Physical inactivity increases the risk of chronic diseases (2,7). Given that low proportions of adults meet typical guidelines for health benefit (30 min or more of moderate- to vigorous-intensity activity on most days of the week) (3,55), promoting physical activity is a public health priority (37). Walking has become a focus of public health strategies designed to promote active lifestyles (17) because it is a common behavior with known health benefits (46), can be incorporated in daily living, requires no special equipment or facilities, and can be amenable to change (39). There is the potential to bring about widespread and sustainable increases in adults’ physical activity by creating environments that facilitate walking (67). Such environmental initiatives need to be informed by evidence on the specific attributes that can influence walking for particular purposes (34,56).
Of the reviews on environmental correlates of adults’ physical activity (4,23,27,41,66,79) and walking (23,56,64,65), the most recent review summarizing evidence on walking for specific purposes (64) was published in 2008, dealing with studies published from 2005 to May 2006; many empirical studies on environmental correlates of walking have been published subsequently. There is a more recent review on walking (23), but it did not stratify walking by purposes and focused on environmental attributes aligned with a particular planning principle (smart growth). There is increasing recognition of the need to examine walking for specific purposes (20) and to synthesize research evidence in ways that facilitate research translations, particularly for those in the planning and transport sectors (53). Studies to date have examined environmental correlates of domain-specific physical activity behaviors, and reviews follow this distinction, focusing on active transport (walking and cycling for transport) (66) or utilitarian and recreational walking (56,64). However, concerning environmental attributes, studies have examined them in various ways, depending on the focus of the study and the instrument used; some attributes were also combined to produce higher level dimensions. For instance, studies have used concepts consisting of several aspects of the environment, such as comfort (1,8), compact neighborhood (15), functionality (58,75), and activity friendliness (28). The term “accessibility” is used in different ways in different studies: many studies consider this as the presence of or distance to neighborhood destinations, but several studies define this as a mixture of route qualities and availability of destinations (1,40), the presence or maintenance of walking paths (57), and whether cost is involved in using recreational facilities (38).
In this review, a specific framework, building on models developed in planning and transport research, is applied to organize environmental factors (Fig. 1). It focuses on neighborhood environments because much of adults’ walking often takes place in their neighborhoods (33,73). This framework first separates the environment into two key dimensions: destinations and routes (to destinations). Destinations are further divided into two types: utilitarian (e.g., shops, services, transit stops) and recreational (e.g., parks, playgrounds, sports fields). For each destination type, three attributes are then considered: presence, proximity, and quality. This review focuses on destinations per se, rather than on land use mix as examined in previous reviews (4,23,64–66) because this allows examination of how walking is related to the specific attributes of destinations. Attributes of routes include sidewalks (e.g., availability, maintenance), street connectivity (e.g., intersection density, block size), aesthetics (e.g., interesting things to look at, scenery, attractive buildings, incivilities), traffic (e.g., speed, volume, noise), and safety (e.g., crime, lighting); these five route attributes are broadly consistent with those identified by the previous review (64).
The proposed framework builds on a concept of environmental dimensions relevant to walking, which consists of “3Ds”: density, diversity, and design (11). Two of the 3Ds, density and diversity, are interrelated and concerned with the access to destinations such as retail outlets, services, workplaces, or places for recreation. Neighborhoods with higher population densities and diverse land uses typically have increased access to a range of utilitarian and recreational destinations; design, on the other hand, is mainly concerned with the quality of routes to reach destinations, such as sidewalk availability, street connectivity, and neighborhood aesthetics (11). This specificity has practical and policy targets because environmental initiatives involve many distinct aspects that are managed by different agencies such as urban planning, urban design, and recreation and sport facility planning (64,65).
We examine current evidence on the associations of utilitarian and recreational walking with the attributes of neighborhood destinations and routes.
Database search strategy.
A systematic literature search was conducted in April 2011 with Web of Science, PubMed, Transport Research Information Services, GEOBASE, and SPORTDiscus using three sets of search terms: environmental attributes (environment, neighborhood, urban form, urban design, destination, facility, access, proximity, space, sidewalk, footpath, connectivity, aesthetic, traffic, safety), activity (physical activity, walk, walking, nonmotorized), and purpose of walking (transport, utilitarian, commuting, recreation, leisure, exercise). Studies with children and adolescents were excluded, and the searches were limited to English-language publications, but no limitation was applied for the search period.
Inclusion and exclusion criteria.
The initial search produced 415 articles, after excluding duplicates. Publications in conference proceedings, review articles, articles in unrelated disciplines, and nonacademic literature (n = 204) were removed by judging from the title and source of articles, resulting in 211 articles. The abstracts and/or full texts of the remaining articles were examined by two authors for eligibility (T.S., M.N.). The main inclusion criterion was studies examining associations of neighborhood environmental attributes, which fit the proposed framework, with utilitarian and/or recreational walking. The exclusion criteria were studies without quantitative analysis, studies using overall environmental indicators such as walkability and sprawl, studies examining overall walking only, studies examining environments but not in neighborhood settings (e.g., workplace), and studies reporting bivariate analysis only. In this process, 170 articles were removed, resulting in 41 articles. They were complemented by five articles obtained from recent literature reviews (64,79). The total number of articles included was 46.
Information extracted included study location, sample size, outcome variables, environmental attributes, measurement methods of environmental attributes (objective or perceived), covariates, and results. Nonmodifiable environmental attributes such as the presence of hills and access to a beach were excluded. In the case of destinations, the distinction between presence and proximity was not always clear. Variables using objectively measured distance or proximity categories (either objective or perceived) were considered as proximity. However, “the presence of destinations within a certain distance,” which was used in several studies, was considered as presence. All articles included were examined independently by two authors (T.S., M.N.). Agreement was reached through discussion when they disagreed.
Results were coded into “significant positive association only in subgroups” (+S), “mixed association” (Mix), “nonsignificant association” (N), and “significant negative association” (−S). A +S refers to a significant (P < 0.05) relationship between an environmental attribute and walking in a direction consistent with a hypothesis. For instance, the presence of more destinations is expected to be associated with more walking. If a study found fewer destinations to be associated with more walking, it was considered a negative association. Mixed associations apply to a situation where a +S is reported only for subsamples. This review extracted not only significant associations but also N. For instance, variables included in the initial analysis but screened out before the final analysis were categorized as nonsignificant.
When a study reported many models (e.g., unadjusted, adjusted for sociodemographic variables, and further adjusted for other environmental attributes), we report the results from models adjusted for sociodemographic variables. This is partly because the present review aims to identify potential high-leverage environmental factors from the literature across studies (rather than within individual studies). Studies that used both objective and perceived measures of a particular environmental attribute were treated as separate investigations, and both results were listed individually. However, in a study that used many items to measure the same environmental attribute (e.g., perceived traffic volume and perceived traffic speed), they were not treated as separate cases. In these cases, if any item for the environmental attribute was significantly associated with walking, the particular attribute was reported as significant. The results were organized in this way because listing individual items would overrepresent results from particular studies (many studies combined variables into one dimension, often using principle component analysis).
Table 1 shows the details of the 46 articles identified. About one fifth of the studies (n = 9) reviewed were included in the most recent review by Saelens and Handy (64), with two-thirds of the articles (n = 31) published after their review. This suggests that research examining specific environmental attributes and specific types of walking has been conducted relatively recently. One-half of the studies were conducted in North America (n = 23), with 11 in Australia and eight in Europe. Studies conducted in South America (n = 3) and in Japan (n = 1) were reported after 2009. The majority of studies reviewed used general adults as a sample (n = 33, of which 9 studies excluded older adults). However, some studies focused on specific populations such as middle-age and older adults (n = 6), older adults (n = 2), women (n = 2), those with type 2 diabetes (n = 2), and parents of primary school children (n = 1). Sample size ranged from 133 to 38,359; about one-third of the studies had a sample size smaller than 1000 (n = 17), and less than 20% of them used a sample size larger than 3000 participants (n = 8). For outcome variables, about two-thirds of the studies used categorical outcomes in which walking was divided into some levels (n = 30); other studies used walking duration (n = 7), frequency (n = 6), and percent mode share (n = 3). More than half of the studies (n = 24) included both utilitarian and recreational walking, nine included utilitarian walking only, and 13 included recreational walking only. Twenty-six studies examined both destination and route attributes, with 13 focusing on destination attributes only and seven focusing on route attributes only. Less than one fifth (n = 8) used both objective (geographic information systems or audit) and perceived environmental measures, but the rest used either objective (n = 19) or perceived measures (n = 19) only. About three quarters of the articles (n = 34) were published in public health and physical activity journals, and the remainder was published in planning and transportation journals.
Tables 2 and 3 present the findings reported in the individual articles on associations of specific environmental attributes with utilitarian and recreational walking, respectively. Covariates used for analyses were classified into the following categories: sociodemographic (e.g., age, gender, education), health related (e.g., body mass index, health status, health-related behaviors), psychosocial (e.g., perceived benefits, social support), and residential preference (e.g., preferred neighborhood characteristics). Table 4 summarizes the findings, showing the number of cases of +S, Mix, N, and −S.
Correlates of utilitarian walking.
Utilitarian walking was most consistently associated with the presence and proximity of utilitarian destinations, such as local shops, services, and transit stops. +S were found in 80% of the studies examining the roles of these destination attributes in walking for transport (24 of 30 cases). One study found the presence of mixed types of destinations to be positively associated with residents’ utilitarian walking (52), confirming the importance of diversity, as argued in the model of 3Ds (11). Attributes of recreational destinations such as parks and sport facilities were found to be relevant to utilitarian walking in about one quarter of the studies (5 of 18).
Some aspects of routes to destinations were associated with utilitarian walking. In particular, street connectivity was significantly associated with utilitarian walking in 58% of the studies examined. The presence or maintenance of sidewalks was also found relevant to walking for transport in 42% of the studies. However, only a few studies found significant associations of utilitarian walking with aesthetics, traffic, and personal safety.
Correlates of recreational walking.
One-fifth of the relevant studies (5 of 25) found that recreational walking was associated with either the presence of or proximity to utilitarian destinations. Areas with utilitarian destinations may attract some recreational walkers. More than one-third of the studies found positive associations of recreational walking with attributes of recreational destinations (11 of 31 cases). Of these 31 cases, 18 cases examined natural facilities (parks, open spaces), and 44% of them (eight cases) showed a positive significant association with walking for recreation. Fewer studies examining built facilities (e.g., gym, fitness club, and sports ground) showed a positive significant association (3 of 13 cases).
For the route attributes, more than one-third of the studies examined (7 of 20 cases) found significant associations between recreational walking and route aesthetics. Modest evidence was also found for street connectivity, which was associated with recreational walking in 30% of the studies. However, sidewalks, traffic, and safety did not seem relevant to recreational walking: less than 20% of studies reported significant associations.
Our review findings are consistent with those of the most recent review in relation to the importance of neighborhood destinations for utilitarian walking, the moderate importance of connectivity for utilitarian walking, the relevance of aesthetics to recreational walking, and the lack of evidence on the association of traffic with both types of walking. However, there are notable differences in the findings of our review compared with this previous review. Our review distinguished utilitarian and recreational destinations explicitly and identified specific associations of walking for transport with utilitarian destinations (but not with recreational destinations). These two reviews also differed in their findings on the role of personal safety. Our review, using more recent studies, found safety to be unrelated to utilitarian walking for most studies. In contrast, the previous review (64) reported that safety was associated with walking for transport in about one-half of them. At this stage, it is too early to dismiss safety as unimportant for walking. A review on neighborhood crime and physical activity also reported inconsistent findings (26). Because most studies used perceptions of safety reported by participants, future studies need to use both perceived and objective measures (crime statistics) to understand whether safety is a barrier for walking.
For utilitarian walking, we found consistent evidence of associations with availability and proximity of relevant destinations and a modest level of evidence for the importance of the functional aspects of routes (sidewalks and street connectivity). Findings suggest that compact neighborhoods with easy access to local shops, services, and public transit stops via sidewalks and better street connectivity would help adult residents walk more for transport. The other route attributes (aesthetics, traffic, and safety) seem to have a limited direct effect on adults’ utilitarian walking. It could be argued that poor neighborhood conditions in these aspects are noticeable but may not be a deterrent for walking by adults. Notably, a few studies reported poorer traffic and safety conditions to be associated with more utilitarian walking. It is possible that those who walk more for transport are more sensitized to or more aware of traffic and safety issues than others (56). Moreover, environments with a diverse range of destinations may invite more traffic, strangers, and incivilities.
Unlike utilitarian walking, no dominant environmental attributes consistently associated with recreational walking were found. Moderate evidence suggests that recreational destinations, in particular natural facilities such as parks, and aesthetic aspects of routes (i.e., general attractiveness, interesting things to look at, scenery) may encourage walking for recreation. These findings suggest that recreational walking may be less dependent on neighborhood environmental attributes than is utilitarian walking and that decisions to walk for recreation may be influenced more by nonenvironmental (personal, social) factors. However, it is notable that all studies examining the quality of recreational destinations (e.g., attractiveness of, satisfaction with, or incivilities in parks and physical activity facilities) reported significant associations with walking for recreation (14,38,72,74). More research examining the role of this aspect is warranted.
In the studies reviewed, 252 cases of relationships between walking and environmental attributes were identified: of these, only one-third (84 cases) identified significant associations. Although N may indicate a genuine lack of relationships between walking and the environmental attributes of interest, this may be also attributable to the limitations of the studies. For instance, if a study area is relatively homogeneous in a particular environmental attribute, the association between walking and the attribute is likely to be nonsignificant. Similarly, if there is a nonlinear relationship between walking and environmental attributes (e.g., traffic may discourage walking only when it is excessive), a study area with a narrow range of the attributes may produce an N. Mismatch between where walking takes place and where environmental attributes are measured may also result in null findings. Although the studies reviewed examined neighborhood environments, only a few of them measured walking that occurred within participants’ neighborhoods (1,70,72). Because other studies assessed walking without specifying where it occurred, walking conducted outside of one’s neighborhood (e.g., near work) may have acted as noise in the relationship. Another potential reason for nonsignificance is that physically active adults, who go out more often, may be more likely to report poor environmental conditions than those who are inactive. It has been also reported that those who are physically inactive are more likely to misperceive neighborhood walkability (29). Such systematic bias could act to obscure relationships between walking and environments.
On the basis of the aforementioned perspectives, the following nine research priorities for studies on neighborhood environmental attributes and walking are suggested.
Understand potential thresholds in the relationships of environmental attributes with walking.
The studies reviewed showed consistent associations of utilitarian destinations with walking for transport. However, little is known how close they need to be to facilitate walking. More research is needed to identify a threshold distance within which the presence of destinations is conducive to walking. The types, mix, and number of destinations required to encourage walking are also policy-relevant research questions. Although examining threshold is challenging because it may vary across the life course and for different behaviors, this information would assist planners and policymakers to construct activity-friendly neighborhoods.
Identify how the quality of destinations affects walking behaviors.
Although only a few studies to date have examined the effect of destination quality, most of them have reported a significant contribution of this aspect to walking (8,14,38,72,74). More research on the quality of destinations (including how to measure the relevant qualities) is therefore necessary for different types of destinations. In particular, the quality of recreational settings such as parks should be examined further in light of evidence showing that the quality (or attractiveness) of open spaces is a stronger correlate of recreational walking than their mere presence or proximity (30,72).
Enhance the correspondence between walking and environmental measures.
The studies reviewed focused on neighborhood environments, but most of them measured walking without specifying where it takes place. To accurately assess the role of neighborhood environments, studies need to use location-specific walking measures. In studies using objective environmental measures, different-sized buffers from a participant’s home or an administrative area in which participants reside were used to identify environmental attributes. To achieve greater correspondence between behaviors and the settings where environmental attributes are measured (34,56), research needs to identify more accurately the size of a neighborhood in which residents walk and examine whether that is different for different activity domains (utilitarian and recreational) and for different population groups. Global Positioning Systems (GPS) that can track participants may be used to determine areas where people walk on a regular basis. The use of GPS devices could also allow researchers to identify environmental factors that support walking directly by examining attributes common in places where walking occurs, without specifying neighborhood areas. GPS devices are now widely available in daily use (e.g., mobile phones, car navigators). Location-specific behavior data obtained from GPS will help advance our understanding of environmental attributes that can facilitate walking.
Develop the objective measurement of utilitarian and recreational walking.
It is well known that selfreport measures involve reporting errors and bias. Accelerometers are now available widely and used in many studies that examine physical activity. However, because they cannot distinguish movement for different purposes, they are not currently used for measuring specific physical activities. In fact, all the studies included in this review relied on self-report to measure walking. Using motion sensors along with activity diaries is a potential solution, but it is burdensome for participants. Because there is a need for determining specific types of physical activity accurately, it is important to develop methods to objectively measure walking for different purposes.
Consider neighborhood selection.
Most of the studies reviewed have not considered neighborhood selection. Six studies examined the effect of self-selection (e.g., residential preference) (8–10,15,36,70), and four found associations of walking with environmental attributes after adjustment (8,15,36,70). To demonstrate that environmental correlates of walking are independent of individual predisposition (e.g., preference for shops within walking distance), future studies need to include measures of self-selection as a covariate.
Conduct studies in diverse settings, particularly in regional areas and developing countries.
Research on environmental correlates of physical activity has been conducted predominantly in urban/suburban areas of Western countries. More studies from regional areas are required to inform policy and planning initiatives to increase physical activity in less dense settings. Although studies conducted in South America (12,35,57) and in Japan (42) have been reported recently, more research from non-Western countries should be also encouraged because they may have different behavior patterns and neighborhood environments. Combining studies conducted in diverse areas or countries with comparable measures would be also recommended to increase variance in environmental attributes. Pooled analyses may be able to show significant associations between walking and a particular attribute, for which variability may be limited within a single country or area.
Further develop the measurement of neighborhood walkability.
Given that studies consistently show associations of walking for transport with utilitarian destinations and street connectivity, there is the potential to further develop “walkability” measurements based on these constructs. Currently, walkability is often conceptualized to consist of residential density, land use mix, intersection density, and net retail area ratio (65). However, land use mix involves complex calculation and is known to be affected by the choice of land use and geographical scale (13,22). Data necessary to determine net retail area ratio are also not easily obtainable. An index incorporating destinations and connectivity may serve as a simplified version of walkability, which could be a useful tool for local authorities to relatively easily identify neighborhoods that do not support residents’ utilitarian walking. This would allow local authorities to decide how best to support active lifestyles in particular neighborhoods (e.g., promoting redevelopment to increase destinations, improving physical activity facilities to encourage recreational walking).
Use comprehensive ecological models to guide study design.
Advances in active living research have been propelled by the uptake of ecological models, but only a limited number of studies to date have adopted such comprehensive models to assess the relative importance of individual, social, and environmental factors (6,18). Although the environment is important, alone, it may not be sufficient to increase and maintain behavior change (31). Comprehensive models can help clarify the independent effects of the environment over and above individual and social factors. In addition, studying the relative influence of multiple factors associated with physical activity is required to fully engage the multisector partners.
Conduct prospective studies and natural experiments.
Research needs to assess whether environmental changes and policies implemented in fact increase walking and that there are no unintended negative consequences. Examining the outcomes of natural experiments is increasingly being called for as an important future direction for physical activity research (68), and recent research has begun to examine the effects of new infrastructure development (51). Prospective studies are needed to disseminate compelling evidence outside the research community, particularly those who can influence environmental and policy initiatives.
In conclusion, this review identified particular neighborhood destination and route attributes that have the potential to be modified so as to enhance adults’ utilitarian and recreational walking. Given that different sectors undertake environmental initiatives involving these attributes, research evidence synthesized using this framework may be effective for informing strategies to facilitate adults’ active lifestyles.
Sugiyama and Owen received a grant from Queensland Health for this work and are supported in part by the Victorian Government’s Operational Infrastructure Support Program. Neuhaus and Owen are supported by Core Infrastructure Funding from Queensland Health. Owen is supported by program grant 569940 and senior principal research fellowship number 1003960 from the National Health and Medical Research Council of Australia. Giles-Corti is supported by VicHealth and a National Health and Medical Research Council of Australia Principal Research Fellowship number 1004900.
All authors declare no conflict of interest.
The results of the present study do not constitute endorsement by the American College of Sports Medicine.
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