Abstract:Objective: Examine how socio-economic status (SES) and health outcomes affect binge-drinking demand using a novel approach integrating population health with consumer expenditure data.Design, Setting, and Participants: The study design uses a structural equation model to uncover the association between binge-drinking and SES. I use the 2016 wave of two annually conducted national population surveys in this research: the Behavioral Risk Factor Surveillance (BRFS) and the Consumer Expenditure Survey (CEX), to examine the correlates of binge-drinking. The combined aggregated data integrates alcohol expenditure shares and state-level alcohol prices from the CEX with the BRFS data. The BRFS data partially identifies the at-risk for binge-drinking respondents for our analysis.Main outcome and exposures: Alcohol consumption > 0 in 30 days and binge-drinking is positive (per occasion drinks > 5 male or > 4 female).Results: The binge-drinking prevalence in the BRFS sample, with 457,202 respondents 18 and older, is 17.0% points. Associations with binge-drinking are the same for the poorest and richest income quartiles. Age has the strongest variation. Compared to those over 65, ages 18 ¬– 21 participated in binge-drinking more, and ages 30 – 64 participated much less. Contrasted with those out-of-the-labor-force, the employed participated in binge-drinking more by 3.5% [95% CI, 2.3%, 5.0%] and those unable to work by 4.5% [95% CI, 3.3%, 6.0%] less. The estimated structural models show that, conditional on binge-drinking in a 30-day period, those with high school education or more increased binge-drinking intensity by 3.4% [95% CI, 1.3%, 5.5%] to 5.0% [95% CI, 2.8%, 7.2%] .As people age, expenditure shares on alcohol and cigarettes decrease but healthcare expenditure shares increase proportionately. Furthermore, compared to those without any chronic health conditions alcohol shares decrease by 0.5 [95% CI, -0.57, -0.43] times as number of health conditions increase; this decrease in alcohol consumptions is substituted by increased expenditure shares on food and health care proportionately. Compared to those without high school education alcohol shares decrease with education 0.13 [95% CI, 0.05, 0.23] times for high school graduates and 0.10 [95% CI, 0.3 0.21] times for those with college degrees.Conclusion and Relevance: Bridging the gap between population health and consumer data reveals income effects of binge-drinking are best captured using BRFS because we can characterize a population at risk for binge drinking. CEX best captures income shares and substitution effects between alcohol, smoking, health and food. Alcohol consumption is associated with employment and engaging in other risky behaviors. While this analysis was conducted using 2016 BRFS data the results are generalizable to 2019 BRFS data and extendable to COVID-19 era. Preliminary indications are that alcohol consumption have gone up during COVID-19 thus mobilizing resources to reduce binge-drinking is welfare enhancing. A plausible policy implication from this study is to advertise safe drinking on all alcoholic beverages and provide alcohol-specific education on self-and-other harm.
Gambling Problems Are Associated with Alcohol Misuse and Insomnia: Results from a Representative National Telephone Survey