Faculty Bibliography

Increasing alcohol outlet density is well-documented to be associated with increased alcohol use and problems, leading to the policy recommendation that limiting outlet density will decrease alcohol problems. Yet few studies of decreasing problematic outlets and outlet density have been conducted. We estimated the association between closing alcohol outlets and alcohol use and alcohol-related violence, using an agent-based model of the adult population in New York City. The model was calibrated according to the empirical distribution of the parameters across the city's population, including the density of on- and off-premise alcohol outlets. Interventions capped the alcohol outlet distribution at the 90th up to the 50th percentiles of the New York City density, and closed 5% to the 25% of outlets with the highest levels of violence. Capping density led to a lower population of light drinkers (42.2% at baseline vs. 38.1% at the 50th percentile), while heavy drinking increased slightly (12.0% at baseline vs. 12.5% at the 50th percentile). Alcohol-related homicides and non-fatal violence remained unchanged. Closing violent outlets was not associated with changes in alcohol use or related problems. Results suggest that focusing solely on closing alcohol outlets may not be an effective strategy to reduce alcohol-related problems.

INTRODUCTION/BACKGROUND:We sought to understand the association between youthful self-harm and subsequent chronic disease-related healthcare utilization and whether self-harm reflects unique vulnerability in comparison with severe psychiatric disorders. METHODS:We used a retrospective matched cohort design with statewide, all-payer, individually linked emergency department (ED) data from California, USA. Risk of future ED visits for common chronic conditions in adolescence (headaches, asthma, epilepsy, diabetes, and gastrointestinal disorders, assessed using ICD-9 diagnoses) were compared between three adolescent study groups presenting to an ED in 2010: self-harm patients (n = 5,484), patients with psychiatric complaints but no self-harm (n = 14,235), and patients with other complaints (n = 16,452). Cohort follow-up ended on Sept. 30, 2015. Analyses were adjusted for patients' prior histories of ED utilization for chronic conditions as well as patient- and area-level sociodemographic characteristics. RESULTS:Risk of subsequent ED visits was higher among self-harm patients compared to non-psychiatric control patients for subsequent epilepsy- (aRR = 1.77, 95% CI [1.42, 2.21]). Risk of subsequent ED visits was higher among psychiatric patients compared to non-psychiatric control patients for subsequent headache- (aRR = 1.31, 95% CI [1.21, 1.42]), and epilepsy-related problems (aRR = 1.85, 95% CI [1.55, 2.21]). Self-harm patients were at higher risk than psychiatric patients for subsequent gastrointestinal disorder (aRR = 1.76, 95% CI [1.03, 3.01]). CONCLUSIONS:Findings suggest that self-harm behavior and psychiatric disorders are associated with increased ED utilization for subsequent chronic disease-related ED utilization. Chronic disease among adolescent psychiatric patients should be attended to, potentially involving new models of clinical follow-up care.

OBJECTIVE:To determine whether restrictiveness-permissiveness of state gun laws or gun ownership are associated with mass shootings in the US. DESIGN/METHODS:Cross sectional time series. SETTING AND POPULATION/METHODS:US gun owners from 1998-2015. EXPOSURE/METHODS:An annual rating between 0 (completely restrictive) and 100 (completely permissive) for the gun laws of all 50 states taken from a reference guide for gun owners traveling between states from 1998 to 2015. Gun ownership was estimated annually as the percentage of suicides committed with firearms in each state. MAIN OUTCOME MEASURE/METHODS:Mass shootings were defined as independent events in which four or more people were killed by a firearm. Data from the Federal Bureau of Investigation's Uniform Crime Reporting System from 1998-2015 were used to calculate annual rates of mass shootings in each state. Mass shooting events and rates were further separated into those where the victims were immediate family members or partners (domestic) and those where the victims had other relationships with the perpetrator (non-domestic). RESULTS:Fully adjusted regression analyses showed that a 10 unit increase in state gun law permissiveness was associated with a significant 11.5% (95% confidence interval 4.2% to 19.3%, P=0.002) higher rate of mass shootings. A 10% increase in state gun ownership was associated with a significant 35.1% (12.7% to 62.7%, P=0.001) higher rate of mass shootings. Partially adjusted regression analyses produced similar results, as did analyses restricted to domestic and non-domestic mass shootings. CONCLUSIONS:States with more permissive gun laws and greater gun ownership had higher rates of mass shootings, and a growing divide appears to be emerging between restrictive and permissive states.

BACKGROUND:Prescription drug monitoring program are designed to reduce harms from prescription opioids; however, little is known about what populations benefit the most from these programs. We investigated how the relation between implementation of online prescription drug monitoring programs and rates of hospitalizations related to prescription opioids and heroin overdose changed over time, and varied across county levels of poverty and unemployment, and levels of medical access to opioids. METHODS:Ecologic county-level, spatiotemporal study, including 990 counties within 16 states, in 2001-2014. We modeled overdose counts using Bayesian hierarchical Poisson models. We defined medical access to opioids as the county-level rate of hospital discharges for noncancer pain conditions. RESULTS:In 2010-2014, online prescription drug monitoring programs were associated with lower rates of prescription opioid-related hospitalizations (rate ratio 2014 = 0.74; 95% credible interval = 0.69, 0.80). The association between online prescription drug monitoring programs and heroin-related hospitalization was also negative but tended to increase in later years. Counties with lower rates of noncancer pain conditions experienced a lower decrease in prescription opioid overdose and a faster increase in heroin overdoses. No differences were observed across different county levels of poverty and unemployment. CONCLUSIONS:Areas with lower levels of noncancer pain conditions experienced the smallest decrease in prescription opioid overdose and the faster increase in heroin overdose following implementation of online prescription drug monitoring programs. Our results are consistent with the hypothesis that prescription drug monitoring programs are most effective in areas where people are likely to access opioids through medical providers.

BACKGROUND:Medical cannabis laws (MCL) have received increased attention as potential drivers of cannabis use (CU), but little work has explored how the broader policy climate, independent of MCL, may impact CU outcomes. We explored the association between state-level policy liberalism and past-year cannabis use (CU) and cannabis use disorder (CUD). METHODS:We obtained state-level prevalence of past-year CU and CUD among past year cannabis users for ages 12-17, 18-25, and 26+ from the 2004-2006 and 2010-2012 National Surveys on Drug Use and Health. States were categorized as liberal, moderate, or conservative based on state-level policy liberalism rankings in 2005 and 2011. Linear models with random state effects examined the association between policy liberalism and past-year CU and CUD, adjusting for state-level social and economic covariates and medical cannabis laws. RESULTS:In adjusted models, liberal states had higher average past-year CU than conservative states for ages 12-17 (+1.58 percentage points; p = 0.03) and 18-25 (+2.96 percentage points; p = 0.01) but not for 26+ (p = 0.19). CUD prevalence among past year users was significantly lower in liberal compared to conservative states for ages 12-17 (-2.87 percentage points; p = 0.045) and marginally lower for ages 26+ (-2.45 percentage points; p = 0.05). CONCLUSION/CONCLUSIONS:Liberal states had higher past-year CU, but lower CUD prevalence among users, compared to conservative states. Researchers and policy makers should consider how the broader policy environment, independent of MCL, may contribute to CU outcomes.

BACKGROUND:Prescription opioid overdose (POD) and heroin overdose (HOD) rates have quadrupled since 1999. Community-level socioeconomic characteristics are associated with opioid overdoses, but whether this varies by urbanicity is unknown. METHODS:In this serial cross-sectional study of zip codes in 17 states, 2002-2014 (n = 145,241 space-time units), we used hierarchical Bayesian Poisson space-time models to analyze the association between zip code-level socioeconomic features (poverty, unemployment, educational attainment, and income) and counts of POD or HOD hospital discharges. We tested multiplicative interactions between each socioeconomic feature and zip code urbanicity measured with Rural-Urban Commuting Area codes. RESULTS:Percent in poverty and of adults with ≤ high school education were associated with higher POD rates (Rate Ratio [RR], 5% poverty: 1.07 [95% credible interval: 1.06-1.07]; 5% low education: 1.02 [1.02-1.03]), while median household income was associated with lower rates (RR, $10,000: 0.88 [0.87-0.89]). Urbanicity modified the association between socioeconomic features and HOD. Poverty and unemployment were associated with increased HOD in metropolitan areas (RR, 5% poverty: 1.12 [1.11-1.13]; 5% unemployment: 1.04 [1.02-1.05]), and median household income was associated with decreased HOD (RR, $10,000: 0.88 [0.87-0.90]). In rural areas, low educational attainment alone was associated with HOD (RR, 5%: 1.09 [1.02-1.16]). CONCLUSIONS:Regardless of urbanicity, elevated rates of POD were found in more economically disadvantaged zip codes. Economic disadvantage played a larger role in HOD in urban than rural areas, suggesting rural HOD rates may have alternative drivers. Identifying social determinants of opioid overdoses is particularly important for creating effective population-level interventions.

BACKGROUND AND AIMS/OBJECTIVE:Prescription drug monitoring programs (PDMP), defined as state-level databases used in the USA that collect prescribing information when controlled substances are dispensed, have varied substantially between states and over time. Little is known about the combinations of PDMP features that, collectively, may produce the greatest impact on prescribing and overdose. We aimed to (1) identify the types of PDMP models that have developed from 1999 to 2016, (2) estimate whether states have transitioned across PDMP models over time, and (3) examine whether states have adopted different types of PDMP models in response to the burden of opioid overdose. METHODS:A latent transition analysis of PDMP models based on an adaptation of nine PDMP characteristics classified by prescription opioid policy experts as potentially important determinants of prescribing practices and prescription opioid overdose events. RESULTS:We divided the time period into three intervals (1999-2004, 2005-2009, 2010-2016), and found three distinct PDMP classes in each interval. The classes in the first and second interval can be characterized as "No/Weak", "Proactive", and "Reactive" types of PDMPs, and in the third interval as "Weak", "Cooperative", and "Proactive". The meaning of these classes changed over time: until 2009, states in the "No/Weak" class had no active PDMP, whereas states in the "Proactive" class were more likely to proactively provide unsolicited information to PDMP users, provide open access to law enforcement, and require more frequent data reporting than states in the "Reactive" class. In 2010-2016, the "Weak" class resembled the "Reactive" class in previous intervals. States in the "Cooperative" class in 2010-2016 were less likely than states in the "Proactive" class proactively to provide unsolicited reports, or to provide open access to law enforcement; however, they were more likely than those in the "Proactive" class to share PDMP data with other states, and to report more federal drug schedules. CONCLUSIONS:Since 1999, US states have tended to transition to more robust classes of prescription drug monitoring programs (PDMPs). Opioid overdose deaths in prior years predicted the state's PDMP class but did not predict transitions between PDMP classes over time.

PURPOSE/OBJECTIVE:In 1991, California implemented a law that mandated a background check for all firearm purchases with limited exceptions (comprehensive background check or CBC policy) and prohibited firearm purchase and possession for persons convicted within the past 10 years of certain violent crimes classified as misdemeanors (MVP policy). We evaluated the population effect of the simultaneous implementation of CBC and MVP policies in California on firearm homicide and suicide. METHODS:Quasi-experimental ecological study using the synthetic control group methodology. We included annual firearm and nonfirearm mortality data for California and 32 control states for 1981-2000, with secondary analyses up to 2005. RESULTS:The simultaneous implementation of CBC and MVP policies was not associated with a net change in the firearm homicide rate over the ensuing 10 years in California. The decrease in firearm suicides in California was similar to the decrease in nonfirearm suicides in that state. Results were robust across multiple model specifications and methods. CONCLUSIONS:CBC and MVP policies were not associated with changes in firearm suicide or homicide. Incomplete and missing records for background checks, incomplete compliance and enforcement, and narrowly constructed prohibitions may be among the reasons for these null findings.

AIMS/OBJECTIVE:To use simulation to estimate the impact of alcohol taxation on drinking, non-fatal violent victimization and homicide in New York City (NYC). We simulate the heterogeneous effects of alcohol price elasticities by income, level of consumption and beverage preferences, and examine whether taxation can reduce income inequalities in alcohol-related violence. DESIGN/METHODS:Agent-based modeling simulation. SETTING/METHODS:NYC, USA. PARTICIPANTS/METHODS:Adult population aged 18-64 years in the year 2000 in the 59 community districts of NYC. The population of 256 500 agents approximates a 5% sample of the NYC population. MEASUREMENTS/METHODS:Agents were parameterized through a series of rules that governed alcohol consumption and engagement in violence. Six taxation interventions were implemented based on extensive reviews and meta-analyses, increasing universal alcohol tax by 1, 5 and 10%, and beer tax by 1, 5 and 10%. FINDINGS/RESULTS:Under no tax increase, approximately 12.2% [95% credible interval (prediction interval, PI) = 12.1-12.3%] were heavy drinkers. Taxation decreased the proportion of heavy drinkers; a 10% tax decreased heavy drinking to 9.6% (95% PI = 9.4-9.8). Beer taxes had the strongest effect on population consumption. Taxation influenced those in the lowest income groups more than the highest income groups. Alcohol-related homicide decreased from 3.22 per 100 000 (95% PI = 2.50-3.73) to 2.40 per 100 000 under a 10% universal tax (95% PI = 1.92-2.94). This translates into an anticipated benefit of ~1200 lives/year. CONCLUSION/CONCLUSIONS:Reductions in alcohol consumption in a large urban environment such as New York City can be sustained with modest increases in universal taxation. Alcohol tax increases also have a modest effect on alcohol-related violent victimization. Taxation policies reduce income inequalities in alcohol-related violence.