Infant mortality in Brazil, 1980-2000: A spatial panel data analysis

Background: Infant mortality is an important measure of human development, related to the level of welfare of a society. In order to inform public policy, various studies have tried to identify the factors that influence, at an aggregated level, infant mortality. The objective of this paper is to analyze the regional pattern of infant mortality in Brazil, evaluating the effect of infrastructure, socio-economic, and demographic variables to understand its distribution across the country. Methods: Regressions including socio-economic and living conditions variables are conducted in a structure of panel data. More specifically, a spatial panel data model with fixed effects and a spatial error autocorrelation structure is used to help to solve spatial dependence problems. The use of a spatial modeling approach takes into account the potential presence of spillovers between neighboring spatial units. The spatial units considered are Minimum Comparable Areas, defined to provide a consistent definition across Census years. Data are drawn from the 1980, 1991 and 2000 Census of Brazil, and from data collected by the Ministry of Health (DATASUS). In order to identify the influence of health care infrastructure, variables related to the number of public and private hospitals are included. Results: The results indicate that the panel model with spatial effects provides the best fit to the data. The analysis confirms that the provision of health care infrastructure and social policy measures (e. g. improving education attainment) are linked to reduced rates of infant mortality. An original finding concerns the role of spatial effects in the analysis of IMR. Spillover effects associated with health infrastructure and water and sanitation facilities imply that there are regional benefits beyond the unit of analysis. Conclusions: A spatial modeling approach is important to produce reliable estimates in the analysis of panel IMR data. Substantively, this paper contributes to our understanding of the physical and social factors that influence IMR in the case of a developing country.

Near-Term Fetal Hypoxia-Ischemia in Rabbits MRI Can Predict Muscle Tone Abnormalities and Deep Brain Injury

Background and Purpose-The pattern of antenatal brain injury varies with gestational age at the time of insult. Deep brain nuclei are often injured at older gestational ages. Having previously shown postnatal hypertonia after preterm fetal rabbit hypoxia-ischemia, the objective of this study was to investigate the causal relationship between the dynamic regional pattern of brain injury on MRI and the evolution of muscle tone in the near-term rabbit fetus. Methods-Serial MRI was performed on New Zealand white rabbit fetuses to determine equipotency of fetal hypoxia-ischemia during uterine ischemia comparing 29 days gestation (E29, 92% gestation) with E22 and E25. E29 postnatal kits at 4, 24, and 72 hours after hypoxia-ischemia underwent T2- and diffusion-weighted imaging. Quantitative assessments of tone were made serially using a torque apparatus in addition to clinical assessments. Results-Based on the brain apparent diffusion coefficient, 32 minutes of uterine ischemia was selected for E29 fetuses. At E30, 58% of the survivors manifested hind limb hypotonia. By E32, 71% of the hypotonic kits developed dystonic hypertonia. Marked and persistent apparent diffusion coefficient reduction in the basal ganglia, thalamus, and brain stem was predictive of these motor deficits. Conclusions-MRI observation of deep brain injury 6 to 24 hours after near-term hypoxia-ischemia predicts dystonic hypertonia postnatally. Torque-displacement measurements indicate that motor deficits in rabbits progressed from initial hypotonia to hypertonia, similar to human cerebral palsy, but in a compressed timeframe. The presence of deep brain injury and quantitative shift from hypo-to hypertonia may identify patients at risk for developing cerebral palsy. (Stroke. 2012;43:2757-2763.)

Cost-effectiveness analysis of universal childhood hepatitis A vaccination in Brazil: Regional analyses according to the endemic context

Objective: To To conduct a cost-effectiveness analysis of a universal childhood hepatitis A vaccination program in Brazil. Methods: An age and time-dependent dynamic model was developed to estimate the incidence of hepatitis A for 24 years. The analysis was run separately according to the pattern of regional endemicity, one for South + Southeast (low endemicity) and one for the North + Northeast + Midwest (intermediate endemicity). The decision analysis model compared universal childhood vaccination with current program of vaccinating high risk individuals. Epidemiologic and cost estimates were based on data from a nationwide seroprevalence survey of viral hepatitis, primary data collection, National Health Information Systems and literature. The analysis was conducted from both the health system and societal perspectives. Costs are expressed in 2008 Brazilian currency (Real). Results: A universal immunization program would have a significant impact on disease epidemiology in all regions, resulting in 64% reduction in the number of cases of icteric hepatitis, 59% reduction in deaths for the disease and a 62% decrease of life years lost, in a national perspective. With a vaccine price of R$16.89 (US$7.23) per dose, vaccination against hepatitis A was a cost-saving strategy in the low and intermediate endemicity regions and in Brazil as a whole from both health system and society perspective. Results were most sensitive to the frequency of icteric hepatitis, ambulatory care and vaccine costs. Conclusions: Universal childhood vaccination program against hepatitis A could be a cost-saving strategy in all regions of Brazil. These results are useful for the Brazilian government for vaccine related decisions and for monitoring population impact if the vaccine is included in the National Immunization Program. (C) 2012 Elsevier Ltd. All rights reserved.

How deforestation pattern in the Amazon influences vertebrate richness and community composition

The effects of habitat configuration on species persistence are predicted to be most apparent when remaining habitat cover is below 30%. We tested this prediction by comparing vertebrate communities in 21 landscapes located in the southern Amazonia, including 7 control landscapes (similar to 100% of forest cover) and 14 fragmented landscapes (4 x 4 km). The fragmented landscapes retained similar proportions of forest (similar to 25%), but had contrasting configurations, resulting from two different deforestation patterns: the "fish-bone pattern" common in small properties, and the large-property pattern generally used by large ranchers. Vertebrates were surveyed in all landscapes in February-July 2009 with interviews (n = 150). We found a significant difference in reported species richness among the fish-bone, large-property, and control areas (mean = 29.3, 38.8 and 43.5 respectively). Control areas and large-properties tended to have a higher number of specialist species (mean = 13.7, and 11.7, respectively), when compared with the fish-bone pattern (5.1). Vertebrate community composition in the control and large-properties was more similar to one another than to those of the fish-bone landscapes. The number of fragments was the main factor affecting the persistence of species, being negatively associated with specialist species richness. Species richness was also positively related with the size of the largest fragment structurally connected to the studied landscapes (i.e., a regional scale effect). Our results demonstrated that the large-property pattern, which results in less fragmented landscapes, can maintain a more diverse community of large vertebrates, including top predators, which are considered fundamental for maintaining ecosystem integrity. These results support the hypothesis that landscape configuration contributes to the persistence and/or extirpation of species.