Anna K. Piazza-Gardner

Drunkorexia: Understanding the Co-Occurrence of Alcohol Consumption and Eating/Exercise Weight Management Behaviors.

Abstract Objective: Examine the co-occurrence of alcohol consumption, physical activity, and disordered eating behaviors via a drunkorexia perspective. Participants: Nationally representative sample (n = 22,488) of college students completing the Fall 2008 National College Health Assessment. Methods: Hierarchical logistic regression was employed to determine if physical activity and disordered eating behaviors uniquely predicted binge drinking, while controlling for age, race, gender, year in college, Greek membership, and place of residence. Results: Physical activity and disordered eating made unique, statistically significant contributions. Moreover, including physical activity and disordered eating behaviors allowed for the correct classification of an additional 431 cases (ie, binge drinkers) over and above the predictive ability of the covariate-only model. Conclusions: Findings corroborate prior research indicating highly active college students are more likely to binge drink than their nonactive peers, and highlight the potential of a drunkorexia perspective in explaining the counterintuitive alcohol–activity association among college students.

The impact of alcohol on Alzheimer's disease: A systematic review

Currently, there is discrepancy regarding alcohols impact on Alzheimers disease (AD). Consequently, the purpose of this systematic review was to determine whether alcohol serves as a protective agent against the development of AD, as well as whether protective effects are influenced by quantity and/or frequency of drinking. Adapted versions of the Matrix Method and PRISMA guidelines were used in order to identify, organize, and synthesize relevant research. Overall, there is no consensus regarding alcohols impact on AD. Specifically, seven articles suggested drinking alcohol decreases the risk of AD, three studies found drinking led to an increased risk of AD, and yet another nine reported alcohol had no impact on AD. Validity and consistency of both alcohol and AD measures across studies represents a severe limitation. Prior to the development of standards and/or clinical recommendations, more investigations into the association between alcohol and AD are necessary. Considering the current evidence base, alcohol should not be used as a means to decrease risk of developing AD.

Examining Physical Activity Levels and Alcohol Consumption: Are People Who Drink More Active?:

Objective. Summarize/categorize current scientific literature examining the association between alcohol consumption (AC) and levels of physical activity (PA). Data Source. Electronic databases spanning education, psychology, sociology, medicine, and interdisciplinary reports. Study Inclusion and Exclusion Criteria. Included studies (n = 17) must be published in a peer-reviewed, English language journal; measure either AC or PA as an independent/dependent variable; and primarily examine the relationship between AC and PA. Data Extraction. Search terms/phrases included alcohol, alcohol consumption, drinking, physical activity, exercise, and physically active. Data Synthesis. The Matrix Method and PRISMA guidelines organized pertinent literature and identified/extracted salient findings. Results. Alcohol consumers of all ages were more physically active than nondrinking peers. Further, several studies suggest a dose-response relationship between AC and PA, indicating that as drinking increases, so does PA level. Conclusion. Reviewed studies support a positive association between AC and PA across all ages. Findings were contrary to the hypothesis of the investigators. Future research should place specific emphasis on identifying why alcohol consumers exercise at higher levels than non–alcohol consumers.

Validity and Reliability Reporting Practices in the Field of Health Education and Behavior A Review of Seven Journals

Health education and behavior researchers and practitioners often develop, adapt, or adopt surveys/scales to quantify and measure cognitive, behavioral, emotional, and psychosocial characteristics. To ensure the integrity of data collected from these scales, it is vital that psychometric properties (i.e., validity and reliability) be assessed. The purpose of this investigation was to (a) determine the frequency with which published articles appearing in health education and behavior journals report the psychometric properties of the scales/subscales employed and (b) outline the methods used to determine the reliability and validity of the scores produced. The results reported herein are based on a final sample of 967 published articles, spanning seven prominent health education and behavior journals between 2007 and 2010. Of the 967 articles examined, an exceedingly high percentage failed to report any validity (ranging from 40% to 93%) or reliability (ranging from 35% to 80%) statistics in their articles. For health education/behavior practitioners and researchers to maximize the utility and applicability of their findings, they must evaluate the psychometric properties of the instrument employed, a practice that is currently underrepresented in the literature. By not ensuring the instruments employed in a given study were able to produce accurate and consistent scores, researchers cannot be certain they actually measured the behaviors and/or constructs reported.

The impact of pregaming on subsequent blood alcohol concentrations: an event-level analysis.

Pregaming has been highlighted as an especially deleterious college drinking ritual. The present study assessed (a) event-level associations between pregaming and biologic samples of blood alcohol concentration (BrAC) and (b) the impact of ones alcohol-related behaviors (measured by AUDIT-C scores) on the likelihood that respondents would report pregaming prior to a night out drinking. The sample included adult (n=1029; collegiate and non-college-affiliated) bar patrons in a southeastern college community. Multiple and linear regressions were conducted to determine the association between pregaming and BrAC levels, and pregaming and the presence of an alcohol use disorder, respectively. After controlling for the influence of time of data collection, gender, age, college student status, and ethnicity, the linear regression model explained 15.5% (R2=.155) of the variance in BrAC levels (F (10, 915)=16.838, p<0.001), of which 10.8% was accounted for by self-reported pregaming alone. Furthermore, pregamers exhibited significantly higher BrACs compared to non-pregamers (β=.332, p<.001). Logistic regression analyses indicated that AUDIT-C scores were the only significant predictor of pregaming status (OR=1.305, Wald=64.843), such that respondents with higher AUDIT-C scores (B=0.266) were more likely to pregame. This event-level study highlights the practice of pregaming as an insidious behavior associated with enhanced levels of drinking behavior and overall intoxication.

Gender Differences in the Associations Among Body Mass Index, Weight Loss, Exercise, and Drinking Among College Students

Abstract Objective: To explore gender differences regarding weight management behaviors of college drinkers. Participants: Nationally representative sample of college students from the fall 2008 American College Health Associations National College Health Assessment II (N = 26,062 students). Methods: Structural equation modeling was used to examine potential gender differences in associations among exercise, weight loss behaviors, and alcohol use. Results: Critical ratio tests revealed that associations between exercise and weight loss behaviors were more strongly correlated among females as compared with males. For females, there was a small negative association between exercise and drinking behaviors; in contrast, for males, there was a positive relationship between exercise and alcohol use. Weight loss behaviors were positively associated with drinking for both female and male students; however, the association was significantly stronger for females. Conclusions: This investigation furthers previous research on drunkorexia and also sheds additional light on the gender-based differences in weight management behaviors of drinkers.

Covariates of alcohol consumption among career firefighters

BACKGROUND Little is known about rates of alcohol consumption in career firefighters. AIMS To assess the quantity and frequency of alcohol consumption among career firefighters and the covariates that influence consumption levels. METHODS A convenience sample of career firefighters completed an online, self-administered, health assessment survey. Hierarchical binary logistic regression assessed the ability of several covariates to predict binge drinking status. RESULTS The majority of the sample (n = 160) consumed alcohol (89%), with approximately one-third (34%) having a drinking binge in the past 30 days. The regression model explained 13-18% of the variance in binge drinking status and correctly classified 71% of cases. Race (P < 0.05) and time of service (P < 0.01) were the only covariates that made a statistically significant contribution to the model. After controlling for other factors in the model, white respondents were ~4.5 times more likely to binge drink than non-white respondents (95% CI: 1.15-17.4). For each additional year of service, firefighters were 1.08 times less likely to binge drink (95% CI: 0.87-0.97). CONCLUSIONS Drinking levels observed in this study exceed those of the general adult population, including college students. Thus, it appears that firefighters represent an at-risk drinking group. Further investigations addressing reasons for alcohol use and abuse among firefighters are warranted. This study and subsequent research will provide information necessary for the development and testing of tailored interventions aimed at reducing firefighter alcohol consumption.

Appropriate Terminology for the Alcohol, Eating, and Physical Activity Relationship

Abstract “Drunkorexia” merges prior literature identifying positive relationships between (a) alcohol use/abuse and disordered eating/eating disorders, (b) alcohol use/abuse and physical activity, and (c) disordered eating/eating disorders and physical activity. The term, highlighting an individuals proactive and/or reactive weight management behaviors (ie, disordered eating, physical activity) in relation to alcohol consumption, originated in news editorials and has recently gained recognition via use in scholarly publications. The purpose of this commentary is to recommend discontinuing use of the term “drunkorexia” due to (a) inconsistent definitions of drunkorexia across investigations, (b) drunkorexia being a misnomer, and (c) the medical communitys lack of recognition/acceptance of drunkorexia. Because the behaviors encompassed by drunkorexia are of concern to researchers and health professionals, future investigations are still warranted. However, until a medically recognized term/phrase is accepted, scholars should utilize more appropriate characterizations such as “weight-conscious drinkers,” “weight management behaviors of drinkers,” or “Eating Disorders Not Otherwise Specified” (Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition, Text Revision).

Alcohol use among college athletes: do intercollegiate, club, or intramural student athletes drink differently?

Background: Varsity student athletes are a high-risk drinking group, exhibiting a greater propensity to binge drink than their non-sport peers. Moreover, as intercollegiate athletic involvement increases, so too does alcohol consumption. There is little research, however, which examines drinking behaviors of students who participate in nonvarsity athletics. Objectives: Identify differences in alcohol-related behaviors and associated consequences among U.S. varsity, club, and intramural athletes, and nonathlete college students. Methods: Secondary data analysis of the 2011 National College Health Assessment (n = 29,939). Results: Intramural athletes binge drank more frequently (M = 1.1, SD = 1.7) than club athletes (M = 1.0, SD = 1.6), intercollegiate athletes (M = 0.9, SD = 1.5), and nonathletes (M = 0.6, SD = 1.3) and also experienced greater alcohol-related consequences. Intramural athletes consumed the most during their last drinking episode (M = 4.1, SD = 4.0) and reached the highest blood alcohol concentration (BAC) (M = 0.062, SD = 0.09).Compared to club and varsity athletes [M = 0.8, SD = 1.4; t (8,131) = −9.6, p < .001], intramural-only athletes reported binge drinking significantly more frequently (M = 1.2, SD = 1.7) and also reached significantly higher BACs during most recent drinking episode (M = 0.064, SD = 0.08) than organized sport athletes [M = 0.057, SD = 0.08; t (8,050) = −3.0, p = .003]. Conclusions: Intramural athletes represent a higher-risk drinking group than other athlete and nonathlete college students. Future research should investigate factors contributing to drinking differences among different athlete groups.

Assessing the alcohol–BMI relationship in a US national sample of college students

Objective: This study sought to assess the body mass index (BMI)–alcohol relationship among a US national sample of college students. Design: Secondary data analysis using the Fall 2011 National College Health Assessment (NCHA). Setting: A total of 44 US higher education institutions. Methods: Participants included a national sample of college students (N = 27,774). BMI, frequency of alcohol consumption and binge drinking were measured based on responses to items in the NCHA. T-tests and two-way analysis of variance (ANOVA) identified differences in BMI based on drinking status and sex. Results: Drinkers exhibited significantly lower BMIs than non-drinkers, t(26,968) = 5.55, p < .001. Binge drinkers exhibited significantly lower BMIs than non-binge-drinkers, t(27,094) = 2.64, p < .001. A significant interaction for drinking frequency and sex existed, F(5, 20,434) = 4.121, p = .001, but no interaction effect was present for sex and binge drinking frequency. Respondents drinking 1–20 days/month had lower BMIs compared to non-drinkers. Furthermore, frequency of past month drinking (β = −.08, p < .001) made a unique contribution to explaining BMI, such that BMI decreased as the days one consumed alcohol increased. Conclusion: Non-drinkers exhibited significantly higher BMIs than drinkers, regardless of whether consumption was measured as drinking status, frequency of past 30 day use, or binge drinking frequency. Findings build on previous literature which has produced mixed results depending on the operationalisation of alcohol use. Future research into why differences exist in BMI among drinkers versus non-drinkers is warranted.