Together, the partners of the LongITools consortium take pride in the project's accomplishments. First and foremost, we have contributed to moving forward the exposome paradigm. Through joint efforts, we have provided robust evidence that the ambient environment, including air quality, noise levels and built spaces, relates to the risk of somatic diseases, including obesity, type 2 diabetes, hypertension, myocardial infarction, atrial fibrillation and mental health conditions, such as depression and anxiety disorders. The associations are complex in nature, but they show comparable effects (or absence of effects) in the studied populations in Finland, the Netherlands, the UK, France, Italy and Norway. One level of the complexity that LongITools aimed to tackle was to better understand how the risk associated with adverse environmental exposures accumulates through the life-course and how this influences health trajectories or changes in health status across the life-course by studying the effect in multiple generations and age-groups of Europeans. A second level of complexity was to reduce the dimensionality of the data to clarify the concepts behind the exposome; indeed, populations are exposed to a mixture of risks that relate to each other (e.g. traffic noise and air pollution). Multiple studies in LongITools have tried to target this by focusing either on the concepts of exposome profiles, exposome scores and joint effects on health outcomes, while other works were engaged to decipher precise exposures such as traffic noise, air pollution, and green spaces. The latter have further questioned the biological changes associated factors to the exposures, including changes in the epigenome, transcriptome and metabolome. A third level of complexity that LongITools addressed was that of causal relationships and exposure-triggered mechanisms. We built projects upon life-course and econometric models to characterise the pathways linking the exposome to the risk of obesity, via molecular factors, and questioned how this may be altered by targeted health policies. The fourth challenge was to integrate exposome AI-based prediction into a personal health risk assessment system, including a new mobile app and the LongITools Environmental Hub, based in people's homes. Finally, we targeted the communication, dissemination and exploitation of the results to relevant stakeholders, increasing the impact of the project's results. A final policy briefing was produced at the end of the project, providing recommendations to policymakers, offering the potential to improve the health of EU citizens and their environments.
