Mortalidade infantil e condições socioeconômicas nas microrregiões do Nordeste Brasileiro

The study aims to answer the following question: what are the different profiles of infant mortality, according to demographic, socioeconomic, infrastructure and health care, for the micro-regions at the Northeast of Brazil? Thus, the main objective is to analyze the profiles or typologies associated mortality levels sociodemographic conditions of the micro-regions, in the year 2010. To this end, the databases of birth and death certificates of SIM and SINASC (DATASUS/MS), were taken from the 2010 population Census microdata and from SIDRA/IBGE. As a methodology, a weighted multiple linear regression model was used in the analysis in order to find the most significant variables in the explanation child mortality for the year 2010. Also a cluster analysis was performed, seeking evidence, initially, of homogeneous groups of micro-regions, from of the significant variables. The logit of the infant mortality rate was used as dependent variable, while variables such as demographic, socioeconomic, infrastructure and health care in the micro-regions were taken as the independent variables of the model. The Bayesian estimation technique was applied to the database of births and deaths, due to the inconvenient fact of underreporting and random fluctuations of small quantities in small areas. The techniques of Spatial Statistics were used to determine the spatial behavior of the distribution of rates from thematic maps. In conclusion, we used the method GoM (Grade of Membership), to find typologies of mortality, associated with the selected variables by micro-regions, in order to respond the main question of the study. The results points out to the formation of three profiles: Profile 1, high infant mortality and unfavorable social conditions; Profile 2, low infant mortality, with a median social conditions of life; and Profile 3, median and high infant mortality social conditions. With this classification, it was found that, out of 188 micro-regions, 20 (10%) fits the extreme profile 1, 59 (31.4%) was characterized in the extreme profile 2, 34 (18.1%) was characterized in the extreme profile 3 and only 9 (4.8%) was classified as amorphous profile. The other micro-regions framed up in the profiles mixed. Such profiles suggest the need for different interventions in terms of public policies aimed to reducing child mortality in the region

Estimação clássica e Bayesiana em modelos de sobrevida com fração de cura

In Survival Analysis, long duration models allow for the estimation of the healing fraction, which represents a portion of the population immune to the event of interest. Here we address classical and Bayesian estimation based on mixture models and promotion time models, using different distributions (exponential, Weibull and Pareto) to model failure time. The database used to illustrate the implementations is described in Kersey et al. (1987) and it consists of a group of leukemia patients who underwent a certain type of transplant. The specific implementations used were numeric optimization by BFGS as implemented in R (base::optim), Laplace approximation (own implementation) and Gibbs sampling as implemented in Winbugs. We describe the main features of the models used, the estimation methods and the computational aspects. We also discuss how different prior information can affect the Bayesian estimates

Mortalidade segundo sua causa de morte e seus determinantes: uma análise para as capitais brasileiras e municípios do nordeste do Brasil, 2000 e 2010

This dissertation considered the development of two papers, both related to mortality in Brazil. In the first article, "The context of mortality according to the three broad groups of causes of death in Brazilian capitals, 2000 and 2010", the objective was to analyze the mortality rate according to the three major groups of causes of death in Brazilian capitals. In the second article, "Typology and characteristics of mortality from external causes in the municipalities in the Northeast of Brazil, 2000 and 2010", it was built up a typology for the Northeastern municipalities taking into account information on mortality from external causes and a set of indicators related to socioeconomic, demographic, and infrastructure aspects of such municipalities, both articles for the years 2000 and 2010. Thus, we used data from the Mortality Information System of the Ministry of Health. Furthermore, it was used information from the Demographic Census for those years. The variables relating to socioeconomic and demographic conditions used in this study were those available on the home page of the United Nations Program for Development. The variables relating to socioeconomic and demographic conditions used in this study were those available on the home page of the United Nations Program for Development. Was used in Article 1 the pro-rata distribution method to accomplish the redistribution of ill-defined causes. Moreover, made use of the technique of cluster analysis with the aim of grouping the capital that had proportions of deaths from ill-defined causes similar to each other. Already in Section 2, we used the technique of Empirical Bayesian estimation; spatial statistics technique; and finally, the Grade of Membership method to find types of municipalities from information on mortality from external causes associated with socioeconomic, demographic and infrastructure variables. As the main results, it stands out in Article 1, in relation to data quality, we observed the formation of four groups of similar capital between themselves, as the proportion of illdefined causes. Regarding the behavior of mortality, according to the three major groups of causes of death, it was noted both for 2000 and for 2010 the prevalence of deaths from noncommunicable diseases for both sexes, although the reduction was identified rates in some of the capitals. Communicable diseases stood out as the second cause of death among women. Also, we found that deaths due to external causes are responsible for the second cause of death among men, as well as presenting an increase among women. As for the Article 2, stands out, in general, not just an extension of mortality from external causes in the municipalities, as well as an enlargement of the configurator stain existence of external cause deaths for the whole area of Northeast. Regarding the typology of municipalities, three vi extreme profiles were buit: the profile 1, which comprises municipalities with high rates of mortality from external causes and the best social indicators; the profile 2, that was composed of municipalities that are characterized by having low mortality rates from external causes and the lowest social indicators; and the profile 3, that brings together municipalities with intermediate mortality rates and median values considered in relation to social indicators. Although we have not seen changes in the characteristics of the profiles, we observed an increase in the proportion of municipalities that belong to the extreme profile 3, taking into account the mixed profiles.