Sociodemographic correlates of energy drink consumption with and without alcohol: results of a community survey. Addict Behav 2011 May;36(5):516-9
Date
02/01/2011Pubmed ID
21276661Pubmed Central ID
PMC3073443DOI
10.1016/j.addbeh.2010.12.027Scopus ID
2-s2.0-79951850633 (requires institutional sign-in at Scopus site) 101 CitationsAbstract
OBJECTIVE: We examined the sociodemographic correlates of energy drink use and the differences between those who use them with and without alcohol in a representative community sample.
METHODS: A random-digit-dial landline telephone survey of adults in the Milwaukee, Wisconsin area responded to questions about energy drink and alcohol plus energy drink use.
RESULTS: Almost one-third of respondents consumed at least one energy drink in their lifetime, while slightly over 25% used energy drinks in the past year and 6% were past-year alcohol plus energy drink users. There were important racial/ethnic differences in consumption patterns. Compared to non-users, past-year energy drink users were more likely to be non-Black minorities; and past-year alcohol plus energy drink users when compared to energy drink users only were more likely to be White and younger. Alcohol plus energy drink users also were more likely to be hazardous drinkers.
CONCLUSIONS: Our results which are among the first from a community sample suggest a bifurcated pattern of energy drink use highlighting important population consumption differences between users of energy drinks only and those who use alcohol and energy drinks together.
Author List
Berger LK, Fendrich M, Chen HY, Arria AM, Cisler RAAuthors
Ron Cisler PhD Professor in the Health Informatics & Administration, Public Health department at University of Wisconsin - MilwaukeeMichael Fendrich PhD Professor in the Emergency Medicine department at Medical College of Wisconsin
MESH terms used to index this publication - Major topics in bold
AdolescentAdult
Aged
Aged, 80 and over
Alcohol Drinking
Alcoholic Beverages
Beverages
Caffeine
Central Nervous System Stimulants
Data Collection
Female
Humans
Logistic Models
Male
Middle Aged
Prevalence
Risk-Taking
Socioeconomic Factors
Statistical Distributions
Wisconsin
Young Adult
