Within-Person Variation in Nutrient Intakes across Populations and Settings: Implications for the Use of External Estimates in Modeling Usual Nutrient Intake Distributions

Author:

French Caitlin D12ORCID,Arsenault Joanne E3,Arnold Charles D2,Haile Demewoz12ORCID,Luo Hanqi12,Dodd Kevin W4,Vosti Stephen A5,Slupsky Carolyn M16,Engle-Stone Reina12ORCID,Engle-Stone Reina,French Caitlin D,Arsenault Joanne E,Arnold Charles D,Haile Demewoz,Wiesmann Doris,Martin-Prevel Yves7,Brouwer Inge D8,Daniels Melissa C9,Nyström Christine Delisle10,Löf Marie10,Ndjebayi Alex11,Palacios Cristina12,Prapkree Lukkamol12,Palmer Amanda13,Caswell Bess L14,Hn Brown Kenneth14,Lietz Georgn15,Haskell Marjorien14,Miller Jody14,

Affiliation:

1. Department of Nutrition, University of California, Davis, Davis, CA, USA

2. Institute for Global Nutrition, University of California, Davis, CA, USA

3. Intake–Center for Dietary Assessment, FHI Solutions, Washington, DC, USA

4. National Cancer Institute, National Institutes of Health, Rockville, MD, USA

5. Department of Agricultural and Resource Economics, University of California, Davis, CA, USA

6. Department of Food Science and Technology, University of California, Davis, Davis, CA, USA

7. Nutripass, University of Montpellier, Institut de Recherche pour le Développement, Montpellier SupAgro, Montpellier, France

8. Division of Human Nutrition and Health, Wageningen University, Wageningen, Netherlands

9. Department of Nutrition, University of North Carolina, Chapel Hill, NC, USA

10. Department of Biosciences and Nutrition, Karolinska Institutet, Stockholm, Sweden

11. Helen Keller International, Yaoundé, Cameroon

12. Department of Dietetics and Nutrition, Florida International University, Miami, FL, USA

13. Department of International Health, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA

14. Department of Nutrition and Institute for Global Nutrition, University of California, Davis, Davis, CA, USA

15. Human Nutrition Research Centre, Population Health Sciences Institute, Newcastle University, Newcastle upon Tyne, UK

Abstract

ABSTRACT Determining the proportion of a population at risk of inadequate or excessive nutrient intake is a crucial step in planning and managing nutrition intervention programs. Multiple days of 24-h dietary intake data per subject allow for adjustment of modeled usual nutrient intake distributions for the proportion of total variance in intake attributable to within-individual variation (WIV:total). When only single-day dietary data are available, an external adjustment factor can be used; however, WIV:total may vary by population, and use of incorrect WIV:total ratios may influence the accuracy of prevalence estimates and subsequent program impacts. WIV:total values were compiled from publications and from reanalyses of existing datasets to describe variation in WIV:total across populations and settings. The potential impact of variation in external WIV:total on estimates of prevalence of inadequacy was assessed through simulation analyses using the National Cancer Institute 1-d method. WIV:total values were extracted from 40 publications from 24 countries, and additional values were calculated from 15 datasets from 12 nations. Wide variation in WIV:total (from 0.02 to 1.00) was observed in publications and reanalyses. Few patterns by population characteristics were apparent, but WIV:total varied by age in children (< vs. >1 y) and between rural and urban settings. Simulation analyses indicated that estimates of the prevalence of inadequate intake are sensitive to the selected ratio in some cases. Selection of an external WIV:total estimate should consider comparability between the reference and primary studies with regard to population characteristics, study design, and statistical methods. Given wide variation in observed ratios with few discernible patterns, the collection of ≥2 days of intake data in at least a representative subsample in population dietary studies is strongly encouraged. In the case of single-day dietary studies, sensitivity analyses are recommended to determine the robustness of prevalence estimates to changes in the variance ratio.

Funder

Bill & Melinda Gates Foundation

National Institutes of Health

Publisher

Oxford University Press (OUP)

Subject

Nutrition and Dietetics,Medicine (miscellaneous),Food Science

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