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The Spatial Analysis of Health Data: Health Disparities and the Development of High Priority Target Areas
- 1. The Spatial Analysis of Health Data Health Disparities and the Development of High Priority Target Areas September 10, 2009 Virginia Health Equity Conference Virginia Department of Health Office of Minority Health and Public Health Policy Ken Studer, PhD Rexford Anson-Dwamena, MPH
- 2. Types of Spatial Analysis Space as Variables Exploratory Spatial Data Analysis Spatial Data Models Space Process Models Each of these has different inferential/predictive abilities, and requires different amounts of data and knowledge of the spatial system itself. (see, Geoffrey M Jacquez, 2004)
- 3. Surrounded by Clusters! 'Tobler's first law of geography' "everything is related to everything else, but near things are more related than distant things"
- 4. Double Jeopardy describes children (under 18 years old) that live in poor families and in poor neighborhoods. Poor neighborhoods are defined as census tracts (CTs) with greater than 20.0% poverty. The racial categories include persons of Hispanic and non-Hispanic origin; 'Other' includes American Indian, Alaska Native, Native Hawaiian and other Pacific Islander, some other race alone, and two or more races. **Total number of children living below the federal poverty level reflects the sum of the four racial categories since Hispanic ethnicity could not be determined for each race. Source: Census 2000, SF3, P159. Where is the Map?
- 5. Abraham Verghese: Urbs in Rure Verghese, A., S. Berk, and F. Sarubbi. 1989. Urbs in Rure: HIV infections in rural Tennessee. Journal of Infectious Diseases 160(6): 1051-1055.
- 6. Spatial Analysis of Prostate Cancer Incidence in Virginia* * Oliver, MN, E Smith, M Siadaty, FR Hauck, LW Pickle, Spatial Analysis of Prostate Cancer Incidence and Race in Virginia, 1990–1999. Am J Prev Med 2006;30(2S):S67–S76. Census Tract Level Analysis County Level Analysis
- 7. Source: United States Department of Agriculture: Economic Research Service, 2004 County Typologies; Census 2000, SF3-PCT25. County/Census Tract Low Education in Virginia Census Tract Level County Level
- 9. Mortality Ratio by Census Tract
- 10. Things Change but…. …systems remain highly sensitive to initial conditions
- 12. 31
- 14. 50% Infant Mortality in Richmond Block Groups: 1990-2005
- 15. Percentage (yellow) of Richmond Homicides by Census Tract, 2007 Richmond, Virginia Infant Deaths by Census Block Group, 1990-2005 Thematic Map (Choropleth Map)
- 17. NOVA Infant Deaths per Census Block Group Source: VDH Vital Statistics, 1990-2005.
- 18. Predictive Kriging Analysis Infant Deaths by Block Group Source: VDH Vital Statistics, 1990-2005. Kernel Density Analysis Low Birth-weight Infants based on Census Tract Data with Optimum Locations for Clinics Source: VDH Vital Statistics, 1996-2005.
- 19. The Pareto Principle Personal: 20% of our clothes we wear 80% of the time 80% of our time is spent with 20% of our acquaintances Business: 80% of sales come from 20% of clients 20% of customers take up 80% of one's time GIS 20% of the time is required to create a map 40% of the time is required to understand the data 40% to understand the spatial analysis 80% of the time only 20% of an audience understands what is being discussed (Maybe overly optimistic)
- 20. Health Disparity
- 21. Kernel Density Smoothed Surface
- 23. Cluster #1 Filter Decomposition
- 24. Rural Cluster #2
- 25. Breast Cancer Residual Analysis
- 26. Combined Kernel Density and Kriging Analysis—State Standard
- 27. Combined Kernel Density and Kriging Analysis—NOVA Standard
- 28. Combined Kernel Density and Kriging Analysis— Potentially Underreported Incidence
- 30. White Breast Cancer Rates
- 31. Black Breast Cancer Rates
- 32. Black/White Breast Cancer Disparities
- 33. Black/White Breast Cancer Disparities
- 34. Levels of Clustering Techniques Thematic Maps Hotspot Analysis Kernel Density Kriging GeoDa SaTScan Spatial Regression GWR, Logistic, Poisson GeoSurveillance Space as a Variable Exploratory Spatial Data Analysis Spatial Data Modeling Spatial Process Modeling Spatial Clustering Algorithms Level of Spatial Analysis B L U E* *best linear unbiased estimators
- 35. Contact Information: Ken Studer, PhD [email_address] Rexford Anson-Dwamena, MPH rexford.dwamena @vdh.virginia.gov