Alcohol and cannabis use and co-use among Whites and Hispanics on and off the U.S./Mexico border in California.

This paper examines self-reported rates of drinking and cannabis use and co-use among White and Hispanic adults randomly selected in four counties in California: Imperial on the border; and Kern, Tulare, and Madera in California's Central Valley. Co-use was significantly higher among the U.S. born than among those born abroad, and in the Central Valley than on the border. Co-users were heavier drinkers, had higher rates of alcohol use disorder, other alcohol problems, and a positive history of illicit drug use than drinkers only.

Changes in Opioid and Benzodiazepine Poisoning Deaths After Cannabis Legalization in the US: A County-level Analysis, 2002-2020.

BACKGROUND: Cannabis legalization for medical and recreational purposes has been suggested as an effective strategy to reduce opioid and benzodiazepine use and deaths. We examined the county-level association between medical and recreational cannabis laws and poisoning deaths involving opioids and benzodiazepines in the US from 2002 to 2020. METHODS: Our ecologic county-level, spatiotemporal study comprised 49 states. Exposures were state-level implementation of medical and recreational cannabis laws and state-level initiation of cannabis dispensary sales. Our main outcomes were poisoning deaths involving any opioid, any benzodiazepine, and opioids with benzodiazepines. Secondary analyses included overdoses involving natural and semi-synthetic opioids, synthetic opioids, and heroin. RESULTS: Implementation of medical cannabis laws was associated with increased deaths involving opioids (rate ratio [RR] = 1.14; 95% credible interval [CrI] = 1.11, 1.18), benzodiazepines (RR = 1.19; 95% CrI = 1.12, 1.26), and opioids+benzodiazepines (RR = 1.22; 95% CrI = 1.15, 1.30). Medical cannabis legalizations allowing dispensaries was associated with fewer deaths involving opioids (RR = 0.88; 95% CrI = 0.85, 0.91) but not benzodiazepine deaths; results for recreational cannabis implementation and opioid deaths were similar (RR = 0.81; 95% CrI = 0.75, 0.88). Recreational cannabis laws allowing dispensary sales was associated with consistent reductions in opioid- (RR = 0.83; 95% CrI = 0.76, 0.91), benzodiazepine- (RR = 0.79; 95% CrI = 0.68, 0.92), and opioid+benzodiazepine-related poisonings (RR = 0.83; 95% CrI = 0.70, 0.98). CONCLUSIONS: Implementation of medical cannabis laws was associated with higher rates of opioid- and benzodiazepine-related deaths, whereas laws permitting broader cannabis access, including implementation of recreational cannabis laws and medical and recreational dispensaries, were associated with lower rates. The estimated effects of the expanded availability of cannabis seem dependent on the type of law implemented and its provisions.

Drinking in Mexico by Whites and Hispanics on and off the US/Mexico border in California.

This paper compares drinking patterns of Whites and Hispanics who after crossing the U.S./Mexico border drink and do not drink in Mexico. Data came from a household survey of 1,209 adults 18 to 39 years of age in California. Residence near the US/Mexico border increases the likelihood of drinking in Mexico (AOR = 4.57; 95%CI = 2.45-8.52; p < .001). Hispanics (AOR = 1.91; 95%CI = 1.26-2.90; p < .01), those who drink more frequently (AOR = 1.05; 95%CI = 1.02-1.09; p < .01) and those who drink six or more drinks in day (AOR = 1.91; 95%CI = 1.26-2.29; p < .01) are more likely than Whites and lighter drinkers to report this behavior. Crossing the U.S./Mexico border to drink is influenced by living close to the border, Hispanic ethnicity, and drinking many drinks in a day.

A Spatiotemporal Analysis of the Association of California City and County Cannabis Policies with Cannabis Outlet Densities.

BACKGROUND: Cannabis outlets may affect health and health disparities. Local governments can regulate outlets, but little is known about the effectiveness of local policies in limiting outlet densities and discouraging disproportionate placement of outlets in vulnerable neighborhoods. METHODS: For 241 localities in California, we measured seven policies pertaining to density or location of recreational cannabis outlets. We geocoded outlets using web-scraped data from the online finder Weedmaps between 2018 and 2020. We applied Bayesian spatiotemporal models to evaluate associations of local cannabis policies with Census block group-level outlet counts, accounting for confounders and spatial autocorrelation. We assessed whether associations differed by block group median income or racial-ethnic composition. RESULTS: Seventy-six percent of localities banned recreational cannabis outlets. Bans were associated with fewer outlets, particularly in block groups with higher median income, fewer Hispanic residents, and more White and Asian residents. Outlets were disproportionately located in block groups with lower median income [posterior RR (95% credible interval): 0.76 (0.70, 0.82) per $10,000], more Hispanic residents [1.05 (1.02, 1.09) per 5%], and fewer Black residents [0.91 (0.83, 0.98) per 5%]. For the six policies in jurisdictions permitting outlets, two policies were associated with fewer outlets and two with more; two policy associations were uninformative. For these policies, we observed no consistent heterogeneity in associations by median income or racial-ethnic composition. CONCLUSIONS: Some local cannabis policies in California are associated with lower cannabis outlet densities, but are unlikely to deter disproportionate placement of outlets in racial-ethnic minority and low-income neighborhoods.

Equity in Coverage of Local Cannabis Control Policies in California, 2020‒2021.

Objectives. To assess whether cannabis control policies that may protect public health were adopted evenly across California localities with differing sociodemographic compositions. Methods. From November 2020 to January 2021, we measured cannabis control policies for 241 localities across California and linked them to data on the characteristics of the communities affected by these policies. We evaluated whether disadvantaged communities were more likely to allow cannabis businesses and less likely to be covered by policies designed to protect public health. Results. Localities with all-out bans on cannabis businesses (65% of localities) were disproportionately high-education (55.8% vs 50.5% with any college) and low-poverty (24.3% vs 34.2%), with fewer Black (4.4% vs 6.9%) and Latinx (45.6% vs 50.3%) residents. Among localities that allowed retail cannabis businesses (28%), there were more cannabis control policies in localities with more high-income and Black residents, although the specific policies varied. Conclusions. Cannabis control policies are unequally distributed across California localities. If these policies protect health, inequities may be exacerbated. Public Health Implications. Uniform adoption of recommended cannabis control policies may help limit any inequitable health impacts of cannabis legalization. (Am J Public Health. 2022;112(11):1640-1650. https://doi.org/10.2105/AJPH.2022.307041).

Trends and correlates of spatially aggregated alcohol-involved crashes among Whites and Hispanics in California.

AIMS: This paper examines trends and correlates of alcohol-involved motor vehicle crashes (AMVCs) in California between 2005 and 2016 among Hispanic and non-Hispanic Whites (Whites hereafter). Together these two groups comprise 76% of the state population. The paper also examines whether alcohol outlet density, percentage of Hispanics in census tract populations, and distance to the U.S./Mexico border are related to greater risks for AMVCs. The border is of interest given the greater availability of alcohol in the area. METHODS: Crash data come from Statewide Integrated Traffic Records System maintained by the California Highway Patrol. Sociodemographic and community characteristics data from the U.S. Census and alcohol outlet density were aggregated to census tracts. Total motor vehicle crashes and AMVCs were related to these characteristics using hierarchical Bayesian Poisson space-time models. RESULTS: There were over two million injury and fatality crashes during the period of analysis, of which 11% were AMVCs. About 1.7% of these crashes had fatalities. The rate of AMVCs increased among both Whites and Hispanics until 2008. After 2008, the rate among Whites declined through 2016 while the rate among Hispanics declined for 2 years (2009 and 2010) and increased thereafter. Crash distance from the border (RR = 1.016, 95% CI = 1.010 to 1.022) and percent Hispanic population (RR = 1.006; 95% CI = 1.003 to 1.009) were well-supported results with 95% credible intervals that did not include 1. The percentages of the following: bars/pubs, males, individuals aged 18 to 29 and 40 to 49 years, U.S. born population, individuals below the 150% poverty level, unemployed, housing vacant, and housing owner-occupied were all positively associated with AMVCs and well supported. CONCLUSIONS: Between 2005 and 2016 the rate of AMVCs in California declined among Whites but not among Hispanics. Population-level indicators of percent Hispanic population, distance to the U.S. Mexico border, gender, age distribution, and socioeconomic stability were positively associated with crash rates, indicating that important contextual characteristics help determine the level of AMVC rates in communities.

Alcohol use disorder among Whites and Hispanics on and off the U.S./Mexico border in California.

This paper examines whether U.S./Mexico border residence in California is related to the prevalence of DSM-5 alcohol use disorder (AUD) among Whites and Hispanics. Household survey data were obtained from 1,209 adults (59.7% female) 18 to 39 years of age resident in four counties in California: Imperial on the U.S./Mexico border; and Kern, Tulare, and Madera in California's Central Valley. Households were selected using a list assisted sample, with data collected on the phone or online. Results show that AUD rates were not different between border and non-border location and between Whites and Hispanics. AUD was negatively associated with higher income ($20,000 to $60,000: AOR=.38; 95%CI=.17-.86; p<.01-more than $60,000: AOR=.27; 95%CI: .09-.81; p<.01) and poor risk perception (AOR=.86; 95%CI=.78-.94; p<.01). AUD was positively associated with continued volume of drinking (AOR = 1.05; 95%CI = 1.01-1.09; p<.01), drinking in Mexico (AOR = 4.28; 95%CI = 1.61-11.36; p<.01), marijuana use (AOR = 4.11; 95%CI = 1.73-9.77; p<.01), and impulsivity (AOR = 1.55; 95%CI = 1.23-1.94). Efforts to prevent AUD in the population in California, and especially among those who live close to the border with Mexico, should take into consideration factors such as impulsivity, marijuana use, border crossing to drink in Mexico, all of which increased risk of AUD.

Multiresolution Analyses of Neighborhood Correlates of Crime: Smaller Is Not Better.

Population analyses of the correlates of neighborhood crime implicitly assume that a single spatial unit can be used to assess neighborhood effects. However, no single spatial unit may be suitable for analyses of the many social determinants of crime. Instead, effects may appear at multiple spatial resolutions, with some determinants acting broadly, others locally, and still others as some function of both global and local conditions. We provide a multiresolution spatial analysis that simultaneously examines US Census block, block group, and tract effects of alcohol outlets and drug markets on violent crimes in Oakland, California, incorporating spatial lag effects at the 2 smaller spatial resolutions. Using call data from the Oakland Police Department from 2010-2015, we examine associations of assaults, burglaries, and robberies with multiple resolutions of alcohol outlet types and compare the performance of single (block-level) models with that of multiresolution models. Multiresolution models performed better than the block models, reflected in improved deviance and Watanabe-Akaike information criteria and well-supported multiresolution associations. By considering multiple spatial scales and spatial lags in a Bayesian framework, researchers can explore multiresolution processes, providing more detailed tests of expectations from theoretical models and leading the way to more effective intervention efforts.

Spatiotemporal Analysis of the Association Between Pain Management Clinic Laws and Opioid Prescribing and Overdose Deaths.

Pain management clinic (PMC) laws were enacted by 12 states to promote appropriate opioid prescribing, but their impact is inadequately understood. We analyzed county-level opioid overdose deaths (National Vital Statistics System) and patients filling long-duration (≥30 day) or high-dose (≥90 morphine milligram equivalents per day) opioid prescriptions (IQVIA, Inc.) in the United States in 2010-2018. We fitted Besag-York-Mollié spatiotemporal models to estimate annual relative rates (RRs) of overdose and prevalence ratios (PRs) of high-risk prescribing associated with any PMC law and 3 provisions: payment restrictions, site inspections, and criminal penalties. Laws with criminal penalties were significantly associated with reduced PRs of long-duration and high-dose opioid prescriptions (adjusted PR = 0.82, 95% credible interval (CrI): 0.82, 0.82, and adjusted PR = 0.73, 95% CI: 0.73, 0.74 respectively) and reduced RRs of total and natural/semisynthetic opioid overdoses (adjusted RR = 0.86, 95% CrI: 0.80, 0.92, and adjusted RR = 0.84, and 95% CrI: 0.77, 0.92, respectively). Conversely, PMC laws were associated with increased relative rates of synthetic opioid and heroin overdose deaths, especially criminal penalties (adjusted RR = 1.83, 95% CrI: 1.59, 2.11, and adjusted RR = 2.59, 95% CrI: 2.22, 3.02, respectively). Findings suggest that laws with criminal penalties were associated with intended reductions in high-risk opioid prescribing and some opioid overdoses but raise concerns regarding unintended consequences on heroin/synthetic overdoses.

Predicting the Future Course of Opioid Overdose Mortality: An Example From Two US States.

BACKGROUND: The rapid growth of opioid abuse and the related mortality across the United States has spurred the development of predictive models for the allocation of public health resources. These models should characterize heterogeneous growth across states using a drug epidemic framework that enables assessments of epidemic onset, rates of growth, and limited capacities for epidemic growth. METHODS: We used opioid overdose mortality data for 146 North and South Carolina counties from 2001 through 2014 to compare the retrodictive and predictive performance of a logistic growth model that parameterizes onsets, growth, and carrying capacity within a traditional Bayesian Poisson space-time model. RESULTS: In fitting the models to past data, the performance of the logistic growth model was superior to the standard Bayesian Poisson space-time model (deviance information criterion: 8,088 vs. 8,256), with reduced spatial and independent errors. Predictively, the logistic model more accurately estimated fatality rates 1, 2, and 3 years in the future (root mean squared error medians were lower for 95.7% of counties from 2012 to 2014). Capacity limits were higher in counties with greater population size, percent population age 45-64, and percent white population. Epidemic onset was associated with greater same-year and past-year incidence of overdose hospitalizations. CONCLUSION: Growth in annual rates of opioid fatalities was capacity limited, heterogeneous across counties, and spatially correlated, requiring spatial epidemic models for the accurate and reliable prediction of future outcomes related to opioid abuse. Indicators of risk are identifiable and can be used to predict future mortality outcomes.

Measuring Relationships Between Proactive Reporting State-level Prescription Drug Monitoring Programs and County-level Fatal Prescription Opioid Overdoses.

BACKGROUND: Prescription drug monitoring programs (PDMPs) that collect and distribute information on dispensed controlled substances have been adopted by nearly all US states. We know little about program characteristics that modify PDMP impact on prescription opioid (PO) overdose deaths. METHODS: We measured associations between adoption of any PDMP and changes in fatal PO overdoses in 2002-2016 across 3109 counties in 49 states and D.C. We then measured changes related to the adoption of "proactive PDMPs," which report outlying prescribing/dispensing patterns and provide broader access to PDMP data by law enforcement. Comparisons were made within 3 time intervals that broadly represent the evolution of PDMPs (2002-2004, 2005-2009, and 2010-2016). We modeled overdoses using Bayesian space-time models. RESULTS: Adoption of electronic PDMP access was associated with 9% lower rates of fatal PO overdoses after three years (rate ratio [RR] = 0.91, 95% credible interval [CI]: 0.88-0.93) with well-supported effects for methadone (RR = 0.86,95% CI: 0.82-0.90) and other synthetic opioids (RR = 0.82, 95% CI: 0.77-0.86). Compared with states with no/weak PDMPs, proactive PDMPs were associated with fewer deaths attributed to natural/semi-synthetic opioids (2002-2004: RR = 0.72 [0.66-0.78]; 2005-2009: RR = 0.93 [0.90-0.97]; 2010-2016: 0.89 [0.86-0.92]) and methadone (2002-2004: RR = 0.77 [0.69-0.85]; 2010-2016: RR = 0.90 [0.86-0.94]). Unintended effects were observed for synthetic opioids other than methadone (2005-2009: RR = 1.29 [1.21-1.38]; 2010-2016: RR = 1.22 [1.16-1.29]). CONCLUSIONS: State adoption of PDMPs was associated with fewer PO deaths overall while proactive PDMPs alone were associated with fewer deaths related to natural/semisynthetic opioids and methadone, the specific targets of these programs. See video abstract at, http://links.lww.com/EDE/B619.

Microecological Relationships Between Area Income, Off-Premise Alcohol Outlet Density, Drinking Patterns, and Alcohol Use Disorders: The East Bay Neighborhoods Study.

BACKGROUND: Distinguishing the impacts of neighborhood income and off-premise alcohol outlet density on alcohol use has proven difficult, particularly given the conflation of these measures across neighborhood areas. We explicitly test for differential effects related to individual and area income and outlet densities on alcohol use and alcohol use disorders (AUDs) by implementing a stratified microecological sample. METHODS: The East Bay Neighborhoods Study included a survey of 984 residents of 72 microenvironments within a geographically contiguous 6-city area in California and Systematic social observations of each site. The sites included 18 areas in each of 4 strata (high/low median household income and off-premise outlet density). We assessed 4 outcomes: 28-day drinking frequency, average quantity of alcohol consumed per drinking occasion, 28-day drinking volume, and Alcohol Use Disorders Identification Test (AUDIT) score. We used zero-inflated negative binomial regression with standard errors adjusted for site clusters to relate drinking measures to individual-level age, race/ethnicity, gender, marital status, education, and income, and neighborhood indicators of site strata, physical disorder, and physical decay. An interaction term was tested representing site-level by individual-level income. RESULTS: Living in a high-income site, regardless of off-premise alcohol outlet density, was associated with more frequent drinking and higher alcohol dependence/problems. Both individual-level income and site-level income were related to greater frequencies of use, but lower income drinkers in high-income areas drank more than comparable drinkers in low-income areas. Study participants living in high-density off-premise alcohol outlet sites drank less frequently but did not differ in terms of either AUDIT scores or heavy drinking from participants living in low-density sites. CONCLUSIONS: Using a stratified microecological sampling design, we were able to directly assess statistical associations of off-premise outlet density and neighborhood median household income with patterns of drinking and AUDs. Caution should be used interpreting prior study findings linking off-premise outlet densities to drinking.

Proximity to the Southern Border and Sociodemographic Correlates of Drinking and Driving Arrests in California.

BACKGROUND: About 30% of all motor vehicle fatalities in the United States are associated with alcohol-impaired motor vehicle crashes. Arrests for drinking and driving (Driving under the influence [DUI]) are 1 of the most important deterrence actions to minimize DUI. This paper examines trends and population-level correlates of drinking driving arrests (DUI) from 2005 to 2017 in California. METHODS: Arrest data come from the Monthly Arrest and Citation Register compiled by the California Department of Justice. Sociodemographic and community characteristic data from the U.S. Census, alcohol outlet density, and distance to the U.S.-Mexico border from Law Enforcement Reporting Areas (LERA) centroids were aggregated at the level of 499 LERA contributing to the report. Reported arrest rates were related to area sociodemographic characteristics using hierarchical Bayesian Poisson space-time models. RESULTS: Both among men and women rates showed an upward trend until 2008, decreasing after that year. DUI arrest rates were greater among Hispanics than Whites for the 2 younger age groups, 18 to 29 (p < 0.001) and 30 to 39 years (p < 0.001). DUI arrest rates in LERA areas are positively related to proximity to the California/Mexico border; a higher percent of bar/pub outlets; a higher percent of Hispanic population; a higher percent of population 18 to 29, 30 to 39, and 40 to 49 years of age; a higher percent of US-born population; a higher percent of population with annual income of $100,000 or more; a higher percent of population 150% below the federal poverty line; and a higher level of law-enforcement activities. CONCLUSIONS: Results of this analysis of spatial correlates of DUI arrests overlap well with the literature on individual-level data and arrest rates. The decrease in arrest rates as distance to the California/Mexico border increases is potentially associated with the greater availability of alcohol in the border area.

Measuring Alcohol Outlet Density: An Overview of Strategies for Public Health Practitioners.

CONTEXT: Excessive alcohol use is responsible for 88 000 deaths in the United States annually and cost the United States $249 billion in 2010. There is strong scientific evidence that regulating alcohol outlet density is an effective intervention for reducing excessive alcohol consumption and related harms, but there is no standard method for measuring this exposure. PROGRAM: We overview the strategies available for measuring outlet density, discuss their advantages and disadvantages, and provide examples of how they can be applied in practice. IMPLEMENTATION: The 3 main approaches for measuring density are container-based (eg, number of outlets in a county), distance-based (eg, average distance between a college and outlets), and spatial access-based (eg, weighted distance between town center and outlets). EVALUATION: While container-based measures are the simplest to calculate and most intuitive, distance-based or spatial access-based measures are unconstrained by geopolitical boundaries and allow for assessment of clustering (an amplifier of certain alcohol-related harms). Spatial access-based measures can also be adjusted for population size/demographics but are the most resource-intensive to produce. DISCUSSION: Alcohol outlet density varies widely across and between locations and over time, which is why it is important to measure it. Routine public health surveillance of alcohol outlet density is important to identify problem areas and detect emerging ones. Distance- or spatial access-based measures of alcohol outlet density are more resource-intensive than container-based measures but provide a much more accurate assessment of exposure to alcohol outlets and can be used to assess clustering, which is particularly important when assessing the relationship between density and alcohol-related harms, such as violent crime.

Prescription Drug Monitoring Programs and Opioid Overdoses: Exploring Sources of Heterogeneity.

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.

Heterogeneous Dose-Response Analyses of Alcohol Abuse and Dependence.

BACKGROUND: Survey-based estimates of the prevalence of alcohol abuse, dependence, and disorders in the United States rely upon self-reports of drinking patterns (e.g., binge drinking), social problems (e.g., trouble at work), physiological responses to use (e.g., tolerance), and desistance from use (e.g., withdrawal). Diagnostic criteria derived from these reports enable prevalence estimates of abuse and dependence, but moderating structural relationships among symptom groups may lead some light and moderate drinkers to appear to exhibit an alcohol use disorder (AUD). METHODS: A dynamic model of drinking and problems predicts that symptoms of dependence will moderate relationships between drinking measures and symptoms of abuse. Wave 1 National Epidemiologic Survey on Alcohol and Related Conditions data on DSM-IV diagnoses of abuse and dependence were used to test predictions from this model and assess whether moderating effects were observed among lighter and heavier drinkers (those who drink 1 to 3 vs. 4 or more drinks on average). A dose-response model that accounts for other known sources of risk heterogeneity related to drinking and problems enabled us to test these predictions. RESULTS: As expected from previous work, symptoms of abuse and dependence and dependence criteria were nonlinearly related to drinking patterns; more symptom reports appeared and criteria were met among less frequent drinkers who drank more on each occasion and this pattern of dose-response was substantially moderated among heavier drinkers. Controlling for these effects, relationships between drinking and symptoms of abuse were moderated among respondents who met more dependence criteria. These effects were observed among both lighter and heavier drinkers. CONCLUSIONS: Moderating relationships observed between measures of drinking, abuse, and dependence criteria among lighter and heavier drinkers suggest that the same etiologic forces are at play among all drinking groups. Greater symptoms of dependence among lighter drinkers may lead to greater reports of symptoms of abuse and an AUD diagnosis.

Associations between self-harm and chronic disease among adolescents: Cohort study using statewide emergency department data.

INTRODUCTION: 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.

DSM-5 Alcohol Use Disorder Severity in Puerto Rico: Prevalence, Criteria Profile, and Correlates.

BACKGROUND: Our aim was to examine lifetime criteria profiles and correlates of severity (mild, moderate, severe) of DSM-5 alcohol use disorders (AUD) in Puerto Rico. METHODS: Data are from a household random sample of individuals 18 to 64 years of age in San Juan, Puerto Rico. The survey response rate was 83%. DSM-5 AUD was identified with the Spanish version of the World Health Organization's Composite International Diagnostic Interview. The analyses also identify correlates of each severity level using an ordered logistic regression model. RESULTS: The prevalence of lifetime DSM-5 AUD among men and women was 38 and 16%, respectively. Mild lifetime DSM-5 AUD was the most prevalent severity level among both men (18%) and women (9%). The most common criteria, independent of gender and severity level, were drinking larger quantities and for longer than planned (men range: 80 to 97%; women range: 78 to 91%) and hazardous use (men range: 56 to 91%; women range: 42 to 74%). Results from ordered logistic regression showed that the adjusted odds ratio for weekly drinking frequency, greater volume of alcohol consumed per drinking occasion, positive attitudes about drinking, drinking norms, and male gender invariantly increased risks across all DSM-5 AUD severity levels (mild, moderate, severe). Greater negative attitudes about drinking, low family cohesion, and Protestant religion were related to greater risks at higher AUD severity levels. CONCLUSIONS: AUD prevalence is high in San Juan, Puerto Rico. Prevalence rates for some criteria are equally high across severity levels and poorly differentiate between mild, moderate, or severe DSM-5 AUD. The sociodemographic and alcohol-related risks vary across DSM-5 severity levels.

Space-Time Analyses of Alcohol Outlets and Related Motor Vehicle Crashes: Associations at City and Census Block-Group Levels.

BACKGROUND: Past research has linked alcohol outlet densities to drinking, drunken driving, and alcohol-related motor vehicle crashes (MVCs). Because impaired drivers travel some distances from drinking places to crash locations, spatial relationships between outlets and crashes are complex. We investigate these relationships at 3 geographic levels: census block groups (CBGs), adjacent (nearby) areas, and whole cities. METHODS: We examined risks of all injury MVCs as well as "had been drinking" (HBD) and single-vehicle-nighttime (SVN) subgroups using data from the Statewide Integrated Traffic Records System across CBGs among 50 California cities from 2001 to 2008. Relationships between outlet densities at the city level, within CBGs, and in adjacent CBGs and crashes were examined using Bayesian Poisson space-time analyses controlling for population size income and other demographics (all as covariates). RESULTS: All injury MVCs were positively related to adjacent CBG population size (relative rate [RR] = 1.008, 95% credible interval (CI) = 1.004, 1.012), and outlet densities at CBG (RR = 1.027, CI = 1.020, 1.035), nearby area (RR = 1.084, CI = 1.060, 1.106) and city levels (RR = 1.227, CI = 1.147, 1.315), and proportion of bars or pubs at the city level (RR = 2.257, CI = 1.187, 4.125). HBD and SVN crashes were comparatively less frequent in high outlet density CBG (RR = 0.993, CI = 0.987, 0.999; RR = 0.963, CI = 0.951, 0.975) and adjacent areas (RR = 0.979, CI = 0.962, 0.996; RR = 0.909, CI = 0.883, 0.936), but positively associated with city-level proportions of bars (RR = 3.373, CI = 0.736, 15.644; RR = 10.322, CI = 1.704, 81.215). Overall, a 10% increase in all outlets was related to 2.8% more injury crashes (CI = 2.3, 3.3) and 2.5% more HBDs (CI = 1.7, 3.3). A 10% increase in bars was related to 1.4% more crashes, 4.3% more HBDs, and 10.3% more SVNs. CONCLUSIONS: Population size and densities of bars or pubs were found to be associated with crash rates, with population effects appearing across cities and outlet effects appearing within dense downtown areas. Summary estimates of outlet and population impacts on MVCs must consider varying contributions at multiple spatial scales.

Spatial Epidemiology of Alcohol- and Drug-Related Health Problems Among Northern Plains American Indians: Nebraska and South Dakota, 2007 to 2012.

BACKGROUND: Despite high abstinence rates, American Indians experience elevated rates of many alcohol and other drug problems. American Indians also predominantly reside in poor and rural areas, which may explain some observed health disparities. We investigated whether geographic areas including reservations or large American Indian populations exhibited greater incidence of alcohol- and drug-related hospitalizations. METHODS: We obtained inpatient hospitalization records for 2 Northern Plain states (Nebraska and South Dakota) for the years 2007 to 2012. We constructed zip code counts for 10 categories of hospitalization with diagnoses or injury causation commonly associated with alcohol or drug use. We related these to community sociodemographic characteristics using Bayesian Poisson space-time regression models and examined associations with and without controls for whether each zip code was located within an American Indian reservation. RESULTS: Controlling for other demographic and economic characteristics, zip codes with greater percentage of American Indians exhibited greater incidence for all 10 substance abuse-related health outcomes (9 of 10 well supported); zip code areas within American Indian reservations had greater incidence of self-inflicted injury and drug dependence and abuse, and reduced incidence of alcohol cirrhosis and prescription opioid poisoning. However, the analyses generally demonstrated no well-supported differences in incidence associated with local residence percentages of American Indian versus African American. CONCLUSIONS: In our analyses, ethnicity or heredity alone did not account for alcohol- and drug-related hospitalizations among Native populations. Aspects of social, economic, and political dimensions of Native lives must be considered in the etiology of alcohol- and drug-related problems for rural-dwelling indigenous peoples.