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Mendeley readers
Attention Score in Context
Title |
Ten-year trends in major lifestyle risk factors using an ongoing population surveillance system in Australia
|
---|---|
Published in |
Population Health Metrics, October 2014
|
DOI | 10.1186/s12963-014-0031-z |
Pubmed ID | |
Authors |
Anne W Taylor, Eleonora Dal Grande, Jing Wu, Zumin Shi, Stefano Campostrini |
Abstract |
Understanding how risk factors (tobacco, alcohol, physical inactivity, unhealthy diet, high blood pressure, and high cholesterol) change over time is a critical aim of public health. The associations across the social gradient over time are important considerations. Risk factor surveillance systems have a part to play in understanding the epidemiological distribution of the risk factors so as to improve preventive measures and design public health interventions for reducing the burden of disease. |
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 % |
---|---|---|
Practitioners (doctors, other healthcare professionals) | 1 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 61 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
Country | Count | As % |
---|---|---|
Indonesia | 1 | 2% |
Unknown | 60 | 98% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Student > Master | 11 | 18% |
Student > Ph. D. Student | 10 | 16% |
Researcher | 9 | 15% |
Student > Bachelor | 5 | 8% |
Student > Postgraduate | 3 | 5% |
Other | 9 | 15% |
Unknown | 14 | 23% |
Readers by discipline | Count | As % |
---|---|---|
Medicine and Dentistry | 13 | 21% |
Social Sciences | 8 | 13% |
Nursing and Health Professions | 7 | 11% |
Economics, Econometrics and Finance | 4 | 7% |
Psychology | 3 | 5% |
Other | 6 | 10% |
Unknown | 20 | 33% |
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 30 October 2014.
All research outputs
#20,196,575
of 24,827,122 outputs
Outputs from Population Health Metrics
#361
of 408 outputs
Outputs of similar age
#193,396
of 266,243 outputs
Outputs of similar age from Population Health Metrics
#6
of 8 outputs
Altmetric has tracked 24,827,122 research outputs across all sources so far. This one is in the 10th percentile – i.e., 10% of other outputs scored the same or lower than it.
So far Altmetric has tracked 408 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 14.1. This one is in the 2nd percentile – i.e., 2% 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 266,243 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 15th percentile – i.e., 15% of its contemporaries scored the same or lower than it.
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 2 of them.