All Title Author
Keywords Abstract

Health  2015 

Analyzing Spatial Patterns of Cardiorespiratory Diseases in the Federal District, Brazil

DOI: 10.4236/health.2015.710143, PP. 1283-1293

Keywords: Environmental Health, Spatial Patterns, Cardiorespiratory Diseases

Full-Text   Cite this paper   Add to My Lib

Abstract:

Cardiorespiratory diseases are a serious public health problem worldwide. Identification of spatial patterns in health events is an efficient tool to guide public policies in environmental health. However, only few studies have considered spatial pattern analysis which is considered the evaluation of spatial autocorrelation, degree of autocorrelation and dependence behavior in terms of distances. Therefore, the objective of this study is to propose a set of procedures to evaluate the spatial patterns of cardiorespiratory diseases in the Federal District, Brazil. Specifically, our proposal will be based on four questions: a) is the spatial distribution of all patients clustered, random or dispersed? b) what is the degree of clustering for either high values or low values of patients? c) what is the spatial dependence behavior? d) considering the spatial variation, at what distance does the type of distribution (cluster, random or disperse) begin to change? We chose four methods to answer these questions Global Moran’s I (question “a”); Getis-Ord General G (question “b”); semivariogram analysis (question “c”); and multi-distance spatial cluster-K-function (question “d”). Our results suggest that there is a different behavior for people up to 5 years old (cluster, p < 0.01), especially in distances below 2.5 km. For people above 59 years old, cluster is significant just in short distances (<200 m). For other age groups, the spatial distribution is basically random. Our study showed that it was possible to capture evidences of health disparities in the Federal District.

References

[1]  Mortimer, K., Gordon, S.B., Jindal, S.K., Accinelli, R.A., Balmes, J. and Martin, W.J. (2012) Household Air Pollution Is a Major Avoidable Risk Factor for Cardiorespiratory Disease. Chest, 142, 1308-1315.
http://dx.doi.org/10.1378/chest.12-1596
[2]  WHO. Global Health Observatory (2014)
http://www.who.int/gho/ncd/mortality_morbidity/en/
[3]  Ignotti, E., Valente, J.G., Longo, K.M., Freitas, S.R., Hacon, S. de S. and Netto, P.A. (2010) Impact on Human Health of Particulate Matter Emitted from Burnings in the Brazilian Amazon region. Revista de Saúde Pública, 44, 121-130.
http://dx.doi.org/10.1590/S0034-89102010000100013
[4]  Xu, Z., Hu, W., Williams, G., Clements, C.A., Kan, H.D. and Tong, S. (2013) Air Pollution, Temperature and Pediatric Influenza in Brisbane, Australia. Environment International, 59, 384-388.
http://dx.doi.org/10.1016/j.envint.2013.06.022
[5]  Ning, Z., Wubulihairen, M. and Yang, F. (2012) PM, NOx and Butane Emissions from On-Road Vehicle Fleets in Hong Kong and Their Implications on Emission Control Policy. Atmospheric Environment, 61, 265-274.
http://dx.doi.org/10.1016/j.atmosenv.2012.07.047
[6]  Troncoso, R. and Cifuentes, L.A. (2012) Effects of Environmental Alerts and Pre-Emergencies on Pollutant Concentrations in Santiago, Chile. Atmospheric Environment, 61, 550-557.
http://dx.doi.org/10.1016/j.atmosenv.2012.07.077
[7]  Brajer, V., Hall, J. and Rahmatian, M. (2012) Air Pollution, Its Mortality Risk , and Economic Impacts in Tehran, Iran. Iranian Journal of Public Health, 41, 31-38.
[8]  Tayra, F., Ribeiro, H. and Nardocci, A. de C. (2012) Avaliacao Econpmica dos Custos da Poluicao em Cubatao—SP com Base nos Gastos com Saúde Relacionados às Doencas dos Aparelhos Respiratório e Circulatório. Saúde e Sociedade, 21, 760-775.
http://dx.doi.org/10.1590/S0104-12902012000300020
[9]  Hsu, H.-H., Adamkiewicz, G., Houseman, E.A., et al. (2012) The Relationship between Aviation and Ultraine Particulate Matter Concentrations near a Mid-Sized Airport. Atmospheric Environment, 50, 328-337.
http://dx.doi.org/10.1016/j.atmosenv.2011.12.002
[10]  Leiva, M., Santibanez, D., Ibarra, E.S., Matus, C.P. and Seguel, R. (2013) A Five-Year Study of Particulate Matter (PM2.5) and Cerebrovascular Diseases. Environmental Pollution, 181, 1-6.
http://dx.doi.org/10.1016/j.envpol.2013.05.057
[11]  Gonzalez-Barcala, F.J., Pertega, S., Garnelo, L., et al. (2013) Truck Traffic Related Air Pollution Associated with Asthma Symptoms in Young Boys: A Cross-Sectional Study. Public Health, 127, 275-281.
http://dx.doi.org/10.1016/j.puhe.2012.12.028
[12]  Zou, B., Peng, F., Wan, N. and Mamady, K. (2014) Wilson GJsCD of APEI across the US. Spatial Cluster Detection of Air Pollution Exposure Inequities across the United States. PLoS One, 9, e91917.
http://dx.doi.org/10.1371/journal.pone.0091917
[13]  Mitchell, A. (1999) The Esri Guide to GIS Analysis: Geographic Patterns & Relationships. 1st Edition, Esri Press; Nova York.
[14]  Kurland, K. and Gorr, W. (2012) Gis Tutorial Fo Health. 4th Edition, Esri Press, Nova York.
[15]  IBGE. IBGE Cidades (2013)
www.cidades.ibge.gov.br
[16]  Datasus (2013) Base de dados: Endereco dos pacientes atendidos e internados no Dist Fed.
[17]  Sedhab (2012) Base de dados: Organ Territ do Dist Fed.
[18]  IBGE (2012) Base de informacoes geográficas do setor censitário.
http://www.ibge.gov.br/home/download/estatistica.shtm
[19]  Anselin, L. (1995) Local Indicators of Spatial Association—LISA. Geographical Analysis, 27, 93-115.
http://dx.doi.org/10.1111/j.1538-4632.1995.tb00338.x
[20]  Getis, A. and Ord, J. (1992) The Analysis of Spatial Association by Use of Distance Statistics. Geographical Analysis, 24, 189-206.
http://dx.doi.org/10.1111/j.1538-4632.1992.tb00261.x
[21]  Chun, Y. and Griffith, D. (2013) Spatial Statistics & Geostatistics. Vol First. Sage, London.
[22]  Tobler, W. (1970) A Computer Movie Simulating Urban Growth in the Detroit Region. Economic Geography, 46, 234-240.
http://dx.doi.org/10.2307/143141
[23]  Nandasena, S., Wickremasinghe, A.R. and Sathiakumar, N. (2012) Respiratory Health Status of Children From Two Different Air Pollution Exposure Settings of Sri Lanka: A Cross-Sectional Study. American Journal of Industrial Medicine, 55, 1137-1145.
http://dx.doi.org/10.1002/ajim.22020
[24]  Hoffman, K., Kalkbrenner, A.E., Vieira, V.M. and Daniels, J.L. (2012) The Spatial Distribution of Known Predictors of Autism Spectrum Disorders Impacts Geographic Variability in Prevalence in Central North Carolina. Environmental Health, 11, 80.
http://dx.doi.org/10.1186/1476-069X-11-80
[25]  Fan, X., Lam, K. and Yu, Q. (2012) Differential Exposure of the Urban Population to Vehicular Air Pollution in Hong Kong. Science of The Total Environment, 426, 211-219.
http://dx.doi.org/10.1016/j.scitotenv.2012.03.057
[26]  Young, G.S., Fox, M., Trush, M., Kanarek, N., Glass, T.A. and Curriero, F.C. (2012) Differential Exposure to Hazardous Air Pollution in the United States: A Multilevel Analysis of Urbanization and Neighborhood Socioeconomic Deprivation. International Journal of Environmental Research and Public Healt, 9, 2204-2225.
http://dx.doi.org/10.3390/ijerph9062204
[27]  Scoggins, A., Kjellstrom, T., Fisher, G., Connor, J. and Gimson, N. (2004) Spatial Analysis of Annual Air Pollution Exposure and Mortality. Science of the Total Environment, 321, 71-85.
http://dx.doi.org/10.1016/j.scitotenv.2003.09.020
[28]  Poulsen, E. and Kennedy, L.W. (2004) Using Dasymetric Mapping for Spatially Aggregated Crime Data. Journal of Quantitative Criminology, 20, 243-263.
http://dx.doi.org/10.1023/B:JOQC.0000037733.74321.14
[29]  Freitas, M. de B.C., Xavier, A.M. de S. and Fragoso, R.M. de S. (2012) Redistributing Agricultural Data by a Dasymetric Mapping Methodology. Agricultural and Resource Economics Review, 3, 351-366.
[30]  Cook, A.J., Gold, D.R. and Li, Y. (2013) Spatial Cluster Detection for Longitudinal Outcomes Using Administrative Regions. Commun Stat Theory Methods, 42, 2105-2117.
[31]  Tian, N., Wilson, G. and Zhan, B. (2010) Female Breast Cancer Mortality Clusters within Racial Groups in the United States. Health Place, 16, 209-218.
http://dx.doi.org/10.1016/j.healthplace.2009.09.012
[32]  Barrozo, L.V. (2014) Contribuicoes da cartografia aos estudos de geografia da saúde: Investigando associacoes entre padroes espaciais. Revista do Departamento de Geografia—USP, Volume Especial Cartogeo, 413-425.
[33]  Miranda, M.J.De, Costa, C., Santana, P. and Barrozo, L.V. (2014) Associacao espacial entre variáveis socioeconomicas e risco relativo de nascimentos pré-termo na Regiao Metropolitana de Sao Paulo (RMSP) e na área Metropolitana de Lisboa (AML). Saúde e Sociedade, 23, 1142-1153.
http://dx.doi.org/10.1590/S0104-12902014000400002
[34]  Campos, F.G.De, Barrozo, L.V., Ruiz, T., et al. (2008) Distribuicao espacial dos idosos de um município de médio porte do interior paulista segundo algumas características sócio-demográficas e de morbidade. Cadernos de Saúde Pública, 25, 77-86.
http://dx.doi.org/10.1590/S0102-311X2009000100008
[35]  Bando, D.H., Moreira, R.S., Pereira, J.C. and Barrozo, L.V. (2012) Spatial Clusters of Suicide in the Municipality of Sao Paulo 1996-2005: An Ecological Study. BMC Psychiatry, 12, 124.
http://dx.doi.org/10.1186/1471-244X-12-124
[36]  Muller, E.V., Aranha, S.R.R., Roza, W.S.S.Da and Gimeno, S.G.A. (2012) Distribuicao espacial da mortalidade por doencas cardiovasculares no Estado do Paraná, Brasil: 1989-1991 e 2006-2008. Cadernos de Saúde Pública, 28, 1067-1077.
http://dx.doi.org/10.1590/S0102-311X2012000600006
[37]  Almeida, S.L. de. (2013) Análise espacial doas doencas respiratórias e a poluicao relacionada ao tráfego no município de Sao Paulo.

Full-Text

comments powered by Disqus