Abstract
AimsTo 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.MethodsA 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.ResultsThe 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.ConclusionsMultimorbidity was associated with sociodemographic and physical characteristics, self-rated health, quality of life and loneliness.
Highlights
Population ageing and changes in patterns of exposure to risk factors have increased the number of people living with chronic conditions [1]
The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript
A cross-sectional population-based study was carried out using data from wave 6 release 7.0.0 of the Survey of Health, Ageing and Retirement in Europe (SHARE), the first multidisciplinary, cross-country, longitudinal research project conducted in Europe [17]
Summary
Population ageing and changes in patterns of exposure to risk factors have increased the number of people living with chronic conditions [1]. The European continent has experienced a rise in costs given the increased demand for health services owing to the increase in patients with multimorbidity. Differences in prevalence need to be studied in detail by gender and age groups. It is necessary to analyse which diseases occur more frequently among people with multimorbidity and what combinations of conditions are more common, in order to identify the different patterns of multimorbidity [4,5]. Identifying the patterns of multimorbidity is important for public policies, because this condition increases the consumption of drugs as well as the use and costs of health services, affecting the population’s quality of life [6]
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