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Childhood body mass index trajectories: modeling, characterizing, pairwise correlations and socio-demographic predictors of trajectory characteristics

Overview of attention for article published in BMC Medical Research Methodology, March 2012
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  • Average Attention Score compared to outputs of the same age and source

Mentioned by

twitter
1 tweeter

Citations

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79 Dimensions

Readers on

mendeley
97 Mendeley
Title
Childhood body mass index trajectories: modeling, characterizing, pairwise correlations and socio-demographic predictors of trajectory characteristics
Published in
BMC Medical Research Methodology, March 2012
DOI 10.1186/1471-2288-12-38
Pubmed ID
Authors

Xiaozhong Wen, Ken Kleinman, Matthew W Gillman, Sheryl L Rifas-Shiman, Elsie M Taveras

Abstract

Modeling childhood body mass index (BMI) trajectories, versus estimating change in BMI between specific ages, may improve prediction of later body-size-related outcomes. Prior studies of BMI trajectories are limited by restricted age periods and insufficient use of trajectory information.

Twitter Demographics

The data shown below were collected from the profile of 1 tweeter 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 97 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 2 2%
Brazil 1 1%
Australia 1 1%
Czechia 1 1%
United Kingdom 1 1%
Netherlands 1 1%
Unknown 90 93%

Demographic breakdown

Readers by professional status Count As %
Researcher 20 21%
Student > Master 20 21%
Student > Ph. D. Student 16 16%
Student > Doctoral Student 8 8%
Professor > Associate Professor 7 7%
Other 20 21%
Unknown 6 6%
Readers by discipline Count As %
Medicine and Dentistry 42 43%
Social Sciences 10 10%
Agricultural and Biological Sciences 7 7%
Nursing and Health Professions 5 5%
Mathematics 4 4%
Other 14 14%
Unknown 15 15%

Attention Score in Context

This research output has an Altmetric Attention Score of 1. 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 02 April 2012.
All research outputs
#2,369,640
of 4,504,824 outputs
Outputs from BMC Medical Research Methodology
#342
of 550 outputs
Outputs of similar age
#33,296
of 76,194 outputs
Outputs of similar age from BMC Medical Research Methodology
#17
of 35 outputs
Altmetric has tracked 4,504,824 research outputs across all sources so far. This one is in the 31st percentile – i.e., 31% of other outputs scored the same or lower than it.
So far Altmetric has tracked 550 research outputs from this source. They receive a mean Attention Score of 4.2. This one is in the 24th percentile – i.e., 24% of its peers scored the same or lower than it.
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 76,194 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 38th percentile – i.e., 38% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 35 others from the same source and published within six weeks on either side of this one. This one is in the 34th percentile – i.e., 34% of its contemporaries scored the same or lower than it.