ArticleJAMA network open2026
Unhealthy Food Television Advertising and Body Weight in Mexican Children.
Article in JAMA network open, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
10 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Importance: Exposure to television advertisements for unhealthy food and beverages has been associated with poor dietary habits and childhood obesity. In Mexico, most school-aged children are regularly exposed to advertisements. Objective: To examine the association of removing television advertisements of unhealthy food and beverages with body weight among school-aged youth. Design, Setting, and Participants: This decision analytical model used a simulation model based on nonlinear differential equations to estimate 1-year changes in energy intake and obesity by removing television advertisements for unhealthy foods among children and adolescents aged 10 to 17 years. The study used national, representative survey waves from 2022 and 2023 (data collected between September and December of each year) of nonpregnant, nonlactating youths aged 10 to 17 years in Mexico with a plausible body mass index. Data were analyzed from May to December 2025. Exposure: Complete removal of television advertisements for unhealthy foods and beverages was simulated. For the main scenario, we assumed the intervention would apply to all children and adolescents exposed to television advertising (79.2%) regardless of the time of exposure. Sensitivity analyses varied adherence (30%-100%) and assumed a dose response between exposure time to advertisements and energy intake. Main Outcomes and Measures: Primary outcomes were changes in daily energy intake, body weight, body mass index, obesity prevalence, and obesity cases. Results: The analytic sample included 2834 children and adolescents, representing 17 735 608 individuals, with mean television viewing time of 99.8 min/d (95% CI, 92.5-107.2 min/d) and mean daily exposure to unhealthy food advertising of 2.8 min/d (95% CI, 2.6-3.0) min/d. Removing advertisements resulted in a projected mean decrease of 47 kcal/d (95% uncertainty interval [UI], 3-92 kcal/d), leading to a mean weight reduction of 1.2 kg (95% UI, 0.1-2.2 kg) per child in 1 year. Obesity prevalence decreased by 8.3% (95% UI, 0.3%-18.1%), equivalent to 271 000 cases averted. Results assumed no increase in digital marketing. Conclusions and Relevance: In this decision analytical model, removing unhealthy food and beverage advertisements from television was associated with a substantial reduction in body weight and obesity among children and adolescents in Mexico. These results suggest that strong legislation should be prioritized to protect child health.
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.