title: Finding big shots: small-area mapping and spatial modelling of obesity among Swiss male conscripts.
abstract: BACKGROUND
  In Switzerland, as in other developed countries, the prevalence of overweight and obesity has increased substantially since the early 1990s. Most of the analyses so far have been based on sporadic surveys or self-reported data and did not offer potential for small-area analyses. The goal of this study was to investigate spatial variation and determinants of obesity among young Swiss men using recent conscription data.
  
  
  METHODS
  A complete, anonymized dataset of conscription records for the 2010-2012 period were provided by Swiss Armed Forces. We used a series of Bayesian hierarchical logistic regression models to investigate the spatial pattern of obesity across 3,187 postcodes, varying them by type of random effects (spatially unstructured and structured), level of adjustment by individual (age and professional status) and area-based [urbanicity and index of socio-economic position (SEP)] characteristics.
  
  
  RESULTS
  The analysed dataset consisted of 100,919 conscripts, out of which 5,892 (5.8 %) were obese. Crude obesity prevalence increased with age among conscripts of lower individual and area-based SEP and varied greatly over postcodes. Best model's estimates of adjusted odds ratios of obesity on postcode level ranged from 0.61 to 1.93 and showed a strong spatial pattern of obesity risk across the country. Odds ratios above 1 concentrated in central and north Switzerland. Smaller pockets of elevated obesity risk also emerged around cities of Geneva, Fribourg and Lausanne. Lower estimates were observed in North-East and East as well as south of the Alps. Importantly, small regional outliers were observed and patterning did not follow administrative boundaries. Similarly as with crude obesity prevalence, the best fitting model confirmed increasing risk of obesity with age and among conscripts of lower professional status. The risk decreased with higher area-based SEP and, to a lesser degree - in rural areas.
  
  
  CONCLUSIONS
  In Switzerland, there is a substantial spatial variation in obesity risk among young Swiss men. Small-area estimates of obesity risk derived from conscripts records contribute to its understanding and could be used to design further studies and interventions.
authors.affiliation: Institute of Evolutionary Medicine, University of Zurich, Winterthurerstrasse 190, CH-8057 Zurich, Switzerland ; Institute of Social and Preventive Medicine, University of Bern, Finkenhubelweg 11, CH-3012 Bern, Switzerland.
authors.forename: Radoslaw
authors.initials: R
authors.lastname: Panczak
authors.affiliation: Epidemiology, Biostatistics and Prevention Institute, University of Zurich, Hirschengraben 84, CH-8001 Zurich, Switzerland.
authors.forename: Leonhard
authors.initials: L
authors.lastname: Held
authors.affiliation: Institute of Social and Preventive Medicine, University of Bern, Finkenhubelweg 11, CH-3012 Bern, Switzerland.
authors.forename: André
authors.initials: A
authors.lastname: Moser
authors.affiliation: Department of Geography, Swansea University, Wallace Building, Singleton Park, Swansea, SA2 8PP UK.
authors.forename: Philip A
authors.initials: PA
authors.lastname: Jones
authors.affiliation: Institute of Evolutionary Medicine, University of Zurich, Winterthurerstrasse 190, CH-8057 Zurich, Switzerland.
authors.forename: Frank J
authors.initials: FJ
authors.lastname: Rühli
authors.affiliation: Institute of Evolutionary Medicine, University of Zurich, Winterthurerstrasse 190, CH-8057 Zurich, Switzerland.
authors.forename: Kaspar
authors.initials: K
authors.lastname: Staub
keywords: Conscripts; Disease mapping; Integrated nested Laplace approximation; Obesity; Spatial hierarchical Bayesian analysis; Switzerland