Reproducibility of Bioelectrical Impedance Analysis in Pregnancy and the Association of Body Composition with the Risk of Gestational Diabetes: A Substudy of MUMS Cohort

Association between Maternal Body Composition in Second Trimester and Risk of Fetal Macrosomia: A Population-Based Retrospective Study in China

(1) Background: Female body composition undergoes significant changes to support fetal growth and development during pregnancy. This study investigated the association of maternal body composition in the second trimester and macrosomia and explored whether body-composition-related indicators could be used to predict macrosomia. (2) Methods: This study was conducted in China from December 2016 to December 2021. Women with singleton pregnancies, gestational ages between 37 and 42 weeks, and an absence of pregnancy complications were included. In the second trimester, bioelectric impedance analysis (BIA) was used to measure body-composition-related indicators. Logistic regression analysis was performed to explore the risk factors for macrosomia. The predictive performance of maternal body composition and clinical indicators for macrosomia were assessed using the area under the receiver-operating-characteristics curve (AUC). (3) Results: This retrospective study involved 43,020 pregnant women; we collected 2008 cases of macrosomia. Gravidity, gestational age, body mass index (BMI), gestational weight gain (GWG), total body water, fat mass, fat-free mass (FFM), skeletal muscle mass, and visceral fat level were risk factors for macrosomia (p < 0.05 for all). In the prediction model, the AUC of FFM for predicting macrosomia was the largest (0.742). (4) Conclusions: Body-composition-related indicators associated with macrosomia and body composition measurements in the second trimester can predict the risk of macrosomia, enabling clinicians to implement interventions earlier to reduce adverse perinatal outcomes.

Mental Health during the Interpregnancy Period and the Association with Pre-Pregnancy Body Mass Index and Body Composition: Data from the INTER-ACT Randomized Controlled Trial

Mental health problems and obesity are two common complications during pregnancy and postpartum. The preconception period is considered an appropriate period for prevention. Therefore, insights into interpregnancy mental health and the impact on weight and body composition are of interest to developing effective weight management strategies. The primary aim of this study is to assess the difference in women's mental health during the interpregnancy period and the association with pre-pregnancy body mass index (BMI) and body composition. The secondary aim is to study whether this association is affected by socio-demographic factors, interpregnancy interval and sleep. The study is a secondary analysis of the INTER-ACT e-health-supported lifestyle trial. Women were eligible if they had a subsequent pregnancy and mental health measurements at 6 weeks after childbirth and at the start of the next pregnancy (n = 276). We used univariate analyses to assess differences in mental health and performed regression analysis to assess their association with pre-pregnancy BMI and body composition at the start of the next pregnancy. Our results show a statistically significant increase in anxiety and depressive symptoms between 6 weeks after childbirth and the start of the next pregnancy (sSTAI-6 ≥ 40: +13%, p =≤ 0.001; GMDS ≥ 13: +9%, p = 0.01). Of the women who were not anxious at 6 weeks after childbirth (sSTAI < 40), more than one-third (39%) developed anxiety at the start of the next pregnancy (p =≤ 0.001). Regression analysis showed that sense of coherence (SOC-13) at the start of the next pregnancy was independently associated with women's pre-pregnancy BMI and fat percentage. We believe that the development of preconception lifestyle interventions that focus on both weight reduction and support in understanding, managing and giving meaning to stressful events (sense of coherence) may be of added value in optimizing women's preconception health.

Mental health after childbirth and the impact on postpartum weight retention and body composition. Data from the INTER-ACT randomized controlled trial

OBJECTIVE

To study the evolution of maternal mental health during the first year after childbirth in women with previous excessive gestational weight gain, and the relationship with postpartum weight retention and body composition.

METHODS

Anthropometric and mental health data of 505 women of the INTER-ACT RCT control group were collected and assessed using descriptive statistics and mixed model analyses.

RESULTS

At 6 weeks postpartum 28% of women reported depressive symptoms, 46% anxiety, 47% low sense of coherence and 48% low quality of life. From 6 weeks to 12 months postpartum there was a monthly increase (+0.38, p = .003) in anxiety and a monthly decrease (-0.39, p = .008) in quality of life. High levels of depressive symptoms at 6 weeks postpartum predicted higher body fat (+0.9%, p = .01) and higher waist circumference (+1.3 cm, p = .02) in the first year postpartum. High sense of coherence at 6 weeks postpartum predicted lower body fat (-0.8%, p = .01) the first year postpartum.

CONCLUSIONS

In women with a history of excessive gestational weight gain, the first year after childbirth is characterized by a high prevalence of mental health problems in which levels of anxiety and quality of life deteriorate over time. Moreover, high levels of depressive symptoms and low sense of coherence in the first weeks postpartum predict unfavourable body composition outcomes in the year after childbirth.

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.

Bioelectrical Impedance Analysis for the Assessment of Body Composition in Sarcopenia and Type 2 Diabetes

Sarcopenia is emerging as a severe complication in type 2 diabetes (T2DM). On the other hand, it has been documented that nutritional aspects, such as insufficient protein or total energy intake, increase sarcopenia risk. The analysis of body composition is a relevant approach to assess nutritional status, and different techniques are available. Among such techniques, bioelectrical impedance analysis (BIA) is particularly interesting, since it is non-invasive, simple, and less expensive than the other techniques. Therefore, we conducted a review study to analyze the studies using BIA for body composition analysis in T2DM patients with sarcopenia or at risk of catching it. Revised studies have provided important information concerning relationships between body composition parameters (mainly muscle mass) and other aspects of T2DM patients’ conditions, including different comorbidities, and information on how to avoid muscle mass deterioration. Such relevant findings suggest that BIA can be considered appropriate for body composition analysis in T2DM complicated by sarcopenia/muscle loss. The wide size of the patients’ cohort in many studies confirms that BIA is convenient for clinical applications. However, studies with a specific focus on the validation of BIA, in the peculiar population of patients with T2DM complicated by sarcopenia, should be considered.

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.

Performing nutrition assessment remotely via telehealth

Performing nutrition assessment remotely via telehealth is a topic of significant interest given the global pandemic in 2020 that has necessitated physical distancing and virtual communications. This review presents an evidence-based approach to conducting nutrition assessments remotely. The authors present suggestions for adaptations that can be used to perform a remote nutrition-focused physical exam. Direct-to-consumer technologies that can be used in remote nutrition assessment are discussed and compared. Practice tips for conducting a telehealth visit are also presented. The aim of this publication is to provide interdisciplinary clinicians a set of guidelines and best practices for performing nutrition assessments in the era of telehealth.