Soda versus Cereal and Sugar versus Fat: Drivers of Healthful Food Intake and the Impact of Diabetes Diagnosis
Bibliographic record
Abstract
This study examines how household members’ personal characteristics and key marketing factors affect the healthfulness of food purchased for in-home consumption; it further considers how food intake changes following a diagnosis of Type 2 diabetes in the household. Using a combination of grocery purchases over four years, survey data about health status, and the nutrition content of 13 of the largest packaged food categories, this study shows that households with higher education and nutrition interest consume fewer calories, sugar, and total carbohydrates, whereas those with higher self-control consume more, because they offset their lower intake of “unhealthy” categories (e.g., soft drinks) with higher intake of “healthy” categories (e.g., cereal). The consumption of sugar and carbohydrates decreases significantly in response to a diabetes diagnosis, whereas the intake of fat and sodium increases. Education, nutrition interest, and self-control are not associated with healthier changes in response to a diagnosis, but younger and higher-income households, as well as those in which the diabetes patient is female, make healthier changes. These findings have notable implications for marketers, consumers, consumer researchers, and public health professionals.
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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 | 0.002 | 0.002 |
| 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".