The Body Composition in Early Pregnancy is Associated with the Risk of Development of Gestational Diabetes Mellitus Late During the Second Trimester

Body composition and risk of gestational diabetes mellitus: A univariable and multivariable Mendelian randomization study

OBJECTIVE

In this study, we employed a Mendelian randomization (MR) approach to investigate the independent causal associations of six body composition traits with gestational diabetes mellitus (GDM).

METHODS

Genome-wide significant levels (P < 10 × 5-8 ) of single nucleotide polymorphisms associated with body water mass, total protein, whole body fat-free mass, weight, whole body fat mass, and body fat percentage were used as instrumental variables. Data on GDM were obtained from the FinnGen Consortium, and both univariable and multivariable Mendelian randomization were performed. We utilized five different analytical methods including inverse-variance weighted (IVW), MR Egger, weighted median, simple mode, and weighted mode to assess the robustness of the results.

RESULTS

With univariable Mendelian randomization, the risk of GDM increased per 1-standard deviation (SD) increase in weight (ORweight  = 1.297, P = 3.06 × 10-5 ), whole body fat mass (ORwhole body fat mass  = 1.408, P = 1.32 × 10-6 ), and the risk of GDM increased per percent increase in body fat percentage (ORbody fat percentage  = 1.661, P = 1.01 × 10-8 ). Total protein had a protective effect on the risk of GDM (ORtotal protein  = 0.880, P = 0.048). However, there was no significant causal association between increases in body water mass and whole body fat-free mass per SD and the risk of GDM. Causal associations between weight, whole body fat mass, body fat percentage, and total protein with GDM were reduced to null in multivariable Mendelian randomization.

CONCLUSION

The present study furnishes genetic evidence to elucidate the causal relationship between body composition traits and GDM. Additionally, further studies are imperative to establish a causal connection between body composition traits and gestational diabetes mellitus.

The Association of the Triglyceride and Muscle to Fat Ratio During Early Pregnancy with the Development of Gestational Diabetes Mellitus

Objective

This study explored the association between metabolic factors and body composition during the first trimester of gestational diabetes mellitus (GDM).

Methods

This prospective study recruited pregnant women in their first trimester. Clinical information and glucose and lipid measurements were collected, and body composition was assessed using multifrequency bioelectrical impedance analysis. GDM was diagnosed on the basis of an oral glucose tolerance test at 24-28 gestational week. Factors related to GDM were investigated using correlation, and risk ratios (RRs) and 95% CIs of potential risk factors with GDM were estimated using Poisson regression. The area under the receiver operating characteristic (ROC) curve was used to determine predictive effects.

Results

59/302 women (19.5%) developed GDM. Older (RR 1.076, 95% CI 1.005-1.152), higher body mass index (BMI) before pregnancy (pre-BMI) (RR 1.012, 95% CI 1.005-1.063), triglycerides (RR 4.052, 95% CI 1.641-6.741), and lower skeletal muscle mass (SMM) to fat mass (FM) ratio (SMM/FM) (RR 0.213, 95% CI 0.051-0890) in the first trimester, and family history of type 2 diabetes (RR 1.496, 95% CI 1.014-2.667) significantly associated with the risk of GDM, but neither fasting plasma glucose nor glycated albumin was associated with GDM. The combined multivariate prediction model achieved good discrimination with an AUC of 0.806 (95% CI 0.737-0.895, P<0.001). According to ROC curve, the cut-off values of TG and SMM/FM were 0.925 mmol/L and 1.305.

Conclusion

Reduced SMM/FM and elevated triglyceride (TG) levels in the first trimester are associated with GDM development, and should be screened in early pregnancy to identify high-risk subjects for GDM.

Association of body composition in early pregnancy with gestational diabetes mellitus: A meta-analysis

INTRODUCTION

Body composition as dynamic indices constantly changes in pregnancy. The use of body composition indices in the early stages of pregnancy has recently been considered. Therefore, the current meta-analysis study was conducted to investigate the relationship between body composition in the early stages of pregnancy and gestational diabetes.

METHOD

Valid databases searched for papers published from 2010 to December 2021 were based on PRISMA guideline. Newcastle Ottawa was used to assess the quality of the studies. For all analyses, STATA 14.0 was used. Mean difference (MD) of anthropometric indices was calculated between the GDM and Non-GDM groups. Pooled MD was estimated by "Metan" command, and heterogeneity was defined using Cochran's Q test of heterogeneity, and I 2 index was used to quantify heterogeneity.

RESULTS

Finally, 29 studies with a sample size of 56438 met the criteria for entering the meta-analysis. Pooled MD of neck circumference, hip circumference, waist hip ratio, and visceral adipose tissue depth were, respectively, 1.00 cm (95% CI: 0.79 to 1.20) [N = 5; I^2: 0%; p: 0.709], 7.79 cm (95% CI: 2.27 to 13.31) [N = 5; I2: 84.3%; P<0.001], 0.03 (95% CI: 0.02 to 0.04) [N = 9; I2: 89.2%; P<0.001], and 7.74 cm (95% CI: 0.11 to 1.36) [N = 4; I^2: 95.8%; P<0.001].

CONCLUSION

Increased neck circumference, waist circumference, hip circumference, arm circumference, waist to hip ratio, visceral fat depth, subcutaneous fat depth, and short stature increased the possibility of developing gestational diabetes. These indices can accurately, cost-effectively, and affordably assess the occurrence of gestational diabetes, thus preventing many consequences with early detection of gestational diabetes.

Association between maternal adiposity measures and adverse maternal outcomes of pregnancy: Systematic review and meta-analysis

Maternal obesity increases pregnancy-related risks. Women with a body mass index (BMI) ≥ 30 kg/m2 are considered to be at risk and should receive additional care, although approximately half will have uncomplicated pregnancies. This systematic review aimed to identify early pregnancy measures of adiposity associated with adverse maternal health outcomes. Searches included six databases, reference lists, citations, and contacting authors. Screening and quality assessment were carried out by two authors independently. Random effects meta-analysis and narrative synthesis were conducted. Seventy studies were included with a pooled sample of 89,588 women. Meta-analysis showed significantly increased odds of gestational diabetes mellitus (GDM) with higher waist circumference (WC) categories (1.40, 95% confidence interval [CI] 1.04, 1.88) and per unit increase in WC (1.31, 95% CI 1.03, 1.67). Women with GDM had higher WC than controls (mean difference [MD] 6.18 cm, 95% CI 3.92, 8.44). WC was significantly associated with hypertensive disorders, delivery-related outcomes, metabolic syndrome, and composite pregnancy outcomes. Waist to hip ratio was significantly associated with GDM, hypertensive disorders, and delivery-related outcomes. Fat mass, neck circumference, skinfolds, and visceral fat were significantly associated with adverse outcomes, although limited data were available. Our findings identify the need to explore how useful adiposity measures are at predicting risk in pregnancy, compared with BMI, to direct care to women with the greatest need.

Insulin Resistance in Gestational Diabetes Mellitus and Its Association With Anthropometric Fetal Indices

Background:

In pregnant women with gestational diabetes mellitus (GDM), insulin resistance (IR) increases the risk of developing manifest type 2 diabetes mellitus and is associated with complications in both mother and fetus.

Objectives:

This research aimed to evaluate the associations between IR evaluated by 3 indices (namely updated homeostasis model assessment model (HOMA2), QUICKI, and McAuley’s index) and the diabetes risk factors and the fetal growth indices in Vietnamese women with GDM.

Methods:

A cross-sectional descriptive study was conducted on 370 women with GDM and 40 healthy pregnant women from January 2015 to May 2019. IR was calculated by HOMA2 (HOMA2-IR), QUICKI, and McAuley’s index. Fetal anthropometric measurements were assessed via ultrasound which was performed and interpreted by ultrasound experts.

Results:

In the simple regression analysis, McAuley’s index illustrated had statistically significant correlations to the highest number of risk factors of diabetes mellitus compared with HOMA2-IR and QUICKI indices. Moreover, McAuley’s index correlated statistically significantly to the highest number of fetal ultrasound measurements factors such as including biparietal diameter (BPD) (r = −0.271, P < .001), head circumference (HC) (r = −0.225, P < .001), abdominal circumference (AC) (r = −0.214, P < .001), femur length (FL) (r = −0.231, P < .001), estimated fetal weight (EFW) (r = −0.239, P < .001) and fetal estimated age (r = −0.299, P < .001). In the multivariable analysis, the McAuley’s index contributed the greatest to AC (Standardized B of −0.656, P < .001).

Conclusion:

The McAuley’s index was significantly associated with a higher number of more risk factors for diabetes mellitus as well as fetal ultrasound sonography findings measurements than compared with HOMA2-IR and QUICKI indices.

Relationship of anthropometric measurements with glycated hemoglobin and 1-h blood glucose after 50 g glucose challenge test in pregnant women: A longitudinal cohort study in Southern Thailand

AIMS

To assess correlations of anthropometric measurements with glycated hemoglobin (HbA1c) and 1-h blood glucose after a 50 g glucose challenge test during the first and late second trimesters and explore their relationships of anthropometric measurements with neonatal birth weight.

METHODS

A longitudinal study was conducted among pregnant Thai women with gestational age ≤14 weeks. Anthropometric measurements, using body mass index, body compositions, and circumferences, and skinfold thickness, were measured at four-time points: ≤14, 18-22, 24-28, and 30-34 weeks of gestation. HbA1c and 1-h blood glucose were examined at ≤14 and 24-28 weeks. Neonatal birth weight was recorded.

RESULTS

Of 312 women, HbA1c was more correlated with anthropometric measurements during pregnancy than 1-h blood glucose. At 24-28 weeks, women with high/very high body fat percentage were more likely to have higher HbA1c. Women with high subscapular skinfold thickness were more likely to have higher 1-h blood glucose at ≤14 and 24-28 weeks. High hip circumference significantly increased neonatal birth weights.

CONCLUSION

Anthropometric measurements were longitudinally correlated with HbA1c and 1-h blood glucose, higher in the late second than first trimesters, as well as neonatal birth weight. The mechanisms to explain the relationship of different anthropometric measurements are required to be further studied.

Association between MRI-based visceral adipose tissues and metabolic abnormality in a Chinese population: a cross-sectional study

Background

Previous studies have indicated that the deposition of abdominal adipose tissue was associated with the abnormalities of cardiometabolic components. The aim of this study was to examine the relationship of visceral adipose tissue (VAT), subcutaneous adipose tissue (SAT) and metabolic status and the different effects between males and females.

Methods

The 1388 eligible subjects were recruited in a baseline survey of metabolic syndrome in China, from two communities in Hangzhou and Chengdu. Areas of abdominal VAT and SAT were measured by magnetic resonance imaging (MRI). Serum total triglycerides (TG), high-density lipoprotein cholesterol (HDL-C) were measured by an automated biochemical analyzer. Metabolic abnormality (MA) was defined more than one abnormal metabolic components, which was based on the definition of metabolic syndrome (IDF 2005). Multiple logistic regression was used to calculate the odds ratios (ORs) and 95% confidence intervals (95%CI). Predictive value was assessed by area under the curve (AUC), net reclassification improvement (NRI), and integrated discrimination improvement (IDI), respectively.

Results

Their mean age was 53.8 years (SD: 7.1 years), the mean body mass index (BMI) was 23.7 kg/m², and 44.8% of the subjects were male. Both male and female with MA had higher VAT levels compared to subjects with normal metabolism (MN), and male had higher SAT levels than female (P < 0.05). Higher VAT was significantly associated with MA with ORs in the fourth quartile (Q4) of 6.537 (95% CI = 3.394–12.591) for male and 3.364 (95% CI = 1.898–5.962) for female (P for trend < 0.05). In female, VAT could increase the risk of metabolic abnormalities, but SAT could increase the risk of MA in the second and fourth quartiles (Q2 and Q4) only at BMI > 24 kg/m². In male, VAT improved the predictive value of MA compared to BMI and waist circumference (WC), the AUC was 0.727 (95% CI = 0.687–0.767), the NRI was 0.139 (95% CI = 0.070–0.208) and 0.106 (95% CI = 0.038–0.173), and the IDI was 0.074 (95% CI = 0.053–0.095) and 0.046 (95% CI = 0.026–0.066). Similar results were found in female.

Conclusions

In male, VAT and SAT could increase the risk of metabolic abnormalities both at BMI < 24 kg/m² and at BMI ≥ 24 kg/m². In female, VAT could increase the risk of metabolic abnormalities but SAT could increase the risk of MA in the second and fourth quartiles (Q2 and Q4) only at BMI > 24 kg/m². Deposition of abdominal adipose tissue was associated with metabolic abnormalities. VAT improved the predictive power of MA.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12986-022-00651-x.

Correlation of body composition in early pregnancy on gestational diabetes mellitus under different body weights before pregnancy

OBJECTIVE

The prediction of gestational diabetes mellitus (GDM) by body composition-related indicators in the first trimester was analyzed under different body mass index (BMI) values before pregnancy.

METHODS

This was a retrospective analysis of pregnant women who were treated, had documented data, and received regular perinatal care at the Third Affiliated Hospital of Zhengzhou University from January 1, 2021, to December 31, 2021. Women with singleton pregnancies who did not have diabetes before pregnancy were included. In the first trimester (before the 14th week of pregnancy), bioelectric impedance assessment (BIA) was used to analyze body composition-related indicators such as protein levels, mineral levels, fat volume, and the waist-hip fat ratio. The Pearman's correlation coefficient was used to evaluate the linear relationship between the continuous variables and pre-pregnancy body mass index (BMI). In the univariate body composition analysis, the association with the risk of developing GDM was included in a multivariate analysis using the relative risk and 95% confidence interval obtained from logarithmic binomial regression, and generalized linear regression was used for multivariate regression analysis. Furthermore, the area under the curve (AUC) was calculated by receiver operating characteristic (ROC) curves. The optimal cutoff value of each risk factor was calculated according to the Youden Index.

RESULTS

In a retrospective study consisting of 6698 pregnant women, we collected 1109 cases of gestational diabetes. Total body water (TBW), protein levels, mineral levels, bone mineral content (BMC), body fat mass (BFM), soft lean mass (SLM), fat-free mass (FMM), skeletal muscle mass (SMM), percent body fat (PBF), the waist-hip ratio (WHR), the visceral fat level (VFL), and the basal metabolic rate (BMR) were significantly higher in the GDM group than in the normal group (P<0.05). Under the pre-pregnancy BMI groupings, out of 4157 pregnant women with a BMI <24 kg/m², 456 (10.97%) were diagnosed with GDM, and out of 2541 pregnant women with a BMI ≥24 kg/m², 653 (25.70%) were diagnosed with GDM. In the generalized linear regression model, it was found that in all groups of pregnant women, pre-pregnancy BMI, age, gestational weight gain (GWG) in the first trimester, and weight at the time of the BIA had a certain risk for the onset of GDM. In Model 1, without adjusting for confounders, the body composition indicators were all positively correlated with the risk of GDM. In Model 3, total body water, protein levels, mineral levels, bone mineral content, soft lean mass, fat-free mass, skeletal muscle mass, and the basal metabolic rate were protective factors for GDM. After Model 4 was adjusted for confounders, only the waist-hip ratio was positively associated with GDM onset. Among pregnant women with a pre-pregnancy BMI <24 kg/m², the body composition-related indicators in Model 2 were all related to the onset of GDM. In Model 3, total body water, soft lean mass, fat-free mass, and the basal metabolic rate were negatively correlated with GDM onset. In the body composition analysis of among women with a pre-pregnancy BMI ≥ 24 kg/m², only Model 1 and Model 2 were found to show positive associations with GDM onset. In the prediction model, in the basic data of pregnant women, the area under the receiver operating characteristic curve predicted by gestational weight gain for GDM was the largest (0.795), and its cutoff value was 1.415 kg. In the body composition results, the area under the receiver operating characteristic curve of body fat mass for predicting GDM risk was larger (0.663) in all pregnant women.

CONCLUSIONS

Through this retrospective study, it was found that the body composition-related indicators were independently associated with the onset of GDM in both the pre-pregnancy BMI <24 kg/m² and pre-pregnancy BMI ≥24 kg/m² groups. Body fat mass, the visceral fat level, and the waist-hip ratio had a higher correlation with pre-pregnancy BMI. Total body water, protein levels, mineral levels, bone mineral content, soft lean mass, fat-free mass, skeletal muscle mass, and the basal metabolic rate were protective factors for GDM after adjusting for some confounders. In all pregnant women, the waist-hip ratio was found to be up to 4.562 times the risk of GDM development, and gestational weight gain had the best predictive power for GDM. Gestational weight gain in early pregnancy, body fat mass, and the waist-hip ratio can assess the risk of GDM in pregnant women, which can allow clinicians to predict the occurrence of GDM in pregnant women as early as possible and implement interventions to reduce adverse perinatal outcomes.

The Possibility of Using Bioelectrical Impedance Analysis in Pregnant and Postpartum Women

Pregnancy is a time of significant changes occurring in the composition of a woman’s body in order to provide support for the growth and development of the foetus. Bioelectrical impedance analysis (BIA) is used to assess the body composition and hydration status. This technique represents a non-invasive, reliable, and fast clinical approach, which is well tolerated by patients. A segmental impedance measurement might be advantageous in pregnant women, particularly in late pregnancy. The purpose of this paper is to provide a review of different applications of BIA in pregnant and postpartum women. It seems that BIA has a better prognostic potential for gestational and post-partum outcomes than body mass index. The BIA method can be successfully used to study the effect of excessive gestational weight gain in pregnancy on the development of obstetric complications. Studying the mother’s body composition and correlating it with her energy balance could facilitate the development of dietary recommendations for women. Evaluation of the body composition can provide important clues for diagnosis of gestational diabetes mellitus in pregnant women with a low risk of this disease. BIA is also used as one of the additional tests in assessing the risk of developing gestational hypertension and preeclampsia.

Risk of gestational diabetes mellitus by pre-pregnancy body mass index: A systematic review and meta-analysis

Gestational diabetes mellitus (GDM) is serious health challenges. This study aimed at determining the risk of GDM among pregnant women by pre-pregnancy BMI. Five electronic databases including Medline (PubMed), Scopus, Embase, Web of Science and Google Scholar were searched for literature published form 2015 to January 1, 2021. The pooled estimate risk of GDM among pregnant women was 16.8% (95% CI: 15.3-18.4). The risk of GDM in underweight/normal group and overweight/obese group were 10.7% (95% CI: 9.1-12.4) and 23% (95% CI: 20.2-25.9), respectively. The risk of GDM is high among overweight/obese pregnant women.

Body composition helps: Differences in energy expenditure between pregnant and nonpregnant females

OBJECTIVES

Human pregnancy is associated with important physiological changes that usually increase energetic requirements. However, great variability exists in the costs and mechanisms required to bear pregnancy. Since body mass (BM) and composition are modified during gestation, it is of great interest to compare the influence of BM on energy expenditure (EE) in pregnant and nonpregnant females.

METHODS

BM, body composition, and EE of 77 volunteers (35 pregnant and 42 nonpregnant females) were measured. The pregnant volunteers completed two measurement rounds at 28 and 32 gestation weeks. Differences on the measured parameters were sought, and comparison of regression lines was computed to test how BM affected the EE of the volunteers.

RESULTS

BM and body composition parameters are significantly higher in pregnant females, but EE is not statistically different. Pregnant females have a larger percentage of fat mass, but lower percentage of fat-free mass (FFM). The EE per kg of FFM is similar in both groups. Comparison of regression lines shows that pregnancy does not change the relationship between BM and EE, but for similar BM pregnant females expend less energy than nonpregnant females.

CONCLUSIONS

We propose that their larger percentage of passive body tissues is the reason why pregnant females expend less energy than nonpregnant females of similar BM, without changing the scaling of EE on BM. Thus, pregnancy could not be as energetically constraining as usually assumed, with important consequences for human reproductive ecology.