Using network analysis to identify leverage points based on causal loop diagrams leads to false inference.

Network analysis is gaining momentum as an accepted practice to identify which factors in causal loop diagrams (CLDs)-mental models that graphically represent causal relationships between a system's factors-are most likely to shift system-level behaviour, known as leverage points. This application of network analysis, employed to quantitatively identify leverage points without having to use computational modelling approaches that translate CLDs into sets of mathematical equations, has however not been duly reflected upon. We evaluate whether using commonly applied network analysis metrics to identify leverage points is justified, focusing on betweenness- and closeness centrality. First, we assess whether the metrics identify the same leverage points based on CLDs that represent the same system but differ in inferred causal structure-finding that they provide unreliable results. Second, we consider conflicts between assumptions underlying the metrics and CLDs. We recognise six conflicts suggesting that the metrics are not equipped to take key information captured in CLDs into account. In conclusion, using betweenness- and closeness centrality to identify leverage points based on CLDs is at best premature and at worst incorrect-possibly causing erroneous identification of leverage points. This is problematic as, in current practice, the results can inform policy recommendations. Other quantitative or qualitative approaches that better correspond with the system dynamics perspective must be explored.

How theory can help to understand the potential impact of food environment policies on socioeconomic inequalities in diet: an application of Bourdieu's capital theory and the scarcity theory.

Government policies that promote healthy food environments are considered promising to reduce socioeconomic inequalities in diet. Empirical evidence of effects on these inequalities, however, is relatively scarce and, with a few exceptions, tends to be inconclusive. We use two contemporary theories that help to understand socioeconomic inequalities in health and health-related behaviours (Bourdieu's capital theory and Mullainathan and Shafir's scarcity theory) to reason how policies influencing food environments may differentially impact lower and higher socioeconomic groups. In essence, these theories enable us to understand how specific elements of broader daily living conditions (e.g. social practices that lead to habitus formation, material conditions that shape experiences of scarcity) may lead to a greater benefit of certain food environment policies for the healthfulness of diets of lower or higher socioeconomic groups. We conclude that the application of theories on the mechanisms underlying socioeconomic inequalities in health can help to guide future empirical studies in testing theory-based hypotheses on differential effects of policies, and thereby enhance the development of effective policies tackling socioeconomic inequalities in dietary intakes.

Dynamics of the complex food environment underlying dietary intake in low-income groups: a systems map of associations extracted from a systematic umbrella literature review.

BACKGROUND: Inequalities in obesity pertain in part to differences in dietary intake in different socioeconomic groups. Examining the economic, social, physical and political food environment of low-income groups as a complex adaptive system - i.e. a system of multiple, interconnected factors exerting non-linear influence on an outcome, can enhance the development and assessment of effective policies and interventions by honouring the complexity of lived reality. We aimed to develop and apply novel causal loop diagramming methods in order to construct an evidence-based map of the underlying system of environmental factors that drives dietary intake in low-income groups. METHODS: A systematic umbrella review was conducted on literature examining determinants of dietary intake and food environments in low-income youths and adults in high/upper-middle income countries. Information on the determinants and associations between determinants was extracted from reviews of quantitative and qualitative studies. Determinants were organised using the Determinants of Nutrition and Eating (DONE) framework. Associations were synthesised into causal loop diagrams that were subsequently used to interpret the dynamics underlying the food environment and dietary intake. The map was reviewed by an expert panel and systems-based analysis identified the system paradigm, structure, feedback loops and goals. RESULTS: Findings from forty-three reviews and expert consensus were synthesised in an evidence-based map of the complex adaptive system underlying the food environment influencing dietary intake in low-income groups. The system was interpreted as operating within a supply-and-demand, economic paradigm. Five sub-systems ('geographical accessibility', 'household finances', 'household resources', 'individual influences', 'social and cultural influences') were presented as causal loop diagrams comprising 60 variables, conveying goals which undermine healthy dietary intake. CONCLUSIONS: Our findings reveal how poor dietary intake in low-income groups can be presented as an emergent property of a complex adaptive system that sustains a food environment that increases the accessibility, availability, affordability and acceptability of unhealthy foods. In order to reshape system dynamics driving unhealthy food environments, simultaneous, diverse and innovative strategies are needed to facilitate longer-term management of household finances and socially-oriented practices around healthy food production, supply and intake. Ultimately, such strategies must be supported by a system paradigm which prioritises health.

Cross-sectional interactions between quality of the physical and social environment and self-reported physical activity in adults living in income-deprived communities.

BACKGROUND: Understanding the environmental determinants of physical activity in populations at high risk of inactivity could contribute to the development of effective interventions. Socioecological models of activity propose that environmental factors have independent and interactive effects of physical activity but there is a lack of research into interactive effects. OBJECTIVES: This study aimed to explore independent and interactive effects of social and physical environmental factors on self-reported physical activity in income-deprived communities. METHODS: Participants were 5,923 adults in Glasgow, United Kingdom. Features of the social environment were self-reported. Quality of the physical environment was objectively-measured. Neighbourhood walking and participation in moderate physical activity [MPA] on ≥5 days/week was self-reported. Multilevel multivariate logistic regression models tested independent and interactive effects of environmental factors on activity. RESULTS: 'Social support' (walking: OR:1.22,95%CI = 1.06-1.41,p<0.01; MPA: OR:0.79,95%CI = 0.67-0.94,p<0.01), 'social interaction' (walking: OR:1.25,95%CI = 1.10-1.42,p<0.01; MPA: OR:6.16,95%CI = 5.14-7.37,p<0.001) and 'cohesion and safety' (walking: OR:1.78,95%CI = 1.56-2.03,p<0.001; MPA: OR:1.93,95%CI = 1.65-2.27,p<0.001), but not 'trust and empowerment', had independent effects on physical activity. 'Aesthetics of built form' (OR:1.47,95%CI = 1.22-1.77,p<0.001) and 'aesthetics and maintenance of open space' (OR:1.32, 95%CI = 1.13-1.54,p<0.01) were related to walking. 'Physical disorder' (OR:1.63,95%CI = 1.31-2.03,p<0.001) had an independent effect on MPA. Interactive effects of social and physical factors on walking and MPA were revealed. CONCLUSIONS: Findings suggest that intervening to create activity-supportive environments in deprived communities may be most effective when simultaneously targeting the social and physical neighbourhood environment.