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Blood alcohol content/concentration (BAC) is a measure of the amount of alcohol present in the blood of an individual. While the relationship between the amount of alcohol consumed and BAC may be affected by factors such as body composition (Cederbaum, 2012), metabolic tolerance (Lapham, 2010), and the ratio of alcohol-to-fluids intake (Dilley et al., 2019), BAC remains an internationally recognized objective measure of intoxication (Droste et al., 2018). Furthermore, BAC is associated with risky behavior like dangerous driving (Desapriya et al., 2003) and health problems like acute respiratory distress syndrome (Afshar et al., 2014). Prior research has probed the timing of alcohol consumption among alcohol users in the United States. Alcohol users often consume alcohol at night, which aligns with the pattern of business activity at alcohol-serving establishments (Hoeppner et al., 2012; Mustonen et al., 2016; Reed et al., 2013). Specifically, activity at these establishments and self-reported alcohol use are highest during weekend nights, peaking on Friday and Saturday nights (Hoeppner et al., 2012; Reed et al., 2013; Tremblay et al., 2010). Elevated levels of alcohol consumption and alcohol-related accidents occur around celebrations, such as a national holiday (Glindemann et al., 2007). Determining specific time periods of high BAC measurement is immensely valuable for enforcing BAC laws that have reduced the number of road accidents and fatalities (Tippetts et al., 2005). This information can also help law enforcement appropriately allocate public resources, such as setting up sobriety checkpoints, which are highly cost-efficient and have demonstrably lowered crash fatalities (Bergen et al., 2014). Policymakers may also consult BAC levels over time to consider legislative propositions for lower BAC driving limits (Wagenaar et al., 2007). Beyond public health and safety, tracking BAC levels at different times and locations informs theories about motivators for alcohol use. For example, researchers have speculated that drinkers may seek to relieve negative affect and/or stress from workdays (Ostafin & Brooks, 2011; Parker & Williams, 2003). Researchers also examined the demographics of alcohol users to assess the risk of alcohol-related harms and alcohol use disorder (AUD) in certain populations. Alcohol consumption is higher in more affluent neighborhoods, but the resources and privileges attached to higher socioeconomic status (SES) serve as protective factors that actually result in a lower rate of AUD (Calling et al., 2019). Another factor involved in the translation of BAC to real-world impact is people’s ability to self-estimate their BAC. The accuracy of self-estimated BAC levels has been the topic of an increasingly large body of literature due to its implication for avoiding excessive drinking and alcohol use interventions. Previous research indicates that alcohol users are not able to predict their level of impairment before consuming a set amount of alcohol and are unaware of how much alcohol they can consume before becoming legally impaired (Aston & Liguori, 2013). This inaccuracy in self-estimated BAC is worth investigating because it is associated with riskier driving behavior (Laude & Fillmore, 2016). Just as BAC levels vary throughout the day and differ based on location, so can the accuracy of BAC self-estimates. Given the literature on cognitive fatigue (Borragán et al., 2017), we hypothesize that BAC self-estimate is least accurate at night on weekdays because the cognitive effort during the workday has tired the participants, and the participants are no longer able to sustain the cognitive load necessary for monitoring their feelings of intoxication. In contrast, BAC self-estimates may be most accurate on weekends due to the absence of cognitive load from work. In the context of a year, the holiday season in winter could be a source of high stress and cognitive fatigue. When examining coronary data from Los Angeles County, researchers found that the number of monthly deaths in December and January was around 33% higher than the number from June to September (Kloner et al., 1999). Researchers cited stress from holidays as a potential reason for the increase in death. Following our hypothesized relationship between cognitive fatigue and BAC self-estimate accuracy, we expect BAC self-estimates to be the least accurate in the colder winter months, especially during the holiday season. BAC self-estimate training programs have been effective among moderate drinkers but not heavy drinkers (Aston & Liguori, 2013). These programs offer internal and external training: internal modules involve recognizing physiological sensations at different BAC levels; external modules involve psychoeducation on how participants’ body compositions affect their individual alcohol absorption rates. Given the disparity in training outcomes, the current project seeks to stratify the participants based on initial levels of drinking. With BAC feedback, lighter drinkers may exhibit changes in BAC level and self-estimation accuracy that differ from heavier drinkers' changes. No previous study has analyzed such a large number of objective BAC measurements and recorded BAC self-estimates nationwide. Participants used BACtrack breathalyzer products to obtain their BAC readings and consented to their data being uploaded for research purposes through the accompanying BACtrack mobile application. Other studies investigating alcohol consumption may ask participants to estimate their alcohol use in the past, but these retrospective self-reports may be unreliable (Barbosa et al., 2021). Furthermore, the same amount of alcohol consumed by different people may produce different effects, and this individual difference may be captured by the consistent use of personal breathalyzers. This data set also tracks readings of each anonymized user, which enables the present study to compare BAC levels and self-estimate accuracy within participants across different drinking sessions and within each drinking session. Prior research found that participants were able to more accurately estimate their BAC after receiving feedback from previous drinking days when controlled for BAC levels (Bullers & Ennis, 2006). Bullers and Ennis (2006) also noted that participants recorded higher BAC levels when first using breathalyzers than later in the study, which may be attributable to participants’ intentions to experiment with the breathalyzer. BAC levels dropped after the first week of using breathalyzers, and the change was larger among light drinkers than heavy drinkers. The current project is interested in patterns of change in BAC self-estimation accuracy between individual breathalyzer readings, within each participant, and across participants. |
