Université Paris 13, Equipe de Recherche en Epidémiologie Nutritionnelle (EREN), Centre de Recherche en Epidémiologie et Statistiques, Inserm (U1153), Inra (U1125), Cnam, COMUE Sorbonne Paris Cité, Bobigny, France.
Unité de Surveillance en Epidémiologie Nutritionnelle (USEN), Institut de Veille Sanitaire, Université Paris 13, Centre d'Epidémiologie et Biostatistiques, Sorbonne Paris Cité, Bobigny, France.
J Epidemiol Community Health. 2015 Sep;69(9):893-8. doi: 10.1136/jech-2014-205263. Epub 2015 Apr 1.
A recurring concern in traditional and in Web-based studies pertains to non-representativeness due to volunteer bias. We investigated this issue in an ongoing, large population-based e-cohort.
The sample included 122 912 individuals enrolled in the Internet-based, nutrition-focused NutriNet-Santé study between May 2009 and March 2014, with complete baseline data. Participants were recruited via recurrent multimedia campaigns and other traditional and online strategies. Individuals aged 18+ years, residing in France and having Internet access, were eligible for enrolment. Their sociodemographic characteristics were compared with the corresponding 2009 Census data via χ(2) goodness-of-fit tests. The effectiveness of statistical weighting of the e-cohort data was also explored.
The sample exhibited marked geographical and sociodemographic diversity, including volunteers belonging to typically under-represented subgroups in traditional surveys (unemployed, immigrants, the elderly). Nonetheless, the proportions of women, relatively well-educated individuals and those who are married or cohabiting, were notably larger compared with the corresponding national figures (women: 78.0% vs 52.4%; postsecondary education: 61.5% vs 24.9%; married or cohabiting: 70.8% vs 62.0%, respectively; all p<0.0001).
There were notable sociodemographic differences between the general French population and this general population-based e-cohort, some of which were corrected by statistical weighting. The findings bear on the potential generalisability of future investigations in the context of e-epidemiology.
传统研究和基于网络的研究都存在一个反复出现的问题,即由于志愿者的偏差导致代表性不足。我们在一个正在进行的、基于人群的大型网络队列研究中调查了这个问题。
该样本包括 2009 年 5 月至 2014 年 3 月期间参加基于互联网、以营养为重点的 NutriNet-Santé 研究的 122912 名个体,他们具有完整的基线数据。参与者是通过多次多媒体宣传活动以及其他传统和在线策略招募的。年龄在 18 岁以上、居住在法国并能上网的个体有资格参加。通过 χ(2)拟合优度检验,将他们的社会人口统计学特征与相应的 2009 年人口普查数据进行了比较。还探讨了对网络队列数据进行统计加权的效果。
该样本具有明显的地理和社会人口学多样性,包括传统调查中通常代表性不足的亚组志愿者(失业者、移民、老年人)。尽管如此,与相应的全国数据相比,女性、受过较高教育的个体以及已婚或同居的个体的比例明显更大(女性:78.0%比 52.4%;中学后教育:61.5%比 24.9%;已婚或同居:70.8%比 62.0%,均 p<0.0001)。
普通法国人群与该基于人群的网络队列之间存在显著的社会人口学差异,其中一些差异通过统计加权得到了纠正。这些发现对电子流行病学背景下未来研究的潜在普遍性具有重要意义。