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Our World in Data presents the empirical evidence on global development in entries dedicated to specific topics.
This blog post draws on data and research discussed in our entry on Gender Ratio.
Across the world there are differences in the sex ratio at different life stages. This imbalance in the male and female population can in some cases be traced back to birth: in some countries the number of boys and girls born each year is significantly skewed.
In the map below we see the differences in sex ratio at birth across the world. Here the sex ratio is measured as the number of male births for every 100 female births; a value greater than 100 indicates there are more boys than girls born that year. A figure of 110 would indicate that there are 110 male births for every 100 female births.
The first striking point is that in every single country of the world there are more boys born than girls. This has been true for all years for which we have data (as far back as 1962) in all countries of the world, as you can when you move the timeslider below the map further back.
Does this mean every country selects for boys prior to birth; for example, through induced abortion practices which preferentially select for boys? Not necessarily.
In the absence of selective abortion practices, births in a given population are typically male-biased – the chances of having a boy are very slightly higher than having a girl.
Why are births naturally expected to be male-biased?
For most countries, there are around 105 males per 100 female births. This is what the World Health Organization (WHO) estimates as the ‘expected’ sex ratio at birth: in the absence of gender discrimination or interference we’d expect there to be around 105 boys born per 100 girls, although this can range from around 103 to 107 boys per 100 girls. Why is this?
In the most comprehensive study of its kind, Orzack et al. (2015) monitored the trajectory of sex ratio from conception through to birth across five different methods.1 This produced the largest dataset available on the sex ratio throughout the stages of pregnancy.
A key result from this study was that the sex ratio at conception is equal: there is no difference in the number of males and females conceived. For births to be consistently male-biased, there must be gender differences in the probability of miscarriage through pregnancy.
The study found that although the probability of miscarriage varies between genders across the course of a pregnancy, female mortality is slightly higher than male mortality over the full period:
- there is a higher probability that an embryo with chromosomal abnormalities2 is male – in the first week of pregnancy, excess male mortality therefore means pregnancy is female-biased;
- in the next 10-15 weeks of pregnancy female mortality is higher, which increases the ratio in favor of males;
- male and female mortality is approximately equal around week 20;
- between weeks 28-35 of pregnancy, there is higher male mortality.
Overall, a male-biased sex ratio at birth is the result.
In some countries the sex ratio is skewed beyond the expected sex ratio
Some male-bias in births is what we expect with no deliberate gender selection through parents or society more broadly. There are, however, some key outliers in the world today: in countries including China, India, Vietnam, Pakistan, and Azerbaijan this ratio is very skewed. Here it’s likely that deliberate selection practices explain part of the high sex ratio as we explore here.
- Orzack, S. H., Stubblefield, J. W., Akmaev, V. R., Colls, P., Munné, S., Scholl, T., … & Zuckerman, J. E. (2015). The human sex ratio from conception to birth. Proceedings of the National Academy of Sciences, 112(16), E2102-E2111.
- In the paper the authors differentiate between ‘karyotypically normal’ and ‘karyotypically abnormal’. This refers to whether there are mutations in chromosomes, such as an extra, missing or irregular portion of chromosomal DNA. ‘karyotypically abnormal’ embryos have a lower probability of surviving to birth, or often lead to other human diseases/conditions.
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Photo credit: OurWorldInData