Lassale Camille, Péneau Sandrine, Touvier Mathilde, Julia Chantal, Galan Pilar, Hercberg Serge, Kesse-Guyot Emmanuelle
UREN-Nutritional Epidemiology Research Unit, Inserm-U557, Inra-U1125, Université Paris 13, Sorbonne Paris Cité, Cnam, Bobigny, France.
J Med Internet Res. 2013 Aug 8;15(8):e152. doi: 10.2196/jmir.2575.
With the growing scientific appeal of e-epidemiology, concerns arise regarding validity and reliability of Web-based self-reported data.
The objectives of the present study were to assess the validity of Web-based self-reported weight, height, and resulting body mass index (BMI) compared with standardized clinical measurements and to evaluate the concordance between Web-based self-reported anthropometrics and face-to-face declarations.
A total of 2513 participants of the NutriNet-Santé study in France completed a Web-based anthropometric questionnaire 3 days before a clinical examination (validation sample) of whom 815 participants also responded to a face-to-face anthropometric interview (concordance sample). Several indicators were computed to compare data: paired t test of the difference, intraclass correlation coefficient (ICC), and Bland-Altman limits of agreement for weight, height, and BMI as continuous variables; and kappa statistics and percent agreement for validity, sensitivity, and specificity of BMI categories (normal, overweight, obese).
Compared with clinical data, validity was high with ICC ranging from 0.94 for height to 0.99 for weight. BMI classification was correct in 93% of cases; kappa was 0.89. Of 2513 participants, 23.5% were classified overweight (BMI≥25) with Web-based self-report vs 25.7% with measured data, leading to a sensitivity of 88% and a specificity of 99%. For obesity, 9.1% vs 10.7% were classified obese (BMI≥30), respectively, leading to sensitivity and specificity of 83% and 100%. However, the Web-based self-report exhibited slight underreporting of weight and overreporting of height leading to significant underreporting of BMI (P<.05) for both men and women: -0.32 kg/m² (SD 0.66) and -0.34 kg/m² (SD 1.67), respectively. Mean BMI underreporting was -0.16, -0.36, and -0.63 kg/m² in the normal, overweight, and obese categories, respectively. Almost perfect agreement (ie, concordance) was observed between Web-based and face-to-face report (ICC ranged from 0.96 to 1.00, classification agreement was 98.5%, and kappa 0.97).
Web-based self-reported weight and height data from the NutriNet-Santé study can be considered as valid enough to be used when studying associations of nutritional factors with anthropometrics and health outcomes. Although self-reported anthropometrics are inherently prone to biases, the magnitude of such biases can be considered comparable to face-to-face interview. Web-based self-reported data appear to be an accurate and useful tool to assess anthropometric data.
随着电子流行病学的科学吸引力不断增加,基于网络的自我报告数据的有效性和可靠性引发了关注。
本研究的目的是评估基于网络的自我报告体重、身高及由此得出的体重指数(BMI)与标准化临床测量结果相比的有效性,并评估基于网络的自我报告人体测量数据与面对面申报之间的一致性。
法国NutriNet-Santé研究的2513名参与者在临床检查前3天完成了一份基于网络的人体测量问卷(验证样本),其中815名参与者还回应了面对面的人体测量访谈(一致性样本)。计算了几个指标来比较数据:体重、身高和BMI作为连续变量的差异配对t检验、组内相关系数(ICC)以及Bland-Altman一致性界限;BMI类别(正常、超重、肥胖)的有效性、敏感性和特异性的kappa统计量和百分比一致性。
与临床数据相比,有效性较高,ICC范围从身高的0.94到体重的0.99。BMI分类在93%的病例中是正确的;kappa为0.89。在2513名参与者中,基于网络自我报告有23.5%被分类为超重(BMI≥25),而测量数据为25.7%,导致敏感性为88%,特异性为99%。对于肥胖,分别有9.1%和10.7%被分类为肥胖(BMI≥30),导致敏感性和特异性分别为83%和100%。然而,基于网络的自我报告显示体重略有少报,身高多报,导致男性和女性的BMI均有显著少报(P<0.05):分别为-0.32kg/m²(标准差0.66)和-0.34kg/m²(标准差1.67)。正常、超重和肥胖类别中BMI的平均少报分别为-0.16、-0.36和-0.63kg/m²。基于网络和面对面报告之间观察到几乎完美的一致性(即一致性)(ICC范围从0.96到1.00,分类一致性为98.5%,kappa为0.97)。
NutriNet-Santé研究中基于网络的自我报告体重和身高数据可被认为足够有效,可用于研究营养因素与人体测量学和健康结果之间的关联。尽管自我报告的人体测量数据固有地容易产生偏差,但这种偏差的程度可被认为与面对面访谈相当。基于网络的自我报告数据似乎是评估人体测量数据的准确且有用的工具。