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Heritability of dietary food intake patterns

Overview of attention for article published in Acta Diabetologica, March 2012
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About this Attention Score

  • Above-average Attention Score compared to outputs of the same age (55th percentile)
  • Good Attention Score compared to outputs of the same age and source (66th percentile)

Mentioned by

5 tweeters


8 Dimensions

Readers on

35 Mendeley
Heritability of dietary food intake patterns
Published in
Acta Diabetologica, March 2012
DOI 10.1007/s00592-012-0387-0
Pubmed ID

Linda van den Berg, Peter Henneman, Ko Willems van Dijk, Henriette A. Delemarre-van de Waal, Ben A. Oostra, Cornelia M. van Duijn, A. Cecile J. W. Janssens


The quality and quantity of food intake affect body weight, but little is known about the genetics of such human dietary intake patterns in relation to the genetics of BMI. We aimed to estimate the heritability of dietary intake patterns and genetic correlation with BMI in participants of the Erasmus Rucphen Family study. The study included 1,690 individuals (42 % men; age range, 19-92), of whom 41.4 % were overweight and 15.9 % were obese. Self-report questionnaires were used to assess the number of days (0-7) on which participants consumed vegetables, fruit, fruit juice, fish, unhealthy snacks, fastfood, and soft drinks. Principal component analysis was applied to examine the correlations between the questionnaire items and to generate dietary intake pattern scores. Heritability and the shared genetic and shared non-genetic (environmental) correlations were estimated using the family structure of the cohort. Principal component analysis suggested that the questionnaire items could be grouped in a healthy and unhealthy dietary intake pattern, explaining 22 and 18 % of the phenotypic variance, respectively. The dietary intake patterns had a heritability of 0.32 for the healthy and 0.27 for the unhealthy pattern. Genetic correlations between the dietary intake patterns and BMI were not significant, but we found a significant environmental correlation between the unhealthy dietary intake pattern and BMI. Specific dietary intake patterns are associated with the risk of obesity and are heritable traits. The genetic factors that determine specific dietary intake patterns do not significantly overlap with the genetic factors that determine BMI.

Twitter Demographics

The data shown below were collected from the profiles of 5 tweeters who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 35 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Netherlands 2 6%
Unknown 33 94%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 8 23%
Student > Bachelor 5 14%
Researcher 4 11%
Professor 3 9%
Student > Master 3 9%
Other 9 26%
Unknown 3 9%
Readers by discipline Count As %
Medicine and Dentistry 19 54%
Biochemistry, Genetics and Molecular Biology 4 11%
Agricultural and Biological Sciences 3 9%
Nursing and Health Professions 3 9%
Computer Science 1 3%
Other 3 9%
Unknown 2 6%

Attention Score in Context

This research output has an Altmetric Attention Score of 3. 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 19 December 2017.
All research outputs
of 12,319,220 outputs
Outputs from Acta Diabetologica
of 492 outputs
Outputs of similar age
of 115,093 outputs
Outputs of similar age from Acta Diabetologica
of 6 outputs
Altmetric has tracked 12,319,220 research outputs across all sources so far. This one is in the 46th percentile – i.e., 46% of other outputs scored the same or lower than it.
So far Altmetric has tracked 492 research outputs from this source. They receive a mean Attention Score of 3.5. This one has gotten more attention than average, scoring higher than 60% 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 115,093 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 55% of its contemporaries.
We're also able to compare this research output to 6 others from the same source and published within six weeks on either side of this one. This one has scored higher than 4 of them.