Literature DB >> 33347464

The dynamics of food shopping behavior: Exploring travel patterns in low-income Detroit neighborhoods experiencing extreme disinvestment using agent-based modeling.

Igor Vojnovic1, Arika Ligmann-Zielinska2, Timothy F LeDoux3.   

Abstract

Only a handful of studies have leveraged agent-based models (ABMs) to examine public health outcomes and policy interventions associated with uneven urban food environments. While providing keen insights about the role of ABMs in studying urban food environments, these studies underutilize real-world data on individual behavior in their models. This study provides a unique contribution to the ABM and food access literature by utilizing survey data to develop an empirically-rich spatially-explicit ABM of food access. This model is used to simulate and scrutinize individual travel behavior associated with accessing food in low-income neighborhoods experiencing disinvestment in Detroit (Michigan), U.S. In particular, the relationship between trip frequencies, mode of travel, store choice, and distances traveled among individuals grouped into strata based on selected sociodemographic characteristics, including household income and age, is examined. Results reveal a diversified picture of not only how income and age shape food shopping travel but also the different thresholds of tolerance for non-motorized travel to stores. Younger and poorer population subgroups have a higher propensity to utilize non-motorized travel for shopping than older and wealthier subgroups. While all groups tend to travel considerable distances outside their immediate local food environment, different sociodemographic groups maintain unique spatial patterns of grocery-shopping behavior throughout the city and the suburbs. Overall, these results challenge foundational tenets in urban planning and design, regarding the specific characteristics necessary in the built environment to facilitate accessibility to urban amenities, such as grocery stores. In neighborhoods experiencing disinvestment, sociodemographic conditions play a more important role than the built environment in shaping food accessibility and ultimately travel behavior.

Entities:  

Year:  2020        PMID: 33347464      PMCID: PMC7751856          DOI: 10.1371/journal.pone.0243501

Source DB:  PubMed          Journal:  PLoS One        ISSN: 1932-6203            Impact factor:   3.240


  13 in total

Review 1.  Disparities and access to healthy food in the United States: A review of food deserts literature.

Authors:  Renee E Walker; Christopher R Keane; Jessica G Burke
Journal:  Health Place       Date:  2010-04-24       Impact factor: 4.078

2.  Differences in food environment perceptions and spatial attributes of food shopping between residents of low and high food access areas.

Authors:  Inderbir Sohi; Bethany A Bell; Jihong Liu; Sarah E Battersby; Angela D Liese
Journal:  J Nutr Educ Behav       Date:  2014-02-20       Impact factor: 3.045

Review 3.  Agent-based modeling of noncommunicable diseases: a systematic review.

Authors:  Roch A Nianogo; Onyebuchi A Arah
Journal:  Am J Public Health       Date:  2015-01-20       Impact factor: 9.308

4.  A narrative review of the use of agent-based modeling in health behavior and behavior intervention.

Authors:  Yong Yang
Journal:  Transl Behav Med       Date:  2019-11-25       Impact factor: 3.046

5.  Exploring walking differences by socioeconomic status using a spatial agent-based model.

Authors:  Yong Yang; Ana V Diez Roux; Amy H Auchincloss; Daniel A Rodriguez; Daniel G Brown
Journal:  Health Place       Date:  2012-01       Impact factor: 4.078

6.  Walking distance by trip purpose and population subgroups.

Authors:  Yong Yang; Ana V Diez-Roux
Journal:  Am J Prev Med       Date:  2012-07       Impact factor: 5.043

7.  An agent-based model of income inequalities in diet in the context of residential segregation.

Authors:  Amy H Auchincloss; Rick L Riolo; Daniel G Brown; Jeremy Cook; Ana V Diez Roux
Journal:  Am J Prev Med       Date:  2011-03       Impact factor: 5.043

8.  Using simple agent-based modeling to inform and enhance neighborhood walkability.

Authors:  Hannah Badland; Marcus White; Gus Macaulay; Serryn Eagleson; Suzanne Mavoa; Christopher Pettit; Billie Giles-Corti
Journal:  Int J Health Geogr       Date:  2013-12-11       Impact factor: 3.918

Review 9.  Agent-Based Modeling in Public Health: Current Applications and Future Directions.

Authors:  Melissa Tracy; Magdalena Cerdá; Katherine M Keyes
Journal:  Annu Rev Public Health       Date:  2018-01-12       Impact factor: 21.981

10.  A community-based system dynamics approach suggests solutions for improving healthy food access in a low-income urban environment.

Authors:  Yeeli Mui; Ellis Ballard; Eli Lopatin; Rachel L J Thornton; Keshia M Pollack Porter; Joel Gittelsohn
Journal:  PLoS One       Date:  2019-05-14       Impact factor: 3.240

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  1 in total

1.  Smart city lifestyle sensing, big data, geo-analytics and intelligence for smarter public health decision-making in overweight, obesity and type 2 diabetes prevention: the research we should be doing.

Authors:  Maged N Kamel Boulos; Keumseok Koh
Journal:  Int J Health Geogr       Date:  2021-03-03       Impact factor: 3.918

  1 in total

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