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Evaluation of a nutrient-rich food index score in the Netherlands
Nutrient-rich food (NRF) index scores are dietary quality indices based on nutrient density. We studied the design aspects involved in the development and validation of NRF index scores, using the Dutch consumption data and guidelines as an example. We evaluated fifteen NRF index scores against the...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Cambridge University Press
2015
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4462757/ https://www.ncbi.nlm.nih.gov/pubmed/26097700 http://dx.doi.org/10.1017/jns.2015.4 |
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author | Sluik, Diewertje Streppel, Martinette T. van Lee, Linde Geelen, Anouk Feskens, Edith J. M. |
author_facet | Sluik, Diewertje Streppel, Martinette T. van Lee, Linde Geelen, Anouk Feskens, Edith J. M. |
author_sort | Sluik, Diewertje |
collection | PubMed |
description | Nutrient-rich food (NRF) index scores are dietary quality indices based on nutrient density. We studied the design aspects involved in the development and validation of NRF index scores, using the Dutch consumption data and guidelines as an example. We evaluated fifteen NRF index scores against the Dutch Healthy Diet Index (DHD-index), a measure of adherence to the Dutch dietary guidelines, and against energy density. The study population included 2106 adults from the Dutch National Food Consumption Survey 2007–2010. The index scores were composed of beneficial nutrients (protein, fibre, fatty acids, vitamins, minerals), nutrients to limit (saturated fat, sugar, Na) or a combination. Moreover, the influence of methodological decisions was studied, such as the choice of calculation basis (100 g or 100 kcal (418 kJ)). No large differences existed in the prediction of the DHD-index by the fifteen NRF index scores. The score that best predicted the DHD-index included nine beneficial nutrients and three nutrients to limit on a 100-kcal basis, the NRF9.3 with a model R(2) of 0·34. The scores were quite robust with respect to sex, BMI and differences in calculation methods. The NRF index scores were correlated with energy density, but nutrient density better predicted the DHD-index than energy density. Consumption of vegetables, cereals and cereal products, and dairy products contributed most to the individual NRF9.3 scores. In conclusion, many methodological considerations underlie the development and evaluation of nutrient density models. These decisions may depend upon the purpose of the model, but should always be based upon scientific, objective and transparent criteria. |
format | Online Article Text |
id | pubmed-4462757 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2015 |
publisher | Cambridge University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-44627572015-06-19 Evaluation of a nutrient-rich food index score in the Netherlands Sluik, Diewertje Streppel, Martinette T. van Lee, Linde Geelen, Anouk Feskens, Edith J. M. J Nutr Sci Research Article Nutrient-rich food (NRF) index scores are dietary quality indices based on nutrient density. We studied the design aspects involved in the development and validation of NRF index scores, using the Dutch consumption data and guidelines as an example. We evaluated fifteen NRF index scores against the Dutch Healthy Diet Index (DHD-index), a measure of adherence to the Dutch dietary guidelines, and against energy density. The study population included 2106 adults from the Dutch National Food Consumption Survey 2007–2010. The index scores were composed of beneficial nutrients (protein, fibre, fatty acids, vitamins, minerals), nutrients to limit (saturated fat, sugar, Na) or a combination. Moreover, the influence of methodological decisions was studied, such as the choice of calculation basis (100 g or 100 kcal (418 kJ)). No large differences existed in the prediction of the DHD-index by the fifteen NRF index scores. The score that best predicted the DHD-index included nine beneficial nutrients and three nutrients to limit on a 100-kcal basis, the NRF9.3 with a model R(2) of 0·34. The scores were quite robust with respect to sex, BMI and differences in calculation methods. The NRF index scores were correlated with energy density, but nutrient density better predicted the DHD-index than energy density. Consumption of vegetables, cereals and cereal products, and dairy products contributed most to the individual NRF9.3 scores. In conclusion, many methodological considerations underlie the development and evaluation of nutrient density models. These decisions may depend upon the purpose of the model, but should always be based upon scientific, objective and transparent criteria. Cambridge University Press 2015-04-20 /pmc/articles/PMC4462757/ /pubmed/26097700 http://dx.doi.org/10.1017/jns.2015.4 Text en © The Author(s) 2015 This is an Open Access article, distributed under the terms of the Creative Commons Attribution licence (http://creativecommons.org/licenses/by/3.0/), which permits unrestricted re-use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Research Article Sluik, Diewertje Streppel, Martinette T. van Lee, Linde Geelen, Anouk Feskens, Edith J. M. Evaluation of a nutrient-rich food index score in the Netherlands |
title | Evaluation of a nutrient-rich food index score in the Netherlands |
title_full | Evaluation of a nutrient-rich food index score in the Netherlands |
title_fullStr | Evaluation of a nutrient-rich food index score in the Netherlands |
title_full_unstemmed | Evaluation of a nutrient-rich food index score in the Netherlands |
title_short | Evaluation of a nutrient-rich food index score in the Netherlands |
title_sort | evaluation of a nutrient-rich food index score in the netherlands |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4462757/ https://www.ncbi.nlm.nih.gov/pubmed/26097700 http://dx.doi.org/10.1017/jns.2015.4 |
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