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Associations of the Local Food Environment with Diet Quality--A Comparison of Assessments based on Surveys and Geographic Information Systems: The Multi-Ethnic Study of Atherosclerosis
Open accessAbstract
There is growing interest in understanding how food environments affect diet, but characterizing the food environment is challenging. The authors investigated the relation between global diet measures (an empirically derived "fats and processed meats" (FPM) dietary pattern and the Alternate Healthy Eating Index (AHEI)) and three complementary measures of the local food environment: 1) supermarket density, 2) participant-reported assessments, and 3) aggregated survey responses of independent informants. Data were derived from the baseline examination (2000-2002) of the Multi-Ethnic Study of Atherosclerosis, a US study of adults aged 45-84 years. A healthy diet was defined as scoring in the top or bottom quintile of AHEI or FPM, respectively. The probability of having a healthy diet was modeled by each environment measure using binomial regression. Participants with no supermarkets near their homes were 25-46% less likely to have a healthy diet than those with the most stores, after adjustment for age, sex, race/ethnicity, and socioeconomic indicators: The relative probability of a healthy diet for the lowest store density category versus the highest was 0.75 (95% confidence interval: 0.59, 0.95) for the AHEI and 0.54 (95% confidence interval: 0.42, 0.70) for FPM. Similarly, participants living in areas with the worst-ranked food environments (by participants or informants) were 22-35% less likely to have a healthy diet than those in the best-ranked food environments. Efforts to improve diet may benefit from combining individual and environmental approaches.
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“Four larger cross-sectional studies found that greater accessibility to neighborhood supermarkets (presence, number, or distance) was associated with more healthful dietary habits284–287; 1 small cross-sectional study288 and the only large longitudinal study289 did not.”
From Population Approaches to Improve Diet, Physical Activity, and Smoking Habits: A Scientific Statement From the American Heart Association (2012) · cites this paper as [286]
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Metadata
- Authors
- Moore, L. V., Diez Roux, A. V., Nettleton, J. A., & Jacobs, D. R.
- Affiliations
- University of Michigan (US)
- University of Minnesota (US)
- Venue
- American Journal of Epidemiology
- Publisher
- Oxford University Press (OUP)
- Published
- 2008-02-25
- Volume
- 167
- Issue
- 8
- Pages
- 917-924
- ISSN
- 0002-9262 (ISSN-L)
- 1476-6256
- PMC
- PMC2587217
- OpenAlex
- W2108989089
- Cited by
- 563
- References
- 45
- Citations by year
- 2026: 7 · 2025: 17 · 2024: 22 · 2023: 19 · 2022: 22 · 2021: 20 · 2020: 27 · 2019: 29 · 2018: 28 · 2017: 43 · 2016: 37 · 2015: 43 · 2014: 44 · 2013: 53 · 2012: 43
- FWCI
- 35.62
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Locations
- American Journal of Epidemiology (publishedVersion)
- PubMed (publishedVersion)
- PubMed Central (acceptedVersion)
- Funders
- National Institutes of Health (n01hc95165-34-0-1, n01hc095169-003, n01hc95159-40-0-1)
- National Heart, Lung, and Blood Institute (N01 HC-95159, N01-HC095169, N01-HC-095165, N01 HC95165, N01-HC-095159, R01HL071759, N01 HC95169)
- Topics
- Health Sciences › Medicine › Public Health, Environmental and Occupational Health › Nutritional Studies and Diet
- Health Sciences › Medicine › Public Health, Environmental and Occupational Health › Food Security and Health in Diverse Populations
- Health Sciences › Nursing › Nutrition and Dietetics › Nutrition, Health and Food Behavior
- Keywords
- local food environment, diet quality, Alternative Healthy Eating Index, food environment assessment, Multi-Ethnic Study of Atherosclerosis, healthy eating, food access
- MeSH terms
- Aged, Aged, 80 and over, Arteriosclerosis, Black or African American, Diet, Female, Food Supply, Hispanic or Latino, Humans, Male, Middle Aged, New York, Nutrition Surveys, Nutritional Status, Residence Characteristics, United States, Models, Statistical, Geographic Information Systems
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