Abstract
Background:
Opioid overdoses have increased at a concerning rate in recent years. Middle-aged individuals have been reported as an age group of high concern for opioid overdoses. The purpose of this study was to assess trends in opioid overdose 911 dispatches between Q1 2018 and Q3 2023 among different age groups. It was hypothesized that the steepest increase in dispatches would be among middle-aged individuals.
Methods:
We assessed age-related trends in opioid-related 911 dispatches using emergency medical service (EMS) data collected by biosptial, io. Data encompassed all 50 states and were broken into yearly quarters between Q1 2018 and Q3 2023. Age groups included younger- (10 to 29), middle- (30 to 49), and older-aged (50 to 69) individuals. Joinpoint regression was utilized to examine these trends.
Results:
There were a total of 1,420,298 opioid-related 911 dispatches reported. Most were reported among middle-aged individuals, accounting for 48.9 % (n = 682,132) of all dispatches. Significant increases in dispatches were identified overall between Q1 2018 and Q2 2021 (β = 0.096, SE = 0.006, P ≤ 0.001). The steepest increase was identified among middle-aged individuals between Q1 2018 and Q2 2021 (β = 0.104, SE = 0.007, P ≤ 0.001). There was a significant decrease in dispatches among younger-aged individuals between Q2 2021 and Q3 2023 (β = −0.024, SE = 0.011, P = .036).
Conclusion:
Middle-aged individuals experienced significant increases in opioid-related 911 dispatches between Q1 2018 and Q2 2021, and had the steepest increase compared to the other age groups. Conversely, younger-aged individuals have experienced a recent decrease in dispatches. These findings support previous indications that middle-aged individuals are at significant risk for opioid overdose. Additional research is necessary to identify geographic and demographic factors that may affect these trends.
Keywords: Opioids, Overdose, 911 dispatches, Age
1. Introduction
Opioid-related overdoses have emerged as a major concern in public health, and despite ongoing reduction efforts, the number of overdoses continues to rise [1]. In 2020, age-adjusted drug overdose deaths in the US increased by 31 % from 2019, with 56 % involving synthetic opioids [2]. In 2021, drug overdose mortality rates increased by 14 %, with 22 % involving synthetic opioids [3]. The opioid epidemic has had a detrimental impact on the life expectancy of people in the US [4] and has cost the US economy an estimated $1.02 trillion in 2017 [5]. Chen and colleagues predict that fatalities related to opioid use will continue to rise through 2025, resulting in 700,400 individuals in the US dying from opioid overdoses, with 80 % being attributed to synthetic opioids [6].
The opioid epidemic began with the first wave of prescription opioids in 1999, followed by a second wave that started between 2010 and 2011 with the increase in heroin-related deaths. The third wave, involving synthetic opioids like fentanyl, began between 2013 and 2014 and continues to the present day [7–12]. The rising potency and adverse effects associated with synthetic opioids, especially fentanyl and its analogs (e.g., carfentanil, acetylfentanyl, butyrfentanyl, and furanyl fentanyl), have raised even more concerns [13]. Fentanyl is predicted to be 50–100 times more potent compared to morphine [12]. There have been recent mentions of a potential fourth wave involving the polysubstance use of fentanyl with other substances such as stimulants [13–17]. This may compound with changes in substance use patterns observed during the COVID-19 pandemic to result in an increase in opioid overdoses. Given the evolving and persistent threat of the opioid epidemic, it is pertinent to identify characteristics of these trends, including age, in order to respond effectively.
Previous literature has indicated that individuals in middle age are at the highest risk for opioid overdoses [4,17]. According to the Center for Disease Control and Prevention (CDC), from 2019 to 2021, the rate of drug overdose deaths was highest among people in the middle-age group, specifically those aged 35 to 44 [2,3]. With the ongoing discussion regarding the changing landscape of polysubstance use in opioid overdoses and the possibility of a fourth wave, we aim to identify age-related trends in nonfatal opioid overdoses using 911 dispatch data between Q1 2018 and Q3 2023. We hypothesized that middle-aged individuals (aged 30 to 49) would account for the highest number of opioid overdose-related 911 dispatches, along with males.
2. Methods
2.1. Procedure
Emergency medical service (EMS) data gathered by biospatial, Inc. was assessed quarterly for trends in opioid-related dispatches. This included data from 2235 counties among all 50 US states between January 1st, 2018 (Q1 2018), and September 30th, 2023 (Q3 2023). Opioid-related 911 dispatches were identified using the Rhode Island Enhanced State Opioid Overdose Surveillance criteria. This criteria assesses EMS elements (primary and secondary impression of provider, symptoms, medication administered, and response to administered medication) to determine opioid involvement in a reported overdose. Opioid-involved 911 dispatch data was shared with the National Drug Early Warning System as part of an ongoing collaboration. No personally identifiable information was utilized in these analyses; thus an Institutional Review Board approval was not needed for this study.
Years were broken into quarter years, with Q1 including January through March, Q2 including April through June, Q3 including July through September, and Q4 including October through December. Age was defined categorically in intervals from 10 to 29 years old (younger-aged), 30–49 years old (middle-aged), and 50–69 years old (older-aged). Records of overdose dispatches for persons under age 10 and above 69 were small in sample sizes and were not included. Sex was defined as “Male” or “Female” and race was defined as “White”, “Black”, “Hispanic/Latino”, “Asian”, “Native American”, “Pacific Islander”, or “Unknown”.
2.2. Statistical analysis
Trends in opioid overdose-related 911 dispatches were assessed through Joinpoint Regression version 4.8.0.1 [18]. This method of regression utilizes a log-transformed scale to fit weighted least-square regression models to the count data [19,20]. The procedure utilized Monte Carlo permutation tests (with Bonferroni correction for multiple testing) to identify the trends across time as well as joinpoints, points in the analysis period that indicate a significant shift. All other data visualization and analysis was conducted in R version 4.3.0 [21].
3. Results
Between Q1 2018 and Q3 2023, there were a total of 1,420,298 opioid overdose-related 911 dispatches reported. Table 1 displays opioid overdose-related 911 dispatches by sex. Most dispatches were reported among middle-aged individuals, accounting for 48.9 % (n = 682,132) of all dispatches. The majority (57.53 %, n = 723,794) were “White”, while 19.5 % (n = 276,751) were “Black”, 8.7 % (n = 123,201) were “Hispanic/Latino”, 0.9 % (n = 12,133) were “Native American”, 0.5 % (n = 6848) were “Asian”, 0.2 % (n = 2975) were “Pacific Islander”, and 0.03 % (305) were “Other”. There were 13.8 % (n = 196,553) with no race reported. Males accounted for approximately two-thirds 67.2 % (n = 955,242) of all reported dispatches and Females accounted for 32.8 % (n = 459,697).
Table 1.
Sample characteristics and bivariate analyses examining differences in opioid overdose dispatches by sex.
| Overalla (n=1,420,298) | Sex |
|||
|---|---|---|---|---|
| Male (n=955,242) | Female (n=459,697) | p-value | ||
|
| ||||
| Age (yrs), n (%) | <.001 | |||
| 10 – 29 | 328,541 (23.2) | 222,853 (23.4) | 104,271 (22.7) | |
| 30 – 49 | 682,132 (48.9) | 466,580 (48.8) | 212,907 (46.3) | |
| 50 – 69 | 409,621 (28.9) | 265,809 (27.8) | 142,519 (31.0) | |
| Race, n (%) | <.001 | |||
| White | 801,528 (56.4) | 512,289 (53.6) | 287,957 (62.6) | |
| Black/African American | 276,751 (19.5) | 199,967 (20.9) | 76,208 (16.6) | |
| Hispanic/Latino | 123,201 (8.7) | 94,825 (9.9) | 28,080 (6.1) | |
| Native American | 12,133 (0.9) | 6,944 (0.8) | 5,143 (1.1) | |
| Asian | 6,848 (0.5) | 4,712 (0.5) | 2,120 (0.5) | |
| Pacific Islander | 2,975 (0.2) | 2,028 (0.2) | 941 (0.2) | |
| Other | 305 (0.0) | 204 (0.0) | 101 (0.0) | |
| Not reported | 196,553 (13.8) | 134,273 (14.1) | 59,147 (12.9) | |
Note. P-values are from χ2 testing. Significance is indicated by:
p<.05
p<.01
p<.001
Includes 5,359 individuals with missing sex.
Fig. 1 presents trends in opioid overdose-related 911 dispatches between Q1 2018 and Q3 2023 by age group. Overall, counts of opioid overdose-related 911 dispatches increased significantly between Q1 2018 and Q2 2021 (β = 0.096, SE = 0.010, P ≤ 0.001). There were no further significant trends overall through Q3 2023. Younger-aged individuals experienced a significant increase in opioid overdose-related 911 dispatches between Q1 2018 and Q2 2021 (β = 0.093, SE = 0.006, P ≤ 0.001), followed by a significant decrease between Q2 2021 and Q3 2023 (β = −0.024, SE = 0.011, P = .037). For middle-aged individuals, the number of opioid overdose-related 911 dispatches increased significantly between Q1 2018 and Q3 2021 (β = 0.082, SE = 0.004, P ≤ 0.001). There were no additional periods of significant change through Q3 2023 for this age group. Older-aged individuals experienced a significant increase in opioid overdose-related 911 dispatches between Q1 2018 and Q2 2021 (β = 0.11, SE = 0.01, P ≤ 0.001), with no further significant trends through Q3 2023.
Fig. 1.
Trends in opioid-related 911 dispatches by age group from Q1 2018 to Q3 2023.
Table 2 details the average quarterly percent change (AQPC) over the entire analysis period for each age group; all AQPCs were significant between Q1 2018 and Q3 2023. There was an overall AQPC of 6.02 % (95 % CI: 5.24, 6.75). Younger-aged individuals had the smallest AQPC at 4.63 % (95 % CI: 3.71, 5.50), while middle-aged individuals had the highest AQPC at 6.74 % (95 % CI: 5.80, 7.62). Older-aged individuals had an AQPC of 5.81 % (95 % CI: 5.03, 6.49).
Table 2.
AQPCs (Average Quarterly Percent Change) and 95% Confidence Intervals
| Age Range | AQPC (%) | 95% Confidence Interval |
|
|---|---|---|---|
| Lower | Upper | ||
|
| |||
| 10 to 29 Years old | 4.63* | 3.71 | 5.50 |
| 30 to 49 Years old | 6.74* | 5.80 | 7.62 |
| 50 to 69 Years old | 5.81* | 5.03 | 6.49 |
| Overall | 6.02* | 5.24 | 6.75 |
Indicates that the slope is significantly different from zero at alpha = 0.05.
4. Discussion
This study examined trends in opioid overdose-related 911 dispatches among different age groups using EMS data from across all 50 US states. There was an overall significant increase in these dispatches between Q1 2018 and Q2 2021. There were periods of significant increase in each age group, but middle-aged individuals experienced the steepest increase. The only period of significant decrease identified was among younger-aged individuals between Q2 2021 and Q3 2023. AQPCs were significant across all age groups, as well as overall, with the highest AQPC also among middle-aged individuals.
Most published studies assessing opioid overdose trends have reported findings in relation to other substances or characteristics: however, this study focused on further exploring trends by age differences specifically. The increases in opioid-related overdose 911 dispatches overall identified in this study support previous findings of increasing opioid overdoses in the US [22,23]. The findings also support results from other studies using 911 dispatch data to assess opioid-related overdose trends [24].
Previous studies have found increases in opioid-related overdoses among young people [25] that follow the increase seen in this analysis between Q1 2018 and Q2 2021. The recent (Q2 2021 to Q3 2023) decrease in opioid overdose-related 911 dispatches identified among younger adults may indicate opioid-related overdoses among younger-aged individuals are declining from the spike seen during the COVID-19 pandemic. Middle-aged individuals appear to maintain the highest increase in dispatches across the analysis period, as well as the largest AQPC. While trends were not significant past Q2 2021, counts appear to be stable, or slightly increasing, suggesting that the rate of increase in opioid-related overdoses may be slowing down. Similar results were seen among older-aged individuals, with a significant increase through Q3 2021 and no significant trend through Q3 2023. Counts again appear to be relatively stable (or slightly increasing) through Q3 2023. AQPCs ranged from 4.63 % to 6.74 %. Ultimately, a single period of decrease was identified in younger individuals, while significant increases were seen across all age groups. These overall increases indicate a growing need for public health interventions, especially among middle-aged individuals.
4.1. Limitations
There are several limitations of the study. While data included came from all 50 states, coverage in each state varies, limiting generalizability. Additionally, the criteria included for identifying opioid-involved overdoses does not include biological or toxicological data to corroborate the presence of an opioid. The impact of the COVID-19 pandemic also must be considered, with EMS agencies having limited ability to respond to emergencies in early 2020. Despite these limitations, the large sample size and recency of the data support the strength of these findings.
4.2. Conclusion
Significant increases in opioid-related 911 dispatches were identified between Q1 2018 and Q3 2023 in the US, with middle-aged individuals accounting for the most dispatches and experiencing the steepest increase. Each age group had at least one period of significant increase, and only one age group had a period of significant decrease. While further research is necessary, the findings of this study indicate that opioid overdoses are increasing in adults—especially among middle-aged individuals. Future studies should consider analyzing individual level characteristics, as well as utilizing multiple data sources to strengthen findings. Healthcare providers should consider these populations when assessing substance use disorders.
Sources of support
Research reported in this manuscript was supported by funding from the National Institute on Drug Abuse of the National Institutes of Health under Award Number T32DA035167 (PI: Cottler), by the National Drug Early Warning System Award Number U01DA051126 (PI: Cottler), and by the University of Florida Clinical and Translational Science Institute, which is supported in part by the NIH National Center for Advancing Translational Sciences under Award Number UL1TR001427. The content is solely the responsibility of the author (s) and does not necessarily represent the official views of the National Institutes of Health.
Funding
Research reported in this manuscript was supported by funding from the National Institute of Drug Abuse of the National Institutes of Health, and by the University of Florida Clinical and Translational Science Institute, which is supported in part by the National Institutes of Health National Center for Advancing Translational Sciences. The content is solely the responsibility of the author(s) and does not necessarily represent the official views of the National Institutes of Health.
Abbreviation:
- AQPC
Average Quarterly Percent Change
Footnotes
Declaration of competing interest
None.
CRediT authorship contribution statement
Andrew J. McCabe: Writing – review & editing, Writing – original draft, Visualization, Validation, Supervision, Software, Resources, Project administration, Methodology, Investigation, Funding acquisition, Formal analysis, Data curation, Conceptualization. Nae Y. Won: Writing – review & editing, Writing – original draft, Methodology, Conceptualization. Linda B. Cottler: Writing – review & editing, Writing – original draft, Validation, Supervision, Resources, Project administration, Methodology, Investigation, Funding acquisition, Data curation, Conceptualization.
Data availability
Data that supports the findings of the present study are available from the corresponding author upon reasonable request.
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Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Data Availability Statement
Data that supports the findings of the present study are available from the corresponding author upon reasonable request.