Date of Award

12-17-2019

Degree Type

Thesis

Degree Name

Master of Public Health (MPH)

Department

Public Health

First Advisor

Dr. Heather Bradley

Second Advisor

Dr. Laura Edison

Abstract

INTRODUCTION: The opioid epidemic continues to be a major public health issue across the United States. From 2010 – 2018 the rate of opioid overdose death in the state of Georgia increased more than 70%. Until 2013 prescription opioids were the driving force of this increase, although in recent years illicit opioids such as heroin and fentanyl have been rapidly increasing. The literature has demonstrated nationally that certain occupations that have an increased risk of injury also have a higher risk of opioid-involved death. Occupational data for the state of Georgia has never been analyzed for a potential relationship with opioid-involved death but could be a valuable resource for identifying populations at an increased risk of opioid-involved death and informing public health action and intervention.

AIM: To determine the risk of opioid-involved overdose death compared to other causes of death for residents of the state of Georgia who died in 2014 and previously worked in industries with a high risk of non-fatal work-related injury.

METHODS: Death certificate data for 2014 was obtained from the Office of Vital Records at the Georgia Department of Public Health and SAS Enterprise Guide 7.1 was used to clean, manage, and analyze the data. The dataset analyzed contained records for all residents in the state of Georgia who died during the 2014 calendar year. Opioid-involved overdose death was the dependent variable of interest. Deaths were identified using the international classification of diseases, 10th revision (ICD-10), and deaths identified as intentional (suicides and assault) were excluded due to poor data quality. The independent variable of interest was industries with a high risk of non-fatal work-related injury and were identified using the Georgia Occupational Health Surveillance Report, 2008 – 2012 (Lavender, Benson, & Bayakly, 2015). Covariates sex, age at death, marital status, and maximum education level obtained at death were coded as categorical variables and analyzed for possible confounding and effect modification of the relationship between occupational type and opioid-involved death. The independent and dependent variables of interest were coded as dichotomous variables and analyzed along with covariates using a multivariate logistic regression model.

RESULTS: Decedents previously working in industries with a high risk of non-fatal work-related injury had an increased odds of opioid-related death compared to decedents with other causes of death (OR = 1.10, 95% CI: [0.97, 1.26]) when compared to all other industries (OR = 0.91, 95% CI [0.79, 1.03]); however this association was not statistically significant. Sex, marital status at death and maximum education level obtained at death were determined to be confounders with sex acting as an effect modifier. After adjusting for these confounders, male decedents in industries with a high risk of non-fatal work-related injury were found to have a 25% increased odds of opioid-involved overdose death (OR = 1.25, 95% CI: [1.06, 1.48]) when compared to males employed in all other industries (OR = 0.8, 95% CI [0.68, 0.95]). Female decedents from industries with a high risk of non-fatal work-related injury had decreased odds of opioid-involved overdose death (OR = 0.94, 95% CI [0.76, 1.17]) that was not statistically significant when compared to female decedents who previously worked in all other industries (OR = 1.06, 95% CI [0.85, 1.33]). Additionally, those who were married had 33% decreased odds of opioid-involved overdose death (OR = 0.67, 95% CI: [0.59, 0.77]) when compared to those who were not married, and those with a high school diploma had 24% greater odds (OR = 1.24, 95% CI: [1.06, 1.46]) of opioid-involved death compared to those with a college degree.

DISCUSSION: The results of this study support previous research that demonstrated males have a higher odds of opioid-involved overdose death compared to females and that persons in industries with a high-risk of non-fatal work-related injury have increased odds of opioid-involved overdose death compared to all industries. This indicates a likely relationship between occupational injury and opioid-involved overdose death and that prevention efforts may be made more efficient by targeting persons employed in specific industries or occupations. More research should also be done to better understand the role of sex in this relationship to determine why males appear to have higher odds of opioid-involved overdose death compared to females. A more thorough understanding of the role occupation plays in the opioid epidemic could also be valuable for improving public health interventions to more efficiently combat the opioid epidemic in Georgia and the United States.

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