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Socio-economic development and emotion-health connection revisited: a multilevel modeling analysis using data from 162 counties in China

Overview of attention for article published in BMC Public Health, March 2016
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Title
Socio-economic development and emotion-health connection revisited: a multilevel modeling analysis using data from 162 counties in China
Published in
BMC Public Health, March 2016
DOI 10.1186/s12889-016-2926-z
Pubmed ID
Authors

Zonghuo Yu, Fei Wang

Abstract

Substantial research has shown that emotions play a critical role in physical health. However, most of these studies were conducted in industrialized countries, and it is still an open question whether the emotion-health connection is a "first-world problem". In the current study, we examined socio-economic development's influence on emotion-health connection by performing multilevel-modeling analysis in a dataset of 33,600 individuals from 162 counties in China. Results showed that both positive emotions and negative emotions predicted level of physical health and regional Gross Domestic Product Per Capita (GDPPC) had some impact on the association between emotion and health through accessibility of medical resources and educational status. But these impacts were suppressed, and the total effects of GDPPC on emotion-health connections were not significant. These results support the universality of emotion-health connection across levels of GDPPC and provide new insight into how socio-economic development might affect these connections.

X Demographics

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The data shown below were collected from the profiles of 2 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 17 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 17 100%

Demographic breakdown

Readers by professional status Count As %
Student > Doctoral Student 3 18%
Student > Ph. D. Student 3 18%
Student > Master 2 12%
Professor 2 12%
Student > Bachelor 1 6%
Other 2 12%
Unknown 4 24%
Readers by discipline Count As %
Psychology 6 35%
Social Sciences 4 24%
Business, Management and Accounting 2 12%
Arts and Humanities 1 6%
Unknown 4 24%
Attention Score in Context

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 21 January 2019.
All research outputs
#15,364,458
of 22,856,968 outputs
Outputs from BMC Public Health
#11,368
of 14,888 outputs
Outputs of similar age
#178,915
of 300,258 outputs
Outputs of similar age from BMC Public Health
#171
of 219 outputs
Altmetric has tracked 22,856,968 research outputs across all sources so far. This one is in the 22nd percentile – i.e., 22% of other outputs scored the same or lower than it.
So far Altmetric has tracked 14,888 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 13.9. This one is in the 16th percentile – i.e., 16% 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 300,258 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 31st percentile – i.e., 31% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 219 others from the same source and published within six weeks on either side of this one. This one is in the 15th percentile – i.e., 15% of its contemporaries scored the same or lower than it.