A combined approach to geostatistical models and spatial information systems to evaluate the role of spatial parameters in the prevalence of cancer in Iran: a case study: bladder cancer

Vafaeinejad, Alireza; Soleimani matin, sahar; Haery, sana

doi:10.61186/jgst.14.1.13

[Home ] [Archive]

[ فارسی ]

Journal of Geomatics Science and Technology

Main Menu

Home

Browse

Journal Info

Guide for Authors

Submit Manuscript

Articles archive

For Reviewers

Contact us

Site Facilities

Reviewers

Search in website

Receive site information

Volume 14, Issue 1 (9-2024)

JGST 2024, 14(1): 13-24

Back to browse issues page

A combined approach to geostatistical models and spatial information systems to evaluate the role of spatial parameters in the prevalence of cancer in Iran: a case study: bladder cancer

Alireza Vafaeinejad ^*

, Sahar Soleimani matin

, Sana Haery

Abstract: (179 Views)

According to the statistics of the World Health Organization, about 7.6 million people die from cancer every year, which is 70% of all deaths in low- and middle-income countries. It is also estimated that this number will reach more than 13 million people by 2030. Since the rate of cancer is increasing and the issues related to the spread of diseases, especially cancer, are directly related to geography and environment, this issue has been considered for a long time. The aim of this study is to develop statistical location models and use spatial information system to evaluate the role of spatial parameters and environmental factors in the prevalence of bladder cancer in the provinces of Iran. According to the statistical analysis of bladder cancer data in Iranian provinces, it was found that Yazd and Sistan-Baluchestan provinces have the highest and lowest incidence rates of bladder cancer in Iran, respectively. Also, by setting a minimum value and considering the global average of bladder cancer as a threshold, it was found that the rate of bladder cancer is low in 23% of the provinces, average in 30% of them, and higher than the global average in the remaining 47%. Bladder cancer, as one of the common public health problems in Iran, has a heterogeneous distribution in the country. Using random forest algorithm, this study examines the spatial distribution of bladder cancer in Iran and predicts its incidence in different regions. The results show that the random forest algorithm predicts the incidence of bladder cancer throughout Iran with considerable accuracy. Running the model on about 30% of the test data showed that the actual value of the data was predicted with an accuracy of 0.62. Finally, by implementing a statistical model, the risk factors of this disease are ranked and the rate of bladder cancer in the country is predicted. According to the results of this study, because the hot spots of bladder cancer are located in the central provinces of Iran, especially Isfahan, Chaharmahal and Bakhtiari provinces, it is suggested to conduct more detailed medical and statistical research in this field.

Article number: 2

Keywords: Spatial Information System, Geostatistics, Bladder Cancer, Iran

Full-Text [PDF 925 kb] (79 Downloads)

Type of Study: Research | Subject: GIS
Received: 2024/06/10

References

1. Karami J, Delfan S, Shamsoddini A. Role of Time in Spatial Analysis of Diseases in Tehran. JGST 2016; 5, 4 PP. 227-238. (in Persian).

2. Baghi,F ,. Balaz,F ,. Jajic,I ,. Stojsin,V ,. (2008) "Mycotoxin content in different parts of Fusarium infected wheat heads." 3rd Int. FHB Symposium Szeged,36, PP. 341-342.

3. Stillwell,J.,Karikari,I., Stillwell,J, Carver,S,(2003), "Land administration and GIS: the case of Ghana." Progress in Development Studies, 3, 3. PP.223-242. [DOI:10.1191/1464993403ps050ra]

4. Elliott,P, Wakefield,J, Best,N,. and Briggs, D, (2000) "Spatial Epidemiology: Methods and Applications.", International Journal of Epidemiology, 30, 5, PP.1204-1205.

5. Alexander, F., Freda E. T. James Ricketts, Joan Williams, Ray A, (1991). "Methods of mapping and identifying small clusters of disease with applications to geograhical epidemiology." Geographical Analysis., 23. PP. 156-173. [DOI:10.1111/j.1538-4632.1991.tb00231.x]

6. Hashemian,M ,. poustchi,H, Mohammadi NasrAbadi,F,. Sharafhkah,M ,. Fazeltabar,A ,. Hekmatdoost,A ,. Malekzadeh,R. (1395). "Manganese intake and the risk of esophageal cancer in the Golestan cohort study." Digestion, 21,1, PP.20-26, (in Persian).

7. Botteman,F,. , Pashos,C,. , Redaelli,A,. Laskin,B ,. Hauser,R ,. (2003), "The health economics of bladder cancer: a comprehensive review of the published literatur." Pharmacoeconomics ,21,18, PP.1315-30. [DOI:10.1007/BF03262330]

8. Bindu, A., Janak, P. (2012). "GIS IN EPIDEMIOLOGY: APPLICATIONS AND SERVICES." National Journal of Community Medicine. 259, 3, PP.259,263.

9. Elebead, F., Amna, H. Saad Hilmi, H., and Galal, H. (2012). "Mapping Cancer Disease Using Geographical Information System (GIS) in Gezira State-Sudan." Journal of Community Health., 37. PP. 830-839. [DOI:10.1007/s10900-011-9517-9]

10. Akbari,M, Naghibzade-Tahami. Khanjani,N ,.Baneshi,M,. Kamali, E, Hesampour,M,.and Haghdoost,A. (2015). "Opium as a Risk Factor for Bladder Cancer: A Population-based Case-control Study in Iran", Arch Iran Med., 18. PP. 567- 571.

11. Masoumi,Z ,. Mesgari,M ,. (1385). "Fitting a spatial-statistical model on skin cancer incidence in order to support decision making." Geomatic conference, 85, (in Persian).

12. Khademi,N, Reshadat,S. and Zangeneh, A. (2016). "Identifying HIV distribution pattern based on clustering test using GIS software, Kermanshah, Iran." HIV & AIDS Review. 15(4), PP. 147-152. [DOI:10.1016/j.hivar.2016.11.003]

13. Zoungrana, M. Andrianisa, H. Yonaba, B. Mabia, A. Thiam, S. and Bonki, B. (2024). "A GIS-based approach for improving urban sanitation planning and services delivery: A case study from Ouagadougou, Burkina Faso." Habitat International. 143, 102993. PP. [DOI:10.1016/j.habitatint.2023.102993]

14. Yomralioglu, T., Colak, E., Aydinoglu, A. (2009). "Geo-Relationship between Cancer Cases and the Environment by GIS: A Case Study of Trabzon in Turkey" Int J Environ Res Public Health., 6. PP. 3190-3204. [DOI:10.3390/ijerph6123190]

15. Niculita-Hirzel, H. Hirzel, A. Wild, P. (2024). "A GIS-based approach to assess the influence of the urban built environment on cardiac and respiratory outcomes in older adults." Building and Environment, 253. PP. [DOI:10.1016/j.buildenv.2024.111362]

16. Smith, N, Prasad, S, Patel, A, Weiner, A, Pariser, J, Razmara, Maene, C, Schuble, T, Pierce, B, Steinberg, D, (2016). "Bladder Cancer Mortality in the United States: A Geographic andTemporal Analysis of Socioeconomic and Environmental Factors." The Journal of Urology, 195,2. PP.290-296. [DOI:10.1016/j.juro.2015.07.091]

17. Atabi, F., Mirzahosseini, S. (2013). "GIS based assessment of cancer risk due to benzene in Tehran Ambient air." Int J Occup Med Environ Health., 26. PP. 770-779. [DOI:10.2478/s13382-013-0157-4]

18. Razavi-Termeh, S. Sadeghi-Niaraki,A . Choi, S. "Coronavirusdisease vulnerability map using a geographic information system (GIS) from 16 April to 16 May 2020." Physics and Chemistry of the Earth ,126,103043.PP. [DOI:10.1016/j.pce.2021.103043]

19. Mohammadbeigi A. Saghafipour, A. Jesri, N. Tarkhan. F. Karami and Jooshin,M . (2020). "Spatial distribution of vaccine-preventable diseases in central Iran in 2015-2018: A GIS-based study." Physics and Chemistry of the Earth, Parts A/B/C. 126, 12. PP. [DOI:10.1016/j.heliyon.2020.e05102]

20. Kumar,V, Sundaram,D,. Sebastian,G ,and Lakshmanan,J. (2016). "Spatial mapping of acute diarrheal disease using GIS and estimation of relative risk using empirical Bayes approach." Clinical Epidemiology and Global Health. PP. 87-92. [DOI:10.1016/j.cegh.2016.07.004]

21. Matin,S ,. Chehreh Chelgani,S . (2016). "Estimation of coal gross calorific value based on various analyses by random forest method," Fuel, 177. PP. 274-278. [DOI:10.1016/j.fuel.2016.03.031]

22. Matin,S , Hower,J ,. Frahzadi,L ,. and Chehreh,S (2016). "Explaining relationships among various coal analyses with coal grindability index by Random Forest." International Journal of Mineral Processing.155, PP. 140-146. [DOI:10.1016/j.minpro.2016.08.015]

23. Chehreh Chelgani,S ,. Matin,S ,. (2016). "Explaining relationships between coke quality index and coal properties by Random Forest method." Fuel., 182, PP. 754-760. [DOI:10.1016/j.fuel.2016.06.034]

24. Chehreh Chelgani,S ,. , Matin,S. and Makaremi,S ,. (2016). "Modeling of free swelling index based on variable importance measurements of parent coal properties by random forest method, Measurement." Measurement, 94, PP. 416-422. [DOI:10.1016/j.measurement.2016.07.070]

25. Akyol., Calik, E, Bayir, S, Sen, B, and Cavusoglu, A. (2015). "Analysis of Demographic Characteristics Creating Coronary Artery Disease Susceptibility using Random Forests Classifier." Procedia Computer Science, 62. PP. 39-46. [DOI:10.1016/j.procs.2015.08.407]

26. Cromely,A , McLafferty,S. (2012) "Public participation GIS and community health GIS and public health." Public health, PP. 411-422.

27. Djukpen,R .(2012). "Mapping the HIV/AIDS epidemic in Nigeria using exploratory spatial data analysis". GeoJournal, 77, PP. 555-569. [DOI:10.1007/s10708-010-9350-1]

28. Burger,M , Catto,J,. Dalbagni,G, Grossman,H , Herr,H, Karakiewicz,P,. Kassouf, W, Kiemeney, L, Vecchia,C, Shariat,SH, and Lotan,Y,. (2013). "Epidemiology and Risk Factors of Urothelial Bladder Cancer." 63,2, PP. 234-241. [DOI:10.1016/j.eururo.2012.07.033]

Send email to the article author

Add your comments about this article

‎ 10.61186/jgst.14.1.13

Mendeley

Zotero

RefWorks

Vafaeinejad A, Soleimani matin S, Haery S. A combined approach to geostatistical models and spatial information systems to evaluate the role of spatial parameters in the prevalence of cancer in Iran: a case study: bladder cancer. JGST 2024; 14 (1) : 2
URL: http://jgst.issgeac.ir/article-1-1186-en.html

Rights and permissions
	This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.

Volume 14, Issue 1 (9-2024)

Back to browse issues page