2. Spatial Clustering of Scleroderma in Three Michigan Counties “The Toledo Twins” Sharon HensleyAlford Sarah Ann Cleveland   

3.  Background  The disease that “turns people to stone” –Chronic, connective tissue disease –Unknown cause –Collagen accumulation in some organs Classifications –Localized –Systemic

4.  Who has scleroderma  Approximately 150,000 people in the United States 4 times more women than men

5.  Symptoms May Include  Raynaud’s Phenomenon Swelling of hands and feet Pain and stiffness of joints Thickening of the skin Kidney, heart, and lung involvement Oral, facial, and dental problems

6.  Diagnosis  Difficult Involvement of several specialists May take months to years

7.  Rates in Study Area  Prevalence 242 cases per 1million adults Incidence 19 new cases per 1 million adults per year Reference: Prevalence, incidence and survival rates of systemic sclerosis in the Detroit metropolitan area. Mayes et al.

8.  Age Distribution of Cases 

9.  Sex Distribution  134 Females 37 Males 3.62 times more females than males

10.  Etiologies  UNKNOWN Possibilities include: –silica dust –vinyl chloride monomer –pet ownership –some solvents –appetite suppressants

11.  Significance  To Explore... Environmental associations Spatial pattern  Disease process

12.  Materials  Disease Data –Incidence data for 1989-1991 (N=171) –Three counties: Macomb Oakland Wayne Population Data –1990 Census data –Block and Tract divisions

13.  Methods  Gathering population data –Finding census data –Extract pertinent information Geocoding cases –ArcView Batch Match –Digitizing unmatched cases

14.  Working with Unmatched Cases  Verifying address: US Post: www.usps.gov Using web map programs –Mapquest: www.mapquest.com gives county lines –Vicinity: www.mablast.com Digitizing

15.  Matching Rate  171 Original 5 Unmatchable Addresses n=166 Batch-Matched Addresses n=148 Non-matched n=18 Digitized n=13 Unable to Digitize n=5 161 Matched/166 Total 96% Matching Rate

19.  Statistical Analysis  Null Hypothesis: No spatial clustering Alter. Hypothesis: Spatial clustering Test statistic: Ipop, Moran’s I Statistical Program: STAT!

20.  Macomb/Tracts  Assumption R Variance : 0.0000000 z-score : -0.3175953 Significance : 0.7507920 (2-tailed) Approximation Variance : 0.0000000 z-score : -0.3121641 Significance : 0.7549158 (2-tailed) Simulation Significance : 0.8800000 (2-tailed) STAT Output 4/13/1999 Results from Ipop test Number of runs : 99 Ipop calculations Areas (m) : 194 cases (n) : 30 Population (x) : 724110 Ipop : -0.0000099 Ipop' : -0.2377846 E[I] : -0.0000014 % within : 99.9752702 % among : 0.0247298

21.  Macomb/Block  STAT Output 4/14/1999 Results from Ipop test Number of runs : 99 Ipop calculations Areas (m) : 661 cases (n) : 30 Population (x) : 724112 Ipop : -0.0000208 Ipop' : -0.5008514 E[I] : -0.0000014 % within : 99.9957345 % among : 0.0042655 Assumption R Variance : 0.0000000 z-score : -0.3930764 Significance : 0.6942630 (2-tailed) Approximation Variance : 0.0000000 z-score : -0.3855452 Significance : 0.6998335 (2-tailed) Simulation Significance : 0.6400000 (2-tailed)

22.  Oakland/Tracts  STAT Output 4/13/1999 Results from Ipop test Number of runs : 99 Ipop calculations Population (x) : 1101540 Ipop : 0.0000033 Ipop' : 0.0817093 E[I] : -0.0000009 % within : 99.8772695 % among : 0.1227305 Assumption R Variance : 0.0000000 z-score : 0.2045747 Significance : 0.8379044 (2-tailed) Approximation Variance : 0.0000000 z-score : 0.2022084 Significance : 0.8397538 (2-tailed) Simulation Significance : 0.5600000 (2-tailed)

23.  Oakland/Blocks 

24.  Wayne/Tracts  STAT Output 4/13/1999 Results from Ipop test Number of runs : 99 Ipop calculations Areas (m) : 632 cases (n) : 86 Population (x) : 2159815 Ipop : -0.0000062 Ipop' : -0.1565116 E[I] : -0.0000005 % within : 100.4700628 % among : -0.4700628 Assumption R Variance : 0.0000000 z-score : -0.3578355 Significance : 0.7204664 (2-tailed) Approximation Variance : 0.0000000 z-score : -0.3542334 Significance : 0.7231640 (2-tailed) Simulation Significance : 0.9200000 (2-tailed)

25.  Wayne/Blocks 

26.  Discussion  Limitations of Analysis –Position uncertainty –Residential history –Reliability of census data Future Analysis –Stratification by age, sex, race –3 county combination analysis –Space/Time Analysis

27.  Thank You  First Honors: Andy Long Mark Wilson Dr. Mayes Geoff Jacquez