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Trends in Prescriptions for Non-opioid Pain Medications among U.S. Adults with Moderate or Severe Pain, 2014-2018

Gorfinkel, Lauren R; Hasin, Deborah; Saxon, Andrew J; Wall, Melanie; Martins, Silvia S; Cerdá, Magdalena; Keyes, Katherine; Fink, David S; Keyhani, Salomeh; Maynard, Charles C; Olfson, Mark
As opioid prescribing has declined, it is unclear how the landscape of prescription pain treatment across the US has changed. We used nationally-representative data from the Medical Expenditure Health Survey, 2014-2018 to examine trends in prescriptions for opioid and non-opioid pain medications, including acetaminophen, non-steroidal anti-inflammatory drugs (NSAIDs), gabapentinoids, and antidepressants among US adults with self-reported pain. Overall, from 2014-2018, the percentage of participants receiving a prescription for opioids declined, (38.8% vs. 32.8%), remained stable for NSAIDs (26.8% vs. 27.7%), and increased for acetaminophen (1.6% vs. 2.3%), antidepressants (9.6% vs. 12.0%) and gabapentinoids (13.2% vs. 19.0%). In this period, the adjusted odds of receiving an opioid prescription decreased (aOR=0.93, 95% CI=0.90-0.96), while the adjusted odds of receiving antidepressant, gabapentinoid and acetaminophen prescriptions increased (antidepressants: aOR=1.08, 95% CI=1.03-1.13 gabapentinoids: aOR=1.11, 95% CI=1.06-1.17; acetaminophen: aOR=1.10, 95% CI: 1.02-1.20). Secondary analyses stratifiying within the 2014-2016 and 2016-2018 periods revealed particular increases in prescriptions for gabapentinoids (aOR=1.13, 95% CI=1.05-1.21) and antidepressants (aOR=1.23, 95% CI=1.12-1.35) since 2016.
PMID: 35143969
ISSN: 1528-8447
CID: 5156872

Cannabis legalization and traffic injuries: exploring the role of supply mechanisms

Kilmer, Beau; Rivera-Aguirre, Ariadne; Queirolo, Rosario; Ramirez, Jessica; Cerdá, Magdalena
BACKGROUND AND AIM/OBJECTIVE:In Uruguay, residents age 18 and older seeking legal cannabis must register with the government and choose one of three supply mechanisms: self-cultivation, non-profit cannabis clubs or pharmacies. This is the first paper to measure the association between type of legal cannabis supply mechanism and traffic crashes involving injuries. DESIGN/METHODS:Ecological study using ordinary least squares regression to examine how department-level variation in registrations (overall and by type) is associated with traffic crashes involving injuries. SETTING/METHODS:Uruguay. CASES/METHODS:532 department-quarters. MEASUREMENTS/METHODS:Quarterly cannabis registration counts at the department level and incident-level traffic crash data were obtained from government agencies. The analyses controlled for department-level economic and demographic characteristics and, as a robustness check, we included traffic violations involving alcohol for departments reporting this information. Department-level data on crashes, registrations and alcohol violations were denominated by the number of residents ages 18 and older. FINDINGS/RESULTS:From 2013 to 2019, the average number of registrations at the department-quarter level per 10 000 residents age 18 and older for self-cultivation, club membership and pharmacy purchasing were 17.7 (SD = 16.8), 3.6 (SD = 8.6), and 25.1 (SD = 50.4), respectively. In our multivariate regression analyses, we did not find a statistically significant association between the total number of registrations and traffic crashes with injuries (β = -0.007; P = 0.398; 95% CI = -0.023, 0.01). Analyses focused on the specific supply mechanisms found a consistent, positive and statistically significant association between the number of individuals registered as self-cultivators and the number of traffic crashes with injuries (β = 0.194; P = 0.008; 95% CI = 0.058, 0.329). Associations for other supply mechanisms were inconsistent across the various model specifications. CONCLUSIONS:In Uruguay, the number of people allowed to self-cultivate cannabis is positively associated with traffic crashes involving injuries. Individual-level analyses are needed to assess better the factors underlying this association.
PMID: 35129240
ISSN: 1360-0443
CID: 5190752

Pain, cannabis use, and physical and mental health indicators among veterans and non-veterans: results from National Epidemiologic Survey on Alcohol and Related Conditions-III

Enkema, Matthew C; Hasin, Deborah S; Browne, Kendall C; Stohl, Malki; Shmulewitz, Dvora; Fink, David S; Olfson, Mark; Martins, Silvia S; Bohnert, Kipling M; Sherman, Scott E; Cerda, Magdalena; Wall, Melanie; Aharonovich, Efrat; Keyhani, Salomeh; Saxon, Andrew J
ABSTRACT/UNASSIGNED:Chronic pain is associated with mental and physical health difficulties and is prevalent among veterans. Cannabis has been put forth as a treatment for chronic pain, and changes in laws, attitudes, and use patterns have occurred over the last two decades. Differences in prevalence of non-medical cannabis use and cannabis use disorder (CUD) were examined across two groups: veterans/non-veterans and those reporting/not reporting recent pain. Data from the National Epidemiologic Survey on Alcohol and Related Conditions-III (2012-2013; n=36,309) were analyzed using logistic regression. Prevalence Differences (PD) for three cannabis outcomes: (1) past-year non-medical cannabis use, (2) frequent (≥3 times a week) non-medical use, and (3) DSM-5 CUD were estimated for those reporting recent moderate-severe pain (veterans/non-veterans), and veterans reporting/not reporting recent pain. Difference in differences were calculated to investigate prevalence differences on outcomes associated with residence in a state with medical cannabis laws (MCLs). Associations between physical and mental health and cannabis variables were tested. Results indicated that the prevalence of recent pain was greater among veterans (PD=7.25%, 95% CI [4.90, 9.60]). Among veterans, the prevalence of frequent cannabis use was greater among those with pain (PD=1.92%, 98% CI [0.21, 3.63]), and, among veterans residing in a state with MCLs, the prevalence of CUD was greater among those reporting recent pain (PD=3.88%, 98% CI [0.36, 7.39]). Findings failed to support the hypothesis that cannabis use improves mental or physical health for veterans with pain. Providers treating veterans with pain in MCL states should monitor such patients closely for CUD.
PMID: 34108436
ISSN: 1872-6623
CID: 4900072

Explaining US Adolescent Depressive Symptom Trends Through Declines in Religious Beliefs and Service Attendance

Kreski, Noah T; Chen, Qixuan; Olfson, Mark; Cerdá, Magdalena; Hasin, Deborah; Martins, Silvia S; Keyes, Katherine M
Over the past decade, US adolescents' depressive symptoms have increased, and changing religious beliefs and service attendance may be contributing factors. We examined the contribution of religious factors to depressive symptoms among 417,540 US adolescents (grades: 8, 10, 12), years:1991-2019, in survey-weighted logistic regressions. Among adolescents who felt religion was personally important, those who never attended services had 2.23 times higher odds of reporting depressive symptoms compared to peers attending weekly. Among adolescents who did not feel that religion was important, the pattern was reversed. Among adolescents, concordance between importance of religion and religious service attendance may lower risk of depressive symptoms. Overall, we estimate that depressive symptom trends would be 28.2% lower if religious factors had remained at 1991 levels.
PMID: 34417680
ISSN: 1573-6571
CID: 4998372

Age, period, and cohort effects of internalizing symptoms among US students and the influence of self-reported frequency of ≥ 7 hours sleep attainment: Results from the Monitoring the Future Survey 1991-2019

Kaur, Navdep; Hamilton, Ava D; Chen, Qixuan; Hasin, Deborah; Cerda, Magdalena; Martins, Silvia S; Keyes, Katherine M
Adolescent internalizing symptoms have increased since 2010, while adequate sleep has declined for several decades. It remains unclear how self-reported sleep attainment has impacted internalizing symptoms trends. Using 1991-2019 MTF data (N~390,000), we estimate age-period-cohort effects in adolescent internalizing symptoms (loneliness, self-esteem, self-derogation, depressive affect) and the association with yearly prevalence of a survey-assessed, self-reported measure of ≥ 7 hours sleep attainment. We focus our main analysis on loneliness and use median odds ratios (MORs), measures of variance in loneliness associated with period differences. We observed limited signals for cohort effects and modeled only period effects. Loneliness increased by 0.83% per year; adolescents in 2019 had 0.68 (95% CI: 0.49, 0.87) increased log-odds of loneliness compared with the mean, consistent by race/ethnicity and parental education. Girls experienced steeper increases than boys (p<0.0001). The period effect MOR for loneliness was 1.16 (variance=0.09; 95% CI: 0.06, 0.17) before adjusting for self-reported frequency of ≥ 7 hours sleep vs. 1.07 (variance=0.02; 95% CI: 0.01, 0.03) after adjusting. Adolescents across cohorts are experiencing worsening internalizing symptoms. Self-reported frequency of <7 hours sleep partially explains increases in loneliness, indicating the need for feasibility trials to study the effect of increasing sleep attainment on internalizing symptoms.
PMID: 35048117
ISSN: 1476-6256
CID: 5131642

Emerging Zoonotic Infections, Social Processes and Their Measurement and Enhanced Surveillance to Improve Zoonotic Epidemic Responses: A "Big Events" Perspective

Friedman, Samuel R; Jordan, Ashly E; Perlman, David C; Nikolopoulos, Georgios K; Mateu-Gelabert, Pedro
Zoonotic epidemics and pandemics have become frequent. From HIV/AIDS through COVID-19, they demonstrate that pandemics are social processes as well as health occurrences. The roots of these pandemics lie in changes in the socioeconomic interface between humanity and non-human host species that facilitate interspecies transmission. The degree to which zoonoses spread has been increased by the greater speed and extent of modern transportation and trade. Pre-existing sociopolitical and economic structures and conflicts in societies also affect pathogen propagation. As an epidemic develops, it can itself become a social and political factor, and change and interact with pre-existing sociobehavioral norms and institutional structures. This paper uses a "Big Events" approach to frame these processes. Based on this framework, we discuss how social readiness surveys implemented both before and during an outbreak might help public health predict how overall systems might react to an epidemic and/or to disease control measures, and thus might inform interventions to mitigate potential adverse outcomes or possibly preventing outbreaks from developing into epidemics. We conclude by considering what "pathways measures", in addition to those we and others have already developed, might usefully be developed and validated to assist outbreak and epidemic disease responses.
PMID: 35055817
ISSN: 1660-4601
CID: 5131792

A Systematic Review of Simulation Models to Track and Address the Opioid Crisis

Cerdá, Magdalena; Jalali, Mohammad S; Hamilton, Ava D; DiGennaro, Catherine; Hyder, Ayaz; Santaella-Tenorio, Julian; Kaur, Navdep; Wang, Christina; Keyes, Katherine M
The opioid overdose crisis is driven by an intersecting set of social, structural, and economic forces. Simulation models offer a tool to help us understand and address this complex, dynamic, and nonlinear social phenomenon. We conducted a systematic review of the literature on simulation models of opioid use and overdose up to September 2019. We extracted modeling types, target populations, interventions, and findings. Further, we created a database of model parameters used for model calibration, and evaluated study transparency and reproducibility. Of the 1,398 articles screened, we identified 88 eligible articles. The most frequent types of models were compartmental (36%), Markov (20%), system dynamics (16%), and Agent-Based models (16%). Over a third evaluated intervention cost-effectiveness (40%), and another third (39%) focused on treatment and harm reduction services for people with opioid use disorder (OUD). More than half (61%) discussed calibrating their models to empirical data, and 31% discussed validation approaches used in their modeling process. From the 63 studies that provided model parameters, we extracted the data sources on opioid use, OUD, OUD treatment, cessation/relapse, emergency medical services, and mortality parameters. This database offers a tool that future modelers can use to identify potential model inputs and evaluate comparability of their models to prior work. Future applications of simulation models to this field should actively tackle key methodological challenges, including the potential for bias in the choice of parameter inputs, investment in model calibration and validation, and transparency in the assumptions and mechanics of simulation models to facilitate reproducibility.
PMID: 34791110
ISSN: 1478-6729
CID: 5049332

G-computation and agent-based modeling for social epidemiology: Can population interventions prevent post-traumatic stress disorder?

Mooney, Stephen J; Shev, Aaron B; Keyes, Katherine M; Tracy, Melissa; Cerdá, Magdalena
Agent-based modeling and G-computation can both be used to estimate impacts of intervening on complex systems. We explored each modeling approach within an applied example: interventions to reduce posttraumatic stress disorder (PTSD). We used data from a cohort of 2,282 adults representative of the adult population of the New York City metropolitan area from 2002-2006, of whom 16.3% developed PTSD over their lifetimes. We built four models: G-computation, an agent-based model with no between-agent interactions, an agent-based model with violent interaction dynamics, and an agent-based model with neighborhood dynamics. Three interventions were tested: reducing violent victimization by 1) 37.2% (real-world reduction), 2) 100%, and 3) supplementing the income of 20% of lower-income participants. The G-computation model estimated population-level PTSD risk reductions of 0.12% (95% CI: -0.16, 0.29), 0.28% (95% CI: -0.30, 0.70), and 1.55% (95% CI: 0.40, 2.12), respectively. The agent-based model with no interactions replicated the findings from G-computation. Introduction of interaction dynamics modestly decreased estimated intervention effects (income supplement risk reduction dropped to 1.47%), whereas introduction of neighborhood dynamics modestly increased effectiveness (income supplement risk reduction increased to 1.58%). As compared with G-computation, agent-based modeling permitted deeper exploration of complex systems dynamics at the cost of further assumptions.
PMID: 34409437
ISSN: 1476-6256
CID: 5090842

A Sociology of Empathy and Shared Understandings: Contextualizing Beliefs and Attitudes on Why People Use Opioids

Ezell, Jerel M.; Olson, Brooke; Walters, Suzan M.; Friedman, Samuel R.; Ouellet, Lawrence; Pho, Mai T.
There has been a steep rise in overdoses and mortality among people who use opioids or who inject drugs (PWUD), including in North America, the United Kingdom, and parts of Eastern Europe, with some of the sharpest increases amassing in rural communities. Currently, the literature lacks a comparative focus on the views and experiences of rural PWUD and professionals who regularly work and interface with them, in terms of their understandings of the rural drug use initiation/relapse trajectory. Considering a renewed sociology of emotions and empathy and the constructs of direct experience (e.g., of personal drug use) versus role-playing (e.g., envisioning oneself in another's position), we used a modified constant comparison method to analyze interviews conducted with PWUD and professional stakeholders in rural southern Illinois, an opioid overdose hotspot. Findings suggest that rural opioid use is adopted in service of an intricate interplay of sensory, relational, somatic, and psychosocial benefits, with a sharp divergence between PWUD, who express considerable agency in their drug use behaviors, and professionals, who fail to successful role-play in emphasizing PWUD's limited willpower and "deviant" sociocultural predilection. These dynamics illuminate challenges to advancing nuanced, culturally humble programming to advance public health goals related to the opioid and drug injection epidemic.
ISSN: 0036-0112
CID: 5199572

Utilization of Medications for Opioid Use Disorder Across US States: Relationship to Treatment Availability and Overdose Mortality

Krawczyk, Noa; Jent, Victoria; Hadland, Scott E; Cerdá, Magdalena
OBJECTIVE:Availability of medications for opioid use disorder (MOUD) remains sparse. To date, there has been no national, state-by-state comparison of patient MOUD utilization relative to treatment availability and burden of overdose deaths. We aimed to quantify, for each state, the number of MOUD patients relative to (1) office-based buprenorphine providers and opioid treatment programs (OTPs) and (2) overdose deaths. METHODS:We conducted a spatial analysis of patients receiving MOUD from OTPs or buprenorphine providers in March 2017 across all 50 states and Washington, DC. For each state, we calculated the number of patients receiving MOUD from OTPs and buprenorphine prescriptions, relative to available OTPs and buprenorphine providers; as well as ratios of number of patients receiving MOUD relative to overdose deaths. RESULTS:In March 2017, 942,368 patients attended an OTP (410,288) or received a buprenorphine prescription (486,318). Patient to OTP ratio was highest in West Virginia, Delaware, Washington, DC, New Jersey, New Hampshire, Connecticut and Ohio, ranging from 91 to 193 patients per OTP in the first quintile to 430 to 648 in the fifth. Patient to buprenorphine provider ratio was highest in Kentucky and West Virginia, ranging from 3 to 7 patients per provider in the first quintile to 19 to 28 in the fifth. Median MOUD patients per overdose death was 21 (IQR:14.9-28.2). Of high overdose states, Washington, DC, New Jersey, and Ohio had the smallest number of patients on MOUD relative to deaths. CONCLUSIONS:High patient volume relative to treatment availability in overdose-burdened areas may indicate strain on MOUD providers and OTPs. Promoting greater utilization while expanding MOUD providers and programs is critical.
PMID: 35120067
ISSN: 1935-3227
CID: 5153932