Alexia Sawyer

Despite the need to transform food systems to improve human and planetary health, the activities and actors of food systems remain largely intransigent to change. The Mandala research consortium offers a case study of how three methodological principles—interdisciplinary science, systems thinking and stakeholder collaboration—can be integrated to identify interventions with transformative potential in an urban food system. An existing conceptual framework was employed to interrogate the case study and reflect on the challenges and opportunities of its methods across two phases: (i) understanding the food system and identifying places to intervene; (ii) envisioning and prioritizing food system interventions. Ambitions to work across the breadth of the urban food system were supported by interdisciplinary science and stakeholder collaboration; tailoring the research process accommodated the epistemic, social, symbolic, spatial and temporal differences between stakeholders. A complex adaptive systems approach enabled identification of promising food system interventions. Nevertheless, challenges arose in every aspect of the work. A collaborative interdisciplinary systems approach to system transformation was articulated using a real-world example. While opportunities support the funding and design of research using a similar methodological approach, the documented challenges of adopting this approach may be overcome with practical solutions. This article is part of the theme issue ‘Transforming terrestrial food systems for human and planetary health’.

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.

Habitual behaviours are learned responses that are triggered automatically by associated environmental cues. The unvarying nature of most workplace settings makes workplace physical activity a prime candidate for a habitual behaviour, yet the role of habit strength in occupational physical activity has not been investigated. Aims of the present study were to: (i) document occupational physical activity habit strength; and (ii) investigate associations between occupational activity habit strength and occupational physical activity levels. A sample of UK office-based workers (n = 116; 53% female, median age 40 years, SD 10.52) was fitted with activPAL accelerometers worn for 24 h on five consecutive days, providing an objective measure of occupational step counts, stepping time, sitting time, standing time and sit-to-stand transitions. A self-report index measured the automaticity of two occupational physical activities (“being active” (e.g., walking to printers and coffee machines) and “stair climbing”). Adjusted linear regression models investigated the association between occupational activity habit strength and objectively-measured occupational step counts, stepping time, sitting time, standing time and sit-to-stand transitions. Eighty-one per cent of the sample reported habits for “being active”, and 62% reported habits for “stair climbing”. In adjusted models, reported habit strength for “being active” were positively associated with average occupational sit-to-stand transitions per hour (B = 0.340, 95% CI: 0.053 to 0.627, p = 0.021). “Stair climbing” habit strength was unexpectedly negatively associated with average hourly stepping time (B = −0.01, 95% CI: −0.01 to −0.00, p = 0.006) and average hourly occupational step count (B = −38.34, 95% CI: −72.81 to −3.88, p = 0.030), which may reflect that people with stronger stair-climbing habits compensate by walking fewer steps overall. Results suggest that stair-climbing and office-based occupational activity can be habitual. Interventions might fruitfully promote habitual workplace activity, although, in light of potential compensation effects, such interventions should perhaps focus on promoting moderate-intensity 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.

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. This study aimed to explore independent and interactive effects of social and physical environmental factors on self-reported physical activity in income-deprived communities. 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. ‘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. 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.

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.

Research supporting relationships between sleep quality, weight, depression and anxiety has typically examined the relationships separately rather than simultaneously, potentially hampering insights into the characteristics of reported links. This study aimed to fill this gap in the research to provide further insight into the factors associated with sleep. Data from wave 4 of the G1219 cohort were used in cross-sectional analyses. The sample comprised 1392 adult twins and siblings aged 18–27 years. Participants completed a self-report questionnaire which included the Pittsburgh Sleep Quality Index as a measure of sleep quality, the Short Mood and Feelings Questionnaire as a measure of depression symptoms and the Revised Symptoms of Anxiety Scale as a measure of anxiety symptoms. Participants were asked to self-report general health and weight and height so researchers could derive weight status from measures of body mass index. An analysis of covariance including weight status, depression, anxiety and general health as predictors and sleep quality as the outcome revealed main effects of depression (F(3,1163) = 10.93, p < 0.001) and general health (F(4,1163) = 5.72, p < 0.001) only. A direct relationship between weight and sleep should not be assumed as it is possible that the relationship is at least in part accounted for by depression symptoms or general health. Depression symptoms and general health may also account for the association between sleep quality and anxiety symptoms in young adults.