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Mate Choice and the Origin of Menopause

Overview of attention for article published in PLoS Computational Biology, June 2013
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Title
Mate Choice and the Origin of Menopause
Published in
PLoS Computational Biology, June 2013
DOI 10.1371/journal.pcbi.1003092
Pubmed ID
Authors

Richard A. Morton, Jonathan R. Stone, Rama S. Singh

Abstract

Human menopause is an unsolved evolutionary puzzle, and relationships among the factors that produced it remain understood poorly. Classic theory, involving a one-sex (female) model of human demography, suggests that genes imparting deleterious effects on post-reproductive survival will accumulate. Thus, a 'death barrier' should emerge beyond the maximum age for female reproduction. Under this scenario, few women would experience menopause (decreased fertility with continued survival) because few would survive much longer than they reproduced. However, no death barrier is observed in human populations. Subsequent theoretical research has shown that two-sex models, including male fertility at older ages, avoid the death barrier. Here we use a stochastic, two-sex computational model implemented by computer simulation to show how male mating preference for younger females could lead to the accumulation of mutations deleterious to female fertility and thus produce a menopausal period. Our model requires neither the initial assumption of a decline in older female fertility nor the effects of inclusive fitness through which older, non-reproducing women assist in the reproductive efforts of younger women. Our model helps to explain why such effects, observed in many societies, may be insufficient factors in elucidating the origin of menopause.

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X Demographics

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 151 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United Kingdom 2 1%
Austria 2 1%
Portugal 1 <1%
Chile 1 <1%
Turkey 1 <1%
Colombia 1 <1%
Brazil 1 <1%
Peru 1 <1%
Russia 1 <1%
Other 1 <1%
Unknown 139 92%

Demographic breakdown

Readers by professional status Count As %
Student > Bachelor 33 22%
Student > Master 22 15%
Researcher 19 13%
Student > Ph. D. Student 19 13%
Professor 8 5%
Other 24 16%
Unknown 26 17%
Readers by discipline Count As %
Agricultural and Biological Sciences 58 38%
Biochemistry, Genetics and Molecular Biology 13 9%
Medicine and Dentistry 11 7%
Psychology 10 7%
Social Sciences 8 5%
Other 19 13%
Unknown 32 21%