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Standardised coding of diet records: experiences from INTERMAP UK

Published online by Cambridge University Press:  09 March 2007

Rana Conway
Affiliation:
Department of Nutrition and Dietetics, Kings College London, 150 Stamford Street, London SE1 8WA, UK
Claire Robertson*
Affiliation:
Department of Epidemiology and Public Health, Imperial College London, St Mary's Campus, Norfolk Place, London W2 1PG, UK
Barbara Dennis
Affiliation:
Department of Biostatistics, Collaborative Studies Coordinating Center, University of North Carolina at Chapel Hill, Chapel Hill NC, USA
Jeremiah Stamler
Affiliation:
Department of Preventive Medicine, The Feinberg School of Medicine, Northwestern University, Chicago IL, USA
Paul Elliott
Affiliation:
Department of Epidemiology and Public Health, Imperial College London, St Mary's Campus, Norfolk Place, London W2 1PG, UK
*
*Corresponding author: Dr Claire Robertson, fax +44 20 7402 2150, email [email protected]
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Abstract

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Coding diet records is a basic element of most dietary surveys, yet it often receives little attention even though errors in coding can lead to flawed study results. In the INTERnational study of MAcro- and micronutrients and blood Pressure (INTERMAP study), efforts were made to minimise errors in coding the 18 720 diet records. Staff were centrally trained and certified before being able to process study data and ongoing quality control checks were performed. This involved the senior (site) nutritionist re-coding randomly selected diet records. To facilitate standardisation of coding in the UK, a code book was designed; it included information about coding brand items, density and portion size information, and default codes to be assigned when limited information was available for food items. It was found that trainees, despite previous experience in coding elsewhere, made coding errors that resulted in errors in estimates of daily energy and nutrient intakes. As training proceeded, the number of errors decreased. Compilation of the code book was labour-intensive, as information from food manufacturers and retailers had to be collected. Strategies are required to avoid repetition of this effort by other research groups. While the methods used in INTERMAP to reduce coding errors were time consuming, the experiences suggest that such errors are important and that they can be reduced.

Type
Research Article
Copyright
Copyright © The Nutrition Society 2004

Footnotes

copies of the INTERMAP study manuals and INTERMAP UK code book please contact the corresponding author.

References

Bingham, SA (1987) The dietary assessment of individuals; methods, accuracy, new techniques and recommendations. Nutr Abstr Rev A57, 705742.Google Scholar
Bingham, SA (1991) Limitations of the various methods of collecting dietary intake data. Ann Nutr Metab 35, 117127.CrossRefGoogle ScholarPubMed
Black, AE, Goldberg, GR, Jebb, SA, Livingstone, MB, Cole, TJ & Prentice, AM (1991) Critical evaluation of energy intake data using fundamental principles of energy physiology: 2. Evaluating the results of published surveys. Eur J Clin Nutr 45, 583599.Google ScholarPubMed
Buzzard, IM, Schakel, SF & Ditter-Johnson, J (1995) Quality control in the use of food and nutrient databases for epidemiologic studies. In Quality and Accessibility of Food Related Data, pp. 241252 [Greenfield, H, editor]. Arlington VA: AOAC International.Google Scholar
Crawley, H (1993) Food Portion Sizes. LondonH. M. Stationery Office.Google Scholar
Dennis, B, Ernst, N, Hjortland, J & Grambsch, V (1980) The NHLBI nutrition data system. J Am Diet Assoc 77, 641647.CrossRefGoogle ScholarPubMed
Dennis, B, Stamler, J, Buzzard, M, Conway, R, Elliott, P, Moag-Stahlberg, A, Okayama, A, Okuda, N, Robertson, C & Robinson, F (2003) INTERMAP: the dietary data – process and quality control. J Hum Hypertens 17, 609622.CrossRefGoogle ScholarPubMed
Eagles, JA, Whiting, MG & Olsen, RE, (1966) Dietary appraisal: problems in processing dietary data. Am J Clin Nutr 19, 19.CrossRefGoogle ScholarPubMed
Food Standards Agency (2002) McCance and Widdowson's The Composition of Foods, 6th summary ed. CambridgeThe Royal Society of Chemistry.Google Scholar
Food Standards Agency (2003) Programme of Mini-surveys: Sausages Survey. Food Surveillance Information Sheets. http://www.foodstandards.gov.uk/science/surveillance/fsis-2003/sausagesurveyfsis4103 (accessed 30 September 2003).Google Scholar
Gregory, J, Foster, K, Tyler, H & Wiseman, M (1990) The Dietary and Nutritional Survey of British Adults. London: H. M. Stationery Office.Google Scholar
Guilland, JC, Aubert, R, Lhuissier, M, Peres, G, Montagnon, B, Fuchs, F, Merlet, N & Astorg, PO (1993) Computerized analysis of food records: role of coding and food composition database. Eur J Clin Nutr 47, 445453.Google ScholarPubMed
International Consumer Research and Testing Ltd (1998) Parallel Food Testing: Fortified Foods. London: International Consumer Research and Testing Ltd.Google Scholar
Johansson, L, Solvoll, K, Bjorneboe, GE & Dreven, CA (1998) Under- and over-reporting of energy intake related to weight status and lifestyle in a nationwide sample. Am J Clin Nutr 68, 266274.CrossRefGoogle Scholar
Ministry of Agriculture Fisheries and Food (1996) National Food Survey 1995. London: H. M. Stationery Office.Google Scholar
National Institutes of Health (1992) Data Preview, Baseline Survey, Sub-sample (1983–86) Part 2, Nutrition, Fall/Spring. Washington, DC: US Department of Health and Human Services.Google Scholar
Nelson, M, Atkinson, M & Meyer, J, on behalf of the Nutritional Epidemiology Group UK (1997) A Photographic Atlas of Food Portion Sizes. London: MAFF.Google Scholar
J Sainsbury plc (2004) Frequently Asked Questions. http://www.j-sainsbury.co.uk/media/press_questions7.htmGoogle Scholar
Schakel, SF, Buzzard, IM & Gebhardt, SE (1997) Procedures for estimating nutrient values for food composition databases. J Food Compos Anal 10, 102114.CrossRefGoogle Scholar
Schakel, SF, Dennis, BH, Wold, CA, Conway, R, Zhao, L, Okunda, N, Okayama, A, Moag-Stahlberg, A, Robertson, C & Van Heel, N (2003) Enhancing data on nutrient composition of foods eaten by participants in the INTERMAP study in China, Japan, the United Kingdon, and the United States. J Food Compos Anal 16, 395408.CrossRefGoogle Scholar
Stamler, J, Elliott, P, Dennis, B, Dyer, A, Kesteloot, H, Liu, K, Ueshima, H 7 Zhou, BF (2003) INTERMAP: background, aims, design, methods, and descriptive statistics (nondietary). J Hum Hypertens 17, 591608.CrossRefGoogle ScholarPubMed