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Wark PA, Hardie LJ, Frost GS, Alwan NA, Carter M, Elliott P, Ford HE, Hancock N, Morris MA, Mulla UZ, Noorwali EA, Petropoulou K, Murphy D, Potter GDM, Riboli E, Greenwood DC, Cade JE. Validity of an online 24-h recall tool (myfood24) for dietary assessment in population studies: comparison with biomarkers and standard interviews. BMC Med 2018; 16:136. [PMID: 30089491 PMCID: PMC6083628 DOI: 10.1186/s12916-018-1113-8] [Citation(s) in RCA: 71] [Impact Index Per Article: 11.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/17/2017] [Accepted: 06/29/2018] [Indexed: 11/17/2022] Open
Abstract
BACKGROUND Online dietary assessment tools can reduce administrative costs and facilitate repeated dietary assessment during follow-up in large-scale studies. However, information on bias due to measurement error of such tools is limited. We developed an online 24-h recall (myfood24) and compared its performance with a traditional interviewer-administered multiple-pass 24-h recall, assessing both against biomarkers. METHODS Metabolically stable adults were recruited and completed the new online dietary recall, an interviewer-based multiple pass recall and a suite of reference measures. Longer-term dietary intake was estimated from up to 3 × 24-h recalls taken 2 weeks apart. Estimated intakes of protein, potassium and sodium were compared with urinary biomarker concentrations. Estimated total sugar intake was compared with a predictive biomarker and estimated energy intake compared with energy expenditure measured by accelerometry and calorimetry. Nutrient intakes were also compared to those derived from an interviewer-administered multiple-pass 24-h recall. RESULTS Biomarker samples were received from 212 participants on at least one occasion. Both self-reported dietary assessment tools led to attenuation compared to biomarkers. The online tools resulted in attenuation factors of around 0.2-0.3 and partial correlation coefficients, reflecting ranking intakes, of approximately 0.3-0.4. This was broadly similar to the more administratively burdensome interviewer-based tool. Other nutrient estimates derived from myfood24 were around 10-20% lower than those from the interviewer-based tool, with wide limits of agreement. Intraclass correlation coefficients were approximately 0.4-0.5, indicating consistent moderate agreement. CONCLUSIONS Our findings show that, whilst results from both measures of self-reported diet are attenuated compared to biomarker measures, the myfood24 online 24-h recall is comparable to the more time-consuming and costly interviewer-based 24-h recall across a range of measures.
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Affiliation(s)
- Petra A Wark
- Centre for Innovative Research Across the Life Course (CIRAL), Faculty of Health and Life Sciences, Coventry University, Coventry, CV1 5FB, UK
- Global eHealth Unit, Department of Primary Care and Public Health, Imperial College, Imperial College, London, SW7 2AZ, UK
| | - Laura J Hardie
- Division of Epidemiology and Biostatistics, Leeds Institute for Cardiovascular and Metabolic Medicine, School of Medicine, University of Leeds, Leeds, LS2 9JT, UK
| | - Gary S Frost
- Nutrition and Dietetic Research Group, Division of Diabetes, Endocrinology and Metabolism, Faculty of Medicine, Imperial College London, London, W12 ONN, UK
| | - Nisreen A Alwan
- Academic Unit of Primary Care and Population Sciences, Faculty of Medicine, University of Southampton, Southampton, SO16 6YD, UK
- NIHR Southampton Biomedical Research Centre, University of Southampton and University Hospital Southampton NHS Foundation Trust, Southampton, SO16 6YD, UK
| | - Michelle Carter
- Nutritional Epidemiology Group, School of Food Science and Nutrition, University of Leeds, Leeds, LS2 9JT, UK
| | - Paul Elliott
- MRC-PHE Centre for Environment and Health, Department of Epidemiology and Biostatistics, School of Public Health, Faculty of Medicine, Imperial College London, London, W2 1PG, UK
| | - Heather E Ford
- Nutrition and Dietetic Research Group, Division of Diabetes, Endocrinology and Metabolism, Faculty of Medicine, Imperial College London, London, W12 ONN, UK
| | - Neil Hancock
- Nutritional Epidemiology Group, School of Food Science and Nutrition, University of Leeds, Leeds, LS2 9JT, UK
| | - Michelle A Morris
- Leeds Institute of Data Analytics, University of Leeds, Leeds, LS2 9JT, UK
| | - Umme Z Mulla
- Centre for Innovative Research Across the Life Course (CIRAL), Faculty of Health and Life Sciences, Coventry University, Coventry, CV1 5FB, UK
| | - Essra A Noorwali
- Nutritional Epidemiology Group, School of Food Science and Nutrition, University of Leeds, Leeds, LS2 9JT, UK
- Department of Clinical Nutrition, Faculty of Applied Medical Sciences, Umm Al-Qura University, P.O. Box 715, Makkah, 21955, Saudi Arabia
| | - K Petropoulou
- Nutrition and Dietetic Research Group, Division of Diabetes, Endocrinology and Metabolism, Faculty of Medicine, Imperial College London, London, W12 ONN, UK
| | - David Murphy
- Division of Epidemiology and Biostatistics, Leeds Institute for Cardiovascular and Metabolic Medicine, School of Medicine, University of Leeds, Leeds, LS2 9JT, UK
| | - Gregory D M Potter
- Division of Epidemiology and Biostatistics, Leeds Institute for Cardiovascular and Metabolic Medicine, School of Medicine, University of Leeds, Leeds, LS2 9JT, UK
| | - Elio Riboli
- MRC-PHE Centre for Environment and Health, Department of Epidemiology and Biostatistics, School of Public Health, Faculty of Medicine, Imperial College London, London, W2 1PG, UK
| | - Darren C Greenwood
- Division of Epidemiology and Biostatistics, Leeds Institute for Cardiovascular and Metabolic Medicine, School of Medicine, University of Leeds, Leeds, LS2 9JT, UK
- Leeds Institute of Data Analytics, University of Leeds, Leeds, LS2 9JT, UK
| | - Janet E Cade
- Nutritional Epidemiology Group, School of Food Science and Nutrition, University of Leeds, Leeds, LS2 9JT, UK.
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