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What’s the difference? A gender perspective on understanding educational inequalities in all-cause and cause-specific mortality

Overview of attention for article published in BMC Public Health, September 2018
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • Good Attention Score compared to outputs of the same age (73rd percentile)
  • Average Attention Score compared to outputs of the same age and source

Mentioned by

twitter
10 tweeters

Citations

dimensions_citation
4 Dimensions

Readers on

mendeley
38 Mendeley
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Title
What’s the difference? A gender perspective on understanding educational inequalities in all-cause and cause-specific mortality
Published in
BMC Public Health, September 2018
DOI 10.1186/s12889-018-5940-5
Pubmed ID
Authors

Karen van Hedel, Frank J. van Lenthe, Joost Oude Groeniger, Johan P. Mackenbach

Abstract

Material and behavioural factors play an important role in explaining educational inequalities in mortality, but gender differences in these contributions have received little attention thus far. We examined the contribution of a range of possible mediators to relative educational inequalities in mortality for men and women separately. Baseline data (1991) of men and women aged 25 to 74 years participating in the prospective Dutch GLOBE study were linked to almost 23 years of mortality follow-up from Dutch registry data (6099 men and 6935 women). Cox proportional hazard models were used to calculate hazard ratios with 95% confidence intervals, and to investigate the contribution of material (financial difficulties, housing tenure, health insurance), employment-related (type of employment, occupational class of the breadwinner), behavioural (alcohol consumption, smoking, leisure and sports physical activity, body mass index) and family-related factors (marital status, living arrangement, number of children) to educational inequalities in all-cause and cause-specific mortality, i.e. mortality from cancer, cardiovascular disease, other diseases and external causes. Educational gradients in mortality were found for both men and women. All factors together explained 62% of educational inequalities in mortality for lowest educated men, and 71% for lowest educated women. Yet, type of employment contributed substantially more to the explanation of educational inequalities in all-cause mortality for men (29%) than for women (- 7%), whereas the breadwinner's occupational class contributed more for women (41%) than for men (7%). Material factors and employment-related factors contributed more to inequalities in mortality from cardiovascular disease for men than for women, but they explained more of the inequalities in cancer mortality for women than for men. Gender differences in the contribution of employment-related factors to the explanation of educational inequalities in all-cause mortality were found, but not of material, behavioural or family-related factors. A full understanding of educational inequalities in mortality benefits from a gender perspective, particularly when considering employment-related factors.

Twitter Demographics

The data shown below were collected from the profiles of 10 tweeters who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 38 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 38 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 10 26%
Researcher 7 18%
Student > Master 5 13%
Student > Doctoral Student 3 8%
Student > Bachelor 2 5%
Other 2 5%
Unknown 9 24%
Readers by discipline Count As %
Social Sciences 10 26%
Medicine and Dentistry 6 16%
Nursing and Health Professions 3 8%
Psychology 3 8%
Mathematics 1 3%
Other 1 3%
Unknown 14 37%

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 17 September 2018.
All research outputs
#2,406,824
of 13,807,706 outputs
Outputs from BMC Public Health
#2,770
of 9,528 outputs
Outputs of similar age
#69,606
of 267,953 outputs
Outputs of similar age from BMC Public Health
#7
of 13 outputs
Altmetric has tracked 13,807,706 research outputs across all sources so far. Compared to these this one has done well and is in the 82nd percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 9,528 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 11.2. This one has gotten more attention than average, scoring higher than 70% 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 267,953 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 73% 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 is in the 46th percentile – i.e., 46% of its contemporaries scored the same or lower than it.