Radon, the primary source of natural ionizing radiation and one of the leading causes of lung cancer, is a critical yet often neglected component of exposomics. Integrating radon into the exposome framework requires accurate exposure quantification and a clear understanding of dose–response relationships, while relevant knowledge remains fragmented across disciplines. This review synthesizes three decades of multidisciplinary research across three key areas: exposure quantification, health effects, and molecular mechanisms. Our key findings highlight: (1) Despite Internet of Things and artificial intelligence have improved the estimation of radon exposure at the population level, challenges in terms of model scalability, interpretability, universality, and individual exposure uncertainty still need to be addressed. (2) The causal link to lung cancer has been established, yet evidence for nonlung cancer outcomes (e.g., cardiovascular disease, leukemia) remains uncertain, necessitating the need for large-scale prospective studies. (3) Molecular pathways like oxidative stress and DNA damage are implicated, but requiring high-throughput multiomics approaches to define precise interaction networks and identify robust biomarkers. Therefore, we propose a roadmap prioritizing refined exposure assessment techniques, systematic evaluation of nonlung cancer health effects, and multiomics-driven biomarker discovery. This review emphasizes the necessity of incorporating radon into exposomics and offers a foundation for developing more effective, evidence-based public health interventions.
Han et al. (Thu,) studied this question.