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http://conacyt.repositorioinstitucional.mx/jspui/handle/1000/333| Comprehensive Spatiotemporal Analysis of Opioid Poisoning Mortality in Ohio from 2010 to 2016 | |
| Sara Crawford Jean R. Clemenceau Chihyun Park Tae Hyun Hwang Gowtham Atluri Tyler Coy Rocio Lopez Anna Seballos | |
| Novel Coronavirus | |
| Acceso Abierto | |
| Atribución-NoComercial-SinDerivadas | |
| 10.1101/19005454 | |
| Objective: We aimed to identify (1) differences in opioid poisoning mortality among population groups, (2) geographic clusters of opioid-related deaths over time, and (3) health conditions co-occurring with opioid-related death in Ohio by computational analysis. Materials and Methods: We used a large-scale Ohio vital statistic dataset from the Ohio Department of Health (ODH) and U.S. Census data from 2010-2016. We surveyed population differences with demographic profiling and use of relative proportions, conducted spatiotemporal pattern analysis with spatial autocorrelation via Moran statistics at the census tract level, and performed comorbidity analysis using frequent itemset mining and association rule mining. Results: Our analyses found higher rates of opioid-related death in people aged 25-54, whites, and males. We also found that opioid-related deaths in Ohio became more spatially concentrated during 2010-2016, and tended to be most clustered around Cleveland, Columbus and Cincinnati. Drug abuse, anxiety and cardiovascular disease were found to predict opioid-related death. Discussion: Comprehensive data-driven spatiotemporal analysis of opioid-related deaths provides essential identification of demographic, geographic and health factors related to opioid abuse. Future research should access personal health information for more detailed comorbidity analysis, as well as expand spatiotemporal models for real-time use. Conclusion: Computational analyses revealed demographic differences in opioid poisoning, changing regional patterns of opioid-related deaths, and health conditions co-occurring with opioid overdose for Ohio from 2010-2016, providing essential knowledge for both government officials and caregivers to establish policies and strategies to best combat the opioid epidemic. ### Competing Interest Statement The authors have declared no competing interest. ### Funding Statement This research received no specific grant from any funding agency in the public, commercial or not-for-profit sectors. ### Author Declarations All relevant ethical guidelines have been followed and any necessary IRB and/or ethics committee approvals have been obtained. Yes All necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived. Not Applicable Any clinical trials involved have been registered with an ICMJE-approved registry such as ClinicalTrials.gov and the trial ID is included in the manuscript. Not Applicable I have followed all appropriate research reporting guidelines and uploaded the relevant Equator, ICMJE or other checklist(s) as supplementary files, if applicable. Not Applicable Data was obtained from the publicly available U.S. Census datasets and American Community Survey. Mortality data was obtained from the Ohio Department of Health. Access and use was approved by the ODH IRB. <https://www.census.gov/programs-surveys/acs/data.html> | |
| Cold Spring Harbor Laboratory Press | |
| 2019 | |
| Preimpreso | |
| https://www.medrxiv.org/content/10.1101/19005454v1 | |
| Inglés | |
| VIRUS RESPIRATORIOS | |
| Aparece en las colecciones: | Artículos científicos |
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| Comprehensive Spatiotemporal.pdf | 693.77 kB | Adobe PDF | Visualizar/Abrir |