Where Is Obesity Prevention on the Map?: Distribution and Predictors of Local Health Department Prevention Activities in Relation to County-Level Obesity Prevalence in the United States

ArticleinJournal of public health management and practice: JPHMP 18(5):402-11 · September 2012with7 Reads
Impact Factor: 1.47 · DOI: 10.1097/PHH.0b013e318221718c · Source: PubMed

    Abstract

    The system of local health departments (LHDs) in the United States has the potential to advance a locally oriented public health response in obesity control and reduce geographic disparities. However, the extent to which obesity prevention programs correspond to local obesity levels is unknown.
    This study examines the extent to which LHDs across the United States have responded to local levels of obesity by examining the association between jurisdiction-level obesity prevalence and the existence of obesity prevention programs.
    Data on LHD organizational characteristics from the Profile Study of Local Health Departments and county-level estimates of obesity from the Behavioral Risk Factor Surveillance System were analyzed (n = 2300). Since local public health systems are nested within state infrastructure, multilevel models were used to examine the relationship between county-level obesity prevalence and LHD obesity prevention programming and to assess the impact of state-level clustering.
    Two thousand three hundred local health department jurisdictions defined with respect to county boundaries.
    Practitioners in local health departments who responded to the 2005 Profile Study of Local Health Departments.
    Likelihood of having obesity prevention activities and association with area-level obesity prevalence.
    The existence of obesity prevention activities was not associated with the prevalence of obesity in the jurisdiction. A substantial portion of the variance in LHD activities was explained by state-level clustering.
    This article identified a gap in the local public health response to the obesity epidemic and underscores the importance of multilevel modeling in examining predictors of LHD performance.