- Background
- Scoring Algorithm
- Scoring Algorithm Output
- Selected Publications: Research Uses of the HEFI-2019
- References
Canada’s Food Guide (CFG) 2019 includes dietary guidance both on healthy food choices and eating behaviors. The Healthy Eating Food Index (HEFI)-2019 is a scoring tool developed to measure adherence to recommendations on healthy food choices in CFG (Brassard, Elvidge Munene, St-Pierre, Guenther, et al. 2022). The HEFI-2019 has 10 components, of which 5 are based on the intake of foods, 1 on beverages, and 4 on nutrients. The total HEFI-2019 score has a maximum of 80 points.
Health Canada has a web page dedicated to Canada’s Food Guide Research Tools.
For the HEFI-2019, Health Canada has also made available a series of resources and files to assist in the calculation of scores. Notably, the data and other documents are available under the name The Healthy Eating Food Index 2019 on the Open Government data portal. These files are especially helpful to assist in the preliminary steps, i.e., the classification of foods and beverages, the addition of data on free sugars as well as data on reference amounts per gram of foods.
The goal of the hefi2019 code is to apply the HEFI-2019 scoring
algorithm to dietary constituents in the dataset provided by the user.
The original variables are kept in the output data set, along with new
variables including:
- density of intakes (i.e., ratios of dietary constituents);
- the HEFI-2019 component scores; and
- the total HEFI-2019 score.
See the development and evaluation articles for more details as well as information on classification of foods (Brassard, Elvidge Munene, St-Pierre, Guenther, et al. 2022; Brassard, Elvidge Munene, St-Pierre, Gonzalez, et al. 2022). Of note, when no foods, beverages or energy is reported, ratios are not calculated and a score of 0 is assigned to the corresponding components.
The scoring algorithm should ideally be applied to a dataset in the “long” format, where observations are rows and dietary constituents are columns. Other layouts are also possible.
| Participants | Food1 | Food2 | Food3 | Food… |
|---|---|---|---|---|
| 1 | 2 | 1 | 9 | … |
| 2 | 4 | 4 | 5 | … |
| 3 | 2 | 7 | 6 | … |
| 4 | 5 | 4 | 5 | … |
| 5 | 6 | 4 | 2 | … |
SAS and R versions of the scoring algorithm are available. Both versions will yield the same HEFI-2019 scores and output when applied to the same data.
A detailed example application of the HEFI-2019 for the Canadian Community Health Survey 2015 - Nutrition is presented in the Example_SAS_cchs folder.
The SAS code illustrates how to prepare data and how to calculate HEFI-2019 scores according to the population ratio method (Freedman et al. 2008) as well as based on measurement error-corrected dietary intakes using the National Cancer Institute multivariate method (Zhang et al. 2011).
- 01_CCHS2015_Data_preparation.sas: preparation of data files
- 02_CCHS2015_Descriptive1d.sas: population ratio method
- 03A_CCHS2015_DescriptiveU.sas: measurement error correction with the multivariate method
- 03B_CCHS2015_DescriptiveU.sas: estimation of usual intake distribution
A detailed example application of the HEFI-2019 for the Canadian Community Health Survey 2015 - Nutrition is presented in the Example_R_cchs folder.
The R code illustrates how to prepare data and how to calculate HEFI-2019 scores according to the population ratio method (Freedman et al. 2008) as well as based on measurement error-corrected dietary intakes using the National Cancer Institute multivariate method (Zhang et al. 2011).
- 01_CCHS2015_Data_preparation.md: preparation of data files
- 02_CCHS2015_Descriptive1d.md: population ratio method
- 03A_CCHS2015_DescriptiveU.md: measurement error correction with the multivariate method
- 03B_CCHS2015_DescriptiveU.md: preparation of distribution estimates based on simulation data and overview
A simple application for the R version is shown below.
You can install the released version of the hefi2019 from
GitHub with:
devtools::install_github("didierbrassard/hefi2019")The scoring algorithm is used by indicating the name of the input data
set and the name of each variable representing dietary constituents of
the HEFI-2019. In the case where a given dietary constituents was not
reported in an entire sample, a 0 can be assigned to that variable.
Upon execution, the title of the function is displayed.
# Install the hefi2019 scoring algorithm from GitHub, if not already done
devtools::install_github("didierbrassard/hefi2019")
# Load library
library(hefi2019)
# Apply the scoring algorithm to user-provided data
mydata_scored <-
hefi2019(indata = mydata,
vegfruits = "RA_vegfruits",
wholegrfoods = "RA_wholegrfoods",
nonwholegrfoods = "RA_nonwgfoods",
profoodsanimal = "RA_profoodsanimal",
profoodsplant = "RA_profoodsplant",
otherfoods = "RA_otherfoods",
waterhealthybev = "G_waterhealthybev",
unsweetmilk = "G_milk",
unsweetplantbevpro = "G_plantbevpro",
otherbeverages = "G_otherbeverages" ,
mufat = "G_mufa" ,
pufat = "G_pufa" ,
satfat = "G_sfa" ,
freesugars = "G_freesugars",
sodium = "MG_sodium",
energy = "energy"
)
## Healthy Eating Food Index-2019 Scoring Algorithm R version 1.5The scoring algorithm creates 10 variables for density of intakes: RATIO_VF, RATIO_WGTOT, RATIO_WGGR, RATIO_PRO, RATIO_PLANT, RATIO_BEV, RATIO_UNSFAT, RATIO_FA, SFA_PERC, SUG_PERC, and SODDEN.
The variable corresponding to the total HEFI-2019 is HEFI2019_TOTAL_SCORE and the 10 variables corresponding to each component of the HEFI-2019 are HEFI2019C1_VF, HEFI2019C2_WHOLEGR, HEFI2019C3_GRRATIO, HEFI2019C4_PROFOODS, HEFI2019C5_PLANTPRO, HEFI2019C6_BEVERAGES, HEFI2019C7_FATTYACID, HEFI2019C8_SFAT, HEFI2019C9_FREESUGARS, and HEFI2019C10_SODIUM.
Epidemiology & Health Outcomes Research
- Brassard, D., Manikpurage, H. D., Theriault, S., Arsenault, B. J., & Lamarche, B. (2022). Greater adherence to the 2019 Canada’s Food Guide recommendations on healthy food choices reduces the risk of cardiovascular disease in adults: a prospective analysis of UK Biobank data. Am J Clin Nutr, 116(6), 1748-1758.
Nutrition Surveillance
- Sebai, I., Nardocci, M., Ing, A., Fediuk, K., Chan, H. M., & Batal, M. (2025). Exploring the Association Between the Healthy Eating Food Index-2019 (HEFI-2019), the Canadian Healthy Eating Index 2007 (C-HEI 2007) and Health Among First Nation Adults Across Canada. Appl Physiol Nutr Metab.
- Blais, A., Ahmed, M., L’Abbe, M. R., Sellen, D., & Malik, V. (2025). Evaluating the Nutritional Quality of School Food Programs in Canada Compared to National Nutritional Guidelines. Appl Physiol Nutr Metab.
- Simpson, A., Fisher, M., Harrison, S., Morisset, A. S., Borghese, M. M., Braun, J. M., Bouchard, M. F., Saha, T., Panagiotopoulos, C., Booij, L., Morrison, K., & Ashley-Martin, J. (2025). Diet quality in relation to serum perfluoroalkyl substance concentrations in Canadian preadolescents. Environ Res, 279(Pt 2), 121790.
- Sebai, I., Ing, A., Nardocci Fusco, M., Fediuk, K., Sadik, T., Chan, H. M., & Batal, M. (2024). Eating traditional foods enhances diet quality among First Nations in Canada: an analysis using the Healthy Eating Food Index-2019 (HEFI-2019) and the Canadian Healthy Eating Index 2007 (C-HEI 2007). Appl Physiol Nutr Metab, 50, 1-13.
- Brassard, D., & Chevalier, S. (2023). Relationship between adherence to the 2019 Canada’s Food Guide recommendations on healthy food choices and nutrient intakes in older adults. J Nutr, 153(9), 2699-2708.
Randomized Controlled Trials
- Bernier, E., Plante, A. S., Lemieux, P., Robitaille, J., Lemieux, S., Desroches, S., Belanger-Gravel, A., Maheux-Lacroix, S., Weisnagel, S. J., Demers, S., Camirand Lemyre, F., Boulet, M., Baillargeon, J. P., & Morisset, A. S. (2023). Promoting healthy eating in early pregnancy in individuals at risk of gestational diabetes mellitus: does it improve glucose homeostasis? A study protocol for a randomized control trial. Front Nutr, 10, 1336509.
- Olstad, D. L., Beall, R., Spackman, E., Dunn, S., Lipscombe, L. L., Williams, K., Oster, R., Scott, S., Zimmermann, G. L., McBrien, K. A., Steer, K. J. D., Chan, C. B., Tyminski, S., Berkowitz, S., Edwards, A. L., Saunders-Smith, T., Tariq, S., Popeski, N., White, L., . . . Campbell, D. J. T. (2022). Healthy food prescription incentive programme for adults with type 2 diabetes who are experiencing food insecurity: protocol for a randomised controlled trial, modelling and implementation studies. BMJ Open, 12(2), e050006.
Sustainability
- Rochette, M., Rochefort, G., Laramee, C., Lapointe, A., Lemieux, S., Belanger-Gravel, A., Desroches, S., Provencher, V., & Lamarche, B. (2024). Local food procurement behavior and overall diet quality among adults in Quebec: results from the NutriQuebec project. Nutr J, 23(1), 143.
- Rochefort, G., Robitaille, J., Lemieux, S., Provencher, V., & Lamarche, B. (2024). Are the 2019 Canada’s Food Guide Recommendations on Healthy Food Choices Consistent with the EAT-Lancet Reference Diet from Sustainable Food Systems? J Nutr, 154(4), 1368-1375.
- Rochefort, G., Brassard, D., Desroches, S., Robitaille, J., Lemieux, S., Provencher, V., & Lamarche, B. (2023). Transitioning to sustainable dietary patterns: learnings from animal-based and plant-based dietary patterns in French Canadian adults. Frontiers in Nutrition, 10.
- Rochefort, G., Brassard, D., Paquette, M. C., Robitaille, J., Lemieux, S., Provencher, V., & Lamarche, B. (2022). Adhering to Canada’s Food Guide Recommendations on Healthy Food Choices Increases the Daily Diet Cost: Insights from the PREDISE Study. Nutrients, 14(18).
Validation Research and Methods
- Brassard, D., Presse, N., & Chevalier, S. (2025). Estimating the Effect of Adhering to the Recommendations of the 2019 Canada’s Food Guide on Health Outcomes in Older Adults: Protocol for a Target Trial Emulation. JMIR Res Protoc, 14:e65182.
- Panahimoghadam, S., Veugelers, P. J., Dabravolskaj, J., Tran, T., & Maximova, K. (2024). Comparing three summary indices to assess diet quality of Canadian children: a call for consensus. Front Nutr, 11, 1519829.
- Lee, J. J., Ahmed, M., Julia, C., Ng, A. P., Paper, L., Lou, W. Y., & L’Abbe, M. R. (2023). Examining the diet quality of Canadian adults and the alignment of Canadian front-of-pack labelling regulations with other front-of-pack labelling systems and dietary guidelines. Front Public Health, 11, 1168745.
- Hutchinson, J. M., Dodd, K. W., Guenther, P. M., Lamarche, B., Haines, J., Wallace, A., Perreault, M., Williams, T. E., Louzada, M., Jessri, M., Lemieux, S., Olstad, D. L., Prowse, R., Simpson, J. R., Vena, J. E., Szajbely, K. & Kirkpatrick, S. I. (2023). The Canadian Food Intake Screener for assessing alignment of adults’ dietary intake with the 2019 Canada’s Food Guide healthy food choices recommendations: scoring system and construct validity. Appl Physiol Nutr Metab, 48(8), 620-633.
- Mercier, A. P., Rochefort, G., Fortier, J., Parent, G., Provencher, V., Lemieux, S., & Lamarche, B. (2022). Development and Validation of a Short Questionnaire Assessing the Behavior of Local Food Procurement in Quebec, Canada. Curr Dev Nutr, 6(9), nzac097.
Brassard, D., L. A. Elvidge Munene, S. St-Pierre, A. Gonzalez, P. M. Guenther, M. Jessri, J. Vena, et al. 2022. “Evaluation of the Healthy Eating Food Index (HEFI)-2019 Measuring Adherence to Canada’s Food Guide 2019 Recommendations on Healthy Food Choices.” Journal Article. Appl Physiol Nutr Metab. https://doi.org/10.1139/apnm-2021-0416.
Brassard, D., L. A. Elvidge Munene, S. St-Pierre, P. M. Guenther, S. I. Kirkpatrick, J. Slater, S. Lemieux, et al. 2022. “Development of the Healthy Eating Food Index (HEFI)-2019 Measuring Adherence to Canada’s Food Guide 2019 Recommendations on Healthy Food Choices.” Journal Article. https://doi.org/10.1139/apnm-2021-0415.
Freedman, L. S., P. M. Guenther, S. M. Krebs-Smith, and P. S. Kott. 2008. “A Population’s Mean Healthy Eating Index-2005 Scores Are Best Estimated by the Score of the Population Ratio When One 24-Hour Recall Is Available.” Journal Article. J Nutr 138 (9): 1725–29. https://doi.org/10.1093/jn/138.9.1725.
Zhang, S., D. Midthune, P. M. Guenther, S. M. Krebs-Smith, V. Kipnis, K. W. Dodd, D. W. Buckman, J. A. Tooze, L. Freedman, and R. J. Carroll. 2011. “A New Multivariate Measurement Error Model with Zero-Inflated Dietary Data, and Its Application to Dietary Assessment.” Journal Article. Ann Appl Stat 5 (2B): 1456–87. https://doi.org/10.1214/10-AOAS446.