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The use of Enhanced Vegetation Index for assessing access to different types of green space in epidemiological studies
Journal of Exposure Science & Environmental Epidemiology, Volume: 34, Pages: 753 - 760
Swansea University Authors: Amy Mizen , Daniel Thompson, Alan Watkins , Ashley Akbari , Ronan Lyons , Gareth Stratton , Rich Fry
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DOI (Published version): 10.1038/s41370-024-00650-5
Abstract
Background: Exposure to green space can protect against poor health through a variety of mechanisms. However, there is heterogeneity in methodological approaches to exposure assessments which makes creating effective policy recommendations challenging.Objective: Critically evaluate the use of a sate...
Published in: | Journal of Exposure Science & Environmental Epidemiology |
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ISSN: | 1559-0631 1559-064X |
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2024
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However, there is heterogeneity in methodological approaches to exposure assessments which makes creating effective policy recommendations challenging.Objective: Critically evaluate the use of a satellite-derived exposure metric, the Enhanced Vegetation Index (EVI), for assessing access to different types of green space in epidemiological studies.Methods: We used Landsat 5-8 (30 m resolution) to calculate average EVI for a 300m radius surrounding 1.4 million households in Wales, UK for 2018. We calculated two additional measures using topographic vector data to represent access to green spaces within 300m of household locations. The two topographic vector-based measures were total green space area stratified by type and average private garden size. We used linear regression models to test whether EVI could discriminate between publicly accessible and private green space and Pearson correlation to test associations between EVI and green space types.Results: Mean EVI for a 300m radius surrounding households in Wales was 0.22 (IQR= 0.12). Total green space area and average private garden size were significantly positively associated with corresponding EVI measures (= <0.0001, 95% CI: 0.0000,0.0000; = 0.0001, 95% CI: 0.0001,0.0001 respectively). In urban areas, as average garden size increases by 1m2, EVI increases by 0.0002. Therefore, in urban areas, to see a 0.1 unit increase in EVI index score, garden size would need to increase by 500m2. The very small values represent no ‘measurable real-world’ associations. When stratified by type, we observed no strong associations between greenspace and EVI.Significance: Satellite-derived measures such as EVI offer the opportunity to objectively measure exposure to greenness in the hyperlocal environment. However, EVI should be interpreted with care as a greater EVI score does not necessarily mean greater access to publicly available green spaces in the hyperlocal environment.</abstract><type>Journal Article</type><journal>Journal of Exposure Science & Environmental Epidemiology</journal><volume>34</volume><journalNumber/><paginationStart>753</paginationStart><paginationEnd>760</paginationEnd><publisher>Springer Nature</publisher><placeOfPublication/><isbnPrint/><isbnElectronic/><issnPrint>1559-0631</issnPrint><issnElectronic>1559-064X</issnElectronic><keywords>Enhanced Vegetation Index (EVI), Exposure assessment, Residential greenness, Epidemiological studies</keywords><publishedDay>1</publishedDay><publishedMonth>9</publishedMonth><publishedYear>2024</publishedYear><publishedDate>2024-09-01</publishedDate><doi>10.1038/s41370-024-00650-5</doi><url/><notes/><college>COLLEGE NANME</college><department>Medical School</department><CollegeCode>COLLEGE CODE</CollegeCode><DepartmentCode>MEDS</DepartmentCode><institution>Swansea University</institution><apcterm/><funders>This research was conducted as part of independent research funded by the National Institute for Health Research (NIHR), project number 16/07/07. The views expressed are those of the author(s) and not necessarily those of the NHS, the NIHR or the Department of Health and Social Care.</funders><projectreference/><lastEdited>2024-10-03T10:18:15.9175911</lastEdited><Created>2024-02-14T14:03:26.5250253</Created><path><level id="1">Faculty of Medicine, Health and Life Sciences</level><level id="2">Swansea University Medical School - Health Data Science</level></path><authors><author><firstname>Amy</firstname><surname>Mizen</surname><orcid>0000-0001-7516-6767</orcid><order>1</order></author><author><firstname>Daniel</firstname><surname>Thompson</surname><order>2</order></author><author><firstname>Alan</firstname><surname>Watkins</surname><orcid>0000-0003-3804-1943</orcid><order>3</order></author><author><firstname>Ashley</firstname><surname>Akbari</surname><orcid>0000-0003-0814-0801</orcid><order>4</order></author><author><firstname>Joanne K.</firstname><surname>Garrett</surname><order>5</order></author><author><firstname>Rebecca</firstname><surname>Geary</surname><order>6</order></author><author><firstname>Rebecca</firstname><surname>Lovell</surname><order>7</order></author><author><firstname>Ronan</firstname><surname>Lyons</surname><orcid>0000-0001-5225-000X</orcid><order>8</order></author><author><firstname>Mark</firstname><surname>Nieuwenhuijsen</surname><order>9</order></author><author><firstname>Sarah C.</firstname><surname>Parker</surname><order>10</order></author><author><firstname>Francis M.</firstname><surname>Rowney</surname><order>11</order></author><author><firstname>Jiao</firstname><surname>Song</surname><order>12</order></author><author><firstname>Gareth</firstname><surname>Stratton</surname><orcid>0000-0001-5618-0803</orcid><order>13</order></author><author><firstname>Benedict W.</firstname><surname>Wheeler</surname><order>14</order></author><author><firstname>James</firstname><surname>White</surname><order>15</order></author><author><firstname>Mathew P.</firstname><surname>White</surname><order>16</order></author><author><firstname>Sue</firstname><surname>Williams</surname><order>17</order></author><author><firstname>Sarah E.</firstname><surname>Rodgers</surname><order>18</order></author><author><firstname>Rich</firstname><surname>Fry</surname><orcid>0000-0002-7968-6679</orcid><order>19</order></author></authors><documents><document><filename>65638__29883__4be000d06ffe4fbfba1735421298fb3f.pdf</filename><originalFilename>65638VoR.pdf</originalFilename><uploaded>2024-04-03T11:50:26.4955255</uploaded><type>Output</type><contentLength>1354824</contentLength><contentType>application/pdf</contentType><version>Version of Record</version><cronfaStatus>true</cronfaStatus><documentNotes>This article is licensed under a Creative Commons Attribution 4.0 International License.</documentNotes><copyrightCorrect>true</copyrightCorrect><language>eng</language><licence>http://creativecommons.org/licenses/by/4.0/</licence></document></documents><OutputDurs/></rfc1807> |
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v2 65638 2024-02-14 The use of Enhanced Vegetation Index for assessing access to different types of green space in epidemiological studies 9e9db8229784e27fcd79a14ee097e10b 0000-0001-7516-6767 Amy Mizen Amy Mizen true false 40739e67f38acf288da063663d77850a Daniel Thompson Daniel Thompson true false 81fc05c9333d9df41b041157437bcc2f 0000-0003-3804-1943 Alan Watkins Alan Watkins true false aa1b025ec0243f708bb5eb0a93d6fb52 0000-0003-0814-0801 Ashley Akbari Ashley Akbari true false 83efcf2a9dfcf8b55586999d3d152ac6 0000-0001-5225-000X Ronan Lyons Ronan Lyons true false 6d62b2ed126961bed81a94a2beba8a01 0000-0001-5618-0803 Gareth Stratton Gareth Stratton true false d499b898d447b62c81b2c122598870e0 0000-0002-7968-6679 Rich Fry Rich Fry true false 2024-02-14 MEDS Background: Exposure to green space can protect against poor health through a variety of mechanisms. However, there is heterogeneity in methodological approaches to exposure assessments which makes creating effective policy recommendations challenging.Objective: Critically evaluate the use of a satellite-derived exposure metric, the Enhanced Vegetation Index (EVI), for assessing access to different types of green space in epidemiological studies.Methods: We used Landsat 5-8 (30 m resolution) to calculate average EVI for a 300m radius surrounding 1.4 million households in Wales, UK for 2018. We calculated two additional measures using topographic vector data to represent access to green spaces within 300m of household locations. The two topographic vector-based measures were total green space area stratified by type and average private garden size. We used linear regression models to test whether EVI could discriminate between publicly accessible and private green space and Pearson correlation to test associations between EVI and green space types.Results: Mean EVI for a 300m radius surrounding households in Wales was 0.22 (IQR= 0.12). Total green space area and average private garden size were significantly positively associated with corresponding EVI measures (= <0.0001, 95% CI: 0.0000,0.0000; = 0.0001, 95% CI: 0.0001,0.0001 respectively). In urban areas, as average garden size increases by 1m2, EVI increases by 0.0002. Therefore, in urban areas, to see a 0.1 unit increase in EVI index score, garden size would need to increase by 500m2. The very small values represent no ‘measurable real-world’ associations. When stratified by type, we observed no strong associations between greenspace and EVI.Significance: Satellite-derived measures such as EVI offer the opportunity to objectively measure exposure to greenness in the hyperlocal environment. However, EVI should be interpreted with care as a greater EVI score does not necessarily mean greater access to publicly available green spaces in the hyperlocal environment. Journal Article Journal of Exposure Science & Environmental Epidemiology 34 753 760 Springer Nature 1559-0631 1559-064X Enhanced Vegetation Index (EVI), Exposure assessment, Residential greenness, Epidemiological studies 1 9 2024 2024-09-01 10.1038/s41370-024-00650-5 COLLEGE NANME Medical School COLLEGE CODE MEDS Swansea University This research was conducted as part of independent research funded by the National Institute for Health Research (NIHR), project number 16/07/07. The views expressed are those of the author(s) and not necessarily those of the NHS, the NIHR or the Department of Health and Social Care. 2024-10-03T10:18:15.9175911 2024-02-14T14:03:26.5250253 Faculty of Medicine, Health and Life Sciences Swansea University Medical School - Health Data Science Amy Mizen 0000-0001-7516-6767 1 Daniel Thompson 2 Alan Watkins 0000-0003-3804-1943 3 Ashley Akbari 0000-0003-0814-0801 4 Joanne K. Garrett 5 Rebecca Geary 6 Rebecca Lovell 7 Ronan Lyons 0000-0001-5225-000X 8 Mark Nieuwenhuijsen 9 Sarah C. Parker 10 Francis M. Rowney 11 Jiao Song 12 Gareth Stratton 0000-0001-5618-0803 13 Benedict W. Wheeler 14 James White 15 Mathew P. White 16 Sue Williams 17 Sarah E. Rodgers 18 Rich Fry 0000-0002-7968-6679 19 65638__29883__4be000d06ffe4fbfba1735421298fb3f.pdf 65638VoR.pdf 2024-04-03T11:50:26.4955255 Output 1354824 application/pdf Version of Record true This article is licensed under a Creative Commons Attribution 4.0 International License. true eng http://creativecommons.org/licenses/by/4.0/ |
title |
The use of Enhanced Vegetation Index for assessing access to different types of green space in epidemiological studies |
spellingShingle |
The use of Enhanced Vegetation Index for assessing access to different types of green space in epidemiological studies Amy Mizen Daniel Thompson Alan Watkins Ashley Akbari Ronan Lyons Gareth Stratton Rich Fry |
title_short |
The use of Enhanced Vegetation Index for assessing access to different types of green space in epidemiological studies |
title_full |
The use of Enhanced Vegetation Index for assessing access to different types of green space in epidemiological studies |
title_fullStr |
The use of Enhanced Vegetation Index for assessing access to different types of green space in epidemiological studies |
title_full_unstemmed |
The use of Enhanced Vegetation Index for assessing access to different types of green space in epidemiological studies |
title_sort |
The use of Enhanced Vegetation Index for assessing access to different types of green space in epidemiological studies |
author_id_str_mv |
9e9db8229784e27fcd79a14ee097e10b 40739e67f38acf288da063663d77850a 81fc05c9333d9df41b041157437bcc2f aa1b025ec0243f708bb5eb0a93d6fb52 83efcf2a9dfcf8b55586999d3d152ac6 6d62b2ed126961bed81a94a2beba8a01 d499b898d447b62c81b2c122598870e0 |
author_id_fullname_str_mv |
9e9db8229784e27fcd79a14ee097e10b_***_Amy Mizen 40739e67f38acf288da063663d77850a_***_Daniel Thompson 81fc05c9333d9df41b041157437bcc2f_***_Alan Watkins aa1b025ec0243f708bb5eb0a93d6fb52_***_Ashley Akbari 83efcf2a9dfcf8b55586999d3d152ac6_***_Ronan Lyons 6d62b2ed126961bed81a94a2beba8a01_***_Gareth Stratton d499b898d447b62c81b2c122598870e0_***_Rich Fry |
author |
Amy Mizen Daniel Thompson Alan Watkins Ashley Akbari Ronan Lyons Gareth Stratton Rich Fry |
author2 |
Amy Mizen Daniel Thompson Alan Watkins Ashley Akbari Joanne K. Garrett Rebecca Geary Rebecca Lovell Ronan Lyons Mark Nieuwenhuijsen Sarah C. Parker Francis M. Rowney Jiao Song Gareth Stratton Benedict W. Wheeler James White Mathew P. White Sue Williams Sarah E. Rodgers Rich Fry |
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Journal of Exposure Science & Environmental Epidemiology |
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34 |
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753 |
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2024 |
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Swansea University |
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1559-0631 1559-064X |
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10.1038/s41370-024-00650-5 |
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Springer Nature |
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Faculty of Medicine, Health and Life Sciences |
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facultyofmedicinehealthandlifesciences |
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Faculty of Medicine, Health and Life Sciences |
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Faculty of Medicine, Health and Life Sciences |
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Swansea University Medical School - Health Data Science{{{_:::_}}}Faculty of Medicine, Health and Life Sciences{{{_:::_}}}Swansea University Medical School - Health Data Science |
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description |
Background: Exposure to green space can protect against poor health through a variety of mechanisms. However, there is heterogeneity in methodological approaches to exposure assessments which makes creating effective policy recommendations challenging.Objective: Critically evaluate the use of a satellite-derived exposure metric, the Enhanced Vegetation Index (EVI), for assessing access to different types of green space in epidemiological studies.Methods: We used Landsat 5-8 (30 m resolution) to calculate average EVI for a 300m radius surrounding 1.4 million households in Wales, UK for 2018. We calculated two additional measures using topographic vector data to represent access to green spaces within 300m of household locations. The two topographic vector-based measures were total green space area stratified by type and average private garden size. We used linear regression models to test whether EVI could discriminate between publicly accessible and private green space and Pearson correlation to test associations between EVI and green space types.Results: Mean EVI for a 300m radius surrounding households in Wales was 0.22 (IQR= 0.12). Total green space area and average private garden size were significantly positively associated with corresponding EVI measures (= <0.0001, 95% CI: 0.0000,0.0000; = 0.0001, 95% CI: 0.0001,0.0001 respectively). In urban areas, as average garden size increases by 1m2, EVI increases by 0.0002. Therefore, in urban areas, to see a 0.1 unit increase in EVI index score, garden size would need to increase by 500m2. The very small values represent no ‘measurable real-world’ associations. When stratified by type, we observed no strong associations between greenspace and EVI.Significance: Satellite-derived measures such as EVI offer the opportunity to objectively measure exposure to greenness in the hyperlocal environment. However, EVI should be interpreted with care as a greater EVI score does not necessarily mean greater access to publicly available green spaces in the hyperlocal environment. |
published_date |
2024-09-01T10:18:15Z |
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11.036837 |