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Urban–rural inequalities in suicide mortality: a comparison of urbanicity indicators

Overview of attention for article published in International Journal of Health Geographics, October 2017
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  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (80th percentile)
  • Good Attention Score compared to outputs of the same age and source (76th percentile)

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Title
Urban–rural inequalities in suicide mortality: a comparison of urbanicity indicators
Published in
International Journal of Health Geographics, October 2017
DOI 10.1186/s12942-017-0112-x
Pubmed ID
Authors

M. Helbich, V. Blüml, T. de Jong, P. L. Plener, M.-P. Kwan, N. D. Kapusta

Abstract

Urban-rural disparities in suicide mortality have received considerable attention. Varying conceptualizations of urbanity may contribute to the conflicting findings. This ecological study on Germany assessed how and to what extent urban-rural suicide associations are affected by 14 different urban-rural indicators. Indicators were based on continuous or k-means classified population data, land-use data, planning typologies, or represented population-based accessibility indicators. Agreements between indicators were tested with correlation analyses. Spatial Bayesian Poisson regressions were estimated to examine urban-rural suicide associations while adjusting for risk and protective factors. Urban-rural differences in suicide rates per 100,000 persons were found irrespective of the indicator. Strong and significant correlation was observed between different urban-rural indicators. Although the effect sign consistently referred to a reduced risk in urban areas, statistical significance was not universally confirmed by all regressions. Goodness-of-fit statistics suggested that the population potential score performs best, and that population density is the second best indicator of urbanicity. Numerical indicators are favored over classified ones. Regional planning typologies are not supported. The strength of suicide urban-rural associations varies with respect to the applied indicator of urbanicity. Future studies that put urban-rural inequalities central are recommended to apply either unclassified population potentials or population density indicators, but sensitivity analyses are advised.

X Demographics

X Demographics

The data shown below were collected from the profiles of 13 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 140 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 140 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 19 14%
Researcher 18 13%
Student > Ph. D. Student 18 13%
Student > Doctoral Student 10 7%
Student > Bachelor 9 6%
Other 20 14%
Unknown 46 33%
Readers by discipline Count As %
Social Sciences 29 21%
Medicine and Dentistry 17 12%
Psychology 16 11%
Economics, Econometrics and Finance 4 3%
Computer Science 3 2%
Other 19 14%
Unknown 52 37%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 10. 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 05 December 2022.
All research outputs
#3,244,893
of 23,275,636 outputs
Outputs from International Journal of Health Geographics
#115
of 634 outputs
Outputs of similar age
#62,831
of 329,386 outputs
Outputs of similar age from International Journal of Health Geographics
#3
of 13 outputs
Altmetric has tracked 23,275,636 research outputs across all sources so far. Compared to these this one has done well and is in the 86th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 634 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 9.5. This one has done well, scoring higher than 81% 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 329,386 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 80% 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 done well, scoring higher than 76% of its contemporaries.