The neighbourhood matters: studying exposures relevant to childhood obesity and the policy implications in Leeds, UK. Issue 3 (24th August 2009)

• Record Type: Journal Article
• Authors: Edwards, K L; Clarke, G P; Ransley, J K; Cade, J
• Is Part Of: Journal of epidemiology and community health. Volume 64:Issue 3(2010)
• Page Start: 194
• Page End: 201
• Publication Date: 2009-08-24
• Subjects: Childhood obesity -- geographically weighted regression -- public health policy -- spatial microsimulation modelling -- UK -- child health -- geography FQ -- Obesity EPI -- small-area stats; Public health -- Periodicals; Epidemiology -- Periodicals; 614.4
• DOI: 10.1136/jech.2009.088906
• Languages: English
• ISSNs: 0143-005X

Abstract

Abstract : 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.