ArticleJAMA network open2020
Association of Chain Restaurant Advertising Spending With Obesity in US Adults.
Article in JAMA network open, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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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.
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Who cites it
4 citing papers in PubMed.
- Restaurant Advertising Expenditure Patterns in US Counties by Race, Ethnicity, and Income.Journal of urban health : bulletin of the New York Academy of Medicine · 2026Article
- An Indicator Measuring the Influence of the Online Public Food Environment: An Analytical Framework and Case Study.Frontiers in nutrition · 2022Article
- Nutrition and origin of US chain restaurant seafood.The American journal of clinical nutrition · 2021Article
- Ethnic differences in fast-food advertising exposure and body mass index among Asian American/Pacific Islander and White young adults.Obesity research & clinical practiceArticle
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Authors and funding
8 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Importance: Restaurants spend billions of dollars on marketing. However, little is known about the association between restaurant marketing and obesity risk in adults. Objective: To examine associations between changes in per capita county-level restaurant advertising spending over time and changes in objectively measured body mass index (BMI) for adult patients. Design, Setting, and Participants: This cohort study used regression models with county fixed effects to examine associations between changes in per capita county-level (370 counties across 44 states) restaurant advertising spending over time with changes in objectively measured body mass index (BMI) for US adult patients from 2013 to 2016. Different media types and restaurant types were analyzed together and separately. The cohort was derived from deidentified patient data obtained from athenahealth. The final analytic sample included 5 987 213 patients, and the analysis was conducted from March 2018 to November 2019. Exposure: Per capita county-level chain restaurant advertising spending. Main Outcomes and Measures: Individual-level mean BMI during the quarter. Results: The included individuals were generally older (37.1% older than 60 years), female (56.8%), and commercially insured (53.5%). For the full population of 29 285 920 person-quarters, there was no association between changes in all restaurant advertising per capita (all media types, all restaurants) and changes in BMI. However, restaurant advertising spending was positively associated with weight gain for patients in low-income counties but not in high-income counties. A $1 increase in quarterly advertising per capita across all media and restaurant types was associated with a 0.053-unit increase in BMI (95% CI, 0.001-0.102) for patients in low-income counties, corresponding to a 0.12% decrease in BMI at the 10th percentile of changes in county advertising spending vs a 0.12% increase in BMI at the 90th percentile. Conclusions and Relevance: The results of this study suggest that restaurant advertising is associated with modest weight gain among adult patients in low-income counties. To date, there has been no public policy action or private sector action to limit adult exposure to unhealthy restaurant advertising. Efforts to decrease restaurant advertising in low-income communities should be intensified and rigorously evaluated to understand their potential for increasing health equity.
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