The effect of leg-to-body ratio on male attractiveness depends on the ecological validity of the figures.
Thomas M M VersluysWilliam J SkylarkPublished in: Royal Society open science (2017)
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.
Keyphrases
- deep learning
- convolutional neural network
- artificial intelligence
- body composition
- optical coherence tomography
- climate change
- machine learning
- soft tissue
- big data
- healthcare
- white matter
- physical activity
- human health
- mental health
- wound healing
- polycystic ovary syndrome
- metabolic syndrome
- risk assessment
- pregnant women
- adipose tissue
- case control