Built environmental correlates of cycling for transport across Europe

Mertens, Lieze; Compernolle, Sofie; Deforche, Benedicte; Mackenbach, Joreintje D.; Lakerveld, Jeroen; Brug, Johannes; Roda, Célina; Feuillet, Thierry; Oppert, Jean Michel; Glonti, Ketevan; Rutter, Harry; Bárdos, Helga; Bourdeaudhuij, Ilse De; Dyck, Delfien Van

doi:10.1016/j.healthplace.2017.01.007

Cited by 101 publications

(57 citation statements)

References 60 publications

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“…The Variance Inflation Factors (VIFs) were checked in R with the ‘usdm’ package. All VIFs were low (<2), indicating that multicollinearity was not present [67,68]. …”

Section: Discussionmentioning

confidence: 99%

The Association of Urban Greenness and Walking Behavior: Using Google Street View and Deep Learning Techniques to Estimate Residents’ Exposure to Urban Greenness

Lü

2018

IJERPH

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Many studies have established that urban greenness is associated with better health outcomes. Yet most studies assess urban greenness with overhead-view measures, such as park area or tree count, which often differs from the amount of greenness perceived by a person at eye-level on the ground. Furthermore, those studies are often criticized for the limitation of residential self-selection bias. In this study, urban greenness was extracted and assessed from profile view of streetscape images by Google Street View (GSV), in conjunction with deep learning techniques. We also explored a unique research opportunity arising in a citywide residential reallocation scheme of Hong Kong to reduce residential self-selection bias. Two multilevel regression analyses were conducted to examine the relationships between urban greenness and (1) the odds of walking for 24,773 public housing residents in Hong Kong, (2) total walking time of 1994 residents, while controlling for potential confounders. The results suggested that eye-level greenness was significantly related to higher odds of walking and longer walking time in both 400 m and 800 m buffers. Distance to the closest Mass Transit Rail (MTR) station was also associated with higher odds of walking. Number of shops was related to higher odds of walking in the 800 m buffer, but not in 400 m. Eye-level greenness, assessed by GSV images and deep learning techniques, can effectively estimate residents’ daily exposure to urban greenness, which is in turn associated with their walking behavior. Our findings apply to the entire public housing residents in Hong Kong, because of the large sample size.

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“…The Variance Inflation Factors (VIFs) were checked in R with the ‘usdm’ package. All VIFs were low (<2), indicating that multicollinearity was not present [67,68]. …”

Section: Discussionmentioning

confidence: 99%

The Association of Urban Greenness and Walking Behavior: Using Google Street View and Deep Learning Techniques to Estimate Residents’ Exposure to Urban Greenness

Lü

2018

IJERPH

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“…Even though length and time taken are important factors for route choice, the data show that greenspace also plays an equally important role, while providing healthier environmental conditions [40,41]. In addition, as roads with little traffic and existing cycle paths are of great importance to the majority, urban transport planning should prioritize cycle route planning along roads and paths other than main roads, through green areas with separate cycle (high)ways where necessary [42]. Some studies have evaluated the positive effects of alternative route choices on lower air pollution exposure [43,44].…”

Section: Tackling the Exposure Awareness Gapmentioning

confidence: 99%

Cyclists’ Multiple Environmental Urban Exposures—Comparing Subjective and Objective Measurements

et al. 2019

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Citizens in urban areas are exposed to multiple environmental stressors like noise, heat, and air pollution, with impact on human health. There is a great deal of evidence that connects human health, objective environmental exposure, and place of residence. However, little is known about subjective and objective multiple personal exposures while being mobile. To address this research gap, this paper presents results from a mixed-methods exploratory study with cyclists in the City of Leipzig, Germany. In the summer of 2017, cyclists (n = 66) wore a unique combination of sensors that measured particle number counts (PNC), noise, humidity, temperature, geolocation, and the subjective perception of each exposure on everyday routes for one week (n = 730). A smartphone application was developed to question participants about their perception of subjective exposure. The data were analyzed with three aims: (i) to compare the multiple exposure profiles of the cyclists, (ii) to contrast the objective data and subjective individual perception, and (iii) to examine the role of route decision-making and awareness of health impacts for healthier route choices. The results indicate distinct differences between the exposure profiles of cyclists. Over 80% of the cyclists underestimated their exposure to noise and air pollution. Except for heat, no significant associations between the objective and subjective data were found. This reveals an exposure awareness gap that needs to be considered in urban health planning and risk communication. It is argued that knowledge about health impacts and route characteristics plays a crucial role in decision-making about route choices. The paper concludes with suggestions to harness smart sensing for exposure mitigation and research in health geography.

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“…Two studies [30,64] found inconsistent results when using different analyzed geographic units. Five studies [25,30,42,58,62] found inconsistent results when using different measurements of AT. One study [48] found inconsistent relationships between land use mix and walking to different destinations.…”

Section: Inconsistent Results From Studies With Different Designsmentioning

confidence: 99%

“…Access to destinations [58] • Access to retail jobs was positively related to the frequency of cycling for transport • Access to retail jobs was negatively related to the participation in cycling for transport [64] • 500-m buffer: access to destination was not related to walking for transport • 1000-m buffer: access to destination was positively related to walking for transport Neighborhood aesthetics [62] • Presence of trees was positively related to the participation in cycling for transport • Presence of trees was negatively related to the duration of cycling for transport…”

Section: Built Environment Factors Reference Resultsmentioning

confidence: 99%

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The Relationship between the Neighborhood Built Environment and Active Transportation among Adults: A Systematic Literature Review

Wang

Chen

2017

Urban Science

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Active transportation (AT) has aroused great interest in recent years as it may benefit public health and reduce the dependency on cars. This article aims to summarize recent findings on the relationship between the objectively measured built environment and AT among adults, to examine if different study designs may generate different results, and to provide directions for future research. A systematic literature review of journal articles from different databases was conducted. Fifty-one articles published between 2005 and 2017 were identified, and twelve built environment factors were extracted. The results showed that residential density, land use mix, street connectivity, retail land use, walkability, sidewalk, and access to destinations had a convincing positive relationship with walking for transport. Regarding cycling for transport, while street connectivity and bike lane showed a convincing positive relationship, neighborhood aesthetics and access to destinations showed a convincing negative relationship. Studies that use different analyzed geographic units and different measurements of AT may generate different results, so choosing suitable geographic units and measurement of AT is necessary to reduce the mismatch in the relationships. In addition, we need more longitudinal studies, more studies on cycling for transport, and more studies in countries outside North America and Australasia.

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Built environmental correlates of cycling for transport across Europe

Cited by 101 publications

References 60 publications

The Association of Urban Greenness and Walking Behavior: Using Google Street View and Deep Learning Techniques to Estimate Residents’ Exposure to Urban Greenness

The Association of Urban Greenness and Walking Behavior: Using Google Street View and Deep Learning Techniques to Estimate Residents’ Exposure to Urban Greenness

Cyclists’ Multiple Environmental Urban Exposures—Comparing Subjective and Objective Measurements

The Relationship between the Neighborhood Built Environment and Active Transportation among Adults: A Systematic Literature Review

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