Relationship between gestational body mass index change and the risk of gestational diabetes mellitus: a community-based retrospective study of 41,845 pregnant women

Risk Factors for Gestational Diabetes Mellitus in Mainland China: A Systematic Review and Meta-Analysis

Objective

This study aimed to identify and evaluate risk factors associated with gestational diabetes mellitus (GDM) in mainland China.

Methods

Eight electronic databases were searched for literature published from January 2010 until December 2023. Heterogeneity was quantified using I2. Data were pooled by fixed or random effects models and expressed as odds ratio and 95% confidence intervals.

Results

A total of 69 observational studies with an overall sample size of 2,138,032 Chinese women and 219,303 patients with GDM were included in the analysis. After adjusting confounders, older maternal age (OR = 1.12, 95% CI: 1.09-1.15), maternal age ≥35 years (OR = 1.96, 95% CI: 1.74-2.21), higher pre-pregnancy body mass index (OR = 1.24, 95% CI: 1.17-1.32), pre-pregnancy overweight (OR = 1.78, 95% CI: 1.64-1.92) or obesity (OR 2.52, 95% CI: 2.06-3.08), family history of diabetes (OR = 1.85, 95% CI: 1.58-2.17), history of GDM (OR = 4.09, 95% CI: 2.13-7.82), and elevated levels of fasting plasma glucose (OR = 2.54, 95% CI: 2.13-3.01), hemoglobin (OR = 1.47, 95% CI: 1.14-1.89) and serum triglycerides (OR = 1.69, 95% CI: 1.31-2.16) in early pregnancy were associated with an increased risk of GDM in mainland China. But gravidity ≥2 (OR = 1.06, 95% CI: 0.89-1.27), conception by assisted reproductive technology analyses (OR = 1.54, 95% CI: 0.95-2.51) were not associated with GDM, and parity ≥1 (OR = 0.88, 95% CI: 0.82-0.94) was related to lower risk of GDM. In available unadjusted studies, history of abortion (OR = 1.34, 95% CI: 1.31-1.37) increased risk of GDM, non-Han ethnicity (OR = 0.78, 95% CI: 0.59-1.03) and high school or lower education level (OR1.09, 95% CI: 0.94-1.26) showed no correlation with GDM.

Conclusion

The key risk factors for GDM in mainland China included older maternal age, maternal age ≥35 years, pre-pregnancy overweight or obesity, family history of diabetes, history of GDM, elevated levels of FPG, Hb, and serum TG in early pregnancy. Early identification and intervention for women at high risk should be performed to prevent the development of GDM.

Using a robust model to detect the association between anthropometric factors and T2DM: machine learning approaches

BACKGROUND

The aim of this study was to evaluate the potential models to determine the most important anthropometric factors associated with type 2 diabetes mellitus (T2DM).

METHOD

A dataset derived from the Mashhad Stroke and heart atherosclerotic disorders (MASHAD) study comprising 9354 subject aged 65 - 35. 25% (2336 people) of subjects were diabetic and 75% (7018 people) where non-diabetic was used for the analysis of 10 anthropometric factors and age that were measured in all patients. A K-nearest neighbor (KNN) model was used to assess the association between T2DM and selected factors. The model was evaluated using accuracy, sensitivity, specificity, precision and f1-measure parameters. The receiver operating characteristic (ROC) curve and factor importance analysis were also determined. The performance of the KNN model was compared with Artificial neural network (ANN) and support vector machine (SVM) models.

RESULT

After feature selection analysis and assessing multicollinearity, six factors (Mid-arm Circumference (MAC), Waist Circumference (WC), Body Roundness Index (BRI), Body Adiposity Index (BAI), Body Mass Index (BMI), age) were used in the final model. BRI, BAI and MAC factors in males and BMI, BRI, and MAC factors in females were found to have the greatest association with T2DM. The accuracy of the KNN model was approximately 93% for both genders. The best K (number of neighbors) for the model was 4 which had the lowest error rate. The area under the ROC curve (AUC) was 0.985 for men and 0.986 for women. The KNN model achieved the best result of the models explored.

CONCLUSION

The KNN model had a high accuracy (93%) for predicting the association between anthropometric factors and T2DM. Selecting the K parameter (nearest neighbor) has an essential impact on reducing the error rate. Feature selection analysis reduces the dimensions of the KNN model and increases the accuracy of final results.

Decision-making behavior of blood glucose management and its influencing factors in pregnant women with gestational diabetes mellitus

BACKGROUND

Currently, most studies only focus on the glucose management level and self- management behavior of pregnant women with gestational diabetes mellitus, but lack analysis and discussion on their decision-making behavior and influencing factors during glucose management.

AIM

This study aimed to investigate the decision-making behavior of blood glucose management and its influencing factors among pregnant women with gestational diabetes mellitus in China.

METHODS

This was a prospective study. A convenience sampling method was used to select pregnant women with gestational diabetes mellitus. A total of 1,405 pregnant women with gestational diabetes mellitus from eight hospitals in China were included between June 1 and December 31, 2023. Three types of questionnaires on knowledge, protection motivation, and decision-making behavior regarding blood glucose management were administered to participants. Multivariable logistic regression was conducted to determine the decision-making behavior of blood glucose management and its influencing factors (P<0.05).

RESULTS

The mean score of the glucose management knowledge was 39.56 ± 8.45 points (standard score 65.9%). The score for decision-making behavior was 70.05 ± 9.85 points (standard score 93.4%). Most dimensions of protection motivations were higher than 20 points (standard score 80.0%).

CONCLUSIONS

The mean score for glucose management knowledge was at a medium score level. Most dimensions of protection motivations were at a high or medium score level. The decision-making behavior was at a high score level. The pregnant women with rich glucose management knowledge and protection motivation are more likely to take active decision-making behaviors and actively manage their blood glucose levels. The influencing factors of decision-making behavior included length of time after diagnosed with gestational diabetes mellitus, gestational diabetes mellitus history, self-efficacy, severity, susceptibility, response efficacy, and response costs (P<0.05, for all).

Association between Pre-pregnancy BMI and Pregnancy Outcomes in Women with Gestational Diabetes: A Retrospective Cohort Study

Background & Objective

The specific influence of the pre-pregnancy body mass index (PPBMI) on women with gestational diabetes mellitus (GDM) is unclear. Our objective was to investigate how PPBMI categories affect pregnancy and neonatal outcomes in women with GDM.

Methods

A retrospective cohort study was conducted using data from patients attending the Fujian Maternity and Child Health Hospital (Fuzhou, China) from 2021 to 2023. The participant records were stratified into four groups according to their BMI values: underweight, normal-weight, overweight, and obese. The pregnancy and neonatal outcomes for these BMI categories were analyzed using multivariable logistic regression.

Results

The study included data from 2,909 pregnant women diagnosed with GDM. Underweight women with GDM showed significantly lower risks of pregnancy-induced hypertension (PIH) (adjusted OR, 0.26) and cesarean sections (adjusted OR, 0.55) but higher risks of low body weight (LBW) infants (adjusted OR, 3.40). Overweight and obese women experienced higher risks of PIH (adjusted OR, 2.96), cesarean sections (adjusted OR, 1.62), and macrosomia (adjusted OR, 1.43).

Conclusion

PPBMIs significantly impact pregnancy outcomes in women with GDM. Both underweight and overweight/obese categories are associated with adverse outcomes, highlighting the need for pre-pregnancy counseling and interventions to achieve and maintain a healthy BMI.

Prevalence and factors associated with gestational diabetes mellitus in Malaysia: a population-based study comparing 2016 and 2022

BACKGROUND

Gestational diabetes mellitus (GDM) poses substantial health risks to both mothers and infants. Malaysia exhibits a heightened prevalence of GDM.

OBJECTIVE

This study aims to examine the changes in the prevalence of GDM between 2016 and 2022 and its determining factors.

METHODS

The data analysed in this study were derived from the National Health and Morbidity Survey (NHMS) 2016 and 2022, a nationwide study employing a two-stage stratified random sampling design in Malaysia. Changes in the prevalence were compared between data from NHMS 2016 and 2022, while factors were evaluated based on data from NHMS 2022. Descriptive statistics and multiple logistic regression analyses were performed using IBM SPSS version 27.

RESULTS

The prevalence of GDM increased from 12.5% in 2016 to 27.1% in 2022. In both years, the prevalence was highest among those aged 44-49 years, those of Indian ethnicity, those in higher income groups and those with higher education levels. Advanced maternal age, high body mass index (BMI) and hypertension were associated with a greater risk of GDM.

CONCLUSION

The prevalence of GDM among the Malaysian population doubled from 2016 to 2022. The findings underscore the importance of implementing targeted programs for expectant mothers in high-risk groups to mitigate the incidence of GDM and its associated morbidities.

Non-Pharmacological Management of Gestational Diabetes Mellitus with a High Fasting Glycemic Parameter: A Hospital-Based Study in Vietnam

Background/Objectives: The prevalence of gestational diabetes mellitus (GDM) is increasing at an alarming rate worldwide. Delayed management can lead to adverse composite outcomes for both mother and her offspring. To our knowledge, the clinical association between glycemic parameters and the results of the non-pharmacological GDM approach remains limited; thus, this study aimed to address this important clinical issue in the literature. Methods: This was a retrospective cross-sectional study of 174 Vietnamese pregnant women with the positive oral glucose tolerance test (OGTT) for a high fasting glycemic parameter at Hung Vuong Hospital from 04/2022 to 07/2022. This study aimed to evaluate the success rate of GDM with an elevated index of fasting glycemic concentration which was managed after 2 weeks of a dietary regimen combined with adequate physical activities and to reveal its related factors. Results: Out of 174 singleton pregnancies that met the inclusion criteria, 103 GDM pregnant women were successfully managed after 2 weeks of monitoring (59.2%; 95% confidence intervals (CI): 51.9-66.5). The study revealed a fair correlation between the corresponding test of blood glucose at OGTT and after 2 weeks of GDM management (r = 0.270-0.290, p < 0.0001). The GDM pregnant women with an elevated fasting glycemic parameter and with any of elevated 1 h or 2 h blood glucose levels and in cases of three elevated glycemic parameters (fasting, 1 h, and 2 h blood glucose at the initial results of OGTT) reduced the success rate of glycemic control to 56.5%, 49.2%, respectively, compared to the group with solely a high fasting index of blood glucose (69.6%). The pregnant women who participated in high-intensity sports activities related to a two-fold increase in success rate compared with the group engaging in light and moderate-intensity physical activity. Conclusions: The success rate of glycemic control in GDM women was highest in the group with solitary fasting hyperglycemia and lower in the contributory groups with two and three high parameters. The application of diet therapy plus physical activities among GDM pregnant women is potentially necessary to improve the effectiveness of treatment, minimize adverse pregnancy outcomes, and reduce substantially the hospitalization rate.

Effects of thyroid hormones modify the association between pre-pregnancy obesity and GDM: evidence from a mediation analysis

Objective

Conflicting associations have been noted between thyroid function and gestational diabetes mellitus (GDM), with indications that pre-pregnancy BMI might influence these relationships. This study aims to examine the effect of thyroid hormone indices and their mediation role on the risk of GDM.

Methods

Pregnant women in our study were recruited from the Zhoushan Pregnant Women Cohort, Zhejiang Province, China. Participants who had their first prenatal follow-up and measured thyroid biomarkers in the first trimester, and oral glucose tolerance test (OGTT) records in the second trimester were eligible for inclusion in this study. The data were extracted from the Electronic Medical Record System database, at Zhoushan Maternal and Child Care Hospital. Maternal information about sociodemographic and health-related characteristics was extracted from the dataset. A unique personal identification number was provided to link both datasets. Multivariate logistic regression models were applied to investigate the correlations between thyroid hormone indices with GDM. The interaction effects of first-trimester thyroid hormone indices with pre-pregnancy BMI on GDM risk using a generalized linear regression model. Furthermore, the mediation analysis was used to explore the potential mediating effects of thyroid hormone indices on the relationship between pre-pregnancy BMI and GDM.

Results

Overall, 5895 pregnant women were included in this study. The first-trimester FT4, thyroid feedback quantile-based index (TFQI), thyrotropin index (TSHI) and thyrotroph thyroxine resistance index (TT4RI) levels were negatively associated with fasting blood glucose (FBG) and postprandial blood glucose (PBG2H) in the second trimester (all P<0.05); FT3 and the FT3-to-FT4 ratio levels were positively associated with PBG1H and PBG2H in the second trimester (all P<0.05). Moreover, there were significant correlations between the highest quartile FT4, FT3, FT3-to-FT4 ratio, TSHI, and TFQI with GDM (all P < 0.05). The mediating effect of thyroid hormone parameters was 24.9% on the association between pre-pregnancy BMI and GDM.

Conclusions

In conclusion, the low FT4, high FT3-to-FT4 ratio, and low TFQI in the first trimester significantly increase the risk of GDM and should be given more attention. Furthermore, increased pre-pregnancy BMI might partially increase the risk of GDM by influencing the body's thyroid function.

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.

Exposure of pregnant women to neonicotinoids in Wenzhou City, East China: A biomonitoring study

BACKGROUND

China produces and consumes a large amount of neonicotinoids. A non-negligible exposure to neonicotinoids might occur for Chinese pregnant women, but relevant data remain limited.

OBJECTIVE

To investigate the exposure to neonicotinoids by urinary biomonitoring in pregnant women from Wenzhou City, East China.

METHODS

We selected 432 pregnant women in Wenzhou City in 2022. A total of eight parent neonicotinoids and four metabolites were determined in single spot urine by liquid chromatography coupled to mass spectrometry. Basic characteristics, physical activity, pre-pregnant body mass index, and intake of drinking water and food were investigated by the questionnaire. Health risk was assessed by hazard quotient (HQ) and hazard index (HI) based on human safety thresholds derived from different health endpoints.

RESULTS

Neonicotinoids and their metabolites in urine had a detection frequency between 0 % and 80.1 %. At least one neonicotinoid or metabolite was detected in 93.5 % of urine samples. Except for clothianidin (51.2 %) and N-desmethyl-acetamiprid (80.1 %), the detection frequencies of other neonicotinoids and metabolites ranged from 0 % to 43.8 %. The summed concentrations of all neonicotinoids and their metabolites ranged from < LOD to 222.83 μg/g creatinine with the median concentration of 2.58 μg/g creatinine. Maternal age, educational level, occupation, household income, screen time, and pre-pregnant body mass index were associated with detection frequencies or concentrations of neonicotinoids and their metabolites. Pregnant women with higher consumption frequencies of wheat, fresh vegetable, shellfish, fresh milk, and powdered milk had higher detection frequencies of neonicotinoids and their metabolites. Both HQ and HI were less than one.

CONCLUSIONS

Overall, pregnant women in Wenzhou City showed a notable frequency of exposure to at least one neonicotinoid, although the exposure frequency for each specific neonicotinoid was generally low. Several food items derived from plants and animals were potential exposure sources. A low health risk was found based on current safety thresholds.

Identifying First-Trimester Risk Factors for SGA-LGA Using Weighted Inheritance Voting Ensemble Learning

The classification of fetuses as Small for Gestational Age (SGA) and Large for Gestational Age (LGA) is a critical aspect of neonatal health assessment. SGA and LGA, terms used to describe fetal weights that fall below or above the expected weights for Appropriate for Gestational Age (AGA) fetuses, indicate intrauterine growth restriction and excessive fetal growth, respectively. Early prediction and assessment of latent risk factors associated with these classifications can facilitate timely medical interventions, thereby optimizing the health outcomes for both the infant and the mother. This study aims to leverage first-trimester data to achieve these objectives. This study analyzed data from 7943 pregnant women, including 424 SGA, 928 LGA, and 6591 AGA cases, collected from 2015 to 2021 at the Third Affiliated Hospital of Sun Yat-sen University in Guangzhou, China. We propose a novel algorithm, named the Weighted Inheritance Voting Ensemble Learning Algorithm (WIVELA), to predict the classification of fetuses into SGA, LGA, and AGA categories based on biochemical parameters, maternal factors, and morbidity during pregnancy. Additionally, we proposed algorithms for relevance determination based on the classifier to ascertain the importance of features associated with SGA and LGA. The proposed classification solution demonstrated a notable average accuracy rate of 92.12% on 10-fold cross-validation over 100 loops, outperforming five state-of-the-art machine learning algorithms. Furthermore, we identified significant latent maternal risk factors directly associated with SGA and LGA conditions, such as weight change during the first trimester, prepregnancy weight, height, age, and obstetric factors like fetal growth restriction and birthing LGA baby. This study also underscored the importance of biomarker features at the end of the first trimester, including HDL, TG, OGTT-1h, OGTT-0h, OGTT-2h, TC, FPG, and LDL, which reflect the status of SGA or LGA fetuses. This study presents innovative solutions for classifying and identifying relevant attributes, offering valuable tools for medical teams in the clinical monitoring of fetuses predisposed to SGA and LGA conditions during the initial stage of pregnancy. These proposed solutions facilitate early intervention in nutritional care and prenatal healthcare, thereby contributing to enhanced strategies for managing the health and well-being of both the fetus and the expectant mother.

Is gestational diabetes mellitus in lean women a distinct entity warranting a modified management approach?

During pregnancy, insulin resistance and impaired insulin secretion may lead to the development of Gestational Diabetes Mellitus (GDM). Although a higher Body Mass Index (BMI) is often cited as a risk factor for the development of GDM, lean pregnant women are also at risk of developing GDM based on evidence from several studies. It is proposed that insulin deficiency (more than insulin resistance) leads to the development of GDM in women with low BMI (BMI <18.5 kg/m2). Neonates of these women are more at risk of preterm birth and small-for-gestational-age. Given this unique pathophysiology and phenotype, this entity needs a modified management approach. This article aims to raise awareness of GDM in lean women to encourage more research on this topic and create a modified management approach.

Source and health risk of urinary neonicotinoids in Tibetan pregnant women

High altitude could influence the level of exposure to neonicotinoids, but relevant data remain limited for people living in Tibet. We investigated 476 Tibetan pregnant women from Lhasa of Tibet, China in 2021 and measured eight neonicotinoids and four metabolites in urine. Food consumption was investigated by a food frequency questionnaire. Health risk was assessed by using hazard quotient (HQ) and hazard index (HI) based on acceptable daily dose or chronic reference dose. Neonicotinoids and metabolites were overall detected in 56.5% of urine samples with a median concentration being 0.73 μg g-1 creatinine. Four neonicotinoids or metabolites were detected in more than 10% of urine samples, including N-desmethyl-acetamiprid (47.5%), clothianidin (15.5%), thiamethoxam (16.0%), and imidacloprid (10.5%). Annual household income, family smoking, and pre-pregnancy body mass index were associated with the detection frequencies of neonicotinoids. Pregnant women with a higher consumption frequency of wheat, rice, fresh vegetable, fresh fruit, beef and mutton, fresh milk, yoghourt, candy and chocolate, or carbonated drinks had a higher detection frequency of neonicotinoids. Both HQ and HI were less than one. There was an evident exposure to neonicotinoids in Tibetan pregnant women with both plant- and animal-derived food items as exposure sources, but a low health risk was found based on current safety thresholds.

The relative validity of a semiquantitative food frequency questionnaire among pregnant women in the United Arab Emirates: The Mutaba'ah study

Background: Food frequency questionnaire (FFQ) is the most frequently used dietary assessment method in estimating dietary intakes in epidemiological studies. Aim: This study aimed to assess the relative validity of a semiquantitative FFQ in evaluating dietary intake among pregnant women in the United Arab Emirates. Methods: Within the Mutaba'ah study, a subsample of 111 pregnant women completed a semiquantitative FFQ and a single 24-hour dietary recall (24-HDR) regarded as the reference method. Absolute and energy-adjusted nutrient and food intakes between the FFQ and 24-HDR were compared using the Wilcoxon signed ranks test, correlations, Bland-Altman analysis, cross-classification, and weighted kappa analysis. Results: There were no significant differences in reported absolute intakes between the FFQ and 24-HDR for carbohydrates, whole grains, white meat, beta-carotene, vitamin K, sodium, and selenium. Spearman's correlation coefficients between the FFQ and 24-HDR ranged from 0.09 (trans fatty acids) to 0.5 (potassium) for absolute intakes. Correlation decreased after energy adjustment. Bland-Altman analysis showed that the FFQ overestimated intakes compared with 24-HDR and that the limits of agreement were wide. The average percentage of pregnant women classified into the same or adjacent quartile of intake by both methods was 73%. Weighted kappa values ranged from -0.02 (white meat) to 0.33 (magnesium). Conclusion: Our findings showed that the semi-quantitative FFQ is a useful tool in ranking pregnant women from the Emirati population according to their dietary intake. However, the validity of some estimated intakes was poor; hence, certain intakes should be interpreted with caution.

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

BACKGROUND

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

MATERIALS AND METHODS

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

RESULTS

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

CONCLUSION

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

Is There a Relationship between Adverse Pregnancy Outcomes and Future Development of Atherosclerosis?

Cardiovascular disease is one of the main death causes globally. Effective cardiovascular risk management requires a thorough understanding of the mechanisms underlying the disorder. Establishing early markers of the disease allows a timely intervention and prevention of further atherosclerosis development. Multiple studies confirm the correlation between pregnancy disorders and cardiovascular disease in the postpartum period. Moreover, over 30% of women experience adverse pregnancy outcomes. Thus, the examination of the links between these conditions and atherosclerotic cardiovascular disease may help to identify gender-specific risk factors. In this review, we will explore the association between several adverse pregnancy outcome conditions and atherosclerosis. The current analysis is based on the data from several recent studies on the mechanisms behind gestational diabetes, hypertensive disorders of pregnancy, miscarriages, and stillbirths and their implications for the female cardiovascular system.

Pre-pregnancy weight, the rate of gestational weight gain, and the risk of early gestational diabetes mellitus among women registered in a tertiary care hospital in India

BACKGROUND

The impact of pre-pregnancy weight and the rate of gestational weight gain (GWG) together on the risk of early GDM (< 24 weeks gestation; eGDM) has not been studied in the Indian context. We aimed to study the influence of (1) pre-pregnancy weight on the risk of eGDM diagnosed in two time intervals; and (2) in addition, the rate of GWG by 12 weeks on the risk of eGDM diagnosed in 19-24 weeks.

METHOD

Our study utilized real-world clinical data on pregnant women routinely collected at an antenatal care clinic at a private tertiary hospital, in Pune, India. Women registering before 12 weeks of gestation (v1), with a singleton pregnancy, and having a follow-up visit between 19-24 weeks (v2) were included (n = 600). The oral glucose tolerance test was conducted universally as per Indian guidelines (DIPSI) at v1 and v2 for diagnosing eGDM. The data on the onset time of eGDM were interval censored; hence, we modeled the risk of eGDM using binomial regression to assess the influence of pre-pregnancy weight on the risk of eGDM in the two intervals. The rate of GWG by 12 weeks was added to assess its impact on the risk of eGDM diagnosed in v2.

RESULT

Overall, 89 (14.8%) women (age 32 ± 4 years) were diagnosed with eGDM by 24 weeks, of which 59 (9.8%) were diagnosed before 12 weeks and 30 of 541 (5.5%) women were diagnosed between 19-24 weeks. Two-thirds (66%) of eGDM were diagnosed before 12 weeks of gestation. Women's pre-pregnancy weight was positively associated with the risk of GDM in both time intervals though the lower confidence limit was below zero in v1. The rate of GWG by 12 weeks was not observed to be associated with the risk of eGDM diagnosed between 19-24 weeks of gestation. These associations were independent of age, height, and parity.

CONCLUSION

Health workers may focus on pre-pregnancy weight, a modifiable risk factor for eGDM. A larger community-based study measuring weight and GDM status more frequently may be warranted to deepen the understanding of the role of GWG as a risk factor for GDM.

Double burden of malnutrition and its associated factors among women in low and middle income countries: findings from 52 nationally representative data

BACKGROUND

Double burden of malnutrition (DBM) is an emerging global public health problem. The United Nations member states adopted eradicating all forms of malnutrition as an integral component of the global agenda. However, there is evidence of a high burden of undernutrition among women and rising rates of overweight and obesity, especially in low and middle income countries (LMICs). Therefore, this study aimed to investigate the prevalence and associated factors of underweight, overweight, and obesity among women of reproductive age in LMICs.

METHODS

Data for the study were drawn from a recent 52 Demographic and Health Surveys (DHS) conducted in LMICS. We included a sample of 1,099,187 women of reproductive age. A multilevel multinomial logistic regression model was used to identify factors associated with DBM. Adjusted relative risk ratio (RRR) with a 95% Confidence Interval (CI) was reported to show an association.

RESULTS

The prevalence of underweight, overweight, and obesity in LMICs among women of reproductive age was 15.2% (95% CI: 15.1-15.3), 19.0% (95% CI: 18.9- 19.1), and 9.1% (95% CI: 9.0-9.2), respectively. This study found that women aged 24-34 years, aged ≥ 35 years, with primary, secondary, and above educational level, from wealthy households, using modern contraceptives, exposed to media (radio and television), and with high parity (more than one birth) were more likely to have overweight and obesity and less likely to have underweight. Moreover, the risk of having obesity (RRR = 0.59; 95% CI = 0.58-0.60 and overweight (RRR = 0.78; 95% CI = 0.77-0.79) were lower among rural women, while the risk of being underweight was (RRR = 1.13; 95% CI = 1.11-1.15) higher among rural women compared to urban women.

CONCLUSION

The prevalence of underweight, overweight, and obesity was high among women of reproductive age in LMICs. Underweight, overweight, and obesity are influenced by sociodemographic, socioeconomic, and behavioral-related factors. This study shows that, in order to achieve Sustainable Development Goal 2, a multifaceted intervention approach should be considered to prevent both forms of malnutrition in women of reproductive age. This can be achieved by raising awareness and promoting healthy behaviors such as healthy eating and physical activity, especially among educated women, women from wealthy households, and women exposed to the media.

Unfolding the role of placental-derived Extracellular Vesicles in Pregnancy: From homeostasis to pathophysiology

The human placenta is a critical structure with multiple roles in pregnancy, including fetal nutrition and support, immunological, mechanical and chemical barrier as well as an endocrine activity. Besides, a growing body of evidence highlight the relevance of this organ on the maternofetal wellbeing not only during gestation, but also from birth onwards. Extracellular vesicles (EVs) are complex macromolecular structures of different size and content, acting as carriers of a diverse set of molecules and information from donor to recipient cells. Since its early development, the production and function of placental-derived EVs are essential to ensure an adequate progress of pregnancy. In turn, the fetus receives and produce their own EVs, highlighting the importance of these components in the maternofetal communication. Moreover, several studies have shown the clinical relevance of EVs in different obstetric pathologies such as preeclampsia, infectious diseases or gestational diabetes, among others, suggesting that they could be used as pathophysiological biomarkers of these diseases. Overall, the aim of this article is to present an updated review of the published basic and translational knowledge focusing on the role of placental-derived EVs in normal and pathological pregnancies. We suggest as well future lines of research to take in this novel and promising field.

Association between body mass index in the first half of pregnancy and gestational diabetes: A systematic review

Gestational diabetes mellitus is a more common complication in pregnancy and rising worldwide and screening for treating gestational diabetes mellitus is an opportunity for preventing its complications. Abnormal body mass index is the cause of many complications in pregnancy that is one of the major and modifiable risk factors in pregnancy too. This systematic review aimed to define the association between body mass index in the first half of pregnancy (before 20 weeks of gestation) and gestational diabetes mellitus. Web of Science, PubMed/Medline, Embase, Scopus, ProQuest, Cochrane library, and Google Scholar databases were systematically explored for articles published until April 31, 2022. Participation, exposure, comparators, outcomes, study design criteria include pregnant women (P), body mass index (E), healthy pregnant women (C), gestational diabetes mellitus (O), and study design (cohort, case–control, and cross-sectional). Newcastle–Ottawa scale checklists were used to report the quality of the studies. Eighteen quality studies were analyzed. A total of 41,017 pregnant women were in the gestational diabetes mellitus group and 285,351 pregnant women in the normal glucose tolerance group. Studies have reported an association between increased body mass index and gestational diabetes mellitus. Women who had a higher body mass index in the first half of pregnancy were at higher risk for gestational diabetes mellitus. In the first half of pregnancy, body mass index can be used as a reliable and available risk factor to assess gestational diabetes mellitus, especially in some situations where the pre-pregnancy body mass index is not available.