Kristianna J. Radley - Department of Psychology, University of Utah. u1119263@utah.edu. Rebecca R. Steed - Population Science, Huntsman Cancer Institute; Department of Geography, University of Utah. Dr. Huong Meeks - Population Science, Huntsman Cancer Institute, University of Utah. Dr. Ken R. Smith - Utah Population Database, Population Sciences, Huntsman Cancer Institute; Department of Family and Consumer Studies, University of Utah. (University of Utah)
Faculty Advisor: Smith, Ken (University of Utah, Department of Family and Consumer Studies)
How is your risk of mortality as an adult affected by your living circumstances, your family and your neighborhood that existed earlier? In the state of Utah, we have a historical collection of data on individual circumstances early in life and death records for the entire population through the Utah Population Database (UPDB). This work began by creating geographical representations of the longevity in Utah by neighborhoods based on residential location in 1940 to determine if certain areas are associated with higher, or possibly lower, adult mortality rates. The 1940 census was used because it represents the most recent census year where specific identifiers are available that allows us to follow individuals until their deaths or their current age. We found that mortality risks vary based on an individual's location residence in 1940, specifically adults living in urban areas. This research is being extended by exploring individual characteristics that may explain these spatial longevity differentials. For this work, it will also be important to explore how individual and neighborhood characteristics may interact, where certain combinations serve to either increase or decrease the risk of adult mortality. We are continuing this research by adding a third level of analysis by including a familial component in relation to mortality risk. This additional component allows us to determine if family members share a risk of mortality which might be associated with neighborhood clustering (since family members may be more likely to live near one another) or because of shared genetics. By studying all three levels of mortality risk, this research will lead to a more comprehensive assessment of the social and geographic origins of mortality risk (at the level of the individual, family, and community). This work may have the ability to identify community characteristics that will promote healthier and longer lives.