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Understanding obesity‐related behaviors in youth from a systems dynamics perspective: The use of causal loop diagrams
Author(s) -
Waterlander Wilma E.,
Singh Amika,
Altenburg Teatske,
Dijkstra Coosje,
Luna Pinzon Angie,
Anselma Manou,
Busch Vincent,
Houtum Lieke,
Emke Helga,
Overman Meredith L.,
Chinapaw Mai J.M.,
Stronks Karien
Publication year - 2021
Publication title -
obesity reviews
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.845
H-Index - 162
eISSN - 1467-789X
pISSN - 1467-7881
DOI - 10.1111/obr.13185
Subject(s) - causal loop diagram , psychological intervention , perspective (graphical) , framing (construction) , system dynamics , computer science , psychology , intervention (counseling) , artificial intelligence , engineering , structural engineering , psychiatry
Summary This paper reports how we applied systems dynamics methods to gain insight into the complexity of obesity‐related behaviors in youth, including diet, physical activity, sedentary behavior, and sleep, by integrating a literature review into causal loop diagrams (CLDs). Results showed that the CLDs consisted of multiple subsystems and three types of dynamics appeared, including (1) feedback loops, (2) connections between feedback loops and subsystems, and (3) mechanisms. We observed clear similarities in the dynamics for the four behaviors in that they relate to “traditional” subsystems, such as home and school environments, as well as to newly added subsystems, including macroeconomics, social welfare, and urban systems. The CLDs provided insights that can support the development of intervention strategies, including (1) the confirmation that a range of mechanisms cover and connect multiple levels and settings, meaning that there is no silver bullet to address obesity; (2) understanding of how interventions in one particular setting, such as school, might be influenced by the interactions with other settings, such as urban systems; and (3) a comprehensive view of (un)intended consequences. This way of framing the problem will assist moving towards public health interventions that respond to and operate in the complexity of the real world.