The Impact of Standard Nutrition Labels on Alcoholic Beverages.

ABSTRACT Whether or not to mandate nutrition labels on alcoholic beverages is a topic of debate. We examined the effect of nutrition labels on (1) plans for drinking and (2) alcohol expectancies. Study 1, n=80 underage college drinkers responded to an image of a beer with or without a nutrition label. Study 2, n=98 community drinkers responded to either: an accurate label, none, enhanced vitamin C label, extreme low-calorie label. Study 3, n=191 community drinkers compared different labels across five beverages/foods. Results showed mdl effects for labels; however, 86.1% to 87.0% preferred having information. Though participants reported not believing labels would affect drinking, they largely preferred unrealistically low-calorie alcohol. This may apply toward decisional balance. Nutrition-related approaches offer fruitful directions. Keywords: Nutrition labels, alcohol, policy, heavy drinking ********** Heavy alcohol consumption poses a worldwide public health threat (Global Status Report on Alcohol, 2011); yet the question of whether or not to mandate nutrition labels on alcoholic beverages is a topic of controversy in the U.S. (Department of the Treasury, 2013; Locke, 2011; Stromberg, 2015). For example, and as it pertains to the industry, breweries have maintained that labels disclosing carbohydrate and calorie contents--which are arguably high for many beers--may harm sales, whereas distillers support labeling if it would make liquor appear as a "diet" drink (CSPI, 2007). As it pertains to the public, there is disagreement on how much and what kind of information would pose maximum benefit to individuals (CSPI, 2003; Stromberg, 2015). Individuals' intentions and perceptions are thought to be important predictors of eventual actions such as alcohol consumption (Cooke, Dahdah, Norman & French, 2014). Specifically, under the general Theory of Planned Behavior (Ajzen, 1985; Ajzen, 1991), behaviors (e.g., health-related behaviors including alcohol and drug use, or medication use) are predicted by individuals' intentions to engage in the behavior, as well as their perceptions (i.e., attitudes or beliefs) about the behavior. These perceptions or attitudes can include: (1) attitudes about the behavior in general (e.g., beliefs about how drinking affects one's functioning and health, and what subjective and physiological effects alcohol should typically have when consumed; Fromme, Stroot & Kaplan, 1993; Knauper, Rabiau, Cohen & Patriciu, 2004), (2) attitudes about how much control one has over acting on the behavior (Leeman et al., 2014), and importantly, (3) what an individual believes are the social norms regarding the behavior (see Depue, Southwell, Betzner & Walsh, 2015). From a norms perspective, it is possible that the presence of nutrition labels--which inform individuals of consumption-based norms or standards--would provide a gentle means for individuals to personally assess their alcohol consumption and modify their actions (Kerr, McCann & Livingstone, 2015; Prochaska, et al., 1994; Rollnick & Allison, 2004). Via a similar process, labels may also help shape individuals' general beliefs about alcohol and direct them toward a health-focused and moderate approach (where alcohol-related beliefs have been shown to be associated with alcohol consumption; Kuntsche, Wiers, Janssen & Gmel, 2010; Lee, Atkins, Cronce, Walter & Leigh, 2015). Furthermore, studies have shown that college youths--who are at particular risk for heavy drinking (Johnston, O'Malley, Bachman, Schulenberg & Miech, 2014)--are relatively ignorant of nutrition information pertaining to alcohol, suggesting that additional information may have some educational utility for at-risk groups (Bui, Burton, Howlett & Kozup, 2008). However, there is a dearth of empirical work to inform the debate (Kypri, et al., 2007; Stromberg, 2015). Thus, our aim was to assess the impact of standard nutrition labels--specifically, how they may affect individuals' plans for alcohol consumption and their beliefs--in three unique samples. …