Dauphinot V, Wolff H, Naudin F, Guéguen R, Sermet C, Gaspoz J-M, Kossovsky M P
CETAF, Centre Technique d'Appui et de Formation des Centres d'Examens de Santé, Saint-Etienne, France.
J Epidemiol Community Health. 2009 Feb;63(2):128-32. doi: 10.1136/jech.2008.077800. Epub 2008 Sep 18.
Since subjects included in population studies tend to underreport their weight and overestimate their height, obesity prevalence based on these data is often inaccurate. A reduced obesity threshold for self-reported height and weight was proposed and evaluated for its accuracy.
Self-reported heights and weights were compared with 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.
The Swiss population sample consisted of 13 162 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 to be non-obese according to their self-report. Considering measures as a reference, a lower BMI cut-off of 29.2 kg/m(2) was identified 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 similar results.
The reduced threshold based on self-report allowed a better estimation of obesity prevalence. Its use should be limited to population studies only.
由于纳入人群研究的受试者往往会少报体重并高估身高，基于这些数据得出的肥胖患病率往往不准确。因此提出了一个针对自我报告身高和体重的降低的肥胖阈值，并对其准确性进行了评估。
在瑞士城市成年人群代表性样本中，将自我报告的身高和体重与测量的身高和体重进行比较。参与者被询问身高和体重，并被邀请接受健康检查，在此期间测量这些数据。使用受试者工作特征（ROC）曲线分析评估最佳体重指数（BMI）值，并在外部法国人群样本上测试其正确估计肥胖患病率的能力。
瑞士人群样本包括13162名受试者（平均年龄51.4岁）。自我报告数据与测量数据的比较表明，根据申报计算出的肥胖患病率被低估了：在肥胖受试者（根据测量的BMI）中，33.6%的男性和27.5%的女性根据自我报告被认为是非肥胖者。以测量值为参考，基于自我报告确定的男女肥胖定义的较低BMI临界值为29.2kg/m²。男性和女性的误分类率分别降至17.9%和16.9%。在法国人群样本（n = 1858）上的验证程序产生了类似的结果。
基于自我报告的降低的阈值能够更好地估计肥胖患病率。其应用应仅限于人群研究。
