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From causal loop diagrams to future scenarios: Using the cross-impact balance method to augment understanding of urban health in Latin America
Journal article   Open access   Peer reviewed

From causal loop diagrams to future scenarios: Using the cross-impact balance method to augment understanding of urban health in Latin America

Ivana Stankov, Andres Felipe Useche, Jose D. Meisel, Felipe Montes, Lidia M. O. Morais, Amelia A. L. Friche, Brent A. Langellier, Peter Hovmand, Olga Lucia Sarmiento, Ross A. Hammond, …
Social science & medicine (1982), v 282, pp 114157-114157
01 Aug 2021
DOI: https://doi.org/10.1016/j.socscimed.2021.114157
PMID: 34182357
Featured in Collection :   UN Sustainable Development Goals @ Drexel
url
https://doi.org/10.1016/j.socscimed.2021.114157View
Published, Version of Record (VoR)CC BY V4.0,  Open

Abstract

Biomedical Social Sciences Life Sciences & Biomedicine Public, Environmental & Occupational Health Science & Technology Social Sciences Social Sciences, Biomedical
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 crossimpact 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.

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15 citations in Web of Science
17 citations in Scopus

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UN Sustainable Development Goals (SDGs)

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#9 Industry, Innovation and Infrastructure

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Collaboration types
Domestic collaboration
International collaboration
Web of Science research areas
Public, Environmental & Occupational Health
Social Sciences, Biomedical
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