Abstract MP67: Reduction in Calories Purchased by Employees Two Years After Implementation of Cafeteria Traffic-light Labels and Choice Architecture
Bibliographic record
Abstract
Background: Point-of-purchase strategies, such as traffic-light labels and choice architecture, promote healthy food choices. However, there is little research to determine if these interventions reduce caloric intake and prevent weight gain. Methods: We previously demonstrated that a worksite cafeteria traffic-light labeling and choice architecture intervention increased employees’ green (healthy) purchases and reduced red (unhealthy) purchases over 2 years. The objective of the current study is to determine if the intervention reduced calories purchased. We analyzed cafeteria purchases of 5,695 employees who visited the cafeteria during the 3-mo baseline period (Dec 2009-Feb 2010) and the 24-mo intervention period (March 2010-Feb 2012). We compared mean calories purchased per transaction (kcal/transaction) during the baseline quarter to the kcal/transaction purchased during the same 1-year (Dec 2010-Feb 2011) and 2-year (Dec 2011-Feb 2012) quarters. All analyses were adjusted for employee age, gender, race/ethnicity, and job type. To assess potential impact of a change in purchased calories on weight, we analyzed the total calories purchased per quarter (kcal/quarter) by employees who visited the cafeteria frequently (≥36 times/quarter). We calculated the combined mean change from baseline in kcal/quarter at 1 and 2-years and divided this number by 90 days to estimate change in daily calories per employee. We predicted the effect of the change in daily calories on employees’ weight using a dynamic model of weight change (Hall, et al. Lancet , 2011). Results: Employees’ mean age was 34 yrs; 71% were female and 73% white. Mean kcal/transaction was 499.5 at baseline, 478.9 at 1 year, and 470.2 at 2 years (change from baseline to 2 years: -29.3 [95% CI, -33.7, -25.0], p<.001). The decrease in kcal/transaction at 2 years occurred for both food (-17.0, p<.001) and beverages (-17.6, p<.001). At 2 years compared to baseline, kcal/transaction increased for green-labeled items (13.3, p<.001) and decreased for red-labeled items (-42.0, p<.001). Among 461 employees with ≥36 transactions/quarter, mean total calories purchased during the baseline quarter was 37,198 kcal; this decreased by 4,380 kcal/quarter (p<.001) at 1 year and 5,666 kcal/quarter (p<.001) at 2 years relative to baseline. Assuming no other changes in employees’ dietary intake or activity, this equates to a reduction of 56 kcal/day; if maintained over time, the dynamic model of weight change predicts weight loss of 2.8 lbs at 1 year and 5.3 lbs at 3 years. Conclusions: A traffic-light labeling and choice architecture intervention reduced calories purchased by employees over 2 years. These findings have implications for helping employees manage their weight, particularly those who use the cafeteria regularly. Simple point-of-purchase interventions are important tools for addressing the obesity epidemic.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| 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 | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".