Graham Clarke

The Geography of Fast Food Outlets: A Review

The availability of food high in fat, salt and sugar through Fast Food (FF) or takeaway outlets, is implicated in the causal pathway for the obesity epidemic. This review aims to summarise this body of research and highlight areas for future work. Thirty three studies were found that had assessed the geography of these outlets. Fourteen studies showed a positive association between availability of FF outlets and increasing deprivation. Another 13 studies also included overweight or obesity data and showed conflicting results between obesity/overweight and FF outlet availability. There is some evidence that FF availability is associated with lower fruit and vegetable intake. There is potential for land use policies to have an influence on the location of new FF outlets. Further research should incorporate good quality data on FF consumption, weight and physical activity.

Food retail change and the growth of food deserts: a case study of Cardiff

“Food deserts” in British cities are partly the result of the expansion of multiple food retailing. New large stores force smaller stores to close down, thus depriving local residents of food shopping opportunities. Examines this proposition through an analysis of changes in consumer access to food shopping in Cardiff over the last 20 years. Shows that although accessibility scores have increased in Cardiff since 1980 they have increased at a faster rate in higher income areas. In a pocket of deprived areas accessibility has declined over the decade. Thus, there has been a polarisation effect with a widening gap in accessibility scores across the city.

Fast Food and Obesity: A Spatial Analysis in a Large United Kingdom Population of Children Aged 13–15

BACKGROUND The childhood obesity epidemic is a current public health priority in many countries, and the consumption of fast food has been associated with obesity. PURPOSE This study aims to assess the relationship between fast-food consumption and obesity as well as the relationship between fast-food outlet access and consumption in a cohort of United Kingdom teenagers. METHODS A weighted accessibility score of the number of fast-food outlets within a 1-km network buffer of the participants residence at age 13 years was calculated. Geographically weighted regression was used to assess the relationships between fast-food consumption at age 13 years and weight status at ages 13 and 15 years, and separately between fast-food accessibility and consumption. Data were collected from 2004 to 2008. RESULTS The consumption of fast food was associated with a higher BMI SD score (β=0.08, 95% CI=0.03, 0.14); higher body fat percentage (β=2.06, 95% CI=1.33, 2.79); and increased odds of being obese (OR=1.23, 95% CI=1.02, 1.49). All these relationships were stationary and did not vary over space in the study area. The relationship between the accessibility of outlets and consumption did vary over space, with some areas (more rural areas) showing that increased accessibility was associated with consumption, whereas in some urban areas increased accessibility was associated with lack of consumption. CONCLUSIONS There is continued need for nutritional education regarding fast food, but public health interventions that place restrictions on the location of fast-food outlets may not uniformly decrease consumption.

Improving the Synthetic Data Generation Process in Spatial Microsimulation Models

Simulation models are increasingly used in applied research to create synthetic micro-populations and predict possible individual-level outcomes of policy intervention. Previous research highlights the relevance of simulation techniques in estimating the potential outcomes of changes in areas such as taxation and child benefit policy, crime, education, or health inequalities. To date, however, there is very little published research on the creation, calibration, and testing of such micro-populations and models, and little on the issue of how well synthetic data can fit locally as opposed to globally in such models. This paper discusses the process of improving the process of synthetic micropopulation generation with the aim of improving and extending existing spatial microsimulation models. Experiments using different variable configurations to constrain the models are undertaken with the emphasis on producing a suite of models to match the different sociodemographic conditions found within a typical city. The results show that creating processes to generate area-specific synthetic populations, which reflect the diverse populations within the study area, provides more accurate population estimates for future policy work than the traditional global model configurations.

Predicting breastfeeding in women living in areas of economic hardship: Explanatory role of the theory of planned behaviour.

This study employed the theory of planned behaviour (TPB) and additional variables (descriptive norm, moral norm, self-identity) to investigate the factors underlying breastfeeding intention and subsequent breastfeeding at four time points (during hospital stay, at hospital discharge, 10 days postpartum and 6 weeks postpartum) in a sample of women selected from defined areas of economic hardship (N = 248). A model containing the TPB, additional variables and demographic factors provided a good prediction of both intention (R 2 = 0.72; attitude, perceived behavioural control, moral norm and self-identity significant predictors) and behaviour – breastfeeding at birth (88.6% correctly classified; household deprivation, intention, attitude significant), at discharge from hospital (87.3% correctly classified; intention, attitude significant), 10 days after discharge (83.1% correctly classified; education, intention, attitude, descriptive norm significant) and 6 weeks after discharge (78.0% correctly classified; age, household deprivation, ethnicity, moral norm significant). Implications for interventions are discussed, such as the potential usefulness of targeting descriptive norms, moral norms and perceived behavioural control (PBC) when attempting to increase breastfeeding uptake.

The neighbourhood matters: studying exposures relevant to childhood obesity and the policy implications in Leeds, UK

Background Reducing childhood obesity is a key UK government target. Obesogenic environments are one of the major explanations for the rising prevalence and thus a constructive focus for preventive strategies. Spatial analysis techniques are used to provide more information about obesity at the neighbourhood level in order to help to shape local obesity-prevention policies. Methods Childhood obesity was defined by body mass index, using cross-sectional height and weight data for children aged 3–13 years (obesity>98th centile; British reference dataset). Relationships between childhood obesity and 12 simulated obesogenic variables were assessed using geographically weighted regression. These results were applied to three wards with different socio-economic backgrounds, tailoring local obesity-prevention policy. Results The spatial distribution of childhood obesity varied, with high prevalence in deprived and affluent areas. Key local covariates strongly associated with childhood obesity differed: in the affluent ward, they were perceived neighbourhood safety and fruit and vegetable consumption; in the deprived ward, expenditure on food, purchasing school meals, multiple television ownership and internet access; in all wards, perceived access to supermarkets and leisure facilities. Accordingly, different interventions/strategies may be more appropriate/effective in different areas. Conclusions These analyses identify the covariates with the strongest local relationships with obesity and suggest how policy can be tailored to the specific needs of each micro-area: solutions need to be tailored to the locality to be most effective. This paper demonstrates the importance of small-area analysis in order to provide health planners with detailed information that may help them to prioritise interventions for maximum benefit.

The design and validation of a spatial microsimulation model of obesogenic environments for children in Leeds, UK: SimObesity☆☆☆

Obesogenic environments are a major explanation for the rapidly increasing prevalence in obesity. Investigating the relationship between obesity and obesogenic variables at the micro-level will increase our understanding about local differences in risk factors for obesity. SimObesity is a spatial microsimulation model designed to create micro-level estimates of obesogenic environment variables in the city of Leeds in the UK: consisting of a plethora of health, environment, and socio-economic variables. It combines individual micro-data from two national surveys with a coarse geography, with geographically finer scaled data from the 2001 UK Census, using a reweighting deterministic algorithm. This creates a synthetic population of individuals/households in Leeds with attributes from both the survey and census datasets. Logistic regression analyses identify suitable constraint variables to use. The model is validated using linear regression and equal variance t-tests. Height, weight, age, gender, and residential postcode data were collected on children aged 3-13 years in the Leeds metropolitan area, and obesity described as above the 98th centile for the British reference dataset. Geographically weighted regression is used to investigate the relationship between different obesogenic environments and childhood obesity. Validation shows that the small-area estimates were robust. The different obesogenic environments, as well as the parameter estimates from the corresponding local regression analyses, are mapped, all of which demonstrate non-stationary relationships. These results show that social capital and poverty are strongly associated with childhood obesity. This paper demonstrates a methodology to estimate health variables at the small-area level. The key to this technique is the choice of the models input variables, which must be predictors for the output variables; this factor has not been stressed in other spatial microsimulation work. It also provides further evidence for the existence of obesogenic environments for children.

Retail Saturation, Retail Location, and Retail Competition: An Analysis of British Grocery Retailing

The appreciably dramatic idea that British grocery retailing is facing imminent saturation has attracted increasing attention particularly since the mid-1980s to late 1980s. In this paper we seek to review and attempt to sophisticate the debate over saturation by providing a detailed discussion and spatial analysis of current levels of retail provision. This analysis, in itself, offers a view of the potential for future retail expansion. We argue here, however, that spatial patterns of retail provision must be interpreted carefully, particularly given the profoundly different competitive conditions that characterise British grocery retailing in the 1990s as compared with the 1980s. In considering both the spatial patterns of, and competitive processes underlying, British food retailing, we offer an account of recent retail geography in a way that synthesises approaches that are all too frequently presented as antagonistic.

GIS and microsimulation for local labour market analysis

This paper outlines the findings of ongoing research on ways of employing and combining geographical information systems (GIS) and microsimulation methodologies for the evaluation and analysis of local labour market problems and policies. First, it is shown how data sets from different sources are integrated to create an urban labour market GIS. In the context of this information system, ways of mapping thematically the local labour market demand and supply are presented. In addition, travel-to-work flows are mapped and it is demonstrated how this data can be used to build local labour market Spatial Interaction Models. Further, it is shown how GIS can be combined with microsimulation techniques to highlight urban problems and enhance the analysis and evaluation of potential social and employment policies. In particular, it is shown how GIS and microsimulation can be used as tools in order to analyse a regions economy and labour market and to estimate the degree of labour market segmentation and socio-economic dualism within an urban system. Also, it is outlined how what-if spatial policy analysis of local labour markets can be performed (i.e. simulating new policy initiatives, firm closures, changes in benefit policies and performing regional multiplier analysis). Finally, the paper presents outputs from SimLeeds, which is a spatial microsimulation model for the Leeds labour market, and explores the potential of GIS combined with microsimulation modelling to create a new framework for the formulation, analysis and evaluation of socio-economic policies at the individual or household level.

Using geographical information systems and spatial microsimulation for the analysis of health inequalities.

The paper presents a spatial microsimulation approach to the analysis of health inequalities. A dynamic spatial microsimulation model of Britain, under development at the Universities of Leeds and Sheffield, uses data from the censuses of 1971, 1981 and 1991 and the British Household Panel Survey to simulate urban and regional populations in Britain. Geographical information systems and spatial microsimulation are used for the analysis of health inequalities in British regions in a 30 year simulation. The interdependencies between socio-economic characteristics and health variables such as limiting long-term illness are discussed. One of the innovative features of the model is the estimation of variables such as household income at the small area level, which can then be used to classify individuals. The health situation of different simulated individuals in different areas is investigated and the role of socio-economic characteristics in determining health is evaluated.