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Zheng L, Kwan MP, Liu Y, Liu D, Huang J, Kan Z. How mobility pattern shapes the association between static green space and dynamic green space exposure. ENVIRONMENTAL RESEARCH 2024; 258:119499. [PMID: 38942258 DOI: 10.1016/j.envres.2024.119499] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/19/2024] [Revised: 06/24/2024] [Accepted: 06/25/2024] [Indexed: 06/30/2024]
Abstract
Greenspaces are crucial for enhancing mental and physical health. Recent research has shifted from static methods of assessing exposure to greenspaces, based on fixed locations, to dynamic approaches that account for individual mobility. These dynamic evaluations utilize advanced technologies like GPS tracking and remote sensing to provide more precise exposure estimates. However, little work has been conducted to compare dynamic and static exposure assessments and the effect of individual mobility on these evaluations. This study delves into how greenspaces around homes and workplaces, along with mobility patterns, affect dynamic greenspace exposure in Hong Kong. Data was collected from 787 participants in four communities in Hong Kong using GPS, portable sensors, and surveys. Using multiple statistical tests, our study revealed significant variations in participants' daily mobility patterns across socio-demographic and temporal factors. Further, using linear mixed-effects models, we identified complex and statistically significant interactions between participants' static greenspace exposure and their mobility patterns. Our findings suggest that individual mobility patterns significantly modify the relationship between static and dynamic greenspace exposure and play a critical role in explaining socio-demographic and temporal context differences in the relationship between static and dynamic greenspace exposure.
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Affiliation(s)
- Lingwei Zheng
- Department of Geography and Resource Management, Wong Foo Yuan Building, The Chinese University of Hong Kong, Hong Kong SAR, China; Institute of Space and Earth Information Science, Fok Ying Tung Remote Sensing Science Building, The Chinese University of Hong Kong, Hong Kong SAR, China.
| | - Mei-Po Kwan
- Department of Geography and Resource Management, Wong Foo Yuan Building, The Chinese University of Hong Kong, Hong Kong SAR, China; Institute of Space and Earth Information Science, Fok Ying Tung Remote Sensing Science Building, The Chinese University of Hong Kong, Hong Kong SAR, China.
| | - Yang Liu
- Department of Geography and Resource Management, Wong Foo Yuan Building, The Chinese University of Hong Kong, Hong Kong SAR, China; Institute of Space and Earth Information Science, Fok Ying Tung Remote Sensing Science Building, The Chinese University of Hong Kong, Hong Kong SAR, China.
| | - Dong Liu
- Institute of Space and Earth Information Science, Fok Ying Tung Remote Sensing Science Building, The Chinese University of Hong Kong, Hong Kong SAR, China.
| | - Jianwei Huang
- Institute of Space and Earth Information Science, Fok Ying Tung Remote Sensing Science Building, The Chinese University of Hong Kong, Hong Kong SAR, China.
| | - Zihan Kan
- Department of Geography and Resource Management, Wong Foo Yuan Building, The Chinese University of Hong Kong, Hong Kong SAR, China; Institute of Space and Earth Information Science, Fok Ying Tung Remote Sensing Science Building, The Chinese University of Hong Kong, Hong Kong SAR, China.
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Zhong S, Ma F, Gao J, Bian L. Who Gets the Flu? Individualized Validation of Influenza-like Illness in Urban Spaces. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2023; 20:ijerph20105865. [PMID: 37239591 DOI: 10.3390/ijerph20105865] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/31/2023] [Revised: 04/27/2023] [Accepted: 05/15/2023] [Indexed: 05/28/2023]
Abstract
Urban dwellers are exposed to communicable diseases, such as influenza, in various urban spaces. Current disease models are able to predict health outcomes at the individual scale but are mostly validated at coarse scales due to the lack of fine-scaled ground truth data. Further, a large number of transmission-driving factors have been considered in these models. Because of the lack of individual-scaled validations, the effectiveness of factors at their intended scale is not substantiated. These gaps significantly undermine the efficacy of the models in assessing the vulnerability of individuals, communities, and urban society. The objectives of this study are twofold. First, we aim to model and, most importantly, validate influenza-like illness (ILI) symptoms at the individual scale based on four sets of transmission-driving factors pertinent to home-work space, service space, ambient environment, and demographics. The effort is supported by an ensemble approach. For the second objective, we investigate the effectiveness of the factor sets through an impact analysis. The validation accuracy reaches 73.2-95.1%. The validation substantiates the effectiveness of factors pertinent to urban spaces and unveils the underlying mechanism that connects urban spaces and population health. With more fine-scaled health data becoming available, the findings of this study may see increasing value in informing policies that improve population health and urban livability.
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Affiliation(s)
- Shiran Zhong
- Department of Geography, University of Western Ontario, London, ON N6A 3K7, Canada
| | - Fenglong Ma
- College of Information Sciences and Technology, Pennsylvania State University, University Park, State College, PA 16802, USA
| | - Jing Gao
- School of Electrical and Computer Engineering, Purdue University, West Lafayette, IN 47907, USA
| | - Ling Bian
- Department of Geography, University at Buffalo, The State University of New York, Buffalo, NY 14261, USA
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