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Intake24 Diet Recall Software

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Intake24 is an open-source web-based 24-hour diet recall system for assessing total dietary intake in people aged 11 years and over.[1][2][3]. The system was designed to be self-completed[4] and takes the user through the previous day asking them to record all foods and drinks they consumed. Instructions and login details can be emailed to participants allowing all data collection to be conducted remotely. The system incorporates a free text search function for entering foods which links to the system's food database. All foods and drinks within the database are linked to a nutrient composition code and portion size estimation method (food photograph, pack size or household measure)[5]. The original UK system is linked to the Composition of foods integrated dataset.[6] The nutrient composition of a user's intake can be downloaded as soon as the recall is submitted and the user has the option of receiving detailed feedback on their intake[5]

History

Intake24 contains over 2500 photographs for portion size assessment[1] based on portion size assessment tools originally developed for use with children. The development of these tools is detailed here.

In 2003 the Food Standards Agency (UK) commissioned Newcastle University to develop and pilot test food portion size tools for use in dietary assessment with children. Portion size assessment tools using 3 different media were developed: food photographs, food models and IPSAS (a computer-based version of the food photographs linked to nutrient composition codes and food weights).

The pilot study tested the accuracy with which children (n=200) aged 4 to 11 years were able to estimate the portion size of 22 commonly consumed foods. These foods were served to children in school and prepared to be specific weights and any food waste was recorded. The children were found to be able to estimate portion size with reasonable accuracy using the food photographs and IPSAS but not using the food models.[7]. Accuracy and precision of the portion size estimates improved as age increased[8]. IPSAS and the food photographs were further developed to cover the top 100 foods consumed in the UK and were tested against parent/researcher recorded 4 day weighed food diaries. For both tools children aged 11 years and over were found to give portion size estimates which were as accurate as their parent's with energy intake under-estimated by 3% on average in comparison with the weighed food diary[9][10].

The food photographs were published as a series of 3 food atlases for nutrition researchers to use with children of pre-school (18 months to 4 years), primary school (4 to 11 years) or secondary school age (11 to 16 years), and their parents[11].

As IPSAS was linked to both nutrient composition codes and food weights the potential for the system to be developed into a self-completed 24hr recall system (SCRAN)[1] for children aged 11 years and older was recognised by the Food Standards Agency who granted an extension to the project in order to adapt and test the system.

In 2014 Food Standards Agency Scotland now Food Standards Scotland (FSS) funded a series of projects to further develop, validate and test the prototype tool SCRAN24 (renamed Intake24) into a web-based 24hr dietary recall system suitable for use in people aged 11 years and over.

Development, validation and testing of Intake24

Intake24 was developed at Newcastle University as a collaboration between nutrition and human-computer interaction researchers. Initial development followed a user-centred approach with 4 iterative cycles of user interaction, evaluation and feedback. The evaluation included think aloud protocol, eye tracking and post-completion feedback interviews. Participants were asked to complete the system usability scale and with a score of 83[5] the usability of the system was rated "excellent"[12].

Intake24 was then tested in a relative validation (comparison study) against traditional interviewer-led multiple pass 24-hour recalls with 180 people aged 11-24 years. Each participant completed both an Intake24 24-hour recall and an interviewer-led 24-hour recall on the same day on four occasions during one calendar month[5]. The method of Bland-Altman was used to examine the accuracy and precision of mean daily energy and nutrient intakes reported in Intake24 compared to the interviewer-led recall. Intake24 was found to provide mean intakes for energy, carbohydrate, fat and protein that were close to those reported in the nutritionist administered interview, demonstrating good agreement for nutrients[4]. Energy intake was under-estimated by just 1% on average in comparison with the interviewer-led method. Mean intakes for all of the macronutrients and micronutrients (except non-milk extrinsic sugars) were within 4% of the interviewer-led recall[13].

Energy intakes reported using the system have also been validated against doubly labeled water (DLW) in a study of adults aged 40-65 years[5]. Energy intakes were found to be under-reported by around 25% compared to total energy expenditure measured by doubly-labelled water[5][14]. This is around the degree of under-reporting seen with more resource intensive methods such as the 4-day estimated-weight food diary which was previously used in the UK National Diet and Nutrition Survey[15].

Versions

Intake24 source code is open source and available under the terms of the Apache licence. The food database, food photographs and nutritional information are available under Creative Commons licence and Open Government Licence.

The system has been translated into a number of different languages and has been developed for different countries and populations through adaptations to the food lists, linking to local food composition data, food portion data and the addition of new portion size photographs. Currently there are versions available for use in:

  • United Kingdom
  • Australia
  • New Zealand
  • Denmark
  • Portugal
  • United Arab Emirates

Use of the system

The system is being used in the UK[16], New Zealand[17], Ireland[18], India[19], Sri-Lanka[19], Bangladesh[19], Australia[20], Portugal[21] and Denmark[21] to collect dietary data on adults[21][19][22], children[23][7], post-partum women[24], jockeys[18], older adults[25][17][16], overweight and obese individuals[26], people with type II diabetes[27] and in studies examining topics as diverse as gestational diabetes[24], food insecurity[22], sarcopenia[25], non-alcoholic fatty liver disease[28], Familial hypercholesterolaemia,[29] mindful eating,[30] treatment of type II diabetes,[27] school food standards,[23] weight-loss maintenance[21] and sarcopenia[25] in addition to it's use by the UK government in it's national surveillance programme[31].

Significant uses of Intake24 to date include the government run Scottish Health Survey[32] and the multicentre European EU Horizon 2020 project[21] NoHoW. In 2018 Intake24 was selected as the new method for dietary data collection in the UK government National Diet and Nutrition Survey Rolling Programme[31] and In 2020 Intake24 was selected for use in the Australian Intergeneration Health and Mental Health Survey[33]. It was also used in an evaluation of the impact of the Public Health England Sugar Smart marketing campaign[34].

Intake24 is currently being adapted for use in Sri Lanka, Bangladesh, India and Pakistan as part of the South Asia Biobank study[35][36]

The system design and development continues to be led by Ivan Poliakov at Newcastle University, in collaboration with the MRC Epidemiology Unit at Cambridge University and Action Lab, Monash University.

References

  1. 1.0 1.1 1.2 Schoeller, Dale; Westerterp, M (2017). Advances in the Assessment of Dietary Intake. CRC Press. Search this book on
  2. "DAPA Toolkit".
  3. "Nutritools".
  4. 4.0 4.1 Amoutzopoulos, B (2018). "Traditional methods v. new technologies–dilemmas for dietary assessment in large-scale nutrition surveys and studies: a report following an international panel discussion at the 9th International Conference on Diet and Activity Methods (ICDAM9), Brisbane, 3 September 2015". Journal of Nutritional Science. 7: e11. doi:10.1017/jns.2018.4. PMC 5906559. PMID 29686860.
  5. 5.0 5.1 5.2 5.3 5.4 5.5 Gazan, R; Vieux, F; Mora, S; Havard, S; Dubuisson, C (2021). "Potential of existing online 24-h dietary recall tools for national dietary surveys". Public Health Nutrition. 24 (16): 5361–5386. doi:10.1017/S1368980021003517. PMID 34392853 Check |pmid= value (help). Unknown parameter |s2cid= ignored (help)
  6. "Composition of foods integrated dataset (CoFID)".
  7. 7.0 7.1 Pérez-Rodrigo, C (2015). "Dietary assessment in children and adolescents: issues and recommendations". Nutricion Hospitalaria. 31 (3): 76–83. doi:10.3305/nh.2015.31.sup3.8755. PMID 25719775.
  8. Foster, E.; Matthews, J. N. S.; Lloyd, J.; L.; Mathers, J. C.; Nelson, M.; Barton, K. L.; Wrieden, W. L.; Cornelissen, P.; Harris, J.; Adamson, A. J. (January 2008). "Children's estimates of food portion size: the development and evaluation of three portion size assessment tools for use with children". British Journal of Nutrition. 99 (1): 175–184. doi:10.1017/S000711450779390X. PMID 17697426. Unknown parameter |s2cid= ignored (help)
  9. Foster, E.; Hawkins, A.; Simpson; Adamson, A. J. (January 2014). "Developing an interactive portion size assessment system (IPSAS) for use with children". Journal of Human Nutrition and Dietetics. 27: 18–25. doi:10.1111/jhn.12127. PMID 23682796. Unknown parameter |third1= ignored (help)
  10. Foster, Emma; Hawkins, Adrian; Barton; Stamp; Matthews, John N. S.; Adamson, Ashley J. (15 February 2017). "Development of food photographs for use with children aged 18 months to 16 years: Comparison against weighed food diaries – The Young Person's Food Atlas (UK)". PLOS ONE. 12 (2): e0169084. doi:10.1371/journal.pone.0169084. PMC 5310878. PMID 28199319. Unknown parameter |third3= ignored (help); Unknown parameter |third4= ignored (help)
  11. Young Person's Food Atlas—Secondary. E Foster, A Hawkins, A Adamson. Food Standards Agency: London, UK
  12. "Measuring and Interpreting System Usability Scale (SUS)". UIUX Trend. 31 May 2017.
  13. Bradley, Jennifer; Simpson, Emma; Poliakov; Matthews, John; Olivier; Adamson, Ashley; Foster, Emma (9 June 2016). "Comparison of INTAKE24 (an Online 24-h Dietary Recall Tool) with Interviewer-Led 24-h Recall in 11–24 Year-Old". Nutrients. 8 (6): 358. doi:10.3390/nu8060358. PMC 4924199. PMID 27294952. Unknown parameter |third5= ignored (help); Unknown parameter |third3= ignored (help)
  14. Foster, Emma; Lee, Clement; Imamura; Hollidge; Westgate; Venables; Poliakov; Rowland; Osadchiy; Bradley, Jennifer C.; Simpson, Emma L.; Adamson, Ashley J.; Olivier; Wareham; Forouhi; Brage (2019). "Validity and reliability of an online self-report 24-h dietary recall method (Intake24): a doubly labelled water study and repeated-measures analysis". Journal of Nutritional Science. 8: e29. doi:10.1017/jns.2019.20. PMC 6722486 Check |pmc= value (help). PMID 31501691. Unknown parameter |third9= ignored (help); Unknown parameter |third4= ignored (help); Unknown parameter |third8= ignored (help); Unknown parameter |third5= ignored (help); Unknown parameter |third3= ignored (help); Unknown parameter |third7= ignored (help); Unknown parameter |third13= ignored (help); Unknown parameter |third16= ignored (help); Unknown parameter |third15= ignored (help); Unknown parameter |third14= ignored (help); Unknown parameter |third6= ignored (help)
  15. "NDNS Appendix X Misreporting in the National Diet and Nutrition Survey Rolling Programme" (PDF). food.gov.uk. Retrieved 28 March 2022.
  16. 16.0 16.1 Shannon OM, Lee V, Bundy R, Gillings R, Jennings A, Stephan B, Hornberger M, Balanos G, Paddick SM, Hanson S, Hardeman W, Holmes R, Garner N, Aldred S, Siervo M, Mathers JC, Minihane AM (2021). "Feasibility and acceptability of a multi-domain intervention to increase Mediterranean diet adherence and physical activity in older UK adults at risk of dementia: protocol for the MedEx-UK randomised controlled trial". BMJ Open. 11 (2). e042823. doi:10.1136/bmjopen-2020-042823. PMC 7925921 Check |pmc= value (help). PMID 33550254 Check |pmid= value (help).
  17. 17.0 17.1 Tay, E; Barnett, D; Leilua; Kerse; Rowland; Rolleston; Waters; Edlin; Connolly; Hale, L; Pillai; Teh (2021). "The Diet Quality and Nutrition Inadequacy of Pre-Frail Older Adults in New Zealand". Nutrients. 13 (7): 2384. doi:10.3390/nu13072384. PMC 8308886 Check |pmc= value (help). PMID 34371894 Check |pmid= value (help). Unknown parameter |third9= ignored (help); Unknown parameter |third4= ignored (help); Unknown parameter |third8= ignored (help); Unknown parameter |third5= ignored (help); Unknown parameter |third3= ignored (help); Unknown parameter |third7= ignored (help); Unknown parameter |third12= ignored (help); Unknown parameter |third11= ignored (help); Unknown parameter |third6= ignored (help)
  18. 18.0 18.1 Dunne, A; Warrington; McGoldrick (2021). "Physical and Lifestyle Factors Influencing Bone Density in Jockeys: A Comprehensive Update of the Bone Density Status of Irish Jockeys". Int J Exerc Sci. 14 (6): 324–337. PMC 8136608 Check |pmc= value (help). PMID 34055173 Check |pmid= value (help). Unknown parameter |third2= ignored (help); Unknown parameter |third3= ignored (help)
  19. 19.0 19.1 19.2 19.3 Tandon, N; Gupta; Kapoor (2022). "Effects of a Lifestyle Intervention to Prevent Deterioration in Glycemic Status Among South Asian Women With Recent Gestational Diabetes: A Randomized Clinical Trial". JAMA Netw Open. 5 (3). e220773. doi:10.1001/jamanetworkopen.2022.0773. PMC 8892226 Check |pmc= value (help). PMID 35234881 Check |pmid= value (help). Unknown parameter |third2= ignored (help); Unknown parameter |third3= ignored (help)
  20. Whitton, C; Healy; Collins; Mullan; Rollo; Dhaliwal; Norman; Boushey; Delp; Zhu; McCaffrey; Kirkpatrick; Atyeo; Mukhtar; Wright; Ramos-García; Pollard; Kerr (2021). "Accuracy and Cost-effectiveness of Technology-Assisted Dietary Assessment Comparing the Automated Self-administered Dietary Assessment Tool, Intake24, and an Image-Assisted Mobile Food Record 24-Hour Recall Relative to Observed Intake: Protocol for a Randomized Crossover Feeding Study". JMIR Res Protoc. 10 (12). e32891. doi:10.2196/32891. PMC 8726032 Check |pmc= value (help). PMID 34924357 Check |pmid= value (help). Unknown parameter |third18= ignored (help); Unknown parameter |third9= ignored (help); Unknown parameter |third4= ignored (help); Unknown parameter |third8= ignored (help); Unknown parameter |third17= ignored (help); Unknown parameter |third2= ignored (help); Unknown parameter |third5= ignored (help); Unknown parameter |third10= ignored (help); Unknown parameter |third3= ignored (help); Unknown parameter |third7= ignored (help); Unknown parameter |third13= ignored (help); Unknown parameter |third16= ignored (help); Unknown parameter |third12= ignored (help); Unknown parameter |third11= ignored (help); Unknown parameter |third15= ignored (help); Unknown parameter |third14= ignored (help); Unknown parameter |third6= ignored (help)
  21. 21.0 21.1 21.2 21.3 21.4 Scott, Sarah; Duarte; Encantado; Evans; Harjumaa; Heitmann; Horgan; Larsen; Marques; Mattila; Matos; Mikkelsen; Palmeira; Pearson; Ramsey; Sainsbury; Santos; Sniehotta; Stalker; Teixera; Stubbs (2019). "The NoHoW protocol: a multicentre randomised controlled trial investigating an evidence-based digital toolkit for weight loss maintenance in 1600 European adults". BMJ Open. 9 (9). e029425. doi:10.1136/bmjopen-2019-029425. PMC 6773359 Check |pmc= value (help). PMID 31575569. Unknown parameter |third18= ignored (help); Unknown parameter |third9= ignored (help); Unknown parameter |third4= ignored (help); Unknown parameter |third8= ignored (help); Unknown parameter |third17= ignored (help); Unknown parameter |third19= ignored (help); Unknown parameter |third2= ignored (help); Unknown parameter |third5= ignored (help); Unknown parameter |third21= ignored (help); Unknown parameter |third20= ignored (help); Unknown parameter |third10= ignored (help); Unknown parameter |third3= ignored (help); Unknown parameter |third7= ignored (help); Unknown parameter |third13= ignored (help); Unknown parameter |third16= ignored (help); Unknown parameter |third12= ignored (help); Unknown parameter |third11= ignored (help); Unknown parameter |third15= ignored (help); Unknown parameter |third14= ignored (help); Unknown parameter |third6= ignored (help)
  22. 22.0 22.1 Shinwell, J; Bateson; Nettle; Pepper (2021). "Food insecurity and patterns of dietary intake in a sample of UK adults". British Journal of Nutrition: 1–8. doi:10.1017/S0007114521003810. PMID 34551836 Check |pmid= value (help). Unknown parameter |third4= ignored (help); Unknown parameter |third2= ignored (help); Unknown parameter |s2cid= ignored (help); Unknown parameter |third3= ignored (help)
  23. 23.0 23.1 Murphy M, Pallan M, Lancashire E, Duff R, Adamson AJ, Bartington S, Frew E, Griffin T, Hurley KL, Parry J, Passmore S, Ravaghi V, Sitch AJ, Spence S, Rowland MK, Wheeldon S, Adab P (2020). "The Food provision, cUlture and Environment in secondary schooLs (FUEL) study: protocol of a mixed methods evaluation of national School Food Standards implementation in secondary schools and their impact on pupils' dietary intake and dental health". BMJ Open. 10 (10). e042931. doi:10.1136/bmjopen-2020-042931. PMC 7569925 Check |pmc= value (help). PMID 33067305 Check |pmid= value (help).
  24. 24.0 24.1 Stevens, R; Kelaiditi; Myrissa (2021). "Exploration of the dietary habits, lifestyle patterns and barriers to healthy eating in UK post‐partum women". Nutrition Bulletin. 46 (1): 26-39. doi:10.1111/nbu.12483. Unknown parameter |third2= ignored (help); Unknown parameter |s2cid= ignored (help); Unknown parameter |third3= ignored (help)
  25. 25.0 25.1 25.2 Granic A, Hurst C, Dismore L, Davies K, Stevenson E, Sayer AA, Aspray T (2019). "Milk and resistance exercise intervention to improve muscle function in com-munity-dwelling older adults at risk of sarcopenia (MIlkMAN): protocol for a pi-lot study". BMJ Open. 9 (10). e031048. doi:10.1136/bmjopen-2019-031048. PMC 6797244 Check |pmc= value (help). PMID 31597652.
  26. Babateen, AM; Rubele; Shannon; Okello; Smith; McMahon; O'Brien; Wightman; Kennedy; Mathers; Siervo (2020). "Protocol and recruitment results from a 13-week randomized controlled trial comparing the effects of different doses of nitrate-rich beetroot juice on cognition, cerebral blood flow and peripheral vascular function in overweight and obese older people". Contemporary Clinical Trials Communications. 18: 100571. doi:10.1016/j.conctc.2020.100571. PMC 7212182 Check |pmc= value (help). PMID 32405570 Check |pmid= value (help). Unknown parameter |third2= ignored (help); Unknown parameter |third5= ignored (help); Unknown parameter |third10= ignored (help); Unknown parameter |third3= ignored (help); Unknown parameter |third7= ignored (help); Unknown parameter |third4= ignored (help); Unknown parameter |third11= ignored (help); Unknown parameter |third9= ignored (help); Unknown parameter |third8= ignored (help); Unknown parameter |third6= ignored (help)
  27. 27.0 27.1 "The RESULT study: REmote SUpport for Low-carbohydrate Treatment of type 2 diabetes" (PDF). University of Oxford, Nuffield Department of Primary Care Health Sciences.
  28. Haigh, L; McPherson; Mathers (2021). "Nutrigenetics-based intervention approach for adults with non-alcoholic fatty liver disease (NAFLD): study protocol for a randomised controlled feasibility trial". BMJ Open. 11 (4). e045922. doi:10.1136/bmjopen-2020-045922. Unknown parameter |third2= ignored (help); Unknown parameter |s2cid= ignored (help); Unknown parameter |third3= ignored (help)
  29. Kinnear FJ, Lithander FE, Searle A, Bayly G, Wei C, Stensel DJ, Thackray AE, Hunt L, Shield JP (2020). "Reducing cardiovascular disease risk among families with familial hypercholesterolaemia by improving diet and physical activity: a randomised controlled feasibility trial". BMJ Open. 10 (12). e044200. doi:10.1136/bmjopen-2020-044200. PMC 7772289 Check |pmc= value (help). PMID 33372081 Check |pmid= value (help).
  30. Seguias, L; Tapper (2022). "A Randomized Controlled Trial Examining the Effects of Mindful Eating and Eating without Distractions on Food Intake over a Three-Day Period". Nutrients. 14 (5): 1043. doi:10.3390/nu14051043. Unknown parameter |third2= ignored (help)
  31. 31.0 31.1 "Evaluation of change in dietary methodology in NDNS rolling programme: Stage 1". Public Health England. 22 September 2021 – via GOV.UK.
  32. "Scottish Health Survey".
  33. "Food Standards Australia New Zealand Annual Report 2020-2021". 29 October 2021. Retrieved 28 April 2022.
  34. Bradley, Jennifer; Gardner; Rowland; Fay; Mann; Holmes; Foster, Emma; Exley; Don Bosco; Hugueniot; Moynihan (December 2020). "Impact of a health marketing campaign on sugars intake by children aged 5–11 years and parental views on reducing children's consumption". BMC Public Health. 20 (1): 331. doi:10.1186/s12889-020-8422-5. PMC 7104521 Check |pmc= value (help). PMID 32223751 Check |pmid= value (help). Unknown parameter |third2= ignored (help); Unknown parameter |third5= ignored (help); Unknown parameter |third10= ignored (help); Unknown parameter |third3= ignored (help); Unknown parameter |third4= ignored (help); Unknown parameter |s2cid= ignored (help); Unknown parameter |third11= ignored (help); Unknown parameter |third9= ignored (help); Unknown parameter |third8= ignored (help); Unknown parameter |third6= ignored (help)
  35. "About Sout Asia Biobank". South Asia Biobank.
  36. Song, P; Gupta; Goon; Hasan; Mahmood; Pradeepa; Siddiqui; Frost; Kusuma; Miraldo; Sassi; Wareham; Ahmed; Anjana; Brage; Forouhi; Jha; Kasturiratne; Katulanda; Khawaja; Loh; Mridha; Kasturiratne; Kooner; Chambers (2021). "Data Resource Profile: Understanding the patterns and determinants of health in South Asians—the South Asia Biobank". International Journal of Epidemiology. 50 (3): 717–718e. doi:10.1093/ije/dyab029. PMC 8271208 Check |pmc= value (help). PMID 34143882 Check |pmid= value (help). Unknown parameter |third22= ignored (help); Unknown parameter |third18= ignored (help); Unknown parameter |third9= ignored (help); Unknown parameter |third4= ignored (help); Unknown parameter |third17= ignored (help); Unknown parameter |third25= ignored (help); Unknown parameter |third8= ignored (help); Unknown parameter |third24= ignored (help); Unknown parameter |third19= ignored (help); Unknown parameter |third23= ignored (help); Unknown parameter |third2= ignored (help); Unknown parameter |third5= ignored (help); Unknown parameter |third21= ignored (help); Unknown parameter |third20= ignored (help); Unknown parameter |third10= ignored (help); Unknown parameter |third3= ignored (help); Unknown parameter |third7= ignored (help); Unknown parameter |third13= ignored (help); Unknown parameter |third16= ignored (help); Unknown parameter |third12= ignored (help); Unknown parameter |third11= ignored (help); Unknown parameter |third15= ignored (help); Unknown parameter |third14= ignored (help); Unknown parameter |third6= ignored (help)

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