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D. Ballas (2004)
Simulating trends in poverty and income inequality on the basis of 1991 and 2001 census data: a tale of two citiesArea, 36
K. Procter, G. Clarke, J. Ransley (2008)
Micro-level analysis of childhood obesity, diet, physical activity, residential socioeconomic and social capital variables: where are the obesogenic
M. Tomintz, G. Clarke, J. Rigby (2008)
The geography of smoking in Leeds: estimating individual smoking rates and the implications for the location of stop smoking servicesArea, 40
A. González, S. Sweetland, E. Spencer (2003)
A meta-analysis of obesity and the risk of pancreatic cancerBritish Journal of Cancer, 89
G. Danaei, S. Hoorn, Alan Lopez, C. Murray, M. Ezzati (2005)
Causes of cancer in the world: comparative risk assessment of nine behavioural and environmental risk factorsThe Lancet, 366
D. Ballas, G. Clarke (2001)
Modelling the Local Impacts of National Social Policies: A Spatial Microsimulation ApproachEnvironment and Planning C: Government and Policy, 19
R. Summerbell, N. Logan, M. Parsons, M. Power (1999)
Childhood predictors of adult obesity: a systematic review.International journal of obesity and related metabolic disorders : journal of the International Association for the Study of Obesity, 23 Suppl 8
A. Timperio, J. Salmon, A. Telford, D. Crawford (2005)
Perceptions of local neighbourhood environments and their relationship to childhood overweight and obesityInternational Journal of Obesity, 29
E. Frezza, M. Wachtel, M. Chiriva-Internati (2005)
Influence of obesity on the risk of developing colon cancerGut, 55
K. Edwards, G. Clarke (2009)
The design and validation of a spatial microsimulation model of obesogenic environments for children in Leeds, UK: SimObesity.Social science & medicine, 69 7
S. Larsson, A. Wolk (2007)
Obesity and colon and rectal cancer risk: a meta-analysis of prospective studies.The American journal of clinical nutrition, 86 3
M. Okasha, P. McCarron, J. Mcewen, J. Durnin, G. Smith (2003)
Childhood social class and adulthood obesity: findings from the Glasgow Alumni CohortJournal of Epidemiology and Community Health, 57
T. Key, N. Allen, E. Spencer, R. Travis (2002)
The effect of diet on risk of cancerThe Lancet, 360
B. Anderson (2009)
Welsh small area estimates of income deprivation
R. Kaaks, A. Lukanova, M. Kurzer (2002)
Obesity , Endogenous Hormones , and Endometrial Cancer Risk : A Synthetic Review 1
C. Baum, C. Ruhm (2007)
Age, Socioeconomic Status and Obesity GrowthLabor: Human Capital
A. Lake, T. Townshend, S. Alvanides (2010)
Obesogenic Environments: complexities, perceptions and objective measures
C. Ross (2000)
Walking, exercising, and smoking: does neighborhood matter?Social science & medicine, 51 2
KL Procter, GP Clarke, JK Ransley, J Cade (2008)
Micro-level analysis of childhood obesity, diet, physical activity, residential socio-economic and social capital variables: where are the obesogenic environments in Leeds?Area, 40
IH Langford (1994)
Using Empirical Bayes estimates in the geographical analysis of disease riskArea, 26
N. Wrigley (2002)
'Food Deserts' in British Cities: Policy Context and Research PrioritiesUrban Studies, 39
H. Møller, A. Mellemgaard, K. Lindvig, J. Olsen (1994)
Obesity and cancer risk: a Danish record-linkage study.European journal of cancer, 30A 3
David Voas, P. Williamson (2001)
Evaluating Goodness-of-Fit Measures for Synthetic MicrodataGeographical and Environmental Modelling, 5
D. Ballas, G. Clarke, D. Dorling, J. Rigby, B. Wheeler (2006)
Using geographical information systems and spatial microsimulation for the analysis of health inequalitiesHealth Informatics Journal, 12
J. Mohan, L. Twigg, S. Barnard, K. Jones (2005)
Social capital, geography and health: a small-area analysis for England.Social science & medicine, 60 6
F. Bianchini, R. Kaaks, H. Vainio (2002)
Overweight, obesity, and cancer risk.The Lancet. Oncology, 3 9
J. Lovejoy, A. Sainsbury (2009)
Sex differences in obesity and the regulation of energy homeostasisObesity Reviews, 10
P. Scarborough, S. Allender, M. Rayner, M. Goldacre (2009)
Validation of model-based estimates (synthetic estimates) of the prevalence of risk factors for coronary heart disease for wards in England.Health & place, 15 2
J. Peto (2001)
Cancer epidemiology in the last century and the next decadeNature, 411
C. Power, T. Parsons (2000)
Nutritional and other influences in childhood as predictors of adult obesityProceedings of the Nutrition Society, 59
Stephanie Coen, N. Ross (2006)
Exploring the material basis for health: characteristics of parks in Montreal neighborhoods with contrasting health outcomes.Health & place, 12 4
D. Ballas, D. Rossiter, Bethan Thomas, G. Clarke, D. Dorling (2004)
Geography Matters: Simulating the Local Impacts of National Social Policies
S. Curtis, B. Cave, A. Coutts (2002)
Is Urban Regeneration Good for Health? Perceptions and Theories of the Health Impacts of Urban ChangeEnvironment and Planning C: Government and Policy, 20
(2003)
WHO: World Cancer Report
Karyn Morrissey, G. Clarke, D. Ballas, S. Hynes, C. O’Donoghue (2008)
Examining access to GP services in rural Ireland using microsimulation analysisArea, 40
A. Gatrell, S. Elliott (2001)
Geographies of Health: An Introduction
T. Dummer, M. Gibbon, A. Hackett, G. Stratton, Sue Taylor (2005)
Is overweight and obesity in 9–10-year-old children in Liverpool related to deprivation and/or electoral ward when based on school attended?Public Health Nutrition, 8
A. Leyland, C. Davies (2005)
Empirical Bayes methods for disease mappingStatistical Methods in Medical Research, 14
A. Bergström, P. Pisani, V. Tenet, A. Wolk, H. Adami (2001)
Overweight as an avoidable cause of cancer in EuropeInternational Journal of Cancer, 91
Melissa Nelson, P. Gordon-Larsen, Yan Song, B. Popkin (2006)
Built and social environments associations with adolescent overweight and activity.American journal of preventive medicine, 31 2
EFuller. DJotangia, Y-K Tu, A. Woolston, P. Baxter, M. Gilthorpe
IN ENGLAND: FINDINGS FROM THE SMOKING,
Dianna Smith, G. Clarke, K. Harland (2009)
Improving the Synthetic Data Generation Process in Spatial Microsimulation ModelsEnvironment and Planning A, 41
M. Kulldorff (1997)
A spatial scan statisticCommunications in Statistics-theory and Methods, 26
P Rees, DM Martin, P Williamson (2002)
The Census Data System, (chapter 1)
S. Asthana, S. Curtis, C. Duncan, M. Gould (2002)
Themes in British health geography at the end of the century: a review of published research 1998-2000.Social science & medicine, 55 1
G. Clarke, H. Eyre, C. Guy (2002)
Deriving Indicators of Access to Food Retail Provision in British Cities: Studies of Cardiff, Leeds and BradfordUrban Studies, 39
D. Josefson (2001)
Obesity and inactivity fuel global cancer epidemicBMJ : British Medical Journal, 322
S. Macintyre, A. Ellaway, S. Cummins (2002)
Place effects on health: how can we conceptualise, operationalise and measure them?Social science & medicine, 55 1
A. Whelan, N. Wrigley, D. Warm, E.J.S. Cannings (2002)
Life in a 'Food Desert'Urban Studies, 39
R. Hardy, M. Wadsworth, D. Kuh (2000)
The influence of childhood weight and socioeconomic status on change in adult body mass index in a British national birth cohortInternational Journal of Obesity, 24
M. Allman-Farinelli, T. Chey, A. Bauman, T. Gill, W. James (2008)
Age, period and birth cohort effects on prevalence of overweight and obesity in Australian adults from 1990 to 2000European Journal of Clinical Nutrition, 62
G. Clarke (1996)
Microsimulation for urban and regional policy analysis
P. Zaninotto, J. Head, E. Stamatakis, H. Wardle, J. Mindell (2008)
Trends in obesity among adults in England from 1993 to 2004 by age and social class and projections of prevalence to 2012Journal of Epidemiology & Community Health, 63
B. Swinburn, B. Swinburn, G. Egger, Fezeela Raza, Fezeela Raza (1999)
Dissecting obesogenic environments: the development and application of a framework for identifying and prioritizing environmental interventions for obesity.Preventive medicine, 29 6 Pt 1
Christiaan Monden, F. Lenthe, J. Mackenbach (2006)
A simultaneous analysis of neighbourhood and childhood socio-economic environment with self-assessed health and health-related behaviours.Health & place, 12 4
M. Bajekal (2004)
Health Survey for England
S. Cummins, S. Curtis, A. Diez-Roux, S. Macintyre (2007)
Understanding and representing 'place' in health research: a relational approach.Social science & medicine, 65 9
D. Reidpath, C. Burns, J. Garrard, M. Mahoney, M. Townsend (2002)
An ecological study of the relationship between social and environmental determinants of obesity.Health & place, 8 2
K. Procter (2007)
Measuring the obesogenic environment of childhood obesity
Spatial microsimulation models can be used to estimate previously unknown data at the micro-level, although validation of these models can be challenging. This paper seeks to describe an approach to validation of these models. Obesity data in adults were estimated at the small area level using a static, deterministic, spatial microsimulation model called SimObesity. This model utilised both Census 2001 data and the Health Survey for England for 2004–2006. Regression analysis was used to identify the covariates that were the strongest predictors of obesity and these were used as the model input variables. The model was calibrated using regression and equal variance t-tests. Two methods of external validation were undertaken; aggregating obesity data to a coarser geographical level at which obesity data was available, and secondly using small area level cancer data for tumour sites known to be correlated to obesity. The output obesity data were mapped and statistically significant hot (cold) spots of high (low) prevalence of obesity identified. Both internal and external validation showed low errors, suggesting this was a satisfactory simulation. Statistically significant hot and cold spots of (simulated) obesity prevalence existed, even after adjusting for age. This paper emphasises three steps to validation of spatial microsimulation models: 1. Accurate simulations require strong correlations between the input and output variables; 2. It is essential to internally validate the models; 3. Use all means possible to externally validate the model.
Applied Spatial Analysis and Policy – Springer Journals
Published: Oct 22, 2010
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