IPESE: UMA ANÁLISE DA PERFORMANCE SOCIOECONÔMICA DOS MUNICÍPIOS BAIANOS

The Index of Socioeconomic Performance – IPESE is an indicator that aims to measure the capacity and the quality in offering basic services to the population in each municipality in Bahia. The index is the result of the association of three dimensions: health, education and economy, separated in 16 different indicators. The IPESE is the result of an arithmetic mean of the obtained values in the three components: Index of Health Status – INS, Index of Education Status – INE, and Index of Economics and Finances – IEF. The result of the municipality shows its position inside the IPESE, which goes from 0 to 1, and the higher results indicate the best performances. The database used to the IPESE calculation, are administrative records available in DATASUS, IBGE and MTE/Caged/Rais. The presented results for the 417 municipalities in Bahia for 2012, indicate that a good part of the municipalities are medium/low level, considering the established goals in the indicators, showing that there’s still a notable space for a government acting through public policies to decrease socioeconomic inequalities.O Índice de Performance Socioeconômica – IPESE, é um indicador que tem por objetivo medir a capacidade dos municípios baianos em ofertar serviços básicos à sua população e a qualidade destes serviços prestados. O índice é resultado da agregação de três dimensões: saúde, educação e economia, desmembradas em um conjunto de 16 indicadores. O IPESE é o produto da média aritmética dos valores obtidos nos três índices componentes: Índice do Nível de Saúde – INS, Índice do Nível de Educação – INE e Índice de Economia e Finanças – IEF. O resultado do indicador de um município aponta a posição relativa deste no IPESE, variando entre 0 e 1, e os valores mais elevados indicam os melhores desempenhos. Os dados utilizados para cálculo são de registros administrativos disponíveis no DATASUS, IBGE e MTE/Caged/Rais. Os resultados apresentados para os 417 municípios baianos, em 2012, indicam que boa parte dos municípios está em nível médio / baixo, considerando as metas estabelecidas nos indicadores, demonstrando que ainda há um espaço considerável para a atuação do estado por meio de políticas públicas a fim de mitigar as desigualdades socioeconômicas. Palavras-chave: índice, performance, socioeconômica, políticas públicas

Prediction of postoperative facial swelling, pain and trismus following third molar surgery based on preoperative variables

Objective: This paper investigates the relationship between preoperative findings and short-term outcome in third molar surgery. Study design: A prospective study was carried out involving 80 patients who required 160 surgical extractions of impacted mandibular third molars between January 2009 and December 2010. All extractions were performed under local anesthesia by the same dental surgeon. Swelling and maximal inter-incisor distance were measured at 48 h and on the 7th day postoperatively. Mean visual analogue pain scores were determined at four different time periods. Results: One-hundred eight (67.5%) of the 160 extractions were performed on male subjects and 52 (32.5%) were performed on female subjects. Median age was 22.46 years. The amount of facial swelling varied depending on gender and operating time. Trismus varied depending on gender, operating time and tooth sectioning. The influence of age, gender and operating time varied depending on the pain evaluation period (p < 0.05). Conclusions: Short-term outcomes of third molar operations (swelling, trismus and pain) differ depending on the patients' characteristics (age, gender and body mass index). Moreover, surgery characteristics such as operating time and tooth sectioning were also associated with postoperative variables

Pervasive gaps in Amazonian ecological research

Biodiversity loss is one of the main challenges of our time,1,2 and attempts to address it require a clear un derstanding of how ecological communities respond to environmental change across time and space.3,4 While the increasing availability of global databases on ecological communities has advanced our knowledge of biodiversity sensitivity to environmental changes,5–7 vast areas of the tropics remain understudied.8–11 In the American tropics, Amazonia stands out as the world’s most diverse rainforest and the primary source of Neotropical biodiversity,12 but it remains among the least known forests in America and is often underrepre sented in biodiversity databases.13–15 To worsen this situation, human-induced modifications16,17 may elim inate pieces of the Amazon’s biodiversity puzzle before we can use them to understand how ecological com munities are responding. To increase generalization and applicability of biodiversity knowledge,18,19 it is thus crucial to reduce biases in ecological research, particularly in regions projected to face the most pronounced environmental changes. We integrate ecological community metadata of 7,694 sampling sites for multiple or ganism groups in a machine learning model framework to map the research probability across the Brazilian Amazonia, while identifying the region’s vulnerability to environmental change. 15%–18% of the most ne glected areas in ecological research are expected to experience severe climate or land use changes by 2050. This means that unless we take immediate action, we will not be able to establish their current status, much less monitor how it is changing and what is being lostinfo:eu-repo/semantics/publishedVersio