Observable variations in human sex ratio at birth
- 1. University of Chicago
- 2. Karolinska Institutet
Description
The human sex ratio at birth (SRB), defined as the ratio between the number of newborn boys to the total number of newborns, is typically slightly greater than 1/2 (more boys than girls) and tends to vary across different geographical regions and time periods. In this large-scale study, we sought to validate previously-reported associations and test new hypotheses using statistical analysis of two very large datasets incorporating electronic medical records (EMRs). One of the datasets represents over half (∼ 150 million) of the US population for over 8 years (IBM Watson Health MarketScan insurance claims) while another covers the entire Swedish population (∼ 9 million) for over 30 years (the Swedish National Patient Register). After testing more than 100 hypotheses, we showed that neither dataset supported models in which the SRB changed seasonally or in response to variations in ambient temperature. However, increased levels of a diverse array of air and water pollutants, were associated with lower SRBs, including increased levels of industrial and agricultural activity, which served as proxies for water pollution. Moreover, some exogenous factors generally considered to be environmental toxins turned out to induce higher SRBs. Finally, we identified new factors with signals for either higher or lower SRBs. In all cases, the effect sizes were modest but highly statistically significant owing to the large sizes of the two datasets. We suggest that while it was unlikely that the associations have arisen from sex-specific selection mechanisms, they are still useful for the purpose of public health surveillance if they can be corroborated by empirical evidences.
Data availability
Aggregate data associated with described analyses and R scripts used in this analysis are available at https://github.com/yananlong/SRB. In particular, https://git.io/Jg5zx for the list of counties with neighbours, https://git.io/Jg5iy for the number of male and female newborns plus the exogenous factors derived from the EQI dataset for each county, and https://git.io/Jg5MJ for the county, sex and birthday for each mother--newborn pair.
Files
journal.pcbi.1009586.pdf
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Additional details
Identifiers
- DOI
- 10.1371/journal.pcbi.1009586
- Other
- oai:uchicago.tind.io:5888
Funding
- ARO
- DARPA Big Mechanism program
- National Institutes of Health
- R01HL122712
- National Institutes of Health
- 1P50MH094267
- National Institutes of Health
- U01HL108634
- Liz and Kent Dauten
- King Abdullah University of Science and Technology
- FCS/1/4102-02-01
- King Abdullah University of Science and Technology
- FCC/1/1976-26-01
- King Abdullah University of Science and Technology
- REI/1/0018-01-01
- King Abdullah University of Science and Technology
- REI/1/4473-01-01