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Author (up) Rybnikova, N.; Stevens, R.G.; Gregorio, D.I.; Samociuk, H.; Portnov, B.A. url  doi
  Title Kernel density analysis reveals a halo pattern of breast cancer incidence in Connecticut Type Journal Article
  Year 2018 Publication Spatial and Spatio-temporal Epidemiology Abbreviated Journal Spatial and Spatio-temporal Epidemiology  
  Volume 26 Issue Pages 143-151  
  Keywords Human Health; Remote Sensing  
  Abstract Breast cancer (BC) incidence rates in Connecticut are among the highest in the United States, and are unevenly distributed within the state. Our goal was to determine whether artificial light at night (ALAN) played a role. Using BC records obtained from the Connecticut Tumor Registry, we applied the double kernel density (DKD) estimator to produce a continuous relative risk surface of a disease throughout the State. A multi-variate analysis compared DKD and census track estimates with population density, fertility rate, percent of non-white population, population below poverty level, and ALAN levels. The analysis identified a “halo” geographic pattern of BC incidence, with the highest rates of the disease observed at distances 5-15 km from the state's major cities. The “halo” was of high-income communities, with high ALAN, located in suburban fringes of the state's main cities.  
  Corporate Author Thesis  
  Publisher Place of Publication Editor  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN 1877-5845 ISBN Medium  
  Area Expedition Conference  
  Notes Approved no  
  Call Number GFZ @ kyba @ Serial 1961  
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