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.

Background: Whole‐systems approaches (WSAs) are well placed to tackle the complex local environmental influences on overweight and obesity, yet there are few examples of WSAs in practice. Amsterdam Healthy Weight Approach (AHWA) is a long‐term, municipality‐led program to improve children's physical activity, diet, and sleep through action in the home, neighborhood, school, and city. Adopting a WSA, local political, physical, social, educational, and healthcare drivers of childhood obesity are viewed as a complex adaptive system. Since 2013, AHWA has reached >15,000 children. During this time, the estimated prevalence of 2–18‐year‐olds with overweight or obesity in Amsterdam has declined from 21% in 2012 to 18.7% in 2017. Declining trends are rarely observed in cities. There is a need to formally articulate AHWA program theory in order to: (i) inform future program evaluation which can interpret this decline within the context of AHWA and (ii) contribute a real‐life example of a WSA to the literature.Methods: This study aimed to formally document the program theory of AHWA to permit future evaluation. A logic framework was developed through extensive document review and discussion, during program implementation.Results: The working principles of the WSA underpinning AHWA were made explicit in an overarching theory of change, articulated in a logic framework. The framework was operationalized using an illustrative example of sugar intake.Conclusions: The logic framework will inform AHWA development, monitoring, and evaluation and responds to a wider need to outline the working principles of WSAs in public health.

Ecological models of physical activity posit that social and physical environmental features exert independent and interactive influences on physical activity, but previous research has focussed on independent influences. This systematic review aimed to synthesise the literature investigating how features of neighbourhood physical and social environments are associated with physical activity when both levels of influence are simultaneously considered, and to assess progress in the exploration of interactive effects of social and physical environmental correlates on physical activity. A systematic literature search was conducted in February 2016. Articles were included if they used an adult (≥15 years) sample, simultaneously considered at least one physical and one social environmental characteristic in a single statistical model, used self-reported or objectively-measured physical activity as a primary outcome, reported findings from quantitative, observational analyses and were published in a peer-reviewed journal. Combined measures including social and physical environment items were excluded as they didn't permit investigation of independent and interactive social and physical effects. Forty-six studies were identified. An inconsistent evidence base for independent environmental correlates of physical activity was revealed, with some support for specific physical and social environment correlates. Most studies found significant associations between physical activity and both physical and social environmental variables. There was preliminary evidence that physical and social environmental variables had interactive effects on activity, although only 4 studies examined interactive effects. Inconsistent evidence of independent associations between environmental variables and physical activity could be partly due to unmeasured effect modification (e.g. interactive effects) creating unaccounted variance in relationships between the environment and activity. Results supported multiple levels of environmental influence on physical activity. It is recommended that further research uses simultaneous or interaction analyses to gain insight into complex relationships between neighbourhood social and physical environments and physical activity, as there is currently limited research in this area.

Individuals in office-based occupations have low levels of physical activity but there is little research into the socio-ecological correlates of workplace activity. To identify factors contributing to office-based workers’ perceptions of the office environment and explore cross-sectional relationships between these factors and occupational physical activity. Participants in the Active Buildings study reported perceptions of their office environment using the Movement at Work Survey. A principal component analysis (PCA) was conducted on survey items. A sub-sample wore the ActivPAL^3TM accelerometer for ≥3 workdays to measure occupational step count, standing, sitting and sit-to-stand transitions. Linear regression analyses assessed relationships between environmental perceptions and activity. There were 433 participants, with accelerometer data available for 115 participants across 11 organ izations. The PCA revealed four factors: (i) perceived distance to office destinations, (ii) perceived office aesthetics and comfort, (iii) perceived office social environment and (iv) perceived management discouragement of unscheduled breaks. Younger participants perceived office destinations as being closer to their desk. Younger and female participants perceived more positive office social environments; there were no other socio-demographic differences. Within the sub-sample with accelerometer data, perceived discouragement of breaks by management was related to occupational step count/hour (B = −64.5; 95% CI −109.7 to −19.2). No other environmental perceptions were related to activity or sitting. Perceived managerial discouragement of breaks could be related to meaningful decreases in occupational step count. Future research should aim to elucidate the role of the workplace socio-cultural environment in occupational walking, with a focus on the role of management.

The importance of physical activity to paediatric health warrants investigation into its determinants. Objective measurement allows a robust examination of genetic and environmental influences on physical activity. To systematically review the evidence on the extent of genetic and environmental influence on children's objectively-measured activity levels from twin studies. Medline, EMBASE, PsycINFO, Health and Psychosocial Instruments and all Ovid Databases. Search terms: "accelerometer" OR "actometer" OR "motion sensor" OR "heart rate monitor" OR "physical activity energy expenditure" AND "twin". Limited to Human, English language and children (0-18 years). Seven sets of analyses were included in the review. Six analyses examined children's daily-life activity and found that the shared environment had a strong influence on activity levels (weighted mean 60%), with a smaller contribution from genetic factors (weighted mean 21%). Two analyses examined short-term, self-directed activity in a standard environment and found a smaller shared environment effect (weighted mean 25%) and a larger genetic estimate (weighted mean 45%). Although genetic influences may be expressed when children have brief opportunities for autonomous activity, activity levels in daily-life are predominantly explained by environmental factors. Future research should aim to identify key environmental drivers of childhood activity.

Office-based workers spend a large proportion of the day sitting and tend to have low overall activity levels. Despite some evidence that features of the external physical environment are associated with physical activity, little is known about the influence of the spatial layout of the internal environment on movement, and the majority of data use self-report. This study investigated associations between objectively-measured sitting time and activity levels and the spatial layout of office floors in a sample of UK office-based workers. Participants wore activPAL accelerometers for at least three consecutive workdays. Primary outcomes were steps and proportion of sitting time per working hour. Primary exposures were office spatial layout, which was objectively-measured by deriving key spatial variables: ‘distance from each workstation to key office destinations’, ‘distance from participant’s workstation to all other workstations’, ‘visibility of co-workers’, and workstation ‘closeness’. 131 participants from 10 organisations were included. Fifty-four per cent were female, 81% were white, and the majority had a managerial or professional role (72%) in their organisation. The average proportion of the working hour spent sitting was 0.7 (SD 0.15); participants took on average 444 (SD 210) steps per working hour. Models adjusted for confounders revealed significant negative associations between step count and distance from each workstation to all other office destinations (e.g., B = −4.66, 95% CI: −8.12, −1.12, p < 0.01) and nearest office destinations (e.g., B = −6.45, 95% CI: −11.88, −0.41, p < 0.05) and visibility of workstations when standing (B = −2.35, 95% CI: −3.53, −1.18, p < 0.001). The magnitude of these associations was small. There were no associations between spatial variables and sitting time per work hour. Contrary to our hypothesis, the further participants were from office destinations the less they walked, suggesting that changing the relative distance between workstations and other destinations on the same floor may not be the most fruitful target for promoting walking and reducing sitting in the workplace. However, reported effect sizes were very small and based on cross-sectional analyses. The approaches developed in this study could be applied to other office buildings to establish whether a specific office typology may yield more promising results.