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Designing optimal food intake patterns to achieve nutritional goals for Japanese adults through the use of linear programming optimization models

Overview of attention for article published in Nutrition Journal, June 2015
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (90th percentile)
  • Above-average Attention Score compared to outputs of the same age and source (60th percentile)

Mentioned by

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1 news outlet
policy
1 policy source
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6 X users

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141 Mendeley
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Title
Designing optimal food intake patterns to achieve nutritional goals for Japanese adults through the use of linear programming optimization models
Published in
Nutrition Journal, June 2015
DOI 10.1186/s12937-015-0047-7
Pubmed ID
Authors

Hitomi Okubo, Satoshi Sasaki, Kentaro Murakami, Tetsuji Yokoyama, Naoko Hirota, Akiko Notsu, Mitsuru Fukui, Chigusa Date

Abstract

Simultaneous dietary achievement of a full set of nutritional recommendations is difficult. Diet optimization model using linear programming is a useful mathematical means of translating nutrient-based recommendations into realistic nutritionally-optimal food combinations incorporating local and culture-specific foods. We used this approach to explore optimal food intake patterns that meet the nutrient recommendations of the Dietary Reference Intakes (DRIs) while incorporating typical Japanese food selections. As observed intake values, we used the food and nutrient intake data of 92 women aged 31-69 years and 82 men aged 32-69 years living in three regions of Japan. Dietary data were collected with semi-weighed dietary record on four non-consecutive days in each season of the year (16 days total). The linear programming models were constructed to minimize the differences between observed and optimized food intake patterns while also meeting the DRIs for a set of 28 nutrients, setting energy equal to estimated requirements, and not exceeding typical quantities of each food consumed by each age (30-49 or 50-69 years) and gender group. We successfully developed mathematically optimized food intake patterns that met the DRIs for all 28 nutrients studied in each sex and age group. Achieving nutritional goals required minor modifications of existing diets in older groups, particularly women, while major modifications were required to increase intake of fruit and vegetables in younger groups of both sexes. Across all sex and age groups, optimized food intake patterns demanded greatly increased intake of whole grains and reduced-fat dairy products in place of intake of refined grains and full-fat dairy products. Salt intake goals were the most difficult to achieve, requiring marked reduction of salt-containing seasoning (65-80 %) in all sex and age groups. Using a linear programming model, we identified optimal food intake patterns providing practical food choices and meeting nutritional recommendations for Japanese populations. Dietary modifications from current eating habits required to fulfil nutritional goals differed by age: more marked increases in food volume were required in younger groups.

X Demographics

X Demographics

The data shown below were collected from the profiles of 6 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 141 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United Kingdom 1 <1%
Ethiopia 1 <1%
Germany 1 <1%
France 1 <1%
Unknown 137 97%

Demographic breakdown

Readers by professional status Count As %
Student > Master 29 21%
Student > Bachelor 23 16%
Student > Ph. D. Student 18 13%
Researcher 12 9%
Lecturer 6 4%
Other 15 11%
Unknown 38 27%
Readers by discipline Count As %
Medicine and Dentistry 25 18%
Nursing and Health Professions 25 18%
Mathematics 12 9%
Agricultural and Biological Sciences 11 8%
Computer Science 8 6%
Other 20 14%
Unknown 40 28%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 18. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 21 March 2023.
All research outputs
#1,778,226
of 23,567,572 outputs
Outputs from Nutrition Journal
#451
of 1,447 outputs
Outputs of similar age
#23,603
of 267,825 outputs
Outputs of similar age from Nutrition Journal
#11
of 28 outputs
Altmetric has tracked 23,567,572 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 92nd percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 1,447 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 37.2. This one has gotten more attention than average, scoring higher than 68% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 267,825 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 90% of its contemporaries.
We're also able to compare this research output to 28 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 60% of its contemporaries.