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Considerations When Using Individual GPS Data in Food Environment Research: A Scoping Review of ‘Selective (Daily) Mobility Bias’ in GPS Exposure Studies and Its Relevance to the Retail Food Environment

  • Reilley Plue
  • Lauren Jewett
  • Michael J. WidenerEmail author
Chapter
Part of the Global Perspectives on Health Geography book series (GPHG)

Abstract

Advancements in geospatial technologies including geographic information systems and global positioning system (GPS) devices have provided insights on how the retail food environment might be contributing to the ongoing obesity epidemic. Caution has been raised, however, around the potential for research that uses GPS-captured activity spaces to overestimate the impact that exposure to food retailers has on food choices and behaviour. This phenomenon, where it is difficult to discern whether an individual is passively exposed to a space or actively seeks it out, is referred to as a ‘selective (daily) mobility bias’. Researchers’ understanding of this bias is relatively new and understudied, particularly in the food environment literature, where the bias could have serious implications. This chapter reviews 14 peer-reviewed papers and two doctoral theses to identify and critique the methods proposed for handling this bias and offer recommendations to consider as the use of GPS-activity space studies continues to grow.

Keywords

GPS Built environment Selective (daily) mobility bias Environment Health 

Abbreviations

FFR

Fast food retailer

GIS

Geographical information systems

GPS

Global positioning system

HPF

Highly processed food

SDMB

Selective daily mobility bias

SMB

Selective mobility bias

References

  1. Ahalya, M., Jane, Y. P., Éric, R., Marc, L., Tina, M., & Leia, M. M. (2017). Geographic retail food environment measures for use in public health. Health Promotion and Chronic Disease Prevention in Canada: Research, Policy and Practice, 37(10), 357–362.CrossRefGoogle Scholar
  2. Beshara, M., Hutchinson, A., & Wilson, C. (2010). Preparing meals under time stress. The experience of working mothers. Appetite, 55(3), 695–700.  https://doi.org/10.1016/j.appet.2010.10.003.CrossRefGoogle Scholar
  3. Bes-Rastrollo, M., Sayon-Orea, C., Ruiz-Canela, M., & Martinez-Gonzalez, M. A. (2016). Impact of sugars and sugar taxation on body weight control: A comprehensive literature review. Obesity, 24(7), 1410–1426.  https://doi.org/10.1002/oby.21535.CrossRefGoogle Scholar
  4. Boone-Heinonen, J., Gordon-Larsen, P., Kiefe, C. I., Shikany, J. M., Lewis, C. E., & Popkin, B. M. (2011). Fast food restaurants and food stores: Longitudinal associations with diet in young adults: The CARDIA Study. Archives of Internal Medicine, 171(13), 1162–1170.  https://doi.org/10.1001/archinternmed.2011.283.CrossRefGoogle Scholar
  5. Boswell, R. G., & Kober, H. (2016). Food cue reactivity and craving predict eating and weight gain: A meta-analytic review. Obesity Reviews: An Official Journal of the International Association for the Study of Obesity, 17(2), 159–177.  https://doi.org/10.1111/obr.12354.CrossRefGoogle Scholar
  6. Bramer, W. M., Rethlefsen, M. L., Kleijnen, J., & Franco, O. H. (2017). Optimal database combinations for literature searches in systematic reviews: A prospective exploratory study. Systematic Reviews, 6.  https://doi.org/10.1186/s13643-017-0644-y.
  7. Burgoine, T., & Monsivais, P. (2013). Characterising food environment exposure at home, at work, and along commuting journeys using data on adults in the UK. International Journal of Behavioral Nutrition and Physical Activity, 10, 85.  https://doi.org/10.1186/1479-5868-10-85.CrossRefGoogle Scholar
  8. Burgoine, T., Jones, A. P., Namenek Brouwer, R. J., & Benjamin Neelon, S. E. (2015). Associations between BMI and home, school and route environmental exposures estimated using GPS and GIS: Do we see evidence of selective daily mobility bias in children? International Journal of Health Geographics, 14, 8.  https://doi.org/10.1186/1476-072X-14-8.CrossRefGoogle Scholar
  9. Byrnes, H. F., Miller, B. A., Morrison, C. N., Wiebe, D. J., Remer, L. G., & Wiehe, S. E. (2016). Brief report: Using global positioning system (GPS) enabled cell phones to examine adolescent travel patterns and time in proximity to alcohol outlets. Journal of Adolescence, 50, 65–68.  https://doi.org/10.1016/j.adolescence.2016.05.001.CrossRefGoogle Scholar
  10. Camacho, S., & Ruppel, A. (2017). Is the calorie concept a real solution to the obesity epidemic? Global Health Action, 10(1), 1289650.  https://doi.org/10.1080/16549716.2017.1289650.CrossRefGoogle Scholar
  11. 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.  https://doi.org/10.1016/j.healthplace.2012.05.006.CrossRefGoogle Scholar
  12. Cawley, J., & Wen, K. (2018). Policies to prevent obesity and promote healthier diets: A critical selective review. Clinical Chemistry, 64(1), 163–172.  https://doi.org/10.1373/clinchem.2017.278325.CrossRefGoogle Scholar
  13. Cebrecos, A., Díez, J., Gullón, P., Bilal, U., Franco, M., & Escobar, F. (2016). Characterizing physical activity and food urban environments: A GIS-based multicomponent proposal. International Journal of Health Geographics, 15.  https://doi.org/10.1186/s12942-016-0065-5.
  14. Cetateanu, A., & Jones, A. (2016). How can GPS technology help us better understand exposure to the food environment? A systematic review. SSM - Population Health, 2, 196–205.  https://doi.org/10.1016/j.ssmph.2016.04.001.CrossRefGoogle Scholar
  15. Chaix, B., Kestens, Y., Perchoux, C., Karusisi, N., Merlo, J., & Labadi, K. (2012). An interactive mapping tool to assess individual mobility patterns in neighborhood studies. American Journal of Preventive Medicine, 43(4), 440–450.  https://doi.org/10.1016/j.amepre.2012.06.026.CrossRefGoogle Scholar
  16. Chaix, B., Méline, J., Duncan, S., Merrien, C., Karusisi, N., Perchoux, C., et al. (2013). GPS tracking in neighborhood and health studies: A step forward for environmental exposure assessment, a step backward for causal inference? Health & Place, 21, 46–51.  https://doi.org/10.1016/j.healthplace.2013.01.003.CrossRefGoogle Scholar
  17. Chen, X., & Kwan, M.-P. (2012). Choice set formation with multiple flexible activities under space–time constraints. International Journal of Geographical Information Science, 26(5), 941–961.  https://doi.org/10.1080/13658816.2011.624520.CrossRefGoogle Scholar
  18. Christian, W. J. (2012). Using geospatial technologies to explore activity-based retail food environments. Spatial and Spatio-Temporal Epidemiology, 3(4), 287–295.CrossRefGoogle Scholar
  19. Clary, C., Matthews, S. A., & Kestens, Y. (2017). Between exposure, access and use: Reconsidering foodscape influences on dietary behaviours. Health & Place, 44, 1–7.  https://doi.org/10.1016/j.healthplace.2016.12.005.CrossRefGoogle Scholar
  20. Cornelsen, L., Green, R., Dangour, A., & Smith, R. (2015). Why fat taxes won’t make us thin. Journal of Public Health, 37(1), 18–23.  https://doi.org/10.1093/pubmed/fdu032.CrossRefGoogle Scholar
  21. Crézé, C., Notter-Bielser, M.-L., Knebel, J.-F., Campos, V., Tappy, L., Murray, M., & Toepel, U. (2018). The impact of replacing sugar- by artificially-sweetened beverages on brain and behavioral responses to food viewing – An exploratory study. Appetite, 123, 160–168.  https://doi.org/10.1016/j.appet.2017.12.019.CrossRefGoogle Scholar
  22. Drewnowski, A., & Kawachi, I. (2015). Diets and health: How food decisions are shaped by biology, economics, geography, and social interactions. Big Data, 3(3), 193–197.  https://doi.org/10.1089/big.2015.0014.CrossRefGoogle Scholar
  23. Eckert, J., & Shetty, S. (2011). Food systems, planning and quantifying access: Using GIS to plan for food retail. Applied Geography, 31(4), 1216–1223.  https://doi.org/10.1016/j.apgeog.2011.01.011.CrossRefGoogle Scholar
  24. Fong, K. C., Hart, J. E., & James, P. (2018). A review of epidemiologic studies on greenness and health: Updated literature through 2017. Current Environmental Health Reports, 5(1), 77–87.  https://doi.org/10.1007/s40572-018-0179-y.CrossRefGoogle Scholar
  25. Giskes, K., van Lenthe, F., Avendano-Pabon, M., & Brug, J. (2011). A systematic review of environmental factors and obesogenic dietary intakes among adults: Are we getting closer to understanding obesogenic environments? Obesity Reviews, 12(5), e95–e106.  https://doi.org/10.1111/j.1467-789X.2010.00769.x.CrossRefGoogle Scholar
  26. Haddaway, N. R., Collins, A. M., Coughlin, D., & Kirk, S. (2015). The role of Google Scholar in evidence reviews and its applicability to grey literature searching. PLoS One, 10(9), e0138237.  https://doi.org/10.1371/journal.pone.0138237.CrossRefGoogle Scholar
  27. Hager, E. R., Cockerham, A., O’Reilly, N., Harrington, D., Harding, J., Hurley, K. M., & Black, M. M. (2017). Food swamps and food deserts in Baltimore City, MD, USA: Associations with dietary behaviours among urban adolescent girls. Public Health Nutrition, 20(14), 2598–2607.  https://doi.org/10.1017/S1368980016002123.CrossRefGoogle Scholar
  28. Hall, K. D. (2017). Did the food environment cause the obesity epidemic? Obesity, 26(1), 11–13.  https://doi.org/10.1002/oby.22073.CrossRefGoogle Scholar
  29. Harrison, F., Burgoine, T., Corder, K., van Sluijs, E. M., & Jones, A. (2014). How well do modelled routes to school record the environments children are exposed to?: A cross-sectional comparison of GIS-modelled and GPS-measured routes to school. International Journal of Health Geographics, 13(1), 5.  https://doi.org/10.1186/1476-072X-13-5.CrossRefGoogle Scholar
  30. Health Canada. (2013, October 9). Measuring the Food Environment in Canada [research]. Retrieved May 3, 2018, from https://www.canada.ca/en/health-canada/services/food-nutrition/healthy-eating/nutrition-policy-reports/measuring-food-environment-canada.html.
  31. Hebebrand, J., Albayrak, Ö., Adan, R., Antel, J., Dieguez, C., de Jong, J., et al. (2014). “Eating addiction”, rather than “food addiction”, better captures addictive-like eating behavior. Neuroscience & Biobehavioral Reviews, 47, 295–306.  https://doi.org/10.1016/j.neubiorev.2014.08.016.CrossRefGoogle Scholar
  32. Kestens, Y., Lebel, A., Daniel, M., Thériault, M., & Pampalon, R. (2010). Using experienced activity spaces to measure foodscape exposure. Health & Place, 16(6), 1094–1103.  https://doi.org/10.1016/j.healthplace.2010.06.016.CrossRefGoogle Scholar
  33. Kestens, Y., Lebel, A., Chaix, B., Clary, C., Daniel, M., Pampalon, R., et al. (2012). Association between activity space exposure to food establishments and individual risk of overweight. PLoS One, 7(8), e41418.  https://doi.org/10.1371/journal.pone.0041418.CrossRefGoogle Scholar
  34. Kwan, M.-P. (2018). The limits of the neighborhood effect: Contextual uncertainties in geographic, environmental health, and social science research. Annals of the American Association of Geographers, 0(0), 1–9.  https://doi.org/10.1080/24694452.2018.1453777.CrossRefGoogle Scholar
  35. Laska, M. N., Hearst, M. O., Lust, K., Lytle, L. A., & Story, M. (2015). How we eat what we eat: Identifying meal routines and practices most strongly associated with healthy and unhealthy dietary factors among young adults. Public Health Nutrition, 18(12), 2135–2145.  https://doi.org/10.1017/S1368980014002717.CrossRefGoogle Scholar
  36. Ma, Y., Ratnasabapathy, R., & Gardiner, J. (2017). Carbohydrate craving: Not everything is sweet. Current Opinion in Clinical Nutrition & Metabolic Care, 20(4), 261.  https://doi.org/10.1097/MCO.0000000000000374.CrossRefGoogle Scholar
  37. McCrorie, P. R., Fenton, C., & Ellaway, A. (2014). Combining GPS, GIS, and accelerometry to explore the physical activity and environment relationship in children and young people - a review. International Journal of Behavioral Nutrition and Physical Activity, 11(1), 93.  https://doi.org/10.1186/s12966-014-0093-0.CrossRefGoogle Scholar
  38. Minaker, L. M. (2016). Retail food environments in Canada: Maximizing the impact of research, policy and practice. Canadian Journal of Public Health = Revue Canadienne De Sante Publique, 107.(Suppl 1, 5632.Google Scholar
  39. Minaker, L. M., Shuh, A., Olstad, D. L., Engler-Stringer, R., Black, J. L., & Mah, C. L. (2016). Retail food environments research in Canada: A scoping review. Canadian Journal of Public Health, 107(0), 4–13.CrossRefGoogle Scholar
  40. Mitchell, C. (2016). Children’s physical activity and the built environment: The impact of neighbourhood opportunities and contextual environmental exposure. Electronic Thesis and Dissertation Repository. Retrieved from https://ir.lib.uwo.ca/etd/3524
  41. Monsivais, P., Aggarwal, A., & Drewnowski, A. (2014). Time spent on home food preparation and indicators of healthy eating. American Journal of Preventive Medicine, 47(6), 796–802.  https://doi.org/10.1016/j.amepre.2014.07.033.CrossRefGoogle Scholar
  42. Moubarac, J.-C., Batal, M., Louzada, M. L., Martinez Steele, E., & Monteiro, C. A. (2017). Consumption of ultra-processed foods predicts diet quality in Canada. Appetite, 108(Suppl C), 512–520.  https://doi.org/10.1016/j.appet.2016.11.006.CrossRefGoogle Scholar
  43. Nederkoorn, C., & Jansen, A. (2002). Cue reactivity and regulation of food intake. Eating Behaviors, 3(1), 61–72.  https://doi.org/10.1016/S1471-0153(01)00045-9.
  44. Pelletier, J. E., Graham, D. J., & Laska, M. N. (2014). Social norms and dietary behaviors among young adults. American Journal of Health Behavior, 38(1), 144.  https://doi.org/10.5993/AJHB.38.1.15.CrossRefGoogle Scholar
  45. Perchoux, C., Chaix, B., Brondeel, R., & Kestens, Y. (2016). Residential buffer, perceived neighborhood, and individual activity space: New refinements in the definition of exposure areas – The RECORD Cohort Study. Health & Place, 40(Suppl C), 116–122.  https://doi.org/10.1016/j.healthplace.2016.05.004.CrossRefGoogle Scholar
  46. Ridder, D. D., Manning, P., Leong, S. L., Ross, S., Sutherland, W., Horwath, C., & Vanneste, S. (2016). The brain, obesity and addiction: An EEG neuroimaging study. Scientific Reports, 6(34122).  https://doi.org/10.1038/srep34122.
  47. Robinson, E. (2017). Overweight but unseen: A review of the underestimation of weight status and a visual normalization theory. Obesity Reviews, 18(10), 1200–1209.  https://doi.org/10.1111/obr.12570.CrossRefGoogle Scholar
  48. Sadler, R. C., & Gilliland, J. A. (2015). Comparing children’s GPS tracks with geospatial proxies for exposure to junk food. Spatial and Spatio-Temporal Epidemiology, 14–15, 55–61.  https://doi.org/10.1016/j.sste.2015.09.001.CrossRefGoogle Scholar
  49. Scully, J. Y. (2016). Human Mobility, Exposure to the Built Environment, and Health (Thesis). Retrieved from https://digital.lib.washington.edu:443/researchworks/handle/1773/36862.
  50. Spook, J. E., Paulussen, T., Kok, G., & Empelen, P. V. (2013). Monitoring dietary intake and physical activity electronically: Feasibility, usability, and ecological validity of a mobile-based ecological momentary assessment tool. Journal of Medical Internet Research, 15(9), e214.  https://doi.org/10.2196/jmir.2617.CrossRefGoogle Scholar
  51. Steele, E. M., Baraldi, L. G., Louzada, M. L. d. C., Moubarac, J.-C., Mozaffarian, D., & Monteiro, C. A. (2016). Ultra-processed foods and added sugars in the US diet: Evidence from a nationally representative cross-sectional study. BMJ Open, 6(3), e009892.  https://doi.org/10.1136/bmjopen-2015-009892.CrossRefGoogle Scholar
  52. Sturm, R., & Cohen, D. A. (2009). Zoning for health? The year-old ban on new fast-food restaurants in South LA. Health Affairs (Project Hope), 28(6), w1088–w1097.  https://doi.org/10.1377/hlthaff.28.6.w1088.CrossRefGoogle Scholar
  53. Tang, D. W., Fellows, L. K., Small, D. M., & Dagher, A. (2012). Food and drug cues activate similar brain regions: A meta-analysis of functional MRI studies. Physiology & Behavior, 106(3), 317–324.  https://doi.org/10.1016/j.physbeh.2012.03.009.
  54. Teixeira, P. J., Carraça, E. V., Marques, M. M., Rutter, H., Oppert, J.-M., De Bourdeaudhuij, I., et al. (2015). Successful behavior change in obesity interventions in adults: A systematic review of self-regulation mediators. BMC Medicine, 13, 84.  https://doi.org/10.1186/s12916-015-0323-6.CrossRefGoogle Scholar
  55. Thompson, D. (2017, June 20). The Golden Age of Restaurants Is Stranger Than It Seems. Retrieved July 30, 2018, from https://www.theatlantic.com/business/archive/2017/06/its-the-golden-age-of-restaurants-in-america/530955/.
  56. Ventura, A. K., & Mennella, J. A. (2011). Innate and learned preferences for sweet taste during childhood. Current Opinion in Clinical Nutrition & Metabolic Care, 14(4), 379.  https://doi.org/10.1097/MCO.0b013e328346df65.CrossRefGoogle Scholar
  57. White, M. (2016). Population approaches to prevention of type 2 diabetes. PLoS Medicine, 13(7), e1002080.  https://doi.org/10.1371/journal.pmed.1002080.CrossRefGoogle Scholar
  58. WHO | Obesity and overweight. (n.d.). Retrieved November 29, 2017, from http://www.who.int/mediacentre/factsheets/fs311/en/.
  59. Widener, M. J., & Shannon, J. (2014). When are food deserts? Integrating time into research on food accessibility. Health & Place, 30, 1–3.  https://doi.org/10.1016/j.healthplace.2014.07.011.CrossRefGoogle Scholar
  60. Widener, M. J., Farber, S., Neutens, T., & Horner, M. (2015). Spatiotemporal accessibility to supermarkets using public transit: An interaction potential approach in Cincinnati, Ohio. Journal of Transport Geography, 42, 72–83.  https://doi.org/10.1016/j.jtrangeo.2014.11.004.CrossRefGoogle Scholar
  61. Widener, M. J., Minaker, L. M., Reid, J. L., Patterson, Z., Ahmadi, T. K., & Hammond, D. (2018). Activity space-based measures of the food environment and their relationships to food purchasing behaviours for young urban adults in Canada. Public Health Nutrition, 21, 1–14.  https://doi.org/10.1017/S1368980018000435.CrossRefGoogle Scholar
  62. Yoo, S., Baranowski, T., Missaghian, M., Baranowski, J., Cullen, K., Fisher, J. O., et al. (2006). Food-purchasing patterns for home: A grocery store-intercept survey. Public Health Nutrition, 9(3), 384–393.  https://doi.org/10.1079/PHN2005864.CrossRefGoogle Scholar
  63. Zenk, S. N., Schulz, A. J., Matthews, S. A., Odoms-Young, A., Wilbur, J., Wegrzyn, L., et al. (2011). Activity space environment and dietary and physical activity behaviors: A pilot study. Health & Place, 17(5), 1150–1161.  https://doi.org/10.1016/j.healthplace.2011.05.001.CrossRefGoogle Scholar
  64. Zenk, S. N., Matthews, S. A., Kraft, A. N., & Jones, K. K. (2018). How many days of global positioning system (GPS) monitoring do you need to measure activity space environments in health research? Health & Place, 51, 52–60.  https://doi.org/10.1016/j.healthplace.2018.02.004.CrossRefGoogle Scholar
  65. Zientek, L. R., Werner, J. M., Campuzano, M. V., & Nimon, K. (n.d.). The use of Google Scholar for research and research dissemination. New Horizons in Adult Education and Human Resource Development, 30(1), 39–46.  https://doi.org/10.1002/nha3.20209.

Copyright information

© Springer Nature Switzerland AG 2020

Authors and Affiliations

  • Reilley Plue
    • 1
  • Lauren Jewett
    • 1
  • Michael J. Widener
    • 1
    • 2
    Email author
  1. 1.Department of Geography & PlanningUniversity of TorontoTorontoCanada
  2. 2.Dalla Lana School of Public Health, University of TorontoTorontoCanada

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