Validity of self-reported weight and height for BMI classification: A cross-sectional study among young adults
Abstract
OBJECTIVE
The aim of this study was to validate self-reported anthropometric measurements and body mass index (BMI) classifications in a young adult population.
METHODS
Both 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.
RESULTS
Strong 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).
CONCLUSIONS
Good agreement was detected between…
How strong is the evidence?
Evidence Hub reads this as a cross-sectional, done in people. Its evidence level is 4 of 5 (Low · observational). Observational designs can show an association but not prove cause. Reported size: 100 participants or records.
Read the paper
Related studies
- Drug repositioning: a brief overview
- Cyclic nucleotide phosphodiesterases in Drosophila melanogaster
- Time-resolved in silico modeling of fine-tuned cAMP signaling in platelets: feedback loops, titrated phosphorylations and pharmacological modulation
- Current View on Green Tea Catechins Formulations, Their Interactions with Selected Drugs, and Prospective Applications for Various Health Conditions
- In silico Structure-based Identification of Novel Acetylcholinesterase Inhibitors Against Alzheimer’s Disease
- Development and In Vitro Evaluation of Controlled Release Viagra® Containing Poloxamer-188 Using Gastroplus™ PBPK Modeling Software for In Vivo Predictions and Pharmacokinetic Assessments
Go deeper in Evidence Hub
Evidence Hub adds a study data sheet (design, sample size, evidence level, key numbers), an AI summary and a chat grounded in the paper's text.