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Urban health is shaped by a system of factors spanning multiple levels and scales, and through a complex set of interactions. Building on causal loop diagrams developed via several group model building workshops, we apply the cross-impact balance (CIB) method to understand the strength and nature of the relationships between factors in the food and transportation system, and to identify possible future urban health scenarios (i.e., permutations of factor states that impact health in cities). We recruited 16 food and transportation system experts spanning private, academic, non-government, and policy sectors from six Latin American countries to complete an interviewer-assisted questionnaire. The questionnaire, which was pilot tested on six researchers, used a combination of questions and visual prompts to elicit participants' perceptions about the bivariate relationships between 11 factors in the food and transportation system. Each participant answered questions related to a unique set of relationships within their domain of expertise. Using CIB analysis, we identified 21 plausible future scenarios for the system. In the baseline model, 'healthy' scenarios (with low chronic disease, high physical activity, and low consumption of highly processed foods) were characterized by high public transportation subsidies, low car use, high street safety, and high free time, illustrating the links between transportation, free time and dietary behaviors. In analyses of interventions, low car use, high public transport subsidies and high free time were associated with the highest proportion of factors in a healthful state and with high proportions of 'healthy' scenarios. High political will for social change also emerged as critically important in promoting healthy systems and urban health outcomes. The CIB method can play a novel role in augmenting understandings of complex urban systems by enabling insights into future scenarios that can be used alongside other approaches to guide urban health policy planning and action. • We used the CIB method to augment findings from group model building workshops. • The CIB method highlights possible future scenarios to guide health policy planning. • We identified 21 plausible future scenarios for cities in Latin America. • Healthy scenarios featured low car use, high public transport subsidies and safety. • Political will appears critically important in promoting healthy urban scenarios. [ABSTRACT FROM AUTHOR]

We discuss the design, implementation, and results of a collaborative process designed to elucidate the complex systems that drive food behaviors, transport, and health in Latin American cities and to build capacity for systems thinking and community-based system dynamics (CBSD) methods among diverse research team members and stakeholders. During three CBSD workshops, 62 stakeholders from 10 Latin American countries identified 98 variables and a series of feedback loops that shape food behaviors, transportation and health, along with 52 policy levers. Our findings suggest that CBSD can engage local stakeholders, help them view problems through the lens of complex systems and use their insights to prioritize research efforts and identify novel solutions that consider mechanisms of complexity., (Copyright © 2019 The Authors. Published by Elsevier Ltd.. All rights reserved.)