The state of health in the European Union in 2019

Background

The European Union (EU) faces many health-related challenges. Accurate and timely data on mortality and morbidity from diseases and injuries and their trends over time are essential for health planning and priority setting.

Methods

We use the GBD 2019 study estimates and 95% uncertainty intervals for the whole EU and each country to evaluate age-standardized death, YLL, YLD and DALY rates for Level 2 causes. We evaluate trends by comparing estimates for the year 2019 with those for the year 2010.

Results

In 2019, the age-standardized death and DALY rates in the EU were 465.8 and 20 251.0 per 100 000 inhabitants, respectively. Between 2010 and 2019, there were significant decreases for age-standardized, death and YLL rates across EU countries. However, YLD rates remained mainly unchanged, with increases in the Netherlands and the ‘. The largest decreases in age-standardized DALY rates were observed for HIV/AIDS and sexually transmitted diseases and transport injuries (both -19%). On the other hand, only diabetes and kidney diseases showed a significant increase for age-standardized DALY rates in the EU (3.5%). Mental disorders showed an increasing age-standardized YLD rate, as well.

Conclusions

Overall, there was a visible trend of improvement in the health status in the EU with substantial differences between countries. EU health policy makers need to tackle incidence of diseases and injuries, with specific attention to causes such as mental disorders. There are many opportunities for mutual learning among otherwise similar countries with different patterns of disease.

Burden of diseases and injuries attributable to risk factors in the European Union in 2019

Background

In addition to information on mortality and morbidity from diseases and injuries, it is important to identify the attributable burden of risk factors to allow for health planning and prioritization.

Methods

For the whole EU and each country, using estimates and 95% uncertainty intervals from the GBD 2019 study, we report attributable (all-cause and by level 2 risk factors) age-standardized death and DALY rates, as well as summary exposure values (SEV). We evaluate trends by comparing estimates for the year 2019 with those for the year 2010.

Results

Age-standardized death and DALY rates attributable to risk factors declined by 10.7% (95%UI 13.8%-7.6%) and 9.1% (95%UI 12.0%-6.3%), between 2010 and 2019 in the EU. While there was a decreasing trend for both age-standardized death and DALY rates for almost all risk factors, some showed an increasing trend on SEV, including low physical activity and intimate partner violence.

Conclusions

Despite the improvement of health metrics attributable to risk factors, several modifiable behavioral and metabolic risk factors remain unchanged over the years. It is crucial to ensure a swift implementation of evidence-based policies and interventions in EU member states to achieve the targets of the Sustainable Development Goals.

Lipidomic profiling identifies signatures of metabolic risk

BACKGROUND

Metabolic syndrome (MetS), the clustering of metabolic risk factors, is associated with cardiovascular disease risk. We sought to determine if dysregulation of the lipidome may contribute to metabolic risk factors.

METHODS

We measured 154 circulating lipid species in 658 participants from the Framingham Heart Study (FHS) using liquid chromatography-tandem mass spectrometry and tested for associations with obesity, dysglycemia, and dyslipidemia. Independent external validation was sought in three independent cohorts. Follow-up data from the FHS were used to test for lipid metabolites associated with longitudinal changes in metabolic risk factors.

RESULTS

Thirty-nine lipids were associated with obesity and eight with dysglycemia in the FHS. Of 32 lipids that were available for replication for obesity and six for dyslipidemia, 28 (88%) replicated for obesity and five (83%) for dysglycemia. Four lipids were associated with longitudinal changes in body mass index and four were associated with changes in fasting blood glucose in the FHS.

CONCLUSIONS

We identified and replicated several novel lipid biomarkers of key metabolic traits. The lipid moieties identified in this study are involved in biological pathways of metabolic risk and can be explored for prognostic and therapeutic utility.