Dataset Information

Social norms and obesity prevalence: From cohort to system dynamics models.

ABSTRACT: Group-level obesity can be seen as an emergent property of a complex system, consisting of feedback loops between individual body weight perception, individual weight-related behaviour and group-level social norms (a product of group-level 'normal' body mass index (BMI) and sociocultural 'ideal' BMI). As overweight becomes normal, the norm might be counteracting health awareness in shaping individual weight-related behaviour. System dynamics modelling facilitates understanding and simulating this system's emergent behaviour. We constructed six system dynamics models (SDMs) based on an expert-informed causal loop diagram and data from six sociocultural groups (Dutch, Moroccan and South-Asian Surinamese men and women). The SDMs served to explore the effect of three scenarios on group-level BMI: 'what if' weight-related behaviour were driven by (1) health awareness, (2) norms or (3) a combination of the two. Median BMI decreased approximately 50% and 30% less in scenarios 2 and 3, respectively, than in 1. In men, the drop in BMI was approximately two times larger in scenario 1 versus 3, whereas in women, the drop was approximately equal in these scenarios. This study indicates that the overweight norm in men holds group-level BMI close to overweight despite health awareness. Since norms are counteracting health awareness less strongly in women, other drivers of obesity must be more relevant.

SUBMITTER: Crielaard L

PROVIDER: S-EPMC7507199 | biostudies-literature | 2020 Sep

REPOSITORIES: biostudies-literature

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Social norms and obesity prevalence: From cohort to system dynamics models.

Crielaard Loes L Dutta Pritha P Quax Rick R Nicolaou Mary M Merabet Nadège N Stronks Karien K Sloot Peter M A PMA

Obesity reviews : an official journal of the International Association for the Study of Obesity 20200513 9

Group-level obesity can be seen as an emergent property of a complex system, consisting of feedback loops between individual body weight perception, individual weight-related behaviour and group-level social norms (a product of group-level 'normal' body mass index (BMI) and sociocultural 'ideal' BMI). As overweight becomes normal, the norm might be counteracting health awareness in shaping individual weight-related behaviour. System dynamics modelling facilitates understanding and simulating thi ...[more]

PMID: 32400030

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Project description:BackgroundUnderstanding the social environmental around obesity has been limited by available data. One promising approach used to bridge similar gaps elsewhere is to use passively generated digital data.PurposeThis article explores the relationship between online social environment via web-based social networks and population obesity prevalence.MethodsWe performed a cross-sectional study using linear regression and cross validation to measure the relationship and predictive performance of user interests on the online social network Facebook to obesity prevalence in metros across the United States of America (USA) and neighborhoods within New York City (NYC). The outcomes, proportion of obese and/or overweight population in USA metros and NYC neighborhoods, were obtained via the Centers for Disease Control and Prevention Behavioral Risk Factor Surveillance and NYC EpiQuery systems. Predictors were geographically specific proportion of users with activity-related and sedentary-related interests on Facebook.ResultsHigher proportion of the population with activity-related interests on Facebook was associated with a significant 12.0% (95% Confidence Interval (CI) 11.9 to 12.1) lower predicted prevalence of obese and/or overweight people across USA metros and 7.2% (95% CI: 6.8 to 7.7) across NYC neighborhoods. Conversely, greater proportion of the population with interest in television was associated with higher prevalence of obese and/or overweight people of 3.9% (95% CI: 3.7 to 4.0) (USA) and 27.5% (95% CI: 27.1 to 27.9, significant) (NYC). For activity-interests and national obesity outcomes, the average root mean square prediction error from 10-fold cross validation was comparable to the average root mean square error of a model developed using the entire data set.ConclusionsActivity-related interests across the USA and sedentary-related interests across NYC were significantly associated with obesity prevalence. Further research is needed to understand how the online social environment relates to health outcomes and how it can be used to identify or target interventions.

Dataset Information

Social norms and obesity prevalence: From cohort to system dynamics models.

Publications

Social norms and obesity prevalence: From cohort to system dynamics models.

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