Association between Air Cane Field Burning Pollution and Respiratory Diseases: A Bayesian Approach

Jorge Alberto Achcar, Mayara Piani Luna da Silva Sicchieri, Edson Zangiacomi Martinez

Department of Social Medicine, Ribeir?o Preto Medical School, University of S?o Paulo, Ribeir?o Preto, Brazil..

DOI: 10.4236/jep.2013.48A1018                

Abstract

Respiratory diseases and air pollution are the goals of many scientific works, but studies of the relations between these diseases and cane field burning pollution are still not well studied in the literature. In this work, we consider the times between days of extrapolations of the number of daily hospitalizations due to respiratory diseases as our data. To analyze this data set, we introduce different statistical models related to burning focus pollution and their relations with the counting of hospitalizations due to respiratory diseases. Under a Bayesian approach and with the help of the free available WinBUGS software, we get posterior summaries of interest using standard MCMC (Markov Chain Monte Carlo) methods.

Keywords

Hospitalization Counting; Bayesian Models; Times between Hospitalization Extrapolation Days; Respiratory Diseases

Conflicts of Interest

The authors declare no conflicts of interest.

References

[1]	Brazil, Ministério da Saúde. Secretaria Executiva. DATASUS. Informacoes de Saúde. Morbidade Hospitalar do SUS por local de internacao. http://tabnet.datasus.gov.br/cgi/deftohtm.exe?sih/cnv/nisp.def
[2]	D. Magalhaes, R. E. Bruns and P. C. Vasconcellos, “Polycyclic Aromatic Hydrocarbons as Tracers of Burning Cane Sugar: A Statistical Approach,” Química Nova, Vol. 30, No. 3, 2007, pp. 577-588. doi:10.1590/S0100-40422007000300014
[3]	F. S. Lopes and H. Ribeiro, “Mapping of Hospitalizations for Respiratory Problems and Possible Associations to Human Exposure to Products of Straw Burning of Sugar Cane in Sao Paulo,” Brazilian Journal of Epidemiology, Vol. 9, No. 2, 2006, pp. 215-225.
[4]	M. A. Arbex, J. E. D. Cancado, L. A. A. Pereira, A. L. F. Braga and P. H. N. Saldiva, “Biomass Burning and Its Effects on Health,” Brazilian Journal of Pulmonology, Vol. 30, No. 2, 2004, pp. 158-175.
[5]	L. C. Martins, M. R. D. O. Latorre, M. R. A. Cardoso, F. L. T. Goncalves, P. H. N. Saldiva and A. L. F. Braga, “Air Pollution and Emergency Room Visits for Pneumonia and Influenza in Sao Paulo, Brasil,” Revista de Saúde Pública, Vol. 36, No. 1, 2002, pp. 88-94. doi:10.1590/S0034-89102002000100014
[6]	Banco de Dados Queimadas (BDQUEIMADAS). http://www.dpi.inpe.br/proarco/bdqueimadas/
[7]	C. Baird, “Environmental Chemistry,” 2nd Edition, W.H. Freeman and Company, New York, 1999.
[8]	J. M. Bernardo and A. F. M. Smith, “Bayesian Theory,” Wiley, Chichester, 1994. doi:10.1002/9780470316870
[9]	D.J. Lunn, A. Thomas, N. Best and D. Spiegelhalter, “WinBUGS—A Bayesian Modelling Framework: Concepts, Structure, and Extensibility,” Statistics and Computing, Vol. 10, No. 4, 2000, pp. 325-337. doi:10.1023/A:1008929526011
[10]	B. P. Carlin and T. A. Louis, “Bayes and Empirical Bayes Methods for Data Analysis,” 2nd Edition, Chapman and Hall, Boca Raton, 2000. doi:10.1201/9781420057669
[11]	D. J. Spiegelhalter, N. G. Best, B. P. Carlin and A. Van Der Linde, “Bayesian Measures of Model Complexity and Fit,” Journal of the Royal Statistical Society, Series B, Vol. 64, No. 4, 2002, pp. 583-639. doi:10.1111/1467-9868.00353
[12]	A. Gelman and D. R. Rubin, “Inference from Iterative Simulation Using Multiple Sequences,” Statistical Science, Vol. 7, No. 4, 1992, pp. 457-472. doi:10.1214/ss/1177011136
[13]	D. Rigueira, P. A. Andre and D. M. T. Zanetta, “Sugar Cane Burning Pollution and Respiratory Symptoms in Schoolchildren in Monte Aprazível, Southeastern Brazil,” Revista de Saúde Pública, Vol. 45, No. 5, 2011, pp. 878-886.