Objective:To assess the quality of mortality information by analyzing the frequency of garbage codes (GC) registered as underlying cause-of-death in Belo Horizonte, Minas Gerais, Brazil. Methods: Data of deaths of residents from 2011 to 2013 were selected. GC causes were classified as proposed by the Global Burden of Disease Study (GBD) 2015. They were grouped into GCs from ICD-10 Chapter XVIII and GCs excluding codes of Chapter XVIII. Proportions of GC were calculated by sex, age, and place of occurrence. Results: In Belo Horizonte, 30.5% of the total of 44,123 deaths were GC. Higher proportion of these codes was observed in children (1 to 4 years) and in people aged over 60 years. The following leading GCs observed were: other ill-defined and unspecified causes of death (code R99), unspecified pneumonia ( J18.9), unspecified stroke (hemorrhagic or ischemic) (I64), and unspecified septicemia (A41.9). The proportions of GC were 28.7% and 36.9% in deaths that occurred in hospitals and at home, respectively. An important difference occurred in the GC group from Chapter XVIII of ICD-10: 1.7% occurred in hospitals and 16.9% at home. Conclusion: The high proportions of GC in mortality statistics in Belo Horizonte demonstrated its importance for assessing the quality of information on causes of death.

RESUMO: Objetivo: Avaliar a mortalidade por áreas de Belo Horizonte (BH) durante a pandemia de COVID-19 conforme a vulnerabilidade social, visando a uma estratégia de vacinação. Métodos: Estudo ecológico com análise de mortalidade, segundo setores censitários classificados pelo índice de vulnerabilidade da saúde, composto de indicadores de saneamento e socioeconômicos. Óbitos por causas naturais e COVID-19 foram obtidos do Sistema de Informação sobre Mortalidade, entre a 10ª e a 43ª semanas epidemiológicas (SE) de 2020. Calculou-se o excesso de mortalidade por modelo de série temporal, considerando-se as mortes observadas por SE entre 2015 e 2019, por setor censitário. Taxas de mortalidade (TM) foram calculadas e padronizadas por idade com base em estimativas populacionais do Instituto Brasileiro de Geografia e Estatística (IBGE). Resultados: Houve 16,1% (n = 1.524) de excesso de mortalidade em BH: 11, 18,8 e 17,3% nas áreas de baixa, média e elevada vulnerabilidade, respectivamente. As diferenças entre TM observadas e esperadas por causas naturais, padronizadas por idade, foi igual a 59/100 mil habitantes em BH, aumentando de 31 para 77 e 95/100 mil, nas áreas de baixa, média e elevada vulnerabilidade, respectivamente. Houve gradiente de aumento com a idade nas TM por COVID-19, variando de 4 a 611/100 mil habitantes entre as idades de 20-39 anos e 75+ anos. A TM por COVID-19 por 100 mil idosos (60+ anos) foi igual a 292, aumentando de 179 para 354 e 476 nos setores de baixa, média e elevada vulnerabilidade, respectivamente. Conclusão: Desigualdades na mortalidade, mesmo entre idosos, aliadas à baixa oferta de doses, demonstram a importância de priorizar áreas socialmente vulneráveis durante a vacinação contra COVID-19.

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This study analyzes the profile of deaths from road traffic accidents in Belo Horizonte, Minas Gerais State, Brazil, by linking two public databases, the Information System of the Urban Transportation and Transit Company (BH10) and the Mortality Information System (SIM). The linked database (n = 306) identified a 24% under-recording rate for deaths and differed in the age distribution from the BH10 database and in roadway user category when compared to the mortality database. The mortality rate for road traffic accidents within the city limits was 10.2 per 100,000 thousand, and was higher among men, young adults, and the elderly. Poisson multivariate regression showed a higher mean death rate for motorcycle occupants (rate ratio – RR: 1.81); pedestrians (RR: 1.32); males (RR: 1.24); single/divorced (RR: 1.27); young adults 18-29 years of age (RR: 1.75); elderly (RR: 1.59); and deaths at the crash site (RR: 1.39) when compared to the reference categories. The study unveils the city’s traffic violence, expressed by the large proportion of deaths at the crash site and within the first 24 hours, and confirms the relevance of database linkage for characterizing vulnerable groups and traffic accident mortality in the urban setting.

ObjectiveDerive filtered tungsten X-ray spectra used in digital mammography systems by means of Monte Carlo simulations.Materials and MethodsFiltered spectra for rhodium filter were obtained for tube potentials between 26 and 32 kV. The half-value layer (HVL) of simulated filtered spectra were compared with those obtained experimentally with a solid state detector Unfors model 8202031-H Xi R/F & MAM Detector Platinum and 8201023-C Xi Base unit Platinum Plus w mAs in a Hologic Selenia Dimensions system using a direct radiography mode.ResultsCalculated HVL values showed good agreement as compared with those obtained experimentally. The greatest relative difference between the Monte Carlo calculated HVL values and experimental HVL values was 4%.ConclusionThe results show that the filtered tungsten anode X-ray spectra and the EGSnrc Monte Carlo code can be used for mean glandular dose determination in mammography.