ABSTRACT | Rapidly rising drug overdose rates in the United States during the past three decades underscore the critical need to prevent overdose deaths and reduce the development of opioid and related substance use disorders (SUDs). Traditional public health models of prevention emphasize the biological and physical risks of SUDs, often neglecting to consider the broader environmental and social factors that influence health and well-being. Taking a socioecological approach, the authors aim to illustrate the complex interplay among individual, interpersonal, societal, and structural factors that contribute to the development of SUD and overdose risk. The authors propose evidence-informed strategies and interventions across primary, secondary, and tertiary levels of prevention. By doing so, the authors hope to encourage policymakers, funders, service providers, and community leaders to broaden their approaches to SUD prevention and consider how they can create and advocate for a health-promoting environment by addressing the social and structural factors that drive rising SUD and overdose trends.

Introduction

Clinical medicine and public health have long held dueling perspectives of illness. Leading public health thinkers have consistently connected socioeconomic factors to illness, while some traditional clinical medicine professionals have held views restricted to the somatic parameters and “the organic elements . . . of human malfunction” (Jones-Eversley and Dean, 2018; Engel, 1977). The biomedical model described in the latter half of the previous sentence forms the basis of classical Western medical training, in which illness can be reduced to a biological or physiological physical element. Rudolf Virchow (1848), considered the father of modern pathology, stated that “medicine is a social science” and understood that disease operates at the cellular level. He also recognized the social conditions that facilitated the spread of disease, yet this acknowledgment had minimal influence in the evolution of the biomedical model.

In many ways, the American health care system still struggles with the same dilemma today: reimbursement structures incentivize delivery of high acuity care and surgical procedures and rarely pay for care coordination, case management, or other services known to impact long-term health outcomes. But there is an increasingly urgent need, made more salient during the co-occurring COVID-19 and overdose epidemics, to resolve the philosophical debate over clinical medicine’s scope of responsibility for identifying, treating, and preventing substance use disorder (SUD). While the importance of understanding the social and economic conditions of patients is a common component of medical training, the application of this notion to people who use drugs (PWUD) is less common (Yoast et al., 2008). Furthermore, training on the importance of patient socioeconomic conditions may not translate to an understanding of how medical professionals can play an active role in addressing them, through prevention, treatment, or policy advocacy.

Effectively addressing SUDs and their associated social determinants of health requires a collaborative, cross-sector approach involving not only health care systems and professionals, but also schools, social service organizations, and local communities. By working together, partners can have a greater impact and yield more significant outcomes. They can realize collective impact by fostering strategic partnerships to invest in and implement prevention programs and by improving both the capacity to treat SUDs and the awareness of available supportive service (Health and Human Services Office of the Surgeon General, 2016).

The urgency of such collaborative strategies has been underscored in an era marked by the COVID-19 pandemic, which has heightened society’s awareness of nonbiomedical influences on health. The pandemic has exacerbated risk factors for increased substance use and SUD, disrupting employment, housing, health care access, and social connection, and heightening fear, anxiety, financial stress, and grief—particularly among those with preexisting structural vulnerabilities (Collins et al., 2022). Pandemic-related stressors have been tied to escalation of the ongoing overdose epidemic and increases in substance use (Ghose, Forati, and Mantsch, 2022). For example, caregiving responsibilities, stress, depression, and anxiety were associated with increased substance use during the pandemic (Schmidt et al., 2021). After a historic 30 percent year-to-year increase in overdose fatalities from 2019 to 2020, estimates suggest that the United States again experienced a 15 percent increase in overdose fatalities in 2021, with a record-breaking 109,179 deaths—75 percent of which were related to opioids (Centers for Disease Control and Prevention, 2021). Overdose fatalities remained steady in 2022, with provisional data indicating 109,680 deaths (Ahmad et al., 2023).

Among those in the United States who died of overdose, the racial inequity that existed before the pandemic was amplified by the heavier economic, social, and health burdens carried by non-Hispanic Black individuals during the pandemic. This group had the greatest annual increase in drug-related overdose deaths in 2020 (Mistler et al., 2021; SAMHSA, 2020a). While rates of drug overdose death have consistently been higher among the White versus Black population, Black people have seen a 3.6-fold increase in overdose deaths since 2015, compared to the 1.7-fold increase among White individuals. In 2021, the age-adjusted drug death rates of Black (44 per 100,000) and American Indian/Alaskan Native (56 per 100,000) people were significantly higher than the rate for White people (36.8 per 100,000; National Center for Health Statistics, n.d.). To mitigate the worsening overdose crisis, the broader health and human services system must consider the structural and social determinants behind these growing disparities.

To make this case, this paper first explores the historical events that have informed the current US biomedical paradigm for SUD prevention, using the example of opioid use disorder (OUD), and the problems that have, in part, resulted from this approach. The authors then discuss how a socioecological framework—which considers the complex interplay among individual, interpersonal, societal, and structural factors—can offer a more comprehensive and effective means of understanding SUD prevention. The paper concludes with an exercise in which the authors apply a socioecological lens to the traditional public health model of OUD prevention, elucidating evidence-informed strategies and interventions across primary, secondary, and tertiary levels of prevention that aim not only to prevent disease but also to promote overall health and well-being.

The authors recognize the pivotal role the socioecological approach has played in shaping responses to various health conditions, including mental health conditions (Akers et al., 2023; National Institute on Minority Health and Health Disparities, 2017). However, despite its proven merits, the socioecological approach remains underused and its integration into the field of SUD prevention has been limited. Therefore, the primary purpose of this paper is to articulate the application of this approach and underscore its significance within the overarching context of SUD prevention. Further, this paper seeks to catalyze the expansion and uptake of this approach, empowering stakeholders to identify strategies that align with their circumstances and available resources.

From Moralization to Medicalization

The United States has a long history of politicizing, moralizing, and racializing drug use, a history that existed for nearly a century before President Richard Nixon formally declared the “war on drugs” in the 1970s (Rosino and Hughey, 2018). Political rhetoric preceding legislation that restricted or criminalized the possession of opium, cocaine, and cannabis featured statements that stoked fears of lost virtues and moral hygiene, and often cited unsubstantiated claims of the victimization of White women at the hands of people of certain races and ethnicities. For example, prior to the enactment of the 1914 Harrison Narcotics Act, proponents of racial prejudice warned Congress, claiming that “[m]ost of the attacks upon [W]hite women of the South are the direct result of a cocaine-crazed Negro brain” (Nunn, 2002). Congress passed the act, which regulated and taxed the production, importation, and distribution of opiates, and spurred federal agencies to prohibit physicians from prescribing opioids to persons with addiction, effectively initiating the criminalization of SUD in the United States at the federal level (Courtwright, 2015; Kleber, 2008).

Contrary to popular belief, the process of “scheduling”—which categorizes drugs based on their potential for abuse— as controlled substances was not informed by a systematic examination of relative drug risk, but rather by geopolitical and commercial interests and xenophobic ideologies that marginalized certain racial and ethnic populations (Daniels et al., 2021). For instance, the Controlled Substance Act of 1970, which laid the foundation for the current US drug scheduling system, emerged amid a broader cultural and political shift during the Nixon administration. Strategically aiming to neutralize the 1960s counterculture, the Nixon administration “knew [they] couldn’t make it illegal to be either against the war or [B]lack, but by getting the public to associate hippies with marijuana and [B]lacks with heroin, and then with criminalizing both heavily, [they] could disrupt those communities” (Baum, 2016).

In the ensuing years, US drug policy has consistently prioritized addressing the perceived moral outrage against drug use through tough-on-crime policies and a seemingly unrestricted cascade of federal dollars invested in drug interdiction (Shepard and Blackley, 2004). However, rather than serving as an effective public health strategy, this punitive approach has only served to perpetuate stigmatizing attitudes by erroneously associating drug use with social deviance and criminality (Dineen and Pendo, 2021). Prevention strategies have often relied on harsh criminal legal actions and fear-based educational campaigns, ostensibly to send a warning to individuals who might sell or use drugs. Nevertheless, research suggests that compulsory detention, other harsh criminal penalties, and youth-focused scare tactics have had little impact on reducing drug supply or curbing demand (Substance Abuse and Mental Health Services Administration, 2015; Global Commission on Drug Policy, 2011; Degenhardt et al., 2010).

To counter the prevailing erroneous theories of addiction as a moral failing, the medical community put forth the brain disease model, which expressed addiction in scientific terms, namely explaining that SUD resulted from a brain system that had been dysregulated by drug use (Heilig et al., 2021; Leshner, 1997). However, the mechanistic view of drugs “hijacking” the brain was not in conflict with the interdiction paradigm that similarly targeted drugs as the source of growing social ills. The mechanistic causal narrative continued to focus on regulating drugs and the drug supply instead of interrogating the social factors that drove the demand for drugs (El-Sabawi, 2019; Office of the Surgeon General, 2016; Institute of Medicine et al., 1994; Hawkins, Catalano, and Miller, 1992). In more recent years, and in response to greater attention to racial disparities in the criminal legal system, advocates within the medical community have called for reform of the criminal legal response to SUD and targeted broader social change, including increased access to housing, education, and health care (AMA, 2022; AMA, 2021; ASAM, 2021a; ASAM, 2021b; AMA, 2020).

From Medicalization to a Socioecological Approach

Prescriptive biomedical views of SUD prevention have led to simplistic problem statements and unidimensional solutions. For example, the United States experienced an excessive focus on increased opioid prescribing as a response to the opioid overdose crisis, often at the expense of supportive strategies (Dasgupta, Beletsky, and Ciccarone, 2018). The increase in prescribing stemmed from a complex interplay between predatory marketing of opioids and the need to address the undertreatment of chronic pain in the 1990s and early 2000s (DeWeerdt, 2019). However, the disproportionate emphasis on pharmaceuticals in the public narrative obscured other important drivers of the crisis, while fostering a defensive dynamic between patients and prescribers.

Key factors—such as the high prevalence of illicitly manufactured opioids, the counterproductive role of prohibition policies in creating an increasingly toxic drug supply, and evolving trends in substance use—have been largely overlooked. This reductionist view diverted attention from the myriad of contextual factors related to the onset and progression of SUD (Herzberg et al., 2016; Wailoo, 2014). A case in point is the rigid misapplication of prescribing limits outlined in the 2016 “CDC [Centers for Disease Control and Prevention] Guideline for Prescribing Opioids for Chronic Pain,” which contributed to many patients with pain who benefited from opioid therapy being nonconsensually tapered or denied further treatment (Kroenke et al., 2019; Dowell, Haegerich, and Chou, 2016). Consequently, some individuals resorted to seeking illicit alternatives for pain relief, paradoxically exacerbating the very issue that the guideline sought to address (Coffin et al., 2020).

The focus on reducing opioid prescriptions may have the veneer of a less punitive and more medical approach to preventing SUD but is still a supply-side narrative (El-Sabawi, 2019). Moreover, a purely biomedical focus for preventing SUD offers limited insight into the structural and systemic factors driving racial and ethnic disparities in overdose deaths.

Service providers and policymakers should consider how they can create a health-promoting environment regardless of whether an individual has ever used drugs, is diagnosed with SUD, or engages in high-risk substance use. Indeed, the health care industry depends on the biomedical model, with a focus on diagnosis, precise and prescriptive treatment, and decision-chart resolutions (Fricton et al., 2015). However, expanding the broader health care system’s understanding of prevention beyond the body’s mechanistic functions is critical to stemming the nation’s ongoing rise in overdoses and future substance use epidemics.

While it is now socially acceptable in many circles to state that addiction is not a moral failing—an advancement that goes against a long history of socially accepted condemnation of PWUD—the debate has now shifted to whether addiction is a brain disease, a chronic disease, or not a disease at all (Volkow and Boyle, 2018; Racine, Sattler, and Escande, 2017; Szalavitz, 2016; ASAM, n.d.). The conversation needs to be elevated beyond individual positions on the matter to include structural and societal factors. Here, the authors seek not to discredit the biomedical view but merely to provide support for more inclusive problem statements and solutions.

A Socioecological Theoretical Framework for SUD Prevention

A socioecological framework for SUD prevention recognizes the complex interactions between people and their environments at the individual, interpersonal, and macro levels (Agency for Toxic Substances and Disease Registry, 2015; Bronfenbrenner, 1979). Social epidemiologists have established causal mechanisms to support the application of a socioecological framework to health broadly and to clarify how structural and social determinants of health create socially patterned distributions of disease (Berkman, Kawachi, and Glymour, 2015; Krieger, Dorling, and McCartney, 2012; Glass and McAtee, 2006; Link and Phelan, 1995). Social epidemiologic research supports the assertion that the context in which individuals make health-related choices serves as a barrier to or facilitates health (Galea, Nandi, and Vlahov, 2004; DuBois, 2003). Race, often treated in biomedical perspectives as biologically defined (Ioannidis, Powe, and Yancy, 2021), is recognized as a socially constructed factor that is not biologically determined but does create differences in biological outcomes (Krieger, Dorling, and McCartney, 2012; Roberts, 2012).

Figure 1 illustrates the nested levels of factors considered in a socioecological framework, which have been highly simplified for the purpose of organizing the current argument. Macro-level factors, such as policies and practices, can have direct impacts on individuals’ health by subjecting them to stigma, trauma, and discrimination stemming from these broader influences. These experiences then physically manifest via stress response mechanisms (Hatzenbuehler et al., 2015; Geller et al., 2014). Additionally, macro-level factors shape the interpersonal structures in communities, influencing individuals’ access to resources and opportunities, and their health-related behaviors and beliefs. Importantly, the interplay among levels is interdependent and multidirectional, with influences at one level often facilitated or inhibited by elements at another level.

Understanding this interplay, social epidemiology recognizes that people make places and places make people (Macintyre and Ellaway, 2003). Due to the complex feedback loops and interactions between people and their environments (e.g., people may not buy healthy foods because stores do not carry healthy foods, and stores may not carry healthy foods because of a perception that people will not buy them), reductionist views of health can be antithetical to the socioecological perspective. While not the focus of this current work, the authors recognize that this complex person-environment interaction can occur across the life course and is intergenerational (Latimore et al., in press).

The application of a socioecological framework to SUD is not new (American Institutes for Research, 2022; Park et al., 2020; Jalali et al., 2020; Galea, Nandi, and Vlahov, 2004), but the addiction field has been slow to adopt the framework in practice. Macro-level risk factors such as restrictive drug policies and stigma isolate people with SUD from social and economic resources, such as services associated with SUD prevention, treatment, recovery, and harm reduction. These resources influence health at the individual level through physiological, psychosocial, and health behavior pathways. Similarly, racial disparities in SUD result from the experience of race in society and the distribution of economic and social resources that affect health. For the remainder of the paper, the authors focus on OUD, because of its relative contribution to the current overdose epidemic and the availability of resources targeted to OUD. However, the authors recognize the evolving nature of drug trends, the need for attention to other SUDs, and the applicability of this theoretical approach and related strategies to related SUDs.

Applying a Socioecological Framework for a More Nuanced View of OUD and Public Health Prevention

In the biomedical model of health and health care, prevention interventions have traditionally been classified according to three distinct levels: primary, secondary, and tertiary (Leavell and Clark, 1965). Primary prevention strategies aim to mitigate risk factors and prevent health conditions from ever developing. Secondary prevention interventions seek to identify a health condition as early as possible to halt or slow its progression. Tertiary prevention approaches strive to minimize acute negative consequences, like death, among those who have the disease.

In the context of OUD, a primary prevention approach under the traditional biomedical model aims to avoid the onset of OUD by, for example, educating clinicians and patients on alternative modalities and non-opioid medications for effective pain management to reduce exposure to prescribed opioids. Similarly, screening and referring patients to be prescribed medications for OUD constitute one approach to achieving the secondary prevention goal of identifying, diagnosing, and treating OUD as early as possible. Lastly, providing naloxone to those using opioids is an example of tertiary prevention, as naloxone can reduce the risk of opioid overdose and death among individuals with OUD.

While the primary, secondary, and tertiary classification can be useful for partitioning types of responses, its typical application to a biomedical model focuses on a clinical response and does not include efforts to address structural determinants of health and the complex interactions among the human body, the environment, and an individual’s life circumstances included in the socioecological perspective.

For example, negative stereotypes persist about people with OUD that do not exist for people with other chronic conditions; the latter are met with relatively clear pathways to additional testing, treatment, and support. Comparatively, upon discovery of their nonprescribed opioid use, too often individuals face judgement or blame and are left without connections to appropriate, evidence-based care (Tsai et al., 2019). Such counterproductive interactions with health care professionals and the health care system deter individuals from seeking help at critical moments before and after the development of OUD and associated negative health and social consequences. Widespread recognition that OUD is a treatable condition, and that stigmatizing language has negative impacts on people with OUD, is critical for reducing the continuous rise in overdoses.

The primary, secondary, and tertiary prevention classification is somewhat ill-fitting for the nonlinear nature of addiction and other chronic health conditions, particularly if the treatment approach does not consider the social and environment factors impacting disease and health. OUD is a medical diagnosis defined by a pattern of opioid use that leads to problems or distress (e.g., physical, mental, interpersonal, and financial; American Psychiatric Association, 2013). Most people who are exposed to opioids do not develop OUD. Of the estimated 10.1 million individuals 12 years or older who reported problematic use of opioids in 2019, 1.6 million met The Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition, Text Revision, criteria for OUD (SAMHSA, 2020b). Among individuals prescribed opioids long term for chronic pain, between 8 percent and 12 percent will develop an addiction to opioids, although nuance exists in the reported estimates (Dowell, Haegerich, and Chou, 2016; Volkow and McLellan, 2016; Vowles et al., 2015). Individuals can move in and out of the “diagnosed” and “high-risk” categories as they reduce their drug use and no longer meet the criteria for OUD. Among those with an OUD diagnosis, the extent to which they participate in drug use behaviors that place them at high risk for overdose can fluctuate.

The definitions of recovery and remission are hotly debated topics that involve differing schools of thought (Office of the Surgeon General, 2016). While there is general agreement that recovery involves achieving a state of improved well-being, varying perspectives exist on the nature of addiction, the goals of treatment, the necessity of treatment, and the possibility of complete remission. At one end of the spectrum, proponents argue that long-term abstinence is the primary criterion for recovery. Conversely, alternative schools of thought adopt a more inclusive approach to recovery, recognizing that complete abstinence may not be immediately feasible or desirable for everyone. Instead, they emphasize harm reduction approaches and focus on positive behavior changes and improved well-being as indicators of recovery.

Socioecological Levels of Prevention for OUD

To address the limitations of the classical prevention categorizations, the authors have recast OUD prevention with a socioecological framework that recognizes the nonlinear interconnectivity between people and their environments. Hood et al. (2016) estimate that individual health behavior accounts for about one-third of health outcomes; the remaining two-thirds of health factors can be broadly defined as social determinants and include social and economic factors (47 percent), the physical environment (3 percent), and access to quality health care (16 percent). These social determinants can be broken into two categories: risk factors and protective factors. Protective factors—such as community safety, supportive relationships, financial stability, and access to care—are associated with positive health outcomes. Conversely, unsafe living conditions, food insecurity, poverty, and social isolation are associated with negative health outcomes.

Risk and protective factors exist within the contexts in which a person interacts and exists. Combining the socioecological framing of risk and protective factors with the classical framing of prevention (Figures 2, 3, and 4) is a start to identifying individual, interpersonal, and macro-level strategies that can promote or deter health for those at different stages of the prevention continuum.

Primary Prevention of OUD Using a Socioecological Model

Primary prevention using a socioecological framework seeks to prevent the onset of disease and acknowledges that an individual’s risk of developing OUD is shaped by a combination of intersecting biopsychosocial and environmental risk and protective factors, as outlined in Figure 2. Evidence-based primary prevention interventions address both biopsychosocial and environmental risk and protective factors at the individual, interpersonal, and macro levels to prevent the onset of OUD (Office of the Surgeon General, 2016).

An example could involve adverse childhood experiences (ACEs) and positive childhood experiences (PCEs), which both play crucial roles in shaping a person’s life trajectory. ACEs—which encompass negative, stressful, and traumatizing events that occur before the age of 18—are strongly associated with increased risk of developing OUD over the life span (Guarino et al., 2021). On the other hand, PCEs, such as supportive relationship and safe environments, can act as protective factors against the harmful effects of ACEs (Bethell et al., 2019). Factors that contribute to ACEs include the lack of a consistent caring adult during childhood and/or growing up with food insecurity, while factors that promote PCEs involve creating and sustaining safe, stable, and nurturing relationships and environments in which children and families can thrive (CDC, 2022; CDC, 2019). Recognizing the prevalence of ACEs and their strong association with opioid use and related behavioral health outcomes, it is crucial to prioritize prevention of ACEs. Further research is needed to describe the cultivation of PCEs and impact on incidence of OUD. (National Academies of Science, Engineering, and Medicine, 2019).

Applying the socioecological lens to primary prevention provides targets at the individual, interpersonal, and macro levels for preventing the onset of OUD (Figure 2). Examples of interventions at each of these levels include the following:

Individual: Mentoring and Out-of-School Programs

Research demonstrates that school completion, stable career employment, and quality relationships are associated with reduced high-risk substance use patterns, including opioid use, leading into young adulthood (Merrin et al., 2020). Mentoring and out-of-school programs—such as Big Brothers Big Sisters of America (n.d.), After School Matters (n.d.), and Powerful Voices (n.d.)—support the growth and development of youth and adolescents by addressing the need for positive adult contact and offering skills development opportunities, resources, and platforms. The enhanced support helps to increase confidence and foster professional values, such as leadership, teamwork, and respect, all of which have been shown to reduce problematic drug use among youth (Erdem and Kaufman, 2020; CDC, 2019).

Interpersonal: Family Support Programs

Data support the assertion that close family relationships can ameliorate the impact that trauma, stress, and adversity have on an individual’s physical health over their life span (Chen, Brody, and Miller, 2017; Brody et al., 2016). Culturally relevant and asset-based family support programs, such as the Strong African American Families Program (University of Georgia, Center for Family Research, n.d.), help to foster positive family environments and improve supportive parenting practices, including positive racial socialization, communication, and consistent discipline, thereby enhancing parents’ and caregivers’ efforts to help youth develop positive goals as well as skills to resist involvement in risk behaviors, like early initiation of opioid or other drug use (Brody et al. 2006).

Macro: Federal and State Policies and/or Investments That Support Resource-Limited Families

The harmful effects of economic hardship and financial instability on child health and development are well documented (Sandstrom and Huerta, 2013). Research shows that when families can meet their basic needs—such as food, housing, and health care—parents and caregivers can better provide the critical emotional and material support that children need to grow into healthy, productive adults (Masten, Lombardi, and Fisher, 2021). Policies and investments in social programs—including livable minimum wage requirements, child care subsidies, and federal tax credits—can be important levers to reduce the strain on low-income families to meet their basic needs, thereby reducing socioeconomic risks for parents and their children, which in turn decreases the risk of developing OUD (Cooper, Mokhiber, and Zipperer, 2021; Milligan and Stabile, n.d.).

For additional examples of socioecological primary prevention interventions for OUD, please refer to Table A-1.

Secondary Prevention of OUD Using a Socioecological Model

Secondary prevention interventions using a socioecological framework focus on biopsychosocial and environmental strategies that target early identification of OUD and support for those with OUD. As illustrated in Figure 3, several risk factors impede and/or challenge the success of screening and treatment referral, including stigma, discrimination, and insufficient provider competency and/or knowledge, all of which can influence an individual’s engagement in their health and human services.

Applying the socioecological lens to secondary prevention provides targets at the individual, interpersonal, and macro levels for supporting those in the early or mild stages of OUD. Examples of interventions at each of these levels include the following:

Individual: Access to Trauma-Informed Care

Based on a large population-based survey, an estimated 50 percent to 60 percent of adults in the United States have experienced some type of traumatic event at least once in their lives (Husarewycz et al., 2014). Given the strong link between exposure to trauma and OUD, receiving trauma-informed care—which includes considering a person’s traumatic experiences when providing care and adopting policies, procedures, and practices that avoid retraumatization and support healing and recovery—can help to improve patient engagement, OUD treatment adherence, and health outcomes (SAMHSA, 2014a).

Interpersonal: Training in Structural and Cultural Competency

Culturally and linguistically diverse populations face greater challenges to accessing OUD treatment (Gainsbury, 2016). Consequently, it is vital that health and treatment providers create a more inclusive care environment by developing a greater awareness and understanding of the cultural, structural, and linguistic factors that may help their patients feel more comfortable in accessing care. Training and education programs for health professionals that focus on developing cultural and structural competencies—such as the National Culturally and Linguistically Appropriate Services Standards (Office of Minority Health, n.d.) can help to improve patient engagement in services, therapeutic relationships between patients and providers, and treatment retention and outcomes to advance health equity (Jones and Branco, 2021; SAMHSA, 2014b).

Macro: Comprehensive, Interprofessional Addiction Curricula and Training Programs

OUD touches nearly every aspect of the health care system. Individuals who experience a nonfatal opioid overdose are likely to interact with at least one health professional in the six months preceding their overdose (Wagner et al., 2015). Given this context, it is critical that all health professionals have the requisite knowledge, skills, abilities, and attitudes to effectively identify and support those with problematic substance use. Adoption of interprofessional curricula and training programs, such as those outlined in the National Academy of Medicine’s 3Cs Framework for Pain and Unhealthy Substance Use (Holmboe et al., 2022), provide the opportunity to better prepare health professionals across the care continuum to identify and meet the complex and varied needs of patients with unhealthy substance use behaviors. (See Table A-2 for additional examples of secondary prevention interventions using the socioecological framework.)

Tertiary Prevention of OUD Using a Socioecological Model

Tertiary prevention strategies seek to mitigate the negative consequences and worsening of symptoms among those with OUD through a wide range of services and supports. These could include treatment and recovery services, self-help, and mutual aid groups, as well as harm reductions services to support individuals who are active in their substance use. Tertiary prevention strategies do not stop new cases of OUD from emerging, yet they do significantly reduce opioid-related morbidity and mortality and improve overall well-being. Many of the interventions at this stage are typically categorized as harm reduction; however, it is worth noting that harm reduction includes a spectrum of interventions, including strategies across the primary and secondary levels of prevention.

The socioecological model acknowledges that more can be done to address and prevent collateral consequences and comorbidities associated with OUD, including incarceration and spread of infectious diseases (see Figure 4).

Applying the socioecological lens to tertiary prevention provides targets at the individual, interpersonal, and macro levels for preventing severe consequences among those with OUD, such as overdose death and infectious diseases like HIV and hepatitis C (HCV) related to injection drug use. Examples of interventions at each of these levels include the following:

Individual: Low-Barrier Access to Harm Reduction Services and Supplies

Harm reduction services, which include interventions such as the distribution of sterile syringes and naloxone, have been proven to be effective at preventing morbidity and mortality associated with injection drug use. However, a significant number of PWUD do not have access to these services, a gap that frequently stems from geographical limitations (e.g., for those residing in rural areas) and the enduring stigma associated with the receipt of such services (Harm Reduction International, 2020). Innovative, remote harm-reduction platforms like NEXT Distro have emerged to address these obstacles, leveraging the reach and convenience of digital technologies (e.g., internet, text messaging, and e-mail) to mail essential harm reduction supplies directly to those in need (NEXT Distro, n.d.). These platforms not only dismantle geographical and stigma-related access barriers but also provide comprehensive harm reduction resources and support (Barnett et al., 2021; Yang, Favaro, and Meacham, 2021). With an emphasis on anonymity and privacy, these services expand accessibility, offering a practical, transformative solution for PWUD.

Interpersonal: Education on Safer Injection Practices

Higher risk of HIV and HCV infections, abscesses, cellulitis, and other skin infections is associated with certain drug injection practices (CDC, n.d.). Promoting safer injection practices among PWUD through education and training—like that of the National Harm Reduction Coalition’s Getting Off Right: A Safety Manual for Injection Drug Users (National Harm Reduction Coalition, 2020)—empowers individuals to minimize potential harms associated with injection drug use (Roux et al., 2021).

Macro: Syringe Service Programs

Nearly 30 years of research strongly support the conclusion that syringe service programs (SSPs) play an important role in promoting community safety and reducing the transmission of HIV, HCV, and other blood-borne infections commonly associated with injection drug use (Javed et al., 2020). Policies that remove barriers to the development of SSPs are critical to increasing access to this evidence-based prevention practice. (An example is Florida’s Infectious Disease Elimination Act [IDEA] of 2016, which permitted county commissions to authorize SSPs through grants and donations from private resources and funds, enabling the University of Miami to open the state’s first and only SSP: IDEA Exchange [IDEA Exchange, n.d.]). These programs are instrumental in ensuring that high-risk individuals have access to the full range of services made available by SSPs, including access to and disposal of sterile syringes and injection equipment, vaccination, testing, and links to infectious disease care and OUD treatment. (Table A-3 includes additional examples of

tertiary prevention interventions.)

Interconnected and Multidirectional Levels of Influences

The above examples highlight the complex interplay among the three levels of prevention and the socioecological levels of influence, wherein multidirectional interactions among levels means that factors at one level are often facilitated or restricted by factors at another. For example, individual-level factors—such as individual behaviors, psychological state, and physiological mechanisms—are both supported and limited by interpersonal factors like social support, sense of community cohesion, and access to person-centered care. However, these interpersonal factors do not exist in isolation; they are influenced and shaped by macro-level factors, such as drug control policies, fragmented and unaccountable treatment delivery systems, concentrated poverty, and stigmatizing cultural narratives about people with OUD. Thus, each level is not only dependent on but also instrumental in shaping the dynamics of the others, thereby creating a complex web of interconnected influences.

Additional examples of socioecological primary, secondary, and tertiary interventions that further illustrate this dynamic are provided in Tables A-1, A-2, and A-3. The interventions included in the tables have been limited to those with promising evidence to reduce the risks associated with precursors of OUD, OUD incidence, OUD morbidity, and OUD-related mortality; however, their inclusion does not suggest, and should not be taken as, an endorsement by the National Academy of Medicine or any of the authors’ organizations.

The goal of this exercise is neither to provide an exhaustive list of all possible interventions, nor to grade the available evidence for various interventions. Instead, the focus is specifically to provide a socioecological public health prevention framework to support a holistic vision for OUD policy, research, and service delivery solutions. Additionally, the socioecological foundation of this framework will foster adaptable and effective solutions that are responsive to the underlying needs of those who are most affected by OUD.

The outlined interventions and strategies can serve as a starting point and inspiration for stakeholders interested in addressing OUD and other related SUDs. By offering examples that make a socioecological approach to OUD prevention practical, the authors hope to provide tangible strategies that can be applied to other SUDs more broadly and that will encourage and empower practitioners, policymakers, funders, service providers, and community leaders to take action through relational dynamics, institutional practices, policy, and advocacy. The tables do not prioritize specific interventions, since each advocate operates within a unique context. Therefore, when determining which strategies and interventions to adopt, advocates should consider their target population and sphere of influence, and the resources they have at their disposal.

Conclusion

Given the severity of the impact of overdose deaths on the nation and the dramatically increasing rates of OUD and other related SUDs in the United States over the past 20 years, it is critical that a public health framework is applied when considering policy, research, and service delivery solutions. This approach is particularly important in light of the structural and systemic factors driving the growing racial and ethnic disparities in SUD treatment and care (Center for Behavioral Health Statistics and Quality, 2021). This discussion paper applies principles of social epidemiology to a traditional public health prevention framework and elucidates contextual and structural points of intervention.

The authors hope to expand the purview of action and responsibility beyond the individual, encourage an expanded lens for those who ascribe only to the biomedical approach to health and well-being, and promote an evergreen focus on SUD prevention that elevates the conversation beyond any particular drug. Leveraging a socioecological approach empowers leaders to champion prevention strategies that address health equity and amend the nation’s historically unjust practices, some of which persist today. With health equity in mind, the authors encourage US leaders to sharpen their attention toward macro-level solutions for prevention; these hold the greatest potential for sustainably improving health for all citizens across a broad set of health outcomes.

While there are a variety of evidence-based and promising practices related to SUD and overdose prevention, there remain significant gaps in researchers’ and practitioners’ understanding. Public funds addressing overdose trends should ensure individual-, interpersonal-, and macro-level investments across the primary, secondary, and tertiary prevention spectrum and support continued research on intended and unintended health outcomes of all funded interventions.

The nation can no longer solely target individuals for one of the greatest social ills of modern times (Reinarman and Levine, 1997). Rather, it must embrace a more comprehensive, multitiered approach that also considers the interpersonal, societal, and structural factors in which individuals interact. This view will ensure that the health care system not only treats the symptoms of disease but also concentrates on the underlying drivers that have fueled the unrelenting rise in incidence of SUD and overdose. In turn, this broader focus on prevention and treatment can also contribute significantly to promoting overall health and well being. Addressing these underlying determinants of health has the potential to enhance not only addiction outcomes but also broader societal health outcomes, fostering healthier, more resilient communities.

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NOTES: Some interventions address both risks and protective factors; other interventions may address only one.

The interventions included in the table have been limited to those with promising evidence to reduce the risks associated with precursors of SUD, SUD incidence, SUD morbidity, or SUD-related mortality; however, their inclusion does not suggest, and should not be taken as, an endorsement by the National Academy of Medicine or any of the authors’ organizations. Additionally, it should be noted that this table does not encompass an exhaustive list of all primary level interventions.

The selection process involved a thorough review of existing scientific literature, including published studies, meta-analyses, systematic reviews, and program evaluations. In determining the inclusion of interventions, the authors considered various factors, such as the strength of evidence supporting the program’s effectiveness, the quality of research studies conducted on the intervention, the consistency of positive outcomes across multiple studies, and the intervention’s relevance to the prevention of OUD and its associated risks.

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NOTES: Some interventions address both risks and protective factors; other interventions may address only one.

The interventions included in the table have been limited to those with promising evidence to reduce the risks associated with precursors of SUD, SUD incidence, SUD morbidity, or SUD-related mortality. In some cases the interventions are specific to harms related to opioid use/opioid use disorder, and this is clearly described in the table. However, their inclusion does not suggest, and should not be taken as, an endorsement by the National Academy of Medicine or any of the authors’ organizations. Additionally, it should be noted that this table does not encompass an exhaustive list of all secondary level interventions.

The selection process involved a thorough review of existing scientific literature, including published studies, meta-analyses, systematic reviews, and program evaluations. In determining the inclusion of interventions, the authors considered various factors, such as the strength of evidence supporting the program’s effectiveness, the quality of research studies conducted on the intervention, the consistency of positive outcomes across multiple studies, and the intervention’s relevance to the prevention of OUD and its associated risks.

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NOTES: Some interventions address both risks and protective factors; other interventions may address only one.

The interventions included in the table have been limited to those with promising evidence to reduce the risks associated with precursors of SUD, SUD incidence, SUD morbidity, or SUD-related mortality. In some cases the interventions are specific to harms related to opioid use/opioid use disorder, and this is clearly described in the table. However, their inclusion does not suggest, and should not be taken as, an endorsement by the National Academy of Medicine or any of the authors’ organizations. Additionally, it should be noted that this table does not encompass an exhaustive list of all tertiary level interventions.

The selection process involved a thorough review of existing scientific literature, including published studies, meta-analyses, systematic reviews, and program evaluations. In determining the inclusion of interventions, the authors considered various factors, such as the strength of evidence supporting the program’s effectiveness, the quality of research studies conducted on the intervention, the consistency of positive outcomes across multiple studies, and the intervention’s relevance to the prevention of OUD and its associated risks.

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References

Saturday, August 31, is International Overdose Awareness Day, when we collectively remember those who have lost their lives to drug overdose, support those who grieve those losses, and offer encouragement to those who seek recovery from addiction. It is also an opportunity to share new knowledge about the overdose crisis and strategies for confronting it. There is some very good news this year: Provisional data from the CDC show that, overall, overdose deaths dropped by 7.5% in the 12 months ending March, 2024, the largest decline in decades. It is cause for optimism. But unfortunately, for some groups, we continue to see only greater escalation of the overdose crisis.

A recent New York Times article highlighted the tragic epidemic of overdose deaths among older Black men in Baltimore. It is a city that has been especially hard-hit by the overdose crisis, but the trend is being seen nationwide. Although white and Black people use drugs at similar rates, fatal overdoses have escalated in Black people at a much higher rate than in other groups over the past decade, and multiple recent studies have documented especially high rates of overdose deaths among older Black men.

Fentanyl, often in combination with stimulants, is driving increased overdose deaths in most demographic groups. In all groups, men are at greater risk of overdose than women, but additional factors, including age-related health disparities, social isolation, and lifetime exposure to structural racism, may be colliding to produce the rise in overdoses among older Black men especially, and it points to the urgent need for intervention.

A NIDA analysis found that between 2015 and 2023 (provisional data), there was a nearly 5-fold increase in overdose deaths among non-Hispanic Black men 55 and older (figure). In 2023, deaths in that demographic category were nearly triple the national average for that age group. The largest proportion of these deaths, and the steepest increases, involved fentanyl and cocaine. The overdose rate in older Black men is markedly higher than that for Black men overall.

Image Source: NH=non-Hispanic. The Multiple Cause of Death final data are reported by NCHS, CDC. Estimates are based on final data through 2022. *Data for 2023 are based on provisional data. From 1999, data specifies Asian NH or Pacific Islander NH as one race category. From 2018, this race category was separated into Asian NH and Native Hawaiian or Other Pacific Islander NH (NHOPI). In this graph, these races were combined since data for NHOPI were suppressed because of counts <10 or noted as unreliable for counts <20. Data is also omitted for American Indian and Alaska Native NH death for years in which rates are suppressed or unreliable.

An increase in drug use and drug problems is being seen in older people of all races and ethnicities. Over the past two decades, substance use treatment admissions have increased among people aged 50 and over. In older adults, the risk of problematic opioid use is raised by chronic illness, and pain may be an especially important factor. Chronic pain is prevalent among older adults, and treatment for pain is less effective in this age group than it is in younger people; it negatively impacts quality of life and is a risk factor for cognitive decline and premature death.

As people age, they may start to lose partners and social contacts. A recent National Academies report identified social isolation as a major contributing factor to illness and poor quality of life in older people; it particularly impacts men, who tend to have fewer social supports in later life than women. Loneliness and social isolation are well-known risk factors for substance use, and in an analysis of substance use patterns among older people with varying degrees of social connectedness and perceived loneliness, those who lived alone and felt lonely had the highest rates of nonmedical drug use. Although Black and Hispanic older adults have lower odds of social isolation than white older adults, as well as lower rates of alcohol use, one analysis of overdose deaths among middle-aged and older adults in Illinois identified a common profile of socially isolated, predominantly Black men who had alcohol in their system when they died.

Health and other social disparities likely contribute to escalating overdose rates among older Black men. Black people face discrimination and implicit bias in healthcare settings, including significantly longer wait times for emergency treatment of health problems. Black patients tend to be undertreated for pain, compared to white patients. Such discrimination goes along with other social determinants of health including under-resourced urban environments, housing instability, and food insecurity that may contribute to higher rates of premature mortality and a higher burden of chronic illnesses. Excess mortality from causes including heart disease, cancer, assault, cerebrovascular disease, and diabetes is also higher among Black men.

Discrimination takes a toll on mental health. An analysis of data from the National Epidemiologic Survey on Alcohol and Related Conditions found that discrimination against Black people was associated with higher odds of illicit drug use. Along with other minoritized groups like American Indians, Black people are less likely than white people to engage or remain in substance use treatment. Black people seeking addiction treatment face greater delays obtaining it than white people, and they are much less likely than white patients to be prescribed buprenorphine, which significantly reduces the risk of overdose death. Unfortunately, even when older Black people receive substance use treatment, they are more likely than their white counterparts to have their treatment terminated by a treatment facility.

Structural discrimination is nothing new. The greater devastation fentanyl is wreaking in Black neighborhoods and communities like Baltimore could partly reflect longstanding patterns of economic disadvantage and mental health impacts of adversity—a reemerging signal that had been temporarily drowned out by the white overdose deaths that dominated the statistics and the headlines during the first two decades of the opioid epidemic. Overdose death rates among older black men have been consistently higher than for any other racial/ethnic group of the same age and have accelerated just as fast if not faster than in other groups for nearly a decade.

In a widely cited 2015 paper, Princeton economists Anne Case and Angus Deaton argued that increased economic hardships for white people without college education in the years 1999-2013 contributed to increased mortality in this group from drug overdose, suicide, and alcohol-related liver disease—what came to be called “deaths of despair.” However, economic disadvantage has long been the reality for minoritized groups whose higher risks of addiction and its consequences were invisible or ignored. Until 2001, deaths from overdose among Black people were consistently much higher than in white people, yet in that era, the drug problem in Black communities was framed as a problem of crime and deviance, not legitimized through a lens like despair. Overdose rates among Black people again surpassed those for white people in 2020.

The tragic situation the New York Times highlighted in Baltimore appears to be a nationwide problem, and it is clearly a complex one with many intersecting factors at play. Research alone cannot solve it, but it is necessary to understand why the current dangerous illicit drug supply is disproportionately affecting this population. Is there more to it than the additive risk factors of being male, Black, and older? We also need to understand how the increased burden of potentially co-occurring health conditions, including pain, may affect overdose risk in this group, as well as how their opioid use may intersect with other substance use. Answering these questions can guide the development and implementation of prevention, treatment, and harm-reduction strategies tailored for these communities.

Historically, prevention research has mainly focused on children, adolescents, and young adults, but along with the rise in opioid-related overdoses in older individuals in most racial and ethnic groups, increased use of other drugs like cannabis in older adults highlights the need for different kinds of interventions. This could include interventions to prevent opioid misuse or the transition from use to misuse specifically in older adults taking opioids for chronic pain. It might also include public-health interventions aimed at addressing social isolation and loneliness in older people, which could have benefits for a wide range of physical and mental health outcomes beyond substance use and its consequences.

Understanding structural factors affecting the health of underserved groups, both in the healthcare system and communities, is a primary objective of research that NIDA is funding as part of its Racial Equity Initiative. This research can help illuminate barriers to accessing substance use services in Black communities and inform the development of approaches to overcome them.

NIDA’s Intramural Research Program (IRP), which is located in Baltimore, is already leading several outreach and community-based research initiatives aimed at both better understanding and preventing fatal overdose in the city. For example, along with the Maryland Center for Health Equity at the University of Maryland School of Public Health, NIDA’s IRP is partnering with community barbershops to offer overdose education and naloxone distribution in settings frequented and trusted by Black clients. Analysis of hair samples swept from the floors of these barbershops is being used to monitor the levels of fentanyl in these Baltimore neighborhoods in a completely anonymous manner—a novel approach that could inform how interventions are targeted in these communities.

Ending the overdose epidemic, especially for the hardest-hit groups like older Black men, will not be easy. It will require coordinated work involving health service providers, community coalitions, policy makers, and—critically—people with lived and living experience of substance use. Researchers, too, will be essential, both for developing new and improved interventions and demonstrating how they can be effectively deployed so that they reach the people who need them.

The pandemic-era coverage policies, including the Medicaid continuous enrollment provision and the enhanced Marketplace subsidies, continued to impact health coverage in the U.S. in 2023. During the pandemic, the coverage expansions put in place by the Affordable Care Act (ACA), including Medicaid expansion and subsidized Marketplace coverage, served as a safety net for people who experienced economic and coverage disruptions. Gains in Medicaid and Marketplace coverage contributed to significant declines in the uninsured rate through 2022. Although states began the process of unwinding continuous enrollment in Medicaid in April 2023 and resumed disenrolling people from Medicaid, the full effect of Medicaid disenrollments were not felt in 2023. In addition, the enhanced Marketplace subsidies, which were extended through 2025, remained in place. Both these factors contributed to maintaining most of the coverage gains experienced during the pandemic period in 2023.

This issue brief describes trends in health coverage in 2023, examines the characteristics of the uninsured population ages 0-64, and summarizes the access and financial implications of not having coverage. Using data from the American Community Survey (ACS), this analysis examines changes in health coverage from 2022 to 2023 and compares data for 2023 to data for 2019 to report on coverage trends during the pandemic and through the start of the unwinding of the Medicaid continuous enrollment provision. Because of disruptions in data collection during the pandemic, the Census Bureau did not release 1-year ACS estimates in 2020. The analysis focuses on coverage among people ages 0-64 since Medicare offers near universal coverage for people ages 65 and older, with just 457,000, or less than 1%, of people over age 65 uninsured.

Key Takeaways

How many people are uninsured: Despite the unwinding of the Medicaid continuous enrollment provision that began in April 2023, the number of people ages 0-64 who were uninsured held steady at 25.3 million in 2023. However, the number of uninsured children increased from 3.8 million in 2022 to 4.0 million in 2023. Compared to 2019, the number of people who were uninsured declined by 3.6 million.

Despite the unwinding of the Medicaid continuous enrollment provision that began in April 2023, the number of people ages 0-64 who were uninsured held steady at 25.3 million in 2023. However, the number of uninsured children increased from 3.8 million in 2022 to 4.0 million in 2023. Compared to 2019, the number of people who were uninsured declined by 3.6 million. Who is uninsured: Most uninsured people are in low-income families and have at least one worker in the family. Reflecting the more limited availability of public coverage in some states, adults ages 19-64 are more likely to be uninsured than children. Despite gains across groups over time, racial and ethnic disparities in coverage persist.

Most uninsured people are in low-income families and have at least one worker in the family. Reflecting the more limited availability of public coverage in some states, adults ages 19-64 are more likely to be uninsured than children. Despite gains across groups over time, racial and ethnic disparities in coverage persist. Why are people uninsured: Many uninsured people cite the high cost of insurance as the main reason they lack coverage. In 2023, 63% of uninsured adults ages 18-64 said that they were uninsured because the cost of coverage was too high. Many uninsured people do not have access to coverage through a job, and some people, particularly poor adults in states that have not expanded Medicaid, remain ineligible for financial assistance for coverage. Although over half of people who are uninsured may be eligible for Medicaid or subsidized coverage in the Marketplaces, they may not be aware of these coverage options or may face barriers to enrolling. In some cases, even with subsidies, Marketplace coverage may not be affordable.

Many uninsured people cite the high cost of insurance as the main reason they lack coverage. In 2023, 63% of uninsured adults ages 18-64 said that they were uninsured because the cost of coverage was too high. Many uninsured people do not have access to coverage through a job, and some people, particularly poor adults in states that have not expanded Medicaid, remain ineligible for financial assistance for coverage. Although over half of people who are uninsured may be eligible for Medicaid or subsidized coverage in the Marketplaces, they may not be aware of these coverage options or may face barriers to enrolling. In some cases, even with subsidies, Marketplace coverage may not be affordable. How does not having coverage affect health care access: People without insurance coverage are less likely to access care and more likely to delay or forgo care because of costs. Although difficult to establish direct causality, research has linked Medicaid expansion to improved health outcomes, including lower mortality rates from cancer, cardiovascular disease, liver disease, and maternal mortality.

People without insurance coverage are less likely to access care and more likely to delay or forgo care because of costs. Although difficult to establish direct causality, research has linked Medicaid expansion to improved health outcomes, including lower mortality rates from cancer, cardiovascular disease, liver disease, and maternal mortality. What are the financial implications of being uninsured: Uninsured people often face unaffordable medical bills when they do seek care. Nearly half (49%) of uninsured adults say they have difficulty affording health care costs, more than double the share of those with private insurance (21%). These costs can quickly translate into medical debt since most people who are uninsured have low or moderate incomes and have little, if any, savings. More than six in ten (62%) uninsured adults report having health care debt compared to over four in ten (44%) insured adults.

Although coverage rates for the overall population ages 0-64 held steady in 2023, future changes to Medicaid and Marketplace coverage could have a significant impact on health coverage. Proposals that would alter how Medicaid is financed or that would impose work requirements on certain adults enrolled in the program would likely lead to a loss of Medicaid coverage. Moreover, the temporary enhanced Marketplace subsidies will expire after 2025 unless Congress acts. Without a permanent extension, the Congressional Budget Office estimates that the number of uninsured people will increase by 3.8 million, on average, in each year from 2026 to 2034. The combined Medicaid and Marketplace coverage losses could lead to a sizable increase in the number of people who are uninsured. In turn, the loss of coverage could have implications for access to care and financial stability associated with having health coverage and could lead to a worsening of disparities in health outcomes.

How many people are uninsured?

Among the population ages 0-64, both the number of uninsured (25.3 million) and the uninsured rate (9.5%) remained at historic lows in 2023. A continued decline in the number of uninsured adults ages 19-64 was offset by an increase in the number of uninsured children. Compared to 2019, prior to the start of the pandemic, the number of uninsured and the uninsured rate for the population ages 0-64 were both significantly lower in 2023. Nearly all groups experienced coverage gains, but American Indian or Alaska Native (AIAN) and Hispanic people had larger gains than their White counterparts and low-income individuals and those in working families had bigger gains than those at higher incomes and those without a worker in the family.

Key Details:

In 2023, 25.3 million people ages 0 to 64 were uninsured, and the uninsured rate for this population was 9.5%, both statistically unchanged from 2022. While the uninsured rate held steady from 2022, it was lower than in 2019 (10.9%) prior to the start of the coronavirus pandemic (Figure 1).

From 2019-2023, the uninsured rate declined by 1.4%, driven primarily by gains in Medicaid and Marketplace coverage because of pandemic-era coverage protections. The Medicaid continuous enrollment provision required states to keep people enrolled in Medicaid during the pandemic in exchange for enhanced federal funding and enhanced ACA Marketplace subsidies, first enacted in the American Rescue Plan Act (ARPA) and renewed through 2025 in the Inflation Reduction Act of 2022 (IRA). Although the enhanced Marketplace subsidies remained in effect in 2023, Medicaid continuous enrollment ended on March 31, 2023, and states resumed disenrolling people from Medicaid, though the full effects of the disenrollments were not felt in 2023. During this time period, employer coverage declined by 0.5% (Figure 2).

While there was no change in the uninsured rate for the overall population ages 0 to 64 in 2023, the share of children 18 and younger without insurance increased from 5.1% in 2022 to 5.3% in 2023. At the same time, the uninsured rate for adults ages 19 to 64 decreased to 11.1% in 2023 from 11.3% the previous year (Figure 2). An increase in Medicaid coverage for adults 19-64 from 16.3% to 16.5% in 2023 drove the decline in the uninsured rate for this group. Despite the uptick in the uninsured rate for children in 2023, the share of children without health insurance coverage was still lower in 2023 compared to 2019.

Although nearly all groups experienced coverage gains during the pandemic-period, they were largest for AIAN and Hispanic people and individuals in low-income families. From 2019 to 2023, the uninsured rate for AIAN people fell 3.0 percentage points (from 21.7% to 18.7%) and the uninsured rate for Hispanic people decreased by 2.1 percentage points (from 20.0% to 17.9%), although these groups remain more likely to be uninsured than their White counterparts. Native Hawaiian or Pacific Islander (NHPI) people did not experience a significant decline in the uninsured rate during this period, which may, in part, reflect the smaller sample size for NHPI people, which limits the power to detect statistically significant differences. While the uninsured rate dropped for people at all income levels, individuals in low-income families experienced the largest declines. From 2019-2023, the uninsured rate for poor individuals dropped 2.2 percentage points (18.0% to 15.8%) and 2.7 percentage points for individuals with income 100-199% FPL (18.2% to 15.5%, Figure 3).

From 2022 to 2023, the uninsured rate for the population ages 0 to 64 fell in six states (Florida, Hawaii, Illinois, Missouri, North Dakota, and Oregon) but increased in two states, Iowa and Idaho (Appendix Table A). At the same time, the uninsured rate for children increased in six states (Alabama, Idaho, New Mexico, South Carolina, Texas, and Washington). While these changes occurred in both expansion and non-expansion states, the uninsured rate was lower in expansion states (7.6%) compared to non-expansion states (14.1%) in 2023 (Figure 6).

Who is uninsured?

Most of the 25.3 million people ages 0-64 who are uninsured are adults, in working low-income families, and are people of color. Reflecting geographic variation in income and the availability of public coverage, most uninsured people live in the South or West. In addition, most who are uninsured have been without coverage for long periods of time. (See Appendix Table B for detailed data on characteristics of the uninsured population.)

Key Details:

In 2023, of the total uninsured population ages 0 to 64, nearly three in four (73.7%) had at least one full-time worker in their family, and 11.2% had a part-time worker in their family (Figure 4). More than eight in ten (80.9%) uninsured people were in families with incomes below 400% of the federal poverty level, and nearly half (46.6%) had incomes below 200% FPL. White people made up 37.1% of the uninsured, and the remaining 62.9% included Hispanic (41.1%), Black (12.5%), and Asian (3.7%) people and people of other racial or ethnic backgrounds (Figure 4). Most uninsured individuals (74.2%) were U.S. citizens, while 25.8% were noncitizens. Almost three-quarters (73.9%) of uninsured people lived in the South or West.

Adults ages 19 to 64 are more likely to be uninsured than children. In 2023, the uninsured rate for children was 5.3%, less than half the rate for adults at 11.1%.

Uninsured rates in the U.S. still show clear racial and ethnic disparities. In 2023, 17.9% of Hispanic people and 18.7% of AIAN people ages 0 to 64 were uninsured—more than two and a half times the rate for White people (6.5%). Asian individuals had the lowest uninsured rate at 5.8%.

Noncitizens are more likely than citizens to be uninsured. Nearly one-third of noncitizen immigrants were uninsured in 2023, while the uninsured rate for U.S.-born citizens was 7.5% and 8.9% for naturalized citizens. (Appendix Table B).

Uninsured rates vary by state and by region; individuals living in non-expansion states are more likely to be uninsured (Figure 6). Six of the ten states with the highest uninsured rates in 2023 were non-expansion states (Figure 5 and Appendix Table A).

Nearly two-thirds (64%) of people who were uninsured in 2023 have been without coverage for more than a year. People who have been without coverage for long periods may be particularly hard to reach through outreach and enrollment efforts.

Why are people uninsured?

Lack of access to affordable health coverage is the main reason many people say they are uninsured. A majority of working age adults in the U.S. obtain health insurance through an employer; however, not all workers are offered employer-sponsored coverage or, if offered, can afford their share of the premiums. Medicaid covers many low-income individuals, especially children, but Medicaid eligibility for adults remains limited in most states that have not adopted the ACA expansion. Marketplace subsidies make coverage more affordable for many, but even subsidized Marketplace coverage can be unaffordable for some, and few people can afford to purchase private coverage without financial assistance.

Key Details:

Cost is the most commonly cited reason for being uninsured. In 2023, 63.2% of uninsured adults ages 18-64 said they were uninsured because coverage is not affordable (Figure 7). Other reasons included not being eligible for coverage (27.0%), not needing or wanting coverage (26.6%), and signing up being too difficult (23.9%).

Not all workers have access to coverage through their job. In 2023, 64.7% of uninsured workers worked for an employer that did not offer them health benefits. Among uninsured workers who are offered coverage by their employers, cost is often a barrier to taking up the offer. From 2014 to 2024, total premiums for family coverage increased by 52%, outpacing wage growth, and the worker’s share increased by 31%. Low-income families with employer-based coverage spend a significantly higher share of their income toward premiums and out-of-pocket medical expenses compared to those with income above 200% FPL. Particularly among people working for small employers , premium contributions for dependents can be unaffordable.

Medicaid eligibility varies across states and eligibility for adults is limited in states that have not expanded Medicaid. As of December 2024, 41 states including DC had adopted the ACA Medicaid expansion. Two states implemented the expansion in 2023—South Dakota in July and North Carolina in December. In states that have not expanded Medicaid, the median eligibility level for parents is just 34% FPL and adults without dependent children are ineligible in most cases. Additionally, in non-expansion states, millions of poor uninsured adults fall into a “coverage gap” because they earn too much to qualify for Medicaid but not enough to qualify for Marketplace premium tax credits.

Many lawfully present immigrants must meet a five-year waiting period after receiving qualified immigration status before they can qualify for Medicaid. States have the option to cover eligible children and pregnant people without a waiting period, and as of May 2024, 37 states have elected the option for children and 31 states have taken up the option for pregnant individuals. Lawfully present immigrants, including those who are not eligible for Medicaid because they have not met the five-year waiting period, are eligible for Marketplace tax credits. However, Some states have taken steps to provide fully state-funded coverage to some or all immigrants who are not eligible for federal coverage.

Though financial assistance is available under the ACA to many of the remaining uninsured, not everyone who is uninsured is eligible for free or subsidized coverage. Nearly six in ten (14.5 million) uninsured individuals in 2023 were eligible for financial assistance either through Medicaid or through subsidized Marketplace coverage (Figure 8). However, over four in ten uninsured (10.9 million) are outside the reach of the ACA because their state did not expand Medicaid, they have an ineligible immigration status, or they were deemed to have access to an affordable Marketplace plan or offer of employer coverage.

How does not having coverage affect health care access?

Health insurance makes a difference in whether and when people get necessary medical care, where they get their care, and ultimately, how healthy they are. Uninsured adults are far more likely than those with insurance to postpone health care or forgo it altogether because of concerns over costs. The consequences can be severe, particularly when preventable conditions or chronic diseases go undetected.

Key Details:

Uninsured adults are more likely to forgo needed care than their insured counterparts. In 2023, nearly half (46.6%) of uninsured adults ages 18 to 64 reported not seeing a doctor or health care professional in the past 12 months compared to 15.6% with private insurance and 14.2% with public coverage. Part of the reason for not accessing care among uninsured individuals is that many (42.8%) do not have a regular place to go when they are sick or need medical advice (Figure 9). But cost also plays a role. Over one in five (22.6%) adults without coverage said that they went without needed care in the past year because of cost compared to 5.1% of adults with private coverage and 7.7% of adults with public coverage. A KFF survey that asks about cost barriers for individuals and their family members reports higher percentages of both uninsured and insured people delaying or forgoing needed care due to cost.

Uninsured children were also more likely than those with private insurance or public insurance to go without needed care due to cost in 2023 (9.5% compared to 0.7% and 1.0%, respectively). Furthermore, over a quarter (27.4%) of uninsured children had not seen a doctor in the past year, compared to 4.8% of children with public coverage and 3.7% of those with private coverage (Figure 9).

Studies repeatedly demonstrate that uninsured individuals are less likely than those with insurance to receive preventive care and services for major health conditions and chronic diseases. , , , Because people without health coverage are less likely than those with insurance to have regular outpatient care, they are more likely to be hospitalized for avoidable health problems and to experience declines in their overall health. When they are hospitalized, uninsured people receive fewer diagnostic and therapeutic services and also have higher mortality rates than those with insurance. , , , ,

Because people without health coverage are less likely than those with insurance to have regular outpatient care, they are more likely to be hospitalized for avoidable health problems and to experience declines in their overall health. When they are hospitalized, uninsured people receive fewer diagnostic and therapeutic services and also have higher mortality rates than those with insurance. Research demonstrates that gaining health insurance improves access to health care considerably and diminishes the adverse effects of having been uninsured. A review of research on the effects of the ACA Medicaid expansion finds that expansion led to positive effects on access to care, utilization of services, the affordability of care, and financial security among the low-income population.

More recent research generally shows Medicaid expansion is associated with improved health outcomes, although establishing direct causality between health insurance and health outcomes is complex. For example, Medicaid expansion is associated with increased early-stage diagnosis rates for cancer, lower rates of cardiovascular mortality, and increased odds of tobacco cessation. , Medicaid expansion has also been linked to lower mortality rates, including those from cancer, cardiovascular disease, liver disease, and maternal mortality. , Evidence suggests it also aids long-term recovery for substance use disorders and improves treatment management for conditions such as diabetes and HIV.

Medicaid expansion has also been linked to lower mortality rates, including those from cancer, cardiovascular disease, liver disease, and maternal mortality. Evidence suggests it also aids long-term recovery for substance use disorders and improves treatment management for conditions such as diabetes and HIV. Public hospitals, community clinics and health centers, and local providers that serve underserved communities provide an important health care safety net for uninsured people. However, safety net providers have limited resources and service capacity, and not all uninsured people have geographic access to a safety net provider.,, High uninsured rates contribute to rural hospital closures and greater financial challenges for rural hospitals, leaving individuals living in rural areas at an even greater disadvantage to accessing care., Research indicates that Medicaid expansion is associated with reductions in uncompensated care costs and improved financial performance for rural hospitals and other providers.

What are the financial implications of being uninsured?

Uninsured individuals often face unaffordable medical bills when they do seek care. These bills can quickly translate into medical debt since most people who are uninsured have low or moderate incomes and have little, if any, savings.

Key Details:

Those without insurance for an entire calendar year pay for almost 40% of their care out-of-pocket. In addition, hospitals frequently charge uninsured patients higher rates than those paid by private health insurers and public programs. , , ,

Uninsured adults ages 18 to 64 are much more likely than their insured counterparts to lack confidence in their ability to afford usual medical costs. Nearly half (49%) of uninsured adults said they or a family member had problems paying for health care compared to 21% of insured adults, and over eight in ten (84%) uninsured adults said they worried that health care costs would put them in debt or increase their existing debt, compared to 71% of adults with insurance (Figure 10).

Addressing these negative conditions and factors can help prevent suicide and suicide attempts. CDC is concerned with groups disproportionately impacted by suicide and uses a comprehensive public health approach to reduce suicide risk and save lives.

While anyone can experience suicide risk, some populations experience more negative social conditions and have higher rates of suicide or suicide attempts than the general U.S. population. The excess burden of suicide in some populations are called health disparities. 2 Examples of groups experiencing suicide health disparities include veterans, people who live in rural areas, sexual minorities, middle-aged adults, people of color, and tribal populations.

Suicide and suicidal behavior are influenced by negative conditions. These conditions, sometimes called social determinants of health, can include racism and discrimination in our society, economic hardship (such as high unemployment), poverty, limited affordable housing, lack of educational opportunities, and barriers to physical and mental healthcare access, among others. Additional factors that can increase suicide risk include relationship problems or feeling a lack of connectedness to others, easy access to lethal means among people at risk, experiences of violence 1 such as child abuse and neglect, adverse childhood experiences, bullying, and serious health conditions.

Suicide and suicide attempts can have lasting emotional, mental, and physical health impacts, as well as economic consequences. They can also impact people who struggle with their own risk of suicide and/or mental health challenges (called “lived experience”).

Additionally, CDC funds the Comprehensive Suicide Prevention program , which aims to reduce suicide among groups that experience health disparities in suicide. These programs use suicide prevention strategies based on the best available evidence to help states and communities prevent suicide. These strategies can be found in CDC’s Suicide Prevention Resource for Action , and include:

CDC is supporting states, tribes, territories, non-governmental organizations, and university research programs to address four strategic priority areas in suicide prevention:

Populations impacted

Suicide rates differ by age

Adults

Adults aged 35–64 years account for 46.8% of all suicides in the United States, and suicide is the 8th leading cause of death for this age group.3

Among men in this age group, suicide rates were highest for non-Hispanic American Indian or Alaska Native (AI/AN) men (41.3 suicides per 100,000), followed by non-Hispanic White men (35.7 per 100,000). 3

Among women in this age group, suicide rates were highest among non-Hispanic American Indian or Alaska Native women (12.8 per 100,000) and non-Hispanic White women (10.7 per 100,000). 3

Older Adults

Adults aged 75 and older have one of the highest suicide rates (20.3 per 100,000). Men aged 75 and older have the highest rate (42.2 per 100,000) compared to other age groups. Non-Hispanic White men have the highest suicide rate compared to other racial/ethnic men in this age group (50.1 per 100,000).3

What CDC and funded partners are doing to prevent suicide among middle-aged adults Massachusetts, Michigan, and Maine are working to reduce suicide disparities in middle-aged adults. Massachusetts and Maine are implementing gatekeeper training, which teaches community members how to identify people at risk for suicide and refer them to care. Massachusetts is also training providers to identify and support at-risk middle-aged adults and to use evidence-based screening and treatments. Massachusetts also aims to reduce access to lethal means by promoting safe storage. Massachusetts is working to increase access to and education on the benefits of firearm storage safes and trigger locks, and to promote lock bags, locked cabinets, and safe disposal of over-the-counter drugs among middle-aged males. For more information on what funded states are doing to prevent suicide, visit: Comprehensive Suicide Prevention: Program Profiles.

Youth and Young Adults

Youth and young adults ages 10–24 years account for 15% of all suicides. The suicide rate for this age group (11.0 per 100,000) is lower than other age groups.3 However, suicide is the second leading cause of death for this age group, accounting for 7,126 deaths.3 Additionally, suicide rates for this age group increased 52.2% between 2000-2021.

Youth and young adults most impacted include non-Hispanic American Indian or Alaska Native, with a suicide rate of 36.3 per 100,000.3

Youth and young adults have high rates of emergency department (ED) visits for self-harm. In 2020, the ED visit rate for this age group was 354.4 per 100,000, compared with 128.9 per 100,000 among middle-aged adults ages 35-64 years.4

There were an estimated 224,341 ED visits for self-harm among youth and young adults. 4

The rate of ED visits among girls in 2020 was approximately double compared to 2001 (244.3 per 100,000 4

In 2021, 9% of high school students reported attempting suicide during the previous 12 months.5 Suicide attempts were reported most frequently among girls compared to boys (12.4% vs. 5.3%) and among non-Hispanic American Indian or Alaska Native students (20.1%).5

What CDC and funded partners are doing to prevent youth suicide Colorado, Connecticut, Massachusetts, and Tennessee are working with their states’ departments of education to advance and provide social-emotional learning programs to promote coping and problem-solving skills. Colorado, Connecticut, North Carolina, and Vermont have implemented Counseling on Access to Lethal Means (CALM) in EDs to educate families of youth who are at increased risk for suicide on safe storage of lethal means (such as firearms, medications, and sharp objects) within the home. For more information on what funded states are doing to prevent suicide, visit: Comprehensive Suicide Prevention: Program Profiles.

Suicide risk is higher among people who identify as lesbian, gay, or bisexual

Data are limited on frequency of suicide among people who identify as sexual minorities. However, research shows that high school students who identify as sexual minorities have a higher prevalence of suicide attempts compared to heterosexual students.5

In 2021, more than a quarter (26.3%) of high school students identifying as lesbian, gay, or bisexual reported attempting suicide in the prior 12 months. This was five times higher than the prevalence among heterosexual students (5.2%).5

Data from 2020 show the prevalence of individuals reporting suicide attempts in the prior 12 months among adult sexual minorities decreased with age, from 5.5% among people ages 18-25 to 2.2% among people ages 26-49.6

Suicide rates are higher among veterans

In 2020, 6,146 veterans died by suicide. Suicide was the 13th leading cause of death among veterans overall, and the second leading cause of death among veterans under age 45.7 Veterans have an age-adjusted suicide rate that is 57.3% greater than the non-veteran U.S. adult population.7 Veterans account for about 13.9% of suicides among adults in the United States.7

Additionally, in 2019, 1.6% of veteran young adults ages 18-25 reported making a suicide attempt during the previous 12 months. This was an increase from 0.9% in 2009.8

What CDC and funded partners are doing to prevent suicide among veterans Massachusetts, North Carolina, Louisiana, and the University of Pittsburgh are identifying and supporting veterans at risk by implementing gatekeeper training. – Massachusetts is requiring all staff working in Massachusetts Career Centers to complete gatekeeper training. – North Carolina offers gatekeeper training as an option to healthcare providers. – University of Pittsburgh provides gatekeeper trainings that teaches about risk factors and warning signs for suicide among veterans. – Louisiana implemented gatekeeper trainings in nine local health department regions serving veterans. Massachusetts, Louisiana, and the University of Pittsburgh are promoting connectedness among veterans. – Massachusetts is focusing on community engagement to increase diversity, inclusion, and representation of veterans on the MassMen website. MassMen features articles, blog posts, self-assessments, and men’s stories to help men find solidarity, promote wellness, and increase help-seeking. – The University of Pittsburgh is implementing community greening projects to promote connectedness and decrease social isolation among veterans in Pennsylvania. – Louisiana is developing peer-to-peer norm groups with veterans. Peer norm programs seek to promote connectedness and normalize protective factors for suicide such as help-seeking, reaching out, and talking to trusted friends and loved ones. North Carolina, Louisiana, and the University of Pittsburgh are strengthening access to and delivery of suicide care. – North Carolina and Louisiana are providing increased veteran access to telemental health services to reduce provider shortages. – The University of Pittsburgh is working to strengthen access to and delivery of suicide care for veterans by working toward equal coverage of mental health conditions. – The University of Pittsburgh is also working to raise awareness and education among healthcare providers and community members on existing mental health parity laws. For more information on what funded states are doing to prevent suicide, visit: Comprehensive Suicide Prevention: Program Profiles.

Suicide rates vary by race and ethnicity

Age-adjusted suicide rates are highest among non-Hispanic American Indian and Alaska Native (AI/AN) people (28.1 per 100,000) and non-Hispanic White people (17.4 per 100,0003).

Suicide is the 9th leading cause of death among AI/AN people. Non-Hispanic AI/AN people have a higher age-adjusted rate of suicide (28.1 per 100,000) compared with Hispanic AI/AN people (2.0 per 100,000). The suicide rate among non-Hispanic AI/AN males ages 15–34 is 82.1 per 100,000.

Suicide is the 11th leading cause of death for both Hispanic and non-Hispanic people of all races.

Between 2018-2021, suicide rates significantly increased overall among non-Hispanic AI/AN (26%) and non-Hispanic Black (19.2%) people, and declined by 3.9% among non-Hispanic White people.

What CDC and funded partners are doing to prevent suicide in tribal communities Southern Plains Tribal Health Board and Wabanaki Public Health and Wellness are working to increase capacity to adapt, implement, and evaluate suicide prevention programs to reduce suicide-related morbidity and mortality. Each tribal organization is: – Reviewing existing data to describe the general problem and identify a subgroup that is at increased risk for suicide compared to the general tribal population. – Developing an inventory of existing suicide prevention programs for the general tribal population and the selected subgroup to identify gaps and opportunities that will complement existing programs. – Selecting at least one program from CDC’s Suicide Prevention Resource for Action, or another evidence-informed program, to fill prevention gaps and complement existing programs. – Adapting the selected program to fit the cultural context of the tribe and implement and evaluate the approach or program. – Conducting listening sessions to obtain input during the project to adapt the approach of program. – Disseminating results, success stories, and lessons learned. For more information on CDC’s funded tribal suicide prevention program, visit: Tribal Suicide Prevention.

Suicide ideation is higher among people with disabilities

Limited data are available on suicide among people with disabilities. However, a recent survey highlighted that in 2021, adults with disabilities were three times more likely to report suicidal ideation in the past month compared to people without disabilities (30.6% versus 8.3% in the general U.S. population9). Prior research also shows that the prevalence of reported mental distress, which is a risk factor for suicide, was 4.6 times higher among people with disabilities (32.9%) than among people without disabilities (7.2%10).

What CDC and funded partners are doing to prevent suicide among people with disabilities – Vermont is working to reduce suicide disparities among people with disabilities by providing training to primary care providers to promote safe storage among this population. – Vermont is supplementing and scaling up the state’s Zero Suicide work by engaging primary care providers serving people with disabilities. For more information on what funded states are doing to prevent suicide, visit: Comprehensive Suicide Prevention: Program Profiles.

Suicide rates differ by industry and occupation

Industry is the type of activity at a person’s workplace and occupation is the kind of work a person does to earn a living. A CDC study examining data in 32 states found that the suicide rate among workers in certain industries and occupations was significantly greater than the general U.S. population, particularly for males.11

The industry groups that had the highest suicide rates were:

Mining, Quarrying, and Oil and Gas Extraction (males: 54.2 per 100,000) Construction (males: 45.3 per 100,000) Other Services (such as automotive repair; males: 39.1 per 100,000) Agriculture, Forestry, Fishing, and Hunting (males: 36.1 per 100,000) Transportation and Warehousing (males: 29.8 per 100,000; females: 10.1 per 100,000)

The occupation groups that had higher suicide rates than the general population were:

Construction and Extraction (males: 49.4 per 100,000; females: 25.5 per 100,000) Installation, Maintenance, and Repair (males: 36.9 per 100,000) Arts, Design, Entertainment, Sports, and Media (males: 32.0 per 100,000) Transportation and Material Moving (males: 30.4 per 100,000; females: 12.5 per 100,000) Protective Service (females: 14.0 per 100,000) Healthcare Support (females: 10.6 per 100,000)

What CDC and funded partners are doing to prevent suicide for people in at-risk occupations Massachusetts, Colorado, and Connecticut are promoting connectedness among people working in occupations that are at greater risk for suicide. – Massachusetts and Colorado are implementing peer norm programs for at-risk occupations, such as Signs of Suicide (S.O.S.). – Connecticut is supporting community engagement efforts and providing workplaces for at-risk occupations with suicide prevention resources and materials. – Massachusetts and Connecticut are identifying and supporting occupations at higher risk for suicide via healthcare provider education. – Massachusetts, Connecticut, Michigan, and Colorado are promoting the implementation of organizational policies and culture in workplaces to create protective environments for people in at-risk occupations. The workplace provides an important opportunity for suicide prevention efforts because it is where many adults spend a great deal of their time. Visit the National Institute for Occupational Safety and Health website for more information about workplace suicide prevention strategies. For more information on what funded states are doing to prevent suicide, visit: Comprehensive Suicide Prevention: Program Profiles.

Suicide rates differ based on where you live

Suicide rates can vary substantially across geographic regions.* For example, suicide rates increase as population density decreases and an area becomes more rural.

2021 suicide rates based on population density:

Large central metropolitan: 11.6 per 100,000

Large fringe metro: 12.8 per 100,000

Medium metro: 15.7 per 100,000

Small metro: 17.8 per 100,000

Micropolitan (non-metro): 19.2 per 100,000

Noncore (non-metro): 21.7 per 100,000

Suicide rates in rural (non-metro) areas are highest among non-Hispanic AI/AN males (61.8 per 100,000) and non-Hispanic White males (36.8 per 100,0003).

*For information on how areas are classified, visit this page: Data Access – Urban Rural Classification Scheme for Counties (cdc.gov)

In 2024, the majority of First Nations people living off reserve (86%), Métis (70%) and Inuit (82%) reported that it was very or somewhat important to have health care services that support Indigenous traditional medicines, healing and wellness practices.

Released today, new data from the Survey Series on First Nations People, Métis and Inuit sheds light on health care access and experiences among Indigenous people aged 15 and older. The purpose of this survey series is to improve the visibility of First Nations people living off reserve, Métis and Inuit in national statistics and to fill key data gaps with timely and culturally relevant data.

Over one-quarter of Indigenous people wait two weeks or more for non-urgent care with a health care provider

Primary health care providers serve a crucial role in health maintenance and are linked to better health outcomes. In 2024, 70% of Métis, 66% of First Nations people living off reserve, and 52% of Inuit consulted a health care provider for a non-urgent primary health care need (such as check-ups and prescription refills) in the 12 months prior to the survey.

Timely access to a primary health care provider is important, yet wait times have been increasing in Canada and they tend to be longer in more remote areas among Indigenous people. Among those who had consulted a primary health care provider in the 12 months prior to the survey, most reported wait times that ranged from two days to less than two weeks. Inuit were most likely to report waiting one month or more to access a primary health care provider (18%, compared with 14% for First Nations people living off reserve and 11% of Métis) (Chart 1).

Chart 1

Percentage distribution of First Nations people living off reserve, Métis and Inuit aged 15 and older, by time taken between requesting and speaking with a primary health care provider, Canada, 2024

When asked about their level of satisfaction with wait times, about half of First Nations people living off reserve (50%), Métis (52%) and Inuit (57%) reported being satisfied or very satisfied.

Over one-quarter of Indigenous people have unmet health care needs

Indigenous people often face barriers to health care that contribute to health disparities, including navigating complex health care policies and funding, and sometimes even having to travel outside their communities to access services.

Unmet health care needs in the 12 months prior to the survey were reported by 32% of First Nations people living off reserve, 30% of Métis, and 29% of Inuit. A higher percentage of off-reserve First Nations women than men reported unmet health care needs in the 12 months prior to the survey (Table 1).

When asked why their health care needs were unmet, commonly reported reasons among First Nations people living off reserve, Métis and Inuit were difficulty getting a referral to a specialist and not being given the correct treatment or prescription. Among First Nations people living off reserve and Inuit, another commonly reported reason was health care services not being in their area/being too far away (Table 2).

Among Indigenous people who need mental health care and seek such care, about three-quarters report needs that are partially met or unmet

Mental health disparities among Indigenous people have been widely reported. These disparities are rooted in historical factors such as colonial, assimilationist policies, that have had adverse direct and intergenerational impacts, as well as contemporary factors such as access barriers to mental health services.

Almost half (47%) of First Nations people living off reserve, 43% of Métis and 35% of Inuit reported needing mental health care in the 12 months prior to the survey. More First Nations, Métis, and Inuit women than men reported that they needed mental health care. The need for mental health care trended higher among younger than older First Nations people living off reserve, Métis and Inuit with significant differences found between the oldest and youngest age groups (Table 3).

Among those who needed mental health care and sought such care, 28% of First Nations people living off reserve, 23% of Métis and 22% of Inuit reported that their needs were fully met, while nearly three-quarters reported partially met or unmet mental health care needs.

Inuit report travelling significant distances from their community to access health care

For some Indigenous people, extensive travel is necessary to access health care, and this can result in financial burdens, emotional stress, anxiety, and feelings of isolation. Roughly one in five First Nations people living off reserve (18%), 16% of Metis and 40% of Inuit travelled outside their community to access health care services in the 12 months prior to the survey.

While most First Nations people living off reserve and Métis who travelled for health care in the 12 months prior to the survey reported travelling less than 500 km (55% and 63%, respectively), a different scenario was seen among Inuit, just over half of whom reported travelling 1,500 km or more (Table 4).

Roughly one in five Indigenous people report experiencing unfair treatment, racism or discrimination from a health care professional

Racism, discrimination, and marginalization within the health care system are documented barriers to health care for Indigenous people. About 24% of First Nations people living off reserve, 23% of Inuit and 18% of Métis reported that they experienced some form of unfair treatment, racism, or discrimination from a health care professional in the 12 months prior to the survey. First Nations women living off reserve and Métis women were nearly twice as likely to report this compared to men (Chart 2).

Chart 2

Percentage of First Nations people living off reserve, Métis and Inuit aged 15 and older who reported unfair treatment, racism, or discrimination from any health care professional in the 12 months prior to the survey, by gender, Canada, 2024

Among First Nations people living off reserve and Inuit who had experienced unfair treatment, racism or discrimination from a health care professional, the most reported setting was the hospital emergency room (50% for First Nations people living off reserve and 34% for Inuit), with 36% of Métis also reporting similar experiences in this setting. Among Métis, the most reported setting was the doctor’s office (46%) (Table 5).

Most Indigenous people report that having health care services that support Indigenous traditional medicines, healing and wellness practices are very or somewhat important

In the Indigenous context, the integration of culturally appropriate and safe care—defined as care that reflects the values, traditions, and social norms of a patient’s culture and where patients feel respected, safe and valued—is important. In addition, the Truth and Reconciliation Commission of Canada called on the Canadian health care system to recognize and integrate traditional knowledge, therapies and healing practices into the treatment approach for Indigenous people.

In 2024, health care services that support Indigenous traditional medicines, healing and wellness practices in the Canadian health care system were very or somewhat important to First Nations people living off reserve (86%), Inuit (82%) and Métis (70%) (Chart 3).

Chart 3

Percentage distribution of First Nations people living off reserve, Métis and Inuit aged 15 and older, by importance of having health care services that support Indigenous traditional medicines, healing and wellness practices, Canada, 2024

However, most Indigenous people experiencing unfair treatment, racism or discrimination felt that their concerns and values were not taken into consideration in their interactions with health care professionals. More specifically, among those who experienced unfair treatment, racism or discrimination in the 12 months preceding the survey, 67% of First Nations people living off reserve, 65% of Métis and 58% of Inuit reported that their health concerns were minimized or dismissed (Table 6).

A further 21% of First Nations people living off reserve, 12% of Métis and 9% of Inuit indicated that their cultural protocols were not respected (e.g., not allowed to smudge or use traditional medicines).

Of those who stated that culturally appropriate services were important, 68% of First Nations people living off reserve, 67% of Inuit and 61% of Métis reported such services would make them feel respected for their culture, beliefs and identity. Roughly half of First Nations people living off reserve (49%) and Inuit (50%) reported that such services would make them more likely to seek health care. About half of Inuit (48%), 41% of First Nations people living off reserve and 32% of Métis reported that these services would make them feel safer discussing sensitive or traumatic experiences (Table 7).

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Note to readers The data in this release are from the first survey of Statistics Canada’s Survey Series on First Nations People, Métis and Inuit (SSFNPMI). The SSFNPMI is a new panel series as part of the Transformational Approach to Indigenous Data initiative. The survey series aims to fill known data gaps identified by Indigenous and federal government partners and was developed based on an analysis of indicators that align with the Truth and Reconciliation Commission Calls to Action, the National Inquiry into Missing and Murdered Indigenous Women and Girls Calls for Justice, as well as the Canadian Indicator Framework for Sustainable Development Goals and Canada’s Quality of Life Framework. The SSFNPMI consists of three very short online surveys given to the same individuals over a period of one year. These voluntary surveys are based on a probability panel consisting of 6,206 individuals who agreed to participate in further studies when they responded to the 2022 Indigenous Peoples Survey. They represent the Canadian population aged 15 years and older living off reserve who identify as First Nations, Métis or Inuit. The first survey in the SSFNPMI survey series collected data on Indigenous peoples’ experiences with health care and access to different types of health care. On the first survey, 878 respondents were First Nations people living off reserve (single identity), 695 were Métis (single identity), 495 were Inuit (single identity), and 45 respondents identified with more than one Indigenous identity group. For this study, survey weights were adjusted to minimize bias that could arise from panel non-response. Non-response adjustments and calibration using available auxiliary information were applied and are reflected in the survey weights provided with the data file. Despite these adjustments, the high degree of non-response to the panel increases the risk of remaining bias, which may impact estimates produced using the panel data. Users should therefore use caution when interpreting all results of the study. Further information on data quality guidelines and considerations can be obtained in the SSFNPMI user guide. Single and multiple responses to the Indigenous identity question are used when reporting data for the three Indigenous groups. This paper reports on gender, not sex at birth, which includes the non-binary population. The non-binary population is small, with data aggregation to a two-category gender variable done to protect the confidentiality of responses. Individuals in the category “non-binary persons” are distributed into the other two gender categories and are denoted by the “+” symbol. Significance testing was used to establish differences between groups. This data release is from the first survey in the series, which focuses on health care access and experiences. The second survey in the series focuses on well-being and the impacts of rising prices, and the third focuses on emergency preparedness. Find more statistics on Indigenous Peoples in Canada. Definitions : Health care professional : When asked about health care professionals in the survey, examples provided included doctors, visiting physicians, nurse practitioners, nurses, physiotherapists, or other specialists such as rheumatologists and endocrinologists. Non-urgent primary health care needs : In the survey this was defined as routine care such as check-ups and prescription refills as well as other things you would make an appointment for, such as an infection, fever, headache, a sprained ankle, vomiting or an unexplained rash.

Contact information

For more information, or to enquire about the concepts, methods or data quality of this release, contact us (toll-free 1-800-263-1136; 514-283-8300; infostats@statcan.gc.ca) or Media Relations (statcan.mediahotline-ligneinfomedias.statcan@statcan.gc.ca).