TY - JOUR
T1 - The impact of relative residence times on the distribution of heavy drinkers in highly distinct environments
AU - Mubayi, Anuj
AU - Greenwood, Priscilla E.
AU - Castillo-Chavez, Carlos
AU - Gruenewald, Paul J.
AU - Gorman, Dennis M.
N1 - Funding Information:
Carlos Castillo-Chavez : Regents and Joaquin Bustoz Jr. Professor, School of Human Evolution and Social Change, Arizona State University, Tempe. He earned B.S., M.S. and Ph.D. degrees in mathematics from the University of Wisconsin at Stevens Point (B.S.), Milwaukee (M.S.), and Madison (Ph.D.). Professor Castillo-Chavez's research interests focus on the application of computational, modeling and mathematical approaches to problems in population biology with emphasis on ecology, epidemiology and social dynamics. His research has been funded by NIH, NSF, NSA, and the Sloan Foundation, and has been presented at universities, institutes and government agencies around the world. Professor Castillo-Chavez's publications have appeared in a variety of journals including American Journal of Veterinary Research, American Scientist, Emerging Infectious Diseases, JAMA, Mathematical Biosciences, Nature, Physica A, Physics Rev. E., Scientometrics, SIAM Journal of Applied Mathematics, Statistics in Medicine, Substance Use & Misuse, The Journal of Mathematical Biology , and The Journal of Theoretical Biology . Professor Castillo-Chavez is a fellow of the American Association for the Advancement of Science (AAAS), is the recipient of two White House Awards (1992, 1997) and the 2007 AAAS Mentor award.
Funding Information:
Paul J. Gruenewald : Senior Research Scientist and Scientific Director of the Prevention Research Center, Pacific Institute for Research and Evaluation, Berkeley, CA. He earned a B.S. from the University of Georgia, Athens, and the Ph.D. (Experimental Psychology) from Duke University, Durham, NC. His research focuses on the social, economic and physical availability of alcohol, alcohol use, and related problems. Additional foci include mathematical models of alcohol use and related problems, evaluation methodologies appropriate to community-based preventive interventions, and environmental prevention. Dr. Gruenewald is Principal Investigator on the ÒEnvironmental Approaches to Prevention Ó Research Center grant from the National Institute on Alcohol Abuse and Alcoholism within the National Institutes of Health. It is a grant to further the scientific bases of environmental preventive interventions. He has received a National Institutes of Health Merit Award to support continued studies of alcohol outlets and violence. Dr. Gruenewald's recent research has been published in Addiction, Journal of Studies on Alcohol, Journal of Drug Education, Substance Use & Abuse, Accident Analysis & Prevention , and Alcoholism: Clinical and Experimental Research .
Funding Information:
Dennis M. Gorman : Professor, School of Rural Public Health at the Texas A&M Health Science Center in College Station. He earned a B.A. (Hons.) from the Polytechnic of Central London (now the University of Westminster), an M.Sc. from the University of London, and the Ph.D., from Essex University. Professor Gorman's research interests focus on the ecology of alcohol availability and violence, the evaluation of alcohol and drug prevention policies, and the application of evidence-based practice to alcohol, drug and violence prevention. His research has been funded by agencies such as the NIH, the Robert Wood Johnson Foundation, and the Smith Richardson Foundation. Selected findings from this research have been published in a variety of public health, addiction and evaluation journals, including the American Journal of Public Health, Preventive Medicine, Addiction, Journal of Studies on Alcohol, Drug and Alcohol Review, Evaluation and Program Planning , and Evaluation Review .
PY - 2010/3
Y1 - 2010/3
N2 - Alcohol consumption is a function of social dynamics, environmental contexts, individuals' preferences and family history. Empirical surveys have focused primarily on identification of risk factors for high-level drinking but have done little to clarify the underlying mechanisms at work. Also, there have been few attempts to apply nonlinear dynamics to the study of these mechanisms and processes at the population level. A simple framework where drinking is modeled as a socially contagious process in low- and high-risk connected environments is introduced. Individuals are classified as light, moderate (assumed mobile), and heavy drinkers. Moderate drinkers provide the link between both environments, that is, they are assumed to be the only individuals drinking in both settings. The focus here is on the effect of moderate drinkers, measured by the proportion of their time spent in "low-" versus "high-" risk drinking environments, on the distribution of drinkers. A simple model within our contact framework predicts that if the relative residence times of moderate drinkers are distributed randomly between low- and high-risk environments then the proportion of heavy drinkers is likely to be higher than expected. However, the full story even in a highly simplified setting is not so simple because "strong" local social mixing tends to increase high-risk drinking on its own. High levels of social interaction between light and moderate drinkers in low-risk environments can diminish the importance of the distribution of relative drinking times on the prevalence of heavy drinking.
AB - Alcohol consumption is a function of social dynamics, environmental contexts, individuals' preferences and family history. Empirical surveys have focused primarily on identification of risk factors for high-level drinking but have done little to clarify the underlying mechanisms at work. Also, there have been few attempts to apply nonlinear dynamics to the study of these mechanisms and processes at the population level. A simple framework where drinking is modeled as a socially contagious process in low- and high-risk connected environments is introduced. Individuals are classified as light, moderate (assumed mobile), and heavy drinkers. Moderate drinkers provide the link between both environments, that is, they are assumed to be the only individuals drinking in both settings. The focus here is on the effect of moderate drinkers, measured by the proportion of their time spent in "low-" versus "high-" risk drinking environments, on the distribution of drinkers. A simple model within our contact framework predicts that if the relative residence times of moderate drinkers are distributed randomly between low- and high-risk environments then the proportion of heavy drinkers is likely to be higher than expected. However, the full story even in a highly simplified setting is not so simple because "strong" local social mixing tends to increase high-risk drinking on its own. High levels of social interaction between light and moderate drinkers in low-risk environments can diminish the importance of the distribution of relative drinking times on the prevalence of heavy drinking.
KW - College students
KW - Drinking environments
KW - Drinking patterns
KW - Mathematical model
KW - Residence times
KW - Social influence
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U2 - 10.1016/j.seps.2009.02.002
DO - 10.1016/j.seps.2009.02.002
M3 - Article
AN - SCOPUS:70350554056
SN - 0038-0121
VL - 44
SP - 45
EP - 56
JO - Socio-Economic Planning Sciences
JF - Socio-Economic Planning Sciences
IS - 1
ER -