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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Do differences in the administrative structure of populations confound comparisons of geographic health inequalities?
|
|---|---|
| Published in |
BMC Medical Research Methodology, August 2010
|
| DOI | 10.1186/1471-2288-10-74 |
| Pubmed ID | |
| Authors |
Andrew L Jackson, Carolyn A Davies, Alastair H Leyland |
| Abstract |
Geographical health inequalities are naturally described by the variation in health outcomes between areas (e.g. mortality rates). However, comparisons made between countries are hampered by our lack of understanding of the effect of the size of administrative units, and in particular the modifiable areal unit problem. Our objective was to assess how differences in geographic and administrative units used for disseminating data affect the description of health inequalities. |
X Demographics
The data shown below were collected from the profiles of 2 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Ireland | 1 | 50% |
| Unknown | 1 | 50% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Scientists | 1 | 50% |
| Practitioners (doctors, other healthcare professionals) | 1 | 50% |
Mendeley readers
The data shown below were compiled from readership statistics for 42 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United Kingdom | 2 | 5% |
| Switzerland | 1 | 2% |
| Kenya | 1 | 2% |
| Spain | 1 | 2% |
| Japan | 1 | 2% |
| United States | 1 | 2% |
| Unknown | 35 | 83% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Master | 10 | 24% |
| Researcher | 7 | 17% |
| Other | 5 | 12% |
| Student > Ph. D. Student | 4 | 10% |
| Professor > Associate Professor | 3 | 7% |
| Other | 8 | 19% |
| Unknown | 5 | 12% |
| Readers by discipline | Count | As % |
|---|---|---|
| Medicine and Dentistry | 9 | 21% |
| Social Sciences | 9 | 21% |
| Nursing and Health Professions | 4 | 10% |
| Economics, Econometrics and Finance | 3 | 7% |
| Agricultural and Biological Sciences | 2 | 5% |
| Other | 8 | 19% |
| Unknown | 7 | 17% |
Attention Score in Context
This research output has an Altmetric Attention Score of 2. 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 30 September 2014.
All research outputs
#14,158,070
of 22,689,790 outputs
Outputs from BMC Medical Research Methodology
#1,373
of 2,001 outputs
Outputs of similar age
#74,600
of 94,476 outputs
Outputs of similar age from BMC Medical Research Methodology
#12
of 14 outputs
Altmetric has tracked 22,689,790 research outputs across all sources so far. This one is in the 35th percentile – i.e., 35% of other outputs scored the same or lower than it.
So far Altmetric has tracked 2,001 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 10.2. This one is in the 28th percentile – i.e., 28% 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 94,476 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 20th percentile – i.e., 20% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 14 others from the same source and published within six weeks on either side of this one. This one is in the 14th percentile – i.e., 14% of its contemporaries scored the same or lower than it.