Traffic light labelling could prevent mortality from noncommunicable diseases in Canada: A scenario modelling study

Autoři: Marie-Eve Labonté aff001;  Teri E. Emrich aff001;  Peter Scarborough aff002;  Mike Rayner aff002;  Mary R. L’Abbé aff001
Působiště autorů: Department of Nutritional Sciences, Faculty of Medicine, University of Toronto, Toronto, ON, Canada aff001;  Nuffield Department of Population Health, University of Oxford, Oxford, Oxfordshire, United Kingdom aff002
Vyšlo v časopise: PLoS ONE 14(12)
Kategorie: Research Article
doi: 10.1371/journal.pone.0226975



Traffic-light labelling (TLL) is a promising front-of-pack system to help consumers make informed dietary choices. It has been shown that adopting TLL in Canada, through an optimistic scenario of avoiding, if possible, foods with red traffic lights, could effectively reduce Canadians’ intakes of energy, total fat, saturated fat, and sodium by 5%, 13%, 14% and 6%, respectively. However, the potential health impact of adopting TLL has not been determined in the North American context.


This study modelled the potential impact of adopting TLL on mortality from noncommunicable diseases (NCDs) in Canada, due to the previously predicted improved nutrient intakes.


Investigators used data from adults (n = 19,915) in the 2004 nationally representative Canadian Community Health Survey (CCHS)-Cycle 2.2. Nutrient amounts in foods consumed by CCHS respondents were profiled using the 2013 United Kingdom’s TLL criteria. Whenever possible, foods assigned at least one red light (non-compliant foods) were replaced with similar, but compliant, foods identified from a Canadian brand-specific food database. Respondents’ nutrient intakes were calculated under the original CCHS scenario and the counterfactual TLL scenario, and entered in the Preventable Risk Integrated ModEl (PRIME) to estimate the health impact of adopting TLL. The primary outcome was the number of deaths attributable to diet-related NCDs that could be averted or delayed based on the TLL scenario compared with the baseline scenario.


PRIME estimated that 11,715 deaths (95% CI 10,500–12,865) per year due to diet-related NCDs, among which 72% are specifically related to cardiovascular diseases, could be prevented if Canadians avoided foods labelled with red traffic lights. The reduction in energy intakes would by itself save 10,490 deaths (9,312–11,592; 90%).


This study, although depicting an idealistic scenario, suggests that TLL (if used to avoid red lights when possible) could be an effective population-wide intervention to improve NCD outcomes in Canada.

Klíčová slova:

Canada – Cardiovascular diseases – Death rates – Fats – Food consumption – Medical risk factors – Nutrients


1. Wartella EA, Lichtenstein AH, Boon CS. Examination of Front-of-Package Nutrition Rating Systems and Symbols: Phase I Report. Institute of Medicine (IOM). Washington, D.C.: The National Academies Press; 2010 [Cited 2016 November 21]. Available from:

2. Emrich TE, Qi Y, Mendoza JE, Lou W, Cohen JE, L'Abbe M R. Consumer perceptions of the Nutrition Facts table and front-of-pack nutrition rating systems. Appl Physiol Nutr Metab. 2014;39(4):417–24. doi: 10.1139/apnm-2013-0304 24669982

3. Gorton D, Ni Mhurchu C, Chen MH, Dixon R. Nutrition labels: a survey of use, understanding and preferences among ethnically diverse shoppers in New Zealand. Public Health Nutr. 2009;12(9):1359–65. doi: 10.1017/S1368980008004059 19087382

4. Feunekes GI, Gortemaker IA, Willems AA, Lion R, van den Kommer M. Front-of-pack nutrition labelling: testing effectiveness of different nutrition labelling formats front-of-pack in four European countries. Appetite. 2008;50(1):57–70. doi: 10.1016/j.appet.2007.05.009 17629351

5. Maubach N, Hoek J, Mather D. Interpretive front-of-pack nutrition labels. Comparing competing recommendations. Appetite. 2014;82:67–77. doi: 10.1016/j.appet.2014.07.006 25038407

6. Cecchini M, Warin L. Impact of food labelling systems on food choices and eating behaviours: a systematic review and meta-analysis of randomized studies. Obes Rev. 2016;17(3):201–10. doi: 10.1111/obr.12364 26693944

7. Hawley KL, Roberto CA, Bragg MA, Liu PJ, Schwartz MB, Brownell KD. The science on front-of-package food labels. Public Health Nutr. 2013;16(3):430–9. doi: 10.1017/S1368980012000754 22440538

8. Egnell M, Talati Z, Hercberg S, Pettigrew S, Julia C. Objective Understanding of Front-of-Package Nutrition Labels: An International Comparative Experimental Study across 12 Countries. Nutrients. 2018;10(10). doi: 10.3390/nu10101542 30340388

9. Ni Mhurchu C, Volkova E, Jiang Y, Eyles H, Michie J, Neal B, et al. Effects of interpretive nutrition labels on consumer food purchases: the Starlight randomized controlled trial. Am J Clin Nutr. 2017;105(3):695–704. doi: 10.3945/ajcn.116.144956 28148503

10. Temple NJ. Front-of-package food labels: A narrative review. Appetite. 2019;144:104485. doi: 10.1016/j.appet.2019.104485 31605724

11. Talati Z, Egnell M, Hercberg S, Julia C, Pettigrew S. Food Choice Under Five Front-of-Package Nutrition Label Conditions: An Experimental Study Across 12 Countries. Am J Public Health. 2019:e1–e6. doi: 10.2105/AJPH.2019.305319 31622139

12. Kleef EV, Dagevos H. The growing role of front-of-pack nutrition profile labeling: a consumer perspective on key issues and controversies. Crit Rev Food Sci Nutr. 2015;55(3):291–303. doi: 10.1080/10408398.2011.653018 24915389

13. Scarborough P, Harrington RA, Mizdrak A, Zhou LM, Doherty A. The Preventable Risk Integrated ModEl and Its Use to Estimate the Health Impact of Public Health Policy Scenarios. Scientifica (Cairo). 2014;2014:748750. doi: 10.1155/2014/748750 25328757

14. Sacks G, Veerman JL, Moodie M, Swinburn B. 'Traffic-light' nutrition labelling and 'junk-food' tax: a modelled comparison of cost-effectiveness for obesity prevention. Int J Obes (Lond). 2011;35(7):1001–9. doi: 10.1038/ijo.2010.228 21079620

15. Egnell M, Crosetto P, d'Almeida T, Kesse-Guyot E, Touvier M, Ruffieux B, et al. Modelling the impact of different front-of-package nutrition labels on mortality from non-communicable chronic disease. Int J Behav Nutr Phys Act. 2019;16(1):56. doi: 10.1186/s12966-019-0817-2 31307496

16. Scarborough P, Matthews A, Eyles H, Kaur A, Hodgkins C, Raats MM, et al. Reds are more important than greens: how UK supermarket shoppers use the different information on a traffic light nutrition label in a choice experiment. Int J Behav Nutr Phys Act. 2015;12:151. doi: 10.1186/s12966-015-0319-9 26652916

17. Balcombe K, Fraser I, Falco SD. Traffic lights and food choice: A choice experiment examining the relationship between nutritional food labels and price. Food Policy. 2010;35(3):211–20. doi: 10.1016/j.foodpol.2009.12.005

18. Thorndike AN, Sonnenberg L, Riis J, Barraclough S, Levy DE. A 2-phase labeling and choice architecture intervention to improve healthy food and beverage choices. Am J Public Health. 2012;102(3):527–33. doi: 10.2105/AJPH.2011.300391 22390518

19. Thorndike AN, Riis J, Sonnenberg LM, Levy DE. Traffic-light labels and choice architecture: promoting healthy food choices. Am J Prev Med. 2014;46(2):143–9. doi: 10.1016/j.amepre.2013.10.002 24439347

20. Hieke S, Wilczynski P. Colour Me In—an empirical study on consumer responses to the traffic light signposting system in nutrition labelling. Public Health Nutr. 2012;15(5):773–82. doi: 10.1017/S1368980011002874 22115180

21. Emrich TE, Qi Y, Lou WY, L'Abbe MR. Traffic-light labels could reduce population intakes of calories, total fat, saturated fat, and sodium. PLoS One. 2017;12(2):e0171188. doi: 10.1371/journal.pone.0171188 28182630

22. Health Canada, Office of Nutrition Policy and Promotion, Health Products and Food Branch. Canadian Community Health Survey Cycle 2.2, Nutrition (2004): A Guide to Accessing and Interpreting the Data. Ottawa, Ontario: Health Canada; 2006 [Cited 2017 April 26]. Available from:

23. Béland Y, Dale V, Dufour J, Hamel M. The Canadian Community Health Survey: Building on the Success from the Past. In: Proceedings of the American Statistical Association Joint Statistical Meeting, Section on Survey Research Methods, 2–6 August 2005. Minneapolis, MN: American Statistical Association; 2005. pp. 2738–2746.

24. United States Department of Agriculture, Agricultural Research Service. AMPM—USDA Automated Multiple-Pass Method [Cited 2015 October 8]. Available from:

25. Health Canada. The Canadian Nutrient File. Nutrition Research Division. Ottawa (ON): Health Canada; 2015 [Cited 2018 February 26]. Available from:

26. United States Department of Agriculture, Agricultural Research Service. National Nutrient Database for Standard Reference Release 19. [Cited 2015 October 8]. Database: [Internet]. Available from:

27. Government of UK—Department of Health, Food Standards Agency, Welsh Government, The Scottish Government. Guide to Creating a Front of Pack (FoP) Nutrition Label for Pre-packed Products Sold through Retail Outlets. 2013 June [Cited 2015 February 19]. Available from:

28. Schermel A, Emrich TE, Arcand J, Wong CL, L'Abbe M R. Nutrition marketing on processed food packages in Canada: 2010 Food Label Information Program. Appl Physiol Nutr Metab. 2013;38(6):666–72. doi: 10.1139/apnm-2012-0386 23724885

29. Statistics Canada. Table 051–0001—Estimates of population, by age group and sex for July 1, Canada, provinces and territories, annual (persons unless otherwise noted); 2016 [Cited 2016 January 27]. Database: CANSIM [Internet]. Available from:

30. Statistics Canada. Table 102–0522—Deaths, by cause, Chapter II: Neoplasms (C00 to D48), age group and sex, Canada, annual (number); 2016 [Cited 2016 January 29]. Database: CANSIM [Internet]. Available from:

31. Statistics Canada. Table 102–0524—Deaths, by cause, Chapter IV: Endocrine, nutritional and metabolic diseases (E00 to E90), age group and sex, Canada, annual (number); 2016 [Cited 2016 January 29]. Database: CANSIM [Internet]. Available from:

32. Statistics Canada. Table 102–0529—Deaths, by cause, Chapter IX: Diseases of the circulatory system (I00 to I99), age group and sex, Canada, annual (number); 2016 [Cited 2016 January 27]. Database: CANSIM [Internet]. Available from:

33. Statistics Canada. Table 102–0531—Deaths, by cause, Chapter XI: Diseases of the digestive system (K00 to K93), age group and sex, Canada, annual (number); 2016 [Cited 2016 January 29]. Database: CANSIM [Internet]. Available from:

34. Statistics Canada. Table 102–0534—Deaths, by cause, Chapter XIV: Diseases of the genitourinary system (N00 to N99), age group and sex, Canada, annual (number); 2016 [Cited 2016 January 29]. Database: CANSIM [Internet]. Available from:

35. SAS [computer program]. Version 9.3. Cary, NC: SAS Institute; 2011.

36. Software for Intake Distribution Estimation (SIDE) [computer program]. Version 1.11. Ames, IA: Iowa State University; 2001.

37. Statistics Canada. Canadian Community Health Survey (CCHS) Cycle 2.2 (2004) Nutrition–General Health (Including Vitamin & Mineral Supplements) & 24-Hour Dietary Recall Components: User Guide. Ottawa: 2008 April [Cited 2017 April 26]. Available from:

38. Hawkes C, Smith TG, Jewell J, Wardle J, Hammond RA, Friel S, et al. Smart food policies for obesity prevention. Lancet. 2015;385(9985):2410–21. doi: 10.1016/S0140-6736(14)61745-1 25703109

39. Health Canada. Toward Front-of-Package Nutrition Labels for Canadians: Consultation Document. 2016 [Cited 2017 February 22]. Available from:

40. Raine KD. Determinants of healthy eating in Canada: an overview and synthesis. Can J Public Health. 2005;96 Suppl 3:S8–14, S8-5.

41. Lee A, Mhurchu CN, Sacks G, Swinburn B, Snowdon W, Vandevijvere S, et al. Monitoring the price and affordability of foods and diets globally. Obes Rev. 2013;14 Suppl 1:82–95. doi: 10.1111/obr.12078 24074213

42. Kanter R, Vanderlee L, Vandevijvere S. Front-of-package nutrition labelling policy: global progress and future directions. Public Health Nutr. 2018;21(8):1399–408. doi: 10.1017/S1368980018000010 29559017

43. Grunert KG, Wills JM. A review of European research on consumer response to nutrition information on food labels. J Public Health. 2007;15:385–99. doi: 10.1007/s10389-007-0101-9

Článek vyšel v časopise


2019 Číslo 12