3. Why does estrogen make my brown eyes blue? Sex linkage of hair and eye colors

My wish list for research in 2024

Various eye colors (Richard A. Sturm, University of Queensland)

Estrogen seems to favor the expression of non-black hair and non-brown eyes during fetal development. The “new” hair and eye colors are not only more frequent among women but also associated, in the case of blue eyes, with feminization of male face shape, female shoulder width, and female waist-to-hip ratio. Blue eyes are also associated with shyness in young boys.

Europeans have a surprising variety of hair and eye colors. Their hair is not only black but also brown, flaxen, golden, or red. Their eyes are not only brown but also blue, gray, hazel, or green (Frost, 2006; Frost, 2022). This differentiation from the original black hair and brown eyes seems to have begun among women and gone farther among them.

Hair color - Women more often have the new hair colors, particularly red and blond. Conversely, their hair is less often black—three to five times less often. This sex difference is natural (Hysi et al., 2018; Shekar et al., 2008). Among Czechs, 19% of women and 11% of men have the highest gradation of hair redness (Frost et al., 2017).

Eye color - Women more often have the new eye colors, particularly green and hazel (Frost et al., 2017). Conversely, their eyes are less often brown. The first new eye color seems to have been blue, which then differentiated to create gray, green, and hazel. Thus, “blue” in its narrow sense has lost ground among women to the derived variants of green and hazel.

Population frequencies of eye colors, for men and women (Frost et al., 2017)

The new hair and eye colors are unusual in two ways. First, they are brighter than the original black and brown. They thus reflect more light and have a higher chance of standing out against the visual landscape. Second, they are “purer”—they occupy thinner slices of the visible spectrum than the original black and brown. In nature, pure colors are typically found in situations where an animal or a plant has to catch attention, such as to get pollinated, to warn predators, or to attract a mate.

This need for attention may explain how a single hair or eye color evolved into a diverse palette of hues. A color gets noticed not only for its brightness and purity but also for its novelty. The last quality is frequency-dependent. If a noticeable color becomes too frequent in a population, it thereby becomes less noticeable and, hence, less novel. The desire for novelty is now reoriented toward less frequent colors, including those that have recently appeared through mutation. Thus, over successive generations, the population will accumulate more and more color variants. This is likely how hair and eye color became polymorphic (see Note #1).

Again, the evidence seems to point to women being the main target of this selection for brighter, purer, and more novel colors. One piece of evidence is the higher frequency of the new hair and eye colors in the female population. Another is the role of estrogen in this sex-linkage. The female hormone seems to favor the expression of non-black hair and non-brown eyes during fetal development.

Red is the hair color that differs the most in frequency between women and men. Red hair should therefore be most clearly associated with increased exposure to estrogen during fetal development. This hypothesis is supported by the higher incidence of estrogen-dependent diseases in redhaired women. According to a health survey of over seven thousand people, male redheads are as healthy as other men, doing better on average in three categories and worse in three. Female redheads, however, do worse on average than other women in ten categories and better in only three. They are especially prone to four types of cancer: colorectal, cervical, uterine, and ovarian—three of which are estrogen-dependent (Frost et al., 2017). Being both female and red-haired therefore generates the highest level of risk for estrogen-dependent diseases, probably because of the combined effect of these two risk factors.

In sum, the new hair and eye colors were favored by a selection pressure that acted primarily on European women, with European men acquiring them as a side-effect (since the new alleles are only partly sex-linked). The selection was specifically for eye-catching qualities—brightness, spectral purity, and relative novelty.

This looks like sexual selection, but why would women have a greater need to get noticed on the mate market? Usually, it is the other way around, both for humans and for mammals in general. Females are less available for mating because of the limitations of pregnancy, lactation, and early infant care. Conversely, males are more available, and thus often have more than one mate at any one time. That was, in fact, the situation of most humans in prehistory. But that situation changed as they expanded their range out of the tropics and into more seasonal environments. At higher latitudes, proportionately fewer men were available for mating at any one time. There were two reasons:

• Polygyny was more costly for men. With men specializing in hunting and women in gathering, women became dependent on men during winter—since there was little food to be gathered. Men thus had to bear a greater share of food provisioning, with the result that polygyny became impossible for all but the ablest hunters.

• Death rates were higher for men than for women. Because men had to hunt for more food and over longer distances, they suffered a higher death rate at younger ages. They were thus fewer in number overall.

Male scarcity was most acute in an environment that no longer exists: the steppe-tundra of the last ice age, essentially the vast plains stretching from the Baltic to western Siberia. That environment supported large herds of reindeer and other herbivores, which could in turn support a large human population. But at a cost: women depended almost entirely on their hunting husbands for food, and those hunters had to cover long distances without alternative food sources, thus risking death from starvation or exposure. The result was an imbalance in the operational sex ratio: too many women for too few men, and strong selection for women with eye-catching features (Frost, 2006; Frost, 2022; Frost, 2023).

Proposed study

The aim here is to determine whether the ratio of estrogens to androgens in fetal tissues influences the development of hair and eye color. One way would be to measure the “digit ratio”—the length of the index finger divided by the length of the ring finger. This measure of fetal exposure to the sex hormones is relatively inexpensive, though disputed by some researchers. The lower your digit ratio, the more you have been masculinized by androgens during fetal development; the higher your digit ratio, the more you have been feminized by estrogens during fetal development. The left-hand digit ratio is associated with prenatal and postnatal exposure to the sex hormones. The right-hand ratio is associated much more with prenatal exposure (see Note #2).

An unpublished study, using a sample of 644 British participants, found that the left-hand digit ratio was significantly higher on average among individuals with blond hair than among those with brown, red, or other hair colors. For eye color, there was a similar but weaker relationship: the left-hand digit ratio was higher on average among individuals with blue eyes than among those with other eye colors.

That study was not published because of two objections from the referees: hair dyeing could not be excluded as a possible factor; and identification of hair and eye color was too subjective. Yet it is difficult to see how hair dyeing or misidentification can explain the digit ratio differences. Such methodological problems would introduce more noise into the data and make any differences less significant.

I wish to see that study replicated with a more rigorous experimental design, specifically a larger sample and narrower age range. Age interacts with the effects of the sex hormones, i.e., prenatal effects on hair color are the opposite of pubertal effects. Whereas women are lighter-haired than men from 17 onward, they are actually darker-haired up to the age of 14 (Steggerda, 1941). The right-hand digit ratio should thus be better at predicting the darkening of hair color before puberty, and the left-hand digit ratio better at predicting the lightening of hair color after puberty.

In addition, I wish to see whether the relationship between fetal estrogenization and eye color explains three other relationships between non-brown eyes and certain behavioral/physical traits:

• Blue-eyed boys tend to be shy. This is the “little boy blue” effect. A study of preschoolers found more social wariness in blue-eyed boys than in brown-eyed boys. The difference was greatest at the extremes of wariness. Among the very inhibited boys, 13 out of 14 were blue-eyed. Among the very uninhibited, only 4 out of 10 were. There was no such relationship among the girls, whose eyes were blue in 5 out of 9 among the very inhibited and in 6 out of 11 among the very uninhibited (Coplan et al., 1988).

• Blue-eyed women tend to have narrower shoulders and lower waist-to-hip ratios. A Latvian study found small but significant correlations between female eye color and certain sexually dimorphic features. Shoulders were narrower and waist-to-hip ratios lower in blue-eyed women than in brown-eyed women (Kažoka and Vētra, 2011).

• Blue-eyed men tend to have more feminine faces. This was an unintended finding of two Czech studies whose participants were asked to rate male and female facial photos. Initially, the brown-eyed male faces were rated as more dominant than the blue-eyed male faces. When, as a control, the brown-eyed faces were photoshopped to make them blue-eyed, they were still rated as more dominant. On careful examination, the originally brown-eyed faces were found to be more masculine with broader and more massive chins, broader mouths, larger noses, larger eyebrows, and closer-set eyes. The originally blue-eyed faces had smaller and sharper chins, narrower mouths, smaller noses, and greater distance between the eyes. Blue eyes were associated with a more feminine face shape only in male participants. This is perhaps because a male fetus normally does not have enough estrogen to feminize the face. If enough estrogen is present to feminize the face, there is probably enough to influence the development of eye color (Kleisner et al., 2010; Kleisner et al., 2013).

  Were brown eyes associated with a different face shape because some of the brown-eyed men were partly Jewish or Roma and had a more Mediterranean appearance? In that case, face shape would have been more variable in the brown-eyed men. It was not. This explanation also fails to explain the effect of gender: why were blue eyes associated with facial feminization in men but not in women?

Averaged faces of blue-eyed men (left) and brown-eyed men (right), Czech population (Kleisner et al., 2010).

The above studies suggest that the association between the "new" colors and physical/behavioral feminization is largely confined to men. (In women, these colors show only a weak association with shoulder breadth or waist-to-hip ratio). This is probably because the feminization effects are triggered when the estrogen level has risen above a certain threshold. That threshold would already be surpassed by almost all female fetuses.

Notes

1. Preference for rare hair colors was demonstrated by Thelen (1983), who showed pictures of attractive women to male participants and then asked them to choose the one they most wanted to marry. There were three series of pictures: the first had equal numbers of brunettes and blondes; the second had one brunette for every five blondes; and the third had one brunette for every eleven blondes. The scarcer the brunettes were in a series, the more attractive they seemed, i.e., each brunette had a better chance of being chosen.

   Thelen’s findings were not replicated by Janif et al. (2015), whose male participants made their choices online, i.e., in private and on their home computers. There was thus no control over the female images they may have previously viewed on the same computer screen or might still be viewing on an alternate screen or split screen. This source of unwanted female imagery introduces noise into the data, thus increasing the minimum number of online raters to produce replicable ratings of female facial attractiveness. Devcic et al. (2010) report that their mean ratings of facial attractiveness did not become stable until they had recruited 857 online raters. Popenko et al. (2012) state that they needed a minimum of 992 online raters to achieve stable ratings. By comparison, Janif et al. (2015) used 658 male raters, while making their data even noisier by recruiting an ethnically diverse pool of raters, i.e., over a third were of non-European descent. Those raters would have tended to perceive female faces with black hair as ethnic insiders and female faces with non-black hair as ethnic outsiders.

2. Using a meta-study, Sorokowski and Kowal, 2023) concluded that the digit ratio indicates only an individual’s prenatal exposure to testosterone (and only in amniotic fluid, not in core blood). The authors, however, did not look at the ratio of estrogens to androgens. Their exclusion of data on estrogen levels is puzzling, since fetal exposure to estrogens is no less important than fetal exposure to androgens.

References

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Devcic, Z., Karimi, K., Popenko, N., and Wong, B.J.F. (2010). A web-based method for rating facial attractiveness. Laryngoscope, 120(5), 902-906. https://doi.org/10.1002/lary.20857

Frost, P. (2006). European hair and eye color - A case of frequency-dependent sexual selection? Evolution and Human Behavior 27(2): 85-103. https://doi.org/10.1016/j.evolhumbehav.2005.07.002

Frost, P. (2022). European Hair, Eye, and Skin Color: Solving the Puzzle. Washington: Academica Press, 169 pp., ISBN 9781680538724 https://www.academicapress.com/node/549

Frost, P. (2023). A people of many colors. Peter Frost’s Newsletter. January 24. https://peterfrost.substack.com/p/a-people-of-many-colors

Frost, P., K. Kleisner, and J. Flegr. (2017). Health status by gender, hair color, and eye color: Red-haired women are the most divergent. PLoS One 12(12): e0190238. https://doi.org/10.1371/journal.pone.0190238  

Hysi, P.G., A.M. Valdes, F. Liu, N.A. Furlotte, D.M. Evans, V. Bataille, et al. (2018). Genome-wide association meta-analysis of individuals of European ancestry identifies new loci explaining a substantial fraction of hair color variation and heritability. Nature Genetics 50(5): 652-656. https://doi.org/10.1038/s41588-018-0100-5

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Kleisner, K., T. Kocnar, A. Rubešová, and J. Flegr. (2010). Eye color predicts but does not directly influence perceived dominance in men. Personality and Individual Differences 49(1): 59-64. https://doi.org/10.1016/j.paid.2010.03.011

Kleisner, K., L. Priplatova, P. Frost, and J. Flegr. (2013). Trustworthy-looking face meets brown eyes. PLoS One 8(1): e53285. https://doi.org/10.1371/journal.pone.0053285

Popenko, N.A., Devcic, Z., Karimi, K., and Wong, B.J.F. (2012). The virtual focus group. A modern methodology for facial attractiveness rating. Plastic and Reconstructive Surgery, 130(3), 455e-461e. https://doi.org/10.1097/PRS.0b013e31825dcb48

Shekar, S.N., D.L. Duffy, T. Frudakis, G.W. Montgomery, M.R. James, R.A. Sturm, and N.G. Martin. (2008). Spectrophotometric methods for quantifying pigmentation in human hair-Influence of MC1R genotype and environment. Photochemistry and Photobiology 84(3): 719-726. https://doi.org/10.1111/j.1751-1097.2007.00237.x  

Sorokowski, P., and M. Kowal. (2023). Relationship between the 2D:4D and prenatal testosterone, adult level testosterone, and testosterone change: Meta-analysis of 54 studies. American Journal of Biological Anthropology. 183(1): 20-38. https://doi.org/10.1002/ajpa.24852

Steggerda, M. (1941). Change in hair color with age. Journal of Heredity 32(11): 402-403. https://doi.org/10.1093/oxfordjournals.jhered.a104977

Thelen, T.H. (1983). Minority type human mate preference. Social Biology 30(2): 162-180. https://doi.org/10.1080/19485565.1983.9988531