Drinking patterns in French adult men--a cluster analysis of alcoholic beverages and relationship with lifestyle

Eur J Nutr. 2004 Apr;43(2):69-76. doi: 10.1007/s00394-004-0442-x. Epub 2004 Jan 6.

Abstract

Background: Establishing patterns of alcohol consumption may be useful for investigating the relationship between alcohol and diseases.

Methods: We used a hierarchical agglomerative clustering method to describe the intake of eight types of alcoholic beverages and to determine drinking patterns in a cohort of 1797 men enrolled in a French 8-year intervention study involving nutritional doses of vitamins and minerals, the SU.VI.MAX study.

Results: Cluster 1, referred to as 'abstainers', was defined a priori and included 329 men who drank less than 5 g of alcohol per day. Six drinking patterns were defined in alcohol drinkers, with increasing mean alcohol intake: cluster 2, 'low drinkers', included 670 subjects, who drank little of any type of alcoholic beverage; cluster 3, 'high quality wines', included 584 men with a high intake of champagne, high quality wines, and high-alcohol aperitifs; cluster 4, 'beer and cider', included 190 subjects with a high intake of beer and cider; cluster 5, 'digestives', included 54 men with a specifically high consumption of digestive beverages; cluster 6, 'local wines', included 238 subjects with a high intake of local wines and low-alcohol aperitifs; cluster 7, 'table wines', included 61 men with a high intake of table wines and high-alcohol aperitifs. These clusters were significantly associated with socioeconomic and lifestyle variables such as place of residence, occupation, mean caloric intake and distribution of energy intake throughout the day, body mass index, and smoking habits.

Conclusions: They will be useful in future studies of the relationship between alcohol intake and medical conditions or risk factors.

MeSH terms

  • Alcohol Drinking* / epidemiology
  • Body Mass Index
  • Cluster Analysis
  • Cohort Studies
  • Diet Records
  • Employment / statistics & numerical data
  • Energy Intake / physiology
  • Factor Analysis, Statistical
  • France / epidemiology
  • Humans
  • Life Style*
  • Male
  • Middle Aged
  • Residence Characteristics / statistics & numerical data
  • Smoking
  • Socioeconomic Factors