Columbia University scientists have developed a computational method to investigate the relationship between birth month and disease risk. The researchers used this algorithm to examine New York City medical databases and found 55 diseases that correlated with the season of birth. Overall, the study indicated people born in May had the lowest disease risk, and those born in October the highest. The study was published in the Journal of American Medical Informatics Association.
“This data could help scientists uncover new disease risk factors,” said study senior author Nicholas Tatonetti, PhD, an assistant professor of biomedical informatics at Columbia University Medical Center (CUMC) and Columbia’s Data Science Institute. The researchers plan to replicate their study with data from several other locations in the U.S. and abroad to see how results vary with the change of seasons and environmental factors in those places. By identifying what’s causing disease disparities by birth month, the researchers hope to figure out how they might close the gap.
Earlier research on individual diseases such as ADHD and asthma suggested a connection between birth season and incidence, but no large-scale studies had been undertaken. This motivated Columbia’s scientists to compare 1,688 diseases against the birth dates and medical histories of 1.7 million patients treated at NewYork-Presbyterian Hospital/CUMC between 1985 and 2013.