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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.

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BACKGROUND: This paper examines the association between drinking context use by Whites and Hispanics on and off the US/Mexico border and alcohol problems. METHODS: Data come from a household sample of 1209 adults 18 to 39 years of age resident in Imperial County on the California/Mexico border; and Kern, Tulare, and Madera in California's Central Valley. Data were collected on the phone or online and analyzed with an ordinal generalized linear model. RESULTS: The pattern of statistically significant associations between the frequency and the volume of drinking in different contexts varies across problem types. Furthermore, some contexts of drinking are associated with problems in more than one area. For instance, frequency of drinking at bars/pubs is associated with social problems, risky sex, and fights, but not with injuries. Injuries are associated with the frequency of drinking at home alone or with family and at restaurants. Volume of drinking at bars/pubs is also significantly associated with three different contexts: social problems, injury, and fights. But the volume of drinking at the home of friends or relatives is associated with fights only. Border location is an effect modifier, changing the effect of frequency of drinking at bars and pubs from protective to a factor of risk for social problems and fights. CONCLUSION: These results provide support for the social ecology of drinking and micro environmental factors or risk. The effect of border location on frequency of drinking in bars/pubs underlines the importance of the macro environment in problem generation.

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OBJECTIVE: To examine self-reported rates of driving under the influence (DUI) with and without arrest among border and non-border residents in California. METHODS: Data were obtained from 1,209 adults 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. Data were collected on the phone or online and analyzed with a heteroskedastic ordinal generalized linear model. RESULTS: Driving after drinking (11.1% vs. 6.5%; q = 0.04) and the lifetime DUI arrest rates were higher for men than women (10.7% vs. 4%; q = 0.001). In multivariable analysis driving after drinking and DUI arrests were not higher on the border, not higher among Hispanics than Whites, and among Hispanics, the rates were not higher among those located on the border. Income was positively associated with drinking and driving. Impulsivity was positively and significantly associated with both drinking and driving and lifetime DUI arrest. CONCLUSION: The null results suggest that DUI related risk behaviors may not be higher on the border than in other areas of California. There may be health related risk behaviors of higher prevalence in the border population than in other areas, but DUI related behavior may not be one of them.

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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.

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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.

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OBJECTIVE: The purpose of this study was to examine drug-related arrest rates in California from 2005 to 2017 with a focus on the measurement of presumptive excess arrests across areas proximate to the U.S.-Mexico border. METHOD: Arrest data come from the Monthly Arrest and Citation Register (MACR) by the California Department of Justice. U.S. Census demographic population information, and alcohol outlet data from the California Department of Alcoholic Beverage Control, were aggregated at the level of 499 Law Enforcement Reporting Areas (LERA) that contributed to the MACR report. Multivariable analyses were conducted using hierarchical Bayesian Poisson spacetime models. RESULTS: Multivariable results showed that felony and misdemeanor arrests increased with distance from the U.S.-Mexico border (felony relative rate [RR] = 1.007, 95% CI [1.003, 1.010]; misdemeanor RR = 1.013, 95% CI [1.010, 1.016]) and were greater in areas with greater outlet concentrations (felony RR = 1.008, 95% CI [1.008, 1.008]; misdemeanor RR = 1.007, 95% CI [1.007, 1.007]) and a greater percentage of bars and pubs (felony RR = 1.031, 95% CI [1.030, 1.032]; misdemeanor RR = 1.052, 95% CI [1.051, 1.053]). Areas with greater Black populations had greater felony and fewer misdemeanor arrests (felony RR = 1.078, 95% CI [1.076, 1.079]; misdemeanor RR = 0.865, 95% CI [0.864, 0.867]). Areas with greater Hispanic populations had greater misdemeanor arrests (RR = 1.008, 95% CI [1.006, 1.009]). The percentage of off-premise outlets was inversely associated with misdemeanor arrest rates (RR = 0.995, 95% CI [0.994, 0.995]). CONCLUSIONS: Although arrest rates were substantively related to the racial composition of areas across California, there was no evidence of excess drug-related arrests along border areas.

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This paper examines trends and population-level correlates of violent crime rates from 2005 to 2017 in California, including proximity to the U.S./Mexico border and alcohol outlet density. Crime data come from the Crimes and Clearances report compiled by the California Department of Justice. These and U.S. Census data were aggregated at the level of 499 Law Enforcement Reporting Areas (LERA) that contributed to the report. Reported crime rates were related to area characteristics using hierarchical Bayesian Poisson space-time models. Violent crime rates declined 16% from 2005 to 2017. Crime rates were positively related to distance to the border, total alcohol outlet density, percent outlets that are bars and pubs, percent population Black, percent population Hispanic, percent population 30-49 years of age, percent population U.S. born, percent 150% below federal poverty level, percent high school graduate, and percent houses vacant. Violent crimes were negatively related to percent total outlets that are off-premise, percent population male, percent with higher than 2017 adjusted median income, percent owner occupied houses, and lower population density. In conclusion, several population level characteristics including ethnic composition, community socioeconomic stability, and alcohol availability are associated with violent crime rates. Contrary to public perceptions, violent crime rates increase as distance to the Mexico border increases.

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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.

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