Accuracy of segmental bioelectrical impedance analysis for predicting body composition in pre- and postmenopausal women

Association of skeletal muscle function, quantity, and quality with gut microbiota in Japanese adults: A cross-sectional study

AIM

The gut microbiota has emerged as a new intervention target for sarcopenia. Prior studies in humans have focused on the association between gut microbiota and skeletal muscle quantity, while the evidence on muscle function and quality is lacking. This study aimed to identify gut microbiota genera associated with skeletal muscle function, quantity, and quality in a general population of Japanese adults.

METHODS

This cross-sectional study included 164 participants aged 35-80 years, women and men recruited from urban areas of Japan. Fecal samples were collected and analyzed using 16S rRNA gene amplicon sequencing. Skeletal muscle function was measured using handgrip strength and leg extension power (LEP), while skeletal muscle mass was estimated using bioelectrical impedance analysis. Phase angle was used as a measure of skeletal muscle quality. Multivariate linear regression analysis stratified by age group was used to examine the association between the dominant genera of the gut microbiota and skeletal muscle variables.

RESULTS

A significant association was found between Bacteroides and Prevotella 9 with LEP only in the ≥60 years group. When both Bacteroides and Prevotella 9 were included in the same regression model, only Bacteroides remained consistently and significantly associated with LEP. No significant associations were observed between skeletal muscle mass, handgrip strength, and phase angle and major gut microbiota genera.

CONCLUSIONS

In this study, we observed a significant positive association between Bacteroides and leg muscle function in older adults. Further studies are required to elucidate the underlying mechanisms linking Bacteroides to lower-extremity muscle function. Geriatr Gerontol Int 2024; 24: 53-60.

Association between skeletal muscle mass or percent body fat and metabolic syndrome development in Japanese women: A 7-year prospective study

Previous cross-sectional studies have indicated that low relative appendicular lean mass (ALM) against body weight (divided by body weight, ALM/Wt, or divided by body mass index, ALM/BMI) was negatively associated with metabolic syndrome (MetS). Conversely, previous cross-sectional studies have indicated that the absolute ALM or ALM divided by squared height (ALM/Ht2) were positively associated with MetS. The aim of this longitudinal study was to investigate the association between low absolute or relative skeletal muscle mass, leg muscle power, or percent body fat and the development of MetS in Japanese women in a 7-y prospective study. The study participants included 346 Japanese women aged 26 to 85 years. The participants were divided into low and high groups based on the median values of ALM/Wt, ALM/BMI, ALM/Ht2, absolute ALM, or leg power. The longitudinal relationship between ALM indices or leg power and MetS development was examined using Kaplan-Meier curves and Cox regression models (average follow-up duration 7 years, range 1 to 10 years). During follow-up, 24 participants developed MetS. MetS incidence was higher in the low ALM/Wt group than the high ALM/Wt group even after controlling for age, obesity, waist circumference, family history of diabetes, smoking, and physical activity [adjusted hazard ratio = 5.60 (95% CI; 1.04-30.0)]. In contrast, MetS incidence was lower in the low ALM/Ht2 group than the high ALM/Ht2 group [adjusted hazard ratio = 10.6 (95%CI; 1.27-89.1)]. MetS incidence was not significantly different between the low and high ALM/BMI, absolute ALM, and leg power groups. Both ALM/Ht2 and ALM/Wt were not significant predictive variables for MetS development when fat mass or percent body fat was taken into account in the Cox model. At the very least, the results of this study underscore the importance of body composition measurements in that percent body fat, but not ALM, is associated with MetS development.

A review of menopause nomenclature

Menopause nomenclature varies in the scholarly literature making synthesis and interpretation of research findings difficult. Therefore, the present study aimed to review and discuss critical developments in menopause nomenclature; determine the level of heterogeneity amongst menopause definitions and compare them with the Stages of Reproductive Aging Workshop criteria. Definitions/criteria used to characterise premenopausal and postmenopausal status were extracted from 210 studies and 128 of these studies were included in the final analyses. The main findings were that 39.84% of included studies were consistent with STRAW classification of premenopause, whereas 70.31% were consistent with STRAW classification of postmenopause. Surprisingly, major inconsistencies relating to premenopause definition were due to a total lack of reporting of any definitions/criteria for premenopause (39.84% of studies). In contrast, only 20.31% did not report definitions/criteria for postmenopause. The present findings indicate that there is a significant amount of heterogeneity associated with the definition of premenopause, compared with postmenopause. We propose three key suggestions/recommendations, which can be distilled from these findings. Firstly, premenopause should be transparently operationalised and reported. Secondly, as a minimum requirement, regular menstruation should be defined as the number of menstrual cycles in a period of at least 3 months. Finally, the utility of introducing normative age-ranges as supplementary criterion for defining stages of reproductive ageing should be considered. The use of consistent terminology in research will enhance our capacity to compare results from different studies and more effectively investigate issues related to women's health and ageing.

Association of adiposity evaluated by anthropometric, BIA, and DXA measures with cardiometabolic risk factors in nonobese postmenopausal women: the CoLaus/OsteoLaus cohort

OBJECTIVE

After menopause, body composition changes with body fat accumulation, and an increase in cardiometabolic risk factors. Total fat mass, regional fat mass, and visceral adipose tissue (VAT) may be estimated with anthropometric measures, bioelectrical impedance analysis (BIA), and dual-energy X-ray absorptiometry (DXA). The aim of our study was to assess which measurement correlated best with cardiometabolic risk factors in healthy nonobese postmenopausal women.

METHODS

The CoLaus/OsteoLaus cohort included 1,500 postmenopausal women (age range 50-80). We analyzed correlations between: 1) measurements of body composition assessed by anthropometric measures, BIA, and DXA and 2) these measurements and different selected cardiometabolic risk factors, such as blood pressure, lipid markers (cholesterol subtypes and triglycerides), and metabolic markers (glucose, insulin, adiponectin, and leptin). Spearman correlation coefficient, stepwise forward regression, and linear regression analyses were used to determine association between anthropometric measurements and cardiometabolic risk factors.

RESULTS

In the 803 included participants (mean age 62.0 ± 7.1 y, mean body mass index 25.6 kg/m2 ± 4.4), correlations between total fat mass measured by BIA and total fat mass, android fat, gynoid fat, or VAT measured by DXA are very strong (from r = 0.531, [99% confidence interval (CI), 0.443-0.610] to r = 0.704, [99% CI, 0.640-0.758]). Body mass index and waist circumference have a higher correlation with VAT (r = 0.815, [99% CI, 0.772-0.851] and r = 0.823 [99% CI, 0.782-0.858], respectively) than BIA (r = 0.672 [99% CI, 0.603-0.731]). Among the anthropometric measurement and the measurements derived from DXA and BIA, VAT is the parameter most strongly associated with cardiometabolic risk factors. VAT better explains the variation of most of the cardiometabolic risk factors than age and treatment. For example, nearly 5% of the variability of the diastolic blood pressure (9.9 vs 4.9), nearly 15% of the variability of high-density lipoprotein cholesterol (20.3 vs 3.8) and triglyceride (21.1 vs 6.5), 25.3% of the variability of insulin (33.3 vs 8.1), and 37.5% of the variability of leptin (37.7 vs 1.1) were explained by VAT.

CONCLUSIONS

BIA seems not to be a good tool to assess VAT. At the population level, waist circumference and body mass index seem to be good tools to estimate VAT. VAT measured by DXA is the parameter most correlated with cardiometabolic risk factors and could become a component of the cardiometabolic marker on its own.

A practical nutritional guide for the management of sleep disturbances in menopause

Sleep disturbances (SD) represent one of the main symptoms of menopause and they are caused by several factors. Hormonal changes such as the reduction of oestrogen levels and the consequent vasomotor symptoms (VMS) along with psychiatric disorders such as depression and anxiety could contribute to the onset of SD. Furthermore, obesity per sè or through the obstructive sleep apnoea (OSA) could blunt sleep. Moreover, in menopause is usual a reduction in melatonin, that could contribute to SD. Nutritional strategies are paramount because they could contribute to manage menopause-related SD, in particular tackling obesity and overweight. Furthermore, some foods, such as soy, fish, whole grains, vegetables and fruit could decrease symptoms like depression and VMS, correlated with SD in postmenopausal women. Therefore, the aim of this review is to provide an overview of the current evidence on SD in menopause and to provide nutritional strategies for managing SD in this context.

Association of lean body mass to menopausal symptoms: The Study of Women's Health Across the Nation

Background

The purpose of this study was to examine the association of lean body mass (LBM) to the development of vasomotor symptoms (VMS) as women transition through menopause.

Methods

This study is a secondary use of data available for public use from follow up visits six through 10 for participants in the Study of Women’s Health Across the Nation. The study examined 2533 women, between the ages 42–52 years, each year over a10-year period. Data was modeled for associations of lean body mass and VMS. Changes in LBM since prior visit and since baseline were also modeled along with differences in means using binary logistic regression, adjusting for covariates.

Results

LBM was significantly associated to concurrent VMS (p = .036), percent change in LBM since prior visit (p = .003), percent change since baseline (p < .001), and overall means associations (p = .023). LBM was not significant for VMS at individual visit measures. In mixed regression modeling, time was significant (p < .0001) at all visits. The estimated probability of developing VMS decreases significantly as LBM increases.

Conclusions

Lean body mass is negatively associated with incident VMS. Our data suggests that maintaining higher levels of LBM during the menopausal transition may be protective against the development of VMS. Every woman will experience menopause in her life and the ability to potentially prevent the onset of specific symptoms through basic interventions, such as resistance training to increase lean body mass, may positively impact this large population.

Association of snoring and body composition in (peri-post) menopausal women

BACKGROUND

Little attention has been paid to whether snoring frequency is associated with body composition in menopausal women, particularly in China. This study objected to investigate the association between self-reported snoring and body composition in (peri-post) menopausal Chinese women as well as metabolic indicators.

METHODS

This cross-sectional study enrolled 715 participants aged 40-67 years from the Menopause Clinic in the Shanghai Sixth People's Hospital. Participants were categorized into four subgroups stratified by self-reported snoring frequency: never, rarely (< 1 night per week), occasionally (1-2 nights per week), regularly (≥3 nights per week), while body composition was measured using bioelectrical impedance analysis (BIA). Besides, blood sample were collected to test the glycolipid indicators.

RESULTS

In our sample of investigation, regular snoring (≥3 nights per week) was found to be an independent risk factor for higher fat mass (total, upper limbs, trunk), with the highest risk of 2.4 times for fat mass of trunk after adjusting for metabolic confounders(p = 0.003). Meanwhile, regular snoring was independently associated with higher fat mass (total and each segment) only in menopausal transition (p = 0.023).

CONCLUSIONS

We suggested that self-reported regular snoring may be taken as a simple alternative to predict higher fat mass (≥17.11 kg, upper quartile) in menopausal women. Similarly, body composition should be attached to the great importance to those who in menopausal transition in order to help to prevent obstructive sleep apnea (OSA).

Mediterranean diet as medical prescription in menopausal women with obesity: a practical guide for nutritionists

Menopausal transition is associated with weight gain and increased visceral fat distribution, which acts as an endocrine organ secreting the pro-inflammatory adipocytokines, which leads to metabolic disorders typical of menopause, including type 2 diabetes and cardiovascular diseases. Given the increasing number of aging population, the nutritional strategies to prevent obesity and obesity-related diseases in menopausal women is becoming a growing need and it should be one of the main objective for Nutritionists. The Mediterranean diet is characterized from foods with anti-inflammatory and antioxidant actions, such as extra-virgin olive oil, vegetables, fruits, legumes, nuts, red wine, and whole-grain cereals. Several evidences showed that the Mediterranean diet acts on both weight control and menopause, in addition to the known effects of the Mediterranean diet on cardiovascular and metabolic diseases. The Mediterranean diet is comparable with pharmacological interventions in terms of reducing the risk of obesity and cardiovascular and metabolic events. Considering that there are no specific dietary guidelines to manage weight in menopause, the aim of this review is to provide a nutritional guideline for the management of weight in menopause, particularly focusing on the Mediterranean diet.

Fat mass changes during menopause: a metaanalysis

OBJECTIVE

Data: Fat mass has been shown to increase in aging women; however, the extent to which menopausal status mediates these changes remains unclear. The purpose of this review was to determine (1) how fat mass differs in quantity and distribution between premenopausal and postmenopausal women, (2) whether and how age and/or menopausal status moderates any observed differences, and (3) which type of fat mass measure is best suited to the detection of differences in fat mass between groups.

STUDY

This review with metaanalyses is reported according to Metaanalysis of Observational Studies in Epidemiology guidelines.

STUDY APPRAISAL AND SYNTHESIS METHODS

Studies (published up to May 2018) were identified via PubMed to provide fat mass measures in premenopausal and postmenopausal women. We included 201 cross-sectional studies in the metaanalysis, which provided a combined sample size of 1,049,919 individuals and consisted of 478,734 premenopausal women and 571,185 postmenopausal women. Eleven longitudinal studies were included in the metaanalyses, which provided a combined sample size of 2472 women who were premenopausal at baseline and postmenopausal at follow up.

RESULTS

The main findings of this review were that fat mass significantly increased between premenopausal and postmenopausal women across most measures, which included body mass index (1.14 kg/m²; 95% confidence interval, 0.95-1.32 kg/m²), bodyweight (1 kg; 95% confidence interval, 0.44-1.57 kg), body fat percentage (2.88%; 95% confidence interval, 2.13-3.63%), waist circumference (4.63 cm; 95% confidence interval, 3.90-5.35 cm), hip circumference (2.01 cm; 95% confidence interval, 1.36-2.65 cm), waist-hip ratio (0.04; 95% confidence interval, 0.03-0.05), visceral fat (26.90 cm²; 95% confidence interval, 13.12-40.68), and trunk fat percentage (5.49%; 95% confidence interval, 3.91-7.06 cm²). The exception was total leg fat percentage, which significantly decreased (-3.19%; 95% confidence interval, -5.98 to -0.41%). No interactive effects were observed between menopausal status and age across all fat mass measures.

CONCLUSION

The change in fat mass quantity between premenopausal and postmenopausal women was attributable predominantly to increasing age; menopause had no significant additional influence. However, the decrease in total leg fat percentage and increase in measures of central fat are indicative of a possible change in fat mass distribution after menopause. These changes are likely to, at least in part, be due to hormonal shifts that occur during midlife when women have a higher androgen (ie, testosterone) to estradiol ratio after menopause, which has been linked to enhanced central adiposity deposition. Evidently, these findings suggest attention should be paid to the accumulation of central fat after menopause, whereas increases in total fat mass should be monitored consistently across the lifespan.

Association of body composition with menopausal symptoms in (peri-)menopausal women

OBJECTIVE

To explore the correlation of body composition with the severity of menopausal symptoms, as well as each classic menopausal symptom.

METHODS

A total of 758 (peri-)menopausal women were recruited (aged from 40 to 67 years) from the Menopause Clinic in the Shanghai Sixth People's Hospital. Different regions of fat mass, lean mass and fat-free mass were measured by bioelectrical impedance analysis, while menopausal symptoms were evaluated by valid modified Kupperman's index (KMI) in the Chinese version.

RESULTS

After adjusting for potential confounders, logistic regression revealed that trunk lean mass (odds ratio 0.29, 95% confidence interval 0.09-0.99) was the independent determinant of moderate to severe menopausal symptoms (KMI ≥ 16). In multiple regression analysis, significant relationships were found between body mass index and hot flushes/sweating and diabetes (p < 0.05). There was a significant relationship between lean mass and muscle/joint pain and sexual problems (p < 0.05). We also observed significant relationships between fat mass and hot flushes/sweating and muscle/joint pain.

CONCLUSIONS

Our findings indicated that trunk lean mass was an independent protective factor for moderate to severe menopausal symptoms. Strengthening the trunk lean mass may alleviate menopausal symptoms.

Developing and Validating an Age-Independent Equation Using Multi-Frequency Bioelectrical Impedance Analysis for Estimation of Appendicular Skeletal Muscle Mass and Establishing a Cutoff for Sarcopenia

Background: Appendicular skeletal muscle (or lean) mass (ALM) estimated using dual-energy X-ray absorptiometry (DXA) is considered to be a preferred method for sarcopenia studies. However, DXA is expensive, has limited portability, and requires radiation exposure. Bioelectrical impedance analysis (BIA) is inexpensive, easy to use, and portable; thus BIA might be useful in sarcopenia investigations. However, a large variety of models have been commercially supplied by different companies, and for most consumer products, the equations estimating ALM are not disclosed. It is therefore difficult to use these equations for research purposes. In particular, the BIA equation is often age-dependent, which leads to fundamental difficulty in examining age-related ALM loss. The aims of the current study were as follows: (1) to develop and validate an equation to estimate ALM using multi-frequency BIA (MF-BIA) based on theoretical models, and (2) to establish sarcopenia cutoff values using the equation for the Japanese population. Methods: We measured height (Ht), weight, and ALM obtained using DXA and a standing-posture 8-electrode MF-BIA (5, 50, 250 kHz) in 756 Japanese individuals aged 18 to 86-years-old (222 men and 301 women as developing equation group and 97 men and 136 women as a cross validation group). The traditional impedance index (Ht²/Z₅₀) and impedance ratio of high and low frequency (Z₂₅₀/Z₅) of hand to foot values were calculated. Multiple regression analyses were conducted with ALM as dependent variable in men and women separately. Results: We created the following equations: ALM = (0.6947 × (Ht²/Z₅₀)) + (-55.24 × (Z₂₅₀/Z₅)) + (-10,940 × (1/Z₅₀)) + 51.33 for men, and ALM = (0.6144 × (Ht²/Z₅₀)) + (-36.61 × (Z₂₅₀/Z₅)) + (-9332 × (1/Z₅₀)) + 37.91 for women. Additionally, we conducted measurements in 1624 men and 1368 women aged 18 to 40 years to establish sarcopenia cutoff values in the Japanese population. The mean values minus 2 standard deviations of the skeletal muscle mass index (ALM/Ht²) in these participants were 6.8 and 5.7 kg/m² in men and women, respectively. Conclusion: The current study established and validated a theoretical and age-independent equation using MF-BIA to estimate ALM and provided reasonable sarcopenia cutoff values.

Quantification of whole-body and segmental skeletal muscle mass using phase-sensitive 8-electrode medical bioelectrical impedance devices

Background/Objectives:

Bioelectrical impedance analysis (BIA) provides noninvasive measures of skeletal muscle mass (SMM) and visceral adipose tissue (VAT). This study (i) analyzes the impact of conventional wrist-ankle vs segmental technology and standing vs supine position on BIA equations and (ii) compares BIA validation against magnetic resonance imaging (MRI) and dual X-ray absorptiometry (DXA).

Subjects/Methods:

One hundred and thirty-six healthy Caucasian adults (70 men, 66 women; age 40±12 years) were measured by a phase-sensitive multifrequency BIA (seca medical body composition analyzers 515 and 525). Multiple stepwise regression analysis was used to generate prediction equations. Accuracy was tested vs MRI or DXA in an independent multiethnic population.

Results:

Variance explained by segmental BIA equations ranged between 97% for total SMM_MRI, 91–94% for limb SMM_MRI and 80–81% for VAT with no differences between supine and standing position. When compared with segmental measurements using conventional wrist-ankle technology. the relationship between measured and predicted SMM was slightly deteriorated (r=0.98 vs r=0.99, P<0.05). Although BIA results correctly identified ethnic differences in muscularity and visceral adiposity, the comparison of bias revealed some ethnical effects on the accuracy of BIA equations. The differences between LST_DXA and SMM_MRI at the arms and legs were sizeable and increased with increasing body mass index.

Conclusions:

A high accuracy of phase-sensitive BIA was observed with no difference in goodness of fit between different positions but an improved prediction with segmental compared with conventional wrist-ankle measurement. A correction factor for certain ethnicities may be required. When compared with DXA MRI-based BIA equations are more accurate for predicting muscle mass.