OBJECTIVE: To disaggregate composite food codes used in the UK National Diet and Nutrition Survey (NDNS) into their individual food components in order to provide a more complete estimate of intake at the individual food level. METHODS: A total of 3216 composite food codes from the NDNS food composition databank were subject to disaggregation. The main food components used were meat, fish, fruit, vegetables and cheese, which were further divided into 26 subcategories. RESULTS: It was shown that previous determination of meat containing composite food codes provided an overestimate of meat intake and underestimate of additional components such as fruit and vegetables. CONCLUSIONS: By incorporating disaggregated data into NDNS, variations will be seen in consumption of some main food groups, but these variations may be also attributable to trends in consumption.
OBJECTIVE: To disaggregate composite food codes used in the UK National Diet and Nutrition Survey (NDNS) into their individual food components in order to provide a more complete estimate of intake at the individual food level. METHODS: A total of 3216 composite food codes from the NDNS food composition databank were subject to disaggregation. The main food components used were meat, fish, fruit, vegetables and cheese, which were further divided into 26 subcategories. RESULTS: It was shown that previous determination of meat containing composite food codes provided an overestimate of meat intake and underestimate of additional components such as fruit and vegetables. CONCLUSIONS: By incorporating disaggregated data into NDNS, variations will be seen in consumption of some main food groups, but these variations may be also attributable to trends in consumption.
Authors: Emily Fitt; Darren Cole; Nida Ziauddeen; David Pell; Elizabeth Stickley; Anna Harvey; Alison M Stephen Journal: Public Health Nutr Date: 2014-03-27 Impact factor: 4.022
Authors: Hayley Syrad; Clare H Llewellyn; Laura Johnson; David Boniface; Susan A Jebb; Cornelia H M van Jaarsveld; Jane Wardle Journal: Sci Rep Date: 2016-06-20 Impact factor: 4.379
Authors: Laura Pimpin; Gina L Ambrosini; Clare H Llewellyn; Laura Johnson; Cornelia H M van Jaarsveld; Susan A Jebb; Jane Wardle Journal: Am J Clin Nutr Date: 2013-09-18 Impact factor: 7.045
Authors: Nida Ziauddeen; Eva Almiron-Roig; Tarra L Penney; Sonja Nicholson; Sara F L Kirk; Polly Page Journal: Nutrients Date: 2017-12-02 Impact factor: 5.717