Trends in fatal opioid-related overdose in American Indian/Alaska Native Communities 1999–2021

Abstract

Introduction:

Opioid-related overdose (OOD) mortality rates have increased sharply in the U.S. over the past two decades, and inequities across racial and ethnic groups have been documented. OOD trends among American Indian/Alaska Native (AI/AN) require further quantification and assessment.

Methods:

Observational, U.S. population-based registry data on OOD mortality between 1999–2021 were extracted in 2023 using ICD-10 codes from the CDC WONDER multiple cause of death file by race, Hispanic ethnicity, sex, and age. Segmented time series analyses were conducted to estimate OOD mortality growth rates among AI/AN population between 1999–2021. Analyses were performed in 2023.

Results:

Two distinct time segments revealed significantly different OOD mortality growth rates within the overall AI/AN population, from 0.36 per 100,000 (95% CI: 0.32, 0.41) between 1999 and 2019, to 6.5 (5.7, 7.31) between 2019–2021, with the most pronounced increase among those of 24 to 44 years old. Similar patterns were observed within the AI/AN population with Hispanic ethnicity, but the estimated growth rates were generally steeper across most age groups compared to the overall AI/AN population. Patterns of OOD mortality growth rates were similar between AI/AN females and males between 2019–2021.

Conclusions:

Sharp increases in OOD mortality rates among AI/AN communities are evident by age and Hispanic ethnicity, highlighting the need for culturally-sensitive fatal OOD prevention, opioid use disorder treatment, and harm reduction efforts. Future research should aim to understand the underlying factors contributing to these high mortality rates and employ interventions that leverage the strengths of AI/AN culture, including the strong sense of community.

Introduction

Opioid-related overdose (OOD) mortality rates have increased sharply in the U.S. over the past two decades,¹ and inequities across racial and ethnic groups have been documented.² In recent years, OOD mortality rates have risen precipitously among American Indian and Alaska Native (AI/AN) populations in the U.S., from 4.3 per 100,000 in 1999 to 24.3 per 100,000 in 2021.^3,4 The AI/AN non-Hispanic population had the highest OOD mortality rate among all racial and ethnic groups in 2020–2021,^5,6 surpassing that of White non-Hispanic individuals in 2017 and reaching 41.4 per 100,000 in 2021, a rate 30.8% higher than that of White non-Hispanic individuals.⁶

The opioid overdose crisis in the U.S. is characterized by four overlapping waves.^7,8 The first wave, tied to prescription opioids, began in 1999. The second wave, comprising a rise of fatal heroin-related overdoses, began in 2010.^7,9 The third wave, related to use of synthetic opioids, and especially fentanyl, began in 2013, leading to precipitous increases in OOD mortality.⁷ A more recent fourth wave, characterized by the increasing presence of opioids in stimulant-related fatal overdoses, has contributed to growing rates in many communities.^8,10,11 These unique waves of the opioid overdose crisis have impacted demographic subpopulations in distinct ways. The first wave largely impacted the non-Hispanic White population in the early 2000s,¹² subsequently impacting the AI/AN population in later years.^3,13 In 2015, the AI/AN population aged 12 and older had a higher annual growth rate of initiation for nonmedical use of prescription opioids (6.9%) compared to the national average (4.2%),¹⁴ which had already transitioned through the second wave and into the third. Further, by 2017, AI/AN adolescents in the U.S. were found to have twice the odds of nonmedical use of prescription opioids compared to White adolescents.¹⁵ While these examples provide an initial understanding of distinct OOD mortality growth rates within the AI/AN population, more current temporal patterns in OOD mortality rates, and distinct patterns within AI/AN subpopulations, are understudied.¹⁶

In spite of historical and present day colonization, it is critical to recognize that AI/AN individuals and communities have formidable strengths upon which to build health solutions as demonstrated by Wall, O’Keefe, and others.^17–19 Culturally-specific interventions leverage the unique strengths of the AI/AN community, including resilience, as defined by Kirmayer: “regulating emotion and supporting adaptation through relational, ecocentric, and cosmocentric concepts of self and personhood; revisioning collective history in ways that valorize collective identity; revitalizing language and culture as resources for narrative self-fashioning, social positioning, and healing; and renewing individual and collective agency through political activism, empowerment, and reconciliation.”¹⁸

The overarching goal of this study was to quantify the unique trends in OOD mortality rates within the AI/AN population. The choice to employ segmented time series analysis stems from the observation that while opioid overdose mortality rates have been increasing over the years, as previously reported, this increase is dynamic and does not follow a linear pattern. Employing segmented time series analyses facilitates extensions of existing research to pinpoint specific time periods exhibiting significant inflection points in OOD mortality growth rates, enhancing understanding of epidemiologically significant events, and providing information to inform targeted public health interventions for unique subpopulations. Findings can also facilitate hypothesis generation regarding potential underlying risk factors to better inform development and implementation of culturally appropriate prevention strategies to mitigate impacts of the opioid overdose epidemic within AI/AN communities.

Methods

Study Population

OOD mortality data from 1999 through 2021 were obtained from the U.S. Centers for Disease Control and Prevention’s (CDC) Wide-Ranging Online Data for Epidemiologic Research (WONDER) database.²⁰ While the primary focus was on the AI/AN population, data for all racial groups were also compiled based on CDC definitions - AI/AN, Asian or Pacific Islander, Black or African American, and White - for analytical context and comparison. Within the AI/AN population, stratified analyses were conducted to assess OOD mortality data by ethnicity (i.e., Hispanic vs. non-Hispanic) and age groups (15–24, 25–34, 35–44, 45–54, and 55–64). It is noteworthy that CDC WONDER implemented a change in its racial categorization: in the earlier data release (1999–2020), available race categories included White, Black or African American, AI/AN, and Asian or Pacific Islanders. More recent data releases (2018–2021) offered a more comprehensive racial breakdown, including White, Black or African American, AI/AN, Asian, Native Hawaiian or Pacific Islander, as well as a category for individuals identifying as multiracial. Due to this change, Asian, Native Hawaiian or Pacific Islanders were combined into one group (i.e., Asian or Pacific Islanders) for the year 2021 in this analysis. IRB approval wasn’t required as the study used publicly available deidentified data.

Measures

CDC WONDER data were compiled in March 2023, including death counts, population sizes (based on the U.S. Census), and mortality rates per 100,000 population. Deaths were reported as suppressed when counts in a subpopulation or given year were <10, and mortality rates were deemed unreliable when death counts were below 20. Due to significant data suppression, those under 15 and over 65 years of age were excluded. Detailed information regarding the underlying and multiple cause of death data, derived from ICD-10 codes used for data queries, is available in the Appendix. For summary data used in these analyses, see (Appendix Table 1 and Appendix Table 2).

Statistical Analysis

Segmented time series analyses were conducted to discern distinct time segments and corresponding time points demonstrating statistically significant changes (p<0.05) in OOD mortality growth rates, with technical details in Appendix Methods. Briefly, segmented regression analysis partitions the annual OOD mortality rates per 100,000 into linear segments, each with a uniquely estimated temporal slope. The changes in growth rates are assessed by comparing the estimated slopes between time segments.²¹ The number of break points (e.g., 2 or 3) and the subsequent time segments were determined by the data. The best-fitting models were selected using Akaike information criterion and the goodness of fit R².

Using the CDC WONDER data, segmented time series analyses were conducted on OOD mortality rates by racial/ethnicity groups (AI/AN overall, Asian or Pacific Islander, Black or African American, and White populations). The same analyses were performed on the AI/AN population stratified by age and by Hispanic ethnicity. All analyses were performed in R software version 4.2.2 (R Project for Statistical Computing, Vienna, Austria) using the segmented package.²²

Results

Persistent increase in OOD mortality rates was identified across all racial groups since 1999, with the most pronounced acceleration observed in most recent years leading up to 2021 (Figure 1A). During 1999–2009, the annual OOD mortality rate in the AI/AN overall population was lower than that in the White population, with growth rates comparable across the AI/AN, Black or African American, and White populations. In recent years, however, the annual OOD mortality rates within the AI/AN population increased from 9.3 in 2018 to 24.3 per 100,000 in 2021, representing a 161.3% increase. By comparison, the concurrent OOD mortality rate increased within the White population by 59.4%, from 16.0 to 25.5, and by 142.5% in the Black or African American population, from 13.9 to 33.7 per 100,000. With the AI/AN population stratified by Hispanic ethnicity, OOD morality rates within the non-Hispanic population increased by 178.9%, from 14.0 in 2018 to 38.9 in 2021, notably higher than that in the Hispanic population, which increased by 100%, from 2.6 in 2018 and 5.2 in 2021 per 100,000 (Figure 1B). The precise long-term temporal trend for OOD mortality rates in the AI/AN Hispanic population could not be determined due to substantial data suppression during 1999–2007 and 2010–2011.

Figure 1.

Opioid-related overdose mortality rates by race: American Indian or Alaska Native (AI/AN overall), Asian or Pacific Islander, Black or African American, and White (Panel A) and by AI/AN regarding Hispanic origin (AI/AN overall, AI/AN Hispanic and AI/AN non-Hispanic (Panel B). The OOD mortality rates among AI/AN with Hispanic origin exhibit significant suppression due to small counts in years 1999–2007 and 2010–2011, displayed as missing data in this figure. Data source: CDC WONDER, 1999–2021.

Through segmented time series analysis, two distinct segments with substantially different growth rates were identified in OOD mortality within the overall AI/AN overall (Table 1). Between 1999–2019, the annual growth rate was estimated as 0.36 per 100,000 (95% CI: 0.32, 0.41), and between 2019–2021, it increased sharply to 6.5 (5.7, 7.31). This increase was second only to that of the Black or African American population between 2019–2021, with an estimated annual growth rate of 8.35 (7.75, 8.95). Compared to the overall AI/AN population, the AI/AN non-Hispanic population had even higher growth rates between 1999–2019 (0.63 [0.57, 0.7]) and 2019–2021 (10.75 [9.62, 11.88]) (Appendix Figure 3). By comparison, the OOD mortality rate in the White population was characterized by three distinctive segments, with an estimated growth rate of 0.47 (0.39, 0.55) between 1999–2013, 1.35 (0.93, 1.77) between 2013–2019, and 3.92 (2.97, 4.86) between 2019–2021 (Table 1).

Table 1.

Estimated growth rates of opioid-related overdose mortality by race groups between 1999–2021.

Race	Change Points (years)	Time Segments	Growth Rate (95% CI)
AI/AN overall	2019	1999–2019	0.36 (0.32, 0.41)
AI/AN overall	2019	2019–2021	6.5 (5.7, 7.31)
Asian or Pacific Islander	2015	1999–2015	0.06 (0.04, 0.07)
Asian or Pacific Islander	2015	2015–2021	0.36 (0.26, 0.45)
Black or African American	2012, 2015, 2019	1999–2012	0.01 (−0.05, 0.08)
Black or African American	2012, 2015, 2019	2012–2015	0.75 (0.15, 1.35)
Black or African American	2012, 2015, 2019	2015–2019	2.45 (2.07, 2.83)
Black or African American	2012, 2015, 2019	2019–2021	8.35 (7.75, 8.95)
White	2013, 2019	1999–2013	0.47 (0.39, 0.55)
White	2013, 2019	2013–2019	1.35 (0.93, 1.77)
White	2013, 2019	2019–2021	3.92 (2.97, 4.86)

Results in this table were obtained from segmented time series analyses using CDC WONDER data. The table presents identified years with statistically significant changes in the estimated growth rate of OOD mortality for American Indian or Alaska Native (AI/AN) irrespective of Hispanic origin (AI/AN overall), Asian or Pacific Islander, Asian or Pacific Islander and White.

In the overall AI/AN population, pronounced growth rates were identified in the 25–34 and 35–44 age groups between 2019–2021, with estimated annual increases of 12.8 (10.88, 14.72) and 11.76 (8.7, 14.8), respectively. The older age groups of 45–54 and 55–64 exhibited a significant shift in OOD mortality growth rates in 2020. A similar pattern was observed in the AI/AN non-Hispanic population with all age groups (except 15–24) experiencing sharp increase in OOD mortality around 2019, and the increases generally being steeper compared to the overall AI/AN population. Unfortunately, data suppression prevented similar analyses for the AI/AN Hispanic population (Table 2; Figure 2).

Table 2.

Estimated growth rates of opioid-related overdose mortality for AI/AN population by age groups between 1999–2021.

Hispanic Origin	Age Groups	Change Points (years)	Time Segments	Growth Rate
				(95% CI)
AI/AN Overall	15–24 years	2015, 2018	1999–2015	−0.07 (−0.26, 0.12)
AI/AN Overall	15–24 years	2015, 2018	2015–2018	0.76 (0.21, 1.30)
AI/AN Overall	15–24 years	2015, 2018	2018–2021	3.44 (2.57, 4.31)
AI/AN Overall	25–34 years	2013, 2019	1999–2013	0.51 (0.32, 0.71)
AI/AN Overall	25–34 years	2013, 2019	2013–2019	1.22 (0.57, 1.87)
AI/AN Overall	25–34 years	2013, 2019	2019–2021	12.8 (10.88, 14.72)
AI/AN Overall	35–44 years	2019	1999–2019	0.58 (0.42, 0.75)
AI/AN Overall	35–44 years	2019	2019–2021	11.76 (8.7, 14.8)
AI/AN Overall	45–54 years	2006, 2020	1999–2006	1.36 (0.38, 2.34)
AI/AN Overall	45–54 years	2006, 2020	2006–2020	0.28 (−0.13, 0.42)
AI/AN Overall	45–54 years	2006, 2020	2020–2021	14.7 (11.6, 17.8)
AI/AN Overall	55–64 years	2009, 2016, 2020	1999–2009	−0.6 (−1.73, 0.53)
AI/AN Overall	55–64 years	2009, 2016, 2020	2009–2016	0.75 (0.45, 1.05)
AI/AN Overall	55–64 years	2009, 2016, 2020	2016–2020	0.0 (−1.13, 1.13)
AI/AN Overall	55–64 years	2009, 2016, 2020	2020–2021	13.7 (11.44, 15.96)
AI/AN non-Hispanic	15–24 years	2015, 2018	1999–2015	−0.05 (−0.33, 0.24)
AI/AN non-Hispanic	15–24 years	2015, 2018	2015–2018	1.04 (−0.53, 2.6)
AI/AN non-Hispanic	15–24 years	2015, 2018	2018–2021	5.25 (3.69, 6.81)
AI/AN non-Hispanic	25–34 years	2019	1999–2019	1.18 (0.98, 1.38)
AI/AN non-Hispanic	25–34 years	2019	2019–2021	19.25 (16.11, 22.39)
AI/AN non-Hispanic	35–44 years	2019	1999–2019	1.2 (0.91, 1.48)
AI/AN non-Hispanic	35–44 years	2019	2019–2021	20.55(15.3, 25.8)
AI/AN non-Hispanic	45–54 years	2017, 2019	1999–2017	1.08 (0.87, 1.29)
AI/AN non-Hispanic	45–54 years	2017, 2019	2017–2019	−1.31 (−3.8, 1.19)
AI/AN non-Hispanic	45–54 years	2017, 2019	2019–2021	24.02(19.04, 29.0)
AI/AN non-Hispanic	55–64 years	2009, 2013, 2019	1999–2009	−0.96 (−4.42, 2.5)
AI/AN non-Hispanic	55–64 years	2009, 2013, 2019	2009–2013	1.56 (0.46, 2.66)
AI/AN non-Hispanic	55–64 years	2009, 2013, 2019	2013–2019	0.31 (−0.15, 0.76)
AI/AN non-Hispanic	55–64 years	2009, 2013, 2019	2019–2021	18.62 (15.15, 22.09)

Results in this table were obtained from segmented time series analyses using CDC WONDER data. The table presents identified years with statistically significant changes in the estimated growth rate of OOD mortality for American Indian or Alaska Native (AI/AN) irrespective of Hispanic origin (AI/AN overall), and AI/AN with non-Hispanic origin. Similar analyses could not be conducted for the AI/AN Hispanic population due to data suppression.

Figure 2:

Age-stratified opioid-related mortality (OOD) trends based on segmented time series analysis among: (A) American Indian or Alaska Native irrespective of Hispanic origin (AI/AN overall) and (B) AI/AN with non-Hispanic origin. Reported OOD data from CDC WONDER are presented as dots; estimated temporal trends are presented as the fitted line. Data source: CDC WONDER, 1999–2021.

OOD mortality growth rates within the AI/AN population, stratified by sex are presented in (Appendix Table 4 and Appendix Figure 7). For both AI/AN females and males, a notable shift in OOD growth rates was identified in 2019. Within the AI/AN female population, the OOD mortality growth rate increased from 0.31 (0.27, 0.35) between 1999–2019, to 6.5 per 100,000 (4.87 to 8.13) after 2019. A similar increase was observed for the AI/AN male population, with the growth rate increasing from 0.42 (0.34, 0.5) between 1999–2019, to 7.55 per 100,000 (6.1 to 9) between 2019–2021.

Changes in population sizes were also identified temporally across different racial groups, and among the overall AI/AN population compared to the AI/AN Hispanic and AI/AN non-Hispanic population. While the population of all racial and ethnic subpopulations increased between 1999–2021, increases in the population size among the Hispanic population was the steepest, contributing to overall increases in AI/AN population sizes and denominators in rate calculations (Appendix Figure 5).

Discussion

This study advances prior research by identifying significant shifts in OOD mortality rates within the AI/AN population between 1999 and 2021, comparing these rates to other racial populations in the U.S., as well as AI/AN trends by Hispanic ethnicity. A considerable escalation was identified in OOD mortality growth rates within the AI/AN population, particularly between 2019 and 2021, with an annual growth rate that approached and was exceeded only by that in the Black or African American population. OOD mortality rates by age strata were higher in the AI/AN non-Hispanic population versus the overall AI/AN population (Appendix Figure 1). OOD mortality rates by age strata for the Hispanic AI/AN population were not evaluated due to data suppression (Appendix Figure 2).

While this work draws attention to population outcomes that are troubling and deserve urgent attention, these results should be viewed within the historical context of centuries of colonization, violence, dispossession, oppression, and neglect tied to structural racism and Eurocentric economic power.^23,24 This research, along with that of many others, identifies inequities that are connected to the fatal opioid overdose crisis including disparate delivery of OUD treatment and harm reduction.²⁵

Study findings highlight the need for OOD prevention interventions that take into account culturally-specific practices tied to holistic, community-engaged physical, mental, and spiritual health.²⁶ Interventions that are sensitive to tribal beliefs regarding the body, mind, and spirit, incorporating cultural adaptations in the provision of education, MOUD, and recovery care may be more likely to succeed. These interventions may be implemented through Tribal and Indigenous People Serving Organizations (TIPSOs), developed in partnership with tribal elders and public health leadership, as recently achieved in Massachusetts during the COVID-19 response.²⁷ Study findings can also inform sex and age specific interventions for AI/AN people.²⁸

This study identified a precipitous increase in OOD mortality rates within the AI/AN population, the highest among all racial groups in the U.S., which were comparable to those presented by Kleinman et al.,³ particularly within the non-Hispanic AI/AN population.⁵ Prior research found that overdose mortality rates for all substances, including opioids and stimulants, were highest within AI/AN population, compared to all other racial and ethnic populations, between 2020–2021,⁵ pointing to evidence of the impacts of the fourth wave of the overdose crisis on the AI/AN population. Current study results advance those found in prior research, which focused on observed fatal OOD rates²⁹ or estimated monthly percent changes in overdose mortality rates,³⁰ as significant changes were identified in OOD growth rates across the past two decades and within distinct AI/AN subpopulations.

Segmented time series analysis identified distinct change points across different racial and ethnic groups, as well as specific age strata within the overall AI/AN population, and the AI/AN non-Hispanic population. While prior studies focused on overall AI/AN OOD mortality trends, by sex, opioid-only, and polysubstance use that included opioids,²⁹ and race/ethnicity by age strata,³⁰ the strength of this analysis is the calculation of growth rate parameters (with 95% CIs), providing measures that were easy to interpret and compare across different subpopulations. Notably, annual fatal OOD growth rates increased 18-fold over the initial years of the COVID-19 pandemic and the fourth wave of the opioid overdose crisis.⁸ During the early months of the pandemic, the overdose mortality rate for the AI/AN population increased by 55% between 2019–2020, reaching 25.7 per 100,000 population.⁵ During more recent months of the pandemic, overdose death rates in the AI/AN non-Hispanic population increased further,^5,6 and findings from the current study identified featured segmented break point regression analyses to estimate precise OOD mortality growth rates.

Further, fatal OOD growth rates were calculated for age-specific strata of the AI/AN population. AI/AN non-Hispanic decedents who were 25–34 and 35–44 of age experienced the most significant increases in OOD mortality rates. Elevated risk within this 25–44 year-old age group was comparable to those identified by Lee for the overall population during the advent of the COVID-19 pandemic.³⁰ Additionally, AI/AN decedents between 55–64 years of age appeared to have fatal OOD break points that were most consistent with the time periods associated with the four-waves of the opioid overdose crisis, albeit with a lower or delayed burden tied to the first wave. Increases in AI/AN fatal OOD rates in recent years may be attributable to the combined effects of the fourth wave of the opioid overdose crisis and the COVID-19 pandemic. Indeed, Lee found that mortality rates within the AI/AN population surpassed those of the White population during March of 2021, and Qeadan³¹ reported associations between COVID-19 infection rates and opioid-related deaths. Findings in this study, taken together with those from prior studies, help to explain significant increases in opioid-related mortality among AI/AN populations who use opioids alone or in combination with other substances, most notably methamphetamine.²⁹

Limitations

Study results should be considered within the context of several limitations. There is large, historic misclassification (34% in the most recent analysis) of AI/AN race on death certificates leading to undercounting of OOD deaths in the AI/AN population.^32,33 This underreporting has always been substantial but has varied over time, and can affect estimations of the temporal slope of recent OOD mortality.^34,35 Additionally, decedent data may rely on the reporting of a single race/ethnicity noted in death certificate data, excluding from the count a portion of decedents who identify as AI/AN and other races and ethnicities. An additional factor, which could impact OOD mortality trends and their interpretation is the rapid, 255% increase in AI/AN population counts since 1960 as self-identification of race and multiple races became possible in the U.S. Census.^36,37 Such increases in AI/AN population counts (Appendix Figure 5) contribute to larger denominators for AI/AN mortality rate calculations, especially when considering the Hispanic population, thus tempering increases in OOD mortality rates over time. This is exacerbated when the numerator, compiled from AI/AN decedent data on death certificates do not account for AI/AN race and Hispanic ethnicity, contributing to smaller counts (Appendix Figure 4). Finally, prior research has shown that individuals identifying as AI/AN are much more likely to be identified on death certificates as AI/AN decedents when they are in an area where tribal membership is common, such as tribal lands.³⁴ Consequently, there may also be geographic misclassification of AI/AN populations in decedent data. Due to data suppression, assessment of such geographic variations is not available. These limitations are not unique to CDC WONDER data; other databases and reporting systems also likely encounter similar issues.

Despite these limitations, this study has several strengths. First, a comprehensive analysis was conducted using segmented time series to quantify temporal OOD mortality growth rates in the AI/AN population. The estimated annual rate increases provide meaningful context for the precipitous and significant increases in recent years. Second, while focusing on the AI/AN population, the analysis was conducted in comparison with other racial populations to contextualize estimated annual rate increases and identify significant temporal inflection points. Finally, trends in OOD mortality rates within the AI/AN population were examined by Hispanic ethnicity and age strata. This is important, as recent reports highlighting elevated OOD mortality rates have not always considered the impact on OOD rates of drastically different denominators for non-Hispanic and Hispanic populations.

Conclusions

Sharp increase in OOD mortality growth rates within the AI/AN population were quantified, providing a nuanced understanding of significant changes in mortality trends. This analysis revealed distinct subgroups of AI/AN individuals facing increased risks associated with age and Hispanic ethnicity, highlighting the need for culturally-specific OOD prevention, OUD treatment, and harm reduction efforts. While focusing on risk in this study, vulnerabilities in AI/AN communities are understood as consequences of colonization and systemic racism. Future research should prioritize understanding the important strengths of AI/AN individuals and communities and how these strengths can be leveraged to improve health outcomes. Additionally, efforts to enhance data quality and consistency in the classification of AI/AN race and ethnicity across decedent, U.S. Census data, and public health surveillance systems are crucial for accurately monitoring and addressing health disparities in this population.