Data Science Day @ Columbia University

An individual’s birth month has a significant impact on their lifetime disease risk. Previous studies reveal relationships between birth month and several diseases including asthma, attention deficit hyperactivity disorder, and myopia, leaving most diseases completely unexplored. We developed a hypothesis-free method called SeaWAS (Season-Wide Association Study) that systematically investigates disease-birth month patterns across all conditions. Our algorithm was first applied at Columbia University Medical Center on a dataset containing 1,749,400. We found that 9 cardiovascular conditions were significantly associated with birth month (Jan-Apr), which had never been reported previously. External validation of these findings was performed at Mount Sinai Hospital (MSH, N=1,169,599) also located in New York City (same climate). Seven of the nine conditions revealed at CUMC had significantly correlated birth month – disease risk patterns at MSH. We also explore relationships between biological mechanisms underlying these novel relationships including maternal flu infection and serum vitamin D levels.