title: A comparison of the spatial dependence of body mass index among adults and children in a Swiss general population.
abstract: BACKGROUND
  Body mass index (BMI) may cluster in space among adults and be spatially dependent. Whether BMI clusters among children and how age-specific BMI clusters are related remains unknown. We aimed to identify and compare the spatial dependence of BMI in adults and children in a Swiss general population, taking into account the area's income level.
  
  
  METHODS
  Geo-referenced data from the Bus Santé study (adults, n=6663) and Geneva School Health Service (children, n=3601) were used. We implemented global (Moran's I) and local (local indicators of spatial association (LISA)) indices of spatial autocorrelation to investigate the spatial dependence of BMI in adults (35-74 years) and children (6-7 years). Weight and height were measured using standardized procedures. Five spatial autocorrelation classes (LISA clusters) were defined including the high-high BMI class (high BMI participant's BMI value correlated with high BMI-neighbors' mean BMI values). The spatial distributions of clusters were compared between adults and children with and without adjustment for area's income level.
  
  
  RESULTS
  In both adults and children, BMI was clearly not distributed at random across the State of Geneva. Both adults' and children's BMIs were associated with the mean BMI of their neighborhood. We found that the clusters of higher BMI in adults and children are located in close, yet different, areas of the state. Significant clusters of high versus low BMIs were clearly identified in both adults and children. Area's income level was associated with children's BMI clusters.
  
  
  CONCLUSIONS
  BMI clusters show a specific spatial dependence in adults and children from the general population. Using a fine-scale spatial analytic approach, we identified life course-specific clusters that could guide tailored interventions.
authors.affiliation: 1] Unit of Population Epidemiology, Division of Primary Care Medicine, Department of Community Medicine, Primary Care and Emergency Medicine, Geneva University Hospitals and Faculty of Medicine, University of Geneva, Geneva, Switzerland [2] Community Prevention Unit, University Institute of Social and Preventive Medicine, Lausanne University Hospital, Lausanne, Switzerland.
authors.forename: I
authors.initials: I
authors.lastname: Guessous
authors.affiliation: Laboratory of Geographical Information Systems (LASIG), Ecole Polytechnique Fédérale de Lausanne (EPFL), Station 18, Lausanne, Switzerland.
authors.forename: S
authors.identifier: 0000000211847501
authors.initials: S
authors.lastname: Joost
authors.affiliation: 1] Institute of Social and Preventive Medicine, Faculty of Medicine, University of Geneva, Geneva, Switzerland [2] Department of Public Instruction, School Health Service, Geneva, Switzerland.
authors.forename: E
authors.initials: E
authors.lastname: Jeannot
authors.affiliation: Unit of Population Epidemiology, Division of Primary Care Medicine, Department of Community Medicine, Primary Care and Emergency Medicine, Geneva University Hospitals and Faculty of Medicine, University of Geneva, Geneva, Switzerland.
authors.forename: J-M
authors.initials: JM
authors.lastname: Theler
authors.affiliation: Department of Public Instruction, School Health Service, Geneva, Switzerland.
authors.forename: P
authors.initials: P
authors.lastname: Mahler
authors.affiliation: Unit of Population Epidemiology, Division of Primary Care Medicine, Department of Community Medicine, Primary Care and Emergency Medicine, Geneva University Hospitals and Faculty of Medicine, University of Geneva, Geneva, Switzerland.
authors.forename: J-M
authors.initials: JM
authors.lastname: Gaspoz