Jon M. Hager and John S. Batchelder
University of North Georgia
Abstract
Deaths associated with the use of prescription opioids have been increasing rapidly for the past decade. Accelerated use of prescription opioids is currently fueled by the growing number of doctors willing to prescribe them, the social acceptance of using medications without stigma, and aggressive tactics used by pharmaceutical companies to market their products and increase sales. These medications include codeine, oxycodone, morphine, fentanyl, and hydrocodone. Misuse of these drugs can be fatal, with the deceased victims falling into two categories (cause of death): those who died from prescription opioids with no other drugs or alcohol consumed, and those who died from prescription opioids plus another substance. This study examined the frequently researched factors associated with prescription opioid mortality in an attempt to provide insight for the criminal justice community, and assist in prevention. Two of the three factors were found to be statistically significant: age and biological sex. The third factor, racial background, had no impact on the dependent variable: cause of death.
Factors Associated with Adult Deaths Caused by Prescription Opioid Use in Conjunction with Alcohol, Marijuana, Methamphetamine, or Cocaine
Introduction
According to the National Institute on Drug Abuse (2018b), prescription opioids are medications designed to reduce the intensity of pain-signal perception, and are most commonly used to address acute and chronic pain. Prescription opioids have become problematic, because they are similar in chemical composition to heroin, and produce a euphoria with an increased risk of abuse, often leading to death. Popular prescription opioids include codeine, oxycodone, morphine, fentanyl, and hydrocodone, with the latter being the most commonly prescribed (National Institute on Drug Abuse, 2018b).
The increase in prescription opioid deaths since 1999 has been identified as a crisis by federal, state, and local governments. However, it was not until 2011 that the White House developed a strategy to combat the prescription opioid overdose epidemic (National Institute on Drug Abuse, 2018a). Approximately 70,000 individuals died from drug overdoses in 2017, and 68% of those deaths (47,000) were by prescription or illicitly obtained opioids. In 2019, the Centers for Disease and Prevention Control (CDC) reported drug overdose as the leading cause of injury-related deaths in the United States.
At the national level, the CDC (2018) identified several “evidence-based” strategies for effectively preventing opioid overdoses: medication-assisted treatment, academic detailing, medications that have no prior-authorization requirements, routine testing for Fentanyl in clinical settings, 911 Good Samaritan Laws, and Naloxone distribution in treatment and criminal justice settings. In response to the example set by federal authorities to fight this crisis, state and local authorities are taking steps to eliminate the problem as well. In Georgia, where opioid deaths have increased at more than twice the rate of the national average (Jayawardhana, et al., 2018), the Substance Abuse Research Alliance (2017) reported measures taken to address the epidemic:
1) Increased access to opioid treatment and Naloxone; 2) increased funding for prevention education and physician education; 3) creating a commission on substance use recovery and neonatal abstinence; and 4) strengthening prescription drug monitoring programs with increased oversight of pain clinics.
The epidemic comes with a substantial social and economic cost. According to Birnbaum et al. (2011), in 2007, the overall cost of the prescription opioid epidemic nationwide was approximately $55.7 billion. Officials in Fulton County, Georgia, are seeking to recover some of those costs, and have taken legal actions against distributors, manufacturers, and doctors, who are allegedly responsible for illegal distribution. In fact, Fulton County, Georgia, which is where this study took place, filed a 258-page complaint that accused drug companies of minimizing opioid addiction, and using deceptive marketing practices in order to increase sales (Redmon, 2018). Additionally, pharmaceutical companies are actively engaged in minimizing the number of prescription opioid-related deaths (Redmon, 2018). The purpose of this study is to analyze commonly researched factors associated with opioid-related deaths between 2014 and 2016 in Fulton County, to analyze the impact of using multiple substances as a contributor for the increase in those deaths, and to make recommendations on prevention.
Literature Review
Roxburgh et al. (2017) examined trends in opioid overdose deaths by opioid type (heroin and prescription) between 2001 and 2012 in Australia. Out of 8547 cases of opioid overdose deaths, 34% were heroin overdoses, and 58% were resulting from opioid prescriptions. Among the factors examined in that study were age, gender, and intent of death. The overall trend showed that heroin deaths did not increase significantly over the period, however, prescription opioid deaths did increase.
Chihuri and Li’s (2017) analysis of traffic-fatalities connected both prescription opioids and elevated blood alcohol concentrations with other drug use, but those findings were restricted to deaths caused by injuries inflicted in the accident, which leaves unanswered questions regarding the impact of using multiple substances as a contributor to the increase in opioid- related deaths. This notion was briefly explored by Kandel, Hu, Griesler, and Wall (2017), whose research analyzed the interaction between psychoactive substances and prescription opioid overdose deaths, and their findings concluded that a link is likely. By comparing different time frames, those findings suggested the possibility of opioid-related deaths being associated with polysubstance use. That demonstrates the need for further research on the influence of psychoactive substances, such as alcohol, marijuana, methamphetamine, and cocaine in combination with prescription opioids that result in death.
In a follow-up study, Griesler, Hu, Wall, and Kandel (2019) examined the medical use and misuse of prescription opioids in the U.S. adult population from 2016 to 2017. Using data obtained from the National Surveys on Drug Use and Health, their findings demonstrated a link between marijuana, benzodiazepine, and heroin among individuals who misuse prescription opioids. These findings further support the investigation of polysubstance use with misuse of prescription opioids, when it is revealed as a primary factor in the cause of death. The National Institute on Drug Abuse (2018a) identified three different paths to addiction among heroin users in Chicago: 1) The path from prescription opioid abuse to heroin use; 2) the path from polysubstance abuse to heroin use, and 3) the path from cocaine use to heroin use, the most common being path number two: polysubstance to heroin. Four percent of the individuals using prescription opioids to the pathway of heroin use (path number one) may already be predisposed to polysubstance use.
Esther, Carole, and Traci (2014) examined the gender differences in emergency department (ER) visits related to nonmedical-prescription opioid use. With a national sample size over 1 million, 24% of the emergency department visits were related to nonmedical use of prescription drugs and 39% involved opioids. The damage visited upon our society by this scourge is alarming. Although these authors found no significant differences between men and women in the number of ER visits, the implication seems to suggest that the epidemic is now reaching an undesirable degree of gender-equality, particularly because these findings were similar regardless of age and racial background.
Green et al. (2010), analyzed the epidemiology and the geographic distribution of accidental deaths related to opioids, and determined the leading cause of injury deaths among adults in Connecticut between 1997 and 2007 was drug poisonings. The historical data, obtained from the Office of the Chief Medical Examiner, attempted to uncover any risk factors related to opioid intoxications compared to deaths associated with heroin, prescription opioids, and methadone. They mapped the death locations to uncover geographic patterns of 2900 drug poisoning deaths; 2231 (77%) of which were attributed to opioids. That study concluded that heroin-only deaths were primarily associated with non-whites, and likely to involve alcohol or cocaine, while prescription opioids-only were most likely to include another type of medication. The study focused primarily on geographic differences by opioid type and risk factors.
Using data from the Office of the Chief Coroner of Ontario, Singh et al. (2018) examined the role of alcohol in 737 opioid-related deaths in 2015, noting that the majority of the deaths were men living in low socio-economic urban areas, half of which were 45 to 65 years-of-age.
The study found 25% of the decedents were previously diagnosed with alcohol use disorder, but failed to examine any links with marijuana, methamphetamine, and cocaine. Monnat et al. (2019) examined opioid mortality rates across the U.S. between 2014 to 2016, using labor market characteristics, demographics, and socioeconomic factors at the county-level. Those researchers concluded that the drug mortality rates were highest in counties with an economic disadvantage, and those with higher numbers of opioid prescriptions among service industry and blue-collar workers. Also, that economically-disadvantaged counties were less likely to use heroin class drugs. The current study builds on these findings, and further examines age, sex, and race factors as well. Data from the California Electronic Death Reporting system records, and the San Francisco Medical Examiner’s office for the years 2006 to 2012, provided insight on 816 unintentional opioid-overdose deaths. Twenty-five percent were by heroin injection, the modal category in that study, with 205 decedents (Hurstak, et al., 2017).
There is data from The National Institute on Drug Abuse (2018a) that further supports the need regarding the polysubstance pathway. Young adults who transitioned from non-injection drug use to injecting opioid pain relievers before converting to injecting methamphetamine or heroin informs the notion that a pathway to polysubstance use via prescription opioids and heroin is becoming a widespread problem. Boslett et al. (2019) examined economic disparities in unclassified deaths by drug overdose, and found not only geography, but biological sex and education factors played a role as well. Surprisingly, White, Non-Hispanic females, aged 30-59, with college education had higher rates of unclassified drug-overdose deaths.
The forgoing research points to the need to acquire evidence on the connection between prescription opioid-deaths and polysubstance use, while considering age, race, and gender factors. Clearly, there is a need to further investigate the difference between decedents who engaged in polysubstance use in addition prescription opioid use, and decedents who engaged in prescription opioid use alone, and to include a variety of covariates (gender, race, and age) in the analysis. This study intends to fill gaps in the research regarding interactive effects of opioid and polysubstance use leading to death.
Methodology
Sample
Fulton County, located in North Georgia, where approximately 10% of Georgia’s 10.3 million persons reside, is 48% male, 45% Caucasian, 44% African-American, 7% Asian, and 7% Hispanic (U.S. Census Bureau, 2018). The subjects in this study are taken from a population consisting of 287 opioid-related deaths occurring from 2014 through 2016 as identified by the Fulton County Medical Examiner’s Office. To be included in the study, data on the subjects needed to contain information on the decedent’s age, biological sex, and race, in addition to the primary cause of death: prescription opioids only, or polysubstance use. Polysubstance use is defined as prescription opioid plus one or more of the following drugs: cocaine, methamphetamine, marijuana, or alcohol.
To comprise a coherent study-group, 35 cases were excluded because primary cause of death was either not specific, was not relevant to the research, or information was otherwise incomplete, leaving 252 decedents whose death was attributed to opioid overdose during the time period. Two more subjects in the study group were later excluded because the cause of death did not involve prescription opioids, but rather, death caused by heroin. Because the focus of this research is adult deaths, an additional three decedents among the subjects in the study-group were excluded because they had not reached 18 years-of-age.
Variables
This study is investigating the cause of death among persons who had been identified by the Medical Examiner’s Office as having been attributed to prescription opioids. Therefore, the analysis of the variable of principle concern is a dichotomous dependent variable: cause of death (opioid-only or polysubstance). The independent variables in this study are biological sex, age, and race. Using those three independent variables, three hypotheses were formed to ascertain if the difference in observed cases of cause of death (between levels of the factors examined) could have occurred by chance.
H1: There is a statistically significant difference among opioid-only deaths and polysubstance- user deaths between the two levels of biological sex (male and female).
H2: There is a statistically significant difference among opioid-only deaths and polysubstance- user deaths between the two age-groupings (age-39 and below or greater than age-39).
H3: There is a statistically significant difference among opioid-only deaths and polysubstance- user deaths between the racial background-groupings (Caucasian or African-American, Latino, and Asian).
Data Analysis
Statistical analyses were performed using IBM SPSS 24 to determine if the prevailing factors associated with opioid deaths produced verifiable patterns among users whose death was attributable to only opioids, and those decedents who used opioids and either cocaine, methamphetamine, marijuana, or alcohol (polysubstance use). A two-way Chi-Square procedure was chosen because we used the dichotomous independent variables biological sex, age, and race, in the analysis of the dichotomous dependent variable cause of death. This was necessary because some cells in the original variable format did not have enough cases to proceed with the Chi-Square procedure otherwise.
Results
Descriptive Statistics
The final data-set received from the Fulton County Medical Examiner’s Office on deaths in Fulton County that were attributed to opioids produced a study-group of 247 decedents. There were 162 males and 85 females. By death type, 107 victims died by ingesting prescription opioid medication alone, whereas 140 died by poly-substance use (prescription opioid plus one or more of the following: marijuana, methamphetamine, alcohol, or cocaine). Of the 247 subjects, 152 were Caucasian (62%), 87 were African- American (35%), and the remaining eight decedents were Asian (5) and Latino (3). Since the latter two categories were under-represented, (1% and 2% respectively), the variable “Race of Decedent” was recoded, grouping Caucasian and Non-Caucasian decedents dichotomously by racial background. The subjects ranged from 18 to 68 years-of-age, with a mean of 39.77-years-of-age. With the median age of the study group also at age-39, the variable age was recoded into a dichotomous nominal variable at the median age of 39 and below, and age-40 and above.
Inferential Statistics
The first factor examined in the study was biological sex. The data revealed that the null hypothesis that corresponded to H1 (male and female) was rejected because significant differences were found on the independent variable gender across levels of the dependent variable prescription only or polysubstance χ2(1,N = 247) = 10.834, p. = .001. The effect size, as expressed by Lambda, was 12%. The women deaths investigated in this study were less likely to be caused by the use of additional substances when taking prescription drugs (42%), whereas male fatalities were typified by a pattern of using a combination of drugs when taking prescriptions (64%). The second factor examined in the study was racial background. The data revealed that the null hypothesis that corresponded to H2 (Caucasian or other racial background) failed to be rejected, because no significant differences were found among the independent variable racial background across levels of the dependent variable prescription only or polysubstance χ2(1,N = 250) = 0.323, p. = .570.
The final factor examined in the study was age. The data revealed that the null hypothesis that corresponded to H3 (age 39 and below, or age 40 and above) was rejected because significant differences were found on the independent variable age-group across levels of the dependent variable prescription only or polysubstance χ2(1,N = 250) = 3.905, p. = .048. Younger decedent-deaths investigated in this study were more likely to be caused by the use of additional substances when taking prescription drugs (63%), whereas among those fatalities who were age 40 and above were typified using only prescription opioids (37%).
Discussion
Biological Sex
Internationally, authors are united in their findings regarding biological sex: men use and are harmed by prescription opioids in greater numbers, but women are currently at greater risk, and our study was in agreement with those findings. Just as Roxburgh et al. (2017) found Australian males had a much higher death rate among prescription opioid users, we found males to be higher in the polysubstance category. That study found female deaths by prescription opioids were increasing at a faster rate (females increased threefold from 9.6 to 28.9 compared with 6.1 to 15.4 among males), the gender differences we discovered amplify the increasing risk for females in Fulton County.
This trend is also evident in Canada, where Agterberg, Schubert, and Corace (2018), discovered similar findings. This increased risk for females alarms public health officials in Georgia, who, like in Australia and Canada, find men more likely to die from an opioid overdose than women, but the rate of opioid-related deaths for women is increasing at a more rapid pace. Recent data analyzed by Silver and Hur (2020) found that although men were more likely than women to report prescription opioid misuse, women were significantly more likely to report prescription opioid use for both their lifetime and the past year. And, reinforcing how similar and consistent these findings are to our own, their differences remained significant after accounting for other demographics. The current study also had similar findings as Agterberg, Schubert, and Corace (2018) in terms of biological sex. We found that 64% of males died from the pattern of using a combination of drugs when taking prescription opioids, while women was 42%. So the present study, along with the other three discussed here, have findings in lockstep: males were more likely to die from an opioid-related death with or without a combination of drugs. And, although male pharmaceutical opioid deaths have increased faster over the long term, short-term data show women advancing at a disturbing rate. Currently, Fentanyl patch prescriptions are higher among females than males. With our findings confirming that male-deaths were more likely to occur among poly-substance users, policies that target females may be able to limit their rapidly accelerating rate of opioid-deaths overall. This conclusion holds true especially in view of the success rate experienced by subjects who have had their prescriptions restricted, and whose elevated treatment access gave them the chance to break free of opioid-dependence.
Age
The Roxburgh et al. (2017) study examined age as a factor among subjects who were prescribed fentanyl using 10-year age groups (those aged 20–29 years, 30–39 years, 40–49 years, 50–59 years, 60–69 years, and 70–79 years). Since all of those decades showed a significant increase, it became of interest to us to explore if there was a point at which researchers might be able to identify additional factors that will inform comprehensive policy. Since the median age of death in the Australian study was 39 years, and both the mean age and the median age in the current study was 39 years, the current study dichotomized age by those below age-39 and those age 40-and-older. With age, while heroin deaths did not change or decrease over time between age groups, opioid deaths increased across all age groups. Although the findings across age- groups are not as salient or alarming as those among biological sex, they still have the potential to inform future research exploring the factors associated with opioid-deaths.
Prevention
This study highlighted the relationship between opioid-related deaths and polysubstance use. Though preventive measures are being taken at the federal, state, and local levels to reduce opioid addiction and deaths, few studies address prescribing opioids to individuals who previously or currently use other drugs such as alcohol, marijuana, heroin, methamphetamine, or cocaine. In September of 2019, the CDC (n.d.) announced a three-year cooperative agreement with Overdose Data to Action to focus on the crisis. The agreement utilizes a public health, interdisciplinary, and comprehensive approach to suppress drug overdoses. Components of this initiative include the collection of data from emergency rooms and descriptions of drug overdose deaths obtained from the medical examiner and coroner autopsy reports (CDC, n.d.). A follow- up study will be needed to determine if the Overdose Data to Action was an effective plan for reducing drug overdoses.
The authors would also suggest collecting data from primary physicians who have patients that die while hospitalized (inpatient). In some cases, those deaths are not reported to a medical examiner or coroner, thus leaving important data uncollected. For individuals who die in the emergency room, it is more difficult to obtain a medical history, especially if they are presented in an unconscious state. While inpatient, the physicians should be able to obtain a full medical history, and determine whether there was previous or current use of alcohol, marijuana, heroin, methamphetamine, or cocaine. If so, physicians would be more informed in the diagnosis, and may even refrain from prescribing opioids to the patient. The results of this study demonstrate the heightened risks associated with prescribing opioids to an individual that it is using alcohol, marijuana, heroin, methamphetamine, or cocaine.
These findings address a critical public-health issue, and highlight the importance of educating the public, healthcare professionals, and criminal justice officials about reducing overdoses by polysubstance users who are prescribed opioids. Healthcare professionals need to be fully transparent with their patients regarding the risks of taking prescription opioids with alcohol, marijuana, heroin, methamphetamine, or cocaine. The public needs to be better educated by the criminal justice community about the Good Samaritan laws, which provide protections for individuals who report an unintentional drug overdose of another. Although this may not prevent individuals from polysubstance use, the law would assist in reducing the number of deaths. And survivors who are educated by healthcare professionals about the danger of polysubstance use and the risk of death can pass that knowledge on to others.
Overall, the study addresses the high probability of a death outcome when prescribing opioids to polysubstance users. The cause of prevention would be furthered through a collaborative effort among the public, healthcare professionals, and the criminal justice community to overcome this problem. Combining communication and education among physicians and patients, as well as among criminal justice professionals and the public, and among public health officials and the public, would go a long way towards limiting the number of deaths of individuals who are being prescribed opioids while using alcohol, marijuana, heroin, methamphetamine, or cocaine. Those simple prevention efforts may have resulted in fewer deaths related to prescription opioids and polysubstance use in Fulton County, Georgia.
Conclusion
This study expanded the current body of research by examining opioid-related deaths that involved polysubstance use with marijuana, cocaine, methamphetamine, and alcohol. We examined the factors that are frequently found to be statistically significant contributors to explaining variability among users: biological sex, age, and racial background. Although there are frequently statistically significant findings involving drug use between persons with different racial background, among the decedents in this study, racial background seemed to play no role.
The findings of recent studies have enlightened the research community and produced an awareness of the urgent need for formulating reduction and prevention policies. Our findings demonstrate that policies aimed at prescription-opioid users, particularly those that also use other drugs, including ethanol, cocaine, methamphetamines, benzodiazepine, or heroin, may gain traction in efforts geared toward the reduction of deaths. Although more work needs to be done, this study has provided grounds for further investigation of the factors common to individuals who misuse drugs along with prescription opioids, because of the potential to be a primary factor in the cause of death. Clearly, there needs to be more emphasis on determining if patients have in the past, or are now, using these other drugs, and if so, restricting the violator’s access prior to prescribing opioids.
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John Stuart Batchelder is a Professor of Criminal Justice at University of North Georgia who specializes in statistical analysis and corrections. He received his doctorate in Adult Education from the University of Southern Mississippi. His research interests focus on prison education and intervention and quantitative methodologies.
Jon M. Hager is an Assistant Professor of Criminal Justice at the University of North Georgia specializing in forensic science and specifically death investigations. He received his doctorate in Psychology with a concentration in Criminal Justice from the University of the Rockies. His current research interests include forensic science and death investigations.