Abstract
Childhood obesity is a principal public health concern. Understanding the geographic distribution of childhood obesity can inform the design and delivery of interventions. To better understand the causes of spatial dependence in rates of childhood obesity across neighborhoods. This cohort study used data from a legislatively mandated body mass index screening program for public school children in Arkansas from the 2003-2004 through 2014-2015 academic years. Spatial autoregressive moving average (SARMA) models for panel data were used to estimate spatial dependency in childhood obesity at 2 levels of spatial aggregation. Data were analyzed from August 2017 to February 2018. The SARMA models included geographic fixed effects to capture time-invariant differences in neighborhood characteristics along with controls for the mean age of children and the proportion of children by race/ethnicity, school meal status, and sex. The proportion of obese schoolchildren in Arkansas neighborhoods by year, defined at larger (census tract) and smaller (census block group) spatial scales. The geographic aggregations were based on 935 800 children with a mean (SD) age of 132 (39) months. Of these children, 51% were male; 65% were white, 21% were black, 10% were Hispanic, 2% were Asian, and the remainder were of other or unidentified race/ethnicity. In models without geographic fixed effects, there was evidence of positive and significant spatial autocorrelation in obesity rates across tracts (ρ = 0.511; 95% CI, 0.469-0.553) and block groups (ρ = 0.569; 95% CI, 0.543-0.595). When geographic fixed effects were included, spatial autocorrelation diminished at the census tract level (ρ = 0.271; 95% CI, 0.147-0.396) and disappeared at the census block group level (ρ = -0.075; 95% CI, -0.264 to 0.114). Because block groups are smaller than tracts, children in neighboring block groups were more likely to attend the same schools and interact through neighborhood play. Thus, geographic-based social networks were more likely to span block group boundaries. The lack of evidence of spatial autocorrelation in block group-level models suggests that social contagion may be less important than differences in neighborhood context across space. Caution should be used in interpreting significant spatial autocorrelation as evidence of social contagion in obesity.
Highlights
Childhood obesity is a persistent problem in the United States, with 17% of children having obesity.[1]
In models without geographic fixed effects, there was evidence of positive and significant spatial autocorrelation in obesity rates across tracts (ρ = 0.511; 95% CI, 0.469-0.553) and block groups (ρ = 0.569; 95% CI, 0.543-0.595)
When geographic fixed effects were included, spatial autocorrelation diminished at the census tract level (ρ = 0.271; 95% CI, 0.147-0.396) and disappeared at the census block group level (ρ = −0.075; 95% CI, −0.264 to 0.114)
Summary
Childhood obesity is a persistent problem in the United States, with 17% of children having obesity.[1] A finding in the literature is that the incidence of obesity can cluster through social networks.[2,3] obesity is not a disease that can be transmitted through contact, the analog remains that children who reside in close proximity are more likely to form friendships, which in turn can lead to the spread of obesity through the development of common habits or by altering one’s body type to identify with peers This phenomenon could be defined broadly as social contagion and could be associated with spatial dependency similar to that found in studies of contagious diseases. Support for this argument can be found in studies of infectious diseases, in which the mechanism of spread is through contact between infected individuals, and there is evidence of positive spatial autocorrelation in rates of infection across geographic units.[5,6,7,8,9,10,11,12,13] There is evidence of positive spatial autocorrelation in rates of childhood obesity[14,15] and adult obesity[16,17] across geographic units
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