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Applying the Bradford Hill criteria in the 21st century: how data integration has changed causal inference in molecular epidemiology

Overview of attention for article published in Emerging Themes in Epidemiology, September 2015
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About this Attention Score

  • In the top 5% of all research outputs scored by Altmetric
  • One of the highest-scoring outputs from this source (#1 of 155)
  • High Attention Score compared to outputs of the same age (99th percentile)

Mentioned by

news
58 news outlets
blogs
4 blogs
policy
2 policy sources
twitter
111 X users
wikipedia
2 Wikipedia pages
video
4 YouTube creators

Citations

dimensions_citation
460 Dimensions

Readers on

mendeley
1276 Mendeley
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Title
Applying the Bradford Hill criteria in the 21st century: how data integration has changed causal inference in molecular epidemiology
Published in
Emerging Themes in Epidemiology, September 2015
DOI 10.1186/s12982-015-0037-4
Pubmed ID
Authors

Kristen M. Fedak, Autumn Bernal, Zachary A. Capshaw, Sherilyn Gross

Abstract

In 1965, Sir Austin Bradford Hill published nine "viewpoints" to help determine if observed epidemiologic associations are causal. Since then, the "Bradford Hill Criteria" have become the most frequently cited framework for causal inference in epidemiologic studies. However, when Hill published his causal guidelines-just 12 years after the double-helix model for DNA was first suggested and 25 years before the Human Genome Project began-disease causation was understood on a more elementary level than it is today. Advancements in genetics, molecular biology, toxicology, exposure science, and statistics have increased our analytical capabilities for exploring potential cause-and-effect relationships, and have resulted in a greater understanding of the complexity behind human disease onset and progression. These additional tools for causal inference necessitate a re-evaluation of how each Bradford Hill criterion should be interpreted when considering a variety of data types beyond classic epidemiology studies. Herein, we explore the implications of data integration on the interpretation and application of the criteria. Using examples of recently discovered exposure-response associations in human disease, we discuss novel ways by which researchers can apply and interpret the Bradford Hill criteria when considering data gathered using modern molecular techniques, such as epigenetics, biomarkers, mechanistic toxicology, and genotoxicology.

X Demographics

X Demographics

The data shown below were collected from the profiles of 111 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 1,276 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United Kingdom 2 <1%
United States 2 <1%
Mexico 1 <1%
Korea, Republic of 1 <1%
Unknown 1270 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 213 17%
Student > Bachelor 163 13%
Researcher 119 9%
Student > Ph. D. Student 111 9%
Student > Postgraduate 64 5%
Other 218 17%
Unknown 388 30%
Readers by discipline Count As %
Medicine and Dentistry 356 28%
Nursing and Health Professions 129 10%
Biochemistry, Genetics and Molecular Biology 63 5%
Agricultural and Biological Sciences 42 3%
Pharmacology, Toxicology and Pharmaceutical Science 39 3%
Other 208 16%
Unknown 439 34%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 554. 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 May 2024.
All research outputs
#44,863
of 25,939,391 outputs
Outputs from Emerging Themes in Epidemiology
#1
of 155 outputs
Outputs of similar age
#435
of 287,395 outputs
Outputs of similar age from Emerging Themes in Epidemiology
#1
of 4 outputs
Altmetric has tracked 25,939,391 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 99th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 155 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 18.0. This one has done particularly well, scoring higher than 99% 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 287,395 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 99% 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