Bovet, Jeanne, Barkat-Defradas, Mélissa, Durand, Valérie, Faurie, Charlotte and Raymond, Michel (2017) Women's attractiveness is linked to expected age at menopause. Journal of Evolutionary Biology, 31 (2). pp. 229-238.

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Identification Number : 10.1111/jeb.13214

Abstract

A great number of studies have shown that features linked to immediate fertility explain a large part of the variance in female attractiveness. This is consistent with an evolutionary perspective, as men are expected to prefer females at the age at which fertility peaks (at least for short-term relationships) in order to increase their reproductive success. However, for long-term relationships, a high residual reproductive value (the expected future reproductive output, linked to age at menopause) becomes relevant as well. In that case, young age AND late menopause are expected to be preferred by men. However, the extent to which facial features provide cues to the likely age at menopause has never been investigated so far. Here, we show that expected age at menopause is linked to facial attractiveness of young women. As age at menopause is heritable, we used the mother's age at menopause as a proxy for her daughter's expected age of menopause. We found that men judged faces of women with a later expected age at menopause as more attractive than those of women with an earlier expected age at menopause. This result holds when age, cues of immediate fertility and facial ageing were controlled for. Additionally, we found that the expected age at menopause was not correlated with any of the other variables considered (including immediate fertility cues and facial ageing). Our results show the existence of a new correlate of women's facial attractiveness, expected age at menopause, which is independent from immediate fertility cues and facial ageing.

Item Type: Article
Language: English
Date: 2017
Refereed: Yes
Subjects: B- ECONOMIE ET FINANCE
Divisions: TSE-R (Toulouse)
Site: UT1
Date Deposited: 17 Apr 2018 11:52
Last Modified: 02 Apr 2021 15:57
OAI Identifier: oai:tse-fr.eu:32273
URI: https://publications.ut-capitole.fr/id/eprint/25784
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