Regional disparities in obesity prevalence in the United States: A spatial regime analysis

Published on Feb 1, 2015in Obesity3.97
· DOI :10.1002/oby.20963
Candice A. Myers7
Estimated H-index: 7
(Pennington Biomedical Research Center),
Tim Slack15
Estimated H-index: 15
(LSU: Louisiana State University)
+ 2 AuthorsSteven B. Heymsfield101
Estimated H-index: 101
(Pennington Biomedical Research Center)
Objective Significant clusters of high- and low-obesity counties have been demonstrated across the United States (US). This study examined regional disparities in obesity prevalence and differences in the related structural characteristics across regions of the US. Methods Drawing on model-based estimates from the Centers for Disease Control and Prevention, regional differences in county-level adult obesity prevalence (percent of the adult population [≥ 20 years] that was obese [BMI ≥ 30 kg/m2] within a county, 2009) were assessed with a LISA (Local Indicators of Spatial Association) analysis to identify geographic concentrations of high and low obesity levels. Regional regime analysis was utilized to identify factors that were differentially associated with obesity prevalence between regions of the US. Results High- and low-obesity county clusters and the effect of a number of county-level characteristics on obesity prevalence differed significantly by region. These included the positive effect of African American populations in the South, the negative effect of Hispanic populations in the Northeast, and the positive effect of unemployed workers in the Midwest and West. Conclusions Our findings suggest the need for public health policies and interventions that account for different regional characteristics underlying obesity prevalence variation across the US.
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  • Citations (22)
#1Tim Slack (LSU: Louisiana State University)H-Index: 15
#2Candice A. Myers (Pennington Biomedical Research Center)H-Index: 7
Last.Steven B. Heymsfield (Pennington Biomedical Research Center)H-Index: 62
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#1Laura Dwyer-Lindgren (UW: University of Washington)H-Index: 15
#2Greg Freedman (UW: University of Washington)H-Index: 13
Last.Ali A. Mokdad (UW: University of Washington)H-Index: 89
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#1Sophie Knipper (UdeM: Université de Montréal)H-Index: 2
#2Elio Mazzone (UdeM: Université de Montréal)H-Index: 4
Last.Pierre I. Karakiewicz (UdeM: Université de Montréal)H-Index: 88
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#1Meifang Chen (CSU: California State University)
#2Thomas N. Creger (UAB: University of Alabama at Birmingham)H-Index: 1
Last.Kevin R. Fontaine (UAB: University of Alabama at Birmingham)H-Index: 9
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#1Susan A. Carlson (CDC: Centers for Disease Control and Prevention)H-Index: 20
#2Geoffrey P. Whitfield (CDC: Centers for Disease Control and Prevention)H-Index: 4
Last.Janet E. Fulton (CDC: Centers for Disease Control and Prevention)H-Index: 44
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