Explaining the spatial association between the objective and perceived walkability of urban neighborhoods (Case study: districts of 4, 8 and 13 of Tehran city)

Document Type : Original Research

Authors
I. Asadi
P. Maleki
University of Mazandaran, Faculty of Arts and Architecture, Department of Urban Planning
Abstract
Extended Abstract

Introduction

A large number of researches demonstrated that built environment attributes affect the walking and cycling for transportation (Ewing & Cervero, 2010; Bauman et al., 2012). Studies examining the potential effect of the built environment on physical activity have employed objective and/or perceived (self-report) measures to assess characteristics of the neighborhood environment. Findings illustrated people who live in neighborhoods with traditional or walkable designs report about 30 minutes more walking for transportation each week and more total physical activity, compared to those who live in neighborhoods with less walkable suburban designs (Frank, et al., 2006). Therefore, the association between the built environment and walking activity are complicated due to spatial heterogeneity, self-selection issues such as attitudes and perceptions on walking behavior, and methodological differences (Lee, et al., 2017). Some evidence shows that residents’ self-reports of their neighborhood environment may be less revealing than are objective assessments. However, other studies suggest that perceived neighborhood environment exerts a unique effect and may be a more telling indicator for individual health than objective neighborhood characteristics (Wen et al., 2006). So, the aim of this research is discovering the preferences of the residence towards the walkable spaces and explaining spatial association of the perceived and objective measures of neighborhood walkability in district of 4, 8 and 13 of Tehran.

Methodology

This research is a descriptive and exploratory research that has been conducted with quantitative research approach. In this regard, GIS software were used to mapping the neighborhood walkability criteria. Network analyst functions, also, was used in order to service area determination and accessibility to public services. Exploratory factor analysis and multiple regression were cooperatively employed with regard to reduce the set of variables and extract variables that explain the objective and perceived measures of neighborhoods walkability at a 95% confidence interval in Tehran metropolitan. In relation to perceived measure of neighborhoods walkability, we used the standard questionnaire developed by Saelens et al. (2002), as well as Cerin et al. (2006), has been developed as Neighborhood Environment Walkability Scale (NEWS). The questionnaire has the following dimensions: Time taken to get from residence home to the nearest businesses or facilities, Access to services, Streets condition or quality in the neighborhood, Places for walking and cycling, Neighborhood surroundings, Safety from traffic, Safety from crime neighborhood satisfaction. In the present study for each neighborhood, walkability index, which is the sum of the standard Z score of four urban form metrics, is defined as a function of net residential density (ratio of the number of residential units to residential areas in each neighborhood per hectare), sum of the ratio of floor area of retail units to their parcels in each neighborhood, Land-use mix index (entropy coefficient) and street connectivity (Number of intersections with 3 or more legs per km2). Also, census data, land use and road layers and survey data were used. The statistical population of the present study is the population of all districts of the 22 districts of Tehran. The statistical samples which selected by purposeful method were 31 neighborhoods.

Results and discussion

Findings revealed that the gap between the objective and the perceived walkability, except the component of walking and cycling places, the rest of the studied dimensions, including the time of access to shops or stores, facilities, etc., access to services; neighborhood streets; neighborhood environment; perceived security of traffic and crime; and the satisfaction of the neighborhood in relation to subjective pedestrian assessment have a higher mean in neighborhoods with high objective walkability compared to those with low walkable neighborhoods. Research findings in regard to the people preferences about the walkable spaces are in line with other studies. Residents of our case study in connection with the issue of walking, as well as people from other parts of the world, prefer spaces with appropriate access to services, facilities and infrastructure needed for everyday life, and safe, attractive, lively and free of contamination and traffic environments as well as well-defined spaces for walking. The point that needs to be mentioned is the population density, the density of residential units, as well as the density of activities (commercial and service as well as offices or administrative activities). In most previous investigations, mainly in link to walking, built environment with urban sprawl form are compared to more compact cities or so-called smart cities with mixed and diverse land uses, and the result is typically that urban environments which have a dense and smart urban form that are high in density of population, activity and residential are reported proper for walking behavior. In this regard, although the urban form of the studied neighborhoods of this research compared to many previous case studies in terms of those variables, is still more compact, according to the participants’ opinion, they prefer to walkability of their residential spaces, neighborhoods that have diverse land uses (cloth stores, food markets, supermarkets, juices and ice cream shops, home appliances malls and etc.), as well as green and open spaces and environments that have more attractive facets.

Conclusion

In order to achieve the appropriate developmental model to increase the subjective and objective walkability of urban neighborhoods, some steps must be taken to increase the green and public open spaces and redistribute the land uses in accordance with the urban smart growth pattern, by through less dependence on the personal car usage, many challenges of Tehran metropolitan will reduce in line with sustainable development.

Keywords

Subjects

1. Abdollahi A.A, Fatahi M. (2017). Evaluation of smart urban growth indicators using ELEKTRE technique (Case study: regions of Kerman city). MJSP. 21 (2):147-171 URL: http://journals.modares.ac.ir/article-21-11656-fa.html (In Persian)
2. Adams, M. A., Todd, M., Kurka, J., Conway, T. L., Cain, K. L., Frank, L. D., & Sallis, J. F. (2015). Patterns of walkability, transit, and recreation environment for physical activity. American journal of preventive medicine, 49(6), 878-887.
3. Arvidsson, D., Kawakami, N., Ohlsson, H., & Sundquist, K. (2012). Physical activity and concordance between objective and perceived walkability. Med Sci Sports Exerc, 44(2), 280-7.
4. Asadi R, shahabian P. (2017). Planning and Assessing the Walkability of Tajrish Metro stations by ANP & QFD. MJSP. 21 (1):253-278 URL: http://journals.modares.ac.ir/article-21-10776-fa.html (In Persian)
5. Azadi Ghatar. S, Meshkini, A., Eftekhari, R.A., Mostafavi E., Ahadnejad Reveshti M. (2017). Explanation of Relationship between Urban Walkability and Death Spatial Distribution caused by Colorectal and Breast Cancer. MJSP. 21 (3):55-94 URL: http://journals.modares.ac.ir/article-21-6831-fa.html (In Persian)
6. Azmi, D. I., & Karim, H. A. (2018). Promoting Sustainable Urban Neighborhood towards Walkability. Asian Journal of Environment-Behaviour Studies, 3(8), 167-175.
7. Bauman, A. E., Reis, R. S., Sallis, J. F., Wells, J. C., Loos, R. J., Martin, B. W., & Lancet Physical Activity Series Working Group. (2012). Correlates of physical activity: why are some people physically active and others not?. The lancet, 380(9838), 258-271.
8. Cerin E, Cain KL, Conway TL, Van Dyck D, Hinckson E, Schipperijn J, De Bourdeaudhuij I, Owen N, Davey RC, Hino AA, Mitáš J, Orzanco-Garralda R, Salvo D, Sarmiento OL, Christiansen LB, Macfarlane DJ, Schofield G, Sallis JF. (2014). Neighborhood environments and objectively measured physical activity in 11 countries. Med Sci Sports Exerc. 46(12): 2253–64.
9. Cerin, E., Macfarlane, D. J., KO, H. H., & Chan, K. C. A. (2007). Measuring perceived neighbourhood walkability in Hong Kong. Cities, 24(3), 209-217.
10. Cerin, E., Saelens, B. E., Sallis, J. F., & Frank, L. D. (2006). Neighborhood Environment Walkability Scale: validity and development of a short form. Medicine & Science in Sports & Exercise, 38(9), 1682-1691.
11. Ding, D., & Gebel, K. (2012). Built environment, physical activity, and obesity: what have we learned from reviewing the literature? Health & place, 18(1), 100-105.
12. Eom, H. J., & Cho, G. H. (2015). Exploring thresholds of built environment characteristics for walkable communities: Empirical evidence from the Seoul Metropolitan area. Transportation Research Part D: Transport and Environment, 40, 76-86.
13. Ewing, R., & Cervero, R. (2010). Travel and the built environment: a meta-analysis. Journal of the American planning association, 76(3), 265-294.
14. Ferrer, S., & Ruiz, T. (2018). The impact of the built environment on the decision to walk for short trips: Evidence from two Spanish cities. Transport policy, 67, 111-120.
15. Frank, L. D., Sallis, J. F., Conway, T. L., Chapman, J. E., Saelens, B. E., & Bachman, W. (2006). Many pathways from land use to health: associations between neighborhood walkability and active transportation, body mass index, and air quality. Journal of the American planning Association, 72(1), 75-87.
16. Frank, L. D., Sallis, J. F., Saelens, B. E., Leary, L., Cain, K., Conway, T. L., & Hess, P. M. (2010). The development of a walkability index: application to the Neighborhood Quality of Life Study. British journal of sports medicine, 44(13), 924-933.
17. Hirsch, J. A., Moore, K. A., Evenson, K. R., Rodriguez, D. A., & Roux, A. V. D. (2013). Walk Score® and Transit Score® and walking in the multi-ethnic study of atherosclerosis. American journal of preventive medicine, 45(2), 158-166.
18. Khoshdel, A. R., Ziaei, M., Ghaffari, H. R., Azadi, S., & Alimohamadi, Y. (2018). The Prediction Number of New Cases and Death of Gastric Cancer among Iranian Military Community during 2007-2019. Multidisciplinary Cancer Investigation, 2(2), 14-19.
19. King, W. C., Brach, J. S., Belle, S., Killingsworth, R., Fenton, M., & Kriska, A. M. (2003). The relationship between convenience of destinations and walking levels in older women. American Journal of Health Promotion, 18(1), 74-82.
20. Lee, H. S., & Park, E. Y. (2015). Use of Neighborhood Facilities and Perception of Walking Environment in Older Rural Women-Focused on the Chungnam Province. Journal of Korean Society of Rural Planning, 21(3), 59-66.
21. Lee, S., Sung, H., & Woo, A. (2017). The Spatial Variations of Relationship between Built Environment and Pedestrian Volume: Focused on the 2009 Seoul Pedestrian Flow Survey in Korea. Journal of Asian Architecture and Building Engineering, 16(1), 147-154.
22. Leslie, E., Saelens, B., Frank, L., Owen, N., Bauman, A., Coffee, N., & Hugo, G. (2005). Residents’ perceptions of walkability attributes in objectively different neighbourhoods: a pilot study. Health & place, 11(3), 227-236.
23. Lotfi, S., & Koohsari, M. J. (2011). Neighborhood walkability in a city within a developing country. Journal of Urban Planning and Development, 137(4), 402-408.
24. Mansfield, Theodore J. (2016). Health impacts of transportation and the built environment: A quantitative risk assessment (Doctoral dissertation, The University of North Carolina at Chapel Hill).
25. Martínez-Martínez, O. A., & Ramírez-López, A. (2018). Walkability and the built environment: validation of the Neighborhood Environment Walkability Scale (NEWS) for urban areas in Mexico. Quality & Quantity, 52(2), 703-718.
26. Moeini, S. M. (2006). Increasing walkability: steps towards a more human city, HONAR-HA-YE-ZIBA, 27(27) - Serial Number 1192, pp 5-16. (In Persian)
27. Mohammadi, S. and Mahin N. (2015). An Analysis of the association between urban form and Public Health: emphasizing of resident’s movement patterns, Third International Congress on Civil Engineering, Urban Architecture and Development, Tehran. https://www .civilica.com / Paper-ICSAU03-ICSAU03_1676.html (In Persian).
28. Nielsen, T. A. S., & Skov-Petersen, H. (2018). Bikeability–Urban structures supporting cycling. Effects of local, urban and regional scale urban form factors on cycling from home and workplace locations in Denmark. Journal of Transport Geography, 69, 36-44.
29. Nyunt, M. S. Z., Shuvo, F. K., Eng, J. Y., Yap, K. B., Scherer, S., Hee, L. M., ... & Ng, T. P. (2015). Objective and subjective measures of neighborhood environment (NE): relationships with transportation physical activity among older persons. International journal of behavioral nutrition and physical activity, 12(1), 108.
30. Reza Zadeh R., Esfandiar Z. And Latifi Scuya, L. (2011). Perceptual measurement of neighborhood walkability and its influential factors in neighborhoods (Case study: Chizar neighborhood), Urban Management, 9(28) pp 297 -313. (In Persian)
31. Rigolon, A., Toker, Z., & Gasparian, N. (2018). Who has more walkable routes to parks? An environmental justice study of Safe Routes to Parks in neighborhoods of Los Angeles. Journal of Urban Affairs, 40(4), 576-591.
32. Rosso, A. L., Auchincloss, A. H., & Michael, Y. L. (2011). The urban built environment and mobility in older adults: a comprehensive review. Journal of aging research, 2011.
33. Saelens, B. E., Sallis, J. F., Black, J., & Chen, D. (2002). Neighborhood Environment Walkability Scale (NEWS).
34. Safari Shali, R. and Habibpour, K. 2012. Comprehensive Guide to SPSS in Survey Research (Quantitative Data Analysis), Tehran: Loyeh publications. (In Persian)
35. Sahafnia, B. (2008). Measuring the policy effects of building urban trails in promoting quality of the urban environment (case study: tarbiat tabriz tabriz), Master thesis of Urban Planning, Faculty of Arts and Architecture, Tarbiat Modares University. (In Persian).
36. Statistics Center of Iran (2011). Census blocks data of Tehran city.
37. Sung, H., & Lee, S. (2015). Residential built environment and walking activity: Empirical evidence of Jane Jacobs’ urban vitality. Transportation Research Part D: Transport and Environment, 41, 318-329.
38. Tajik, A., and Partovi, P. (2014). Walkability Conceptual Model and Analytical Framework with the Emphasis on New Urbanism Approach (case study: 4th phase of Mehrshahr). Motaleate Shahri, 3(9), 81-96. (In Persian).
39. Tehran Municipality ICT Organization. (2010). Urban land use base maps, GIS Department.
40. Tehran Municipality ICT Organization. (2012). Urban Road layer, GIS Department.
41. Tuckel, P., & Milczarski, W. (2015). Walk ScoreTM, perceived neighborhood walkability, and walking in the US. American journal of health behavior, 39(2), 242-256.
42. Wang, Y., Chau, C. K., Ng, W. Y., & Leung, T. M. (2016). A review on the effects of physical built environment attributes on enhancing walking and cycling activity levels within residential neighborhoods. Cities, 50, 1-15.
43. Wen, M., Hawkley, L. C., & Cacioppo, J. T. (2006). Objective and perceived neighborhood environment, individual SES and psychosocial factors, and self-rated health: An analysis of older adults in Cook County, Illinois. Social science & medicine, 63(10), 2575-2590.
44. www.ipaq.ki.se/scoring.htm
The Journal of Spatial Planning and Geomatics
Volume 23, Issue 4
December 2019
Pages 147-191