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Whyte M, Douwes J, Ranta A. Green space and stroke: A scoping review of the evidence. J Neurol Sci 2024; 457:122870. [PMID: 38219382 DOI: 10.1016/j.jns.2024.122870] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/31/2023] [Revised: 12/18/2023] [Accepted: 01/04/2024] [Indexed: 01/16/2024]
Abstract
BACKGROUND Global industrialisation and urbanisation has led to an increased interest in the link between the environment and health. Stroke is a major cause of morbidity and mortality, and there is increased evidence that environmental factors may affect both the incidence and severity of stroke. This review summarises the evidence for relationship between green space exposure and stroke incidence and outcomes. METHODS We conducted a literature search in Medline and Scopus until 1 August 2023, and screened references of relevant articles. Selected articles were appraised for their relevance, and critically reviewed. The findings were thematically categorised. RESULTS Of the 1342 papers identified, 27 were included. These involved a mix of study designs (cohort, cross-sectional, quasi-experimental, time stratified case crossover and ecological). There was consistent evidence indicating a protective association between green space exposure and disability and stroke-related death with mortality hazard ratios between 0.66 and 0.95. Most studies also showed that green space was inversely associated with stroke risk, with risk estimates from studies showing a protective effect ranging between 0.4 and 0.98; however, results were more mixed and some did not reach statistical significance. The moderating effects of green spaces on ambient temperatures, noise and air pollution, and psychosocial health plus greater enjoyment and opportunity for exercise and enrichment of the human microbiome may underly these associations. CONCLUSION There is likely some protective effect of green space on stroke, with the benefits most convincingly shown for post-stroke outcomes. More research is recommended to confirm the protective association between green space exposure and reduced stroke risk.
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Affiliation(s)
- Mina Whyte
- Department of Medicine, University of Otago Wellington, PO Box 7343, Wellington 6242, New Zealand
| | - Jeroen Douwes
- Research Centre for Hauora and Health, Massey University, Wellington, New Zealand
| | - Annemarei Ranta
- Department of Medicine, University of Otago Wellington, PO Box 7343, Wellington 6242, New Zealand.
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Li F, Liu W, Hu C, Tang M, Zhang Y, Ho HC, Peng S, Li Z, Wang Q, Li X, Xu B, Li F. Global association of greenness exposure with risk of nervous system disease: A systematic review and meta-analysis. THE SCIENCE OF THE TOTAL ENVIRONMENT 2023; 877:162773. [PMID: 36933739 DOI: 10.1016/j.scitotenv.2023.162773] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/11/2022] [Revised: 03/06/2023] [Accepted: 03/06/2023] [Indexed: 05/06/2023]
Abstract
Nervous system disease (NSD) is a global health burden with increasing prevalence in the last 30 years. There is evidence that greenness can improve nervous system health through a variety of mechanisms; however, the evidence is inconsistent. In the present systematic review and meta-analysis, we examined the relationship between greenness exposure and NSD outcomes. Studies on the relationship between greenness and NSD health outcomes published till July 2022 were searched in PubMed, Cochrane, Embase, Scopus, and Web of Science. In addition, we searched the cited literature and updated our search on Jan 20, 2023, to identify any new studies. We included human epidemiological studies that assess the association of greenness exposure with the risk of NSD. Greenness exposure was measured using NDVI (the normalized difference vegetation index) and the outcome was the mortality or morbidity of NSD. The pooled relative risks (RRs) were estimated using a random effects model. Of 2059 identified studies, 15 studies were included in our quantitative evaluation, in which 11 studies found a significant inverse relationship between the risk of NSD mortality or incidence/prevalence and an increase in surrounding greenness. The pooled RRs for cerebrovascular diseases (CBVD), neurodegenerative diseases (ND), and stroke mortality were 0.98 (95 % CI: 0.97, 1.00), 0.98 (95 % CI: 0.98, 0.99), and 0.96 (95 % CI: 0.93, 1.00), respectively. The pooled RRs for PD incidence and stroke prevalence/incidence were 0.89 (95 % CI: 0.78, 1.02) and 0.98 (95 % CI: 0.97, 0.99), respectively. The confidence of evidence for ND mortality, stroke mortality, and stroke prevalence/incidence was downgraded to "low", while CBVD mortality and PD incidence were downgraded to "very low" due to inconsistency. We found no evidence of publication bias and the sensitivity analysis results of all subgroups are robust except for the stroke mortality subgroup. This is the first comprehensive meta-analysis of greenness exposure and NSD outcomes in which an inverse relationship was observed. It is necessary to conduct further research to ascertain the role greenness exposure plays in various NSDs and the management of greenness should be considered a public health strategy.
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Affiliation(s)
- Fangzheng Li
- School of Landscape Architecture, Beijing Forestry University, Beijing 100083, China.
| | - Wei Liu
- School of Art, Qufu Normal University, Rizhao 276826, China
| | - Chengyang Hu
- Department of Epidemiology and Biostatistics, School of Public Health, Anhui Medical University, Hefei 230032, China
| | - Mingcheng Tang
- School of Landscape Architecture and Forestry, Qingdao Agricultural University, Qingdao 266109, China
| | - Yunquan Zhang
- Department of Epidemiology and Biostatistics, School of Public Health, Wuhan University of Science and Technology, Wuhan 430065, China
| | - Hung Chak Ho
- Department of Anaesthesiology, School of Clinical Medicine, LKS Faculty of Medicine, The University of Hong Kong, Hong Kong
| | - Shijia Peng
- Charles Davis's Lab Department of Organismic and Evolutionary Biology, Harvard University, Cambridge, MA 02138, USA
| | - Zhouyuan Li
- School of Grassland Science, Beijing Forestry University, Beijing 100083, China
| | - Qing Wang
- China CDC Key Laboratory of Environment and Population Health/National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing 100021, China
| | - Xiong Li
- School of Landscape Architecture, Beijing Forestry University, Beijing 100083, China
| | - Bing Xu
- Department of Earth System Science, Tsinghua University, 10084 Beijing, China
| | - Fengyi Li
- School of Landscape Architecture and Forestry, Qingdao Agricultural University, Qingdao 266109, China.
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Wang G, Yang FF, Lin G, Wang Z, Zhang X. Modification of low temperature-related hospital admissions for cardiovascular diseases by multiple green space indicators at multiple spatial scales: Evidence from Guangzhou, China. Int J Hyg Environ Health 2023; 251:114193. [PMID: 37247607 DOI: 10.1016/j.ijheh.2023.114193] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/24/2022] [Revised: 05/21/2023] [Accepted: 05/24/2023] [Indexed: 05/31/2023]
Abstract
BACKGROUND Extreme temperatures have an adverse effect on the occurrence of cardiovascular diseases (CVDs). Previous literatures tend to discuss the modification of CVDs occurrence by green space under high temperature. Relatively less attention is paid to the modification under low temperature. The variation of different attributes and spatial scales of green space in affecting CVDs occurrence are also overlooked. METHODS This study collected a total of 4364 first-time admission cases due to CVDs in a tertiary hospital in Guangzhou from 2012 to 2018, measured the scale of green space by greening rate (GR) and percentage of landscape (PLAND), the distribution of green space by patch density (PD), mean nearest neighbor distance (ENN_MN) and largest patch index (LPI), and the accessibility of green space by green patch accessibility index (GPAI). Using the time stratified case crossover design method, the modification of low temperature-related CVDs occurrence by the above green space indicators is evaluated in an area with a radius of 100-1000 m which is further divided at an interval of 100 m. RESULTS We found high GR, high PLAND, high PD, low ENN_MN, high LPI, and low GPAI corresponds to low risk of CVDs occurrence, the optimal modification scale of each green space indicator, which is radius corresponding to the maximum risk difference between high and low indicator subgroups, is around 800 m (GR), 600 m (PLAND and PD), 500 m (GPAI), and 300 m (LPI and ENN_MN), respectively. As the temperature decreases further, the health benefit from low GPAI at the optimal scale is weakened, whereas the benefits from the others are strengthened. CONCLUSIONS Low temperature related CVDs occurrence risk can be modified by multiple green space indicators, and these modifications have spatial scale effect. Our findings have important theoretical and practical significance for the formulation and implementation of local green space policies.
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Affiliation(s)
- Guobin Wang
- School of Geography and Planning, Sun Yat-Sen University, GuangZhou, 510006, China
| | - Fiona Fan Yang
- School of Geography and Planning, Sun Yat-Sen University, GuangZhou, 510006, China
| | - Geng Lin
- School of Geography and Planning, Sun Yat-Sen University, GuangZhou, 510006, China.
| | - Zhuoqing Wang
- Department of Scientific Research & Discipline Development, The First Affiliated Hospital Sun Yat-sen University, 58 Zhongshan Road 2nd, Guangzhou, 510080, China.
| | - Xiangxue Zhang
- State Key Laboratory of Earth Surface Processes and Resource Ecology, Beijing Normal University, Beijing, 100875, China
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Liu L, Wu Q, Li X, Song R, Wei N, Liu J, Yuan J, Yan S, Sun X, Liang Y, Li Y, Jin X, Wu Y, Mei L, Song J, Yi W, Pan R, Cheng J, Su H. Sunshine duration and risks of schizophrenia hospitalizations in main urban area: Do built environments modify the association? THE SCIENCE OF THE TOTAL ENVIRONMENT 2023; 871:162057. [PMID: 36758693 DOI: 10.1016/j.scitotenv.2023.162057] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/06/2022] [Revised: 02/01/2023] [Accepted: 02/02/2023] [Indexed: 06/18/2023]
Abstract
BACKGROUND Although studies have explored the relationship between sunshine duration and schizophrenia, the evidence was ambiguous. Different built environments may alter the effect of sunlight on schizophrenia, thus the purpose of this study was to investigate the effects of built environments on the sunshine duration-schizophrenia association. MATERIALS AND METHODS Daily schizophrenia hospitalizations data during 2017-2020 in Hefei's main urban area, China, and corresponding meteorological factors as well as ambient pollutants were collected. The impact of sunshine duration on schizophrenia admissions in urban areas was investigated using a generalized additive model combined with a distributed lagged nonlinear model. Additionally, the various modifying effects of different Building Density, Building Height, Normalized Vegetation Index, and Nighttime Light were also explored between sunshine duration and schizophrenia. RESULTS We observed that inadequate sunshine duration (<5.3 h) was associated with an increase in schizophrenia hospital admissions, with a maximum relative risk of 1.382 (95 % confidence interval (CI): 1.069-1.786) at 2.9 h. In turn, adequate sunshine duration reduced the risk of schizophrenia hospitalizations. Subgroup analyses indicated females and old patients were particularly vulnerable. In the case of insufficient sunshine duration, significant positive effects were noticed on schizophrenia risk at High-Building Density and High-Nighttime Light. Higher NDVI as well as Building Height were found to be associated with lower risks of schizophrenia. CONCLUSIONS Given that sunshine duration in various built environments might lead to distinct effects on schizophrenia hospitalizations. Our findings assist in identifying vulnerable populations that reside in particular areas, thus suggesting policymakers provide advice to mitigate the onset of schizophrenia by allocating healthcare resources rationally and avoiding adverse exposures to vulnerable populations timely.
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Affiliation(s)
- Li Liu
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, Hefei, Anhui 230032, China; Inflammation and Immune Mediated Diseases Laboratory of Anhui Province, Hefei, Anhui 230032, China
| | - Qing Wu
- Anhui Mental Health Center, Hefei, Anhui, China
| | - Xuanxuan Li
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, Hefei, Anhui 230032, China; Inflammation and Immune Mediated Diseases Laboratory of Anhui Province, Hefei, Anhui 230032, China
| | - Rong Song
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, Hefei, Anhui 230032, China; Inflammation and Immune Mediated Diseases Laboratory of Anhui Province, Hefei, Anhui 230032, China
| | - Ning Wei
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, Hefei, Anhui 230032, China; Inflammation and Immune Mediated Diseases Laboratory of Anhui Province, Hefei, Anhui 230032, China
| | - Jintao Liu
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, Hefei, Anhui 230032, China; Inflammation and Immune Mediated Diseases Laboratory of Anhui Province, Hefei, Anhui 230032, China
| | - Jiajun Yuan
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, Hefei, Anhui 230032, China; Inflammation and Immune Mediated Diseases Laboratory of Anhui Province, Hefei, Anhui 230032, China
| | - Shuangshuang Yan
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, Hefei, Anhui 230032, China; Inflammation and Immune Mediated Diseases Laboratory of Anhui Province, Hefei, Anhui 230032, China
| | - Xiaoni Sun
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, Hefei, Anhui 230032, China; Inflammation and Immune Mediated Diseases Laboratory of Anhui Province, Hefei, Anhui 230032, China
| | - Yunfeng Liang
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, Hefei, Anhui 230032, China; Inflammation and Immune Mediated Diseases Laboratory of Anhui Province, Hefei, Anhui 230032, China
| | - Yuxuan Li
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, Hefei, Anhui 230032, China; Inflammation and Immune Mediated Diseases Laboratory of Anhui Province, Hefei, Anhui 230032, China
| | - Xiaoyu Jin
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, Hefei, Anhui 230032, China; Inflammation and Immune Mediated Diseases Laboratory of Anhui Province, Hefei, Anhui 230032, China
| | - Yudong Wu
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, Hefei, Anhui 230032, China; Inflammation and Immune Mediated Diseases Laboratory of Anhui Province, Hefei, Anhui 230032, China
| | - Lu Mei
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, Hefei, Anhui 230032, China; Inflammation and Immune Mediated Diseases Laboratory of Anhui Province, Hefei, Anhui 230032, China
| | - Jian Song
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, Hefei, Anhui 230032, China; Inflammation and Immune Mediated Diseases Laboratory of Anhui Province, Hefei, Anhui 230032, China
| | - Weizhuo Yi
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, Hefei, Anhui 230032, China; Inflammation and Immune Mediated Diseases Laboratory of Anhui Province, Hefei, Anhui 230032, China
| | - Rubing Pan
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, Hefei, Anhui 230032, China; Inflammation and Immune Mediated Diseases Laboratory of Anhui Province, Hefei, Anhui 230032, China
| | - Jian Cheng
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, Hefei, Anhui 230032, China; Inflammation and Immune Mediated Diseases Laboratory of Anhui Province, Hefei, Anhui 230032, China
| | - Hong Su
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, Hefei, Anhui 230032, China; Inflammation and Immune Mediated Diseases Laboratory of Anhui Province, Hefei, Anhui 230032, China.
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