Background: To improve physical activity in Latin American cities, several interventions have been promoted, such as Open Streets programmes. Our study aims to quantify the health and economic effects of Open Streets-related physical activity in 15 Latin American cities.
Methods: We used a quantitative health impact assessment approach to estimate annual premature deaths and disease incidence (ischaemic heart disease, ischaemic stroke, type 2 diabetes, colon cancer, breast cancer, and dementia) avoided, the disability-adjusted life-years (DALYs) gained, and the cost saving (from reduced premature mortality) related to increased physical activity from Open Streets programmes in 15 Latin American cities. Input data were obtained from scientific publications, reports, and open street city surveys spanning 2017 to 2019. Physical activity data were converted to metabolic equivalent of the task. Exposure-response relationship functions were applied to estimate relative risk and population-attributable fraction, enabling the assessment of premature deaths and disease incidence.
Findings: The percentage of male users of the Open Streets programmes ranged from 55% (27 500 of 50 000 in Guatemala) to 75% (2250 of 3000 in El Alto, Bolivia), and female users ranged from 25% (750; El Alto) to 45% (22 500; Guatemala). We estimated that the current Open Streets programmes in the 15 Latin American cities studied could prevent 363 (95% CI 271-494) annual premature deaths due to increased physical activity, with an annual economic impact of US$194·1 million (144·9 million-263·9 million) saved and an annual reduction of 1036·7 DALYs (346·7-1778·3). If one Open Streets event is added per week in each of those cities, the potential benefit could increase to 496 (370 to 677) premature deaths prevented each year.
Interpretation: Open Streets programmes in Latin America can provide health and economic benefits related to increased physical activity and can be used as a health promotion and disease prevention tool.
Funding: EU's Horizon 2020 research and innovation programme.
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http://dx.doi.org/10.1016/S2542-5196(23)00109-2 | DOI Listing |
Arch Orthop Trauma Surg
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Roadside tree segmentation and parameter extraction play an essential role in completing the virtual simulation of road scenes. Point cloud data of roadside trees collected by LiDAR provide important data support for achieving assisted autonomous driving. Due to the interference from trees and other ground objects in street scenes caused by mobile laser scanning, there may be a small number of missing points in the roadside tree point cloud, which makes it familiar for under-segmentation and over-segmentation phenomena to occur in the roadside tree segmentation process.
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Institute of Chemical Technology - Vietnam Academy of Science and Technology, 1A TL29 Street, Thanh Loc Ward, District 12, Ho Chi Minh City, Vietnam.
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