1. RESIDENTIAL MOVEMENT BETWEEN TIME OF CANCER DIAGNOSIS & DEATH Recinda Sherman, MPH, CTR Florida Cancer Data System

2. Place is important 2  Epidemiologic triad  Technological advancements  Desktop GIS, geocoding, mapping  Spatial statistic, hypothesis testing  Geographic patterns  Disease and risk not randomly distributed  Important for prevention strategies  Causality

3. Exposure measurements  Lack biologic measurements; proxies  Model incomplete risk  Residential risk versus work or school  Cross-sectional residential history Lack of residential history Lag time between exposure and diagnosis Migration  Fallacy  Denominator Issues 3

4. Breast cancer screening  Community A  Low  Community B  Low  Community C  High  Community A  Low  Community B  High  Community C  Low 4 Incidence riskMortality risk

5. Residential mobility  Incidence and mortality data presented same years  Women diagnosed with breast cancer  Women dying from breast cancer  Migration in (and die)?  Migration out (with diagnosis)? 5

6. Research questions  Do cancer patients get diagnosed and die at same residence?  First primary reported to Florida  Death certificate issued by Florida  If the residence is different, is the community similar?  SES  Rurality 6

7. Methods  Address at diagnosis versus death  Cancer cases linked with Vital Stats  Probabilistic matching; SSN, name, dob  1995-2006, 1 st primary, no DCOs  Valid dx and death year, sex, age  Geocoded by FCDS and Vital Stats  Unit of analysis  Census Tract 7

8. Results – Selection Bias 8  446,722 cases for analysis  44% of total first primary cases  Significantly (p < 0.001)  Older (7 years)  Sicker More late stage (26%), more subsequent primaries (3%)  More Males (6%)  More Blacks (1%)  Less Hispanics (2%)

9. Results: Overall Migration 9 Percent Same County96% Contiguous County2% Same Tract83% Same Poverty Level94% Same Rurality Level99% Diff County/Same Poverty62% Diff County/Diff Poverty/Same Rurality85%

10. Results: Tract Movement Predictors  More Likely  Poverty Neighborhood at dx OR 1.1; 1.6  Rural Community at dx OR 1.3; 1.9  Longer survival OR 1.2 per year  Non-white OR 1.2  Dying in Nursing Home/Hospice OR 1.1  Less Likely  Increasing Age at dx 0.99 per year  Increasing Stage OR 0.91; 0.72  Married at death OR 0.45  Female OR 0.93  Second Primary OR 0.97 10

11. Results: Poverty Movement Predictors  More Likely  Longer survival OR 1.2 per year  Non-white OR 1.7  Dying in Nursing Home/Hospice OR 1.1  Less Likely  Increasing Age at dx 0.99 per year  Increasing Stage OR 0.89; 0.75  Married at death OR 0.42  Female OR 0.93  Second Primary Not a predictor 11

12. Results: Urban/Rural Movement Predictors  More Likely  Longer survival OR 1.1 per year  Non-white OR 0.75  Dying in Nursing Home/Hospice OR 1.2  Less Likely  Increasing Age at dx 0.98 per year  Increasing Stage OR 0.89; 0.83  Married at death OR 0.52  Female OR 0.76  Second Primary Not a predictor 12

13. Implications  Vast majority do not move  Women, married, White, and sicker advanced disease, older age  Misclassification bias  Reduce effect size  Unlikely to produce erroneous results  Target  Based on physical community and demographic profile 13

14. Future directions  Do people change residences after a cancer diagnosis?  Who do not die Linkage: DMV, Voter Reg, Medical billing Proprietary residential history databanks  Who die outside Florida Linkage: state/county from SSDI State data exchange 14

15. Acknowledgements  We acknowledge the CDC for financial support under cooperative agreement U58/DP000844  Contents are responsibility of authors and do not represent views of CDC, FL DOH, or FCDS  Gary Levin  Brad Wohler 15