Design effects associated with dietary nutrient intakes from a clustered design of 1 to 14-year-old children

Eur J Clin Nutr. 2007 Sep;61(9):1064-71. doi: 10.1038/sj.ejcn.1602618. Epub 2007 Jan 31.

Abstract

Objective: To calculate intra-cluster and intra-household design effects and intra-class correlation coefficients for dietary nutrients obtained from a 24 h record-assisted recall.

Design: Children were recruited using clustered probability sampling. Randomly selected starting-point addresses were obtained with probability proportional to mesh block size.

Setting: Children aged 1-14 years in New Zealand.

Subjects: There were 125 children in 50 clusters, giving an average of 2.498 children per cluster. In 15 homes, there were two children for the calculation of intra-household statistics.

Results: Intra-cluster design effects ranged from 1.0 for cholesterol, beta-carotene, vitamin A, vitamin D, vitamin E, selenium, fructose and both carbohydrate and protein expressed as their contribution to total energy intakes to 1.552 for saturated fat, with a median design effect of 1.148. Their corresponding intra-cluster correlations ranged from 0 to 0.37, respectively. Intra-household design effects ranged from 1.0 for height to 1.839 for vitamin B(6), corresponding to intra-household correlations of 0 and 0.839. The median intra-household design effect was 1.550. Using a sampling design of two to three households per cluster for estimating dietary nutrient intakes would need, on average, a 15% increase in sample size compared with simple random sampling with a maximum increase of 55% to cover all nutrients.

Conclusions: These data enable sample sizes for dietary nutrients to be estimated for both cluster and non-cluster sampling for children aged 1-14 years. The larger design effects found within households suggest that little extra information may be obtained by sampling more than one child per household.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Adolescent
  • Child
  • Child Nutritional Physiological Phenomena*
  • Child, Preschool
  • Cluster Analysis
  • Diet Records
  • Diet Surveys*
  • Feeding Behavior*
  • Female
  • Humans
  • Infant
  • Male
  • Mental Recall
  • New Zealand
  • Nutrition Assessment*
  • Random Allocation
  • Sample Size*