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DDI2.5 XML CODEBOOK RECORD FOR STUDY NUMBER 6533 National Diet and Nutrition Survey Years 1-15, 2008-2023 653310.5255/UKDA-SN-6533-22 University of Cambridge, MRC Epidemiology Unit NatCen Social Research <a href="https://www.nationalarchives.gov.uk/information-management/re-using-public-sector-information/uk-government-licensing-framework/crown-copyright/" target="_blank">© Crown copyright</a> held jointly with the National Centre for Social Research Food Standards Agency in Northern IrelandDepartment of Health, Social Services and Public Safety (Northern Ireland)Food Safety Promotion Board (Safefood) (Ireland)Food Standards AgencyFood Standards ScotlandPublic Health England UK Data Service 12 August 2010 ECONOMIC ACTIVITYFRUITPHYSICAL ACTIVITIESHOURS OF WORKPREGNANCYMILKORGANIC FOODSCONSUMPTIONSOCIO-ECONOMIC STATUSSOCIAL CLASSSUPERVISORY STATUSAGEHOUSING TENURECOHABITATIONQUALIFICATIONSHEIGHT (PHYSIOLOGY)WEIGHT (PHYSIOLOGY)CHRONIC ILLNESSCOOKING FACILITIESADULTSNUTRIENTSEDIBLE FATSALCOHOL USEDIET AND EXERCISEFOODANTHROPOMETRIC DATAHOUSEHOLDSSPECIAL DIETSEMPLOYMENT HISTORYEMPLOYEESVEGETABLESCARBOHYDRATESSELF-EMPLOYEDSMOKINGVEGETARIANISMCLINICAL TESTS AND MEASUREMENTSCEREALSNATIONAL IDENTITYFURNISHED ACCOMMODATIONUNFURNISHED ACCOMMODATIONSTATUS IN EMPLOYMENTEMPLOYMENTETHNIC GROUPSDOMESTIC APPLIANCESFOOD STORAGESHOPSCOOKINGFREE SCHOOL MEALSMEDICAL DIETSSLIMMING DIETSHEALTHILL HEALTHACCIDENTSSURGERYBREAST-FEEDINGPHYSICAL MOBILITYPRESCRIPTION DRUGSVASCULAR DISEASESSMOKING CESSATIONEXPOSURE TO THE SUNSUN PROTECTIONHOLIDAYSDIARIESBLOODHAEMOGLOBINHEALTH STATUS General health and well-beingHealth behaviourSocial behaviour and attitudes Abstract copyright UK Data Service and data collection copyright owner.The National Diet and Nutrition Survey (NDNS) Rolling Programme (RP) began in 2008 and is designed to assess the diet, nutrient intake and nutritional status of the general population aged 1.5 years and over living in private households in the UK. (For details of the previous NDNS series, which began in 1992, see the documentation for studies 3481, 4036, 4243 and 5140.)The programme is funded by Public Health England (PHE), an executive agency of the Department of Health, and the UK Food Standards Agency (FSA).The NDNS RP is currently carried out by a consortium comprising NatCen Social Research (NatCen) (NatCen, contract lead) and the MRC Epidemiology Unit, University of Cambridge (scientific lead). The MRC Epidemiology Unit joined the consortium in November 2017. Until December 2018, the consortium included the MRC Elsie Widdowson Laboratory, Cambridge (former scientific lead). In Years 1 to 5 (2008/09 – 2012/13) the consortium also included the University College London Medical School (UCL).Survey activities at the MRC Epidemiology Unit are delivered with the support of the National Institute for Health Research (NIHR) Cambridge Biomedical Research Centre (IS-BRC-1215- 20014), comprising the NIHR BRC Nutritional Biomarker Laboratory and NIHR BRC Dietary Assessment and Physical Activity Group. The NIHR Cambridge Biomedical Research Centre is a partnership between Cambridge University Hospitals NHS Foundation Trust and the University of Cambridge, funded by the NIHR. <div>The NDNS RP provides the only source of high quality, nationally representative UK data on the types and quantities of foods consumed by individuals, from which estimates of nutrient intake for the population are derived. Results are used by Government to develop policy and monitor progress toward diet and nutrition objectives of UK Health Departments, for example work to tackle obesity and monitor progress towards a healthy, balanced diet as visually depicted in the <a title="Eatwell Guide" href="https://www.gov.uk/government/publications/the-eatwell-guide" style="background-color: rgb(255, 255, 255);">Eatwell Guide</a>. The NDNS RP provides an important source of evidence underpinning the <a title="Scientific Advisory Committee on Nutrition" href="https://www.gov.uk/government/groups/scientific-advisory-committee-on-nutrition" style="background-color: rgb(255, 255, 255);">Scientific Advisory Committee on Nutrition</a> (SACN) work relating to national nutrition policy. The food consumption data are also used by the FSA to assess exposure to chemicals in food, as part of the risk assessment and communication process in response to a food emergency or to inform negotiations on setting regulatory limits for contaminants.</div><div> </div>Further information is available from the gov.uk <a title="National Diet and Nutrition Survey" href="https://www.gov.uk/government/collections/national-diet-and-nutrition-survey">National Diet and Nutrition Survey</a> webpage. The study currently includes data and documentation covering Years 1-15 of the NDNS RP.The Yrs 9-11 food level dietary data are presented in separate annual files due to their size, rather than one combined file as for previous years. A syntax file is included for SPSS users to join these files together if required. Latest edition information For the 22nd edition (November 2025) replacement version of the data file 'ndns_yr12-15a_indiv' was deposited. Two documentation 'ndns_rp_yr12-15_uk_variable_list' and 'ndns_yrs9-11_variable_list_v4' have also been updated.Note to users, December 2025:The depositor has provided the following information:The labels on variables qeimd, qsimd, qwimd, qnimd in the dataset ndns_yr12-15a_indiv should be as follows: 1 ‘Most deprived’ to 5 ‘Least deprived’. They are currently 1 ‘Least deprived’ to 5 ‘Most deprived’.There is also incorrect labelling on SIMD_2012_quintile in the Yrs9-11 indiva datasets, although there are other SIMD variables, 2009 and 2016 which would show the discrepancy a crosstab be run on the two. For the Yrs9-11 data, dataset ndns_rp_yr9-11a_indiv_20211020 the variable SIMD_2012_quintile should display 1 ‘Most deprived’ to 5 ‘Least deprived’.The data will be resupplied in due course.Main Topics: The study includes dietary data obtained from an unweighed four-day food diary and information from a face-to-face interview (on food shopping, preparation and eating habits, smoking and drinking, physical activity,  general health), physical measurements (height and weight) and collection of a spot urine sample. A nurse interview is also conducted to collect information on prescribed medicines take physical and blood pressure measurements  and a blood sample.  Other measures may have been included in other years. February 2008 - July 202301 February 200831 July 2023 United Kingdom IndividualsNational Individuals aged 1.5 years and over living in private households in the UK. Numeric Repeated cross-sectional study Multi-stage stratified random sample DiariesClinical measurementsPhysical measurements and testsTelephone interview: Computer-assisted (CATI)Face-to-face interview: Computer-assisted (CAPI/CAMI)Self-administered questionnaire: Computer-assisted (CASI) The Data Collection is available to UK Data Service registered users subject to the <a href="https://ukdataservice.ac.uk/app/uploads/cd137-enduserlicence.pdf" target="_blank">End User Licence Agreement</a>.Commercial use of the data requires approval from the data owner or their nominee. The UK Data Service will contact you. See <restrctn> https://www.gov.uk/government/collections/national-diet-and-nutrition-survey https://www.food.gov.uk/research/national-diet-and-nutrition-survey-ndns http://www.natcen.ac.uk/our-research/research/national-diet-and-nutrition-survey-ndns/ https://www.ukdataservice.ac.uk/bounce?type=case-study&id=10 Usher-Smith, J., Sharp, S., Luben, R. and Griffin, S. (2018) 'Development and validation of lifestyle-based models to predict incidence of the most common potentially preventable cancers', Cancer Epidemiology, Biomarkers & Prevention, pii: cebp.0400.2018 https://doi.org/10.1158/1055-9965.EPI-18-0400 Coulthard, J., Palla, L. and Pot, G. (2017) 'Breakfast consumption and nutrient intakes in 4–18-year-olds: UK National Diet and Nutrition Survey Rolling Programme (2008–2012)', British Journal of Nutrition, 118, 4, 280-290, https://doi.org/10.1017/S0007114517001714. https://doi.org/10.1017/S0007114517001714 https://doi.org/10.1017/S0007114517001714 Smith, D.M., Vogel, C., Campbell, M., Alwan, N. and Moon, G. (2021) 'Adult diet in England: Where is more support needed to achieve dietary recommendations?', PLOS ONE 16(6): e0252877. doi:10.1371/journal.pone.0252877 https://doi.org/10.1371/journal.pone.0252877 Flynn, A.N., Hall, K.D., Courville, A.B., Rogers, P.J. and Brunstrom, J.M. (2022) 'Time to revisit the passive overconsumption hypothesis? Humans show sensitivity to calories in energy-rich meals', American Jnl of Clinical Nutrition, 116(2), pp.581–588. doi:10.1093/ajcn/nqac112 https://doi.org/10.1093/ajcn/nqac112 Flynn, A.N., Rogers, P.J., Hall, K.D., Courville, A.B. and Brunstrom, J.M. (2023) 'Reply to Robinson et al.', American Jnl of Clinical Nutrition, 117(3), pp.637–638. doi:10.1016/j.ajcnut.2022.10.009 https://doi.org/10.1016/j.ajcnut.2022.10.009 Flynn, A.N., Rogers, P.J. and Brunstrom, J.M. (2022) 'Sensitivity to, and ‘overcompensation’ for, calories in higher energy-dense meals: evidence in both restrained and unrestrained eaters', Appetite, 179, 106201 Flynn, A.N., Hall, K.D., Courville, A.B., Rogers, P.J. and Brunstrom, J. (2022) 'Sensitivity to energy density in humans: meal size decreases with energy density, but more consistently in meals with high energy density', Appetite, 169, 105483, 105493. Shewry, P. et al. (2023) 'Increasing fibre in white flour and bread: implications for health and processing', Food and Nutrition Bulletin, 48, pp.587-593 doi:10.1111/nbu.12648 https://doi.org/10.1111/nbu.12648 Phillips-Farfán, B.V. (2024) 'Selecting, optimizing and externally validating a preexisting machine-learning regression algorithm for estimating waist circumference', Comput Biol Med., 169:107909. doi:10.1016/j.compbiomed.2023.107909. https://doi.org/10.1016/j.compbiomed.2023.107909 Y. Yang, Y. Ke, X. Liu, Z. Zhang, R. Zhang, F. Tian, et al. Navigating the B vitamins: Dietary diversity, microbial synthesis, and human health. Cell Host Microbe 2024 Vol. 32 Issue 1 p.12-18. doi:0.1016/j.chom.2023.12.004 https://doi.org/10.1016/j.chom.2023.12.004 Usher-Smith, J., Sharp, S., Luben, R. and Griffin, S. (2018) 'Development and validation of lifestyle-based models to predict incidence of the most common potentially preventable cancers', Cancer Epidemiology, Biomarkers & Prevention, https://doi.org/10.1158/1055-9965.EPI-18-0400. https://doi.org/10.1158/1055-9965.EPI-18-0400 Marr, C., Breeze, P., and Caton, S. (2021) 'Examination of dietary intake of UK preschool children by varying carers: Evidence from the 2008-2016 UK National Diet and Nutrition Survey', British Journal of Nutrition, 1-35. doi:10.1017/S0007114521004712 https://doi.org/10.1017/S0007114521004712 Chawner, L. R., Blundell-Birtill, P. and Hetherington, M. M. (2021) 'Predictors of vegetable consumption in children and adolescents: analyses of the UK National Diet and Nutrition Survey (2008–2017)', British Journal of Nutrition, 126(2), 295-306. doi:10.1017/S0007114520004109 https://doi.org/10.1017/S0007114520004109 Owen, E. J. et al. (2021) 'Derivation and validation of a total fruit and vegetable intake prediction model to identify targets for biomarker discovery using the UK National Diet and Nutrition Survey, Journal of Nutrition. doi:10.1093/jn/nxaa406 https://doi.org/10.1093/jn/nxaa406 Kissock, K.R. et al. (2022) 'Aligning nutrient profiling with dietary guidelines: modifying the Nutri-Score algorithm to include whole grains', European Journal of Nutrition, 61. doi:10.1007/s00394-021-02718-6 https://link.springer.com/article/10.1007/s00394-021-02718-6 Perez-Cornago, A., et al (2021) 'Description of the updated nutrition calculation of the Oxford WebQ questionnaire and comparison with the previous version among 207,144 participants in UK Biobank', European Journal of Nutrition, 60(7), pp.4019-4030. https://pubmed.ncbi.nlm.nih.gov/33956230/ Piernas, C. et al. (2021) 'Describing a new food group classification system for UK biobank: analysis of food groups and sources of macro-and micronutrients in 208,200 participants', European Journal of Nutrition, 60(5), pp.2879-2890. https://pubmed.ncbi.nlm.nih.gov/33768317/ Dineva, M., Rayman, M.P., and Bath, S.C. (2020) 'Iodine status of consumers of milk-alternative drinks v. cows’ milk: data from the UK National Diet and Nutrition Survey', British Journal of Nutrition 126 (1), pp.28-36. doi:10.1017/S0007114520003876 https://doi.org/10.1017/S0007114520003876 Neill, H.R. et al. (2021) ‘Vitamin D biofortification of pork may offer a food-based strategy to increase Vitamin D Intakes in the UK Population’, Frontiers in Nutrition. doi:10.3389/fnut.2021.777364. https://doi.org/10.3389/fnut.2021.777364 Weir, R.R. et al. (2020) ‘Vitamin D3 content of cows’ milk produced in Northern Ireland and its efficacy as a vehicle for vitamin D fortification: a UK model’, International Journal of Food Sciences and Nutrition. doi:10.1080/09637486.2020.1837743 https://doi.org/10.1080/09637486.2020.1837743 Demirdjian, S.P. et al. (2024) 'Association between adiposity and iron status in women of reproductive age: data from the UK National Diet and Nutrition Survey (NDNS) 2008–2019', The Journal of Nutrition, 154(10), pp.3048-3059. doi:10.1016/j.tjnut.2024.08.026 https://doi.org/10.1016/j.tjnut.2024.08.026 https://oai.ukdataservice.ac.uk:8443/oai/provider 6533 2025-12-17T06:19:01Z ddi:codebook:2_5