Journal of Emergencies, Trauma, and Shock
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 Table of Contents    
ORIGINAL ARTICLE  
Year : 2022  |  Volume : 15  |  Issue : 2  |  Page : 83-87
Opioid-related overdose fatality cases in two Florida counties


1 Department of Environmental and Occupational Health, Center for Environmental and Occupational Risk Analysis and Management, College of Public Health, University of South Florida, Tampa, Florida, USA
2 Florida State University College of Medicine, Sarasota, FL, USA

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Date of Submission22-Sep-2021
Date of Acceptance29-Apr-2022
Date of Web Publication27-Jun-2022
 

   Abstract 


Introduction: This study evaluates trends in drug-related death cases within both Pasco and Pinellas County, Florida, from the calendar years 2011 to 2016. Specifically, it focuses on opioids and the role of fentanyl in overdose-related mortality in rural versus suburban populations. Methods: Two sets of data from each calendar year were obtained from a Medical Examiner's Office. These data were compared by year to assess differences using the nonparametric ANOVA test with the statistical software SAS, University Edition. Binary logistic regression was performed to assess which drugs occurred most frequently in the presence or absence of fentanyl. Results: There was not a significant difference in the month of the year or the day of the week that drug-related fatalities occurred. More drug-related mortalities occurred during daylight hours (e.g., 8:00 AM–4:00 PM) and more fentanyl-related mortalities occurred in Pinellas County compared to Pasco County. Fentanyl and heroin tended to co-occur in mortalities, while ethanol, hydrocodone, morphine, oxycodone, and methadone were negatively associated with fentanyl-related overdose cases. Conclusion: The characteristics of drug-related mortalities identified here may be used to better target interventions against drug abuse and overdose.

Keywords: Fentanyl, mortality, opioid

How to cite this article:
Powell AT, Bourgeois MM, Lichterman J, Johnson GT, Galwankar S, Harbison RD. Opioid-related overdose fatality cases in two Florida counties. J Emerg Trauma Shock 2022;15:83-7

How to cite this URL:
Powell AT, Bourgeois MM, Lichterman J, Johnson GT, Galwankar S, Harbison RD. Opioid-related overdose fatality cases in two Florida counties. J Emerg Trauma Shock [serial online] 2022 [cited 2022 Sep 25];15:83-7. Available from: https://www.onlinejets.org/text.asp?2022/15/2/83/348349





   Introduction Top


The National Institute on Drug Abuse has published that between 26.4 and 36 million people around the world abuse opiates. According to the Center for Disease Control and Prevention (CDC), 115 Americans die every single day due to an opioid overdose. Collectively, more than 630,000 people have died from drug overdoses from 1999 to 2016. The CDC estimates that in America the economic burden of opiate abuse costs $78.5 billion dollars per year; including lost productivity, judicial system costs, and addiction treatment.[1] America has a problem with opiate addiction.[2] Notably, at the state level, Florida has a statistically higher level of drug overdose than the national average.[3]

It is known that the United States is experiencing an opioid epidemic.[4],[5],[6] The impact of the epidemic has been so profound that American life expectancy has been suggested to be decreased by 0.1 years, resulting in a life expectancy of 78.6 for the year 2017.[7] Although we know that hundreds of Americans are dying every day from opioid drug overdoses, we do not know what formulations of opioids are most susceptible to opioid overdose. National and State trends that have occurred during the opioid overdose have been published. Regional data and an effective understanding of the opioid epidemic at a local level have yet to be elucidated.

The purpose of this study is to analyze the population of decedents in a medical examiner district in Florida to assess the opioid epidemic in general, and due to the substantial increase in fentanyl toxicity, the fentanyl-related overdose cases at a regional level.[8] In addition, this study will characterize the population to determine trends and look for correlations in multi-drug toxicity overdose-related deaths. This study encompasses the years from 2011 to 2016. These years align with the end of the second wave of the opioid epidemic and include the third wave as published by the CDC. This regional study will help elucidate if the regional opioid epidemic reflects the national opioid epidemic.


   Methods Top


The data for this study were generated by the Florida District 6 Medical Examiner's Office (MEO) in the general course of business. An exemption was received from the Institutional Review Board (PRO: 00032603) for this study. After the exemption was granted, a public records request was placed with the District 6 MEO requesting specific data categories.

Two data sets for each year, 2011 through 2016, were obtained through the data request. The Case Detail Report contained approximately 1,800–2,000 cases for the years 2011, 2012, 2013, 2014, 2015, and 2016. The Florida Department of Law Enforcement Drug Stats–Drug-Related Cause report contained approximately 320–465 cases each year. Information from both data sets from all years was consolidated so all information for each drug-related death case with toxicological data was combined into a single database. The database used for analysis contained 2258 cases and was formatted to be SAS compatible.

The data were analyzed to produce the mean frequency of mortality events by drug composition. Comparators of interest were evaluated with the nonparametric ANOVA test. Binary logistic regression was performed to evaluate the odds of mortality between observed drug compositions as compared to fentanyl alone. For the purpose of this study, opioids are defined as substances that act upon the opioid receptor as a mechanism of action. Select opioids, specifically fentanyl, are selected for an independent analysis. P > 0.05 was considered nonsignificant.


   Results Top


Collectively, 2258 drug-related death cases with toxicology data from the years 2011 to 2016 were studied. It should be noted that there are demographic differences between Pinellas and Pasco County. Pasco county's population is approximately half that of Pinellas County. In addition, Pinellas County is more diverse with people of color composing approximately 11% of the population and Caucasians composing 82.7%. People of color make up approximately 8% of the population in Pasco County. Pinellas County's population is slightly older than Pasco County with 24% and 22% of the population being over the age of 65 years, respectively.

For this analysis, opiates were defined as codeine, heroin, hydrocodone, hydromorphone, morphine, oxycodone, and oxymorphone. Opiate death rates were highest in 2011. Pasco County has a higher opiate-related death rate for all 6 years analyzed [Figure 1].
Figure 1: Pinellas and Pasco County frequency of opiate drug-related deaths by year. The X-axis is the year analyzed, and the Y-axis is the mortality rate of opioid-related deaths included in the data, which is broken down by county

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Fentanyl mortality rates have consistently risen in both counties between 2011 and 2016 [Figure 2]. These rates were by far the highest in 2016. In the years 2015 and 2016, the fentanyl mortality rate in Pinellas County was almost twice that of Pasco County
Figure 2: Frequency of fentanyl-related mortality for Pinellas and Pasco County by year. The X-axis is the year analyzed, and the Y-axis is the mortality rate for fentanyl-related deaths included in the database, broken down by county

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Among deaths positive for pharmaceuticals opioids, fentanyl, or heroin, there is no significant differences in ages between males and females [Figure 3]. While the average age trends down over consecutive years, the trend is not statistically significant
Figure 3: Box plot demonstrating gender and age at death for fentanyl or heroin. Data are grouped by gender. The year is analyzed on the X-axis, and age is on the Y-axis. The boxes enclose the 25th–75th percentile. Means are designated by circles. Bars represent minimums and maximums

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[Figure 4] illustrates the average ages for fentanyl or fentanyl analog deaths for males and females from 2011 to 2016. The age ranges of males and females with fentanyl-related deaths were nearly identical to that of fentanyl and heroin deaths. Notably, 2016 is the only year the average age of fentanyl-related deaths for both males and females is < 40 [Figure 4]
Figure 4: Box plot demonstrating gender and age of death with fentanyl present. Data are grouped by gender. The boxes enclose the 25th–75th percentile. Means are signified by circles. Bars represent minimums and maximums

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There is a substantial difference in drug-related deaths between White, Black, and Asian populations when adjusting for the population percentage. While this difference is evident in both counties, the difference between the Black and White race adjusted fatality rates is less pronounced in Pinellas County [Figure 5].
Figure 5: Bar chart showing total drug-related deaths by race adjusted for percentage of population. The X-axis represents county data subdivided by race, and the Y-axis represents mortality data per capita. The mortality rate for all drug-related deaths was calculated using the individual county demographics

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A significant difference exists in the mortality rate of opiate and fentanyl-related deaths for White versus Black and Asian populations in Pasco and Pinellas counties. Caucasians were disproportionately affected by opiate and fentanyl-related mortality across both counties when subdivided by race.

Binary logistic regression

Binary logistic regression was used to determine which drugs are most and least likely to be present in drug-related deaths at the same time as fentanyl [Figure 6]. Based on the drugs observed, only heroin had a positive odds ratio point estimate, with a 3.650 odds ratio of co-occurrence [Table 1].
Figure 6: Bar chart demonstrating opiate and fentanyl-drug-related deaths by race adjusted for the percentage of population. The X-axis represents county data subdivided by race, and the Y-axis represents mortality rate for opiate and fentanyl-related deaths. Mortality rate was calculated using individual county demographics

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Table 1: Odds ratio from binary logistic regression of fentanyl exposure in the total counties' population from 2011 to 2016

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   Discussion Top


Drug-related deaths occurred in District 6 in Florida. This district includes Pinellas and Pasco Counties. Pinellas and Pasco Counties are geographically close but have different demographics. Uncovering predictable patterns in drug mortality rates would allow the region to better allocate resources in a way to more effectively and efficiently combat drug-related deaths. The time range includes portions of the second and third waves of the opioid epidemic. Opioids and fentanyl were the focus of this study, although the other major drug classes were considered when the probability of co-occurrence with fentanyl was assessed.

While there are differences in the average variance from the yearly mean in both the month and day of the week data, these differences are not statistically significant. It is interesting that the month and day of the week do not substantially change because Florida is a tourist destination with predictable fluctuations in population demographics. These include tourists on Spring Break or winter season residents. Despite these demographic variations throughout the year, the population of drug-related fatalities does not seem to be influenced by them. When looking at all drug-related deaths by day of the week, there do appear to be more deaths on Friday and Saturday. However, these increased rates are not statistically significant. The evaluation of the time range data reveals that certain times of day have significantly different averages as compared to the yearly mean. This indicates that certain time frames contain higher or lower deaths. The most drug-related mortality occurs between the hours of 8:00 AM and 4:00 PM. The expectation was that overdoses would be highest late at night. These data suggest drug abusers seem to need their daily dose or “fix” during their normal day and are more prone to daytime drug-related fatality. This trend carries through regardless of the day of the week or time of year.

Although Pinellas and Pasco Counties are both serviced by the same MEO, there was a difference in the impact of the opioid epidemic in each county. Pasco county is approximately half the population size as Pinellas county. Total drug-related deaths, adjusted for population, demonstrated a similar overall profile for both counties. When the data were broken down by opioids other than fentanyl versus fentanyl drug-related deaths, it was clear that there were consistent differences between the counties. Pasco county had consistently higher opioid-related mortality across all years analyzed. It is worth noting that fentanyl was excluded from the analysis of opioid-related fatality for this analysis. Fentanyl was analyzed individually. Pinellas county had significantly higher levels of fentanyl-related deaths relative to Pasco, almost double, in 2015 and 2016. In addition, Pinellas County had a higher rate of fentanyl-related fatalities over every year analyzed. This is a surprising difference in opioid-related death rates given that the overall death statistics match so well. Furthermore, it is interesting that Pinellas, which has a higher average income than Pasco, has a higher fentanyl-related mortality rate. Fentanyl is often used as a cheaper substitute for expensive prescription opioids. Pinellas and Pasco County had double the amount of fentanyl-related overdose deaths from the years 2015–2016. These data track national.[9]

It has been reported that the life expectancy in the United States has decreased since the beginning of 2015.[10] It has also been shown that the number of opioid deaths increased while concurrently the age of death decreased.[11] Furthermore, male-drug-related overdose deaths per capita were significantly higher as of 2016 compared to female-drug-related deaths.[11] When contrasting data in this study to the national data, it is shown that Florida District 6 does not totally correspond with national trends. The age of death shifts lower in 2016 but the change is not statistically significant. It is possible that more recent data that included 2017 and 2018 could demonstrate a continued trend toward younger opioid drug-related deaths. In addition, contrary to national statistics there were no significant differences when gender was analyzed in opioid drug-related deaths for any of the years analyzed. Both Pinellas and Pasco County had comparable opioid gender mortality rates overall years.

The data sets originally obtained in the public records request contained broad race categories white, black, and Asian. These categories were analyzed utilizing population adjusted by race to compensate for the District's demographics. It was found that Caucasians were disproportionately affected by drug-related deaths and opioid, including fentanyl, related deaths in Pinellas and Pasco County. These data are supported by published data which characterize the opioid epidemic as impacting lower-income white communities.[12],[13] The cause of these racial disparities is not known, but may be attributed to limited access to healthcare by minorities, or doctors prescribing fewer opioid medications to minorities groups.[13],[14]

Binary logistic regression was used to determine which drugs are most and least likely to be present in drug-related deaths at the same time as fentanyl. Convergence and model fit analysis indicated that the model was an adequate fit. Of the drugs that were calculated to be statistically significant explanatory factors, only heroin had an odds ratio point estimate > 1. The heroin odds ratio of 3.650 indicates the probability of co-occurrence is much higher than that of either drug exclusively. This result could be explained by drug users consuming fentanyl-contaminated heroin, or drug users specifically seeking out illicit fentanyl. Additionally, heroin is often cut or adulterated with fentanyl which would result in co-occurrence.[15] Additionally, differences in route of administration could impact these results. Binary logistic regression also elucidated five drugs with odds ratios < 1. This indicates these drugs tend toward mutual exclusivity in cases resulting in overdose deaths. These drugs include morphine, ethanol, hydrocodone, oxycodone, and methadone in order of diminishing odds ratio. Finding that some opioids negatively correlate with fentanyl overdose was not expected. Given that these drugs can be used in lieu of fentanyl by opioid-addicted individuals. The explanatory variable with the lowest significant odds ratio was methadone (odds ratio of 0.195). Interestingly, this suggests that methadone, a common treatment for opioid addiction, is likely effective. This conclusion is drawn because fentanyl and methadone occur together less than expected based on global probabilities calculated from the data set. This suggests that methadone may be an effective tool in the prevention of fentanyl-related fatalities.

Research quality and ethics statement

This study was determined not to require the Ethics Committee review. An exemption was received from the Institutional Review Board (PRO: 00032603) for this study. The authors followed applicable EQUATOR Network (“http:// www.equator-network.org/) guidelines during the conduct of this research project.

Financial support and sponsorship

Nil.

Conflicts of interest

There are no conflicts of interest.



 
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Drug Enforcement Administration. Alarming Spike in Fentanyl-Related Overdose Deaths Leads Officials to Issue Public Warning, United States Drug Enforcement Administration; 2020. Available from: https://www.dea.gov/press-releases/2020/08/06/alarming-spike-fentanyl-related-overdose-deaths-leads-officials-issue. [Last accessed on 2022 Jan 12].  Back to cited text no. 15
    

Top
Correspondence Address:
Raymond D Harbison
Department of Environmental and Occupational Health, Center for Environmental and Occupational Risk Analysis and Management, College of Public Health, University of South Florida, 13201 Bruce B. Downs Blvd., Tampa, Florida 33612
USA
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Source of Support: None, Conflict of Interest: None


DOI: 10.4103/jets.jets_130_21

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