Alcohol to-go sales policies at on-premise drinking establishments near large public US universities during the COVID-19 pandemic.

AIMS: Sweeping policy changes during the COVID-19 pandemic increased alcohol availability through permitted to-go sales, potentially posing unique risks to college students. While to-go sales may make binge drinking more convenient, little remains known about these practices. Therefore, this study aimed to assess whether drinking establishments' to-go sales practices are associated with their other operational practices and state policy. METHOD: This cross-sectional analysis included 221 randomly selected bars, nightclubs, and restaurants within two miles of a large public university. Telephone interviews assessed establishment practices, and the Alcohol Policy Information System provided state alcohol to-go laws. Regression models tested whether establishment to-go sales practices were associated with their business practices (logistic regression) and state policy (generalized estimating equations). RESULTS: Nearly one-half (44.8%) of drinking establishments sold alcohol to-go. Establishments with higher vodka prices had nearly 30% higher odds of selling spirits to-go (aOR = 1.29) and establishments offering happy hours specials had more than twice the odds of selling beer (aOR = 2.22), wine (aOR = 2.53), and spirits to-go (aOR = 2.60). Additionally, establishments that implemented physical distance requirements had higher odds of selling wine to-go (aOR = 3.00). State to-go laws were associated with higher odds of selling wine (aOR = 3.99) and spirits to-go (aOR = 5.43) in the full sample and beer to-go (aOR = 4.92) in urban counties. CONCLUSIONS: Establishments that sell alcohol to-go tend to engage in other practices designed to drive sales. Evaluations of alcohol to-go sales laws on risky consumption among priority populations, including college students, are urgently needed to inform decisions about how to appropriately regulate sales.

Intimate partner violence and suicide mortality: a cross-sectional study using machine learning and natural language processing of suicide data from 43 states.

INTRODUCTION: Intimate partner violence (IPV) is associated with suicidal ideation, yet it remains unclear how often IPV precipitates suicide mortality. To overcome limitations with national data, we applied novel methods to: (1) document the prevalence of IPV-related suicide in the USA and (2) identify correlates for IPV-related suicide. METHODS: Using National Violent Death Reporting System data (NVDRS, 2015-2019, n=1 30 550), we recorded IPV circumstances (yes/no) by leveraging prior textual reviews of death narratives and applying a validated natural language processing tool. We could not systematically differentiate IPV perpetration versus victimisation given limited details in NVDRS. Logistic regression compared IPV-related suicides with referent group suicides (no evidence of IPV), stratified by sex. RESULTS: 7.1% of suicides were IPV related (n=9210), most were isolated suicide events (82.8%, n=7625; ie, not homicide suicide). There were higher odds of IPV circumstances when the decedent had civil legal problems (aOR for men: 3.6 (3.3 to 3.9), aOR for women: 2.6 (2.2 to 3.2)), criminal legal problems (aOR men: 2.3 (2.2 to 2.5), aOR for women: 1.7 (1.4 to 2.1)), or used a firearm (aOR men: 1.9 (1.8 to 2.0), aOR for women: 1.9 (1.7 to 2.1)). There were lower odds of IPV circumstances when the decedent had a current mental health problem (aOR men: 0.7 (0.7 to 0.8), aOR for women: 0.7 (0.6 to 0.8)). CONCLUSIONS: IPV circumstances contribute to a notable proportion of suicides. IPV-related suicides are distinct from other suicide deaths. Targeted suicide screening and intervention in IPV settings may be beneficial for prevention.

Detecting intimate partner violence circumstance for suicide: development and validation of a tool using natural language processing and supervised machine learning in the National Violent Death Reporting System.

BACKGROUND: Intimate partner violence (IPV) victims and perpetrators often report suicidal ideation, yet there is no comprehensive national dataset that allows for an assessment of the connection between IPV and suicide. The National Violent Death Reporting System (NVDRS) captures IPV circumstances for homicide-suicides (<2% of suicides), but not single suicides (suicide unconnected to other violent deaths; >98% of suicides). OBJECTIVE: To facilitate a more comprehensive understanding of the co-occurrence of IPV and suicide, we developed and validated a tool that detects mentions of IPV circumstances (yes/no) for single suicides in NVDRS death narratives. METHODS: We used 10 000 hand-labelled single suicide cases from NVDRS (2010-2018) to train (n=8500) and validate (n=1500) a classification model using supervised machine learning. We used natural language processing to extract relevant information from the death narratives within a concept normalisation framework. We tested numerous models and present performance metrics for the best approach. RESULTS: Our final model had robust sensitivity (0.70), specificity (0.98), precision (0.72) and kappa values (0.69). False positives mostly described other family violence. False negatives used vague and heterogeneous language to describe IPV, and often included abusive suicide threats. IMPLICATIONS: It is possible to detect IPV circumstances among singles suicides in NVDRS, although vague language in death narratives limited our tool's sensitivity. More attention to the role of IPV in suicide is merited both during the initial death investigation processes and subsequent NVDRS reporting. This tool can support future research to inform targeted prevention.

Typology of Adolescents Exposed to Non-medical Cannabis Marketing and Associations with Consumption Patterns.

Latent class analysis (LCA) identified subtypes of cannabis marketing exposure among adolescents and assessed whether the classes were associated with three cannabis use outcomes: past 28-day use, poly-cannabis use, and symptoms of cannabis use disorder (CUD). Survey data were from 471 adolescents (aged 15-19 years) who lived in four states with legal non-medical cannabis in 2018. Measures included social media engagement and cannabis outcomes. LCA with robust maximum likelihood estimation identified latent classes. Chi-squared tests assessed whether empirically derived classes differed across demographics, and logistic regression tested associations with cannabis use outcomes. Three classes were identified: digitally engaged (35.5%), digitally unengaged (36.5%), and traditional (28.0%). Both digitally engaged and unengaged classes were exposed to marketing on social media platforms, but youth in the engaged class interacted with posts and brands. Class membership differed by age (χ2 = 14.89, p < 0.001) and school type, with the digitally engaged group older and not in school or in non-traditional schools (χ2 = 16.22, p=0.01). As compared to the traditional class, youth in the digitally engaged class had 10.63 times the odds of past 28-day cannabis use (95% CI: 5.25, 21.51), 7.84 times the odds of poly-cannabis use (95% CI: 3.54, 17.33), and 13.85 times the odds of symptoms of CUD (95% CI: 3.96, 48.48). Youth in the digitally engaged class had higher odds of all cannabis use behaviors than the traditional class. These findings point to the possible use of algorithmic marketing to adolescents and suggest a need for monitoring and possible restrictions on digital cannabis marketing.

Eye-tracking to examine differences in alcohol product appeal by sex among young people.

Background: Advertising of traditional alcopops contains elements that appeal to youth, especially females. Supersized alcopops are marketed differently than traditional alcopops and contain up to 5.5 standard alcoholic drinks. Young females are more likely to underestimate the alcohol content of supersized alcopops, putting them at higher risk of overconsumption. Similar to supersized alcopops, beer is packaged in large cans and in the same areas of store shelves.Objective: This study examined among young people whether supersized alcopops versus beer products disproportionately appealed to females.Methods: Eleven adolescents (13-17 years old) and 72 college students (21-26 years old) were recruited during 2019-2020. Participants viewed 19 photos of convenience store display cases containing both supersized alcopop and beer products. While viewing each image, participants were instructed to click on the beverage that looked the "coolest" (i.e. most appealing). Eye-tracking hardware and software measured the amount of time participants visually fixated on each product. Participants completed a survey to record demographic characteristics.Results: Compared to males (n=25), females (n=58) fixated on supersized alcopops for 6.8 seconds longer (95%CI 0.3,13.3). Females also had 3.7 times the odds of selecting a supersized alcopop as the product they found most appealing compared to males (95%CI 1.68,8.01), adjusting for amount of time visually fixating on supersized alcopops, which was also a significant predictor.Conclusions: Young females' strong preference for supersized alcopops is concerning given they disproportionately underestimate their potency, relative to males, and are more likely to obtain dangerously high BAC levels from consuming one or two supersized alcopops.

Excise Taxes as a Policy Lever for Reaching Healthy North Carolina 2030 Targets.

Excise taxes can raise the price of unhealthy products, reducing consumption and associated health risks and costs. Raising state excise taxes on tobacco, alcohol, and sugary drinks and allowing local governments to do the same are win-win strategies for achieving three Healthy North Carolina 2030 health behavior targets while increasing state revenues.

The Societal Cost of Excessive Drinking in North Carolina, 2017.

BACKGROUND Excessive drinking, including binge and heavy drinking, is a leading cause of morbidity and mortality in North Carolina. In 2010, excessive drinking cost North Carolina $7.03 billion, and this analysis aimed to update this figure for 2017.METHODS Following the methods of Sacks, et al. (2015), we obtained proxies for the 2010 and 2017 incidence and price for 26 alcohol-attributable cost components. We then multiplied each component's 2010 cost by the incidence trend (2017 incidence/2010 incidence) and price trend (2017 price/2010 price) to estimate the 2017 cost. Finally, we summed these cost components to calculate the total cost and allocated them by payer and county.RESULTS Excessive drinking cost $9.72 billion in North Carolina in 2017, which equals approximately $2.09 per standard drink. Government paid $4.43 billion (45.6%), drinkers paid $3.76 billion (38.7%), and persons other than the drinker paid $1.53 billion (15.7%).LIMITATIONS These methods relied on alcohol-attributable fractions, which were calculated using scientific literature and national data. If consumption patterns differ between the United States and North Carolina, these fractions may not generalize. Scaling processes may over- or underestimate individual cost components, so total state costs should be interpreted as estimates.CONCLUSIONS The societal costs from excessive drinking are high but spread across public sectors. This can make it difficult to attribute this burden to alcohol. While drinkers paid less than half of the costs of excessive drinking, a broad range of stakeholders bore the burden. Evidence-based strategies to reduce excessive drinking may decrease these costs.

Support for Alcohol Policies in Marginalized Populations.

AIM: Kingdon [(2014) Agendas, Alternatives, and Public Policies. Essex. United Kingdom: Pearson Education Limited] argues that windows of opportunity to pass policies emerge when problems, solutions and policy support co-occur. This study aims to identify a set of alcohol policies with the potential to reduce alcohol-related disparities given high levels of support from marginalized groups, such as racial/ethnic minorities and lower-income groups. METHODS: This study used data from five US National Alcohol Surveys, which were based on household probability samples of adults in 1995 (n = 4243), 2000 (n = 5736), 2005 (n = 1445), 2010 (n = 4164) and 2015 (n = 4041). We used multiple logistic regression to determine the odds of policy support by racial/ethnic group and income level, considering price, place and marketing policies as well as individual-level interventions. RESULTS: Overall a majority of Americans supported banning alcohol sales in corner stores (59.4%), banning alcohol advertisements on television (55.5%), and establishing universal health coverage for alcohol treatment (80.0%). Support was particularly high among Blacks, Hispanics/Latinos and lower-income persons. Multivariate models showed that compared with White people, foreign-born Hispanics/Latinos had the most robust levels of support, including raising alcohol taxes (aOR = 2.40, 95% CI: 2.00, 2.88, P < 0.0001), banning alcohol sales in corner stores (aOR = 2.85, 95% CI: 2.22, 3.65, P < 0.0001) and reducing retail sales hours (aOR = 2.91, 95% CI: 2.38, 3.55, P < 0.0001). CONCLUSION: Of the policies examined, banning alcohol sales at corner stores is most likely to be in a "window of opportunity" for reducing alcohol-related disparities. By simultaneously reducing population-level consumption and harms from others' drinking, place-based policies have the potential to reduce harms experienced by marginalized groups.

Interested constituents: identifying groups to mobilize in community organizing efforts to strengthen alcohol control policies.

Background: Policy support research identifies demographic profiles of those who support policies, but community organizers aim to mobilize groups with an existing structure. Thus, identifying established groups that support alcohol policies may aid organizing efforts.Objective: This paper calculates prevalence and odds of policy support among three potential constituency groups (i.e., religious affiliation, persons harmed by others' drinking, and persons in recovery from alcohol) for three policies: alcohol tax increases, banning alcohol in corner stores, and universal coverage for alcohol treatment.Methods: Using the 2014-15 National Alcohol Survey (n = 3,444; 1,457 male, 1,987 female) and logistic regression, this study explores associations between constituency groups and policy support.Results: Support was higher for the individual-level strategy of alcohol treatment (80.8%) than raising taxes (27.5%) and banning sales in corner stores (52.2%). Support for taxes was higher among persons who valued religion highly (vs not; aOR = 1.46, p < .01), persons harmed by others' drinking (vs not; aOR = 1.71, p < .001), and persons in recovery (vs. not; aOR = 1.76, p = .02); Catholics had lower odds of support for taxes (vs no denomination; aOR = 0.63, p = .01). Persons who valued religion highly (aOR = 1.53, p < .001), Protestants (aOR = 1.63, p < .01), Catholics (aOR = 1.46, p = .03), and persons with other religious denominations (aOR = 2.17, p = .02) had higher odds of supporting bans in corner stores. Only those in recovery showed greater support for treatment (aOR = 3.20, p < .001).Conclusion: Overall, support was lower for population-wide approaches, but results revealed constituency groups that supported these policies. These groups may be allies to organizers who seek to reduce population-level alcohol consumption and harms.

The Health Impact of Alcohol on American Cities: Modeling the Local Burden of Current Alcohol Use in One Jurisdiction.

Measurement of alcohol use and associated harms at the city level is often incomplete or non-existent even though such data are often critical to informing local prevention strategies. This paper models how to generate local estimates of the morbidity, mortality, and cost of current alcohol use instead of abstaining. Administrative data sources, including medical examiner records, hospital records, and police records, among others, were used to obtain local estimates of alcohol-attributable outcomes. In 2018, we used alcohol-attributable fractions and scaled national estimates to quantify the burden of current alcohol use in Baltimore, MD, in 2013. Fifty-two percent of Baltimore adults reported past 30-day drinking. There were 276 alcohol-attributable deaths in 2013, and 106 (38.4%) of these were persons other than the drinker. In 2013, current alcohol use cost $582.3 million in Baltimore City. This burden was distributed across drinkers (40.1%), persons other than the drinker (21.3%), and the government (38.6%). It is possible to quantify this burden at the local level, and these data could be used to inform evidence-based alcohol policy strategies at the local level.