Export file:

Format

  • RIS(for EndNote,Reference Manager,ProCite)
  • BibTex
  • Text

Content

  • Citation Only
  • Citation and Abstract

Local Spatial Analysis and Dynamic Simulation of Childhood Obesity and Neighbourhood Walkability in a Major Canadian City

1 Health Services Research & Evaluation, Alberta Health Services, 2430 Southport Atrium, 10101 Southport Road SW, Calgary, AB, Canada, T2W 3N2;
2 Department of Geography, University of Calgary, 2500 University Drive NW, Calgary, AB, Canada, T2N 1N4

Special Issues: Spatial Aspects of Health: Methods and Applications

Body weight is an important indicator of current and future health and it is even more critical in children, who are tomorrow’s adults. This paper analyzes the relationship between childhood obesity and neighbourhood walkability in Calgary, Canada. A multivariate analytical framework recognizes that childhood obesity is also associated with many factors, including socioeconomic status, foodscapes, and environmental factors, as well as less measurable factors, such as individual preferences, that could not be included in this analysis. In contrast with more conventional global analysis, this research employs localized analysis and assesses need-based interventions. The one-size-fit-all strategy may not effectively control obesity rates, since each neighbourhood has unique characteristics that need to be addressed individually. This paper presents an innovative framework combining local analysis with simulation modeling to analyze childhood obesity. Spatial models generally do not deal with simulation over time, making it cumbersome for health planners and policy makers to effectively design and implement interventions and to quantify their impact over time. This research fills this gap by integrating geographically weighted regression (GWR), which identifies vulnerable neighbourhoods and critical factors for childhood obesity, with simulation modeling, which evaluates the impact of the suggested interventions on the targeted neighbourhoods. Neighbourhood walkability was chosen as a potential target for localized interventions, owing to the crucial role of walking in developing a healthy lifestyle, as well as because increasing walkability is relatively more feasible and less expensive then modifying other factors, such as income. Simulation results suggest that local walkability interventions can achieve measurable declines in childhood obesity rates. The results are encouraging, as improvements are likely to compound over time. The results demonstrate that the integration of GWR and simulation modeling is effective, and the proposed framework can assist in designing local interventions to control and prevent childhood obesity.
  Figure/Table
  Supplementary
  Article Metrics

Keywords child obesity; walkability; geographically weighted regression; simulation modeling; obesogenic environment; Canada

Citation: Rizwan Shahid, Stefania Bertazzon. Local Spatial Analysis and Dynamic Simulation of Childhood Obesity and Neighbourhood Walkability in a Major Canadian City. AIMS Public Health , 2015, 2(4): 616-637. doi: 10.3934/publichealth.2015.4.616

References

  • 1. Ulijaszek Sj, Lofink H (2006) Obesity in biocultural perspective. Ann Rev Anthropol 35: 337-360.    
  • 2. James WPT (2008) The epidemiology of obesity: the size of the problem. J Inter Med 236: 336-352.
  • 3. WHO: World Health Organization (1997) Obesity: Preventing and Managing the Global Epidemic. Report of a WHO Consultation on Obesity. Geeneva.
  • 4. Pouliou T, Elliott SJ (2010) Individual and socio-environmental determinants of overweight and obesity in urban Canada. Health & Place 16: 389-398.
  • 5. Statistics Canada (2011) Overweight and obese adults (Self Reported). Catalogue 82-625- X.
  • 6. Colls R, Evans B (2014) Making space for fat bodies?: A critical account of ‘the obesogenic environment’. Progress Human Geog 38(6): 733-753.
  • 7. Cugnetto ML, Saab PG, Llabre MM, et al. (2008) Lifestyle factors, body mass index, and lipid profile in adolescents. J Pediatr Psycho 33(7): 761-771.
  • 8. Catenacci VA, Hill JO, Wyatt HR (2009) The obesity epidemic, Clin Chest Med 30:415-444.
  • 9. Petit CL, Berthelot J-M (2006) Obesity-a growing issue, Health Reports 17(3), Statistics Canada, Catalogue 82-003.
  • 10. Behan DF, Cox SH, et al. [Internet]. Obesity and its relation to mortality and morbidity costs, The Society of Actuaries Report; [updated 2010 Nov 30; cited 2015 May 13]. Available from: https://www.soa.org/Files/Research/Projects/research-2011-obesity-relation- mortality.pdf.
  • 11. CDC Newsroom [Internet]. New CDC data show encouraging development in obesity rates among 2 to 5 years old; [updated 2014 Nov 25; cited 2015 May 05]. Available from: http://www.cdc.gov/media/releases/2014/p0225-child-obesity.html.
  • 12. Fraser LK, Edwards KL (2010) The association between the geography of fast food outlets and childhood obesity rates in Leeds, UK. Health & Place 16: 1124-1128.
  • 13. Levy E, Zambo ZM, Edellm D, Borys J-M (2015) The potential of reducing the prevalence of overweight and obese children in Canada using the EPOSE methodology. Can J Diabetes 39(1): S70-71.
  • 14. Shields M (2006) Overweight and Obesity among children and youth. Health Reports 17(3), Statistics Canada Catalogue 82-003.
  • 15. Alberta Health Services: Obesity Facts [Internet]. AHS, Alberta Health Services; [cited 2015 Apr 22]. Available from: http://www.albertahealthservices.ca/7467.asp.
  • 16. Belluck P: The New York Times [Internet]. Children’s life expectancy being cut short by obesity; [updated 2005 Mar 17; cited 2015 May 13]. Available from: http://query.nytimes.com/gst/fullpage.html?res=9F01E3D7133CF934A25750C0A9639C8B6 3&sec=health&spon=&pagewanted=all.
  • 17. WHO: World Health Organization (2014) Obesity: Preventing and Managing the Global Epidemic. WHO Technical Report Series No. 894. Geeneva.
  • 18. Dehghan S, Akhtar-Danesh N, Merchant AT (2005) Childhood obesity, prevalence and prevention, Nutrition, 4:24.
  • 19. Kuczmarski RJ, Ogden CL, Grummer-Strawn LM, Flegal KM, Guo SS, Wei R & others (2000) CDC growth charts: United States. Adv Data, 314, 1-27.
  • 20. Smith DM, Cummins S (2009) Obese cities: how our environment shaped overweight. Geogra Com 3(1): 518-534.
  • 21. Stunkard AJ (2000) Factors in Obesity: Current Views, Obesity and Poverty, In: Pena M, Bacallao J (eds) Obesity and Poverty: A new Public Health Challenge. Pan Am H Organ: 23-28.
  • 22. Carnell S, Wardle J (2007) Measuring behavioural susceptibility to obesity: validation of the child eating behaviour questionnaire. Appetite 48 (1): 104-113.
  • 23. Burgoine T, Alvandies S, Lake AA (2013) Creating ‘obesogenic realities’; do our methodological choices make a difference when measuring the food environment? Inter J H Geog 12: 33.    
  • 24. Spence JC, Cutumisu N, Edward J, et al. (2009). Relation between local food environments and obesity among adults. BMC Public Health 9: 192.
  • 25. Marks J, Barnett LM, Foulkes C, et al. (2013) Using social network analysis to identify key child care center staff for obesity prevention interventions: A pilot study. Obesity 2013: 2013.
  • 26. Chalkias C, Papadopoulos AG, Kalogeropoulos K, et al. (2013) Geographical heterogeneity of the relationship between childhood obesity and socio-environmental status: empirical evidence from Athens, Greece. App Geog 37: 34-43.    
  • 27. Wen TH, Chen DR, Tsai MJ (2010) Identifying geographical variations in poverty- obesity relationships: empirical evidence from Taiwan. Geospatial H 4(2): 257-265.
  • 28. Lake AA, Burgoine T, Stamp E, Grieve R (2012) The foodscape: classification and field validation of secondary data sources across urban/rural and socio-economic classifications in England. Inter J Behavi Nutrition Physical Act 9: 35.    
  • 29. McCormack GR, Shiell A, Giles-Corti B, et al. (2012) The association between sidewalk length and walking for different purposes in established neighborhoods. Inter J Behavi Nutrition Physical Act 9: 92.    
  • 30. Spence JC, Holt NL, Sprysak CJ, et al. (2012) Non-refundable tax Credits are an inequitable policy instrument for promoting physical activity among Canadian children. Can J P H 103(3): 175-177.
  • 31. Shannon J (2014) Food deserts: Governing obesity in the neoliberal city. Progress Human Geog38(2: 248-266.
  • 32. Inagami S, Cohen DA, Brown AF, Steven MA (2009) Body mass index, neighbourhood fast food and restaurant concentration, and car ownership. J Urban Health: Bulletin of the New York Academ Med 86(5): 683-695.
  • 33. Niedzwiedz C, Katikireddi SV, Pell JP, Mitchell R (2012) Life course socio-economic position and quality of life in adulthood: a systematic review of life course models. BMC Public Health 12: 628.    
  • 34. Potestio ML, Patel AB, Powell CD, et al. (2009) Is there an association between spatial access to parks/green space and childhood overweight/obesity in Calgary, Canada? Inter J Behavi Nutrition and Physical Act 6: 77.
  • 35. Tjepkema M (2006) Adult obesity, Health Reports 17(3). Statistics Canada, Catalogue 82-003.
  • 36. Janssen I, Boyce W, Simpson K, Pickett W (2006) Influence of individual- and area-level measures of socioeconomic status on obesity, unhealthy eating, and physical inactivity in Canadian adolescents. Am J Clinic Nutrition 83: 139-145.
  • 37. Belanger-Ducharme F, Tremblay A (2005) Prevalence of obesity in Canada. Obesity Rev 6(3): 183-186.
  • 38. Kirchengast S, Schober E (2006) To be an immigrant: a risk factor for developing overweight and obesity during childhood and adolescence? J Biosocial Sci 38: 695-705.    
  • 39. A concise report, Alberta Centre for Active Living [Internet]. Alberta Walking Survey; [cited 2015 May 13]. Available from: http://www.albertahealthservices.ca/HealthWellness/hi-hw-al-wc-survey.pdf
  • 40. Abdel-Hamid TK (2009) Thinking in circles about obesity, applying systems thinking to weight management, Springer.
  • 41. Raghunathan R, Naylor RW, Hoyer WD (2006) The unhealthy = tasty intuition and its effects on taste inferences, enjoyment, and choice of food products. J Am Market Ass 70(4): 170-184.
  • 42. Hollands S, Campbell MK, Gilliland J, Sarma S (2013) A spatial analysis of the association between restaurant density and body mass index in Canadian adults. Prevent Med 13: S0091-7435.
  • 43. Sadler RC, Gilliland JA, Arku G (2013) A food retail-based intervention on food security and consumption. Inter J Environ Res Public Health 10: 3325-3346.    
  • 44. Andreyeva T, Kelly IR, Harris JL (2011) Exposure to food advertising on television: Associations with children’s fast food and soft drink consumption and obesity. Economics & Human Biology 9(3): 221-223.
  • 45. Duncan DT, Aldstadt J, Whalen J, et al. (2011) Validation of Walkscore for estimating neighborhood walkability; an analysis of four US metropolitan areas. Inter J Environ Res. Public Health 8: 4160-4179.    
  • 46. Sandalack BA, Uribe FGA, Zanjani AE, et al. (2013) Neighbourhood type and walkshed size. J Urbanism: Inter Res Placemaking Urban Sustain 11: 11
  • 47. McCormack G, Giles-Corti B, Lange A, et al (2004) An update of recent evidence of the relationship between objective and self-report measure of the physical environment and physical activity behaviours. J Sci Med Sport 7(1): Supplement, 81-92.
  • 48. Laxer RE, Janssen I (2013) The proportion of youth’s physical inactivity attributable to neighborhood built environment features. Inter J Health Geog 12: 31.    
  • 49. Carr LJ, Dunsiger SI, Marcus BH (2010) Walk Score as a global estimate of neighbourhood walkability. Am J Prevent Med 39(5): 460-463.
  • 50. Dewulf B, Neutens T, Dyck DV, et al. (2012) Correspondence between objective and perceived walking time to urban destinations: influence of physical activity, neighbourhood walkability, and socio-demographics. Inter J Health Geog 11: 43.    
  • 51. Dyck DV, Sallis JF, Cardon G, et al. (2013) Associations of neighbourhood characteristics with active park use: an observational study in two cities in the USA and Belgium. Inter J Health Geog 12: 26.    
  • 52. Kligerman M, Sallis JF, Ryan S, et al. (2007) Association of neighborhood design and recreation environment variables with physical activity and body mass index in adolescents. Am J Health Promotion 21(4): 274-277.
  • 53. Karanfil O, Moore T, Finley P, et al. (2011) A multi-scale paradigm to design policy options for obesity prevention: exploring the integration of individual-based modeling and system dynamics. Proceedings of the 29th Inter Confer Sys D Soci, July 24-28, 2011. Washington DC, USA.
  • 54. Homer J, Milstein B, Dietz W, et al. (2006) Obesity Population Dynamics: Exploring historical growth and plausible future in the US. Proceedings of the 24th Inter Confer Sys D Soci, July 23-27, 2006. Nijmegen, Netherlands.
  • 55. Ahmad S, Simonovic SP (2004) Spatial system dynamics: new approach for simulation of water resources systems. J Comp Civil Eng 18(4): 331-340.
  • 56. Fotheringham AS, Brunsdon C, Charlton M (2002) Geographically Weighted Regression: The analysis of spatially varying relationships. Wiley, West Sussex.
  • 57. Mahamoud A, Roche B, Homer J. (2013) Modeling the social determinants of health and simulating short-term and long-term intervention impacts for the city of Toronto, Canada. Social Sci & Med 93: 247-255.
  • 58. Bailie A, Beckstead C: PEMBINA Institute [Internet]. Canada's Coolest Cities. Technical Report; [updated 2010 May 26; cited 2015 Apr 25]. Available from: http://www.pembina.org/pub/2021.
  • 59. Statistics Canada (2006) Community Profiles.
  • 60. Gauvin L, Robitaille R, Riva M, et al. (2007) Conceptualizing and operationalizing and neighbourhoods: the conundrum of identifying territorial units. Can J Public Health 98: 518-526.
  • 61. Riger S, Lavrakas PJ (1981) Community ties: patterns of attachment and social interaction in urban neighborhoods, Am J Com Psycho 9(1): 55-66.
  • 62. Grigsby-Toussaint D, Chi S-H, Fiese BH (2011) Where they live, how they play: neighborhood greenness and outdoor physical activity among preschoolers. Inter J Health Geog 10: 66.    
  • 63. Routine immunization schedule [Internet]. Alberta Health; [cited 2013 Nov 09]. Available from: http://www.health.alberta.ca/health-info/imm-routine-schedule.html.
  • 64. PCTF (Postal Code Translator File), 2013, Alberta Health.
  • 65. ESRI: Environmental System Research Institute [Internet]. Redlands, CA (USA); [cited 2013 Apr 21]. Available from: http://www.esri.com.
  • 66. Preston S, Heuveline P, Guillot M (2000) Demography: Measuring and Modeling Population Processes, Blackwell Publishing, Oxford.
  • 67. Census Dictionary (2006). Statistics Canada, Catalogue no. 92-566-X.
  • 68. DMTI EPOI (2011) Enhanced Point of Interest, User Manual, V2011.3.
  • 69. Schoeppe S, Duncan MJ, Badland H, et al. (2014) Associations between children’s independent mobility and physical activity. BMC Public Health 14: 19.    
  • 70. Jones LR (2010) Investigating neighborhood walkability and its association with physical activity levels and body composition of a sample of Maryland adolescent girls. E & B T D, UMD Thesis and Dissertations.
  • 71. Walkscore [Internet]. USA; [cited 2013 Feb 17]. Available from: http://www.walkscore.com.
  • 72. Open data, Pathways and Bikeway [Internet]. City of Calgary; [cited 2013 Apr 21]. Available from http://www.calgary.ca/CSPS/Parks/Pages/Pathways/Pathways-in- Calgary.aspx.
  • 73. Brunsdon C, Charlton M, Harris P (2012) Living with collinearity in local regression models, Proceedings of the 10th Inter Sym Spatial Accur Ass Natural Res Environ Sci, Florianopolis SC, Brazil.
  • 74. Cho S-H, Lambert DM, Chen Z (2010) Geographically weighted regression bandwidth selection and spatial autocorrelation: an empirical example using Chinese agriculture data, App Eco L 17, 767-772.
  • 75. Wheeler D, Calder CA (2007) An assessment of coefficient accuracy in linear regression models with spatially varying coefficients, J Geog Sys 9, 145-166.
  • 76. Brunsdon C, Fotheringham AS, Charlton ME (1996) Geographically weighted regression: a method for exploring spatial non-stationarity. Geog Anal 28(4): 281-298.
  • 77. Weisent J, Rohrbach B, Dunn J, Odoi A (2012) Socioeconomic determinants of geographic disparities in campylobacteriosis risk: a comparison of global and local modeling approaches. Inter J Health Geog 11: 45.    
  • 78. Mennis J (2006) Mapping the results of geographically weighted regression. Cart J 43(2): 171-179.
  • 79. Ingalls EJ, Kolesar P, Walker WE (2008) Using simulation to develop and validate analytic models: some case studies. Operations Res 26(2): 237-253.
  • 80. Hovmand PS, Pitner R (2005) Combining system dynamics, social networks, and geographic information systems, perception of safety. Proceedings of the 23rd International Conference of the System Dynamics Society, July 17-21, 2005. Boston MA, USA.
  • 81. Forrester JW (1971) Principles of Systems. Waltham: Pegasus Communications, Inc.
  • 82. Sterman JD (2000) Business Dynamics: System Thinking and Modeling for a Complex World. Bosten, M: Irwin McGraw-Hill.
  • 83. Vensim. Ventana Systems Inc. [Internet]. Harvard, MA (USA); [cited 2013 May05]. Available from: http://vensim.com/.
  • 84. Babb C, Burke M, Tranter P (2011) Developing neighbourhood ‘walkability’ indices for children’s active transport, Proceedings of the Healthy City and Planning, Track 18, 3rd World Planning Schools Congress, Perth (WA).
  • 85. Holt NL, Spence JC, Sehn ZL, Cutumisu N (2008) Neighborhood and developmental differences in children’s perceptions of opportunities for play and physical activity. Health & Place 14(1): 2-14.
  • 86. Finn K, Johannsen N, Specker B (2003) Factors associated with physical activity in preschool children, J Pedi 140(1): 81-85.
  • 87. Weinberger R, Sweet MN (2012) Integrating walkability into planning practice, Transportation Research Record. J Transport Res B 2322: 20-20.    
  • 88. Robinson WS (2009) Ecological correlations and the behavior of individuals. Inter J Epidem38(2), 337-341.
  • 89. Openshaw S (1977) A geographical solution to scale and aggregation problems in region- building, partitioning, and spatial modelling. Transact I Brit Geog, New series 2, 459-472.
  • 90. Parenteau M-P, Sawada MC (2011) The modifiable areal unit problem (MAUP) in the relationship between exposure to NO2 and respiratory health. Inter J Health Geog 10(1), 58.

 

This article has been cited by

  • 1. Stefania Bertazzon, Rizwan Shahid, Schools, Air Pollution, and Active Transportation: An Exploratory Spatial Analysis of Calgary, Canada, International Journal of Environmental Research and Public Health, 2017, 14, 8, 834, 10.3390/ijerph14080834
  • 2. , Exploratory Temporal and Spatial Analysis of Myocardial Infarction Hospitalizations in Calgary, Canada, International Journal of Environmental Research and Public Health, 2017, 14, 12, 1555, 10.3390/ijerph14121555
  • 3. Yunmi Park, Max Garcia, Pedestrian safety perception and urban street settings, International Journal of Sustainable Transportation, 2019, 1, 10.1080/15568318.2019.1641577

Reader Comments

your name: *   your email: *  

Copyright Info: 2015, Rizwan Shahid, et al., licensee AIMS Press. This is an open access article distributed under the terms of the Creative Commons Attribution Licese (http://creativecommons.org/licenses/by/4.0)

Download full text in PDF

Export Citation

Copyright © AIMS Press All Rights Reserved