Adolescence is a critical life stage marked by rapid physical, psychological, and social changes with long-term implications for health and wellbeing. Despite growing recognition within global frameworks—such as the Global Strategy for Women’s, Children’s and Adolescents’ Health and the Countdown to 2030—adolescents remain underrepresented in health data systems and policy agendas, particularly regarding non-communicable diseases (NCDs). This thesis investigates the burden of NCDs among adolescents in Europe, focusing on the utility, strengths, and limitations of the Global Burden of Disease (GBD) Study estimates for informing public health strategies and planning.
The research involved a comprehensive assessment of adolescents’ health status across 28 European Union Member States using GBD 2019 estimates, disaggregated by age, sex, location, and cause, over a 30-year period. Diabetes mellitus (both type 1 and type 2) was identified as the highest rising NCD in terms of disability-adjusted life years (DALYs) among adolescents. Additionally, an in-depth analysis examined diabetes trends across Western Europe, with also a specific case study on type 1 diabetes estimates in Finland, and a comparative evaluation between GBD 2021 subnational estimates and primary data from the Piemonte Regional Diabetes Registry in Italy.
The findings, presented in four research papers, reveal rising disability burdens and persistent data gaps—particularly for type 2 diabetes. This PhD thesis provides critical insights into the burden of NCDs among adolescents in Europe through the lens of the GBD framework, highlighting both its utility and its limitations. The research underscores the urgent need for improved primary data—especially for diabetes mellitus—to enhance the accuracy and policy relevance of health estimates and inform effective public health responses. Moreover, the thesis evaluates the GBD framework’s strengths—such as universality, comparability, and transparency—while also identifying inherent limitations, including challenges in accurately estimating type-specific diabetes and a lack of data granularity to capture local health disparities. These findings call for enhanced data infrastructure and better integration of local data sources to complement global models.
By addressing the complex challenges of adolescent health—from disease prevention and care delivery to data infrastructure—this work contributes to the foundation for comprehensive, age- and gender-sensitive interventions. It emphasizes the need to invest in robust health information systems, improved modelling techniques, and disaggregated data to support evidence-based policymaking. A harmonized approach to data collection, analysis, and dissemination will enable more effective decision-making, strengthen health system efficiency, and ensure high-quality care for adolescents—ultimately promoting healthier future generations.
