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Noise2NAKOAI: What AI and Machine Learning Tell Us About the Link Between Environment and Human Health

Transfer, Environmental Health, EPI,

Our health and the environment around us are profoundly intertwined. But how do air pollution and other environmental factors interact with each other and determine our health for each individual and the neighborhood? Furthermore, how can artificial intelligence (AI) and machine learning (ML) assist us in comprehending and identifying the impending effects?

In 2020, Helmholtz Munich in collaboration with Helmholtz AI and the German Aerospace Center (DLR) launched the "Noise2NAKOAI" project – an innovative initiative that utilizes artificial intelligence (AI) and machine learning (ML) techniques to explore the intricate connections between the environment and human health. In detail, the focus is on the effects of environmental noise on cardiovascular health. The three-year project addresses the pressing need for advanced spatial and spatio-temporal exposure models to accurately reflect real-life exposures and to unravel the complex relationship between environmental factors and population health.

The "Noise2NAKOAI" project is focused on achieving three primary goals. By utilizing AI and ML techniques the scientists aim to expand and refine traffic noise maps for more accurate geographical coverage. In addition, they are comparing various traditional and machine learning approaches to link noise maps with neighborhood data from the German National Cohort (NAKO) in order to identify clusters vulnerable to health risks due to noise pollution but also other environmental factors. Another goal is to extend the prediction model by incorporating individual-specific information from the NAKO to investigate the complex interplay of individual risk factors on hypertension and health outcomes, employing AI and ML methods and interpretable approaches for comprehensive insights.

Dr. Kathrin Wolf, Senior Scientist at the Institute of Epidemiology at Helmholtz Munich and the project's lead researcher elaborated on the aim of the endeavor: „In our case study, we develop extensive noise maps for entire Germany and link them with neighborhood and individual health data of participants of the German National Cohort to identify the main environmental drivers for the risk of hypertension and cardiovascular mortality.”


More information

Read more about the Noise2NAKOAI project and Dr. Kathrin Wolf at the Institute of Epidemiology at Helmholtz Munich. The project is also supported by Helmholtz AI consultants at Helmholtz Munich.


About the NAKO

The German National Cohort (NAKO Gesundheitsstudie) is the largest health study in Germany, launched in 2014, involving over 205,000 adults across 18 study centers nationwide. NAKO aims to uncover long-term insights into major diseases, such as cardiovascular issues, cancer, diabetes, neurodegenerative conditions, and more. By conducting thorough baseline assessments, including biomedical tests, interviews, and biosample collection, the study seeks to improve early detection, prevention, and treatment strategies. With regular follow-ups and interdisciplinary collaboration among 27 German scientific institutions, NAKO holds promise for advancing population-based epidemiology and healthcare research.