Volume 29, Issue 136 (September & October 2021)                   J Adv Med Biomed Res 2021, 29(136): 263-270 | Back to browse issues page


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Soleimani M, Jalilvand A, Soleimani R. Geographic Information System of Stroke Incidence in Zanjan Province, Iran During 2012-2019. J Adv Med Biomed Res 2021; 29 (136) :263-270
URL: http://journal.zums.ac.ir/article-1-6211-en.html
1- Dept. of Medical Informatics, Mousavi Hospital, School of Medicine, Zanjan University of Medical Sciences, Zanjan, Iran. , Mohsensoleymani66@gmail.com
2- Dept. of Pathology, Mousavi Hospital, School of Medicine, Zanjan University of Medical Sciences, Zanjan, Iran.
3- Dept.of General Psychology, Islamic Azad University, Zanjan Branch, Zanjan, Iran.
Abstract:   (131685 Views)

Background and Objective: Stroke is the second leading cause of mortality and the third leading cause of morbidity worldwide. This study aimed to examine the spatial-temporal distribution of stroke in rural districts, Zanjan Province, Iran.
Materials and Methods: This cross-sectional study was conducted at Zanjan University of Medical Sciences (ZUMS). Patients with a discharge diagnosis of stroke (the ICD-10 code of I64), hospitalized during 2012-2019 at ZUMS hospitals, were selected as the study sample. Spatial statistical tools, autocorrelation Moran’s I, high-low clustering analysis, and hot spot analysis were used for spatial data analysis. ArcGIS 10.7, R 3.6.0, and RStudio 1.2.1335 software packages were used to analyze the data.
Results: During 2012-2019, 8404 stroke cases were hospitalized at ZUMS hospitals, with an incidence of 697 patients per 100 000 people. Men had a higher rate of stroke incidence (52.06%) compared with women (47.94%). The mean age of patients was 69.3±14.7 years; the mean length of stay was 158.8±270 hours. In the study area, 4 significantly hot spot areas and 4 low-high outliers of stroke were found.
Conclusion: This study showed a high incidence of stroke in Zanjan Province, Iran, from 2012 to 2019. Identifying high-risk areas of stroke is a warning to healthcare authorities and policymakers to focus on major risk factors. It can help to figure out the possible causes of stroke and implement prevention programs to reduce stroke incidence in these areas.

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✅ This study showed a high incidence of stroke in Zanjan Province, Iran, from 2012 to 2019. Identifying high-risk areas of stroke is a warning to healthcare authorities and policymakers to focus on major risk factors. It can help to figure out the possible causes of stroke and implement prevention programs to reduce stroke incidence in these areas.


Type of Study: Original Article | Subject: Epidemiologic studies
Received: 2020/09/9 | Accepted: 2020/11/28 | Published: 2021/04/4

References
1. Johnson CO, Nguyen M, Roth GA, et al. Global, regional, and national burden of stroke, 1990-2016: a systematic analysis for the Global Burden of Disease Study 2016. Lancet Neurol. 2019;18(5):439-58. [DOI:10.1016/S1474-4422(19)30034-1]
2. Farhoudi M, Mehrvar K, Sadeghi-Bazargani H, et al. Stroke subtypes, risk factors and mortality rate in northwest of Iran. Iran J Neurol. 2017;16(3):112-7.
3. Mazaheri S, Beheshti F, Hosseinzadeh A, Mazdeh M, Ghiasian M. Epidemiologic study of cardinal risk factors of stroke in patients who referred to Farshchian hospital of Hamadan during 2014-2015. Avicenna J Clin Med. 2016;22(4):331-7.
4. Borhani-Haghighi A, Safari R, Heydari ST, et al. Hospital mortality associated with stroke in southern iran. Iran J Med Sci. 2013;38(4):314-20.
5. Sridharan SE, Unnikrishnan JP, Sukumaran S, et al. Incidence, types, risk factors, and outcome of stroke in a developing country: the Trivandrum Stroke Registry. Stroke. 2009;40(4):1212-8. [DOI:10.1161/STROKEAHA.108.531293]
6. Mungrue K, Saroop K, Samsundar A, et al. The epidemiology and spatial analysis of stroke in Trinidad and Tobago in the first decade of the 21st century (2000-2009). Health. 2014;06:729-37. [DOI:10.4236/health.2014.68094]
7. Soleimani M, Jalilvand A, Soleimani R. Geographical epidemiology of cardiovascular diseases in Zanjan province: analysis of groups from the international classification of diseases, 10th Revision. J Adv Med Biomed Res. 2020;28(127):90-6. [DOI:10.30699/jambs.28.127.90]
8. Boehme AK, Esenwa C, Elkind MSV. Stroke risk factors, genetics, and prevention. Circ Res. 2017;120(3):472-95. [DOI:10.1161/CIRCRESAHA.116.308398]
9. Engstrom G, Jerntorp I, Pessah-Rasmussen H, Hedblad B, Berglund G, Janzon L. Geographic distribution of stroke incidence within an urban population: relations to socioeconomic circumstances and prevalence of cardiovascular risk factors. Stroke. 2001;32(5):1098-103. [DOI:10.1161/01.STR.32.5.1098]
10. Rheenen S, Watson T, Alexander S, Hill M. An analysis of spatial clustering of stroke types, in-hospital mortality, and reported risk factors in Alberta, Canada, using geographic information systems. Can J Neurol Sci. 2015;42:1-11. [DOI:10.1017/cjn.2015.241]
11. Neuhaus AA, Couch Y, Hadley G, Buchan AM. Neuroprotection in stroke: the importance of collaboration and reproducibility. Brain. 2017;140(8):2079-92. [DOI:10.1093/brain/awx126]
12. Dworkis DA, Marvel J, Sanossian N, Arora S. Neighborhood-level stroke hot spots within major United States cities. Am J Emerg Med. 2020. 38(4):794-98 [DOI:10.1016/j.ajem.2019.06.044]
13. Sánchez Martín JM, Rengifo Gallego J, Morato R. Hot spot analysis versus cluster and outlier analysis: An enquiry into the grouping of rural accommodation in Extremadura (Spain). Int J Geo-Inform. 2019;8:176. [DOI:10.3390/ijgi8040176]
14. Khan D, Rossen LM, Hamilton BE, He Y, Wei R, Dienes E. Hot spots, cluster detection and spatial outlier analysis of teen birth rates in the U.S., 2003-2012. Spat Spatiotemporal Epidemiol. 2017;21:67-75. [DOI:10.1016/j.sste.2017.03.002]
15. Iran SCo. IRAN Statistical yearbook 2016-2017. Tehran: Statistical Center of Iran; 2017.
16. Putaala J, Yesilot N, Waje-Andreassen U, et al. Demographic and geographic vascular risk factor differences in European young adults with ischemic stroke the 15 cities young stroke study. Stroke. 2012;43:2624-30. [DOI:10.1161/STROKEAHA.112.662866]
17. Avan A, Digaleh H, Di Napoli M, et al. Socioeconomic status and stroke incidence, prevalence, mortality, and worldwide burden: an ecological analysis from the Global Burden of Disease Study 2017. BMC Med. 2019;17(1):191. [DOI:10.1186/s12916-019-1397-3]
18. Farghaly W, El-Tallawy H, Shehata G, et al. Epidemiology of nonfatal stroke and transient ischemic attack in Al-Kharga District, New Valley, Egypt. Neuropsychiatr Dis Treat. 2013;9:1785-90. [DOI:10.2147/NDT.S48322]
19. Hosininezhad M , Bakhshayesh B , Moaddabi Y , Hatamyan HR .Investigating the seasonal pattern of stroke incidence and the association between daily stroke occurrences and meteorological factors. J Guilan Univ Med Sci. 2014;23(90):50-8.
20. Jacquez G. Spatial Cluster Analysis. The handbook of geographic information science: S. Fotheringham and J. Wilson. Blackwell Publishing; 2005.
21. Rajan S, Baraniuk S, Parker S, Wu T-C, Bowry R, Grotta J. Implementing a mobile stroke unit program in the United States: Why, how, and how much? JAMA Neurol. 2015; 72(2):229-34 [DOI:10.1001/jamaneurol.2014.3618]

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