Advertisement

Food Security

, Volume 11, Issue 5, pp 1087–1099 | Cite as

Food access inequalities in Chinese urban neighborhoods: a case study of the Dalian development zone

  • Jiaojiao Li
  • Guobao SongEmail author
  • Henry Musoke Semakula
  • Yijie Dou
  • Shushen Zhang
Original Paper
  • 39 Downloads

Abstract

Difficulties in accessing food exist in some Chinese cities, and it can be a challenge for residents to buy affordable, good-quality and nutritious fresh foods. This study proposes a residential building-based measure to evaluate food accessibility based on Geographic Information Systems. We used a total of eight types of food retailers and 28 food categories in our analysis and explored whether inequities in access to food existed among neighborhoods with different housing prices in the Dalian Development Zone using Kruskal-Wallis test methods. Our results show that 38% of residents living in 3724 residential buildings required between five and 10 min to access the nearest supermarket, while 10% required more than 20 min. The mean walking accessibility to stores with eggs (10 min) and with milk (10 min) was quicker than that to other types of food stores (14–16 min). In addition, high-wealth neighborhoods had better food accessibility than did low-wealth neighborhoods. However, in comparison to the other studied neighborhoods, those with medium-low-wealth had the highest level of food accessibility. Our results can be used by policymakers to better understand food access in residential areas and to help improve the food environment in Chinese cities.

Keywords

Food accessibility Public health Geographic information systems Urbanization China 

Notes

Acknowledgments

We are grateful to Dr. Danny Hsu of Dalian University of Foreign Languages for his suggestions that helped us to improve our writing. We also appreciate the suggestions by Dr. Yong Wang of Dongbei University of Finance and Economics concerning the selection of a nonparametric test model. This study was supported by the Fundamental Research Funds for the Central Universities (DUT18LAB13), the Program of Introducing Talents of Disciplines to Universities (B13012) and the National Natural Science Foundation of China (No.71872031). Additionally, we appreciate the efforts made by several anonymous reviewers and editors to improve our submission.

Compliance with ethical standards

Conflict of interest

The authors declared that they have no conflicts of interest.

References

  1. Ahmed, S., Shanks, C. B., Smith, T., & Shanks, J. (2018). Fruit and vegetable desirability is lower in more rural built food environments of Montana, USA using the produce desirability (ProDes) tool. Food Security, 10(1), 169–182.Google Scholar
  2. Algert, S. J., Agrawal, A., & Lewis, D. S. (2006). Disparities in access to fresh produce in low-income neighborhoods in Los Angeles. American Journal of Preventive Medicine, 30(5), 365–370.CrossRefGoogle Scholar
  3. Apparicio, P., Cloutier, M., & Shearmur, R. (2007). The case of Montréal's missing food deserts: Evaluation of accessibility to food supermarkets. International Journal of Health Geographics, 6, 1), 1–1),13.CrossRefGoogle Scholar
  4. Ball, K., Timperio, A., & Crawford, D. (2009). Neighborhood socioeconomic inequalities in food access and affordability. Health & Place, 15(2), 578–585.CrossRefGoogle Scholar
  5. Bodor, J. N., Rose, D., Farley, T. A., Swalm, C., & Scott, S. K. (2008). Neighborhood fruit and vegetable availability and consumption: The role of small food retailers in an urban environment. Public Health Nutrition, 11(4), 413–420.CrossRefGoogle Scholar
  6. Caspi, C. E., Sorensen, G., Subramanian, S. V., & Kawachi, I. (2012). The local food environment and diet: A systematic review. Health & Place, 18(5), 1172–1187.CrossRefGoogle Scholar
  7. Chen, X. (2017). Take the edge off: A hybrid geographic food access measure. Applied Geography, 87, 149–159.CrossRefGoogle Scholar
  8. Chen, X., & Kwan, M. P. (2015). Contextual uncertainties, human mobility, and perceived food environment: The uncertain geographic context problem in food access research. American Journal of Public Health, 105(9), 1734–1737.CrossRefGoogle Scholar
  9. Cheng, G. (2013). Evaluation and analysis of domestic online map service. Geospatial Information, 11(6), 148–155.Google Scholar
  10. Chiang, Y. H., Peng, T. C., & Chang, C. O. (2015). The nonlinear effect of convenience stores on residential property prices: A case study of Taipei, Taiwan. Habitat International, 46, 82–90.CrossRefGoogle Scholar
  11. Coveney, J., & O’Dwyer, L. A. (2009). Effects of mobility and location on food access. Health & Place, 15(1), 45–55.CrossRefGoogle Scholar
  12. Cummins, S., & Macintyre, S. (2002). "Food deserts" - evidence and assumption in health policy making. BMJ, 325(7361), 436–438. Google Scholar
  13. Eckert, J., & Shetty, S. (2011). Food systems, planning and quantifying access: Using GIS to plan for food retail. Applied Geography, 31(4), 1216–1223.CrossRefGoogle Scholar
  14. Farber, S., Morang, M. Z., & Widener, M. J. (2014). Temporal variability in transit-based accessibility to supermarkets. Applied Geography, 53, 149–159.CrossRefGoogle Scholar
  15. Gordon, C., Purciel-Hill, M., Ghai, N. R., Kaufman, L., Graham, R., & Wye, G. V. (2011). Measuring food deserts in new York City’s low-income neighborhoods. Health & Place, 17(2), 696–700.CrossRefGoogle Scholar
  16. Hendrickson, D., Smith, C., & Eikenberry, N. (2006). Fruit and vegetable access in four low-income food deserts communities in Minnesota. Agriculture and Human Values, 23(3), 371–383.CrossRefGoogle Scholar
  17. Herforth, A., & Ahmed, S. (2015). The food environment, its effects on dietary consumption, and potential for measurement within agriculture-nutrition interventions. Food Security, 7(3), 505–520.CrossRefGoogle Scholar
  18. Horowitz, C. R., Colson, K. A., Hebert, P. L., & Lancaster, K. (2004). Barriers to buying healthy foods for people with diabetes: Evidence of environmental disparities. American Journal of Public Health, 94(9), 1549–1554.CrossRefGoogle Scholar
  19. Jang, M., & Kang, C. D. (2015). Retail accessibility and proximity effects on housing prices in Seoul, Korea: A retail type and housing submarket approach. Habitat International, 49, 516–528.CrossRefGoogle Scholar
  20. Jiao, J., Moudon, A. V., Ulmer, J., Hurvitz, P. M., & Drewnowski, A. (2012). How to identify food deserts: Measuring physical and economic access to supermarkets in King County, Washington. American Journal of Public Health, 102(10), e32–e39.CrossRefGoogle Scholar
  21. Lai, Y., Li, K., & Shen, L. (2015). The interactive relationship between wealth gap and real estate prices. Statistics and Decision, (23), 137–140 (In Chinese).Google Scholar
  22. Larson, N., Story, M., & Nelson, M. (2009). Neighborhood environments disparities in access to healthy foods in the US. American Journal of Preventive Medicine, 36(1), 74–81.CrossRefGoogle Scholar
  23. LeClair, M. S., & Aksan, A. (2014). Redefining the food desert: Combining GIS with direct observation to measure food access. Agriculture and Human Values, 31(4), 537–547.CrossRefGoogle Scholar
  24. Leete, L., Bania, N., & Sparks-Ibanga, A. (2012). Congruence and coverage: Alternative approaches to identifying urban food deserts and food hinterlands. Journal of Planning Education & Research, 32(2), 204–218.CrossRefGoogle Scholar
  25. Lin, C. (2004). Analysis on the development progress track in time order for Dalian economic and technological development area. Journal of Dalian Maritime University, 3(4), 72–75 (In Chinese).Google Scholar
  26. McEntee, J., & Agyeman, J. (2010). Towards the development of a GIS method for identifying rural food deserts: Geographic access in Vermont, USA. Applied Geography, 30(1), 165–176.CrossRefGoogle Scholar
  27. McKenzie, B. S. (2014). Access to supermarkets among poorer neighbourhoods: A comparison of time and distance measures. Urban Geography, 35(1), 133–151.CrossRefGoogle Scholar
  28. National Cancer Institute (NIH) (2016). https://www.cancer.gov/. Accessed 2 Sep 2016.
  29. National People's Congress (NPC) (2016). Road traffic safety law of the People's Republic of China. Beijing: PR China. Accessed 12 May 2016.Google Scholar
  30. Neumeier, S. (2015). Street petrol station shops as an alternative to missing local food suppliers - contribution to the German discourse on ‘Daseinsvorsorge’: A German view. Applied Geography, 60, 150–164.CrossRefGoogle Scholar
  31. Pearce, J., Witten, K., & Bartie, P. (2006). Neighbourhoods and health: A GIS approach to measuring community resource accessibility. Journal of Epidemiology and Community Health, 60(5), 389–395.CrossRefGoogle Scholar
  32. Powell, L. M., Slater, S., Mirtcheva, D., Bao, Y., & Chaloupka, F. J. (2007). Food store availability and neighborhood characteristics in the United States. Preventive Medicine, 44(3), 189–195.CrossRefGoogle Scholar
  33. Raja, S., Ma, C., & Yadav, P. (2008). Beyond food deserts measuring and mapping racial disparities in neighbourhood food environments. Journal of Planning Education and Research, 27(4), 469–482.CrossRefGoogle Scholar
  34. Rose, D., Bodor, J. N., Swalm, C. M., Rice, J. C., Farley, T. A., & Hutchinson, P. L. (2009). Deserts in New Orleans? Illustrations of urban food access and implications for policy. National Poverty Center Working Paper.Google Scholar
  35. Russell, S. E., & Heidkamp, C. P. (2011). ‘Food desertification’: The loss of a major supermarket in New Haven, Connecticut. Applied Geography, 31(4), 1197–1209.CrossRefGoogle Scholar
  36. Satellite Surveying and Mapping Application Center (SASMAC) (2013). http://sjfw.sasmac.cn. Accessed 22 Sep 2013.
  37. Seto, K. C., & Ramankutty, N. (2016). Hidden linkages between urbanization and food systems. Science, 352(6288), 943–945.CrossRefGoogle Scholar
  38. Sharkey, J. R., & Horel, S. (2008). Neighbourhood socioeconomic deprivation and minority composition are associated with better potential spatial access to the ground-truthed food environment in a large rural area. The Journal of Nutrition, 138(3), 620–627.CrossRefGoogle Scholar
  39. Song, G. B., Li, M. J., Fullana-I-Palmer, P., Williamson, D., & Wang, Y. X. (2017). Dietary changes to mitigate climate change and benefit public health in China. Science of the Total Environment, 577, 289–298.CrossRefGoogle Scholar
  40. United Nations Development Programme (2012). http://www.undp.org/content/undp/en/home/sustainable-development-goals.html. Accessed 1 Nov 2018.
  41. USDA (2009). Access to affordable and nutritious food: measuring and understanding food deserts and their consequences. Washington, D.C: United States Department of Agriculture.Google Scholar
  42. USDA (2012). Food Access Research Atlas. Washington, D.C: United States Department of Agriculture.Google Scholar
  43. Ver Ploeg, M., Dutko, P., & Breneman, V. (2015). Measuring food access and food deserts for policy purposes. Applied Economic Perspectives and Policy, 37(2), 205–225.CrossRefGoogle Scholar
  44. Wang, Y., Qiang, L., Wang, S. J., & Qin, J. (2014). Determinants and dynamics of spatial differentiation of housing price in Yangzhou. Progress in Geography, 33(3), 375–388.Google Scholar
  45. Wang, H., Tao, L., Qiu, F., & Lu, W. (2016). The role of socio-economic status and spatial effects on fresh food access: Two case studies in Canada. Applied Geography, 67, 27–38.CrossRefGoogle Scholar
  46. Widener, M. J. (2018). Spatial access to food: Retiring the food desert metaphor. Physiology & Behavior, 193, 257–260.CrossRefGoogle Scholar
  47. Widener, M.J., Steven, F., Tijs, N., & Horner, M. (2015). Spatiotemporal accessibility to supermarkets using public transit: an interaction potential approach in Cincinnati, Ohio. Journal of Transport Geography, 42(2015), 72–83.Google Scholar
  48. Winkler, E., Turrell, G., & Patterson, C. (2006). Does living in a disadvantaged area mean fewer opportunities to purchase fresh fruit and vegetables in the area? Findings from the Brisbane food study. Health & Place, 12(4), 741–748.CrossRefGoogle Scholar
  49. Xiao, Y., Chen, X., Li, Q., Yu, X., Chen, J., & Guo, J. (2017). Exploring determinants of housing prices in Beijing: An enhanced hedonic regression with open access POI data. International Journal of Geo-Information, 6, 358.CrossRefGoogle Scholar

Copyright information

© International Society for Plant Pathology and Springer Nature B.V. 2019

Authors and Affiliations

  1. 1.Key Laboratory of Industrial Ecology and Environmental Engineering (MOE), School of Environmental Science and TechnologyDalian University of TechnologyDalianPeople’s Republic of China
  2. 2.Department of Geography, Geo-Informatics and Climatic SciencesMakerere UniversityKampalaUganda
  3. 3.Center for Industrial and Business OrganizationDongbei University of Finance and EconomicsDalianChina

Personalised recommendations