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- Title
Predicting height from ulna length for the determination of weight status in New Zealand adolescents: A cross‐sectional study.
- Authors
Ng, Hwei Min; MacDonell, Sue; Yap, Jia; Peddie, Meredith C.; Scott, Tessa; Haszard, Jillian Joy
- Abstract
Background: The measurement of height is crucial for weight status assessment. When standing height is difficult to measure, ulna length may offer a convenient and accurate surrogate of height measure. Adolescence is a period of accelerated linear growth; hence, the validation of age‐specific equations that predict height from ulna length in adolescents is warranted. The present study aimed to develop and validate age‐ and sex‐specific equations for predicting height from ulna length in New Zealand adolescents. Methods: Height, weight and ulna length were measured in 364 adolescents (n = 110 males, n = 254 females) aged 15.0–18.8 years, who were enrolled in the SuNDiAL (Survey of Nutrition Dietary Assessment and Lifestyle) project, a cross‐sectional survey performed in 2019 and 2020. Regression models were used to determine equations to predict height from ulna length. Agreement between measured and predicted height, body mass index (BMI) and BMI z‐score was assessed with intra‐class correlation coefficients (ICC) and Bland–Altman plots. Sensitivity and specificity were calculated for classifying obesity. Results: Strong agreement was found between predicted and measured height (ICC = 0.78; mean difference = 0; 95% confidence interval = −0.5 to 0.5 cm) and BMI (ICC = 0.95; mean difference = 0; 95% confidence interval = −0.1 to 0.1 kg m–2). Predicted height was 88.1% accurate when classifiying weight status, showing high sensitivity (93.8%) and specificity (99.4%) for classifying obesity. Conclusions: Ulna length measurement can accurately estimate height and subsequently weight status in New Zealand adolescents aged 15–18 years.
- Subjects
NEW Zealand; STATURE; BODY weight; CONFIDENCE intervals; CROSS-sectional method; ULNA; INTRACLASS correlation; BODY mass index; SENSITIVITY &; specificity (Statistics)
- Publication
Journal of Human Nutrition & Dietetics, 2022, Vol 35, Issue 2, p406
- ISSN
0952-3871
- Publication type
Article
- DOI
10.1111/jhn.12918