Análise, imputação de dados e interfaces computacionais em estudos de séries temporais epidemiológicas

• Autor(a) principal: Junger, Washington Leite
• Data de Publicação: 2008
• Tipo de documento: Tese
• Idioma: por
• Título da fonte: Biblioteca Digital de Teses e Dissertações da UERJ
• Texto Completo: http://www.bdtd.uerj.br/handle/1/4632
• topic: Environmental epidemiology; Air pollution; Time series; Statistical modeling; Statistical computing; Poluição do ar; Epidemiologia ambiental; Séries temporais; Modelagem estatística; Estatística computacional; CNPQ::CIENCIAS DA SAUDE::SAUDE COLETIVA::EPIDEMIOLOGIA

Air pollution is a public health problem in major urban areas and its effects are frequently observed in the morbidity and mortality due respiratory and cardiovascular causes, lung cancer, decreasing in the respiratory function, school absenteeism, and pregnancy outcomes. This thesis presents studies on the effects of air pollution on health in the Rio de Janeiro city and tackle some methodological issues on data analysis and missing data imputation in epidemiologic time series. Daily time series were used to estimate the effect of the air pollution on deaths among the elderly due to lung cancer during 2000 and 2001. The purpose of the study was to evaluate if air pollution is associated with premature deaths of people that already are in risk population. Another study was conducted to assess the relationship between air pollution and low birth weight of singleton full term babies. A crosssectional design was used on data available during the year 2002. Moderate effects of the air pollution were estimated in both studies. Methodological aspects of epidemiologic studies on air pollution are also approached. A data imputation method is presented and implemented as library for the statistical package R. The imputation methodology is evaluated and compared to others often used for data imputation in time series of air pollutant concentrations, through simulation techniques. The proposed method has shown best performance compared to those traditionally used. A brief review on the methodology used in the time series studies on the effects of air pollution on health is also presented. The issues approached in the review are also implemented as a library for the analysis of epidemiologic time series in R. The use of the library is exemplified with the analysis on the data of hospital admissions of children due to respiratory causes in the city of Rio de Janeiro. The methodological studies were carried out under the umbrella of the multi-city study to assess the effects of air pollution on health in the Latin America the ESCALA Project.