Population Alcohol Consumption as a Predictor of Alcohol-Specific Deaths: A Time-Series Analysis of Aggregate Data.

Aims: The study examines whether the number of alcohol-specific deaths can be predicted by population total and/or beverage-specific alcohol consumption and if, how precisely. The data are annual series of spirits, wine, beer and total consumption and alcohol-specific deaths in Finland in the years 1969-2015.

Methods: We specify a Auto Regressive Distributed Lags model with cointegrated variables, to be used in prediction. In our model, the number of alcohol-specific deaths is the response variable, and log of spirits consumption and log of non-spirits consumption, are the explanatory variables. The response variable has one added annual lag and the explanatory variables have both four annual added lags in the model.

Results: In our data alcohol-specific deaths, log of spirits and log of non-spirits consumption are significantly cointegrated. The precision of the estimated model is good. The prediction results include prediction of the 2008 downturn in alcohol deaths, using the data from the years 1969-2004, forecasting the as yet unknown 2016 alcohol deaths on the basis of known values of alcohol consumption up to 2016, and forecasts of future (2017-2020) alcohol deaths from 2016 on. Forecasted effects of a proposed Finnish alcohol policy change, leading to six percent total consumption increase, are estimated.

Conclusions: The number of alcohol-specific deaths can be predicted with an appropriate time-series regression model on the basis of population consumption. It is important to consider also beverage type because of the improved predictive power. The model is useful in an evaluation of proposed alcohol policy changes.