ZusammenfassungThe primary aim is to compare different Data Science and Machine Learning (ML) methods and their potential to investigate the influence of environmental indicators and socio-economic factors on health. As case study, we will focus on noise as environmental exposure and hypertension/high blood pressure, in order to investigate whether these new and emerging methods are helpful and suitable for epidemiological analyses in our specific environmental health context. Noise maps are not yet available for entire Germany, but will be compiled within this project and linked to the residential addresses of all NAKO participants. Hypertension/high blood pressure was chosen as an established and well-studied outcome with relatively high prevalence (in the NAKO and the German population) that was previously linked to increased noise levels.

Schlüsselwörter Blutdruck DataScience Hypertonie Lärm Umwelteinflüsse machine-learning

EinrichtungenHelmholtz Zentrum München