Confusing Correlation with Causation (Alcohol Examples)

Confusing correlation with causation is natural. We all tend to fall into the trap.

The classic example is the correlation between high ice cream sales and drownings. And the sale of sunglasses. But ice cream sales don’t cause either drownings or the sale of sunglasses.

The cause of these things is clearly warm weather. It’s not caused by high ice cream sales!


I.   Alcohol Sales Outlets

II.  Alcohol Merchandise

III. Ads for Alcohol

IV.  Eating Together

V.   Resources

I. Alcohol Sales Outlets

The same way, people often note that drinking tends to be higher in some areas. That is, in those places with many alcohol sales outlets. They then call to reduce the density of such outlets. They say this would reduce drinking.

But to assume that alcohol outlets cause high  seems wrong. Don’t stores locate where sales are higher? 

A high concentration of grocery stores doesn’t cause people to eat more. Or to become obese. We can’t fight weight gain by reducing the number of grocery stores.

The economist Dr. Steven Levitt relates this folktale. The czar discovered that the most diseased province in the country had the highest concentration of doctors. To reduce the high disease rate the czar had all the doctors in that province killed.

Be sure to visit Spanking and Later Alcohol Abuse. It’s another great example of confusing correlation with causation!

Some would have us believe that the alcohol sales outlets are causing the drinking rate. They would have us follow the lead of the misguided folktale czar. It’s very good there would be no killings. Yet they would have us reduce the number of sales outlets. That’s just as illogical.

Reducing the number of alcohol sales outlets is a “feel good” approach doomed to failure.

II. Alcohol Merchandise 

Confusing correlation with causation“Alcohol Merchandise Encourages Underage Drinking.” That headline was carried by major news sources. It was widely printed article. It said the sale of alcohol-related merchandise to those under 21 was bad. Indeed, it was “a wake-up call” for the nation.

What did this study of a small sample of young people reveal? Simply that young people who drank were more likely to have shirts and other things with alcohol logos.

Of course, religious people are more likely to wear religious items. But wearing religious items doesn’t cause people to become religious. And wearing a shirt with a beer label doesn’t cause people to begin drinking alcohol.

Research also shows that “sensation-seeking” linked with wearing alcohol logos. It’s also related with drinking, having peers who drink and smoke. It may be linked to gambling, bungee jumping, and unprotected sex. The enduring trait of sensation-seeking is more likely to cause drinking than wearing a cap with a beer brand.

A headline of  “Sensation-Seeking Personality Encourages Underage Drinking” wouldn’t grab attention. But it would be much closer to the truth.

It’s another example of confusing correlation with causation.

 III. Alcohol Ads

Confusing correlation with causationResearchers have found that young people who remember seeing alcohol ads are more likely to drink. They then jump to the conclusion that seeing alcohol ads causes young people to drink. 

In making this leap of faith, they ignore evidence to the contrary. Here are two examples.

    • People who want to buy a new car tend to pay more attention to auto ads. People who want to buy a new house tend to pay more attention to real estate ads. And those who want to drink probably pay more attention to alcohol ads.
    • Expenditures for alcohol ads have little or no relationship to alcohol consumption.

Research on the latter has been done for decades. And by governments, health agencies, and colleges around the world. The result? There’s no good evidence that alcohol ads cause non-drinkers to begin drinking. Nor drinkers to consume more.

Then why do alcohol producers advertise? They do so to increase their market share. Both research and experience has shown that effective ads can increase a producer’s share of the market. It gains its share at the expense of others, who lose some of their share. 

But research consistently shows that ads do not increase overall alcohol consumption.

The authors of the attention-grabbing report need to go back and take Research 101.

IV. Eating Together

A nation-wide public service campaign urged parents to eat dinner with their children. This was to reduce youthful drug use. The advice was based on a report. The report supposedly showed that eating dinner as a family reduced risk of drug use. In short, it reduced it by half among young people. 

“There is no more important thing a parent can do” to reduce the chance that their children will use drugs. So insisted anti-drug leader Joe Califano. He said that it “is the key to ridding our nation of the scourge of substance abuse.” 

Eating together as a family probably has many benefits. But what of the claim that doing so reduces drug use risk by 50%?

     Study Did Not Show

The study did not show that eating together as a family caused lower drug use. What did it find? That those who ate with their parents scored 50% lower on a substance-abuse test. 

People should see red flags everywhere. Indeed, the report could well serve as a case study in how not to conduct research.

For starters, the samples of parents and young people is not at all representative of U.S. families. The researchers began with over 37,000 phone numbers. They dropped one-third because of language barriers, no one answered the phone, and other reasons. Of the remaining phone numbers, 9,000 were people who refused to answer questions. And about 1,000 “were cut off.“ 

The company that did the survey admitted that it had “a very low response rate.” Yet nothing was done to address this serious problem. 

The report concluded that frequently eating together as a family reduced drug risk by 50%. But it failed to consider the effects of age. Seventeen-year-olds are much more likely to use drugs than are 12-year-olds. And they are also much more likely to eat apart from their families. Ignoring this important and obvious fact makes the findings meaningless. 

     What the Study Did Find

But science writer Carl Bialik asked the survey company to conduct a simple analysis. That is, to examine the effects of age. The result? “[A]ge correlated more strongly with risk than did family dinners.” 

The company also failed to take into account family social status or financial status. Or location. Were they rural or urban? And the list goes on. 

Confusing correlation with causationAnother serious problem is that the company didn’t actually compare family dining with drug use. Instead it compared dining behavior with a “drug risk score” that it made up. The risk score was based on such things a whether or not respondents said their friends use drugs. 

The company actually asked respondents if they used drugs themselves. But that information was not used for reasons unknown. Perhaps it didn’t support the report’s conclusion. But who knows?

     No Peer Review

The report was self-published by the sponsoring group. Thus, it avoided the scrutiny of peer review. And that’s required for publication in research journals. 

Confusing correlation with causationReports that bypass the peer review process may use faulty sampling techniques. They may use improper statistical analyses. Or draw unwarranted conclusions. They may make unsubstantiated assertions. In the absence of peer review, the public is completely unprotected. Special interest groups can pass off shoddy reports. Or even intentionally deceptive reports as legitimate scientific research. 

Eating dinner together regularly is probably a reflection of strong family ties. Of a desire to communicate. And of a generally well functioning family. In short, it’s almost certainly a result rather than a cause of such functioning. So a dysfunctional family that decides to eat together regularly will probably fail to prevent abuse.

So what’s the harm in urging people to eat together? Nothing. Unless it misleads people into thinking that by simply by doing so they can solve the problem of substance abuse. 

This is a great example of confusing correlation with causation.

V. Resources: Confusing Correlation with Causation




    • This website urges readers to avoid confusing correlation with causation. Indeed, that’s the purpose of this web page.