Personalised fish intake recommendations: the effect of background exposure on optimisation

Inez Maria Persson*, Sisse Fagt, Maarten Nauta

*Corresponding author for this work

Research output: Contribution to journalJournal articleResearchpeer-review

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Abstract

National dietary guidelines are directed at the general population. However, these guidelines may be perceived as unrealistic by a substantial part of the population, as they differ considerably from individual consumption patterns and preferences. Personalised dietary recommendations will probably improve adherence, and it has been shown that these recommendations can be derived by mathematical optimisation methods. However, to better account for risks and benefits of specific foods, the background exposure to nutrients and contaminants needs to be considered as well. This background exposure may come from other foods and supplements, and also from environmental sources like the air and the sun. The objective of this study was therefore to analyse the effect of including individual variation in background exposure when modelling personalised dietary recommendations for fish. We used a quadratic programming model to generate recommended fish intake accounting for personal preference by deviating as little as possible from observed individual intake. Model constraints ensure that the modelled intake meets recommendations for EPA, DHA and vitamin D without violating tolerable exposure to methyl mercury, dioxins and dioxin-like polychlorinated biphenyls. Several background exposures were analysed for 3016 Danish adults, whose food intakes and body weights were reported in a national dietary survey. We found that the lower nutrient constraints were critical for the largest part of the study population, and that a total of 55% should be advised to increase their fish intake. The modelled fish intake recommendations were particularly sensitive to the vitamin D background exposure.
Original languageEnglish
JournalBritish Journal of Nutrition
Volume120
Issue number8
Pages (from-to) 946-957
ISSN0007-1145
DOIs
Publication statusPublished - 2018

Keywords

  • Personalised dietary recommendations
  • Dietary habits
  • Diet optimisation model
  • Quadratic programming
  • Background exposure
  • 25-hydroxyvitamin D
  • Dioxin-like polychlorinated biphenyls
  • Low dioxin

Cite this

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title = "Personalised fish intake recommendations: the effect of background exposure on optimisation",
abstract = "National dietary guidelines are directed at the general population. However, these guidelines may be perceived as unrealistic by a substantial part of the population, as they differ considerably from individual consumption patterns and preferences. Personalised dietary recommendations will probably improve adherence, and it has been shown that these recommendations can be derived by mathematical optimisation methods. However, to better account for risks and benefits of specific foods, the background exposure to nutrients and contaminants needs to be considered as well. This background exposure may come from other foods and supplements, and also from environmental sources like the air and the sun. The objective of this study was therefore to analyse the effect of including individual variation in background exposure when modelling personalised dietary recommendations for fish. We used a quadratic programming model to generate recommended fish intake accounting for personal preference by deviating as little as possible from observed individual intake. Model constraints ensure that the modelled intake meets recommendations for EPA, DHA and vitamin D without violating tolerable exposure to methyl mercury, dioxins and dioxin-like polychlorinated biphenyls. Several background exposures were analysed for 3016 Danish adults, whose food intakes and body weights were reported in a national dietary survey. We found that the lower nutrient constraints were critical for the largest part of the study population, and that a total of 55{\%} should be advised to increase their fish intake. The modelled fish intake recommendations were particularly sensitive to the vitamin D background exposure.",
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author = "Persson, {Inez Maria} and Sisse Fagt and Maarten Nauta",
year = "2018",
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Personalised fish intake recommendations: the effect of background exposure on optimisation. / Persson, Inez Maria; Fagt, Sisse; Nauta, Maarten .

In: British Journal of Nutrition, Vol. 120, No. 8, 2018, p. 946-957.

Research output: Contribution to journalJournal articleResearchpeer-review

TY - JOUR

T1 - Personalised fish intake recommendations: the effect of background exposure on optimisation

AU - Persson, Inez Maria

AU - Fagt, Sisse

AU - Nauta, Maarten

PY - 2018

Y1 - 2018

N2 - National dietary guidelines are directed at the general population. However, these guidelines may be perceived as unrealistic by a substantial part of the population, as they differ considerably from individual consumption patterns and preferences. Personalised dietary recommendations will probably improve adherence, and it has been shown that these recommendations can be derived by mathematical optimisation methods. However, to better account for risks and benefits of specific foods, the background exposure to nutrients and contaminants needs to be considered as well. This background exposure may come from other foods and supplements, and also from environmental sources like the air and the sun. The objective of this study was therefore to analyse the effect of including individual variation in background exposure when modelling personalised dietary recommendations for fish. We used a quadratic programming model to generate recommended fish intake accounting for personal preference by deviating as little as possible from observed individual intake. Model constraints ensure that the modelled intake meets recommendations for EPA, DHA and vitamin D without violating tolerable exposure to methyl mercury, dioxins and dioxin-like polychlorinated biphenyls. Several background exposures were analysed for 3016 Danish adults, whose food intakes and body weights were reported in a national dietary survey. We found that the lower nutrient constraints were critical for the largest part of the study population, and that a total of 55% should be advised to increase their fish intake. The modelled fish intake recommendations were particularly sensitive to the vitamin D background exposure.

AB - National dietary guidelines are directed at the general population. However, these guidelines may be perceived as unrealistic by a substantial part of the population, as they differ considerably from individual consumption patterns and preferences. Personalised dietary recommendations will probably improve adherence, and it has been shown that these recommendations can be derived by mathematical optimisation methods. However, to better account for risks and benefits of specific foods, the background exposure to nutrients and contaminants needs to be considered as well. This background exposure may come from other foods and supplements, and also from environmental sources like the air and the sun. The objective of this study was therefore to analyse the effect of including individual variation in background exposure when modelling personalised dietary recommendations for fish. We used a quadratic programming model to generate recommended fish intake accounting for personal preference by deviating as little as possible from observed individual intake. Model constraints ensure that the modelled intake meets recommendations for EPA, DHA and vitamin D without violating tolerable exposure to methyl mercury, dioxins and dioxin-like polychlorinated biphenyls. Several background exposures were analysed for 3016 Danish adults, whose food intakes and body weights were reported in a national dietary survey. We found that the lower nutrient constraints were critical for the largest part of the study population, and that a total of 55% should be advised to increase their fish intake. The modelled fish intake recommendations were particularly sensitive to the vitamin D background exposure.

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