AIMS: US college drinking data and a simple population model of alcohol consumption are used to explore the impact of social and contextual parameters on the distribution of light, moderate and heavy drinkers. Light drinkers become moderate drinkers under social influence, moderate drinkers may change environments and become heavy drinkers. We estimate the drinking reproduction number, R(d) , the average number of individual transitions from light to moderate drinking that result from the introduction of a moderate drinker in a population of light drinkers. DESIGN AND SETTINGS: Ways of assessing and ranking progression of drinking risks and data-driven definitions of high- and low-risk drinking environments are introduced. Uncertainty and sensitivity analyses, via a novel statistical approach, are conducted to assess R(d) variability and to analyze the role of context on drinking dynamics. FINDINGS: Our estimates show R(d) well above the critical value of 1. R(d) estimates correlate positively with the proportion of time spent by moderate drinkers in high-risk drinking environments. R(d) is most sensitive to variations in local social mixing contact rates within low-risk environments. The parameterized model with college data suggests that high residence times of moderate drinkers in low-risk environments maintain heavy drinking. CONCLUSIONS: With regard to alcohol consumption in US college students, drinking places, the connectivity (traffic) between drinking venues and the strength of socialization in local environments are important determinants in transitions between light, moderate and heavy drinking as well as in long-term prediction of the drinking dynamics.
AIMS: US college drinking data and a simple population model of alcohol consumption are used to explore the impact of social and contextual parameters on the distribution of light, moderate and heavy drinkers. Light drinkers become moderate drinkers under social influence, moderate drinkers may change environments and become heavy drinkers. We estimate the drinking reproduction number, R(d) , the average number of individual transitions from light to moderate drinking that result from the introduction of a moderate drinker in a population of light drinkers. DESIGN AND SETTINGS: Ways of assessing and ranking progression of drinking risks and data-driven definitions of high- and low-risk drinking environments are introduced. Uncertainty and sensitivity analyses, via a novel statistical approach, are conducted to assess R(d) variability and to analyze the role of context on drinking dynamics. FINDINGS: Our estimates show R(d) well above the critical value of 1. R(d) estimates correlate positively with the proportion of time spent by moderate drinkers in high-risk drinking environments. R(d) is most sensitive to variations in local social mixing contact rates within low-risk environments. The parameterized model with college data suggests that high residence times of moderate drinkers in low-risk environments maintain heavy drinking. CONCLUSIONS: With regard to alcohol consumption in US college students, drinking places, the connectivity (traffic) between drinking venues and the strength of socialization in local environments are important determinants in transitions between light, moderate and heavy drinking as well as in long-term prediction of the drinking dynamics.
Authors: Anuj Mubayi; Priscilla E Greenwood; Carlos Castillo-Chávez; Paul Gruenewald; Dennis M Gorman Journal: Socioecon Plann Sci Date: 2010-03-01 Impact factor: 4.923
Authors: Anuj Mubayi; Priscilla E Greenwood; Carlos Castillo-Chávez; Paul Gruenewald; Dennis M Gorman Journal: Socioecon Plann Sci Date: 2010-03-01 Impact factor: 4.923
Authors: Tracey A Garcia; Brittney A Hultgren; Jessica R Canning; Michael S Gilson; Mary E Larimer Journal: Alcohol Clin Exp Res Date: 2022-04-30 Impact factor: 3.928
Authors: Victor Moreno; Baltazar Espinoza; Kamal Barley; Marlio Paredes; Derdei Bichara; Anuj Mubayi; Carlos Castillo-Chavez Journal: Theor Biol Med Model Date: 2017-01-28 Impact factor: 2.432