Integrating multi-modal commuting behavior into measures of spatial food accessibility

Authors: Jiawen Zhang*, University of Florida, Liang Mao, University of Florida
Topics: Medical and Health Geography, Geography and Urban Health, Transportation Geography
Keywords: Food access, Travel modes, Commuting pattern, Health geography
Session Type: Paper
Day: 4/4/2019
Start / End Time: 1:10 PM / 2:50 PM
Room: Jackson, Marriott, Mezzanine Level
Presentation File: No File Uploaded


People can access to healthy food via different travel modes, such as by car, transit, bicycle and foot. We taxonomize current indicators of food accessibility under an origin-destination-mode framework and find that few of them are able to integrate multi-modal travels. As a result, these indicators can bias the identification of low access areas. To fill this gap, we propose two new measures that integrate sub-populations of various travel modes and estimate an overall multi-modal food accessibility of a population. Taking Florida, USA, as an example, we illustrate our measures by using actual multi-modal commuting data from the U.S census transportation planning products (CTPP), and compare them to single-modal measures (by car only). The results indicate that the single-modal measures tend to estimate smaller population with low accessibility and more accessible markets than the multi-modal measures, particularly in urban areas. By considering modal-split subpopulations, our measures offer a more realistic representation of local people’s travel pattern, and thus a better identification of food deserts. Further, the finer modeling scale for subpopulations provide health and urban planners more flexibility in policy design, in that interventions can be tailored for not only a specific neighborhood but also a specific subpopulation within it. Such knowledge could improve the cost-effectiveness of intervention programs.

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