Spatial Perspectives on Health and Social Issues

Sara McLaffertyUniversity of Illinois

SPACE Workshop, Ohio State University, July 13, 2005

What is a ‘spatial perspective’?

Why does it matter for understanding health?

Biomedical perspective

• Health as an individual property• Risk factors and behaviors• Methodologies

– Case-control– Longitudinal

But, this is changing

• ‘New’ public health• Health as socially constructed

– Contextual factors• Health inequalities

Spatial Concepts

• Uneven spatial distribution• Tobler’s first law

– Distance/proximity• Place• Scale

Three examples

• Health inequalities -- low birthweight• Environmental health• Access to health care• Sample spatial analysis lab

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

Low birthweight infants, Brooklyn NY, 2000

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

LBW Density, 1.0 mile bandwidth

LBW Density, 2.0 mile bandwidth

Births ‘constrain’ the spatial distribution of LBW

Smoothed LBW proportion, 2000, 1.5 mi bandwidth

Different groups have different residential locations: Density of Pakistani and Mexican mothers in Brooklyn, 2000

Residential density affects geographical access to prenatal clinics

Are there spatial clusters of high LBW?

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

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

Smoothed LBW, 1990

Smoothed LBW, 2000

Compositional Change

Exploring the patterns (GEODA)

• Linking and brushing• Parallel coordinate plots

Spatial Brushing --GEODA

Spatial Analysis and Environmental Health

Using GIS to characterize neighborhood environments

Miranda et al (2002) Envir Health Perspectives

Hazardous Facilities in Urbana, IL

From: US EPA, Toxics Release Inventory

Measuring ‘exposure’ to environmental hazards/resources• Proximity measures

– Number/density– Distance

• Behavioral measures

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.

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

Human activity patterns underpin environmental exposures: Space-time prism

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.

Spatial analysis and health care access

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

0.8411YesJam21

DensEducMedicaidEthnicityAge

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

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

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

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

• Data – percent late-stage breast cancer by county

• Spatial weights – ‘Rook’

Percent late-stage breast cancer

Identify highest and lowest rate counties

Record numbers of cases in each high/low rate county

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?

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

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.

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.

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/