Background: Mental health is a public health issue for European young people, with great heterogeneity in resource allocation. Representative population-based studies are needed. The Global Burden of Disease (GBD) Study 2019 provides internationally comparable information on trends in the health status of populations and changes in the leading causes of disease burden over time. Methods: Prevalence, incidence, Years Lived with Disability (YLDs) and Years of Life Lost (YLLs) from mental disorders (MDs), substance use disorders (SUDs) and self-harm were estimated for young people aged 10-24 years in 31 European countries. Rates per 100,000 population, percentage changes in 1990-2019, 95% Uncertainty Intervals (UIs), and correlations with Sociodemographic Index (SDI), were estimated. Findings: In 2019, rates per 100,000 population were 16,983 (95% UI 12,823 - 21,630) for MDs, 3,891 (3,020 - 4,905) for SUDs, and 89·1 (63·8 - 123·1) for self-harm. In terms of disability, anxiety contributed to 647·3 (432-912·3) YLDs, while in terms of premature death, self-harm contributed to 319·6 (248·9-412·8) YLLs, per 100,000 population. Over the 30 years studied, YLDs increased in eating disorders (14·9%;9·4-20·1) and drug use disorders (16·9%;8·9-26·3), and decreased in idiopathic developmental intellectual disability (-29·1%;23·8-38·5). YLLs decreased in self-harm (-27·9%;38·3-18·7). Variations were found by sex, age-group and country. The burden of SUDs and self-harm was higher in countries with lower SDI, MDs were associated with SUDs. Interpretation: Mental health conditions represent an important burden among young people living in Europe. National policies should strengthen mental health, with a specific focus on young people. Funding: The Bill and Melinda Gates Foundation.
- Publikační typ
- časopisecké články MeSH
Background: The availability of data generated from different sources is increasing with the possibility to link these data sources with each other. However, linked administrative data can be complex to use and may require advanced expertise and skills in statistical analysis. The main objectives of this study were to describe the current use of data linkage at the individual level and artificial intelligence (AI) in routine public health activities, to identify the related estimated health indicators (i.e., outcome and intervention indicators) and health determinants of non-communicable diseases and the obstacles to linking different data sources. Method: We performed a survey across European countries to explore the current practices applied by national institutes of public health, health information and statistics for innovative use of data sources (i.e., the use of data linkage and/or AI). Results: The use of data linkage and AI at national institutes of public health, health information and statistics in Europe varies. The majority of European countries use data linkage in routine by applying a deterministic method or a combination of two types of linkages (i.e., deterministic & probabilistic) for public health surveillance and research purposes. The use of AI to estimate health indicators is not frequent at national institutes of public health, health information and statistics. Using linked data, 46 health outcome indicators, 34 health determinants and 23 health intervention indicators were estimated in routine. The complex data regulation laws, lack of human resources, skills and problems with data governance, were reported by European countries as obstacles to routine data linkage for public health surveillance and research. Conclusions: Our results highlight that the majority of European countries have integrated data linkage in their routine public health activities but only a few use AI. A sustainable national health information system and a robust data governance framework allowing to link different data sources are essential to support evidence-informed health policy development. Building analytical capacity and raising awareness of the added value of data linkage in national institutes is necessary for improving the use of linked data in order to improve the quality of public health surveillance and monitoring activities.
- Publikační typ
- časopisecké články MeSH
