Electronic Theses and Dissertations

Date

2020

Date of Award

2020

Document Type

Dissertation

Degree Name

Doctor of Philosophy

Committee Chair

Esra Ozdenerol

Committee Member

Angela Antipova

Committee Member

Hsiang Kung

Committee Member

Marian Levy

Abstract

The objective of this dissertation research was to explore the use of geodemographic segmentation as a socioeconomic variable to spatially analyze opioid related mortalities and hospital discharges. Opioid data were investigated by three ICD-10 classifications: heroin, other opioids, and other synthetic narcotics. Demographic and spatial characteristics of opioid mortality were examined using data from the Centers for Disease Controls (CDC) National Vital Statistics System mortality (NVSS-M) multiple causes of death dataset via the WONDER database for the year 2017. This was followed by a literature review of previous research that investigated the use of geodemographic segmentation systems in health research.Spatial rules association data mining was used to explore the relationship between county level ESRI Tapestry segmentation and opioid mortality rates from the CDC NVSS-M for the years 2015-2017. These findings were further examined by comparing the results to the 2017 Tennessee opioid mortality and Tapestry data at the ZIP code level. Additional demographic analysis was conducted using county level socioeconomic variables, unemployment, and opioid prescribing rates.Tennessee opioid related hospital discharge and mortality data from the year 2017 were analyzed using rate mapping, ANOVA, descriptive statistics, and spatial rules based association data mining. The rates were associated with ESRI Tapestry LifeMode groupings. The results of the analysis of Tennessees ZIP code level data were compared to the CDCs county level data from 2017 to examine scale dependency of the analysis and data.

Comments

Data is provided by the student.

Library Comment

Dissertation or thesis originally submitted to ProQuest

Share

COinS