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Suicide rates in China, 2004–2014: comparing data from two sample-based mortality surveillance systems

Overview of attention for article published in BMC Public Health, February 2018
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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)

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1 blog
twitter
2 tweeters
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1 video uploader

Citations

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18 Dimensions

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50 Mendeley
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Title
Suicide rates in China, 2004–2014: comparing data from two sample-based mortality surveillance systems
Published in
BMC Public Health, February 2018
DOI 10.1186/s12889-018-5161-y
Pubmed ID
Authors

Feng Sha, Qingsong Chang, Yik Wa Law, Qi Hong, Paul S. F. Yip

Abstract

The decreasing suicide rate in China has been regarded as a major contributor to the decline of global suicide rate in the past decade. However, previous estimations on China's suicide rates might not be accurate, since often they were based on the data from the Ministry of Health's Vital Registration ("MOH-VR") System, which is biased towards the better-off population. This study aims to compare suicide data extracted from the MOH-VR System with a more representative mortality surveillance system, namely the Center for Disease Control and Prevention's Disease Surveillance Points ("CDC-DSP") System, and update China's national and subnational suicide rates in the period of 2004-2014. The CDC-DSP data are obtained from the National Cause-of-Death Surveillance Dataset (2004-2014) and the MOH-VR data are from the Chinese Health Statistics Yearbooks (2005-2012) and the China Health and Family Planning Statistics Yearbooks (2013-2015). First, a negative binomial regression model was used to test the associations between the source of data (CDC-DSP/MOH-VR) and suicide rates in 2004-2014. Joinpoint regression analyses and Kitagawa's decomposition method are then applied to analyze the trends of the crude suicide rates. Both systems indicated China's suicide rates decreased over the study period. However, before the two systems merged in 2013, the CDC-DSP System reported significantly higher national suicide rates (IRR = 1.18, 95% Confidence Interval [CI]: 1.13-1.24) and rural suicide rates (IRR = 1.29, 95% CI: 1.21-1.38) than the MOH-VR System. The CDC-DSP System also showed significant reversing points in 2011 (95% CI: 2006-2012) and 2006 (95% CI: 2006-2008) on the rural and urban suicide trends. Moreover, the suicide rates in the east and central urban regions were reversed in 2011 and 2008. The biased MOH-VR System underestimated China's national and rural suicide rates. Although not widely appreciated in the field of suicide research, the CDC-DSP System provides more accurate estimations on China's suicide rates and is recommended for future studies to monitor the reversing trends of suicide rates in China's more developed areas.

Twitter Demographics

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Mendeley readers

The data shown below were compiled from readership statistics for 50 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 50 100%

Demographic breakdown

Readers by professional status Count As %
Student > Bachelor 11 22%
Unspecified 7 14%
Researcher 6 12%
Student > Master 4 8%
Student > Doctoral Student 2 4%
Other 7 14%
Unknown 13 26%
Readers by discipline Count As %
Medicine and Dentistry 10 20%
Social Sciences 8 16%
Unspecified 7 14%
Psychology 4 8%
Nursing and Health Professions 3 6%
Other 4 8%
Unknown 14 28%

Attention Score in Context

This research output has an Altmetric Attention Score of 9. 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 03 January 2020.
All research outputs
#2,527,260
of 16,725,085 outputs
Outputs from BMC Public Health
#2,776
of 11,431 outputs
Outputs of similar age
#71,846
of 375,132 outputs
Outputs of similar age from BMC Public Health
#1
of 4 outputs
Altmetric has tracked 16,725,085 research outputs across all sources so far. Compared to these this one has done well and is in the 84th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 11,431 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 12.3. This one has done well, scoring higher than 75% 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 375,132 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 4 others from the same source and published within six weeks on either side of this one. This one has scored higher than all of them