The effect of leg-to-body ratio on male attractiveness depends on the ecological validity of the figures

Abstract

Leg-to-body ratio (LBR) predicts evolutionary fitness, and is therefore expected to influence bodily attractiveness. Previous investigations of LBR attractiveness have used a wide variety of stimuli, including line drawings, silhouettes, and computer-generated images based on anthropometric data. In two studies, community samples of heterosexual women from the USA rated the attractiveness of male figures presented as silhouettes and as detailed computer-generated images with three different skin tones (white, black, and an artificial grey). The effects of LBR depended on the image format. In particular, a curve-fitting analysis indicated that the optimally-attractive LBR for silhouettes was fractionally below the baseline, whereas the optima for more detailed computer-generated images was approximately 0.5 s.d. above the baseline and was similar for all three skin-tones. In addition, the participants' sensitivity to changes in the LBR was lowest for the silhouettes and highest for the grey figures. Our results add to evidence that the most attractive LBR is close to, but slightly above, the population mean, and caution that the effects of limb proportions on attractiveness depend on the ecological validity of the figures.

The influence of leg-to-body ratio, arm-to-body ratio and intra-limb ratio on male human attractiveness

“…Subsequent work has typically used silhouettes based on photographs and has found a preference for average or above-average LBRs [ 19 , 20 ] (see also [ 21 – 23 ]). Some researchers have suggested that silhouettes lack ecological validity and may not accurately represent human body morphology [ 24 , 25 ], and more recent research has progressed to using naturalistic 3D-rendered CGI figures [ 26 , 27 ]. In a study of Japanese participants, Kiire [ 27 ] examined a wide range of LBRs using realistic rendered figures and, using a curve-fitting approach, found that the optimal attractiveness was very close to the population mean; in a similar study, Versluys & Skylark [ 25 ] found that, for heterosexual American women, the optimally attractive LBR for rendered male figures was approximately half a standard deviation above the population average.…”

“…Some researchers have suggested that silhouettes lack ecological validity and may not accurately represent human body morphology [ 24 , 25 ], and more recent research has progressed to using naturalistic 3D-rendered CGI figures [ 26 , 27 ]. In a study of Japanese participants, Kiire [ 27 ] examined a wide range of LBRs using realistic rendered figures and, using a curve-fitting approach, found that the optimal attractiveness was very close to the population mean; in a similar study, Versluys & Skylark [ 25 ] found that, for heterosexual American women, the optimally attractive LBR for rendered male figures was approximately half a standard deviation above the population average. (These authors also found that the effect of LBR was different for 3D-rendered images and silhouettes, confirming that studies of silhouette figures should be treated with some caution.)…”

“…Participants were tested online (e.g. [ 25 ]), and the inclusion criteria were as follows: female, heterosexual, aged 18 or over, who reported no problems with viewing the experimental stimuli and whose IP address had not occurred earlier in the experiment or experimental series (i.e. who had not previously participated in the present or closely related studies).…”

“…The stimulus values are listed in table 1 . The faces were pixelated using Lunapic ( ) [ 25 ]; pixilation was applied separately for each figure, resulting in some (non-systematic) variation between stimuli. Images were saved as jpeg files; example stimuli are shown in figure 1 .…”

“…The relationship between limb ratio and attractiveness has previously been described well by a quadratic curve (e.g. [ 25 ]). We must be cautious about applying this approach here because we only tested a small number of ratios, but it is nonetheless instructive to fit quadratic regression curves of the form to the mean judgements for each condition.…”