%0 Journal Article
%T Assessment of the Retail Food Environment Using Integrated GIS and Modified Measures in Wuhan, China
%A Yitian Liu
%A Guangping Chen
%J Journal of Geographic Information System
%P 421-439
%@ 2151-1969
%D 2023
%I Scientific Research Publishing
%R 10.4236/jgis.2023.155021
%X The retail food environment (RFE) has a significant impact on people¡¯s
dietary behavior and diet-related outcomes. Although RFE research has received a lot of attention, there are very few studies that shed light on
the foodscape
and assessment methodologies in the China context. Based on open data obtained
from Dianping.com and AutoNavi map, we classified all food outlets into six
types. Geographic Information Systems (GIS) techniques were employed to create
two network buffer areas (1-km and 3-km) and calculate the absolute measures
and relative measures (<i>i.e.</i>, <i>mRFEI</i> and <i>Rmix</i>). We modified the calculation of<i> </i>relative measures by adding items and assigning weights. The mean <i>mRFEI</i> using the 1-km and 3-km buffer
sizes across the communities were 10.45 and 20.12, respectively, while the mean <i>mRmix </i>of the two buffer sizes were 20.97 and 58.04, indicating that residents in
Wuhan have better access to fresh and nutritious food within 3-km network
buffers. Residents in urban areas are more likely to be exposed to an unhealthy
food environment than those in rural areas. Residents in Xinzhou and Qiaokou
districts are more likely to be subjected to unfavorable neighborhood
RFE. The open data-driven methods for assessing RFE in Wuhan, China may guide community-level food policy
interventions and promote active living by shifting built environments to
increase residents¡¯ access to healthy food.
%K Retail Food Environment (RFE)
%K Diet Quality
%K Geographic Information Systems (GIS)
%K Density
%K Big Data
%U http://www.scirp.org/journal/PaperInformation.aspx?PaperID=127653