URBANOME: an exposome-based framework linking urban interventions to molecular, health, and policy-relevant outcomes

Urban environments expose residents to multiple simultaneous stressors that often act synergistically (e.g., air pollution and extreme heat amplifying cardiovascular and respiratory risks), contributing to a substantial public health burden. Environmental factors account for an estimated 13% of all deaths in the European Union, with ambient air pollution alone responsible for approximately 400,000 premature deaths per year. Most of this burden is mediated through chronic non-communicable diseases, including cardiovascular disease, stroke, cancer, respiratory disease, and mental health outcomes. Because these conditions are shaped by interacting environmental, social, and lifestyle determinants, traditional single-hazard approaches are insufficient, motivating adoption of an exposome paradigm. This paper presents the URBANOME methodological framework, an integrated exposome-based architecture for evaluating urban interventions across external exposures, internal biological responses, functional health outcomes, and policy-relevant indicators, and reports illustrative pilot findings from its first multi-site implementation. In a four-year Horizon 2020 study across nine European cities (Aarhus, Aberdeen, Athens, Ljubljana, Madrid, Milan, Montpellier, Stuttgart, and Thessaloniki), URBANOME implemented an integrated exposome framework through Urban Living Labs (ULLs). Co-created interventions (combining active mobility, urban greening, and traffic calming) were evaluated using a before–after design. Methods included ambient and personal exposure monitoring (wearable sensors, smartphone applications), agent-based population exposure modeling, validated health and well-being questionnaires, objective clinical measures (spirometry, blood pressure, heart rate variability), and multi-omics analyses (untargeted metabolomics and transcriptomics) on biological samples. A cost–benefit analysis quantified the economic return of interventions. The framework was successfully implemented across the nine ULLs, although intervention type, comparator availability, sample size, and follow-up duration varied by site (Table 1). Across paired participants, self-reported air-pollution annoyance and sleep-related breathing problems decreased between baseline and follow-up assessments, and pollution-related differences in forced vital capacity (FVC) were attenuated in higher-exposure neighbourhoods. In an exploratory pilot omics sub-cohort with paired pre/post samples, a four-metabolite panel (L-tyrosine, ascorbic acid, choline, coenzyme Q10) showed apparent perfect internal separation of pre- and post-intervention samples (apparent area under the receiver operating characteristic curve, AUROC ≈ 1.0); given the small sample size and absence of an independent held-out validation set, this result is preliminary and likely overoptimistic, and must be interpreted as a hypothesis-generating finding requiring external validation. Exploratory exposome–lifestyle analyses suggested that co-exposure to poor diet and higher pollution was associated with greater oxidative-stress-related metabolic signals, while combined healthy environments and lifestyles were associated with anti-inflammatory metabolite profiles. An exploratory cost–benefit analysis, based on value-transfer assumptions and standard health-economic unit costs, estimated benefit–cost ratios in the range of approximately €19–€143 per €1 invested across heterogeneous interventions; this range reflects substantial between-site variability and the assumptions detailed in the Methods, and should be interpreted as illustrative rather than as a precise return-on-investment estimate. This paper presents the URBANOME exposome-based evaluation framework and reports illustrative pilot findings from its multi-site implementation. The framework is feasible to deploy across heterogeneous European urban contexts and links external exposure assessment, internal biological profiling, functional health outcomes, and economic appraisal within a single architecture. Observed pre/post changes in self-reported, functional, and molecular endpoints are consistent with potentially beneficial responses to bundled urban interventions, but should be considered preliminary given the heterogeneous before–after design, variable comparator availability, small omics sub-cohorts, and short follow-up. External validation of the candidate biomarker panel and replication in independent settings are required before the framework’s outputs can support firm conclusions about intervention effectiveness or cost-effectiveness. The URBANOME framework operationalises the urban exposome through co-created interventions in nine European Urban Living Labs (ULLs). Integrated sensors, agent-based modelling, and multi-omics link urban exposures to internal biological responses. A four-metabolite candidate panel showed apparent perfect internal separation of pre/post samples in a small pilot omics sub-cohort and is presented as a hypothesis-generating finding requiring external validation. Pre/post changes in self-reported sleep, lung function, and stress-related molecular pathways were consistent with potential intervention-related effects, pending replication. An exploratory cost–benefit analysis estimated wide between-site benefit–cost ratios (approximately €19–€143 per €1 invested) and suggested potential equity gains under targeted scenarios; full assumptions and sensitivity analyses are reported in the Methods.