Literature DB >> 20161388

Impact of Relative Residence Times in Highly Distinct Environments on the Distribution of Heavy Drinkers.

Anuj Mubayi1, Priscilla E Greenwood, Carlos Castillo-Chávez, Paul Gruenewald, Dennis M Gorman.   

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 is 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.

Entities:  

Year:  2010        PMID: 20161388      PMCID: PMC2782832          DOI: 10.1016/j.seps.2009.02.002

Source DB:  PubMed          Journal:  Socioecon Plann Sci        ISSN: 0038-0121            Impact factor:   4.923


  35 in total

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Journal:  Subst Use Misuse       Date:  2004       Impact factor: 2.164

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5.  Affinity in paired event probability.

Authors:  S Blythe; S Busenberg; C Castillo-Chavez
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7.  Adolescent drinking behavior: an observational study of the influence of situational factors on adolescent drinking rates.

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8.  The relationship of alcohol outlet density to heavy and frequent drinking and drinking-related problems among college students at eight universities.

Authors:  Elissa R Weitzman; Alison Folkman; M P H Kerry Lemieux Folkman; Henry Wechsler
Journal:  Health Place       Date:  2003-03       Impact factor: 4.078

9.  Alcohol abuse and dependence among U.S. college students.

Authors:  John R Knight; Henry Wechsler; Meichun Kuo; Mark Seibring; Elissa R Weitzman; Marc A Schuckit
Journal:  J Stud Alcohol       Date:  2002-05

10.  Attendance and alcohol use at parties and bars in college: a national survey of current drinkers.

Authors:  Thomas C Harford; Henry Wechsler; Mark Seibring
Journal:  J Stud Alcohol       Date:  2002-11
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  4 in total

1.  Types of drinkers and drinking settings: an application of a mathematical model.

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Journal:  Addiction       Date:  2010-12-23       Impact factor: 6.526

2.  The role of mobility and health disparities on the transmission dynamics of Tuberculosis.

Authors:  Victor Moreno; Baltazar Espinoza; Kamal Barley; Marlio Paredes; Derdei Bichara; Anuj Mubayi; Carlos Castillo-Chavez
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3.  Role of imitation and limited rehabilitation capacity on the spread of drug abuse.

Authors:  Josiah Mushanyu
Journal:  BMC Res Notes       Date:  2018-07-18

4.  Impact of media coverage on the drinking dynamics in the scale-free network.

Authors:  Hai-Feng Huo; Yan-Yan Wang
Journal:  Springerplus       Date:  2016-02-27
  4 in total

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