Fat-free Mass Index Research Articles

Improving the nutritional evaluation in head neck cancer patients using bioelectrical impedance analysis: Not only the phase angle matters.

Malnutrition and sarcopenia are highly prevalent in patients with head neck cancer (HNC). An accurate early diagnosis is necessary for starting nutritional support, as both are clearly associated with clinical outcomes and mortality. We aimed to evaluate the applicability and accuracy of body composition analysis using electrical bioimpedance vectorial analysis (BIVA) for diagnosing malnutrition and sarcopenia in patients with HNC cancer undergoing systemic treatment with chemotherapy or radiotherapy. Cross-sectional, observational study that included 509 HNC patients. A comprehensive nutritional evaluation that included BIVA was performed. The prevalence of malnutrition was higher in patients that received treatment with chemotherapy (59.2% vs. 40.8%, P<0.001); increased mortality was observed in malnourished patients (33.3% vs. 20.1%; P<0.001); ECOG status (1-4) was also worse in malnourished patients (59.2% vs. 22.8% P<0.001). Body cell mass (BCM) and fat mass were the most significantly associated parameters with malnutrition [OR 0.88 (0.84-0.93) and 0.98 (0.95-1.01), respectively]; BCM and fat free mass index (FFMI) were associated with several aspects including (1) the patient-generated subjective global assessment [OR 0.93 (0.84-0.98) and 0.86 (0.76-0.97), respectively], (2) the presence of sarcopenia [OR 0.81 (0.76-0.87) and 0.78 (0.66-0.92), respectively]. A BCM index (BCMI)<7.8 in combination with other parameters including FFMI and BCM accurately predicted patients with malnutrition [accuracy 95% CI: 0.803 (0.763-0.839); kappa index: 0.486; AUC: 0.618 (P<0.01)]. A BCMI cutoff of 7.6 was enough for identifying males with malnutrition (P<0.001), while it should be combined with other parameters in females. Body composition parameters determined by BIVA accurately identify patients with HNC and malnutrition. Phase angle, but other parameters including BCMI, FFMI and BCM provide significant information about nutritional status in patients with HNC.

Anthropometric indices in older adults with and without Locomotive Syndrome

BackgroundLocomotive syndrome is a major challenge for older adults, and anthropometric indices can greatly affect the musculoskeletal system. This study aimed to compare the anthropometric indices between older adults with and without locomotive syndrome.MethodsThis descriptive-analytical study was performed on 211 older adults using random cluster sampling from a population of over-60 individuals covered by comprehensive health service centers in Sari in Autumn, 2021. Participants were divided into two groups: with and without locomotive syndrome. Locomotive syndrome was assessed via the 25-item Geriatric Locomotive Function Scale questionnaire, and the level of anthropometric indices was determined through the Bioelectrical Impedance Analysis device. Data were analyzed by independent t-test, Mann-Whitney U, Chi-Square, and Binary logistic regression in SPSS, Version 23 (P < 0.05).ResultsThe average age of older adult participants was 78.4 ± 6.6 years. In older adults with locomotive syndrome, the average percentage of fat-free mass (P < 0.001) was significantly lower while the average percentage of fat mass and fat mass index (P < 0.001) was significantly higher. Older adults with locomotive syndrome were shorter in height (P < 0.001) and had a higher body mass index (P < 0.05). Fat-free mass percentage (OR = 0.59) and body mass index (OR = 1.4) predicted the incidence of locomotive syndrome in the subjects. Significant differences such as chronic diseases, chronic pain, falls, age, and gender were observed between the two groups (P < 0.05).ConclusionAnthropometric indices can play an important role in the occurrence of locomotive syndrome in older adults. Evaluation of anthropometric indices and management of body composition can help prevent locomotive syndrome and improve the quality of life of older adults.

Associations of Urinary Cadmium with Body Composition and Fat Distribution in US Adults: Findings from NHANES 2011-2018.

The effects of cadmium (Cd) on metabolic physiology remain controversial. Given the varying metabolic impacts associated with different body compositions, investigating the relationship between Cd exposure and body composition may facilitate further research. Here, the associations of body composition and fat distribution with urine Cd (UCd) were evaluated. This analysis included 2979 adult participants from the 2011-2018 National Health and Demographic Survey (NHANES). UCd was measured using inductively coupled plasma mass spectrometry and adjusted for urinary creatinine. Body composition and fat distribution were estimated using dual-energy x-ray absorptiometry (DXA). The study results show that UCd was negatively associated with fat mass index (FMI) and percent fat mass (p for trend < 0.001), and the negative correlation between UCd and FMI was stronger in males and smokers (all p for interaction < 0.05). In terms of abdominal fat distribution, UCd was negatively associated with abdominal subcutaneous adipose tissue (SAT) mass (p for trend < 0.001), but with abdominal visceral adipose tissue (VAT) mass only in those with low percent fat mass (< 32.3%) (p for trend = 0.026 and p for interaction < 0.05). UCd was positively related to percent VAT (p for trend < 0.001) and visceral-to-subcutaneous (VAT/SAT) ratio (p for trend = 0.003). And there was a significant negative association between UCd and android-to-gynoid (A/G) ratio (p for trend = 0.001). Meanwhile, UCd was negatively correlated with fat-free mass index (FFMI) (p for trend < 0.001). And the negative correlation between UCd and FFMI was stronger in males, smokers, and individuals with < 32.3 percent fat mass (all p for interaction < 0.05). We found the association of UCd with body composition and fat distribution, with distinct patterns observed in different demographic groups. These findings underscore the importance of considering UCd exposure in the context of body composition and fat distribution.

Prognostic value of the fat-free mass index-based cachexia index in patients with colorectal cancer

Studies have shown that the cachexia index (CXI) is a useful predictor of cachexia in patients with colorectal cancer. However, the application of the CXI is limited stemming from the intricacy and additional cost of radiographic examinations. This study aimed to develop an easy-to-use and practical CXI based on fat-free mass index (FFMI-CXI) to evaluate the prognostic value of FFMI-CXI in CRC. A total of 656 patients with CRC were enrolled in the Investigation on Nutrition Status and Clinical Outcome of Common Cancers (INSCOC) study. The FFMI-CXI was calculated as [FFMI (kg)/height (m)2 × serum albumin (g/L)]/neutrophil-lymphocyte ratio. The cutoff value for FFMI-CXI was determined through the analysis of ROC curves and Youden’s index for both male and female cohorts. Kaplan–Meier survival curves with log-rank tests were conducted to compare time–event relationships between different groups. Cox proportional hazards regression models incorporating both univariate and multivariate variables were employed to explore the independent prognostic factors associated with OS. Logistic regression analysis was performed to assess the association of the FFMI-CXI with secondary outcomes. The major outcome was 5-year overall survival (OS). Based on the cutoff values, 331 patients had low FFMI-CXI, and 325 patients had high FFMI-CXI. Patients in the low FFMI-CXI subgroup were significantly older and had advanced TNM stage, malnutrition, high systemic inflammation, long hospitalizations, high hospitalization costs, adverse short-term outcomes, and all-cause mortality. Multivariate Cox regression analyses revealed that FFMI-CXI (HR 0.47, 95% CI 0.33–0.66; p < 0.001) and TNM stage (HR 3.38, 95% CI 2.63–4.35; p < 0.001) were independently associated with OS in CRC patients. K-M survival curves revealed that the CRC patients with a high FFMI-CXI had significantly more favorable OS than those with low FFMI-CXI (62.84% vs. 84.31%; log-rank p < 0.001). Furthermore, the FFMI-CXI was valuable for predicting 90-day outcomes, malnutrition, cancer cachexia, length of hospitalization, and hospitalization expenses. This study revealed that the FFMI-CXI can be used as a prognostic indicator in patients with CRC. Patients with low FFMI-CXI should receive more attention.

12271 Differential Impacts Of Body Composition Indices On Cortisol Response And Hpa Axis Activity

Abstract Disclosure: S.G. Gonsalves: None. A. Ross: None. M.E. Steele: None. L.N. Saligan: None. Aim: The continued interest in the influence of muscle mass and fat distribution on stress stems from its implications on preventative healthcare. Fat mass index (FMI) and fat-free mass index (FFMI) were proposed as valuable indicators of body composition beyond body mass index (BMI). This study investigated correlations of FMI and FFMI with inflammatory stress markers, hypothesizing that these body composition indices identify inflammatory stress markers more distinctly than BMI. Methods: Skeletal muscle mass was assessed by Dual-Energy X-ray Absorptiometry, HPA axis response through an adrenocorticotropic hormone (ACTH) stimulation test, and markers of inflammation and stress response (e.g., dehydroepiandrosterone, DHEA) from peripheral blood of 104 healthy individuals aged 18-71 years, 52% female, with a mean BMI of 26.3 (+4.83). Perceived stress and fatigue were captured using patient-reported outcome questionnaires before the HPA procedure. Results: ACTH correlated with FFMI at baseline (ρ=0.299, p=0.009) and 60 minutes (ρ=0.254, p=0.041). Cortisol correlated with FFMI at 15 (ρ=–0.248, p≤0.025), 30 (ρ=–0.284, p≤0.010), and 60 minutes (ρ=–0.364, p≤0.001), and with BMI at 15 (ρ=–0.228, p=0.041). FMI and BMI did not correlate with ACTH and FMI with cortisol at any timepoint. With repeated measures ANOVA, FFMI at 50th percentile had large effect on cortisol (p=0.005, partial eta=0.094) at each timepoint, higher for the under lean than those with higher FFMI, compared to BMI at the same percentile (p=0.037, partial eta=0.054). None of the indices reached significance with ACTH. FMI correlated with Erythrocyte Sedimentation Rate (ESR) (ρ=0.521), C-reactive protein (CRP, ρ=0.493, both at p≤0.001), DHEA (ρ=0.252, p=0.030), and epinephrine (ρ=–0.246, p=0.045). FFMI was not correlated with ESR and CRP. BMI correlated only with albumin (ρ = –0.412, p ≤ 0.001 and CRP (ρ=0.342, p≤0.003). Discussion: The higher correlations of inflammatory stress markers with FMI and FFMI, as compared to BMI, supports our study hypothesis. These results hint that these body composition indices may detect subtle stress-related inflammatory changes than BMI. Future research should clarify underlying mechanisms driving these associations and explore the impact of targeted interventions on these indices and subsequent changes to inflammation and stress. Presentation: 6/1/2024

7522 Effects of Trikafta On Bone Mineral Density And Body Composition In Patients With Cystic Fibrosis

Abstract Disclosure: N. Mon: None. S.S. Krishnasamy: None. G. Bakeerathan: None. L. Healy: None. E. Favier: None. S. Foushee: None. Background: Cystic fibrosis related bone disease (CFBD) is a common complication of adult Cystic fibrosis (CF) patients due to calcium, vitamin D and K malabsorption from exocrine pancreatic insufficiency, increased inflammatory cytokines, glucocorticoid therapy, delayed puberty, physical inactivity, and hypogonadism. Newer CF transmembrane conductance regulator (CFTR) modulator therapy elexacaftor/tezacaftor/ivacaftor (Trikafta) has proven benefit in pulmonary and nutritional outcomes. There is limited data on effects of Trikafta on bone health and body composition. The aim is to examine the effects of Trikafta on bone mineral density (BMD) at the lumbar spine (LS) and femoral neck (FN), and body composition in terms of fat free mass index (FFMI) and fat mass index (FMI) in our CF patients. Method: We conducted a cross sectional and retrospective review of 38 adults with CF (Ages 20-59, 28 males and 10 females) in our CF clinic. Body Mass Index (BMI), Body composition measured by bioelectric impedance analysis, BMD of LS and FN by Dual-energy X-ray absorptiometry, Vitamin D level, and forced expiratory volume in one second (FEV1 % predicted) in patients taking Trikafta were analyzed and compared with control CF group who were not on Trikafta. Results: 38 subjects on Trikafta, aged 33.29 ± 10.36 years with FEV1 % predicted 65.11± 28.14% were studied. Serum 25-hydroxyvitamin D level was 35.92 ± 18.52 ng/dL. Of the 38 study patients, 23 (60.53%) had a diagnosis of CF related diabetes (CFRD). Among the Trikafta cohort, 18 (50%) had low BMD with Z-scores ≤ -2.0 and 7 (19.44%) of them had Z score ≤ -1.0 and &amp;gt; -2.0. Compared with the control group, LS BMD 0.93 ± 0.16 g/cm2 and FN BMD 0.73± 0.13g/cm2 (p &amp;gt;0.05) were not improved significantly. BMI of study population 23.09 ± 4.21 kg/m2 (p &amp;lt;0.05) and FMI 6.11 ± 4.25 kg/m2 (p &amp;lt;0.05) increased significantly; however, there was a decrease in FFMI 9.60 ± 1.44 kg/m2 (p &amp;lt;0.05). Conclusion: Treatment with Trikafta in CF patients was associated with increases in BMI and fat mass index but decrease in fat free mass index. There was no statistically significant difference in BMD at LS and FN in our study cohort. This study has limitations in terms of gender differences within the study cohort, duration of Trikafta use in relation to bone mass, and also extent of glucocorticoid use among the study subjects. Larger prospective clinical trials are needed to study efficacy of Trikafta on CFBD. Presentation: 6/3/2024

Plasma proteomics and carotid intima-media thickness in the UK biobank cohort.

Ultrasound derived carotid intima-media thickness (cIMT) is valuable for cardiovascular risk stratification. We assessed the relative importance of traditional atherosclerosis risk factors and plasma proteins in predicting cIMT measured nearly a decade later. We examined 6,136 UK Biobank participants with 1,461 proteins profiled using the proximity extension assay applied to their baseline blood draw who subsequently underwent a cIMT measurement. We implemented linear regression, stepwise Akaike Information Criterion-based, and the least absolute shrinkage and selection operator (LASSO) models to identify potential proteomic as well as non-proteomic predictors. We evaluated our model performance using the proportion variance explained (R 2). The mean time from baseline assessment to cIMT measurement was 9.2 years. Age, blood pressure, and anthropometric related variables were the strongest predictors of cIMT with fat-free mass index of the truncal region being the strongest predictor among adiposity measurements. A LASSO model incorporating variables including age, assessment center, genetic risk factors, smoking, blood pressure, trunk fat-free mass index, apolipoprotein B, and Townsend deprivation index combined with 97 proteins achieved the highest R 2 (0.308, 95% C.I. 0.274, 0.341). In contrast, models built with proteins alone or non-proteomic variables alone explained a notably lower R 2 (0.261, 0.228-0.294 and 0.260, 0.226-0.293, respectively). Chromogranin b (CHGB), Cystatin-M/E (CST6), leptin (LEP), and prolargin (PRELP) were the proteins consistently selected across all models. Plasma proteins add to the clinical and genetic risk factors in predicting a cIMT measurement. Our findings implicate blood pressure and extracellular matrix-related proteins in cIMT pathophysiology.

Changes in fat-free mass index by energy intake of patients with head and neck cancer after undergoing concurrent chemoradiotherapy

Changes in fat-free mass index by energy intake of patients with head and neck cancer after undergoing concurrent chemoradiotherapy

Study of malnutrition in patients with idiopathic pulmonary fibrosis

Background Although the interest in Idiopathic Pulmonary Fibrosis (IPF) has increased in recent years due to the appearance of new therapies however the interest has focused on pulmonary involvement with little concern for systemic manifestations such as the nutritional status abnormalities. Thus, our study assessed the malnutrition prevalence in patients with IPF and the best indicators for the assessment of malnutrition among them. Patients and methods This work was conducted on 110 stable IPF patients who attended the outpatient clinic of Ain Shams University Hospitals from October 2020 to July 2021. Data about the detailed history and nutritional assessment was collected. Results 22.7% and 20.9% were malnourished according to the definition of fat-free mass index (FFMI) and body mass index (BMI), respectively. Most malnourished patients according to low FFMI were female; not using PPI was a significant independent predictors of malnutrition. There was a statistically significant relation between low FFMI and low serum albumin, hemoglobin, and oxygen saturation. Our findings also revealed that measuring BMI and being less than or equal to 22.1 kg/m2 and mid-arm circumference (MAC) less than or equal 28.5 cm is significantly related to low free fat mass index (malnutrition) and increases that risk by 31.63 folds. Conclusion Nearly one-quarter of IPF patients were malnourished and it was found that measuring BMI less than or equal to 22.1 kg/m2 together with MAC less than or equal to 28.5 cm can predict low FFMI and that can be used in our clinical approach.

Variation of All-Cause Mortality with Fat-Free Mass Index (FFMI) and Fat Mass Index (FMI) in Individuals with Asthma: Results from the NHANES Database Retrospective Cohort Study.

The relationship between fat-free mass index (FFMI), fat mass index (FMI), and mortality in patients with asthma remains unknown. This study aimed to examine the associations between FFMI and FMI and all-cause mortality in a cohort of American adults diagnosed with asthma. This study included 15,200 adults from NHANES. To assess mortality, we linked participant records to the National Death Index. FMI and FFMI were measured and evaluated using dual-energy X-ray absorptiometry (DXA). Survival differences across quintiles of FFMI and FMI were explored using Kaplan-Meier plots and log-rank tests, with the proportional hazards assumption assessed using Schoenfeld residuals. Cox proportional hazards regression models were used to estimate the hazard ratios (HRs) for mortality associated with FFMI and FMI, adjusting for potential confounders including age, sex, smoking status, physical activity, and other relevant factors. Additionally, stratified analyses based on theoretical considerations were conducted to identify subgroups of individuals exhibiting an elevated risk of mortality. This study also examined the nonlinear relationships between FFMI, FMI, and mortality using restricted cubic splines (RCS). After a median follow-up of 184 months, 12.11% of individuals had died. Kaplan-Meier plots revealed significant differences in all-cause mortality among patients with asthma across the FFMI and FMI quintiles. Specifically, individuals in the lowest FFMI quintile (Q1, 10.4-16.0, representing the range of FFMI values) exhibited a significantly increased risk of all-cause mortality (HR: 4.63; 95% CI: 1.59, 13.5; p < 0.01). Similarly, elevated risks of all-cause mortality were observed in the upper three quintiles of FMI, with Q3 (4.8-6.1) having an HR of 2.9 (95% CI: 1.20, 7.00; p < 0.05), Q4 (6.2-8.3) having an HR of 3.37 (95% CI: 1.41, 8.03; p < 0.01), and Q5 (8.4-22.8) having an HR of 4.6 (95% CI: 1.31, 16.2; p < 0.05). Moreover, the risk of all-cause mortality increased with increasing FMI and decreasing FFMI (p for non-linearity < 0.001 in both cases). Subgroup analyses further elucidated these associations across different categories. In examining the association between FMI and all-cause mortality among asthma patients across various subgroups, a heightened mortality risk found among males, individuals with medium education levels, medium income levels, and those who consume alcohol. The study shows that both high FMI and low FFMI are associated with increased mortality in patients with asthma. These findings underscore the critical role of FMI and FFMI in the health management of asthma patients. Therefore, it is recommended that clinicians proactively monitor and adjust these indices to improve patient prognosis and enhance health outcomes for individuals with asthma..

Relationship between fat-free mass index and nutrient intake in protein supplement user among Japanese collegiate soccer athletes

[Purpose] Protein supplements are widely used by athletes, prompting the scrutiny of their impact on low energy availability. This study investigated whether habitual protein supplement use is linked to physical characteristics and nutrient intake in Japanese university soccer athletes. In addition, an attempt was made to examine the differences in physical characteristics and nutrient intake according to muscle mass in protein supplement users using the fat-free mass index (FFMI), which reflects muscle mass.[Methods] A dietary survey, physical activity survey, and measurement of the physical characteristics of 38 Japanese collegiate soccer players were conducted.[Results] The habitual protein supplement utilization rate among the participants was 50%, and the participants exhibited an FFMI of 19.2 ± 1.3 kg/m&lt;sup&gt;2&lt;/sup&gt;. Significant disparities between the two groups were noted in exercise energy expenditure (&lt;i&gt;p&lt;/i&gt; = 0.023); carbohydrates (&lt;i&gt;p&lt;/i&gt; = 0.039); copper (&lt;i&gt;p&lt;/i&gt; = 0.003); and vitamins B1 (&lt;i&gt;p&lt;/i&gt; = 0.016), B2 (&lt;i&gt;p&lt;/i&gt; = 0.040), B6 (&lt;i&gt;p&lt;/i&gt; = 0.003), C (&lt;i&gt;p&lt;/i&gt; = 0.012), and D (&lt;i&gt;p&lt;/i&gt; = 0.033), with higher levels observed in the protein-consuming cohort compared to the non-consuming cohort. Protein supplement users (n = 15) were stratified into two groups based on the median FFMI of the entire population (18.9 kg/m&lt;sup&gt;2&lt;/sup&gt;). While the energy balance ratios were comparable between the groups, the high FFMI group tended to exhibit elevated energy intake (&lt;i&gt;p&lt;/i&gt; = 0.169), consumption (&lt;i&gt;p&lt;/i&gt; = 0.076), and carbohydrate consumption (&lt;i&gt;p&lt;/i&gt; = 0.092), compared to the low FFMI group.[Conclusion] These findings suggest that adequate carbohydrate and protein intakes are crucial for preserving or augmenting muscle mass in young Japanese soccer athletes, including those consuming protein supplements.

A comparison of principal component analysis, reduced-rank regression, and partial least–squares in the identification of dietary patterns associated with cardiometabolic risk factors in Iranian overweight and obese women

BackgroundAccording to epidemiological studies, unhealthy dietary patterns and lifestyle lead to rising obesity and cardiometabolic diseases in Iran. Hybrid techniques were used to identify a dietary pattern characterized by fiber, folic acid, and carotenoid intake due to their association with cardiometabolic risk factors such as anthropometric measurements, blood pressure, lipid profile, C-Reactive Protein (CRP), Plasminogen Activator Inhibitor (PAI), Homeostatic Model Assessment Index (HOMA Index), cardiometabolic index (CMI), and monocyte chemoattractant protein (MCP-1). So, the objective of the recent study is to compare the reduced-rank regression (RRR) and partial least–squares (PLS) approaches to principal component analysis (PCA) for estimating diet-cardiometabolic risk factor correlations in Iranian obese women.MethodsData on dietary intake was gathered from 376 healthy overweight and obese females aged 18 to 65 years using a 147-item food frequency questionnaire (FFQ). In this cross-sectional study, participants were referred to health centers of Tehran. Dietary patterns were developed using PCA, PLS, and RRR, and their outputs were assessed to identify reasonable patterns connected to cardiometabolic risk factors. The response variables for PLS and RRR were fiber, folic acid, and carotenoid intake.ResultsIn this study, 3 dietary patterns were identified by the PCA method, 2 dietary patterns by the PLS method, and one dietary pattern by the RRR method. High adherence to the plant-based dietary pattern identified by all methods were associated with higher fat free mass index (FFMI) (P < 0.05). Women in the highest tertile of the plant-based dietary pattern identified by PLS had 0.06 mmol/L (95% CI: 0.007,0.66, P = 0.02), 0.36 mmHg (95% CI: 0.14,0.88, P = 0.02), and 0.46 mg/l (95% CI: 0.25,0.82, P < 0.001), lower FBS, DBP, and CRP respectively than women in the first tertile. Also, PLS and RRR-derived patterns explained greater variance in the outcome (PCA: 1.05%; PLS: 11.62%; RRR: 25.28%), while the PCA dietary patterns explained greater variance in the food groups (PCA: 22.81%; PLS: 14.54%; RRR: 1.59%).ConclusionPLS was found to be more appropriate in determining dietary patterns associated with cardiometabolic-related risk factors. Nevertheless, the advantage of PLS over PCA and RRR must be confirmed in future longitudinal studies with extended follow-up in different settings, population groups, and response variables.

The oxygen uptake efficiency slope does not accurately predict O2peak of children - the Arkansas Active Kids study.

Cardiorespiratory fitness (CRF) is a vital indicator of health. However, accurately measuring peak oxygen consumption ( O2peak) to determine CRF in children can be challenging. The oxygen uptake efficiency slope (OUES) has been proposed as an alternative metric for predicting O2peak in children, but its accuracy and agreement with measured O2peak remain unclear. A post hoc analysis was conducted in 94 children (ages 7-10years) who completed an incremental cycle ergometer test to measure O2peak. Body composition (Dual-energy X-ray absorptiometry) was measured, and fat mass index (FMI, kg/m2) and fat-free mass index (FFMI, kg/m2) were calculated. OUES was determined using all respiratory data (OUES100%) collected during the cycle ergometer test and using data only up to 60% of heart rate reserve (OUES60%HRR). Regression equations to predict O2peak (Pred- O2peak) were derived from simple and multiple linear regression analysis. Bland-Altman analysis assessed the level of agreement between Pred- O2peak and measured O2peak. OUES60%HRR (β = 0.46, p < 0.0001), age (β = 56.0, p = 0.0004), White race (β = 173.3, p < 0.0003), FFMI (β = 0.98.6, p < 0.000), and FMI (β = -0.40.8, p < 0.000) were retained in the final model. The difference between measured O2peak and Pred- O2peak was not different from zero (p = 0.999). There was a positive association between the difference of measured O2peak and Pred- O2peak and the average of the two methods (β = 0.79, p = 0.0028). There was no mean bias between measured O2peak and Pred- O2peak. However, magnitude bias was present even after considering other significant predictors of O2peak (FMI, FFMI, race, and age) in the regression equation. Caution is advised when using OUES to predict O2peak in children.

Dietary Patterns by Level of Maternal Education and Their Contribution to BMI, Fat Mass Index, and Fat-Free Mass Index at Age 5 and the Longitudinal Association with BMI at Age 10.

Our aim was to identify dietary patterns by the level of maternal education that contribute to BMI, fat mass index (FMI), and fat-free mass index (FFMI) in children at age 5 and to assess if these dietary patterns are related to BMI at age 10. Per group (low/middle/high level), Reduced Rank Regression (RRR) was used to derive dietary patterns for the response variables BMI z-score, FMI, and FFMI in 1728 children at age 5 in the Amsterdam Born Children and their Development (ABCD) cohort. Regression analyses were then used to determine the association with BMI at age 10. In each group, pattern 1 was characterized by its own cluster of food groups. Low: water/tea, savory snacks, sugar, low-fat meat, and fruits; middle: water/tea, low-fat cheese, fish, low-fat dairy, fruit drink, low-fat meat, and eggs; and high: low-fat cheese, fruits, whole-grain breakfast products, and low-fat and processed meat. Additionally, in each group, pattern 1 was positively associated with BMI z-scores at age 10 (low: β ≤ 0.43 [95% CI ≤ 0.21; 0.66], p < 0.001, middle: β ≤ 0.23 [0.09; 0.36], p ≤ 0.001, and high: β ≤ 0.24 [0.18; 0.30], p < 0.001). The dietary patterns stratified by the level of maternal education are characterized by different food groups. But in all the groups, pattern 1 is positively associated with BMI at age 10.

An Analysis of Body Composition and Physical status of middle aged Women

Background: Body composition and physical status are essential indicators of overall health, especially in middle-aged women. This group often undergoes significant physiological changes due to aging, hormonal shifts, and lifestyle factors, affecting their body composition, including fat mass, lean muscle mass, and bone density. Methodology: A total of 100 women from Varanasi city, comprising both employed individuals and housewives, participated in this study. These women were divided into two groups, each consisting of 100 subjects aged between 35 and 50 years. The selected variables for body composition analysis included total body fat, fat-free mass, bone mass, muscle mass, body mass index, and physical status. Results: The t-test for Equality of Means revealed a significant difference between the groups, t(198) = 1.660, with p-values indicating substantial differences in total body fat (p &lt; .001), fat-free mass (p &lt; .001), bone mass (p &lt; .000), muscle mass (p &lt; .001), and body mass index (p &lt; .001). Furthermore, there was a significant difference in physical activity levels, t(198) = 11.714, p &lt; .001). Conclusion: The study found a considerable difference in body composition parameters between employed women and housewives. Employed women exhibited lower total body fat and BMI, and higher muscle mass, fat-free mass, and bone mass compared to housewives. This suggests that employed women, likely due to more structured schedules and better access to physical exercise, maintain a healthier body composition.

Analysis of metabolic alterations as 30 days intensive care mortality predictors for patients undergoing continuous renal replacement therapy

BackgroundAcute kidney injury patients on continuous renal replacement therapy are subjected to alterations in metabolism, which in turn are associated with worse clinical outcome and mortality. The aim of this study is to determine which metabolism indicators can be used as independent predictors of 30 days intensive care unit (ICU) mortality. MethodsThis was a prospective observational study on critical care patients on renal replacement therapy. Integrated approach of metabolism evaluation was used, combining the energy expenditure measured by indirect calorimetry, bioelectrical impedance provided fat free mass index (FFMI), amino acid and glucose concentrations. ICU mortality was defined as all cause 30 days mortality. Regression analysis was conducted to determine the conventional and metabolism associated predictors of mortality. ResultsThe study was conducted between the 2021 March and 2022 October. 60 high mortality risk patients (APACHE II of 22.98±7.87, 97% on vasopressors, 100% on mechanical ventilation) were included during the period of the study. The rate of 30 days ICU mortality was 50% (n=30). Differences across survivors and non-survivors in metabolic predictors were noted in energy expenditure (kcal/kg/day) (19.79 ±5.55 vs 10.04 ±3.97 p=0.013), amino acid concentrations (mmol/L) (2.40 ±1.06 vs 1.87 ±0.90 p=0.040) and glucose concentrations (mmol/L) (7.89 ±1.90 vs 10.04 ±3.97 p=0.010). No differences were noted in FFMI (23.38 ±4.25 vs 21.95 ±3.08 p=0.158). In the final linear regression analysis model, lower energy expenditure (exp(B)= 0.852 CI95%: 0.741-0.979 p=0.024) and higher glucose (exp(B)=1.360 CI95%: 1.013-1.824 p=0.041) remained as independent predictors of the higher mortality. ConclusionThe results of the study imply strong association between the metabolic alterations and ICU outcome. Our findings suggest that lower systemic amino acid concentration, lower energy expenditure and higher systemic glucose concentration are predictive of 30 days ICU mortality.

Relationship between obesity, body composition, and pulmonary function among Korean adults aged 40 years and older

Pulmonary function is influenced by factors such as age, sex, height, and weight. This study investigated the relationship between obesity, body composition, and pulmonary function measures (forced expiratory volume in one second [FEV1], forced vital capacity [FVC], and the FEV1-to-FVC ratio) of Korean adults aged 40 years and older. Using the fifth Korea national health and nutrition examination survey in 2010 and 2011, multiple regression analyses were performed to identify factors associated with pulmonary function, stratified by sex. Independent variables were waist circumference (WC) and an additional measure of obesity/muscularity (weight in model 1, body mass index [BMI] in model 2, and fat-free mass index [FFMI] in model 3). Among 3918 adults, the mean FFMI was 17.7 and 15.0 kg/m2 for men and women, respectively. Weight and BMI were positively associated with only FEV1 (B = 0.003 and B = 0.006, respectively, p < 0.01) and the FEV1-to-FVC ratio (B = 0.001, p < 0.01) in women. FFMI was positively associated with FEV1 and FVC in both sexes (B = 0.019, p < 0.05 for FEV1 and B = 0.020, p < 0.01 for FVC in men; B = 0.025, p < 0.0001 for FEV1 and B = 0.022, p < 0.0001 for FVC in women). WC was inversely associated with FEV1 and FVC in men and FEV1 in women, respectively. Weight and BMI behaved as indicators of body size based on their positive associations with pulmonary function. In conclusion, FFMI can be an important and consistent predictor of pulmonary function in both men and women.

Contrasting presentations of children with ADHD and subthreshold ADHD.

We aimed to explore the differences and relationships in body composition, social function, and comorbidities between children with attention-deficit/hyperactivity disorder (ADHD) and subthreshold ADHD. A case-control study was conducted to analyze the differences between children with ADHD and subthreshold ADHD. Logistic regression models were used to analyze the factors influencing social functional impairments and comorbidities. Children with ADHD and subthreshold ADHD had a higher fat mass index than healthy children (p < 0.05). The scores of all six social functional domains were higher in the subthreshold ADHD and ADHD groups than in the control group (p < 0.05). The prevalence of comorbidity was higher in children with subthreshold ADHD and ADHD compared to the control group (p < 0.05). Inattention and comorbid anxiety/depression increased the risk of functional impairments in children with ADHD (full syndrome/subthreshold), whereas a higher fat-free mass index reduced the risk. The severity of hyperactivity was associated with a higher risk of comorbidity in children with ADHD (full syndrome/subthreshold). Children with subthreshold ADHD and ADHD had more fat mass and higher rates of social functional impairments and comorbidities than healthy children. There were clinical correlations between body composition, social functional impairments, and comorbidities in ADHD. 1. Children with subthreshold ADHD and ADHD had higher fat mass levels than normal children. 2. The social function impairments and comorbidities of children with subthreshold ADHD were similar to those with ADHD. 3. Inattentiveness and anxiety/depression increased the risk of functional impairments in children with ADHD (full syndrome/subthreshold), while a higher fat-free mass index and skeletal muscle-to-body fat ratio reduced the risk.

Neonatal nutrition and early childhood body composition in infants born extremely preterm

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. 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. 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. 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.

Changes in Fat Mass Index and Fat-Free Mass Index Vary Significantly by Age and Sex of the Patient, and by Type of Bariatric Surgery.

The loss of fat-free mass after rapid weight loss following bariatric surgery shows BMI is inadequate for reporting weight loss, emphasizing the need for a more accurate body composition metric. This study assessed changes in fat mass index (FMI), fat-free mass index (FFMI), and dietary intake over 6months after one-anastomosis gastric bypass (OAGB), Roux-en-Y gastric bypass (RYGB), and sleeve gastrectomy (SG) across age and sex groups. This prospective observational study included 151 bariatric surgery candidates. Data on demographics, anthropometric, body composition, and food intake data were collected before and 6months after surgery. SPSS version 22 was used for analysis, employing ANOVA and t-tests to assess group differences. Younger patients (≤ 35years) had higher percent total and excess weight loss (%TWL and %EWL) across all bariatric surgeries, and those undergoing SG experienced more favorable changes in fat-free mass (FFM) and visceral fat compared to other procedures (P = 0.002). Males had higher percent change in fat mass index (%∆ FMI) and visceral fat than females with OAGB and RYGB (P < 0.05). Women undergoing SG and RYGB had a more significant decrease in energy intake compared to OAGB (P < 0.001), and the ≤ 35 and 35-44 age groups demonstrated lower reductions in energy intake following OAGB. Age, sex, and surgery type significantly affect bariatric surgery outcomes. Younger patients achieved greater weight-related improvements, while men undergoing RYGB experienced more substantial fat mass changes than women.