The Relationship between the Neighborhood Built Environment and Active Transportation among Adults: A Systematic Literature Review
Abstract
:1. Introduction
2. Materials and Methods
2.1. Search Strategy and Inclusion/Exclusion Criteria
- Objective measurement of the urban neighborhood environment.
- Transport-related physical activity measured with self-reported methods. Self-reported methods are most frequently used in obtaining physical activity data [16]. Therefore, we only focused on studies using self-reported physical activity data and excluded studies using objectively measured physical activity data.
- Mean age of study respondents of between 18 and 65 years old. Studies that solely focused on older adults (>65 years old) were excluded because older adults might have declined mobility [24], which might lead to a different relationship between built environment and AT.
- Quantitative studies with cross-sectional or longitudinal data.
2.2. Data Extraction
2.3. Coding of Evidence
2.4. Quality Assessment Criteria
3. Results
3.1. Study Characteristics
3.2. Results of Quality Assessment
3.3. Relationship between Neighborhood Built Environment and AT
3.3.1. Walking for Transport
3.3.2. Cycling for Transport
3.3.3. General AT
3.3.4. Inconsistent Results from Studies with Different Designs
4. Discussion
4.1. Summary of Evidence
4.1.1. Comparison of Results between Walking and Cycling for Transport
4.1.2. Comparison with Existing Literature Reviews
4.2. Differences in the Results of Studies with Different Designs
4.2.1. Study Location
4.2.2. Study Quality
4.2.3. Analyzed Geographic Unit and Different Measurements of AT
4.3. Limitation and Implications for Future Research
4.3.1. Limitation of the Included Studies
4.3.2. Limitation of the Systematic Review
4.3.3. Implication for Future Research
5. Conclusions
Acknowledgments
Author Contributions
Conflicts of Interest
References
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Built Environment Factor | Relevant Items or Examples Used in Included Articles |
---|---|
Residential density | Population density; dwelling density |
Land use mix | Land use diversity |
Street connectivity | Intersection density; street crossing density |
Retail land use | Retail area ratio; commercial land use; commercial intensity; density of services |
Walkability | Walkability score; walkability index; Walk Score; active living potential |
Street integration | The extent of access to a street segment or set of streets from other street segments or other parts of the city |
Sidewalk | The presence or length of sidewalk; sidewalk/pedestrian network |
Bicycle lane | The presence or density or length of bicycle lane; the proximity to bicycle lane; bicycle network connectivity |
Access to destinations | The presence or number of a range of destinations; the proximity/access to shop, services, restaurant, bus stop/railway station, school, work, church, etc. |
Traffic volume/speed | Traffic volume; traffic speed |
Hilliness | Hill; slope |
Neighborhood aesthetics | Presence of trees; green canopy coverage; greenness; green space; streetscape; the number of parks; park land use |
Type of results | Description | Code |
---|---|---|
Not able to get a summary result | 0–4 studies reach a conclusion for the built environment factor; | - |
0–40% of studies reach a conclusion in the same direction; | ||
41–50% of studies reach a conclusion in the same direction and ≥25% in the opposite direction | ||
Possible relationship | 41–50% of studies reach a conclusion in the same direction and <25% in the opposite direction | P; O; N |
Convincing relationship | 51–100% of studies reach a conclusion in the same direction | P; O; N |
Component | Explanation | Score |
---|---|---|
Response rate | The overall response rate of the questionnaire survey of physical activity |
|
Representativeness | Whether the study sample could represent the target population |
|
Outcome measures | Whether the study used a valid questionnaire |
|
Confounding factors | Whether the study controlled for socioeconomic factors and self-selection factors |
|
Final grade | The final result of the quality assessment after summing up the scores above |
|
Author, (Year), Reference | Location, Sample Size | Mean Age/Age Range (Years) | Objective Measures of Built Environment | Travel Mode | Analyzed Geographic Unit |
---|---|---|---|---|---|
McCormack et al. (2012) [25] | Australia, 1681 | 40.2 | GIS-based measures | 1 | 1.6-km road network buffer around home address |
Knuiman et al. (2014) [26] | Australia, 1703 (baseline d) | 39.9 | GIS-based measures | 1 | 1.6-km road network buffer around home address |
Kamruzzaman et al. (2016) [27] | Australia, 3612 (baseline) | 40–70 | Archival datasets e | 1 | 1-km circular buffer around home address |
Wasfi et al. (2016) [28] | Canada, 2976 (baseline) | 18–55 | Walk Score metric | 1 | Walk Score based on residential location |
Miles et al. (2008) [29] | USA, 72 | 40; 44 | GIS-based measures; direct observations | 1 | 402-m, 805-m, 1609-m of the center of the neighborhoods |
Lee and Moudon (2006) [30] | USA, 438 | ≥18 | GIS-based measures | 1 | Land use and infrastructure: 1-km around home address; access to destination: 3-km around home address; density: parcel level and 1-km around home address |
Handy et al. (2006) [31] | USA, 1672 | 43.3; 54.7 | GIS-based measures | 1 | 400-m, 800-m, 1600-m street network buffer around home address |
Pikora et al. (2006) [32] | Australia, 1678 | 18–59 | SPACES c instrument | 1 | 400-m radius buffer around home address |
Forsyth et al. (2007) [33] | USA, 715 | 44/49 | GIS-based measures | 1 | 805 × 805 m2; 0.2-km, 0.4-km, 0.8-km, 1.6-km street network and straight-line buffer around home address |
Rodríguez et al. (2009) [34] | USA, 5529 | 45–84 | GIS-based measures | 1 | 200-m radius buffer around home address |
Sundquist et al. (2011) [35] | Sweden, 2269 | 20–66 | GIS-based measures | 1 | Neighborhood based on administrative area |
Carlson et al. (2012) [36] | USA, 679 | 52 | Built environment metrics | 1 | Neighborhood based on administrative area |
Karusisi et al. (2014) [37] | France, 7290 | 30–79 | GIS-based measures | 1 | 500-m street network radius buffer around home and workplace |
Sung et al. (2014) [38] | Korea, 1826 | 39.6 | GIS-based measures | 1 | 250-m, 500-m, 1000-m, 1500-m circular buffers around home |
Jack and McCormack (2014) [39] | Canada, 1875 | ≥18 | GIS-based measures | 1 | 1.6-km street network buffer around home address |
Reyer et al. (2014) [40] | Germany, 1871 | 54.1 | GIS-based measures; Walk Score metric | 1 | Walk Score: 500-m area around home address |
Thielman et al. (2015) [41] | Canada, 151,318 | >12 | Walk Score metric | 1 | Walk Score values were assigned to postal codes and a single postal code can include multiple respondents |
Owen et al. (2007) [42] | Australia, 2650 | 20–65 | GIS-based measures | 1 | Census Collectors’ Districts |
Tilt et al. (2007) [43] | USA, 529 | ≥18 | GIS-based measures | 1 | 0.4-mi street networks buffer of residential parcels |
Saelens et al. (2012) [44] | USA, 2199 | 45.2 | GIS-based measures | 1 | 1-km street network buffer around home address |
Riva et al. (2009) [45] | Canada, 2716 | ≥45 | GIS-based measures | 1 | Dissemination area-level: stable geographic units composed of one or more neighboring street blocks, with a population of 400–700 persons |
Turrell et al. (2013) [46] | Australia, 10,711 | 40–65 | Archival datasets | 1 | Census Collectors’ Districts |
Wineman et al. (2014) [47] | USA, 460 | 50.9 | GIS-based measures | 1 | Street connectivity and integration: 0.5-mi radius from survey participant’s residential block; density and land use mix: 0.25-mi, 0.5-mi radius |
Oliver et al. (2011) [48] | Canada, 1602 | 47 | GIS-based measures | 1 | 1-km road network buffer around each respondent’s postal code |
Koohsari et al. (2017) [49] | Japan, 569 | 55.8 | GIS-based measures | 1 | Intersection density: 800-m radius buffer around home address; Street integration: 1-km radius buffer |
Larrañaga et al. (2016) [50] | Brazil, 442 household | 43 | GIS-based measures | 1 | 500-m buffer from the geometric center of the census tract of residence |
Kelley et al. (2016) [51] | USA, 906 | 55 | Walk Score metric | 1 | Walk Scores base on home address |
Koohsari et al. (2017) [52] | Australia, 16,345 | 46.6 | Archival datasets; Walk Score metric | 1 | Statistical Area 1 (the smallest geographic unit in Australia) |
Dill and Voros (2007) [53] | USA, 566 | ≥18 | GIS-based measures | 2 | 0.25-mi buffer around home address |
Owen et al. (2010) [54] | Australia, 1940 | 45.4 | GIS-based measures | 2 | Census Collectors’ Districts |
Rybarczyk and Wu (2014) [55] | USA, 6210 | 18–74 | GIS-based measures | 2 | 3-km straight-line buffers around home address |
Zhao (2014) [56] | China, 613 | 48.1; 43.7 | Archival datasets | 2 | 3.5-km radius from the centroid of a community |
Foster et al. (2011) [57] | UK, 13,927 | 41–80 | GIS-based measures | 2 | 0.5-km, 1-km, 2-km, 3.2-km buffers around home address |
Ma and Dill (2015) [58] | USA, 616 | 51.3 | GIS-based measures | 2 | 0.5-mi circular and network buffers around home address |
Heesch et al. (2015) [59] | Australia, 10,328 | 40–65 | GIS-based measures | 2 | Neighborhood suburbs (a median of 3.9 km2 in size) |
Zahabi et al. (2016) [60] | Canada, 21,188 (baseline); | ≥15 | GIS-based measures | 2 | 500-m grid cell level |
Braun et al. (2016) [61] | Spain, 765 | 18–65 | GIS-based measures | 2 | 400-m circular buffer around home address |
Mertens et al. (2017) [62] | Five countries a, 3904 | 45.5 | SPOTLIGHT Virtual Audit Tool | 2 | In Hungary: 1 km2 areas in greater Budapest; in other countries: neighborhoods based on local administrative boundaries |
Kondo et al. (2009) [63] | Japan, 156 | 51.0; 53.8 | GIS-based measures | 3 | 500-m radius buffer around home address |
Cervero et al. (2009) [64] | Colombia, 1285 | ≥18 | GIS-based measures | 3 | 500-m straight-line radius around the sampled neighborhoods; and 1000-m straight-line beyond the perimeters of sampled neighborhoods |
Van Dyck et al. (2009) [65] | Belgium, 120 | 43 | Field observations, geographical map data | 3 | 800-m radius buffer around home address |
Van Dyck et al. (2010) [66] | Belgium, 1166 | 42.7 | GIS-based measures | 3 | Neighborhood based on statistical sectors |
Fan et al. (2014) [67] | USA, 39,660 census tracts | 37.7 | GIS-based measures | 3 | Census tract (between 1200 and 8000 residents) |
Munshi (2016) [68] | India, 2050 | 38; 39; 40; 44 | Archival datasets | 3 | 100-m equal size grid cell level |
Christiansen et al. (2016) [69] | Ten countries b, 12,181 | 18–66 | GIS-based measures | 3 | 500-m and 1-km street-network buffer around home address |
Witten et al. (2012) [70] | New Zealand, 2033 | 20–65 | GIS-based measures and SPACES c instrument | 4 | Accessibility: 800-m along street network of a meshblock centroid; other variables: at the meshblock level |
Frank et al. (2006) [71] | USA, 1228 | 44 | Archival datasets | 4 | 1-km street network buffer around home address |
Hoehner et al. (2005) [72] | USA, 1053 | 18–96 | Environmental audits | 4 | 400-m buffer around home address |
de Sa and Ardern (2014) [73] | Canada, 1158 | 47.9 | GIS-based measures | 4 | 500-m radius buffer around home address |
Mäki-Opas et al. (2016) [74] | Finland, 2098 | 30–64 | GIS-based measures | 4 | The pedestrian and cycling network within 500-m buffer around home address |
Feng (2016) [75] | China, 5051 | ≥20 | Archival datasets | 4 | 1-km radius circle buffer around the center of each traffic analysis zone |
Author, (Year), Reference | Response Rate | Representativeness | Outcome Measures | Confounding Factors | Global Rating | |
---|---|---|---|---|---|---|
McCormack et al. (2012) [25] | 2 | 0 | 2 | 2 | 6 | Strong |
Knuiman et al. (2014) [26] | 2 | 0 | 2 | 2 | 6 | Strong |
Kamruzzaman et al. (2016) [27] | 2 | 2 | 2 | 2 | 8 | Strong |
Wasfi et al. (2016) [28] | 2 | 2 | 1 | 2 | 7 | Strong |
Miles et al. (2008) [29] | 0 | 2 | 2 | 1 | 5 | Moderate |
Lee and Moudon (2006) [30] | 2 | 1 | 2 | 2 | 7 | Strong |
Handy et al. (2006) [31] | 2 | 1 | 0 | 2 | 5 | Moderate |
Pikora et al. (2006) [32] | 2 | 0 | 0 | 2 | 4 | Moderate |
Forsyth et al. (2007) [33] | 0 | 1 | 2 | 1 | 4 | Moderate |
Rodríguez et al. (2009) [34] | 2 | 0 | 2 | 1 | 5 | Moderate |
Sundquist et al. (2011) [35] | 2 | 1 | 2 | 1 | 6 | Strong |
Carlson et al. (2012) [36] | 2 | 1 | 1 | 1 | 5 | Moderate |
Karusisi et al. (2014) [37] | 2 | 1 | 0 | 1 | 4 | Moderate |
Sung et al. (2014) [38] | 0 | 1 | 1 | 1 | 3 | Weak |
Jack and McCormack (2014) [39] | 2 | 0 | 2 | 2 | 6 | Strong |
Reyer et al. (2014) [40] | 0 | 1 | 1 | 1 | 3 | Weak |
Thielman et al. (2015) [41] | 2 | 2 | 1 | 1 | 6 | Strong |
Owen et al. (2007) [42] | 1 | 1 | 2 | 2 | 6 | Strong |
Tilt et al. (2007) [43] | 1 | 1 | 1 | 1 | 4 | Moderate |
Saelens et al. (2012) [44] | 2 | 0 | 2 | 2 | 6 | Strong |
Riva et al. (2009) [45] | 2 | 2 | 2 | 1 | 7 | Strong |
Turrell et al. (2013) [46] | 2 | 2 | 0 | 1 | 5 | Moderate |
Wineman et al. (2014) [47] | 2 | 1 | 2 | 1 | 6 | Strong |
Oliver et al. (2011) [48] | 2 | 0 | 0 | 1 | 3 | Weak |
Koohsari et al. (2017) [49] | 2 | 1 | 2 | 1 | 6 | Strong |
Larrañaga et al. (2016) [50] | 2 | 1 | 0 | 2 | 5 | Moderate |
Kelley et al. (2016) [51] | 2 | 2 | 0 | 1 | 5 | Moderate |
Koohsari et al. (2017) [52] | 2 | 1 | 1 | 1 | 5 | Moderate |
Dill and Voros (2007) [53] | 2 | 0 | 0 | 2 | 4 | Moderate |
Owen et al. (2010) [54] | 1 | 0 | 2 | 1 | 4 | Moderate |
Rybarczyk and Wu (2014) [55] | 0 | 1 | 1 | 1 | 3 | Weak |
Zhao (2014) [56] | 0 | 2 | 0 | 1 | 3 | Weak |
Foster et al. (2011) [57] | 0 | 2 | 1 | 1 | 4 | Moderate |
Ma and Dill (2015) [58] | 2 | 1 | 0 | 2 | 5 | Moderate |
Heesch et al. (2015) [59] | 2 | 2 | 0 | 2 | 6 | Strong |
Zahabi et al. (2016) [60] | 0 | 1 | 1 | 2 | 4 | Moderate |
Braun et al. (2016) [61] | 2 | 1 | 0 | 1 | 4 | Moderate |
Mertens et al. (2017) [62] | 1 | 0 | 2 | 1 | 4 | Moderate |
Kondo et al. (2009) [63] | 2 | 0 | 2 | 1 | 5 | Moderate |
Cervero et al. (2009) [64] | 2 | 2 | 2 | 1 | 7 | Strong |
Van Dyck et al. (2009) [65] | 2 | 1 | 2 | 2 | 7 | Strong |
Van Dyck et al. (2010) [66] | 2 | 1 | 2 | 1 | 6 | Strong |
Fan et al. (2014) [67] | 0 | 1 | 1 | 1 | 3 | Weak |
Munshi (2016) [68] | 0 | 1 | 0 | 2 | 3 | Weak |
Christiansen et al. (2016) [69] | 0 | 1 | 2 | 1 | 4 | Moderate |
Witten et al. (2012) [70] | 2 | 1 | 2 | 2 | 7 | Strong |
Frank et al. (2006) [71] | 2 | 1 | 2 | 1 | 6 | Strong |
Hoehner et al. (2005) [72] | 2 | 1 | 2 | 1 | 6 | Strong |
De Sa and Ardern (2014) [73] | 2 | 2 | 1 | 1 | 6 | Strong |
Mäki-Opas et al. (2016) [74] | 2 | 2 | 2 | 1 | 7 | Strong |
Feng (2016) [75] | 0 | 1 | 1 | 1 | 3 | Weak |
Built Environment Factors | Positive Relationship | Not Related | Negative Relationship | Overall Results | |
---|---|---|---|---|---|
A | B | ||||
Residential density | [27] [29] [30] [33] [34] [50] [67] * [68] * | [26] [30] [30] [63] [64] | [30] [47] | 8/15 | P |
Land use mix | [26] [38] * [38] * [46] [48] * [68] * [69] | [48] * [64] | 7/9 | P | |
Street connectivity | [26] [27] [27] [36] [44] [46] [49] [50] [64] [67] * | [37] [63] [64] | 10/13 | P | |
Retail land use | [34] [38] * [44] [48] * [50] | 5/5 | P | ||
Walkability | [25] [28] [32] [35] [39] [39] [40] * [40] * [41] [42] [45] [51] m [52] [65] [66] | [25] [42] [51] f | 15/18 | P | |
Street integration | [47] [52] | [49] | 2/3 | - | |
Sidewalk | [25] [25] [32] [36] | [30] [63] | 4/6 | P | |
Access to destinations | [26] [29] [30] [31] [32] [37] [38] * [38] * [43] [64] | [64] | [67] * | 10/12 | P |
Traffic volume/speed | [30] [32] | 2/2 | - | ||
Hilliness | [30] [50] [64] | 3/3 | - | ||
Neighborhood aesthetics | [48] * | [30] [32] [43] | [67] * | 3/5 | O |
Built Environment Factors | Positive Relationship | Not Related | Negative Relationship | Overall Results | |
---|---|---|---|---|---|
A | B | ||||
Residential density | [68] * | [56] * [61] [63] | 3/4 | - | |
Land use mix | [56] * [63] f [69] | [63] m | 3/4 | - | |
Street connectivity | [53] [55] * [56] * [60] [67] * [69] | [63] | 6/7 | P | |
Retail land use | [61] | 1/1 | - | ||
Walkability | [54] [66] | [65] | 2/3 | - | |
Sidewalk | [63] | 1/1 | - | ||
Bicycle lane | [56] * [58] [58] [60] [61] [62] | [53] [61] [64] | 6/9 | P | |
Access to destinations | [58] [59] | [56] * [58] [61] [67] * | 4/6 | N | |
Traffic volume/speed | [57] | [62] | 1/2 | - | |
Hilliness | [64] | 1/1 | - | ||
Neighborhood aesthetics | [62] | [69] | [55] * [62] [67] * | 3/5 | N |
Built Environment Factors | Positive Relationship | Not Related | Negative Relationship | Overall Results | |
---|---|---|---|---|---|
A | B | ||||
Residential density | [70] [73] | 2/2 | - | ||
Land use mix | [75] * | 1/1 | - | ||
Street connectivity | [70] [75] * | 2/2 | - | ||
Walkability | [71] | 1/1 | - | ||
Sidewalk | [74] [75] * | 2/2 | - | ||
Bicycle lane | [74] [75] * | 2/2 | - | ||
Access to destinations | [70] [72] | 2/2 | - | ||
Neighborhood aesthetics | [75] * | [73] | [72] [74] | 2/4 | - |
Built Environment Factors | Reference | Result |
---|---|---|
Residential density | [30] |
|
Land use mix | [48] |
|
Street connectivity | [64] |
|
Walkability | [25] |
|
[42] |
| |
Bicycle lane | [61] |
|
Access to destinations | [58] |
|
[64] |
| |
Neighborhood aesthetics | [62] |
|
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Wang, L.; Wen, C. The Relationship between the Neighborhood Built Environment and Active Transportation among Adults: A Systematic Literature Review. Urban Sci. 2017, 1, 29. https://doi.org/10.3390/urbansci1030029
Wang L, Wen C. The Relationship between the Neighborhood Built Environment and Active Transportation among Adults: A Systematic Literature Review. Urban Science. 2017; 1(3):29. https://doi.org/10.3390/urbansci1030029
Chicago/Turabian StyleWang, Luqi, and Chen Wen. 2017. "The Relationship between the Neighborhood Built Environment and Active Transportation among Adults: A Systematic Literature Review" Urban Science 1, no. 3: 29. https://doi.org/10.3390/urbansci1030029