Cutoff points of adiposity anthropometric indices for low muscle mass screening in middle-aged and older healthy women

BMC Musculoskeletal Disorders

Saionara Maria Aires da Câmara¹  Maria Socorro Medeiros de Morais²  Mayle Andrade Moreira³  Álvaro Campos Cavalcanti Maciel⁴  Rafaella Silva dos Santos Aguiar Gonçalves⁴  Mariana Carmem Apolinário Vieira⁴  Rafaela Andrade do Nascimento⁴ 

[1] Faculty of Health Sciences of Trairi, Santa Cruz, Brazil, Vila Trairi St, CEP: 59200-000, Santa Cruz, RN, Brazil;Health Sciences Center of Federal, University of Rio Grande Do Norte, General Gustavo Cordeiro de Farias St, Petrópolis, CEP 59012-570, Natal, RN, Brazil;Physiotherapy Department of Federal, University of Ceará, 949 Alexandre Baraúna St, Rodolfo Teófilo, CEP: 60430-110, Fortaleza, Brazil;Physiotherapy, Department of Federal, University of Rio Grande Do Norte, 3000 Senador Salgado Filho Avenue, S/N, Lagoa Nova, CEP: 59072-970, Natal, RN, Brazil;

关键词: Aging;    Body composition;    Adiposity;    Muscle mass;    Women;   

DOI  :  10.1186/s12891-021-04532-x

来源: Springer

【 摘 要 】

BackgroundThe reduction of female sex hormones causes changes in the contractile properties of muscles as well as infiltration of fat in the muscle tissue. This results in a consequent decline in muscle strength. These changes are related to higher levels of functional impairment and physical disability. In this sense, several anthropometric indices have been used to quantify body and visceral fat. Thus, the objective of this paper is to propose cutoff points for adiposity anthropometric indices in order to identify low muscle mass, as well as to analyze the relationship between these indices and low muscle mass in middle-aged and older women.MethodsCross-sectional analytical study carried out in the Northeast of Brazil. The sample was formed by 593 women between 40—80 years old. Data collection included anthropometric assessment (BMI: Body Mass Index – WC: Waist Circumference – WHR: Waist-to-hip Ratio – WHtR: Waist-to-height Ratio – CI: Conicity Index – BAI: Body Adiposity Index – VAI: Visceral Adiposity Index – LAP: Lipid Accumulation Product), bioimpedance test and biochemical dosage. Moreover, sociodemographic data and practice of physical activity were collected. Descriptive statistics, Student's t-test, ROC curves, chi-squared and logistic regression were performed.ResultsThe participants had a mean age of 53.11 (8.89) years, BMI of 28.49 (5.17) kg/m2 and WC of 95.35 (10.39). The prevalence of low muscle mass was 19.4%. Based on sensitivity and specificity of adiposity anthropometric indices, cutoff points were developed to identify the presence of low muscle mass (p < 0.05), except for VAI. After logistic regression, WC (OR = 6.2; CI 95%: 1.4—28.1), WHR (OR = 1.8; CI: 1.0—3.4), WHtR (OR = 5.0; CI 95%: 1.0—23.7) and BAI (OR = 14.5; CI 95%: 6.6—31.7) were associated with low muscle mass.ConclusionsAll anthropometric indices, except VAI, showed adequate accuracy in identifying low muscle mass in women, especially those that took into account WC. This suggests that they can become accessible and also be cost-effective strategies for assessing and managing health outcomes related to muscle mass analysis.

【 授权许可】

CC BY