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. 2007 Jan;15(1):188-96.
doi: 10.1038/oby.2007.504.

Comparison of self-reported and measured BMI as correlates of disease markers in US adults

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Free article

Comparison of self-reported and measured BMI as correlates of disease markers in US adults

Mara A McAdams et al. Obesity (Silver Spring). 2007 Jan.
Free article

Abstract

Objective: The purpose of this study is to evaluate the validity of BMI based on self-reported data by comparison with technician-measured BMI and biomarkers of adiposity.

Research methods and procedures: We analyzed data from 10,639 National Health and Nutrition Education Study III participants > or =20 years of age to compare BMI calculated from self-reported weight and height with BMI from technician-measured values and body fatness estimated from bioelectrical impedance analysis in relation to systolic blood pressure, fasting blood levels of glucose, high-density lipoprotein-cholesterol, triglycerides, C-reactive protein, and leptin.

Results: BMI based on self-reported data (25.07 kg/m2) was lower than BMI based on technician measurements (25.52 kg/m2) because of underreporting weight (-0.56 kg; 95% confidence interval, -0.71, -0.41) and overreporting height (0.76 cm; 95% confidence interval, 0.64, 0.88). However, the correlations between self-reported and measured BMI values were very high (0.95 for whites, 0.93 for blacks, and 0.90 for Mexican Americans). In terms of biomarkers, self-reported and measured BMI values were equally correlated with fasting blood glucose (r = 0.43), high-density lipoprotein-cholesterol (r = -0.53), and systolic blood pressure (r = 0.54). Similar correlations were observed for both measures of BMI with plasma concentrations of triglycerides and leptin. These correlations did not differ appreciably by age, sex, ethnicity, or obesity status. Correlations for percentage body fat estimated through bioelectrical impedance analysis with these biomarkers were similar to those for BMI.

Discussion: The accuracy of self-reported BMI is sufficient for epidemiological studies using disease biomarkers, although inappropriate for precise measures of obesity prevalence.

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