title: Seasonality of alcohol-related phenomena in Estonia.
abstract: We studied alcohol consumption and its consequences as a seasonal phenomenon in Estonia and analysed the social and environmental factors that may cause its seasonal rhythm. There are two important questions when researching the seasonality of human activities: (1) whether it is caused by natural or social factors, and (2) whether the impact of the factors is direct or indirect. Often the seasonality of social phenomena is caused by social factors, but the triggering mechanisms are related to environmental factors like temperature, precipitation, and radiation via the circannual calendar. The indicators of alcohol consumption in the current paper are grouped as: (1) pre-consumption phenomena, i.e. production, tax and excise, sales (beer, wine and vodka are analysed separately), and (2) post-consumption phenomena, i.e. alcohol-related crime and traffic accidents and the number of people detained in lockups and admitted to alcohol treatment clinics. In addition, seasonal variability in the amount of alcohol advertising has been studied, and a survey has been carried out among 87 students of Tartu University. The analysis shows that different phenomena related to alcohol have a clear seasonal rhythm in Estonia. The peak period of phenomena related to beer is in the summer, from June to August and the low point is during the first months of the year. Beer consumption correlates well with air temperature. The consumption of vodka increases sharply at the end of the year and in June; the production of vodka does not have a significant correlation with negative temperatures. The consumption of wine increases during summer and in December. The consequences of alcohol consumption, expressed as the rate of traffic accidents or the frequency of medical treatment, also show seasonal variability. Seasonal variability of alcohol consumption in Estonia is influenced by natural factors (temperature, humidity, etc.) and by social factors (celebrations, vacations, etc.). However, distinguishing between impacts of direct and indirect relationships is complicated, as they are interlinked.
authors.affiliation: Institute of Geography, University of Tartu, Vanemuise st 46, Tartu 51014, Estonia.
authors.forename: Siiri
authors.initials: S
authors.lastname: Silm
authors.forename: Rein
authors.initials: R
authors.lastname: Ahas
mesh_terms: D000063:Accidents, Traffic / Q000706:statistics & numerical data; D000428:Alcohol Drinking / Q000453:epidemiology* / Q000517:prevention & control; D001515:Beer / Q000191:economics / Q000706:statistics & numerical data; D003415:Crime / Q000706:statistics & numerical data; D003625:Data Collection; D004957:Estonia / Q000453:epidemiology; D005260:Female; D006801:Humans; D008297:Male; D011330:Prisons; D012621:Seasons; D013334:Students; D016320:Substance Abuse Treatment Centers / Q000706:statistics & numerical data; D013696:Temperature; D014920:Wine / Q000191:economics / Q000706:statistics & numerical data