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Mendeley readers
Attention Score in Context
| Title |
Effect of interleukin-6 polymorphism on risk of preterm birth within population strata: a meta-analysis
|
|---|---|
| Published in |
BMC Genomic Data, April 2013
|
| DOI | 10.1186/1471-2156-14-30 |
| Pubmed ID | |
| Authors |
Wilfred Wu, Erin A S Clark, Gregory J Stoddard, W Scott Watkins, M Sean Esplin, Tracy A Manuck, Jinchuan Xing, Michael W Varner, Lynn B Jorde |
| Abstract |
Because of the role of inflammation in preterm birth (PTB), polymorphisms in and near the interleukin-6 gene (IL6) have been association study targets. Several previous studies have assessed the association between PTB and a single nucleotide polymorphism (SNP), rs1800795, located in the IL6 gene promoter region. Their results have been inconsistent and SNP frequencies have varied strikingly among different populations. We therefore conducted a meta-analysis with subgroup analysis by population strata to: (1) reduce the confounding effect of population structure, (2) increase sample size and statistical power, and (3) elucidate the association between rs1800975 and PTB. |
X Demographics
The data shown below were collected from the profile of 1 X user who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 1 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 1 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 41 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Uruguay | 2 | 5% |
| United States | 1 | 2% |
| Unknown | 38 | 93% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 11 | 27% |
| Student > Master | 6 | 15% |
| Student > Bachelor | 4 | 10% |
| Researcher | 3 | 7% |
| Professor > Associate Professor | 3 | 7% |
| Other | 5 | 12% |
| Unknown | 9 | 22% |
| Readers by discipline | Count | As % |
|---|---|---|
| Medicine and Dentistry | 15 | 37% |
| Agricultural and Biological Sciences | 9 | 22% |
| Pharmacology, Toxicology and Pharmaceutical Science | 3 | 7% |
| Biochemistry, Genetics and Molecular Biology | 2 | 5% |
| Nursing and Health Professions | 1 | 2% |
| Other | 2 | 5% |
| Unknown | 9 | 22% |
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 27 June 2013.
All research outputs
#22,756,649
of 25,371,288 outputs
Outputs from BMC Genomic Data
#1,008
of 1,203 outputs
Outputs of similar age
#180,195
of 205,930 outputs
Outputs of similar age from BMC Genomic Data
#17
of 20 outputs
Altmetric has tracked 25,371,288 research outputs across all sources so far. This one is in the 1st percentile – i.e., 1% of other outputs scored the same or lower than it.
So far Altmetric has tracked 1,203 research outputs from this source. They receive a mean Attention Score of 4.3. This one is in the 1st percentile – i.e., 1% 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 205,930 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 20 others from the same source and published within six weeks on either side of this one. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.