Cause and effect: the epidemiological approach Raj Bhopal, Bruce and John Usher Professor of Public Health, Public Health Sciences Section, Division of Community Health Sciences, University of Edinburgh, Edinburgh EH89AG Raj.Bhopal@ed.ac.uk
On completion of your studies you should understand:
The purpose of studying cause and effect in epidemiology is to generate knowledge to prevent and control disease.
That cause and effect understanding is difficult to achieve in epidemiology because of the long natural history of diseases and because of ethical restraints on human experimentation.
How causal thinking in epidemiology fits in with other domains of knowledge, both scientific and non-scientific.
The potential contributions of various study designs for making contributions to causal knowledge.
Cause and effect
Cause and effect understanding is the highest form of achievement of scientific knowledge.
Causal knowledge permits rational plans and actions to break the links between the factors causing disease, and disease itself.
Causal knowledge can help predict the outcome of an intervention and help treat disease.
Quote Hippocrates "To know the causes of a disease and to understand the use of the various methods by which the disease may be prevented amounts to the same thing as being able to cure the disease".
Epidemiological contributions to cause and effect
A philosophy of health and disease.
Models which illustrate that philosophy.
Frameworks for interpreting and applying the evidence.
Study designs to produce evidence.
Evidence for cause and effect in the relationships of numerous factors and diseases.
Development of the reasoning of other disciplines including philosophy and microbiology, in reaching judgement.
The first and difficult question is, what is a cause?
A cause is something which has an effect.
In epidemiology a cause can be considered to be something that alters the frequency of disease, health status or associated factors in a population.
Philosophers have grappled with the nature of causality for thousands of years.
David Hume's philosophy has been influential.
A cause cannot be deduced logically from the fact that two events are linked.
Because thunder follows lightning does not mean thunder is caused by lightning. Observing this one million times does not make it true.
The axiom “Association does not mean causation”.
Cause and effect deductions need more than observation alone - they need understanding.
The contribution of another philosopher, John Stuart Mill, captured in his canons, is so similar to the modern empirically based ideas of epidemiology.
Epidemiological strategy and reasoning: the example of Semelweis
Diseases form patterns, which are ever changing.
Clues to the causes of disease are inherent within these pattern.
Semelweis (1818-1865) observed that the mortality from childbed fever (now known as puerperal fever) was lower in women attending clinic 2 run by midwives than it was in those attending clinic 1 run by doctors.
Do these observations spark off any ideas of causation in your mind?
Births, deaths, and mortality rates (%) for all patients at the two clinics 1841-1846
In 1847, his colleague and friend Professor Kolletschka died following a fingerprick with a knife used to conduct an autopsy.
Kolletschka’s autopsy showed inflammation to be widespread, with peritonitis, and meningitis.
“Day and night I was haunted by the image of Kolletschka’s disease and was forced to recognise, ever more decisively that the disease from which Kolletschka died was identical to that from which so many maternity patients died.”
Semelweis' inspired idea was that particles had been transferred from the scalpel to the vascular system of his friend and that the same particles were killing maternity patients.
If so, something stronger than ordinary soap was needed for handwashing
He introduced chlorina liquida, and then for reasons of economy, chlorinated lime.
The maternal mortality rate plummeted.
Semelweis’s discovery was resented in Vienna.
Lessons from Semmelweis’s work
Deep knowledge derives from the explanation of disease patterns, rather than in their description.
Inspiration is needed, and may come from unexpected sources, as here from Kolletschka’s autopsy.
Action cannot always await understanding the mechanism.
Epidemiological data to show that laying an infant on its front (prone position) to sleep raises the risk of 'cot death' or sudden infant death syndrome.
A campaign to persuade parents to lay their infants on their backs has halved the incidence of cot death.
Epidemiological principles and models of cause and effect
Most important of the cause and effect ideas underpinned by epidemiology is that disease is virtually always a result of the interplay of the environment, the genetic and physical makeup of the individual, and the agent of disease.
Diseases attributed to single causes are invariably so by definition.
The fact that “tuberculosis” is “caused” by the tubercle bacillus is a matter of definition.
The causes of tuberculosis, from an epidemiological or public-health perspective, are many, including malnutrition and overcrowding.
This idea is captured by several well known disease causation models, such as the line, triangle, the wheel, and the web.