An approach to estimate between- and within-group correlation coefficients in multicenter studies: plasma carotenoids as biomarkers of intake of fruits and vegetables

Am J Epidemiol. 2005 Sep 15;162(6):591-8. doi: 10.1093/aje/kwi242. Epub 2005 Aug 10.

Abstract

In a multicenter study, the overall correlation between two variables can be broken down into a within- and a between-group correlation reflecting associations at the individual and aggregate levels, respectively. A random-effects model is used to estimate variance components of nutrition-related variables and the within- and between-group correlation coefficients. Using data from the European Prospective Investigation into Cancer and Nutrition (EPIC), the authors analyzed the association between levels of three plasma carotenoids (alpha-carotene, beta-cryptoxanthin, and lycopene) and dietary intake of three items (total fruits, carrots, and tomatoes), assessed through dietary questionnaire and single 24-hour dietary recall measurements, in a cross-sectional study involving 3,089 subjects from nine European countries. Intraclass correlation coefficients were 0.178 for alpha-carotene, 0.216 for beta-cryptoxanthin, and 0.299 for lycopene. The between-group correlation coefficients were higher than the within-group coefficients for all three carotenoids. For beta-cryptoxanthin and fruit intake, the between-group versus the within-group correlations were 0.78 and 0.26 for the dietary questionnaire and 0.85 and 0.19 for the 24-hour dietary recall. Results indicate that variability of exposure is driven mainly by the individual compared with the aggregate variation and that biomarker levels perform fairly accurately in discriminating population-level consumption of fruits and vegetables.

Publication types

  • Multicenter Study

MeSH terms

  • Adult
  • Algorithms
  • Analysis of Variance
  • Biomarkers / blood
  • Carotenoids / blood*
  • Cohort Studies
  • Diet Surveys
  • Diet*
  • Female
  • Fruit*
  • Humans
  • Male
  • Models, Statistical*
  • Regression Analysis
  • Vegetables*

Substances

  • Biomarkers
  • Carotenoids