TY - JOUR
T1 - Improved prediction equations for estimating height in adults from ethnically diverse backgrounds
AU - Madden, Angela
AU - Mashanova, Alla
AU - Amirabdollahian, Farzad
AU - Ghuman, Sandeep
AU - Makda, Munibah
AU - Collinson, Avril
AU - Dean, Frances
AU - Hirsz, Malgorzata
AU - Lennie, Susan
AU - Maynard, Maria J
AU - Power, Brian
N1 - © 2019 Elsevier Ltd and European Society for Clinical Nutrition and Metabolism. All rights reserved.
PY - 2019/6/21
Y1 - 2019/6/21
N2 - Background and aims: When body height cannot be measured, it can be predicted from ulna length (UL). However, commonly used published prediction equations may not provide useful estimates in adults from all ethnicities. This study aimed to evaluate the relationship between UL and height in adults from diverse ethnic groups and to consider whether this can be used to provide useful prediction equations for height in practice.Methods: Standing height and UL were measured in 542 adults at seven UK locations. Ethnicity was self-defined using UK Census 2011 categories. Data were modelled to give two groups of height prediction equations based on UL, sex and ethnicity and these were tested against an independent dataset (n=180). Results: UL and height were significantly associated overall and in all groups except one with few participants (P=0.059). The new equations yielded predicted height (Hp) that was closer to measured height in the Asian and Black subgroups of the independent population than the Malnutrition Universal Screening Tool (MUST) equations. For Asian men, (Hp (cm) = 3.26 UL (cm) + 83.58), mean difference from measured (95% confidence intervals) was -0.6 (-2.4, +1.2); Asian women, (Hp = 3.26 UL + 77.62), mean difference +0.5 (-1.4, 2.4) cm. For Black men, Hp = 3.14 UL + 85.80, -0.4 (-2.4, 1.7); Black women, Hp = 3.14 UL + 79.55, -0.8 (-2.8, 1.2). These differences were not statistically significant while predictions from MUST equations were significantly different from measured height.Conclusions: The new prediction equations provide an alternative for estimating height in adults from Asian and Black groups and give mean predicted values that are closer to measured height than MUST equations.
AB - Background and aims: When body height cannot be measured, it can be predicted from ulna length (UL). However, commonly used published prediction equations may not provide useful estimates in adults from all ethnicities. This study aimed to evaluate the relationship between UL and height in adults from diverse ethnic groups and to consider whether this can be used to provide useful prediction equations for height in practice.Methods: Standing height and UL were measured in 542 adults at seven UK locations. Ethnicity was self-defined using UK Census 2011 categories. Data were modelled to give two groups of height prediction equations based on UL, sex and ethnicity and these were tested against an independent dataset (n=180). Results: UL and height were significantly associated overall and in all groups except one with few participants (P=0.059). The new equations yielded predicted height (Hp) that was closer to measured height in the Asian and Black subgroups of the independent population than the Malnutrition Universal Screening Tool (MUST) equations. For Asian men, (Hp (cm) = 3.26 UL (cm) + 83.58), mean difference from measured (95% confidence intervals) was -0.6 (-2.4, +1.2); Asian women, (Hp = 3.26 UL + 77.62), mean difference +0.5 (-1.4, 2.4) cm. For Black men, Hp = 3.14 UL + 85.80, -0.4 (-2.4, 1.7); Black women, Hp = 3.14 UL + 79.55, -0.8 (-2.8, 1.2). These differences were not statistically significant while predictions from MUST equations were significantly different from measured height.Conclusions: The new prediction equations provide an alternative for estimating height in adults from Asian and Black groups and give mean predicted values that are closer to measured height than MUST equations.
KW - Adults
KW - Anthropometry
KW - Ethnicity
KW - Height
KW - Prediction equations
KW - Ulna
UR - http://www.scopus.com/inward/record.url?scp=85068378466&partnerID=8YFLogxK
U2 - 10.1016/j.clnu.2019.06.007
DO - 10.1016/j.clnu.2019.06.007
M3 - Article
SN - 0261-5614
VL - 39
SP - 1454
EP - 1463
JO - Clinical Nutrition
JF - Clinical Nutrition
IS - 5
ER -