A comparison of 2013 and 2017 baseline characteristics among treatment-seeking patients who used opioids with co-occurring disorders

Spatial associations between alcohol detection in opioid overdose deaths and alcohol outlets

BACKGROUND

Alcohol enhances the depressant effect of opioids on the central nervous system, increasing overdose risk and mortality. The built environment influences substance use patterns and overdose risk. Little research has explored the impact of alcohol outlets on opioid overdose death.

METHODS

We calculated the distance between the location of each fatal overdose event in Connecticut in 2019 and 2020 and the nearest alcohol outlet, similarly calculating the distance between each decedent's residence and the nearest alcohol outlet. We also calculated the density of alcohol outlets and number of ethanoldetected opioid overdose deaths in each census tract. We used regression models to determine how the spatial distribution of alcohol outlets at the individual and ecological levels related to ethanol detection in opioid overdose deaths. We conducted sensitivity analyses limiting our sample to off-premise alcohol outlets (e.g., package stores, supermarkets).

RESULTS

Ethanol was detected in one-third (33.6 %) of all opioid overdose deaths. Alcohol outlet proximity was associated with increased odds of ethanol detection in opioid overdose death; this association did not remain significant after controlling for age and sex. Alcohol outlet density was positively associated with the number ethanol-detected opioid overdose deaths at the census tract level even after controlling for social vulnerability. This association remained significant when analysis was limited to off-premise alcohol outlets.

CONCLUSION

These findings highlight the importance of incorporating alcohol outlets into overdose education and naloxone distribution efforts as well as the critical role of community investment.

Increases in primary opioid use disorder diagnoses co-occurring with anxiety or depressive disorder diagnoses in mental health treatment in the United States, 2015-2019

BACKGROUND

Opioid use disorders (OUDs) often co-occur with anxiety and depressive disorders. While the proportion of mental health (MH) treatment facilities providing substance use treatment has increased, the proportion of these facilities able to simultaneously treat MH and substance use decreased. This warrants investigation into the integrated treatment needs of persons with a primary OUD diagnosis treated in MH treatment facilities.

METHODS

Using the Mental Health Client Level Data, we examined a sample of N = 83,975 adults with OUD as their primary diagnosis who received treatment from a MH treatment facility in the United States from 2015 to 2019. Joinpoint regression was used to examine annual trends of the number of individuals with co-occurring anxiety or depression diagnoses.

RESULTS

Most of the sample were men (53.7%) and received treatment in a community-based program (93.3%). Approximately 17% of the sample had either an anxiety or depressive disorder diagnosis. Approximately 9% of our sample had an anxiety disorder diagnosis, and 10% had a depressive disorder diagnosis. An increase in the number of individuals with a co-occurring anxiety disorder diagnosis from 2015 to 2019 was identified (annual percent change (APC) = 61.4; 95% confidence interval (CI) = [10.0, 136.9]; p =.029). An increase in the number of individuals with a co-occurring depressive disorder diagnosis from 2015 to 2019 was identified (APC = 39.0; 95% CI = [7.4; 79.9]; p =.027).

CONCLUSIONS

This study highlights increases in adults receiving MH treatment for OUD having co-occurring anxiety or depression diagnoses, furthering the importance of integrated dual disorder treatment.

Substance use disorders and social determinants of health from electronic medical records obtained during Kentucky's "triple wave"

Social determinants of health (SDOH) play a critical role in the risk of harmful drug use. Examining SDOH as a means of differentiating populations with multiple co-occurring substance use disorders (SUDs) is particularly salient in the era of prevalent opioid and stimulant use known as the "Third Wave". This study uses electronic medical records (EMRs) from a safety net hospital system from 14,032 patients in Kentucky from 2017 to 2019 in order to 1) define three types of SUD cohorts with shared/unique risk factors, 2) identify patients with unstable housing using novel methods for EMRs and 3) link patients to their residential neighborhood to obtain quantitative perspective on social vulnerability. We identified patients in three cohorts with statistically significant unique risk factors that included race, biological sex, insurance type, smoking status, and urban/rural residential location. Adjusting for these variables, we found a statistically significant, increasing risk gradient for patients experiencing unstable housing by cohort type: opioid-only (n = 7385, reference), stimulant-only (n = 4794, odds ratio (aOR) 1.86 95 % confidence interval (CI): 1.66-2.09), and co-diagnosed (n = 1853, aOR = 2.75, 95 % CI: 2.39 to 3.16). At the neighborhood-level, we used 8 different measures of social vulnerability and found that, for the most part, increasing proportions of patients with stimulant use living in a census tract was associated with more social vulnerability. Our study identifies potentially modifiable factors that can be tailored by substance type and demonstrates robust use of EMRs to meet national goals of enhancing research on social determinants of health.

Exploring Differences in Baseline Characteristics among Adults Entering Integrated Residential Treatment for Co-occurring Disorders in 2013 and 2017

Little is known about patients' addiction severity, substance use, or mental health symptoms upon entering integrated treatment. This is the first study to compare baseline characteristics among cohorts of patients with co-occurring disorders entering a private integrated residential treatment program in 2013 and 2017; a period when severe and persistent mental illness diagnoses, mental health service use, and overdose deaths increased. Our sample includes 3400 patients entering private, integrated residential treatment during 2013 (n = 1535) and 2017 (n = 1865). Trained staff completed admission interviews of all participants that included the Addiction Severity Index (ASI), a semi-structured interview to evaluate the past 30-day functioning of the following domains: medical, employment, alcohol, drug, legal, family or social support systems, and psychiatric. We used a p-value of 0.05 to assess significance. With the exception of the drug composite score, the 2017 cohort scored higher than the 2013 cohort on all other composite scores. Compared to the 2013 cohort, the 2017 cohort reported more days using alcohol, cocaine, amphetamines, and engaging in polysubstance use. Conversely, the 2017 cohort reported fewer days using other prescription opioids and sedatives than the 2013 cohort. After controlling for age, the 2017 cohort reported more days of marijuana use than the 2013 cohort. The 2017 cohort reported higher rates of the following symptoms: depression, anxiety, hallucinations, and suicidal ideation. Findings underscore differences among integrated treatment patient cohorts for baseline addiction severity, substance use, or mental health symptoms.

Identifying the Physical and Mental Healthcare Needs of Opioid Treatment Program Clients

Background: Individuals with opioid use disorder (OUD) often have significant medical and behavioral health needs that are unaddressed. Opioid treatment programs (OTP) are uniquely positioned to provide integrated services for OUD, physical and mental health but are underutilized for this purpose. This study aims to describe the physical and mental healthcare needs of OTP clients in order to inform integrated care implementation in OTPs. Method: OTP clients (n = 1261) in an integrated care program in the Bronx borough of New York City were assessed for mental health symptoms (e.g., anxiety, depression), chronic disease indicators (e.g., blood pressure, cholesterol), and general functioning (e.g., capability of managing healthcare needs). Results: Symptoms of anxiety, post-traumatic stress, and depression were common. Self-reported health status and level of functioning were generally poor. Heavy smoking and obesity were the most frequent physical health risks. Other chronic disease indicators (e.g., blood pressure) showed 25-46% may be at risk. Sixty percent had multiple mental health risks and 85% had multiple physical health risks. Older clients had a higher rate of hypertension and diabetes risk than younger clients. Conclusions: Integrated care programs in OTPs must be prepared to address and coordinate care for chronic mental and physical health conditions in addition to OUD.

Dynamics of Parental Opioid Use and Children's Health and Well-Being: An Integrative Systems Mapping Approach

The seemingly intractable opioid epidemic compels researchers, the media, and families to better understand the causes and effects of this complex and evolving public health crisis. The effects of this crisis on people using opioids, maternal prenatal opioid exposure, and neonatal abstinence syndrome are well-documented, but less is known about the impact of caregivers' opioid use on children's health and well-being. One challenge to understanding the effects of parental opioid use disorder (OUD) on child and adolescent outcomes is the numerous interrelated pathways in which a child's health and well-being can be impacted. To better understand these dynamic relationships, we applied a systems mapping approach to visualize complex patterns and interactions between pathways and potential leverage points for interventions. Specifically, we developed a causal loop diagram system map to elucidate the complex and interconnected relationships between parental OUD, social determinants of health at the family and socio-environmental levels, family strengths, social supports, and possible adverse impacts on children's physical and mental health and risks for future substance misuse. The goals of this research are to (1) identify factors and dynamics that contribute to the relationship between parental OUD and children's health and well-being and (2) illustrate how systems mapping as a tool can aid in understanding the complex factors and dynamics of the system(s) that influence the well-being of children and their parents or primary caregivers.

A comprehensive multivariate model of biopsychosocial factors associated with opioid misuse and use disorder in a 2017-2018 United States national survey

BACKGROUND

Few studies have comprehensively and contextually examined the relationship of variables associated with opioid use. Our purpose was to fill a critical gap in comprehensive risk models of opioid misuse and use disorder in the United States by identifying the most salient predictors.

METHODS

A multivariate logistic regression was used on the 2017 and 2018 National Survey on Drug Use and Health, which included all 50 states and the District of Columbia of the United States. The sample included all noninstitutionalized civilian adults aged 18 and older (N = 85,580; weighted N = 248,008,986). The outcome of opioid misuse and/or use disorder was based on reported prescription pain reliever and/or heroin use dependence, abuse, or misuse. Biopsychosocial predictors of opioid misuse and use disorder in addition to sociodemographic characteristics and other substance dependence or abuse were examined in our comprehensive model. Biopsychosocial characteristics included socioecological and health indicators. Criminality was the socioecological indicator. Health indicators included self-reported health, private health insurance, psychological distress, and suicidality. Sociodemographic variables included age, sex/gender, race/ethnicity, sexual identity, education, residence, income, and employment status. Substance dependence or abuse included both licit and illicit substances (i.e., nicotine, alcohol, marijuana, cocaine, inhalants, methamphetamine, tranquilizers, stimulants, sedatives).

RESULTS

The comprehensive model found that criminality (adjusted odds ratio [AOR] = 2.58, 95% confidence interval [CI] = 1.98-3.37, p < 0.001), self-reported health (i.e., excellent compared to fair/poor [AOR = 3.71, 95% CI = 2.19-6.29, p < 0.001], good [AOR = 3.43, 95% CI = 2.20-5.34, p < 0.001], and very good [AOR = 2.75, 95% CI = 1.90-3.98, p < 0.001]), no private health insurance (AOR = 2.12, 95% CI = 1.55-2.89, p < 0.001), serious psychological distress (AOR = 2.12, 95% CI = 1.55-2.89, p < 0.001), suicidality (AOR = 1.58, 95% CI = 1.17-2.14, p = 0.004), and other substance dependence or abuse were significant predictors of opioid misuse and/or use disorder. Substances associated were nicotine (AOR = 3.01, 95% CI = 2.30-3.93, p < 0.001), alcohol (AOR = 1.40, 95% CI = 1.02-1.92, p = 0.038), marijuana (AOR = 2.24, 95% CI = 1.40-3.58, p = 0.001), cocaine (AOR = 3.92, 95% CI = 2.14-7.17, p < 0.001), methamphetamine (AOR = 3.32, 95% CI = 1.96-5.64, p < 0.001), tranquilizers (AOR = 16.72, 95% CI = 9.75-28.65, p < 0.001), and stimulants (AOR = 2.45, 95% CI = 1.03-5.87, p = 0.044).

CONCLUSIONS

Biopsychosocial characteristics such as socioecological and health indicators, as well as other substance dependence or abuse were stronger predictors of opioid misuse and use disorder than sociodemographic characteristics.

Assessment of Co-Occurring Substance Use During Opiate Treatment Programs in the United States

The effectiveness of opiate treatment programs (OTPs) can be significantly influenced by co-occurring substance use, yet there are no standardized guidelines for assessing the influence of co-occurring substance use on treatment outcomes. In this review, we aim to provide an overview on the status of the assessment of co-occurring substance use during participation in OTPs in the United States. We searched 4 databases-MEDLINE/PubMed, EMBASE, PsychINFO, and the Cumulative Index to Nursing and Allied Health Literature (CINAHL)-from database inception to November 2018 to select relevant publications on OTPs that assessed participants' co-occurring substance use. We used a standardized protocol to extract study, intervention, and co-occurring substance use characteristics. Methodological quality was assessed using the Quality in Prognosis Studies tool. Of the 3,219 titles screened, 614 abstracts and 191 full-text original publications were assessed, leaving 85 eligible articles. Co-occurring substance use was most often assessed during opioid treatments using combined (pharmacological and behavioral) (n = 57 studies) and pharmacological (n = 25 studies) interventions. Cocaine, alcohol, marijuana, and benzodiazepines were frequently measured, while amphetamines and tobacco were rarely assessed. Great variation existed between studies in the timing and measurement of co-occurring substance use, as well as definitions for substances and polysubstance/polydrug use. Inconsistencies in the investigation of co-occurring substance use make comparison of results across studies challenging. Standardized measures and consensus on research on co-occurring substance use is needed to produce the evidence required to develop personalized treatment programs for persons using multiple substances and to inform best-practice guidelines for addressing polydrug use during participation in OTPs.