From my own perspective as a scientist in biology, there are three very obvious reasons why media reports about human health might contradict each other. This has everything to do with medical experiments, which are supposed to be the basis for the claims both pro and con. I don’t necessarily condone the experiments themselves, but I can see why their outcome might be confusing.
First, biology is complex, which may sound trite, but it contains the essence of the problem. Not only is biology more complex than we imagine, it frequently turns out to be more complex than we can imagine. The current Covid-19 pandemic is a perfect case in point — the more we learn about the SARS-CoV2 virus, the more we realize just how complex is the human immune response to this virus.
Remember, biology is actually the study of why we are not dead. The natural state of the universe is for things to be not alive, and yet lots of things are actually alive, at least for a while. Being alive turns out to be much more complex than being dead — being inanimate does not require very much, really, but being animate has all sorts of complex chemical requirements.
For our purposes here, the important consequence of this complexity is that anything with positive effects on one part of our body is likely to have at least some negative effects on some other body part; and vice versa. Nothing is ever “all good” or “all bad” in biology, no matter how much optimism might encourage you towards a search for the former. So, it is rather easy to find circumstances where wine seems to have positive effects on health, and also just as easy to find the opposite. It would be naïve to expect anything else.
The second of our three reasons is that it is impractical to actually carry out the medical experiments required to study human health. For example, there is much discussion at the moment about the effectiveness of having the public wear medical-style face-masks during the current pandemic (eg. “masks might help you”). This is because, as far as I know, no-one has ever done an experiment to find out whether they do help in practice. It would not be easy! The same thing applies to understanding transmission of the virus from person to person (Scientists estimate the speed and distance of coronavirus transmission when people cough, sneeze, speak — and run).
The classic form of a scientific experiment is what we call a Manipulative Experiment (or Intervention Experiment). Here, we try to deliberately modify the world in some way, in order to test some hypothesis about how the world functions. This is often straightforward for inanimate objects, at least in theory, but it is almost impossible for animate objects.
For example, to study dietary health, we would need to take two groups of people, one lot healthy and the other lot unhealthy, and subject each group to both an apparently healthy diet and an unhealthy one. That is, we try to make some of the healthy people healthy, and make some of the others unhealthy; and we also try to make some of the unhealthy people healthy, and make some of the others unhealthy. That gives us four different experimental groups of people to study.
How are we going to get people to agree to do this? After all, we have to assign the people to the different treatments (making them healthy or unhealthy) at random — the people cannot choose which treatment they will get. You’d have to be a nutter to agree to be made unhealthy when you are currently healthy, even in the name of Science. So, the ideal medical experiment is called a Randomized Controlled Trial, and you don’t see too many of them when studying healthy vs. unhealthy lifestyles.
To take one straightforward example, let’s look at a particular experiment studying the hypothesized health benefits of a Mediterranean diet (with wine!):
Tarini Shankar Ghosh, and 30 others (2020) Mediterranean diet intervention alters the gut microbiome in older people reducing frailty and improving health status. Gut 69: 1218–1228.They describe their experiment this way:
We profiled the gut microbiota in 612 subjects across five European countries (UK, France, Netherlands, Italy and Poland) before and after the administration of a 12-month long Mediterranean Diet tailored to elderly subjects.This is all very well (people before and after changing to a Mediterranean diet), but where is the rest of the experiment? Where are the people who normally consume a Mediterranean experiment but changed to another diet? The Mediterranean diet is characterized by increased consumption of vegetables, legumes, fruits, nuts, olive oil and fish (and maybe a glass of wine!), along with low consumption of red meat, dairy products and saturated fats. Well, for a proper experiment, some fish-and-vegetable eaters should have started eating a meats-dairy-fats diet, and also been measured before and after their change. This gives us four groups of data in our experiment, not two, as shown in this figure.
Sadly, this failure is all too typical of medical experiments.
Finally, even if some people do agree to take part in an experiment, it is unethical to put people in experiments that can have risky outcomes. The medical scientists aren’t going to jail just to find out in which ways wine is good for you! Besides, the sort of person who volunteers to take risks is rarely a representative example of Homo sapiens.
So, most medical experiments are what we call Descriptive Experiments (or Observational Experiments). Here, we don’t try to manipulate people’s health, but instead study different groups through time, to see how things turn out under different natural circumstances. For example, groups of people might be studied who drink different amounts of wine in their daily lives, and we try to detect some health differences between the groups through time.
This can be very helpful way to learn things, but it is not necessarily a good substitute for a Manipulative Experiment. The main limitation is that we might end up with a biased sample of people, so that our results are skewed in some (unknown) way. That is, other factors can get in the way of studying the thing you want to be looking at — these are called confounding factors. For example, there is an obvious association between health and wealth — wealthy people can afford to look after themselves properly. Moreover, wealth is also associated with drinking — heavy drinkers and abstainers tend to be poorer than moderate drinkers. So, how do we extricate the effects of wealth on health compared to the effects of drinking? This question does not arise for Manipulative Studies, because we randomly assign people to the experimental groups.
The third of our three reasons for apparently contradictory medical results is that human health is a long-term issue, while experiments don’t usually get funded for all that long. Most experiments on humans end before there has been much effect on the participants’ health. Indeed, it can take decades to find out about health issues; and even the longevity of of the scientists themselves can cut short such experiments!
To make this point clear, let’s look at an actual example, where we can also comment on the first two points above, as well:
Katherine M. Keyes, and 6 others (2019) Alcohol consumption in later life and mortality in the United States: results from nine waves of the Health and Retirement Study. Alcoholism: Clinical & Experimental Research 43: 1734–1746.This is a Descriptive Experiment, since there is no actual medical intervention. A large group of Americans were simply followed through time, being evaluated every couple of years:
We report on 16 years of follow-up from the Health and Retirement Study (HRS) cohorts born 1931 to 1941 (N = 7,904, baseline mean age = 61, SD = 3.18). Respondents were queried about drinking frequency/quantity. Mortality was established via exit interviews and confirmed with the national death index.The idea was to see whether drinking habits have any effect on how long we live. In practice, we cannot do a Manipulative Experiment, because that would involve (among other things) getting some abstainers to take up alcohol, and getting some alcoholics to go cold turkey. It is much simpler to just let elderly people drink whatever they want, and then see how long they live. If we have a large enough group of people, and we continue to follow them for long enough, we will eventually get an answer to our experimental question.
The problem is that lots of factors in a person’s life affect how much they drink, and some of these also directly affect their health. There are also factors that affect health indirectly. Even worse, some of these factors vary throughout our lives, not necessarily remaining constant — as we get older we change our behavior, especially in response to illness. Therefore, these other factors can confound our experiment, which is aimed to study the effects of alcohol alone. This is the basic limitation of Descriptive Experiments (reason 2 above), especially when studying complex phenomena (Reason 1 above).
The authors explicitly try to address this issue:
Time-varying confounders included but were not limited to household assets, smoking, body mass index, health / functioning, depression, chronic disease; time-invariant confounders included baseline age, education, sex, and race.One of the interesting issues here is reverse causation. For example, people might reduce alcohol consumption due to illness, making it look like smaller amounts of alcohol cause you to die earlier.
The important aspect of the experimental design was to distinguishes moderate drinking from abuse drinking. The failure to do this is repeatedly discussed in wine blogs (eg. One more reason to be wary of alcohol health studies). One of the comments to that Wine Curmudgeon post notes; “temperance movements focus on the deleterious effects of excessive alcohol consumption and routinely fail to acknowledge the beneficial effects of moderate consumption.” An “all or none” approach to health management is ludicrous, biologically (but temperance arguments have never been biological, they are instead social).
So, the authors grouped the participants into these categories, based on drinking habits:
- Lifetime Abstainer — <12 drinks in their lifetime
- Current Abstainer — drank in the past but not during the experiment
- Occasional Drinker — drinking less than 1 day per week
- Moderate Drinker — 1-2 (women) or 1-3 (men) drinks 1 or more days per week
- Heavy Drinker — >3 drinks per day or >5 drinks in a single session for men, or 2 resp. 4 for women.
Note, first, that it took at least 3 years to find a detectable difference between the groups for men, and 5 years for women; and most of the people are still alive at the end of the measurement period, so that there is a long way to go in this experiment. That is the main take-away message here — any shorter experiment will be misleading.
However, we can also note that if we take the Lifetime Abstainers as our comparison for longevity, the Current Abstainers and Heavy Drinkers do worse (ie. tend to die sooner) while the Occasional Drinkers and Moderate Drinkers do better (ie. tend to live longer). The result for the Heavy Drinkers needs no explanation; but the authors note that the Current Abstainers were often people who had quit drinking due to illness, so that lack of alcohol was not directly associated with them dying sooner.
This experiment lead the authors to conclude that: “There are consistent associations between moderate / occasional drinking and lower mortality.” However, there was less of an effect for men versus women, and for smokers versus non-smokers (ie. smoking will eventually get you, whether you drink or not).
So, there you have it — three good reasons why reports of the outcome of medical experiments might contradict each other. Does moderate wine consumption improve your health? In some ways, apparently “yes”; but don’t overdo your drinking — after all, there is always this thing called “too much”.