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Diet and exercise changes following direct-to-consumer personal genomic testing

Overview of attention for article published in BMC Medical Genomics, May 2017
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About this Attention Score

  • In the top 5% of all research outputs scored by Altmetric
  • Among the highest-scoring outputs from this source (#14 of 952)
  • High Attention Score compared to outputs of the same age (94th percentile)
  • High Attention Score compared to outputs of the same age and source (99th percentile)

Mentioned by

news
1 news outlet
blogs
2 blogs
twitter
36 tweeters
facebook
2 Facebook pages

Citations

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15 Dimensions

Readers on

mendeley
106 Mendeley
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Title
Diet and exercise changes following direct-to-consumer personal genomic testing
Published in
BMC Medical Genomics, May 2017
DOI 10.1186/s12920-017-0258-1
Pubmed ID
Authors

Daiva Elena Nielsen, Deanna Alexis Carere, Catharine Wang, J. Scott Roberts, Robert C. Green

Abstract

The impacts of direct-to-consumer personal genomic testing (PGT) on health behaviors such as diet and exercise are poorly understood. Our investigation aimed to evaluate diet and exercise changes following PGT and to determine if changes were associated with genetic test results obtained from PGT. Customers of 23andMe and Pathway Genomics completed a web-based survey prior to receiving PGT results (baseline) and 6 months post-results. Fruit and vegetable intake (servings/day), and light, vigorous and strength exercise frequency (days/week) were assessed. Changes in diet and exercise were examined using paired t-tests and linear regressions. Additional analyses examined whether outcomes differed by baseline self-reported health (SRH) or content of PGT results. Longitudinal data were available for 1,002 participants. Significant increases were observed for vegetable intake (mean Δ = 0.11 (95% CI = 0.05, 0.17), p = 0.0003) and strength exercise (Δ = 0.14 (0.03, 0.25), p = 0.0153). When stratified by SRH, significant increases were observed for all outcomes among lower SRH participants: fruit intake, Δ = 0.11 (0.02, 0.21), p = 0.0148; vegetable intake, Δ = 0.16 (0.07, 0.25), p = 0.0005; light exercise, Δ = 0.25 (0.03, 0.47), p = 0.0263; vigorous exercise, Δ = 0.23 (0.06, 0.41), p = 0.0097; strength exercise, Δ = 0.19 (0.01, 0.37), p = 0.0369. A significant change among higher SRH participants was only observed for light exercise, and in the opposite direction: Δ = -0.2468 (-0.06, -0.44), p = 0.0111. Genetic results were not consistently associated with any diet or exercise changes. The experience of PGT was associated with modest, mostly positive changes in diet and exercise. Associations were independent of genetic results from PGT.

Twitter Demographics

The data shown below were collected from the profiles of 36 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 106 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 106 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 21 20%
Student > Ph. D. Student 13 12%
Student > Bachelor 12 11%
Student > Master 12 11%
Other 11 10%
Other 17 16%
Unknown 20 19%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 25 24%
Medicine and Dentistry 13 12%
Psychology 8 8%
Agricultural and Biological Sciences 8 8%
Social Sciences 7 7%
Other 21 20%
Unknown 24 23%

Attention Score in Context

This research output has an Altmetric Attention Score of 47. 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 16 October 2019.
All research outputs
#561,159
of 17,897,867 outputs
Outputs from BMC Medical Genomics
#14
of 952 outputs
Outputs of similar age
#15,354
of 274,116 outputs
Outputs of similar age from BMC Medical Genomics
#1
of 8 outputs
Altmetric has tracked 17,897,867 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 96th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 952 research outputs from this source. They receive a mean Attention Score of 4.7. This one has done particularly well, scoring higher than 98% 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 274,116 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 94% of its contemporaries.
We're also able to compare this research output to 8 others from the same source and published within six weeks on either side of this one. This one has scored higher than all of them