Estimation of body weight from selected body circumferences in the hospital setting - M.J.V. Parasvita; V. Wijaya; N. Budiman; L. Wibowo; W. Lukito (Clinical Nutrition Open Science)
Summary: Background and Aims: In hospital settings, body weight (BW) measurement can only sometimes be done, even though it is indispensable to justify nutritional and pharmacologic interventions. To be able to monitor the BW and define the dynamic of hospital malnutrition, it is pertinent to pursue an estimate of BW using the accessible body circumferences (BCs) variables, as described in the current study. Methods: Four hundred seventy-seven patients (aged 17–76) were recruited. Only those who could stand up for measuring direct body weight (BW), height (H), and selected BCs were eligible for the study. Thirty-seven patients were excluded from the statistical analyses: 18 with significant edema, 16 with BW > 110 kg (considered outliers), and three without BW data. A total of 440 patients (155 men and 285 women) were included in the final analyses. BW was measured using bioelectrical impedance SECA type 514, and BCs, namely mid-upper arm circumference (MUAC), abdominal circumference (AC), and calf circumference (CC), were measured using a SECA 201 non-elastic tape (SECA 201). We used hierarchical analyses to estimate BW (eBW) with gender and the existence of disease as control variables and BCs as predicted variables. Results: After controlling for gender and disease, the regression model could predict 94.1% of BW variability (R2= 0.942) using a combination of 3 BCs as predicted variables, 89.0–93.3% (R2=0.891–0.933) of BW variability using a combination of 2 BCs; and 81.2–84.6% of BW variability (R2 = 0.814–0.847) with single BC as predicted variables. Conclusions: The best-fit model to estimate patients' BW used a combination of 3 BCs as predicted variables. Nevertheless, other models with the predictability of BW variability of at least 80% could be considered alternatives in developing countries and Asian people with diverse hospital capacities. Further study is needed to validate these BW prediction formulas in clinical practices and describe their variations against the actual BW values.