Neighborhood Environment and Physical Activity Among Youth

Neighborhood Environment and Physical Activity Among Youth

Neighborhood Environment and Physical Activity Among Youth A Review Ding Ding, MPH, James F. Sallis, PhD, Jacqueline Kerr, PhD, Suzanna Lee, MPH, Dori...

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Neighborhood Environment and Physical Activity Among Youth A Review Ding Ding, MPH, James F. Sallis, PhD, Jacqueline Kerr, PhD, Suzanna Lee, MPH, Dori E. Rosenberg, PhD, MPH

Context: Research examining the association between environmental attributes and physical activity among youth is growing. An updated review of literature is needed to summarize the current evidence base, and to inform policies and environmental interventions to promote active lifestyles among young people. Evidence acquisition: A literature search was conducted using the Active Living Research (ALR) literature database, an online database that codes study characteristics and results of published papers on built/social environment and physical activity/obesity/sedentary behavior. Papers in the ALR database were identifıed through PubMed, Web of Science, and SPORTDiscus using systematically developed and expert-validated search protocols. For the current review, additional inclusion criteria were used to select observational, quantitative studies among youth aged 3–18 years. Evidence synthesis: Papers were categorized by design features, sample characteristics, and measurement mode. Relevant results were summarized, stratifıed by age (children or adolescents) and mode of measurement (objective or perceived) for environmental attributes and physical activity. Percentage of signifıcant results was calculated.

Conclusions: Mode of measurement greatly influenced the consistency of associations between environmental attributes and youth physical activity. For both children and adolescents, the most consistent associations involved objectively measured environmental attributes and reported physical activity. The most supported correlates for children were walkability, traffıc speed/volume, access/proximity to recreation facilities, land-use mix, and residential density. The most supported correlates for adolescents were land-use mix and residential density. These fındings support several recommendations for policy and environmental change from such groups as the IOM and National Physical Activity Plan. (Am J Prev Med 2011;41(4):442– 455) © 2011 American Journal of Preventive Medicine

Context

P

hysical activity offers numerous health benefıts to young people.1 It is recommended that youth participate in moderate to vigorous physical activity for at least 60 minutes daily.2 Recent accelerometer data2,3 indicated, however, that only 42% of children and 8% of adolescents in the U.S. met this guideline.

From the Graduate School of Public Health (Ding, Lee); the Department of Psychology (Sallis), San Diego State University, San Diego; the Department of Family and Preventive Medicine, University of California San Diego (Ding, Kerr), La Jolla, California; and the Department of Rehabilitation, University of Washington (Rosenberg), Seattle, Washington Address correspondence to: Ding Ding, MPH, 3900 5th Avenue, Suite 310, San Diego CA 92103. E-mail: [email protected]. 0749-3797/$17.00 doi: 10.1016/j.amepre.2011.06.036

442 Am J Prev Med 2011;41(4):442– 455

Ecologic models postulate multiple environmental influences on physical activity.4 Growing literature from public health, transportation, urban planning, and leisure studies5–7 has examined the association between the built environment (i.e., physical environment) and physical activity. However, these associations are less understood among young people than among adults, as reflected by fewer published studies.8,9 Understanding environmental correlates of physical activity among young people is especially important because children and adolescents have less autonomy in their behaviors and are more likely than adults to be influenced by the environment, directly or indirectly through parents or peers.9 –12 Informed decision making about environmental interventions, often through policy changes, requires a comprehensive understanding of environmental correlates of

© 2011 American Journal of Preventive Medicine • Published by Elsevier Inc.

Ding et al / Am J Prev Med 2011;41(4):442– 455 13

physical activity. The preferred method of deriving lessons from scientifıc literature is to use a systematic approach to synthesize empirical fındings.14 A recent review of reviews8 identifıed a small number of review papers on environmental correlates of youth physical activity. Most of the identifıed reviews included a broad range of correlates, of which the built environment attributes constituted only a small percentage of variables reviewed.15,16 Some reviews12,17–19 were limited to a specifıc type of physical activity (e.g., active commute to school) or a specifıc activity setting (e.g., school). The most thorough review of the built environment and youth physical activity was by Davison and Lawson in 2006,7 which included 33 papers. Because the number of studies has increased rapidly, an updated review is needed to better represent the current evidence base. To date, fındings regarding the built environment and physical activity revealed complex patterns,8 characterized by inconsistent associations with some environmental attributes.9,20,21 Heterogeneity across studies poses a major challenge for summarizing fındings.21 Mode of measurement (e.g., objective or perceived) may influence environmental variables’ associations with physical activity.8,9,22 Similarly, mode of measuring overall or domainspecifıc physical activity (e.g., active commute) is expected to affect associations with environmental attributes, because these associations are highly specifıc to domains of physical activity.16,23 Completeness of literature search and accuracy of reporting studies are also concerns that may influence conclusions of a review.14 The present study summarized fındings from peerreviewed papers on the associations between neighborhood environment and physical activity among youth. The review focused on attributes that can be modifıed through policies and planning initiatives (e.g., sidewalks, traffıc). To improve on previous reviews, the current review included a larger number of studies from multiple disciplines, employed systematic literature search and data extraction methods, used a semi-quantitative approach for summarizing results,23 and stratifıed results by age and by measurement modes of environmental attributes and physical activity.

Evidence Acquisition Data Sources The present review used the Active Living Research (ALR) literature database, a publicly accessible online database that codes study characteristics and results of published papers on the relationship between built and social environment variables and physical activity, obesity, and sedentary behavior. The database can be accessed at www.activelivingresearch.org/litdb. October 2011

443

Since 2002, researchers at ALR have conducted semiannual literature searches through PubMed, Web of Science, and SPORTDiscus, using a systematically developed and expert-validated search protocol. The protocol defıned comprehensive search terms, term combinations, and search limitations, which can be accessed at http:// www.activelivingresearch.org/litdb/papers.php?action⫽ background. The resulting papers were screened by researchers based on inclusion and exclusion criteria. Inclusion criteria were as follows: (1) published in English language; (2) dependent variables included a measure of physical activity, weight status, or sedentary behavior; and (3) for observational studies, the environmental attributes were measured as independent variables, and for intervention studies, environmental change was an experimental condition. Papers were screened for inclusion in three steps based on reading the title, abstract, and full text. Two researchers conducted screening independently, and the fınal lists were compared to ensure completeness and accuracy of screening. Trained research assistants coded design features, methods, and results using a detailed protocol. For quality control, another research assistant and a supervisor checked each coded variable. The corresponding author of each paper was invited to approve the coding of their paper. If the corresponding author was not reachable, a second author was contacted. If corrections were requested by authors, their suggestions were compared with the database protocol, and decisions for correction were made accordingly. By October 2010, the ALR database included 648 coded papers.

Inclusion and Exclusion Criteria for Review Additional inclusion criteria were applied to select papers from the ALR database for the current review. These criteria were: (1) observational study design; (2) study population was children or adolescents (aged 3–18 years); (3) sample size was 50 or larger; (4) study was published before January 2010; (5) dependent variables included total, recreational, or transport physical activity; (6) independent variables were specifıc environmental attributes of neighborhoods; (7) test statistics for associations between dependent and independent variables were provided and signifıcance could be determined. Studies were excluded if: (1) the study population included other age groups in addition to children and adolescents that could not be separated; (2) physical activity was observed in specifıc settings only (e.g., park, school); (3) the study reported only descriptive or qualitative results. Although experimental studies provide stronger evidence for causality, such studies were not included because of the small number of papers available and the diffıculty of separating effects from different components of interventions.

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Environmental Variables Reviewed Considering the large number of environmental variables included in papers, only common neighborhood environmental attributes with at least three coded results were selected for review (Table 1). When the variable could not be categorized because of lack of specifıcity, a more general category was created (e.g., unspecifıed safety). Broad and nonmodifıable variables such as urban/rural and SES were not included. Study results were stratifıed by objective and perceived measures separately for children and adolescents.

Table 1. Expected directions of associations between attributes of neighborhood environment and domains of physical activity among youth Expected direction of association

Domains of physical activitya

Parks (access/density/proximity)

Positive

Leisure-time (Transport)

Recreation facilities (access/density/ proximity)

Positive

Leisure-time (Transport)

Land-use mix/destinations

Positive

Transport

Residential density

Positive

Transport

Street connectivity

Positive

Transport

Walkability

Positive

Transport

Walking/biking facilities (e.g., sidewalks, bike paths)

Positive

Transport Leisure-time

Traffic speed/volume

Inverse

Transport Leisure-time

Pedestrian safety structures (e.g., zebra crossing, traffic lights)

Positive

Transport Leisure-time

Neighborhood incivilities/disorders

Inverse

Transport Leisure-time

Crime-related safety

Positive

Transport Leisure-time

Vegetation

Positive

Leisure-time (Transport)

Environmental attributes

a

Primary domain of physical activity expected to be associated with environmental attributes is presented without parentheses, secondary domain is presented in parentheses.

Data Extraction Methods. The following information was extracted from each paper: study design, study region, total sample size, sample age, year of publication, and measures of the environment and physical activity (Table 2). Sample age was determined using reported mean or median age: Those aged 3–12 years were coded as children and those aged 13–18 years were coded as adolescents. Nine studies including both children and adolescents presented separate analyses for each sample.62,108 These studies were coded as “including both children and adolescents” for sample characteristics description (Table 2), and their results were summarized separately for children and adolescents (Tables 3– 6). Objectively measured physical activity included overall physical activity (total or moderate-to-vigorous) captured by motion detectors such as accelerometers and pedometers. Reported physical activity included self- or parent-reports using a survey instrument. Examples of objective and perceived measures of neighborhood environmental attributes are presented in Appendix A (www.ajpmonline.org). Coding of results. Separate results were presented for children and adolescents because age was expected to affect the associations between neighborhood environment and physical activity.12 In each paper, all results (adjusted and unadjusted) regarding statistical tests of associations between environmental variables and phys-

ical activity were considered for the review. Multiple entries for an association might be reported from one study as a result of different statistical tests, participant subgroups, and covariates adjusted. Associations of environmental attributes with conceptually mismatched domains of physical activity (Table 1) were excluded. Direction of each association was coded as ⫹, –, or 0: ⫹ indicated a signifıcant association in the hypothesized direction; – signifıed a signifıcant association not in the hypothesized direction; and 0 stood for a nonsignifıcant association. Hypothesized directions of associations were based on theories and previous literature,4,5,127–129 and are presented in Table 1. The signifıcance and direction of each result were tallied separately for children and adolescents and stratifıed by measurement mode of environmental attributes and physical activity. The total number of associations is presented for each code (⫹, –, or 0), and the number of studies from which the results were abstracted is presented in parentheses. A percentage (⫹%) was calculated to represent the proportion of comparisons supporting the hypothesized association (i.e., those coded as ⫹) over the total number of comparisons for each environmental variable. When interpreting the percentages, rules used by a previous review23 were adopted to classify variables based on strength of evidence for associations with physical acwww.ajpmonline.org

Ding et al / Am J Prev Med 2011;41(4):442– 455

Table 2. Characteristics of papers reviewed (n⫽103) Characteristics of paper

Paper counts

Reference no.

52–250

22

24–45

251–499

21

46–66

500–999

14

67–80

1000–1999

21

81–101

2000–4999

13

102–114

ⱖ5000

11

115–125

1

126

Total sample size

Not reported Study design Cross-sectional Longitudinal

99 4

24–29, 31–54, 56–77, 79–115, 117–126 30, 55, 78, 116

Sample age (years) Children

56

24, 26, 28, 29, 31–34, 40–42, 45–48, 50–52, 54–56, 58, 60, 65, 69, 70, 72, 75, 77, 78, 80–83, 85, 86, 94, 95, 97, 99, 101, 104, 106, 107, 109, 110, 112, 114–116, 120, 121, 123–126

Adolescents

38

25, 27, 30, 36–39, 43, 44, 49, 57, 59, 61, 63, 66, 68, 71, 73, 74, 76, 84, 87–93, 96, 98, 100, 102, 103, 105, 113, 117, 119, 122

Both

9

35, 53, 62, 64, 67, 79, 108, 111, 118

Geographic origin Asia

1

88

Australia/New Zealand

11

41, 42, 49, 54, 55, 64, 67, 99, 112, 113, 125

Europe

18

44, 46, 50, 56, 58, 59, 66, 71, 73, 75, 76, 81, 86, 87, 90, 96, 107, 118

North America

73

24–40, 43, 47, 48, 51–53, 57, 60–63, 65, 68–70, 72, 74, 77–80, 82–85, 89, 91–95, 97, 98, 100–106, 108–111, 114–117, 119–124, 126

Year of publication 1993–1999

4

29, 78, 100, 107

2000–2004

10

24, 25, 41, 58, 68, 77, 79, 89, 104, 112

2005–2009

89

26–28, 30–40, 42–57, 59–67, 69–76, 80–88, 90–99, 101–103, 105, 106, 108–111, 113–126

Objective

25

26, 30–33, 38, 39, 48, 50, 61, 64, 67, 70, 74, 80, 82, 83, 104, 105, 108, 109, 111, 117, 122, 124

Perceived

58

24, 27, 29, 34, 35, 40–44, 46, 47, 49, 52, 53, 55–60, 62, 65, 66, 68, 71, 73, 75, 77–79, 86–92, 94–96, 98–103, 106, 107, 109, 112–116, 118, 119, 123

Both

20

25, 28, 36, 37, 45, 51, 54, 63, 69, 72, 76, 81, 84, 85, 93, 97, 120, 121, 125, 126

Objective

18

24, 26, 28–30, 32, 33, 38, 39, 42, 48, 51, 60, 64, 74, 82, 83, 85

Report

77

25, 27, 31, 34–36, 40, 41, 43–47, 49, 50, 52, 53, 55, 56–59, 62, 63, 65, 66, 68, 69–73, 75–77, 80, 81, 84, 86–94, 96, 98–126

445

tivity (0%–33%, little evidence/no association; 34%–59%, intermediate evidence/inconsistent association; 60%–100%, strong evidence/association).

Evidence Synthesis General Characteristics of Papers Reviewed A total of 103 papers were reviewed. Most studies were cross-sectional and conducted in North America (fıve in Canada, 68 in the U.S.). There has been a dramatic growth in the number of papers in the last few years, with 86% of papers published between 2005 and 2009. Sample sizes ranged from 52 to 68,288, with a median of 781. There were more studies of children than adolescents. A large majority of papers used only reported measures for neighborhood environment and for physical activity. For comparisons involving reported physical activity, domain-specifıc results are summarized in the text to aid interpretation, but results in tables are not domain-specifıc.

Environmental measures

Physical activity measures

Both

October 2011

8

37, 54, 61, 67, 78, 79, 95, 97

Neighborhood Environment and Physical Activity Among Children A total of 878 comparisons were reviewed from 65 papers, including 317 using objective measures of neighborhood environment and 561 using perceived measures. More than two thirds of the comparisons involved re-

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Table 3. Summary of associations between objectively measured environmental attributes and physical activity of children (aged 3–12 years)

Objectively measured environmental variables

References

Objectively measured physical activity outcomesa

Reported physical activity outcomea

Result counts (paper counts)a

Result counts (paper counts)a



0



⫹%



0



⫹%

Total ⫹%

23 (4)

30 (4)

0 (0)

43

4 (1)

8 (2)

0 (0)

33

42

10 (4)

0 (0)

41

11 (2)

0 (0)

0 (0) 100

64





25 (4)

13 (2)

0 (0)

66

66

Recreation environment Parks (access/density/ proximity)

28, 31–33, 80, 83, 108

Recreation facilities (access/density/ proximity)

28, 31, 32, 51, 64, 80, 82, 110

7 (3)

Land-use mix destinations

69, 70, 108, 110, 126





Residential density

31, 33, 69, 70, 72, 108, 110, 111, 120, 121

4 (1)

5 (1)

0 (0)

44

23 (8)

8 (4)

3 (1)

68

63

Street connectivity

31, 33, 67, 69, 70, 83, 104, 108, 110

4 (1)

12 (4)

5 (1)

19

5 (3)

10 (4)

0 (0)

33

25

Walkability

45, 69









3 (2)

0 (0)

0 (0) 100 100

Walking/biking facilities

26, 28, 64, 67, 70, 83, 126

8 (3)

13 (4)

3 (1)

33

4 (1)

1 (1)

0 (0)

80

41

Traffic speed/volume

50, 67, 125









14 (2)

7 (2)

0 (0)

67

67

Pedestrian safety structures

50, 67

0 (0)

2 (1)

4 (1)

0

8 (1)

1 (1)

0 (0)

89

53

Crime-related safety

28, 32, 64

3 (2)

13 (4)

0 (0)

19







19

Incivilities/disorders

26, 28, 50

0 (0)

5 (2)

0 (0)

0

4 (1)

2 (1)

0 (0)

67

36

26, 50, 64, 70, 83

3 (2)

5 (2)

0 (0)

38

4 (1)

0 (0)

0 (0) 100

58

52

95

12

33

105

50

Neighborhood design

Transportation environment

Social environment —

Other Vegetation Total results

3

66

50

⫹, significant association in the expected direction; 0, nonsignificant association; –, significant association in the unexpected direction; ⫹%, number of results coded as ⫹/total number of results.

a

ported physical activity (n⫽609), and less than one third used objective measures of physical activity (n⫽269).

Results Based on Objective Measures of Neighborhood Environment Among Children When neighborhood environmental attributes were measured objectively (Table 3), 50% of the results showed significant associations in the expected direction. The percentage of signifıcant associations (⫹%) was higher when physical activity was measured by reports (66%) compared with objectively measured overall physical activity (33%). Several environmental variables had “inconsistent” associations with objectively measured physical activity, including resi-

dential density (44%); parks (43%); recreation facilities (41%); and vegetation (38%). No environmental attribute was associated with objectively measured physical activity in more than 60% of the results. Stronger evidence existed for associations between neighborhood environmental attributes and reported physical activity; nine of 11 variables had ⫹% ⬎60%. Walkability, access to recreation facilities/open space, and vegetation (i.e., presence of street trees) were associated with domain-specifıc physical activity in all comparisons. Pedestrian safety structures (89%) and social incivilities (67%) were associated with several reported physical activity outcomes, such as active commute and www.ajpmonline.org

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Table 4. Summary of associations between perceived environmental attributes and physical activity of children (aged 3–12 years)

Perceived environmental variables

References

Objectively measured physical activity outcomes

Reported physical activity outcomes

Result counts (paper counts)a

Result counts (paper counts)a



0





25

4 (2)

15 (6)

0 (0)

21

22

18 18 (7)

37 (7)

2 (1)

32

28

9 (4)

23 (5)

6 (1)

24

23

17 (5)

0 (0)

43

43

6 (3)

5 (2)

0 (0)

55

55

25 12 (6)

21 (6)

1 (1)

35

32

1 (1)

36

34

0



Total ⫹% ⫹%

⫹%

Recreation environment Parks (access/density/ proximity)

24, 35, 47, 50, 52, 62, 79, 80, 85, 109, 112

2 (1)

6 (2) 0 (0)

Recreation facilities (access/density/ proximity)

24, 35, 47, 50, 52, 62, 79, 80, 85, 109, 112

4 (1) 17 (4) 1 (1)

Neighborhood design Land-use mix/destinations 42, 50, 52, 62, 69, 85, 101

1 (1) 18 (2) 1 (1)

5

Residential density

50, 62, 69, 81







— 13 (2)

Street connectivity

62, 69, 112









Transportation environment Walking/biking facilities

34, 35, 40, 50, 52, 56, 62, 69, 85, 86, 94, 95, 101, 114

3 (1)

8 (1) 1 (1)

Traffic speed/volume

46, 52, 54, 85, 95, 101, 112, 114, 125, 126

0 (0)

4 (1) 2 (1)

Pedestrian safety structures

114, 125

Traffic safety (unspecified) 40, 41, 46, 54, 56, 62, 69, 86, 107, 114, 125

0 35 (10) 61 (10)









5 (2)

1 (1)

0 (0)

83

83







— 10 (6)

13 (6)

0 (0)

43

43

25 (8)

2 (1)

34

25

1 (1)

27

22

Social environment Crime-related safety

40, 41, 46, 52, 60, 62, 69, 79, 85, 86, 95, 114, 125, 126

2 (1) 19 (3) 2 (1)

9 14 (8)

Unspecified safety

34, 52–54, 58, 65, 79, 81, 86, 95, 99, 102, 106, 109, 114, 115, 123, 124

1 (1) 18 (5) 0 (0)

5 17 (12) 44 (14)

Incivilities/disorders

52, 54, 77









7 (3)

8 (3)

0 (0)

47

47

52, 54, 58, 62, 114, 118









4 (4)

13 (5)

1 (1)

22

22

13

90

7

12

154

283

14

34

30

Other Vegetation Total results

⫹, significant association in the expected direction; 0, nonsignificant association; –, significant association in the unexpected direction; ⫹%, number of results coded as ⫹/total number of results.

a

playing outdoors. Land-use mix (66%); residential density (68%); walking facilities (e.g., sidewalk; 80%); and traffıc speed/volume (67%) were consistently associated with transport physical activity or walking.

Results Based on Perceived Measures of Neighborhood Environment Among Children Neighborhood environment–physical activity associations were much weaker when environmental attributes October 2011

were measured by participants’ perceptions (Table 4). Only 30% of all comparisons were signifıcant. When the perceived environment– objective physical activity combination was used, none of the environmental attributes had consistent associations with overall physical activity (all ⫹%⬍33%). The consistency of associations was higher when physical activity was measured by reports. The most supported association involved pedestrian safety

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448

Table 5. Summary of associations between objectively measured environmental attributes and physical activity of adolescents (aged 13–18 years) Objectively measured physical activity outcomes

Reported physical activity outcomes

Result counts (paper counts)a

Result counts (paper counts)a

References



0



⫹%



0



⫹%

Total ⫹%

Parks (access/density/ proximity)

25, 37, 61, 74, 76, 108

2 (2)

8 (3)

0 (0)

20

9 (4)

10 (5)

0 (0)

47

38

Recreation facilities (access/density/ proximity)

74, 117, 64, 76, 80, 93

3 (2)

9 (2)

0 (0)

25

16 (3)

21 (2)

0 (0)

43

39

Land-use mix/destinations

38, 39, 74, 108

4 (3)

3 (1)

0 (0)

57

5 (1)

3 (1)

0 (0)

63

60

Residential density

30, 74, 108, 111

0 (0)

3 (2)

0 (0)

0

4 (2)

1 (1)

0 (0)

80

50

Street connectivity

63, 67, 74, 105, 108

6 (1)

19 (2)

2 (1)

22

14 (4)

15 (2)

0 (0)

48

36

Walkability

39, 74

1 (1)

4 (2)

0 (0)

20









20

Walking/biking facilities

64, 67, 76

0 (0)

11 (2)

0 (0)

0

0 (0)

4 (1)

0 (0)

0

0

Traffic speed/volume

67









0 (0)

5 (1)

0 (0)

0

0

Pedestrian safety structures

67

3 (1)

13 (1)

2 (1)

17

5 (1)

14 (1)

2 (1)

24

21

25, 37, 61, 64

0 (0)

10 (3)

0 (0)

0

1 (1)

5 (3)

0 (0)

17

6

64

1 (1)

3 (1)

0 (0)

25









25

4

19

54

78

2

40

31

Objectively measured environmental variables Recreation environment

Neighborhood design

Transportation environment

Social environment Crime-related safety Other Vegetation Total results

20

83

⫹, significant association in the expected direction; 0, nonsignificant association; –, significant association in the unexpected direction; ⫹%, number of results coded as ⫹/total number of results.

a

structures (e.g., traffıc lights, crosswalks) and reported physical activity (83%). Several environmental attributes showed inconsistent associations with reported physical activity, including street connectivity (55%); incivilities (47%); residential density (43%); unspecifıed traffıc safety (43%); walking/biking facilities (35%); traffıc speed/volume (36%); and crime-related safety (34%).

Neighborhood Environment and Physical Activity Among Adolescents A total of 843 comparisons from 47 studies were reviewed. More results involved perceived environmental measures (n⫽602) than objective measures (n⫽241). Similarly, more results were based on reported physical activity (n⫽702) than objective measures (n⫽141).

Results Based on Objective Measures of Neighborhood Environment Among Adolescents When objective measures were employed for neighborhood environmental attributes (Table 5), 31% of all associations were signifıcant in expected directions. Similar to patterns found among children, results were more likely to be significant when objective environmental measures were matched with reported physical activity measures than with objective physical activity (19% vs 40%). None of the environmental attributes was signifıcantly associated with objective physical activity in more than 60% of the comparisons. However, land-use mix was signifıcant in 57% of comparisons, providing intermediate evidence. When physical activity was measured by reports, evidence supported associations of land-use mix (63%) and residential density (80%) with reported physical activity. www.ajpmonline.org

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Table 6. Summary of associations between perceived environmental attributes and physical activity of adolescents (aged 13–18 years)

Perceived environmental variables

References

Objectively measured physical activity outcomes

Reported physical activity outcomes

Result counts (paper counts)a

Result counts (paper counts)a



0



⫹% ⫹

0



Total ⫹% ⫹%

Recreation environment Parks 35–37, 44, 61, 71, 76, 79, 93, (access/density/proximity) 102, 113

1 (1)

6 (2)

0 (0)

14

9 (7)

25 (7)

0 (0)

26

24

Recreation facilities 27, 35–37, 44, 49, 57, 59, 62, (access/density/proximity) 66, 68, 71, 76, 79, 84, 87, 88, 90–92, 96, 98, 100, 113, 122

0 (0)

6 (2)

0 (0)

0

64 (17)

120 (18)

1 (1)

35

34

Neighborhood design Land-use mix/destinations

35, 44, 49, 59, 62, 71, 88, 90, 96









13 (6)

36 (8)

2 (1)

25

25

Residential density

62, 96









3 (1)

11 (2)

0 (0)

21

21

Street connectivity

35, 44, 59, 62, 71, 90, 96









5 (3)

19 (7)

0 (0)

21

21

3 (1)

8 (1)

1 (1)

25

21 (7)

24 (8)

0 (0)

47

42

Transportation environment Walking/biking facilities

35, 44, 59, 62, 71, 76, 87, 88, 90, 96, 113

Traffic speed/volume

49, 71, 90, 96









15 (2)

24 (3)

0 (0)

38

38

Traffic safety (unspecified)

35, 59, 62









7 (3)

12 (3)

0 (0)

37

37

Social environment Crime-related safety

27, 35, 43, 49, 59, 61, 62, 79, 89, 90, 96, 98

0 (0)

3 (2)

0 (0)

0

11 (4)

60 (10)

1 (1)

15

15

Unspecified safety

25, 27, 37, 44, 49, 53, 57, 79, 88, 91, 92, 100, 103, 113, 119

0 (0)

6 (2)

0 (0)

0

13 (8)

52 (13)

0 (0)

20

20

Incivilities/disorders

27, 89









4 (2)

4 (2)

0 (0)

50

50

44, 62, 87, 118









1 (1)

11 (4)

0 (0)

8

8

4

29

1

12

166

398

4

29

28

Other Vegetation Total results

⫹, significant association in the expected direction; 0, nonsignificant association; –, significant association in the unexpected direction; ⫹%, number of results coded as ⫹/total number of results.

a

Access to parks (47%); recreation facilities (43%); and street connectivity (48%) had inconsistent relationships with reported physical activity.

Results Based on Perceived Measures of Neighborhood Environment Among Adolescents As Table 6 shows, when perceived measures of environmental attributes were matched with objective measures of overall physical activity, none of the environmental attributes showed a consistent association (all ⫹% ⬍33%), and the overall percentage of signifıcant associations was only 12%. October 2011

When perceived measures of neighborhood environment were matched with reported physical activity, 29% of all comparisons were signifıcant, and no environmental attribute was strongly related (all ⫹%⬍60%) to physical activity. However, a few variables had inconsistent associations with domainspecifıc physical activity measures. These variables included social incivilities (50%); walking/biking facilities (47%); traffıc speed/volume (38%); unspecifıed traffıc safety (37%); and access to recreation facilities (35%).

Results Summary Table 7 summarizes the consistency of neighborhood environment–physical activity associations. Consis-

450

Ding et al / Am J Prev Med 2011;41(4):442– 455

tency of associations was generally higher among children than adolescents except for the perceived environment– objective physical activity combination, for which the level of consistency of associations was low among both age groups. For both children and adolescents, associations were the most consistent when comparisons involved the objective environment–reported physical activity combination, and the least consistent was the perceived environment– objective physical activity combination.

Discussion This review extracted 1721 results from 103 papers. A key fınding was that mode of measurement influenced observed associations between neighborhood environment and youth physical activity (Table 7). Objectively measured environmental attributes were much more consistently related to physical activity. This pattern may be explained by less measurement error in objective measures. In contrast, reported physical activity was much more consistently related to neighborhood environment than was objectively measured physical activity. This may be because reported measures captured specifıc domains of physical activity (e.g., active transport, leisure-time physical activity), which provided a more precise test of association. This fınding is consistent with theory and literature127,129,130 indicating that environmental influence on physical activity is domain-specifıc and context-specifıc. Based on present results, conclusions based on objectively measured environmental variables seem more credible. For children, evidence supports associations of reported physical activity with objective measures of access to recreation facilities, land-use mix, residential density, walkability, walking/biking facilities, traffıc speed/ volume, pedestrian safety structures, incivilities/ disorders, and vegetation. Inconsistent evidence exists for park access and street connectivity. For adolescents, evidence supported the associations of reported PA with objective measures of residential density and land-use mix, and inconsistent evidence existed for parks, recreation facilities, and street connectivity. All reported physical activity measures pertained to a specifıc domain (e.g., transportation) or a specifıc type (e.g., walking). Such domain-specifıc and behaviorspecifıc fındings are well documented among adults,5,14 so the present review provides evidence that such associations generalize to youth as well. There is suffıcient evidence to recommend policy changes to enhance access to parks and recreation facilities and to encourage mixeduse developments to promote physical activity across a wide age range.

Crime and general measures of safety were extensively studied, but there was very limited support for associations with youth physical activity. There are two caveats for this literature. First, one paper49 contributed a large proportion of results on reported crime-related safety, mostly nonsignifıcant, possibly skewing the results. Second, measures of safety, especially reported measures, were often crude and rarely validated. Studies often did not distinguish crime from traffıc safety, or combined different domains of safety in one scale, which might obscure associations with physical activity.131 The current review revealed that associations between physical activity and traffıc safety were more consistently supported than those with crime-related safety, suggesting differential effects from different domains of safety. Given high levels of safety concerns among parents as a barrier to youth physical activity, further studies, including more-sophisticated and specifıc measures, are warranted.11 When both street connectivity and physical activity were measured objectively, there were about as many – associations as ⫹. This was especially the case for children. This pattern is contrary to that from adult studies,20,132 in which street connectivity has consistent and positive associations with physical activity. This pattern among youth could be a result of different functions of streets across age groups. For adults, better-connected streets provide more direct routes for active transport.128,133 For children, however, streets may offer opportunities for both active transport and leisure-time physical activity. Previous studies74,134 suggested that neighborhoods with low street connectivity had cul-desacs or low-traffıc areas that provided locations for children’s safe outdoor play. These possibilities are worthy of more detailed study.

Neighborhood–Physical Activity Associations: What Are Appropriate Standards? Using an arbitrary criterion adopted by a previous review,23 it was found that no environmental variable was supported as a consistent correlate of physical activity across all four combinations of measurement modes. Thus, there is no clear conclusion that one or more environmental variables are unambiguously supported as physical activity correlates. This fınding was similar to those from several reviews,8,16,17 in which very few features of the neighborhood environment were identifıed as consistently being associated with physical activity. The level of consistency of fındings from the present review is lower than that from an earlier review23 of mainly psychosocial correlates of physical activity that used a similar approach to coding results. However, the previous review did not code every fınding as was done in www.ajpmonline.org

Ding et al / Am J Prev Med 2011;41(4):442– 455

451

Table 7. Summary of associations between the neighborhood environment and physical activity among children and adolescents stratified by measurement modes Environmental measures Objective Physical activity measure

Result counts (paper counts)

Perceived ⫹%

⫹%

Strengths

Objective Children

159 (13)

33

Adolescents

107 (8)

19

Children

158 (20)

66

Adolescents

134 (14)

40

Reported

⫹%, number of results coded as ⫹/total number of results.

the present review. Given the present inclusion of adjusted and unadjusted tests and multiple outcome measures in multiple subgroups, it is unclear how the consistency of associations should be judged. A more-selective review of studies with the strongest methodology taking a more quantitative meta-analytic approach may be more defınitive. In a recent review of environmental correlates of physical activity among adults, Wendel-Vos et al.20 found a large proportion of null associations and suggested that studies might have “defıned or measured [environmental attributes] in a wrong way.” Because the area of the built environment and physical activity is still young,135 more studies with improved conceptualization and measures are needed to expand the current knowledge base, from which more-consistent and convincing conclusions can be drawn.

Recommendation for Future Studies One major area of improvement for future studies is measurement. The current review found that consistency of associations varied greatly by measurement modes. Future studies should include both objective and perceived measures in one study, whenever possible, to compare and contrast the impact of measurement mode,136 on total and domain-specifıc physical activity. Future studies should also improve perceived measures by using specifıc defınitions and validated instruments. Future papers should provide methodologic details regarding the operationalization of environmental constructs to facilitate the synthesis of fındings. Longitudinal study designs are encouraged to improve the rigor of research. More studies outside the U.S. can help understand generalizability of fındings. Several understudied environmental attributes, such as vegetation, neighborhood incivilities, and pedestrian safety structures are high October 2011

Result counts (paper counts)

priorities for further research. Subgroup-specifıc analyses could help understand for whom built and social environments are most influential.

The large number of studies and fındings included in this review provided a 34 (3) 12 useful update. Studies were searched systemati451 (41) 34 cally from several search 568 (35) 29 engines using a comprehensive list of search terms. Review and data extraction were conducted systematically, and coding was checked by at least two researchers. Results were based on all associations reported in a paper, not selected fındings. Stratifıcations of results by age and by mode of measurement were informative. 110 (12)

12

Limitations First, the present review considered only the signifıcance and direction of each association, not effect size. Therefore, no comparison could be made about the magnitude of associations across variables or measurement modes. Second, although expert-validated protocols were used to classify environmental variables, some variables could not be precisely classifıed because of lack of information. Third, this review employed a vote count review method, which disregarded sample size and gave results from the same study and those from different studies the same weight. Therefore, conclusions may be heavily influenced by a large number of studies with small sample sizes or a few studies that reported many results.137 Fourth, some individual fındings could be considered over-adjusted because variables in the causal pathways (e.g., other built environment variables) were controlled for, possibly leading to fewer signifıcant fındings. Fifth, environment– physical activity associations may vary by subgroup. However, because of a small number of gender- or location-specifıc studies, no subgroup-specifıc summaries could be reported. Finally, the current analyses did not formally stratify counts by types or domains of reported physical activity measures. This was because the review aimed to summarize overall associations of neighborhood environment with physical activity, instead of with a specifıc type of physical activity. Acknowledging that the environment–

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physical activity associations are context- and domainspecifıc,129 only specifıc types or domains of physical activity outcomes that were conceptually matched with the environmental variables were selected. The domainspecifıcity of associations is not always clear, because at least one study35 found that proximity to recreation facilities was related to active transport because children could walk or bike to a park to do recreational physical activity. Variables like crime, traffıc safety, and sidewalks are expected to be relevant for more than one physical activity domain.

Conclusion The best use of the present review may be to identify the neighborhood environmental attributes that are most strongly supported, because such fındings can inform environment and policy change priorities being pursued for chronic disease prevention. More confıdence can be placed in studies in which environmental variables were measured objectively. The most supported correlates for children were traffıc speed/ volume, access/proximity to recreation facilities, mixed land use, residential density, and walkability. The most supported correlates for adolescents were land-use mix and residential density. Because these associations have been supported for both youth and adults, there is growing empirical support for policies that target these environmental conditions.24-126 Policies to enhance access to parks could include development regulations for new or redeveloped neighborhoods, joint use agreements that lead to schools opening their facilities for community use, and incentives for private recreation facilities to locate in underserved neighborhoods. Zoning reform is needed in many cities to allow or require mixed-use development as the default. New road design standards and “complete streets” policies would need to be adopted to create roadways that are more pedestrian-friendly and safer automobile traffıc patterns. Present results provide additional evidence that generally supports childhood physical activity promotion and obesity prevention policy recommendations from the IOM,138 The U.S. Surgeon General,139 The White House Task Force on Childhood Obesity Prevention,140 and the U.S. National Physical Activity Plan.141 This study was funded by Active Living Research, a national program of the Robert Wood Johnson Foundation. The authors thank all graduate assistants who contributed to the Active Living Research Literature Database: Holly Forman, Ashley Withers, Anna Stachel, Jordan Carlson, Erin Merz,

Courtney Corle, and Kalisha McIntosh. Special thanks to Carmen Cutter, Deputy Director of Active Living Research. No fınancial disclosures were reported by the authors of this paper.

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Appendix Supplementary data Supplementary data associated with this article can be found, in the online version, at doi:10.1016/j.amepre.2011.06.036.