Accounting for misreporting when comparing energy intake across time in Canada.
Bibliographic record
Abstract
BACKGROUND: Estimates of energy intake are lower in 2015 compared with 2004. The difference observed is too large to be explained by a change in energy requirements or physical activity at the population level. Self-reported dietary intake is subject to misreporting and may explain part of this difference. The objectives of this study are to assess how misreporting has changed from 2004 to 2015 and to demonstrate how these changes may affect the interpretation of the national intake data of Canadians. DATA AND METHODS: Data from the 2004 Canadian Community Health Survey - Nutrition (CCHS - Nutrition) and the 2015 CCHS - Nutrition were used to estimate energy intake and requirements for all participants aged 2 or older. The ratio of energy intake to total energy expenditure requirements (EI:TEE) was used to categorize respondents as under-reporters (EI:TEE ⟨ 0.70), over-reporters (EI:TEE ⟩ 1.42) or plausible reporters (EI:TEE = 0.70 to 1.42). Descriptive analyses by category of respondent were conducted for respondents aged 2 or older who participated in the measured height and weight component. The main caloric sources that contributed to the difference in estimated energy requirements were used to show the impact of misreporting on the analysis. RESULTS: The prevalence of under-reporters was 7.5% higher in 2015 compared with 2004, while the prevalence of over-reporters was 7.4% lower. There was no change in the prevalence of plausible reporters. Estimated energy intake from participants categorized as plausible reporters showed a difference of 84 kcal from 2004 to 2015, compared with a difference of 250 kcal for the entire sample. Estimated energy intake was lower in 2015 compared with 2004 across all categories of respondents for many foods, including sugar-sweetened beverages and milk, and was higher for only pastries and nuts. DISCUSSION: Misreporting changes will affect analysis and should, at a minimum, be acknowledged when comparing 2015 with 2004. Using a comparable category of plausible reporters or adjusting for reporting status are options that will allow a better comparison of these two datasets.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
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 teacher head, 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".