It is paramount to expand the knowledge base and minimize the consequences of the pandemic caused by the new Coronavirus (SARS-Cov2). Spain is among the most affected countries that declared a countrywide lockdown. An ecological study is presented herein, assessing the trends for incidence, mortality, hospitalizations, Intensive Care Unit admissions, and recoveries per autonomous community in Spain. Trends were evaluated by the Joinpoint software. The timeframe employed was when the lockdown was declared on March 14, 2020. Daily percentage changes were also calculated, with CI = 95% and p<0.05. An increase was detected, followed by reduction, for the evaluated indicators in most of the communities. Approximately 18.33 days were required for the mortality rates to decrease. The highest mortality rate was verified in Madrid (118.89 per 100,000 inhabitants) and the lowest in Melilla (2.31). The highest daily percentage increase in mortality occurred in Catalonia. Decreasing trends were identified after approximately two weeks of the institution of the lockdown by the government. Immediately the lockdown was declared, an increase of up to 33.96% deaths per day was verified in Catalonia. In contrast, Ceuta and Melilla presented significantly lower rates because they were still at the early stages of the pandemic at the moment of lockdown. The findings presented herein emphasize the importance of early and assertive decision-making to contain the pandemic.
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.
Background The objective of this work was to analyse the prevalence trends of multimorbidity among European community-dwelling adults. Methods A temporal series study based on waves 1, 2, 4, 5, 6 and 7 of the Survey of Health, Ageing and Retirement in Europe (SHARE) was conducted, and community-dwelling participants aged 50+ (n = 274,614) from 15 European countries were selected for the period 2004–2017. Prevalence, adjusted by age, Average Annual Percentage Change (APC) and 95% confidence interval (95% CI) were all calculated. Trend analyses were realised by period, age groups and groups of diseases. Results The results showed a large variability in the prevalence of multimorbidity in adults aged 50 and over among European countries. Increase in the prevalence of multimorbidity in the countries of central Europe (Austria, Belgium, Czech Republic, France, Germany and Switzerland) and Spain in both sexes, and in the Netherlands among men. Stability was observed in northern and eastern European countries. Musculoskeletal and neurodegenerative groups showed more significant changes in the trend analyses. Conclusions This information can be useful for policy makers when planning health promotion and prevention policies addressing modifiable risk factors in health.
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