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The Month You're Born May Affect Your Disease Risk, Research Suggests

And it's not looking great for those born in October.

FIONA MACDONALD
10 JUN 2015
 

People try to pin a lot of things on when you're born (personality, favourite colour, ideal careers), usually with no scientific backing whatsoever. But a new study has found compelling evidence to suggest that the month you're born actually can affect your risk of developing 55 different diseases, including asthma and heart disease.

A team of data scientists from Columbia University Medical Center in the US looked at the medical records of more than 1.7 million people and found that the healthiest month to be born in the Northern Hemisphere is May, while the month associated with the most diseases is October, closely followed by November.

 

But before all you October babies start freaking out, don't worry, none of this is cause to panic. “It’s important not to get overly nervous about these results because even though we found significant associations the overall disease risk is not that great,” said lead researchers and data scientist Nicholas Tatonetti in a press release. “The risk related to birth month is relatively minor when compared to more influential variables like diet and exercise.”

The point of the research wasn't to scare people off giving birth in certain months, but rather to use the mass of data available to uncover new disease risk factors, says Tatonetti.

In particular, their study helped to confirm the findings from 39 previous studies on birth season and disease risk, and suggest that "seasonally dependent early developmental mechanisms may play a role in increasing lifetime risk of disease," as the authors write in the paper, published in the Journal of the American Medical Informatics Association.

It's these seasonally linked environmental mechanisms - potentially things such as pollen counts, dust mite exposure and temperature fluctuations - that the team now hope to identify using additional data.

“Astrology puts a lot of stock on what month you were born in, and that really hurts this type of research, since there isn’t much scientific evidence to support that,” Tatonetti told Alice Park over at Time. “But seasonality is a proxy for variable environmental factors present at the time of your birth, and we are learning more about the very large role that environment, and gene-environment interactions, plays in our development. This could be one way to start mapping out those gene-environment effects.”

To asses the link between birth month and disease risk, Tatonetti and his team looked at data collected between 1985 and 2013 on more than 1.7 patients all born in the last century. They then created a computational algorithm that would see out any association between patients' birth months and 1,688 different medical conditions.

What they found was that, regardless of how old patients were or their sex, there were certain months that were more closely linked to the risk of particular diseases than others. For instance, people born in September seemed to have a higher risk of asthma, while those born in November were slightly more likely to have ADHD. And people born in March have the highest risk of several different heart conditions.

The researchers have mapped this data below, but keep in mind that the results are from the Northern Hemisphere, and so the seasons are opposite for those of us on the other side of the world:

disease association calplot annot final

LiveScience have also created this handy infographic so you can quickly chart your risk of developing certain conditions depending on when you were born:

Chart shows links between birth month and risk of diseases.
Source: LiveScience

Obviously there are some serious limitations of this study - primarily the fact that all the data was taken from patients admitted to a hospital in New York. But the researchers now hope they can use their algorithm to perform further research on broader datasets.

“Faster computers and electronic health records are accelerating the pace of discovery,” said first author of the study Mary Regina Boland. “We are working to help doctors solve important clinical problems using this new wealth of data.”

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