The objective was to investigate if there is an association between the mortality rates due to oral and oropharyngeal cancer in Brazil and the expansion of access to public primary and specialized dental care services that resulted from the implementation of the National Oral Health Policy, between 2000 and 2013. The mortality data were obtained from the records of the Mortality Information System and the exposure variables were obtained from databases of the Brazilian Ministry of Health and the Brazilian Institute of Geography and Statistics. The main exposures investigated were “coverage of primary dental care” and “number of specialized dental care centers”. Additional covariates included “Gini index of household income”, “average number of years of study”, “proportion of unemployed people” and “proportion of smokers”. For the statistical analysis, a random coefficient model was used. There was a statistically significant association between the mortality rates by oral and oropharyngeal cancer with coverage by primary dental care and the number of specialized dental care centers with males. This study found that the expansion of the coverage of primary dental care and the number of specialized dental care centers are associated with the reduction of mortality rates due to oral and oropharyngeal cancer in Brazil. There is plausibility for the association found, which needs to be confirmed by implementation studies.

Resumo Observações generalizadas de tendências temporais de mortalidade podem encobrir padrões específicos relevantes. O objetivo deste estudo é analisar a tendência das taxas de mortalidade por câncer bucal e de orofaringe no Brasil, no período de 2000 a 2013, considerando as diferenças por sexo, sítio anatômico, faixa etária e raça/cor. Os dados sobre a mortalidade por câncer bucal e de orofaringe foram obtidos do Sistema de Informações sobre Mortalidade. A tendência das taxas de mortalidade da série histórica, por estrato, foi estimada por regressão linear generalizada pelo método de Prais-Winsten. De 2000 a 2013, ocorreram 61.190 óbitos por essa doença (média de 3,50 óbitos/100 mil hab./ano). A tendência das taxas mostrou-se estacionária para homens e crescente para mulheres (1,31%/ano). Identificou-se padrão de crescimento para homens de 20-29 anos (2,92%/ano) e para homens pardos (20,36%/ano). Padrão de crescimento também foi identificado para mulheres brancas (2,70%/ano) e pardas (8,24%/ano). Conclui-se que a vigilância dessa condição deve considerar as diferenças sociodemográficas da população para um planejamento equânime das estratégias de cuidado, pois estas refletiram em padrões distintos de tendência das taxas mortalidade por câncer bucal e de orofaringe no Brasil.

Here we present a theoretical study on the main properties of Fractionally Integrated Exponential Generalized Autoregressive Conditional Heteroskedastic (FIEGARCH) processes. We analyze the conditions for the existence, the invertibility, the stationarity and the ergodicity of these processes. We prove that, if {Xt}t∈Z is a FIEGARCH(p, d, q) process then, under mild conditions, {ln(X 2 t )}t∈Z is an ARFIMA(q, d, 0), that is, an autoregressive fractionally integrated moving average process. The convergence order for the polynomial coefficients that describes the volatility is presented and results related to the spectral representation and to the covariance structure of both processes {ln(X 2 t )}t∈Z and {ln(σ 2 t )}t∈Z are also discussed. Expressions for the kurtosis and the asymmetry measures for any stationary FIEGARCH (p, d, q) process are also derived. The h-step ahead forecast for the processes {Xt}t∈Z, {ln(σ 2 t )}t∈Z and {ln(X 2 t )}t∈Z are given with their respective mean square error forecast. The work also presents a Monte Carlo simulation study showing how to generate, estimate and forecast based on six different FIEGARCH models. The forecasting performance of six models belonging to the class of autoregressive conditional heteroskedastic models (namely, ARCH-type models) and radial basis models is compared through an empirical application to Brazilian stock market exchange index.

In this work we introduce the class of beta autoregressive fractionally integrated moving average models for continuous random variables taking values in the continuous unit interval (0, 1). The proposed model accommodates a set of regressors and a long-range dependent time series structure. We derive the partial likelihood estimator for the parameters of the proposed model, obtain the associated score vector and Fisher information matrix. We also prove the consistency and asymptotic normality of the estimator under mild conditions. Hypotheses testing, diagnostic tools and forecasting are also proposed. A Monte Carlo simulation is considered to evaluate the finite sample performance of the partial likelihood estimators and to study some of the proposed tests. An empirical application is also presented and discussed.