Bioelectrical Impedance Vector Analysis (BIVA) for the monitoring of body composition in pregnancy

Association Between Pro-inflammatory Cytokine Levels (IL-1β, IL-6, and TNF-α) in Human Colostrum and Maternal Body Composition Components

Background: Obesity is characterized as a low-grade chronic inflammatory state, marked by elevated inflammatory biomarkers. Breast milk (BM) is rich in nutritional elements, vitamins, minerals, immunological factors, and bioactive components. These bioactive components, capable of influencing biological processes, may vary in concentration based on maternal body composition. Research Aim/Question(s): This study aimed to explore the association between pro-inflammatory cytokine levels (interleukin-1 beta [IL-1β], interleukin-6 [IL-6], and tumor necrosis factor-alpha [TNF-α]) in human colostrum and maternal body composition, as analyzed through bioelectrical impedance vector analysis (BIVA). Method: In this cross-sectional study, 117 healthy postpartum participants were included, with each group (normal weight, overweight, and obese) comprising 39 individuals, as classified by BIVA. Colostrum samples were collected within the first 24 hours postpartum. Results: IL-1β levels did not significantly differ across the groups, with concentrations of 69.5 ± 103 pg/mL in normal-weight, 79.7 ± 97.9 pg/mL in overweight, and 68.7 ± 108 pg/mL in obese women. IL-6 levels were significantly higher in the overweight group (55 ± 72.4 pg/mL) than in the normal-weight (48.1 ± 74.1 pg/mL) and obese groups (28.9 ± 36.2 pg/mL) (p = 0.02). Similarly, TNF-α levels were higher in the overweight group, with concentrations of 58.7 ± 74.9 pg/mL, than in the normal-weight group, with concentrations of 38.6 ± 95.4 pg/mL, and 52.6 ± 115 pg/mL in obese women (p = 0.02). Conclusion: This study shows that IL-6 and TNF-α concentrations were statistically higher in the colostrum of overweight women, suggesting that maternal body composition may influence the inflammatory profile of BM.

Total and segmental phase angle in a cohort of hospitalised patients with COVID-19: mortality prediction and changes throughout hospitalisation

Body composition and phase angle (PhA) have been used to predict mortality in multiple diseases. However, little has been studied regarding segmental measurements, which could potentially help assess subtle changes in specific tissue segments. This study aimed to identify the total PhA cut-off point associated with mortality risk and changes in body composition within a week of hospitalisation in non-critical hospitalised patients with COVID-19. A cohort study was conducted where patients underwent to a complete nutritional assessment upon admission and after seven days, and followed up until hospital discharge or death. A receiver operating characteristic curve was constructed to determine the PhA cut-off point, and the Kaplan–Meier estimator was used to determine survival analysis. Segmental and complete body compositions on admission and after 7 d were compared. We included 110 patients (60 men) with a mean age of 50·5 ± 15·0 years and a median BMI of 28·5 (IQR, 25·6–33·5) kg/m2. The median length of hospital stay was 6 (IQR, 4–9) d, and the mortality rate was 13·6 %. The PhA cut-off point obtained was 4°, with significant differences in the survival rate (P < 0·001) and mortality (HR = 5·81, 95 % CI: 1·80, 18·67, P = 0·003). Segmental and whole-body compositions were negatively affected within one week of hospitalisation, with changes in the approach by the graphical method in both sexes. Nutritional status deteriorates within a week of hospitalisation. PhA < 4° is strongly associated with increased mortality in non-critical hospitalised patients with COVID-19.

Proposal and validation of an equation to identify sarcopenia using bioelectrical impedance analysis-derived parameters

OBJECTIVE

This study aimed to develop a simpler approach for diagnosing sarcopenia by using only bioelectrical impedance vector analysis parameters.

METHODS

The study design was a cross-sectional study. The research was conducted based on the Itabashi Longitudinal Study on Aging, a community-based cohort study, with data collected from the 2022 and 2023 surveys in Itabashi Ward, Tokyo, Japan. The development cohort consisted of 1146 participants from the 2022 survey, and the validation cohort included 656 participants from the 2023 survey. Both cohorts were comprised of community-dwelling older adults with similar inclusion criteria. Sarcopenia was defined according to the Asian Working Group for Sarcopenia 2019 criteria. The logistic model utilized height divided by impedance at 50 kHz and phase angle to establish a new regression equation to identify sarcopenia. Regression equations were generated for the development cohort and validated for the validation cohort. Discriminatory ability was assessed using the area under the receiver operating characteristic curve (AUC) for men and women.

RESULTS

The prevalence of sarcopenia was 20.7% and 14.8% in the development and validation cohort, respectively. The AUC (95% confidence interval) of the logistic model in discriminating sarcopenia was 0.92 (0.88, 0.95) for men and 0.82 (0.78, 0.86) for women in the development cohort and 0.85 (0.78, 0.91) for men and 0.90 (0.86, 0.95) for women in the validation cohort.

CONCLUSION

The study demonstrated that a simple formula using bioelectrical parameters at 50 kHz proved useful in identifying sarcopenia in the older adult population.

The bioelectrical impedance analysis (BIA) international database: aims, scope, and call for data

BACKGROUND

Bioelectrical impedance analysis (BIA) is a technique widely used for estimating body composition and health-related parameters. The technology is relatively simple, quick, and non-invasive, and is currently used globally in diverse settings, including private clinicians' offices, sports and health clubs, and hospitals, and across a spectrum of age, body weight, and disease states. BIA parameters can be used to estimate body composition (fat, fat-free mass, total-body water and its compartments). Moreover, raw measurements including resistance, reactance, phase angle, and impedance vector length can also be used to track health-related markers, including hydration and malnutrition, and disease-prognostic, athletic and general health status. Body composition shows profound variability in association with age, sex, race and ethnicity, geographic ancestry, lifestyle, and health status. To advance understanding of this variability, we propose to develop a large and diverse multi-country dataset of BIA raw measures and derived body components. The aim of this paper is to describe the 'BIA International Database' project and encourage researchers to join the consortium.

METHODS

The Exercise and Health Laboratory of the Faculty of Human Kinetics, University of Lisbon has agreed to host the database using an online portal. At present, the database contains 277,922 measures from individuals ranging from 11 months to 102 years, along with additional data on these participants.

CONCLUSION

The BIA International Database represents a key resource for research on body composition.

Impedance Analysis to Evaluate Nutritional Status in Physiological and Pathological Conditions

A thorough knowledge of body composition assessment techniques is the cornerstone for initiating a customized nutritional program. The second step is to consider the potential of their application in different physiological and pathological conditions and their effectiveness in the management of a monitoring pathway during dietary interventions. To date, bioimpedance analysis is the most effective and reliable method for assessing body composition due to its advantages in terms of speed of execution, non-invasiveness and low cost. Therefore, this review article aims to analyze the main concepts and application areas of bioimpedance measurement techniques, in particular vector frequency-based analysis (BIVA) systems, in order to assess their validity in both physiological and pathological conditions.

Gestational obesity: An unconventional endocrine disruptor for the fetus

Obesity has reached pandemic proportions and is a growing concern throughout the world. A parallel trend has also been observed among women in reproductive age, leading to the increasing global prevalence of gestational obesity (GO). The well-known obesity-related health problems also extend to pregnancy, where they are responsible for giving rise to a variety of medical and obstetrical complications, resulting in an increased incidence of adverse maternal and fetal outcomes. In this context, several epidemiological and clinical studies have shown that nutritional changes through different stages of gestation can have a substantial impact on the future health and development of the child. Therefore, it is clear that GO is a modifiable endocrine disruptor that negatively influences the health of the fetus and the newborn, with long-term metabolic implications. This review aims to describe the impact of GO on maternal and fetal outcomes using the available scientific literature and highlighting the evidence-based nutritional approaches currently recommended for the management of GO.