• Alyse Davies, Lyndal Wellard-Cole, Anna Rangan, and Margaret Allman-Farinelli.
• The University of Sydney, Nutrition and Dietetics Group, School of Life and Environmental Science, Charles Perkins Center, New South Wales, Australia. Electronic address: adav5418@uni.sydney.edu.au.
• Nutrition. 2020 Mar 1; 71: 110622.

ObjectiveThe aim of this study was to validate self-reported anthropometric measurements and body mass index (BMI) classifications in a young adult population.MethodsBoth self-reported and directly measured weight and height of 100 young adults 18 to 30 y of age were collected. Participants were measured at one of two university clinics by two research dietitians and within 2 wk self-reported their body weight and height via a questionnaire as part of a larger study. BMI was calculated and categorized according to the World Health Organization's cut-points for underweight, healthy weight, and overweight or obesity. The validity of measured against self-reported weight and height was examined using Pearson's correlation, Bland-Altman plots, and Cohen's kappa statistic.ResultsStrong correlation was observed between measured and self-reported weight (r = 0.99; P < 0.001), height (r = 0.95; P < 0.001), and BMI (r = 0.94; P < 0.001). Bland-Altman plots indicated that the mean difference between self-reported and direct BMI measurements were small in the total sample (0.1 kg/m2). The majority of values fell within the limits of agreement (2 SD), with random scatter plots and no systemic bias detected. The classification of BMI from self-reported and direct measurements showed that 88% were placed in the equivalent weight category with very good agreement Cohen's kappa (0.76; 95% confidence interval, 0.63-0.89; P < 0.001).ConclusionsGood agreement was detected between self-reported and direct anthropometric measurements. The criticism of self-reported anthropometric measurements is unwarranted. The findings provide support for using self-reported height and weight data for research in Australian young adults when direct measurements are not feasible.Copyright © 2019 Elsevier Inc. All rights reserved.

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