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Parents with several children of the same sex might try for \u201cone more\u201d in hopes of conceiving the opposite sex, but new research suggests they\u2019re more likely to have another child of the same sex.<\/p>\n
Led by researchers at Harvard T.H. Chan School of Public Health, the study challenges the long-held belief that sex at birth is random, like a coin toss.<\/p>\n
\u201cIf you\u2019ve had 2 girls or 3 girls and you\u2019re trying for a boy, you should know your odds are not 50\u201350. You\u2019re more likely than not to have another girl,\u201d said Dr. Jorge Chavarro<\/a>, professor of nutrition and epidemiology and senior author of the study, published in Science Advances<\/a>.<\/p><\/blockquote>\n
Is sex at birth really random?<\/b><\/p>\n
Sex at birth has traditionally been considered an example of binomial distribution. After Chavarro and colleagues noticed several real-life examples of individuals producing children of only one sex, they decided to explore whether sex at birth is as random as once thought.<\/p>\n
The research team accessed data from 58,007 women living in the US who had experienced 2 or more live births from 1956 to 2015, totaling 146,000 pregnancies. All women were recruited into one of two large ongoing studies: Nurses\u2019 Health Study II (NHSII)<\/a> and Nurses\u2019 Health Study 3 (NHS3)<\/a>.<\/p>\n
\u201cWe aimed to answer two questions at the maternal level: (i) whether sex at birth follows a simple binomial distribution or beta-binomial distribution, and (ii) whether there are highly heritable traits (e.g., natural hair color, ABO blood type, height and chronotype) and\/or reproductive factors (e.g., age at menarche and age at first birth) associated with having offspring of a single sex,\u201d the authors explained<\/a>.<\/p>\n
<\/b>
\nBinomial distribution vs beta-binomial distribution <\/b><\/p>\nA binomial distribution is a statistical probability that informs of the probability of getting a certain outcome (such as having a baby boy or a girl) in a fixed number of independent trials (or births, in this example) where the probability of that outcome remains the same each time.<\/p>\n
A beta-binomial distribution is similar, but it allows for the probability of an outcome to vary from one family to another. For example, instead of assuming that every family has a 50% chance of having a boy each time a baby is born, the beta-binomial allows for there to be a slightly higher or lower chance for that to happen based on factors such as genetics.<\/p>\n
Larger families are more likely to have children of the same sex<\/b><\/p>\n
Some families were more likely to have children of the same sex, deviating from a simple binomial distribution. This effect was observed more in larger families, where mothers had three or more children.<\/p>\n
\u201cWe found that older maternal age at first birth may be a risk factor for repeatedly giving birth to children of only one sex, even after adjustment for sibship size,\u201d Chavarro and colleagues said<\/a>.<\/p>\n
Speculating on why this might be the case, the researchers suggest that physiological changes that occur as women age \u2013 such as changes in vaginal pH and the follicular phase \u2013 may promote the survival of X or Y chromosomes. \u201cEach woman may have a different predisposition to each of these factors as they age, which could lead to a higher probability of consistently producing same-sex offspring,\u201d they described<\/a>.<\/p>\n
A genome-wide association study identified maternal single-nucleotide polymorphisms \u2013 a common type of genetic variation \u2013 linked to having male-only offspring (TSHZ1) and female-only offspring (NSUN6) in the cohort.<\/p>\n
\u201cWe don\u2019t know why these genes would be associated with sex at birth, but they are, and that opens up new questions,\u201d Chavarro said<\/a>.<\/p><\/blockquote>\n
The authors acknowledge that their study is limited by only collecting data on women, and that paternal factors may also contribute to sex determination. The study cohort largely comprises white women (95%), thus the sex ratio distribution observed in this study may not apply to other populations or cultures where reproductive behaviors and sex preferences differ.<\/p>\n
\u201cFuture research is essential to replicate our findings, explore new risk factors (e.g., lifestyle, nutritional status, and exposure to environmental chemicals), and investigate the possibility of gene-gene\/gene-environment interactions,\u201d the authors concluded<\/a>.<\/p>\n
Reference: <\/b>Wang S, Rosner BA, Huang H, et al. Is sex at birth a biological coin toss? Insights from a longitudinal and GWAS analysis. Sci Adv. 11(29):eadu7402. doi: 10.1126\/sciadv.adu7402<\/a><\/p>\n