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Multicenter Study
. 2021 Sep 1;13(9):3077.
doi: 10.3390/nu13093077.

Long-Term Trends (1994-2011) and Predictors of Total Alcohol and Alcoholic Beverages Consumption: The EPIC Greece Cohort

Nikolaos Skourlis  1 , Paraskevi Massara  1 , Ioannis Patsis  1 , Eleni Peppa  1 , Klea Katsouyanni  1   2 , Antonia Trichopoulou  1
Affiliations
Multicenter Study

Long-Term Trends (1994-2011) and Predictors of Total Alcohol and Alcoholic Beverages Consumption: The EPIC Greece Cohort

Nikolaos Skourlis et al. Nutrients. .

Abstract

The aim of this study was to evaluate the longitudinal changes in alcohol consumption (total alcohol and types of alcoholic beverages) of the Greek EPIC cohort participants (28,572) during a 17-year period (1994-2011), with alcohol information being recorded repeatedly over time. Descriptive statistics were used to show crude trends in drinking behavior. Mixed-effects models were used to study the consumption of total alcohol, wine, beer and spirits/other alcoholic beverages in relation to birth cohort, socio-demographic, lifestyle and health factors. We observed a decreasing trend of alcohol intake as age increased, consistent for total alcohol consumption and the three types of beverages. Older birth cohorts had lower initial total alcohol consumption (8 vs. 10 g/day) and steeper decline in wine, spirits/other alcoholic beverages and total alcohol consumption compared to younger cohorts. Higher education and smoking at baseline had a positive association with longitudinal total alcohol consumption, up to +30% (vs. low education) and more than +25% (vs. non-smoking) respectively, whereas female gender, obesity, history of heart attack, diabetes, peptic ulcer and high blood pressure at baseline had a negative association of -85%, -25%, -16%, -37%, -22% and -24% respectively. Alcohol consumption changed over age with different trends among the studied subgroups and types of alcohol, suggesting targeted monitoring of alcohol consumption.

Keywords: EPIC; alcohol consumption; linear mixed models; longitudinal.

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Conflict of interest statement

All authors declare no support from any organization for the submitted work, no financial relationships with any organizations that might have an interest in the submitted work in the previous three years and no competing interest related to this work. No financial disclosures to be reported.

Figures

Figure A1
Figure A1
Line plots of average annual consumption for wine, beer, spirits/other alcoholic beverages (glasses/week) and total alcohol consumption (grams/day) for men and women of different birth cohorts over interview year.
Figure A2
Figure A2
Line plots of average annual consumption for wine, beer, spirits/other alcoholic beverages (glasses/week) and total alcohol consumption (grams/day) for men and women of different birth cohorts over the baseline period and the follow-up waves.
Figure 1
Figure 1
Line plots of frequencies of consumption for wine, beer and spirits/other alcoholic beverages at the baseline and the follow up periods (“None”, “Less than 1 glass/week”, “More than 1 glass/week”).
Figure 2
Figure 2
Average alcohol consumption (grams/day) from all sources for non-abstainers and proportion (%) of abstainers across time.
Figure 3
Figure 3
Line plots of average annual consumption for wine, beer, spirits/other alcoholic beverages (glasses/week) and total alcohol consumption (grams/day) for men and women of different birth cohorts.
Figure 4
Figure 4
Line plots of estimated consumption for wine, beer and spirits/other alcoholic beverages over age at interview for four birth cohorts for men and women, based on the linear mixed model Model 0 (M0).
Figure 5
Figure 5
Average marginal effects of socio-demographic and lifestyle factors on wine, beer, spirits/other alcoholic beverages and total alcohol consumption based on model of Table 2.
See this image and copyright information in PMC

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