Objective: Birth month and climate impact lifetime disease risk, while the underlying exposures remain largely elusive. We seek to uncover distal risk factors underlying these relationships by probing the relationship between global exposure variance and disease risk variance by birth season.
Material And Methods: This study utilizes electronic health record data from 6 sites representing 10.5 million individuals in 3 countries (United States, South Korea, and Taiwan). We obtained birth month-disease risk curves from each site in a case-control manner. Next, we correlated each birth month-disease risk curve with each exposure. A meta-analysis was then performed of correlations across sites. This allowed us to identify the most significant birth month-exposure relationships supported by all 6 sites while adjusting for multiplicity. We also successfully distinguish relative age effects (a cultural effect) from environmental exposures.
Results: Attention deficit hyperactivity disorder was the only identified relative age association. Our methods identified several culprit exposures that correspond well with the literature in the field. These include a link between first-trimester exposure to carbon monoxide and increased risk of depressive disorder (R = 0.725, confidence interval [95% CI], 0.529-0.847), first-trimester exposure to fine air particulates and increased risk of atrial fibrillation (R = 0.564, 95% CI, 0.363-0.715), and decreased exposure to sunlight during the third trimester and increased risk of type 2 diabetes mellitus (R = -0.816, 95% CI, -0.5767, -0.929).
Conclusion: A global study of birth month-disease relationships reveals distal risk factors involved in causal biological pathways that underlie them.
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http://dx.doi.org/10.1093/jamia/ocx105 | DOI Listing |
J Am Med Inform Assoc
March 2018
Department of Biomedical Informatics, Columbia University, New York, NY, USA.
Objective: Birth month and climate impact lifetime disease risk, while the underlying exposures remain largely elusive. We seek to uncover distal risk factors underlying these relationships by probing the relationship between global exposure variance and disease risk variance by birth season.
Material And Methods: This study utilizes electronic health record data from 6 sites representing 10.
AMIA Annu Symp Proc
July 2017
Explorys, an IBM Company, Cleveland, OH.
We have sought to replicate and extend the Season-wide Association Study (SeaWAS) of Boland, et al. in identifying birth month-disease associations from electronic health records (EHRs). We used methodology similar to that implemented by Boland on three geographically distinct cohorts, for a total of 11.
View Article and Find Full Text PDFAMIA Jt Summits Transl Sci Proc
August 2016
Department of Biomedical Informatics, Columbia University; Department of Medicine, Columbia University; Department of Systems Biology, Columbia University; Observational Health Data Sciences and Informatics, Columbia University.
Prenatal and perinatal exposures vary seasonally (e.g., sunlight, allergens) and many diseases are linked with variance in exposure.
View Article and Find Full Text PDFEnter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!