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The incomparability of cause of death statistics under “one country, two systems”: Shanghai versus Hong Kong

Overview of attention for article published in Population Health Metrics, September 2017
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • Among the highest-scoring outputs from this source (#31 of 389)
  • High Attention Score compared to outputs of the same age (91st percentile)
  • High Attention Score compared to outputs of the same age and source (87th percentile)

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3 news outlets
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5 X users

Citations

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8 Dimensions

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42 Mendeley
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Title
The incomparability of cause of death statistics under “one country, two systems”: Shanghai versus Hong Kong
Published in
Population Health Metrics, September 2017
DOI 10.1186/s12963-017-0155-z
Pubmed ID
Authors

Jiaying Zhao, Edward Jow-Ching Tu, Chi-kin Law

Abstract

Valid and comparable cause of death (COD) statistics are crucial for health policy analyses. Variations in COD assignment across geographical areas are well-documented while socio-institutional factors may affect the process of COD and underlying cause of death (UCD) determination. This study examines the comparability of UCD statistics in Hong Kong and Shanghai, having two political systems within one country, and assesses how socio-institutional factors influence UCD comparability. A mixed method was used. Quantitative analyses involved anonymized official mortality records. Mortality rates were analyzed by location of death. To analyze the odds ratio of being assigned to a particular UCD, logistic regressions were performed. Qualitative analyses involved literature reviews and semi-structural interviews with key stakeholders in death registration practices. Thematic analysis was used. Age-standardized death rates from certain immediate conditions (e.g., septicemia, pneumonia, and renal failure) were higher in Hong Kong. Variations in UCD determination may be attributed to preference of location of death, procedures of registering deaths outside hospital, perceptions on the causal chain of COD, implications of the selected UCD for doctors' professional performance, and governance and processes of data quality review. Variations in socio-institutional factors were related to the process of certifying and registering COD in Hong Kong and Shanghai. To improve regional data comparability, health authorities should develop standard procedures for registering deaths outside hospital, provide guidelines and regular training for doctors, develop a unified automated coding system, consolidate a standard procedure for data review and validity checks, and disseminate information concerning both UCD and multiple causes of death.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 42 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 42 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 8 19%
Researcher 5 12%
Student > Bachelor 4 10%
Student > Ph. D. Student 4 10%
Student > Doctoral Student 3 7%
Other 6 14%
Unknown 12 29%
Readers by discipline Count As %
Medicine and Dentistry 13 31%
Social Sciences 5 12%
Biochemistry, Genetics and Molecular Biology 3 7%
Nursing and Health Professions 2 5%
Psychology 2 5%
Other 4 10%
Unknown 13 31%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 27. 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 April 2022.
All research outputs
#1,258,959
of 23,571,271 outputs
Outputs from Population Health Metrics
#31
of 389 outputs
Outputs of similar age
#27,110
of 321,843 outputs
Outputs of similar age from Population Health Metrics
#1
of 8 outputs
Altmetric has tracked 23,571,271 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 94th percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 389 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 14.0. This one has done particularly well, scoring higher than 92% 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 321,843 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 91% of its contemporaries.
We're also able to compare this research output to 8 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