In a statement that echoed throughout his administration, the ‘highly backed’ claim linked the pre-natal usage of acetaminophen to kids being born with autism.
As a new week comes into effect, so does another round of medical misinformation from the Trump administration.
It is astounding to think that despite his government being filled with anti-science members, somehow there’s always news around ‘heavily backed scientific findings’.
With that in mind, it was just a few days ago that President Donald Trump, himself make the comical claim that the usage of acetaminophen (Tylenol) results in autism. To be more specific, he stated that pregnant women who were to ingest the medication, would increase the risk of their kid being born within the autism spectrum disorder (ASD).
The apparent thought process behind such a claim was to address the ‘skyrocketing’ cases of autism in the US. As a result, he cautioned pregnant women to limit their usage of acetaminophen, and that the Food and Drug Administration would modify the safety labels of the medication.
Autism is known for being a complex neurodevelopmental condition affecting communication, social interaction, and an individual’s perception of the world. This disorder does not have a singular cause and often varies from person to person. Often, it arises from an interplay of genetic and environmental factors.
Now, Trump isn’t wrong about the rise in such cases, but the reason behind them is much different than to what he claimed. The latest stats show that an estimated 1 in 31 children aged 8 and above have been identified with ASD.
This is compared to the year 2,000, wherein this number was a mere 1 in 150 children. The main reason for such a jump is an increase in diagnostic practices and awareness among parents.
Don’t be mistaken, there are actual studies done on the relationship between acetaminophen usage by pregnant mothers and kids being born with ASD. However, these studies show varying results, and only look at a correlation rather than a causal relationship. This is to say that even though some studies show a positive correlation between the two, often it is attributed to confounding variables.




