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Are Foods of Higher Nutritional Quality More Expensive Than Their Less Healthy Counterparts? An Analysis of Canadian Packaged Foods

2016· article· en· W2574724525 on OpenAlexafffundabout
Marie‐Ève Labonté, Sheida Noorhosseini, Jodi T. Bernstein, Mavra Ahmed, Mary R. L’Abbé

Bibliographic record

VenueThe FASEB Journal · 2016
Typearticle
Languageen
FieldMedicine
TopicNutritional Studies and Diet
Canadian institutionsUniversity of Toronto
FundersCanadian Institutes of Health Research
KeywordsFortificationNutrientPopulationFood supplyConfidence intervalAgricultural scienceFood scienceMealEnvironmental healthMedicineToxicologyBusinessMathematicsBiologyStatistics

Abstract

fetched live from OpenAlex

Price‐related differences in the nutritional quality of food products may create unintended disparities in healthy food availability between different socioeconomic segments of the population. This study assessed whether healthier products are more expensive than less healthy products within specific food categories in the Canadian food supply. Data on nutritional composition and price were obtained from the University of Toronto Food Label Information Program (FLIP) 2013 database, which contains information on n=15,401 packaged products from the four largest national retailers by sales. Ready‐to‐eat breakfast cereals (n=250) and yogurts (n=236) were included in the present analyses. The Food Standards Australia New Zealand Nutrient Profiling Scoring Criterion (FSANZ‐NPSC) was used to calculate a summary score of the healthfulness of each product based on its content of nutrients to limit (e.g. sodium) and nutrients to encourage (e.g. fibre). Additionally, food products were classified either as “healthier” or “less healthy” based on the established cutoff score in the FSANZ‐NPSC model. The Student's t‐test was used to compare different price measures (price per 100 g, per serving, and per 100 Kcal) between “healthier” and “less healthy” breakfast cereals and yogurts. “Healthier” breakfast cereals had a higher price per serving than breakfast cereals of lower nutritional quality (geometric mean [95% confidence interval] = CAD $0.53 [0.49–0.57] vs. 0.44 [0.41–0.47], respectively, P =0.0004). Price per 100 g and price per 100 Kcal did not differ according to the degree of healthfulness of breakfast cereals (both P ≥0.60). “Healthier” yogurts had a lower price per serving and price per 100 g than yogurts of lower nutritional quality (per serving: CAD $0.82 [0.77–0.87] vs. 1.13 [0.91–1.40], respectively, P =0.006; per 100g: CAD $0.67 [0.64–0.70] vs. 0.81 [0.72–0.92], P =0.03), but a higher price per 100 Kcal (CAD $0.93 [0.88–0.98] vs. 0.61 [0.57–0.65], P <0.0001). These data suggest that healthier food products are not necessarily more expensive than less healthy products. Importantly, the relationship between the healthfulness of foods and their price varies depending on the type of food products evaluated and the selected price measures. These factors must be taken into consideration when communicating research results to a general audience. Support or Funding Information Canadian Institutes of Health Research (CIHR) Fellowship (MEL); CIHR Open Operating Grant (ML); and Burroughs Wellcome Fund – Innovation in Regulatory Science (ML)

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.025
Threshold uncertainty score0.179

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.010
Science and technology studies0.0020.001
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.088
GPT teacher head0.344
Teacher spread0.256 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations1
Published2016
Admission routes3
Has abstractyes

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