Facial Shape Analysis Identifies Valid Cues to Aspects of Physiological Health in Caucasian, Asian, and African Populations

Cheeks appearance as a novel predictor of obstructive sleep apnea: the CASA score study

STUDY OBJECTIVES

Four well-established predictors of obstructive sleep apnea (OSA) risk are body mass index, age, sex, and neck circumference. We have previously reported cheeks appearance as an OSA predictor, which may represent a combination of such predictors in a single, readily available feature. This study sought to answer the question: Is cheeks appearance an OSA risk predictor?

METHODS

This was a prospective cross-sectional diagnostic accuracy study based on STARD (standards for reporting diagnostic accuracy studies). Patients undergoing polysomnography to investigate sleep complaints at a sleep clinic affiliated with a university hospital were assessed using cheeks appearance scored 0-3 for volume and 0-3 for flaccidity to create the Cheeks Appearance for Sleep Apnea (CASA) score ranging from 0 to 6. Appearance was judged by 3 blinded and independent evaluators.

RESULTS

Among 265 patients evaluated, 248 were included. Fifty-seven patients had a CASA score of 0 and 191 had a CASA score between 1 and 6. Polysomnography diagnosed 177 of the individuals with OSA; of these, 167 had an altered CASA score. Sensitivity was 87%, specificity was 82%, positive-predictive value was 94%, negative-predictive value was 66%, and accuracy was 86%.

CONCLUSIONS

Our results suggest that combining volume and flaccidity of cheeks appearance in a single index may constitute a reliable OSA predictor. CASA score is a novel predictor of OSA with internal validity in a sleep laboratory adult population. Our findings support further studies to confirm the external validity of this practical diagnostic tool.

CLINICAL TRIAL REGISTRATION

Registry: ClinicalTrials.gov; Name: Cheeks Appearance as a Novel Predictor of Obstructive Sleep Apnea: The CASA Score Study (CASA); URL: https://clinicaltrials.gov/study/NCT04980586; Identifier: NCT04980586.

CITATION

Prikladnicki A, Gomes E, Sousa LCCR, Gonçalves SC, Martinez D. Cheeks appearance as a novel predictor of obstructive sleep apnea: the CASA score study. J Clin Sleep Med. 2024;20(6):879-885.

Frailty assessment using photographs in patients undergoing transcatheter aortic valve replacement

BACKGROUND

When frailty is considered in patient selection, better outcomes are achieved in transcatheter aortic valve replacement (TAVR) procedures. This study investigated whether patient photographs could be utilized to qualitatively assess patient frailty and independently predict poor outcomes following TAVR.

METHODS

This study included 1345 patients with severe aortic stenosis who underwent TAVR at the Sakakibara Heart Institute, Japan, between 2013 and 2022. Patient photographs were taken prior to the initial outpatient clinic examination or at discharge in case the patient's first visit was unplanned admission. Frailty was assessed from patient photographs using a four-point photographic frailty scale; 1 (non-frail), 2 (vulnerable), 3 (mild frail), and 4 (frail). Photographic frailty scale of 3 and 4 were defined as high. The primary endpoint was all-cause mortality following TAVR.

RESULTS

Seven hundred ninety-six patients who had their facial photographs taken within six months before the TAVR procedure were analyzed. Patients with a higher photographic frailty scale belonged to New York Heart Association classes III/IV, and had higher Society of Thoracic Surgeons scores, higher incidence of wheelchair usage, lower hemoglobin, and smaller aortic valve areas. According to the frailty assessment, patients with a higher photographic frailty scale exhibited slower performance in the 5-m walk test, reduced hand grip strength, more severe dementia, had a higher clinical frailty scale, and lower serum albumin level. Multivariable Cox regression analysis revealed that the high photographic frailty scale was independently associated with all-cause mortality (adjusted hazard ratio 1.62, 95 % confidence interval 1.12-2.33, p = 0.010). Kaplan-Meier analysis indicated that patients with high photographic frailty scale had higher all-cause mortality rates compared to those with low scale (log-rank p = 0.011).

CONCLUSIONS

Patient registration photographs can be used to obtain qualitative assessments of frailty in severe aortic stenosis cases, and such assessments can independently predict poor outcomes following TAVR.

Using Generative Artificial Intelligence Tools in Cosmetic Surgery: A Study on Rhinoplasty, Facelifts, and Blepharoplasty Procedures

Artificial intelligence (AI), notably Generative Adversarial Networks, has the potential to transform medical and patient education. Leveraging GANs in medical fields, especially cosmetic surgery, provides a plethora of benefits, including upholding patient confidentiality, ensuring broad exposure to diverse patient scenarios, and democratizing medical education. This study investigated the capacity of AI models, DALL-E 2, Midjourney, and Blue Willow, to generate realistic images pertinent to cosmetic surgery. We combined the generative powers of ChatGPT-4 and Google's BARD with these GANs to produce images of various noses, faces, and eyelids. Four board-certified plastic surgeons evaluated the generated images, eliminating the need for real patient photographs. Notably, generated images predominantly showcased female faces with lighter skin tones, lacking representation of males, older women, and those with a body mass index above 20. The integration of AI in cosmetic surgery offers enhanced patient education and training but demands careful and ethical incorporation to ensure comprehensive representation and uphold medical standards.

Influence of the nutritional status on facial morphology in young Japanese women

Evidence regarding the possible influence of nutritional status on the facial morphology has thus far been insufficient. We examined whether or not the physical body compositions and dietary behaviors were correlated with any morphological characteristics of the face. One hundred and fifteen young Japanese women participated. Variables representing the dietary behaviors were extracted from self-reported survey data, and corresponding three-dimensional (3D) facial images and body compositions were examined. Multivariate analyses identified significant relationships between the nutritional status and facial topography (p < 0.05). The clustering method revealed the existence of three dietary condition patterns ("balanced diet", "high-calorie-diet" with obesity tendency, and "imbalanced low-calorie-diet" with sarcopenic obesity tendency). Among these three patterns, a round face (increased facial width; analysis of variance [ANOVA], p < 0.05) was observed in the high-calorie-diet pattern, while the imbalanced low-calorie-diet pattern showed a more masculine face (increased face height, decreased eye height, increased non-allometric sexual shape differences; ANOVA, p < 0.05), thus suggesting the possibility of sex-hormonal influences. In summary, the body composition and dietary behaviors were found to influence the facial morphology, and potential biological influences were discussed.

Use of Facial Morphology to Determine Nutritional Status in Older Adults: Opportunities and Challenges

Undiagnosed malnutrition is a significant problem in high-income countries, which can reduce the quality of life of many individuals, particularly of older adults. Moreover, it can also inflate the costs of existing health care systems because of the many metabolic complications that it can cause. The current methods for assessing malnutrition can be cumbersome. A trained practitioner must be present to conduct an assessment, or patients must travel to facilities with specialized equipment to obtain their measurements. Therefore, digital health care is a possible way of closing this gap as it is rapidly gaining traction as a scalable means of improving efficiency in the health care system. It allows for the remote monitoring of nutritional status without requiring the physical presence of practitioners or the use of advanced medical equipment. As such, there is an increasing interest in expanding the range of digital applications to facilitate remote monitoring and management of health issues. In this study, we discuss the feasibility of a novel digital remote method for diagnosing malnutrition using facial morphometrics. Many malnutrition screening assessments include subjective assessments of the head and the face. Facial appearance is often used by clinicians as the first point of qualitative indication of health status. Hence, there may be merit in quantifying these subtle but observable changes using facial morphometrics. Modern advancements in artificial intelligence, data science, sensors, and computing technologies allow facial features to be accurately digitized, which could potentially allow these previously intuitive assessments to be quantified. This study aims to stimulate further discussion and discourse on how this emerging technology can be used to provide real-time access to nutritional status. The use of facial morphometrics extends the use of currently available technology and may provide a scalable, easily deployable solution for nutritional status to be monitored in real time. This will enable clinicians and dietitians to keep track of patients remotely and provide the necessary intervention measures as required, as well as providing health care institutions and policy makers with essential information that can be used to inform and enable targeted public health approaches within affected populations.

A survey of U.S. public perspectives on facial recognition technology and facial imaging data practices in health and research contexts

Facial imaging and facial recognition technologies, now common in our daily lives, also are increasingly incorporated into health care processes, enabling touch-free appointment check-in, matching patients accurately, and assisting with the diagnosis of certain medical conditions. The use, sharing, and storage of facial data is expected to expand in coming years, yet little is documented about the perspectives of patients and participants regarding these uses. We developed a pair of surveys to gather public perspectives on uses of facial images and facial recognition technologies in healthcare and in health-related research in the United States. We used Qualtrics Panels to collect responses from general public respondents using two complementary and overlapping survey instruments; one focused on six types of biometrics (including facial images and DNA) and their uses in a wide range of societal contexts (including healthcare and research) and the other focused on facial imaging, facial recognition technology, and related data practices in health and research contexts specifically. We collected responses from a diverse group of 4,048 adults in the United States (2,038 and 2,010, from each survey respectively). A majority of respondents (55.5%) indicated they were equally worried about the privacy of medical records, DNA, and facial images collected for precision health research. A vignette was used to gauge willingness to participate in a hypothetical precision health study, with respondents split as willing to (39.6%), unwilling to (30.1%), and unsure about (30.3%) participating. Nearly one-quarter of respondents (24.8%) reported they would prefer to opt out of the DNA component of a study, and 22.0% reported they would prefer to opt out of both the DNA and facial imaging component of the study. Few indicated willingness to pay a fee to opt-out of the collection of their research data. Finally, respondents were offered options for ideal governance design of their data, as "open science"; "gated science"; and "closed science." No option elicited a majority response. Our findings indicate that while a majority of research participants might be comfortable with facial images and facial recognition technologies in healthcare and health-related research, a significant fraction expressed concern for the privacy of their own face-based data, similar to the privacy concerns of DNA data and medical records. A nuanced approach to uses of face-based data in healthcare and health-related research is needed, taking into consideration storage protection plans and the contexts of use.

Using Facial Recognition Tools for Health Assessment

The number of applications for facial recognition technology is increasing due to the improvement in image quality, artificial intelligence, and computer processing power that has occurred during the last decades. Algorithms can be used to convert facial anthropometric landmarks into a computer representation, which can be used to help identify nonverbal information about an individual's health status. This article discusses the potential ways a facial recognition tool can perform a health assessment. Because facial attributes may be considered biometric data, clinicians should be informed about the clinical, ethical, and legal issues associated with its use.

Association of Craniofacial and Upper Airway Morphology with Cardiovascular Risk in Adults with OSA

BACKGROUND AND OBJECTIVE

Clinical and population-based studies have demonstrated a strong association between obstructive sleep apnea (OSA) and cardiovascular disease (CVD). Anatomical abnormalities of the craniofacial region and upper airway are important risk factors for OSA. The objective of this study was to investigate the association of craniofacial and upper airway morphology with CVD risk biomarkers.

METHODS

One hundred and sixty-nine male patients with OSA underwent in-laboratory polysomnography (PSG) and upper airway computed tomography (CT) scanning. Ten-year Framingham CVD risk score (FRS) was calculated and categorized into low- and moderate-to-high-risk groups. N-terminal pro B-type natriuretic peptide (NT-proBNP) was measured as a biomarker of increased myocardial wall stress.

RESULTS

Compared to the low-risk group, total sleep time (TST), the proportion of N3 (N3%) and mean oxygen saturation (SpO2mean) were lower, while the arousal index of non-rapid eye movement (NREM) sleep, apnea index (AI) of NREM sleep, apnea hypopnea index (AHI) of NREM sleep, oxygen desaturation index (ODI) and percentage of total sleep time spent with oxyhemoglobin saturation below 90% (TST90) were higher in the moderate-to-high risk group. The corrected upper airway length (UAL), ANB angle and gonion-gnathion-hyoid angle were larger for subjects in the moderate-to-high risk group than those in the low-risk group. In multiple regression analysis, TST, AINREM and adjusted UAL were independently associated with moderate-to-high CVD risk. Plasma NT-proBNP levels were higher in patients in the moderate- to high-risk group, and among the PSG and CT scan parameters, only SPO2mean was marginally associated with NT-proBNP (r=0.183, P=0.054).

CONCLUSION

Craniofacial and upper airway features may contain valid cues about CVD risk, and sleep duration, obstructive event type and occurrence phase may be closely related to CVD risk for patients with OSA.

Changes in Computer-Analyzed Facial Expressions with Age

Facial expressions are well known to change with age, but the quantitative properties of facial aging remain unclear. In the present study, we investigated the differences in the intensity of facial expressions between older (n = 56) and younger adults (n = 113). In laboratory experiments, the posed facial expressions of the participants were obtained based on six basic emotions and neutral facial expression stimuli, and the intensities of their faces were analyzed using a computer vision tool, OpenFace software. Our results showed that the older adults expressed strong expressions for some negative emotions and neutral faces. Furthermore, when making facial expressions, older adults used more face muscles than younger adults across the emotions. These results may help to understand the characteristics of facial expressions in aging and can provide empirical evidence for other fields regarding facial recognition.

E-perceptions and Business 'Mating': The Communication Effects of the Relative Width of Males' Faces in Business Portraits

This study investigates the relative impacts of the facial width-to-height ratio (fWHR) on the first impressions business professionals form of business consultants when seeing their photographs on a corporate website or LinkedIn page. By applying conjoint analysis on field experiment data (n = 381), we find that in a zero-acquaintance situation business professionals prefer low-fWHR business consultants. This implies that they prefer a face that communicates trustworthiness to one that communicates success. Further, we have investigated the words that business professionals use to describe their preferred consultant. These approach motivations help practitioners to improve the picture-text alignment. The results underline the necessity to critically assess the pictures and text used on websites and media platforms such as LinkedIn for business purposes, and to see them as a key element of business and self-communication that can be altered in order to improve business 'mating.'

Using Facial Recognition Tools for Health Assessment

The number of applications for facial recognition technology is increasing due to the improvement in image quality, artificial intelligence, and computer processing power that has occurred during the last decades. Algorithms can be used to convert facial anthropometric landmarks into a computer representation, which can be used to help identify nonverbal information about an individual's health status. This article discusses the potential ways a facial recognition tool can perform a health assessment. Because facial attributes may be considered biometric data, clinicians should be informed about the clinical, ethical, and legal issues associated with its use.

Feasibility of using deep learning to detect coronary artery disease based on facial photo

Aims

Facial features were associated with increased risk of coronary artery disease (CAD). We developed and validated a deep learning algorithm for detecting CAD based on facial photos.

Methods and results

We conducted a multicentre cross-sectional study of patients undergoing coronary angiography or computed tomography angiography at nine Chinese sites to train and validate a deep convolutional neural network for the detection of CAD (at least one ≥50% stenosis) from patient facial photos. Between July 2017 and March 2019, 5796 patients from eight sites were consecutively enrolled and randomly divided into training (90%, n = 5216) and validation (10%, n = 580) groups for algorithm development. Between April 2019 and July 2019, 1013 patients from nine sites were enrolled in test group for algorithm test. Sensitivity, specificity, and area under the receiver operating characteristic curve (AUC) were calculated using radiologist diagnosis as the reference standard. Using an operating cut point with high sensitivity, the CAD detection algorithm had sensitivity of 0.80 and specificity of 0.54 in the test group; the AUC was 0.730 (95% confidence interval, 0.699–0.761). The AUC for the algorithm was higher than that for the Diamond–Forrester model (0.730 vs. 0.623, P &lt; 0.001) and the CAD consortium clinical score (0.730 vs. 0.652, P &lt; 0.001).

Conclusion

Our results suggested that a deep learning algorithm based on facial photos can assist in CAD detection in this Chinese cohort. This technique may hold promise for pre-test CAD probability assessment in outpatient clinics or CAD screening in community. Further studies to develop a clinical available tool are warranted.

Do adipokines levels influence facial attractiveness of young women?

OBJECTIVES

Facial attractiveness is thought to reflect an individual's biological condition. This seems to be largely explained by the relationship between facial appearance and body adiposity, a trait that affects various aspects of body homeostasis, including fertility and immunity. The aim of this study was to test if, a part of adipose tissue amount, also levels of hormones secreted by adipose tissue are reflected in women's appearance, focusing on the two most abundant adipokines. Due to the opposing effects of adiponectin and leptin on health, we hypothesized that leptin negatively and adiponectin positively correlate with women's attractiveness.

METHODS

The study sample included 174 young, healthy women (M_age = 28.50, SD_age = 2.38). Serum leptin and adiponectin levels were measured. Estradiol (E2), testosterone (T), and BMI levels were controlled in the analyses. Face photographs were taken and facial attractiveness ratings, assessed by men, were gathered in online questionnaires.

RESULTS

Perceived facial attractiveness correlated negatively with leptin level and leptin/adiponectin ratio, but did not correlate with adiponectin level. The results were similar, when controlled for E2, T, and BMI. Adipokines levels did not mediate or moderate the relationship between facial attractiveness and BMI.

CONCLUSIONS

The results showed that perceived facial attractiveness is predicted by adipose-derived hormones detrimental for health, like leptin, but is not related with beneficial hormones, such as adiponectin. However, the levels of these two adipokines do not impact the relationship between perceived facial attractiveness and adiposity, and thus do not explain the relationship between facial attractiveness, body adiposity, and biological condition.

Identification of the Facial Features of Patients With Cancer: A Deep Learning-Based Pilot Study

BACKGROUND

Cancer has become the second leading cause of death globally. Most cancer cases are due to genetic mutations, which affect metabolism and result in facial changes.

OBJECTIVE

In this study, we aimed to identify the facial features of patients with cancer using the deep learning technique.

METHODS

Images of faces of patients with cancer were collected to build the cancer face image data set. A face image data set of people without cancer was built by randomly selecting images from the publicly available MegaAge data set according to the sex and age distribution of the cancer face image data set. Each face image was preprocessed to obtain an upright centered face chip, following which the background was filtered out to exclude the effects of nonrelative factors. A residual neural network was constructed to classify cancer and noncancer cases. Transfer learning, minibatches, few epochs, L2 regulation, and random dropout training strategies were used to prevent overfitting. Moreover, guided gradient-weighted class activation mapping was used to reveal the relevant features.

RESULTS

A total of 8124 face images of patients with cancer (men: n=3851, 47.4%; women: n=4273, 52.6%) were collected from January 2018 to January 2019. The ages of the patients ranged from 1 year to 70 years (median age 52 years). The average faces of both male and female patients with cancer displayed more obvious facial adiposity than the average faces of people without cancer, which was supported by a landmark comparison. When testing the data set, the training process was terminated after 5 epochs. The area under the receiver operating characteristic curve was 0.94, and the accuracy rate was 0.82. The main relative feature of cancer cases was facial skin, while the relative features of noncancer cases were extracted from the complementary face region.

CONCLUSIONS

In this study, we built a face data set of patients with cancer and constructed a deep learning model to classify the faces of people with and those without cancer. We found that facial skin and adiposity were closely related to the presence of cancer.

The Face of Early Cognitive Decline? Shape and Asymmetry Predict Choice Reaction Time Independent of Age, Diet or Exercise

Slower reaction time is a measure of cognitive decline and can occur as early as 24 years of age. We are interested if developmental stability predicts cognitive performance independent of age and lifestyle (e.g., diet and exercise). Developmental stability is the latent capacity to buffer ontogenetic stressors and is measured by low fluctuating asymmetry (FA). FA is random—with respect to the largest side—departures from perfect morphological symmetry. The degree of asymmetry has been associated with physical fitness, morbidity, and mortality in many species, including humans. We expected that low FA (independent of age, diet and exercise) will predict faster choice reaction time (i.e., correct keyboard responses to stimuli appearing in a random location on a computer monitor). Eighty-eight university students self-reported their fish product consumption, exercise, had their faces 3D scanned and cognitive performance measured. Unexpectedly, increased fish product consumption was associated with worsened choice reaction time. Facial asymmetry and multiple face shape variation parameters predicted slower choice reaction time independent of sex, age, diet or exercise. Future work should develop longitudinal interventions to minimize early cognitive decline among vulnerable people (e.g., those who have experienced ontogenetic stressors affecting optimal neurocognitive development).

The Esthetic Difference of Chinese Beauty Evaluated by Two Different Human Races Based on Three-Dimensional Average Face Analysis

Supplemental Digital Content is available in the text

Purpose:

The aim of this study was to establish a new method of facial soft tissue analysis based on 3dMDface system and to find the different esthetic preferences of Chinese beauties from the Chinese and Indian evaluators perspective.

Methods:

Three-dimensional facial images of 242 females and 168 males were evaluated and ranked by 8 Chinese and nine Indians using a 10-point visual analog scale (VAS). Total 120 subjects in 2 panels (from Chinese perspective and Indian perspective) including 30 male and 30 female faces with top 30 scores were analyzed with the “average face” method respectively. Then 17 linear measurements, 13 curve measurements and 14 ratios of 4 average faces were calculated and compared with the divine proportion.

Results:

Distinct differences were founded based on the average face analysis. Similar total facial types were preferred by both Chinese and Indian evaluators, while Indian evaluators preferred a wider male face with a protrusive lower lip. Delicate noses with lower nose ridge but protrusive lower lips in females were more acceptable by Indian evaluators. The differences of linear measurements were limited in 2.0 mm except the facial width, lower facial width, upper facial height and forehead height while curve measurements differ distinctly as the table shows. No ratios equal to the divine proportion were founded.

Conclusion:

The 3D Average face based on stereophotogrammetry is a feasible method to analyze the facial characters and discrepancy of esthetic preferences. Chinese and Indian evaluators have some certain differences when judging beauties. Attractive faces have some certain ratios but not the divine proportion.

Skin Color Preferences in a Malaysian Chinese Population

Facial skin color influences the perceived health and attractiveness of Caucasian faces, and has been proposed as a valid cue to aspects of physiological health. Similar preferences for skin color have previously been found in African participants, while different preferences have been found among mainland Chinese participants. Here, we asked Malaysian Chinese participants (ethnic Chinese living in an Asian country with high levels of exposure to Western culture) to manipulate the skin color of Malaysian Chinese, Caucasian, and African faces to make them “look as healthy as possible.” Participants chose to increase skin yellowness to a greater extent than to increase skin redness to optimize healthy appearance. The slight reduction in skin lightness chosen was not statistically significant after correction for multiple comparisons. While broadly in line with the preferences of Caucasian and African participants from previous studies, this differs from mainland Chinese participants. There may be a role for culture in skin color preferences, though methodological differences mean that further research is necessary to identify the cause of these differences in preferences.

What Are Important Ethical Implications of Using Facial Recognition Technology in Health Care?

Applications of facial recognition technology (FRT) in health care settings have been developed to identify and monitor patients as well as to diagnose genetic, medical, and behavioral conditions. The use of FRT in health care suggests the importance of informed consent, data input and analysis quality, effective communication about incidental findings, and potential influence on patient-clinician relationships. Privacy and data protection are thought to present challenges for the use of FRT for health applications.

Facial Adiposity, Attractiveness, and Health: A Review

The relationship between facial cues and perceptions of health and attractiveness in others plays an influential role in our social interactions and mating behaviors. Several facial cues have historically been investigated in this regard, with facial adiposity being the newest addition. Evidence is mounting that a robust link exists between facial adiposity and attractiveness, as well as perceived health. Facial adiposity has also been linked to various health outcomes such as cardiovascular disease, respiratory disease, blood pressure, immune function, diabetes, arthritis, oxidative stress, hormones, and mental health. Though recent advances in the analysis of facial morphology has led to significant strides in the description and quantification of facial cues, it is becoming increasingly clear that there is a great deal of nuance in the way that humans use and integrate facial cues to form coherent social or health judgments of others. This paper serves as a review of the current literature on the relationship between facial adiposity, attractiveness, and health. A key component in utilizing facial adiposity as a cue to health and attractiveness perceptions is that people need to be able to estimate body mass from facial cues. To estimate the strength of the relationship between perceived facial adiposity and body mass, a meta-analysis was conducted on studies that quantified the relationship between perceived facial adiposity and BMI/percentage body fat. Summary effect size estimates indicate that participants could reliably estimate BMI from facial cues alone (r = 0.71, n = 458).

The Relative Contribution of Jawbone and Cheekbone Prominence, Eyebrow Thickness, Eye Size, and Face Length to Evaluations of Facial Masculinity and Attractiveness: A Conjoint Data-Driven Approach

Recent work demonstrates the methodological rigor of a type of data-driven analysis (i.e., conjoint analysis; CA), which accounts for the relative contribution of different facial morphological cues to interpersonal perceptions of romantic partner quality. This study extends this literature by using a conjoint face ranking task to predict the relative contribution of five sexually dimorphic facial shape features (jawbone and cheekbone prominence, eyebrow thickness, eye size, face length) to participants’ (N = 922) perceptions of facial attractiveness and sex-typicality (i.e., masculinity/femininity). For overall partner attractiveness, eyebrow thickness and jawbone prominence were relatively more salient than cheekbone prominence and eye size. Interestingly, masculinized (i.e., thicker) eyebrows were marginally more attractive for female than male faces, particularly within a long-term mating context. Masculinized jawbone prominence was more attractive for male than female faces, and feminized jawbone prominence was more attractive for female than male faces. For perceptions of masculinity, eyebrow thickness, jawbone prominence, and facial height were relatively more salient than cheekbone prominence and eye size, although facial height was more important for female than male faces, and jawbone prominence was marginally more important for male than female faces. These findings highlight the prominence of eyebrows, the jawline, and facial height during perception of facial attractiveness and masculinity – though it should be noted that many of these differences were small to moderate in effect size. Findings are interpreted in the context of prior research, and future directions for studying why these facial traits exhibit superior signaling capacity are discussed.