Skip to main content
SpringerLink
Log in

Characteristics of Urban Sidewalks/Streets and Objectively Measured Physical Activity

  • Published:
Journal of Urban Health Aims and scope Submit manuscript

Abstract

Several studies have found significant relationships between environmental characteristics (e.g., number of destinations, aesthetics) and physical activity. While a few of these studies verified that the physical activities assessed were performed in the environments examined, none have done this in an urban, neighborhood setting. This information will help efforts to inform policy decisions regarding the design of more “physically active” communities. Fourteen environmental characteristics of 60, 305-m-long segments, located in an urban, residential setting, were directly measured using standardized procedures. The number of individuals walking, jogging, and biking in the segments was assessed using an observation technique. The segments were heterogeneous with regards to several of the environmental characteristics. A total of 473 individuals were seen walking, bicycling, or jogging in the segments during 3,600 min of observation (60 min/segment). Of the 473 seen, 315 were walking, 116 bicycling, and 42 jogging. A greater number of individuals were seen walking in segments with more traffic, sidewalk defects, graffiti, and litter and less desirable property aesthetics. Only one environmental characteristic was associated with bicycling and none were significantly related with jogging. This study provides further evidence that environmental characteristics and walking are related. It also adds new information regarding the importance of scale (e.g., micro, macro) and how some environmental characteristics of urban, residential sidewalks and streets relate to physical activity.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Similar content being viewed by others

References

  1. Kakafika AI, Liberopoulos EN, Karagiannis A, Athyros VG, Mikhailidis DP. Dyslipidaemia, hypercoagulability and the metabolic syndrome. Curr Vasc Pharmacol. 2006;4(3):175–183.

    Article  PubMed  CAS  Google Scholar 

  2. Van Gaal LF, Mertens IL, De Block CE. Mechanisms linking obesity with cardiovascular disease. Nature. 2006;444(7121):875–880.

    Article  PubMed  CAS  Google Scholar 

  3. Kahn SE, Hull RL, Utzschneider KM. Mechanisms linking obesity to insulin resistance and type 2 diabetes. Nature. 2006;444(7121):840–846.

    Article  PubMed  CAS  Google Scholar 

  4. Garfinkel L. Overweight and cancer. Ann Intern Med. 1995;103:1034–1036.

    Google Scholar 

  5. World Health Organization (WHO). Obesity and overweight. Available at: http://www.who.int/dietphysicalactivity/publications/facts/obesity/en/. Accessed on March 13, 2007.

  6. Finkelstein EA, Fiebelkorn IC, Wang G. State-level estimates of annual medical expenditures attributable to obesity. Obes Res. 2004;12(1):18–24.

    PubMed  Google Scholar 

  7. Birmingham CL, Muller JL, Palepu A, Spinelli JJ, Anis HA. The cost of obesity in Canada. CMAJ. 1999;160(4):483–488.

    PubMed  CAS  Google Scholar 

  8. Von Lengerke T, Reitmeir P, John J. Direct medical costs of (severe) obesity: a bottom-up assessment of over- vs. normal-weight adults in the KORA-study region (Augsburg, Germany). Gesundheitswesen. 2006;68(2):110–115.

    Article  Google Scholar 

  9. Hill JO, Peters JC. Environmental contributions to the obesity epidemic. Science. 1998;280:1371–1374.

    Article  PubMed  CAS  Google Scholar 

  10. Poston WSC, Foreyt JP. Obesity is an environmental issue. Atherosclerosis. 1999;146:201–209.

    Article  PubMed  CAS  Google Scholar 

  11. Giles-Corti B, Donovan RJ. Relative influence of individual, social environmental, and physical environmental correlates of walking. Am J Public Health. 2003;93:1583–1589.

    PubMed  Google Scholar 

  12. Sallis JF, Hovell MF, Hofstetter CR, et al. Distance between homes and exercise facilities related to the frequency of exercise among San Diego residents. Public Health Rep. 1990;105:179–185.

    PubMed  CAS  Google Scholar 

  13. King WC, Belle SH, Brach JS, et al. Objective measures of neighborhood environment and physical activity in older women. Am J Prev Med. 2005;28(5):461–466.

    Article  PubMed  Google Scholar 

  14. Hoehner CM, Brennan Ramirez LK, Elliott MB, Handy SL, Brownson RC. Perceived and objective environmental measures and physical activity among urban adults. Am J Prev Med. 2005;28(2 Suppl 2):105–116.

    Article  PubMed  Google Scholar 

  15. Suminski RR, Petosa R, Poston C, Stevens E, Katzenmoyer L. Features of the neighborhood environment and walking by U.S. Adults. Am J Prev Med. 2005;28:149–155.

    Article  PubMed  Google Scholar 

  16. Huston SL, Evenson KR, Bors P, Gizlice Z. Neighborhood environment, access to places for physical activity, and leisure-time physical activity in a diverse North Carolina population. Am J Health Promot. 2003;18:58–69.

    PubMed  Google Scholar 

  17. Frank LD, Pivo G. Impacts of mixed use and density on utilization of three modes of travel: single-occupant vehicle, transit, and walking. Transp Res Rec. 1995;1466:44–52.

    Google Scholar 

  18. Replogle M. Integrating Pedestrian and Bicycle Factors into Regional Transportation Planning Models: Summary of State-of-the-art and Suggested Steps Forward. Environmental Defense Fund Report, July 20, 1995. Washington, DC: Environmental Defense; 1995.

    Google Scholar 

  19. Humpel N, Owen N, Leslie E. Environmental factors associated with adults’ participation in physical activity: a review. Am J Prev Med. 2002;22:188–199.

    Article  PubMed  Google Scholar 

  20. McKenzie TL. Use of direct observation to assess physical activity. In: Welk GJ, ed. Physical Activity Assessments for Health Related Research. Champaign, IL: Human Kinetics Publishers; 2002:179–195.

    Google Scholar 

  21. Bungum T, Meacham M, Truax N. The effects of signage and the physical environment on stair usage. J Phys Act Health. 2007;4(3):237–244.

    PubMed  Google Scholar 

  22. Sit CH, McManus A, McKenzie TL, Lian J. Physical activity levels of children in special schools. Prev Med. 2007;45(6):424–431.

    Google Scholar 

  23. Blair SN, Haskell WL, Ho P, et al. Assessment of habitual physical activity by a seven-day recall in a community survey controlled experiment. Am J Epidemiol. 1985;122:794–804.

    PubMed  CAS  Google Scholar 

  24. Suminski R, Petosa R, Stevens EA. Method for observing physical activity on residential sidewalks and streets. J Urban Health. 2006;83(3):434–443.

    Article  PubMed  Google Scholar 

  25. Frank LD, Schmid TL, Sallis JF, Chapman J, Saelens BE. Linking objectively measured physical activity with objectively measured urban form: findings from the SMARTRAQ. Am J Prev Med. 2005;28:117–125.

    Article  PubMed  Google Scholar 

  26. U.S. Census Bureau. American fact finder. Census 2000 summary file 3 (SF 3)-sample data. Accessed on: January 22, 2005. Available at: http://factfinder.census.gov.

  27. Pikora T, Giles-Corti B, Bull F, Jamrozik K, Donovan R. Developing a framework for assessment of the environmental determinants of walking and cycling. Soc Sci Med. 2003;56:1693–1703.

    Article  PubMed  Google Scholar 

  28. Landis JR, Koch GG. The measurement of observer agreement for categorical data. Biometrics. 1977;33:159–174.

    Article  PubMed  CAS  Google Scholar 

  29. Rothman KJ. No adjustments are needed for multiple comparisons. Epidemiology. 1990;1:43–49.

    Article  PubMed  CAS  Google Scholar 

  30. Sallis JF, Conway TL, Prochaska JJ, et al. The association of school environments with youth physical activity. Am J Public Health. 2001;91:618–620.

    Article  PubMed  CAS  Google Scholar 

  31. McKenzie TL, Sallis JF, Nader PR, Broyles SL, Nelson JA. Anglo-and Mexican American preschoolers at home and at recess: activity patterns and environmental influences. J Dev Behav Pediatr. 1992;13:173–180.

    Article  PubMed  CAS  Google Scholar 

  32. Sallis JF, Nader PR, Broyles SL, et al. Correlates of physical activity at home in Mexican-American and Anglo-American preschool children. Health Psychol. 1993;12:390–398.

    Article  PubMed  CAS  Google Scholar 

  33. Giles-Corti B, Broomhall MH, Knuiman M, et al. Increasing walking: how important is distance to, attractiveness, and size of public open space? Am J Prev Med. 2005;28:169–176.

    Article  PubMed  Google Scholar 

  34. Titze S, Stronegger WJ, Janschitz S, Oja P. Environmental, social, and personal correlates of cycling for transportation in a student population. J Phys Act Health. 2007;4:66–79.

    PubMed  Google Scholar 

  35. Centers for Disease Control and Prevention. Barriers to children walking and biking to school—United States, 1999. MMWR Morb Mortal Wkly Rep. 2002;51:701–704.

    Google Scholar 

  36. Giles-Corti B, Donovan RJ. Socioeconomic status differences in recreational physical activity levels and real and perceived access to a supportive physical environment. Prev Med. 2002;35:601–611.

    Article  PubMed  Google Scholar 

  37. Ball K, Bauman A, Leslie E, Owen N. Perceived environmental aesthetics and convenience and company area associated with walking for exercise among Australian adults. Prev Med. 2001;33:434–440.

    Article  PubMed  CAS  Google Scholar 

  38. DE Bourdeaudhuij I, Sallis JF, Saelens B. Environmental correlates of physical activity in a sample of Belgian adults. Am J Health Promot. 2003;18:83–92.

    PubMed  Google Scholar 

  39. Pikora TJ, Giles-Corti B, Knuiman MW, et al. Neighborhood environmental factors correlated with walking near home: using SPACES. Med Sci Sports Exerc. 2006;38:708–714.

    Article  PubMed  Google Scholar 

  40. Sallis JF, Saelens BE. Assessment of physical activity by self-report: status, limitations, and future directions. Res Q Exerc Sport. 2000;71(2):1–14.

    Google Scholar 

  41. Washburn RA, Heath GW, Jackson AW. Reliability and validity issues concerning large-scale surveillance of physical activity. Res Q Exerc Sport. 2000;71(2):104–113.

    Google Scholar 

  42. Troped PJ, Saunders RP, Pate RR, et al. Associations between self-reported and objective physical environmental factors and use of a community rail trail. Prev Med. 2001;32:191–200.

    Article  PubMed  CAS  Google Scholar 

  43. Saelens BE, Sailis JF, Black JB, Chen D. Neighborhood-based differences in physical activity: an environment scale evaluation. Am J Public Health. 2003;93:1552–1558.

    PubMed  Google Scholar 

  44. King WC, Brach JS, Belle S, et al. The relationship between convenience of destinations and walking levels in older women. Am J Health Promot. 2003;18:74–82.

    Google Scholar 

  45. Tan RW. (2007). Graffiti art—a solution to urban decay? EzineArticles. Accessed on: December 1, 2007. Available at: http://ezinearticles.com/?Graffiti-Art-A-Solution-to-Urban-Decay?&id=816264.

  46. Humpel N, Owen N, Iverson D, Leslie E, Bauman A. Perceived environment attributes, participant location, and walking for particular purposes. Am J Prev Med. 2004;26:119–125.

    Article  PubMed  Google Scholar 

  47. Sallis JF, Bauman A, Pratt M. Environmental and policy interventions to promote physical activity. Am J Prev Med. 1998;15:379–397.

    Article  PubMed  CAS  Google Scholar 

  48. Dishman RK, ed. Advances in Exercise Adherence. Champaign, IL: Human Kinetics; 1994.

  49. Sallis JF, Cervero R, Ascher WW, et al. An ecological approach to creating active living communities. Annu Rev Public Health. 2006;27:297–322.

    Article  PubMed  Google Scholar 

  50. Pikora TJ, Bull FCL, Jamrozik K, et al. Developing a reliable audit instrument to measure the physical environment for physical activity. Am J Prev Med. 2002;23:187–194.

    Article  PubMed  Google Scholar 

  51. Emery J, Crump C, Bors P. Reliability and validity of two instruments designed to assess the walking and bicycling suitability of sidewalks and roads. Am J Health Promot. 2003;18:38–46.

    PubMed  Google Scholar 

  52. Estabrooks PA, Lee RE, Gyurcsik NC. Resources for physical activity participation: does availability and accessibility differ by neighborhood socioeconomic status? Ann Behav Med. 2003;25:100–104.

    Article  PubMed  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Department of Physiology, Kansas City University of Medicine and Biosciences, 1750 Independence Ave., Kansas, MO, 64106, USA

    Richard R. Suminski & Melissa Hyder

  2. Department of Public Health Sciences, John A. Burns School of Medicine, University of Hawaii at Manoa, Honolulu, HI, USA

    Katie M. Heinrich

  3. Department of Basic Medical Sciences, University of Missouri-Kansas City School of Medicine, Kansas, MO, USA

    Walker S. C. Poston

  4. Department of Family Medicine, Kansas City University of Medicine and Biosciences, Kansas, MO, USA

    Sara Pyle

Authors
  1. Richard R. Suminski
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Katie M. Heinrich
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Walker S. C. Poston
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Melissa Hyder
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Sara Pyle
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Richard R. Suminski.

Additional information

Suminski and Hyder are with the Department of Physiology, Kansas City University of Medicine and Biosciences, Kansas, MO, USA; Heinrich is with the Department of Public Health Sciences, John A. Burns School of Medicine, University of Hawaii at Manoa, Honolulu, HI, USA; Poston is with the Department of Basic Medical Sciences, University of Missouri-Kansas City School of Medicine, Kansas, MO, USA; Pyle is with the Department of Family Medicine, Kansas City University of Medicine and Biosciences, Kansas, MO, USA.

Appendix

Appendix

Measures of Environmental Characteristics

  1. 1.

    Traffic volume: One 10-min observation period was randomly selected from the 5–6 p.m. time period, one from the 6–7 p.m. time period, and one from the 7–8 p.m. time period. During a 10-min observation period, an observer stationed at a randomly selected point in a segment counted the number of motorized vehicles passing by. Outcome variable: Total number of vehicles per 30 min of observation (multiple observation periods summated) per segment.

  2. 2.

    Traffic control efforts: Any efforts to reduce the volume and/or speed of motorized traffic. Examples include signs such as “Children at play,” speed limit signs, or speed bumps. Outcome variable: Total number of traffic control efforts per segment.

  3. 3.

    Streetlights: Any lamp supported on a lamppost whose purpose was to illuminate a street was counted during daylight hours. Outcome variable: Total streetlights per segment.

  4. 4.

    Sidewalk slab displacement (slab incongruence): The length and maximum visible height of unevenness of the spacers between sidewalk slabs. Measurements started with the spacer in front of the first slab of a segment and ended with the final spacer included in that segment. Visible height was used due to coverage of spacers by grass and weeds. Outcome variable: Percent of sidewalk incongruent per segment = [total area of slab incongruence per segment (m2)] ÷ [total sidewalk area of a segment (length * width)] * 100.

  5. 5.

    Defects: The maximum width, length, and depth in meters of all man-made and natural cracks, separations, or holes in sidewalks. Outcome variable: Percent of sidewalk defective per segment = [total volume of defective areas per segment (m3) ÷ total sidewalk volume of a segment (thickness 0.102 m * width * total length of sidewalk)] * 100.

  6. 6.

    Obstructions: A man-made or natural item was considered an obstruction if it extended into the sidewalk 0.2 m or more and was ≥0.15 m above the sidewalk. The height of an obstruction was measured to a maximum of 2.13 m. The width was measured at the most obtrusive part of the obstruction. The requirement of ≥0.15 m was imposed to eliminate the measurement of protruding surface grass, measured as separate variables (crack growth/peripheral overgrowth). The height value was selected to correspond to the maximum height of most humans. Outcome variable: Percent obstructed per segment = [volume of obstructions per segment (width * height * length) ÷ total sidewalk volume of a segment usable for human movement (height 1.98 m * sidewalk width * total length of sidewalk)] * 100.

  7. 7.

    Crack growth/peripheral overgrowth instances: Crack growth was any plant (dead or alive) growing in the slab cracks including the spacers between slabs with a maximum height of 0.15 m. Peripheral overgrowth was considered any plant form extending into the slab 0.2 m or more on either side of the slab, with a maximum height of 0.15 m. Outcome variable: Total number of crack growth and peripheral overgrowth instances per segment.

  8. 8.

    Grass height: The height of grass blades and weeds was determined at the first and last slab of each property in a segment. The measurement was taken at the midpoint of the slab, 50 cm into the property (away from the street). If no grass or weeds were present at this location, a second measurement was made at the quarter point of the slab nearest the end of the section. If no measures could be obtained at this point of the slab, the measurement procedures were conducted at the next slab towards the interior of the property. Outcome variable: Average property grass height in centimeters per segment.

  9. 9.

    Landscapable area: Landscapable area was determined by measuring the linear length of properties or empty lots in a segment that were or could be landscaped. Front yards/lots with grass and/or dirt were considered landscapable, whereas driveways, parking lots, and any other areas void of grass and/or dirt (e.g., paved front yards, paved empty lots, etc.) were considered not landscapable. Outcome variable: Percent of a segment landscapable = [linear meters of landscapable area ÷ total linear meters of a segment (both sides of the street: 610 m)] * 100.

  10. 10.

    Graffiti and/or other defacements: Any institutionally illicit, man-made marks anywhere on a property (house facades, street signs, sidewalks, etc.) considered illegal (e.g., vandalism) to the larger society were counted. Outcome variable: Percent of properties with graffiti per segment = [Instances of graffiti on a property per segment ÷ number of properties per segment] * 100.

  11. 11.

    Litter: Litter was defined as anything on the sidewalk and in an area 5 ft from the sidewalk into a property that did not perform a function or add to the landscape. Outcome variable: Total pieces of litter per segment.

  12. 12.

    Chipped paint: The presence or absence of cracked and/or chipped paint on the facades of properties was noted. Outcome variable: Percent of properties with chipped/cracked paint per segment = [Number of properties with chipped/cracked paint ÷ number of properties per segment] * 100.

  13. 13.

    Trees: Trees present in the area extending from the front of building structure to the street were counted. Outcome variable: Total number of trees per segment.

  14. 14.

    Flowers: presence of flowers on property (yes or no). Outcome variable: Percent of properties with flowers per segment = [Number of properties with flowers per segment ÷ total number of properties per segment] * 100.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Suminski, R.R., Heinrich, K.M., Poston, W.S.C. et al. Characteristics of Urban Sidewalks/Streets and Objectively Measured Physical Activity. J Urban Health 85, 178–190 (2008). https://doi.org/10.1007/s11524-007-9251-x

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11524-007-9251-x

Keywords

Search

Navigation