ArticlePublic health nutrition2020
The relationship between joining a US free trade agreement and processed food sales, 2002-2016: a comparative interrupted time-series analysis.
Article in Public health nutrition, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
3 citing papers in PubMed.
- Monitoring the impacts of international trade and investment agreements on food environments: a Canadian case study.Public health nutrition · 2026Article
- COVID-19, Trade, and Health: This Changes Everything? Comment on "What Generates Attention to Health in Trade Policy-Making? Lessons From Success in Tobacco Control and Access to Medicines: A Qualitative Study of Australia and the (Comprehensive and Progressive) Trans-Pacific Partnership".International journal of health policy and management · 2022Article
- Food environment solutions for childhood obesity in Latin America and among Latinos living in the United States.Obesity reviews : an official journal of the International Association for the Study of Obesity · 2021Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
objectiveTo examine changes in sales of highly processed foods, including infant formulas, in countries joining free trade agreements (FTAs) with the US.
designAnnual country-level data for food and beverage sales come from Euromonitor International. Analyses are conducted in a comparative interrupted time-series (CITS) framework using multivariate random-effects linear models, adjusted for key confounders: gross domestic product (GDP) per capita, percent of the population living in urban areas and female labor force participation rate. Memberships in other FTAs and investment treaties are also explored as possible confounders.
settingChanges are assessed between 2002 and 2016.
participantsTen countries joining US FTAs are compared with eleven countries without US FTAs in force; countries are matched on national income level, world region and World Trade Organization membership.
resultsAfter countries join a US FTA, sales are estimated to increase by: 0·89 (95 % CI 0·16, 1·6; P = 0·016) kg per capita per annum for ultra-processed products, 0·81 (95 % CI 0·47, 1·1; P < 0·001) kg per capita per annum for processed culinary ingredients and 0·17 (95 % CI 0·052, 0·29; P = 0·005) kg per capita under age 5 per annum for baby food. No significant change is estimated for minimally processed foods. In statistical models, large unexplained variations in country-specific trends suggest additional unmeasured country-level factors also impact sales trends following entry into US FTAs.
conclusionsThese findings strongly support the conclusion that joining US FTAs can contribute to detrimental changes in national dietary consumption that increase population risk of non-communicable diseases.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.