Name: Correlation isn’t causation: What headlines often get wrong about health science
Uploaded: 2026-02-28T11:28:11.000Z
Duration: 9 min 10 s
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The news is full of headlines of officials drawing bold lines between two things happening at once.

Americans are eating more ultra processed foods while the number of people with obesity and chronic diseases are rising.

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More children are being vaccinated while autism and ADHD diagnoses climb.

More people are spending time on social media as mental health declines, the implication is often the same.

If two things rise together, then one must be causing the other.

Often these notions are based on data that show timely correlations between two events.

For example, data from the Department of Agriculture and the Centers for Disease Control and Prevention show a strong correlation between national margarine consumption and the divorce rate in Maine.

As margarine consumption steeply declined from 2000 to 2005, divorce rates fell from 2000 to 2008.

People across the country started to eat more margarine, and

lo and behold, more people in Maine got divorced.

As convincing as that graph might be, margarine isn't spreading divorce.

That graph is simply showing a correlation.

Two other things that move together, ice cream sales and shark attacks both increased seasonally in the summer, peaking around August.

They just, they both happen in the summer, you know, and

people are sort of, it's hot and people are swimming more.

So the distinction there is again, correlation is sort of just things that kind of move together.

In a sense, causation is really this concept or idea that something leads to something else.

While some relationships reflect true biological links, others, like ice cream sales and drownings or margarine consumption and divorce rates, are mere coincidences.

Confusing correlation and causation is easy to do.

Researchers report different, sometimes conflicting findings.

But major health and science decisions, such as the approval of a new drug or the reversal of long standing health guidelines, require that scientists and politicians follow careful procedures to sort out correlation from causation.

In the early 1970s, doctors blamed stomach ulcers on stress.

But then in the 1980s, Dr. Barry Marshall and Dr. Robin Warren noticed a certain bacteria called H.

Pylori consistently colonized the stomach lining of stomach ulcer patients.

Pylori is now known to spread through contaminated food or water or through direct contact with a contaminated person's feces.

The doctor's observation was a correlation.

Then in 1984, Marshall, who later won the Nobel Prize, famously drank a culture of H. Pylori bacteria.

A few weeks later, he developed gastritis, an inflammation of the stomach lining that can cause a burning pain or ache in the upper belly, vomiting or a loss of appetite.

This proved causation, albeit in a not so ethical or controlled way.

Marshall then cured himself with antibiotics.

this is sort of very common in the medical and like food and drug association world, is a randomized trial where we might have some exposure of interest, some, again, maybe a new program, a new medication, and

we literally enroll people in a study and randomly assign them to get it or not get it.

In many situations, scientists cannot perform the types of controlled experiments needed to prove causation.

There's a number of approaches that people can use.

You know, so basically a lot of the time in the absence of randomization, people try to sort of at least find a comparison group, like a group of people who didn't get say the new medication, but

who look as similar as possible to those who did.

And so the idea is to again, sort of in some sense try to have data that looks like it could have been randomized.

It wasn't and we have to acknowledge that.

But where we at least say, well, you know, maybe we want to compare.

What is the effect of eating ultra processed foods?

Scientists know that people who eat a lot of ultra processed foods are quite different from those who do not.

They live in different environments, they might have different exercise strategies, they might have other pre existing health conditions.

What an epidemiologist might do is look at their data and find a group of people who are similar to the ones who eat a lot of ultra processed foods, but

who didn't consume them, perhaps because they lived somewhere where they had better access to a grocery store or fresh foods.

Statisticians might try to group people based on similar health conditions, age or other sociodemographic factors.

Whether it's ultra processed foods or autism risk.

New studies are constantly published around the world.

At what point do scientists and policymakers determine that we know enough to form a conclusion?

There's sort of a spectrum here and certainly for say a new drug approval by the Food and Drug Administration, there's a very formal process and they require randomized trials and sort of a very thorough process to sort of establish that causal link.

And in some sense like statistical proof that some new medication or treatment really does improve outcomes in other scenarios where yeah, it's maybe more recommendations like the ultra processed foods.

And honestly also those are often murkier.

There's just sort of, there's so many factors that relate to health broadly.

I think that's where it really is about a body of evidence.

In the early 2000s, nutritional epidemiologist Carlos Augusto Monteiro noticed a shift in Brazil as traditional diets of rice and beans were replaced by soda and cookies.

While he hypothesized that eating ultra processed foods might cause the rise of obesity and chronic disease, so far all he had was a correlation.

Since then, studies have found links between consumption of ultra processed foods and a range of diseases from obesity, diabetes and high blood pressure to depression, anxiety, inflammatory bowel disease, autoimmune disorders and even cancer.

Nutrition science is challenging because health is shaped by intertwining factors such as genetics, income, environment and lifelong eating habits.

That makes controlled experiments difficult.

This has become especially important in recent months when science is cited in public debates to support political claims like what has happened recently with Tylenol and autism.

In late 2025, US researchers reviewed 46 studies examining links between acetaminophen use in pregnancy and autism or ADHD.

Of those, 27 studies reported an increased risk, nine found no association and four suggested a possible protective effect.

Several studies also observed a dose response relationship where higher use was tied to higher risk.

Late last year, President Donald Trump said pregnant women who take acetaminophen, commonly known as Tylenol in the US May increase their child's risk of developing autism.

I mean it's fight like hell not to take it.

There may be a point where you have to and that you'll you have to work out with yourself.

Numerous health organizations pushed back.

Earlier this year, European researchers published a separate comprehensive review.

They found statistically insignificant increases in the odds of autism and intellectual disability, about 3 and 11% higher odds, respectively.

The researchers also found a decrease of 3% in the odds of developing ADHD.

The researchers also examined sibling comparison studies.

These helped control for factors such as shared genetics and family environment, and

those analyses found no increased risk of autism, adhd, or intellectual disability associated with acetaminophen use during pregnancy.

All of the studies included here were observational studies.

Thinking back to the correlation between shark attacks and ice cream sales, there was a third factor at play.

It offered an explanation, and that was temperatures in the summer.

As temperatures rise, more Americans go on beach vacations and swim in the water.

Similarly, other factors might explain sporadic correlations between Tylenol use and autism.

Fever during pregnancy, especially during the first trimester, is linked to an increased risk of autism because pregnant women might be taking Tylenol to treat the fever.

The increased risk of autism and ADHD could be from the fever and not from the medicine.

While the correlation between Tylenol and autism has been well researched, there has yet to be a single study that proves how acetaminophen causes a range of neurodevelopmental disorders.

But this might be difficult, if not impossible, because it would be unethical to experiment on pregnant women and their fetuses.