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

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.