Timothy S Naimi1, Jason Blanchette2, Toben F Nelson3, Thien Nguyen4, Nadia Oussayef5, Timothy C Heeren6, Paul Gruenewald7, James Mosher8, Ziming Xuan4. 1. Section of General Internal Medicine, Boston Medical Center, Boston, Massachusetts; Department of Community Health Sciences, Boston, Massachusetts. Electronic address: tim.naimi@bmc.org. 2. Section of General Internal Medicine, Boston Medical Center, Boston, Massachusetts. 3. Division of Epidemiology and Community Health, University of Minnesota School of Public Health, Minneapolis, Minnesota. 4. Department of Community Health Sciences, Boston, Massachusetts. 5. Department of Health Law, Bioethics and Human Rights, Boston, Massachusetts. 6. Department of Biostatistics, Boston University School of Public Health, Boston, Massachusetts. 7. Prevention Research Center, Pacific Institute for Research and Evaluation, Berkeley. 8. CDM Group, Inc., Felton, California.
Abstract
BACKGROUND: Of outcomes related to excessive drinking, binge drinking accounts for approximately half of alcohol-attributable deaths, two thirds of years of potential life lost, and three fourths of economic costs. The extent to which the alcohol policy environment accounts for differences in binge drinking in U.S. states is unknown. PURPOSE: The goal of the study was to describe the development of an Alcohol Policy Scale (APS) designed to measure the aggregate state-level alcohol policy environment in the U.S. and assess the relationship of APS scores to state-level adult binge drinking prevalence in U.S. states. METHODS: Policy efficacy and implementation ratings were developed with assistance from a panel of policy experts. Data on 29 policies in 50 states and Washington DC from 2000-2010 were collected from multiple sources and analyzed between January 2012 and January 2013. Five methods of aggregating policy data to calculate APS scores were explored; all but one was weighted for relative policy efficacy and/or implementation. Adult (aged ≥18 years) binge drinking prevalence data from 2001-2010 was obtained from the Behavioral Risk Factor Surveillance System surveys. APS scores from a particular state-year were used to predict binge drinking prevalence during the following year. RESULTS: All methods of calculating APS scores were significantly correlated (r >0.50), and all APS scores were significantly inversely associated with adult binge drinking prevalence. Introducing efficacy and implementation ratings optimized goodness of fit in statistical models (e.g., unadjusted beta=-3.90, p<0.0001, R(2)=0.31). CONCLUSIONS: The composite measure(s) of the alcohol policy environment have internal and construct validity. Higher APS scores (representing stronger policy environments) were associated with less adult binge drinking and accounted for a substantial proportion of the state-level variation in binge drinking among U.S. states.
BACKGROUND: Of outcomes related to excessive drinking, binge drinking accounts for approximately half of alcohol-attributable deaths, two thirds of years of potential life lost, and three fourths of economic costs. The extent to which the alcohol policy environment accounts for differences in binge drinking in U.S. states is unknown. PURPOSE: The goal of the study was to describe the development of an Alcohol Policy Scale (APS) designed to measure the aggregate state-level alcohol policy environment in the U.S. and assess the relationship of APS scores to state-level adult binge drinking prevalence in U.S. states. METHODS: Policy efficacy and implementation ratings were developed with assistance from a panel of policy experts. Data on 29 policies in 50 states and Washington DC from 2000-2010 were collected from multiple sources and analyzed between January 2012 and January 2013. Five methods of aggregating policy data to calculate APS scores were explored; all but one was weighted for relative policy efficacy and/or implementation. Adult (aged ≥18 years) binge drinking prevalence data from 2001-2010 was obtained from the Behavioral Risk Factor Surveillance System surveys. APS scores from a particular state-year were used to predict binge drinking prevalence during the following year. RESULTS: All methods of calculating APS scores were significantly correlated (r >0.50), and all APS scores were significantly inversely associated with adult binge drinking prevalence. Introducing efficacy and implementation ratings optimized goodness of fit in statistical models (e.g., unadjusted beta=-3.90, p<0.0001, R(2)=0.31). CONCLUSIONS: The composite measure(s) of the alcohol policy environment have internal and construct validity. Higher APS scores (representing stronger policy environments) were associated with less adult binge drinking and accounted for a substantial proportion of the state-level variation in binge drinking among U.S. states.
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