Copyright © 2007 Elsevier Ltd All rights reserved.
Review
Probabilistic modelling of European consumer exposure to cosmetic products
Received 1 February 2007;
Abstract
In this study, we describe the statistical analysis of the usage profile of the European population to seven cosmetic products. The aim of the study was to construct a reliable model of exposure of the European population from use of the selected products: body lotion, shampoo, deodorant spray, deodorant non-spray, facial moisturiser, lipstick and toothpaste.
The first step in this process was to gather reliable data on consumer usage patterns of the products. These data were sourced from a combination of market information databases and a controlled product use study by the trade association Colipa. The market information study contained a large number of subjects, in total 44,100 households and 18,057 habitual users (males and females) of the studied products, in five European countries.
The data sets were then combined to generate a realistic distribution of frequency of use of each product, combined with distribution of the amount of product used at each occasion using the CREMe software. A Monte Carlo method was used to combine the data sets. This resulted in a new model of European exposure to cosmetic products being constructed.
Keywords: Cosmetics; Exposure; Probabilistic analysis; Monte Carlo; Statistical population modelling
Article Outline
- 1. Introduction
- 2. Materials and methods
- 2.1. Input data sources
- 2.2. Analysis of the ISC data
- 2.2.1. Demographic categories
- 2.2.2. ISC outliers
- 2.3. ISC correlations
- 2.4. Model input data
- 2.4.1. Generating the product usage database by combining the amount of product per use with the ETCD database
- 2.4.2. Parametric versus non-parametric
- 2.4.3. Effect of correlations and generation of correlated amount values
- 2.4.4. Entering data into the model summary
- 2.5. Generating and running the model
- 2.5.1. Simulating GB exposure
- 2.5.2. Europanel scaling factor for GB
- 2.5.3. Simulation engine
- 2.5.4. Description of the CREMe model details
- 2.5.5. Simulating exposure beyond GB (Denmark, Germany, France and Spain)
- 2.5.6. Scaling factors from the Europanel data
- 2.5.7. Entering bodyweight information for each population
- 2.6. EU 15 member states (EU 15) exposure model
- 3. Results
- 3.1. Sensitivity analysis
- 4. Discussion
- 5. Conclusions
- Conflict of interest statement
- References






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