Evaluation of web-based, self-administered, graphical food frequency questionnaire.

Computer-administered food frequency questionnaires (FFQs) can address limitations inherent in paper questionnaires by allowing very complex skip patterns, portion size estimation based on food pictures, and real-time error checking. We evaluated a web-based FFQ, the Graphical Food Frequency System (GraFFS). Participants completed the GraFFS, six telephone-administered 24-hour dietary recalls over the next 12 weeks, followed by a second GraFFS. Participants were 40 men and 34 women, aged 18 to 69 years, living in the Columbus, OH, area. Intakes of energy, macronutrients, and 17 micronutrients/food components were estimated from the GraFFS and the mean of all recalls. Bias (second GraFFS minus recalls) was -9%, -5%, +4%, and -4% for energy and percentages of energy from fat, carbohydrate, and protein, respectively. De-attenuated, energy-adjusted correlations (intermethod reliability) between the recalls and the second GraFFS for fat, carbohydrate, protein, and alcohol were 0.82, 0.79, 0.67, and 0.90, respectively; for micronutrients/food components the median was 0.61 and ranged from 0.40 for zinc to 0.92 for beta carotene. The correlations between the two administrations of the GraFFS (test-retest reliability) for fat, carbohydrate, protein, and alcohol were 0.60, 0.63, 0.73, and 0.87, respectively; among micronutrients/food components the median was 0.67 and ranged from 0.49 for vitamin B-12 to 0.82 for fiber. The measurement characteristics of the GraFFS were at least as good as those reported for most paper FFQs, and its high intermethod reliability suggests that further development of computer-administered FFQs is warranted.

[1]  J. Potter,et al.  VITamins And Lifestyle cohort study: study design and characteristics of supplement users. , 2004, American journal of epidemiology.

[2]  W. Willett,et al.  The relation of diet, cigarette smoking, and alcohol consumption to plasma beta-carotene and alpha-tocopherol levels. , 1988, American journal of epidemiology.

[3]  Ilse De Bourdeaudhuij,et al.  Pilot evaluation of the HELENA (Healthy Lifestyle in Europe by Nutrition in Adolescence) Food-O-Meter, a computer-tailored nutrition advice for adolescents: a study in six European cities , 2011, Public Health Nutrition.

[4]  J. Jobe,et al.  Cognitive research enhances accuracy of food frequency questionnaire reports: results of an experimental validation study. , 2002, Journal of the American Dietetic Association.

[5]  D. Midthune,et al.  Comparative validation of the Block, Willett, and National Cancer Institute food frequency questionnaires : the Eating at America's Table Study. , 2001, American journal of epidemiology.

[6]  I. Thompson,et al.  Dietary patterns, supplement use, and the risk of symptomatic benign prostatic hyperplasia: results from the prostate cancer prevention trial. , 2008, American journal of epidemiology.

[7]  J. Crowley,et al.  Effect of selenium and vitamin E on risk of prostate cancer and other cancers: the Selenium and Vitamin E Cancer Prevention Trial (SELECT). , 2009, JAMA.

[8]  O. Levander The Need for Measures of Selenium Status , 1986 .

[9]  B. Lamarche,et al.  Validity and reproducibility of a web-based, self-administered food frequency questionnaire , 2012, European Journal of Clinical Nutrition.

[10]  Christophe Matthys,et al.  Validity and reproducibility of an adolescent web-based food frequency questionnaire. , 2007, Journal of the American Dietetic Association.

[11]  Albert F. Smith Cognitive processes in long-term dietary recall , 1991 .

[12]  A. Kristal,et al.  Low-fat diet practices of older women: prevalence and implications for dietary assessment. , 1996, Journal of the American Dietetic Association.

[13]  Bruce K. Armstrong,et al.  Principles of Exposure Measurement in Epidemiology , 1992 .

[14]  T. Byers,et al.  Effects of social approval bias on self-reported fruit and vegetable consumption: a randomized controlled trial , 2008, Nutrition Journal.

[15]  C. Rosen,et al.  Validation of a quantitative food frequency questionnaire for rapid assessment of dietary calcium intake. , 1989, Journal of the American Dietetic Association.

[16]  Pamela A Shaw,et al.  Use of recovery biomarkers to calibrate nutrient consumption self-reports in the Women's Health Initiative. , 2008, American journal of epidemiology.

[17]  Raymond J Carroll,et al.  A comparison of a food frequency questionnaire with a 24-hour recall for use in an epidemiological cohort study: results from the biomarker-based Observing Protein and Energy Nutrition (OPEN) study. , 2003, International journal of epidemiology.

[18]  A. Kristal,et al.  Measurement characteristics of the Women's Health Initiative food frequency questionnaire. , 1999, Annals of epidemiology.

[19]  T D Koepsell,et al.  Dietary assessment instruments are susceptible to intervention-associated response set bias. , 1998, Journal of the American Dietetic Association.

[20]  W. Willett,et al.  Predictors of selenium concentration in human toenails. , 1990, American journal of epidemiology.

[21]  Michael M Lieber,et al.  Designing the Selenium and Vitamin E Cancer Prevention Trial (SELECT). , 2005, Journal of the National Cancer Institute.

[22]  Zoe Falomir Llansola,et al.  Technological Applications for the Automation of Food Questionnaires in Medical Studies: a state-of-art-review and future prospective , 2012 .

[23]  R J Carroll,et al.  Empirical evidence of correlated biases in dietary assessment instruments and its implications. , 2001, American journal of epidemiology.

[24]  Amy F Subar,et al.  Carotenoid and tocopherol estimates from the NCI diet history questionnaire are valid compared with multiple recalls and serum biomarkers. , 2006, The Journal of nutrition.

[25]  D. Midthune,et al.  Development and evaluation of a short instrument to estimate usual dietary intake of percentage energy from fat. , 2007, Journal of the American Dietetic Association.

[26]  I. Bourdeaudhuij,et al.  The HELENA online food frequency questionnaire: reproducibility and comparison with four 24-h recalls in Belgian–Flemish adolescents , 2010, European Journal of Clinical Nutrition.

[27]  A. Kristal,et al.  Precision and bias of food frequency-based measures of fruit and vegetable intakes. , 2000, Cancer epidemiology, biomarkers & prevention : a publication of the American Association for Cancer Research, cosponsored by the American Society of Preventive Oncology.

[28]  M. Marmot,et al.  Dietary assessment in Whitehall II: comparison of 7 d diet diary and food-frequency questionnaire and validity against biomarkers , 2001, British Journal of Nutrition.

[29]  R. Carroll,et al.  Performance of a food-frequency questionnaire in the US NIH–AARP (National Institutes of Health–American Association of Retired Persons) Diet and Health Study , 2008, Public Health Nutrition.

[30]  Elizabeth J Johnson,et al.  Total α-Tocopherol Intakes Are Associated with Serum α-Tocopherol Concentrations in African American Adults , 2007 .

[31]  G. Block,et al.  Validity and reliability of the Block98 food-frequency questionnaire in a sample of Canadian women , 2006, Public Health Nutrition.

[32]  J. Crowley,et al.  Chemoprevention of prostate cancer: The prostate cancer prevention trial , 1997, The Prostate.

[33]  Walter C. Willett,et al.  Reproducibility and Validity of Food-Frequency Questionnaires , 1998 .

[34]  William T Riley,et al.  Evaluation of a web-based, pictorial diet history questionnaire , 2009, Public Health Nutrition.

[35]  M. Hughes,et al.  Relative validity of food intake estimates using a food frequency questionnaire is associated with sex, age, and other personal characteristics. , 2006, The Journal of nutrition.

[36]  Zoe Falomir,et al.  Automation of Food Questionnaires in Medical Studies: A state-of-the-art review and future prospects , 2012, Comput. Biol. Medicine.

[37]  A. Kristal,et al.  A randomized trial of a tailored, self-help dietary intervention: the Puget Sound Eating Patterns study. , 2000, Preventive medicine.

[38]  P. Corey,et al.  Sources of variance in 24-hour dietary recall data: implications for nutrition study design and interpretation. , 1979, The American journal of clinical nutrition.

[39]  Sally F. Schakel,et al.  Maintaining a Nutrient Database in a Changing Marketplace: Keeping Pace with Changing Food Products—A Research Perspective , 2001 .