Unfaithful men given away by their ‘macho features’

Unfaithful men given away by their ‘macho features’

Men who commit adultery cannot hide their unfaithfulness from their faces, according to a study by the University of Western Australia.

The facial features that indicate a man has been unfaithful are not awkward expressions or guilty glances but have been instilled into the individual’s genes by evolution.

Dr Yong Zhi Foo led the study that was published in the journal Royal Society Open Science. It involved showing 200 pictures of various male and female faces to a group of 1,500 subjects.

The people in the pictures had been asked if they had ever been unfaithful, and if they had ever attempted to steal a partner from someone else.

The subjects were asked to rate how attractive the people in the pictures were, and how masculine or feminine their features were. They were then asked to identify which faces belonged to those who had a history of unfaithfulness.

The subjects were able to accurately identify the unfaithful male faces to a level much higher than would be expected by chance. The same could not be said of the pictures of unfaithful women.

The researchers believe that the findings can be explained by evolution, with the theory that masculine looking men would be more likely to stray from their partners because they were desirable to others.

The report read; “Given the reproductive costs of being cheated on, evolutionary theories predict that it would be [beneficial] for individuals to evolve strategies to prevent sexual infidelity.

“Accuracy in judging sexual unfaithfulness of others might represent one such strategy.

“In this context, judgments of the propensity for sexual unfaithfulness made from the faces of strangers could play an important role in reducing the risk of developing relationships with partners who may prove unfaithful.”

The fact that unfaithful women could not be identified in the same way could be because make-up and other cosmetic products had overpowered the evolutionary features over time.