title: A mixed-effects model approach for estimating the distribution of usual intake of nutrients: the NCI method.
abstract: It is of interest to estimate the distribution of usual nutrient intake for a population from repeat 24-h dietary recall assessments. A mixed effects model and quantile estimation procedure, developed at the National Cancer Institute (NCI), may be used for this purpose. The model incorporates a Box-Cox parameter and covariates to estimate usual daily intake of nutrients; model parameters are estimated via quasi-Newton optimization of a likelihood approximated by the adaptive Gaussian quadrature. The parameter estimates are used in a Monte Carlo approach to generate empirical quantiles; standard errors are estimated by bootstrap. The NCI method is illustrated and compared with current estimation methods, including the individual mean and the semi-parametric method developed at the Iowa State University (ISU), using data from a random sample and computer simulations. Both the NCI and ISU methods for nutrients are superior to the distribution of individual means. For simple (no covariate) models, quantile estimates are similar between the NCI and ISU methods. The bootstrap approach used by the NCI method to estimate standard errors of quantiles appears preferable to Taylor linearization. One major advantage of the NCI method is its ability to provide estimates for subpopulations through the incorporation of covariates into the model. The NCI method may be used for estimating the distribution of usual nutrient intake for populations and subpopulations as part of a unified framework of estimation of usual intake of dietary constituents.
authors.affiliation: Department of Biostatistical Sciences, School of Medicine, Wake Forest University, Medical Center Boulevard, Winston-Salem, NC 27157, USA. jtooze@wfubmc.edu
authors.forename: Janet A
authors.initials: JA
authors.lastname: Tooze
authors.forename: Victor
authors.initials: V
authors.lastname: Kipnis
authors.forename: Dennis W
authors.initials: DW
authors.lastname: Buckman
authors.forename: Raymond J
authors.initials: RJ
authors.lastname: Carroll
authors.forename: Laurence S
authors.initials: LS
authors.lastname: Freedman
authors.forename: Patricia M
authors.initials: PM
authors.lastname: Guenther
authors.forename: Susan M
authors.initials: SM
authors.lastname: Krebs-Smith
authors.forename: Amy F
authors.initials: AF
authors.lastname: Subar
authors.forename: Kevin W
authors.initials: KW
authors.lastname: Dodd
mesh_terms: D000328:Adult; D000367:Age Factors; D000368:Aged; D000465:Algorithms; D002136:Calcium, Dietary / Q000008:administration & dosage; D003198:Computer Simulation; D004034:Diet Surveys; D004435:Eating; D005260:Female; D006801:Humans; D007407:Interviews as Topic; D019266:Iron, Dietary / Q000008:administration & dosage; D016013:Likelihood Functions; D008297:Male; D008875:Middle Aged; D015233:Models, Statistical; D009010:Monte Carlo Method; D054547:National Cancer Institute (U.S.); D015596:Nutrition Assessment; D012737:Sex Factors; D016008:Statistical Distributions; D011795:Surveys and Questionnaires; D014481:United States; D014801:Vitamin A / Q000008:administration & dosage; D055815:Young Adult
chemical_list: D002136:Calcium, Dietary; D019266:Iron, Dietary; D014801:Vitamin A