Associations between anthropometry, body composition, and body image in athletes: a systematic review.

Introduction: Poor body image is a potent risk factor for disordered eating and eating disorders. Athletes are a population at increased risk for eating disorders despite reports of lower body image concerns compared to non-athletes. Body size and composition may influence an athlete's susceptibility to poor body image. Methods: Five electronic databases (PubMed, Cochrane Library, PsycINFO, Web of Science, SPORTDiscus) were searched to systematically evaluate the literature regarding the association between body measures (i.e., anthropometric and body composition indicators) and body image in athletes. The systematic review was completed following PRISMA guidelines and 27 cross-sectional studies were identified for inclusion and evaluated using the Joanna Briggs Institute Critical Appraisal Checklist for Analytical Cross-Sectional Studies. Results: Studies differed in methodological assessment of anthropometry or body composition (i.e., self-reported versus researcher-measured), methods for evaluating aspects of body image, geographic location, and sport type. Higher body mass index (BMI) or percent body fat (%BF) was significantly associated with greater body dissatisfaction in 16 of 22 studies (72.7%). Positive associations between body measures and aspects of negative body image were most consistently observed among studies that assessed BMI based on self-reported heights and weights, while significant associations between body composition measures (e.g., %BF, fat mass, fat-free mass) were less common. Four of seven studies assessing relationships between BMI and an aspect of positive body image reported significant inverse relationships, while three revealed insignificant associations. Discussion: Overall, higher BMI and body fat were associated with body dissatisfaction among athletes. Future studies are needed to confirm these findings within focused populations and utilizing body composition methods (e.g., bioelectrical impedance techniques). Systematic review registration: https://www.crd.york.ac.uk/prospero/, CRD42023446518.

Malnutrition and pectoralis muscle index in medical intensive care unit patients: A matched cohort study.

BACKGROUND: Muscle assessment is an important component of nutrition assessment. The Global Leadership Initiative on Malnutrition (GLIM) consortium recently underscored the need for more objective muscle assessment methods in clinical settings. Various assessment techniques are available; however, many have limitations in clinical populations. Computed tomography (CT) scans, obtained for diagnostic reasons, could serve multiple purposes, including muscle measurement for nutrition assessment. Although CT scans of the chest are commonly performed clinically, there is little research surrounding the utility of pectoralis muscle measurements in nutrition assessment. The primary aim was to determine whether CT-derived measures of pectoralis major cross-sectional area (PMA) and quality (defined as mean pectoralis major Hounsfield units [PMHU]) could be used to identify malnutrition in patients who are mechanically ventilated in an intensive care unit (ICU). A secondary aim was to evaluate the relationship between these measures and clinical outcomes in this population. METHODS: A retrospective analysis was conducted on 33 pairs of age- and sex-matched adult patients who are being mechanically ventilated in the ICU. Patients were grouped by nutrition status. Analyses were performed to determine differences in PMA and mean PMHU between groups. Associations between muscle and clinical outcomes were also investigated. RESULTS: Compared with nonmalnourished controls, malnourished patients had a significantly lower PMA (P = 0.001) and pectoralis major (PM) index (PMA/height in m2; P = 0.001). No associations were drawn between PM measures and clinical outcomes. CONCLUSION: These findings regarding CT PM measures lay the groundwork for actualizing the GLIM call to action to validate quantitative, objective muscle assessment methods in clinical settings.

Avaliação de modelos avançados de espectroscopia de bioimpedância para medir a composição do corpo em adultos saudáveis (NHANES 1999-2004) e aqueles que sofrem perda de peso em massa após a cirurgia de bypass gástrico Roux-en-Y / Evaluation of Advanced Bioimpedance Spectroscopy Models for Measuring Body Composition in Healthy Adults (NHANES 19992004) and Those Undergoing Massive Weight Loss Following Roux-en-Y Gastric Bypass Surgery

Introduction: Bioimpedance spectroscopy (BIS) devices utilize biophysical modeling to generate body composition data. The addition of body mass index (BMI) to modified Xitron-Hanai-based mixture equations improved BIS estimates of intracellular water (ICW), particularly at the extremes of BMI. A 3-compartment model for distinguishing excess fluid (ExF) from normally hydrated lean (NHLT) and adipose tissue may further improve BIS estimates. Objective:We aimed to validate a BIS approach based on the Chamney model for determining fat mass (FM) in healthy individuals (NHANES) and for measuring FM changes in individuals undergoing massive weight loss. Methods: Using adult NHANES 1999-2004 (2821 female, 3063 male) and longitudinal pre-topost-RYGB (15F) data, we compared dual-energy-X-ray absorptiometry (DXA) and BIS for FM. We applied BIS adiposity-corrected values to Chamney equations for normally hydrated lean and adipose tissue (NHLT, NHAT) and FM. Method agreement was evaluated by correlations, paired t-tests, root mean square error (RMSE), BlandAltman (B-A) analysis, and concordance correlation coefficients (CCC). Results: Method agreement between BIS and DXAFM was good in healthy adults (r=0.96, CCC=0.93, p<.0001), and pre-to-post-RYGB (r=0.93-0.98, CCC=0.81-0.86, p<.001). Although cross-sectional FM measures differed, FM change measures post-RYGB did not (35.6±8.9 vs. 35.2±9.2 kg, BIS vs. DXA) and agreed well (r=0.84, p<.0001). The 15 subjects with follow-up measurements at 1 year lost 11.5±9.8 kg FFM by DXA, but only 1.3±2.5 kg of NHLT by BIS, suggesting that the FFM loss may have been mostly adipose tissue water. Conclusions: Incorporation of the Chamney model into BIS algorithms is a major conceptual advancement for assessing and monitoring body composition. Its ability to differentiate ICW and extracellular water (ECW) in NHLT and NHAT, as well as excess ECW is promising, and would facilitate lean tissue monitoring in obesity and acute/chronic disease.(AU)

Introdução: Os dispositivos de espectroscopia de bioimpedância (DEB) utilizam modelagem biofísica para gerar dados de composição corporal. A adição do índice de massa corporal (IMC) às equações de mistura modificadas com Xitron-Hanai modificadas melhorou as estimativas de DEB de água intracelular (AI), particularmente nos casos extremos do IMC. Um modelo de 3 compartimentos para distinguir o excesso de fluido (ExF) de magro normalmente hidratado (NHLT) e tecido adiposo pode ainda melhorar as estimativas do DEB. Objetivo: Pretendemos validar uma abordagem do DEB com base no modelo de Chamney para determinar a massa de gordura (MG) em indivíduos saudáveis (NHANES) e para medir mudanças de MG em indivíduos submetidos à perda de peso maciça. Método: Usando o NHANES adulto 1999-2004 (2821 mulheres, 3063 homens) e dados longitudinais pré-pós-RYGB (15 F), comparamos a absorção de raios-X de dupla energia (DXA) e DEB para MG. Aplicamos os valores corrigidos de adiposidade do BIS às equações de Chamney para tecidos magros e adiposos normalmente hidratados (NHLT, NHAT) e FM. O acordo de método foi avaliado por correlações, testes t pareados, erro quadrado médio (EQM), análise Bland-Altman (B-A) e coeficientes de correlação de concordância (CCC). Resultados: O acordo de método entre DEB e DXA MG foi bom em adultos saudáveis (r=0,96, CCC=0,93, p<.0001) e pré-pós-RYGB (r=0,93-0,98, CCC=0,81-0,86, p<0,001). Embora as medidas de MG transversais diferissem, as medidas de mudança de MG pós-RYGB não (35,6±8,9 vs. 35,2±9,2 kg, DEBvs. DXA) e concordaram bem (r=0,84, p<.0001). Os 15 sujeitos com medidas de seguimento ao 1 ano perderam 11,5±9,8 kg FFM por DXA, mas apenas 1,3±2,5 kg de NHLT pelo DEB, sugerindo que a perda de FFM pode ter sido principalmente água do tecido adiposo. Conclusões: A incorporação do modelo de Chamney em algoritmos DEB é um grande avanço conceitual para avaliar e monitorar a composição corporal. A sua capacidade de diferenciar AI e água extracelular (AE) no NHLT e NHAT, bem como o excesso de AE é promissor e facilitará a monitorização do tecido magro na obesidade e doença aguda/crônica.(AU)