Título: Journal of Human Nutrition and DieteticsImportada do Authenticus Pesquisar Publicações da Revista

ISSN: 0952-3871

Editora: Wiley-Blackwell

ISI Web of Knowledge - 1 Citação

Scopus - 2 Citações

FOS: Ciências médicas e da saúde

CORDIS: Ciências da Saúde

ID Authenticus: P-00T-WM2

DOI: 10.1111/jhn.12879

Abstract (EN): Background Assessing body weight in older adults may be challenging. Hence, the present study aimed to develop and cross-validate updated and reproducible equations to estimate body weight in a large sample of older adults, namely among the older-old. Methods In total, 1456 individuals aged >= 65 years, from the Nutrition UP 65 study, were included in the present analysis. The participants were randomly assigned to one of two sub-samples: development (n = 991) and validation samples (n = 465). Prediction equations using height, mid-upper arm circumference (MUAC), waist circumference (WC), calf circumference (CC) and triceps skinfold thickness (TST) were generated for the development sample using multiple regression analysis and then validated using the validation sample. Results The model with five predictor variables generated the following equations: females 65-79 years: -114.682 + 0.522 x height (cm) + 0.620 x MUAC (cm) + 0.517 x WC (cm) + 0.893 x CC (cm) + 0.111 x TST (mm) (adjusted r(2 )= 0.883, standard error of the estimate (SEE) = 4.4); females >= 80 years: -110.806 + 0.494 x height (cm) + 0.637 x MUAC (cm) + 0.500 x WC (cm) + 0.986 x CC (cm) + 0.021 x TST (mm) (adjusted r(2 )= 0.890, SEE = 3.9); males 65-79 years: -114.875 + 0.558 x height (cm) + 0.073 x MUAC (cm) + 0.671 x WC (cm) + 0.717 x CC (cm) + 0.182 x TST(mm) (adjusted r(2 )= 0.820, SEE=5.0); and males >= 80 years: -128.789 + 0.546 x height (cm) + 0.202 x MUAC (cm) + 0.612 x WC (cm) + 1.236 x CC (cm) + 0.093 x TST (mm) (adjusted r(2 )= 0.906, SEE = 3.5). Conclusions Body weight can be estimated with good accuracy in older adults using these sex- and age-specific equations generated from regression models using three to five anthropometric predictor variables.

Idioma: Inglês

Tipo (Avaliação Docente): Científica

Nº de páginas: 8