Evidence map›Paper›PMID 33766045›Full record

ArticleInternational journal of health geographics2021

A method for estimating neighborhood characterization in studies of the association with availability of sit-down restaurants and supermarkets.

Ke Peng, Daniel A Rodriguez, Jana A Hirsch, Penny Gordon-Larsen

Abstract read
In one paragraph

Article in International journal of health geographics, 2021. 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
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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

4 authors.

Ke PengDepartment of Urban Planning, School of Architecture, Hunan University, Changsha, Hunan, China. kpeng6@hnu.edu.cn.ORCID 0000-0001-6708-3873
Daniel A RodriguezDepartment of City and Regional Planning and Institute of Transportation Studies, University of California, Berkeley, Berkeley, CA, USA.
Jana A HirschUrban Health Collaborative, Department of Epidemiology and Biostatistics, Dornsife School of Public Health, Drexel University, Philadelphia, PA, USA.
Penny Gordon-LarsenDepartment of Nutrition, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA.ORCID 0000-0001-5322-4188

Funding

UNC-CH CENTER FOR ENVIRONMENTAL HEALTH &SUSCEPTIBILITYP30ES010126 · NIEHS · UNIV OF NORTH CAROLINA CHAPEL HILL · PI Melissa A. Troester · 2001 to 2026
$36.3M
Research Services CoreP2CHD050924 · NICHD · UNIV OF NORTH CAROLINA CHAPEL HILL · PI KAREN B GUZZO · 2015 to 2026
$9.6M
Leveraging multi-omics approaches to examine metabolic challenges of obesity in relation to cardiovascular diseasesR01HL143885 · NHLBI · UNIV OF NORTH CAROLINA CHAPEL HILL · PI AVERY, CHRISTY LEIGH, GORDON-LARSEN, PENNY · 2019 to 2022
$8.9M
Obesity and Metabolic Risk Disparities: Underlying Food Environment FactorsR01HL104580 · NHLBI · UNIV OF NORTH CAROLINA CHAPEL HILL · PI GORDON-LARSEN, PENNY · 2010 to 2014
$2.2M
Environmental Changes and Health Outcomes across 25 Years: Four US CitiesR01HL114091 · NHLBI · UNIV OF NORTH CAROLINA CHAPEL HILL · PI GORDON-LARSEN, PENNY · 2011 to 2014
$2.1M
NHLBI NIH HHS HHSN268201300025CNHLBI NIH HHS HHSN268201800003INHLBI NIH HHS HHSN268201800004INHLBI NIH HHS HHSN268201800005INHLBI NIH HHS HHSN268201800006INHLBI NIH HHS HHSN268201800007INHLBI NIH HHS R01 HL104580NHLBI NIH HHS R01 HL114091NHLBI NIH HHS R01 HL143885NICHD NIH HHS P2C HD050924NIEHS NIH HHS P30 ES010126
6 · The paper itself

Abstract

backgroundAlthough neighborhood-level access to food differs by sociodemographic factors, a majority of research on neighborhoods and food access has used a single construct of neighborhood context, such as income or race. Therefore, the many interrelated built environment and sociodemographic characteristics of neighborhoods obscure relationships between neighborhood factors and food access.

methodsThe objective of this study was to account for the many interrelated characteristics of food-related neighborhood environments and examine the association between neighborhood type and relative availability of sit-down restaurants and supermarkets. Using cluster analyses with multiple measures of neighborhood characteristics (e.g., population density, mix of land use, and sociodemographic factors) we identified six neighborhood types in 1993 in the Twin Cities Region, Minnesota. We then used mixed effects regression models to estimate differences in the relative availability of sit-down restaurants and supermarkets in 1993, 2001, and 2011 across the six neighborhood types.

resultsWe defined six types of neighborhoods that existed in 1993, namely, urban core, inner city, urban, aging suburb, high-income suburb, and suburban edge. Between 1993 and 2011, inner city neighborhoods experienced a greater increase in the percent of sit-down restaurants compared with urban core, urban, and aging suburbs. Differences in the percent of sit-down restaurants between inner city and aging suburbs, high-income suburbs and suburban edge neighborhoods increased between 1993 and 2011. Similarly, aging suburb neighborhoods had a greater percent of supermarkets compared with urban and high-income suburb neighborhoods in 2001 and 2011, but not in 1993, suggesting a more varied distribution of food stores across neighborhoods over time. Thus, the classification of neighborhood type based on sociodemographic and built environment characteristics resulted in a complex and increasingly varied distribution of restaurants and food stores.

conclusionsThe temporal increase in the relative availability of sit-down restaurants in inner cities after accounting for all restaurants might be partly related to a higher proportion of residents who eat-away-from-home, which is associated with higher calorie and fat intake.

Indexed as

Food MarketsRestaurantsCitiesFood SupplyHumansResidence CharacteristicsBuilt environmentFood storesSociodemographicUrbanization

Identifiers

PMID33766045
PMCPMC7995746

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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.