BACKGROUND: Attentional bias (AB) is an implicit selective attention toward processing disorder-significant information while neglecting other environmental cues. Considerable empirical evidence highlights the clinical implication of AB in the onset and maintenance of substance use disorder. An innovative method to explore direct measures of AB relies on the eye-movement activity using technologies like eye-tracking (ET). Despite the growing interest regarding the clinical relevance of AB in the spectrum of alcohol consumption, more research is needed to fully determine the AB patterns and its transfer from experimental to clinical applications. The current study consisted of three consecutive experiments. The first experiment aimed to design an ad-hoc visual attention task (VAT) consisting of alcohol-related and neutral images using a nonclinical sample (n = 15). The objective of the second and third experiments was to analyze whether the effect of type of image (alcohol-related vs. neutral images) on AB toward alcohol content using the VAT developed in the first experiment was different for type of drinker (light vs. heavy drinker in the second experiment [n = 30], and occasional social drinkers versus alcohol use disorder (AUD) patients in the third experiment [n = 48]).
METHODS: Areas of interest (AOIs) within each type of image (neutral and alcohol-related) were designed and raw ET-based data were subsequently extracted through specific software analyses. For experiment 1, attention maps were created and processed for each image. For experiments 2 and 3, data on ET variables were gathered and subsequently analyzed through a two-way ANOVA with the aim of examining the effects of the type of image and drinker on eye-movement activity.
RESULTS: There was a statistically significant interaction effect between type of image and type of drinker (light vs. heavy drinker in experiment 2, F(1, 56) = 13.578, p < 0.001, partial η2 = 0.195, and occasional social drinker versus AUD patients in the experiment 3, F(1, 92) = 35.806, p < 0.001, partial η2 = 0.280) for \"first fixation\" with large effect sizes, but not for \"number of fixations\" and \"dwell time.\" The simple main effect of type of image on mean \"first fixation\" score for AUD patients was not statistically significant.
CONCLUSIONS: The data derived from the experiments indicated the importance of AB in sub-clinical populations: heavy drinkers displayed an implicit preference for alcohol-related images compared to light drinkers. Nevertheless, AB fluctuations in patients with AUD compared to the control group were found. AUD patients displayed an early interest in alcohol images, followed by an avoidance attentional processing of alcohol-related images. The results are discussed in light of recent literature in the field.

BACKGROUND: Most clinical studies of alcohol use disorder (AUD) treatment have short follow-up periods, underestimating the full benefits of alcohol treatment. Furthermore, clinical studies only consider one treatment cycle and do not account for the need for multiple episodes to treat a chronic recurrent condition.
METHODS: A validated microsimulation model of the long-term drinking patterns of people with AUD in the United States simulated 10,000 individuals resembling those from a large clinical trial. The model was used to assess the impact of (1) 1-year, 5-year, and lifetime horizon on alcohol treatment cost-effectiveness estimates and (2) no, one, two, four, and unlimited additional treatment episodes on alcohol treatment cost-effectiveness estimates. Model outcomes included healthcare costs, crime costs, labor market productivity, life expectancy, quality-adjusted life years (QALYs), alcohol-related hospitalizations, and deaths. Cost-effectiveness analyses were conducted for two perspectives: a healthcare perspective that included costs from hospitalization and AUD treatment, and a broader societal perspective that also included crime costs and productivity.
RESULTS: The incremental cost per additional QALY gained for alcohol treatment compared with no treatment decreased from $55,590 after 1 year to $78 when healthcare costs and QALYs were tracked over the lifetime, that is, treatment became more cost effective. Treatment was cost saving for any time frame when the impacts on crime and labor productivity were also accounted for in a societal perspective. Access to multiple treatment episodes dominated (i.e., it was more effective and less costly) than no-treatment and one-episode scenarios. From a healthcare perspective, incremental costs per additional QALY for increasing from a maximum of two to four treatment episodes was $499 and from four to unlimited episodes was $5049. The unlimited treatment scenario dominated all others from a societal perspective. Results were robust in sensitivity analyses.
CONCLUSIONS: A long-term perspective and multiple episodes of alcohol treatment improve cost-effectiveness estimates. When societal impacts are included, alcohol treatment is cost saving. Results support the value of alcohol treatment.

BACKGROUND: Alcohol use disorder (AUD) has been described as a chronic disease given the high rates that affected individuals have in returning to drinking after a change attempt. Many studies have characterized predictors of aggregated alcohol use (e.g., percent heavy drinking days) following treatment for AUD. However, to inform future research on predicting drinking as an AUD outcome measure, a better understanding is needed of the patterns of drinking that surround a treatment episode and which clinical measures predict patterns of drinking.
METHODS: We analyzed data from the Project MATCH and COMBINE studies (MATCH: n = 1726; 24.3% female, 20.0% non-White; COMBINE: n = 1383; 30.9% female, 23.2% non-White). Daily drinking was measured in the 90 days prior to treatment, 90 days (MATCH) and 120 days (COMBINE) during treatment, and 365 days following treatment. Gradient boosting machine learning methods were used to explore baseline predictors of drinking patterns.
RESULTS: Drinking patterns during a prior time period were the most consistent predictors of future drinking patterns. Social network drinking, AUD severity, mental health symptoms, and constructs based on the addiction cycle (incentive salience, negative emotionality, and executive function) were associated with patterns of drinking prior to treatment. Addiction cycle constructs, AUD severity, purpose in life, social network, legal history, craving, and motivation were associated with drinking during the treatment period and following treatment.
CONCLUSIONS: There is heterogeneity in drinking patterns around an AUD treatment episode. This study provides novel information about variables that may be important to measure to improve the prediction of drinking patterns during and following treatment. Future research should consider which patterns of drinking they aim to predict and which period of drinking is most important to predict. The current findings could guide the selection of predictor variables and generate hypotheses for those predictors.

Africa is the continent most affected by esophageal cancer in the world. Alcoholic beverages are controversially blamed, as esophageal cancer is a rare disease in several other countries ranked in the top 10 for consumption of alcoholic beverages. This study aims to conduct a comprehensive systematic review of published literature, statistically summarizing the strength of the association between drinking patterns and types, and the risk of esophageal cancer in Africa. A computerized search of reputable databases such as Medline/PubMed, EMBASE, Web of Science, and African Journals Online was performed to identify relevant studies published up to September 2023. The quality of the studies was evaluated using the Newcastle-Ottawa scale for case-control studies and the Agency for Healthcare Research and Quality tool for cross-sectional studies. A funnel plot and Egger test were utilized to assess potential publication bias. Meta-analyses were conducted using random-effects models with RevMan 5.3 and Stata software to estimate summary effects. The systematic review identified a total of 758,203 studies, primarily from Eastern and Southern Africa. The pooled samples across all studies comprised 29,026 individuals, including 11,237 individuals with cancer and 17,789 individuals without cancer. Meta-analysis revealed a significant association between alcohol consumption and the risk of esophageal cancer (odds ratio [OR] = 1.81; 95% confidence interval [CI], 1.50-2.19). Further analysis based on the frequency of alcoholic beverage consumption indicated a stronger association with daily (OR = 2.38; 95% CI, 1.81-3.13) and weekly (OR = 1.94; 95% CI, 1.32-2.84) drinkers in contrast to occasional drinkers (OR = 1.02; 95% CI, 0.81-1.29). Additionally, consumption of traditional alcoholic beverages was significantly associated with the risk of esophageal cancer in African populations (OR = 2.00; 95% CI, 1.42-2.82). However, no relationship has been established between the exclusive consumption of non-traditional drinks and the risk of esophageal cancer. In conclusion, the results of this study confirm the hypothesis that daily and weekly drinking patterns, significantly increase the risk of esophageal cancer in Africa, while occasional consumption does not show a significant association. Additionally, the consumption of traditional alcoholic beverages is notably linked to the risk of esophageal cancer in African populations.

Aims: The Alcohol Use Disorders Identification Test (AUDIT) is one of the most widely used screening instruments worldwide. Although it was translated into many languages, not many country-specific adaptations exist, and a formal validation procedure of the Russian version has been carried out only recently. The present contribution documents the different steps taken to formally translate and adapt a Russian-specific version of the AUDIT (RUS-AUDIT). Methods: The AUDIT was translated into Russian following an established protocol, revised and adapted to the country context using an expert panel, and field-tested in an iterative approach, in line with WHO rules on instrument translation and adaptation A total of three pilot phases were carried out on 134 patients from primary healthcare (PHC) and 33 patients from specialised alcohol treatment facilities (narcology), guided by a specially established advisory board. Changes in each version were informed by the findings of the previous pilot phase and a thorough panel discussion. Results: Based on the findings of three different pilot phases, the RUS-AUDIT was developed as a paper-and-pencil interview for PHC professionals. Since various issues with representation and counting of standard drinks for the second test item arose, a special show card was developed to support the assessment. Preliminary AUDIT-C scores indicated that more than one-third of the screened women (34.2%) and about half of the screened men (50.9%) from PHC facilities have exceeded risk thresholds. Conclusions: The RUS-AUDIT was constructed as a feasible assessment tool for interviewers and patients. The large number of PHC patients who exceed the risk threshold has corroborated the need for formal validation and Russia-specific cut-off scores, considering the specific drinking patterns.

The incidence of stroke in China is increasing, along with a clear trend in the prevalence of risk factors. Alcohol consumption is also a risk factor for stroke. Many cohort studies have explored the relationship between alcohol consumption and stroke risk. However, findings have been inconsistent.
We used cluster sampling to select 13 districts and counties (at the same level) in Chongqing, China. Then, we used stratified random sampling to distribute the number of people in each district and county. 23,308 adults aged 30-79 were recruited between October 2018 and February 2019. Follow-up was conducted through a monitoring system and questionnaires until September 2022. Information on alcohol consumption and other covariates was collected using a standardized questionnaire. Participants were asked to report their weekly frequency of drinking over the past year and weekly intake of various alcoholic beverages in general. The frequency of drinking was divided into three categories: 1-2 d/week, 3-5 d/week, and 6-7 d/week. The average daily alcohol consumption is calculated based on the amount of alcohol contained in different alcoholic beverages. It is classified as nondrinker (0 g/day), light (0 to 12 g/day), moderate (13 to 36 g/day), and high (> 36 g/day). Cox proportional hazard regression models were used to estimate the association between alcohol consumption and stroke risk. Results are shown as multivariate-adjusted hazard ratios (HRs) and 95% confidence intervals (95% CIs).
With an average follow-up of 3.80 years, there were 310 new stroke events. The incidence of total stroke was 368.69 per 100,000 person-years. Overall, after adjusting for covariates, moderate alcohol consumption (average daily alcohol consumption 13-36 g/d) was associated with a lower risk of total stroke (HR: 0.48; 95% CI: 0.25-0.92) compared with nondrinkers. The adjusted HR and 95% CI for total stroke and ischemic stroke for those who drank alcohol 6-7 days per week were 0.60(0.37, 0.96) and 0.53(0.30, 0.94), respectively. The risk of total stroke (HR: 0.39; 95% CI: 0.17-0.89) was reduced in a pattern of drinking 6-7 days per week but with a mean alcohol consumption of less than 36 g/d. There was no significant association between alcohol consumption and hemorrhagic stroke.
This study suggests moderate alcohol consumption is associated with a lower risk of total stroke. And healthy drinking patterns should be of more significant concern.

Alcohol delivery and to-go sales may contribute to changes in drinking patterns, including where and what people drink. This study tested whether home delivery and to-go alcohol purchases were associated with context- and beverage-specific consumption volumes during the first year of the COVID-19 pandemic after adjusting for pre-pandemic consumption volumes.
Data from a pre-pandemic panel were compared to a during-pandemic panel of the National Alcohol Survey (n = 1,150 adult drinkers, 52.7% female). Outcomes were past-year alcohol consumption volumes in standard drinks (overall, by beverage type, and by location). Independent variables included past-year alcohol delivery and to-go purchases (separately). Covariates comprised baseline beverage- or context-specific volume, demographics, COVID-19 impacts, and drinking motivations. Negative binomial regression tested associations between alcohol purchases and change in overall, beverage-, and context-specific consumption.
On average, respondents who had alcohol delivered (vs. not) reported consuming larger volumes overall (incidence rate ratio [IRR] = 1.58, 95% CI [1.07, 2.32], p = .02), of wine (IRR = 2.90, 95% CI [1.50, 5.63], p < .04), of spirits (IRR = 1.59, 95% CI [1.03, 2.44], p = .04), and at home (IRR = 1.59, 95% CI [1.10, 2.31], p = .01). People who bought alcohol to go (vs. not) reported larger volumes of wine (IRR = 1.41, 95% CI [1.02, 1.96], p = .04), at home (IRR = 1.60, 95% CI [1.10, 2.32], p = .01), and in bars (IRR = 4.55, 95% CI [2.55, 8.11], p < .001). Finally, people who had alcohol delivered reported drinking smaller volumes in bars (IRR = 0.49, 95% CI [0.24, 0.98], p = .04).
During the first year of the pandemic, adults who had alcohol delivered or bought it to go reported larger volumes for several locations and beverage types.

Adjusting for demographics and standard drinking measures, High Intensity Drinking (HID), indexed by the maximum quantity consumed in a single day in the past 12 months, may be valuable in predicting alcohol dependence other harms across high and low income societies. The data consisted of 17 surveys of adult (15,460 current drinkers; 71% of total surveyed) in Europe (3), the Americas (8), Africa (2), and Asia/Australia (4). Gender-disaggregated country analyses used Poison regression to investigate whether HID (8-11, 12-23, 24+ drinks) was incrementally influential, beyond log drinking volume and HED (Heavy Episodic Drinking, or 5+ days), in predicting drinking problems, adjusting for age and marital status. In adjusted models predicting AUDIT-5 for men, adding HID improved the overall model fit for 11 of 15 countries. For women, 12 of 14 countries with available data showed an improved fit with HID included. The results for the five Life-Area Harms were similar for men. Considering the results by gender, each country showing improvements in model fit by adding HID had larger values of the average difference between high intensity and usual consumption, implying variations in amounts consumed on any given day. The amount consumed/day often greatly exceeded HED levels. In many societies of varying income levels, as hypothesized, HID provided important added information on drinking patterns for predicting harms, beyond the standard volume and binging indicators.

UNASSIGNED: To analyse prevalence and trends in older people\'s (60+) alcohol use in Finland in 1993-2018.
UNASSIGNED: Data on people aged 65+ were obtained from the Health Behaviour and Health among the Finnish Elderly study (HBHFE) for the years 1993-2011 and from its successor the National FinSote Survey for the years 2013-2018. Data for 60-64-year-olds and for the reference group (20-59-year-olds) were obtained from the Health Behaviour and Health among the Finnish Adult Population (HBHFA) study for the years 1993-2011 and from the FinSote study for the years 2013-2018. Four measures were chosen to describe prevalence and trends in drinking patterns in five-year age groups among men and women aged 60+: prevalence of current drinking, prevalence of frequent drinking, typical amounts of drinking and prevalence of heavy episodic drinking (HED).
UNASSIGNED: Regarding prevalence of current drinking and frequent drinking, older women have been catching up with men, but older men still consume larger amounts of alcohol per occasion. The long-lasting increase in the prevalence of current drinkers continued in most older female age groups into the 2010s, settled in most older male and some female age groups, and shifted downwards in the oldest male age groups. In most older male and female age groups, the increasing trend in frequent drinking continued to the present. Data on typical amounts consumed and HED were only available for 2013-2018. In that period those measures remained rather stable.
UNASSIGNED: More detailed research on drinking patterns among people aged 60+ years is needed for two reasons: older people\'s drinking is a new cultural phenomenon and alcohol-related social and health harms are increasing in older age groups.

This paper explores trends in beverage preference in adolescents, identifies related regional differences, and examines cluster differences in key drinking measures. Data were obtained from the European School Survey Project on Alcohol and Other Drugs (ESPAD), covering 24 European countries between 1999 and 2019. Trends in the distribution of alcoholic beverages on the participants\' most recent drinking occasion were analysed by sex and country using fractional multinomial logit regression. Clusters of countries based on trends and predicted beverage proportions were compared regarding the prevalence of drinkers, mean alcohol volume and prevalence of heavy drinking. Four distinct clusters each among girls and boys emerged. Among girls, there was not one type of beverage that was preferred across clusters, but the proportion of cider/alcopops strongly increased over time in most clusters. Among boys, the proportion of beer decreased, but was dominant across time in all clusters. Only northern European countries formed a geographically defined region with the highest prevalence of heavy drinking and average alcohol volume in both genders. Adolescent beverage preferences are associated with mean alcohol volume and heavy drinking at a country-level. Future approaches to drinking cultures need to take subpopulations such as adolescents into account.