OP75 Catalysing globesity: an analysis of the impact of us free trade agreements on caloric intake from a natural experiment in canada using the synthetic control method
Bibliographic record
Abstract
Background Free trade and investment agreements (FTAs) are often implicated in the global pandemics of overweight, obesity, and related diseases. Concerns centre on how FTAs increase population exposure to unhealthy, high calorie diets rich in salt, sugar, and fat. Yet the empirical evidence to support these concerns is limited, both methodologically and substantively. Thus, few existing studies of FTAs and dietary change have accounted for unobserved confounding, and many were unable to differentiate the impact of FTAs from contemporaneous macroeconomic and policy changes. Moreover, few have examined any potential effect of FTAs on total caloric intake, despite its critical role in the aetiology of obesity. Here we address these limitations by analysing a unique natural experiment from the unanticipated implementation of the Canada-US Free Trade Agreement (CUSFTA) in 1989. Methods We use data from the UN Food and Agricultural Organisation and the synthetic control method to test the hypothesis that CUSFTA increased caloric intake in Canada. We also anlayse whether these changes were accompanied by increased US investment and imports in the Canadian food and beverage sector. Finally, we simulate the population impact on weight gain of these changes in caloric intake using the models developed by Hall and colleagues (2011) and data from the 1990 Canadian Health Promotion Survey. Results Our analysis identifies a 95.8 kilocalorie per capita per day increase in caloric intake after CUSFTA in Canada compared with the synthetic control. These changes coincided with a $1,820 million (95% CI: 1,179.2 to 2,464.1) increase in US investment in the Canadian food and beverage sector, and a $5,258.3 million (95% CI: 4,894.8 to 5,621.8) rise in food and beverage imports from the US. This estimated rise in caloric intake corresponds to an average individual weight gain of 5.7 kg for women and 5.1 kg for men aged 40 and with low physical activity levels, or 2.5 kg for women and 2.2 kg for men aged 40 and who are very active. Conclusion Our findings suggest that US FTA can substantially alter dietary behaviour by increasing caloric intake. FTA negotiations may be a critical window for shaping dietary behaviours to prevent overnutrition, obesity and related diseases.
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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 | 0.010 | 0.015 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.003 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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 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".