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. Â\copyright 2009 Elsevier Ltd.
College students; Drinking environments; Drinking patterns; Mathematical model; Residence times; Social influence
issn
00380121
correspondence_address1
Mubayi, A.; Mathematical, Computational and Modeling Sciences Center, Arizona State University, Tempe, AZ 85287, United States; email: anujmubayi@yahoo.com
affiliation
Mathematical, Computational and Modeling Sciences Center, Arizona State University, Tempe, AZ 85287, United States; School of Human Evolution and Social Change, Arizona State University, Tempe, AZ 85287, United States; School of Mathematical and Statistical Sciences, Arizona State University, Tempe, AZ 85287, United States; Prevention Research Center, 1995 University Avenue, Berkeley, CA 94704, United States; School of Rural Public Health, Texas A and M Health Science Center, College Station, TX 77845, United States
%0 Journal Article
%1 Mubayi201045
%A Mubayi, A.
%A Greenwood, P.E.
%A Castillo-ChÃ!'vez, C.
%A Gruenewald, P.J.
%A Gorman, D.M.
%D 2010
%J Socio-Economic Planning Sciences
%K alcohol; analysis; empirical impact; model; numerical social student
%N 1
%P 45-56
%R http://dx.doi.org/10.1016/j.seps.2009.02.002
%T The impact of relative residence times on the distribution of heavy drinkers in highly distinct environments
%U http://dx.doi.org/10.1016/j.seps.2009.02.002
%V 44
%X 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. Â\copyright 2009 Elsevier Ltd.
@article{Mubayi201045,
abstract = {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. {\^A}{\copyright} 2009 Elsevier Ltd.},
added-at = {2017-11-10T22:48:29.000+0100},
affiliation = {Mathematical, Computational and Modeling Sciences Center, Arizona State University, Tempe, AZ 85287, United States; School of Human Evolution and Social Change, Arizona State University, Tempe, AZ 85287, United States; School of Mathematical and Statistical Sciences, Arizona State University, Tempe, AZ 85287, United States; Prevention Research Center, 1995 University Avenue, Berkeley, CA 94704, United States; School of Rural Public Health, Texas A and M Health Science Center, College Station, TX 77845, United States},
author = {Mubayi, A. and Greenwood, P.E. and Castillo-Ch{\~A}{!'}vez, C. and Gruenewald, P.J. and Gorman, D.M.},
author_keywords = {College students; Drinking environments; Drinking patterns; Mathematical model; Residence times; Social influence},
biburl = {https://www.bibsonomy.org/bibtex/2b59356ba44fca608d1812e47a73561c9/ccchavez},
correspondence_address1 = {Mubayi, A.; Mathematical, Computational and Modeling Sciences Center, Arizona State University, Tempe, AZ 85287, United States; email: anujmubayi@yahoo.com},
date-added = {2017-11-10 21:45:26 +0000},
date-modified = {2017-11-10 21:45:26 +0000},
document_type = {Article},
doi = {http://dx.doi.org/10.1016/j.seps.2009.02.002},
interhash = {1ea7c21e0785f537747a11c0508bda48},
intrahash = {b59356ba44fca608d1812e47a73561c9},
issn = {00380121},
journal = {Socio-Economic Planning Sciences},
keywords = {alcohol; analysis; empirical impact; model; numerical social student},
language = {English},
number = 1,
pages = {45-56},
timestamp = {2017-11-10T22:48:29.000+0100},
title = {The impact of relative residence times on the distribution of heavy drinkers in highly distinct environments},
url = {http://dx.doi.org/10.1016/j.seps.2009.02.002},
volume = 44,
year = 2010
}