Spatial Perspectives on Health and Social Issues · Spatial Analysis Laboratory, University of...
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Spatial Perspectives on Health and Social Issues
Sara McLaffertyUniversity of Illinois
SPACE Workshop, Ohio State University, July 13, 2005
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What is a ‘spatial perspective’?
Why does it matter for understanding health?
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Biomedical perspective
• Health as an individual property• Risk factors and behaviors• Methodologies
– Case-control– Longitudinal
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But, this is changing
• ‘New’ public health• Health as socially constructed
– Contextual factors• Health inequalities
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Spatial Concepts
• Uneven spatial distribution• Tobler’s first law
– Distance/proximity• Place• Scale
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Three examples
• Health inequalities -- low birthweight• Environmental health• Access to health care• Sample spatial analysis lab
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Health Inequalities
• Low Birthweight– Infants born weighing less than 2500g at
birth– Linked to infant mortality, health and
developmental problems after birth– A potent indicator of infant, maternal and
community health• Focus on Brooklyn, NY
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Low birthweight infants, Brooklyn NY, 2000
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Kernel Estimation
λ(s) = Σ 1/τ k ( di /τ)di<τ
Where:
λ(s) = est. density at grid point sdi = distance from point i to grid point sτ = bandwidthk( ) = kernel function
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LBW Density, 1.0 mile bandwidth
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LBW Density, 2.0 mile bandwidth
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Births ‘constrain’ the spatial distribution of LBW
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Smoothed LBW proportion, 2000, 1.5 mi bandwidth
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Different groups have different residential locations: Density of Pakistani and Mexican mothers in Brooklyn, 2000
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Residential density affects geographical access to prenatal clinics
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Are there spatial clusters of high LBW?
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Analyzing changes in health through space and time
• Change in low birthweight• Components of change:
– Compositional– Contextual
• Combine spatial and statistical methods– GEODA – freeware for exploratory spatial
analysis
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Decompose sources of change in LBW into:
• Change in population composition –ethnicity, race, age, education
• Change in financial coverage –Medicaid
• Change in risk behaviors – smoking, drug use, alcohol consumption
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Smoothed LBW, 1990
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Smoothed LBW, 2000
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Compositional Change
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Exploring the patterns (GEODA)
• Linking and brushing• Parallel coordinate plots
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Spatial Brushing --GEODA
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Spatial Analysis and Environmental Health
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Using GIS to characterize neighborhood environments
Miranda et al (2002) Envir Health Perspectives
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Hazardous Facilities in Urbana, IL
From: US EPA, Toxics Release Inventory
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Measuring ‘exposure’ to environmental hazards/resources• Proximity measures
– Number/density– Distance
• Behavioral measures
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Density measure: Store availability and diabetes (Horowitz et al, 2004)
18.942.2More undesirable stores than desirable stores
23.850.3At least 1 undesirable store
30.226.0At least 1 desirable store
Upper East Side (%)East Harlem (%)Census Block Store Availability
From: Horowitz et al (2004) Barriers to buying healthy foods for people with diabetes. AJPH, 94(9), 1549-54. Compared the availability of stores selling ‘desirable’ and ‘undesirable’ products between high diabetes and low diabetes neighborhoods in NYC.
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Obesity and Neighborhood Characteristics
Burdette H, Whitaker R “Neighborhood playgrounds, fast food restaurants, and crime: relationships to overweight in low-income preschool children. Prev. Med, 2004, 38(1),57-63.
BMI>90% BMI<90%
Playground dist 0.37 0.41
Fast food dist 0.68 0.71
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Human activity patterns underpin environmental exposures: Space-time prism
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Human activity patterns underpin environmental exposures
From: Kai Elgethun, Richard A. Fenske, Michael G. Yost, and Gary J. PalciskoTime-Location Analysis for Exposure Assessment Studies of Children Using a Novel Global Positioning System InstrumentEnvir Health Perspec 111(1), 2003.
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Spatial analysis and health care access
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Use of kernel estimation in exploring access to health care
• Density of health care facilities• Useful in urban context• Health care density can be linked to
population health data– Example – Brooklyn, prenatal clinics
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0.8411YesJam21
DensEducMedicaidEthnicityAge
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Geographical Access to Clinics for Immigrant Mothers
31
84
94
61
% Medicaid
3.7
14.1
9.6
9.4
Late PNC %
.17.27Russia
.21.31Pakistan
.76.79Mexico
.97.92Jamaica
Median density
Average density
Country of Birth
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Summary
• Space matters!• Health inequalities patterned over space• Exposures to disease agents and
environmental hazards and resources vary over space and relate to activity patterns
• Location and distance affect health care access and use
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Thoughts on teaching
• Spatial concepts relevant in many social sciences
• Student backgrounds• Use local data and issues in labs
– many good data sources– data quality and access
• Critical perspective on methods
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Sample lab assignment
• Use GEODA to explore spatial patterns of late-stage breast cancer in Illinois
• Late-stage cancer – not localized, regional spread
• Disease not detected early• May be associated with poor access to
screening and preventive health care
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• Data – percent late-stage breast cancer by county
• Spatial weights – ‘Rook’
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Percent late-stage breast cancer
Identify highest and lowest rate counties
Record numbers of cases in each high/low rate county
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Note that counties with highest and lowest rates tend to have small numbers of cases – rates are unstable due to small numbers
One way to deal with this is to compute spatially smoothed rates –rate for a ‘spatial window’ around each county
Discuss the spatial pattern
What are the advantages of smoothed vs. non-smoothed maps?
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Are high late-stage counties more likely not to have hospital facilities?
The yellow, selected features are counties that lack hospitals.
This histogram suggests little association between high late-stage cancer and absence of hospital facilities
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References Albert D, Gesler W and Levergood B (eds) (2000) Spatial Analysis, GIS and Remote Sensing Applications in the Health Sciences. Chelsea MI: Ann Arbor Press.
Anselin L. (2003) GEODA 0.9 Users Guide. Spatial Analysis Laboratory, University of Illinois, Urbana-Champaign IL. https://geoda.uiuc.edu/.
Bailey T and Gatrell A (1996) Interactive Spatial Data Analysis. New York: John Wiley.
Cromley E (2003) GIS and Disease. Annual Review of Public Health, 24:7-24.
Cromley E. and McLafferty S. (2002) GIS and Public Health, New York: Guilford.
Dolinoy D, Miranda M (2004)GIS modeling of air toxics releases from TRI-reporting and non-TRI-reporting facilities: impacts for environmental justice.Environ Health Perspect. 2004 Dec;112(17):1717-24.
Kawachi I and Berkman L (2003) Neighborhoods and Health. New York NY: Oxford University Press.
Krieger N et al (2003) Geocoding and measurement of neighborhood socioeconomic position: a US perspective. In Kawachi and Berkman, pp. 147-178.
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References, cont.McLafferty S (2003) GIS and Health Care. Annual Reviews of Public Health, 24:25-42.
S. McLafferty and S. Grady (2005) Immigration and Geographical Access to Prenatal Clinics in Brooklyn, NY: A Geographic Information Systems Analysis,” American Journal of Public Health, 95(4), 638-640
Nuckolls JR, Ward MH, Jarup L (2004)Using geographic information systems for exposure assessment in environmental epidemiology studies.Environ Health Perspect. Jun;112(9):1007-15
Richards T, Croner C (1999) Special issues of the Journal of Public Health Management and Practice. Mar, Jul, 5(2) and 5(4).
Rushton G. (1998) GIS in public health, web site. http://www.uiowa.edu/~geog/health/index.html
Waller L, Gotway C (2004) Applied Spatial Statistics for Public Health Data. New York: Wiley.
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Selected health data web sites
• Federal– http://www.cdc.gov/reproductivehealth/GISAtlas/index.htm– http://www3.cancer.gov/atlasplus/index.html– http://www.cdc.gov/ncipc/wisqars/
• Illinois:– http://www.idph.state.il.us/about/epi/cancer.htm– http://www.idph.state.il.us/health/statshome.htm
• Ohio:– http://dwhouse.odh.ohio.gov/datawarehousev2.htm
• New York:– http://www.nyc.gov/html/doh/html/home/home.shtml– http://www.health.state.ny.us/statistics/
• Los Angeles– http://lapublichealth.org/dca/