Estimating alcohol-attributable injury deaths: A comparison of epidemiological methods

Abstract

Background and aims: Injuries often involve alcohol, but determining the proportion caused by alcohol is difficult. Several approaches have been used to determine the causal role of alcohol, but these methods have not been compared directly with one another. Such a comparison would be useful for understanding the strengths and comparability of different approaches. This study compared estimates of average annual alcohol-attributable deaths in the United States from injuries during 2015-19 using a blood alcohol concentration (BAC) method compared with a population attributable fraction (PAF) approach.

Methods: For the BAC method, we used a direct method involving the proportion of decedents with a high blood alcohol concentration (BAC; e.g. ≥ 0.10%). For the PAF approach, we compared the use of unadjusted survey data with average consumption data adjusted using alcohol sales data to account for underreporting and also accounting for the underreporting of binge drinking. Survey data were from the Behavioral Risk Factor Surveillance System and mortality data were from the National Vital Statistics System.

Results: The number of alcohol-attributable injury deaths using the direct method (48 516 deaths annually) was similar to that using PAF methods (47 879 deaths annually), but only when alcohol use measures were adjusted using alcohol sales data. Furthermore, estimates were similar for cause-specific categories of deaths, including non-motor vehicle unintentional injuries and motor vehicle crashes. Among PAF methods, excessive drinking accounted for 38.3% of injury deaths using unadjusted survey data, but 64.8% of injury deaths using adjusted data.

Conclusions: Estimates of alcohol-attributable injury deaths from a direct method and from a population attributable fraction method that adjusts for alcohol use based on alcohol sales data appear to be comparable.

Keywords: Alcohol; alcohol-attributable deaths; alcohol-attributable fractions; binge drinking; injury; population alcohol-attributable fraction.

Figure 1.. Probability function for past 30-day binge drinking by average alcohol use in standard drinks per day, by sex and age

The lines represent the population-weighted relationships between average consumption in U.S. standard drinks per day (x-axis) and the probability of binge drinking (y-axis) calculated using logistic regression. Arrows indicate implemented changes to the estimated average consumption and prevalence of binge drinking in methods 3 and 4, respectively. In method 3, the average consumption based on survey data is adjusted based on per capita consumption from alcohol sales data; the rightward horizontal arrow represents this shift in average consumption. In method 4, a new binge drinking probability is calculated based on the new level of average consumption obtained in method 3; the upward vertical arrow represents this shift in binge drinking probability.