Green space exposure and active transportation during the COVID-19 pandemic: a global analysis using Apple mobility data.

IF 7.1 2区 医学 Q1 PUBLIC, ENVIRONMENTAL & OCCUPATIONAL HEALTH
Ruoyu Wang, Selin Akaraci, Esteban Moro, Pedro C Hallal, Rodrigo Reis, Ruth Hunter
{"title":"Green space exposure and active transportation during the COVID-19 pandemic: a global analysis using Apple mobility data.","authors":"Ruoyu Wang, Selin Akaraci, Esteban Moro, Pedro C Hallal, Rodrigo Reis, Ruth Hunter","doi":"10.1136/bmjgh-2024-017108","DOIUrl":null,"url":null,"abstract":"<p><strong>Introduction: </strong>There is little evidence investigating the association between green space (exposure and inequality) and active transportation during the COVID-19 pandemic. This study focused on the spatial heterogeneity in trajectories of different transportation modes during the COVID-19 pandemic worldwide, as well as the association between green space exposure and inequality and active transportation during the COVID-19 pandemic from a global perspective.</p><p><strong>Methods: </strong>This study was based on an ecological study design and used three different Apple Mobility indices (driving, walking and public transit) to evaluate the trajectories of different transportation modes during the COVID-19 pandemic in 299 cities across 46 countries. Green space exposure was calculated based on fine-resolution population and green space mappings. Green space inequality was calculated by incorporating the Gini index into the green space exposure (green space Gini index). The hot/cold spot analysis was used to explore spatial heterogeneity in trajectories of different transportation modes during the COVID-19 pandemic worldwide, while Gaussian spatial mixed models were used to model the association between green space exposure and inequality and active transportation.</p><p><strong>Results: </strong>The hot/cold spot analysis shows that there were spatial inequalities in the trajectories of different transportation modes worldwide during the COVID-19 pandemic. Results from Gaussian spatial mixed models showed that green space exposure was positively associated with the walking index (Coef.=46.82; SE=18.20), while green space inequality was positively associated with the walking index (Coef.=58.88; SE=26.87) and public transit index (Coef.=162.07; SE=80.16). Also, the effect of green space varied across city development levels, the stringency of policy and COVID-19 severity.</p><p><strong>Conclusions: </strong>Our findings demonstrate the importance of sufficient city-scale green spaces to support active transportation, with important implications to help cities better prepare for future pandemics and support active transportation during non-pandemic times.</p>","PeriodicalId":9137,"journal":{"name":"BMJ Global Health","volume":"10 5","pages":""},"PeriodicalIF":7.1000,"publicationDate":"2025-05-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12083287/pdf/","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"BMJ Global Health","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1136/bmjgh-2024-017108","RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"PUBLIC, ENVIRONMENTAL & OCCUPATIONAL HEALTH","Score":null,"Total":0}
引用次数: 0

Abstract

Introduction: There is little evidence investigating the association between green space (exposure and inequality) and active transportation during the COVID-19 pandemic. This study focused on the spatial heterogeneity in trajectories of different transportation modes during the COVID-19 pandemic worldwide, as well as the association between green space exposure and inequality and active transportation during the COVID-19 pandemic from a global perspective.

Methods: This study was based on an ecological study design and used three different Apple Mobility indices (driving, walking and public transit) to evaluate the trajectories of different transportation modes during the COVID-19 pandemic in 299 cities across 46 countries. Green space exposure was calculated based on fine-resolution population and green space mappings. Green space inequality was calculated by incorporating the Gini index into the green space exposure (green space Gini index). The hot/cold spot analysis was used to explore spatial heterogeneity in trajectories of different transportation modes during the COVID-19 pandemic worldwide, while Gaussian spatial mixed models were used to model the association between green space exposure and inequality and active transportation.

Results: The hot/cold spot analysis shows that there were spatial inequalities in the trajectories of different transportation modes worldwide during the COVID-19 pandemic. Results from Gaussian spatial mixed models showed that green space exposure was positively associated with the walking index (Coef.=46.82; SE=18.20), while green space inequality was positively associated with the walking index (Coef.=58.88; SE=26.87) and public transit index (Coef.=162.07; SE=80.16). Also, the effect of green space varied across city development levels, the stringency of policy and COVID-19 severity.

Conclusions: Our findings demonstrate the importance of sufficient city-scale green spaces to support active transportation, with important implications to help cities better prepare for future pandemics and support active transportation during non-pandemic times.

2019冠状病毒病大流行期间的绿地暴露和主动交通:使用苹果移动数据的全球分析。
导言:在COVID-19大流行期间,几乎没有证据调查绿色空间(暴露和不平等)与主动交通之间的关系。本研究从全球视角研究新冠肺炎大流行期间全球不同交通方式轨迹的空间异质性,以及新冠肺炎大流行期间绿色空间暴露与不平等和主动交通之间的关系。方法:本研究基于生态学研究设计,采用3种不同的Apple Mobility指数(驾车、步行和公共交通)评估46个国家299个城市在2019冠状病毒病疫情期间不同交通方式的发展轨迹。基于精细分辨率的人口和绿地映射计算绿地暴露度。通过将基尼指数纳入绿地暴露(绿地基尼指数)来计算绿地不平等。采用冷热点分析方法探讨新冠肺炎大流行期间全球不同交通方式轨迹的空间异质性,采用高斯空间混合模型模拟绿地暴露、不平等与主动交通之间的关系。结果:冷热点分析显示,新冠肺炎大流行期间,全球不同交通方式的出行轨迹存在空间不平等。高斯空间混合模型结果表明,绿地暴露与步行指数呈正相关(Coef =46.82;SE=18.20),而绿地不平等与步行指数呈正相关(Coef =58.88;SE=26.87)和公共交通指数(Coef =162.07;SE = 80.16)。此外,绿地的效果因城市发展水平、政策的严格程度和疫情的严重程度而异。结论:我们的研究结果证明了充足的城市规模绿地对支持主动交通的重要性,这对帮助城市更好地为未来的大流行做好准备,并在非大流行时期支持主动交通具有重要意义。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
BMJ Global Health
BMJ Global Health Medicine-Health Policy
CiteScore
11.40
自引率
4.90%
发文量
429
审稿时长
18 weeks
期刊介绍: BMJ Global Health is an online Open Access journal from BMJ that focuses on publishing high-quality peer-reviewed content pertinent to individuals engaged in global health, including policy makers, funders, researchers, clinicians, and frontline healthcare workers. The journal encompasses all facets of global health, with a special emphasis on submissions addressing underfunded areas such as non-communicable diseases (NCDs). It welcomes research across all study phases and designs, from study protocols to phase I trials to meta-analyses, including small or specialized studies. The journal also encourages opinionated discussions on controversial topics.
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:604180095
Book学术官方微信