabetes in the Covid-19 Era: Implications of Il-6 In Diabesity

The aim of this review is to highlight the influence of the Mediterranean Diet (MedDiet) on Gestational Diabetes Mellitus (GDM) and Gestational Weight Gain (GWG) during the COVID-19 pandemic era and the specific role of interleukin (IL)-6 in diabesity. It is known that diabetes, high body mass index, high glycated hemoglobin and raised serum IL-6 levels are predictive of poor outcomes in coronavirus disease 2019 (COVID-19). The immunopathological mechanisms of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection include rising levels of several cytokines and in particular IL-6. The latter is associated with hyperglycemia and insulin resistance and could be useful for predicting the development of GDM. Rich in omega-3 polyunsaturated fatty acids, vitamins, and minerals, MedDiet improves the immune system and could modulate IL-6, C reactive protein and Nuclear Factor (NF)-κB. Moreover, polyphenols could modulate microbiota composition, inhibit the NF-κB pathway, lower IL-6, and upregulate antioxidant enzymes. Finally, adhering to the MedDiet prior to and during pregnancy could have a protective effect, reducing GWG and the risk of GDM, as well as improving the immune response to viral infections such as COVID-19.

Sleep disturbances during pregnancy and adverse maternal and fetal outcomes: A systematic review and meta-analysis

Sleep disturbances are highly prevalent in pregnancy and are frequently overlooked as a potential cause of significant morbidity. The association between sleep disturbances and pregnancy outcomes remains largely controversial and needs to be clarified to guide management. To evaluate the association between sleep disturbances and maternal complications and adverse fetal outcomes, we performed a systematic search of PubMed, Embase and Web of Science for English-language articles published from inception to March 6, 2020, including observational studies of pregnant women with and without sleep disturbances assessing the risk of obstetric complications in the antenatal, intrapartum or postnatal period, and neonatal complications. Data extraction was completed independently by two reviewers. We utilized the Newcastle-Ottawa Scales to assess the methodological quality of included studies and random-effect models to pool the associations. A total of 120 studies with 58,123,250 pregnant women were included. Sleep disturbances were assessed, including poor sleep quality, extreme sleep duration, insomnia symptoms, restless legs syndrome, subjective sleep-disordered breathing and diagnosed obstructive sleep apnea. Significant associations were found between sleep disturbances in pregnancy and a variety of maternal complications and adverse fetal outcomes. Overall sleep disturbances were significantly associated with pre-eclampsia (odds ratio = 2.80, 95% confidence interval: 2.38-3.30), gestational hypertension (1.74, 1.54-1.97), gestational diabetes mellitus (1.59, 1.45-1.76), cesarean section (1.47, 1.31-1.64), preterm birth (1.38, 1.26-1.51), large for gestational age (1.40, 1.11-1.77), and stillbirth (1.25, 1.08-1.45), but not small for gestational age (1.03, 0.92-1.16), or low birth weight (1.27, 0.98-1.64). Sleep disturbances were related to higher morbidities in pregnant women who are 30 y or older and overweight before pregnancy. The findings indicate that sleep disturbances, which are easily ignored and treatable for both pregnant women and clinical services, deserve more attention from health care providers during prenatal counseling and health care services.

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

Background

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

Methods

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

Results

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

Conclusions

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

Serum Metabolites as an Indicator of Developing Gestational Diabetes Mellitus Later in the Pregnancy: A Prospective Cohort of a Chinese Population

OBJECTIVE

Gestational diabetes mellitus (GDM) is a common metabolic disorder with onset during pregnancy. However, the etiology and pathogenesis of GDM have not been fully elucidated. In this study, we used a metabolomics approach to investigate the relationship between maternal serum metabolites and GDM in early pregnancy.

METHODS

A nested case-control study was performed. To establish an early pregnancy cohort, pregnant women in early pregnancy (10-13⁺⁶ weeks) were recruited. In total, 51 patients with GDM and 51 healthy controls were included. Serum samples were analyzed using an untargeted high-performance liquid chromatography mass spectrometry metabolomics approach. The relationships between metabolites and GDM were analyzed by an orthogonal partial least-squares discriminant analysis. Differential metabolites were evaluated using a KEGG pathway analysis.

RESULTS

A total of 44 differential metabolites were identified between GDM cases and healthy controls during early pregnancy. Of these, 26 significant metabolites were obtained in early pregnancy after false discovery rate (FDR < 0.1) correction. In the GDM group, the levels of L-pyroglutamic acid, L-glutamic acid, phenylacetic acid, pantothenic acid, and xanthine were significantly higher and the levels of 1,5-anhydro-D-glucitol, calcitriol, and 4-oxoproline were significantly lower than those in the control group. These metabolites were involved in multiple metabolic pathways, including those for amino acid, carbohydrate, lipid, energy, nucleotide, cofactor, and vitamin metabolism.

CONCLUSIONS

We identified significant differentially expressed metabolites associated with the risk of GDM, providing insight into the mechanisms underlying GDM in early pregnancy and candidate predictive markers.

Association between sleep duration in early pregnancy and risk of gestational diabetes mellitus: a prospective cohort study

AIMS

As cohort studies of the impact of sleep duration during early pregnancy on gestational diabetes mellitus (GDM) are lacking, our study aimed to explore the association between sleep duration in the first trimester and GDM in one region of mainland China.

METHODS

For this prospective cohort study, sleep duration data were collected from 3692 pregnant women at the first prenatal care appointment before 14 weeks of gestation. Multivariable log-binomial regression models were used to analyze the association of sleep duration with GDM after adjusting for demographic characteristics, health status (such as family history of diabetes, history of GDM, prepregnancy body mass index, gestational weight gain) and lifestyle habits (such as physical activity, dietary intakes).

RESULTS

Our cohort included 166 (4.5%) short sleepers and 505 (14%) long sleepers. Shorter sleep duration was more likely to be observed in women aged ≥35 years who were multiparous, and had previous pregnancy, insufficient gestational weight gain, engaged in more vigorous physical activity, drank alcohol, were vegan and/or never took folic-acid supplements. Compared with normal sleepers (29%), the prevalence of GDM was significantly higher in short sleepers (38%; P = 0.01), but not in long sleepers (31%; P = 0.224). In the multivariable model, women with short sleep durations during early pregnancy had a 32% greater risk of GDM [adjusted risk ratio (aRR): 1.32, 95% CI: 1.06-1.63], whereas long sleepers did not (aRR: 1.09, 95% CI: 0.94-1.26).

CONCLUSION

Short sleep duration during early pregnancy is associated with an increased risk of GDM. This suggests that more attention should be paid to controlling the development of GDM in pregnant women with insufficient sleep.

Prevalence, Prevention, and Lifestyle Intervention of Gestational Diabetes Mellitus in China

Gestational diabetes mellitus (GDM) has become an epidemic and has caused a tremendous healthy and economic burden in China, especially after the "two-child policy" put into effect on October 2015. The prevalence of GDM has continued to increase during the past few decades and is likely to see a further rise in the future. The public health impact of GDM is becoming more apparent in China and it might lead to the development of chronic non-communicable diseases in the long-term for both mothers and their children. Early identification of high-risk individuals could help to take preventive and intervention measures to reduce the risk of GDM and adverse perinatal outcomes. Therefore, a focus on prevention and intervention of GDM in China is of great importance. Lifestyle interventions, including dietary and physical exercise intervention, are effective and first-line preventive strategies for GDM prevention and intervention. The GDM One-day Care Clinic established in 2011, which educates GDM patients on the basic knowledge of GDM, dietary intervention, physical exercise, weight management, and blood glucose self-monitoring methods, sets a good model for group management of GDM and has been implemented throughout the hospitals as well as maternal and child health centers in China. The current review focus on the prevalence, risk factors, as well as prevention and lifestyle intervention of GDM in China for better understanding of the latest epidemiology of GDM in China and help to improve maternal and neonatal pregnancy outcomes and promote long-term health for women with GDM.

Economic burden of IADPSG gestational diabetes diagnostic criteria in China: propensity score matching analysis from a 7-year retrospective cohort

INTRODUCTION

The International Association of Diabetes and Pregnancy Study Group (IADPSG) criteria for gestational diabetes mellitus (GDM) increased the morbidity significantly, but the cost and effectiveness of its application are still unclear. This study aimed to analyze the impact of the IADPSG criteria for diagnosing GDM in China on the perinatal outcomes, and medical expenditure of GDM women versus those with normal glucose tolerance (NGT).

RESEARCH DESIGN AND METHODS

We conducted a retrospective cohort study involving 7794 women admitted at the First Affiliated Hospital of Jinan University (Guangzhou, China), from November 1, 2010 to October 31, 2017. The perinatal outcomes and medical expenditure were retrieved from the electronic medical records in the hospital. Propensity score matching (PSM, in a 1:1 ratio) algorithm was used to minimize confounding effects on the difference in the two cohorts.

RESULTS

PSM minimized the difference of baseline characteristics between women with and without GDM. Of 7794 pregnant women, half (n=3897) were all of the pregnant women with GDM admitted to the hospital during the period, the other half women had NGT and were selected randomly to match with their counterparts. Adopting the IADPSG criteria was associated with reduced risk of emergency cesarean section, polyhydramnios, turbid amniotic fluid and perineal injury (p<0.01 for all) and having any one of the adverse fetal outcomes (p<0.01), including fetal distress, umbilical cord around the neck, neonatal encephalopathy, admission to neonatal intensive care unit, birth trauma, neonatal hypoglycemia and fetal death. After PSM, the median total medical expenditure by the GDM women was ¥912.9 (US$140.7 in 2015) more than that of the the NGT women (p=0.09).

CONCLUSIONS

Despite the increasing medical expenditure, screening at 24-28 gestational weeks under the IADPSG guidelines with the 2-hour, 75 g oral glucose tolerance test can improve short-term maternal and neonatal outcomes.

A mid-pregnancy risk prediction model for gestational diabetes mellitus based on the maternal status in combination with ultrasound and serological findings

Although previous studies have proposed predictive models of gestational diabetes mellitus (GDM) based on maternal status, they do not always provide reliable results. The present study aimed to create a novel model that included ultrasound data of maternal fat distribution and serum inflammatory factors. The clinical data of 1,158 pregnant women treated at Tangshan Gongren Hospital and eight other flagship hospitals in Tangshan, including the First Hospital of Tangshan Gongren Hospital group, Ninth Hospital of Tangshan Gongren Hospital group, Tangshan Gongren Hospital group rehabilitation hospital, Tangshan railway central hospital, Tangshan Gongren Hospital group Fengnan hospital, Tangshan Gongren Hospital group Qianan Yanshan hospital, Tangshan Gongren Hospital group Qianxi Kangli hospital and Tangshan Gongren Hospital group Jidong Sub-hospital, were analyzed following the division of subjects into GDM and non-GDM groups according to their diagnostic results at 24-28 weeks of pregnancy. Univariate analysis was performed to investigate the significance of the maternal clinical parameters for GDM diagnosis and a GDM prediction model was established using stepwise regression analysis. The predictive value of the model was evaluated using a Homer-Lemeshow goodness-of-fit test and a receiver operating characteristic curve (ROC). The model demonstrated that age, pre-pregnancy body mass index, a family history of diabetes mellitus, polycystic ovary syndrome, a history of GDM, high systolic pressures, glycosylated hemoglobin levels, triglyceride levels, total cholesterol levels, low-density lipoprotein cholesterol levels, serum hypersensitive C-reactive protein, increased subcutaneous fat thickness and visceral fat thickness were all correlated with an increased GDM risk (all P<0.01). The area under the curve value was 0.911 (95% CI, 0.893-0.930). Overall, the results indicated that the current model, which included ultrasound and serological data, may be a more effective predictor of GDM compared with other single predictor models. In conclusion, the present study developed a tool to determine the risk of GDM in pregnant women during the second trimester. This prediction model, based on various risk factors, demonstrated a high predictive value for the GDM occurrence in pregnant women in China and may prove useful in guiding future clinical practice.

Association of circulating CEACAM1 levels and insulin sensitivity in gestational diabetes mellitus

BACKGROUND

The aim of this study was to estimate the levels of circulating carcinoembryonic antigen-related cell adhesion molecule 1 (CEACAM1) in subjects with gestational diabetes mellitus (GDM) and investigate the relationships between CEACAM1 and GDM.

METHODS

Circulating CEACAM1 levels were measured by ELISA kit in 70 women with GDM and 70 normal glucose tolerance (NGT) pregnant women. Blood samples were collected to detect fasting plasma glucose (FPG), fasting insulin (FINS) and glycosylated hemoglobin (HbA1c) levels in all participants. Insulin sensitivity index (ISOGTT) was calculated to assess insulin sensitivity. Correlation analysis was performed between serum CEACAM1 levels and other parameters.

RESULTS

Circulating CEACAM1 levels were higher in the GDM group than that in the NGT pregnant group, however, the difference showed no statistical significance (1889.82 ± 616.14 vs 1758.92 ± 433.15 pg/ml, p > 0.05). In GDM group, CEACAM1 was positively correlated with ISOGTT (R = 0.39, P = 0.001), while negatively with 1 h post-meal plasma insulin level (1hPINS) (R = -0.32, P = 0.008), 2 h post-meal plasma insulin level (2hPINS) (R = -0.33, P = 0.006) and area under curve of insulin (AUCI) (R = -0.36, P = 0.002) when adjusting for maternal age and gestational age.

CONCLUSIONS

The present study showed that circulating CEACAM1 levels did not differ in both GDM and NGT groups. However, we found a significant positively correlation between CEACAM1 and insulin sensitivity in the GDM group.

Prevalence of gestational diabetes mellitus and its determinants among pregnant women in Beijing

Objective: To investigate the prevalence of gestational diabetes mellitus (GDM) and its determinants among pregnant women in the Tongzhou district of Beijing, China.Methods: This study was performed on data collected in the routine work of the prenatal health care system from 27,119 pregnant women in the Tongzhou district of Beijing during 2013-2018. Univariate and multivariate logistic regression analyses were used to assess the factors associated with GDM.Results: The overall prevalence of GDM was 24.24%, and it showed an increasing trend over the 6 years. A univariate analysis showed that the prevalence of GDM increased with age (p < .001). In multivariate analysis, it was found that women with a non-local household registration, as well as those without a local household registration but whose husbands had one, had a lower risk for GDM than both spouses who had local registration. Women who were overweight/obese had a higher risk for GDM than women with a normal pre-pregnancy body mass index. Multipara women had a lower likelihood of developing GDM.Conclusions: We found a slightly higher prevalence of GDM in the Tongzhou district of Beijing than has been found in other studies, and the prevalence rose over the 6 years of the study. Advanced age, pre-pregnancy overweight or obesity, and local household registration were important risk factors for GDM. Multiparity may be a protective factor against developing GDM. Intensive health education on related determinants should be strengthened for the prevention and control of GDM, especially in high-risk women.

A Critical Review of Proteomic Studies in Gestational Diabetes Mellitus

Gestational diabetes mellitus is a progressive and complex pregnancy complication, which threatens both maternal and fetal health. It is urgent to screen for specific biomarkers for early diagnosis and precise treatment, as well as to identify key moleculars to better understand the pathogenic mechanisms. In the present review, we comprehensively summarized recent studies of gestational diabetes using mass spectrometry-based proteomic technologies. Focused on the entire experimental design and proteomic results, we showed that these studies have covered a broad range of research contents in terms of sampling time, sample types, and outcome associations. Although most of the studies only stayed in the stage of initial discovery, several proteins were further verified to be efficient for disease diagnosis. Functional analysis of all the combined significant proteins also showed that a small number of proteins are known to be involved in the regulation of insulin or indirect signaling pathways. However, many factors such as diagnostic criteria, sample processing, proteomic method, and statistical method can greatly affect the identification of reproducible and reliable protein candidates. Thus, we further provided constructive suggestions and recommendations for carrying out proteomic or follow-up studies of gestational diabetes or other pregnancy complications in the future.

Relationship between Maternal Central Obesity and the Risk of Gestational Diabetes Mellitus: A Systematic Review and Meta-Analysis of Cohort Studies

OBJECTIVE

Nowadays, body mass index (BMI) is used to evaluate the risk stratification of obesity-related pregnancy complications in clinics. However, BMI cannot reflect fat distribution or the proportion of adipose to nonadipose tissue. The objective of this study is to evaluate the association of maternal first or second trimester central obesity with the risk of GDM. Research Design and Methods. We searched in PubMed, Embase, and Web of Science for English-language medical literature published up to 12 May 2019. Cohort studies were only included in the search. Abdominal subcutaneous fat thickness, waist circumference, waist-hip ratio or body fat distribution were elected as measures of maternal central obesity, and all diagnostic criteria for GDM were accepted. The random effect meta-analysis was performed to evaluate the relationship between central obesity and the risk of GDM.

RESULTS

A total of 11 cohort studies with an overall sample size of 27,675 women and 2,226 patients with GDM were included in the analysis. The summary estimate of GDM risk in the central obesity pregnant women was 2.76 (95% confidence interval [CI]: 2.35-3.26) using the adjusted odds ratio (OR). The degree of heterogeneity among the studies was low (I ² = 14.4, P = 0.307). The subgroup analyses showed that heterogeneity was affected by selected study characteristics (methods of exposure and trimesters). After adjusting for potential confounds, the OR of adjusted BMI was significant (OR = 3.07, 95% CI: 2.35-4.00).

CONCLUSIONS

Our findings indicate that the risk of GDM was positively associated with maternal central obesity.

Sleep quality and gestational diabetes in pregnant women: a systematic review and meta-analysis

Poor sleep quality is very common among pregnant women. Gestational diabetes mellitus (GDM) has been related to various adverse maternal and neonatal outcomes. The aim of this systematic review was to examine the association between poor sleep quality and gestational diabetes risk. Following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines, a systematic search was conducted in five electronic databases from inception to February 2019. Studies that examined the relationship between sleep quality and glucose in pregnant women were screened for eligibility. Pooled odds ratio (OR) with 95% confidence interval (CI) was calculated from aggregate data using a fixed-effect model. Thirteen non-experimental studies (n = 21,194 women) were eligible for inclusion. Poor sleep quality was measured using subjective questionnaires in nine studies and objective methods (actigraphy or polysomnography) in four studies. GDM was typically diagnosed following standard guidelines. Eight studies were included in the meta-analysis for GDM. Overall, self-reported poor sleep quality was a significant risk factor for GDM (pooled OR = 1.43, 95%CI: 1.16,1.77, p = 0.001). Three studies examined the association between objective sleep quality and GDM, but no significant relationship was observed. Subjective poor sleep quality was related to an increased risk for GDM, while objectively measured sleep quality was not. This review was limited by the assessment of sleep quality. Future larger studies are warranted to examine the effects of sleep quality on glucose metabolism in pregnancy. Ideally, these studies should measure sleep quality using both validated questionnaires and objective methods. These will provide further directions for improving sleep during pregnancy and exploring its effects on glucose metabolism.

Sleep in Pregnancy and Maternal Hyperglycemia: a Narrative Review

PURPOSE OF REVIEW

Prevalence of gestational diabetes is increasing globally and sleep may be a modifiable lifestyle factor associated with it. However, existing findings have been inconsistent.

RECENT FINDINGS

Majority of studies reviewed found a link between extreme sleep durations and elevated risk of maternal hyperglycemia. The findings with sleep-disordered breathing are less consistent. Methodological differences across studies, in terms of sleep assessment methods (subjective vs. objective), study population (low vs. high risk), classification of gestational diabetes and sleep problems, may have contributed to the inconsistent findings. Some studies also suggest the possibility of trimester-specific association between sleep and maternal hyperglycemia. Large-scale prospective studies comprising objective measurements of sleep, preferably over three trimesters and preconception, are needed to better evaluate the relationship between sleep and maternal hyperglycemia.

The effect of prepregnancy body mass index on the risk of gestational diabetes mellitus: A systematic review and dose-response meta-analysis

This study was conducted to investigate the effect of the prepregnancy BMI on the risk of gestational diabetes mellitus (GDM). Five electronic databases, including PubMed, Scopus, Embase, Web of Science, and Google Scholar, were searched for literature published until 1 January 2018. The two-stage, random effect meta-analysis was performed to compare the dose-response relationship between BMI and GDM. As well as studies with categorized BMI, studies that treat BMI as a continuous variable were analysed. A total of 33 observational studies with an overall sample size of 962 966 women and 42 211 patients with GDM were included in analysis. The pooled estimate of GDM risk in the underweight, overweight, and obese pregnant women was 0.68, 2.01, and 3.98 using the adjusted OR and 0.34, 1.52, and 2.24 using the adjusted RR. The GDM risk increased 4% per unit of increase in BMI with both the crude and adjusted OR/RR models. Also, the risk of GDM increased 19% with the crude model and 14% with the adjusted model. The existence of dose-response relationship between the pre-pregnancy BMI and GDM can strengthen the scientific background for vigorous public health interventions for the control of pre-pregnancy BMI as well as the weight gain during pregnancy.

Socioeconomic, environmental and lifestyle factors associated with gestational diabetes mellitus: A matched case-control study in Beijing, China

Gestational diabetes mellitus (GDM) is a common health problem during pregnancy and its prevalence is increasing globally, especially in China. The aim of this study was to investigate socioeconomic, environmental and lifestyle factors associated with GDM in Chinese women. A matched pair case-control study was conducted with 276 GDM women and 276 non-GDM women in two hospitals in Beijing, China. Matched factors include age and pre-pregnancy body mass index (BMI). GDM subjects were defined based on the International Association of Diabetes Study Group criteria for GDM. A conditional logistic regression model with backward stepwise selection was performed to predict the odds ratio (OR) for associated factors of GDM. The analyses of data show that passive smoking at home (OR = 1.52, p = 0.027), passive smoking in the workplace (OR = 1.71, p = 0.01), and family history of diabetes in first degree relatives (OR = 3.07, p = 0.004), were significant factors associated with GDM in Chinese women. These findings may be utilized as suggestions to decrease the incidence of GDM in Chinese women by improving the national tobacco control policy and introducing public health interventions to focus on the social environment of pregnant women in China.