Differences in behavior, time, location, and built environment between objectively measured utilitarian and recreational walking
Introduction
The recently published United States Surgeon General's Call to Action to Promote Walking and Walkable Communities identifies policy gaps and provides future strategies, recognizing the multipurpose nature of walking (U.S. Department of Health and Human Services, 2015). Walking is a complex behavior with diverse motivations including travel (utilitarian walking) and leisure and exercise (recreational walking) (Tudor-Locke et al., 2006). While most researchers have recognized that different mechanisms may trigger and influence walking for these different purposes (Giles-Corti et al., 2005b, Lovasi et al., 2008, Saelens and Handy, 2008, Sugiyama et al., 2012, Tudor-Locke et al., 2006), many studies have treated walking as single behavior (Millward et al., 2013, Owen et al., 2004, Saelens and Handy, 2008). One review of studies on environmental correlates of walking argued that the lack of specificity in distinguishing between utilitarian and recreational walking weakens the predictive power of walking behavior models (Giles-Corti et al., 2005b). Effective interventions and policies to promote walking require specific understanding of why and where people walk.
A major challenge in distinguishing purposes of walking is the lack of standardized, objective, and robust methods to define walking behavior (Heath et al., 2006, Saelens and Handy, 2008, Sugiyama et al., 2012). In most studies stratifying utilitarian and recreational walking, data come from transportation and physical activity surveys or time diaries, in which respondents were asked to record perceived purpose or context of walking activity. The characterization of walking is inconsistent across studies (Kang et al., 2013). Dog walking was considered as utilitarian walking in one study (Agrawal and Schimek, 2007), recreational walking in another (Cutt et al., 2008), and as an independent category separate from recreational walking in yet another study (Yang and Diez-Roux, 2012). Some studies classified walking to a fitness facility as recreational walking (Agrawal and Schimek, 2007, Yang and Diez-Roux, 2012). Yet it could be argued that walking to a fitness facility has explicit transportation utility, because it replaces a trip by car or transit which would not be classified as driving or riding transit for recreation. The ambiguity between trip purpose and destination was also found in another study that defined walking while visiting historic sites as recreational walking (Tudor-Locke et al., 2007). Furthermore, self-reported data being subjective (Sugiyama et al., 2012) may lead to inconsistencies between or even within participants. Reported walking duration estimates are inaccurate. Recall bias in transportation surveys typically leads to underestimating the number of short walking trips, and social desirability bias generates average overestimation of physical activity in surveys making it difficult to quantify walking overall or by purpose (Lee et al., 2011, Wolf et al., 2003).
Shortcomings aside, prior studies pointed to many behavioral differences between utilitarian and recreational walking. In the U.S., utilitarian walking trips were consistently found to be shorter in time but more prevalent than recreational walking. In the 2001 and 2009 National Household Travel Survey (NHTS), the average duration of utilitarian walking trips was less than half that of recreational walking (Agrawal and Schimek, 2007, Yang and Diez-Roux, 2012). In the 2010 National Health Interview Survey (NHIS), the average utilitarian walking trip was 20% shorter than the average recreational walking trip (Paul et al., 2015). The 2003–2005 American Time Use Survey (ATUS) and the 2010 NHIS reported prevalence rates of walking for transportation or utilitarian walking to be 70–160% higher than those of walking for exercise or recreational walking (Paul et al., 2015, Tudor-Locke and Ham, 2008). However, all of these estimates and thus differences between utilitarian versus recreational walking were based on self-report. Furthermore, the afore-mentioned national surveillance systems have different assessment techniques and construct definitions of walking measures, thus resulting in widely varying estimates (Whitfield et al., 2015).
The impact of built environment factors on walking may also differ by walking purpose (Owen et al., 2004, Saelens and Handy, 2008, Sugiyama et al., 2012). In one study, hilly terrain was a barrier to utilitarian walking but it was a facilitator for recreational walking, ostensibly because hills afforded enjoyable vistas that attracted recreational walkers (Lee and Moudon, 2006b). Another study showed that the presence of shops, or the availability of public transport were less important in predicting recreational walking than utilitarian walking (Pikora et al., 2006). Land use mix patterns differed in their association with utilitarian and recreational walking in one recent study (Christian et al., 2011). A review found consistent and significant associations between utilitarian walking and the presence of nearby routine destinations (e.g., shops, services, transit stops) in 25 of the 31 studies reviewed. For recreational walking, results were inconsistent; 17 studies had null associations and 2 had unexpected negative associations between recreational walking and nearby presence of recreation-specific destinations (e.g., parks, playgrounds, sports fields) (Sugiyama et al., 2012).
Associations between purpose-specific walking and the built environment could be inaccurate because of the spatial mismatch between where walking actually occurred and where built environment attributes were measured (Sugiyama et al., 2012). Because of a lack of information on where people actually walked, most prior studies examined associations between home neighborhood characteristics and walking outcomes (Perchoux et al., 2013). The spatial mismatch between walking activity and environment is beginning to be explored in studies tracking participants’ GPS locations and accelerometer-based physical activity. In two studies, between 40% and 50% of moderate or vigorous physical activity (which may or may not include walking) occurred outside of participants’ home neighborhoods, defined as buffers of 1666 m-to-1855 m radii from home locations (Hurvitz et al., 2014a, Troped et al., 2010). Notably, another study found that built environment features significantly differed between participants’ home neighborhoods and their visited locations beyond home neighborhoods, in terms of neighborhood composition, utilitarian destinations, transportation infrastructure, and traffic conditions (Hurvitz and Moudon, 2012). The spatial mismatch between built environment and walking may be further confounded by walking purpose. However, studies with concurrent data on the location and purpose of walking are few (Spinney et al., 2012). To analyze the influence of the environment and inform interventions, it is important to identify the locations of walking activity by purpose.
The present study offers operational definitions and methods to classify the two walking purposes to address the issue of classification standardization. Second, the study explores the multidimensional properties of utilitarian and recreational walking regarding the duration, activity intensity, speed, and time and location distributions of the activity based on a large sample of participants living in a U.S. metropolitan area. Finally, it examines the built environment characteristics of where walking actually occurred.
Section snippets
Participants
Participants in the present study were from the 2008–2009 baseline sample of the Travel Assessment and Community study, which examined the effects on physical activity of a new light-rail system to be planned to open in King County, Washington (Saelens et al., 2014). Participants were selected who lived close to (≤1.6-km) or far from (>1.6 km) future light rail stops, and were matched for household income, ethnicity/race composition, residential property values, residential density, housing
Results
After excluding study participants who had either no GPS data or no travel diary data (n = 3); who did not return the survey questionnaire (n = 19); and whose accelerometer data did not show any physical activity bout during the 7-day assessment period (n = 28), the final sample consisted of 651 participants with 4288 person-days (mean = 6.6 days per person; SD = 1.7). The sample characteristics and home built environments are provided in Table 1.
The sample yielded a total of 6528 raw walking bouts, of
Discussion
The present study clearly showed that walking is not a single behavior, and the observed walking bouts included two distinctively different types of walking. Differences between utilitarian (87.4% of walking bouts) versus recreational walking (12.6%) were largest in terms of walking duration (d = 0.967) and built environment characteristics (densities of residential units, jobs, and street intersections; d ranging from 0.816 to 0.902). The different spatial and temporal distributions of
Conclusion
The present study introduced a new operational definition for classifying utilitarian and recreational walking, which focused on one objective activity feature, having a destination, but not on self-reported activity purpose. This approach may be useful for other studies even with relatively simple data. The findings clearly indicate that utilitarian and recreational walking are substantially different in terms of frequency, speed, duration, and location. Stratification by purpose, location and
Acknowledgments
This study was funded by NIH/NHLBI R01HL091881 and by the Washington Transportation Center TransNow Research Project Agreement No. 61‐7318.
References (58)
- et al.
Extent and correlates of walking in the USA
Transp. Res. Part D Environ.
(2007) - et al.
Psychosocial and environmental factors associated with physical activity among city dwellers in regional Queensland
Prev. Med.
(2005) - et al.
Urban trails and physical activity: a natural experiment
Am. J. Prev. Med.
(2010) - et al.
Stepping towards causation: do built environments or neighborhood and travel preferences explain physical activity, driving, and obesity?
Soc. Sci. Med.
(2007) - et al.
Increasing walking: how important is distance to, attractiveness, and size of public open space?
Am. J. Prev. Med.
(2005) - et al.
Home versus nonhome neighborhood: quantifying differences in exposure to the built environment
Am. J. Prev. Med.
(2012) - et al.
How far from home? The locations of physical activity in an urban US setting
Prev. Med.
(2014) - et al.
The 3Ds+R: Quantifying land use and urban form correlates of walking
Transp. Res. Part D Environ.
(2006) - et al.
Validity of the international physical activity questionnaire short form (IPAQ-SF): a systematic review
Int. J. Behav. Nutr. Phys. Act
(2011) - et al.
Active-transport walking behavior: destinations, durations, distances
J. Transp. Geogr.
(2013)
Understanding environmental influences on walking: review and research agenda
Am. J. Prev. Med.
Conceptualization and measurement of environmental exposure in epidemiology: accounting for activity space related to daily mobility
Health Place
Active transportation and physical activity: opportunities for collaboration on transportation and public opportunities health research
Transp. Res. Part A Policy Pract.
Walking trends among U.S. adults: the Behavioral Risk Factor Surveillance System, 1987–2000
Am. J. Prev. Med.
The built environment and location-based physical activity
Am. J. Prev. Med.
Walking distance by trip purpose and population subgroups
Am. J. Prev. Med.
Walking and measurement
Med. Sci. Sports Exerc.
How important is the land use mix measure in understanding walking behaviour? Results from the RESIDE study
Int. J. Behav. Nutr. Phys. Act
A power primer
Psychol. Bull.
Does getting a dog increase recreational walking?
Int. J. Behav. Nutr. Phys. Act
Travel and the built environment: a synthesis
Transp. Res. Rec.
Travel and the built environment
J. Am. Plann. Assoc.
Urban form, travel time, and cost relationships with tour complexity and mode choice
Transportation
Impacts of mixed use and density on utilization of three modes of travel: single-occupant vehicle, transit, and walking
Transp. Res. Rec.
Understanding physical activity environmental correlates: increased specificity for ecological models
Exerc. Sport Sci. Rev.
Associations among Active Transportation, Physical Activity, and Weight Status in Young Adults
Obesity
Participation by US adults in sports, exercise, and recreational physical activities
J. Phys. Act Health
The effectiveness of urban design and land use and transport policies and practices to increase physical activity: a systematic review
J. Phys. Act Health
Emerging technologies for assessing physical activity behaviors in space and time
Front. Public Health
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