Estimating the environmental burden of disease in children and adolescents in Germany
Limitations and possible solutions
Bibliographic Data
| ID | 22077946 |
|---|---|
| Authors | Myriam Tobollik (Environment Agency, corresponding author), Sarah Kienzler (German Environment Agency), Dirk Wintermeyer (German Environment Agency), Dietrich Plaß (0000-0002-8058-1399, German Environment Agency) |
| Year | 2026 |
| Volume | 14 |
| Pages | 1796283-1796283 |
| Publication date | 2026-04-10 |
| Peer Reviewed | Yes |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | Frontiers in Public Health (JOURNAL) |
| Journal identifiers | ISSN: 2296-2565 • E-ISSN: 2296-2565 |
| Publisher | Frontiers Media SA (PUBLISHER • CH) |
| DOI | 10.3389/fpubh.2026.1796283 |
| PMID | 42040125 |
| OpenAlex | W7153133415 |
| Language | EN |
| References cited | 56 |
Introduction: Children and adolescents play an exceptional role in our society especially when it comes to safeguarding their health and given their higher susceptibility to environmental risk factors and ongoing physical development. Method: We used data from the population-representative cross-sectional German Environmental Survey for Children and Adolescents (GerES V) and assessed the feasibility of applying the environmental burden of disease method for estimating the burden of environmental risks for children and adolescents in Germany. In this context, we highlight the challenges and discuss potential strategies how to deal with them. Results: In a four steps approach encompassing exposure assessment, systematic literature search, input data search and environmental burden of disease quantification, we aimed to estimate the impact of 17 risk factors on the health of children and adolescents. Following exposure assessment, eight risk factors were excluded. For the remaining risk factors systematic literature searches were conducted, which yielded exposure-response functions for five risk factors. The subsequent burden of disease estimations for benzene, bisphenol A, particulate matter, secondhand smoke and traffic noise were not fully standardized, allowing only limited comparability. Discussion: In the end, the burden of disease calculations performed varied widely for each risk factor. This variance can be attributed to diverse factors along the calculation processes, including, e.g., the absence of exposure-response functions tailored to children, insufficient exposure data, and gaps in other input data
Burden of disease · Disability-adjusted life year · Disease · Disease burden · Environmental data · Environmental epidemiology · Public health · Risk assessment · Safeguarding · Air Quality and Health Impacts · Health, Environment, Cognitive Aging · Indoor Air Quality and Microbial Exposure
Amstar 2
Comparative quantification of health risks
The PRISMA 2020 statement
Global, national, and regional burden of acute myeloid leukemia among 60–89 years-old individuals
The Burden of Disease Due to Road Traffic Noise in Hesse, Germany
Environmental Burden of Childhood Disease in Europe
Burden of Disease Due to Ambient Particulate Matter in Germany—Explaining the Differences in the Available Estimates
| Citation velocity | historical |
|---|---|
| Highly cited | No |