Padrões espaciais da mortalidade fetal e carência social no estado de Pernambuco, Brasil / Spatial patterns of fetal mortality and social deprivation in the state of Pernambuco, Brazil / Estándares espaciales de mortalidad fetal y privación social en el estado de Pernambuco, Brasil

A mortalidade fetal é um indicador da assistência obstétrica e de condições de vida capaz de refletir o estado de saúde da mulher e a qualidade e a acessibilidade dos cuidados no pré-natal e na assistência intraparto. Com o objetivo de analisar os padrões espaciais da mortalidade fetal, a evitabilidade dos óbitos e a carência social no estado de Pernambuco, foi realizado um estudo ecológico considerando municípios, regiões de saúde e mesorregiões como unidades de análise. Incluíram-se os óbitos fetais registrados no Sistema de Informação sobre Mortalidade no período de 2010 a 2017. Classificou-se a evitabilidade dos óbitos pela Lista Brasileira de Causas de Mortes Evitáveis por Intervenções do Sistema Único de Saúde. Aplicou-se a estatística descritiva e o teste qui-quadrado para comparação de proporções das causas de morte. Na elaboração do índice de carência social, utilizou-se a técnica de análise fatorial por componentes principais com o teste de esfericidade de Bartlett para identificar a matriz de correlação. Com o índice calculado, os municípios foram agrupados em estratos de carência social pela técnica de k-means. Foram aplicadas a análise bayesiana e a estatística espacial de Moran para identificação de áreas prioritárias de mortalidade fetal e do índice de carência social. Registraram-se 12.337 óbitos fetais, sendo 8.927 (72,3%) por causas evitáveis. As variáveis idade da mãe, número de filhos mortos, tipo de gravidez, tipo de parto e peso ao nascer estiveram relacionadas à evitabilidade do óbito. Na construção do índice de carência social, o teste de esfericidade de Bartlett (χ² de 144,463; p < 0,01) e o coeficiente KMO (0,8) mostraram que as correlações entre os itens eram adequadas para a análise fatorial, assim como as correlações entre os indicadores. O índice de carência social indicou dois fatores que, juntos, explicaram 77,63% da variância total. A taxa de mortalidade fetal evitável apresentou aumento entre estratos de carência social, com taxas de 7,99 por mil nascimentos (baixa carência), 8,06 por mil (média carência), 8,83 por mil (alta carência) e 10,7 por mil (muito alta carência). O índice global de Moran verificou autocorrelação espacial significativa para a taxa de mortalidade fetal bayesiana (I = 0,10; p = 0,05), para a taxa de mortalidade fetal evitável bayesiana (I = 0,13; p = 0,03) e para o índice de carência social (I = 0,53; p = 0,01). Alguns municípios das mesorregiões do São Francisco e do Sertão Pernambucano tiveram simultaneamente elevada mortalidade fetal e mortalidade fetal evitável, além de índice de carência social muito alto. A análise espacial identificou áreas com maior risco para a mortalidade fetal. O índice de carência social relacionou alguns determinantes das mortes fetais em áreas com piores condições de vida. Detectaram-se áreas prioritárias para a intervenção de políticas públicas de redução da mortalidade fetal e seus determinantes.

Fetal mortality is an indicator of obstetric care and living conditions, capable of reflecting the state of women's health and the quality and accessibility of prenatal care and intrapartum care. To analyze the spatial patterns of fetal mortality, preventability of deaths, and social deprivation in the state of Pernambuco, an ecological study was carried out considering municipalities, health regions, and mesoregions as units of analysis. Fetal deaths registered in the Mortality Information System in the period from 2010 to 2017 were included. The deaths are classified as preventable by the Brazilian List of Causes of Preventable Deaths by Interventions of the Unified Health System. Descriptive statistics and the Qui-square test were applied for comparisons of proportions of causes of death. In the elaboration of the social deprivation index, the factorial analysis technique by principal components with the Bartlett's sphericity test was used to identify the correlation matrix. With the calculated index, the municipalities were grouped in social deprivation strata by the k-means technique. Bayesian analysis and Moran's spatial statistics were applied to identify priority areas of fetal mortality and the index of social deprivation. There were 12,337 fetal deaths registered, of which 8,927 (72.3%) were due to preventable causes. The variables of mother's age, number of dead children, type of pregnancy, type of birth, and weight at birth were related to preventability of death. In the construction of the social deprivation index, Bartlett's sphericity test (χ² of 144.463; p < 0.01) and the KMO coefficient (0.8) showed that the correlations between the items were adequate for factor analysis, as well as the correlations between the indicators. The social deprivation index pointed to two factors that, together, explained 77.63% of the total variance. The rate of preventable fetal mortality showed an increase among social deprivation strata, with rates of 7.99 per thousand births (low deprivation), 8.06 per thousand (medium deprivation), 8.83 per thousand (high deprivation), and 10.7 per thousand (very high social deprivation). The global Moran index verified significant spatial autocorrelation for the Bayesian fetal mortality rate (I = 0.10; p = 0.05), for the Bayesian preventable fetal mortality rate (I = 0.13; p = 0.03) e for the o social deprivation index (I = 0.53; p = 0.01). Some municipalities of the mesoregions of São Francisco and of Sertão of Pernambuco have simultaneously high fetal mortality and preventable fetal mortality, in addition to a very high rate of social deprivation. The spatial analysis identified areas with the highest risk for fetal mortality. The index of social deprivation relates to some determinants of fetal deaths in areas with the worst living conditions. We detected priority areas for the intervention of public policies to reduce fetal mortality and its determinants.

La mortalidad fetal es un indicador de la asistencia obstétrica y de las condiciones de vida capaz de reflejar el estado de salud de la mujer y la cualidad y accesibilidad de los cuidados en el prenatal y la asistencia intraparto. Con el objetivo de analizar los estándares espaciales de la mortalidad fetal, la evitabilidad de los fallecimientos y la privación social del estado de Pernambuco (Brasil), se realizó un estudio ecológico con los municipios, las regiones de salud y las mesorregiones como unidades de análisis. Se incluyeron los fallecimientos fetales registrados en el Sistema de Información sobre Mortalidad en el período de 2010 a 2017. Se clasificó la evitabilidad de los fallecimientos desde la Lista Brasileña de Causas de Muertes Evitables por Intervenciones en el Sistema Único de Salud. Se aplicaron la estadística descriptiva y la prueba de chi-cuadrado para comparar las proporciones de las causas de muerte. En la elaboración del índice de privación social, se utilizó la técnica de análisis factorial por componentes principales con la prueba de esfericidad de Bartlett para identificar la matriz de correlación. Con el índice calculado, los municipios se agruparon en estados de privación desde la herramienta de k-means. Se aplicaron el análisis bayesiano y la estadística espacial de Moran para identificar las áreas prioritarias de la mortalidad fetal y el índice de privación social. Se registraron 12.337 fallecimientos fetales, de los cuales 8.927 (72,3%) fueron por causas evitables. Las variables edad de la madre, número de hijos muertos, tipo de embarazo, tipo de parto y peso al nacer estuvieron relacionadas con la evitabilidad del fallecimiento. En la construcción del índice de privación social, la prueba de esfericidad de Bartlett (χ² de 144,463; p < 0,01) y el coeficiente de KMO (0,8) mostraron que las correlaciones entre los ítems estaban adecuadas para el análisis factorial, así como las correlaciones entre los indicadores. El índice de privación social señaló a dos factores que juntos explican el 77,63% de la variancia total. La tasa de mortalidad fetal evitable tuvo un aumento entre los estados de privación social, con tasas de 7,99 por mil nacimientos (baja privación), 8,06 por mil (mediana privación), 8,83 por mil (alta privación) y 10,7 por mil (muy alta privación). El índice global de Moran evaluó la autocorrelación espacial significativa para la tasa de mortalidad fetal bayesiana (I = 0,10; p = 0,05), para la tasa de mortalidad fetal evitable bayesiana (I = 0,13; p = 0,03) y para el índice de privación social (I = 0,53; p = 0,01). Algunos municipios de las mesorregiones de São Francisco y de Sertão Pernambucano tuvieron alta mortalidad fetal, además del índice de privación social muy alto. Un análisis espacial identificó áreas con mayor riesgo de mortalidad fetal. El índice de privación social relacionó algunas de las causas de las muertes fetales en áreas con peores condiciones de vida. Se detectaron las áreas prioritarias a la intervención de las políticas públicas para reducir la mortalidad fetal y sus determinantes.

Deforestation impacts on dengue incidence in the Brazilian Amazon.

The objective of the study is to perform the spatial analysis of the conditioning factors for the increase in the incidence rate of dengue cases in municipalities located in the Amazon biome, in the period from 2016 to 2021. Three statistical approaches were applied: Moran's index, ordinary least squares regression, and geographically weighted regression. The results revealed that the incidence rates of dengue cases cluster in two areas, both located in the south of the Amazon biome, which is associated with the Arc of Deforestation. The variable deforestation influences the increase in dengue incidence rates revealed by the OLS and GWR model. The adjusted R2 of the GWR model was 0.70, that is, the model explains about 70% of the total case variation of dengue incidence rates in the Amazon biome. The results of the study evidence the need for public policies aimed at the prevention and combat of deforestation in the Amazon region.

Analysis of the completeness of self-harm and suicide records in Pernambuco, Brazil, 2014-2016.

INTRODUCTION: Suicides and suicide attempts are major public health problems, and coping strategies are hampered by insufficient or inadequate notifications. Data accuracy influences the formulation of public and mental health policies and suicide prevention strategies. The objective of this study was to analyze the completeness of self-harm and suicide records in the state of Pernambuco, Brazil, 2014-2016. METHODS: This is an evaluative study with a descriptive design. The data were collected from suicide attempt records from the Notifiable Diseases Information System and suicide records from the Mortality Information System. Probabilistic linkage was used to relate these databases, and the degree of completeness of the variables was calculated. Completeness was classified into the following categories: good (≥ 75.1%), regular (50.1%-75.0%), low (25.1%-50.0%), and very low (≤ 25.0%). RESULTS: In the analyzed period, 1,404 notifications of self-harm were studied, with an overall mean completeness of 86.2%. In addition, 1,050 suicide records were analyzed, with an overall mean completeness of 95.8%. Most variables referring to suicide attempts had good completeness, with the exception of the variables "occupation" and "education." The completeness of all suicide-related variables was rated as good. After linkage, a significant improvement was observed in the degree of completeness of the variable "occupation". CONCLUSION: The results of this study showed that the completeness of self-harm and suicide variables improved from the first to the last year. The integration of data from different information systems provides an opportunity to improve suicide prevention programs and the quality of available information. Continuous efforts to increase the completeness and reliability of suicide surveillance systems are fundamental to describe the epidemiological profile and, consequently, plan preventive actions, in addition to contributing to the development and reformulation of strategies aimed at reducing morbidity and mortality related to suicidal behavior.

Spatial patterns of the total mortality over the first 24 hours of life and that due to preventable causes.

This is an ecological study analysing spatial patterns of the total mortality over the first 24 hours of life and that due to preventable causes using data from the mortality information system (SIM) and live birth information system (SINASC) based on the municipalities of Pernambuco State, Brazil. The total mortality rates over the first 24 hours and that due to preventable causes were calculated for each municipality for the decades of 2000 to 2009 and for 2010 to 2019 to enable a comparison of the spatial patterns with spatial scan statistic used to identify clusters. Over the first 24 hours of life, a total of 13,571 deaths were reported, out of which 10,476 (77.2%) were preventable. The total mortality rate over the first 24 hours of life decreased from 5.5 in the 2000- 2009 period to 3.7 per 1000 live births in the following decade: a reduction of 32.7%, while the mortality rate due to preventable causes decreased from 4.4 to 2.8 per 1000 live births, a reduction of 36.7%. In the first decade, spatial exploratory analysis found three mortality rate clusters encompassing 56 municipalities over the first 24 hours of life. With respect to preventable causes over the first 24 hours of life, two mortality rate clusters were identified encompassing 41 municipalities. Risk areas for mortality over the first 24 hours of life were detected through spatial scan statistic. This method, directed towards uncovering the geographical distribution of deaths of very premature infants, can act as a tool for identifying priority areas to guide healthcare interventions.

Spatial analysis of socio-economic factors and their relationship with the cases of COVID-19 in Pernambuco, Brazil.

OBJECTIVES: To analyse the spatial distribution of rates of COVID-19 cases and its association with socio-economic conditions in the state of Pernambuco, Brazil. METHODS: Autocorrelation (Moran index) and spatial association (Geographically weighted regression) models were used to explain the interrelationships between municipalities and the possible effects of socio-economic factors on rates. RESULTS: Two isolated clusters were revealed in the inner part of the state in sparsely inhabited municipalities. The spatial model (Geographically Weighted Regression) was able to explain 50% of the variations in COVID-19 cases. The variables proportion of people with low income, percentage of rented homes, percentage of families in social programs, Gini index and running water had the greatest explanatory power for the increase in infection by COVID-19. CONCLUSIONS: Our results provide important information on socio-economic factors related to the spread of COVID-19 and can serve as a basis for decision-making in similar circumstances.

[Infant mortality due to avoidable causes in a city in Northeastern Brazil]. / Mortalidade infantil por causas evitáveis em uma cidade do Nordeste do Brasil.

This is a cross-sectional study that aimed to describe the occurrence of infant mortality in Recife (PE) between 2000 and 2009, second to avoidable causes. The population composed of cases of deaths between 2000 and 2009 among the infants of mothers living in Recife. Deaths were classified as avoidable by using the List of avoidable causes of deaths resulting from interventions within the Brazilian National Health System (SUS). Descriptive statistics were used for data analysis. A decrease in the infant mortality coefficient from 20.4 to 12.1 per 1.000 live births was observed (reduction of 40.6%). From the total of 3.743 deaths registered, 2.861 (76.4%) were classified as avoidable. It was notable that 61.2% of the deaths could have been avoided through appropriate care for the woman during the pregnancy. An approach in which avoidability is analyzed may assist in discussions relating to organization, quality and access to healthcare service, and in identifying deaths that could have been avoided through appropriate mother-child healthcare.

Viral inactivation in hemotherapy: systematic review on inactivators with action on nucleic acids.

The aim of this study was to conduct a systematic review on the photoinactivators used in hemotherapy, with action on viral genomes. The SciELO, Science Direct, PubMed and Lilacs databases were searched for articles. The inclusion criterion was that these should be articles on inactivators with action on genetic material that had been published between 2000 and 2010. The key words used in identifying such articles were "hemovigilance", "viral inactivation", "photodynamics", "chemoprevention" and "transfusion safety". Twenty-four articles on viral photoinactivation were found with the main photoinactivators covered being: methylene blue, amotosalen HCl, S-303 frangible anchor linker effector (FRALE), riboflavin and inactin. The results showed that methylene blue has currently been studied least, because it diminishes coagulation factors and fibrinogen. Riboflavin has been studied most because it is a photoinactivator of endogenous origin and has few collateral effects. Amotosalen HCl is effective for platelets and is also used on plasma, but may cause changes both to plasma and to platelets, although these are not significant for hemostasis. S-303 FRALE may lead to neoantigens in erythrocytes and is less indicated for red-cell treatment; in such cases, PEN 110 is recommended. Thus, none of the methods for pathogen reduction is effective for all classes of agents and for all blood components, but despite the high cost, these photoinactivators may diminish the risk of blood-transmitted diseases.