The DOI matches its Crossref record; 64 of the 67 references it cites were found in a registry or an index.
The association of fast food consumption with poor dietary outcomes and obesity among children: is it the fast food or the remainder of the diet?
Open accessAbstract
Background Although fast food consumption has been linked to adverse health outcomes, the relative contribution of fast food itself compared with the rest of the diet to these associations remains unclear.Objective Our objective was to compare the independent associations with overweight/obesity or dietary outcomes for fast food consumption compared with dietary pattern for the remainder of intake.Design This cross-sectional analysis studied 4466 US children aged 2-18 y from NHANES 2007-2010. Cluster analysis identified 2 dietary patterns for the non-fast food remainder of intake: Western (50.3%) and Prudent. Multivariable-adjusted linear and logistic regression models examined the association between fast food consumption and dietary pattern for the remainder of intake and estimated their independent associations with overweight/obesity and dietary outcomes.Results Half of US children consumed fast food: 39.5% low-consumers (≤30% of energy from fast food) and 10.5% high-consumers (>30% of energy). Consuming a Western dietary pattern for the remainder of intake was more likely among fast food low-consumers (OR: 1.51; 95% CI: 1.24, 1.85) and high-consumers (OR: 2.21; 95% CI: 1.60, 3.05) than among nonconsumers. The remainder of diet was independently associated with overweight/obesity (β: 5.9; 95% CI: 1.3, 10.5), whereas fast food consumption was not, and the remainder of diet had stronger associations with poor total intake than did fast food consumption.Conclusions Outside the fast food restaurant, fast food consumers ate Western diets, which might have stronger associations with overweight/obesity and poor dietary outcomes than fast food consumption itself. Our findings support the need for prospective studies and randomized trials to confirm these hypotheses.
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“A recent analysis of NHANES 2007–2010 showed that half of US children, ages 2–18 years, consumed fast-food and 10.5 % were high consumers, with more than 30 % of their daily calories coming from fast-food restaurants [5].”
From Comparison of the nutrient content of children’s menu items at US restaurant chains, 2010–2014 (2015) · cites this paper as [5]
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“and the overall proportion of highly processed food in diets has grown (50,51).”
From Food Consumption and its Impact on Cardiovascular Disease: Importance of Solutions Focused on the Globalized Food System (2015) · cites this paper as [51]
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“Model 2 (including fast food and dietary pattern) 21 (28, 6) –12 (220, 25) –39 (246, 232)*** Vegetables(7)”
BackgroundIssues in dietary intake assessment of children and adolescents
Livingstone, M. B. E., Robson, P. J., & Wallace, J. M. W. (2004) · British Journal Of Nutrition · doi:10.1079/bjn20041169 · Cited by 915
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The USDA Automated Multiple-Pass Method Accurately Estimates Group Total Energy and Nutrient Intake
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“Scientific community is focusing on the nutritional qualities of food and their possible associations on the human health [91,92].”
Obesity and the food system transformation in Latin America
Popkin, B. M., & Reardon, T. (2018) · Obesity Reviews · doi:10.1111/obr.12694 · Cited by 629
Self-citationAnand, S. S., Hawkes, C., de Souza, R. J., Mente, A., Dehghan, M., Nugent, R., Zulyniak, M. A., Weis, T., Bernstein, A. M., Krauss, R. M., et al. (2015) · Journal of the American College of Cardiology · doi:10.1016/j.jacc.2015.07.050 · Cited by 507
“Snacking and snack foods have grown in frequency and number (43–48); eating frequency has increased; away-from-home eating in restaurants, in fast food outlets, and from take-out meals is increasing dramatically in LMIC; both at home and away-from-home eating increasingly involves fried and processed food (47,49); and…”
BackgroundSelf-citationPopkin, B. M. (2017) · Nutrition Reviews · doi:10.1093/nutrit/nuw064 · Cited by 341
Self-citationChanging diets and the transformation of the global food system
Vermeulen, S. J., Park, T., Khoury, C. K., & Béné, C. (2020) · Annals of the New York Academy of Sciences · doi:10.1111/nyas.14446 · Cited by 230
Metadata
- Authors
- Poti, J. M., Duffey, K. J., & Popkin, B. M.
- Affiliations
- University of North Carolina at Chapel Hill (US)
- Venue
- The American Journal of Clinical Nutrition
- Publisher
- Elsevier BV
- Published
- 2014-01
- Volume
- 99
- Issue
- 1
- Pages
- 162-171
- ISSN
- 0002-9165 (ISSN-L)
- PMC
- PMC3862453
- OpenAlex
- W2131271354
- Cited by
- 175
- References
- 67
- Citations by year
- 2026: 7 · 2025: 6 · 2024: 8 · 2023: 7 · 2022: 12 · 2021: 11 · 2020: 31 · 2019: 21 · 2018: 13 · 2017: 20 · 2016: 14 · 2015: 13 · 2014: 11
- FWCI
- 12.92
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Licence
- Locations
- American Journal of Clinical Nutrition (publishedVersion)
- Europe PMC (PubMed Central) (publishedVersion)
- PubMed Central (publishedVersion)
- PubMed (publishedVersion)
- Funders
- National Institutes of Health (2r24hd050924-06)
- National Heart, Lung, and Blood Institute (R01HL104580)
- National Institute of Diabetes and Digestive and Kidney Diseases (T32DK007686)
- Eunice Kennedy Shriver National Institute of Child Health and Human Development (R24 HD-050924, 5R24 HD050924)
- Topics
- Health Sciences › Medicine › Public Health, Environmental and Occupational Health › Obesity, Physical Activity, Diet
- Health Sciences › Medicine › Public Health, Environmental and Occupational Health › Nutritional Studies and Diet
- Health Sciences › Nursing › Nutrition and Dietetics › Nutrition, Health and Food Behavior
- Keywords
- fast food consumption, childhood obesity, overweight, dietary habits, Western diet, prudent diet, dietary intake, children, NHANES
- MeSH terms
- Adolescent, Energy Intake, Child, Child, Preschool, Cross-Sectional Studies, Diet, Feeding Behavior, Humans, Nutrition Surveys, Obesity, Regression Analysis, Restaurants, Socioeconomic Factors, Nutrition Assessment, Body Mass Index, Prevalence, Multivariate Analysis, Cluster Analysis, Fast Foods
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