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Estimation of Apple Intake for the Exposure Assessment of Residual Chemicals Using Korea National Health and Nutrition Examination Survey Database
The aims of this study were to develop strategies and algorithms of calculating food commodity intake suitable for exposure assessment of residual chemicals by using the food intake database of Korea National Health and Nutrition Examination Survey (KNHANES). In this study, apples and their processe...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
The Korean Society of Clinical Nutrition
2016
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4855046/ https://www.ncbi.nlm.nih.gov/pubmed/27152299 http://dx.doi.org/10.7762/cnr.2016.5.2.96 |
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author | Kim, Bumsik Baek, Min-Seok Lee, Yongmin Paik, Jean Kyung Chang, Moon-Ik Rhee, Gyu-Seek Ko, Sanghoon |
author_facet | Kim, Bumsik Baek, Min-Seok Lee, Yongmin Paik, Jean Kyung Chang, Moon-Ik Rhee, Gyu-Seek Ko, Sanghoon |
author_sort | Kim, Bumsik |
collection | PubMed |
description | The aims of this study were to develop strategies and algorithms of calculating food commodity intake suitable for exposure assessment of residual chemicals by using the food intake database of Korea National Health and Nutrition Examination Survey (KNHANES). In this study, apples and their processed food products were chosen as a model food for accurate calculation of food commodity intakes uthrough the recently developed Korea food commodity intake calculation (KFCIC) software. The average daily intakes of total apples in Korea Health Statistics were 29.60 g in 2008, 32.40 g in 2009, 34.30 g in 2010, 28.10 g in 2011, and 24.60 g in 2012. The average daily intakes of apples by KFCIC software was 2.65 g higher than that by Korea Health Statistics. The food intake data in Korea Health Statistics might have less reflected the intake of apples from mixed and processed foods than KFCIC software has. These results can affect outcome of risk assessment for residual chemicals in foods. Therefore, the accurate estimation of the average daily intake of food commodities is very important, and more data for food intakes and recipes have to be applied to improve the quality of data. Nevertheless, this study can contribute to the predictive estimation of exposure to possible residual chemicals and subsequent analysis for their potential risks. |
format | Online Article Text |
id | pubmed-4855046 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2016 |
publisher | The Korean Society of Clinical Nutrition |
record_format | MEDLINE/PubMed |
spelling | pubmed-48550462016-05-05 Estimation of Apple Intake for the Exposure Assessment of Residual Chemicals Using Korea National Health and Nutrition Examination Survey Database Kim, Bumsik Baek, Min-Seok Lee, Yongmin Paik, Jean Kyung Chang, Moon-Ik Rhee, Gyu-Seek Ko, Sanghoon Clin Nutr Res Original Article The aims of this study were to develop strategies and algorithms of calculating food commodity intake suitable for exposure assessment of residual chemicals by using the food intake database of Korea National Health and Nutrition Examination Survey (KNHANES). In this study, apples and their processed food products were chosen as a model food for accurate calculation of food commodity intakes uthrough the recently developed Korea food commodity intake calculation (KFCIC) software. The average daily intakes of total apples in Korea Health Statistics were 29.60 g in 2008, 32.40 g in 2009, 34.30 g in 2010, 28.10 g in 2011, and 24.60 g in 2012. The average daily intakes of apples by KFCIC software was 2.65 g higher than that by Korea Health Statistics. The food intake data in Korea Health Statistics might have less reflected the intake of apples from mixed and processed foods than KFCIC software has. These results can affect outcome of risk assessment for residual chemicals in foods. Therefore, the accurate estimation of the average daily intake of food commodities is very important, and more data for food intakes and recipes have to be applied to improve the quality of data. Nevertheless, this study can contribute to the predictive estimation of exposure to possible residual chemicals and subsequent analysis for their potential risks. The Korean Society of Clinical Nutrition 2016-04 2016-04-30 /pmc/articles/PMC4855046/ /pubmed/27152299 http://dx.doi.org/10.7762/cnr.2016.5.2.96 Text en © 2016 The Korean Society of Clinical Nutrition http://creativecommons.org/licenses/by-nc/3.0/ This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/3.0/) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Original Article Kim, Bumsik Baek, Min-Seok Lee, Yongmin Paik, Jean Kyung Chang, Moon-Ik Rhee, Gyu-Seek Ko, Sanghoon Estimation of Apple Intake for the Exposure Assessment of Residual Chemicals Using Korea National Health and Nutrition Examination Survey Database |
title | Estimation of Apple Intake for the Exposure Assessment of Residual Chemicals Using Korea National Health and Nutrition Examination Survey Database |
title_full | Estimation of Apple Intake for the Exposure Assessment of Residual Chemicals Using Korea National Health and Nutrition Examination Survey Database |
title_fullStr | Estimation of Apple Intake for the Exposure Assessment of Residual Chemicals Using Korea National Health and Nutrition Examination Survey Database |
title_full_unstemmed | Estimation of Apple Intake for the Exposure Assessment of Residual Chemicals Using Korea National Health and Nutrition Examination Survey Database |
title_short | Estimation of Apple Intake for the Exposure Assessment of Residual Chemicals Using Korea National Health and Nutrition Examination Survey Database |
title_sort | estimation of apple intake for the exposure assessment of residual chemicals using korea national health and nutrition examination survey database |
topic | Original Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4855046/ https://www.ncbi.nlm.nih.gov/pubmed/27152299 http://dx.doi.org/10.7762/cnr.2016.5.2.96 |
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