Navegando por Assunto "Body composition"

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Acesso aberto (Open Access)
Associação de obesidade sarcopênica, indicadores de composição corporal, de variabilidade da frequência cardíaca e de esforço no teste do degrau de seis minutos com a severidade da Síndrome da Apneia Obstrutiva do Sono: Um estudo transversal
(Universidade Federal do Pará, 2025-12-19) SOUZA, Leornado Brynne Ramos de; CRISP, Alex Harley; http://lattes.cnpq.br/1187580727139009; HTTPS://ORCID.ORG/0000-0003-4683-9576; NEVES, Laura Maria Tomazi; http://lattes.cnpq.br/4235603520707156; https://orcid.org/0000-0002-3115-2571
Introduction: Obstructive sleep apnea syndrome (OSAS) is the most common sleep- related respiratory disorder in the world, with different levels of severity. The literature indicates that increased body fat can increase energy expenditure, alter heart rate variability during sleep and wakefulness and affects the severity of the syndrome. Thus, there is a greater risk of muscle catabolism, negatively influencing cellular health, measured by the phase angle in bioelectrical impedance. However, few studies have expanded the assessment of body composition in relation to sarcopenic obesity in this population. In addition, the results of current research are also conflicting when analyzing the impacts of OSAS severity on metabolic and physical performance during stress tests. Objective: To investigate the association of indicators of body composition, heart rate variability, and stress in the six-minute step test with the severity of OSAS. Methods: Cross-sectional, quantitative study that took place between December 2023 and August 2024, with a single sample of 37 people diagnosed with OSAS, age 53,7 ± 13,8 years, minimum age 28 years and maximum age 78 years, confirmed by type 1 polysomnography. Data collection was performed in two phases: a) Rest, using bioelectrical impedance (Biodynamics BIA 450, Biodynamics Corporation, Washington, USA) to collect body composition data, indirect calorimetry (Quark CPET, Cosmed, Italy) to collect resting metabolic rate and time and frequency domain variables of heart rate variability using a heart rate monitor (SmartLab, HMMGroup, Germany); b) Exercise, using the 6-minute step test with a gas analyzer (Quark CPET, Cosmed, Italy) breath by breath to assess physical and metabolic effort. To determine data normality, the Shapiro-Wilk test was used, with normal data represented by mean and standard deviation and non-normal data represented by median and interquartile range. For multivariate data analysis, principal component analysis (PCA) was used, employing the varimax rotation algorithm to create the components. The reduced value of each component was used to perform a simple linear regression analysis. Results: Thirty-seven individuals with OSAS (54.05% men), BMI 31.1 ± 5.31 kg/m2 and AHI 31.3 (11.3-61.6) were evaluated. The PCA analysis created 6 principal components (PC), which are: 1st PC: body composition; 2nd PC: cellular health; 3rd PC: physical effort; 4th PC: ventilatory reasons; 5th PC: sympathovagal stimulation; 6th PC: sympathovagal stimulation (very low frequency). The body composition indicators component (BMI, neck circumference, resting metabolic rate, body resistance, and capacitance) was associated with higher AHI (F[3,32] = 3.05; p = 0.01), with an adjusted r2 value of 0.22. Conclusion: Body composition is associated with the severity of OSAS, while the components of cellular health, physical effort, ventilatory ratios, sympathovagal stimulation, and very low frequency sympathovagal stimulation were not associated with the severity of the syndrome.
Acesso aberto (Open Access)
Predição da massa livre de gordura e do índice de massa muscular por impedancia bioelétrica em homens com tetraplegia fisicamente ativos
(Universidade Federal do Pará, 2022-05-25) VIEIRA, Andreia Bauermann; KOURY, Josely Correa; http://lattes.cnpq.br/9039270525512042; https://orcid.org/0000-0002-3189-9261; SILVA, Anselmo de Athayde Costa e; http://lattes.cnpq.br/4794918582092514; https://orcid.org/0000-0001-5265-619X
Individuals with cervical spinal cord injury (c-SCI) experience progressive loss of fat-free mass (FFM) due to decreased physical activity and neurological impairments because the function of spinal neuronal circuits below the level of injury is impaired. Therefore, there is a reduction in muscle strength and physical performance, characterizing sarcopenia, similar to what occurs in the elderly. The bioelectrical impedance (BIA) method is valid and accessible for predicting FFM in different population. The ground of the BIA method is based on the principle of constant hydration. However, individuals with c-SCI show important variations in hydration status, a fact that makes it difficult to use generalized predictive equations for FFM by BIA. Considering that the prediction of FFM in individuals with c-SCI is important to monitor changes in body composition and to support studies on sarcopenia, the present dissertation aims to: 1) test the agreement between the FFM values obtained by three different predictive equations by BIA and by dual-energy X-ray absorptiometry (DXA), 2) test the applicability of bioelectrical impedance vector analysis (BIVA) for this group; and 3) compare the use of the muscle mass index (SMI) from the FFM obtained by BIA and DXA for the diagnosis of sarcopenia in people with tetraplegia, considering different levels of physical activity (sedentary, active >150 minutes per week, and very active > 210 minutes per week). Able bodied individuals (n=23) and with c-SCI physically active (n=13) or inactive (n=10) participated in the study. Only the equation by Buchholz et al. showed agreement (coefficient of agreement=0.85) with DXA. Sarcopenia is a common disease after c-SCI and can be diagnosed using the SMI, which was tested in this group using the suggested equations for BIA and DXA. The use of the SMI-BIA to classify sarcopenia in sedentary c-SCI individuals resulted in substantial diagnostic agreement (Kappa=0.727) according to the Kappa coefficient. Buchholz et al. equation presented the best agreement, but this was not enough for this equation to be recommended for use in people with c-SCI and a specific equation for this population should be created. However, the use of cut-off points to diagnose sarcopenia from the SMI-BIA seems promising in sedentary people with c-SCI, necessitating further studies in people with c SCI that are physically active.