Poor quality urban environments substantially increase non-communicable disease. Responsibility for associated decision-making is dispersed across multiple agents and systems: fast growing urban authorities are the primary gatekeepers of new development and change in the UK, yet the driving forces are remote private sector interests supported by a political economy focused on short-termism and consumption-based growth. Economic valuation of externalities is widely thought to be fundamental, yet evidence on how to value and integrate it into urban development decision-making is limited, and it forms only a part of the decision-making landscape. Researchers must find new ways of integrating socio-environmental costs at numerous key leverage points across multiple complex systems. This mixed-methods study comprises of six highly integrated work packages. It aims to develop and test a multi-action intervention in two urban areas: one on large-scale mixed-use development, the other on major transport. The core intervention is the co-production with key stakeholders through interviews, workshops, and participatory action research, of three areas of evidence: economic valuations of changed health outcomes; community-led media on health inequalities; and routes to potential impact mapped through co-production with key decision-makers, advisors and the lay public. This will be achieved by: mapping system of actors and processes involved in each case study; developing, testing and refining the combined intervention; evaluating the extent to which policy and practice changes amongst our target users, and the likelihood of impact on non-communicable diseases (NCDs) downstream. The integration of such diverse disciplines and sectors presents multiple practical/operational issues. The programme is testing new approaches to research, notably with regards practitioner-researcher integration and transdisciplinary research co-leadership. Other critical risks relate to urban development timescales, uncertainties in upstream-downstream causality, and the demonstration of impact.