title: Principal components and generalized linear modeling in the correlation between hospital admissions and air pollution.
abstract: OBJECTIVE To analyze the association between concentrations of air pollutants and admissions for respiratory causes in children. METHODS Ecological time series study. Daily figures for hospital admissions of children aged < 6, and daily concentrations of air pollutants (PM10, SO2, NO2, O3 and CO) were analyzed in the Região da Grande Vitória, ES, Southeastern Brazil, from January 2005 to December 2010. For statistical analysis, two techniques were combined: Poisson regression with generalized additive models and principal model component analysis. Those analysis techniques complemented each other and provided more significant estimates in the estimation of relative risk. The models were adjusted for temporal trend, seasonality, day of the week, meteorological factors and autocorrelation. In the final adjustment of the model, it was necessary to include models of the Autoregressive Moving Average Models (p, q) type in the residuals in order to eliminate the autocorrelation structures present in the components. RESULTS For every 10:49 μg/m3 increase (interquartile range) in levels of the pollutant PM10 there was a 3.0% increase in the relative risk estimated using the generalized additive model analysis of main components-seasonal autoregressive - while in the usual generalized additive model, the estimate was 2.0%. CONCLUSIONS Compared to the usual generalized additive model, in general, the proposed aspect of generalized additive model - principal component analysis, showed better results in estimating relative risk and quality of fit.
authors.affiliation: Programa de Pós-Graduação em Engenharia Ambiental, Univesidade Federal do Espírito Santo, Vitória, ES, Brasil.
authors.forename: Juliana Bottoni de
authors.initials: JB
authors.lastname: Souza
authors.affiliation: Departamento de Estatística, Universidade Federal do Espírito Santo, Vitória, ES, Brasil.
authors.forename: Valdério Anselmo
authors.initials: VA
authors.lastname: Reisen
authors.affiliation: Programa de Pós-Graduação em Engenharia Ambiental, Univesidade Federal do Espírito Santo, Vitória, ES, Brasil.
authors.forename: Jane Méri
authors.initials: JM
authors.lastname: Santos
authors.affiliation: Departamento de Estatística, Universidade Federal de Minas Gerais, Belo Horizonte, MG, Brasil.
authors.forename: Glaura Conceição
authors.initials: GC
authors.lastname: Franco
mesh_terms: D000393:Air Pollutants / Q000009:adverse effects* / Q000032:analysis; D000397:Air Pollution / Q000009:adverse effects*; D001938:Brazil / Q000453:epidemiology; D002648:Child; D004781:Environmental Exposure / Q000009:adverse effects* / Q000032:analysis; D006760:Hospitalization / Q000706:statistics & numerical data*; D006801:Humans; D008962:Models, Theoretical; D052638:Particulate Matter / Q000009:adverse effects* / Q000032:analysis; D016012:Poisson Distribution; D025341:Principal Component Analysis; D012140:Respiratory Tract Diseases / Q000139:chemically induced / Q000453:epidemiology*; D012621:Seasons; D013997:Time Factors
chemical_list: D000393:Air Pollutants; D052638:Particulate Matter