Contribution of facial components to the attractiveness of the smiling face in male and female patients: A cross-sectional correlation study

Introduction

Esthetic improvement is a key motivator in undergoing orthodontic treatment. This study aims to quantify the contribution of the smile and other facial components to the overall esthetics of attractiveness.

Methods

The attractiveness of 60 subjects (30 men, 30 women), aged 18-35 years, before orthodontic treatment, was retrospectively evaluated by 8 laypersons using the Visual Analog Scale. Pearson and stepwise correlations were calculated between the attractiveness of the smiling face and the attractiveness of facial components; namely the smile, nose, eyes, hair, chin, eyebrows, and skin.

Results

A strong correlation between the face and smile attractiveness was found (r = 0.71) for the whole sample. No significant correlations were found between attractiveness and the other facial components. When divided by gender, the smile (r = 0.70) and the eyes (r = 0.51) correlated with the attractiveness of the smiling face for men. For women, the face registered a significant correlation with the smile (r = 0.83) and the skin (r = 0.37).

Conclusions

In general, smile attractiveness was strongly correlated with the attractiveness of the smiling face, which is the only significant component. For men, the smile was responsible for 49% of the variation in the attractiveness of the smiling face, the eyes for 22%, and the hair for 6%. For women, 69% of the variation in facial attractiveness could be attributed to smile.

Highlights

  • The smile is the most important component for the attractiveness of the smiling face.

  • Smile, eyes, and hair were the most important components for facial attractiveness in men.

  • In women, the smile was responsible for most of the facial attractiveness.

Human society has always attempted to quantify ideals of esthetics and the development of perceptions of attractiveness, with a multitude of theories on the essence of beauty. From an interest in the geometry of facial harmony to the esthetic revolutions brought about by fashion and the media, beauty has interested poets, philosophers, and scientists over the centuries.

The influence of physical attractiveness in everyday life is undeniable and occurs in a more or less conscious way. A beautiful face can affect character evaluation, choice of partner, and job opportunities. The quest to improve appearance is motivated by the positive impact of attractiveness in these social interactions.

Malocclusions influence the perception of attractiveness, intelligence, personality, and behaviors. Individuals with a normal occlusion are considered more attractive, intelligent, pleasant and extroverted; anterior crossbites lead to negative perceptions, and people with several diastemas are seen as the least conscientious and agreeable. A recent study of the effect of teeth arrangement on human resources personnel showed that people with ideal smiles were considered smarter and more appropriate for the job.

Physical attractiveness plays a substantial role in interpersonal relationships, and the face is the central contributor. Discrimination is relatively frequent among people with facial differences and the search for ways to improve facial esthetics, such as orthodontic treatment, orthognathic surgery, or cosmetic treatments, has increased over the years.

Research into facial attractiveness is focused on defining which facial traits are associated with beauty. Some studies have shown a preference for symmetrical and average faces, but specific features beyond the mean exist in beautiful faces. No single element in the face is responsible for attractiveness as a whole, and proportions between the parts are also important. Przylipiak et al showed that attractiveness of the human face increased when the eyes were enlarged, and the size of the nose and the mouth was reduced. On the other hand, increased interocular distance has been reported to be less attractive.

In conversation, attention is mainly focused on the mouth and the eyes. Lerner and Karabenick concluded that teeth were of the utmost importance for the whole face, followed by the eyes, nose, mouth, and hair texture. Understanding the influence of each element for facial attractiveness as a whole could help in quantifying the limits of orthodontics when the teeth and the soft tissues undergo treatment.

Differences in facial shape between men and women, such as larger jawbones and more prominent cheekbones in men, are accentuated in puberty by hormones such as testosterone and estrogen. There is considerable evidence, even across different cultures, that feminine features increase the attractiveness of women’s faces. These include a smaller nose, a thinner face, and a more pointed chin. Neonate features such as large eyes and thick lips are also attractive in women. Men seem to value youth in women, because of a strong relationship between age and the ability to produce offspring.

In judging the appearance of the opposite sex, women value attractiveness less than men. The relationship between masculine features and the attractiveness of faces is more ambiguous for men than that for women. Despite some findings showing a preference for more masculine and dominant faces, others have shown that feminine characteristics and faces of low dominance in men are of increased attractiveness.

The primary goal of this study was to analyze the contribution of different facial elements on the frontal evaluation of the attractiveness of smiling faces. As a secondary goal, the hypothesis of gender differences in the correlation between attractiveness of the smile, hair, eyebrows, eyes, nose, chin and skin, and the attractiveness of the smiling face, was evaluated.

Material and methods

The material for this cross-sectional study was collected from 60 consecutive patients (30 men and 30 women) of European ancestry, with a mean age of 23.7 years. The patients were selected from the files of the Department of Orthodontics, University of Lisbon, in Portugal. Inclusion criteria involved no previous orthodontic treatment and the presence of maxillary incisors and canines, of normal shape and size. Exclusion criteria were cavities or fillings on the anterior maxillary teeth, gingivitis or periodontal disease evident when smiling, and craniofacial anomalies. Data were collected over 2 months following approval by the University of Lisbon School of Dentistry Ethics Review Board. Selected subjects were invited to sign an informed consent, and frontal face photographs were taken of patients smiling in a natural head position, on a neutral background. Individuals were standing, relaxed and looking straight ahead. In cases when the subjects’ head were significantly turned up or down, the clinician would guide it toward the correct orientation. A posed smile was used, and the face was free of makeup, glasses, jewelry, and hair. The camera was held by the orthodontist at a standard distance of 1.5 m and the same height as the patient’s head. The photographic equipment consisted of a digital single-lens reflex camera (D80; Nikon, Tokyo, Japan).

Different facial components were isolated from the original photograph of the smiling face, namely the smile, nose, eyes, chin, hair, eyebrows, and skin ( Fig 1 ) using Adobe Photoshop software (Adobe Systems, San Jose, Calif). All the pictures were then set up in a PowerPoint presentation (Microsoft Corp, Redmond, Wash), maintaining their relative size and proportion, using a dark background. A Visual Analogue Scale ( Fig 2 ) was included in every slide, with the indicators for unattractive on the left side, and attractive on the right.

Fig 1
Men and women’s facial components isolated from the smiling frontal photographs. A, skin; B, eyebrows; C, eyes; D, hair; E, nose; F, smile; and G, chin.

Fig 2
Example of a slide with the Visual Analog Scale.

A total of 600 images (60 smiling photographs, 420 element images, and 120 repetitions) were divided into 9 macro-enabled PowerPoint presentations ( Fig 3 ) with no time restrictions to fill out. PowerPoint files were sent and returned by e-mail, and a minimum of 2 weeks separated each of the 9 sessions. One investigator (R.G.) controlled the timings, sent the e-mails, and identified the gender of the individuals to be assessed in each set of images. Session 9 was composed of 15 repeated images from each type to assess the error of the method ( Fig 3 ).

Fig 3
Distribution of the variables through the slide show presentations.

The photographs were evaluated by 8 laypersons (4 men and 4 women) chosen randomly from the campus of the University of Lisbon. They were of European ancestry, with a mean age of 21.2 years, with no history of orthodontic treatment, and participated voluntarily.

The number of individuals to enter the study was calculated in a pilot investigation with a minimum of 55 patients needed to achieve a significance level of 0.05 with a power of 0.9. Eight evaluators were found to be the minimal number leading to strong values of intraclass correlation (ICC; ≥0.8). There were no dropouts among the evaluators.

Statistical analysis

Statistical analysis was done using SPSS version 20.0 for Macintosh (IBM Company, Armonk, NY). The mean, standard deviation, and range were calculated. The Shapiro-Wilk test was used to evaluate the normality in sample distribution. ICC was used to evaluate random errors. A Pearson correlation was used with a significance level of 0.05, followed by stepwise regression to assess the correlation between attractiveness of the face and the components. The data were also stratified by gender to see whether the correlations in attractiveness of the smiling face and the components were the same in men and women.

Results

Intraobserver agreement was good with ICC values between 0.82 and 0.92. Descriptive statistics (mean, standard deviation, and range), as well as the results of the Shapiro-Wilk test for the total sample and by gender are presented in Table I . Normal distribution was verified for the attractiveness of the smiling face and the components evaluated.

Table I
Descriptive statistics and Shapiro-Wilk test results for the face, smile, nose, eyes, chin, hair, eyebrows, and skin attractiveness in the total sample and by gender
Variable Mean SD Range P Mean SD Range P Mean SD Range P
Men and women (n = 60) Men (n = 30) Women (n = 30)
Face 32.3 10.7 11.6-55.1 0.4 35.7 9.1 17.1-50.5 0.6 29.0 11.4 11.6-55.1 0.2
Smile 33.4 14.1 7.4-73.3 0.4 33.1 12.6 11.0-61.1 0.8 33.7 15.6 7.4-73.3 0.5
Nose 38.8 11.4 18.8-66.6 0.2 38.2 10.2 22.6-61.1 0.1 39.4 12.6 18.8-66.6 0.8
Eyes 53.7 13.9 25.3-77.8 0.2 50.8 13.6 25.3-77.7 0.9 56.6 13.7 29.3-77.1 0.2
Chin 34.6 12.5 12.6-57.3 0.1 38.1 12.5 17.3-57.3 0.1 31.1 11.6 12.6-54.8 0.3
Hair 46.0 11.1 20.9-68.9 0.6 44.1 11.6 20.9-68.9 0.6 47.9 10.4 25.8-64.9 0.6
Eyebrows 43.2 10.6 23.3-72.1 0.7 38.5 9.3 23.3-60.0 0.5 47.9 9.9 30.1-72.1 0.9
Skin 47.1 9.8 25.4-64.3 0.1 46.4 11.6 25.4-64.3 0.1 47.9 7.7 31.8-61.0 0.4
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Jan 7, 2020 | Posted by in Orthodontics | Comments Off on Contribution of facial components to the attractiveness of the smiling face in male and female patients: A cross-sectional correlation study
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