Published in

BioMed Central, International Journal of Health Geographics, 1(20), 2021

DOI: 10.1186/s12942-020-00257-7

Links

Tools

Export citation

Search in Google Scholar

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

Journal article published in 2021 by Ke Peng ORCID, Daniel A. Rodriguez, Jana A. Hirsch ORCID, Penny Gordon-Larsen ORCID
This paper is made freely available by the publisher.
This paper is made freely available by the publisher.

Full text: Download

Green circle
Preprint: archiving allowed
Green circle
Postprint: archiving allowed
Green circle
Published version: archiving allowed
Data provided by SHERPA/RoMEO

Abstract

Abstract Background Although 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. Methods The 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. Results We 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. Conclusions The 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.