Abstract
Previous research has largely ignored the neighborhood’s vitality in creating a relaxing and safe environment for the prevalence of physical activity. Neighborhood vitality is critical for a healthy urban environment, and outdoor safety can only be ensured by reducing crime and repurposing underutilized spaces. A global regression and two local regressions are used to model the cross-sectional, ecological relationships between physical inactivity and multiple environmental variables in Chicago, United States. Multiscale geographically weighted regression showed the best model fit (R2 = 0.92). According to the findings, the factors influencing physical inactivity in Chicago neighborhoods are crime, green space, and vacant properties. Physical inactivity is rising in neighborhoods with a high share of 17 aged and younger and children living in poverty. Besides that, the relationships between neighborhood covariates and physical inactivity are spatially heterogeneous. Our study advocates for multiscale and multidisciplinary policies and institutions to create comfortable outdoor spaces for controlling and reducing physical inactivity prevalence.
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References
Anselin, L. (2001). Spatial Econometrics (p. 310330). Blackwell Publishing Ltd.
Basu, S., & Nagendra, H. (2021). Perceptions of park visitors on access to urban parks and benefits of green spaces. Urban Forestry & Urban Greening, 57, 126959.
Boulton, C., Dedekorkut-Howes, A., & Byrne, J. (2022). A ‘tug of war’ between more parks or better greenspace: The dilemma of meeting ‘community expectations’ with limited resources. Cities, 126(2022), 103665.
Buck, C., et al. (2019). Urban Moveability and physical activity in children: longitudinal results from the IDEFICS and I. Family cohort. International Journal of Behavioral Nutrition and Physical Activity, 16(1), 1–13.
Brunsdon, C., Fotheringham, S., & Charlton, M. (1998). Geographically weighted regression. Journal of the Royal Statistical Society: Series D (The Statistician), 47(3), 431–443.
Chander, G., Markham, B. L., & Helder, D. L. (2009). Summary of current radiometric calibration coefficients for Landsat MSS, TM, ETM+, and EO-1 ALI sensors. Remote Sensing of Environment, 113, 893–903.
Cheezum, R. R., et al. (2019). Using PhotoVoice to understand health determinants of formerly homeless individuals living in permanent housing in Detroit. Qualitative Health Research, 29(7), 1043–1055.
Congdon P. (2019). Obesity and Urban Environments. International Journal of Environmental Research and Public Health, 16(3), 464.
Craney, T. A., & Surles, J. G. (2002). Model-dependent variance inflation factor cutoff values. Quality Engineering, 14(3), 391–403.
de Souza Andrade, A. C., Mingoti, S. A., da Silva Costa, D. A., Xavier, C. C., Proietti, F. A., & Caiaffa, W. T. (2019). Built and social environment by systematic social observation and leisure-time physical activity report among Brazilian Adults: a population-based study. Journal of Urban Health : Bulletin of the New York Academy of Medicine, 96(5), 682–691.
Egerer, M., Fouch, N., Anderson, E. C., et al. (2020). Socio-ecological connectivity differs in magnitude and direction across urban landscapes. Science and Reports, 10, 4252.
Feng, X., & Astell-Burt, T. (2019). Can green space quantity and quality help prevent postpartum weight gain? A longitudinal study. Journal of Epidemiology and Community Health, 73(4), 295–302.
Faka, A., Chalkias, C., Georgousopoulou, E. N., Tripitsidis, A., Pitsavos, C., & Panagiotakos, D. B. (2019). Identifying determinants of obesity in Athens, Greece through global and local statistical models. Spatial and Spatio-Temporal Epidemiology, 29, 31–41.
Fotheringham, A. S., Brunsdon, C., & Charlton, M. (2003). Geographically weighted regression: The analysis of spatially varying relationships. John Wiley & Sons.
Fotheringham, A. S., Yang, W., & Kang, W. (2017). Multiscale geographically weighted regression (MGWR). Annals of the American Association of Geographers, 107(6), 1247–1265.
Fotheringham, A. S., Hanchen, Y., Wolf, L. J., Oshan, T. M., & Li, Z. (2022). On the notion of ‘bandwidth’ in geographically weighted regression models of spatially varying processes. International Journal of Geographical Information Science., 36, 1485–1502.
Gehl, J. (2001). Life between buildings: Using public space. The Danish Architectural Press.
Hohl, A., & Lotfata, A. (2022). A geographical analysis of socioeconomic and environmental drivers of physical inactivity in post pandemic cities: The case study of Chicago, IL,, USA. Urban Science., 6(2), 28. https://doi.org/10.3390/urbansci6020028
Hruby, A., & Hu, F. B. (2015). The epidemiology of obesity: A big picture. PharmacoEconomics, 33(7), 673–689.
Iyanda, A. E., & Osayomi, T. (2021). Is there a relationship between economic indicators and road fatalities in Texas? A multiscale geographically weighted regression analysis. GeoJournal, 86, 2787–2807.
Jacobs, J. (1961). The death and life of great American Cities. Vintage Books.
James, P., Banay, R. F., Hart, J. E., & Laden, F. (2015). A review of the health benefits of greenness. Current Epidemiology Reports, 2(2), 131–142.
Krayenhoff, E. S., Jiang, T., Christen, A., Martilli, A., Oke, T. R., Bailey, B. N., Nazarian, N., Voogt, J. A., Giometto, M. G., Stastny, A., & Crawford, B. R. (2020). A multi-layer urban canopy meteorological model with trees (BEP-Tree): Street tree impacts on pedestrian-level climate. Urban Climate, 32, 100590.
Kim, J., & Park, M. J. (2021). Multilevel effect of neighborhood social cohesion and characteristics on suicidal ideation among Korean older adults. Community Mental Health Journal, 57(3), 522–528.
Kohl, H. W., Craig, C. L., Lambert, E. V., Inoue, S., Alkandari, J. R., Leetongin, G., Kahlmeier, S., & Lancet Physical Activity Series Working Group (2012). The pandemic of physical inactivity: global action for public health. Lancet (London, England), 380(9838), 294–305.
Kondo, M. C., Morrison, C., Jacoby, S. F., Elliott, L., Poche, A., Theall, K. P., & Branas, C. C. (2018). Blight abatement of vacant land and crime in New Orleans. Public Health Reports, 133(6), 650–657.
Lane, J. M., & Davis, B. A. (2022). Food, physical activity, and health deserts in Alabama: the spatial link between healthy eating, exercise, and socioeconomic factors. GeoJournal. https://doi.org/10.1007/s10708-021-10568-2
Lopes, M. N., & Camanho, A. S. (2013). Public green space use and consequences on urban vitality: An assessment of European cities. Social Indicators Research, 113(3), 751–767.
Luo, M., Li, H., Pan, X., Fei, T., Dai, S., Qiu, G., Zou, Y., Vos, H., Luo, J., & Jia, P. (2021). Neighbourhood speed limit and childhood obesity. Obesity Reviews : an Official Journal of the International Association for the Study of Obesity, 22(Suppl 1), e13052.
Lunecke, M. G. H., & Mora, R. (2018). The layered city: Pedestrian networks in downtown Santiago and their impact on urban vitality. Journal of Urban Design, 23(3), 336–353.
Lindley, S., Pauleit, S., Yeshitela, K., Cilliers, S., & Shackleton, C. (2018). Rethinking urban green infrastructure and ecosystem services from the perspective of sub-Saharan African cities. Landscape and Urban Planning, 180, 328-338, ISSN 0169-2046 (2018)
Lynch, K. (1984). Good City Form; MIT Press: Cambridge. MA.
Maas, P. R. (1984). Towards a theory of urban vitality. Vancouver, BC, Canada: University of British Columbia.
Macfarlane, G. S., Boyd, N., Taylor, J. E., & Watkins, K. (2021). Modeling the impacts of park access on health outcomes: A utility-based accessibility approach. Environment and Planning b: Urban Analytics and City Science, 48(8), 2289–2306.
McGinn, A. P., Evenson, K. R., Herring, A. H., Huston, S. L., & Rodriguez, D. A. (2007). Exploring associations between physical activity and perceived and objective measures of the built environment. Journal of Urban Health : Bulletin of the New York Academy of Medicine, 84(2), 162–184.
Mouratidis, K., & Poortinga, W. (2020). Built environment, urban vitality and social cohesion: Do vibrant neighborhoods foster strong communities? Landscape and Urban Planning, 204, 103951.
Moran, P. A. (1950). Notes on continuous stochastic phenomena. Biometrika, 37(1/2), 17–23.
Moulay, A., Ujang, N., Maulan, S., & Ismail, S. (2018). Understanding the process of parks’ attachment: Interrelation between place attachment, behavioural tendencies, and the use of public place. City, Culture and Society, 14(2018), 28–36.
Nieuwenhuijsen, M. J., Khreis, H., Triguero-Mas, M., Gascon, M., & Dadvand, P. (2017). Fifty shades of green: Pathway to healthy urban living. Epidemiology (cambridge, Mass), 28(1), 63–71.
Oshan, T. M., Li, Z., Kang, W., Wolf, L. J., & Fotheringham, A. S. (2019). mgwr: A Python implementation of multiscale geographically weighted regression for investigating process spatial heterogeneity and scale. ISPRS International Journal of Geo-Information, 8(6), 269.
Oshan, T. M., & Fotheringham, A. S. (2018). A comparison of spatially varying regression coefficient estimates using geographically weighted and spatial-filter-based techniques. Geographical Analysis, 50(1), 53–75.
Openshaw, S., & Taylor, P. J. (1979). A million or so correlation coefficients: three experiments on the modifiable areal unit problem. In N. Wrigley & R. J. Bennett (Eds.), Statistical applications in the spatial sciences (Vol. 21, pp. 127–144). Pion: London.
Orstad, S. L., Szuhany, K., Tamura, K., Thorpe, L. E., & Jay, M. (2020). Park proximity and use for physical activity among urban residents: Associations with mental health. International Journal of Environmental Research and Public Health, 17(13), 4885.
Pinto, B., Ferreira, F., Spahr, R. W., Sunderman, M. A., & Pereira, L. F. (2022). Analyzing causes of urban blight using cognitive mapping and DEMATEL. Annals of operations research, 1–28. Advance online publication.
Rossi, F., Anderini, E., Castellani, B., Nicolini, A., & Morini, E. (2015). Integrated improvement of occupants’ comfort in urban areas during outdoor events. Building and Environment, 93, 285–292.
Richardson, E. A., Pearce, J., Mitchell, R., & Kingham, S. (2013). Role of physical activity in the relationship between urban green space and health. Public Health, 127(4), 318–324.
Sallis, J. F., Floyd, M. F., Rodríguez, D. A., & Saelens, B. E. (2012). Role of built environments in physical activity, obesity, and cardiovascular disease. Circulation, 125(5), 729–737.
Seefeldt, V., Malina, R. M., & Clark, M. A. (2002). Factors affecting levels of physical activity in adults. Sports Medicine, 32(3), 143–168.
Shanahan, D. F., Franco, L., Lin, B. B., Gaston, K. J., & Fuller, R. A. (2016). The benefits of natural environments for physical activity. Sports Medicine (auckland, N.z.), 46(7), 989–995.
Smith, R., & Miller, K. (2013). Eco-city mapping using GIS: Introducing a planning method for assessing and improving neighborhood vitality. Progress in Community Health Partnerships: Research, Education, and Action, 7(1), 95–106.
Sentell, T., Vamos, S., & Okan, O. (2020). Interdisciplinary perspectives on health literacy research around the world: more important than ever in a time of COVID-19. International Journal of Environmental Research and Public Health, 17, 3010.
U.S. Census Bureau. American Community Survey (ACS), 2014–2018 (5-Year) Socioeconomic Data. 2018. Available online: https://data.census.gov/cedsci/deeplinks?url=https%3A%2F%2Ffactfinder.census.gov%2F (accessed on 25 December 2021).
U.S. Centers for Disease Control and Prevention (CDC) (2021a). Social Determinants of Health. Available online: https://www.cdc.gov/socialdeterminants/about.html (accessed on 15 December 2021a).
U.S. Centers for Disease Control and Prevention (CDC) (2021b). PLACES Project. Local Data for Better Health. Available online: https://www.cdc.gov/places (accessed on 15 December 2021b).
U.S. Healthy Chicago. Available online: https://www.chicago.gov/city/en/depts/cdph/provdrs/healthychicago.html (accessed on 15 December 2021c).
U.S. Chicago Police Department. Available online: https://www.chicago.gov/city/en/depts/cpd.html (accessed on 15 December 2021d).
U.S. Chicago Health Atlas (CHA) Available from: https://chicagohealthatlas.org/. (accessed December 10, 2021e).
U.S. Chicago Data Portal (CDP), Crime, Available from: https://data.cityofchicago.org/resource/x2n5-8w5q.json. (Accessed December 2021f).
U.S. Chicago Health Dashborad (CHD), Children in poverty, Available from: https://www.cityhealthdashboard.com/?gclid=Cj0KCQjwpImTBhCmARIsAKr58czLuodi8c9nFQou8ZnYfj6JQrn-ksdmx7Rq3hWIx94yk8waGQlMg2QaAq5nEALw_wcB . (Accessed on 15 December 2021g).
U.S. American Community Survey (ACS). Available from: https://www.census.gov/geographies/mappingfiles/time-series/geo/tiger-line-file.html (Access 1 January 2022).
U.S. America Health Ranking, Available from: https://www.americashealthrankings.org/. (Accessed 10January 2022).
Van Rossum, G., & Drake, F. L. (2009). Python 3 Reference Manual. Scotts Valley, CA: CreateSpace.
WalletHub (2022). 2022's Best & Worst Cities for an Active Lifestyle. Available from: https://wallethub.com/edu/best-and-worst-cities-for-an-active-lifestyle/8817. (accessed December 5, 2021).
Wheeler, D., & Tiefelsdorf, M. (2005). Multicollinearity and correlation among local regression coefficients I, geographically weighted regression. Journal of Geographical Systems, 7(2), 161–187.
Wu, Z. J., Song, Y., Wang, H. L., Zhang, F., Li, F. H., & Wang, Z. Y. (2019). Influence of the built environment of Nanjing’s Urban Community on the leisure physical activity of the elderly: An empirical study. BMC Public Health, 19(1), 1459.
Xiao, Y., Miao, S., Zhang, Y., Xie, B., & Wu, W. (2022). Exploring the associations between neighborhood greenness and level of physical activity of older adults in shanghai. Journal of Transport & Health, 24, 101312.
Zhang, F., Loo, B. P. Y., & Wang, B. (2021). Aging in place: From the neighborhood environment, sense of community, to life satisfaction. Annals of the American Association of Geographers., 112, 1484–1499.
Zeng, C., Song, Y., He, Q., & Shen, F. (2018). Spatially explicit assessment on urban vitality: Case studies in Chicago and Wuhan. Sustainable Cities and Society, 40, 296–306.
Zumelzu, A., & Barrientos-Trinanes, M. (2019). Analysis of the effects of urban form on neighborhood vitality: Five cases in Valdivia, Southern Chile. Journal of Housing and the Built Environment, 34(3), 897–925.
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Lotfata, A., Helbich, M. Spatial analysis of neighborhood vitality determinants on physical activity: a case study of Chicago. GeoJournal 88, 2187–2197 (2023). https://doi.org/10.1007/s10708-022-10748-8
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DOI: https://doi.org/10.1007/s10708-022-10748-8