Simulación para Estimación de Muertes por Cáncer de Pulmón por Contaminación Ambiental de PM2.5. //Simulation to estimate deaths from lung cancer due to environmental contamination of PM2.5
DOI:
https://doi.org/10.29076/issn.2528-7737vol11iss27.2018pp97-110pKeywords:
Contaminación del aire, Morbilidad, Modelo, Neoplasias pulmonares, Simulación.Abstract
El objetivo de este estudio es estimar el número de muertes por cáncer de pulmón provocadas por la contaminación ambiental debida a la exposición de las personas a material particulado fino menor a 2.5 µm (PM2.5). Para cumplir con este fin, se realizó un estudio con enfoque deductivo en el que se efectuaron simulaciones del modelo de evaluación de la morbilidad ambiental desarrollado por la Organización Mundial de la Salud. Se evaluó la exposición de la población a la contaminación por PM2.5, basado en datos monitoreados en 12 estaciones de calidad de aire del Distrito Metropolitano de Quito en los grupos de población expuestas a PM2.5, y la incidencia en la salud, estimada en la tasa de mortalidad en la población. Para el período de análisis 1990-2020 el total de muertes por neoplasias pulmonares es de 3058 ± 24 de los cuales 523 ± 32 se asociarían con las concentraciones de PM2.5; equivalente al 17.1%, CI=95% [15.9%-18.3%] y un Riesgo Relativo de 1.2046 [1.0688, 1.394]. Estos resultados fueron obtenidos a través de un software desarrollado para el efecto. En conclusión, los valores obtenidos en la presente simulación se encuentran dentro del intervalo de confianza en relación a otros estudios similares.
Abstract
The objective of this study is to simulate the estimation of the number of deaths from lung cancer caused by environmental pollution due to human exposure to fine particulate matter less than 2.5 µm (PM2.5). To achieve this goal, the study was conducted with deductive approach. A simulation environmental model to assess morbidity developed by the World Health Organization was applied, based on population exposure to PM2.5 pollutant. This was done with data obtained from 12 air quality stations of the Metropolitan District of Quito and the population groups exposed to PM2.5, determining the impact on health. The final simulation was calculated using the death rate in the population. For the period 1990-2020, the total number of deaths due to lung neoplasms was 3058 ± 24. The number of these deaths associated to PM2.5 pollution was 523 ± 32, which supposes a Relative Risk of 523 ± 32, equivalent to 17.1%, CI=95% [15.9%-18.3%]. These results were obtained through software developed for this purpose. In conclusion, the values obtained in the present simulation are within the confidence interval of other similar studies.
Downloads
References
Beelen, R., Hoek, G., Brandt, P. A. van dan, Goldbohm, A., Fischer, P., & Schouten, L. J. (2008). Long-Term Effects of Traffic-Related Air Pollution on Mortality in a Dutch Co-hort (NLCS-AIR Study) - ProQuest. Environmental Healt Perspectives, 116(2), 196-202. Doi: 10.1289/ehp.10767.
Blower, Sally, & Medley, G. (1992). Epidemiology, HIV and drugs: mathematical models and data. British Journal of Addiction, 87(3), 371-379. Doi: 10.1111/j.1360-0443.1992.tb01938.x
Blower, SM, & Dowlatabadi, H. (1994). Sensitivity and Uncertainty Analysis of Complex Models of Disease Transmission: An HIV Model, as an Example on JSTOR. Interna-tional Statistical Review/revue Internacionale de Statistique, 62(2), 229-243. Doi: 10.2307/1403510
Burnett, R. T., III, C. A., Majid Ezzati, Casey Olives, Lim, S. S., Sumi, M., & et al. (2014). An Integrated Risk Function for Estimating the Global Burden of Disease Attributable to Ambient Fine Particulate Matter Exposure - UBC Library Open Collections. Environ-mental Health Perspectives, 122(4), 397-403. Doi: 10.1289/ehp.1307049
Chalom, A., Mandai, C., & Prado, P. (2013). Sensitivity analyses: a brief tutorial with R package pse, version 0.1.2. Universidad de Sao Paulo - Instituto de Biociencias. Recupe-rado de https://cran.r-project.org/web/packages/pse/vignettes/pse_tutorial.pdf
Comisión Especial de Estadística Ambiental Ecuador. (2006). Homologación del cálculo del indicador de concentración promedio anual de material particulado PM2.5 en el aire. Recuperado de http://www.ecuadorencifras.gob.ec/documentos/web-inec/Sistema_Estadistico_Nacional/Comisiones/Ambiente/Resoluciones/Res-CEEA-003-Concentracion-promedio-PM2.5-aire.pdf
Dockery, D. W., Pope, C. A., Xu, X., Spengler, J. D., Ware, J. H., Fay, M. E., … Speizer, F. E. (1993). An Association between Air Pollution and Mortality in Six U.S. Cities. New England Journal of Medicine, 329(24), 1753-1759. https://doi.org/10.1056/NEJM199312093292401
EMOV EP. (2016). Informe de Calidad de Aire Cuenca - 2015. Cuenca: EMOV EP. Recupe-rado de http://www.emov.gob.ec/sites/default/files/Calidad%20del%20Aire%20final%202015_0.pdf
EMOV EP. (2017). Informe de Calidad de Aire Cuenca - 2016. Cuenca: EMOV EP. Recupe-rado de http://gis.uazuay.edu.ec/ierse/links_doc_contaminantes/Informes%20Claudia%20Calidad%20del%20Aire/Informe_Calidad_Aire_Cuenca_2016.pdf
Gamble, J. F. (1998). PM2.5 and mortality in long-term prospective cohort studies: cause-effect or statistical associations? Environmental Health Perspectives, 106(9), 535-549.
Iman, R. L., & Helton, J. C. (1988). An Investigation of Uncertainty and Sensitivity Analysis Techniques for Computer Models. Risk Analysis, 8(1), 71-90. Doi: 10.1111/j.1539-6924.1988.tb01155.x
Instituto Nacional de Estadística y Censos - Ecuador. (2015). Defunciones Generales y Feta-les – Bases de Datos. Recuperado de http://www.ecuadorencifras.gob.ec/defunciones-generales-y-fetales-bases-de-datos/
Instituto Nacional de Estadística y Censos -Ecuador. (2014). Proyecciones Poblacionales. Recuperado de http://www.ecuadorencifras.gob.ec/proyecciones-poblacionales/
Jerves, R., & Armijos-Arcos, F. (2016). Análisis y revisión de la red de monitoreo de calidad del aire de la ciudad de Cuenca - Ecuador. La Granja, 23(1), 28-38. Doi: 10.17163/lgr.n23.2016.03
Krewski, D., Jerret, M., Burnett, R. T., Ma, R., Hughes, E., Shi, T., … et al. (2009). Extended follow-up and spatial analysis of the American Cancer Society study linking particulate air pollution and mortality. Research Report Health Effects Institute, 140(5), 5-114. Re-cuperado de https://www.ncbi.nlm.nih.gov/pubmed/19627030
Lepeule, J., Laden, F., Dockery, D., & Schwartz, J. (2012). Chronic Exposure to Fine Particles and Mortality: An Extended Follow-up of the Harvard Six Cities Study from 1974 to 2009. Environmental Health Perspectives, 120(7), 965-970. Doi: 10.1289/ehp.1104660
Lipsett, M. J., Ostro, B. D., Reynolds, P., Goldberg, D., Hertz, A., Jerrett, M., … Bernstein, L. (2011). Long-Term Exposure to Air Pollution and Cardiorespiratory Disease in the California Teachers Study Cohort. American Journal of Respiratory and Critical Care Medicine, 184(7), 828-835. Doi: 10.1164/rccm.201012-2082OC
Loomis, D., Grosse, Y., Lauby-Secretan, B., Ghissassi, F. E., Bouvard, V., Benbrahim-Tallaa, L., & et al. (2013). The carcinogenicity of outdoor air pollution. The Lancet Oncology, 14(13), 1262-1263. Doi: 10.1016/S1470-2045(13)70487-X
McKay, M. D., Beckman, R. J., & Conover, W. J. (1979). A Comparison of Three Methods for Selecting Values of Input Variables in the Analysis of Output from a Computer Code. Technometrics, 21(2), 239-245. Doi: 10.2307/1268522
Ostro, B. D., Hurley, S., & Lipsett, M. J. (1999). Air Pollution and Daily Mortality in the Coachella Valley, California: A Study of PM10 Dominated by Coarse Particles. Envi-ronmental Research, 81(3), 231-238. Doi: 10.1006/enrs.1999.3978
Pope III, C. A., Bates, D. V., & Raizenne, M. E. (1995). Health effects of particulate air pollution: time for reassessment? Environmental Health Perspectives, 103(5), 472.
Pope III, C., Burnett, R., Thun, M., Calle, E., Krewski, D., Ito, K., & et al. (2002). Lung can-cer, cardiopulmonary mortality, and long-term exposure to fine particulate air pollution. - PubMed - NCBI. The Journal of the American Medical Association, 287(9), 1132-1141.
Putaud, J., Van Dingenen, R., Alastuey, A., Bauer, H., Birmili, W., Cyrys, J. … Raes, F. (2010). A European aerosol phenomenology – 3: Physical and chemical characteristics of particulate matter from 60 rural, urban, and kerbside sites across Europe. Atmospheric Environment, 44(10), 1308-1320. Doi: 10.1016/j.atmosenv.2009.12.011
Secretaría de Ambiente. Municipio de Quito. (2015). Indice quiteño de la calidad de aire. Informes. Recuperado de http://quitoambiente.gob.ec/ambiente/index.php/informes
Secretaria Nacional de Planificación y Desarrollo - Ecuador, & Secretaría Nacional de Infor-mación- Ecuador. (2014). Proyecciones y Estudios Demográficos - Sistema Nacional de Información. Recuperado de http://sni.gob.ec/proyecciones-y-estudios-demograficos
Smith, K. R., Bruce, N., Balakrishnan, K., Adair-Rohani, H., Balmes, J., Chafe, Z. … Re-hfuess, E. (2014). Millions Dead: How Do We Know and What Does It Mean? Methods Used in the Comparative Risk Assessment of Household Air Pollution. Annual Review of Public Health, 35(1), 185-206. Doi: 10.1146/annurev-publhealth-032013-182356
US EPA National Center for Environmental Assessment, R. T. P. N., & Sacks, J. (2009). 2009 Final Report: Integrated Science Assessment for Particulate Matter [Reports & As-sessments]. Recuperado de https://cfpub.epa.gov/ncea/risk/recordisplay.cfm?deid=216546
World Health Organization. (2004). WHO. Outdoor air pollution: assessing the environmental burden of disease at national and local levels. Recuperado de http://www.who.int/quantifying_ehimpacts/publications/ebd5/en/
Downloads
Published
Issue
Section
License
Authors can keep the copyright, granting the journal right of first publication. Alternatively, authors can transfer copyright to the journal, which allow authors non-commercial use of the work, including the right to place it in a file open access.
