Resumo O objetivo deste artigo é analisar a tendência temporal da mortalidade por câncer de colo de útero no Brasil e calcular uma projeção até o ano de 2030. Foram analisados os óbitos ocorridos no Brasil de 1996 a 2010 (Sistema de Informações sobre Mortalidade). Foram realizadas análises das tendências da mortalidade por meio da regressão Joinpoint, e para o cálculo das projeções foi utilizado o Nordpred. Para o Brasil, a tendência é de redução (APC = 1,7% IC95%-2,2; −1,1 p < 0,05), sendo significativa nas regiões centro oeste (APC = −1,3% ao ano), sudeste (APC =−3,3%) e sul (APC = −3,9%). As regiões norte e nordeste apresntam tendência de estabilidade. Os estados do Acre (APC = −6,5%) e Rio Grande do Sul (APC = −4,1%) apresentaram as maiores tendências de redução. Na análise das projeções de mortalidade, haverá uma redução das taxas no Brasil a partir do primeiro período projetado, sendo mais marcante para a região sul. As taxas de mortalidade até o ano 2030 serão explicadas, em maior medida, pela redução dos risco para a doença. A mortalidade por câncer de colo de útero apresenta tendência de redução, todavia está desigualmente distribuída no Brasil, com as regiões norte e nordeste apresentando as maiores taxas.

Summary The implementation of mobility restrictions and home office schemes due to the COVID‐19 pandemic have influenced electricity consumption patterns and levels. This study analyzes the effect of physical distancing measures regarding mobility on the energy consumption trends for the Brazilian energy system and its subsystems (Northeast, North, South, and Southeast‐Midwest). Trends were evaluated by the Joinpoint software, and the analysis comprehended the period between January 1 and May 27, 2020. Daily load data was grouped into weeks, with the calculation of weekly percentage changes considering a 95% confidence interval and p < 0.05. The weekly electricity loads were compared in the periods before and after the isolation decrees were enforced in Brazil (March 15, 2020). Statistically significant decreases were observed in the levels of electricity consumption, with trends represented by two joinpoints. Due to the different profiles of consumption across the geographic regions, the resulting electricity dynamics were also different. This is the first study to employ joinpoint analysis for the calculation of energy consumption trends focusing on the COVID‐29 pandemic. Data presented herein is unique, in its focus on Brazil, which enables more accurate implications to be drawn for Brazilian policy makers.

Aims To estimate the prevalence of multimorbidity among European community-dwelling adults, as well as to analyse the association with gender, age, education, self-rated health, loneliness, quality of life, size of social network, Body Mass Index (BMI) and disability. Methods A cross-sectional study based on wave 6 (2015) of the Survey of Health, Ageing and Retirement in Europe (SHARE) was conducted, and community-dwelling participants aged 50+ (n = 63,844) from 17 European countries were selected. Multimorbidity was defined as presenting two or more health conditions. The independent variables were gender, age group, educational level, self-rated health, loneliness, size of network, quality of life, BMI and disability (1+ limitations of basic activities of daily living). Poisson regression models with robust variance were fit for bivariate and multivariate analysis. Results The prevalence of multimorbidity was 28.2% (confidence interval–CI 95%: 27.5.8–29.0) among men and 34.5% (CI95%: 34.1–35.4) among women. The most common health conditions were cardiometabolic and osteoarticular diseases in both genders, and emotional disorders in younger women. A large variability in the prevalence of multimorbidity in European countries was verified, even between countries of the same region. Conclusions Multimorbidity was associated with sociodemographic and physical characteristics, self-rated health, quality of life and loneliness.