Reduction of community alcohol problems: computer simulation experiments in three counties.
A series of alcohol abuse prevention strategies was evaluated using computer simulation for three counties in the United States: Wake County, North Carolina, Washington County, Vermont and Alameda County, California. A system dynamics model composed of a network of interacting variables was developed for the pattern of alcoholic beverage consumption in a community. The relationship of community drinking patterns to various stimulus factors was specified in the model based on available empirical research. Stimulus factors included disposable income, alcoholic beverage prices, advertising exposure, minimum drinking age and changes in cultural norms. After a generic model was developed and validated on the national level, a computer-based system dynamics model was developed for each county, and a series of experiments was conducted to project the potential impact of specific prevention strategies. The project concluded that prevention efforts can both lower current levels of alcohol abuse and reduce projected increases in alcohol-related problems. Without such efforts, already high levels of alcohol-related family disruptions in the three counties could be expected to rise an additional 6% and drinking-related work problems 1-5%, over the next 10 years after controlling for population growth. Of the strategies tested, indexing the price of alcoholic beverages to the consumer price index in conjunction with the implementation of a community educational program with well-defined target audiences has the best potential for significant problem reduction in all three counties.
D000293:Adolescent; D000328:Adult; D000329:Advertising; D000367:Age Factors; D000368:Aged; D000428:Alcohol Drinking; D000434:Alcoholic Beverages / Q000600:supply & distribution; D000435:Alcoholic Intoxication / Q000517:prevention & control; D000437:Alcoholism / Q000517:prevention & control*; D003198:Computer Simulation; D005260:Female; D006801:Humans; D008297:Male; D008875:Middle Aged; D009657:North Carolina; D012306:Risk; D012737:Sex Factors