Healthy cities researchers often ask questions about cause and effect: the causes are built environment interventions via urban planning and design practices, such as park renovation, a new bus line or a housing redevelopment programme; effects are individual and public health outcomes. The growing interest in natural experiments for causal inference in healthy cities research comes mainly from the public health fields. Planning and design knowledge of how the interventions were produced should have a central role in research design but is rarely discussed. This is evident from our analysis of three well-documented natural experiment research projects. This also motivates us to build a conceptual model, with the legal assignment of treatment and control groups and random distribution of confounders (LARD principle) to demonstrate how urban planning and design knowledge can help discover strong natural experiments to reinforce the causal inference in healthy cities research.
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