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
Geographical breakdown
Country | Count | As % |
---|---|---|
United States | 20 | 18% |
United Kingdom | 8 | 7% |
Canada | 7 | 6% |
Australia | 4 | 4% |
Spain | 2 | 2% |
Colombia | 1 | <1% |
Denmark | 1 | <1% |
Serbia | 1 | <1% |
Netherlands | 1 | <1% |
Other | 9 | 8% |
Unknown | 57 | 51% |
Demographic breakdown
Type | Count | As % |
---|---|---|
Members of the public | 84 | 76% |
Scientists | 15 | 14% |
Practitioners (doctors, other healthcare professionals) | 10 | 9% |
Science communicators (journalists, bloggers, editors) | 2 | 2% |
Mendeley readers
Geographical breakdown
Country | Count | As % |
---|---|---|
United Kingdom | 2 | <1% |
United States | 2 | <1% |
Mexico | 1 | <1% |
Korea, Republic of | 1 | <1% |
Unknown | 1256 | 100% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Student > Master | 213 | 17% |
Student > Bachelor | 163 | 13% |
Researcher | 118 | 9% |
Student > Ph. D. Student | 111 | 9% |
Student > Postgraduate | 64 | 5% |
Other | 218 | 17% |
Unknown | 375 | 30% |
Readers by discipline | Count | As % |
---|---|---|
Medicine and Dentistry | 353 | 28% |
Nursing and Health Professions | 130 | 10% |
Biochemistry, Genetics and Molecular Biology | 63 | 5% |
Agricultural and Biological Sciences | 43 | 3% |
Pharmacology, Toxicology and Pharmaceutical Science | 39 | 3% |
Other | 207 | 16% |
Unknown | 427 | 34% |