You are seeing a free-to-access but limited selection of the activity Altmetric has collected about this research output.
Click here to find out more.
X Demographics
Mendeley readers
Attention Score in Context
| Title |
Genetic contributions to stability and change in intelligence from childhood to old age
|
|---|---|
| Published in |
Nature, January 2012
|
| DOI | 10.1038/nature10781 |
| Pubmed ID | |
| Authors |
Ian J. Deary, Jian Yang, Gail Davies, Sarah E. Harris, Albert Tenesa, David Liewald, Michelle Luciano, Lorna M. Lopez, Alan J. Gow, Janie Corley, Paul Redmond, Helen C. Fox, Suzanne J. Rowe, Paul Haggarty, Geraldine McNeill, Michael E. Goddard, David J. Porteous, Lawrence J. Whalley, John M. Starr, Peter M. Visscher |
| Abstract |
Understanding the determinants of healthy mental ageing is a priority for society today. So far, we know that intelligence differences show high stability from childhood to old age and there are estimates of the genetic contribution to intelligence at different ages. However, attempts to discover whether genetic causes contribute to differences in cognitive ageing have been relatively uninformative. Here we provide an estimate of the genetic and environmental contributions to stability and change in intelligence across most of the human lifetime. We used genome-wide single nucleotide polymorphism (SNP) data from 1,940 unrelated individuals whose intelligence was measured in childhood (age 11 years) and again in old age (age 65, 70 or 79 years). We use a statistical method that allows genetic (co)variance to be estimated from SNP data on unrelated individuals. We estimate that causal genetic variants in linkage disequilibrium with common SNPs account for 0.24 of the variation in cognitive ability change from childhood to old age. Using bivariate analysis, we estimate a genetic correlation between intelligence at age 11 years and in old age of 0.62. These estimates, derived from rarely available data on lifetime cognitive measures, warrant the search for genetic causes of cognitive stability and change. |
X Demographics
The data shown below were collected from the profiles of 61 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United Kingdom | 11 | 18% |
| United States | 7 | 11% |
| Japan | 4 | 7% |
| Brazil | 3 | 5% |
| New Zealand | 2 | 3% |
| France | 2 | 3% |
| Spain | 2 | 3% |
| Italy | 2 | 3% |
| Comoros | 1 | 2% |
| Other | 4 | 7% |
| Unknown | 23 | 38% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 45 | 74% |
| Scientists | 10 | 16% |
| Practitioners (doctors, other healthcare professionals) | 5 | 8% |
| Science communicators (journalists, bloggers, editors) | 1 | 2% |
Mendeley readers
The data shown below were compiled from readership statistics for 469 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 15 | 3% |
| United Kingdom | 8 | 2% |
| Japan | 7 | 1% |
| Spain | 3 | <1% |
| Portugal | 2 | <1% |
| Poland | 2 | <1% |
| Sweden | 2 | <1% |
| Austria | 2 | <1% |
| Italy | 1 | <1% |
| Other | 11 | 2% |
| Unknown | 416 | 89% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 108 | 23% |
| Researcher | 73 | 16% |
| Student > Master | 57 | 12% |
| Student > Bachelor | 40 | 9% |
| Professor > Associate Professor | 36 | 8% |
| Other | 97 | 21% |
| Unknown | 58 | 12% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 142 | 30% |
| Psychology | 105 | 22% |
| Medicine and Dentistry | 45 | 10% |
| Biochemistry, Genetics and Molecular Biology | 25 | 5% |
| Neuroscience | 19 | 4% |
| Other | 52 | 11% |
| Unknown | 81 | 17% |
Attention Score in Context
This research output has an Altmetric Attention Score of 89. 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 28 December 2020.
All research outputs
#487,747
of 26,017,215 outputs
Outputs from Nature
#22,327
of 99,074 outputs
Outputs of similar age
#2,647
of 257,633 outputs
Outputs of similar age from Nature
#187
of 941 outputs
Altmetric has tracked 26,017,215 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 98th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 99,074 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 102.3. This one has done well, scoring higher than 77% 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 257,633 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 98% of its contemporaries.
We're also able to compare this research output to 941 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 80% of its contemporaries.