Development of databases for use in validation studies of probabilistic models of dietary exposure to food chemicals and nutrients
Development of databases for use in validation studies of probabilistic models of dietary exposure to food chemicals and nutrients
The data currently available in the European Union in terms of food consumption and of food chemical and nutrient concentration data present many limitations when used for estimating intake. The most refined techniques currently available were used within the European Union FP5 Monte Carlo project to estimate, as accurately as possible, the intake of food additives, pesticide residues and nutrients. Databases of 'true' intakes of food additives (based on brand level food consumption records and additive concentration data), pesticide residues (based on duplicate diet studies) and nutrients (based on biomarker studies) have thus been generated. These kind of estimates are rarely repeatable because the databases generated and used to calculate them require an extraordinary expenditure of time and resources. The databases created served the purpose of estimating as accurately as possible 'true' chemical intakes for assessing the validity of additive, nutrient and pesticide probabilistic models.
probabilistic modelling, Monte Carlo, food additives, pesticides, nutrients, database
S27-S35
Leclercq, C.
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Arcella, D.
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Armentia, A.
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Boon, P.E.
273b5ce2-5026-448f-82cf-59d1a9424b53
Kruizinga, A.G.
ced215c1-f9d1-476a-a768-e6c0634464f9
Gilsenan, M.B.
84b186b7-8921-43d3-85f0-d4351a3d5c92
Thompson, R.L.
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2003
Leclercq, C.
20b23ebe-c227-4957-b7c3-d8f38c10b1c7
Arcella, D.
c3ee1d49-322d-4670-8b8b-6a5fd623a436
Armentia, A.
0b8c49a9-ebb2-41be-b62e-fe0c29fa7eb1
Boon, P.E.
273b5ce2-5026-448f-82cf-59d1a9424b53
Kruizinga, A.G.
ced215c1-f9d1-476a-a768-e6c0634464f9
Gilsenan, M.B.
84b186b7-8921-43d3-85f0-d4351a3d5c92
Thompson, R.L.
1a394a6d-b006-4aec-b9be-b3e6c16fdb7b
Leclercq, C., Arcella, D., Armentia, A., Boon, P.E., Kruizinga, A.G., Gilsenan, M.B. and Thompson, R.L.
(2003)
Development of databases for use in validation studies of probabilistic models of dietary exposure to food chemicals and nutrients.
Food Additives and Contaminants, 20 (Supplement 1), .
(doi:10.1080/0265203031000134938).
Abstract
The data currently available in the European Union in terms of food consumption and of food chemical and nutrient concentration data present many limitations when used for estimating intake. The most refined techniques currently available were used within the European Union FP5 Monte Carlo project to estimate, as accurately as possible, the intake of food additives, pesticide residues and nutrients. Databases of 'true' intakes of food additives (based on brand level food consumption records and additive concentration data), pesticide residues (based on duplicate diet studies) and nutrients (based on biomarker studies) have thus been generated. These kind of estimates are rarely repeatable because the databases generated and used to calculate them require an extraordinary expenditure of time and resources. The databases created served the purpose of estimating as accurately as possible 'true' chemical intakes for assessing the validity of additive, nutrient and pesticide probabilistic models.
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Published date: 2003
Keywords:
probabilistic modelling, Monte Carlo, food additives, pesticides, nutrients, database
Identifiers
Local EPrints ID: 25750
URI: http://eprints.soton.ac.uk/id/eprint/25750
PURE UUID: 19ef0460-93e2-4d3a-bf85-460429f10619
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Date deposited: 10 Apr 2006
Last modified: 15 Mar 2024 07:05
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Contributors
Author:
C. Leclercq
Author:
D. Arcella
Author:
A. Armentia
Author:
P.E. Boon
Author:
A.G. Kruizinga
Author:
M.B. Gilsenan
Author:
R.L. Thompson
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