Table Of Contents:
Preface ix
Acknowledgments xxi

Explaining the Geography of Infant Health 1(20)

Geographic Variations in Infant Health 2(10)

Smoking is Bad 9(1)

What Does It Mean to Be Poor? 10(1)

Stress 11(1)

The Geography of Health 12(6)

References 18(3)

An Introduction to GIS (All Things Data) 21(31)

Data Input 24(13)

Health Data 24(3)

Confidentiality Issues 27(1)

Address Matching/Geocoding 28(3)

Other Useful Data 1: Socioeconomic Data 31(1)

Other Useful Data 2: Boundary and Background Data 32(5)

Data Manipulation 37(10)

Aggregating into Spatial Units 37(4)

Data Reduction 41(1)

Creating New Data 42(1)

Calculating Deprivation Indexes 42(2)

Improving Health Outcome Information 44(1)

Perinatal Periods of Risk (PPOR) 45(2)

References 47(5)

An Introduction to GIS (All Things Spatial) 52(27)

Visualizing the Data 52(10)

Choropleth Map 57(3)

Common Dot Map 60(1)

Isarithmic (Isoline) Map 61(1)

Proportional (Graduated) Point Symbol Map 61(1)

Spatial Analysis 62(8)

CrimeStat® 64(1)

GeoDa™ 65(1)

Geographically Weighted Regression (GWR) 65(1)

SaTScan™ 66(2)

GIS as a Management Information System 68(1)

What is a Neighborhood? 69(1)

Including Geography in the Analysis 70(3)

Holistic Neighborhood Investigations 72(1)

Spatially Synthesizing Previous Research 73(1)

References 73(6)

The Geography of Health Risks 79(67)

Infant Deaths, Low Birth Weight, and Short Gestation Deliveries 83(2)

Medical Risks 85(2)

Behavioral Risks 87(8)

So What Can We Do With GIS? 91(4)

Cohort or Social Risks 95(8)

Social Risks: Disparities in African American Neighborhoods 96(2)

Spatial Cohort 98(1)

Neighborhood Risks 99(1)

Suffer the Children 100(3)

Environmental Risks 103(7)

GIS Analyses of Environmental Risks 107(3)

GIS, Cancer, and Low Birth Weight Research in Louisiana 110(3)

Cancer and Birth Outcome Co-Investigation Template 111(2)

Summarizing It All: The Relationship Between Risk and Stress 113(6)

So What Can Be Done? 114(5)

References 119(27)

GIS and Spatial Analysis: Keeping It Simple 146(28)

Exploratory Analysis vs. Hypothesis Testing 146(2)

Spatial Design 148(1)

Spatial Sampling 149(4)

Aggregation Effects 153(1)

Three Simple Techniques: Overlay, Density, and a Difference of Proportions Test 154(18)

Overlay as Analysis 154(3)

A Cautionary Tale 157(1)

Density Analysis 157(3)

Difference of Proportions Test 160(5)

Results for Year One (Table 1) 165(1)

Results for Year Two (Table 2) 165(2)

Results for Year Three (Table 3) 167(2)

Under-18 Pregnancies (Table 4) 169(3)

References 172(2)

Advanced Spatial Analysis 174(29)

Spatial Autocorrelation 174(5)

Global Spatial Autocorrelation 175(3)

Local Spatial Autocorrelation 178(1)

Cluster Analysis 179(3)

Cluster Techniques 182(6)

Spatial Filtering (DMAP) 182(1)

Nearest Neighbor Hierarchical Clustering (NNHC) 183(1)

Kernel Density Estimation 184(4)

Infant Mortality and Prenatal Risks: The Case of East Baton Rouge 188(11)

Regressing Selected Prenatal Risk Factors on the Infant Mortality Rate 192(2)

Geographically Weighted Regression 194(5)

References 199(4)

Spatial/Temporal Stability in Neighborhoods of Risk: The Mobility of Mothers 203(21)

How Far Do the Mothers Move? 204(4)

Temporal Stability and Implications for Outreach 208(14)

Developing a Neighborhood Categorization Scheme Based on Temporal Stability 208(2)

Constructing Neighborhoods Around Mortality Locations 210(1)

Temporal Stability in Risks Around Infant Deaths 211(5)

Temporal Stability in a Global Risk Investigation 216(2)

Temporal Stability in the Four Neighborhoods 218(1)

Results from the Difference of Proportions t-test 219(2)

Conclusions on Temporal Stability 221(1)

References 222(2)

Patient Confidentiality 224(21)

Confidentiality in Maps 226(1)

Statistical (Attribute) Confidentiality 226(1)

Spatial (Locational) Confidentiality 227(1)

Preserving Confidentiality in Governmental Agencies 227(3)

U.S. Department of Health and Human Services 228(1)

U.S. Census 229(1)

U.S. Department of Justice 229(1)

Geographically Masking the Location of Confidential Point Data 230(13)

Experimental Testing 230(1)

Results for Global Geographic Masking 231(1)

Results for Local Geographic Masking 232(5)

Preserving Spatial Confidentiality of Two Locally Masked Point Patterns 237(3)

Manipulating Both Area Boundaries and the Location of Confidential Point Data 240(3)

References 243(2)

Creating the Baton Rouge Healthy Start GIS 245(23)

Beginnings 246(12)

Determining the Program Area 258(1)

Identifying Areas With No Prenatal Care 259(3)

Neighborhood Profiling 262(1)

Creating the Database 262(4)

Data Input 264(1)

Reaching Out 265(1)

What Next? 266(1)

Post Script 266(1)

References 266(2)

Bioterrorism, Pregnancy, and Old White Men 268(19)

Vulnerability in the U.S. 268(1)

Bioterrorism and Pregnancy Risk 269(2)

GIS and Vulnerability Mapping 271(1)

Identifying the Vulnerable 272(2)

So How Do We Bring Healthy Start into This? 274(1)

Are Pregnant Women Really Vulnerable? 275(4)

Criticisms of Syndromic Surveillance 279(3)

References 282(5)

Rural Health Issues and Their Investigation in a GIS Environment 287(18)

Introduction 287(1)

The Complexity of Rurality 288(1)

Rural Places and Health 289(1)

An Overview of Some Rural Health Issues 290(5)

Rural Geography and Dealing With Rural Data 295(5)

Conclusion 300(1)

References 301(4)
About the Authors 305(2)
Index 307