Search results
Results from the WOW.Com Content Network
Researchers have applied Hill’s criteria for causality in examining the evidence in several areas of epidemiology, including connections between exposures to molds and infant pulmonary hemorrhage, [14] ultraviolet B radiation, vitamin D and cancer, [15] [16] vitamin D and pregnancy and neonatal outcomes, [17] alcohol and cardiovascular ...
Social factors in epidemiology were largely ignored until Doyal, Navarro, and others proposed the theories of SPD and Political Economy of Health in the 1970s, [4] and Krieger later integrated these theories into her writings on Ecosocial Theory (1994, 2011). As described by Doyal, SPD consists of the following key constructs: (1) The ...
In the field of epidemiology, the causal mechanisms responsible for diseases can be understood using the causal pie model.This conceptual model was introduced by Ken Rothman to communicate how constellations of component causes can lead to a sufficient cause to lead to a condition of interest and that reflection on these sets could improve epidemiological study design.
The term epidemiology is now widely applied to cover the description and causation of not only epidemic, infectious disease, but of disease in general, including related conditions. Some examples of topics examined through epidemiology include as high blood pressure, mental illness and obesity. Therefore, this epidemiology is based upon how the ...
Epidemiological (and other observational) studies typically highlight associations between exposures and outcomes, rather than causation. While some consider this a limitation of observational research, epidemiological models of causation (e.g. Bradford Hill criteria) [7] contend that an entire body of evidence is needed before determining if an association is truly causal. [8]
Robert Hermann Koch (11 December 1843 – 27 May 1910) was a German physician who developed Koch's postulates. [1]Koch's postulates (/ k ɒ x / KOKH) [2] are four criteria designed to establish a causal relationship between a microbe and a disease.
Causal analysis is the field of experimental design and statistics pertaining to establishing cause and effect. [1] Typically it involves establishing four elements: correlation, sequence in time (that is, causes must occur before their proposed effect), a plausible physical or information-theoretical mechanism for an observed effect to follow from a possible cause, and eliminating the ...
Biological plausibility is an essential element of the intellectual background of epidemiology. The term originated in the seminal work of determining the causality of smoking-related disease ( The Surgeon General's Advisory Committee on Smoking and Health [1964]).