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dc.rights.licenseAtribución-NoComercial-CompartirIgual 4.0 Internacional
dc.contributor.advisorUrdinola, B. Piedad
dc.contributor.advisorRojas, Néstor Yesid
dc.contributor.authorGonzález Gutiérrez, David Alejandro
dc.coverage.temporal2008-2021
dc.date.accessioned2024-01-30T16:16:33Z
dc.date.available2024-01-30T16:16:33Z
dc.date.issued2023
dc.identifier.urihttps://repositorio.unal.edu.co/handle/unal/85522
dc.descriptionilustraciones (principalmente a color), diagramas
dc.description.abstractLa exposición prolongada a material particulado fino, de tamaño inferior a 2,5 micras (MP2,5), representa uno de los siete factores de mayor riesgo de muertes prematuras en todo el mundo. Con esta motivación, en el presente trabajo se estimó el número de muertes prematuras asociadas a la exposición prolongada de MP2,5 en la ciudad de Bogotá, por localidad y para el período comprendido entre los años 2008 y 2021. Para lograrlo, se realizaron modelos de los niveles de concentración de MP2,5 anualmente y se promediaron, utilizando dos enfoques: un modelo bosque aleatorio (RF) y un modelo refuerzo de gradiente extremo (XGBoost). Además, se calculó el cociente de riesgo para las muertes cardio metabólicas mediante un modelo proporcional de Cox, tomando como población de referencia la que estuvo expuesta a niveles iguales o menores a 15,15µg/m3 . Los resultados revelaron que un incremento en los niveles de MP2,5 está asociado con un aumento en la cantidad de muertes cardio metabólicas, y se identificó que las localidades más afectadas son Kennedy, Bosa y Ciudad Bolívar. Estos hallazgos son coherentes con otros resultados presentados en la literatura. En conclusión, este documento contribuye al análisis del impacto de la contaminación en la salud pública de la ciudad de Bogotá. (Texto tomado de la fuente)
dc.description.abstractLong-term exposure to fine particulate matter, which is less than 2.5 microns in size (PM2.5), is considered one of the seven major risk factors for premature deaths worldwide. As a result, it becomes crucial to investigate its local effects and implement public health policies aimed at reducing premature mortality. This study focuses on estimating the number of premature deaths linked to PM2.5 material exposure in Bogota, analyzing data by locality for the years 2008 to 2021. To achieve this, the concentration levels of PM2.5 were modeled and averaged annually, using two approaches: a random forest model and an XGBoost model. In addition, the hazard ratio for cardio-metabolic deaths was calculated using a Cox proportional model, taking as the reference population those exposed to levels equal to or less than 15.15g/m3 . The findings demonstrate a direct correlation between elevated PM2.5 levels and an increase in cardio-metabolic deaths, with Kennedy, Bosa, and Ciudad Bolivar emerging as the most affected localities. These outcomes align with previous research in the field. Consequently, this document contributes to the broader analysis of pollution’s impact on public health in Bogota.
dc.format.extentxii, 45 páginas
dc.format.mimetypeapplication/pdf
dc.language.isospa
dc.publisherUniversidad Nacional de Colombia
dc.rights.urihttp://creativecommons.org/licenses/by-nc-sa/4.0/
dc.subject.ddc510 - Matemáticas::519 - Probabilidades y matemáticas aplicadas
dc.subject.ddc300 - Ciencias sociales::304 - Factores que afectan el comportamiento social
dc.subject.lccMaterial particulado
dc.subject.lccParticulate matter
dc.titleTendencia espacio temporal de la concentración de MP2,5 y su carga de mortalidad en Bogotá entre 2008 y 2021
dc.typeTrabajo de grado - Maestría
dc.type.driverinfo:eu-repo/semantics/masterThesis
dc.type.versioninfo:eu-repo/semantics/acceptedVersion
dc.publisher.programBogotá - Ciencias - Maestría en Ciencias - Estadística
dc.coverage.cityBogotá
dc.description.degreelevelMaestría
dc.description.degreenameMagíster en Ciencias – Estadística
dc.identifier.instnameUniversidad Nacional de Colombia
dc.identifier.reponameRepositorio Institucional Universidad Nacional de Colombia
dc.identifier.repourlhttps://repositorio.unal.edu.co/
dc.publisher.facultyFacultad de Ciencias
dc.publisher.placeBogotá, Colombia
dc.publisher.branchUniversidad Nacional de Colombia - Sede Bogotá
dc.relation.referencesApte, J. S., Marshall, J. D., Cohen, A. J., & Brauer, M. (2015). Addressing global mortality from ambient PM2. 5. Environmental science & technology, 49 (13), 8057-8066.
dc.relation.referencesArregocés, H. A., Rojano, R., & Restrepo, G. (2023). Health risk assessment for particulate matter: application of AirQ+ model in the northern Caribbean region of Colombia. Air Quality, Atmosphere & Health, 1-16.
dc.relation.referencesBlanco-Becerra, L. C., Miranda-Soberanis, V., Hernández-Cadena, L., Barraza-Villarreal, A., Junger, W., Hurtado-Dıaz, M., & Romieu, I. (2014). Effect of particulate matter less than 10µm (PM10) on mortality in Bogota, Colombia: a time-series analysis, 1998-2006. salud pública de méxico, 56, 363-370.
dc.relation.referencesBonilla, J. A., Morales-Betancourt, R., & Aravena, C. (2021). Análisis de desigualdades múltiples y políticas de reducción de la contaminación.
dc.relation.referencesBreiman, L. (2001). Random forests. Machine learning, 45 (1), 5-32.
dc.relation.referencesBureau, P. R. (2007). Population: A Lively Introduction (Vol. 62).
dc.relation.referencesBurnett, R., Chen, H., Szyszkowicz, M., Fann, N., Hubbell, B., Pope III, C. A., Apte, J. S., Brauer, M., Cohen, A., Weichenthal, S., et al. (2018). Global estimates of mortality associated with long-term exposure to outdoor fine particulate matter. Proceedings of the National Academy of Sciences, 115 (38), 9592-9597.
dc.relation.referencesBurnett, R. T., Pope III, C. A., Ezzati, M., Olives, C., Lim, S. S., Mehta, S., Shin, H. H., Singh, G., Hubbell, B., Brauer, M., et al. (2014). An integrated risk function for estimating the global burden of disease attributable to ambient fine particulate matter exposure. Environmental health perspectives, 122 (4), 397-403.
dc.relation.referencesCasallas, A., Celis, N., Ferro, C., López Barrera, E., Peña, C., Corredor, J., & Ballen Segura, M. (2020). Validation of PM10 and PM2. 5 early alert in Bogotá, Colombia, through the modeling software WRF-CHEM. Environmental Science and Pollution Research, 27 (29), 35930-35940.
dc.relation.referencesCasallas, A., Ferro, C., Celis, N., Guevara-Luna, M. A., Mogollón-Sotelo, C., Guevara-Luna, F. A., & Merchán, M. (2021). Long short-term memory artificial neural network approach to forecast meteorology and pm2. 5 local variables in bogotá, colombia. Modeling Earth Systems and Environment, 1-14.
dc.relation.referencesCheng, Q., Qu, C., Wang, Y., Wang, X., He, R., Cao, H., Liu, B., Zhang, H., Zhang, N., Lai, Z., et al. (2023). Global burden and its association with socioeconomic development status of meningitis caused by specific pathogens over the past 30 years: a population-based study. Neuroepidemiology, 1-1.
dc.relation.referencesChowdhury, S., Dey, S., & Smith, K. R. (2018). Ambient PM2. 5 exposure and expected premature mortality to 2100 in India under climate change scenarios. Nature communications, 9 (1), 318.
dc.relation.referencesCox, D. R. (1997). Some remarks on the analysis of survival data. Proceedings of the First Seattle Symposium in Biostatistics, 1-9.
dc.relation.referencesDavid, C. R., et al. (1972). Regression models and life tables (with discussion). Journal of the Royal Statistical Society, 34 (2), 187-220.
dc.relation.referencesde Ambiente, S. D. (2022). Informe anual de calidad del aire de Bogotá Año 2021.
dc.relation.referencesDockery, D. W., Pope, C. A., Xu, X., Spengler, J. D., Ware, J. H., Fay, M. E., Ferris Jr, B. G., & Speizer, F. E. (1993). An association between air pollution and mortality in six US cities. New England journal of medicine, 329 (24), 1753-1759.
dc.relation.referencesFarrow, A., Anhäuser, A., Chen, Y. J., & Cespedes, T. (2022). La carga de la contaminación del aire en Bogotá, Colombia 2021.
dc.relation.referencesGakidou, E., Afshin, A., Abajobir, A. A., Abate, K. H., Abbafati, C., Abbas, K. M., AbdAllah, F., Abdulle, A. M., Abera, S. F., Aboyans, V., et al. (2017). Global, regional, and national comparative risk assessment of 84 behavioural, environmental and occupational, and metabolic risks or clusters of risks, 1990–2016: a systematic analysis for the Global Burden of Disease Study 2016. The Lancet, 390 (10100), 1345-1422.
dc.relation.referencesGrisales-Romero, H., Piñeros-Jiménez, J. G., Nieto, E., Porras-Cataño, S., Montealegre, N., González, D., & Ospina, D. (2021). Local attributable burden disease to PM 2.5 ambient air pollution in Medellın, Colombia, 2010–2016. F1000Research, 10.
dc.relation.referencesHan, C., Kim, S., Lim, Y.-H., Bae, H.-J., & Hong, Y.-C. (2018). Spatial and temporal trends of number of deaths attributable to ambient PM2. 5 in the Korea. Journal of Korean medical science, 33 (30).
dc.relation.referencesInstituto Nacional de Salud, O. N. d. S. (2018). Carga de enfermedad ambiental en Colombia. Décimo informe técnico especial.
dc.relation.referencesJohnston, F. H., Borchers-Arriagada, N., Morgan, G. G., Jalaludin, B., Palmer, A. J., Williamson, G. J., & Bowman, D. M. (2021). Unprecedented health costs of smoke-related PM2. 5 from the 2019–20 Australian megafires. Nature Sustainability, 4 (1), 42-47.
dc.relation.referencesKlein, J. P., Moeschberger, M. L., et al. (2003). Survival analysis: techniques for censored and truncated data (Vol. 1230). Springer.
dc.relation.referencesLiang, F., Xiao, Q., Huang, K., Yang, X., Liu, F., Li, J., Lu, X., Liu, Y., & Gu, D. (2020). The 17-y spatiotemporal trend of PM2. 5 and its mortality burden in China. Proceedings of the National Academy of Sciences, 117 (41), 25601-25608.
dc.relation.referencesLozano, N. (2004). Air pollution in Bogota, Colombia: A concentration-response approach. Revista Desarrollo y Sociedad, (54), 133-177.
dc.relation.referencesMudu, P., Gapp, C., & Dunbar, M. (2018). AirQ+: example of calculations (inf. téc.). World Health Organization. Regional Office for Europe.
dc.relation.referencesMurray, C. J., Aravkin, A. Y., Zheng, P., Abbafati, C., Abbas, K. M., Abbasi-Kangevari, M., Abd-Allah, F., Abdelalim, A., Abdollahi, M., Abdollahpour, I., et al. (2020). Global burden of 87 risk factors in 204 countries and territories, 1990–2019: a systematic analysis for the Global Burden of Disease Study 2019. The Lancet, 396 (10258), 1223-1249.
dc.relation.referencesOrtiz-Durán, E. Y., & Rojas-Roa, N. Y. (2013). Estimating air quality change-associated health benefits by reducing PM10 in Bogotá. Revista de Salud Pública, 15 (1), 90-102.
dc.relation.referencesPope III, C. A., & Dockery, D. W. (2006). Health effects of fine particulate air pollution: lines that connect. Journal of the air & waste management association, 56 (6), 709-742.
dc.relation.referencesReis, I., Baron, D., & Shahaf, S. (2018). Probabilistic random forest: A machine learning algorithm for noisy data sets. The Astronomical Journal, 157 (1), 16.
dc.relation.referencesRodriguez-Villamizar, L. A., Belalcazar-Ceron, L. C., Castillo, M. P., Sanchez, E. R., Herrera, V., & Agudelo-Castañeda, D. M. (2022). Avoidable mortality due to long-term exposure to PM2. 5 in Colombia 2014–2019. Environmental Health, 21 (1), 137.
dc.relation.referencesSampson, P. D., Richards, M., Szpiro, A. A., Bergen, S., Sheppard, L., Larson, T. V., & Kaufman, J. D. (2013). A regionalized national universal kriging model using Partial Least Squares regression for estimating annual PM2. 5 concentrations in epidemiology. Atmospheric environment, 75, 383-392.
dc.relation.referencesSchapire, R. E., & Freund, Y. (2013). Boosting: Foundations and algorithms. Kybernetes.
dc.relation.referencesSchoenfeld, D. (1982). Partial residuals for the proportional hazards regression model. Biometrika, 69 (1), 239-241.
dc.relation.referencesSoutherland, V. A., Brauer, M., Mohegh, A., Hammer, M. S., Van Donkelaar, A., Martin, R. V., Apte, J. S., & Anenberg, S. C. (2022). Global urban temporal trends in fine particulate matter (PM2.5) and attributable health burdens: estimates from global datasets. The Lancet Planetary Health, 6 (2), e139-e146.
dc.relation.referencesSram, R. J., BeneS, I., Binková, B., Dejmek, J., Horstman, D., Kotsovec, F., Otto, D., Perreault, S. D., Rubes, J., Selevan, S. G., et al. (1996). Teplice program–the impact of air pollution on human health. Environmental health perspectives, 104 (suppl 4), 699-714.
dc.relation.referencesStare, J., & Maucort-Boulch, D. (2016). Odds ratio, hazard ratio and relative risk. Advances in Methodology and Statistics, 13 (1), 59-67.
dc.relation.referencesUrbinato, D. (1994). London’s historic”pea-soupers.”(smog in London, England). EPA journal, 20 (1-2), 44-45.
dc.relation.referencesWachter, K. W. (2014). Essential demographic methods. Harvard University Press.
dc.relation.referencesWinnett, A., & Sasieni, P. (2001). Miscellanea. A note on scaled Schoenfeld residuals for the proportional hazards model. Biometrika, 88 (2), 565-571.
dc.relation.referencesYang, X., Liang, F., Li, J., Chen, J., Liu, F., Huang, K., Cao, J., Chen, S., Xiao, Q., Liu, X., et al. (2020). Associations of long-term exposure to ambient PM2. 5 with mortality in Chinese adults: A pooled analysis of cohorts in the China-PAR project. Environment international, 138, 105589.
dc.relation.referencesZafra-Mejía, C. A., Rodríguez-Miranda, J. P., & Rondón-Quintana, H. A. (2020). The relationship between atmospheric condition and human mortality associated with coarse material particulate in Bogotá (Colombia). Revista Logos Ciencia & Tecnología, 12 (3), 57-68.
dc.relation.referencesZhang, G., Rui, X., & Fan, Y. (2018). Critical review of methods to estimate PM2. 5 concentrations within specified research region. ISPRS International Journal of GeoInformation, 7 (9), 368.
dc.relation.referencesZhang, H., Wang, Z., & Zhang, W. (2016). Exploring spatiotemporal patterns of PM2. 5 in China based on ground-level observations for 190 cities. Environmental Pollution, 216, 559-567.
dc.rights.accessrightsinfo:eu-repo/semantics/openAccess
dc.subject.decsExposición a riesgos ambientales
dc.subject.decsEnvironmental exposure
dc.subject.lembAir-pollution - Measurement
dc.subject.lembContaminación del aire - Mediciones
dc.subject.lembEstadística vital
dc.subject.lembVital statistics
dc.subject.lembMortalidad - Estadísticas
dc.subject.lembMortality - Statistics
dc.subject.lembEvaluación de impacto ambiental - Métodos estadísticos
dc.subject.lembEnvironmental impact analysis - Statistical methods
dc.subject.proposalCarga de mortalidad
dc.subject.proposalCociente de riesgo
dc.subject.proposalPolución
dc.subject.proposalMP2,5
dc.subject.proposalMortalidad
dc.subject.proposalExposición de largo plazo
dc.subject.proposalCurva concentración - Respuesta
dc.subject.proposalMortality burden
dc.subject.proposalHazard ratio
dc.subject.proposalPollution
dc.subject.proposalPM2.5
dc.subject.proposalMortality
dc.subject.proposalLong-term exposure
dc.subject.proposalConcentration-response curve
dc.title.translatedSpatiotemporal trend of PM2.5 and its mortality burden in Bogota between 2008 and 2021
dc.type.coarhttp://purl.org/coar/resource_type/c_bdcc
dc.type.coarversionhttp://purl.org/coar/version/c_ab4af688f83e57aa
dc.type.contentText
dc.type.redcolhttp://purl.org/redcol/resource_type/TM
oaire.accessrightshttp://purl.org/coar/access_right/c_abf2
dcterms.audience.professionaldevelopmentEstudiantes
dcterms.audience.professionaldevelopmentInvestigadores
dcterms.audience.professionaldevelopmentMaestros


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Atribución-NoComercial-CompartirIgual 4.0 InternacionalEsta obra está bajo licencia internacional Creative Commons Reconocimiento-NoComercial 4.0.Este documento ha sido depositado por parte de el(los) autor(es) bajo la siguiente constancia de depósito