Back

Changes in self-reported alcohol consumption at high and low consumption in the wake of the COVID-19 pandemic: A test of the polarization hypothesis

Tran, A.; Jiang, H.; Lange, S.; Stelemekas, M.; Stumbrys, D.; Tamutiene, I.; Rehm, J.

2024-08-01 addiction medicine
10.1101/2024.07.31.24311291 medRxiv
Show abstract

BackgroundThe Coronavirus Disease 2019 (COVID-19) pandemic and associated public health measures had an impact on alcohol use. Based on the literature of past crises (health, economic, etc.), it was hypothesized that the COVID-19 pandemic led to a polarization of drinking-that is, heavy drinkers increased their drinking, while light to moderate drinkers decreased their drinking and/or temporarily abstained. The aim of the current study was to test the respective hypothesis. MethodsData from the Reducing Alcohol Related Harm Standard European Alcohol Survey for Lithuania were obtained for 2015 and 2020. Average daily consumption (in grams per day) was decomposed into deciles for each year, and compared pre-COVID to onset-of-COVID pandemic across the highest, second highest, and lowest deciles. A comparison of population-levels of mental health was conducted between pre-COVID and the onset-of-COVID. ResultsThe findings indicated that overall, there was higher consumption in 2015, M2015 = 11.49 (SD = 8.23) vs. M2020 = 10.71 (SD = 12.12), p < .00001. However the opposite was found in the highest decile M2015 = 29.26 (SD = 5.44) vs. M2020 = 39.23 (SD = 20.58), p = .0003. This reversal pattern was not observed in the second highest nor the lowest decile. There was a lower proportion of respondents indicating "bad" mental health pre- vs.post-COVID (3.4% vs. 6.5%). ConclusionAlthough COVID was associated with nationwide declines in alcohol consumption, this was not the case for all segments of the population. In Lithuania, it appears that there was an increase in consumption among the heaviest drinkers, supporting the polarization hypothesis.

Published in Frontiers in Psychiatry (predicted rank #5) · training set

Matching journals

The top 6 journals account for 50% of the predicted probability mass.

50% of probability mass above

"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.