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, β-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 B6, 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.
Cite
CITATION STYLE
Metcalf, P. A., Scragg, R. K. R., Stewart, A. W., & Scott, A. J. (2007). Design effects associated with dietary nutrient intakes from a clustered design of 1 to 14-year-old children. European Journal of Clinical Nutrition, 61(9), 1064–1071. https://doi.org/10.1038/sj.ejcn.1602618
Register to see more suggestions
Mendeley helps you to discover research relevant for your work.