1
|
van Beek JFE, Malisoux L, Klein O, Bohn T, Tharrey M, Van Lenthe FJ, Beenackers MA, Dijst M, Perchoux C. Longitudinal study of changes in greenness exposure, physical activity and sedentary behavior in the ORISCAV-LUX cohort study. Int J Health Geogr 2024; 23:14. [PMID: 38773577 PMCID: PMC11110334 DOI: 10.1186/s12942-024-00374-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/15/2024] [Accepted: 05/10/2024] [Indexed: 05/24/2024] Open
Abstract
BACKGROUND Greenness exposure has been associated with many health benefits, for example through the pathway of providing opportunities for physical activity (PA). Beside the limited body of longitudinal research, most studies overlook to what extent different types of greenness exposures may be associated with varying levels of PA and sedentary behavior (SB). In this study, we investigated associations of greenness characterized by density, diversity and vegetation type with self-reported PA and SB over a 9-year period, using data from the ORISCAV-LUX study (2007-2017, n = 628). METHODS The International Physical Activity Questionnaire (IPAQ) short form was used to collect PA and SB outcomes. PA was expressed as MET-minutes/week and log-transformed, and SB was expressed as sitting time in minutes/day. Geographic Information Systems (ArcGIS Pro, ArcMap) were used to collect the following exposure variables: Tree Cover Density (TCD), Soil-adjusted Vegetation Index (SAVI), and Green Land Use Mix (GLUM). The exposure variables were derived from publicly available sources using remote sensing and cartographic resources. Greenness exposure was calculated within 1000m street network buffers around participants' exact residential address. RESULTS Using Random Effects Within-Between (REWB) models, we found evidence of negative within-individual associations of TCD with PA (β = - 2.60, 95% CI - 4.75; - 0.44), and negative between-individual associations of GLUM and PA (β = - 2.02, 95% CI - 3.73; - 0.32). There was no evidence for significant associations between greenness exposure and SB. Significant interaction effects by sex were present for the associations between TCD and both PA and SB. Neighborhood socioeconomic status (NSES) did not modify the effect of greenness exposure on PA and SB in the 1000 m buffer. DISCUSSION Our results showed that the relationship between greenness exposure and PA depended on the type of greenness measure used, which stresses the need for the use of more diverse and complementary greenness measures in future research. Tree vegetation and greenness diversity, and changes therein, appeared to relate to PA, with distinct effects among men and women. Replication studies are needed to confirm the relevance of using different greenness measures to understand its' different associations with PA and SB.
Collapse
Affiliation(s)
- Juliette F E van Beek
- Department of Urban Development and Mobility, Luxembourg Institute of Socio-Economic Research, 11 Porte Des Sciences, 4366, Esch-Sur-Alzette, Luxembourg.
- Faculty of Humanities, Education and Social Sciences, Department of Geography and Spatial Planning, University of Luxembourg, 11 Porte Des Sciences, 4366, Esch-Sur-Alzette, Luxembourg.
| | - Laurent Malisoux
- Department of Precision Health, Luxembourg Institute of Health, 1A-B Rue Thomas Edison, 1445, Strassen, Luxembourg
| | - Olivier Klein
- Department of Urban Development and Mobility, Luxembourg Institute of Socio-Economic Research, 11 Porte Des Sciences, 4366, Esch-Sur-Alzette, Luxembourg
| | - Torsten Bohn
- Department of Precision Health, Luxembourg Institute of Health, 1A-B Rue Thomas Edison, 1445, Strassen, Luxembourg
| | - Marion Tharrey
- Department of Urban Development and Mobility, Luxembourg Institute of Socio-Economic Research, 11 Porte Des Sciences, 4366, Esch-Sur-Alzette, Luxembourg
- Department of Precision Health, Luxembourg Institute of Health, 1A-B Rue Thomas Edison, 1445, Strassen, Luxembourg
| | - Frank J Van Lenthe
- Department of Public Health, Erasmus MC, University Medical Center, Dr. Molewaterplein 40, 3015 GD, Rotterdam, The Netherlands
| | - Mariëlle A Beenackers
- Department of Public Health, Erasmus MC, University Medical Center, Dr. Molewaterplein 40, 3015 GD, Rotterdam, The Netherlands
| | - Martin Dijst
- Department of Urban Development and Mobility, Luxembourg Institute of Socio-Economic Research, 11 Porte Des Sciences, 4366, Esch-Sur-Alzette, Luxembourg
- University of Luxembourg, 2 Avenue de L'Universite, 4365, Esch-Sur-Alzette, Luxembourg
| | - Camille Perchoux
- Department of Urban Development and Mobility, Luxembourg Institute of Socio-Economic Research, 11 Porte Des Sciences, 4366, Esch-Sur-Alzette, Luxembourg
| |
Collapse
|
2
|
Patwary MM, Sakhvidi MJZ, Ashraf S, Dadvand P, Browning MHEM, Alam MA, Bell ML, James P, Astell-Burt T. Impact of green space and built environment on metabolic syndrome: A systematic review with meta-analysis. THE SCIENCE OF THE TOTAL ENVIRONMENT 2024; 923:170977. [PMID: 38360326 DOI: 10.1016/j.scitotenv.2024.170977] [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: 12/07/2023] [Revised: 02/03/2024] [Accepted: 02/12/2024] [Indexed: 02/17/2024]
Abstract
Metabolic Syndrome presents a significant public health challenge associated with an increased risk of noncommunicable diseases such as cardiovascular conditions. Evidence shows that green spaces and the built environment may influence metabolic syndrome. We conducted a systematic review and meta-analysis of observational studies published through August 30, 2023, examining the association of green space and built environment with metabolic syndrome. A quality assessment of the included studies was conducted using the Office of Health Assessment and Translation (OHAT) tool. The Grading of Recommendations, Assessment, Development, and Evaluations (GRADE) assessment was used to evaluate the overall quality of evidence. Our search retrieved 18 studies that met the inclusion criteria and were included in our review. Most were from China (n = 5) and the USA (n = 5), and most used a cross-sectional study design (n = 8). Nine studies (50 %) reported only green space exposures, seven (39 %) reported only built environment exposures, and two (11 %) reported both built environment and green space exposures. Studies reported diverse definitions of green space and the built environment, such as availability, accessibility, and quality, particularly around participants' homes. The outcomes focused on metabolic syndrome; however, studies applied different definitions of metabolic syndrome. Meta-analysis results showed that an increase in normalized difference vegetation index (NDVI) within a 500-m buffer was associated with a lower risk of metabolic syndrome (odds ratio [OR] = 0.90, 95%CI = 0.87-0.93, I2 = 22.3 %, n = 4). A substantial number of studies detected bias for exposure classification and residual confounding. Overall, the extant literature shows a 'limited' strength of evidence for green space protecting against metabolic syndrome and an 'inadequate' strength of evidence for the built environment associated with metabolic syndrome. Studies with more robust study designs, better controlled confounding factors, and stronger exposure measures are needed to understand better what types of green spaces and built environment features influence metabolic syndrome.
Collapse
Affiliation(s)
- Muhammad Mainuddin Patwary
- Environment and Sustainability Research Initiative, Khulna, Bangladesh; Environmental Science Discipline, Life Science School, Khulna University, Khulna, Bangladesh.
| | - Mohammad Javad Zare Sakhvidi
- Department of Occupational Health, School of Public Health, Yazd Shahid Sadoughi University of Medical Sciences, Yazd, Iran
| | - Sadia Ashraf
- Environmental Science Discipline, Life Science School, Khulna University, Khulna, Bangladesh
| | - Payam Dadvand
- ISGlobal, Barcelona, Spain; Universitat Pompeu Fabra (UPF), Barcelona, Spain; CIBER Epidemiología y Salud Pública (CIBERESP), Madrid, Spain
| | - Matthew H E M Browning
- Department of Parks, Recreation and Tourism Management, Clemson University, Clemson, SC, USA
| | - Md Ashraful Alam
- Department of Computational Diagnostic Radiology and Preventive Medicine, The University of Tokyo Hospital, Bunkyo-ku, Tokyo, Japan
| | - Michelle L Bell
- Yale School of the Environment, Yale University, New Haven, CT, United States
| | - Peter James
- Department of Environmental Health, Harvard T.H. Chan School of Public Health, Harvard University, Boston, MA, USA; Department of Population Medicine, Harvard Medical School, Harvard Pilgrim Health Care Institute, Harvard University, Boston, MA, USA
| | - Thomas Astell-Burt
- School of Architecture, Design, and Planning, University of Sydney, Australia
| |
Collapse
|
3
|
Yu B, Tang W, Fan Y, Ma C, Ye T, Cai C, Xie Y, Shi Y, Baima K, Yang T, Wang Y, Jia P, Yang S. Associations between residential greenness and obesity phenotypes among adults in Southwest China. Health Place 2024; 87:103236. [PMID: 38593578 DOI: 10.1016/j.healthplace.2024.103236] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/01/2023] [Revised: 02/27/2024] [Accepted: 03/21/2024] [Indexed: 04/11/2024]
Abstract
BACKGROUND Although exposure to greenness has generally benefited human metabolic health, the association between greenness exposure and metabolic obesity remains poorly studied. We aimed to investigate the associations between residential greenness and obesity phenotypes and the mediation effects of air pollutants and physical activity (PA) level on the associations. METHODS We used the baseline of the China Multi-Ethnic Cohort (CMEC) study, which enrolled 87,613 adults. Obesity phenotypes were defined based on obesity and metabolic status, including metabolically unhealthy obesity (MUO), non-obesity (MUNO), metabolically healthy obesity (MHO), and non-obesity (MHNO). Greenness exposure was measured as the 3-year mean values of the normalized difference vegetation index (NDVI) and enhanced vegetation index (EVI) within the 500-m buffer zones around the participants' residence. Multivariable logistic regression was used to estimate the associations between greenness and obesity phenotypes. Stratified analyses by age, sex, educational level, and urbanicity were performed to identify how the effect varies across different subgroups. Causal mediation analysis was used to examine the mediation effects of air pollutants and PA level. RESULTS Compared with MHNO, each interquartile range (IQR) increase in greenness exposure was associated with reduced risks of MHO (ORNDVI [95% CI] = 0.87 [0.81, 0.93]; OREVI = 0.91 [0.86, 0.97]), MUO (ORNDVI = 0.83 [0.78, 0.88]; OREVI = 0.86 [0.81, 0.91]), and MUNO (ORNDVI = 0.88 [0.84, 0.91]; OREVI = 0.89 [0.86, 0.92]). For each IQR increase in both NDVI and EVI, the risks of MHO, MUO, and MUNO were reduced more in men, participants over 60 years, those with a higher level of education, and those living in urban areas, compared to their counterparts. Concentrations of particulate matter (PM) and PA level partially mediated the associations between greenness exposure and obesity phenotypes. CONCLUSIONS Exposure to residential greenness was associated with decreased risks of MHO, MUO, and MUNO, which was mediated by concentrations of PM and PA level, and modified by sex, age, educational level, and urbanicity.
Collapse
Affiliation(s)
- Bin Yu
- Institute for Disaster Management and Reconstruction, Sichuan University-The Hong Kong Polytechnic University, Chengdu, China; West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China
| | - Wenge Tang
- Chongqing Municipal Center for Disease Control and Prevention, Chongqing, China
| | - Yunzhe Fan
- West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China
| | - Chunlan Ma
- West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China
| | - Tingting Ye
- West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China
| | - Changwei Cai
- West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China
| | - Yiming Xie
- Jianyang Center for Disease Control and Prevention, Jianyang, China
| | - Yuanyuan Shi
- School of Resource and Environmental Sciences, Wuhan University, Wuhan, China; International Institute of Spatial Lifecourse Health (ISLE), Wuhan University, Wuhan, China
| | - Kangzhuo Baima
- High Altitude Health Science Research Center of Tibet University, Lhasa, Tibet, China
| | - Tingting Yang
- School of Public Health, The Key Laboratory of Environmental Pollution Monitoring and Disease Control, Ministry of Education, Guizhou Medical University, Guiyang, China
| | - Yanjiao Wang
- School of Public Health, Kunming Medical University, Kunming, China
| | - Peng Jia
- School of Resource and Environmental Sciences, Wuhan University, Wuhan, China; International Institute of Spatial Lifecourse Health (ISLE), Wuhan University, Wuhan, China; Hubei Luojia Laboratory, Wuhan, China; School of Public Health, Wuhan University, Wuhan, China.
| | - Shujuan Yang
- West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China; International Institute of Spatial Lifecourse Health (ISLE), Wuhan University, Wuhan, China.
| |
Collapse
|
4
|
Lei R, Zhang L, Liu X, Liu C, Xiao Y, Xue B, Wang Z, Hu J, Ren Z, Luo B. Residential greenspace and blood lipids in an essential hypertension population: Mediation through PM 2.5 and chemical constituents. ENVIRONMENTAL RESEARCH 2024; 240:117418. [PMID: 37852460 DOI: 10.1016/j.envres.2023.117418] [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: 07/14/2023] [Revised: 10/12/2023] [Accepted: 10/14/2023] [Indexed: 10/20/2023]
Abstract
Fine particulate matter (PM2.5) adversely affects blood lipids, while residential greenspace exposure may improve blood lipids levels. However, the association between exposure to residential greenspace and blood lipids has not been adequately studied, especially in vulnerable populations (e.g. people with essential hypertension). This study aimed to assess the association between residential greenspace exposure and blood lipids, and to clarify whether PM2.5 and chemical constituents was mediator of it. We used a period (May 2010 to December 2011) from the Chinese national hypertension project. The residential greenspace was estimated using satellite-derived normalized difference vegetation index (NDVI). The generalized additive mixed model (GAMM) was used to assess the association between exposure to residential greenspace and blood lipids, and the mediation model was used to examine whether there was a mediating effect of PM2.5 and chemical constituents on that association. The exposure to residential greenspace was negatively associated with the decreased risk of dyslipidemia, especially short-term exposure. For example, the odd ratioshort-term for dyslipidemia was 0.915 (95% CI:0.880 to 0.950). This association was strengthened by physical activity and participants living in the North. PM2.5 and chemical constituents were important mediators in this association, with the proportion of mediators ranging from -5.02% to 26.33%. The association between exposure to residential greenspace and dyslipidemia in this essential hypertensive population, especially participants living in the North and doing daily physical activity, was mediated by PM2.5 and chemical constituents.
Collapse
Affiliation(s)
- Ruoyi Lei
- Institute of Occupational Health and Environmental Health, School of Public Health, Lanzhou University, Lanzhou, Gansu, 730000, China
| | - Ling Zhang
- Institute of Occupational Health and Environmental Health, School of Public Health, Lanzhou University, Lanzhou, Gansu, 730000, China
| | - Xin Liu
- School of Spatial Planning and Design, Hangzhou City University, Hangzhou, Zhejiang, 310015, China
| | - Ce Liu
- Institute of Occupational Health and Environmental Health, School of Public Health, Lanzhou University, Lanzhou, Gansu, 730000, China
| | - Ya Xiao
- Institute of Occupational Health and Environmental Health, School of Public Health, Lanzhou University, Lanzhou, Gansu, 730000, China
| | - Baode Xue
- Institute of Occupational Health and Environmental Health, School of Public Health, Lanzhou University, Lanzhou, Gansu, 730000, China
| | - Zengwu Wang
- Division of Prevention and Community Health, National Center for Cardiovascular Disease, Fuwai Hospital, Peking Union Medical College & Chinese Academy of Medical Sciences, Beijing, 100037, China
| | - Jihong Hu
- School of Public Health, Gansu University of Chinese Medicine, Lanzhou, Gansu, 730000, China.
| | - Zhoupeng Ren
- State Key Laboratory of Resources and Environmental Information System (LREIS), Institute of Geographic Science and Natural Resource Research, Chinese Academy of Sciences, Beijing, 100101, China.
| | - Bin Luo
- Institute of Occupational Health and Environmental Health, School of Public Health, Lanzhou University, Lanzhou, Gansu, 730000, China; Shanghai Key Laboratory of Meteorology and Health, Shanghai Meteorological Bureau, Shanghai, 200030, China; Shanghai Typhoon Institute, China Meteorological Administration, Shanghai, 200030, China.
| |
Collapse
|
5
|
Pan J, Hu K, Yu X, Li W, Shen Y, Song Z, Guo Y, Yang M, Hu F, Xia Q, Du Z, Wu X. Beneficial associations between outdoor visible greenness at the workplace and metabolic syndrome in Chinese adults. ENVIRONMENT INTERNATIONAL 2024; 183:108327. [PMID: 38157607 DOI: 10.1016/j.envint.2023.108327] [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: 08/13/2023] [Revised: 10/13/2023] [Accepted: 11/12/2023] [Indexed: 01/03/2024]
Abstract
BACKGROUND Greenness surrounding residential places has been found to significantly reduce the risk of diseases such as hypertension, obesity, and metabolic syndrome (MetS). However, it is unclear whether visible greenness exposure at the workplace has any impact on the risk of MetS. METHODS Visible greenness exposure was assessed using a Green View Index (GVI) based on street view images through a convolutional neural network model. We utilized logistic regression to examine the cross-sectional association between GVI and MetS as well as its components among 51,552 adults aged 18-60 in the city of Hangzhou, China, from January 2018 to December 2021. Stratified analyses were conducted by age and sex groups. Furthermore, a scenario analysis was conducted to investigate the risks of having MetS among adults in different GVI scenarios. RESULTS The mean age of the participants was 40.1, and 38.5% were women. We found a statistically significant association between GVI and having MetS. Compared to the lowest quartile of GVI, participants in the highest quartile of GVI had a 17% (95% CI: 11-23%) lower odds of having MetS. The protective association was stronger in the males, but we did not observe such differences in different age groups. Furthermore, we found inverse associations between GVI and the odds of hypertension, low high-density lipoprotein cholesterol, obesity, and high levels of FPG. CONCLUSIONS Higher exposure to outdoor visible greenness in the workplace environment might have a protective effect against MetS.
Collapse
Affiliation(s)
- Jiahao Pan
- Center for Clinical Big Data and Analytics School of Public Health and The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou 310000, Zhejiang, China
| | - Kejia Hu
- Center for Clinical Big Data and Analytics School of Public Health and The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou 310000, Zhejiang, China
| | - Xinyan Yu
- Department of Health Management Center and Department of General Medicine, The Second Affiliated Hospital Zhejiang University School of Medicine, Hangzhou, 310009 Zhejiang, China
| | - Wenyuan Li
- Center for Clinical Big Data and Analytics School of Public Health and The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou 310000, Zhejiang, China
| | - Yujie Shen
- Center for Clinical Big Data and Analytics School of Public Health and The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou 310000, Zhejiang, China
| | - Zhenya Song
- Department of Health Management Center and Department of General Medicine, The Second Affiliated Hospital Zhejiang University School of Medicine, Hangzhou, 310009 Zhejiang, China
| | - Yi Guo
- Department of Health Management Center and Department of General Medicine, The Second Affiliated Hospital Zhejiang University School of Medicine, Hangzhou, 310009 Zhejiang, China
| | - Min Yang
- Center for Clinical Big Data and Analytics School of Public Health and The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou 310000, Zhejiang, China
| | - Fang Hu
- Department of Health Management Center and Department of General Medicine, The Second Affiliated Hospital Zhejiang University School of Medicine, Hangzhou, 310009 Zhejiang, China
| | - Qunke Xia
- School of Earth Sciences, Zhejiang University, Hangzhou 310027, China
| | - Zhenhong Du
- School of Earth Sciences, Zhejiang University, Hangzhou 310027, China; Zhejiang Provincial Key Laboratory of Geographic Information Science, Hangzhou 310028, China.
| | - Xifeng Wu
- Center for Clinical Big Data and Analytics School of Public Health and The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou 310000, Zhejiang, China; The Key Laboratory of Intelligent Preventive Medicine of Zhejiang Province, Hangzhou, Zhejiang 310058, China; Cancer Center, Zhejiang University, Hangzhou, Zhejiang 310058 China.
| |
Collapse
|
6
|
Lai KY, Webster C, Gallacher JE, Sarkar C. Associations of Urban Built Environment with Cardiovascular Risks and Mortality: a Systematic Review. J Urban Health 2023; 100:745-787. [PMID: 37580546 PMCID: PMC10447831 DOI: 10.1007/s11524-023-00764-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 06/28/2023] [Indexed: 08/16/2023]
Abstract
With rapid urbanization, built environment has emerged as a set of modifiable factors of cardiovascular disease (CVD) risks. We conducted a systematic review to synthesize evidence on the associations of attributes of urban built environment (e.g. residential density, land use mix, greenness and walkability) with cardiovascular risk factors (e.g. hypertension and arterial stiffness) and major CVD events including mortality. A total of 63 studies, including 31 of cross-sectional design and 32 of longitudinal design conducted across 21 geographical locations and published between 2012 and 2023 were extracted for review. Overall, we report moderately consistent evidence of protective associations of greenness with cardiovascular risks and major CVD events (cross-sectional studies: 12 of 15 on hypertension/blood pressure (BP) and 2 of 3 on arterial stiffness; and longitudinal studies: 6 of 8 on hypertension/BP, 7 of 8 on CVD mortality, 3 of 3 on ischemic heart disease mortality and 5 of 8 studies on stroke hospitalization or mortality reporting significant inverse associations). Consistently, walkability was associated with lower risks of hypertension, arterial stiffness and major CVD events (cross-sectional studies: 11 of 12 on hypertension/BP and 1 of 1 on arterial stiffness; and longitudinal studies: 3 of 6 on hypertension/BP and 1 of 2 studies on CVD events being protective). Sixty-seven percent of the studies were rated as "probably high" risk of confounding bias because of inability to adjust for underlying comorbidities/family history of diseases in their statistical models. Forty-six percent and 14% of the studies were rated as "probably high" risk of bias for exposure and outcome measurements, respectively. Future studies with robust design will further help elucidate the linkages between urban built environment and cardiovascular health, thereby informing planning policies for creating healthy cities.
Collapse
Affiliation(s)
- Ka Yan Lai
- Healthy High Density Cities Lab, HKUrbanLab, The University of Hong Kong, Knowles Building, Pokfulam Road, Hong Kong Special Administrative Region, China.
- Department of Urban Planning and Design, Faculty of Architecture, The University of Hong Kong, Knowles Building, Pokfulam Road, Hong Kong Special Administrative Region, China.
| | - Chris Webster
- Healthy High Density Cities Lab, HKUrbanLab, The University of Hong Kong, Knowles Building, Pokfulam Road, Hong Kong Special Administrative Region, China
- Department of Urban Planning and Design, Faculty of Architecture, The University of Hong Kong, Knowles Building, Pokfulam Road, Hong Kong Special Administrative Region, China
- Urban Systems Institute, The University of Hong Kong, Hong Kong Special Administrative Region, China
| | - John Ej Gallacher
- Department of Psychiatry, University of Oxford, Warneford Hospital, Oxford, OX3 7JX, UK
| | - Chinmoy Sarkar
- Healthy High Density Cities Lab, HKUrbanLab, The University of Hong Kong, Knowles Building, Pokfulam Road, Hong Kong Special Administrative Region, China
- Department of Urban Planning and Design, Faculty of Architecture, The University of Hong Kong, Knowles Building, Pokfulam Road, Hong Kong Special Administrative Region, China
- Department of Psychiatry, University of Oxford, Warneford Hospital, Oxford, OX3 7JX, UK
| |
Collapse
|