For over sixty years, the Alcohol Research Group (ARG) has been actively engaged in critically needed alcohol- and other drug-related public health research. We study drinking and other drug use and how these and other factors such as gender, race/ethnicity, sexual identity, socioeconomic disparities, and environmental differences affect health. ARG is also home to the NIAAA-funded National Alcohol Research Center and training program. A preliminary set of subgroup hierarchical multiple regression analyses were conducted.
Sociodemographic variables
A major focus of this study concerned the role of physical availability in alcohol purchase and consumption decisions. Consequently, participants were required to be of the legal drinking age so that their purchase habits (by legal means) could be assessed (Abbey, Scott, & Smith, 1993). A 2024 report from the American Association for Cancer Research concluded that more than 5% of all cancers in the U.S. are attributable to alcohol use.
What is a misconception that people have about AUD?
- These people — about 8% of the world’s population — often experience facial flushing and a rapid heartbeat after just one drink.
- As found in past research (Cahalan et al., 1969; Clark & Midanik, 1982; NIDA, 1988), men consumed significantly more alcohol than did women, as indicated by all five alcohol consumption indicators.
- A more precise test of the interactional hypothesis would be situation-specific.
- Inspection of the means indicated that while, at all ages, individuals high in coping motives drank more heavily than individuals low in coping motives, this difference diminished with increasing age.
- The unadjusted regression model included drinking motives and no/lo consumption.
- Links between alcohol and mental health have also become clearer in recent years.
Other reasons for drinking have been posited, and their relationship to environmental circumstances and alcohol consumption could also be examined. The AUDIT-C measured hazardous alcohol consumption.43 It discriminates between those at higher or lower risk of alcohol-related harm. A three-item scale captures frequency of alcohol consumption, numbers of units of alcohol consumed during a typical drinking occasion and frequency of heavy episodic drinking (six or more units of alcohol in a single drinking occasion). Responses were recoded to correspond with validated AUDIT-C scoring to produce a total score between 0 and 12, treated as a continuous variable. Non-drinkers were excluded; therefore, scores in the study sample ranged from 1 to 12. The Waksberg (1978) two-stage random digit dialing procedure was used to generate the sample.
Drinking for social reasons was assessed with four items which asked study participants the extent to which they drank alcohol in order to be sociable, to enhance the enjoyment of social situations, because the people they knew drank, and to celebrate social occasions. Age, social grade and education were treated as factors, whereas IMD was treated as a continuous variable. Ethnicity is reported descriptively (white, black, Asian, mixed heritage, other, table 1) but was not included in the regression model due to small numbers of black, Asian and other ethnically diverse groups in the sample population. Finally, we’re learning more about the impact of alcohol on women and older adults. Women have begun to catch up to men in alcohol consumption and alcohol-related harms.
Analysis
Study participants ranged in age from 21 (the minimum legal drinking age in Michigan) to 86 years, with a median age of 37 years. Thirty-three percent of study participants resided in a city, 14% lived in a suburb, 18% lived in a town, and 35% lived in a rural area. Eighty-seven percent of study participants had at least a high school education.
- Further, more older adults are binge drinking and this places them at greater risk of alcohol-medication interactions, falls, and health problems related to alcohol misuse.
- This is the first study to quantitatively explore associations between the reasons adults drink alcohol and the consumption of no/lo drinks.
- All of this has led to a better understanding of how the body changes when one misuses alcohol and the proactive actions we can take to prevent alcohol misuse.
- While ALDH2 is the most common inherited variation to affect how well someone can handle alcohol — and its’ long-term risks — it is not the only factor.
Consequently, the effects of gender, ethnicity, and age on the relationships described above were explored. As found in past research, women, Blacks, and older adults were expected to consume less alcohol than were men, Whites, and younger adults. Past research has produced conflicting results about the relationships between these demographic factors and individuals’ motives for drinking. For example, some studies have found men reporting more coping motives than women (Wechsler & McFadden, 1979).
The median household income for study participants fell in the range of $15,000 to $24,999. As an indicator of heavy alcohol consumption, study participants were asked to why alcoholics drink research insights rate how often in the past month they had consumed five or more alcoholic drinks on one day (Cahalan et al., 1969; Hilton, 1987). This question was answered using a 5-point Likert-type scale with response options ranging from “never” to “nearly every time or every time” they drank.
On average, 2% of additional variance was explained when these interaction terms were included. When coping motives were high as compared to low, individuals experiencing moderate or high levels of stress engaged in more heavy alcohol consumption. When social motives were high as compared to low, individuals whose friends were high-frequency drinkers engaged in the most heavy drinking. The unadjusted regression model included drinking motives and no/lo consumption. The adjusted model controlled for sociodemographic characteristics (gender, age, education, social grade, and IMD) and hazardous drinking (AUDIT-C).
Exploring associations between alcohol drinking motives and no/lo consumption
All “reasons” items were answered using 4-point Likert-type scales with response options ranging from “not at all important” to “very important” as reasons for drinking alcohol. Moderate drinking is typically defined by public health agencies as up to one alcoholic drink per day for women and up to two for men. A standard drink is 12 ounces of beer, 5 ounces of wine or 1.5 ounces of distilled spirits. Factors including age, genetics, body size and existing health conditions all influence how alcohol affects a person. This shift in understanding is particularly significant because it challenges deeply ingrained cultural beliefs about the healthfulness of certain alcoholic beverages. It’s becoming clear that the potential risks of alcohol consumption, even in moderate amounts, may outweigh any perceived benefits.
Understanding the gut-brain connection
People who reported drinking alcohol to be sociable drank more alcohol when their friends frequently consumed alcohol at the social gatherings they attended together. These findings demonstrate the importance of simultaneously considering personal motives for drinking alcohol and the extent to which individuals’ life circumstances correspond to these motives for drinking. Although the amount of variance explained by the interaction effects was not large, these results suggest that a focus on interactive effects can enhance the explanatory power of alcohol research and suggest an avenue for prevention and treatment efforts. As hypothesized, the interaction between stress and coping motives, and the interaction between friends’ alcohol consumption and social motives were significant predictors of all three consumption indicators.
We measured frequency of no/lo consumption as a single item.39 Participants were asked, “How often do you have an alcohol-free or low-alcohol drink (beer, wine, cider, spirits or other type of alcoholic drink under 1.2% ABV)? Participants responded on an 8-point scale, ranging from never to nearly every day. Due to low numbers responding at higher frequencies, responses were recoded as a binary variable–less than monthly/at least monthly, to capture whether respondents were a regular consumer of no/lo drinks or not.
All analyses were population weighted and tests for the key assumptions of this analysis were undertaken.57 The data breached the linearity of log-odds assumption for AUDIT-C; therefore, an exploration of higher polynomial terms for AUDIT-C was undertaken. This indicated that AUDIT-C had a quadratic relationship with the dependent variable; consequently, a linear and quadratic term for AUDIT-C was included in the model. There was no evidence of multicollinearity among independent variables using variance inflation factors (online supplemental Table 2). The discriminative power of the primary model was assessed using receiver operating characteristic area under the curve (AUC). Alcohol consumption has frequently been linked to sociodemographic factors including gender, ethnicity, and age (Cahalan et al., 1969; Clark & Midanik, 1982; Hilton, 1987).