The Relationship between Diet Costs and Dietary Adequacy: A Scoping Review of Measures and Methods with a Focus on Cost Estimation using Food Supply Data
Bibliographic record
Abstract
BACKGROUND: "Diet cost" refers to a methodological approach developed by Drewnowski et al. to estimate individual daily diet costs, where cost vectors are derived by matching prices from food supply data to the food sources of reported intakes from dietary assessment tools. The dietary assessment method and food price collection approach have been found to vary diet cost estimates. There is a need to better understand how food supply prices might be better standardized and attached to price individuals' diets. OBJECTIVES: To conduct a scoping review to examine Drewnowski's diet cost method, with a focus on a detailed description and charting of cost estimation measures and methods used to price individuals' consumed diets. METHODS: Five databases were searched from the inception of each database to March 2023. Included articles comprised analyses of individual-level dietary assessment data matched to food prices to assign estimates of individual daily diet costs. RESULTS: A total of 55 articles were included, published between 1999 and 2022 from 17 countries. In all studies, cost estimates were intended to be representative of price exposures among individual respondents' dietary assessment data. All studies derived cost estimates from separately collected food prices. 34 (62%) of included articles collected food prices from retail (supermarket) audits. A minority of studies (19, 35%) reported the number of food prices used to cost diets, and those varied widely, ranging from 57 to nearly 4600 distinct food prices per study. CONCLUSIONS: In the absence of a standardized approach to study the relationship between diet costs and dietary adequacy, this scoping review has described methodological concepts and parameters used to price individuals' consumed diets. Our review shows that despite common arithmetic to calculate cost vectors, there is substantial variation in the methods used to select and attach prices from the food supply to self-reported dietary intake assessments.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.051 | 0.261 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.008 | 0.011 |
| Bibliometrics | 0.039 | 0.036 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.008 | 0.007 |
| Open science | 0.004 | 0.003 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".