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Variability in variability: does variation in morphological and physiological traits differ between men and women?

Many researchers presume greater variability between female participants than between males due to the menstrual cycle. This view has encouraged a sex bias in health and medical research, resulting in considerable knowledge gaps with important clinical implications. Yet in another field—evolutionary...

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Detalles Bibliográficos
Autores principales: Halsey, Lewis G., Esteves, Gabriel P., Dolan, Eimear
Formato: Online Artículo Texto
Lenguaje:English
Publicado: The Royal Society 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10480696/
https://www.ncbi.nlm.nih.gov/pubmed/37680495
http://dx.doi.org/10.1098/rsos.230713
Descripción
Sumario:Many researchers presume greater variability between female participants than between males due to the menstrual cycle. This view has encouraged a sex bias in health and medical research, resulting in considerable knowledge gaps with important clinical implications. Yet in another field—evolutionary biology—the received wisdom is the reverse: that men are more variable, possibly due to male heterogamety. To test these competing hypotheses, we compared variance between the sexes for 50 morphological and physiological traits, analysing data from the NHANES database. Nearly half the traits did not exhibit sexual dimorphism in variation, while 18 exhibited greater female variation (GFV), indicating GFV does not dominate human characteristics. Only eight traits exhibited greater male variation (GMV), indicating GMV also does not dominate, and in turn offering scant support for the heterogamety hypothesis. When our analysis was filtered to include only women with regular menstrual cycles (and men of equivalent age), the number of traits with GFV and GMV were low and not statistically different, suggesting that the menstrual cycle does not typically explain GFV when it occurs. In practical terms, health and medical researchers should no longer simply assume that female participants will induce additional variation in the traits of interest.