Dietary patterns in the population living in the Sámi core areas of Norway--the SAMINOR study

Int J Circumpolar Health. 2008 Feb;67(1):82-96.

Abstract

Objectives: To identify dietary patterns and to investigate their association with selected life-style and demographic factors, ethnicity and self-perceived health. Study design. Population-based cross-sectional design, using food frequency questionnaires.

Methods: A total of 12,811 subjects aged 36-79 years participated from the municipalities in Norway where more than 5-10% of the population reported to be Simi in the 1970 Census, in addition to some selected districts. The data were collected during 2003-2004. A principal component analysis was used to assess the associations among food variables. Seven principal components were then used as input in a cluster analysis.

Results: Five dietary patterns were identified and labelled "reindeer", "fish", "average", "fruits and vegetables" and "Westernised, traditional marine". The reindeer pattern was highly represented by subjects with three generations of Sámi language (Sámi I), obese subjects and those with low levels of physical activity. The fish pattern was dominated by women and had the largest proportion of individuals who reported their health as being "not so good" (35%). However, this pattern had the largest proportion of subjects in the oldest age categories. The fruits and vegetables pattern was characterised by a health-conscious life-style, included more women than men, and had the largest proportion of subjects reporting "very good" health. Ethnicity did not play a major role in predicting dietary patterns except for the reindeer pattern, especially in the inland areas.

Conclusions: In the dietary cluster analysis we identified five distinct dietary patterns that were also characterised by additional life-style factors.

MeSH terms

  • Adult
  • Aged
  • Arctic Regions
  • Body Mass Index
  • Diet / ethnology*
  • Female
  • Health Behavior / ethnology
  • Humans
  • Male
  • Middle Aged
  • Norway
  • Nutrition Surveys
  • Racial Groups / statistics & numerical data*
  • Socioeconomic Factors