Geographic variation in public health spending: correlates and consequences.
OBJECTIVE
To examine the extent of variation in public health agency spending levels across communities and over time, and to identify institutional and community correlates of this variation.


METHODS
Three cross-sectional surveys of the nation's 2,900 local public health agencies conducted by the National Association of County and City Health Officials in 1993, 1997, and 2005, linked with contemporaneous information on population demographics, socioeconomic characteristics, and health resources.


METHODS
A longitudinal cohort design was used to analyze community-level variation and change in per-capita public health agency spending between 1993 and 2005. Multivariate regression models for panel data were used to estimate associations between spending, institutional characteristics, health resources, and population characteristics.


RESULTS
The top 20 percent of communities had public health agency spending levels >13 times higher than communities in the lowest quintile, and most of this variation persisted after adjusting for differences in demographics and service mix. Local boards of health and decentralized state-local administrative structures were associated with higher spending levels and lower risks of spending reductions. Local public health agency spending was inversely associated with local-area medical spending.


CONCLUSIONS
The mechanisms that determine funding flows to local agencies may place some communities at a disadvantage in securing resources for public health activities.
Mays
Glen P
GP
Department of Health Policy & Management, Fay W. Boozman College of Public Health, University of Arkansas for Medical Sciences, Little Rock, AR 72205, USA. gpmays@uams.edu
Smith
Sharla A
SA
D005102:Health Expenditures; D006801:Humans; D008137:Longitudinal Studies; D017059:Models, Econometric; D015999:Multivariate Analysis; D011635:Public Health Administration / Q000191:economics*; D015980:Public Health Practice / Q000191:economics*; D012044:Regression Analysis; D012111:Residence Characteristics; D012189:Retrospective Studies; D014481:United States
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