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.

BACKGROUND: 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 6 months after one-anastomosis gastric bypass (OAGB), Roux-en-Y gastric bypass (RYGB), and sleeve gastrectomy (SG) across age and sex groups.
METHODS: This prospective observational study included 151 bariatric surgery candidates. Data on demographics, anthropometric, body composition, and food intake data were collected before and 6 months after surgery. SPSS version 22 was used for analysis, employing ANOVA and t-tests to assess group differences.
RESULTS: Younger patients (≤ 35 years) 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.
CONCLUSIONS: 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.

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).

NAFLD has become the leading cause of chronic liver disease in children, as a direct consequence of the high prevalence of childhood obesity. This study aimed to characterize body composition trajectories from childhood to adolescence and their association with the risk of developing nonalcoholic fatty liver disease (NAFLD) during adolescence. The participants were part of the \'Chilean Growth and Obesity Cohort Study\', comprising 784 children who were followed prospectively from age 3 years. Annual assessments of nutritional status and body composition were conducted, with ultrasound screening for NAFLD during adolescence revealing a 9.8% prevalence. Higher waist circumference measures were associated with NAFLD from age 3 years (p = 0.03), all skin folds from age 4 years (p < 0.01), and DXA body fat measurements from age 12 years (p = 0.01). The fat-free mass index was higher in females (p = 0.006) but not in males (p = 0.211). The second and third tertiles of the fat mass index (FMI) had odds ratios for NAFLD during adolescence of 2.19 (1.48-3.25, 95% CI) and 6.94 (4.79-10.04, 95% CI), respectively. Elevated waist circumference, skin folds, and total body fat were identified as risk factors for future NAFLD development. A higher FMI during childhood was associated with an increased risk of NAFLD during adolescence.

Chronic obstructive pulmonary disease (COPD) combined with malnutrition results in decreased exercise capacity and a worse quality of life. We aimed to develop an observational case-control study to explore the effective and convenient method to identify potential individuals is lacking. This study included data from 251 patients with COPD and 85 participants in the control group. Parameters and body composition were compared between groups, and among patients with varied severity. The LASSO approach was employed to select the features for fitting a logistic model to predict the risk of malnutrition in patients with stable COPD. Patients with COPD exhibited significantly lower 6-min walk distance (6MWD), handgrip strength, fat-free mass index (FFMI), skeletal muscle mass (SMM) and protein. The significant predictors identified following LASSO selection included 6MWD, waist-to-hip ratio (WHR), GOLD grades, the COPD Assessment Test (CAT) score, and the prevalence of acute exacerbations. The risk score model yielded good accuracy (C-index, 0.866 [95% CI 0.824-0.909]) and calibration (Brier score = 0.150). After internal validation, the adjusted C-index and Brier score were 0.849, and 0.165, respectively. This model may provide primary physicians with a simple scoring system to identify malnourished patients with COPD and develop appropriate rehabilitation interventions.

BACKGROUND: Low muscle mass is associated with adverse health outcomes such as functional decline and all-cause mortality. This study investigated the relationship between the risk of low muscle mass and the training period and/or frequency of resistance training (RT).
METHODS: We included 126,339 participants (81,263 women) from nationwide cohorts in Korea. Low muscle mass was defined based on the fat-free mass index. To investigate the presence of an inverse dose-response relationship between RT levels and the risk of low muscle mass, the training period (months) and frequency (per week) of RT were used. Multiple logistic regression models were used to assess the risk of low muscle mass according to the RT levels.
RESULTS: Prevalence rates for low muscle mass in our study population were 21.27% and 6.92% in men and women, respectively. When compared with not performing RT, performing RT for 3-4 days/week and ≥5 days/week decreased the risk of low muscle mass by 22% and 27%, respectively, and performing RT for 12-23 months and ≥24 months decreased the risk by 19% and 41%, respectively. When simultaneously considering both training period and frequency, performing RT for either 3-4 days/week or ≥5 days/week was significantly related to risk reduction, provided that the training period was at least 1 year. Importantly, performing RT for more than 2 years resulted in an additional risk reduction. However, there was no additional effect of performing RT for ≥5 days/week compared to 3-4 days/week, regardless of whether the RT duration was 1-2 years or more than 2 years.
CONCLUSIONS: Since performing RT for 5 days/week or more did not yield any additional effects on the risk of low muscle mass, performing RT for 3-4 days/week was sufficient to prevent low muscle mass. The effectiveness of this preventive measure can be further enhanced by engaging in long-term RT, specifically for more than 2 years.

The objectives of this study were to develop age- and sex-specific reference percentiles for fat mass index (FMI) and fat-free mass index (FFMI) in adolescents aged 14 to 19 years and to determine differences in overweight/obesity classification by FMI and body mass index (BMI). The EVA4YOU study is a single-center cross-sectional study conducted in western Austria. Cardiovascular risks including anthropometric measurements and bioelectrical impedance analysis were assessed in adolescents (mean age 17 years). FMI and FFMI were calculated as the ratio of fat mass (FM) and fat-free mass (FFM) to the square of height and compared to study population-specific BMI percentiles. One thousand four hundred twenty-two adolescents were included in the analysis. Girls had a significantly higher mean FM and FMI and a significantly lower mean FFM, FFMI (p < 0.001, each), and mean BMI (p = 0.020) than boys. Body composition classification by FMI and BMI percentiles shows a concordance for the < 75th and > 97th percentile, but a significant difference in percentile rank classifications between these two cut-off values (all p < 0.05). Based on FMI, 15.5% (221/1422) of the whole population and 29.4% (92/313) of those between the 75th and 97th percentiles are classified one category higher or lower than those assigned by BMI.
CONCLUSIONS:  Classification of normal or pathologic body composition based on BMI and FMI shows good accordance in the clearly normal or pathologic range. In an intermediate range, FMI reclassifies categories based on BMI in more than a quarter of adolescents. Cut-off values to differentiate normal from pathologic FMI values on a biological basis are needed.
BACKGROUND: The study is registered at www.
RESULTS: gov  (Identifier: NCT04598685; Date of registration: October 22, 2020).
BACKGROUND: • Chronic non-communicable diseases (NCDs) are the leading cause of morbidity and mortality globally, with major risk factors including unhealthy diets, harmful behaviors, and obesity. Obesity in children and adolescents is a key risk factor for later NCDs, which is commonly measured by Body Mass Index (BMI). • BMI can be misleading as it doesn\'t distinguish between fat mass (FM) and fat-free mass (FFM), leading to potential misclassification of obesity in children. Previous studies have already suggested the use of the Fat Mass Index (FMI) and Fat-Free Mass Index (FFMI) as a more accurate measures of body composition.
BACKGROUND: • This study adds the first age- and sex-specific reference values for FMI and FFMI in Austrian adolescents using bioelectrical impedance analysis (BIA) as a safe and secure measurement method of a large representative cohort. • We found percentile misclassification between BMI and FMI when categorizing for obesity, especially in intermediate categories of body composition. Furthermore, when comparing the new reference values for FMI and FFMI to existing ones from the US, UK, and Germany we could show a good alignment within the European cohorts and major differences with American values, indicating and confirming the difference of FMI and FFMI for different populations of different ethnical background, living on different continents.

To investigate the influence of radiation dose to the swallowing muscles on the nutritional status in patients with head and neck cancer undergoing primary or adjuvant (chemo)radiotherapy (C)RT.
Between 2018 and 2020, 61 patients were prospectively randomized into the so-called HEADNUT trial (head and neck cancer patients undergoing nutritional intervention). Follow-up was continued until 2022. Contouring of the swallowing apparatus included the superior (scm), middle (mcm), and inferior constrictor muscle (icm), the cricopharyngeal muscle (cphm), and the esophageal inlet. Nutritional status was assessed by bioelectrical impedance analysis (BIA) at the beginning and the end of radiotherapy. The posttherapeutic nutritional status was evaluated by the BIA-derived fat-free mass index (FFMI; kg/m2). Malnutrition was assumed at FFMI values of < 15 (women) and < 17 (men) kg/m2. To find differences between dosimetric parameters in well- and malnourished patients, Mann-Whitney U test was used. To model the association between malnutrition and its potentially influencing variables, several logistic regression models were built.
The following parameters differed between well- and malnourished patients at the end of therapy: icm Dmean, V40Gy (%), V50Gy (%), and V60Gy (%), and sphm V40Gy (%). After entering these parameters into a multivariable logistic regression model (dosimetric model), icm Dmean (b = -0.12; Exp(b) = 0.88; 95% CI: 0.78-1.0; p = 0.06) and icm V40Gy (%; b = 0.06; Exp(b) = 1.07; 95% CI: 1-1.13; p = 0.04) proved to be independent dosimetric predictors of malnutrition. We only determined the cut-off value for predicting malnutrition for icm V40Gy (%) since it was the only parameter which met p < 0.05. The optimal cut-off value for the predictor V40Gy (%) based on the Youden Index was 85.6%. Another logistic regression model (dosimetric-clinical model) consisted of icm V40 (%) and the clinical parameters tumor localization, malnutrition before RT, gender, and combined chemotherapy. It was confirmed that both icm V40% (b = -1.9; Exp(b) = -2.7; 95% CI: 0.01-0.8; p = 0.03) and malnutrition at baseline (b = -1.9; Exp(b) = 4.4; 95% CI: 8.4-816.6; p = 0.0002) were independent predictors of subsequent malnutrition the end of RT.
Establishment of a normal nutritional status before the start of RT and adherence to dose constraints for the swallowing apparatus may prevent malnutrition in head and neck cancer patients at the end of therapy. Specifically, we suggest an icm V40Gy (%) of more than 86% to be predictive for nutritional complications.

This study was designed to investigate the differences in skeletal-muscle atrophy between patients with stable chronic obstructive pulmonary disease (COPD) and healthy controls; associated factors were also considered. The study comprised selected residents of communities near the First Affiliated Hospital of Soochow University in Suzhou City, East China.
Included in this study were 123 COPD patients and 60 controls. All patients completed spirometry as well as examinations to determine their functional exercise capacity, body composition, and handgrip strength (HGS).
COPD patients had less fat-free mass (FFM), a lower FFM index (FFMI), and a lower 6-min walking distance (6MWD) compared with controls (P = 0.007, P = 0.020, and P < 0.001, respectively) (FFMI: 17.59 ± 1.83 vs 18.34 ± 1.64). The HGS of these patients was also lower compared with that of controls (32.88 ± 7.84 vs 35.48 ± 7.42), and HGS tended toward statistical significance (P = 0.064, respectively). In multivariate analysis, age (β = -0.107, P < 0.001), gender (β = 0.212, P < 0.001), body mass index (BMI) (β = 0.462, P < 0.001), FEV1% (β = 0.108, P = 0.009), and calf circumference (CC) (β = 0.457, P < 0.001) were significantly associated with FFMI.
Impaired skeletal muscle mass was more common in COPD patients than in controls. Multiple regression analysis showed that CC may be used to detect the degree of impairment, particularly by health-care providers working outside of the hospital.

Differences in the clinical impacts of fat mass index (FMI) and fat-free mass index (FFMI) remain unclear in patients with chronic obstructive pulmonary disease (COPD). We hypothesized that FMI and FFMI have different impacts on 1) emphysema and 2) pulmonary function and health-related quality of life of COPD patients.
Patients with COPD (n = 228), enrolled in a multicenter prospective 3-year cohort were classified into four groups based on baseline median FMI and FFMI values. Emphysema assessed as the ratio of low attenuation area to total lung volume (LAA%) on computed tomography, pulmonary function, and health-related quality of life assessed using the St. George\'s Respiratory Questionnaire (SGRQ) were compared.
The four groups had statistically significant differences in LAA%, pulmonary function, and SGRQ scores. The Low FMI Low FFMI group exhibited the highest LAA%, lowest pulmonary function, and worst SGRQ scores among the four groups. In addition, these differences were consistent over 3 years. Multivariate analysis showed that low FMI was associated with high LAA%, low inspiratory capacity/total lung capacity (IC/TLC), and carbon monoxide transfer coefficient (KCO). In contrast, low FFMI was associated with these factors as well as worse SGRQ scores.
FMI and FFMI have different effects on the clinical manifestations of COPD. Both low fat and muscle mass contributed to severe emphysema, whereas only low muscle mass contributed to worse health-related quality of life in patients with COPD.