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Lies, Damned Lies, and Statistics

Proton Pump Inhibitor Study Published With Questionable COVID-19 Data

American Journal of Gastroenterology published a seemingly groundbreaking study involving people who take so-called proton pump inhibitors are at a much higher risk of getting COVID-19. The study was heavily promoted before the data was questioned by several commentators.

On July 7, 2020, the American Journal of Gastroenterology published a seemingly groundbreaking article claiming that in a study involving over 53,000 people, the ones who take so-called proton pump inhibitors — i.e., drugs like Nexium that treat heartburn and stomach pain — are at a much higher risk of getting COVID-19. This study was reported in the New York Times, Time, MSN, and others.

Oddly enough, all of the data came from a survey firm, not from hospital or medical records. That is, people were given a survey about themselves and their medical conditions, with no independent verification or administrative records involved.


As has been pointed out by a number of Twitter commentators, the initial results should have made the researchers question their data, if not their entire ability to conceive of a research project in the first place. Table 1 of the study claims that while the overall survey respondents were a nationally representative sample — fairly balanced across age, gender, income, race/ethnicity, etc. — there were some surprising imbalances among the survey respondents who got COVID-19:

  • 74.5% were between 30 and 39 years old;
  • 64.7% were female;
  • 69.7% were Latina;
  • 69.6% had only a high school education;
  • 63.5% had an income over $200,000 a year;
  • 73% were daily smokers; and
  • 68.5% lived in the South.

Does anyone believe that in a nationally representative sample of Americans, a huge majority of the COVID-19 cases would be 30-something Latinas who live in the South, smoke every day, have a high school education, but nonetheless make over $200,000 a year? This study shows why the number one rule for researchers should be to take stock of whether the underlying data are believable.