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end of the alcohol-consumption continuum, and as well either improving or impairing
health at the high end of the alcohol-consumption continuum. Scientific method does not
require us to know for certain what and how many confounding variables may appear to
destroy the validity of an experiment which is not double-blind; rather, scientific
method assures us that it is so likely that one or more confounding variables will make
their appearance in a non-double-blind experiment, that such an experiment must be
considered to be fatally defective, and that no cause-effect conclusion can ever be
drawn from it with confidence.
Thus, no valid experiment exists. In short, we can be sure that no experiment has ever
been conducted to ascertain the effect of long-term alcohol consumption on longevity,
and that if such an experiment had ever been conducted, the impossibility of its being
double-blind, or even blind, would render it inconclusive.
The French Paradox Research
Must Have Been Correlational
But if the data featured in your 60 Minutes broadcast was not experimental, then what
was it? It must, by default, have been correlational. That is, rather than subjects
being assigned randomly to groups and being required to drink a given volume of alcohol
each day, it must have been merely observed what volume of alcohol they chose to drink
each day.
Alcohol consumption would be measured by self-report. Well, it is not quite true that
the experimenter would observe what volume of alcohol his subjects drank daily. It
would be impractical to follow subjects around and actually see how much alcohol they
consumed in restaurants, in bars, in their homes. Much more likely is that every once
in a long while, the subjects would be mailed a questionnaire asking them to report how
much alcohol they had been drinking lately. The inability to measure alcohol
consumption directly is already a weakness - subjects might not remember accurately how
much they had been drinking, or they might experience some pressure to distort how much
they had been drinking either upward or downward. However, this is not at all the big
weakness that I want to bring out, so let us get to that without further delay.
We have already seen that random assignment guarantees pre-treatment equality on all
dimensions. I first recapitulate that in the case of the random assignment of subjects
to groups in an experiment, we were guaranteed that the subjects in each group would be
initially equivalent on every conceivable dimension. The larger the random groups, the
closer to being precisely equal on every conceivable dimension would they become. Thus,
in a properly designed and executed double-blind experiment, any differences that
subsequently arose between groups would have to be attributed to the different
treatments that the experiment had administered to them - for example, if some groups
lived longer than others, nothing else would be able to explain this except that some
groups had consumed a different volume of wine than others.
Natural assignment guarantees pre-treatment inequality on many dimensions. But in a
correlational study, subjects are not assigned to groups randomly, they assign
themselves to groups naturally. A subject who is in a no-wine group, for example, is
one who has himself decided that he does not drink wine. Thus, the groups are referred
to not as randomly constituted, but as naturally constituted, as if nature had come
along and assigned each subject to one of the groups. Now here comes the really
important part. It is that experience teaches us that naturally-constituted groups are
capable of differing from each other on every conceivable dimension, and are highly
likely to differ from each other substantially on a number of dimensions. In other
words, people who drink no wine are likely to differ from people who drink several
glasses of wine in many ways. Perhaps the non-drinkers will have more females, and the
drinkers will have more males - or perhaps the opposite. Perhaps the drinkers will be
older or younger. Perhaps the drinkers will be richer or poorer. Perhaps the drinkers
will tend to be single and the teetotallers tend to be married, or vice versa.
Differences may readily be discovered in height, in weight, in education. Differences
could quite plausibly be discovered in smoking, in drug use, in exposure to industrial
pollutants, in diet. People who drink will tend to live in different parts of the city
from people who don't drink. People who drink may watch more television, use microwave
ovens more, spend more time breathing automobile exhaust - or less. As people of
different ethnic backgrounds, or religions, or races drink different amounts, it follows
that people who drink different amounts will differ in ethnic background, in religion,
and in race.
One can speculate about thousands of ways in which drinkers could differ from
teetotallers, and if one actually examined two such groups, one would find a few
dimensions on which such extraneous differences were large, several dimensions on which
such extraneous differences were moderate, and a large number of dimensions on which
such extraneous differences were present but small. The hurdle that the correlational
researcher is never able to overleap is that given that he is unable to look for every
conceivable difference, he will never know all the ways in which his
naturally-constituted groups did indeed differ from each other.
Natural groups may eat different amounts of broccoli. And so then, no cause-effect
conclusion will ever be possible from a correlational study. If the moderate drinkers
happen to live longer, we will never be able to conclude that this is caused by their
moderate drinking, because it might be caused by how close they live to high-voltage
lines or how often they wash their hands or how far they drive to work or how much
toothpaste they swallow or how much they salt their food or how close they sit to their
televisions or how many pets they keep or whether they sleep with their windows open or
whether they finish their broccoli. In an experiment, random assignment of subjects to
groups guarantees equality on all such extraneous dimensions, and this makes
cause-effect conclusions possible. In a correlational study, natural assignment of
subjects to groups guarantees inequality on many such extraneous dimensions, and this
makes cause-effect conclusions impossible.
Correlation does not imply causality. Every textbook on statistics or research
methodology underlines this same caveat, captured in the expression "correlation does
not imply causality," which warns that from correlational data, it is impossible to tell
what caused what. Science has developed only a single method for determining what
caused what - and that method is the experiment. No experiment, no cause effect
conclusion - it's that simple. Given correlational data, furthermore, there is no way
of extracting cause-effect conclusions by more subtle or more advanced analyses - no way
of equating the groups statistically, no way of matching subjects to achieve
statistically the pre-treatment equality that is needed to arrive at cause-effect
conclusions. Advanced methods of analyzing correlational data do exist, and are used by
naive researchers, and to the layman may appear to be effective, but the reality is that
all are fatally flawed, all have been demonstrated in the literature to be ineffective
and to lead to inconclusive results. The bottom line is that there is no way to extract
cause-effect conclusions from correlational data.
You overlooked that the causal direction might be reversed. In the case of The French
Paradox finding, I can readily see a plausible alternative interpretation as to how the
observed data could have arisen. The data do seem to show that as drinking declines
from a high to a moderate level, longevity increases. This accords with the notion that
alcohol is toxic, and that its effects are deleterious. What constitutes The French
Paradox, however, is that when one goes even farther along the drinking continuum from
moderate drinking all the way down to no drinking at all, instead of longevity
increasing still higher, the opposite happens - longevity shrinks.
What distinguishes the scientifically-trained mind from that of the layman in this case
is that the layman thinks of a single interpretation, and seizing on that as the only
one possible, stops thinking. That is, the layman thinks "Drinking not at all is
unhealthy, therefore I can improve my health by drinking." The scientifically-trained
mind, in contrast, recognizes that in correlational data a large number of
interpretations is possible, acknowledges the first interpretation that springs to mind
as one among the many that are possible, and keeps looking, and keeps finding, a number
of alternative interpretations, and ultimately acknowledges the impossibility of
choosing among them.
As illustrated in my own case. Specifically, I happen to find myself in a
naturally-constituted zero-alcohol group. That is, I drink not at all, or very close to
not at all. There is a reason for this, and that is that the effects of alcohol upon me
are toxic. Mainly, I get splitting headaches, even from the ingestion of small amounts
of alcohol, particularly if the alcohol comes in the form of wine. I take this to mean
that my constitution is weak, that I am unable to process alcohol efficiently, that I am
unable to detoxify my body of alcohol the way that others can, that my body chemistry is
not up to par. In other words, I am unwell, and as a result I do not drink.
Please mark well what I have just done - I have reversed the cause-effect conclusion
that you had come to. You concluded that not drinking causes deteriorated health, but
what I am proposing to you at the moment is that deteriorated health can cause not
drinking. The insight that I offer you is that when we observe a correlation, we don't
know what caused what, and one of the possibilities to be considered is that the causal
direction may be the opposite of our first impression, that a situation in which we
first conjectured that A causes B may prove upon more thoughtful examination to be a
situation in which B really causes A. In short, it may be the case that people who are
destined not to live as long as others tend to find themselves unable to drink alcohol.
That's all that the French Paradox may have discovered, and that's not a very good
reason for anybody to follow your recommendation to go out and start drinking.
Common sense alone invalidates The French Paradox conclusion. In other contexts, a
correlation being misinterpreted to mean that drinking promotes either health or
longevity will be obviously laughable. For example, a researcher who observes that
hospitalized patients don't drink will not conclude that teetotalling causes
hospitalization. Or, a researcher who visits death row and discovers that the inmates
don't drink and do have short life expectancies will not conclude that teetotalling
shortens life. In such examples, anyone with a modicum of common sense instantly
recognizes that a correlation between zero wine intake and either poor health or short
life does not mean that zero wine intake causes either poor health or short life. All
that is required to recognize the invalidity of your conclusion in The French Paradox is
to apply this same common sense to an only slightly more subtle case.
Are there not other studies? Undoubtedly there exist in the literature a large number of
studies that have some less direct bearing on the question that we are discussing, and
many of these studies will be genuine experiments which do permit cause effect
conclusions. I am thinking in particular of experiments that may demonstrate that
ingredients found either in grapes or in wine have a certain physiological effect. With
respect to such other studies, I make the following observations: (1) Your chief
conclusion was based not on such experiments, but on one or more correlational studies.
(2) An experiment in which subjects ingest an ingredient of grapes or of wine may
witness a certain effect, even while actually eating grapes or drinking wine produce a
different or an opposite effect. This could happen because in whole grapes or in real
wine, the ingredient with the beneficial effect could be offset by some other ingredient
which has a harmful effect, as by pesticides or nitrates that might be found in wine, or by the alcohol itself in wine. Unless an experiment actually has subjects drinking
wine, no conclusions concerning drinking wine are possible. (3) An experiment
demonstrating a physiological effect of something ingested is likely to be of short
duration, and is not likely to measure the effect on longevity. However, demonstrating
a physiological effect that appears to be beneficial (say a heightened level of HDL, as
mentioned by Kim Marcus above) is not the same as demonstrating increased longevity,
since the relation between the observed effect and longevity is speculative.
In short, the only research that can prove that prolonged drinking of three to five
glasses of wine per day can extend life is the non-feasible experiment that we have
already discussed above in which subjects are required to drink different amounts of
wine over an extended period of time, and the effects on longevity noted.
The Harm That You May Have Done.
What the above reasoning leads us to, then, is that you were without justification for
promoting the conclusion that you did - that drinking three to five glasses of wine each
day extends life. Quite possibly, your conclusion had the effect of increasing the
consumption of alcoholic beverages, particularly wine, and possibly, the effects of this
increased consumption have been uniformly bad.
These may be among the damaging effects of your advice. The level of alcohol
consumption that you advocate slows reaction times and interferes with coordination and
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