How neighborhood environment modified the effects of power outages on multiple health outcomes in New York state?
Background: Although power outage (PO) is one of the most important consequences of increasing weather extremes and the health impact of POs has been reported previously, studies on the neighborhood environment underlying the population vulnerability in such situations are limited. This study aimed...
| Main Authors: | , , , , , , , , , , , , |
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| Format: | Article |
| Language: | English |
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Elsevier
2022-12-01
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| Series: | Hygiene and Environmental Health Advances |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2773049222000393 |
| _version_ | 1797740806735396864 |
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| author | Wangjian Zhang Xinlei Deng Xiaobo X. Romeiko Kai Zhang Scott C. Sheridan Jerald Brotzge Howard H. Chang Eric K. Stern Zhijian Guo Guanghui Dong Ramune Reliene Yuantao Hao Shao Lin |
| author_facet | Wangjian Zhang Xinlei Deng Xiaobo X. Romeiko Kai Zhang Scott C. Sheridan Jerald Brotzge Howard H. Chang Eric K. Stern Zhijian Guo Guanghui Dong Ramune Reliene Yuantao Hao Shao Lin |
| author_sort | Wangjian Zhang |
| collection | DOAJ |
| description | Background: Although power outage (PO) is one of the most important consequences of increasing weather extremes and the health impact of POs has been reported previously, studies on the neighborhood environment underlying the population vulnerability in such situations are limited. This study aimed to identify dominant neighborhood environmental predictors which modified the impact of POs on multiple health outcomes in New York State. Methods: We applied a two-stage approach. In the first stage, we used time series analysis to determine the impact of POs (versus non-PO periods) on multiple health outcomes in each power operating division in New York State, 2001-2013. In the second stage, we classified divisions as risk-elevated and non-elevated, then developed predictive models for the elevation status based on 36 neighborhood environmental factors using random forest and gradient boosted trees. Results: Consistent across different outcomes, we found predictors representing greater urbanization, particularly, the proportion of residents having access to public transportation (importance ranging from 4.9–15.6%), population density (3.3–16.1%), per capita income (2.3–10.7%), and the density of public infrastructure (0.8–8.5%), were associated with a higher possibility of risk elevation following power outages. Additionally, the percent of minority (-6.3–27.9%) and those with limited English (2.2–8.1%), the percent of sandy soil (6.5–11.8%), and average soil temperature (3.0–15.7%) were also dominant predictors for multiple outcomes. Spatial hotspots of vulnerability generally were located surrounding New York City and in the northwest, the pattern of which was consistent with socioeconomic status. Conclusion: Population vulnerability during power outages was dominated by neighborhood environmental factors representing greater urbanization. |
| first_indexed | 2024-03-12T14:17:43Z |
| format | Article |
| id | doaj.art-ada70d75c023494999dd00f1182da4d6 |
| institution | Directory Open Access Journal |
| issn | 2773-0492 |
| language | English |
| last_indexed | 2024-03-12T14:17:43Z |
| publishDate | 2022-12-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Hygiene and Environmental Health Advances |
| spelling | doaj.art-ada70d75c023494999dd00f1182da4d62023-08-20T04:39:01ZengElsevierHygiene and Environmental Health Advances2773-04922022-12-014100039How neighborhood environment modified the effects of power outages on multiple health outcomes in New York state?Wangjian Zhang0Xinlei Deng1Xiaobo X. Romeiko2Kai Zhang3Scott C. Sheridan4Jerald Brotzge5Howard H. Chang6Eric K. Stern7Zhijian Guo8Guanghui Dong9Ramune Reliene10Yuantao Hao11Shao Lin12Department of Medical Statistics, School of Public Health, Sun Yat-sen University, Guangzhou, China; Department of Environmental Health Sciences, University at Albany, State University of New York, Rensselaer, NY, USADepartment of Environmental Health Sciences, University at Albany, State University of New York, Rensselaer, NY, USADepartment of Environmental Health Sciences, University at Albany, State University of New York, Rensselaer, NY, USADepartment of Environmental Health Sciences, University at Albany, State University of New York, Rensselaer, NY, USADepartment of Geography, Kent State University, Kent, OH, USANew York State Mesonet, College of Arts and Sciences, State University of New York, Rensselaer, NY, USADepartment of Biostatistics and Bioinformatics, Rollins School of Public Health, Emory University, Atlanta, GACollege of Emergency Preparedness, Homeland Security and Cybersecurity, State University of New York, Albany, NY, USADepartment of Mathematics and Statistics, State University of New York, Albany, NY, USADepartment of Preventive Medicine, School of Public Health, Sun Yat-sen University, Guangzhou, ChinaCancer Research Center, State University of New York, Rensselaer, NY, USADepartment of Medical Statistics, School of Public Health, Sun Yat-sen University, Guangzhou, China; Corresponding authors.Department of Environmental Health Sciences, University at Albany, State University of New York, Rensselaer, NY, USA; Corresponding authors.Background: Although power outage (PO) is one of the most important consequences of increasing weather extremes and the health impact of POs has been reported previously, studies on the neighborhood environment underlying the population vulnerability in such situations are limited. This study aimed to identify dominant neighborhood environmental predictors which modified the impact of POs on multiple health outcomes in New York State. Methods: We applied a two-stage approach. In the first stage, we used time series analysis to determine the impact of POs (versus non-PO periods) on multiple health outcomes in each power operating division in New York State, 2001-2013. In the second stage, we classified divisions as risk-elevated and non-elevated, then developed predictive models for the elevation status based on 36 neighborhood environmental factors using random forest and gradient boosted trees. Results: Consistent across different outcomes, we found predictors representing greater urbanization, particularly, the proportion of residents having access to public transportation (importance ranging from 4.9–15.6%), population density (3.3–16.1%), per capita income (2.3–10.7%), and the density of public infrastructure (0.8–8.5%), were associated with a higher possibility of risk elevation following power outages. Additionally, the percent of minority (-6.3–27.9%) and those with limited English (2.2–8.1%), the percent of sandy soil (6.5–11.8%), and average soil temperature (3.0–15.7%) were also dominant predictors for multiple outcomes. Spatial hotspots of vulnerability generally were located surrounding New York City and in the northwest, the pattern of which was consistent with socioeconomic status. Conclusion: Population vulnerability during power outages was dominated by neighborhood environmental factors representing greater urbanization.http://www.sciencedirect.com/science/article/pii/S2773049222000393Power outageNeighborhood environmentMultiple health outcomesVulnerabilityMachine learning |
| spellingShingle | Wangjian Zhang Xinlei Deng Xiaobo X. Romeiko Kai Zhang Scott C. Sheridan Jerald Brotzge Howard H. Chang Eric K. Stern Zhijian Guo Guanghui Dong Ramune Reliene Yuantao Hao Shao Lin How neighborhood environment modified the effects of power outages on multiple health outcomes in New York state? Hygiene and Environmental Health Advances Power outage Neighborhood environment Multiple health outcomes Vulnerability Machine learning |
| title | How neighborhood environment modified the effects of power outages on multiple health outcomes in New York state? |
| title_full | How neighborhood environment modified the effects of power outages on multiple health outcomes in New York state? |
| title_fullStr | How neighborhood environment modified the effects of power outages on multiple health outcomes in New York state? |
| title_full_unstemmed | How neighborhood environment modified the effects of power outages on multiple health outcomes in New York state? |
| title_short | How neighborhood environment modified the effects of power outages on multiple health outcomes in New York state? |
| title_sort | how neighborhood environment modified the effects of power outages on multiple health outcomes in new york state |
| topic | Power outage Neighborhood environment Multiple health outcomes Vulnerability Machine learning |
| url | http://www.sciencedirect.com/science/article/pii/S2773049222000393 |
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