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Updated: Apr 26, 2026

Assessment of Child Anthropometry in a Large Epidemiologic Study
Published on: February 2, 2017
Comparison of bias resulting from two methods of self-reporting height and weight: a validation study
Melissa Scribani1, Jessica Shelton1, David Chapel1
1Bassett Healthcare Network Research Institute, One Atwell Road, Cooperstown, NY 13326, USA.
Objectives:
To contrast the validity of two modes of self-reported height and weight data.
Design:
Subjects' self-reported height and weight by mailed survey without expectation of subsequent measurement. Subjects were later offered a physical exam, where they self-reported their height and weight again, just prior to measurement. Regression equations to predict actual from self-reported body mass index (BMI) were fitted for both sets of self-reported values. Residual analyses assessed bias resulting from application of each regression equation to the alternative mode of self-report. Analyses were stratified by gender.
Setting:
Upstate New York.
Participants:
Subjects (n = 260) with survey, pre-exam and measured BMI.
Main Outcome Measures:
Prevalence of obesity based on two modes of self-report and also measured values. Bias resulting from misapplication of correction equations.
Results:
Accurate prediction of measured BMI was possible for both self-report modes for men (R (2 )= 0.89 survey, 0.85 pre-exam) and women (R (2 )= 0.92 survey, 0.97 pre-exam). Underreporting of BMI was greater for survey than pre-exam but only significantly so in women. Obesity prevalence was significantly underestimated by 10.9% (p < 0.001) and 14.9% (p < 0.001) for men and 5.4% (p = 0.007) and 11.2% (p < 0.001) for women, for pre-exam and survey, respectively. Residual analyses showed that significant bias results when a regression model derived from one mode of self-report is used to correct BMI values estimated from the alternative mode.
Conclusions:
Both modes significantly underestimated obesity prevalence. Underestimation of actual BMI is greater for survey than pre-exam self-report for both genders, indicating that equations adjusting for self-report bias must be matched to the self-report mode.
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