Relações entre os diferentes componentes da composição corporal com a massa óssea e o desenvolvimento de uma equação simples para predição de massa magra em mulheres pósmenopausadas

• Ano de defesa: 2019
• Autor(a) principal: Marin, Rosangela Villa [UNIFESP]
• Tipo de documento: Tese
• Tipo de acesso: Acesso aberto
• Idioma: por
• Instituição de defesa: Universidade Federal de São Paulo (UNIFESP)
• Palavras-chave em Português: Body Composition; Bone Mineral Density; Handgrip Strength; Timed Up And Go; Sarcopenia; Osteoporosis; Prediction Equation; Lean Mass; Bone Mass; Composição Corporal; Densidade Mineral Óssea; Força De Preensão Manual; Osteoporose; Equação De Predição; Massa Magra; Massa Óssea
• Link de acesso: https://sucupira.capes.gov.br/sucupira/public/consultas/coleta/trabalhoConclusao/viewTrabalhoConclusao.jsf?popup=true&id_trabalho=7286843; https://repositorio.unifesp.br/handle/11600/59243

Introduction: The aging process implies loss of functional abilities. Currently a major scientific concern is the investigation of sarcopenia due to its implications for the independence of the elderly. Sarcopenia causes a concomitant reduction of muscle strength, bone mass, lean mass and physical performance, which, when taken together, increase the risk of falls and fractures, becoming a major public health problem. Objectives: 1. To verify which components of body composition best correlates with BMD and; 2. To construct a model to estimate total lean mass from variables of easy access and applicability. Methodology: This is a cross-sectional study, using data of women belonging to three different studies, developed with standardization of several criteria in common and obtained by the same group of researchers. Sample: the population included 943 women, aged over 50 years, postmenopausal, non-institutionalized, who participated in three different study protocols developed by the same group of researchers. To evaluate bone mass, women were divided between treated and untreated for osteoporosis. The present study was approved by the Research Ethics Committee of UNIFESP under No. 32882/12. Methods: We performed the measurement of body composition (bone mass, lean mass, fat mass) obtained by bone densitometry (DXA), hand grip strength (TAKEI portable dynamometer), static balance with visual control, functional mobility and stationary gait. Statistical analysis: normality of the data was evaluated by the Kolmogorov Smirnov adhesion test. Data analysis was performed using Pearson's linear correlation and, later, by multiple linear regression analysis. Results were considered significant when p <0.05. Results: There were significant correlations between total body mass and all bone mass sites in women treated and not treated with active osteoporosis drugs. In untreated women the correlations were more expressive and more relevant for the distal femur, explaining bone mass in 30%. In the treated ones, however, this expressiveness was lost in the final results. Using the existing variables, we could construct a statistical model to estimate total lean mass (MMT), defined by the formula: MMT= -10.257 + (0.390 x total body mass) - (0.077 x arm circumference) + (17.733 x height) + (0.057 x right hand grip strength) - (0.019 x functional mobility) + (0.018 x age), with high correlation (r = 0.909) and a satisfactory explanation coefficient, with r2= 0.825; p = 0.001. Conclusions: The lean mass of untreated women with active osteoporosis medication was a better predictor of bone mass than fat mass, especially for the distal femur. This suggests that maintaining a healthy muscle mass may contribute to maintaining bone quality. Treatment with anti-osteoporotic drugs seems to mask these relationships. With simple and easy to obtain measures it was possible to create an equation where the total lean mass could be explained in 82.5%. This may facilitate the characterization of sarcopenia in populations without access to the DXA device, which may have a great impact on the clinical evaluation and the dissemination of this concept in deprived environments.