The Geographical and Temporal Distribution of Vital Statistics in Champaign County, from 2005 to 2009 Lan Luo Supervisor: Awais Vaid (C-UPHD) Dr.Ruiz (University of Illinois at Urbana-Champaign)

Outline Geocode Vital Records Distribution of Vital Statistics (birth and death) in Champaign, adjusted for spatial and temporal effects, and age attributes Grant Application Further Research

Geocode Vital Records Definition of Geocode Geocoding is the process of assigning a location, usually in the form of coordinate values (points), to an address by comparing the descriptive location elements in the address to actual geographical presents in the reference material. Software: SPSS, ArcGIS Geocoding Rate of 2009 Birth Records in Champaign County (2328/2343)×100%=99.36% Geocoding Rate of 2009 Death Records in Champaign County (1072/1079)×100%=99.35%

Difficulties  Incomplete Records: Missing street numbers, Missing zipcodes  Typos: Wrong street numbers, Wrong zipcodes, Incorrect street names  No Unique Identification to connect spatial and attribute portions Solutions  Online Map Interfaces: Google Map, MapQuest  Online Geocoding Tool:  Create the temporal id (TMPID) for each vital records Lessons for other health departments  Create a standard procedure to geocode vital records, not only based on performers’ personal experience  Establish the database for geocoded vital records for further research The Summary of Geocoding Vital Records

The Distribution of Vital Statistics in Champaign Study Unit: Census Tract in 2000, as the small statistical subdivisions (averaging 4,000 persons), stable boundaries, containing relatively homogeneous demographic characteristics (ethnic, economic, living conditions ) The reason of selecting census tract: localized, not violating confidentially Vital Statistics:  Crude rates, equaling to study cases divided by the number of population in 2000  Age-adjusted rates, on the basis of crude rates, computed using standard age-group weight in 2000, to eliminate the bias brought by different age distribution within each census tract

Distribution of Birth Statistics in Champaign (HMO) The Geographical Distribution of Crude Birth Rates in Each Year  Consistent spatial patterns over five years  Census tracts with the highest rates: the north, west, and south edges of Champaign municipality The Geographical Distribution of Five-Year Crude Birth Rates  Census tracts having the highest rates: similar to those of each year The Spatial-Temporal Distribution of Crude Birth Rates in Five Years  The space-time permutation model automatically adjusts for both purely spatial and purely temporal clusters, in purpose to find the ‘hot-spot’ of study cases in a geographical area during a specific time period  Software: SaTScan  Census Tracts with the significant high birth rates: the small southern tip of Champaign city

Distribution of Death Statistics in Champaign (HMO) The Geographical Distribution of Crude Death Rates in Each Year  County-wise: dynamic spatial distribution across five years  Central City-wise: census tracts with high rates cover north Champaign, west side of Savoy, southeast side of Urbana The Geographical Distribution of Age-Adjusted Death Rates in Each Year  Generally similar to those crude death rates The Geographical Distribution of Crude Death Rates by Leading Death Causes in All Five Years  Accidents: the northeast part (County-wise); western Savoy, southeast and middl east of Urbana, and southeast of Champaign (Central City-wise)  Cancer and Chronic Lower Respiratory Diseases : the northeast and southeast portions (County-wise); the southeast Champaign, west Savoy, and the southeastern side of Urbana  Diseases of Heart: the northeast and middle east portions (County-wise); the north and southeast of Champaign, west Savoy, and southeast and middle east Urbana  Influenza and Pneumonia: the northeast and southeast parts (County-wise); scattered in central parts of Champaign city (Central City-wise)  Stroke: the northeast, middle east, and middle west portions (County-wise); the southwest and southeast Champaign, west Savoy, and middle east and southeast of Urbana

The Geographical Distribution of Crude Death Rates by Leading Death Causes in Each Year  Accidents: the northeast and southeast areas (County-wise); inconsistency (Central City-wise)  Cancer: Inconsistency (County-wise); southwest part of Urbana city (Central City-wise)  Chronic Lower Respiratory Diseases: variation in both (County-wise) and (Central City-wise)  Diseases of Heart: the northeast and southwest parts (County-wise); the north portion of Champaign, the southwest side of Urbana, and the east part of Savoy (Central City-wise)  Influenza and Pneumonia: Inconsistency (County-wise); the southwest portion of Urbana and east Savoy (Central City-wise)  Stroke: Inconsistency (County-wise); the southwest Champaign, the southeast part of Urbana, and east of Savoy (Central City-wise) The Geographical Distribution of Age-Adjusted Death Rates by Leading Death Causes in Each Year  The county-wise spatial patterns are similar as those crude rates by leading death causes  Central City-wise: the southwest of Champaign, east Savoy (Cancer) the southwest and north parts of Champaign, northeast Urbana, and east Savoy (Disease of Heart) Distribution of Death Statistics in Champaign (HMO)

The Spatial-Temporal Distribution of Crude Death Rates in Five Years  Four calculated clusters have statistical significant p-value (< 0.05)  Specific locations: the south part of Rantoul city (1 st cluster) the east side of Savoy and southwest Urbana (2 nd cluster) the middle east portion of Urbana (3 rd cluster) the east of Urbana (4 th cluster) The Spatial-Temporal Distribution of Crude Death Rates by Leading Death Causes in Five Years  Only crude death rates caused by accidents have four clusters with statistical significant p-values  Specific locations: the central of Champaign city (1 st cluster) the middle part of Rantoul (2 nd cluster) within Champaign city, next to northeast border (3 rd cluster) the southwest portion of Champaign city (4 th cluster)

The Summary of Vital Statistics Mappings (HMO) Hot-spots of vital statistics are generally located within Champaign, Urbana, and Savoy municipalities Those distribution maps provide a generally spatial and temporal structure of vital statistics in Champaign County during the past five years. Other health departments can also create such maps, given that ‘one map will tell 1,000 sentences’. Drawbacks  Out-of-Dated Base Population: Census 2000  Out-of-Dated Geographical Boundary: Census Tract 2000  Small number problem exists in this study, mainly displaying as small population base, given that high rates of vital statistics are always illustrated in census tracts of northeast part of Champaign

Grant Application: Integrating GIS with National Umbrella Cooperative Agreement Program Minority Health Grant The elimination of health disparities in minority groups has become the national-wide focus. Based on the prevalent paradigm of health informatics, it is necessary to establish a statewide-database, composed of data, statistical results, visual aids, and effective connection among these fields

Further Research Find the spatial and social reasons to cause hot-spots in those patterns of vital statistics Eliminate spatial errors: small number problems; out-of-dated study units and base population Establish a relatively complete step to study vital statistics within a small region (i.e. one County): What? –Why?-How? Compare with the analytical results of vital records in another County in Illinois (i.e., a highly rural County or a highly urbanized County) Continue to study the association of GIS and the disparity of minority health at community level

Thank you. Suggestions are welcome.