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.
Highlights
An increasing body of evidence shows that neighborhood socioeconomic context, measured by neighborhood deprivation, neighborhood segregation or population density, predicts the development of obesity and other related health outcomes.[1,2,3] Poorer physical infrastructures and transports, worse housing conditions, fewer health and community services and lower stocks of social capital in poor neighborhoods are factors that have been proposed to explain how the place of residence might directly affect health.[4]
High–high Body mass index (BMI) cluster areas, where the percentage of children individuals was higher than the percentage of adult individuals in unadjusted analysis
Areas of high–high BMI clusters, where the percentage of adult individuals was higher than the percentage of children individuals (Figure 3 panel b) and areas of low–low BMI clusters were not affected by the adjustment for area’s annual income (Supplementary Figure S2 panel B)
Summary
An increasing body of evidence shows that neighborhood socioeconomic context, measured by neighborhood deprivation, neighborhood segregation or population density, predicts the development of obesity and other related health outcomes.[1,2,3] Poorer physical infrastructures and transports, worse housing conditions, fewer health and community services and lower stocks of social capital in poor neighborhoods are factors that have been proposed to explain how the place of residence might directly affect health.[4]. 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. 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. CONCLUSIONS: BMI clusters show a specific spatial dependence in adults and children from the general population. Using a finescale spatial analytic approach, we identified life course-specific clusters that could guide tailored interventions
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