Geographical Variation of Incidence of Chronic Obstructive Pulmonary Disease in Manitoba, Canada
Abstract
:1. Introduction
2. Methods
2.1. Study Subjects
2.2. Weighting Process
2.3. Specific Hypotheses
3. Results
Region | Method | ||||||||
---|---|---|---|---|---|---|---|---|---|
LISA | CSS | FSS | RR > 1.0 | RR > 1.5 | RR > 2.0 | ||||
BYM | MLE | BYM | MLE | BYM | MLE | ||||
1 | - | - | 3 | 13 | 11 | - | - | - | - |
2 | 1 | - | - | - | - | - | - | - | - |
3 | - | - | - | 11 | 13 | - | - | - | - |
6 | - | - | - | 5 | 5 | 5 | 5 | - | - |
7 | 12 | - | - | - | - | - | - | - | - |
10 | - | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 |
11 | - | - | 1 | 15 | 15 | - | - | - | - |
12 | - | - | 1 | 10 | 10 | - | - | - | - |
13 | - | - | 1 | - | - | - | - | - | - |
14 | - | - | 1 | - | - | - | - | - | - |
16 | 9 | - | - | - | - | - | - | - | - |
20 | - | - | 1 | 4 | 4 | 4 | 4 | - | - |
21 | - | - | 1 | 14 | 14 | - | - | - | - |
24 | 7 | - | - | 6 | 6 | 6 | 6 | - | - |
27 | - | - | 2 | 12 | 12 | - | - | - | - |
43 | 2 | 3 | 2 | 2 | 2 | 2 | 2 | 2 | 2 |
45 | - | 3 | 2 | 7 | 8 | - | - | - | - |
46 | - | - | 2 | - | - | - | - | - | - |
50 | - | - | 2 | 3 | 3 | 3 | 3 | - | - |
51 | - | - | 2 | - | - | - | - | - | - |
54 | - | - | 2 | 17 | 17 | - | - | - | - |
56 | 6 | - | 3 | - | - | - | - | - | - |
57 | 4 | - | - | - | - | - | - | - | - |
58 | 5 | - | - | - | - | - | - | - | - |
60 | 8 | - | 3 | - | - | - | - | - | - |
61 | - | 2 | 3 | 18 | 18 | - | - | - | - |
62 | 3 | 2 | 1 | 8 | 7 | - | - | - | - |
64 | 11 | - | 3 | 9 | 9 | - | - | - | - |
65 | - | - | 3 | 16 | 16 | - | - | - | - |
67 | 10 | - | - | - | - | - | - | - | - |
4. Discussion and Conclusions
Acknowledgments
Author Contributions
Conflicts of Interest
Appendix
Circular Spatial Scan Statistic (CSS)
Flexible Spatial Scan Statistic (FSS)
Bayesian Disease Mapping (BYM)
Frequentist Approach Using Maximum Likelihood Estimation (MLE)
Prediction of Relative Risk:
Local Indicator of Spatial Association (LISA)
References
- Global Initiative for Chronic Obstructive Lung Disease (GOLD). Global Strategy for the Diagnosis, Management and Prevention of COPD. (updated 2013). Available online: http://www.goldcopd.org (accessed on 3 July 2013).
- Eisner, M.D.; Anthonisen, N.; Coultas, D.; Kuenzli, N.; Perez-Padilla, R.; Postma, D.; Romieu, I.; Silverman, E.K.; Balmes, J.R. An official American Thoracic Society public policy statement: Novel risk factors and the global burden on chronic obstructive pulmonary disease. Amer. J. Respir. Crit. Care Med. 2010, 182, 693–718. [Google Scholar] [CrossRef]
- Sezer, H.; Akkurt, I.; Guler, N.; Marakoğlu, K.; Berk, S. A case-control study on the effect of exposure to different substances on the development of COPD. Ann. Epidemiol. 2006, 16, 59–62. [Google Scholar] [CrossRef] [PubMed]
- Burt, L.; Corbridge, S. COPD exacerbations. Amer. J. Nurs. 2013, 113, 34–43. [Google Scholar] [CrossRef]
- Lamprecht, B.; McBurnie, M.A.; Vollmer, W.M.; Gudmundsson, G.; Welte, T.; Nizankowska-Mogilnicka, E.; Studnicka, M.; Bateman, E.; Anto, J.M.; Burney, P.; et al. COPD in never smokers: Results from the population-based burden of obstructive lung disease study. Chest 2011, 139, 752–763. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Canadian Thoracic Society. The Human and Economic Burden of COPD: A Leading Cause of Hospital Admission in Canada; Canadian Thoracic Society: Ottawa, ON, Canada, 2010. [Google Scholar]
- Canadian Institute of Health Information. Health Indicators 2008. Available online: https://secure.cihi.ca/free_products/HealthIndicators2008_ENGweb.pdf (accessed on 3 July 2013).
- Mittmann, N.; Kuramoto, L.; Seung, S.J.; Haddon, J.M.; Bradley-Kennedy, C.; FitzGerald, J.M. The cost of moderate and severe COPD exacerbations to the Canadian healthcare system. Respir. Med. 2008, 102, 413–421. [Google Scholar] [CrossRef] [PubMed]
- Scheinfeld, M.H.; Maniatis, T.; Gurell, D. COPD? Amer. J. Med. 2006, 119, 839–842. [Google Scholar] [CrossRef]
- Lawson, A.B. Statistical Methods in Spatial Epidemiology, 2nd ed.; John Wiley & Sons, Ltd.: London, UK, 2006. [Google Scholar]
- Jennings, J.M.; Curriero, F.C.; Celentano, D.; Ellen, J.M. Geographic identification of high gonorrhea transmission areas in Baltimore, Maryland. Amer. J. Epidemiol. 2005, 161, 73–80. [Google Scholar] [CrossRef]
- Elliott, P.; Briggs, D.; Morris, S.; de Hoogh, C.; Hurt, C.; Jensen, T.K.; Maitland, I.; Richardson, S.; Wakefield, J.; Jarup, L. Risk of adverse birth outcomes in populations living near landfill sites. Brit. Med. J. 2001, 323, 363–368. [Google Scholar] [CrossRef] [PubMed]
- Lawson, A.B.; Biggeri, A.; Williams, F.L.R. A review of modeling approaches in health risk assessment around putative sources. In Disease Mapping and Risk Assessment for Public Health; Lawson, A.B., Biggeri, A., Böhning, D., Lesaffre, E., Viel, J., Bertollini, R., Eds.; Wiley: New York, NY, USA, 1999; pp. 231–245. [Google Scholar]
- Besag, J.E.; York, J.C.; Mollìe, A. Bayesian image restoration with two applications in spatial statistics (with discussion). Ann. Inst. Stat. Math. 1991, 43, 1–59. [Google Scholar] [CrossRef]
- Clayton, D.; Bernardinelli, L. Bayesian methods for mapping disease risk. In Geographical and Environmental Epidemiology: Methods for Small-Area Studies; Elliott, P., Cuzick, J., English, D., Stern, R., Eds.; Oxford University Press: Oxford, UK, 1996; pp. 205–220. [Google Scholar]
- Clayton, D.; Kaldor, J. Empirical Bayes estimates of age-standardized relative risks for use in disease mapping. Biometrics 1987, 43, 671–681. [Google Scholar] [CrossRef] [PubMed]
- Kulldorff, M. A spatial scan statistics. Commun. Statist. A—Theor. Method. 1997, 26, 1481–1496. [Google Scholar]
- Tango, T.; Takahashi, K. A flexibly shaped spatial scan statistic for detecting clusters. Int. J. Health Geogr. 2005, 4, 1–15. [Google Scholar] [CrossRef] [PubMed]
- Besag, J.E.; Newell, J. The detection of clusters in rare diseases. J. R. Stati. Soc. Ser. A 1991, 154, 143–155. [Google Scholar] [CrossRef]
- Torabi, M.; Rosychuk, R.J. Spatial event cluster detection using an approximate normal distribution. Int. J. Health Geogr. 2008, 7, 1–22. [Google Scholar] [CrossRef] [PubMed]
- Tango, T. A test for spatial disease clustering adjusted for multiple testing. Stat. Med. 2000, 19, 191–204. [Google Scholar] [CrossRef] [PubMed]
- Torabi, M.; Rosychuk, R.J. An examination of five spatial disease clustering methodologies for the identification of childhood cancer clusters in Alberta, Canada. Spat. Spatiotemporal Epidemiol. 2011, 2, 321–330. [Google Scholar] [CrossRef] [PubMed]
- Lele, S.R.; Dennis, B.; Lutscher, F. Data cloning: Easy maximum likelihood estimation for complex ecological models using Bayesian Markov chain Monte Carlo methods. Ecol. Lett. 2007, 10, 551–563. [Google Scholar] [CrossRef] [PubMed]
- Lele, S.R.; Nadeem, K.; Schmuland, B. Estimability and likelihood inference for generalized linear mixed models using data cloning. J. Am. Stat. Assoc. 2010, 105, 1617–1625. [Google Scholar] [CrossRef]
- Torabi, M. Spatial disease cluster detection: An application to childhood asthma in Manitoba, Canada. J. Biom. Biostat. 2012. [Google Scholar] [CrossRef]
- Anselin, L. Local indicators of spatial association—LISA. Geogr. Anal. 1995, 2, 93–115. [Google Scholar]
- Statistics Canada. Canadian Community Health Survey User Guide (2001–2010); Statistics Canada: Ottawa, ON, Canada, 2010. [Google Scholar]
- McCullagh, P.; Nelder, J.A. Generalized Linear Models, 2nd ed.; Chapman and Hall: London, UK, 1989. [Google Scholar]
- Richardson, S.; Thomson, A.; Best, N.; Elliott, P. Interpreting posterior risk estimates in disease-mapping studies. Environ. Health Perspect. 2004, 112, 1016–1025. [Google Scholar] [CrossRef] [PubMed]
- Banerjee, S.; Gelfand, A.E.; Carlin, B.P. Hierarchical Modeling and Analysis for Spatial Data; Chapman and Hall: London, UK, 2004. [Google Scholar]
- Fransoo, R.; Martens, P.; Burland, E. The Need to Know Team; Prior, H., Burchill, C., Eds.; Manitoba Centre for Health Policy, Manitoba RHA Indicators Atlas: Winnipeg, MB, Canada, 2009. [Google Scholar]
- Fukuda, Y.; Umezaki, M.; Nakamura, K.; Takano, T. Variations in social characteristics of spatial disease clusters: Examples of colon, lung and breast cancer in Japan. Int. J. Health Geogr. 2005, 4, 1–13. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Kulldorff, M.; Rand, K.; Gherman, G.; Williams, G.; DeFrancesco, D. SaTScan V2.1: Software for the Spatial and Space-Time Scan Statistics; National Centre Institute: Bethesda, MD, USA, 1998. [Google Scholar]
- Takahashi, K.; Yokoyama, T.; Tango, T. FleXScan: Software for the Flexible Scan Statistic; National Institute of Public Health: Nagoya, Japan, 2006. [Google Scholar]
- Bernardinelli, L.; Montomoli, C. Empirical Bayes versus fully Bayesian analysis of geographical variation in disease risk. Stat. Med. 1992, 11, 983–1007. [Google Scholar] [CrossRef] [PubMed]
- Gilks, W.R.; Richardson, S.; Spielhalter, D.J. Markov Chain Monte Carlo in Practice; Chapman and Hall/CRC: London, UK, 1995. [Google Scholar]
- Spiegelhalter, D.; Thomas, A.; Best, N.; Lunn, D. WinBUGS Version 1.4 User Manual; MRC Biostatistics Unit, Institute of Public Health: London, UK, 2004. [Google Scholar]
- Aamodt, G.; Samuelsen, S.O.; Skrondal, A. A simulated study of three methods for detecting disease clusters. Int. J. Health Geogr. 2006, 5, 1–11. [Google Scholar] [CrossRef] [PubMed]
- Hamilton, J.D. A standard error for the estimated state vector of a state-space model. J. Econometrics 1986, 33, 387–397. [Google Scholar] [CrossRef]
- Sólymos, P. Dclone: Data cloning in R. R J. 2010, 2, 29–37. [Google Scholar]
- R Core Team. R: A Language and Environment for Statistical Computing; R Foundation for Statistical Computing: Vienna, Austria, 2013. [Google Scholar]
- Sidák, Z. Rectangular confidence regions for the means of multivariate normal distributions. J. Am. Stat. Assoc. 1967, 62, 626–633. [Google Scholar]
- Bjornstad, O.N. ncf: Spatial Nonparametric Covariance Functions. R Package Version 1.1-5. 21 November 2013. Available online: http://cran.r-project.org/web/packages/ncf/index.html (accessed on 24 July 2014).
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Torabi, M.; Galloway, K. Geographical Variation of Incidence of Chronic Obstructive Pulmonary Disease in Manitoba, Canada. ISPRS Int. J. Geo-Inf. 2014, 3, 1039-1057. https://doi.org/10.3390/ijgi3031039
Torabi M, Galloway K. Geographical Variation of Incidence of Chronic Obstructive Pulmonary Disease in Manitoba, Canada. ISPRS International Journal of Geo-Information. 2014; 3(3):1039-1057. https://doi.org/10.3390/ijgi3031039
Chicago/Turabian StyleTorabi, Mahmoud, and Katie Galloway. 2014. "Geographical Variation of Incidence of Chronic Obstructive Pulmonary Disease in Manitoba, Canada" ISPRS International Journal of Geo-Information 3, no. 3: 1039-1057. https://doi.org/10.3390/ijgi3031039