Faculty Bibliography

BACKGROUND:Psychological stress is a proposed risk factor for cardiovascular disease (CVD), and posttraumatic stress disorder (PTSD), the sentinel stress-related mental disorder, occurs twice as frequently in women as men. However, whether PTSD contributes to CVD risk in women is not established. METHODS AND RESULTS/RESULTS:We examined trauma exposure and PTSD symptoms in relation to incident CVD over a 20-year period in 49 978 women in the Nurses' Health Study II. Proportional hazards models estimated hazard ratios and 95% confidence intervals for CVD events confirmed by additional information or medical record review (n=548, including myocardial infarction [n=277] and stroke [n=271]). Trauma exposure and PTSD symptoms were assessed by using the Brief Trauma Questionnaire and a PTSD screen. In comparison with no trauma exposure, endorsing ≥4 PTSD symptoms was associated with increased CVD risk after adjusting for age, family history, and childhood factors (hazard ratio,1.60; 95% confidence interval, 1.20-2.13). Being trauma-exposed and endorsing no PTSD symptoms was associated with elevated CVD risk (hazard ratio, 1.45; 95% confidence interval, 1.15-1.83), although being trauma-exposed and endorsing 1 to 3 PTSD symptoms was not. After adjusting for adult health behaviors and medical risk factors, this pattern of findings was maintained. Health behaviors and medical risk factors accounted for 14% of the trauma/no symptoms-CVD association and 47% of the trauma/4+ symptoms-CVD association. CONCLUSION/CONCLUSIONS:Trauma exposure and elevated PTSD symptoms may increase the risk of CVD in this population of women. These findings suggest that screening for CVD risk and reducing health risk behaviors in trauma-exposed women may be promising avenues for prevention and intervention.

BACKGROUND:Adolescent use of marijuana is associated with adverse later effects, so the identification of factors underlying adolescent use is of substantial public health importance. The relationship between US state laws that permit marijuana for medical purposes and adolescent marijuana use has been controversial. Such laws could convey a message about marijuana acceptability that increases its use soon after passage, even if implementation is delayed or the law narrowly restricts its use. We used 24 years of national data from the USA to examine the relationship between state medical marijuana laws and adolescent use of marijuana. METHODS:Using a multistage, random-sampling design with replacement, the Monitoring the Future study conducts annual national surveys of 8th, 10th, and 12th-grade students (modal ages 13-14, 15-16, and 17-18 years, respectively), in around 400 schools per year. Students complete self-administered questionnaires that include questions on marijuana use. We analysed data from 1 098 270 adolescents surveyed between 1991 and 2014. The primary outcome of this analysis was any marijuana use in the previous 30 days. We used multilevel regression modelling with adolescents nested within states to examine two questions. The first was whether marijuana use was higher overall in states that ever passed a medical marijuana law up to 2014. The second was whether the risk of marijuana use changed after passage of medical marijuana laws. Control covariates included individual, school, and state-level characteristics. FINDINGS/RESULTS:Marijuana use was more prevalent in states that passed a medical marijuana law any time up to 2014 than in other states (adjusted prevalence 15·87% vs 13·27%; adjusted odds ratio [OR] 1·27, 95% CI 1·07-1·51; p=0·0057). However, the risk of marijuana use in states before passing medical marijuana laws did not differ significantly from the risk after medical marijuana laws were passed (adjusted prevalence 16·25% vs 15·45%; adjusted OR 0·92, 95% CI 0·82-1·04; p=0·185). Results were generally robust across sensitivity analyses, including redefining marijuana use as any use in the previous year or frequency of use, and reanalysing medical marijuana laws for delayed effects or for variation in provisions for dispensaries. INTERPRETATION/CONCLUSIONS:Our findings, consistent with previous evidence, suggest that passage of state medical marijuana laws does not increase adolescent use of marijuana. However, overall, adolescent use is higher in states that ever passed such a law than in other states. State-level risk factors other than medical marijuana laws could contribute to both marijuana use and the passage of medical marijuana laws, and such factors warrant investigation. FUNDING/BACKGROUND:US National Institute on Drug Abuse, Columbia University Mailman School of Public Health, New York State Psychiatric Institute.

BACKGROUND:Violence-related post-traumatic stress disorder (PTSD) remains a prevalent and disabling psychiatric disorder in urban areas. However, the most effective allocation of resources into prevention and treatment to reduce this problem is unknown. We contrasted the impact of two interventions on violence-related PTSD: (1) a population-level intervention intended to prevent violence (i.e., hot-spot policing), and (2) an individual-level intervention intended to shorten PTSD duration (i.e., cognitive-behavioral therapy-CBT). METHODS:We used agent-based modeling to simulate violence and PTSD in New York City under four scenarios: (1) no intervention, (2) targeted policing to hot spots of violence, (3) increased access to CBT for people who suffered from violence-related PTSD, and (4) a combination of the two interventions. RESULTS:Combined prevention and treatment produced the largest decrease in violence-related PTSD prevalence: hot-spot policing plus a 50% increase in CBT for 5 years reduced the annual prevalence of violence-related PTSD from 3.6% (95% confidence interval = 3.5%, 3.6%) to 3.4% (3.3%, 3.5%). It would have been necessary to implement hot-spot policing or to increase CBT by 200% for 10 years for either intervention to achieve the same reduction in isolation. CONCLUSIONS:This study provides an empirically informed demonstration that investment in combined strategies that target social determinants of mental illness and provide evidence-based treatment to those affected by psychiatric disorders can produce larger reductions in the population burden from violence-related PTSD than either preventive or treatment interventions alone. However, neither hot-spot policing nor CBT, alone or combined, will produce large shifts in the population prevalence of violence-related PTSD.

With a majority of humans now living in cities, strategic research is necessary to elucidate the impact of this evolutionarily unfamiliar habitat on neural functions and well-being. In this review, both rodent and human models are considered in the evaluation of the changing physical and social landscapes associated with urban dwellings. Animal models assessing increased exposure to artificial physical elements characteristic of urban settings, as well as exposure to unnatural sources of light for extended durations, are reviewed. In both cases, increased biomarkers of mental illnesses such as major depression have been observed. Additionally, applied human research emphasizing the emotional impact of environmental threats associated with urban habitats is considered. Subjects evaluated in an inner-city hospital reveal the impact of combined specific genetic vulnerabilities and heightened stress responses in the expression of posttraumatic stress disorder. Finally, algorithm-based models of cities have been developed utilizing population-level analyses to identify risk factors for psychiatric illness. Although complex, the use of multiple research approaches, as described herein, results in an enhanced understanding of urbanization and its far-reaching effects--confirming the importance of continued research directed toward the identification of putative risk factors associated with psychiatric illness in urban settings.

BACKGROUND:This study examines changing patterns of past-year heroin use and heroin-related risk behaviors among individuals with nonmedical use of prescription opioids (NMUPO) by racial/ethnic groups in the United States. METHODS:We used data from the National Survey on Drug Use and Health (NSDUH) from 2002 to 2005 and 2008 to 2011, resulting in a total sample of N = 448,597. RESULTS:Past-year heroin use increased among individuals with NMUPO and increases varied by frequency of past year NMUPO and race/ethnicity. Those with NMUPO in the 2008-2011 period had almost twice the odds of heroin use as those with NMUPO in the 2002-2005 period (OR = 1.89, 95%CI: 1.50, 2.39), with higher increases in non-Hispanic (NH) Whites and Hispanics. In 2008-2011, the risk of past year heroin use, ever injecting heroin, past-year heroin abuse or dependence, and the perception of availability of heroin increased as the frequency of NMUPO increased across respondents of all race/ethnicities. CONCLUSION/CONCLUSIONS:Individuals with NMUPO, particularly non-Hispanic Whites, are at high risk of heroin use and heroin-related risk behaviors. These results suggest that frequent nonmedical users of prescription opioids, regardless of race/ethnicity, should be the focus of novel public health efforts to prevent and mitigate the harms of heroin use.

INTRODUCTION/BACKGROUND:Recent epidemiologic studies have shown that nonmedical use of prescription opioids (NMUPO) and major depression frequently co-occur. Comorbid forms of drug use and mental illness such as NMUPO and depression pose a greater disease burden than either condition alone. However, sociodemographic and substance use differences between individuals with either NMUPO or depression and those with comorbid conditions have not yet been fully investigated. METHODS:Data came from the 2011 and 2012 National Survey on Drug Use and Health (NSDUH). Adolescents and adults were examined independently because of differences in screening for major depressive episodes (MDE). Weighted multinomial logistic regression investigated differences between persons with either past-year NMUPO (4.0%) or MDE (5.5%) and those with comorbid NMUPO and MDE (0.6%), compared to persons with neither condition. RESULTS:Females were more likely than males to report either MDE-alone and comorbid NMUPO and MDE, whereas adult men were marginally more likely to report NMUPO-alone (not significant among adolescents). Polydrug use and alcohol use disorders were more pronounced among those with comorbid NMUPO and MDE than persons with either NMUPO-alone or MDE-alone. Persons with independent and comorbid NMUPO and MDE were more likely to report lower income and unemployment versus employment. CONCLUSIONS:This study found that independent and comorbid NMUPO and MDE were disproportionately clustered with burdens of lower socioeconomic position, suggesting that a population-based approach to address NMUPO would target these social determinants of health, whereas a high-risk approach to prevention should be tailored to females experiencing MDE symptoms and polydrug users.

OBJECTIVES/OBJECTIVE:To examine the relationship between nonmedical use of prescription opioids and heroin initiation from childhood to young adulthood, and to test whether certain ages, racial/ethnic, and income groups were at higher risk for this transition. STUDY DESIGN/METHODS:Among a nationally representative sample of US adolescents assessed in the 2004-2011 National Surveys on Drug Use and Health cross-sectional surveys (n = 223,534 respondents aged 12-21 years), discrete-time hazard models were used to estimate the age-specific hazards of heroin initiation associated with prior history of nonmedical use of prescription opioids. Interactions were estimated between prior history of nonmedical use of prescription opioids and age of nonmedical use of prescription opioid initiation, race/ethnicity, and income. RESULTS:A prior history of nonmedical use of prescription opioids was strongly associated with heroin initiation (hazard ratio 13.12, 95% CI 10.73, 16.04). Those initiating nonmedical use of prescription opioids at ages 10-12 years had the highest risk of transitioning to heroin use; the association did not vary by race/ethnicity or income group. CONCLUSIONS:Prior use of nonmedical use of prescription opioids is a strong predictor of heroin use onset in adolescence and young adulthood, regardless of the user's race/ethnicity or income group. Primary prevention of nonmedical use of prescription opioids in late childhood may prevent the onset of more severe types of drug use such as heroin at later ages. Moreover, because the peak period of heroin initiation occurs at ages 17-18 years, secondary efforts to prevent heroin use may be most effective if they focus on young adolescents who already initiated nonmedical use of prescription opioids.

PURPOSE/OBJECTIVE:Little is known about nonmedical use of prescription drugs among non-college-attending young adults in the United States. METHODS:Data were drawn from 36,781 young adults (ages 18-22 years) from the 2008-2010 National Survey on Drug Use and Health public use files. The adjusted main effects for current educational attainment, along with its interaction with gender and race/ethnicity, were considered. RESULTS:Compared to those attending college, non-college-attending young adults with at least and less than a HS degree had a higher prevalence of past-year nonmedical use of prescription opioids [NMUPO 13.1 and 13.2 %, respectively, vs. 11.3 %, adjusted odds ratios (aORs) 1.21 (1.11-1.33) and 1.25 (1.12-1.40)], yet lower prevalence of prescription stimulant use. Among users, regardless of drug type, non-college-attending youth were more likely to have past-year disorder secondary to use [e.g., NMUPO 17.4 and 19.1 %, respectively, vs. 11.7 %, aORs 1.55 (1.22-1.98) and 1.75 (1.35-2.28)]. Educational attainment interacted with gender and race: (1) among nonmedical users of prescription opioids, females who completed high school but were not enrolled in college had a significantly greater risk of opioid disorder (compared to female college students) than the same comparison for men; and (2) the risk for nonmedical use of prescription opioids was negligible across educational attainment groups for Hispanics, which was significantly different than the increased risk shown for non-Hispanic whites. CONCLUSIONS:There is a need for young adult prevention and intervention programs to target nonmedical prescription drug use beyond college campuses.

BACKGROUND:Drug overdose is an important, yet an inadequately understood, public health problem. Global attention to unintentional drug overdose has been limited by comparison with the scope of the problem. There has been a substantial increase in drug overdose incidence and prevalence in several countries worldwide over the past decade, contributing to both increased costs and mortality. OBJECTIVES/OBJECTIVE:The aim of this study was to systematically synthesize the peer-reviewed literature to document the global epidemiological profile of unintentional drug overdoses and the prevalence, time trends, mortality rates, and correlates of drug overdoses. We searched different combinations of Medical Subject Headings (MeSH) terms in PubMed for articles published from 1980 until July 2013, and we organized these results in tabular spreadsheets and compared them. We restricted the search to English-language articles that deal with unintentional overdose, focusing on 1 or more of the following key constructs: prevalence, time trends, mortality rates, and correlates. The term "overdose" as a MeSH major topic yielded 1076 publications. In addition, we searched the following combinations of nonmajor MeSH terms: "street drugs" and "overdose" yielded 180, "death" and "overdose" yielded 114, and "poisoning" and "drug users" yielded 17. There was some overlap among the searches. Based on the search and inclusion and exclusion criteria, we selected a total of 169 relevant articles for this article based on a close review of abstracts. RESULTS:We found wide variability in lifetime prevalence of experiencing a nonfatal overdose or witnessing an overdose, and in mortality rates attributable to overdose. Lifetime prevalence of witnessed overdose among drug users (n = 17 samples) ranged from 50% to 96%, with a mean of 73.3%, a median of 70%, and a standard deviation of 14.1%. Lifetime prevalence of drug users personally experiencing a nonfatal overdose (n = 27 samples), ranged from 16.6% to 68.0% with a mean of 45.4%, a median of 47%, and a standard deviation of 14.4%. Population-based crude overdose mortality rates (n = 28 samples) ranged from 0.04 to 46.6 per 100 000 person-years. This range is likely attributable to the diversity in regions, time periods, and samples. Most studies on longitudinal trends of overdose death rates or overdose-related hospitalization rates showed increases in overdose death rates and in overdose-related hospitalization rates across time, which have led to peaks in these rates at the present time. An overall trend of increasing deaths from prescription opioid use and decreasing deaths from illicit drug use in the past several years has been noted across most of the literature. With the increase in prescription opioid overdose deaths, drug overdose is not just an urban problem: rural areas have seen an important increase in overdose deaths. Lastly, cocaine, prescription opioids, and heroin are the drugs most commonly associated with unintentional drug overdoses worldwide and the demographic and psychiatric correlates associated with unintentional drug overdoses are similar globally. CONCLUSIONS:There is a need to invest in research to understand the distinct determinants of prescription drug overdose worldwide. Several other countries need to collect in a systematic and continuous fashion such data on sales of prescription opioids and other prescription drugs, nonmedical use of prescription drugs, and hospitalization secondary to overdoses on prescription drugs. The sparse evidence on the environmental determinants of overdose suggests a need for research that will inform the types of environmental interventions we can use to prevent drug overdose. Methodological issues for future studies include enhancing data collection methods on unintentional fatal and nonfatal overdoses, and collecting more detailed information on drug use history, source of drug use (for prescription drugs), and demographic and psychiatric history characteristics of the individual who overdosed.