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. Author manuscript; available in PMC: 2024 Apr 1.
Published in final edited form as: J Subst Use Addict Treat. 2023 Feb 18;147:208976. doi: 10.1016/j.josat.2023.208976

Past-year medical and non-medical opioid use by HIV status in a nationally representative US sample: Implications for HIV and substance use service integration

Brooke S West 1, José E Diaz 2, Morgan M Philbin 3, Pia M Mauro 4
PMCID: PMC10100645  NIHMSID: NIHMS1877211  PMID: 36827878

Abstract

Aim:

In the context of the continued overdose epidemic, recent population estimates of opioid use in highly affected groups, such as people at risk for or people living with HIV (PLWH), are essential for service planning and provision. Although nonmedical opioid use is associated with HIV transmission and with lowered adherence and care engagement, most studies rely on clinic-based samples and focus on medical use of opioids only. We examine associations between opioid-related outcomes by HIV status in a community-based nationally representative sample.

Methods:

The 2015–2019 National Survey on Drug Use and Health included 213,203 individuals ages 18 and older. Respondents self-reported whether a health care professional ever told them they had HIV/AIDS (i.e., HIV-positive/PLWH, HIV-negative, HIV-unknown). Opioid-related outcomes included past-year medical opioid use and past-year nonmedical (i.e., prescription opioid and heroin) use. Multinomial logistic regression estimated adjusted relative risk ratios between past-year opioid-related outcomes and HIV status, controlling for age, gender, race/ethnicity, income, population density, and year.

Results:

In 2015–2019, 0.2% of respondents were PLWH and 0.3% self-reported an HIV-unknown status. Past-year medical opioid use was 37.3% among PLWH, 30.4% among HIV-negative and 21.9% among HIV-unknown individuals. Past-year nonmedical use was 11.1% among PLWH, 4.2% among HIV-negative and 7.2% among HIV-unknown individuals. Compared to HIV-negative individuals, PLWH had 3.21 times higher risk of past-year nonmedical use vs. no use (95% CI:2.02–5.08) and 2.02 times higher risk of past-year nonmedical vs. medical opioid use only (95% CI:1.24–2.65).

Conclusion:

Nonmedical opioid use prevalence was almost three times higher among PLWH than HIV-negative individuals. Because opioid use and its related harms disproportionately burden PLWH, integrating HIV and substance use prevention and treatment services may improve both HIV-related and opioid-related outcomes, including overdose.

Keywords: Opioids, Medical opioid use, Nonmedical opioid use, Heroin, HIV, Overdose, Opioid use disorder, Susbtance use treatment, HIV treatment

1. Introduction

Nonmedical opioid use (i.e. use of pharmaceutical opioids in greater doses than prescribed and/or without a prescription, as well as use of non-pharmaceutical opioids) and the related overdose epidemic are ongoing public health challenges that disproportionately impact people living with HIV (PLWH). Opioid use is a driver of HIV acquisition: recently, multiple US-based HIV outbreaks stemmed from opioid use in the context of limited availability of harm-reduction services (Alpren et al., 2020; Golden et al., 2019; Hodder et al., 2021; Kishore et al., 2019; Peters et al., 2016). The use of opioids can precede HIV infection or result from a need for chronic pain management among PLWH, including an increased likelihood of receiving opioid treatment, higher doses of opioids, and long-term opioids use (Cunningham, 2018). Among PLWH, opioid use is positively associated with negative health outcomes, including interruptions in HIV treatment and care (Altice et al., 2010; Azar et al., 2010; Hinkin et al., 2007; Lucas, 2011). Given the widespread consequences of HIV and opioid use, and high rates of overdose attributed to heroin and synthetic opioids (e.g. fentanyl), the field needs more research on patterns of opioid use, particularly nonmedical use, among PLWH and those at risk for HIV.

PLWH are at high risk of both medical (i.e., use as prescribed by a clinician) and nonmedical opioid use; however, previous work comes from studies conducted in clinical settings and focuses primarily on opioid prescribing practices and long-term medical use of opioids (Canan et al., 2019; Merlin et al., 2018; Tsui et al., 2019). PLWH are prescribed more opioids than the general population (Becker et al., 2016; Edelman et al., 2013): upwards of 17% of US-based PLWH receive long-term prescription opioid therapy (Edelman et al., 2013; Merlin et al., 2016; Silverberg et al., 2012) primarily to deal with HIV-related chronic pain (Canan et al., 2019; Frich & Borgbjerg, 2000; Miaskowski et al., 2011; Tsao et al., 2012). Increased medical opioid use has contributed to a higher prevalence of opioid use disorder (OUD) among PLWH compared to the general population (Hansen et al., 2011; Robinson-Papp et al., 2012; Tsao et al., 2007). Specifically, higher population-level exposure to medical opioids can lead to higher nonmedical prescription opioid use and/or the initiation of heroin or other illegal opioids (Banerjee et al., 2016; Edelman et al., 2020), calling for studies distinguishing medical and nonmedical opioid use.

Nonmedical use of opioids, which can occur for a variety reasons (e.g., pain management, euphoric effect, etc.), warrants particular attention because such use is associated with elevated drug-related morbidity and mortality, poorer HIV outcomes, and a range of adverse social outcomes, such as incarceration and housing instability (Degenhardt et al., 2019; Edelman et al., 2020). Among PLWH receiving medical care, 3.3% report nonmedical opioid use, though these data are from 2009to 2014, highlighting the need for updated estimates that more closely reflect the current state of opioid use (Lemons et al., 2019). Nonmedical opioid use is more common among younger adults, males, and non-Hispanic white individuals (Lemons et al., 2019) and is associated with a lower likelihood of being prescribed antiretroviral therapy (ART), interruptions in adherence and care, insufficient viral suppression, and higher HIV transmission rates (Altice et al., 2010; Beer et al., 2015; Jeevanjee et al., 2014; Lucas, 2011). Services and policy responses may thus require tailoring for the unique circumstances of PLWH who use opioids nonmedically.

Nonmedical opioid use among PLWH also raises concerns around overdose. Drug overdose is a leading cause of non-AIDS-related deaths among PLWH, and risk for nonfatal overdose is high (Green et al., 2012). Overdose risk may be elevated for PLWH who use nonmedical, rather than medical, opioids due to exposure to a toxic drug supply. In a systematic review of the relationship between HIV-status and overdose, researchers highlighted the primary importance of environmental factors, noting that many of the structural factors that drive overdose (e.g., access to medication for OUD [MOUD], housing instability, poverty, socioeconomic status, incarceration, isolation) are also more pronounced among PLWH (Green et al., 2012). Together, these factors may contribute to elevated overdose rates in this population.

In our study, we build on work from clinical settings and examine differences in past-year medical and nonmedical opioid use by HIV status in a nationally representative community-based US sample of adults from 2015 to 2019. Unlike clinic-based samples, which often include patients with complex health problems, our findings contribute to an understanding of broader community needs. Our focus on both medical and nonmedical opioid use also provides a more complete assessment of opioid use patterns by HIV status among adults specifically, as children may have distinct substance use and clinical needs. Findings could be used by practitioners and program planners in real-world settings to inform interventions that reduce opioid-related harm and integrate services across HIV and substance use care silos.

2. Methods

We pooled data from the 2015–2019 National Survey on Drug Use and Health (NSDUH), an annual cross-sectional nationally representative survey of the noninstitutionalized US population. The NSDUH used multistage probability sampling to assess substance use and mental health. From 2015 to 2019, the weighted interview response rates for the NSDUH ranged from 64.9% to 69.3% (Quality, 2017–2020). After excluding adolescents aged 12–17 (n=68,263), and then people with blank/refused HIV status responses (n=1,302), the final analytic sample included adults aged 18 years or older who reported having an HIV diagnosis status as positive, negative, or unknown (n=213,203).

2.1. Measures

The main outcomes of interest were: (a) past-year medical opioid use and (b) past-year nonmedical opioid use. Medical opioid use included any use of prescription opioids as directed by a doctor without reporting any past-year nonmedical opioid use. Nonmedical opioid use included nonmedical prescription opioid use (i.e., use of prescription opioids without one’s own prescription or in ways other than prescribed by a medical professional, including dosage) or heroin use.

The primary exposure was HIV status. Respondents indicated whether a doctor or health care provider had ever diagnosed them as having HIV/AIDS. Affirmative responses to HIV/AIDS diagnosis were classified as HIV-positive/PLWH, while negative responses represent HIV-negative status. Unknown HIV status included those who reported not knowing if they had ever been diagnosed with HIV.

Our covariates were selected to represent common sociodemographic controls that other studies have identified as relevant to patterns of opioid use. Control covariates included age (18–25, 26–34, 35–49, 50+), gender (men, women), race and ethnicity (non-Hispanic Black, Hispanic, non-Hispanic white, any other race/multiracial), household income (<$20,000, $20,000–49,999, $50,000–74,999, $75,000 or more), population density (large metro area ≥1 million residents, small metro area <1 million residents, non-metro/rural areas), and year. We also conducted sensitivity analyses with serious psychological distress (i.e. depression, anxiety) to explore potential health comorbidities.

2.2. Statistical analyses

Sample descriptive characteristics were stratified by self-reported HIV status. We calculated weighted prevalence of past-year medical opioid use and nonmedical opioid use by HIV status. Weighted multinomial logistic regression models estimated unadjusted and adjusted relative risk ratios and 95% confidence intervals of nonmedical opioid use relative to medical opioid use and to no use, comparing PLWH and people with HIV-unknown status to those who are HIV-negative. Adjusted models controlled for sociodemographic covariates and year. The study team analyzed data with Stata 17.0 and used survey weighting to reflect the complex NSDUH design.

3. Results

In 2015–2019, 0.2% of the sample reported HIV-positive status (i.e., PLWH), 99.5% HIV-negative, and 0.3% reported their HIV status as unknown (Table 1). Both PLWH and people with unknown HIV status were predominately men, non-Hispanic white, had a household income of < $50,000, and lived in a large metro area. PLWH were predominately aged 50+, while those with HIV unknown status were more evenly spread across age groups.

Table 1.

Sociodemographic characteristics by HIV status, NSDUH 2015–2019, N = 213,203

HIV-Negative HIV-Positive HIV-Unknown
N Wt. Col. % (SE) N Wt. Col. % (SE) N Wt. Col. % (SE)
Total (Wt. Row %)2 212,009 (99.5) 402 (0.2) 792 (0.3)
Gender
Men 98,328 48.1 (0.17) 287 79.5 (3.28) 457 55.3 (3.02)
Women 113,681 51.9 (0.17) 115 20.5 (3.38) 335 44.7 (3.02)
Age Groups
18–25 69,026 13.9 (0.10) 73 5.5 (0.89) 368 23.1 (1.9)
26–34 43,505 16.0 (0.12) 80 16.7 (2.48) 167 20.3 (2.06)
35–49 55,903 24.7 (0.14) 136 27.2 (3.27) 179 26.8 (1.97)
50+ 43,575 45.5 (0.24) 113 50.6 (3.54) 78 29.8 (3.23)
Race/Ethnicity
Non-Hispanic White 128,040 64.1 (0.25) 172 49.1 (3.59) 247 31.3 (2.93)
Non-Hispanic Black 26,529 11.8 (0.18) 135 29.3 (3.02) 121 16.8 (2.53)
Hispanic 36,352 16.0 (0.20) 77 19.2 (3.45) 271 31.6 (2.8)
Non-Hispanic Other 21,088 8.2 (0.11) 18 2.4 (0.88) 153 20.4 (2.24)
Household Income
<$20,000 42,054 16.1 (0.15) 154 32.3 (3.41) 296 37.7 (3.3)
$20,000–49,999 66,076 29.4 (0.20) 130 31.6 (3.23) 291 33.2 (2.79)
$50,000-$74,999 33,227 16.0 (0.12) 43 13.1 (2.55) 75 9.0 (1.33)
$75,000 or more 70,652 38.5 (0.27) 75 23.0 (2.83) 130 20.1 (2.29)
Population Density 3
Large Metro 90,035 53.9 (0.27) 240 73.9 (3.54) 403 64.0 (3.01)
Small Metro 105,207 40.3 (0.30) 146 23.9 (3.24) 339 30.9 (2.8)
Non-Metro 16,767 5.8 (0.16) 16 2.3 (0.90) 50 5.1 (1.28)
Opioid Use
Past-year medical prescription opioid only, yes 60,018 30.4 (0.15) 202 37.3 (3.59) 156 21.9 (2.04)
Past-year nonmedical prescription opioid or heroin use, yes 11,168 4.2 (0.06) 51 11.1 (2.07) 69 7.2 (1.18)
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1

Wt. Col. % = weighted column percentage.

2

Wt. Row % = weighted row percentage.

3

Large metro areas include core-based statistical areas (CBSA) of ≥1 million residents; small metro areas were CBSAs of < 1 million residents, and non-metro areas were classified as non-CBSA areas. Columns may not sum to 100% due to rounding.

Both past-year medical prevalence and nonmedical opioid use prevalence were highest among PLWH: 37.3% of PLWH reported medical opioid use compared to 30.4% of HIV-negative people and 21.9% of people with unknown HIV status. Past-year nonmedical opioid use was reported by 11.1% of PLWH, 7.2% of those with unknown HIV status, and 4.2% of HIV-negative people.

Table 2 presents relative risk ratios of past-year medical opioid use only and nonmedical opioid use relative to no opioid use, and for nonmedical use relative to medical use, both unadjusted and adjusted for age, race/ethnicity, gender, household income, population density, and survey year. In adjusted multivariable models, PLWH had 1.58 times the risk (95% CI: 1.14, 2.20) of past-year medical opioid use vs. no use and 3.21 times the risk (95% CI: 2.02, 5.08) of non-medical opioid use vs. no use compared to HIV-negative people. People with unknown HIV status had a lower relative risk of past-year medical opioid use vs. no use compared to HIV-negative people [adjusted relative risk ratio (aRRR = 0.77, 95% CI: 0.60, 0.97)]. Risk of past-year nonmedical opioid use vs. medical opioid use was higher among both PLWH (aRRR=2.02, 95% CI: 1.23, 3.34) and people with unknown HIV status (aRRR=1.81, 95% CI: 1.24, 2.65) compared to HIV-negative people.

Table 2.

Relative risk ratios of past-year medical opioid use and past-year non-medical opioid use by HIV status and sociodemographic characteristics, NSDUH 2015–2019, n = 213,203

Past-year medical opioid use vs. No use Past-year non-medical opioid use vs. no use Past-year non-medical opioid use vs. Past-year medical opioid use
uRRR (95% CI) aRRR (95% CI) uRRR (95% CI) aRRR (95% CI) uRRR (95% CI) aRRR (95% CI)
HIV Status
HIV-Negative Ref. Ref. Ref. Ref. Ref. Ref.
HIV-Positive 1.55 (1.12, 2.14) 1.58 (1.14, 2.20) 3.35 (2.16, 5.20) 3.21 (2.02, 5.08) 2.16 (1.35, 3.44) 2.02 (1.23, 3.34)
HIV-Unknown 0.67 (0.52, 0.85) 0.77 (0.60, 0.97) 1.58 (1.09, 2.28) 1.39 (0.95, 2.01) 2.37 (1.62, 3.46) 1.81 (1.24, 2.65)
Gender
Men Ref. Ref. Ref. Ref. Ref. Ref.
Women 1.28 (1.24, 1.31) 1.26 (1.22, 1.30) 0.82 (0.78, 0.87) 0.81 (0.77, 0.86) 0.64 (0.61, 0.68) 0.65 (0.61, 0.68)
Age Groups
18–25 Ref. Ref. Ref. Ref. Ref. Ref.
26–34 1.26 (1.22, 1.30) 1.29 (1.25, 1.34) 1.02 (0.96, 1.09) 1.10 (1.04, 1.18) 0.81 (0.76, 0.87) 0.85 (0.79, 0.91)
35–49 1.45 (1.40, 1.49) 1.50 (1.45, 1.55) 0.72 (0.67, 0.77) 0.81 (0.75, 0.87) 0.50 (0.46, 0.53) 0.54 (0.50, 0.58)
50+ 1.72 (1.67, 1.77) 1.67 (1.62, 1.72) 0.40 (0.36, 0.44) 0.41 (0.37, 0.45) 0.23 (0.21, 0.26) 0.24 (0.22, 0.27)
Race/Ethnicity
Non-Hispanic White Ref. Ref. Ref. Ref. Ref. Ref.
Non-Hispanic Black 1.00 (0.96, 1.05) 1.00 (0.96, 1.04) 0.86 (0.77, 0.97) 0.67 (0.60, 0.76) 0.86 (0.76, 0.97) 0.67 (0.59, 0.77)
Hispanic 0.67 (0.65, 0.70) 0.71 (0.67, 0.74) 0.82 (0.75, 0.88) 0.62 (0.57, 0.67) 1.21 (1.12, 1.31) 0.88 (0.80, 0.96)
Non-Hispanic Other 0.63 (0.59, 0.66) 0.67 (0.63, 0.71) 0.60 (0.54, 0.67) 0.52 (0.46, 0.58) 0.96 (0.85, 1.07) 0.78 (0.69, 0.87)
Household Income
<$20,000 Ref. Ref. Ref. Ref. Ref. Ref.
$20,000–49,999 0.95 (0.91, 0.99) 0.92 (0.88, 0.96) 0.74 (0.69, 0.80) 0.74 (0.69, 0.80) 0.79 (0.73, 0.85) 0.80 (0.74, 0.87)
$50,000-$74,999 0.92 (0.87, 0.97) 0.88 (0.83, 0.93) 0.65 (0.59, 0.71) 0.62 (0.56, 0.68) 0.70 (0.64, 0.77) 0.70 (0.64, 0.77)
$75,000 or more 0.83 (0.79, 0.87) 0.80 (0.76, 0.84) 0.52 (0.48, 0.56) 0.49 (0.45, 0.54) 0.62 (0.57, 0.70) 0.62 (0.56, 0.68)
Population Density1
Large Metro Ref. Ref. Ref. Ref. Ref. Ref.
Small Metro 1.20 (1.16, 1.24) 1.13 (1.09, 1.17) 1.11 (1.05, 1.18) 1.01 (0.94, 1.07) 0.92 (0.87, 0.98) 0.89 (0.84, 0.95)
Non-Metro 1.20 (1.15, 1.26) 1.06 (1.00, 1.11) 0.97 (0.86, 1.10) 0.86 (0.75, 0.98) 0.81 (0.72, 0.92) 0.81 (0.71, 0.93)
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uRRR=unadjusted relative risk ratio; aRRR=adjusted relative risk ration; CI= confidence interval. Adjusted models also controlled for survey year.

3

Large metro areas include core-based statistical areas (CBSA) of ≥1 million residents; small metro areas were CBSAs of < 1 million residents, and non-metro areas were classified as non-CBSA areas.

We provide results of sensitivity analyses adjusting for serious psychological distress in Supplemental Table 1. Estimates remained consistent in direction and magnitude, with shifts to significance in risk comparing unknown HIV status to HIV-negative people.

4. Discussion

Using 2015–2019 nationally representative data, we examined associations between HIV status and past-year medical and nonmedical opioid use in a community, rather than clinic-based sample. Compared to samples of PLWH from clinical settings, where around 3% reported nonmedical opioid use between 2009 and 2014 (Lemons et al., 2019), in this study, using more recent data, 11% reported nonmedical use. Nonmedical opioid use prevalence was almost three times higher among PLWH than people who were HIV-negative (4.2%). For people with HIV-unknown status, nonmedical use may also lead to HIV transmission or acquisition. In adjusted models, PLWH and people with unknown HIV status were substantially more likely to report past-year nonmedical opioid use compared to HIV-negative individuals. These findings highlight that PLWH and those with unknown status have heightened risk for negative health consequences related to the synergistic opioid and HIV crises and that risk may be elevated for people who use nonmedical opioids.

Elevated nonmedical opioid use among both PLWH and individuals with unknown HIV status have important implications for HIV treatment and prevention responses. Previous studies show that problematic use of opioids is associated with worsened ART adherence (Jeevanjee et al., 2014) and lowered care engagement (Critchley et al., 2020). However, greater access to OUD treatment, including MOUD, can improve ART access, adherence and viral suppression (Adams et al., 2020; Lappalainen et al., 2015; Malta et al., 2008; Nosyk et al., 2015; Palepu et al., 2004; Palepu et al., 2006; Reddon et al., 2014; Sambamoorthi et al., 2000; Turner et al., 2001). Expanding MOUD is thus a key component of building holistic and effective responses to these duel epidemics.

The availability of quality care may also be more limited for PLWH who use nonmedical opioids. Legal concerns and substantial provider stigma and discrimination against people who use drugs may impede disclosure of substance use to providers (Ahern et al., 2007; Brener et al., 2010; Kulesza et al., 2013; Van Boekel et al., 2013), preventing opportunities for care engagement and leading to negative clinical outcomes (Van Boekel et al., 2013). For PLWH or those with unknown HIV-status, structural barriers, like homelessness, limited service access, perceived discrimination and medical mistrust further prevent HIV testing and subsequent care engagement (Bogart et al., 2019; Brincks et al., 2019; Dale et al., 2016; Underhill et al., 2015). We must address the drivers of both HIV and nonmedical opioid use to improve HIV-related clinical outcomes, supporting programs and policies (e.g. harm reduction) that mitigate the structural disadvantages placing individuals in position of marginality and impede access to care (Hodder et al., 2021).

Despite overlaps between HIV and opioid use, services for substance use and HIV are largely siloed (Perlman & Jordan, 2018). Greater service integration is beneficial to patients and improves clinical outcomes, highlighting the need for comprehensive HIV and substance use prevention and treatment services (Haldane et al., 2017; Oldfield et al., 2018; Volkow & Montaner, 2011). Integrating services, either through co-locating screening and treatment in the same facilities or widening the scope of services within separated care facilities, could have widespread benefits for the health of both PLWH and people whose HIV status is unknown (Oldfield et al., 2018). For instance, screening for HIV, and subsequent care linkage, in substance use treatment settings (or substance use screening in HIV service settings) could reduce HIV acquisition and tr ansmission (Volkow & Montaner, 2011), while also improving care engagement, thus mitigating potential negative health impacts associated with nonmedical opioid use, particularly for PLWH.

Creating integrated care systems could also expand who receives information about overdose prevention, including naloxone distribution and other harm-reduction tools. A suite of critical resources should more consistently be offered in both HIV and harm reduction or substance use treatment settings that support safer opioid use and prevent HIV transmission, including MOUD, syringes, drug checking, pre-exposure prophylaxis (PrEP), HIV testing and counseling (self-tests and other testing), and ART (Hodder et al., 2021). The integration and effective delivery of these services is hampered, however, by widespread stigma against both substance use and HIV, as well as unjust policies that diminish access to quality services (e.g., limited health insurance coverage and the criminalization of drug use) (Hodder et al., 2021). Overall, the bundling of HIV and substance use treatment services could increase the accessibility of crucial care by providing opportunities to reach individuals at greatest risk for morbidity and mortality.

A strength of this study is the use of a nationally representative, community-based, data source, allowing us to compare opioid use among PLWH and those without HIV or with unknown status. Nonetheless, we should note limitations. The NSDUH is not designed to target recruitment by HIV status and may not be representative of PLWH in the United States. HIV-status is self-reported and based on whether a health care professional had told the participant they had HIV/AIDS. HIV status misclassification may not be at random if individuals with an unknown HIV status are less likely to receive HIV testing due to structural vulnerabilities that may also increase risk for HIV infection, and that may intersect with medical or nonmedical opioid use. Due to small sample sizes, we could not analyze nonmedical prescription and heroin use separately, and may not include other synthetic opioids like fentanyl, limiting our understanding of unique opioid patterns. Findings may not generalize to people excluded from NSDUH sampling (i.e., homeless and not in shelters, incarcerated, institutionalized individuals), who may be more likely to have HIV and use nonmedical opioids, so findings may underestimate true associations. In our pooled cross-sectional analysis, we could not determine directionality or temporal ordering assessing whether nonmedical use preceded HIV acquisition or vice versa. In this secondary analysis, we were also limited to existing measures in the public-use NSDUH (e.g., age categories vs. continuous age). Additionally, our sensitivity analyses suggest that a need exists for more attention to health comorbidities, like mental health, that may be mediators in the relationship between HIV status and opioid use. Unfortunately, in this cross-sectional pooled analysis, we could not assess mediation, and we were limited in the number of covariates that we could include due to sample sizes in the HIV+ subsample; however, we do present sensitivity analyses with serious psychological distress in Supplemental Table 1. Although we described associations between HIV status and opioid use controlling for sociodemographic characteristics identified as relevant in other studies, future research should examine how other confounder and mediating variables may contribute to the observed relationships.

5. Conclusion

In this 2015–2019 community-based sample, more than one in 10 PLWH reported past-year nonmedical use and almost four in 10 reported medical opioid use. PLWH may be at elevated risk for negative opioid use-related consequences, including reduced medication adherence, engagement in care and HIV treatment interruptions, and HIV-related complications. Beyond clinical outcomes related to HIV treatment and care, nonmedical use among PLWH and people with unknown HIV status also presents concerns for OUD and overdose. Efforts to increase care integration—particularly integrating HIV care, OUD treatment and overdose prevention—could be targeted to reduce inequities.

Supplementary Material

1

HIGHLIGHTS.

  • In this 2015–2019 nationally representative community-based sample, past-year non-medical use was 11.1% among people with HIV, 4.2% among HIV-negative and 7.2% among HIV-unknown individuals, while past-year medical opioid use was 37.3% among people with HIV, 30.4% among HIV-negative and 21.9% among HIV-unknown individuals.

  • Compared to HIV-negative individuals, people with HIV had more than three times higher risk of past-year non-medical use vs. no use and two times higher risk of past-year non-medical vs. medical opioid use only.

  • Since opioid use and its related harms disproportionately burden people with HIV, integrating HIV and substance use prevention and treatment services may improve clinical outcomes, including access to and utilization of antiretroviral therapy and treatment for opioid use disorders, as well as overdose prevention.

Footnotes

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REFERENCES

  1. Adams JW, Marshall BD, Salleh NAM, Barrios R, Nolan S, & Milloy M-J (2020). Receipt of opioid agonist treatment halves the risk of HIV-1 RNA viral load rebound through improved ART adherence for HIV-infected women who use illicit drugs. Drug and alcohol dependence, 206, 107670. [DOI] [PMC free article] [PubMed] [Google Scholar]
  2. Ahern J, Stuber J, & Galea S (2007). Stigma, discrimination and the health of illicit drug users. Drug and alcohol dependence, 88(2–3), 188–196. [DOI] [PubMed] [Google Scholar]
  3. Alpren C, Dawson EL, John B, Cranston K, Panneer N, Fukuda HD, Roosevelt K, Klevens RM, Bryant J, & Peters PJ (2020). Opioid use fueling HIV transmission in an urban setting: an outbreak of HIV infection among people who inject drugs—Massachusetts, 2015–2018. American journal of public health, 110(1), 37–44. [DOI] [PMC free article] [PubMed] [Google Scholar]
  4. Altice FL, Kamarulzaman A, Soriano VV, Schechter M, & Friedland GH (2010). Treatment of medical, psychiatric, and substance-use comorbidities in people infected with HIV who use drugs. The Lancet, 376(9738), 367–387. [DOI] [PMC free article] [PubMed] [Google Scholar]
  5. Azar MM, Springer SA, Meyer JP, & Altice FL (2010). A systematic review of the impact of alcohol use disorders on HIV treatment outcomes, adherence to antiretroviral therapy and health care utilization. Drug and alcohol dependence, 112(3), 178–193. [DOI] [PMC free article] [PubMed] [Google Scholar]
  6. Banerjee G, Edelman EJ, Barry DT, Becker WC, Cerdá M, Crystal S, Gaither JR, Gordon AJ, Gordon KS, & Kerns RD (2016). Non-medical use of prescription opioids is associated with heroin initiation among US veterans: a prospective cohort study. Addiction, 111(11), 2021–2031. [DOI] [PMC free article] [PubMed] [Google Scholar]
  7. Becker WC, Gordon K, Edelman EJ, Kerns RD, Crystal S, Dziura JD, Fiellin LE, Gordon AJ, Goulet JL, & Justice AC (2016). Trends in any and high-dose opioid analgesic receipt among aging patients with and without HIV. AIDS and Behavior, 20(3), 679–686. [DOI] [PMC free article] [PubMed] [Google Scholar]
  8. Beer L, Valverde EE, Raiford JL, Weiser J, White BL, & Skarbinski J (2015). Clinician perspectives on delaying initiation of antiretroviral therapy for clinically eligible HIV-infected patients. Journal of the International Association of Providers of AIDS Care (JIAPAC), 14(3), 245–254. [DOI] [PMC free article] [PubMed] [Google Scholar]
  9. Bogart LM, Ransome Y, Allen W, Higgins-Biddle M, & Ojikutu BO (2019). HIV-related medical mistrust, HIV testing, and HIV risk in the National Survey on HIV in the Black community. Behavioral Medicine, 45(2), 134–142. [DOI] [PMC free article] [PubMed] [Google Scholar]
  10. Brener L, Hippel WV, Kippax S, & Preacher KJ (2010). The role of physician and nurse attitudes in the health care of injecting drug users. Substance Use & Misuse, 45(7–8), 1007–1018. [DOI] [PubMed] [Google Scholar]
  11. Brincks AM, Shiu-Yee K, Metsch LR, Del Rio C, Schwartz RP, Jacobs P, Osorio G, Sorensen JL, & Feaster DJ (2019). Physician mistrust, medical system mistrust, and perceived discrimination: Associations with HIV care engagement and viral load. AIDS and Behavior, 23(10), 2859–2869. [DOI] [PMC free article] [PubMed] [Google Scholar]
  12. Canan C, Alexander GC, Moore R, Murimi I, Chander G, & Lau B (2019). Medicaid trends in prescription opioid and non-opioid use by HIV status. Drug and alcohol dependence, 197, 141–148. [DOI] [PMC free article] [PubMed] [Google Scholar]
  13. Critchley L, Carrico A, Gukasyan N, Jacobs P, Mandler RN, Rodriguez AE, Del Rio C, Metsch LR, & Feaster DJ (2020). Problem opioid use and HIV primary care engagement among hospitalized people who use drugs and/or alcohol. Addiction science & clinical practice, 15(1), 1–8. [DOI] [PMC free article] [PubMed] [Google Scholar]
  14. Cunningham CO (2018). Opioids and HIV infection: from pain management to addiction treatment. Topics in antiviral medicine, 25(4), 143. [PMC free article] [PubMed] [Google Scholar]
  15. Dale SK, Bogart LM, Wagner GJ, Galvan FH, & Klein DJ (2016). Medical mistrust is related to lower longitudinal medication adherence among African-American males with HIV. Journal of health psychology, 21(7), 1311–1321. [DOI] [PMC free article] [PubMed] [Google Scholar]
  16. Degenhardt L, Grebely J, Stone J, Hickman M, Vickerman P, Marshall BD, Bruneau J, Altice FL, Henderson G, & Rahimi-Movaghar A (2019). Global patterns of opioid use and dependence: harms to populations, interventions, and future action. The Lancet, 394(10208), 1560–1579. [DOI] [PMC free article] [PubMed] [Google Scholar]
  17. Edelman EJ, Gordon K, Becker WC, Goulet JL, Skanderson M, Gaither JR, Braden JB, Gordon AJ, Kerns RD, & Justice AC (2013). Receipt of opioid analgesics by HIV-infected and uninfected patients. Journal of general internal medicine, 28(1), 82–90. [DOI] [PMC free article] [PubMed] [Google Scholar]
  18. Edelman EJ, Li Y, Barry D, Braden JB, Crystal S, Kerns RD, Gaither JR, Gordon KS, Manhapra A, & Merlin JS (2020). Trajectories of self-reported opioid use among patients with HIV engaged in care: Results from a national cohort study. JAIDS Journal of Acquired Immune Deficiency Syndromes, 84(1), 26–36. [DOI] [PMC free article] [PubMed] [Google Scholar]
  19. Frich LM, & Borgbjerg FM (2000). Pain and pain treatment in AIDS patients: a longitudinal study. Journal of pain and symptom management, 19(5), 339–347. [DOI] [PubMed] [Google Scholar]
  20. Golden MR, Lechtenberg R, Glick SN, Dombrowski J, Duchin J, Reuer JR, Dhanireddy S, Neme S, & Buskin SE (2019). Outbreak of human immunodeficiency virus infection among heterosexual persons who are living homeless and inject drugs—Seattle, Washington, 2018. Morbidity and Mortality Weekly Report, 68(15), 344. [DOI] [PMC free article] [PubMed] [Google Scholar]
  21. Green TC, McGowan SK, Yokell MA, Pouget ER, & Rich JD (2012). HIV infection and risk of overdose: a systematic review and meta-analysis. AIDS (London, England), 26(4), 403. [DOI] [PMC free article] [PubMed] [Google Scholar]
  22. Haldane V, Cervero-Liceras F, Chuah FL, Ong SE, Murphy G, Sigfrid L, Watt N, Balabanova D, Hogarth S, & Maimaris W (2017). Integrating HIV and substance use services: a systematic review. Journal of the International AIDS Society, 20(1), 21585. [DOI] [PMC free article] [PubMed] [Google Scholar]
  23. Hansen L, Penko J, Guzman D, Bangsberg DR, Miaskowski C, & Kushel MB (2011). Aberrant behaviors with prescription opioids and problem drug use history in a community-based cohort of HIV-infected individuals. Journal of pain and symptom management, 42(6), 893–902. [DOI] [PMC free article] [PubMed] [Google Scholar]
  24. Hinkin CH, Barclay TR, Castellon SA, Levine AJ, Durvasula RS, Marion SD, Myers HF, & Longshore D (2007). Drug use and medication adherence among HIV-1 infected individuals. AIDS and Behavior, 11(2), 185–194. [DOI] [PMC free article] [PubMed] [Google Scholar]
  25. Hodder SL, Feinberg J, Strathdee SA, Shoptaw S, Altice FL, Ortenzio L, & Beyrer C (2021). The opioid crisis and HIV in the USA: deadly synergies. The Lancet. [DOI] [PubMed] [Google Scholar]
  26. Jeevanjee S, Penko J, Guzman D, Miaskowski C, Bangsberg DR, & Kushel MB (2014). Opioid analgesic misuse is associated with incomplete antiretroviral adherence in a cohort of HIV-infected indigent adults in San Francisco. AIDS and Behavior, 18(7), 1352–1358. [DOI] [PMC free article] [PubMed] [Google Scholar]
  27. Kishore S, Hayden M, & Rich J (2019). Lessons from Scott County—progress or paralysis on harm reduction? New England Journal of Medicine, 380(21), 1988–1990. [DOI] [PMC free article] [PubMed] [Google Scholar]
  28. Kulesza M, Larimer ME, & Rao D (2013). Substance use related stigma: what we know and the way forward. Journal of addictive behaviors, therapy & rehabilitation, 2(2). [DOI] [PMC free article] [PubMed] [Google Scholar]
  29. Lappalainen L, Nolan S, Dobrer S, Puscas C, Montaner J, Ahamad K, Dong H, Kerr T, Wood E, & Milloy MJ (2015). Dose–response relationship between methadone dose and adherence to antiretroviral therapy among HIV-positive people who use illicit opioids. Addiction, 110(8), 1330–1339. [DOI] [PMC free article] [PubMed] [Google Scholar]
  30. Lemons A, DeGroote N, Peréz A, Craw J, Nyaku M, Broz D, Mattson CL, & Beer L (2019). Opioid misuse among HIV-positive adults in medical care: results from the medical monitoring project, 2009–2014. Journal of acquired immune deficiency syndromes (1999), 80(2), 127. [DOI] [PMC free article] [PubMed] [Google Scholar]
  31. Lucas GM (2011). Substance abuse, adherence with antiretroviral therapy, and clinical outcomes among HIV-infected individuals. Life sciences, 88(21–22), 948–952. [DOI] [PMC free article] [PubMed] [Google Scholar]
  32. Malta M, Strathdee SA, Magnanini MM, & Bastos FI (2008). Adherence to antiretroviral therapy for human immunodeficiency virus/acquired immune deficiency syndrome among drug users: a systematic review. Addiction, 103(8), 1242–1257. [DOI] [PubMed] [Google Scholar]
  33. Merlin JS, Long D, Becker WC, Cachay ER, Christopoulos KA, Claborn K, Crane HM, Edelman EJ, Harding R, & Kertesz SG (2018). The association of chronic pain and long-term opioid therapy with HIV treatment outcomes. Journal of acquired immune deficiency syndromes (1999), 79(1), 77. [DOI] [PMC free article] [PubMed] [Google Scholar]
  34. Merlin JS, Tamhane A, Starrels JL, Kertesz S, Saag M, & Cropsey K (2016). Factors associated with prescription of opioids and co-prescription of sedating medications in individuals with HIV. AIDS and Behavior, 20(3), 687–698. [DOI] [PMC free article] [PubMed] [Google Scholar]
  35. Miaskowski C, Penko JM, Guzman D, Mattson JE, Bangsbeg DR, & Kushel MB (2011). Occurrence and characteristics of chronic pain in a community-based cohort of indigent adults living with HIV infection. The Journal of Pain, 12(9), 1004–1016. [DOI] [PMC free article] [PubMed] [Google Scholar]
  36. Nosyk B, Min JE, Colley G, Lima VD, Yip B, Milloy M-J, Wood E, & Montaner JS (2015). The causal effect of opioid substitution treatment on HAART medication refill adherence. AIDS (London, England), 29(8), 965. [DOI] [PMC free article] [PubMed] [Google Scholar]
  37. Oldfield BJ, Muñoz N, McGovern MP, Funaro M, Villanueva M, Tetrault JM, & Edelman EJ (2018). Integration of care for HIV and opioid use disorder: a systematic review of interventions in clinical and community-based settings. AIDS (London, England). [DOI] [PMC free article] [PubMed] [Google Scholar]
  38. Palepu A, Horton NJ, Tibbetts N, Meli S, & Samet JH (2004). Uptake and adherence to highly active antiretroviral therapy among HIV-infected people with alcohol and other substance use problems: the impact of substance abuse treatment. Addiction, 99(3), 361–368. [DOI] [PubMed] [Google Scholar]
  39. Palepu A, Tyndall MW, Joy R, Kerr T, Wood E, Press N, Hogg RS, & Montaner JS (2006). Antiretroviral adherence and HIV treatment outcomes among HIV/HCV co-infected injection drug users: the role of methadone maintenance therapy. Drug and alcohol dependence, 84(2), 188–194. [DOI] [PubMed] [Google Scholar]
  40. Perlman DC, & Jordan AE (2018). The syndemic of opioid misuse, overdose, HCV, and HIV: structural-level causes and interventions. Current HIV/AIDS Reports, 15(2), 96–112. [DOI] [PMC free article] [PubMed] [Google Scholar]
  41. Peters PJ, Pontones P, Hoover KW, Patel MR, Galang RR, Shields J, Blosser SJ, Spiller MW, Combs B, Switzer WM, & Conrad C (2016). HIV infection linked to injection use of oxymorphone in Indiana, 2014–2015. New England Journal of Medicine, 375(3), 229–239. [DOI] [PubMed] [Google Scholar]
  42. Quality, C. f. B. H. S. a. (2017–2020). National Survey on Drug Use and Health: Methodological summary and definitions.
  43. Reddon H, Milloy M-J, Simo A, Montaner J, Wood E, & Kerr T (2014). Methadone maintenance therapy decreases the rate of antiretroviral therapy discontinuation among HIV-positive illicit drug users. AIDS and Behavior, 18(4), 740–746. [DOI] [PMC free article] [PubMed] [Google Scholar]
  44. Robinson-Papp J, Elliot K, Simpson DM, Morgello S, & Manhattan HIV Brain Bank. (2012). Problematic prescription opioid use in an HIV-infected cohort: the importance of universal toxicology testing. . Journal of acquired immune deficiency syndromes (1999), 61(2), 187. [DOI] [PMC free article] [PubMed] [Google Scholar]
  45. Sambamoorthi U, Warner LA, Crystal S, & Walkup J (2000). Drug abuse, methadone treatment, and health services use among injection drug users with AIDS. Drug and alcohol dependence, 60(1), 77–89. [DOI] [PubMed] [Google Scholar]
  46. Silverberg MJ, Ray GT, Saunders K, Rutter CM, Campbell CI, Merrill JO, Sullivan MD, Banta-Green C, Von Korff M, & Weisner C (2012). Prescription long-term opioid use in HIV-infected patients. The Clinical journal of pain, 28(1), 39. [DOI] [PMC free article] [PubMed] [Google Scholar]
  47. Tsao JC, Plankey MW, & Young MA (2012). Pain, psychological symptoms and prescription drug misuse in HIV: A literature review. . Journal of pain management, 5(2), 111. [PMC free article] [PubMed] [Google Scholar]
  48. Tsao JC, Stein JA, & Dobalian A (2007). Pain, problem drug use history, and aberrant analgesic use behaviors in persons living with HIV. Pain, 133(1–3), 128–137. [DOI] [PMC free article] [PubMed] [Google Scholar]
  49. Tsui JI, Walley AY, Cheng DM, Lira MC, Liebschutz JM, Forman LS, Sullivan MM, Colasanti J, Root C, & O’Connor K (2019). Provider opioid prescribing practices and the belief that opioids keep people living with HIV engaged in care: a cross-sectional study. AIDS care. [DOI] [PMC free article] [PubMed] [Google Scholar]
  50. Turner BJ, Zhang D, Laine C, Pomerantz RJ, Cosler L, & Hauck WW (2001). Association of provider and patient characteristics with HIV-infected women’s antiretroviral therapy regimen. Journal of acquired immune deficiency syndromes (1999), 27(1), 20–29. [DOI] [PubMed] [Google Scholar]
  51. Underhill K, Morrow KM, Colleran C, Holcomb R, Calabrese SK, Operario D, Galárraga O, & Mayer KH (2015). A qualitative study of medical mistrust, perceived discrimination, and risk behavior disclosure to clinicians by US male sex workers and other men who have sex with men: implications for biomedical HIV prevention. Journal of Urban Health, 92(4), 667–686. [DOI] [PMC free article] [PubMed] [Google Scholar]
  52. Van Boekel LC, Brouwers EP, Van Weeghel J, & Garretsen HF (2013). Stigma among health professionals towards patients with substance use disorders and its consequences for healthcare delivery: systematic review. Drug and alcohol dependence, 131(1–2), 23–35. [DOI] [PubMed] [Google Scholar]
  53. Volkow ND, & Montaner J (2011). The urgency of providing comprehensive and integrated treatment for substance abusers with HIV. Health Affairs, 30(8), 1411–1419. [DOI] [PMC free article] [PubMed] [Google Scholar]

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