A M Madden1, T Tsikoura, D J Stott. 1. School of Health and Emergency Professions, University of Hertfordshire, Hatfield, UK. a.madden@herts.ac.uk
Abstract
BACKGROUND: Assessments of nutritional status frequently incorporate a measure of height to evaluate a person's relative thinness or fatness. Because height is often difficult to quantify, it may be predicted from alternative anthropometric measurements, including ulna length. Little information is available about the accuracy of these predictions in an ethnically diverse population. The present study aimed to evaluate published equations for predicting height from ulna length in adults from different ethnic groups. METHODS: Ulna length and standing height were measured in a gender-stratified sample of 60 Asian, 69 Black and 65 White healthy volunteers, aged 21-65 years. Height was predicted from ulna length using the Malnutrition Universal Screening Tool (MUST) equations and compared against the measured values. Linear regression analysis was used to develop equations to estimate height from ulna length and to explore the relationship between height and ulna length in subgroups. RESULTS: The mean (SD) age for Asian, Black and White in men was 31.7 (11.0), 32.0 (10.3) and 38.6 (12.5) years and in women was 26.2 (5.4), 32.6 (8.9) and 35.7 (11.7); the mean (SD) height in men was 170.9 (5.2), 178.1 (7.3) and 176.3 (7.7) cm and in women was 157.7 (4.7), 164.0 (5.9) and 163.7 (6.2) cm. Ulna length and measured height were significantly correlated among all subgroups, except Asian women (r=0.11, P=0.57). The mean (SD) difference between predicted and measured height showed significant overestimates for Asian and Black men [4.0 (4.8) and 6.7 (5.3) cm] and Asian and Black women [6.4 (4.9) and 4.4 (4.9) cm] but not for White men and women. CONCLUSIONS: The MUST equations for predicting height from ulna length in healthy adults should be used with some caution among ethnically diverse populations, particularly in Asian women.
BACKGROUND: Assessments of nutritional status frequently incorporate a measure of height to evaluate a person's relative thinness or fatness. Because height is often difficult to quantify, it may be predicted from alternative anthropometric measurements, including ulna length. Little information is available about the accuracy of these predictions in an ethnically diverse population. The present study aimed to evaluate published equations for predicting height from ulna length in adults from different ethnic groups. METHODS: Ulna length and standing height were measured in a gender-stratified sample of 60 Asian, 69 Black and 65 White healthy volunteers, aged 21-65 years. Height was predicted from ulna length using the Malnutrition Universal Screening Tool (MUST) equations and compared against the measured values. Linear regression analysis was used to develop equations to estimate height from ulna length and to explore the relationship between height and ulna length in subgroups. RESULTS: The mean (SD) age for Asian, Black and White in men was 31.7 (11.0), 32.0 (10.3) and 38.6 (12.5) years and in women was 26.2 (5.4), 32.6 (8.9) and 35.7 (11.7); the mean (SD) height in men was 170.9 (5.2), 178.1 (7.3) and 176.3 (7.7) cm and in women was 157.7 (4.7), 164.0 (5.9) and 163.7 (6.2) cm. Ulna length and measured height were significantly correlated among all subgroups, except Asian women (r=0.11, P=0.57). The mean (SD) difference between predicted and measured height showed significant overestimates for Asian and Black men [4.0 (4.8) and 6.7 (5.3) cm] and Asian and Black women [6.4 (4.9) and 4.4 (4.9) cm] but not for White men and women. CONCLUSIONS: The MUST equations for predicting height from ulna length in healthy adults should be used with some caution among ethnically diverse populations, particularly in Asian women.
Authors: Michele R Forman; Yeyi Zhu; Ladia M Hernandez; John H Himes; Yongquan Dong; Robert K Danish; Kyla E James; Laura E Caulfield; Jean M Kerver; Lenore Arab; Paula Voss; Daniel E Hale; Nadim Kanafani; Steven Hirschfeld Journal: J Nutr Date: 2014-07-16 Impact factor: 4.798
Authors: Laura V White; Nathaniel Lee; Flora P Marin; Naomi R Saludar; Tansy Edwards; Sharon E Cox Journal: PLoS One Date: 2019-05-16 Impact factor: 3.240