Abstract
In the world, cardiovascular diseases (CVD) are known as the type of disease with the highest mortality. The mortality rate for this disease is very high in Turkey. Therefore, studies on this disease may direct the activities to be carried out by public health workers/policy makers and effective surveillance studies. In this context, GIS-based spatial analysis offers critical tools to reveal the spatial epidemiology of the disease by modeling the spatial distribution of cardiovascular disease over time and to investigate the risk factors.
In this study, it was aimed to analyze CVD mortality spatiotemporally with GIS-based methodologies and to reveal preliminary information on whether deaths from CVD are related to geographic location and environmental risk factors. Accordingly, CVD mortality that occurred in Turkey at province level between 2009 and 2018 was analyzed through spatial statistical tests (Global Moran's I, Getis-Ord General G, Anselin Local Morans I and Getis-Ord Gi*) and Geographical Information Systems (GIS). The results of spatiotemporal analysis were evaluated. Mortality caused by CVD was examined spatiotemporally with the help of the developed user interface program and spatially significant clusters of CVD were determined. Based on our findings, this study can contribute to understand the spatial nature of the disease and to provide the decision makers with required information on surveillance studies.
This is a preview of subscription content, log in via an institution to check access.
Similar content being viewed by others
References
Akçın, H., Şekertekin, A. (2016). Sürdürülebilir Havza Yönetimi İçin Kömüre Dayalı Kirliliğin Landsat 8 Görüntüleri Ve Jeoistatistiksel Analizlerle Zamansal İncelenmesi. Uzaktan Algılama-CBS Sempozyumu (UZAL-CBS 2016). 76–85. 5–7 Ekim 2016. Adana.
Affan, M., Syukri, M., Wahyuna, L., & Sofyan, H. (2016). Spatial statistic analysis of earthquakes in Aceh province year 1921–2014: cluster seismicity. Aceh International Journal of Science and Technology, 5(2), 54–62. https://doi.org/10.13170/aijst.5.2.4878
Almendra, R., & Santana, P. (2020). Mortality from cardiovascular diseases in the municipalities of mainland Portugal: spatiotemporal evolution between 1991 and 2017. Geogrsphy, Environment, Sustainability, 13, 128–133. https://doi.org/10.24057/2071-9388-2020-06.
Amsalu, E., Liu, M., Li, Q., Wang, X., Tao, X., Liu, X. et al (2019). Spatial-temporal analysis of cause-specific cardiovascular hospital admission in Beijing, China International Journal of Environmental Health Research,1–12 https://doi.org/10.1080/09603123.2019.1677862
Anselin, L. (1995). Local Indicators of Spatial Association—LISA. Geographical Analysis., 27, 93–115. https://doi.org/10.1111/j.1538-4632.1995.tb00338.x
Bendib, A (2020). The effects of spatial clustering of public facilities on social equity and urban congestion in the city of Batna (Algeria) GeoJournal, 1–14 https://doi.org/10.1007/s10708-020-10289-y
Çağlar, O. (2019). Spatial Analysis of A Viral Agent First Time Appeared In Turkey By Geographic Information System: Cattle Noduler Exhantem (Lumpy Skin Disease-LSD), Hacettepe University Graduate School of Health Sciences Epidemiology Program Master of Science Thesis, Ankara.
Caprarelli, G., & Fletcher, S. (2014). A brief review of spatial analysis concepts and tools used for mapping, containment and risk modelling of infectious diseases and other illnesses. Parasitology, 141(5), 581–601. https://doi.org/10.1017/S0031182013001972
Cromley, E. K., & McLafferty, S. L. (2011). GIS and public health. Guilford Press.
David, R. M. (2017). Exploring spatial patterns and hotspots of hepatitis A and amoebic dysentery using GIS and geostatistical analysis in Turkey (Doctoral dissertation).
De Andrade, L., Zanini, V., Batilana, A. P., De Carvalho, E. C., Pietrobon, R., Nihei, O. K., & De Barros Carvalho, M. D. (2013). Regional disparities in mortality after ischemic heart disease in a Brazilian state from 2006 to 2010. PLoS ONE, 8, 19. https://doi.org/10.1371/journal.pone.0059363
Dokmeci, A. H. (2017). Evaluation of heavy metal pollution in the ergene river basin from a public health perspective. Turkish Journal of Public Health, 15(3), 212–221
Elliott, P., Wakefield, J.C. Best, N. G., Briggs, D. J. (2001) Spatial epidemiology: methods and applications Spatial Epidemiology, 3–14 https://doi.org/10.1093/acprof:oso/9780198515326.003.00
Ford MM, Highfield LD. 2016. Exploring the spatial association between social deprivation and cardiovascular disease mortality at the neighborhood level. PLoS One, 11(1). https://doi.org/10.1371/journal.pone.0146085
Fu, W. J., Jiang, P. K., Zhou, G. M., & Zhao, K. L. (2014). Using Moran’s I and GIS to study the spatial pattern of forest litter carbon density in a subtropical region of southeastern China. Biogeosciences, 11, 2401–2409. https://doi.org/10.5194/bg-11-2401-2014
Garipağaoğlu, N. (2003). Türkiye’de Hava Kirliliği Sorununun Coğrafi Bölgelere Göre Dağılımı. Doğu Coğrafya Dergisi., 9, 57–77
Gelman, A., Price P. N. (1999). All maps of parameter estimates are misleading Statistics in Medicine 18 3221 3234 3.0.co;2-m",1,0,0>https://doi.org/10.1002/(sici)1097-0258(19991215)18:23<3221::aid-sim312>3.0.co;2-m
Getis, A., & Ord, J. (1992). The Analysis of Spatial Association by Use of Distance Statistics. Geographical Analysis., 24, 189–206. https://doi.org/10.1007/978-3-642-01976-0_10
Gohari, K., Parsaeian, M., Sheidaei, A., Rahimzadeh, S., Baghestani, A. R., Pourhoseinghol, M. A., Pazhuheian, F., Saeedi Moghaddam, S., Mansouri, A., Naderimagham, S., Kavousi, A., & Farzadfar, F. (2015). Equity chasm in megacities: five leading causes of death in Tehran. Archives of Iranian Medicine, 18, 622–628
Gomez-Barroso, D., Prieto-Flores, M. E., Mellado San Gavino, A., & Moreno Jimenez, A. (2015). Spatial analysis of mortality from cardiovascular diseases in Madrid City, Spain. Revista Española de Salud Pública, 89, 27–37. https://doi.org/10.4321/s1135-57272015000100004
Horst, M. A., & Coco, A. S. (2010). Observing the spread of common illnesses through a community: using Geographic Information Systems (GIS) for surveillance. Journal of the American Board of Family Medicine, 23(1), 32–41. https://doi.org/10.3122/jabfm.2010.01.090137
Ibret, B., & Aydınözü, D. (2010). Şehirleşmede yanlış yer seçiminin hava kirliliği üzerine olan etkisine bir örnek: Kastamonu şehri. Coğrafya Dergisi, 0(18), 71–88.
Ince, O. B., & Turk, T. (2019). Analyzing risk factors for lumpy skin disease by a geographic information system (GIS) in Turkey. Journal of the Hellenic Veterinary Medical Society, 70(4), 1797–1804. https://doi.org/10.12681/jhvms.22222
James, W. L., Cossman, R. E., Cossman, J. S., Campbell, C., & Blanchard, T. (2004). A brief visual primer for the mapping of mortality trend data. International journal of health geographics, 3(1), 7. https://doi.org/10.1186/1476-072X-3-7
Kirby, R. S., Delmelle, E., & Eberth, J. M. (2017). Advances in spatial epidemiology and geographic information systems. Annals of epidemiology, 27(1), 1–9. https://doi.org/10.1016/j.annepidem.2016.12.001
Kocaman, H, Akın, Y, Oğuzhan, A. (2011). Trakya’da Ergene Nehri Kirliliğinin Tarım Üretimine Olan Etkisi: Edirne Örneği . Karadeniz Fen Bilimleri Dergisi, 2(3), 89–104. Retrieved from https://dergipark.org.tr/tr/pub/kfbd/issue/22231/238648
Kurland, K. S., Gorr, W. L., (2007). GIS tutorial for health. Retrieved from https://books.google.com.tr/books?hl=tr&lr=&id=nCwMpoA5l2gC&oi=fnd&pg=PT12&dq=GIS+tutorial+for+health&ots=QVuKmE5tnz&sig=LFrDQ_IOJgUE2CEOGPFU136fMxw&redir_esc=y#v=onepage&q=GIS%20tutorial%20for%20health&f=false
Leiva, M., Santibañez, D., Ibarra, E. S., Matus, C. P., & Seguel, R. (2013). A Five-Year Study of Particulate Matter (PM2.5) and Cerebrovascular Diseases. Environmental Pollution., 181, 1–6. https://doi.org/10.1016/j.envpol.2013.05.057
Li, Y., Rittenhouse-Olson, K., Scheider, W. L., & Mu, L. (2012). Effect of particulate matter air pollution on C-reactive protein: a review of epidemiologic studies. Reviews on Environmental Health, 27, 133–149. https://doi.org/10.1515/reveh-2012-0012
Lim, Y. R., Bae, H. J., Lim, Y. H., Yu, S., Kim, G. B., & Cho, Y. S. (2014). Spatial analysis of PM10 and cardiovascular mortality in the Seoul metropolitan area. Environ Health Toxicol, 29, 1–7. https://doi.org/10.5620/eht.2014.29.e2014005
McLaughlin, C. C., & Boscoe, F. P. (2007). Effects of randomization methods on statistical inference in disease cluster detection. Health & place., 13(1), 152–163. https://doi.org/10.1016/j.healthplace.2005.11.003
Mena, C., Sepulveda, C., Fuentes, E., Ormazabal, Y., & Palomo, I. (2018). Spatial analysis for the epidemiological study of cardiovascular diseases: A systematic literature search. Geospatial Health, 13, 587. https://doi.org/10.4081/gh.2018.587
Mitchell, A. (2005). The ESRI guide to GIS analysis, spatial measurements. ESRI.
Mortimer, K., Gordon, S. B., Jindal, S. K., Accinelli, R. A., Balmes, J., & Martin, W. J. (2012). Household Air Pollution Is a Major Avoidable Risk Factor for Cardiorespiratory Disease. Chest, 142, 1308–1315. https://doi.org/10.1378/chest.12-1596
Namayande, M. S., Nejadkoorki, F., Namayande, S. M., & Dehghan, H. (2016). Spatial hotspot analysis of acute myocardial infarction events in an urban population: a correlation study of health problems and industrial installation. Iran J Pub Health, 45, 94–101
Ord, J. K., & Getis, A. (1995). Local spatial autocorrelation statistics: distributional issues and an application. Geographical Analysis, 27, 286–306. https://doi.org/10.1111/j.1538-4632.1995.tb00912.x
Open. (2016). Epidemiology: An introduction. The Open University. http://www.open.edu/openlearn/science-maths-technology/science/health-sciences/epidemiologyintroduction/content-section-0?utm_source=openlearnutm_campaign=olutm_medium=ebook
Rajabi, M., Mansourian, A., Pilesjo, P., Astrom, D. O., Cederin, K., & Sundquist, K. (2018). Exploring spatial patterns of cardiovascular disease in Sweden between 2000 and 2010. Scand J Public Health., 46, 647–658. https://doi.org/10.1177/1403494818780845
Requia, W., & Roig, H. (2015). Analyzing Spatial Patterns of Cardiorespiratory Diseases in the Federal District. Brazil. Health., 07, 1283–1293. https://doi.org/10.4236/health.2015.710143
Ruiz, M. O., Tedesco, C., Austin, M. T. J., & C, Kitron U. . (2004). Environmental and social determinants of human risk during a West Nile virus outbreak in the greater Chicago area, 2002. International Journal of Health Geographics, 3(1), 8. https://doi.org/10.1186/1476-072X-3-8
Ruzicka, L. T., & Lopez, A. D. (1990). The use of cause-of-death statistics for health situation assessment: national and international experiences Wid hlth stattst., 43, 249–258.
TurkStat. (2018). Turkish Statistical Institute official homepage. Retrieved from https://www.tuik.gov.tr.
Türk, T. (2013). Investigating environmental health studies using geographical information systems: cancer case study. Polish Journal of Environmental Studies., 22, 1505–1517.
WHO. (2018). The top 10 causes of death. Why do we need to know the reasons people die? World Health Organization. Retrieved from https://www.who.int/news-room/fact-sheets/detail/the-top-10-causes-of-death.
Waller, L. A., Gotway, C. A. (2004). Applied spatial statistics for public health data. Hoboken (NJ, USA) John Wiley & Sons, Inc. (Wiley Series in Probability and Statistics). Retrieved from https://doi.org/10.1002/0471662682.
Yalçın, M., & Kaya, K. (2019). Türkiye’de Solunum Sistemine Bağlı Ölüm Oranlarının Mekansal Kümelenmelerinin İncelenmesi. Afyon Kocatepe Üniversitesi Fen ve Mühendislik Bilimleri Dergisi, 19(3), 750–761.
Zhang, C., Luo, L., Xu, W., & Ledwith, V. (2008). Use of local Moran’s I and GIS to identify pollution hotspots of Pb in urban soils of Galway. Ireland. Science of the total environment, 398(1–3), 212–221. https://doi.org/10.1016/j.scitotenv.2008.03.011.
Zhang, L., Qin, L. Q., Cui, H. Y., Liu, A. P., & Wang, P. Y. (2011). Prevalence of cardiovascular risk factors clustering among suburban residents in Beijing. China. Int J Cardiol., 151, 46–49. https://doi.org/10.1016/j.ijcard.2010.04.056.
Acknowledgement
The authors would like to thank the Turkey Statistical Institute because it provides data.
Author information
Authors and Affiliations
Corresponding author
Additional information
Publisher's Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Rights and permissions
About this article
Cite this article
ŞENER, R., Türk, T. Spatiotemporal Analysis of Cardiovascular Disease Mortality with Geographical Information Systems. Appl. Spatial Analysis 14, 929–945 (2021). https://doi.org/10.1007/s12061-021-09382-7
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s12061-021-09382-7