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Economic development and road traffic fatalities in Russia: analysis of federal regions 2004–2011

Overview of attention for article published in Injury Epidemiology, August 2015
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  • In the top 25% of all research outputs scored by Altmetric
  • Good Attention Score compared to outputs of the same age (77th percentile)
  • Good Attention Score compared to outputs of the same age and source (66th percentile)

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32 Mendeley
Title
Economic development and road traffic fatalities in Russia: analysis of federal regions 2004–2011
Published in
Injury Epidemiology, August 2015
DOI 10.1186/s40621-015-0051-6
Pubmed ID
Authors

Huan He, Nino Paichadze, Adnan A. Hyder, David Bishai

Abstract

The relationship between economic development and road safety at sub-national level has not been well established. This study aims to assess the relationships between economic growth (measured by gross regional product (GRP)) and road traffic fatalities (RTFs) and crash fatality ratio (CFR) at sub-national level in Russia. We used published secondary data on annual RTFs and CFR obtained from the traffic police and socioeconomic development indicators from the statistics department for each Russian federal region (referred to in Russia as "subject") for 2004-2011. We used multivariate fixed effects models for longitudinal data to examine the GRP-RTF and the GRP-CFR relationships excluding regions with extreme values. Time (in years) and a set of relevant socioeconomic variables (territory, population, number of privately owned cars, number of public buses, length of public motor roads, number of physicians, and budget expenditure on health care and physical wellness) were also included as covariates in the models. The RTF rates decreased monotonically over time as GRP per capita increased in 66 studied regions during 2004-2011. This relationship was mainly explained by the number of privately owned cars and partially explained by year dummy variables, number of buses, and number of physicians. CFR also decreased monotonically as GRP per capita increased in 67 studied regions. This relationship between economic growth and CFR was fully explained by secular time trends. The year dummy effects on CFR were not mediated by other socioeconomic variables included in the study. For the period of 2004-2011 in Russia, the reduction in RTFs is mostly explained by increasing the number of private cars, while the reduction of CFR is mostly associated with year-effects suggesting a process of diffusion of knowledge, which is not solely dominated by economic growth.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 32 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 32 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 7 22%
Researcher 5 16%
Student > Bachelor 4 13%
Other 3 9%
Professor 2 6%
Other 5 16%
Unknown 6 19%
Readers by discipline Count As %
Medicine and Dentistry 5 16%
Engineering 4 13%
Economics, Econometrics and Finance 4 13%
Computer Science 3 9%
Social Sciences 3 9%
Other 5 16%
Unknown 8 25%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 7. 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 19 April 2017.
All research outputs
#4,643,422
of 22,826,360 outputs
Outputs from Injury Epidemiology
#152
of 320 outputs
Outputs of similar age
#59,910
of 267,486 outputs
Outputs of similar age from Injury Epidemiology
#2
of 6 outputs
Altmetric has tracked 22,826,360 research outputs across all sources so far. Compared to these this one has done well and is in the 79th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 320 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 43.6. This one has gotten more attention than average, scoring higher than 52% 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 267,486 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 77% of its contemporaries.
We're also able to compare this research output to 6 others from the same source and published within six weeks on either side of this one. This one has scored higher than 4 of them.