目标:先前确定的欧洲国家饮酒模式缺乏可比性,由于经济条件和政策框架的变化,可能不再有效。我们的目标是使用数据驱动的方法,根据可比的酒精暴露指标确定欧洲最近的饮酒模式。以及识别时间变化并在这些模式和酒精相关伤害指标之间建立经验联系。
方法:使用来自世界卫生组织监测系统的关于酒精暴露指标的数据。应用重复的横截面层次聚类分析。通过线性回归分析了国家集群之间酒精可归因于的危害的差异。
方法:欧盟国家,加上冰岛,挪威和乌克兰,2000年、2010年、2015年和2019年。
方法:观察包括年度国家数据,在四个不同的时间点接触酒精。危害指标仅包括在2019年。
方法:酒精暴露指标包括人均酒精消费量(APC),特定于饮料的消费量和饮酒状况指标的患病率(终生戒酒者,目前的饮酒者,以前的饮酒者和大量的偶发性饮酒)。可归因于酒精的伤害是使用年龄标准化的可归因于酒精的残疾调整寿命年(DALYs)损失和每10万人死亡来衡量的。
结果:在2019年,2015年和2010年确定了相同的六个集群,主要特征在于酒精饮料的类型和患病率饮酒状况指标,地理解释。随着时间的推移,三分之二的国家仍然在同一个集群中,在2000年发现了一个额外的集群,其特征是低APC。最新的饮酒模式显示与酒精引起的死亡和DALY率显着相关。与饮用葡萄酒的国家相比,在烈酒和“其他”饮料消费量高的东欧,每10万人的死亡率明显更高[β^$$\\hat{\\beta}$$$=90,95%置信区间(CI)=55-126],在东欧,终身戒酒者高,烈性酒消费量高(β^$$\\\hat{\\beta}$$=42,95%CI=4-78)。
结论:欧洲的饮酒模式似乎集中在特定饮料的消费水平上,有大量的偶发性饮酒者,当前饮酒者和终身戒酒者是集群之间的区别因素。尽管集群随着时间的推移整体稳定,一些国家从2000年到2019年在饮酒模式之间发生了转变。总的来说,欧盟的饮酒模式似乎是稳定的,部分取决于地理位置。
OBJECTIVE: Previously identified national drinking patterns in Europe lack comparability and might be no longer be valid due to changes in economic conditions and policy frameworks. We aimed to identify the most recent alcohol drinking patterns in Europe based on comparable alcohol exposure indicators using a data-driven approach, as well as identifying temporal changes and establishing empirical links between these patterns and indicators of alcohol-related harm.
METHODS: Data from the World Health Organization\'s monitoring system on alcohol exposure indicators were used. Repeated cross-sectional hierarchical cluster analyses were applied. Differences in alcohol-attributable harm between clusters of countries were analyzed via linear regression.
METHODS: European Union countries, plus Iceland, Norway and Ukraine, for 2000, 2010, 2015 and 2019.
METHODS: Observations consisted of annual country data, at four different time points for alcohol exposure. Harm indicators were only included for 2019.
METHODS: Alcohol exposure indicators included alcohol per capita consumption (APC), beverage-specific consumption and prevalence of drinking status indicators (lifetime abstainers, current drinkers, former drinkers and heavy episodic drinking). Alcohol-attributable harm was measured using age-standardized alcohol-attributable Disability-Adjusted Life Years (DALYs) lost and deaths per 100 000 people.
RESULTS: The same six clusters were identified in 2019, 2015 and 2010, mainly characterized by type of alcoholic beverage and prevalence drinking status indicators, with geographical interpretation. Two-thirds of the countries remained in the same cluster over time, with one additional cluster identified in 2000, characterized by low APC. The most recent drinking patterns were shown to be significantly associated with alcohol-attributable deaths and DALY rates. Compared with wine-drinking countries, the mortality rate per 100 000 people was significantly higher in Eastern Europe with high spirits and \'other\' beverage consumption [ β ^ $$ \\hat{\\beta} $$ = 90, 95% confidence interval (CI) = 55-126], and in Eastern Europe with high lifetime abstainers and high spirits consumption ( β ^ $$ \\hat{\\beta} $$ = 42, 95% CI = 4-78).
CONCLUSIONS: European drinking patterns appear to be clustered by level of beverage-specific consumption, with heavy episodic drinkers, current drinkers and lifetime abstainers being distinguishing factors between clusters. Despite the overall stability of the clusters over time, some countries shifted between drinking patterns from 2000 to 2019. Overall, patterns of drinking in the European Union seem to be stable and partly determined by geographical proximity.