This paper is in the following e-collection/theme issue:
Online Dietary Intake Estimation: Reproducibility and Validity of the Food4Me Food Frequency Questionnaire Against a 4-Day Weighed Food Record
Rosalind Fallaize1, BSc (Hons);
Hannah Forster2, BSc (Hons);
Anna L Macready1, BSc (Hons), MSc, PhD;
Marianne C Walsh2, BSc (Hons), PhD;
John C Mathers3, BSc (Hons), PhD;
Lorraine Brennan2, BA (Mod), PhD;
Eileen R Gibney2, BSc (Hons), MSc, PhD;
Michael J Gibney2, BAgrSc, MAgrSc, PhD;
Julie A Lovegrove1, BSc (Hons), PhD
1Hugh Sinclair Unit of Human Nutrition and Institute for Cardiovascular and Metabolic Research, Department of Food and Nutritional Sciences, University of Reading, Reading, United Kingdom
2UCD Institute of Food and Health, UCD Centre for Molecular Innovation, University College Dublin, Dublin, Ireland
3Human Nutrition Research Centre, Institute for Health and Ageing, Newcastle University, Newcastle, United Kingdom
Julie A Lovegrove, BSc (Hons), PhD
Hugh Sinclair Unit of Human Nutrition and Institute for Cardiovascular and Metabolic Research
Department of Food and Nutritional Sciences
University of Reading
PO Box 226
Reading, RG6 6AP
Phone: 44 118 378 6418
Fax: 44 118 378 7708
1-3], researchers are seeking new and innovative ways of facilitating dietary change. These include the application of digital technologies, which are revolutionizing the delivery of health-related services because of their reduced costs and wide reach. Online interventions are particularly promising because they have the potential to increase exposure to health promotion material. Recent estimates show that Internet use has increased by 150% in North America and by nearly 400% in Europe since 2000, with a total of 78.6% and 63.2% of these populations, respectively, now classified as Internet users . Given their lower costs, Internet-based services have the potential to enhance the cost-benefit ratio for interventions aimed at prevention of diet-related noncommunicable diseases [5-6]. Furthermore, interactive Web-based interventions have been shown to increase patient activation and self-management capabilities in chronically ill adults  and enhance weight loss in obese individuals (compared with non-Web-based interventions) .
To quantify dietary change in response to an intervention, an accurate and validated means of assessing food intake is essential . Population-level food intake is usually assessed in 1 of 3 ways: a food frequency questionnaire (FFQ), 24-hour recall, or estimated or weighed food record (WFR). The WFR, which involves weighing all foods and drinks consumed over a 3-7 day period, is often considered the most accurate measure of intake and has been referred to as the imperfect gold standard . However, prospective recording of food consumption can alter the type and quantity of foods eaten and, therefore, introduce bias into the estimate of food intake [11-13]. The FFQ and 24-hour recall, which rely on retrospective recording of food consumption, are also prone to reporting bias, including overestimated consumption of “healthy” foods, such as fruit and vegetables, and underestimation of “unhealthy” food intake. WFR require participants to be highly motivated and are labor-intensive for both participants and researchers. Conversely, FFQ are inexpensive to process and can be self-administered electronically, making them suitable for online interventions. Other advantages include reducing paper use, postage costs, and the space; security; and organization required for paper file storage . For this reason, FFQ are most commonly used in large-scale epidemiological and intervention studies to determine food and nutrient intake .
The present research was conducted as part of the Food4Me study, which aims to test the utility of online personalized dietary advice using an online FFQ to assess dietary intake [16,17]. The Food4Me FFQ includes 157 food items and food portion photographs and has been described previously by Forster et al . FFQ are generally validated against existing dietary assessment methods, such as WFR , and several FFQ have been validated for electronic and online use recently [14,20-22].
The Food4Me FFQ has been shown to have good agreement with the European Prospective Investigation of Cancer (EPIC)-Norfolk FFQ for the estimation of energy-adjusted nutrient intakes . The aim of this study is to further validate the Food4Me FFQ against a WFR and to assess its reproducibility using a test-retest methodology.
To accurately estimate the Bland-Altman limits of agreement between 2 methods, a sample size of 50-100 is required . Allowing for 20% dropout, 121 participants aged ≥18 years were recruited from the University of Reading, UK, via email and poster advertising. Participants were provided with a study information sheet before participation and were asked to sign an informed consent form. A participant information form, which included self-reported weight and height measurements, was used to assess suitability for the study. Individuals reporting health issues or ill health, self-reported or diagnosed food intolerances, or special nutritional requirements (eg, pregnancy or lactation) were ineligible to participate. Ethical approval for the study was obtained from the School of Chemistry, Food and Pharmacy Research Ethics Committee, University of Reading, UK (01-12-Lovegrove).
Reproducibility of the Food4Me FFQ was determined by asking participants to complete the questionnaire on 2 occasions 4 weeks apart, mimicking its application in the Food4Me study. To assess the validity of the FFQ against a 4-day WFR, half the sample (those recruited first) were asked to complete a 4-day WFR 1 week following the first administration of the Food4Me-FFQ. Participants who completed both the Food4Me FFQ and 4-day WFR were also asked to complete a dietary record usability-rating questionnaire on Survey Monkey (Survey Monkey Inc, Palo Alto, CA, USA) in the week following the completion of the second Food4Me FFQ. The usability-rating questionnaire included questions about ease of use and willingness to complete the records. Participants were asked not to change their diet during the study.
Weighed Food Record
Participants were asked to record all foods and beverages consumed over a nonconsecutive 4-day period that included 3 weekdays (Monday to Thursday) and 1 weekend day (Saturday to Sunday). Before completing the WFR, participants were coached on how to describe food products by a dietitian and provided with weighing scales (Salter Disc Electronic Kitchen Scales SKU# 1036 WHSSDR). When participants were unable to provide weighed portion size information, this was estimated retrospectively within 1 week using the Ministry of Agriculture, Fisheries and Food Portion Size Atlas .
The self-administered Food4Me FFQ is an online, semiquantitative food frequency questionnaire (developed by University College Dublin and Crème Software Ltd). To complete the questionnaire, participants were provided with a website address and unique log-in details. On logging into the server, participants were directed to a webpage containing detailed instructions on how to complete the FFQ. The questionnaire contained questions on the average consumption of 157 food items over the previous month. The food items were divided into the following 11 categories: (1) cereal, (2) bread and savory biscuits, (3) potatoes, rice and pasta, (4) meat and fish, (5) dairy products and fat, (6) fats and spreads, (7) sweets and snacks, (8) soups, sauces and spreads, (9) drinks, (10) fruit, and (11) vegetables. During completion of the Food4Me FFQ, participants were required to provide information on frequency of consumption and portion size. Frequency of consumption was measured by selecting one of the following options: never or less than once a month, 1-3 times a month, once a week, 2-4 times a week, 5-6 times per week, once a day, 2-3 times per day, 5-6 times per day, and 6 times per day. Food portion size was estimated using photographs. Each food item had 3 photographs representing small, medium, and large portions and these descriptors were provided below the appropriate image. Participants could select one of the following options: very small, small, small/medium, medium, medium/large, large, or very large which were linked electronically to portion sizes (in grams) (see Figure 1). Food intake (g/day) was calculated by multiplying frequency of consumption by the specified portion size (see Forster et al for detailed methods ). Further screenshots of the online Food4Me FFQ are shown in Multimedia Appendix 1.