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X Demographics
Mendeley readers
Attention Score in Context
| Title |
smokeSALUD: exploring the effect of demographic change on the smoking prevalence at municipality level in Austria
|
|---|---|
| Published in |
International Journal of Health Geographics, October 2016
|
| DOI | 10.1186/s12942-016-0066-4 |
| Pubmed ID | |
| Authors |
Melanie Tomintz, Bernhard Kosar, Graham Clarke |
| Abstract |
Reducing the smoking population is still high on the policy agenda, as smoking leads to many preventable diseases, such as lung cancer, heart disease, diabetes, and more. In Austria, data on smoking prevalence only exists at the federal state level. This provides an interesting overview about the current health situation, but for regional planning authorities these data are often insufficient as they can hide pockets of high and low smoking prevalence in certain municipalities. This paper presents a spatial-temporal change of estimated smokers for municipalities from 2001 and 2011. A synthetic dataset of smokers is built by combining individual large-scale survey data and small area census data using a deterministic spatial microsimulation approach. Statistical analysis, including chi-square test and binary logistic regression, are applied to find the best variables for the simulation model and to validate its results. As no easy-to-use spatial microsimulation software for non-programmers is available yet, a flexible web-based spatial microsimulation application for health decision support (called simSALUD) has been developed and used for these analyses. The results of the simulation show in general a decrease of smoking prevalence within municipalities between 2001 and 2011 and differences within areas are identified. These results are especially valuable to policy decision makers for future planning strategies. This case study shows the application of smokeSALUD to model the spatial-temporal changes in the smoking population in Austria between 2001 and 2011. This is important as no data on smoking exists at this geographical scale (municipality). However, spatial microsimulation models are useful tools to estimate small area health data and to overcome these problems. The simulations and analysis should support health decision makers to identify hot spots of smokers and this should help to show where to spend health resources best in order to reduce health inequalities. |
X Demographics
The data shown below were collected from the profiles of 3 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Mexico | 1 | 33% |
| New Zealand | 1 | 33% |
| Unknown | 1 | 33% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 2 | 67% |
| Scientists | 1 | 33% |
Mendeley readers
The data shown below were compiled from readership statistics for 52 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 52 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Bachelor | 13 | 25% |
| Student > Master | 8 | 15% |
| Researcher | 8 | 15% |
| Lecturer | 3 | 6% |
| Other | 3 | 6% |
| Other | 7 | 13% |
| Unknown | 10 | 19% |
| Readers by discipline | Count | As % |
|---|---|---|
| Nursing and Health Professions | 11 | 21% |
| Medicine and Dentistry | 9 | 17% |
| Engineering | 4 | 8% |
| Social Sciences | 4 | 8% |
| Economics, Econometrics and Finance | 2 | 4% |
| Other | 12 | 23% |
| Unknown | 10 | 19% |
Attention Score in Context
This research output has an Altmetric Attention Score of 4. 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 23 October 2016.
All research outputs
#7,176,658
of 22,893,031 outputs
Outputs from International Journal of Health Geographics
#247
of 629 outputs
Outputs of similar age
#109,483
of 320,333 outputs
Outputs of similar age from International Journal of Health Geographics
#4
of 13 outputs
Altmetric has tracked 22,893,031 research outputs across all sources so far. This one has received more attention than most of these and is in the 68th percentile.
So far Altmetric has tracked 629 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 9.4. This one has gotten more attention than average, scoring higher than 60% 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 320,333 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 65% of its contemporaries.
We're also able to compare this research output to 13 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 69% of its contemporaries.