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Published on: January 20, 2023
Street-level neighborhood greenery linked to active transportation: A case study in Milwaukee and Green Bay, WI, USA
Wei-Lun Tsai1, Leah Yngve2, Yuhong Zhou3
1Oak Ridge Institute for Science and Education Research Fellow, U.S. Environmental Protection Agency, Research Triangle Park, NC, USA.
Abstract:
Sedentary lifestyles contribute to many adverse health outcomes and pose concerns for public health worldwide. Studies show that road network design and greenery are critical, independent factors in supporting active lifestyles. Yet greenery along the road network has been insufficiently assessed. This study modelled individual weekly participation in active transportation (AT) using spatially refined measures of street versus overall neighborhood greenery in greater Milwaukee and Green Bay, Wisconsin, USA. Measures of AT (walking or biking for commutes or errands) were collected by the Survey of the Health of Wisconsin. Meter-scale landcover was used to estimate percent tree cover and aggregate greenery (tree and herbaceus cover combined) at increasing distances from each residence (n = 423) along neighborhood streets and in circular buffers. Street greenery metrics were designed to indicate the provision of ecosystem services, including shade and aesthetics, which promote physical activity by enhancing the safety and beauty of the publicly-accessible outdoor environment. Positive associations were consistently observed for street tree cover (e.g., adjusted odds ratio for a 10% increase in sidewalk tree cover within 500 m = 1.19; 95% CI: 1.02-1.40; and in street tree cover within 1250 m = 1.39; 95% CI: 1.09-1.79). Aggregate greenery was significant only in circular buffers, where it was negatively associated with AT. Sensitivity analysis revealed that herbaceous cover alone was consistently negatively associated with AT. Findings inform urban design to promote healthy lifestyles by distinguishing street tree cover as a positive factor in AT. Studies in additional geographic areas and causal designs are recommended.
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