How reliable is internet-based self-reported identity, socio-demographic and obesity measures in European adults?

Carlos Celis-Morales, Katherine M. Livingstone, Clara Woolhead, Hannah Forster, Clare B. O'Donovan, Anna L. Macready, Rosalind Fallaize, Cyril F. M. Marsaux, Lydia Tsirigoti, Eirini Efstathopoulou, George Moschonis, Santiago Navas-Carretero, Rodrigo San-Cristobal, Silvia Kolossa, Ulla L. Klein, Jacqueline Hallmann, Magdalena Godlewska, Agnieszka Surwiłło, Christian A. Drevon, Jildau BouwmanKeith Grimaldi, Laurence D. Parnell, Yannis Manios, Iwona Traczyk, Eileen R. Gibney, Lorraine Brennan, Marianne C. Walsh, Julie A. Lovegrove, J. Alfredo Martinez, Hannelore Daniel, Wim H. M. Saris, Mike Gibney, John C. Mathers

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33 Citations (Scopus)


In e-health intervention studies, there are concerns about the reliability of internet-based, self-reported (SR) data and about the potential for identity fraud. This study introduced and tested a novel procedure for assessing the validity of internet-based, SR identity and validated anthropometric and demographic data via measurements performed face-to-face in a validation study (VS). Participants (n = 140) from seven European countries, participating in the Food4Me intervention study which aimed to test the efficacy of personalised nutrition approaches delivered via the internet, were invited to take part in the VS. Participants visited a research centre in each country within 2 weeks of providing SR data via the internet. Participants received detailed instructions on how to perform each measurement. Individual's identity was checked visually and by repeated collection and analysis of buccal cell DNA for 33 genetic variants. Validation of identity using genomic information showed perfect concordance between SR and VS. Similar results were found for demographic data (age and sex verification). We observed strong intra-class correlation coefficients between SR and VS for anthropometric data (height 0.990, weight 0.994 and BMI 0.983). However, internet-based SR weight was under-reported (Δ -0.70 kg [-3.6 to 2.1], p < 0.0001) and, therefore, BMI was lower for SR data (Δ -0.29 kg m(-2) [-1.5 to 1.0], p < 0.0001). BMI classification was correct in 93 % of cases. We demonstrate the utility of genotype information for detection of possible identity fraud in e-health studies and confirm the reliability of internet-based, SR anthropometric and demographic data collected in the Food4Me study.TRIAL REGISTRATION: NCT01530139 ( ).

Original languageEnglish
Article number28
JournalGenes and Nutrition
Issue number5
Publication statusPublished - Sept 2015


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