An Interview With Miquel Porta, Editor Of The New 6th
Edition Of The Dictionary Of Epidemiology To Be Published June 2014
News of the
publication of the 6th edition of The Dictionary of
Epidemiology reached our offices this month. From the promotional
material for the book, we learned that the 6th edition
reflects multiple changes in the thinking about and practice of
epidemiology. The Dictionary has always been a window on the world
of epidemiology, so we took advantage of the new release to
interview Miquel Porta to get his views about some of the
latest trends.
EM:
You mention that a methodological "revolution" is ongoing and deeply
changing how we think about research and assess validity of findings
in epidemiology. Not everyone will know what you mean by this
statement. Can you expand on your statements a bit more for our
readers?
Porta:
In my view, a methodological “revolution” is ongoing. That is,
fundamental changes in theory, concepts and practice are taking
place. This renewal is deeply changing how we conceive
epidemiological and clinical research, and how we assess the
validity of findings.
I think a
good way to understand what is happening is to read, think, and
assess the changes in the definitions of terms as, for example,
collider, M-bias, causal diagram, backdoor (biasing path),
instrumental variable, negative controls, inverse probability
weighting, attributable fraction, bias, selection bias, confounding,
residual confounding, interaction, cumulative and density sampling,
Berkson’s bias, Simpson’s paradox, overadjustment, identifiability,
transportability, positivity, ignorability, collapsibility,
exchangeable, g-estimation, and marginal structural models.
Other
important changes are occuring on concepts such as risk, rate, risk
ratio, risk set, open population, test hypothesis, null hypothesis,
causal null, causal inference, generalizability, representativeness,
missing data, standardization, frequentist statistics, immortal time
bias, nonmonotonic, potential outcome, sample space, or false
discovery rate.
Of course,
a dictionary is not a textbook. But a new generation of textbooks is
emerging, and two good examples probably are:
--- Hernán
MA, Robins JM. Causal inference. New York: Chapman & Hall / CRC;
2015.
---
VanderWeele TJ. Explanation in causal inference: Methods for
mediation and interaction. New York: Oxford University Press; 2015.
Another
good way to assess what is changing is to follow the work of leaders
such as
James Robins,
Miguel Hernán, Sander Greenland, or Tyler
VanderWeele.
EM:
You also state that the revolution is having a very big impact on
research production and use. Can you give examples or say more about
these consequences?
Porta:
Pick up any issue of the main epidemiologic journals and you will
find several examples of what is going on. All these titles come
from just one such issue:
--- Causal models
and learning from data: integrating causal modeling and statistical
estimation.
--- Methodological
challenges in Mendelian randomization.
---
Obesity paradox:
conditioning on disease enhances biases in estimating the mortality
risks of obesity.
---
Meat intake and
reproductive parameters among young men.
---
Education and
cause-specific mortality: the mediating role of differential
exposure and vulnerability to behavioral risk factors.
---
Racial
residential segregation and preterm birth: built environment as a
mediator.
I suspect that the
ongoing changes are having a high impact on the production of
scientific evidence in the health sciences, but so far nobody has
quantified such an impact, as it is natural.
It is also
understandable that not everybody among the senior generations seems
to be aware of this. Exceptions abound, of course. They include
James Robins and Sander Greenland themselves, as well as
Jan Vandenbroucke and Allen Wilcox, for example.
One substantive
example may be that some “obesity paradoxes” are disappearing as
many “apparent paradoxes” had an explanation. In this case, it
seems, conditioning on a collider was introducing a selection bias.
If the scientific
evidence is changing, then so will the impact on policies, programs,
and services in which such evidence is used. And if this is so, many
institutions, organizations, companies, and millions of people will
be affected. Of course, such changes will need to be tested
empirically. Obviously, this is well beyond the task of the
dictionary.
EM:
Are you aware of other places in print where this revolution and its
impact have been described?
Porta:
No. Please see my response just above. And again, nobody would claim
that this is the role of the dictionary.
EM: Has the
scope of the dictionary been broadened?
Porta:
Not that much. A look at the previous edition (5th) will show that I
already expanded the scope then. And the dictionary always had terms
on related disciplines.
EM:
Did you have a main set of criteria for what should be included and
what should be excluded?
Porta:
The process was subtle, intellectual, and collegial. I don’t think
there could be such a set of criteria, or that it could be applied
in practice. This was more like painting or writing music, as usual
in science.
Porta:
I am confident we did not err, and certainly not in that direction.
If something, less rather than more. I am happy with the space and
price limits I had with this book --not imposed, never made explicit
by Oxford University Press, just my own criteria---. The dictionary
has never been an encyclopedia or a textbook.
We were able to
suggest connections among disciplines without being lengthy or
encyclopedic.
EM:
What have been the most difficult aspects of the work and what have
been the biggest rewards for you?
Porta:
I trust the process of revision of the past edition was wide open,
and that everybody who was capable and willing to take part had a
channel to do so through the specific website, the IEA, and the
editors. This was again a fantastic collegial effort, as always. ■
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