Geospatial Assessment of Residential and Work Sites for Cobb Collection Individuals

Hasan Jackson 1,2

  1. 1W. Montague Cobb Research Laboratory, Howard University
  2. Department of Geographical Studies, University of Maryland

Due to the history of segregation in the Washington area it is likely that the populations of certain neighborhoods were mostly uniform in terms of ethnicity. There may have also been important geographic substructure by occupation as well, resulting in significant clustering of AAs from the CC individuals in the Washington DC region. Social status, occupation, education, and affluence may also have contributed to the selection of neighborhoods and worksites. Communities with lower socioeconomic status likely resided and worked in non-favorable neighborhoods with close proximity to pollutants and increased distance from major roads. The residential and work settings of 19th and 20th century Cobb Collection (CC) individuals resulted in increased levels of exposure to pollutants for some neighborhoods compared with others. Spatial analyses are used to understand the chemical and physical exposure dynamics of Cobb Collection individuals in the District of Columbia metropolitan area from 1920-1960 to environmental factors that could modify the gene expression patterns in 150 individuals. Specifically, this research looks for possible signs of community segregation related to disease status, ethnic background and occupation. The residences and worksites of CC individuals are mapped and the demographic, genomic, and potentially epigenomic influences stratified horizontally across the Washington DC region. Historical maps of the District of Columbia and its surrounding areas dated to the mid-20th century will be obtained from databases of historical maps located in the National Archives as well as gathered from other peer reviewed sources. The CC has address-based residential and occupational information on each individual in the target population. These data will be used to provide a single reference location for each CC individual under study. Residences will be geocoded based upon the historical maps of the region, providing a latitudinal and longitudinal reference for each individual. The Cartesian plane of residences will be ingested into a spatially referenced database. This will allow spatial comparisons to be made for each residential point, the center for each residence (centroid) will be used, and at the level of neighborhood/ward. Previous studies of spatial clustering in urban areas have used spatial aggregation of geocoded data points to identify area level characteristics in studies of health patterns (25-28). ArcGIS 10.2 version (ESRI, Redlands, CA) is used to perform geocoding tasks.

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