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Spatial Models Applied on Modern Epidemiological Research: An Example of Malignant Neoplasms of Larynx, Trachea, Bronchus and Lung

Received: 26 March 2015    Accepted: 26 March 2015    Published: 11 April 2015
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Abstract

Background: The effectiveness of the Greek Health policies is highly doubted, especially in times of economic crisis. We selected a disease associated with one of the highest causes of mortality in Greece to explore this phenomenon. Methods: The number of deaths due to malignant neoplasms of larynx, trachea, bronchus and lung in 2001 and 2006 was used. Mortality rates were analyzed in relation to socioeconomic factors, through Cluster Analysis k-means. Finally, prediction of their variance across the different area of Greece in 2001 and 2006 was fulfilled by the interpolation method of ordinary kriging. Results: Prefectures of the same administrative region are characterised by different behavior while they may match with Prefectures of other administrative regions. In the prediction map, mortality rates range from 0.53 to 1.31, in 2001 and from 0.66 to 1.27, in 2006. There is an increase of mortality from one year to another, especially in some Prefectures that move from low clusters in 2001 to very high ones in 2006. Conclusions: This study outlines the regional and spatial inequalities in health, which could be scientifically revealed through the study of health data and their trends. We suggest the promotion of health maps for communication among public health researchers and decision makers.

DOI 10.11648/j.sjph.s.2015030301.16
Published in Science Journal of Public Health (Volume 3, Issue 3-1, May 2015)

This article belongs to the Special Issue Spatial Analysis and Mathematics in Health Research, During Times of Global Socio-Economic Instability

Page(s) 30-34
Creative Commons

This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.

Copyright

Copyright © The Author(s), 2024. Published by Science Publishing Group

Keywords

Malignant Neoplasms, Mortality Rates, Spatial Models, Kriging-Interpolation, Cluster Analysis

References
[1] L.A.G. Ries, D. Harkins, M. Krapcho, A. Mariotto, B.A. Miller, E.J. Feuer, L. Clegg, M.P. Eisner, M.J. Horner, N. Howlader, M. Hayat, B.F Hankey and B.K. Edwards, Seer Cancer Statistics Review, 1975-2003. National Cancer Institute. Bethesda, http://seer.cancer.gov/csr/1975_2003/, based on November 2005 SEER data submission, posted to the SEER web site, (2006).
[2] J.L.M. Christopher and A.D. Lopez, Mortality by cause for eight regions of the world: Global Burden of Disease Study, The Lancet, 349 (1997) 1269 – 1276.
[3] R. Peto, J. Boreham, A.D. Lopez and M.T.C. Heath, Mortality from tobacco in developed countries: indirect estimation from national vital statistics, The Lancet, 339 (1992) 1268-1278.
[4] F.P. Boscoe, M.H. Ward and P. Reynolds, Current practices in spatial analysis of cancer data: data characteristics and data sources for geographic studies of cancer, International Journal of Health Geographics, 3 (2004) 28.
[5] G.M. Jacquez, Current practices in the spatial analysis of cancer: flies in the ointment, International Journal of Health Geographics, 3 (2004) 22.
[6] F. Buntinx, H. Geys, D. Lousbergh, G. Broeders, E. Cloes, D. Dhollander, L. Op De Beeck, J. Vanden Brande, A. Van Waes and G. Molenberghs, Geographical differences in cancer incidence in the Belgian province of Limburg, European Journal of Cancer, 39 (2003) 2060-2065.
[7] E.A. Freda, Viruses, clusters and clustering of childhood leukaemia: a new perspective? European Journal of Cancer, 29 (1993) 1426-1440.
[8] R.Z. Osmar, Principles of Knowledge Discovery in Databases, Data Clustering: Chapter8, Available at: http://www.cs.ualberta.ca/~zaiane/courses/cmput690/slides/Chapter8/index.html (Accessed: 12 August 2010)
[9] G. Pistolla, P. Prastakos, M. Vassilaki and A. Philalithis, Spatial-Mathematic methods for analysis of indicators of mortality, IJAEST, 2 (2010) 135:14.
[10] S.B. Bell, R.E. Hoskins, L.W. Pickle, and D. Wartenberg, Current practices in spatial analysis of cancer data: mapping health statistics to inform policymakers and the public, International Journal of Health Geographics, 5 (2006) 49.
[11] X. Emery, Simple and Ordinary Kriging Multigaussian Kriging for Estimating recovevearble Reserves, Mathematical Geology, 37 (2005) 295-319.
[12] G.W.A. Heine, Controlled Study of Some Two-Dimensional Interpolation Methods, COGS Computer Contributions, 3 (1986) 60:72.
[13] A.B. McBratney and R. Webster, Choosing Functions for Semi-variograms of Soil Properties and Fitting Them to Sampling Estimates, Journal of Soil Science, 37 (1986) 617:639.
[14] C.A. Pope, R.T. Burnett, M.J. Thun, E.E. Calle, D. Krewski, K. Ito, G.D. Thurston, Lung Cancer, Cardiopulmonary Mortality and Long-term Exposure to Fine Particulate Air Pollution, Journal of American Medical Association, 287 (2002) 1132-1141.
[15] M.A. Oliver, Kriging: A Method of Interpolation for Geographical Information Systems, International Journal of Geographic Information Systems, 4 (1990) 313:332.
[16] M. Anderberg, Cluster Analysis for Applications, (1973) New York :Academic Press.N. Krieger, Place, Space, and Health: GIS and Epidemiology, Epidemiology J, 14 (2003) 384-385.
[17] Hellenic Statistical Authority, 2008. Number of deaths. Available at: http://www.statistics.gr/portal/page/portal/ESYE (Accessed: 10/10/2010)
[18] Greek National cadastre and cartography organization, Greek free geographical data,. Available at: http://geodata.gov.gr/geodata/index.php?option=com_sobi2&catid=16&Itemid=10 (Accessed at: 30/4/2011).
[19] M. Pagano and K. Gauvreau, Principles of Biostatistics, Harvard School of Public Health, (1996) Buhbury Press.
[20] European Commission, Eurostat, 2008-2011. Ε.U Standards for classification. Available at: http://epp.eurostat.ec.europa.eu/portal/page/portal/eurostat/home (Accessed: 10 August 2008)
[21] European Commission, Eurostat, 2008-2011. NUTS 2 level. Available at: http://ec.europa.eu/eurostat/ramon/nuts/codelist_en.cfm?list=nuts , (Accessed: 10 August 2008)
[22] K. Bailey, Cluster Analysis, D.Heise Sociological Methodology, (1975) San Francisco : Jossey- Bass.
[23] E. Crocett and P. Carli, Unexpected reduction of mortality rates from melanoma in males living in central Italy, European Journal of Cancer, 39 (2003) 820:821.
[24] P.N. Post, P.J.M. Kil, M.A. Crommelin , R.F.M. Schapers and J.W.W. Coebergh, Trends in incidence and mortality rates for prostate cancer before and after prostate-specific antigen introduction, A registry-based study in Southeastern Netherlands, 1971–1995, European Journal of Cancer, 34 (1998) 707-709.
[25] H. Van, C.S. Victor, A.P. Adam, N. Ronaldd, W.K. Jonathane, K.P. Davida, K. Sungg and D. Joel, Association of Long-term Air Pollution With Ventricular Conduction and Repolarization Abnormalities, Epidemiology J, 22 (2011) 773-780.
Author Information
  • Epidemiology researcher, GISanalyst, Facutly of Medicine, University of Crete, Iraklion, Crete

  • Mathematician, Facutly of Medicine, University of Crete, Iraklion, Crete

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    Sifaki-Pistolla Dimitra, Pistolla Georgia. (2015). Spatial Models Applied on Modern Epidemiological Research: An Example of Malignant Neoplasms of Larynx, Trachea, Bronchus and Lung. Science Journal of Public Health, 3(3-1), 30-34. https://doi.org/10.11648/j.sjph.s.2015030301.16

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    ACS Style

    Sifaki-Pistolla Dimitra; Pistolla Georgia. Spatial Models Applied on Modern Epidemiological Research: An Example of Malignant Neoplasms of Larynx, Trachea, Bronchus and Lung. Sci. J. Public Health 2015, 3(3-1), 30-34. doi: 10.11648/j.sjph.s.2015030301.16

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    AMA Style

    Sifaki-Pistolla Dimitra, Pistolla Georgia. Spatial Models Applied on Modern Epidemiological Research: An Example of Malignant Neoplasms of Larynx, Trachea, Bronchus and Lung. Sci J Public Health. 2015;3(3-1):30-34. doi: 10.11648/j.sjph.s.2015030301.16

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  • @article{10.11648/j.sjph.s.2015030301.16,
      author = {Sifaki-Pistolla Dimitra and Pistolla Georgia},
      title = {Spatial Models Applied on Modern Epidemiological Research: An Example of Malignant Neoplasms of Larynx, Trachea, Bronchus and Lung},
      journal = {Science Journal of Public Health},
      volume = {3},
      number = {3-1},
      pages = {30-34},
      doi = {10.11648/j.sjph.s.2015030301.16},
      url = {https://doi.org/10.11648/j.sjph.s.2015030301.16},
      eprint = {https://download.sciencepg.com/pdf/10.11648.j.sjph.s.2015030301.16},
      abstract = {Background: The effectiveness of the Greek Health policies is highly doubted, especially in times of economic crisis. We selected a disease associated with one of the highest causes of mortality in Greece to explore this phenomenon. Methods: The number of deaths due to malignant neoplasms of larynx, trachea, bronchus and lung in 2001 and 2006 was used. Mortality rates were analyzed in relation to socioeconomic factors, through Cluster Analysis k-means. Finally, prediction of their variance across the different area of Greece in 2001 and 2006 was fulfilled by the interpolation method of ordinary kriging. Results: Prefectures of the same administrative region are characterised by different behavior while they may match with Prefectures of other administrative regions. In the prediction map, mortality rates range from 0.53 to 1.31, in 2001 and from 0.66 to 1.27, in 2006. There is an increase of mortality from one year to another, especially in some Prefectures that move from low clusters in 2001 to very high ones in 2006. Conclusions: This study outlines the regional and spatial inequalities in health, which could be scientifically revealed through the study of health data and their trends. We suggest the promotion of health maps for communication among public health researchers and decision makers.},
     year = {2015}
    }
    

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  • TY  - JOUR
    T1  - Spatial Models Applied on Modern Epidemiological Research: An Example of Malignant Neoplasms of Larynx, Trachea, Bronchus and Lung
    AU  - Sifaki-Pistolla Dimitra
    AU  - Pistolla Georgia
    Y1  - 2015/04/11
    PY  - 2015
    N1  - https://doi.org/10.11648/j.sjph.s.2015030301.16
    DO  - 10.11648/j.sjph.s.2015030301.16
    T2  - Science Journal of Public Health
    JF  - Science Journal of Public Health
    JO  - Science Journal of Public Health
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    EP  - 34
    PB  - Science Publishing Group
    SN  - 2328-7950
    UR  - https://doi.org/10.11648/j.sjph.s.2015030301.16
    AB  - Background: The effectiveness of the Greek Health policies is highly doubted, especially in times of economic crisis. We selected a disease associated with one of the highest causes of mortality in Greece to explore this phenomenon. Methods: The number of deaths due to malignant neoplasms of larynx, trachea, bronchus and lung in 2001 and 2006 was used. Mortality rates were analyzed in relation to socioeconomic factors, through Cluster Analysis k-means. Finally, prediction of their variance across the different area of Greece in 2001 and 2006 was fulfilled by the interpolation method of ordinary kriging. Results: Prefectures of the same administrative region are characterised by different behavior while they may match with Prefectures of other administrative regions. In the prediction map, mortality rates range from 0.53 to 1.31, in 2001 and from 0.66 to 1.27, in 2006. There is an increase of mortality from one year to another, especially in some Prefectures that move from low clusters in 2001 to very high ones in 2006. Conclusions: This study outlines the regional and spatial inequalities in health, which could be scientifically revealed through the study of health data and their trends. We suggest the promotion of health maps for communication among public health researchers and decision makers.
    VL  - 3
    IS  - 3-1
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