Socioeconomic correlates of incident and fatal opioid overdose among Swedish people with opioid use disorder

Associations among drug acquisition and use behaviors, psychosocial attributes, and opioid-involved overdoses

AIMS

This study sought to develop and assess an exploratory model of how demographic and psychosocial attributes, and drug use or acquisition behaviors interact to affect opioid-involved overdoses.

DESIGN

We conducted exploratory and confirmatory factor analysis (EFA/CFA) to identify a factor structure for ten drug acquisition and use behaviors. We then evaluated alternative structural equation models incorporating the identified factors, adding demographic and psychosocial attributes as predictors of past-year opioid overdose.

SETTING AND PARTICIPANTS

We used interview data collected for two studies recruiting opioid-misusing participants receiving services from a community-based syringe services program. The first investigated current attitudes toward drug-checking (N = 150). The second was an RCT assessing a telehealth versus in-person medical appointment for opioid use disorder treatment referral (N = 270).

MEASUREMENTS

Demographics included gender, age, race/ethnicity, education, and socioeconomic status. Psychosocial measures were homelessness, psychological distress, and trauma. Self-reported drug-related risk behaviors included using alone, having a new supplier, using opioids with benzodiazepines/alcohol, and preferring fentanyl. Past-year opioid-involved overdoses were dichotomized into experiencing none or any.

FINDINGS

The EFA/CFA revealed a two-factor structure with one factor reflecting drug acquisition and the second drug use behaviors. The selected model (CFI = .984, TLI = .981, RMSEA = .024) accounted for 13.1% of overdose probability variance. A latent variable representing psychosocial attributes was indirectly associated with an increase in past-year overdose probability (β = .234, p = .001), as mediated by the EFA/CFA identified latent variables: drug acquisition (β = .683, p < .001) and drug use (β = .567, p = .001). Drug use behaviors (β = .287, p = .04) but not drug acquisition (β = .105, p = .461) also had a significant, positive direct effect on past-year overdose. No demographic attributes were significant direct or indirect overdose predictors.

CONCLUSIONS

Psychosocial attributes, particularly homelessness, increase the probability of an overdose through associations with risky drug acquisition and drug-using behaviors. Further research is needed to replicate these findings with populations at high-risk of an opioid-related overdose to assess generalizability and refine the metrics used to assess psychosocial characteristics.

Clinical prediction of opioid use disorder in chronic pain patients: a cohort-retrospective study with a pharmacogenetic approach

BACKGROUND

Opioids are widely used in chronic non-cancer pain (CNCP) management. However, they remain controversial due to serious risk of causing opioid use disorder (OUD). Our main aim was to develop a predictive model for future clinical translation that include pharmacogenetic markers.

METHODS

An observational study was conducted in 806 pre-screened Spanish CNCP patients, under long-term use of opioids, to compare cases (with OUD, N.=137) with controls (without OUD, N.=669). Mu-opioid receptor 1 (OPRM1, A118G, rs1799971) and catechol-O-methyltransferase (COMT, G472A, rs4680) genetic variants plus cytochrome P450 2D6 (CYP2D6) liver enzyme phenotypes were analyzed. Socio-demographic, clinical and pharmacological outcomes were also registered. A logistic regression model was performed. The model performance and diagnostic accuracy were calculated.

RESULTS

OPRM1-AA genotype and CYP2D6 poor and ultrarapid metabolizers together with three other potential predictors: 1) age; 2) work disability; 3) oral morphine equivalent daily dose (MEDD), were selected with a satisfactory diagnostic accuracy (sensitivity: 0.82 and specificity: 0.85), goodness of fit (P=0.87) and discrimination (0.89). Cases were ten-year younger with lower incomes, more sleep disturbances, benzodiazepines use, and history of substance use disorder in front of controls.

CONCLUSIONS

Functional polymorphisms related to OPRM1 variant and CYP2D6 phenotypes may predict a higher OUD risk. Established risk factors such as young age, elevated MEDD and lower incomes were identified. A predictive model is expected to be implemented in clinical setting among CNCP patients under long-term opioids use.

Use of prescription opioids in Israel and socio-economic correlations between 2010 and 2020

BACKGROUND

The use of opioids has increased dramatically over the past several years in Israel. The aim of this study was to explore the trends of opioid consumption in Israel over a decade (2010-2020) stratified by socioeconomic status (SES), residence in the periphery, and ethnic background.

METHODS

This cross-sectional study included all adult Maccabi Healthcare Services (MHS) patients who filled at least one prescription for opioids during the past decade. In order to standardize dosages and compare different opioid medications, we used the Morphine Milligram Equivalent (MME) conversion factor. We performed The Mann-Kendall test with autocorrelation correction to assess each trend. We then checked the differences between the trends with the Mann-Whitney test (for periphery) and the Kruskal Wallis (for SES and ethnic background).

RESULTS

Between the years 2010-2020, 261,270 MHS members met the study's inclusion criteria. The proportions of opioids consumption were 23.9/1000 patients in 2010 and 27.6/1000 patients in 2020, representing a 15% increase. The average daily consumption of opioids was 4.6 and 10.5 MME in 2010 and 2020, respectively, an increase of 227%. The daily MME during 2020 was higher for residents of the periphery compared to non-periphery residents (daily MME of 14.0 compared to 10.1, respectively). Average daily MME increased gradually during the study period for all levels of SES; the values were highest for the low SES group and the lowest for the high SES group (daily MME in 2020 for the lowest, middle, and high SES groups were 15.2 vs. 11.8 vs. 6.7 respectively).

CONCLUSIONS

This study highlights that the primary concern in the increase of opioid use is the increasing dosages. The increase in the number of patients using opioids is also significant but to a minor extent. These phenomena disproportionately impact vulnerable populations. Education programs should be offered to physicians regarding the possible harms of long-term use of opioids. These programs should emphasize the risk factors associated with the development of opioid use disorder (OUD) and the caution needed when increasing dosages or switching to higher-potency drugs. Pain clinics and centers for rehabilitation for patients with chronic pain or OUD should be available, not only in central areas but also in the periphery of the country. These clinics and centers should use a holistic approach and a multidisciplinary team that includes specialists in pain and addiction. They should be financially accessible for patients from low SES group and provide solutions in multiple languages.

Associations among Drug Acquisition and Use Behaviors, Psychosocial Attributes, and Opioid-Involved Overdoses: A SEM Analysis

Aims

This study sought to develop and assess an exploratory model of how demographic and psychosocial attributes, and drug use or acquisition behaviors interact to affect opioid-involved overdoses.

Methods

We conducted exploratory and confirmatory factor analysis (EFA/CFA) to identify a factor structure for ten drug acquisition and use behaviors. We then evaluated alternative structural equation models incorporating the identified factors, adding demographic and psychosocial attributes as predictors of past-year opioid overdose. We used interview data collected for two studies recruiting opioid-misusing participants receiving services from a community-based syringe service program. The first investigated current attitudes toward drug-checking (N = 150). The second was an RCT assessing a telehealth versus in-person medical appointment for opioid use disorder treatment referral (N = 270). Demographics included gender, age, race/ethnicity, education, and socioeconomic status. Psychosocial measures were homelessness, psychological distress, and trauma. Self-reported drug-related risk behaviors included using alone, having a new supplier, using opioids with benzodiazepines/alcohol, and preferring fentanyl. Past-year opioid-involved overdoses were dichotomized into experiencing none or any.

Results

The EFA/CFA revealed a two-factor structure with one factor reflecting drug acquisition and the second drug use behaviors. The selected model (CFI = .984, TLI = .981, RMSEA = .024) accounted for 13.1% of overdose probability variance. A latent variable representing psychosocial attributes was indirectly associated with an increase in past-year overdose probability (β=.234, p = .001), as mediated by the EFA/CFA identified latent variables: drug acquisition (β=.683, p < .001) and drug use (β=.567, p = .001). Drug use behaviors (β=.287, p = .04) but not drug acquisition (β=.105, p = .461) also had a significant, positive direct effect on past-year overdose. No demographic attributes were significant direct or indirect overdose predictors.

Conclusions

Psychosocial attributes, particularly homelessness, increase the probability of an overdose through associations with risky drug acquisition and drug-using behaviors. To increase effectiveness, prevention efforts might address the interacting overdose risks that span multiple functional domains.

A genome-wide association, polygenic risk score and sex study on opioid use disorder treatment outcomes

Opioid use disorder continues to be a health concern with a high rate of opioid related deaths occurring worldwide. Medication Assisted Treatments (MAT) have been shown to reduce opioid withdrawal, cravings and opioid use, however variability exists in individual's treatment outcomes. Sex-specific differences have been reported in opioid use patterns, polysubstance use and health and social functioning. Candidate gene studies investigating methadone dose as an outcome have identified several candidate genes and only five genome-wide associations studies have been conducted for MAT outcomes. This study aimed to identify genetic variants associated with MAT outcomes through genome-wide association study (GWAS) and test the association between genetic variants previously associated with methadone dose through a polygenic risk score (PRS). Study outcomes include: continued opioid use, relapse, methadone dose and opioid overdose. No genome-wide significance SNPs or sex-specific results were identified. The PRS identified statistically significant results (p < 0.05) for the outcome of methadone dose (R2 = 3.45 × 10-3). No other PRS was statistically significant. This study provides evidence for association between a PRS and methadone dose. More research on the PRS to increase the variance explained is needed before it can be used as a tool to help identify a suitable methadone dose within this population.

Association between socioeconomic status and treatment in patients with low back or neck pain: a population-based cross-sectional study in South Korea

INTRODUCTION

Socioeconomic status affects the treatment of patients with low back pain and/or neck pain. We examined the relationship between socioeconomic status (occupation and household income level) and treatments such as chronic opioid use and interventional procedures among these patients.

METHODS

Data from the National Health Insurance Service database in South Korea were used in this population-based cross-sectional study. Approximately 2.5% of adult patients diagnosed with low back pain and/or neck pain between 2010 and 2019 were selected using a stratified random sampling technique and included in the analysis.

RESULTS

We analyzed the data of 5,861,007 patients with low back pain and/or neck pain in total. Among them, 4.9% were chronic opioid users and 17.7% underwent interventional procedures. Healthcare workers and unemployed individuals had 18% lower and 6% higher likelihood of chronic opioid use compared with office workers, respectively. Those with a very low household income had 18% higher likelihood of chronic opioid use than those with a poor household income. Other workers and unemployed individuals had 4% and 8% higher likelihood of undergoing interventional procedures than office workers, respectively. Healthcare workers had 5% lower likelihood of undergoing interventional procedures than office workers. Patients with middle, high, and very poor household incomes had a higher likelihood of undergoing interventional procedures, while those in the very high household income group had a lower likelihood of undergoing interventional procedures than those with poor household incomes.

CONCLUSIONS

Socioeconomic status factors are associated with treatment in patients with low back pain and/or neck pain.

Endogenous opiates and behavior: 2021

This paper is the forty-fourth consecutive installment of the annual anthological review of research concerning the endogenous opioid system, summarizing articles published during 2021 that studied the behavioral effects of molecular, pharmacological and genetic manipulation of opioid peptides and receptors as well as effects of opioid/opiate agonizts and antagonists. The review is subdivided into the following specific topics: molecular-biochemical effects and neurochemical localization studies of endogenous opioids and their receptors (1), the roles of these opioid peptides and receptors in pain and analgesia in animals (2) and humans (3), opioid-sensitive and opioid-insensitive effects of nonopioid analgesics (4), opioid peptide and receptor involvement in tolerance and dependence (5), stress and social status (6), learning and memory (7), eating and drinking (8), drug abuse and alcohol (9), sexual activity and hormones, pregnancy, development and endocrinology (10), mental illness and mood (11), seizures and neurologic disorders (12), electrical-related activity and neurophysiology (13), general activity and locomotion (14), gastrointestinal, renal and hepatic functions (15), cardiovascular responses (16), respiration and thermoregulation (17), and immunological responses (18).

Healthcare seeking among Swedish patients in opioid substitution treatment – a mixed methods study on barriers and facilitators

Background

Patients in opioid substitution treatment (OST) have poorer health than the general population. Thus, they do not seek somatic health care to the extent that is medically motivated. Barriers hindering patients from seeking medical help through the conventional healthcare system result in a high degree of unmet healthcare needs. Barriers to, and facilitators of, OST patients’ healthcare seeking have been sparsely examined.

Methods

Mixed methods were employed. The quantitative part consisted of a cross-sectional questionnaire covering questions on physical health, healthcare seeking, and barriers thereof, which was collected from 209 patients in OST. A sub-sample of eleven OST patients participated in semi-structured interviews, for the qualitative part of the study, covering experience of healthcare, lifestyle, and self-images, expectations, and ideals of Swedish healthcare.

Results

Confirmed by qualitative data, quantitative data revealed deprioritization, fear of stigma and of being treated badly, and problems in navigation throughout the healthcare system, leading to unsuccessful establishment of contact, being most common reasons for not seeking somatic healthcare. Thus, interviewees provided a deeper knowledge of the barriers stigma, lack of means to prioritize health and difficulties navigating throughout the healthcare system, leading to resignation and deprioritization. On-site primary healthcare (PHC) seemed to contribute to increased access and utilization of healthcare.

Conclusion

Individual and structural barriers decreasing access to healthcare lead to increased inequalities in healthcare utilization, adding to an already deteriorating health of this ageing population. Integration of on-site primary healthcare and OST could provide acceptable and accessible healthcare.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13011-022-00434-w.

Genome-wide association study in individuals of European and African ancestry and multi-trait analysis of opioid use disorder identifies 19 independent genome-wide significant risk loci

Despite the large toll of opioid use disorder (OUD), genome-wide association studies (GWAS) of OUD to date have yielded few susceptibility loci. We performed a large-scale GWAS of OUD in individuals of European (EUR) and African (AFR) ancestry, optimizing genetic informativeness by performing MTAG (Multi-trait analysis of GWAS) with genetically correlated substance use disorders (SUDs). Meta-analysis included seven cohorts: the Million Veteran Program, Psychiatric Genomics Consortium, iPSYCH, FinnGen, Partners Biobank, BioVU, and Yale-Penn 3, resulting in a total N = 639,063 (Ncases = 20,686;Neffective = 77,026) across ancestries. OUD cases were defined as having a lifetime OUD diagnosis, and controls as anyone not known to meet OUD criteria. We estimated SNP-heritability (h2SNP) and genetic correlations (rg). Based on genetic correlation, we performed MTAG on OUD, alcohol use disorder (AUD), and cannabis use disorder (CanUD). A leave-one-out polygenic risk score (PRS) analysis was performed to compare OUD and OUD-MTAG PRS as predictors of OUD case status in Yale-Penn 3. The EUR meta-analysis identified three genome-wide significant (GWS; p ≤ 5 × 10-8) lead SNPs-one at FURIN (rs11372849; p = 9.54 × 10-10) and two OPRM1 variants (rs1799971, p = 4.92 × 10-09; rs79704991, p = 1.11 × 10-08; r2 = 0.02). Rs1799971 (p = 4.91 × 10-08) and another OPRM1 variant (rs9478500; p = 1.95 × 10-08; r2 = 0.03) were identified in the cross-ancestry meta-analysis. Estimated h2SNP was 12.75%, with strong rg with CanUD (rg = 0.82; p = 1.14 × 10-47) and AUD (rg = 0.77; p = 6.36 × 10-78). The OUD-MTAG resulted in a GWAS Nequivalent = 128,748 and 18 independent GWS loci, some mapping to genes or gene regions that have previously been associated with psychiatric or addiction phenotypes. The OUD-MTAG PRS accounted for 3.81% of OUD variance (beta = 0.61;s.e. = 0.066; p = 2.00 × 10-16) compared to 2.41% (beta = 0.45; s.e. = 0.058; p = 2.90 × 10-13) explained by the OUD PRS. The current study identified OUD variant associations at OPRM1, single variant associations with FURIN, and 18 GWS associations in the OUD-MTAG. The genetic architecture of OUD is likely influenced by both OUD-specific loci and loci shared across SUDs.