Exposure to food environments, diet and weight status in children

There is a growing interest in understanding how the built food environment influences health behaviours. Whilst policy interest in the influence of food environments on diet and body weight is growing, the evidence base is limited, particularly for environments beyond the home neighbourhood. Research in children is of particular importance, as it is known that dietary behaviours and weight tend to track into adulthood. This thesis addresses the gap in knowledge surrounding the influence of exposure to the food environment on weight and diet in children. It also takes into consideration the interactions with socio-economic status. Existing research exploring the environmental influences on diet and weight in children is reviewed, and a conceptual framework of key determinants identified is presented. Three studies are presented which investigate associations between different measures of exposure to the food environment and diet and weight. A systematic review investigating the use of GPS in studies of the food environment is also conducted. Additionally, a novel method for assessing environmental exposure is presented. The results from this research suggest that unhealthy food environments measured at an area level are generally conducive to weight gain and poorer diet, while the opposite is true for healthier food environments. Furthermore, this thesis supports the hypothesis that diet, weight and access to food are patterned by social class, and that the food environment partially mediates the well-known association between socio-economic status and weight status. However, findings were equivocal when using measuring exposure to the food environment at an individual level. This suggests that correctly measuring the characteristics of the food environment is important in order to disentangle their effects on health outcomes, and calls for efforts to attempt to reduce the heterogeneity in measures of the food environment employed

How can GPS technology help us better understand exposure to the food environment? A systematic review.

PURPOSE: Global Positioning Systems (GPS) are increasingly being used to objectively assess movement patterns of people related to health behaviours. However research detailing their application to the food environment is scarce. This systematic review examines the application of GPS in studies of exposure to food environments and their potential influences on health. METHODS: Based on an initial scoping exercise, published articles to be included in the systematic review were identified from four electronic databases and reference lists and were appraised and analysed, the final cut-off date for inclusion being January 2015. Included studies used GPS to identify location of individuals in relation to food outlets and link that to health or diet outcomes. They were appraised against a set of quality criteria. RESULTS: Six studies met the inclusion criteria, which were appraised to be of moderate quality. Newer studies had a higher quality score. Associations between observed mobility patterns in the food environment and diet related outcomes were equivocal. Findings agreed that traditional food exposure measures overestimate the importance of the home food environment. CONCLUSIONS: The use of GPS to measure exposure to the food environment is still in its infancy yet holds much potential. There are considerable variations and challenges in developing and standardising the methods used to assess exposure.AC was funded by the Lord Zuckerman PhD scholarship. APJ was partially supported by the Centre for Diet and Activity Research, a UK Clinical Research Collaboration Public Health Research Centre of Excellence. Funding from the British Heart Foundation, Department of Health, Economic and Social Research Council, Medical Research Council, and the Wellcome Trust, under the auspices of the UK Clinical Research Collaboration, is gratefully acknowledged.This is the final version of the article. It first appeared from Elsevier via http://dx.doi.org/10.1016/j.ssmph.2016.04.00

A novel methodology for identifying environmental exposures using GPS data

Aim: While studies using global positioning systems (GPS) have the potential to refine measures of exposure to the neighbourhood environment in health research, one limitation is that they do not typically identify time spent undertaking journeys in motorised vehicles when contact with the environment is reduced. This paper presents and tests a novel methodology to explore the impact of this concern. Methods: Using a case study of exposure assessment to food environments, an unsupervised computational algorithm is employed in order to infer two travel modes: motorised and non-motorised, on the basis of which trips were extracted. Additional criteria are imposed in order to improve robustness of the algorithm. Results: After removing noise in the GPS data and motorised vehicle journeys, 82.43% of the initial GPS points remained. In addition, after comparing a sub-sample of trips classified visually of motorised, non-motorised and mixed mode trips with the algorithm classifications, it was found that there was an agreement of 88%. The measures of exposure to the food environment calculated before and after algorithm classification were strongly correlated. Conclusion: Identifying non-motorised exposures to the food environment makes little difference to exposure estimates in urban children but might be important for adults or rural populations who spend more time in motorised vehicles.APJ was partially supported by the Centre for Diet and Activity Research (CEDAR), a UK Clinical Research Collaboration Public Health Research Centre of Excellence. Funding from the British Heart Foundation, Economic and Social Research Council, Medical Research Council, National Institute for Health Research and the Wellcome Trust, under the auspices of the UK Clinical Research Collaboration, is gratefully acknowledged

Can big data solve a big problem? Reporting the obesity data landscape in line with the Foresight obesity system map.

BACKGROUND: Obesity research at a population level is multifaceted and complex. This has been characterised in the UK by the Foresight obesity systems map, identifying over 100 variables, across seven domain areas which are thought to influence energy balance, and subsequent obesity. Availability of data to consider the whole obesity system is traditionally lacking. However, in an era of big data, new possibilities are emerging. Understanding what data are available can be the first challenge, followed by an inconsistency in data reporting to enable adequate use in the obesity context. In this study we map data sources against the Foresight obesity system map domains and nodes and develop a framework to report big data for obesity research. Opportunities and challenges associated with this new data approach to whole systems obesity research are discussed. METHODS: Expert opinion from the ESRC Strategic Network for Obesity was harnessed in order to develop a data source reporting framework for obesity research. The framework was then tested on a range of data sources. In order to assess availability of data sources relevant to obesity research, a data mapping exercise against the Foresight obesity systems map domains and nodes was carried out. RESULTS: A reporting framework was developed to recommend the reporting of key information in line with these headings: Background; Elements; Exemplars; Content; Ownership; Aggregation; Sharing; Temporality (BEE-COAST). The new BEE-COAST framework was successfully applied to eight exemplar data sources from the UK. 80% coverage of the Foresight obesity systems map is possible using a wide range of big data sources. The remaining 20% were primarily biological measurements often captured by more traditional laboratory based research. CONCLUSIONS: Big data offer great potential across many domains of obesity research and need to be leveraged in conjunction with traditional data for societal benefit and health promotion

Eating behaviour associated with differences in conflict adaptation for food pictures

Objective: The goal conflict model of eating (Stroebe, Mensink, Aarts, Schut, & Kruglanski, 2008) proposes differences in eating behaviour result from peoples’ experience of holding conflicting goals of eating enjoyment and weight maintenance. However, little is understood about the relationship between eating behaviour and the cognitive processes involved in conflict. This study aims to investigate associations between eating behaviour traits and cognitive conflict processes, specifically the application of cognitive control when processing distracting food pictures. Method: A flanker task using food and non-food pictures was used to examine individual differences in conflict adaptation. Participants responded to target pictures whilst ignoring distracting flanking pictures. Individual differences in eating behaviour traits, attention towards target pictures, and ability to apply cognitive control through adaptation to conflicting picture trials were analysed. Results: Increased levels of external and emotional eating were related to slower responses to food pictures indicating food target avoidance. All participants showed greater distraction by food compared to non-food pictures. Of particular significance, increased levels of emotional eating were associated with greater conflict adaptation for conflicting food pictures only. Conclusion: Emotional eaters demonstrate greater application of cognitive control for conflicting food pictures as part of a food avoidance strategy. This could represent an attempt to inhibit their eating enjoyment goal in order for their weight maintenance goal to dominate

Examining the validity and utility of two secondary sources of food environment data against street audits in England

Background: Secondary data containing the locations of food outlets is increasingly used in nutrition and obesity research and policy. However, evidence evaluating these data is limited. This study validates two sources of secondary food environment data: Ordnance Survey Points of Interest data (POI) and food hygiene data from the Food Standards Agency (FSA), against street audits in England and appraises the utility of these data. Methods: Audits were conducted across 52 Lower Super Output Areas in England. All streets within each Lower Super Output Area were covered to identify the name and street address of all food outlets therein. Audit-identified outlets were matched to outlets in the POI and FSA data to identify true positives (TP: outlets in both the audits and the POI/FSA data), false positives (FP: outlets in the POI/FSA data only) and false negatives (FN: outlets in the audits only). Agreement was assessed using positive predictive values (PPV: TP/(TP+FP)) and sensitivities (TP/(TP+FN)). Variations in sensitivities and PPVs across environment and outlet types were assessed using multi-level logistic regression. Proprietary classifications within the POI data were additionally used to classify outlets, and agreement between audit-derived and POI-derived classifications was assessed. Results: Street audits identified 1172 outlets, compared to 1100 and 1082 for POI and FSA respectively. PPVs were statistically significantly higher for FSA (0.91, CI: 0.89-0.93) than for POI (0.86, CI: 0.84-0.88). However, sensitivity values were not different between the two datasets. Sensitivity and PPVs varied across outlet types for both datasets. Without accounting for this, POI had statistically significantly better PPVs in rural and affluent areas. After accounting for variability across outlet types, FSA had statistically significantly better sensitivity in rural areas and worse sensitivity in rural middle affluence areas (relative to deprived). Audit-derived and POI-derived classifications exhibited substantial agreement (p < 0.001; Kappa = 0.66, CI: 0.63 - 0.70). Conclusions: POI and FSA data have good agreement with street audits; although both datasets had geographic biases which may need to be accounted for in analyses. Use of POI proprietary classifications is an accurate method for classifying outlets, providing time savings compared to manual classification of outlets

Is adolescent body mass index and waist circumference associated with the food environments surrounding schools and homes? A longitudinal analysis

Background: There has been considerable interest in the role of access to unhealthy food options as a determinant of weight status. There is conflict across the literature as to the existence of such an association, partly due to the dominance of cross-sectional study designs and inconsistent definitions of the food environment. The aim of our study is to use longitudinal data to examine if features of the food environment are associated to measures of adolescent weight status. Methods: Data were collected from secondary schools in Leeds (UK) and included measurements at school years 7 (ages 11/12), 9 (13/14), and 11 (15/16). Outcome variables, for weight status, were standardised body mass index and standardised waist circumference. Explanatory variables included the number of fast food outlets, supermarkets and ‘other retail outlets’ located within a 1 km radius of an individual’s home or school, and estimated travel route between these locations (with a 500 m buffer). Multi-level models were fit to analyse the association (adjusted for confounders) between the explanatory and outcome variables. We also examined changes in our outcome variables between each time period. Results: We found few associations between the food environment and measures of adolescent weight status. Where significant associations were detected, they mainly demonstrated a positive association between the number of amenities and weight status (although effect sizes were small). Examining changes in weight status between time periods produced mainly non-significant or inconsistent associations. Conclusions: Our study found little consistent evidence of an association between features of the food environment and adolescent weight status. It suggests that policy efforts focusing on the food environment may have a limited effect at tackling the high prevalence of obesity if not supported by additional strategies

Weight gain in mid-childhood and its relationship with the fast food environment

© The Author 2017. Published by Oxford University Press on behalf of Faculty of Public Health. All rights reserved. Background Childhood obesity is a serious public health issue. Understanding environmental factors and their contribution to weight gain is important if interventions are to be effective. Aims The purpose of this research was to assess the relationship between weight gain in children and accessibility of fast-food outlets. Methods A longitudinal sample of 1577 children was created using two time points from the National Child Measurement Programme in South Gloucestershire (2006/7 and 2012/13). A spatial analysis was conducted using a weighted accessibility score on the number of fast-food outlets within a 1-km network radius of each child's residence to quantify access to fast food. Results The mean accessibility score for all children was 0.73 (standard deviation: 1.14). Fast-food outlets were more prevalent in areas of deprivation. A moderate association was found between deprivation score and accessibilty score (r = 0.4, P 50 percentile points) compared to children who had no access to fast-food outlets. Conclusions This paper supports previous research that fast-food outlets are more prevalent in areas of deprivation and presents new evidence on fast-food outlets as a potential contributor towards weight gain in mid-childhood

An exploration of solutions for improving access to affordable fresh food with disadvantaged Welsh communities

Our research is rooted in community operational research (community OR) and adopts a qualitative problem structuring approach to exploring potential solutions for addressing inequality in access to affordable healthy food in disadvantaged communities in Wales, UK. Existing food provisions are synthesised and barriers to their effectiveness are identified. A portfolio of actions and commitment packages is co-developed with multiple stakeholders in order to bring about desired changes. Although these solutions address concerns specific to local Welsh communities, they can be generalised and applied in similar settings where food desert problems prevail. We draw upon insights from the literature on inequality, food deserts, and social capital to conceptualise the solutions around both material (providing and accessing) and social (reconnecting and strengthening) aspects. By addressing both material and social aspects simultaneously, we show how community-driven intervention can contribute to reducing inequality in disadvantaged communities. Our research experience reveals that COR is particularly effective in tackling a ‘wicked’ problem such as food deserts, and allows researchers to engage with communities, gain an understanding about the problematic situation and guide intervention efforts in a sustainable and systemic manner. A number of methodological reflections are offered as a way to contribute to the development of the field as a whole