BACKGROUND: The fat-to-muscle mass ratio (FMR), integrating the antagonistic effects of fat and muscle mass, has been suggested as a valuable indicator to assess cardiometabolic health independent of overall adiposity. However, the specific associations of total and regional FMR with cardiometabolic risk are poorly understood. We aimed to examine sex-specific associations of total and regional FMR with single and clustered cardiometabolic risk factors (CRFs).
METHODS: 13,505 participants aged 20 years and above were included in the cross-sectional study. Fat mass and muscle mass were assessed using a bioelectrical impedance analysis device. FMR was estimated as fat mass divided by muscle mass in corresponding body parts (whole body, arm, leg, and trunk). Clustered CRFs was defined as the presence of two or more risk factors, including hypertension, elevated blood glucose, dyslipidemia, insulin resistance (IR), and hyperuricemia. IR was assessed by the triglyceride glucose (TyG) index. Multivariable logistic regression models were applied to explore the associations of FMR in the whole body and body parts with single and clustered CRFs.
RESULTS: The odds ratios (ORs) increased significantly for all single and clustered CRFs with the per quartile increase of total and regional FMR in both sexes (P for trend < 0.001), following adjustment for confounders. Among the regional parts, FMRs of the legs presented the strongest associations for clustered CRFs in both men and women, with adjusted OR of 8.54 (95% confidence interval (CI): 7.12-10.24) and 4.92 (95% CI: 4.24-5.71), respectively. Significant interactions (P for interaction < 0.05) were identified between age and FMRs across different body parts, as well as between BMI status and FMRs in different regions for clustered CRFs. Restricted cubic splines revealed significant non-linear relationships between FMRs of different body parts and clustered CRFs in both sexes (P for nonlinear < 0.05).
CONCLUSIONS: FMRs in the whole body and different regions were significantly associated with single and clustered CRFs in the general Chinese population. The association between FMR and clustered CRFs was more pronounced in youngers than in the elderly.

UNASSIGNED: Adipose tissue excess is associated with adverse health outcomes, including type 2 diabetes. Body mass index (BMI) is used to evaluate obesity but is inaccurate as it does not account for muscle mass, bone density, and fat distribution. Accurate measurement of adipose tissue through dual-energy X-ray absorptiometry (DXA) and computed axial tomography (CT) is crucial for managing and monitoring adiposity-related diseases. Still, these are not easily accessible in most hospitals in Mexico. Bioelectrical impedance analysis (BIA) is non-invasive and low-cost but may not be reliable in conditions affecting the body\'s hydration status, like diabetes.
UNASSIGNED: To assess fat mass concordance between BIA and DXA in Hispanic-American adults with type 2 diabetes mellitus (T2DM).
UNASSIGNED: Cross-sectional study of a non-probabilistic sample of subjects over 18 years with type 2 diabetes. We used DXA as the reference method.
UNASSIGNED: We evaluated the accuracy of FM estimation through BIA and DXA in 309 subjects with type 2 diabetes. Results showed a trend of overestimating the diagnosis of obesity using BIA, especially in individuals with a higher fat mass index (FMI). At the group level, we found BIA accurate; however, at the individual level, it is not. The bias between the 2 methods showed a statistically significant overestimation of body fat by BIA (P ⩽ .01) in both sexes. BIA demonstrated high precision in estimating fat mass. We were able to provide a correction factor of 0.55 kg in men.
UNASSIGNED: BIA is inaccurate compared to DXA for body composition assessment in patients with diabetes. Inaccurate measurements can result in misclassification. However, BIA is precise for body composition assessment in patients with diabetes, so it is reliable for tracking patient progress over time.
Agreement between bioelectrical impedance analysis and dual-energy X-ray absorptiometry to estimate fat mass in adults with type 2 Diabetes Mellitus This study compares 2 methods for measuring body composition in patients with diabetes in Mexico. The first method is Bioelectrical Impedance Analysis (BIA), which is non-invasive, low-cost, and easy to use but may not be reliable in conditions that affect the body’s hydration status, like diabetes. The second method is Dual-energy X-ray Absorptiometry (DXA), which is more accurate but less easily accessible. The study was a cross-sectional evaluation of 309 participants over 18 years with type 2 diabetes mellitus (T2DM) by HbA1C levels. The present study found BIA to be precise for body composition assessment but not accurate compared to DXA as the reference method. The study showed a trend of overestimating the diagnosis of obesity using BIA, especially in individuals with a higher fat mass index. This study found BIA is accurate at the group level but not at the individual level. The bias between the 2 methods showed a statistically significant overestimation of body fat by BIA. We provided a correction factor of 0.55 kg in men but not women. BIA is not ideal for diagnosing obesity but is reliable for tracking patient progress over time.

BACKGROUND: Breast Cancer-Related Lymphedema (BCRL) is one of the most prominent long-term side effects of breast cancer (BC) treatment. Although an increased BMI is a well-recognized risk factor for BCRL, there is a lack of knowledge regarding the potential associations between body composition and the risk of BCRL. Therefore, this study aimed to analyze the BCRL risk profiles of surgically operated BC patients via body composition and the Tissue Dielectric Constant (TDC) method, respectively.
METHODS: A total of 72 patients were included. Patients\' risk for BCRL was assessed with Moisture MeterD (Delfin, Finland) in 4 different probes each has unique penetration depths from 0.5 (10 mm) to 5.0 (55 mm) at both upper extremities. The body composition was analyzed with Tanita-BC-420 (TANITA, Japan). Comparing the dielectric values of extremities and proportioning to one another as TDC ratio (at-risk side/unaffected side) was used to profile BCRL risk.
RESULTS: TDC values of the thorax reference point were significantly higher in all four probes on the at-risk side (P < .05). TDC ratios in the forearm and Thorax points were significantly correlated with fat mass (r = 0.256, P = .030; r = 0.269, P = .022) as well as with visceral fat rating (VFR) (r = 0.340, P = .003; r = 0.466, P < .001).
CONCLUSIONS: This study highlights the need for further care and investigation in the assessment and prediction of BCRL by considering body composition. Since the risk reduction of BCRL can be maximized by considering the individual features, we can conclude that patients with higher body fat irrespective of the BMI should be followed up regularly.

Previous studies have yielded inconsistent results regarding the relationship between obesity and bone mineral density (BMD). The aim of this study was to determine the influence of body composition on BMD and the serum sclerostin level in overweight and obese adults. The study had a cross-sectional design and included 90 men and 118 women with a body mass index ≥25. Fat mass, lean mass, and spinal and pelvic BMD were measured using dual-emission X-ray absorptiometry. Subcutaneous fat, visceral fat, and lean mass were measured between L2 and L3 by 16-slice spiral computed tomography. The serum sclerostin level was determined by enzyme-linked immunosorbent assay. Pearson analysis showed that fat mass and appendicular lean mass were positively correlated with spinal BMD in both sexes. A positive association of both fat mass and lean mass with pelvic BMD, which was stronger in women, was also found. Partial correlation analysis showed the positive association between fat mass and BMD was significantly attenuated but the positive association between lean mass and pelvic BMD remained after adjustment for age and body weight. A negative correlation was observed between visceral fat and spinal and pelvic BMD only in women, and the positive association between lean mass with pelvic BMD was more obvious in women than in men, indicating body composition seemed to have a greater impact on the BMD in women. The serum sclerostin level was positively associated with BMD but not with body composition. These findings suggest that the correlation between body composition and BMD is influenced by sex and skeletal site.

Factors associated with change in percent body fat (%BF) of children in pediatric weight management (PWM) care may differ from those associated with change in weight status. Objective: To describe %BF and weight status at initial visits to 14 PWM sites, identify differences by sex, and evaluate factors associated with change over 6 months. Methods: Initial visits of 2496 males and 2821 females aged 5-18 years were evaluated. %BF was measured using bioelectrical impedance analysis. Results: Sex-specific logistic regressions [806 males (32.3%), 837 females (29.7%)] identified associations with primary outcomes: lower %BF and metabolically impactful ≥5-point drop in percent of the 95th BMI percentile (%BMIp95) over 6 months. At the initial visit, males had lower %BF and higher %BMIp95 than females. Over 6 months, males had significantly (p < 0.001) greater median drop in %BF (-1.4% vs. -0.4%) and %BMIp95 (-3.0% vs. -1.9%) and a higher frequency of decreased %BF (68.9% vs. 57.8%), but similar percentage with ≥5-point %BMIp95 drop (36.5% vs. 32.4%; p = 0.080). For males, factors significantly associated with decreased %BF (older age, ≥6 visits, lack of developmental or depression/anxiety concerns) were not related to having a ≥5-point %BMIp95 drop. For females, lack of depression/anxiety concern was significantly associated with decreased %BF but was not associated with ≥5-point %BMIp95 drop. Conclusions: There are differences by sex in initial visit %BF and %BMIp95 and in characteristics associated with changes in these measures. PWM interventions should consider evaluating body composition and sex-stratifying outcomes.

Background: Data on reference values for lean mass (LM) and fat mass (FM) in the Southeast Asian populations are currently lacking. Therefore, we aimed to estimate the normative values and generate anthropometric prediction models for LM and FM in the Thai population. Methods: Consecutive community-dwelling individuals aged 20-90 years were recruited from Srinagarind Hospital, Khon Kaen, Thailand, between 2010 and 2015. LM and FM were measured using dual energy X-ray absorptiometry. Age and sex stratified percentile of LM and FM were presented. Anthropometric prediction models for LM and FM were developed by using linear regression to generate competing models. Results: A total of 832 individuals (334 males and 498 females) were included in the study. The mean ± SD age, LM, and FM were 50.0 ± 16.2 years, 38.9 ± 8.0 kg, and 15.5 ± 7.7 kg, respectively. LM decreased with age from 49.4 kg in 20-29 years group to 42.3 kg in ≥70 years group in male and 34.6 kg in 30-39 years group to 30.8 kg in ≥70 years group in females. FM has an inverse U-shaped association with age, which peaked at 11.9 kg in 60-69 years group in males and 20.7 kg in 50-59 years group in females. Among the various anthropometric models, the models incorporating age, sex, weight, and height were considered the best fit for predicting both LM and FM. Conclusion: In the Thai population, peak LM was reached during early adulthood and decline with age, whereas FM showed an inverse U-shaped association with age. The prediction models incorporating age, sex, weight, and height were proposed as practical tools for assessing LM and FM in clinical practice.

UNASSIGNED: The relationships between habitual essential amino acid (EAA) intake and body composition, muscle strength, and physical function in older US adults are not well defined.
UNASSIGNED: This cross-sectional study evaluated associations between usual EAA intakes and body composition, muscle strength, and physical function in US adults ≥65 y.
UNASSIGNED: The Food and Nutrient Database for Dietary Studies (FNDDS) 2001-2018 was linked to the US Department of Agriculture Standard Reference database to access existing amino acid composition data for FNDDS ingredients. FNDDS ingredients without existing amino acid composition data were matched to similar ingredient codes with available data. Usual EAA, leucine, lysine, and sulfur-containing amino acid (SAA; methionine + cysteine) intakes (g/d) from National Health and Nutrition Examination Survey 2001-2018 were calculated for individuals ≥65 y (n = 10,843). Dependent variables included muscle strength measured by isometric grip test, body mass index (BMI), waist circumference, dual-energy X-ray absorptiometry-measured appendicular lean mass and whole-body fat mass, and self-reported physical function (that is, tasks of daily living). Regression analyses were used to determine covariate-adjusted relationships between EAA, leucine, lysine, and SAA intake and functional health outcomes. P < 0.0013 was considered significant.
UNASSIGNED: EAA, leucine, lysine, and SAA intakes, covaried with physical activity level and usual protein intake, were not associated with muscle strength or self-reported physical function in males or females or with body composition in males. EAA intakes were positively associated with waist circumference in females (β ± SEM, 2.1 ± 0.6 cm, P = 0.0007). Lysine intakes were positively associated with BMI (3.0 ± 0.7 kg/m2, P < 0.0001) and waist circumference (7.0 ± 1.7 cm, P = 0.0001) in females.
UNASSIGNED: Habitual EAA, leucine, lysine, and SAA intakes, covaried with physical activity level and usual protein intake, were not associated with lean mass, muscle strength, or physical function in adults ≥65 y. However, EAA intakes, particularly lysine, were positively associated with measures of adiposity in older females.This trial was registered with the Open Science Framework (https://doi.org/10.17605/OSF.IO/25V63) as osf.io/25v63).

OBJECTIVE: Previous studies have observed changes in fat and fat-free mass among preterm infants when compared to term-born infants. However, these studies have mainly focused on moderate or very preterm infants, with a scope limited to the first few years of life. We aimed to compare body composition in extremely preterm infants to term-born infants in early childhood. Additionally, we investigated whether early neonatal nutrition was associated with the distribution of fat- and fat-free mass in later life.
METHODS: The study used dual-energy x-ray absorptiometry to evaluate the body composition of 52 children aged 6-9-years, of whom 35 were born extremely preterm and 17 were born at term and was analyzed using multivariate linear regression. Nutritional intakes of fluids, energy, and macronutrients during the first eight postnatal weeks for 26 extremely preterm infants were investigated in relation to body composition at age 6-9 years using Bayesian regression analysis and Gradient Boosting Machine.
RESULTS: Children born extremely preterm had smaller head circumference (confidence interval -8.7 to -1.7), shorter height (confidence interval -2.7 to -0.6), higher waist to height ratio (confidence interval 0.01-0.05) and lower fat-free mass (confidence interval -3.9 to -0.49), compared to children born at full-term. Children born extremely preterm had a differing response to amount of fluid and macronutrient intake for both fat mass index and fat-free mass index. A bimodal response showed high intake of fluid and macronutrients as associated with high fat mass index for some children, whereas others demonstrated an inverse association, suggesting analysis on cohort-level as problematic.
CONCLUSIONS: Childhood body composition differs between extremely preterm infants and term-born infants. Extremely preterm infants display differing responses in their body composition to varying levels of fluids and macronutrient intake during the neonatal period.

BACKGROUND: Development of body composition (BC) may be disrupted in children with stunting. Such disruption may affect the later risk of excess adiposity and metabolic health, yet few studies have investigated correlates of BC in children with stunting.
OBJECTIVE: We aimed to investigate nutritional status, infection and inflammation, breastfeeding behaviors, and other factors as correlates of BC in children with stunting.
METHODS: Among Ugandan children with a height-for-age z-score <-2, BC was estimated using bioelectrical impedance analysis and compared with United Kingdom references. We used multiple linear regression analysis to identify correlates of fat mass (FM), fat-free mass (FFM), FM-index (FMI), and FFM index (FFMI) and height, adjusting for gender and age.
RESULTS: In 750 children aged 1-5 y, FMI was 0.46 (95% confidence interval [CI]: 0.38, 0.54] and FFMI 0.18 [95% CI: 0.11, 0.26) z-scores lower than United Kingdom references. Elevated serum α1-acid glycoprotein was associated with 1.14 [0.76, 1.52] cm lower height, 0.50 [0.35, 0.65] kg/m2 less FFMI, and 0.48 [0.31, 0.66] kg/m2 greater FMI. Similar, weaker, associations for elevated serum C-reactive protein were detected. A positive malaria rapid test was associated with 0.64 [0.25, 1.02] cm shorter height, but 0.36 [0.18, 0.54] kg/m2 greater FMI. Anemia (according to hemoglobin) was associated with 0.20 [0.07, 0.33] kg less FFM in proportion to shorter height. Longer breastfeeding duration was associated with 0.03 [0.02, 0.04] kg greater FFM per month, in proportion to greater height.
CONCLUSIONS: These children exhibited deficits in FM and FFM, proportionally to their stunted height, compared with United Kingdom references. Systemic inflammation correlated inversely with linear growth and FFM but positively with fatness, making it a possible target for intervention where fat-free tissue accretion is desirable. Longer breastfeeding may offer protection to lean linear growth, but findings for micronutrients were less clear. Longitudinal studies are warranted to support these findings. The study was registered at www.isrctn.com (Ref. ISRCTN13093195).

UNASSIGNED: Many studies define obesity based on body mass index (BMI) and explore its relationship with adult asthma. However, BMI only considers height and weight, ignoring other factors such as body fat, which may have a greater impact on health. We investigated the relationship between body fat distribution and adult asthma using both a cross-sectional study and bidirectional Mendelian randomization (MR) analysis.
UNASSIGNED: Weighted logistic regression models were used to examine the relationship between body fat distribution measurements and adult asthma in the cross-sectional study from National Health and Nutrition Examination Survey (NHANES) 2011-2018. Restricted cubic spline (RCS) curves were employed to explore the dose-response relationship between them. The inverse-variance weighted (IVW) method was used as the main method of MR analysis to explore the causal effect of exposure on outcome.
UNASSIGNED: After adjusting for all covariates, weighted logistic regression analysis indicated that fat mass in the left arm, left leg, right arm, right leg, trunk, and total body is associated with an increased risk of developing adult asthma (p < 0.05). RCS curves showed that all six fat mass indicators exhibit a J-shaped relationship with adult asthma. Forward MR analysis found a causal effect of six fat mass indicators on the increased risk of adult asthma (p < 0.05). However, reverse MR did not reveal any causal effect of adult asthma on these six fat mass indicators (p > 0.05).
UNASSIGNED: Our study supports a positive correlation and a unidirectional causality between body fat distribution measurements and the risk of adult asthma. Further studies are needed to validate our findings.