Older homeless adults are more likely to utilize inpatient health care as a result of SUDs: older homeless adults visit the Emergency Department for substance use at similar rates as younger homeless adults, but older homeless adults are more likely to be admitted.Older homeless adults with SUDs interact frequently with the health care system, yet there are inadequate numbers of substance use and mental health treatment providers who have the expertise in treating older adults to meet the demand for services.Older substance-using homeless adults will challenge both homeless services and substance use treatment programs, which have traditionally targeted younger adults and may be unprepared to deliver treatment to older adults with co-morbid conditions such as cognitive impairment or ADL difficulties.Many shelters exclude participants with active substance use, requiring sobriety as a condition for entrance.The high prevalence of chronic illness and functional disabilities of older homeless adults will increase the likelihood they will need services from long term care facilities, but some facilities exclude older adults with SUDs or do not have sufficient SUD treatment resources.Providers that provide care to older homeless adults should screen for substance use and follow positive screens with brief interventions and referral to treatment. Long term care facilities that care for homeless clients will need resources for treatment of substance use. Long term care facilities, such as skilled nursing facilities, should reevaluate policies that exclude older adults with substance use given the need for services for this high risk population. Given the shortage of geriatric substance use and mental health providers, policymakers seeking to address substance use in homeless adults will need to provide incentives for expansion of training programs for geriatrics, geriatric psychiatry, and geriatric addiction medicine.

Given the health risks of continued substance use, the low prevalence of treatment of older homeless adults with SUDs,cannabis plant growing and the rising proportion of mortality of older homeless adults attributable to substance use,older homeless adults will benefit from targeted treatment programs and geriatric substance use workforce development. The misuse of opiates is a serious problem worldwide, is increasing in young adults, and has substantial individual and societal consequences. In 2014 in the United States alone, approximately 1.9 million people had an opiate use disorder, including 586,000 heroin users. Neuroimaging in opiate dependence indicates both altered brain structure, particularly in the anterior cingulate cortex , and brain function involving dorsolateral prefrontal cortex and ACC. Magnetic resonance spectroscopy allows the non-invasive quantitation of brain metabolites that provide information on the neurophysiologic integrity of brain tissue. The few 1H MRS studies in opiate dependence to date revealed lower concentration of N-acetylaspartate , a marker of neuronal integrity, in the medial frontal cortex, including the ACC, as well as lower glutamate , a primary excitatory neurotransmitter, or glutamate+glutamine concentration in some but not all studies. The discrepant MRS findings may relate to differences among study participants regarding the prevalence and severity of comorbid substance use , the type, dose and duration of replacement therapy for heroin users , and/or participant age. The ACC, DLPFC and orbitofrontal cortexare important components of the brain reward/executive oversight system, a neural network critically involved in the development and maintenance of addictive disorders. Structural brain imaging in opiate dependence revealed generally lower gray matter volume or density in frontal regions, including the DLPFC, with thinner frontal cortices related to longerduration of opiate misuse. Functional MR imaging showed that the DLPFC, OFC and ACC are involved in decision making, and in opiate dependent individuals, lower task-based fMRI activity in the ACC related to compromised behavioural control of cognitive interference. Furthermore, smaller frontal gray matter volume in opiate dependence related to higher impulsivity on the Barratt Impulsivity Scale .

Correspondingly, opiate dependence is associated with cognitive deficits, primarily in executive functioning and self-regulation . Thus, the neuroimaging literature in opiate dependence suggests altered frontal brain structure as well as compromised neuronal integrity and glutamatergic metabolism. Few if any studies however investigated their relationships to opioid and other substance use behaviour or cognition. Further research into specific regional brain effects and their potential cognitive and behavioural correlates may inform better targeted treatment of individuals with opioid use disorders. We measured in opiate dependent individuals’ metabolite concentrations from the ACC and previously unexplored DLPFC and OFC and related them to quantitative measures of neurocognition, self-regulation, and substance use. Specifically, we compared opiate dependent individuals on buprenorphine maintenance to controls . We also included another control group, a substance-dependent ‘control’ group of 3 week abstinent alcohol dependent individuals , a commonly investigated treatment-seeking group to differentiate opiate dependence from not only control individuals but also individuals with a substance dependence . Our primary hypotheses were that:OD have lower NAA and Glu concentrations than CON in ACC, DLPFC, and OFC,these frontal cortical NAA and Glu deficits are associated with the level of opiate use and cigarette-smoking severity,the frontal NAA and Glu deficits in OD relate to higher impulsivity, poorer executive function, and lower decision making skills, and OD have more pronounced metabolite concentration deficits than ALC. The results of this study will contribute to a better understanding of the neurobiology and neuropsychology in OD, helping to identify novel targets for the treatment of opiate dependence. All participants provided informed consent according to the Declaration of Helsinki and underwent procedures approved by the University of California, San Francisco and San Francisco VA Medical Center00000068. Twenty-one chronic cigarette smoking OD, stable on buprenorphine maintenance therapy for at least 3 months, met DSM-IV criteria for dependence on opiates; they were allowed to meet DSMIV criteria for current abuse or dependence on cocaine, amphetamines, and/or cannabis, but dependence on alcohol or benzodiazepines was exclusionary.

OD was part of a buprenorphine treatment program focusing on smoking cessation and they were studied before smoking cessation. For group comparisons of metabolite concentrations specifically in the ACC, DLPFC, and POC and when correlated with neuropsychological variables, there were data from thirty-five cigarette smoking ALC recruited from local treatment programs of the VA and Kaiser Permanente and 28 cigarette smoking CON recruited from the community. The ALC group met DSM-IV criteria for alcohol dependence and was abstinent from alcohol for 21 ± 11 days at time of study. For group comparisons of metabolite concentrations in the OFC and when correlated with neuropsychological variables , smokers and non-smokers were included in the ALC and CON groups: 21 ALC and 19 CONdue to a lack of sufficient data in smokers. All participants were studied with structural MRI, 1H MRS, and neuropsychological testing,cannabis drying racks all were fluent in English and they were allowed to smoke ad libitum before assessment and during breaks. Table 1 contains demographics, tobacco and alcohol use variables, mood measures, and laboratory variables for the three groups. Further exclusion criteria for ALC and CON are described elsewhere. In brief, ALC and CON participants were excluded for neurological disorders , psychiatric disorders , and medical and vascular risk factors , known to affect neurobiology or cognition as well as for MRI contraindications. In OD and ALC, hepatitis C, type-2 diabetes, hypertension, unipolar mood disorder, or generalized anxiety disorders were not exclusionary due to their high prevalence in addiction. Six OD, 4 ALC and 1 CON had hepatitis C , while 4 OD and 13 ALC had medically-controlled hypertension. All OD were on buprenorphine maintenance therapy averaging 15 ± 9 mg/day. Table 2 depicts their recent and lifetime substance use histories. Overall, OD as a group were all cigarette smokers and had comorbid stimulant and marijuana use over lifetime, which they reduced during the year before study. Only a few OD individuals had drug use within the last 30 days: 3 used opiates and/or cocaine but only 1 used opiates for 20 days, 1 other OD used amphetamines daily, and about one-third of the sample used marijuana. The majority of OD individuals were moderate alcohol drinkers over their lifetime, but they reduced their alcohol consumption during the last year before study; only 3 had consumed alcohol on more than 10 days within the last 30 days. The ALC group for the ACC, DLPFC, and POC VOI analyses were cigarette smokers abstinent from alcohol for about 3 weeks and used other drugs occasionally . Thus, the ALC group for the majority of the analyses and the entire OD group were cigarette-smoking treatment seekers, abstinent from their main drug of abuse for several weeks and they had similarly low levels of drug use within the last month before study.OD and ALC completed the Structured Clinical Interview for DSM-IV Axis I disorders Patient Edition, v2.0, CON were administered the corresponding screening module. The clinical and neurocognitive assessments of ALC and CON are detailed elsewhere. In all groups, alcohol consumption was estimated with the lifetime drinking history interview, nicotine dependence was assessed with the Fager strom Tolerance Test for Nicotine Dependence, and lifetime substance use history was assessed with an in-house questionnaire.

A neurocognitive battery assessed the major domains affected by opioid and alcohol use disorders and Z-scores were calculated based on corresponding normative data. Cognitive domains were formed from specific neurocognitive tasks . The cognitive domain scores in ALC and CON were calculated according to the shortened neurocognitive battery of tests administered to the OD group and therefore, the constituent measures for cognitive domains in this study are different from our previous publications. All participants completed self-regulation measures, which included the BIS to assess self reported impulsivity, the Balloon Analogue Risk Task to assess risk taking, and the Iowa Gambling Task to assess decision making. Laboratory tests within 2–3 days of the MR scan evaluated the nutritional status and alcohol-related or other hepatocellular injury in OD and ALC. See Table 1 for laboratory variables, cognitive domain and self-regulation measures for the three groups. Univariate analyses of covariance tested for group differences on demographic and clinical variables. All statistical analyses were performed with SPSS version 22. Separate ANCOVAs were performed for the four VOIs and each metabolite, followed by planned pairwise comparisons to test for group differences in metabolite concentrations between OD, ALC and CON. Given the participants’ wide age range and as age correlates with metabolite concentrations , age was used as a covariate in group comparisons. As GM, WM, and CSF contributions to the VOIs affect brain metabolite levels and as tissue content in ACC and OFC VOIs differed between groups , we included these variables as predictors in the ANCOVAs. Each a priori hypothesis was tested with an alpha level of 0.05. In pairwise group comparisons of metabolite levels without a specific a priori hypothesis, we used corrected alpha levels to account for the multiplicity of metabolites in each VOI via a modified Bonferroni procedure, which yielded adjusted alpha levels for each VOI separately by using the number of metabolites under investigation and their average inter-correlation coefficients . OFC spectra often did not have a well-defined mI resonance and therefore, OFC mI was not analysed. Effect sizes were calculated via Cohen’s d. Correlations between outcome measures were corrected for age , except for correlations with cognitive domains , and reported as Pearson coefficients. Age and years of education did not differ between OD and CON . ALC were equivalent on age to OD and CON, but had fewer years of education. OD had lower hemoglobin and hematocrit than both CON and ALC. There were no significant differences in blood tests of liver function in individuals with and without Hepatitis C within the ALC group and also within the OD group. In addition, none of the individuals with Hepatitis C were taking medications at the time of study for Hepatitis C. Furthermore, the individuals taking hypertension medication did have controlled blood pressure by self report but blood pressure levels at time of study were not measured. Nicotine dependence scores were higher in OD than ALC; OD and CON also smoked significantly more cigarettes per day than ALC, but all groups were equivalent on cigarette smoking duration. Gender did not contribute to any group difference or correlation. See Table 1 for drinking severity measures in OD, CON and ALC. This study compared cortical metabolite concentrations, neurocognition, and self-regulation between cigarette-smoking opiate dependent individuals on buprenorphine maintenance therapy, treatment-seeking alcohol dependent smokers, and smoking controls.