Thaís R Silva1, Poli M Spritzer. 1. 1Gynecological Endocrinology Unit, Division of Endocrinology, Hospital de Clínicas de Porto Alegre (HCPA), Porto Alegre, RS, Brazil 2Laboratory of Molecular Endocrinology, Department of Physiology, Universidade Federal do Rio Grande do Sul (UFRGS), Porto Alegre, RS, Brazil.
Abstract
OBJECTIVE: We investigated the association between skeletal muscle mass and dietary protein intake, habitual physical activity, body composition, and metabolic variables. METHODS: One hundred three healthy postmenopausal women from southern Brazil (age 55.2 ± 4.9 y, body mass index 27.2 ± 4.6 kg/m) were enrolled. Bone mineral density, %body fat, %trunk fat mass, and appendicular lean mass were assessed by dual-energy x-ray absorptiometry, resting metabolic rate by indirect calorimetry, and habitual physical activity by pedometer. Skeletal muscle mass index (SMI) was expressed as appendicular lean mass standardized to body mass index. The cutoff for low lean mass was <0.512. Protein intake was measured by a validated food frequency questionnaire and categorized into tertiles: ≤0.93 g/kg body weight (BW), 0.94 to 1.29 g/kg BW, and ≥1.3 g protein/kg BW. RESULTS: The prevalence of low lean mass (SMI <0.512) was 7%. Waist circumference, %body fat, trunk fat mass, and diastolic blood pressure were higher, whereas SMI and mean daily steps were lower in women with protein intake ≤0.93 g/kg BW. SMI was positively correlated with physical activity (r = 0.205, P = 0.038) and protein intake (r = 0.334, P = 0.001), and negatively correlated with waist circumference (r = -0.505, P < 0.001) and %body fat (r = 0.808, P < 0.001). Linear regression analysis adjusted for age, time since menopause, previous smoking behavior, and energy intake showed an independent, positive contribution of protein intake (mean difference 0.007, 95% CI, 0.001-0.014, P = 0.044) and an independent, negative contribution of %body fat (mean difference -0.010, 95%CI, -0.011 to -0.008, P < 0.001) to SMI. CONCLUSIONS: In our healthy postmenopausal women, SMI was positively associated with protein intake and negatively associated with %body fat.
OBJECTIVE: We investigated the association between skeletal muscle mass and dietary protein intake, habitual physical activity, body composition, and metabolic variables. METHODS: One hundred three healthy postmenopausal women from southern Brazil (age 55.2 ± 4.9 y, body mass index 27.2 ± 4.6 kg/m) were enrolled. Bone mineral density, %body fat, %trunk fat mass, and appendicular lean mass were assessed by dual-energy x-ray absorptiometry, resting metabolic rate by indirect calorimetry, and habitual physical activity by pedometer. Skeletal muscle mass index (SMI) was expressed as appendicular lean mass standardized to body mass index. The cutoff for low lean mass was <0.512. Protein intake was measured by a validated food frequency questionnaire and categorized into tertiles: ≤0.93 g/kg body weight (BW), 0.94 to 1.29 g/kg BW, and ≥1.3 g protein/kg BW. RESULTS: The prevalence of low lean mass (SMI <0.512) was 7%. Waist circumference, %body fat, trunk fat mass, and diastolic blood pressure were higher, whereas SMI and mean daily steps were lower in women with protein intake ≤0.93 g/kg BW. SMI was positively correlated with physical activity (r = 0.205, P = 0.038) and protein intake (r = 0.334, P = 0.001), and negatively correlated with waist circumference (r = -0.505, P < 0.001) and %body fat (r = 0.808, P < 0.001). Linear regression analysis adjusted for age, time since menopause, previous smoking behavior, and energy intake showed an independent, positive contribution of protein intake (mean difference 0.007, 95% CI, 0.001-0.014, P = 0.044) and an independent, negative contribution of %body fat (mean difference -0.010, 95%CI, -0.011 to -0.008, P < 0.001) to SMI. CONCLUSIONS: In our healthy postmenopausal women, SMI was positively associated with protein intake and negatively associated with %body fat.
Authors: Praval Khanal; Lingxiao He; Georgina K Stebbings; Gladys L Onambele-Pearson; Hans Degens; Alun G Williams; Martine Thomis; Christopher I Morse Journal: Aging Clin Exp Res Date: 2021-03-13 Impact factor: 3.636
Authors: Poli Mara Spritzer; Lucas B Marchesan; Betânia R Santos; Felipe V Cureau; Karen Oppermann; Rosana Maria Dos Reis; Rui A Ferriani; Rita Weiss; Ricardo Meirelles; Ana Lucia Candido; Fernando M Reis Journal: BMJ Open Date: 2019-10-22 Impact factor: 2.692