Prediction equations for estimating body weight in older adults.

ABSTRACT

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 × height (cm) + 0.620 × MUAC (cm) + 0.517 × WC (cm) + 0.893 × CC (cm) + 0.111 × TST (mm) (adjusted r2  = 0.883, standard error of the estimate (SEE) = 4.4); females ≥ 80 years -110.806 + 0.494 × height (cm) + 0.637 × MUAC (cm) + 0.500 × WC (cm) + 0.986 × CC (cm) + 0.021 × TST (mm) (adjusted r2  = 0.890, SEE = 3.9); males 65-79 years -114.875 + 0.558 × height (cm) + 0.073 × MUAC (cm) + 0.671 × WC (cm) + 0.717 × CC (cm) + 0.182 × TST(mm) (adjusted r2  = 0.820, SEE=5.0); and males ≥ 80 years -128.789 + 0.546 × height (cm) + 0.202 × MUAC (cm) + 0.612 × WC (cm) + 1.236 × CC (cm) + 0.093 × TST (mm) (adjusted r2  = 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.