Background: Since subjects included in population studies tend to underreport their weight and overestimate their height, obesity prevalence based on these data is often inaccurate. We proposed a reduced obesity threshold for self-reported height and weight, and evaluated its accuracy.
Methods: We compared self-reported to measured heights and weights in a Swiss city adult population representative sample. Participants were asked their height and weight and were invited to undergo a health examination, during which these data were measured. An optimal Body Mass Index [BMI] value was assessed using Receiver Operating Characteristic [ROC] curve analysis and its ability to correctly estimate obesity prevalence was tested on an external French population sample.
Results: The Swiss population sample consisted of 13162 subjects (mean age: 51.4). The comparison between self-reported and measured data showed that obesity prevalence calculated from declarations was underestimated: among obese subjects (according to measured BMI), 33.6% of men and 27.5% of women were considered as non-obese according to their self-report. Considering measures as a reference, we identified a lower BMI cut-off: 29.2 kg/m² for both genders for the definition of obesity based on self-report. Respective misclassification was reduced to 17.9% in men and 16.9% in women. The validation procedure on a French population sample (n=1858) yielded to similar results.
Conclusion: The reduced threshold based on self-report allowed a better estimation of obesity prevalence. Its use should limited to population studies only.
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