Carlos Blanco

Cannabis Use and Risk of Psychiatric Disorders: Prospective Evidence From a US National Longitudinal Study

IMPORTANCEnWith rising rates of marijuana use in the general population and an increasing number of states legalizing recreational marijuana use and authorizing medical marijuana programs, there are renewed clinical and policy concerns regarding the mental health effects of cannabis use.nnnOBJECTIVEnTo examine prospective associations between cannabis use and risk of mental health and substance use disorders in the general adult population.nnnDESIGN, SETTING, AND PARTICIPANTSnA nationally representative sample of US adults aged 18 years or older was interviewed 3 years apart in the National Epidemiologic Survey on Alcohol and Related Conditions (wave 1, 2001-2002; wave 2, 2004-2005). The primary analyses were limited to 34u202f653 respondents who were interviewed in both waves. Data analysis was conducted from March 15 to November 30, 2015.nnnMAIN OUTCOMES AND MEASURESnWe used multiple regression and propensity score matching to estimate the strength of independent associations between cannabis use at wave 1 and incident and prevalent psychiatric disorders at wave 2. Psychiatric disorders were measured with a structured interview (Alcohol Use Disorder and Associated Disabilities Interview Schedule-DSM-IV). In both analyses, the same set of wave 1 confounders was used, including sociodemographic characteristics, family history of substance use disorder, disturbed family environment, childhood parental loss, low self-esteem, social deviance, education, recent trauma, past and present psychiatric disorders, and respondents history of divorce.nnnRESULTSnIn the multiple regression analysis of 34u202f653 respondents (14u202f564 male [47.9% weighted]; mean [SD] age, 45.1 [17.3] years), cannabis use in wave 1 (2001-2002), which was reported by 1279 respondents, was significantly associated with substance use disorders in wave 2 (2004-2005) (any substance use disorder: odds ratio [OR], 6.2; 95% CI, 4.1-9.4; any alcohol use disorder: OR, 2.7; 95% CI, 1.9-3.8; any cannabis use disorder: OR, 9.5; 95% CI, 6.4-14.1; any other drug use disorder: OR, 2.6; 95% CI, 1.6-4.4; and nicotine dependence: OR, 1.7; 95% CI, 1.2-2.4), but not any mood disorder (OR, 1.1; 95% CI, 0.8-1.4) or anxiety disorder (OR, 0.9; 95% CI, 0.7-1.1). The same general pattern of results was observed in the multiple regression analyses of wave 2 prevalent psychiatric disorders and in the propensity score-matched analysis of incident and prevalent psychiatric disorders.nnnCONCLUSIONS AND RELEVANCEnWithin the general population, cannabis use is associated with an increased risk for several substance use disorders. Physicians and policy makers should take these associations of cannabis use under careful consideration.

Prescription Opioid Use, Misuse, and Use Disorders in U.S. Adults: 2015 National Survey on Drug Use and Health

The United States is experiencing an epidemic of prescription opioid misuse, with prescription opioid overdose deaths more than quadrupling between 1999 and 2015 (14). Misuse is defined as use of a psychotropic medication without a prescription; for a reason other than as directed by a physician; or in greater amounts, more often, or longer than prescribed. The potential for misuse complicates prescription of opioids (5, 6). Several studies based on local data (711) or national samples of high school seniors (12, 13) have examined motivations for medication misuse. However, an examination of the prevalence of prescription opioid use, misuse, and use disorders and motivations for misuse in the U.S. adult population has been lacking. Such data could inform efforts to reduce prescription opioid misuse and related morbidity and mortality. Based on a nationally representative sample of U.S. adults, this study examined the 12-month prevalence of prescription opioid use by sociodemographic characteristics, health conditions, and behavioral health status; the prevalence of misuse and use disorders among prescription opioid users by sociodemographic characteristics, health conditions, and behavioral health status; motivations for misuse; and sources of prescription opioids among adults with misuse and use disorders. Methods Survey Methods and Study Population The 2015 National Survey on Drug Use and Health (NSDUH) was a face-to-face household interview survey conducted by the Substance Abuse and Mental Health Services Administration (SAMHSA). The NSDUH used a stratified, multistage area probability sample that was designed to be representative of the nation as a whole as well as each of the 50 states and the District of Columbia. Under a stratified design, with states serving as the primary strata and state sampling regions serving as the secondary strata, census tracts, census block groups, segments within census block groups, and dwelling units within segments were selected using probability-proportional-to-size sampling. After dwelling units were selected, an interviewer visited each unit to obtain a roster of all persons residing there. The roster information obtained from an eligible member of the dwelling unit was used to select 0 to 2 people for the survey. Data collection for NSDUH was approved by the Institutional Review Board at RTI International. Data were collected by interviewers in personal visits to households and noninstitutional group quarters. Each participant provided verbal informed consent. The interview lasted about an hour, and each respondent received

Marijuana use and use disorders in adults in the USA, 2002–14: analysis of annual cross-sectional surveys

30 in cash after completion (14). The NSDUH collected nationally representative data on prescription opioid use, misuse, and use disorders and motivations for misuse among the U.S. civilian, noninstitutionalized population aged 12 years or older (14). Additional details about the NSDUH survey methods and questionnaire are available at SAMHSAs Web site (14). The NSDUH collected data using audio computer-assisted self-interviewing, in which respondents read or listened to the questions on headphones and then entered their answers directly into a laptop computer. This interview technique is designed for accurate reporting of information by providing respondents with a private, confidential way to record answers to sensitive questions. The NSDUH also used computer-assisted personal interviewing, in which interviewers read less sensitive questions to respondents and entered answers into the laptop computer. In 2015, the NSDUH screening process (in which an interviewer visited each selected dwelling unit to obtain a roster of all persons residing there) was completed at 132210 addresses, and the weighted screening response rate was 79.7%, which was not specific to age groups (14). The weighted interview response rate was 68.4% for adults, based on the definitions of the American Association for Public Opinion Research (15). A total of 72600 eligible persons aged 18 years or older were selected for the 2015 NSDUH, and 51200 completed the survey interview. Measures of Main Outcomes and Patient Characteristics The 2015 NSDUH asked about lifetime and past-year use and misuse of prescription opioids. The NSDUH defined prescription opioid misuse as in any way that a doctor did not direct you to use them, including 1) use without a prescription of your own; 2) use in greater amounts, more often, or longer than you were told to take them; or 3) use in any other way a doctor did not direct you to use them (16). Past-year prescription opioid use disorder was defined on the basis of the 11 diagnostic criteria for prescription opioid dependence or abuse specified in the Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition (DSM-IV), including withdrawal; tolerance; use in dangerous situations; trouble with the law; and interference with major obligations at work, school, or home (17). For respondents who reported prescription opioid misuse in the past year, NSDUH asked about the main motivation for the most recent episode with multiple-choice questions that offered the following options: to relieve physical pain, to relax or relieve tension, to experiment or see what the drug was like, to feel good or get high, to help with sleep, to help with feelings or emotions, to increase or decrease the effects of other drugs, because the respondent was hooked or had to have it, or other reason (16). The source of prescription opioids for the most recent episode of misuse was assessed with a multiple-choice question that offered the following options: obtained from a friend or relative for free; prescribed by a physician; stolen from a friend or relative; bought from a friend or relative; bought from a drug dealer or stranger; or stolen from a physicians office, clinic, or pharmacy. If respondents reported that they obtained the prescription opioids from a friend or relative for free, NSDUH asked them where the friend or relative had obtained the opioids. In addition to sociodemographic characteristics (age, sex, race/ethnicity, educational attainment, employment status, family income, marital status, health insurance, metropolitan statistical area, and census region), NSDUH asked respondents about lifetime and past-year use of tobacco, alcohol, cannabis, cocaine, heroin, hallucinogens, and inhalants as well as lifetime and past-year use and misuse of prescription sedatives, tranquilizers, and stimulants. Using survey items assessing DSM-IV diagnostic criteria, the NSDUH estimated prevalence in the past 12 months of major depressive episode and substance use disorders (alcohol, cannabis, cocaine, heroin, hallucinogens, inhalants, prescription tranquilizers or sedatives, and prescription stimulants) in addition to prescription opioid use disorders (17). Nicotine dependence among cigarette smokers was assessed using the Nicotine Dependence Syndrome Scale (18). These measures of substance use and use disorders have demonstrated good validity and reliability (1921). For example, the 2006 NSDUH Reliability Study reported that the coefficient (a standard measure of testretest agreement) was 0.73 for prescription opioid misuse and 0.62 for illicit drug use disorders, suggesting good to excellent reliability (21). Furthermore, a clinical validation study reported sensitivity of 0.85 and specificity of 0.75 for illicit drug use disorders (including prescription opioid use disorder) (20). Finally, the survey asked about medical diagnoses received from a physician or other health care professional (hypertension, heart disease, diabetes mellitus, chronic obstructive pulmonary disease, asthma, cancer, HIV/AIDS, hepatitis B or C, cirrhosis, and kidney disease), respondents self-rated health, and the number of emergency department visits in the prior year. Among the 2015 NSDUH adult participants, item response rates were high (for example, >99% for the prescription opioid misuse and use disorder variables). Furthermore, missing values are imputed in NSDUH using predictive mean neighborhoods (22, 23), a combination of a model-assisted imputation method and a random nearest-neighbor hot-deck procedure. For prescription opioid use, misuse, and use disorders (the main variables of this study), a modified version of predictive mean neighborhoods was used to cycle through a group of variables being imputed as a set (23). Statistical Analysis We estimated the national 12-month prevalence of prescription opioid use overall and by sociodemographic, health, and behavioral health characteristics. Next, among adults with prescription opioid use in the past 12 months, we estimated the national 12-month prevalence of prescription opioid misuse and use disorders overall and by sociodemographic, health, and behavioral health characteristics. Finally, we assessed the main motivations and the sources of prescription opioids for the most recent episode of misuse. We used SUDAAN software (RTI International) (24) to account for the complex sample design and sample weights of NSDUH. The NSDUH weighting procedures adjusted for nonresponse through direct adjustments as well as an indirect adjustment via poststratification (25). Institutional Review Board Approval The NSDUH data collection protocol was approved by the U.S. Office of Management and Budget and the Institutional Review Board at RTI International. Role of the Funding Source The funding sources supported the authors, who were responsible for preparation, review, and approval of the manuscript and the decision to submit the manuscript for publication. The funding sources had no role in the design and conduct of the study, analysis and interpretation of the data, preparation and review of the manuscript, or the decision to submit the manuscript for publication. The funding sources reviewed and approved the manuscript. Results National Prevalence of Prescription Opioid Use, Misuse, and Use Disorders On the basis of the 51200 adult respo

Treatment of Adult Depression in the United States

BACKGROUNDnThe study of marijuana use disorders is urgently needed because of increasing marijuana legalisation in multiple jurisdictions, the effect of marijuana use on future risk of psychiatric disorders, and deleterious effects of marijuana exposure. Thus, understanding trends of marijuana use and use disorders and examining factors that might drive these trends (eg, perceptions of harms from marijuana use) is essential.nnnMETHODSnWe analysed data from US civilians aged 18 years or older who participated in annual, cross-sectional US National Surveys on Drug Use and Health from 2002 to 2014. The sample in each US state was designed to be approximately equally distributed between participants aged 12-17 years, 18-25 years, and 26 years or older. For each survey year, we estimated prevalence of marijuana use and use disorders, initiation of marijuana use, daily or near daily use, perception of great or no risk of harm from smoking marijuana, perception of state legalisation of medical marijuana use, and mean number of days of marijuana use in the previous year. Descriptive analyses, multivariable logistic regressions, and zero-truncated negative binomial regressions were applied.nnnFINDINGSn596u2008500 adults participated in the 2002-14 surveys. Marijuana use increased from 10·4% (95% CI 9·97-10·82) to 13·3% (12·84-13·70) in adults in the USA from 2002 to 2014 (β=0·0252, p<0·0001), and the prevalence of perceiving great risk of harm from smoking marijuana once or twice a week decreased from 50·4% (49·60-51·25) to 33·3% (32·64-33·96; β=-0·0625, p<0·0001). Changes in marijuana use and risk perception generally began in 2006-07. After adjusting for all covariates, changes in risk perceptions were associated with changes in prevalence of marijuana use, as seen in the lower prevalence of marijuana use each year during 2006-14 than in 2002 when perceiving risk of harm from smoking marijuana was included in models. However, marijuana use disorders in adults remained stable at about 1·5% between 2002 and 2014 (β=-0·0042, p=0·22).nnnINTERPRETATIONnPrevalence and frequency of marijuana use increased in adults in the USA starting in approximately 2007 and showing significantly higher results in multivariable models during 2011-14 (compared with 2002). The associations between increases in marijuana use and decreases in perceiving great risk of harm from smoking marijuana suggest the need for education regarding the risk of smoking marijuana and prevention messages.nnnFUNDINGnNone.

Use of Marijuana for Medical Purposes Among Adults in the United States

ImportancenDespite recent increased use of antidepressants in the United States, concerns persist that many adults with depression do not receive treatment, whereas others receive treatments that do not match their level of illness severity.nnnObjectivenTo characterize the treatment of adult depression in the United States.nnnDesign, Setting, and ParticipantsnAnalysis of screen-positive depression, psychological distress, and depression treatment data from 46u202f417 responses to the Medical Expenditure Panel Surveys taken in US households by participants aged 18 years or older in 2012 and 2013.nnnMain Outcome and MeasuresnPercentages of adults with screen-positive depression (Patient Health Questionnaire-2 score of ≥u20093) and adjusted odds ratios (AORs) of the effects of sociodemographic characteristics on odds of screen-positive depression; percentages with treatment for screen-positive depression and AORs; percentages with any treatment of depression and AORs stratified by presence of serious psychological distress (Kessler 6 scale score of ≥13); and percentages with depression treatment by health care professional group (psychiatrists, other health care professionals, and general medical providers); and type of depression treatment (antidepressants, psychotherapy, and both) all stratified by distress level.nnnResultsnApproximately 8.4% (95% CI, 7.9-8.8) of adults screened positive for depression, of which 28.7% received any depression treatment. Conversely, among all adults treated for depression, 29.9% had screen-positive depression and 21.8% had serious psychological distress. Adults with serious compared with less serious psychological distress who were treated for depression were more likely to receive care from psychiatrists (33.4% vs 17.3%, Pu2009<u2009.001) or other mental health specialists (16.2% vs 9.6%, Pu2009<u2009.001), and less likely to receive depression care exclusively from general medical professionals (59.0% vs 74.4%, Pu2009<u2009.001). They were also more likely to receive psychotherapy (32.5% vs 20.6%, Pu2009<u2009.001), though not antidepressant medications (81.1% vs 88.6%, Pu2009<u2009.001).nnnConclusions and RelevancenMost US adults who screen positive for depression did not receive treatment for depression, whereas most who were treated did not screen positive. In light of these findings, it is important to strengthen efforts to align depression care with each patients clinical needs.

Short-term Suicide Risk After Psychiatric Hospital Discharge

Use of Marijuana for Medical Purposes Among Adults in the United States By 2014, 23 states and the District of Columbia had legalized medical marijuana use, suggesting a need for information about national rates of marijuana use for medical purposes.1 Although 17% of past-year marijuana users reported use for medical purposes in states with medical marijuana legalization,2 physic ians might recommend medical marijuana use to patients regardless of their residing states.3 Therefore, we examined differences between medical and nonmedical marijuana users across all US states.

Epidemiology of DSM-5 bipolar I disorder: Results from the National Epidemiologic Survey on Alcohol and Related Conditions – III

ImportancenAlthough psychiatric inpatients are recognized to be at increased risk for suicide immediately after hospital discharge, little is known about the extent to which their short-term suicide risk varies across groups with major psychiatric disorders.nnnObjectivenTo describe the risk for suicide during the 90 days after hospital discharge for adults with first-listed diagnoses of depressive disorder, bipolar disorder, schizophrenia, substance use disorder, and other mental disorders in relation to inpatients with diagnoses of nonmental disorders and the general population.nnnDesign, Setting, and ParticipantsnThis national retrospective longitudinal cohort included inpatients aged 18 to 64 years in the Medicaid program who were discharged with a first-listed diagnosis of a mental disorder (depressive disorder, bipolar disorder, schizophrenia, substance use disorder, and other mental disorder) and a 10% random sample of inpatients with diagnoses of nonmental disorders. The cohort included 770u202f643 adults in the mental disorder cohort, 1u202f090u202f551 adults in the nonmental disorder cohort, and 370 deaths from suicide from January 1, 2001, to December 31, 2007. Data were analyzed from March 5, 2015, to June 6, 2016.nnnMain Outcomes and MeasuresnSuicide rates per 100u202f000 person-years were determined for each study group during the 90 days after hospital discharge and the demographically matched US general population. Adjusted hazard ratios (ARHs) of short-term suicide after hospital discharge were also estimated by Cox proportional hazards regression models. Information on suicide as a cause of death was obtained from the National Death Index.nnnResultsnIn the overall population of 1u202f861u202f194 adults (27% men; 73% women; mean [SD] age, 35.4 [13.1] years), suicide rates for the cohorts with depressive disorder (235.1 per 100u202f000 person-years), bipolar disorder (216.0 per 100u202f000 person-years), schizophrenia (168.3 per 100u202f000 person-years), substance use disorder (116.5 per 100u202f000 person-years), and other mental disorders (160.4 per 100u202f000 person-years) were substantially higher than corresponding rates for the cohort with nonmental disorders (11.6 per 100u202f000 person-years) or the US general population (14.2 per 100u202f000 person-years). Among the cohort with mental disorders, AHRs of suicide were associated with inpatient diagnosis of depressive disorder (AHR, 2.0; 95% CI, 1.4-2.8; reference cohort, substance use disorder), an outpatient diagnosis of schizophrenia (AHR, 1.6; 95% CI, 1.1-2.2), an outpatient diagnosis of bipolar disorder (AHR, 1.6; 95% CI, 1.2-2.1), and an absence of any outpatient health care in the 6 months preceding hospital admission (AHR, 1.7; 95% CI, 1.2-2.5).nnnConclusions and RelevancenAfter psychiatric hospital discharge, adults with complex psychopathologic disorders with prominent depressive features, especially patients who are not tied into a system of health care, appear to have a particularly high short-term risk for suicide.

National Trends in Suicide Attempts Among Adults in the United States

BACKGROUNDnThe objective of this study was to present 12-month and lifetime prevalence, correlates, comorbidity, treatment and disability of DSM-5 bipolar I disorder.nnnMETHODSnNationally representative U.S. adult sample (Nxa0=xa036,309), the 2012-2013 National Epidemiologic Survey on Alcohol and Related Conditions - III.nnnRESULTSnPrevalences of 12-month and lifetime DSM-5 bipolar I disorder were 1.5% and 2.1% and did not differ between men (1.6% and 2.2%) and women (1.5% and 2.0%). Prevalences of bipolar I disorder were greater among Native Americans, and lower among Blacks, Hispanics and Asians/Pacific Islanders than whites. Rates were also lower among younger than older individuals, those previously married than currently married and with lower education and income relative to higher education and income. Bipolar I disorder was more strongly related to borderline and schizotypal personality disorders (adjusted odds ratios (AORS)xa0=xa02.2-4.7)), than to anxiety disorders (AORsxa0=xa01.3-2.9), and substance use disorders (AORsxa0=xa01.3-2.1) overall and among men and women. Quality of life was lower among individuals with bipolar I disorder relative to those without the disorder. Treatment rates among individuals with bipolar I disorder were low in the total sample (46%, SExa0=xa02.63), among men (36.7%, SExa0=xa03.82) and among women (55.8%, SExa0=xa03.32).nnnCONCLUSIONSnBipolar I disorder continues to be common disabling and highly comorbid disorder among men and women, contributing substantially to low quality of life and burden of disease in our society.

Psychiatric disorders and mental health treatment in American Indians and Alaska Natives: results of the National Epidemiologic Survey on Alcohol and Related Conditions

Importance A recent increase in suicide in the United States has raised public and clinical interest in determining whether a coincident national increase in suicide attempts has occurred and in characterizing trends in suicide attempts among sociodemographic and clinical groups. Objective To describe trends in recent suicide attempts in the United States. Design, Setting, and Participants Data came from the 2004-2005 wave 2 National Epidemiologic Survey on Alcohol and Related Conditions (NESARC) and the 2012-2013 NESARC-III. These nationally representative surveys asked identical questions to 69 341 adults, 21 years and older, concerning the occurrence and timing of suicide attempts. Risk differences adjusted for age, sex, and race/ethnicity (ARDs) assessed trends from the 2004-2005 to 2012-2013 surveys in suicide attempts across sociodemographic and psychiatric disorder strata. Additive interactions tests compared the magnitude of trends in prevalence of suicide attempts across levels of sociodemographic and psychiatric disorder groups. The analyses were performed from February 8, 2017, through May 31, 2017. Main Outcomes and Measures Self-reported attempted suicide in the 3 years before the interview. Results With use of data from the 69 341 participants (42.8% men and 57.2% women; mean [SD] age, 48.1 [17.2] years), the weighted percentage of US adults making a recent suicide attempt increased from 0.62% in 2004-2005 (221 of 34 629) to 0.79% in 2012-2013 (305 of 34 712; ARD, 0.17%; 95% CI, 0.01%-0.33%; Pu2009=u2009.04). In both surveys, most adults with recent suicide attempts were female (2004-2005, 60.17%; 2012-2013, 60.94%) and younger than 50 years (2004-2005, 84.75%; 2012-2013, 80.38%). The ARD for suicide attempts was significantly larger among adults aged 21 to 34 years (0.48%; 95% CI, 0.09% to 0.87%) than among adults 65 years and older (0.06%; 95% CI, −0.02% to 0.14%; interaction Pu2009=u2009.04). The ARD for suicide attempts was also significantly larger among adults with no more than a high school education (0.49%; 95% CI, 0.18% to 0.80%) than among college graduates (0.03%; 95% CI, −0.17% to 0.23%; interaction Pu2009=u2009.003); the ARD was also significantly larger among adults with antisocial personality disorder (2.16% [95% CI, 0.61% to 3.71%] vs 0.07% [95% CI, −0.09% to 0.23%]; interaction Pu2009=u2009.01), a history of violent behavior (1.04% [95% CI, 0.35% to 1.73%] vs 0.00% [95% CI, −0.12% to 0.12%]; interaction Pu2009=u2009.003), or a history of anxiety (1.43% [95% CI, 0.47% to 2.39%] vs 0.18% [95% CI, 0.04% to 0.32%]; interaction Pu2009=u2009.01) or depressive (0.99% [95% CI, −0.09% to 2.07%] vs −0.08% [95% CI, −0.20% to 0.04%]; interaction Pu2009=u2009.05) disorders than among adults without these conditions. Conclusions and Relevance A recent overall increase in suicide attempts among adults in the United States has disproportionately affected younger adults with less formal education and those with antisocial personality disorder, anxiety disorders, depressive disorders, and a history of violence.

Estimating the rates of deaths by suicide among adults who attempt suicide in the United States.

PurposeTo examine the prevalence of common psychiatric disorders and associated treatment-seeking, stratified by gender, among American Indians/Alaska Natives and non-Hispanic whites in the United States. Lifetime and 12-month rates are estimated, both unadjusted and adjusted for sociodemographic correlates.MethodAnalyses were conducted with the American Indians/Alaska Native (nxa0=xa0701) and Non-Hispanic white (nxa0=xa024,507) samples in the 2001–2002 National Epidemiologic Survey on Alcohol and Related Conditions [(NESARC) nxa0=xa043,093].ResultsOverall, 70xa0% of the American Indian/Alaska Native men and 63xa0% of the women met criteria for at least one Diagnostic and Statistical Manual-IV lifetime disorder, compared to 62 and 53xa0% of Non-Hispanic white men and women, respectively. Adjusting for sociodemographic correlates attenuated the differences found. Nearly half of American Indians/Alaska Natives had a psychiatric disorder in the previous year; again, sociodemographic adjustments explained some of the differences found. Overall, the comparisons to non-Hispanic whites showed differences were more common among American Indian/Alaska Native women than men. Among those with a disorder, American Indian/Alaska Native women had greater odds of treatment-seeking for 12-month anxiety disorders.ConclusionAs the first study to provide national estimates, by gender, of the prevalence and treatment of a broad range of psychiatric disorders among American Indians/Alaska Natives, a pattern of higher prevalence of psychiatric disorder was found relative to Non-Hispanic whites. Such differences were more common among women than men. Prevalence may be overestimated due to cultural limitations in measurement. Unmeasured risk factors, some specific to American Indians/Alaska Natives, may also partially explain these results.