Evidence map›Paper›PMID 37730612›Full record

ArticleInternational journal of health geographics2023

Assessing the association between food environment and dietary inflammation by community type: a cross-sectional REGARDS study.

Yasemin Algur, Pasquale E Rummo, Tara P McAlexander, S Shanika A De Silva, Gina S Lovasi, Suzanne E Judd, Victoria Ryan, Gargya Malla, Alain K Koyama, David C Lee and 2 more

Abstract read
In one paragraph

Article in International journal of health geographics, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

  1. Article
  2. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

12 authors.

Yasemin AlgurDepartment of Epidemiology and Biostatistics, Drexel University Dornsife School of Public Health, Nesbitt Hall, 3215 Market Street, Philadelphia, PA, 19104, USA. ya383@drexel.edu.
Pasquale E RummoDepartment of Population Health, New York University Grossman School of Medicine, New York, NY, USA.
Tara P McAlexanderDepartment of Epidemiology and Biostatistics, Drexel University Dornsife School of Public Health, Nesbitt Hall, 3215 Market Street, Philadelphia, PA, 19104, USA.
S Shanika A De SilvaDepartment of Epidemiology and Biostatistics, Drexel University Dornsife School of Public Health, Nesbitt Hall, 3215 Market Street, Philadelphia, PA, 19104, USA.
Gina S LovasiDepartment of Epidemiology and Biostatistics, Drexel University Dornsife School of Public Health, Nesbitt Hall, 3215 Market Street, Philadelphia, PA, 19104, USA.
Suzanne E JuddDepartment of Biostatistics, The University of Alabama at Birmingham School of Public Health, Birmingham, AL, USA.
Victoria RyanDepartment of Epidemiology and Biostatistics, Drexel University Dornsife School of Public Health, Nesbitt Hall, 3215 Market Street, Philadelphia, PA, 19104, USA.
Gargya MallaDepartment of Epidemiology, The University of Alabama at Birmingham School of Public Health, Birmingham, AL, USA.
Alain K KoyamaDivision of Diabetes Translation, Centers for Disease Control and Prevention, Atlanta, GA, USA.
David C LeeDepartment of Population Health, New York University Grossman School of Medicine, New York, NY, USA.
Lorna E ThorpeDepartment of Population Health, New York University Grossman School of Medicine, New York, NY, USA.
Leslie A McClureDepartment of Epidemiology and Biostatistics, Drexel University Dornsife School of Public Health, Nesbitt Hall, 3215 Market Street, Philadelphia, PA, 19104, USA.

Funding

VCID and Stroke in a Bi-racial National CohortU01NS041588 · NINDS · UNIVERSITY OF ALABAMA AT BIRMINGHAM · PI CUSHMAN, MARY, HOWARD, GEORGE · 2002 to 2022
$96.0M
Translational Research Support CoreP30ES013508 · NIEHS · UNIVERSITY OF PENNSYLVANIA · PI A. Clementina Mesaros · 2006 to 2026
$35.3M
Why is the prevalence of obesity so high in U.S. Southern States? Regional predictors of BMI and obesity treatment response.P30DK056336 · NIDDK · UNIVERSITY OF ALABAMA AT BIRMINGHAM · PI BARBARA A GOWER · 2000 to 2026
$31.9M
New York Regional Center for Diabetes Translation Research - Translational Intervention Methodology CoreP30DK111022 · NIDDK · ALBERT EINSTEIN COLLEGE OF MEDICINE, INC · PI JEFFREY GONZALEZ · 2016 to 2026
$7.8M
Component A: Impact of Community Factors on Geographic Disparities in Diabetes and Obesity NationwideU01DP006299 · DP · NEW YORK UNIVERSITY SCHOOL OF MEDICINE · PI THORPE, LORNA · 2017 to 2021
$4.1M
The Impact of the Food Environment and Other Environmental Exposures on the Risk of Diabetes in Rural SettingsR01DK124400 · NIDDK · NEW YORK UNIVERSITY SCHOOL OF MEDICINE · PI LEE, DAVID C · 2020 to 2024
$3.5M
Component B: Coordinating Center for Community Characteristics Associated with Geographic Disparities in DiabetesU01DP006293 · DP · DREXEL UNIVERSITY · PI MCCLURE, LESLIE AIN · 2017 to 2021
$3.1M
Communities Designed to Support Cardiovascular Health for Older AdultsR01AG049970 · NIA · DREXEL UNIVERSITY · PI LOVASI, GINA S · 2015 to 2018
$2.8M
Built environments on stroke risk and stroke disparities in a national sampleR01NS092706 · NINDS · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI COLABIANCHI, NATALIE, JUDD, SUZANNE E · 2016 to 2019
$2.5M
ConProject-003R56AG049970 · NIA · DREXEL UNIVERSITY · PI LOVASI, GINA S · 2022 to 2023
$1.3M
ACL HHS U01DP006293ACL HHS U01DP006302CDC HHS U01DP006293CDC HHS U01DP006299CDC HHS U01DP006302NCCDPHP CDC HHS U01 DP006293NCCDPHP CDC HHS U01 DP006299NCCDPHP CDC HHS U01 DP006302NIA NIH HHS R01 AG049970NIA NIH HHS R56 AG049970NIDDK NIH HHS P30 DK056336NIDDK NIH HHS P30 DK111022NIDDK NIH HHS R01 DK124400NIEHS NIH HHS P30 ES013508NIH HHS U01 NS041588NINDS NIH HHS R01 NS092706NINDS NIH HHS U01 NS041588
6 · The paper itself

Abstract

backgroundCommunities in the United States (US) exist on a continuum of urbanicity, which may inform how individuals interact with their food environment, and thus modify the relationship between food access and dietary behaviors.

objectiveThis cross-sectional study aims to examine the modifying effect of community type in the association between the relative availability of food outlets and dietary inflammation across the US.

methodsUsing baseline data from the REasons for Geographic and Racial Differences in Stroke study (2003-2007), we calculated participants' dietary inflammation score (DIS). Higher DIS indicates greater pro-inflammatory exposure. We defined our exposures as the relative availability of supermarkets and fast-food restaurants (percentage of food outlet type out of all food stores or restaurants, respectively) using street-network buffers around the population-weighted centroid of each participant's census tract. We used 1-, 2-, 6-, and 10-mile (~ 2-, 3-, 10-, and 16 km) buffer sizes for higher density urban, lower density urban, suburban/small town, and rural community types, respectively. Using generalized estimating equations, we estimated the association between relative food outlet availability and DIS, controlling for individual and neighborhood socio-demographics and total food outlets. The percentage of supermarkets and fast-food restaurants were modeled together.

resultsParticipants (n = 20,322) were distributed across all community types: higher density urban (16.7%), lower density urban (39.8%), suburban/small town (19.3%), and rural (24.2%). Across all community types, mean DIS was - 0.004 (SD = 2.5; min = - 14.2, max = 9.9). DIS was associated with relative availability of fast-food restaurants, but not supermarkets. Association between fast-food restaurants and DIS varied by community type (P for interaction = 0.02). Increases in the relative availability of fast-food restaurants were associated with higher DIS in suburban/small towns and lower density urban areas (p-values < 0.01); no significant associations were present in higher density urban or rural areas.

conclusionsThe relative availability of fast-food restaurants was associated with higher DIS among participants residing in suburban/small town and lower density urban community types, suggesting that these communities might benefit most from interventions and policies that either promote restaurant diversity or expand healthier food options.

Indexed as

DietInflammationCross-Sectional StudiesHumansRestaurantsRural PopulationCensus TractDietInflammationNeighborhood characteristicsRestaurantsSupermarketsSurveys and questionnaires

Identifiers

PMID37730612
PMCPMC10510199

What OpenQuestion holds

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LicenceCC BY
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Registered trials

None linked

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.