Translating Data into Discovery: Analysis of 10 Years of CDC Data of Mortality Indicates Level of Attainment of Education as a Suicide Risk Factor in USA

Authors

  • Gilberto Diaz
  • Jacob Jones
  • Toni Brandt
  • Todd Gary
  • Ashwini Yenamandra

Keywords:

Center for Disease and Prevention (CDC), Data Science, Demographics, Education, Suicide, Suicide risk factors, Mortality data

Abstract

The goal of this research is to identify and promote awareness of prominent demographic risk factors to predict individuals at risk for suicide and aid in the prevention within the USA. This would support the Education Development Center’s Zero Suicide initiative and provide strategies and tools to health and behavioral health systems to reduce suicide mortality. The research presented in this paper focuses on the hypothesis that demographic variables available in the Center for Disease and Prevention (CDC) mortality data sets should be integrated into initiatives to identify and prevent suicide mortality. A comprehensive analysis of the CDC mortality data from 2003 through 2013 was extracted, transformed, loaded and analyzed utilizing Python, R Scripting, RStudio and Tableau. The CDC mortality data was subsided into a data frame of 17 variables from the original 75 variables that indicated the most statistical significance as a function of the respective suicide ICD10 codes. Education attainment levels of a 12th grade education emerged as one of the most statistically significant variables that contributed to suicidal deaths; this observation is consistent with initial observations of the 2013 CDC mortality data analyzed in our previous studies.1 Based on this unique finding of education emerging as a strong and consistent variable in the comprehensive analysis of CDC data over an 11 year period, the authors hypothesize education attainment level segments are the most significant demographic predictor variable of suicide and a systematic approach to targeting continuing
educational opportunities to patients with low education attainment levels paired with other high risk segments including but not limited to age, race, ethnicity, marital status and gender.

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Published

2017-02-16