Junfeng Jiao

How to identify food deserts: measuring physical and economic access to supermarkets in King County, Washington.

OBJECTIVES We explored new ways to identify food deserts. METHODS We estimated physical and economic access to supermarkets for 5 low-income groups in Seattle-King County, Washington. We used geographic information system data to measure physical access: service areas around each supermarket were delineated by ability to walk, bicycle, ride transit, or drive within 10 minutes. We assessed economic access by stratifying supermarkets into low, medium, and high cost. Combining income and access criteria generated multiple ways to estimate food deserts. RESULTS The 5 low-income group definitions yielded total vulnerable populations ranging from 4% to 33% of the countys population. Almost all of the vulnerable populations lived within a 10-minute drive or bus ride of a low- or medium-cost supermarket. Yet at most 34% of the vulnerable populations could walk to any supermarket, and as few as 3% could walk to a low-cost supermarket. CONCLUSIONS The criteria used to define low-income status and access to supermarkets greatly affect estimates of populations living in food deserts. Measures of access to food must include travel duration and mode and supermarket food costs.

Food environment and socioeconomic status influence obesity rates in Seattle and in Paris

Objective:To compare the associations between food environment at the individual level, socioeconomic status (SES) and obesity rates in two cities: Seattle and Paris.Methods:Analyses of the SOS (Seattle Obesity Study) were based on a representative sample of 1340 adults in metropolitan Seattle and King County. The RECORD (Residential Environment and Coronary Heart Disease) cohort analyses were based on 7131 adults in central Paris and suburbs. Data on sociodemographics, health and weight were obtained from a telephone survey (SOS) and from in-person interviews (RECORD). Both studies collected data on and geocoded home addresses and food shopping locations. Both studies calculated GIS (Geographic Information System) network distances between home and the supermarket that study respondents listed as their primary food source. Supermarkets were further stratified into three categories by price. Modified Poisson regression models were used to test the associations among food environment variables, SES and obesity.Results:Physical distance to supermarkets was unrelated to obesity risk. By contrast, lower education and incomes, lower surrounding property values and shopping at lower-cost stores were consistently associated with higher obesity risk.Conclusion:Lower SES was linked to higher obesity risk in both Paris and Seattle, despite differences in urban form, the food environments and in the respective systems of health care. Cross-country comparisons can provide new insights into the social determinants of weight and health.

Grocery Shopping How Individuals and Built Environments Influence Choice of Travel Mode.

This research investigated the influences of socioeconomic characteristics of individual travelers and of the environments where the travelers live and shop on choice of travel mode for grocery shopping. The data on travel for grocery shopping came from 2,001 respondents to the 2009 Seattle Obesity Study survey in King County, Washington. Eighty-eight percent of the respondents drove to their grocery stores, whereas 12% used transit or taxis, walked, biked, or carpooled. The addresses of 1,994 homes and 1,901 primary grocery stores used by respondents were geographically coded. The characteristics of built environments in the neighborhoods around homes and grocery stores and the distances between those homes and stores were measured in a geographic information system. Four binary logistic models estimated the impact of individual socioeconomic characteristics, distance, and built environments around homes and grocery stores on the travel mode used for grocery shopping. Fourteen variables were significantly related to mode choice. The strongest predictors of driving to the grocery store were more cars per adult household member, more adults per household, living in a single-family house, longer distances between homes and grocery stores (both the stores used and the nearest stores), and more at-ground parking around the grocery store used. Higher street density, more quick-service restaurants around homes, and more nonchain grocery stores near the primary grocery store used were related to not driving. Results suggested that reductions of distances between homes and grocery stores, clustering of grocery stores and other food establishments, and reductions in the amount of the parking around them could lead to less driving for grocery shopping.

Transition Rule Elicitation Methods for Urban Cellular Automata Models

Processing – Multi Criteria Evaluation (AHP-MCE) are discussed. Most of these methods are data driven methods and can be used to elicit the transition potential rules in the urban CA models. In the following, three possible rule elicitation methods: Interview, Document analysis, and Card sorting are explained and demonstrated. These three methods are driven by knowledge and can be used to elicit conflict resolution rules as well as transition potential

Health Implications of Adults' Eating at and Living near Fast Food or Quick Service Restaurants

Background:This paper examined whether the reported health impacts of frequent eating at a fast food or quick service restaurant on health were related to having such a restaurant near home.Methods:Logistic regressions estimated associations between frequent fast food or quick service restaurant use and health status, being overweight or obese, having a cardiovascular disease or diabetes, as binary health outcomes. In all, 2001 participants in the 2008–2009 Seattle Obesity Study survey were included in the analyses.Results:Results showed eating ⩾2 times a week at a fast food or quick service restaurant was associated with perceived poor health status, overweight and obese. However, living close to such restaurants was not related to negative health outcomes.Conclusions:Frequent eating at a fast food or quick service restaurant was associated with perceived poor health status and higher body mass index, but living close to such facilities was not.

Public Participatory GIS and the Geography of Inclusion

Public participatory geographic information systems (PPGIS) have been advanced as a means to include those who have been traditionally excluded from numerous place-specific governance activities, including planning and policymaking and as a way to resolve some of the long-standing tensions between critical traditions in human geography and the ever-expanding field of GIS. Despite the rapid adoption of participatory GIS by academics, government officials, and planning professionals, there are few guidelines of best practices for PPGIS researchers and practitioners to draw on and little effort has been made to understand how and in what ways PPGIS efforts are (or perhaps are not) effective. This article contributes to these important debates by evaluating the geography of participation in a recent participatory planning project undertaken in Muncie, Indiana. Using the mapped information that was generated from a series of public meetings, we have identified the presence of significant spatial bias in the process of participation that affected the resulting plan. This was an unexamined source of bias during this process and an example of why any emerging conversations about the best practices for PPGIS must include a consideration of the geography of participation.

Non-linear effects of the built environment on automobile-involved pedestrian crash frequency: A machine learning approach

Although a growing body of literature focuses on the relationship between the built environment and pedestrian crashes, limited evidence is provided about the relative importance of many built environment attributes by accounting for their mutual interaction effects and their non-linear effects on automobile-involved pedestrian crashes. This study adopts the approach of Multiple Additive Poisson Regression Trees (MAPRT) to fill such gaps using pedestrian collision data collected from Seattle, Washington. Traffic analysis zones are chosen as the analytical unit. The effects of various factors on pedestrian crash frequency investigated include characteristics the of road network, street elements, land use patterns, and traffic demand. Density and the degree of mixed land use have major effects on pedestrian crash frequency, accounting for approximately 66% of the effects in total. More importantly, some factors show clear non-linear relationships with pedestrian crash frequency, challenging the linearity assumption commonly used in existing studies which employ statistical models. With various accurately identified non-linear relationships between the built environment and pedestrian crashes, this study suggests local agencies to adopt geo-spatial differentiated policies to establish a safe walking environment. These findings, especially the effective ranges of the built environment, provide evidence to support for transport and land use planning, policy recommendations, and road safety programs.

The impact of area residential property values on self-rated health: A cross-sectional comparative study of Seattle and Paris.

This study analyzed the impact of area residential property values, an objective measure of socioeconomic status (SES), on self-rated health (SRH) in Seattle, Washington and Paris, France. This study brings forth a valuable comparison of SRH between cities that have contrasting urban forms, population compositions, residential segregation, food systems and transportation modes. The SOS (Seattle Obesity Study) was based on a representative sample of 1394 adult residents of Seattle and King County in the United States. The RECORD Study (Residential Environment and Coronary Heart Disease) was based on 7131 adult residents of Paris and its suburbs in France. Socio-demographics, SRH and body weights were obtained from telephone surveys (SOS) and in-person interviews (RECORD). All home addresses were geocoded using ArcGIS 9.3.1 (ESRI, Redlands, CA). Residential property values were obtained from tax records (Seattle) and from real estate sales (Paris). Binary logistic regression models were used to test the associations among demographic and SES variables and SRH. Higher area property values significantly associated with better SRH, adjusting for age, gender, individual education, incomes, and BMI. The associations were significant for both cities. A one-unit increase in body mass index (BMI) was more detrimental to SRH in Seattle than in Paris. In both cities, higher area residential property values were related to a significantly lower obesity risk and better SRH. Ranked residential property values can be useful for health and weight studies, including those involving social inequalities and cross-country comparisons.

Does urban form influence grocery shopping frequency? A study from Seattle, Washington, USA

Purpose The purpose of this paper is to ascertain how elements of the built environment may or may not influence the frequency of grocery shopping. Design/methodology/approach Using data from the 2009 Seattle Obesity Study, the research investigated the effect of the urban built environment on grocery shopping travel frequency in the Seattle-King County area. Binary and ordered logit models served to estimate the impact of individual characteristics and built environments on grocery shopping travel frequency. Findings The results showed that the respondents’ attitude towards food, travel mode, and the network distance between homes and stores exerted the strongest influence on the travel frequency while urban form variables only had a modest influence. The study showed that frequent shoppers were more likely to use alternative transportation modes and shopped closer to their homes and infrequent shoppers tended to drive longer distances to their stores and spent more time and money per visit. Practical implications This research has implications for urban planners and policy makers as well as grocery retailers, as the seemingly disparate groups both have an interest in food shopping frequency. Originality/value Few studies in the planning or retail literature investigate the influence of the urban built environment and the insights from the planning field. This study uses GIS and a planning framework to provide information that is relevant for grocery retailers and those invested in food distribution.

Impacts of Beijing bus rapid transit on pre-owned home values

Bus Rapid Transit (BRT) has gained increasing popularity worldwide in the last few decades. However, few studies have investigated BRT’s impacts on property values in Chinese cities. This research, taking BRT route 1 (BRT1) and BRT route 3 (BRT3) in Beijing as examples, showed that proximity to BRT3 stops is weakly related to pre-owned home prices along the route, whereas BRT1 has induced a significant price premium. For BRT1, the impact is not linear. Specifically, pre-owned home prices for homes within 5–10 minutes’ walking distance to BRT stations is 5.35% higher than those located closer to or farther away. The difference between the two routes can be explained by resident income differences and BRT route alignments. For homes very close to the subway route, the impacts of BRT vanish.