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Environmental Correlates of Physical Activity: A Review
of Evidence about Parks and Recreation
Andrew T. Kaczynski a; Karla A. Henderson b
a
University of Waterloo Waterloo, Ontario, Canada
b
North Carolina State University, Raleigh, North Carolina, USA
Online Publication Date: 01 July 2007
To cite this Article: Kaczynski, Andrew T. and Henderson, Karla A. (2007)
'Environmental Correlates of Physical Activity: A Review of Evidence about Parks
and Recreation', Leisure Sciences, 29:4, 315 - 354
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Leisure Sciences, 29: 315–354, 2007
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Copyright ISSN: 0149-0400 print / 1521-0588 online
DOI: 10.1080/01490400701394865
Research Articles
Environmental Correlates of Physical Activity:
A Review of Evidence about Parks and Recreation
ANDREW T. KACZYNSKI
University of Waterloo
Waterloo, Ontario, Canada
KARLA A. HENDERSON
North Carolina State University
Raleigh, North Carolina, USA
Research on physical activity (PA) has expanded in recent years to examine environmental influences that enhance or limit the opportunities people have to be active. The
purpose of this study was to review and critically examine evidence related to parks and
recreation as features of the built environment and the relationship of these settings to
PA. Fifty studies were retrieved from four major databases that reported an empirical relationship between parks or recreation variables and PA variables. Mixed associations
with PA were observed for different types of parks or recreation settings, while proximity
to parks or recreation was generally associated with increased PA. Shortcomings exist
in this literature and many opportunities for researching parks, recreation, and active
living are evident for the future.
Keywords active living, literature review, physical activity, social ecological models
The connection between health and physical activity (PA) is well-documented (Hardman
& Stensel, 2003; Sallis & Owen, 1999). This relationship is emphasized almost daily in
relation to issues such as childhood obesity and the physical inactivity of North American
populations. Only one-quarter of the U.S. population engages in the recommended amount
of PA, and another one-quarter are inactive (Centers for Disease Control and Prevention,
2001). Estimates from the 2000–01 Canadian Community Health Survey indicated that
56% of Canadians were classified as insufficiently active (Canadian Fitness and Lifestyle
Research Institute, 2002). Low levels of PA have been linked to a greater prevalence of
obesity and related diseases including diabetes, cardiovascular disease, and cancer (Ball
& McCargar, 2003; Bassuk & Manson, 2005; Stein & Colditz, 2004; U.S. Department
of Health and Human Services, 1996; Westerlind, 2004). Along with poor nutrition and
smoking, lack of exercise is among the top three modifiable risk factors for chronic disease
Received 24 March 2006; accepted 12 September 2006.
We would like to thank three anonymous reviewers for their insightful comments and Deb Bialeschki for
overseeing the editorial process on this manuscript. This paper was presented at the 2006 Cooper Institute on
“Parks, Recreation, and Public Health: Collaborative Frameworks for Promoting Physical Activity.”
Address correspondence to Andrew T. Kaczynski, Department of Recreation and Leisure Studies, University
of Waterloo, Waterloo, Ontario, Canada, N2L 3G1. E-mail: atkaczyn@ahsmail.uwaterloo.ca
315
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A. T. Kaczynski and K. A. Henderson
and premature death (World Health Organization, 2005). Therefore, improving PA levels
has been consistently identified as a top public health priority (U.S. Department of Health
and Human Services, 2000; The Integrated Pan-Canadian Healthy Living Strategy, 2005).
The role that leisure services and parks and recreation settings play in helping people
become physically active, and thus healthier, is beginning to be addressed. For example,
Healthy People 2010 (U.S. Department of Health and Human Services, 2000) emphasized
that the design of communities and the presence of parks, trails, and other public recreational
facilities affect people’s abilities to reach the recommended 30 minutes per day of moderateintensity PA. Similar recommendations about access to places for PA, and specifically trails
and facilities, were made by a collaboration of government agencies and private partners in
the Guide to Community Preventive Services (Task Force on Community Preventive Services, 2002). Yet, the examination and documentation of parks and recreation settings as environmental correlates of PA is in its infancy. The involvement of leisure scientists in addressing many of these health related issues has been lacking (Henderson & Bialeschki, 2005).
The purpose of this study was to review reported empirical evidence about the association between parks and recreation settings (PRSs) as features of the built environment
and PA. Specifically, we aimed to answer the following questions: a) what types of PRSs
are most related to increased PA levels, and b) how is proximity to PRSs related to PA?
We defined PRSs as indoor and outdoor spaces and facilities in the physical and built environments designed for leisure and recreation activities. We anticipate that this review will
provide a foundation and catalyst for new research by researchers with expertise in parks
and recreation through transdisciplinary studies with other professionals.
Review of Literature
Sallis, Linton, and Kraft (2005) described how research on PA and health has entered a fourth
major era. The first era (prior to 1970) dealt with physiological studies that examined the
impact of patterns of PA on fitness. The second era (1970s–1990s) included epidemiological
studies leading to PA being viewed as a major health priority. The third era that occurred in
a similar time period focused on appropriate interventions for promoting PA. Most of this
research primarily addressed psychosocial factors such as self-efficacy, social support, and
stages of change models (Dishman, 1994; King et al., 2002; Sallis, Kraft, & Linton, 2002).
The fourth era, which started early in this century, focused on a broader range of policy and
environmental factors that promote health such as urban planning, transportation, housing,
and parks and recreation.
At the same time, parks, recreation, and leisure research has gone through research
stages that addressed inputs, outputs, benefits, and explanations and meanings of recreation
and leisure. Leisure researchers have moved beyond descriptions of inputs, outputs, and
benefits to analyze how behavior occurs as a result of social and environmental factors (Ellis, 1993). The activities leisure researchers analyze often are broader than PA. However, to
address health issues, these researchers are joining with other scholars (i.e., primarily in public health but also exercise scientists and urban planners) to examine more comprehensively
the built environment associated with environmental correlates and ecological models.
Ecological Models
Ecology generally refers to the interrelations between organisms and their environments
(Hawley, 1950). Social ecological concepts refer to people’s transactions with their physical
and sociocultural environments (Henderson et al., 2001; Sallis & Owen, 2002; Stokols,
1992). Social ecology is derived from systems theory with people-environment transactions
characterized by cultures of mutual influence (Bronfenbrenner, 1979; Green, Richard, &
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Parks, Recreation, and Physical Activity
317
Potvin, 1996). The general thesis of ecological models of behavior is that environments
restrict the range of behaviors by promoting and sometimes demanding certain actions and
by discouraging or prohibiting other behaviors. When environmental constraints operate
in significant ways, they emerge as the overriding determinants of behavior (Bandura,
1986). O’Donnell (2005) argued, “An abundance of opportunity may cancel the need for
education and motivation. An absence of opportunity will probably prevent even the most
knowledgeable and motivated person from practicing a healthy lifestyle” (p. iv).
The overemphasis on psychosocial and educational approaches to PA promotion that
dominated the literature until recently is subject to increasing criticism. Marcus and Forsyth
(1999) divided PA promotion efforts into downstream (e.g., programs to increase exercise
self-efficacy), midstream (e.g., mass media campaigns), and upstream (e.g., altering building codes) interventions. Although they acknowledged at the time that evidence of the efficacy of upstream interventions was limited, they concluded that downstream interventions
produced only 10–25% increases in PA and improvements were short-lived. In contrast,
upstream interventions such as adding sidewalks or bike paths are more permanent strategies and can affect greater numbers of people than just those individuals who are the targets
of downstream or midstream interventions such as mailings or physician counseling. Researchers also have shown that psychological and social factors explain less variance in
moderate-intensity PA than vigorous activity (Sallis & Owen, 1999). This finding is significant because recent PA recommendations focus on promoting moderate-intensity PA (e.g.,
gardening, walking) that is more appealing and practical for a majority of the population
while still providing significant health benefits (Pate et al., 1995). Thus, ecological efforts
add explanatory value beyond the intrapersonal factors that influence people’s involvement
and participation in physically active leisure.
Stokols (1992) suggested that the core assumption of social ecology related to health
promotion is that the healthfulness of the environment and the well-being of people are
influenced by multiple facets of both the physical environment and the social environment.
According to McLeroy et al. (1988), five classes of factors affect how or why a person might
participate or fail to participate in a healthy behavior such as PA: intrapersonal, interpersonal,
institutional, community, and public policy. Intrapersonal is the only factor focused on the
individual and has limited value compared to the other four that acknowledge the context of
people’s lives relative to supportive others as well as enabling and constraining opportunities
and healthy environments. Richard et al. (1996) and Stokols, Allen and Bellingham (1996)
suggested that health problems result from social structure and conditions. Consequently,
constraints and motivations for PA can best be understood by examining the environments
in which people live.
The Built Environment and Physical Activity
The specific relationships between the natural and built environment in communities and
PA have not been prevalent in the leisure and recreation research literature (Henderson &
Bialeschki, 2005). A social psychological approach (Mannell & Kleiber, 1997) has dominated in leisure research with the primary focus on individual behavior within that person’s
environment. The leisure field has been concerned more often with the psychological processes of activity involvement (e.g., enjoyment, perceived freedom, or social interaction)
than with the physiological product (e.g., lowered blood pressure). From a broader social
and political context the value of parks and recreation has also been related to other goals
such as environmental preservation as well as economic and community development, rather
than focused on public health.
Public health researchers, however, are examining the significant role that the built
environment plays in fostering PA. Reviews similar to this study examined a wide array of
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A. T. Kaczynski and K. A. Henderson
environmental variables and found substantial support for the ecological hypothesis. Early
reviews by Sallis, Bauman, and Pratt (1998) and King et al. (1995) lamented a lack of
empirical studies and conceptual models and were the impetus for research that examined
environmental and policy interventions. Since then, researchers have developed increasingly sophisticated systems for classifying PA in community settings (Ainsworth et al.,
2000; Bassett et al., 2000; McKenzie, Cohen, & Sehgal, 2005; McKenzie et al., 2000) as
well as tools for measuring environmental correlates of PA (Brownson et al., 2004; Pikora
et al., 2002; Pikora et al., 2003; Saelens, Sallis, Black, & Chen, 2003). More recent reviews
of the literature (Humpel, Owen, & Leslie, 2002; McCormack et al., 2004; Owen et al.,
2004; Saelens, Sallis, & Frank, 2003) found fairly consistent positive associations between
PA and factors in the built environment such as access to facilities, safety, and aesthetics. These reviews also reported that transportation and zoning variables (e.g., mixed land
use, population density, connectivity of streets, and presence of sidewalks) exhibited strong
relationships with residents’ PA levels.
The role that PRSs may play in fostering increased PA has received growing attention.
For example, Sallis et al.’s (1998) review concluded that children were more active outdoors
and that being outdoors was the most powerful correlate of PA. Corti, Donovan, and Holman
(1997) indicated that parks were more likely to stimulate activity if they were aesthetically
pleasing with tree-lined paths rather than empty open space. Troped et al. (2001) determined
that decreased distance between a person’s home and a trail was associated with greater trail
use. Arguments have also been forwarded recently in the American Journal of Preventive
Medicine that PRSs can make significant contributions to facilitating PA (Bedimo-Rung,
Mowen, & Cohen, 2005; Godbey et al., 2005). Additional recognition of the growing role
that parks and recreation has to play in addressing health and PA was also found in a recent
special issue of Leisure Sciences (Henderson & Bialeschki, 2005), the advocacy promoted
by Payne (2002) and her colleagues (Payne et al., 2005), in National Recreation and Park
Association’s (2005) “Step up to Health” program, and through the focus that the Robert
Wood Johnson Foundation’s Active Living Research Program has placed on research about
parks and recreation (Sallis & Linton, 2005).
Although research has been undertaken addressing the built environment and PA, no
analysis has systematically considered the role of PRSs. Several previous literature reviews
have included a small number of variables related to parks and recreation (Humpel et al.,
2002; Owen et al., 2004), but little detail is available about the complex associations between
these settings and community-based PA. Therefore, the purpose of this article is to review
and critically examine evidence related to PRSs as features of the built environment and the
relationship they have to PA.
Methods
To address our purpose, we identified peer-reviewed journal articles in which an association
between PRSs and PA was reported as part of the investigation. Although most articles did
not provide an explicit definition of PA, PA is commonly defined as “any bodily movement
produced by skeletal muscles that results in energy expenditure” (Caspersen, Powell, &
Christenson, 1985, p. 126). In December 2005, searches were conducted within four major databases—PsycInfo, PubMed, LeisureTourism Abstracts, and Web of Science—using
search terms tailored to each database.1
1
PsycInfo: AB = (“physical activity” OR exercise OR inactivity OR walking) AND AB =
(environment OR neighborhood OR “urban design” OR park OR trail OR greenway). PubMed:
Search (“Motor Activity”[MeSH] OR “Exercise”[MeSH]) AND “Environment Design”[MeSH]
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Parks, Recreation, and Physical Activity
319
Only articles printed in English were requested, and the date range for articles was
delimited to the period 1998–2005. Although one review of environmental correlates predated our selected timeframe (King et al., 1995), as did particular studies mentioned in Sallis
et al.’s (1998) review, the year 1998 was considered a reasonable starting point for identifying research related to the built environment and PA for several reasons. For example, as
noted earlier, Sallis et al. (2005) described the fourth phase of PA research that occurred
since the early 2000s as being primarily concerned with understanding and altering policy
and environmental factors. The Centers for Disease Control and Prevention convened a multidisciplinary conference of health professionals in 1997 and “that meeting was the dawn
of what we are now calling the active living movement” (Killingsworth, Earp, & Moore,
2003, p. 1). In addition, the 1997 Cooper Institute’s annual conference focused on PA interventions including some environmental studies, and papers presented at that conference
were published in a special issue of the American Journal of Preventive Medicine early the
following year (Blair & Morrow, 1998). Therefore, 1998 was an appropriate starting point
for our analysis.
The searches of the four databases returned a total of 1120 distinct articles after merging
the results and removing all duplicate records. The primary author then scanned article
abstracts to determine each paper’s relevance to our current study’s purpose. Articles were
initially excluded from further analysis if they failed to meet any of several criteria. First,
we were only interested in studies that included PA as a dependent variable and not research
that measured relationships between the built environment and other health measures (e.g.,
body mass index, mental health, cardiovascular disease). Second, articles that examined
other psychological or interpersonal correlates of PA (e.g., self-efficacy, social support)
without including environmental variables were omitted. Third, articles that analyzed the
built environment or PA concurrently, but only as these two behaviors related to a third
variable or condition (e.g., maximal oxygen uptake) were excluded. Fourth, studies that
simply controlled for environmental influences and/or PA while examining the relationship
between two other variables were also excluded.
Some studies existed that examined worksite and school environments in relation to
PA. The former were excluded because they appeared minimally related, if at all, to PRSs.
Schools, on the other hand, often constitute an important source of indoor and outdoor
recreational opportunities for communities. However, of the few articles uncovered in our
searches that examined school environments related to PA, none were deemed relevant to our
study’s purpose. For example, some addressed only physical education class participation as
opposed to the broader concept of PA. In other cases, factors not part of the built environment
were the main focus of the study (e.g., length of breaks during the day, available sports
equipment). However, many if not most studies of the built environment measured the
location of PA resources (e.g., a playground) in a manner that was so general that schoolbased PRSs, especially accessible outdoor ones, would likely be included in the tally of
available resources.
Finally, only original empirical studies were examined. Conceptual papers, review
articles, and studies that were purely methodological in purpose (e.g., validating self-report
measures of the built environment or PA) were not considered. In summary, similar to
Humpel et al.’s (2002) work, “Only those studies that measured environmental variables
that could be related individually and directly to measured physical activity variables were
Field: MeSH Terms. LeisureTourism Abstracts: ( (environment) in ABSTRACT OR (neighborhood)
in ABSTRACT OR (park) in ABSTRACT OR (trail) in ABSTRACT)) AND ((physical activity) in
ABSTRACT OR (exercise) in ABSTRACT OR (walking) in ABSTRACT)). Web of Science: TS =
(physical activity OR exercise OR walking) AND TS = (environment OR neighborhood OR urban
design OR park OR trail OR greenway); Database = SSCI.
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A. T. Kaczynski and K. A. Henderson
retained” (p. 189). Application of these criteria temporarily reduced the original set of
articles to a list of 105 studies that described empirical relationships between some aspect
of the built environment and PA levels.
Within these 105 articles, four journals were represented by more than five papers:
American Journal of Health Promotion, American Journal of Preventive Medicine,
American Journal of Public Health, and Preventive Medicine. Subsequently, a total of
263 issues for these four journals from 2000 to 2005 were hand-searched to identify any
relevant articles that were missed by the previously described database searches. This process revealed only two additional studies that satisfied the aforementioned criteria. One
of the 107 articles identified could not be acquired despite extensive search efforts. Four of
the remaining 106 articles were qualitative studies, and within three of these, the utility of
the contextual findings to our study’s purpose was difficult to summarize. Consequently,
all qualitative studies were removed, and we analyzed only quantitative articles. However,
some of this qualitative literature is described in the discussion section of the paper.
Within the remaining set of 102 articles, we sought to identify only those studies that
reported an association between PA and some aspect of parks or recreation settings (e.g.,
presence of, distance to) as features of the built environment. Consequently, although rare,
studies with parks and recreation programming (e.g., skills training) as the focus were
excluded from our review. Similarly, associations between PA levels and questionnaire
items that related solely to the presence of recreational equipment (e.g., treadmills) in
respondents’ homes also were not included in our study.
Some studies that examined environmental influences on PA frequently inquired about
generalized variables such as access to facilities or places to exercise. Such broadly defined
measures were not considered to be clearly related to parks and recreation because they
could easily be interpreted as referring to other PA amenities (e.g., streets). Composite
measures (e.g., aggregations of individual access ratings for multiple types of facilities or
a single summary score covering all aspects of the built environment) were often described
but only included when a large majority of the items in the measure were related to PRSs. In
the end, a total of 50 articles were reviewed that reported empirical quantitative relationships
between PRSs as features of the built environment and PA levels of the study participants.
The following section describes the nature of these relationships.
Results
Table 1 provides brief summaries of the empirical associations that were reported in the 50
primary articles in which a relationship between parks or recreation and PA was directly
analyzed. The first three columns of the table describe the age, location, and size of the
study sample and whether it was representative of the larger population. Brief descriptions
of the parks or recreation and PA variables are provided along with the associations among
them reported by the original authors.
In 20 of the 50 studies (40%), all or most of the associations examined between parks or
recreation and PA variables were positive (Ball et al., 2001; Bauman et al., 1999; Blanchard
et al., 2005; Booth et al., 2000; Brownson et al., 2001; Chad et al., 2005; Deshpande et al.,
2005; Fisher et al., 2004; Giles-Corti et al., 2005; Giles-Corti & Donovan, 2003, 2002a;
Gordon-Larsen, McMurray, & Popkin, 2000; Humpel et al., 2004; Humpel et al., 2004;
Li, Fisher, & Brownson, 2005; Mota et al., 2005; Reed et al., 2004; Troped et al., 2001;
van Lenthe, Brug, & Mackenbach, 2005; Vernez-Moudon et al., 2005). Nine of the articles
(18%) reported that the associations examined were not significant (Atkinson et al., 2005;
Carver et al., 2005; Duncan & Mummery, 2005; Giles-Corti & Donovan, 2002b; Lund,
2003; Norman et al., 2005; Plaut, 2005; Romero, 2005; Wilcox et al., 2000), while one
study reported a negative relationship (Duncan et al., 2004).
321
Population1
18+ year olds in
southeastern U.S.
county
Adults in two
neighborhoods in
San Diego, CA
Adults in New South
Wales, Australia
Authors and date
1. Addy et al.
(2004)
2. Atkinson et
al. (2005)
3. Ball et al.
(2001)
3392∗
102∗
1194∗
N2
Convenience summary
score of agreement on
5-pt scales that 3 items
are within walking
distance: shops, park or
beach, cycle path
Neighborhood (within 0.5
miles or 10-minute walk
of home) and
community (10 miles or
20-minute drive)
recreation facilities,
walking/biking trails,
swimming pools, parks,
playgrounds, sports
fields
Tally of convenience
(5-minute drive,
10-minute walk, or on
frequently traveled
route) for 18 recreational
or exercise facilities
(yes/no for each)
Parks or recreation
variable(s)3
Walking for exercise in
past 2 weeks (any vs.
none)
Sufficiently active (5+
days with 30+ minutes
of moderate PA or 3+
days with 20+ minutes
of vigorous PA in past
week)
Insufficiently active (less
PA)
Inactive (no moderate or
vigorous PA)
Number of self-reported
episodes in past 7 days
of moderate, vigorous
and total PA
Minutes of moderate,
vigorous and total PA
measured by
accelerometer
Physical activity
variable(s)3
Association(s)4
Users of neighborhood recreation
facilities significantly more likely
to be sufficiently active (OR =
4.36) or insufficiently active
(OR = 7.26) than inactive
Users of community parks
significantly more likely to be
sufficiently active (OR = 1.96) or
insufficiently active (OR = 2.20)
than inactive
Convenient recreational facilities
not significantly related to
moderate, vigorous, or total (r =
.17) self-reported PA
Convenient recreational facilities
not significantly related to
moderate, vigorous, or total
minutes of objectively-measured
PA
Respondents reporting low (OR =
.64) and moderate (OR = .84)
convenience of facilities
significantly less likely to walk
for exercise than those reporting
high convenience of facilities.
Similar results found when
sample divided into those in poor
and good health.
(Continued on next page)
TABLE 1 Articles Reporting Empirical Associations between Parks and Recreation Amenities and Physical Activity
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322
18+ year olds in
New South Wales,
Australia
Adults across U.S.
60+ year olds across
Australia
5. Blanchard
et al.
(2005)
6. Booth et al.
(2000)
Population1
4. Bauman
et al.
(1999)
Authors and Date
449∗
6739∗
16,178∗
N2
Access to local exercise
hall, recreation center,
cycle path, golf course,
gym, park, swimming
pool, tennis court,
bowling green (yes/no;
asked individually)
Summary score of
availability of nine
recreation facilities in
neighborhood
Live in postal code that
touches coastline
Parks or Recreation
Variable(s)3
Association(s)4
Respondents from coastal locations
significantly less likely to be
sedentary (OR = .77) and more
likely to be adequately active
(OR = 1.27) or vigorously active
(OR = 1.38) than respondents
from inland locations
Number of days in past
Availability of recreation facilities a
week that included 30+
significant predictor of PA in
minutes of total
normal weight (BMI = 20–25)
moderate or vigorous PA
and overweight (BMI = 25–30)
respondents, but not in obese
(BMI>30) respondents
Sufficiently active (>800 In bivariate analyses, significantly
kcals·kg−1 energy
greater proportion of active than
expenditure per week)
inactive respondents reported
Inactive (<800 kcals.kg−1
access to an exercise hall (38.5%
per week)
vs. 26.9%), recreation center
(38.5% vs. 26.9%), cycle track
(46.9% vs. 34.1%), golf course
(46.9% vs. 37.2%), park (81.0%
vs. 63.7%), and swimming pool
(58.7% vs. 44.4%)
In multivariate analysis, only
having access to a local park
significantly increased odds (OR
= 1.14) of sufficient PA
Vigorously active (>1600
kcal/wk) Adequately
active (>800 kcal/wk)
Sedentary (<50
kcal/wk)
Physical Activity
Variable(s)3
TABLE 1 Articles Reporting Empirical Associations between Parks and Recreation Amenities and Physical Activity (Continued)
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323
Adults across U.S.
18+ year olds from
12 counties in
southeast Missouri
12–14 year olds in
western Sydney,
Australia
7. Brownson
et al.
(2001)
8. Brownson
et al.
(2000)
9. Carver
et al.
(2005)
347
1269∗
1818∗
Access to walking/jogging Meets PA recommendation Meeting PA recommendation
(5+ days with 30+
trail, park, indoor gym
significantly associated with
(yes/no; asked
minutes of moderate PA
access to walking/jogging trails
individually)
or 3+ days with 20+
(OR = 1.55), parks (OR = 1.95),
minutes of vigorous PA
and indoor gyms (OR = 1.94)
in past week)
Access to walking trails
Increase in walking since Of those who reported having
(trails or paths in
beginning to use trail
access to and having used a
area—yes/no)
(yes/no)
walking trail, 55% reported an
Used walking trail
increase in walking since they
(yes/no)
began to use the trail
Length of trail Distance to
Persons using longer trails (>0.25
trail
miles) significantly more likely to
report an increase in walking
since using trail
Distance to trail not significantly
related to an increase in walking
since using the trail
Of all walking or cycling and
Parents’ agreement that
Adolescents’ reports of
“our neighborhood has
their frequency and
purpose combinations, sports
duration of walking and
facilities a significant predictor of
good sports facilities” (1
only frequency (not duration) of
cycling for exercise,
or 2 on a scale ranging
cycling for transport and only in
from -2 to 2)
recreation, transport, and
to/from school
boys
(Continued on next page)
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324
18–65 year olds in
Ghent, Belgium
11. De
Bourdeau–
dhuij et al.
(2003)
12. Deshpande et 20+ year olds in
al. (2005)
Missouri,
Tennessee and
Arkansas
50+ year olds in a
midsized
Canadian city
Population1
10. Chad et al.
(2005)
Authors and Date
278∗
521∗
764
N2
Physical Activity
Variable(s)3
Association(s)4
Summary score for
Significantly higher PA scores for
Presence of facilities
participation in 12
respondents reporting the
within neighborhood
presence of biking trails,
(within 5-minute walk or activities of varying
intensities more specific
walking/hiking trails, golf course,
drive): biking trails,
to older adult
public park, skating rink,
walking/hiking trails,
golf course, public park,
populations (e.g. yard
swimming pool, and tennis
care, volunteering, etc.)
courts. Some minor differences in
skating rink, swimming
significance of facilities when
pool, tennis courts,
dance studio, public
sample split into 50–64, 65–79,
and 80+ age groups.
recreation center
Tally of convenience
Minutes of sitting,
For both males and females,
(5-minute drive from
walking,
convenience of facilities score
work or home or on
moderate-intensity, and
significantly related to amount of
frequently traveled
vigorous-intensity
vigorous activity only
route) for 18 recreational activities during past
or exercise facilities
week (measured
(yes/no for each)
separately)
Use of community
Engage in regular PA
Significantly increased odds of
(30+ minutes at least 5
engaging in regular PA for
facilities in past 30 days
(used/did not use): park,
days per week)
respondents who had used a park
recreation center,
(OR = 4.21), recreation center
(OR = 12.20), trail (OR = 3.81),
biking/walking trail,
public swimming pool,
or health club (OR = 7.48). Odds
health club
increased dramatically with use
Number of minutes to
of 3+ facilities.
walk from home to each
Shorter walking times to park,
recreation center, trail, and health
of above facilities
club associated with more regular
PA
Parks or Recreation
Variable(s)3
TABLE 1 Articles Reporting Empirical Associations between Parks and Recreation Amenities and Physical Activity (Continued)
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325
10–14 year old
siblings in 58
neighborhoods in
Pacific Northwest
U.S.
18+ year olds across
U.S.
14. Duncan
et al.
(2004)
15. Eyler et al.
(2003)
13. Duncan and 18+ year olds in
Rockhampton,
Mummery
Australia
(2005)
1818∗
930∗
1281∗
No walking/jogging trails
There are playgrounds,
parks, or gyms close to
my home or that I can
get to easily (1–5,
disagree-agree)
Number of parks and
exercise and
recreational facilities in
neighborhood
Street network distance to
nearest parkland
(Continued on next page)
Achieves recommended
Participants with parkland beyond
PA level (150 minutes in
600 m significantly more likely to
past week)
achieve recommended PA level
Any recreational walking
(OR = 1.41) than those less than
in past week
600 m from parkland
Parkland proximity not related to
recreational walking
Perceptions of neighborhood
Number of days in past
week that each sibling
recreational facilities and count of
number of neighborhood PA
took part in: vigorous
facilities were both negatively
exercise for 20+
minutes; stretching
and significantly related to family
levels of PA
exercises; strengthening
exercises
Number of days of
vigorous PA in a typical
week for each sibling
Regular walker (5x/week Never walkers significantly more
for 30 min)
likely to report a lack of
Occasional walker (walk
walking/jogging trails than
10+ min at least once
regular walkers (OR = 1.59)
during past week)
Occasional walkers not
Never walker (did not
significantly more likely to report
walk 10+ min at least
a lack of walking/jogging trails
once in past week)
than regular walkers (OR = 1.18)
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326
64–94 year olds
from 56
neighborhoods in
Portland
16–74 year olds
across England
18–59 year olds in
Perth, Australia
17. Foster et al.
(2004)
18. Giles-Corti
et al.
(2005)
Population1
16. Fisher et al.
(2004)
Authors and Date
1803∗
4157∗
582∗
N2
Three models of access to
public open space (each
divided into quartiles:
very poor, poor, good,
very good):
1) Distance only model
2) Distance and
attractiveness model
3) Distance,
attractiveness, and size
model
A park/open space is
within walking distance
(agree/disagree)
A leisure center is within
walking distance from
my home (yes/no)
Total parks, paths, trails
per neighborhood acre
Parks or Recreation
Variable(s)3
Association(s)4
Neighborhood walking
Walking facilities per neighborhood
activity (score derived
acre significantly related to
from individuals’
neighborhood walking activity
responses to 3 behavior
questions rated on 5-pt
scale)
Walking >150 minutes per In bivariate analyses, neither the
week in past four weeks
park nor leisure center variable
Walking at least 15
were significantly related to either
minutes per week in past
walking measure in either men or
four weeks
women
In multivariate analyses, for men,
having a park within walking
distance was only environmental
variable associated with higher
odds of walking >150 minutes
per week (OR = 2.22)
Achieves sufficient PA
For distance-only (OR = 0.69) and
(30+ minutes of
distance plus attractiveness
moderate PA on most
(OR = 0.71) models, poor access
days of week)
to public open space significantly
High levels of walking
decreased odds of achieving
(6+ walking sessions
sufficient PA compared to those
per week totaling 180+
with very poor access
minutes)
For distance, attractiveness, and
size model, having very good
access to public open space
significantly
Physical Activity
Variable(s)3
TABLE 1 Articles Reporting Empirical Associations between Parks and Recreation Amenities and Physical Activity (Continued)
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327
18–59 year olds in
Perth, Australia
18–59 year olds in
Perth, Australia
18–59 year olds in
Perth, Australia
19. Giles-Corti
and
Donovan
(2003)
20. Giles-Corti
and
Donovan
(2002a)
21. Giles-Corti
and
Donovan
(2002b)
1803∗
1803∗
1803∗
Access to built facilities:
e.g. golf course, health
club (divided into
quartiles)
Access to natural
facilities: e.g. beach,
river (divided into
quartiles)
Exercising as
recommended (30+
minutes of moderate PA
on most days of week)
Access to attractive public Walking at recommended
levels (12+ sessions in
open space, river, beach,
previous 2 weeks
golf course (divided into
quartiles)
totaling 360 minutes or
more)
Access to open space (top In past two weeks: any
quartile vs. other three
walking for transport;
quartiles combined)
any walking for
Access to beach (top
recreation; any vigorous
quartile vs. other three
exercise
quartiles combined)
Walking as recommended
(6+ times per week for
30+ minutes)
Exercising vigorously at
recommended level (3+
times per week for 20+
minutes)
(Continued on next page)
increased odds of engaging in
high levels of walking compared
to those with very poor access
(OR = 1.50)
Participants in top quartile of access
exhibited significantly higher
odds of sufficient walking than
those in bottom quartile of access
(OR = 1.47)
Being in top quartile of access to
open space significantly increased
odds of walking for transport (OR
= 1.35) and walking as
recommended (OR = 1.43)
Being in top quartile of access to
beach significantly decreased
odds of walking for transport (OR
= 0.62), but significantly
increased odds of walking for
recreation (OR = 1.49),
exercising vigorously at all in
past two weeks (OR = 1.38), and
exercising vigorously at
recommended level (OR = 1.58)
Neither access to built facilities nor
access to natural facilities
significantly related to exercising
as recommended
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328
Grade 7 students at 5
schools in San
Antonio, TX
Grade 7–12 students
across U.S.
18–96 year olds in
areas of St. Louis,
MO and
Savannah, GA
23. GordonLarsen
et al.
(2000)
24. Hoehner
et al.
(2005)
Population1
22. Gomez
et al.
(2004)
Authors and Date
1073∗
17,766∗
177
N2
Physical Activity
Variable(s)3
Straight line distance from Bouts per week of outdoor,
participant’s home to
non-school related PA
nearest open play area
(based on recall of
(playground, pool,
number of days per
athletic field)
month and number of
months per year)
Use of neighborhood
Number of episodes of
recreation center (use/do
moderate to vigorous PA
not use)
per week (based on
7-day activity recall
questions)
Hours per week of
physical inactivity
(TV/video watching and
video game playing)
There are many places to
Recreational PA (not
including transport)
be active in my
community, not
during leisure-time:
including streets
Meets PA
recommendation (5+
Park, walking trail, private
fitness facility within
days with 30+ minutes
of moderate PA or 3+
5-minute walk of home
days with 20+ minutes
(yes/no–individually)
Number of recreation
of vigorous PA in past
week)
facilities within
5-minute walk of home
Does not meet
recommendation
Parks or Recreation
Variable(s)3
Respondents who agreed that there
are many places to be active
(OR = 2.0) and that reported 2–3
recreation facilities within
5-minute walk (OR = 1.6)
significantly more likely to meet
PA recommendation (but trends
not clear)
Having any of park, walking trail,
or private fitness facility within
5-minute walk not associated
with meeting PA
Using recreation center
significantly increased odds of
falling into highest (5+
episodes/wk) PA category (OR =
1.75), but was not associated with
being in the highest (25+ hrs/wk)
inactivity category (OR = 1.01)
Distance to nearest open play area
inversely and significantly related
to bouts per week of outdoor PA
in boys, but not in girls or total
sample
Association(s)4
TABLE 1 Articles Reporting Empirical Associations between Parks and Recreation Amenities and Physical Activity (Continued)
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329
Faculty and staff at
an Australian
university
40+ year olds from
a coastal
Australian city
25. Humpel,
Marshall
et al.
(2004)
26. Humpel,
Owen,
Iverson
et al.
(2004)
399∗
800∗ and
512 at
10-wk
follow up
Live in postal code that
Number of minutes per
touches coastline
week of neighborhood
Lake or beach within easy
walking, walking for
walking distance
exercise, for pleasure,
and to get to and from
places (separately)
(7 total) Within 400 m of
respondent’s home:
Count of parks with
facilities; Any park, trail
or fitness facility; Count
of recreational facilities
Number of minutes per
Summary ‘convenience’
score of (each item rated
week of neighborhood
1–10 for unfavorable to
walking
favorable):
Walking distance to
park/beach Accessibility
of path/cycle way
Overall convenience of
neighborhood for
walking
In both men and women, increased
perceptions of convenience
related to significantly increased
odds of any increase in walking
(OR = 1.95 and 2.58,
respectively), increase of 30 or
more minutes of walking (OR =
2.02 and 2.31, respectively), and
increase of 60 or more minutes of
walking (OR = 1.98 and 2.01,
respectively)
In bivariate analyses, participants
living in coastal postal code
reported significantly more
minutes walking in neighborhood
(189 vs. 149) and for exercise
(139 vs. 109) than those in
non-coastal postal code
In bivariate analyses, participants
with a lake or beach within
walking distance reported
(Continued on next page)
recommendation
None of the objective measures of
parks or recreation facilities
significantly related to meeting
PA recommendation
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330
Faculty and staff at
an Australian
university
18+ year olds in 6
counties in North
Carolina
28. Huston
et al.
(2003)
Population1
27. Humpel,
Owen,
Leslie
et al.
(2004)
Authors and Date
1796∗
800∗
N2
Physical Activity
Variable(s)3
Association(s)4
significantly more minutes
walking in neighborhood (224 vs.
139), for exercise (163 vs. 100),
and for pleasure (33 vs. 21)
In multivariate analyses, living in
coastal postal code not
significantly associated with
increased odds of any type of
walking for men, but greater odds
of neighborhood walking for
women (OR = 3.32)
In men, participants in high
Number of minutes per
Summary ‘convenience’
week of neighborhood
convenience tertile exhibited
score split into low,
significantly higher odds of
moderate, high tertiles
walking (split into high
and low groups at
neighborhood walking (OR =
based on (each item
median)
2.20) and total PA (OR = 1.82)
rated 1–10 for
than those in low convenience
unfavorable to
Number of minutes per
week of total walking
tertile
favorable):
Walking distance to
(split at median)
In women, those in high (OR =
Number of minutes per
3.78) and moderate (OR = 3.19)
park/beach
week of total PA (split at
convenience tertiles exhibited
Accessibility of path/cycle
significantly higher odds of
way
median)
Overall convenience of
neighborhood walking than those
in low convenience tertile
neighborhood for
walking
Trails in neighborhood
Any leisure-time PA in
In bivariate analyses, respondents
(yes/no)
past month
reporting presence of trails
Meets PA
significantly more likely
recommendation (5+
Parks or Recreation
Variable(s)3
TABLE 1 Articles Reporting Empirical Associations between Parks and Recreation Amenities and Physical Activity (Continued)
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331
52–62 year old
women in
Pittsburgh area
Older women in
Pittsburgh area
29. King et al.
(2005)
30. King et al.
(2003)
149
158
Is facility within walking
distance? (1500 m from
home along road
network): park,
walking/biking trail,
museum or art gallery,
golf course
Is facility within walking
distance? (20-minute
walk from home): park,
walking/biking trail,
community center
Average number of steps
per day (7 days of
pedometer readings)
Walking activity
(kcal/week)
Total PA (kcal/week)
Significantly greater steps per day
for participants with a park or trail
within walking distance, but no
difference for community center
Having none of the three facilities
within walking distance was
associated with significantly
greater self-reported walking or
total PA
(Continued on next page)
to engage in any PA (77.8% vs.
70.3%) and recommended PA
(31.3% vs. 23.8%) than those
reporting no trails
In multivariate analyses, reported
presence of trails not associated
with higher odds of any PA, but
marginally associated with
recommended PA (OR = 1.46, p
< .10)
Average number of steps
Significantly greater steps per day
for participants with a golf course
per day (as measured by
pedometer over 7 days)
within walking distance, but no
difference for having park, trail,
or museum within walking
distance
days with 30+ minutes
of moderate PA or 3+
days with 20+ minutes
of vigorous PA in past
week)
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332
577
65–94 year olds in
56 neighborhoods
in Portland, OR
8 neighbor-hoods in
Portland
32. Li, Fisher,
Brownson
and
Bosworth
(2005)
33. Lund (2003)
n/a
303
N2
65–94 year olds in
28 neighborhoods
in Portland
Population1
31. Li, Fisher
and
Brownson
(2005)
Authors and Date
Association(s)4
Number of strolling or destination
trips not significantly different
between neighborhoods with park
access only and control group of
neighborhoods with no access to
parks or retail amenities
Neighborhood walking
Neighborhoods with greater access
activity (score derived
to recreational PA facilities
from individuals’
showed less decline in walking
responses to 3 behavior
activity over four measurement
questions rated on 5-pt
time points (baseline, 3 months, 6
scale)
months, 12 months)
At neighborhood level, area of
Neighborhood walking
green and open space in
activity (neighborhood
neighborhood significantly
score derived from
individuals’ responses to related to neighborhood walking
At individual resident level, area of
3 behavior questions
green and open space and number
rated on 5-pt scale)
of recreation facilities
significantly related to walking.
Having playgrounds, parks, or
gyms close by not significantly
related to walking.
Physical Activity
Variable(s)3
Total acres of green and
open space for
recreation per
neighbourhood
Total acres of green &
open space for
recreation within 0.5
mile radius of
participant’s home
There are playgrounds,
parks, or gyms close by
that I can get to easily
(1–5, disagree-agree)
Number of recreational
facilities in the
neighborhood (out of 11)
Neighborhood has park
Number of strolling trips
access only (vs. has
in previous week
retail access only, retail Number of destination
and park access, or
trips in previous week
access to neither park or
retail)
There are playgrounds,
parks, or gyms close by
that I can get to easily
(1–5, disagree-agree)
Parks or Recreation
Variable(s)3
TABLE 1 Articles Reporting Empirical Associations between Parks and Recreation Amenities and Physical Activity (Continued)
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333
7th-12th grade
students
11–15 year olds in
San Diego
Adults across U.S.
18–96 year olds in a
rural south-eastern
U.S. community
34. Mota et al.
(2005)
35. Norman
et al.
(2005)
36. Plaut
(2005)
37. Reed et al.
(2004)
1112∗
38,243∗
878
1123
My neighborhood has
PA score out of 20 (5 PA
Significantly greater percentage of
several public recreation
questions scored on 4-pt
active (49.3%) than non-active
facilities, such
scales) divided into
(41.6%) respondents agreed with
as . . . (single item;
non-active (0–10) and
the presence of recreational
agree/disagree)
active (11–20)
facilities
Total minutes spent doing In bivariate analyses for both girls
Recreation in
(OR = 1.01) and boys (OR =
four sedentary activities
neighborhood score
1.08), recreation in neighborhood
assessed by proximity of
(TV, video games, sitting
listening to music, and
score not significantly related to
five facilities (each rated
time spent in sedentary activities
talking on phone) on
on a 5-pt proximity scale
most recent non-school
anchored by 1–5
minutes and 31+
day: <240 minutes vs.
>240 minutes
minutes): school, park,
recreation center, gym,
fitness facility
Live close to green area
Mode of travel to work
37.1% of car commuters, 28.9% of
(within half block)
(car, bicycle, walk)
bicycle commuters, and 36.3% of
people who walk to work live
close to a green area
Use of a community trail
Sufficiently active (5+
42% of trail users reported being
(within 10 miles or 20days with 30+ minutes
sufficiently active and 51%
minute drive): used, did
of moderate PA or 3+
engaged in a lesser amount of PA
not use, did not have
days with 20+ minutes
49% of regular walkers and 35% of
of vigorous PA in past
people who walked a lesser
week)
amount reported using trails
Regular walker (5+ days
per week for 30+
minutes)
(Continued on next page)
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334
Undergraduate
students at a U.S.
university
10–16 year olds in a
mid-sized
southwestern U.S.
city
25–69 year olds in El
Paso County, TX
39. Romero
(2005)
40. Rutt and
Coleman
(2005)
Population1
38. Reed and
Phillips
(2005)
Authors and Date
943∗
74
411∗
N2
Physical Activity
Variable(s)3
Proximity of exercise
Frequency (number of
facility (average
exercise bouts over
distance from home to
7-day period)
facilities used over a one Intensity (sum of METs ×
week period)
minutes for each type of
activity)
Duration (number of
minutes per exercise
bout over 7-day period)
Total PA (METs ×
frequency)
Availability of six
Number of days in past
week that included 20+
facilities (yes/no; 0–6
minutes of vigorous
index score): community
center, outdoor
activity
park/facility,
YMCA/YWCA, school
playground,
backyard/front yard,
home gym
Total number of parks,
Minutes per week during
gyms, schools, and
past month engaged in
biking/walking paths
light (e.g. walking),
within 2.5 miles of
moderate (e.g. yoga),
participant’s home
and vigorous (e.g.
Street distance to each
swimming) activities
type of facility
Parks or Recreation
Variable(s)3
Number of facilities not related to
any PA measure
Distance to facilities a significant
predictor of vigorous PA
Availability of facilities not
significantly correlated to PA
In both total sample and females,
proximity significantly correlated
to intensity and duration
In males, only significant
correlation was between
proximity and frequency
Association(s)4
TABLE 1 Articles Reporting Empirical Associations between Parks and Recreation Amenities and Physical Activity (Continued)
Downloaded By: [University of Washington] At: 23:14 14 March 2008
335
42. Timp-erio
et al.
(2004)
5–6 and 10–12 year
olds and their
parents in
Melbourne,
Australia
41. Sharpe et
18+ year olds in 2
al. (2004)
South Carolina
counties
1210∗
1936∗
Number of days in typical Meets PA recommendation Significantly greater predictors of
(5+ days with 30+
meeting PA recommendation than
month used public trail,
minutes of moderate PA
not meeting recommendation
track, path or mapped
or 3+ days with 20+
included number of days used a
route for PA
minutes of vigorous PA
track, trail, pathway, or mapped
Number of days in a
in past week)
route for PA, number of days used
typical month used a
Does not meet PA
public parks and other outdoor
public park or other
recommendation
recreation areas for PA, and
outdoor recreation area
having higher number of known
for PA
routes for walking and bicycling
Knowledge (number) of
in county
walking or jogging
Perceptions of number of parks,
routes in county
trails, and other outdoor
Knowledge (number) of
recreation areas not associated
known bicycling routes
with meeting PA recommendation
in county
Perceptions of the number
of parks, trails or other
outdoor recreation areas
in county
No parks or sports grounds Child’s walking or cycling Significantly lower odds of walking
near where I live (10–12
to destinations (e.g.
or cycling for 10–12 year olds
year olds’ agreement on
playgrounds, shops,
agreeing with no nearby parks
5-pt scale)
school, etc.) at least
(OR = 0.5), but no association for
Few sporting venues
three times per week
few sporting venues among
within our local area
younger age group
(parents’ agreement on
5-pt scale)
(Continued on next page)
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336
18+ year olds in
Arlington, MA
20–69 year olds in
Eindhoven,
Netherlands
44. Troped et al.
(2001)
45. Van Lenthe
and
Mackenbach
(2005)
46. VernezMoudon et
al. (2005)
8767∗
419∗
413∗
N2
47. Wendel-Vos et 20–59 year olds in
al. (2004)
Maastrict, The
Netherlands
11,541∗
18+ year olds in
608∗
King County, WA
18+ year olds in
Arlington, MA
Population1
43. Troped et al.
(2003)
Authors and Date
Physical Activity
Variable(s)3
Association(s)4
Cyclist (bike at least once Significantly higher odds of cycling
per week in
with presence of bicycle lanes
neighborhood for
and trails
recreation, exercise, or
Distance to closest rail trail
transportation)
associated with higher odds of
cycling
Square hectares of each
Hours per week of each of For leisure-time activity, only
green or recreation
walking and bicycling
significant relationship was
space within 300-m and
for each of leisure-time
between bicycling and sport
500-m radius: woods,
and commuting purposes grounds within 300 m radius
parks, sport grounds
For commuting activity, only
(e.g. tennis courts but
significant relationships were
not fitness centers),
between bicycling and sport
day-trip grounds (e.g.
grounds and parks within a 300 m
zoo)
radius
Presence of bicycle lanes
and trails in
neighborhood
Distance to closest rail
trail
Road network distance to Minutes per week of
Distance to rail-trail significantly
access point for a paved
recreational PA
and negatively related to minutes
community rail-trail
Minutes per week walking of PA for transportation, but not
or cycling for
related to recreational PA
transportation
Distance to bike trail (to
Any use of bike trail over For every 0.25 mile increase in
closest quarter mile)
past four weeks
distance to trail, participants were
0.65 times more likely to use trail
Availability of sport and
Time spent per week on
Respondents with poor proximity to
recreation facilities (5-pt sports participation
sports facilities significantly more
likely to report almost no sports
scale)
(almost none vs. 1+
hours)
participation (OR = 1.23)
Parks or Recreation
Variable(s)3
TABLE 1 Articles Reporting Empirical Associations between Parks and Recreation Amenities and Physical Activity (Continued)
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337
40+ year old women
across U.S.
18–96 year olds in a
rural U.S.
southeastern
county
48. Wilcox
et al.
(2000)
49. Wilson
et al.
(2004)
1194∗
2338
Easy access to walking
Sedentary (no sports or
Easy access to exercise facilities not
trails, swimming pools,
exercise or activities that
significantly related to being
sedentary in either urban (OR =
recreation centers, or
increased heart rate in
bicycle paths (single
past two weeks)
.96) or rural (OR = 1.09) women
item—present/absent)
Meets PA recommendation Significantly greater odds of
Walking or bicycling
trails: respondent uses
(5+ days with 30+
meeting PA recommendation for
minutes of moderate PA
low socio-economic status (SES)
trails, does not use trails,
or 3+ days with 20+
respondents who use trails (OR =
no trails reported within
10 miles or 20- minute
minutes of vigorous PA
2.81), but no association for high
in past week)
SES
drive)
Walk 30+ minutes for 5+ Significantly greater odds of
Parks: respondent uses
parks, does not use
days per week
walking 150+ minutes per week
for low socio-economic status
parks, no parks reported
within 10 miles ore
(SES) respondents who use trails
20-minute drive)
(OR = 3.04) and significantly
lower odds of walking for high
SES respondents who do not use
parks (OR = .44)
(Continued on next page)
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338
18+ year olds in 34
U.S. cities
Population1
n/a∗
N2
Parkland acreage as a
percentage of total city
acreage
Parks or Recreation
Variable(s)3
Association(s)4
Parkland acreage significantly
Utilitarian
walking/bicycling
correlated with utilitarian walking
and bicycling rate
prevalence rate (walking
or biking for transport in Parkland acreage not significantly
past week)
correlated with recreational
walking and bicycling rate
Recreational
walking/bicycling
prevalence rate (walking
or biking one of top two
most frequent physical
activities in past month)
Physical Activity
Variable(s)3
1
Only the sample age and location (where available) are reported here. For additional information about the sample and research design, readers are directed to the
original studies.
2
An asterisk adjacent to the sample size number indicates that the sample was drawn in a manner so as to be representative of the study population (e.g. randomly).
3
Although other variables related to parks or recreation and/or physical activity may have been collected or analyzed (or other values of the variables that are presented),
only the parks and recreation or physical activity variables/values that were related directly and empirically are reported in these columns. Variables in italics were
assessed using some objective method of measurement (e.g., geographic information systems, accelerometer, etc.), rather than subjectively by participants’ self-reports.
4
Unless otherwise noted, the term “significantly” implies differences at the .05 level. Other variables that were adjusted or controlled for in the analyses, if any, are
not reported here. When variables or variable values are listed in the variable columns but associations amongst them are not reported in this column, they were either
absent, insignificant, or both.
50. Zlot and
Schmid
(2005)
Authors and Date
TABLE 1 Articles Reporting Empirical Associations between Parks and Recreation Amenities and Physical Activity (Continued)
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Parks, Recreation, and Physical Activity
339
The remaining 20 articles (40%) reported mixed findings, including at least some
positive relationships between parks or recreation variables and PA (Addy et al., 2004;
Brownson et al., 2000; De Bourdeaudhuij, Sallis, & Saelens, 2003; Eyler et al., 2003;
Foster, Hillsdon, & Thorogood, 2004; Gomez et al., 2004; Hoehner et al., 2005; Humpel et
al., 2004; Huston et al., 2003; King et al., 2005; King et al., 2003; Li et al., 2005; Reed &
Phillips, 2005; Rutt & Coleman, 2005; Sharpe et al., 2004; Timperio et al., 2004; Troped
et al., 2003; Wendel-Vos et al., 2004; Wilson et al., 2004; Zlot & Schmid, 2005). In these
studies, disparate associations were observed when different classifications of the parks
or recreation variables (e.g., type of facility; distance to facility) or PA variables (e.g.,
transportational vs. recreational purpose; moderate vs. vigorous) were analyzed, or when
substituting objective versus subjective measurements of either type of variable altered the
relationships. In a few cases, mixed findings were also observed when different age, gender,
or socio-economic status categories were analyzed. The following sections describe patterns
in the relationships between different types and proximity of parks and recreation variables
and PA.
Relationships Between Different Types of Parks or Recreation Settings and Physical
Activity
To begin, we examined relationships between PA and particular types of parks or recreation settings. Unfortunately, approximately one-third of the studies reviewed used parks
or recreation variables that represented an aggregate or overall score of participants’ ratings
of their access to several recreation facilities (e.g., De Bourdeaudhuij et al., 2003; Mota
et al., 2005). In other cases, a single parks or recreation variable was used to analyze the
relationship with PA, but the particular setting was unspecified (e.g., Gomez et al., 2004).
Consequently, the associations between PA and these indeterminate variables were excluded
from the following descriptions.
The observed relationships between PA and trails/paths, parks, recreation centers,
exercise/fitness facilities, sports fields, golf courses, swimming pools, and living near a
coast/lake/beach are described in Table 2 with more detail in the following paragraphs. Table
2 indicates the number of the 50 studies reviewed that included each type of
TABLE 2 Associations Between Types of Park or Recreation Settings and Physical
Activity
Type of setting
Trails
Parks
Open space
Recreation centers
Exercise facilities
Sports facilities
Golf courses
Swimming pools
Lake/beach/coast
Total
N
Positive
association1
Mixed
associations1
No
association1
17
13
7
7
4
3
3
3
3
76,7,10,12,37,44,46
41,6,10,12
516,18−20,32
41,6,12,23
26,12
78,15,28,30,41,43,49
417,30,41,49
150
31,24,29
513,24,29,33,47
136
310,17,30
124
29,42
36,10,29
110
24,20
138
147
21,12
26
1
1
The larger numbers in each cell indicate the number of studies for each type of park or recreation
setting that reported a positive, mixed, or non-significant association with physical activity. The
superscript numbers in each cell refer to the specific studies as listed in Table 1.
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A. T. Kaczynski and K. A. Henderson
setting, as well as the breakdown of how many reported positive, mixed, or non-significant
associations. The superscript numbers listed beside the total for each association category
refer to the specific studies on which the total is based, as numbered in Table 1. Several
other settings or facilities were mentioned in only one or two studies (e.g., skating rink,
bowling green, dance studio, museum/art gallery, playground, gym, tennis court) and are
not described here.
Trails (or paths) were examined most frequently in the studies reviewed. More than
half (n = 17) of the articles that did not use aggregated or nonspecific measures of parks
or recreation variables included trails as a potential influence on PA, while 13 looked
individually at parks, and 8 employed some total combination of the amount of green or
open space within a specified area (Fisher et al., 2004). For trails exclusively, in most of
the studies at least some, if not all, of the reported relationships between the trail and PA
variables were positive. For example, Troped et al. (2001) concluded that for every quartermile increase in distance to a trail from home, participants were almost half as likely to
have used a bike trail in the past month. In a follow-up analysis, Troped et al. (2003)
reported that distance to the trail was negatively related to the number of minutes per week
spent walking or cycling for transportation, but not to the number of minutes of PA for
recreational purposes. Findings from a study of adults in South Carolina (Sharpe et al.,
2004) indicated the importance of knowledge and use of outdoor areas (i.e., as opposed to
just their presence) for enhancing PA. In this case, meeting the recommended PA level was
not associated with participants’ perceptions of the number of available parks, trails, and
other outdoor recreation areas in their county, but was significantly related to the number
of days they used trails in a typical month and their knowledge of walking/jogging and
bicycling routes in the county. Deshpande et al. (2005) and Reed et al. (2004) provided
similar results about how use of trails was related to engaging in recommended amounts of
PA (e.g., 30 minutes on 5 or more days per week). Finally, Brownson et al. (2000) found
that of the 36% of their study respondents in Missouri who reported having access to a
trail, 39% of them had used a trail, and 55% had increased their level of walking since
starting to use the trail. Increased walking was significantly more common among women
and among people using longer trails (i.e., greater than one-quarter mile) but was unrelated
to the distance from trail access. Several other correlational studies provided supportive
results about the importance of trails (Booth et al., 2000; Brownson et al., 2001; Chad et al.,
2005; Eyler et al., 2003; Huston et al., 2003; King et al., 2003; Vernez-Moudon et al., 2005;
Wilson et al., 2004), while only a few other studies documented non-significant findings
(Addy et al., 2004; Hoehner et al., 2005; King et al., 2005).
The relationship between parks and PA was examined in about one-third (n = 13) of
the articles that reported distinct associations between PRSs and PA. For example, Lund
(2003) featured parks as a key variable in testing the New Urbanism hypothesis “that
placing amenities within walking distance of homes will increase pedestrian travel and
social interaction among neighborhood residents” (p. 414). Eight neighborhoods in Portland
were purposefully selected based on their differing levels of access to parks and shopping
areas. Compared to individuals in the control group of neighborhoods that lacked access
(i.e., within one-quarter mile) to either parks or shopping areas, participants with access
to only parks had taken a similar number of both “strolling” and “destination” trips in the
past week. However, shopping areas appeared to have some influence on purposeful PA in
that individuals in neighborhoods with both retail and park access or just retail access had
a higher number of destination trips than people in neighborhoods with access to just parks
or to neither feature. In another study with similar results, distance to the nearest parkland
was not related to participants engaging in any recreational walking in the past week. Those
individuals with parkland beyond 600 meters from their homes were actually significantly
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Parks, Recreation, and Physical Activity
341
more likely to achieve recommended PA levels than people who lived closer to parkland
(Duncan & Mummery, 2005). Mixed or non-significant findings about the influence of
parks on PA were found in several other articles as well (Foster et al., 2004; Hoehner et al.,
2005; King et al., 2005; Wendel-Vos et al., 2004). Nevertheless, in other studies parks were
found to be one of the only variables that remained associated with achieving sufficient
activity levels when multivariate models were examined (Addy et al., 2004; Booth et al.,
2000). Deshpande et al. (2005) reported that respondents who had used parks in the past
month were more than 4 times more likely to have engaged in PA at least 5 times per week
for more than 30 minutes per episode. Several other studies reviewed also showed positive
associations between parks and assorted PA variables (Chad et al., 2005; King et al., 2003;
Sharpe et al., 2004; Wilson et al., 2004).
In addition to the articles that examined trails and parks, seven studies looked more
generally at open space within a particular area and its relationship to PA. Giles-Corti and
colleagues published several papers that used models involving the distance to, size, and
attractiveness of public open space (Giles-Corti et al., 2005; Giles-Corti & Donovan, 2002a,
2003). All of these articles generally reported that residents in Australia with greater access
to open space reported higher levels of PA. Among older adults in Portland, an overall
measure of walking activity within the neighborhood was significantly associated with the
absolute number of parks, paths, and trails per neighborhood acre (Fisher et al., 2004)
and with the total acreage of green and open space in the neighborhood (Li et al., 2005).
Similarly, Zlot and Schmid (2005) examined parkland acreage as a percentage of total
acreage in the 55 most populated cities in the U.S. (as taken from Harnik, 2003) and found a
strong correlation with the rate of walking and biking for transportation but a nonsignificant
relationship with recreational walking and bicycling. Finally, in a somewhat contradictory
finding, Plaut (2005) analyzed data from the 2001 American Housing Survey and stated
that a relatively equal proportion of people who traveled to work on foot (36.3%), by car
(37.1%), and by bicycle (28.9%) reported living within a half block of a green area.
Recreation centers (or facilities) were examined in seven articles. Three studies reported
positive relationships with participants achieving recommended PA levels (Addy et al., 2004;
Booth et al., 2000; Deshpande et al., 2005), while three showed nonsignificant associations
with various activity outcomes (Chad et al., 2005; Foster et al., 2004; King et al., 2003). In
the remaining study, Gordon-Larsen et al. (2000) analyzed data from almost 18,000 middle
and high-school students who participated in the U.S. National Longitudinal Study of
Adolescent Health. They found that use of a neighborhood recreation center was associated
with a 75% increase in adolescents falling into the highest category of PA (i.e., five or more
episodes per week). Interestingly, not using a recreation center was unrelated to greater
levels of time spent engaged in television/video watching and video game playing.
Four articles discretely examined relationships between exercise facilities and PA. In
two studies of differing age groups, access to a local exercise hall and level of health club
use were significantly associated with being classified as sufficiently active (Booth et al.,
2000; Deshpande et al., 2005). Different proximity measures for exercise facilities were
also positively related to particular PA variables in the articles by Reed and Philips (2005)
and Deshpande et al. However, in the only other study to individually examine this type of
amenity, having a fitness facility within a five-minute walk of home showed no association
with achieving the recommended level of PA during leisure time (Hoehner et al., 2005).
Three research teams examined the relationship between PA and sports facilities (or
grounds or venues). Both Carver et al. (2005) and Timperio et al. (2004) asked parents of
12–14 year olds and 5–6 year olds, respectively, to rate the presence of sports facilities in
their neighborhood or local area on a five-point scale. In the latter study, parents’ ratings
were unrelated to the 5–6 year olds walking or bicycling to get to places at least three times
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A. T. Kaczynski and K. A. Henderson
per week. However, in Carver et al.’s study, sports facilities were a significant predictor of
the frequency of cycling for transport among 12–14 year old boys but were unrelated to
walking or bicycling for exercise, recreation, or to get to and from school for either boys or
girls. In Wendel-Vos et al.’s (2004) study of adults in the Netherlands, the area dedicated to
sports grounds within 300 meters of participants’ homes was significantly associated with
bicycling for both leisure and commuting purposes.
Three studies examined golf courses with all three showing positive and significant
associations with PA. Interestingly, all three studies were conducted with participants ages
50 years and older. In two of the studies, golf courses were just one of several facilities
exhibiting positive associations with PA (Booth et al., 2000; Chad et al., 2005), but in the
other study golf courses were the only setting significantly associated with a greater number
of pedometer-measured steps per day (King et al., 2005).
Swimming pools were included in three of the articles reviewed. Engaging in PA for
30 or more minutes on at least five days per week was not significantly associated with
the number of days respondents had used a community swimming pool in the past month
(Deshpande et al., 2005) or with having a swimming pool within 10 miles or a 20-minute
drive (Addy et al., 2004). However, in the third study, swimming pools were one of several
facilities significantly related to higher PA scores among a sample of Canadian adults 50
years of age and older (Chad et al., 2005).
Finally, access to a coast or lake or beach generally had a positive impact on PA. Across
the three studies that examined these features, significant associations were observed with
being less likely to be sedentary and more likely to be adequately active and vigorously
active (Bauman et al., 1999), with spending more minutes walking in the neighborhood for
exercise and for pleasure (Humpel et al., 2004), and with engaging in any vigorous exercise,
any walking for recreation, and exercising vigorously at recommended levels (Giles-Corti
& Donovan, 2002a).
Relationships between Proximity of Parks or Recreation Settings and Physical Activity
Almost all studies included some form of spatial referent when investigating how features
of the surrounding environment were associated with PA. For example, participants were
asked to indicate opportunities that were found in their “neighborhood” or within “walking
distance.” As Table 1 illustrated, a wide range of spatial definitions were employed in relation
to the availability of PRSs. A small minority of studies employed specific distance or time
referents (e.g., 500 meters, 5-minute walk). Even fewer used continuous measures for the
parks or recreation variables studied (e.g., street network distance to a facility), although
these improved the specificity of the relationships with PA that could be observed. Most of
the studies, however, used a categorical proximity referent that was either quantitative (e.g.,
five-minute walk) or qualitative (e.g., “close by”). Table 3 lists the wide range of proximity
categories and the number of studies (and corresponding reference numbers from Table 1)
in which each distance referent was found to have either a positive, mixed, or nonsignificant
association with PA.
Only a small number of studies included specific distance or time referents. WendelVos et al. (2004) used GIS data to ascertain the presence of several PRSs within 300 meters
and 500 meters of each participant’s home. In their study, none of the facilities beyond 300
meters were significant predictors of either walking or bicycling for leisure or commuting
purposes. However, having sports grounds within 300 meters was associated with increased
bicycling for both leisure and commuting, while parks within 300 meters were associated
with only increased bicycle commuting. Hoehner et al. (2005) found that objective assessments of the facilities within 400 meters of the respondents’ homes were unrelated to
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TABLE 3 Associations Between Proximity to Parks or Recreation Settings and Physical
Activity
Proximity category
Specific distance referent
Specific time referent
Within walking distance
In neighborhood; close by
In community
Access to
Continuous distance measure
Total
N
Positive
association1
4
6
5
12
4
3
7
232,47
210,12
13
55,23,31,34,46
137
26,7
244,46
Mixed
associations1
1,24
2
417,26,29,30
328,32,42
21,49
422,38,40,43
No
association1
213,24
22,11
49,14,33,36
140
148
135
1
The larger numbers in each cell indicate the number of studies for each proximity category that
reported a positive, mixed, or non-significant association with physical activity. The smaller numbers
in each cell refer to the specific studies as listed in Table 1.
meeting PA recommendations during recreational pursuits. As described previously, Duncan and Mummery (2005) dichotomized the distance from participants’ homes to the nearest
parkland into greater and less than 600 meters. In their Australian sample, parkland proximity was not related to engagement in recreational walking, and those individuals with
parkland beyond 600 meters were actually more likely to achieve recommended PA levels.
Finally, the total acres of recreational open space within a half-mile (i.e., 800 meters) of
participants’ homes was significantly related to neighborhood walking activity for a sample
of older adults in Portland (Li, Fisher, Brownson & Bosworth, 2005).
With respect to time, De Bourdeaudhuij et al. (2003), Atkinson et al. (2005), and Chad
et al. (2005) all asked participants to estimate whether numerous park or recreation facilities were within a five-minute drive. The latter two studies also included the concurrent
referents of a 10-minute walk and a 5-minute walk, respectively, while the former two also
included facilities on a frequently traveled route. In two of these studies (De Bourdeaudhuij
et al., Atkinson et al.), the majority of the relationships with the PA variables studied were
not significant, while the other study (Chad et al.) reported almost all positive associations.
In addition to the objective measures described previously, Hoehner et al. (2005) inquired
about participants’ perceptions of amenities within a 5-minute walk of their home. Addy
et al. (2004) used a 10-minute walk criterion while adding the extra referent of 0.5 miles.
Both studies reported some positive and some inconclusive findings about the importance
of different PRSs for PA participation. Finally, Deshpande et al. (2005) found that shorter
walking times (as reported by participants as a continuous variable) to most park or recreation facilities translated into more regular PA.
Some studies asked more generally about facilities within walking distance. For example, Ball et al. (2001) found that Australians’ overall perception of having shops, a park
or beach, and/or cycle path within walking distance was significantly related to increases
in walking for exercise. Humpel et al. (2004) reported that having a lake or beach within
walking distance was associated with increased time spent walking for a variety of purposes,
although most of the latter associations disappeared in more complex multivariate models.
In two separate studies that provided additional descriptors to guide respondents, King et al.
(2005) defined walking distance as 1500 meters from home, while King et al. (2003) defined
it as a 20-minute walk from home. In the former investigation, achieving a significantly
greater number of steps per day on a pedometer was influenced by a golf course, but not a
park, trail, or museum. In the 2003 study, the same PA variable was positively associated
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A. T. Kaczynski and K. A. Henderson
with having a park or trail within walking distance but not a community center. Finally,
Foster et al.’s (2004) study of adults in England showed mixed results for walking with
respect to having a park or leisure center within walking distance.
The largest group of studies used similar terms such as “close by,” “near where I live,” or
“neighborhood” to guide respondents’ thinking about PRSs. A small number also included
additional referents such as “within a half block” or “that I can get to easily.” In almost
half of these investigations, the associations between the PRS and the PA variables studied
were mainly positive and significant (Blanchard et al., 2005; Gordon-Larsen et al., 2000; Li,
Fisher, & Brownson, 2005; Mota et al., 2005; Vernez-Moudon et al., 2005). For example,
Mota et al. asked 1123 middle and high school students to rate on a 4-point scale their
level of agreement with the statement, “My neighborhood has several public recreation
facilities, such as parks, walking trails, bike paths, recreation centers, playgrounds, public
swimming pools, etc.” The PA variable in their study consisted of five questions, each with
four response choices, about sports and PA participation outside school. Participants were
divided into active and nonactive groups using the midpoint of the scale and a significantly
greater percentage of active than non-active students agreed with the presence of the parks
and recreation facilities in their neighborhood. However, several other studies investigating
“nearby” or “neighborhood” facilities reported mixed (Huston et al., 2003; Li et al., 2005;
Timperio et al., 2004) or mostly nonsignificant or negative (Carver et al., 2005; Duncan
et al., 2004; Lund, 2003; Plaut, 2005) findings about the relationship between PRSs and
PA.
Some researchers employed distance or time referents that were more reflective of
community park and recreation settings. Reed et al. (2004) and Wilson et al. (2004) both
found generally positive associations with PA participation for people who used trails that
were within 10 miles or a 20-minute drive of home. Some similar results were found for
parks within the same reference area (Addy et al., 2004; Wilson et al., 2004). However, Rutt
and Coleman (2005) counted the total number of parks, gyms, schools, and walking/biking
paths within 2.5 miles of participants’ homes and found this figure was unrelated to the
number of minutes per week their study participants spent engaged in light, moderate, or
vigorous activities.
A few studies simply asked about participants’ “access to” various parks or recreation
amenities (Booth et al., 2000; Brownson et al., 2001; Wilcox et al., 2000). For example, in
a survey of women 40 years or older across the U.S., Wilcox et al. found that the presence
or absence of easy access to a set of amenities (e.g., walking trails, swimming pools,
recreation centers, or bicycle paths) was unrelated to engagement in no sports or exercise
activities in the past week for either urban or rural respondents. In contrast, Booth et al.
reported that having access to almost all of the park or recreation facilities they studied was
associated with being classified as active for older Australian adults when each facility was
examined individually. Brownson et al.’s telephone survey of adults across the U.S. showed
that having access to trails, parks, and indoor gyms were each associated with meeting PA
recommendations.
Finally, some studies used distance measures that were either continuous or included
several ordered response categories (e.g., one-quarter mile, one-half mile, three-quarter
miles, etc.) that improved their specificity. Studies by Troped et al. (2001, 2003) using these
types of measures found positive associations between distance to a paved rail-trail and
both use of the trail and number of minutes spent walking or cycling for transportation.
Vernez-Moudon et al. (2005) also reported positive associations with distance to a rail-trail
in an examination of cycling. Other researchers that used continuous distance measures
also discovered positive associations. Gomez et al. (2004) found that for the grade 7 boys
(but not girls) in their San Antonio sample, straight line distance from home to the nearest
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Parks, Recreation, and Physical Activity
345
open play area was significantly associated with their number of outdoor bouts of PA per
week. Street distance to various indoor and outdoor facilities was related to minutes per
week of vigorous PA but not to light or moderate PA for a sample of adults in El Paso (Rutt
& Coleman, 2005). Further, Reed and Phillips (2005) calculated the average distance from
university students’ places of residence to the exercise facilities they used over the course
of a week. This measure was related to intensity and duration of use among females and
to frequency of use for males. Finally, in Norman et al.’s (2005) study of 11–15 year old
boys in San Diego, participants indicated the time it would take to walk to each of five
recreation facilities on a five-point scale ranging from 1–5 minutes to 31 or more minutes.
The aggregated “recreation in the neighborhood” score was not significantly related to the
total amount of time the boys spent engaged in several sedentary activities over the course
of a nonschool day.
Discussion
The purpose of this study was to review evidence related to PRSs as features of the built
environment and the relationship these settings had to PA. The degree to which parks and
recreation as part of the built environment contributed to PA and healthier communities
was generally evident. Results concerning the types of PRSs and PA were mixed, but trails,
parks, open spaces, golf courses, and natural settings were more likely to be associated with
PA than recreation centers, exercise facilities, and sports facilities. Drawing conclusions
about the importance of proximity to PRSs was difficult because of the mixed results and
the wide variety of descriptors used to measure access and proximity. However, for all of the
proximity categories, substantially more positive or mixed associations were observed than
nonsignificant relationships. Further, almost all studies using continuous distance measures
reported that increased proximity to PRSs was associated in some way with increased PA.
Overall, this review provided some evidence about the contribution that parks or recreation
make to PA, but the findings are generally inconclusive. The review, however, raised a
number of questions that should be answered with further research regarding PRSs and PA.
Sallis, Owen, and Fotheringham (2000) proposed a five-phase framework to classify
stages of research in behavioral epidemiology:
1.
2.
3.
4.
5.
establish links between the behavior (e.g., park-based PA) and health,
develop measures of the behavior,
identify influences on the behavior (e.g., proximity to park),
evaluate interventions to change the behavior, and
translate research into practice.
Few of the studies we reviewed fell into the latter stages, which would suggest a lack
of maturity in research investigating the relationship of parks and recreation with PA (Sallis
et al., 2000). Most of the studies we reviewed rudimentarily could be classified into phase
three, while few articles uncovered in our broader searches addressed parks or recreation
measurement, interventions, or implementation as they related to promoting PA.
With approximately 80% of the articles showing some significant relationships, PRSs
and PA appeared to share some positive association. However, such generalized conclusions
also must be drawn with caution for several reasons. Only 8 of the 50 studies reviewed
involved participants younger than 18 years (Carver et al., 2005; Duncan et al., 2004;
Gomez et al., 2004; Gordon-Larsen et al., 2000; Mota et al., 2005; Norman et al., 2005;
Romero, 2005; Timperio et al., 2004), and seven out of these eight studies showed either
nonsignificant or mixed findings. Therefore, the strength of the association between parks
or recreation and PA for nonadult samples appears somewhat more attenuated. Additionally,
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A. T. Kaczynski and K. A. Henderson
less than one-fifth of the studies reported findings disaggregated by gender (Carver et al.,
2005; De Bourdeaudhuij et al., 2003; Foster et al., 2004; Gomez et al., 2004; Humpel et al.,
2004; Humpel, Owen, Iverson, et al., 2004; Humpel, Owen, Leslie, et al., 2004; Reed &
Phillips, 2005), despite female rates of PA participation, especially in youth, being lower than
males (Caspersen, Pereira, & Curran, 2000). In about half of these studies, the association
between PRSs and PA was different based on gender. Complex relationships may exist for
other population sub-groups as well (e.g., races, income levels). Similar to what Sallis et
al. (2006) concluded, most of the active living research related to parks and recreation to
date has involved middle class, mostly white adults living in urban and suburban settings.
The studies reviewed employed diverse operationalizations of both parks or recreation
and PA. For example, proximity definitions (e.g., within neighborhood, walking distance)
ranged from 400 m to 1500 m or 5 minutes to 20 minutes, while many studies left it
up to the respondent to define terms like “access/availability” or “neighborhood/near my
home.” Similar diversity was evident in the PA variables employed. In addition, as with any
regression-type analyses such as the frequent use of odds ratios, controlling for or including
different variables changes the impact of the predictor variables on the outcome measures.
Some studies listed the variables that were included in the model at different steps of the
analysis, but other authors either elected not to control for covariates or failed to report this
stage in their narratives.
Another aspect notably missing from this research review was a corpus of qualitative
studies. We noted that a handful of studies were examined (Hesketh et al., 2005; Thompson
et al., 2002; Thomson, Kearns, & Petticrew, 2003). Almost all of the details of PRSs
were lacking. For example, in a qualitative study about perceptions of parents and children
regarding healthy eating, activity, and obesity, Hesketh et al. found that parents thought
the local environment including playgrounds, bike tracks, and sporting facilities helped
encourage children to be physically active. The parents noted that their children “frequently
used the available facilities but expressed a need for a greater number and variety of facilities,
particularly in light of the decreasing size of backyards” (p. 23). Although this qualitative
information is useful, it provides little specificity. Similarly, the American Indian women in
Thompson et al.’s study described the lack of access to affordable and convenient facilities
but provided limited descriptions about the operation of those facilities or the proximity
needed. The value of qualitative studies in the future may be in the potential to elicit more
meaningful descriptions that can be used to design and provide public park and recreation
programs and amenities.
Finally, almost all of the studies reviewed were cross-sectional. Therefore, inferring
causality or the direction of the relationship was nearly impossible, even when one variable
(e.g., proximity of a park) was treated as the independent or predictor variable by the original
researchers. Nevertheless, cross-sectional studies are important for expediently identifying
factors that might be targeted to improve PA in future controlled or community intervention
studies (Sallis & Owen, 1999).
The Dearth of Detail
Several reasons may exist for the dearth of detail about parks and recreation. First, almost
all the articles reviewed appeared in journals that have not typically had recreation and
leisure as a focus (e.g., American Journal of Public Health, American Journal of Preventive Medicine, American Journal of Health Promotion). Further, few of the authors had
parks and recreation as part of their background. Therefore, the nuances and detail of park
and recreation environments often were not described adequately. More researchers with
background in parks, recreation, and leisure should be contributing to this literature. For
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347
historical reasons, however, some recreation and leisure scholars (Henderson et al., 2001)
have tried to differentiate the field from sport and physical education by suggesting that
recreation offers broader benefits to individuals. Although recreation professionals believe
that recreation involves more than physical endeavors, perhaps leisure scholars should focus
again and more intentionally on physical benefits by using both subjective and objective
approaches.
A second reason why the literature about parks and recreation has not been detailed
may be that tools for measuring park and recreation amenities relative to PA have not been
readily available. Although recreation and leisure scholars (Moore & Shafer, 2001; Shafer,
Lee, & Turner, 2000) have studied trails, greenways, and parks, the focus has been on
physical health as only one dimension among many benefits from recreation participation.
Few instruments have been developed to examine specific amenities of parks and recreation
that might affect PA directly. Researchers such as Bedimo-Rung, Gustat, Tompkins, Rice,
and Thomson (2006), Troped et al. (2006), and Saelens et al. (2006) have begun to isolate
the specific aspects of parks and trails that may contribute to PA promotion, but these tools
are relatively new.
Third, a lack of transdisciplinary research that examines the context of PRSs within
neighborhoods and communities is obvious. The Transportation Review Board (TRB, 2005)
published a report identifying aspects of the built community that enhance and promote
PA. The report concluded that the research from several disciplines (e.g., public health,
urban planning, parks and recreation) about the environmental determinants of PA is limited. TRB recommended more interdisciplinary approaches, more complete conceptual
models, and a more detailed examination of the specific characteristics of the built environment and different types of PA. Similarly, Srinivasan, O’Fallon, and Dearry (2003)
noted that many communities do not understand the health consequences of environmental factors and have focused only on adverse health effects. They advocated for multidisciplinary research on positive health impacts of the built environment within planned
communities.
Finally, another reason studies about the built environment and PA have not elicited
detail about the park and recreation structures may be that in addition to transdisciplinary
research that cuts across a number of fields, community-based research to improve public
health is necessary (Israel et al., 1998). A fundamental characteristic of this needed research
may include an emphasis on the participation and influence of nonacademic researchers in
the process of creating a knowledge base (Henderson & Bialeschki, 2005). Practitioners in
parks and recreation have an important role to play in addressing the specifics of how built
environments can promote PA. More depth of inquiry about the settings and amenities is
needed. For example, Payne (2002) called for more research on the reciprocal relationships
between leisure and health, including issues related not only to the design of areas and
facilities, but also leadership, equipment, aesthetics, and participant developmental abilities.
Conclusion
The future for examining parks and recreation as features of the built environment that
enhance PA appears boundless. Until now, the tools and methods for studying parks and
recreation within the built environment have been limited. Further, collaborations and partnerships have been lacking. Nevertheless, leisure scholars as well as all other related disciplinary scholars can contribute a variety of approaches and strategies to promote this line
of study. For example, case studies could be helpful in examining the processes that occur
in designing PRSs and promoting their use for PA. Policy research relative to how parks
and recreation is funded and how these settings and amenities fit into a broader community
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348
A. T. Kaczynski and K. A. Henderson
plan would be useful. Similarly, longitudinal studies might be valuable in examining the
use of facilities over time (e.g., family patterns).
The complexity of conducting research, however, may be minor compared with the
challenges of implementing interventions (Sallis et al., 2006). The interesting aspect of
this dilemma is that parks and recreation providers have been concerned with PA as one
important dimension of their work for more than 100 years. However, as is true with most
types of previous public health interventions, the focus has been on the individual and not on
the park and recreation policies. These attempts to support and invest in parks and recreation
will require public support and political advocacy. These intervention efforts will require
time, energy, money, and creativity. Physical activity as well as parks and recreation will
need to become higher social priorities. Nevertheless, park and recreation agencies exist
in many communities and for the future they must be acknowledged for the significant
potential they have for promoting healthy living through increased PA. Evidence-based
research that shows an empirical relationship between the presence and characteristics of
PRSs and the PA and health of community members is wide open for exploration. As is
apparent from this literature analysis, efforts are underway.
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