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Medical Forum / General / General / January 2004

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Health studies don't  prove cause and effect

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Duke of Hazard - 07 Jan 2004 16:43 GMT
As an engineer I do not understand why journals and the media publish
health studies that do not demonstrate cause and effect. The typical
study goes something like this:

Researchers found that those who:

------ exercised regularly
--or--
------ ate fruits and vegetables

throughout life were less likely to have contracted xyz disease than
those who did not.

One can not make such type of conclusions without first proving there
is a relationship between the variables. The conclusions are as absurd
as saying "people who eat chocolate are less likely to contract xyz
disease". While the statement may be true for the sample population ,
it does not establish there is any relationship between chocolate and
xyz disease.

So my question is why do respectable medical journals and the media
continue to publish these types of pseudo-science studies?
DP - 07 Jan 2004 17:16 GMT
agree completely!
many researchers and 'researchers' respectively in medicine, esp. in
epidemiology lack the ability for logical reasoning...
media? they live from that kind of garbage :-(
brdp
the researcher
> As an engineer I do not understand why journals and the media publish
> health studies that do not demonstrate cause and effect. The typical
[quoted text clipped - 18 lines]
> So my question is why do respectable medical journals and the media
> continue to publish these types of pseudo-science studies?
Mark London - 07 Jan 2004 17:17 GMT
It's not as simple as that.  They usually compare their findings with the
average population, or better yet, a 2nd group of people, which they also
monitor to compare to.  Plus, the bigger the number of people in the group,
the more likely the results are true.  Of course, some studies are designed
better than others, so repeatable of a study is necessary to confirm the
original study, and this is often done.  Sometimes it turns out that it's not
repeatable.  

Also, you have to read the actual article to determine just what was involved
in making the conclusion.  The summaries you see in the media don't reflect
the true design of the study, and the statistics involved in making the
conclusion.  The media often simplifies (and sometimes distort) the
conclusions.

In a previous article, faraz_hussain@yahoo.com (Duke of Hazard) wrote:
->As an engineer I do not understand why journals and the media publish
->health studies that do not demonstrate cause and effect. The typical
->study goes something like this:
->
->Researchers found that those who:
->
->------ exercised regularly
->--or--
->------ ate fruits and vegetables
->
->throughout life were less likely to have contracted xyz disease than
->those who did not.
->
->One can not make such type of conclusions without first proving there
->is a relationship between the variables. The conclusions are as absurd
->as saying "people who eat chocolate are less likely to contract xyz
->disease". While the statement may be true for the sample population ,
->it does not establish there is any relationship between chocolate and
->xyz disease.
->
->So my question is why do respectable medical journals and the media
->continue to publish these types of pseudo-science studies?
David Rind - 08 Jan 2004 01:47 GMT
> As an engineer I do not understand why journals and the media publish
> health studies that do not demonstrate cause and effect. The typical
[quoted text clipped - 18 lines]
> So my question is why do respectable medical journals and the media
> continue to publish these types of pseudo-science studies?

As an engineer, you probably encounter people who know nothing
about engineering and yet think that they have simple solutions
to problems you know are hard. Fields that have existed for a long
time typically have a lot of expertise that may or may not come
through in media reports. Yet making sneering comments about fields
you do not really understand seems to be a common pastime of
many groups.

Medical researchers know perfectly well that (as people in the
biz quote constantly) "association does not prove causation".
They do all sorts of clever things to try to adjust for this, some
of which are more believable than others. However, when dealing
with humans, you often cannot run experiments to answer questions.
How, exactly, would you suggest doing an experiment to figure
out whether exercising for twenty years reduces the risk of heart
disease?

Furthermore, you likely completely believe (and rightly so) some
things that have only been proven because of associations. No
one has ever done an experiment in humans that shows that smoking
causes lung cancer. Yet the evidence from observational studies
of the sort that you are suggesting are not worthy of publication
overwhelmingly demonstrates causation.

You picked an interesting example in particular though with exercise.
There are many reasons to worry that in particular with exercise
causation may run in the other direction. Healthier people are
able to exercise more, and so high levels of exercise may be a marker
for health rather than a cause of health. This is extremely hard
to tease out of observational studies.

Signature

David Rind
drind@caregroup.harvard.edu

Carey Gregory - 08 Jan 2004 03:17 GMT
>As an engineer I do not understand why journals and the media publish
>health studies that do not demonstrate cause and effect. The typical
>study goes something like this:
> *snip*

David Rind addressed your question much better than I could, but I have to
point out that what the media publishes is almost always hyped up,
misinterpreted, grandiose summaries of otherwise reasonable research.  Next
time you see medical research reported in the media, go read the actual
journal articles and I think you'll almost always find valid science with
appropriately restrained conclusions.
LawsonE - 11 Jan 2004 02:34 GMT
"Carey Gregory" <tiredofspam123@comcast.net> wrote in message

> Next
> time you see medical research reported in the media, go read the actual
> journal articles and I think you'll almost always find valid science with
> appropriately restrained conclusions.

Depends on the field and what is being reported: if a study supports the
status quo beliefs, methodology isn't as important a factor in publication
as when a study challenges the standard model.

In behavioral sciences, this problem is so prevelant that as much as 50% of
the studies reporting "no effect" lack sufficient statistical power to find
an effect if there is one (assuming a .5 standard deviation difference
between experimental and control groups).

Jacob Cohen's _Statistical Power in the Behavioral Sciences_ goes into this
in great detail.

My favorite place where this shows up is my own field of interest:
meditation research. The number of lousy, poorly controlled, tiny studies
that find "no difference" between relaxation and meditation, or between two
or more different forms of meditation, is astounding. It has become the
standard model in the field with an assumption that any study that finds
otherwise is somehow flawed or biased, even though it is absolutely trivial
to prove (in the logical/mathematical sense) that this standard model simply
cannot be supported by the research cited by the vast majority of scientists
to support their belief.
Steven O. - 08 Jan 2004 04:15 GMT
I haven't read any of these medical studies myself, and as others have
pointed out, media coverage is necessarily simplified and condensed.
That said, it does seem clear to me that it's worthwhile to pursue
studies which suggest associations.  

First, let's keep our logic straight:  Just because I do not have
proof of a cause and effect relationship between two events -- that
is, just because I don't have precise, detailed knowledge of the
molecular chain of events and energy transfers that may link cause A
to result B -- does not mean that causation does not exist.  

Second, association gives us ground to suspect that a causal relation
does exist, and so serves as a guideline to suggest further research.

Third, the reality is that biochemical systems are very complex.  Our
present state of science, for all its vast sophistication, is still
dwarfed by the complexity of living systems.  It may be that, at our
present point in history, the *possibility* of causality -- inferred
based on association -- may be the best level of knowledge we are able
to achieve.  I'd rather have partial, tentative, preliminary
indications of plausible truths, rather than having no guidelines at
all.

If anything, my gripe with medical science is the opposite.  Too,
often, medicine refuses to consider a possible causal chain unless
it's been validated by formal studies.  The result is that noteworthy
anecdotal evidence is often dismissed.  I've been having high blood
pressure problems.  My doctor put me on a medicine for it, and I
noticed my pulse shot way up.  I checked the Web, and found anecdotal
evidence (accounts from people in newsgroups) that this medicine
occasionally, if rarely, does cause rapid pulse.  But since the side
effect is apparently rare, it's not noted in the literature for the
drug.  Given that we each have a unique body chemistry, it should
certainly be considered that a drug might not show a side effect in a
controlled study of 1000 people, but might show a side effect when
used in a general population of 100,000 people.  (And of course,
occasionally approved drugs are withdrawn when dangerous side effects
are discovered in general use.)  

Anyway, the point is, sometimes knowledge is less than perfect, but
still constitutes useful knowledge all the same.

Steve O.

>As an engineer I do not understand why journals and the media publish
>health studies that do not demonstrate cause and effect. The typical
[quoted text clipped - 18 lines]
>So my question is why do respectable medical journals and the media
>continue to publish these types of pseudo-science studies?

Standard Antiflame Disclaimer:  Please don't flame me.  I may actually *be* an idiot, but even idiots have feelings.
Duke of Hazard - 08 Jan 2004 17:27 GMT
Let me compare back to engineering. Using the health study approach, I
could argue that bridges made of steel are less likely to break
compared to those made of wood. Why? Because historically and
statiscally steel bridges have a better track record than wooden
bridges.

However, any decent bridge engineer knows they can build a wooden
bridge that is 10X stronger than a steel bridge made of thin and
undersized beam sections! This is because they understand the
relationship between loads, forces, stresses, and material properties.
Detailed mathematics , physics and chemistry can explain what the
relationships are.

However, in medicine it seems the health studies really have not
identified the association between exercise and heart disease or
smoking and lung cancer (as poster David Rind pointed out). They seem
content with simply observing that some association may exist which is
just as primitive as saying "all bridges made of steel are less likely
to break than wooden bridges".

I realize that any theory has at its foundation statements which are
accepted as true without being proven.  You cannot build a theory
starting with nothing.It just seems that other sciences are able to
successfully dig a lot deeper into the foundations than medicine is
able to. What do you think? Or is Steve correct in that medicine just
knows too little?
JG - 08 Jan 2004 20:48 GMT
"Duke of Hazard" <faraz_hussain@yahoo.com> wrote...
> Let me compare back to engineering. Using the health study approach, I
> could argue that bridges made of steel are less likely to break
[quoted text clipped - 22 lines]
> able to. What do you think? Or is Steve correct in that medicine just
> knows too little?

Actually, the epidemiologic studies you criticize can and have identified
"associations."  As David implied, various methods have been developed to do
this.  As he also asked, don't you think that biomedical scientists have
been wrestling with this problem for many years?  If you read the statistics
section of such studies, you will see the types of multivariate analysis
usually employed.  The question then becomes whether there is a causal
connection.  Contrary to what you implied, we often do have plausible causal
connections from laboratory studies and/or deductions from known biochemical
or physiologic relationships.  What typically happens is that such analyses
find significant independent connections between A and B in a number of
studies, and laboratory experiments provide a plausible causal link.  It's a
debatable point when the evidence is good enough to accept the relationship,
but this is so for many things in many sciences.

JA Golczewski, Ph.D.
http://users.rcn.com/jigo/jg.HTM
Updates, free book on health and life-extension
Duke of Hazard - 09 Jan 2004 05:01 GMT
Yes, I see your point. I think it's best for me to read some of these
studies directly instead of relying on the media summary. Are they
available on the internet?
JG - 09 Jan 2004 13:55 GMT
> Yes, I see your point. I think it's best for me to read some of these
> studies directly instead of relying on the media summary. Are they
> available on the internet?

Abstracts of just about any study published are available on Medline (which
is publicly accessible and free):

http://www.ncbi.nlm.nih.gov/PubMed/

These do not contain all the details or the statistical analysis.  You can
order the full paper for a price through that site.  Full text of some
papers is available through links.

JA Golczewski, Ph.D.
http://users.rcn.com/jigo/jg.HTM
Updates, free book on health and life-extension
Carey Gregory - 09 Jan 2004 02:18 GMT
>I realize that any theory has at its foundation statements which are
>accepted as true without being proven.  You cannot build a theory
>starting with nothing.It just seems that other sciences are able to
>successfully dig a lot deeper into the foundations than medicine is
>able to. What do you think? Or is Steve correct in that medicine just
>knows too little?

Of course they're able to dig deeper and of course medicine knows too
little.  Isn't that patently obvious?  You can build models of inanimate
structures and subject them to laboratory testing to your heart's content.
You can't do that with living creatures, not even simple ones.  

The most complex structure ever envisioned by engineers is a triviality
compared to the simplest of living creatures.
LawsonE - 11 Jan 2004 02:47 GMT
> >I realize that any theory has at its foundation statements which are
> >accepted as true without being proven.  You cannot build a theory
[quoted text clipped - 10 lines]
> The most complex structure ever envisioned by engineers is a triviality
> compared to the simplest of living creatures.

Google "Science of Complexity" for more discussion of these issues.

A real-life example might highlight the issue: it is perfectly trivial to
build a simple broom balancing apparatus that uses a neural network or
genetic algorithm approach to drive the balancing mechanism. A bright high
schooler could easily design and build one these days using hobbyist
equipment and home-grown software. On the other hand, using a pre-ANN
approach would probably be nearly impossible for all but the most talented
engineers using rather sophisticated and expensive technology.

The point is, the high schooler's AI-based solution would be very difficult,
if not impossible, to describe completely using standard engineering
approaches, while a life sciences approach can describe it in terms of a
simplified model of learning and a software-based implementation of this
model.

And that's a exceedingly trivial example. Now try to model, using any
method, how a cell metabolizes a specific quantity of chemical, keeping in
mind that no static model will adequately encompass all aspects of the cell
that might impact what you are studying. Now model a system of interacting
cells (organ). Now model a system of interacting systems of interacting
cells (human being).
PF Riley - 10 Jan 2004 05:17 GMT
>Second, association gives us ground to suspect that a causal relation
>does exist, and so serves as a guideline to suggest further research.

This is a very important point. One idea behind doing retrospective
"correlation studies" is to see if it would be a waste of time or not
to do a prospective "causation" study.

PF
 
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