Hostname: page-component-78c5997874-lj6df Total loading time: 0 Render date: 2024-11-10T06:37:05.906Z Has data issue: false hasContentIssue false
  • English
  • Français

A Monte Carlo simulation to validate the EAR cut-point method for assessing the prevalence of nutrient inadequacy at the population level

Published online by Cambridge University Press:  02 January 2007

B de Lauzon ,
JL Volatier  and
A Martin
B de Lauzon*
Affiliation:
INSERM, U258, 16 avenue Paul-Vaillant Couturier, 94807 Villejuif Cedex, France
JL Volatier
Affiliation:
Agence Française de Sécurité Sanitaire des Aliments, Maisons-Alfort, France
A Martin
Affiliation:
Agence Française de Sécurité Sanitaire des Aliments, Maisons-Alfort, France
*
*Corresponding author: Email delauzon@vjf.inserm.fr
Rights & Permissions [Opens in a new window]

Abstract

Core share and HTML view are not available for this content. However, as you have access to this content, a full PDF is available via the ‘Save PDF’ action button.
Objective:

The aim of this study was to validate the EAR cut-point method for assessing the prevalence of nutrient inadequacy at the population level.

Design and subjects:

Different methods for estimating the prevalence of inadequate intake were compared: the cut-off point method, with cut-off points at the Recommended Dietary Allowance (RDA), 0.66 RDA, 0.50 RDA and the Estimated Average Requirement (EAR); the probability approach; and a Monte Carlo simulation. In total, 591 men and 674 women, aged 20–55 years, were included in the analyses.

Results:

The prevalence of inadequate intake as estimated by the EAR cut-point method was similar to the prevalence of inadequacy estimated by both probabilistic methods. The cut-point method with RDA, 0.66 RDA and 0.50 RDA as cut-off limits induced an over- or an underestimation of the real prevalence of inadequacy.

Conclusions:

Probabilistic methods consider both the intake variability and the requirement variability, and, as a result, their estimation should be closer to the real prevalence of inadequacy. The use of the EAR cut-point method yields a good estimation of the prevalence of inadequate intake, comparable to the probability approach, and limits over- and underestimation of the prevalence induced by other cut-off points.

Keywords

Nutrient inadequacyRecommended Dietary AllowanceEstimated Average RequirementMonte Carlo simulation
Type
Research Article
Information
Public Health Nutrition , Volume 7 , Issue 7 , October 2004 , pp. 893 - 900
Copyright
Copyright © The Authors 2004

References

1Beaton, GH. Uses and limits of the use of the Recommended Dietary Allowances for evaluating dietary intake data. American Journal of Clinical Nutrition 1985; 41: 155–64.CrossRefGoogle ScholarPubMed
2Subcommittee on Interpretation and Uses of Dietary References Intakes. Dietary Reference Intakes: Applications in Dietary Assessment. Washington, DC: Subcommittee on Interpretation and Uses of Dietary References Intakes, 2000.Google Scholar
3Martin, A. Nutritional recommendations for the French population. Sciences des Aliments 2001; 21: 307–458.Google Scholar
4National Research Council. Nutrient Adequacy: Assessment using Food Consumption Surveys. Washington, DC: Subcommittee on Criteria for Dietary Evaluation, 1985.Google Scholar
5 Haut Comité de la Santé Publique, ed. Pour une politique nutritionnelle de santé publique en France – Enjeux et propositions. Rennes: ENSP, 2000.Google Scholar
6Hercberg, S, Preziosi, P, Galan, P, Deheeger, M, Papoz, L, Dupin, H. [Dietary intake of a representative sample of the population of Val-de-Marne; III. Mineral and vitamin intake]. Revue d'Epidemiologie et de Sante Publique 1991; 39: 245–61.Google ScholarPubMed
7Setiawan, B, Giraud, DW, Driskell, JA. Vitamin B-6 inadequacy is prevalent in rural and urban Indonesian children. Journal of Nutrition 2000; 130: 553–8.CrossRefGoogle ScholarPubMed
8Baer, MT, Kozlowski, BW, Blyler, EM, Trahms, CM, Taylor, ML, Hogan, MP. Vitamin D, calcium, and bone status in children with developmental delay in relation to anticonvulsant use and ambulatory status. American Journal of Clinical Nutrition 1997; 65: 1042–51.CrossRefGoogle ScholarPubMed
9Monge-Rojas, R. Marginal vitamin and mineral intake of Costa Rican adolescents. Archives of Medical Research 2001; 32: 70–8.CrossRefGoogle ScholarPubMed
10Zive, MM, Nicklas, TA, Busch, EC, Myers, L, Berenson, GS. Marginal vitamin and mineral intakes of young adults: the Bogalusa Heart Study. Journal of Adolescent Health 1996; 19: 39–47.CrossRefGoogle ScholarPubMed
11Hodges, P, Gee, M, Grace, M, Thomson, AB. Vitamin and iron intake in patients with Crohn's disease. Journal of the American Dietetic Association 1984; 84: 52–8.CrossRefGoogle ScholarPubMed
12Carriquiry, AL. Assessing the prevalence of nutrient inadequacy. Public Health Nutrition 1999; 2: 23–33.CrossRefGoogle ScholarPubMed
13Volatier, JL, coordinator Enquête Individuelle et Nationale sur les Consommations Alimentaires (INCA). Paris: Agence Française de Sécurité Sanitaire des Aliments, 2000.Google Scholar
14Goldberg, GR, Black, AE, Jebb, SA, Cole, TJ, Murgatroyd, PR, Coward, WA, et al. Critical evaluation of energy intake data using fundamental principles of energy physiology: 1 Derivation of cut-off limits to identify under-recording. European Journal of Clinical Nutrition 1991; 45: 569–81.Google ScholarPubMed
15Guenther, PM, Kott, PS, Carriquiry, AL. Development of an approach for estimating usual nutrient intake distributions at the population level. Journal of Nutrition 1997; 127: 1106–12.CrossRefGoogle ScholarPubMed
16Nusser, SM, Carriquiry, AL, Dodd, KW, Fuller, WA. A semiparametric transformation approach to estimating usual daily intake distribution. Journal of the American Statistical Association 1996; 91(436): 1440–9.CrossRefGoogle Scholar
17Hoffmann, K, Boeing, H, Dufour, A, Volatier, JL, Telman, J, Virtanen, M, et al. EFCOSUM group. Estimating the distribution of usual dietary intake by short-term measurements. European Journal of Clinical Nutrition 2002; 56(Suppl. 2): S53–62.CrossRefGoogle ScholarPubMed
18Anderson, GH. Estimating nutrient deficiencies in a population from dietary records: the use of probability analyses. Nutrition Research 1982; 2: 409–15.CrossRefGoogle Scholar
19Cid-Ruzafa, J, Caulfield, LE, Barron, Y, West, SK. Nutrient intakes and adequacy among an older population on the eastern shore of Maryland: the Salisbury Eye Evaluation. Journal of the American Dietetic Association 1999; 99: 564–71.CrossRefGoogle ScholarPubMed
20Calloway, DH, Murphy, SP, Beaton, GH, Lein, D. Estimated vitamin intakes of toddlers: predicted prevalence of inadequacy in village populations in Egypt, Kenya, and Mexico. American Journal of Clinical Nutrition 1993; 58: 376–84.CrossRefGoogle ScholarPubMed
21Tarasuk, VS, Beaton, GH. Women's dietary intakes in the context of household food insecurity. Journal of Nutrition 1999; 129: 672–9.CrossRefGoogle ScholarPubMed
22Becker, W, Welten, D. Under-reporting in dietary surveys – implications for development of food-based dietary guidelines. Public Health Nutrition 2001; 4: 683–7.CrossRefGoogle ScholarPubMed
23O'Brien, MM, Kiely, M, Harrington, KE, Robson, PJ, Strain, JJ, Flynn, A. The North/South Ireland Food Consumption Survey: vitamin intakes in 18–64-year-old adults. Public Health Nutrition 2001; 4: 1069–79.CrossRefGoogle ScholarPubMed