Validation of digital photographic reference scales for evaluating facial aging signs

2017 ◽  
Vol 24 (2) ◽  
pp. 196-202 ◽  
Author(s):  
Randa Jdid ◽  
Julie Latreille ◽  
Frédérique Soppelsa ◽  
Erwin Tschachler ◽  
Frédérique Morizot
Keyword(s):  
Facial Aging

Smoking status and attractiveness among identical twins discordant for smoking

2017 ◽  
Author(s):  
Andy Skinner ◽  
Andy ◽  
Ian Penton-Voak ◽  
Marcus Robert Munafo
Keyword(s):  
Behaviour Change ◽  
Smoking Status ◽  
Smoking Behaviour ◽  
Identical Twins ◽  
Facial Appearance ◽  
Same Sex ◽  
Facial Aging ◽  
Male And Female ◽  
Separate Sample ◽  
Behaviour Change Interventions

Background and aims: Smoking is associated with negative health of skin and increased signs of facial aging. We aimed to address two questions about smoking and appearance: 1) how does smoking affect the attractiveness of faces, and 2) does facial appearance alone provide an indication of smoking status?Methods: Faces of identical twins discordant for smoking were averaged to make male and female smoking and non-smoking prototypes faces. In Task 1, we presented same sex smoking and non-smoking prototypes side-by-side and participants (n=590) indicated which face was more attractive. Participants were blind to prototype smoking status. In Task 2 a separate sample (n=580) indicated which prototype was the smoker.Results: In Task 1 both male and female participants judged non-smoking prototypes more attractive, irrespective of the sex of the prototype face. In Task 2, both male and female participants selected the smoking prototype as the smoker more often, again irrespective of the sex of the prototype face.Conclusions: Our findings provide evidence that smoking may negatively impact facial appearance, and that facial appearance alone may be sufficient to indicate smoking status. We discuss the possible use of these findings in smoking behaviour change interventions.

Facial aging and asymmetry decomposition based approaches to identification of twins

2015 ◽  
Vol 48 (12) ◽  
pp. 3843-3856 ◽  
Author(s):  
T. Hoang Ngan Le ◽  
Keshav Seshadri ◽  
Khoa Luu ◽  
Marios Savvides
Keyword(s):  
Facial Aging

scholarly journals Dynamics of human facial aging through photoanthropometric analysis and quadratic modeling from child- to adulthood – a multi-centric study

2020 ◽  
Vol 17 (1) ◽  
Author(s):  
Laíse Nascimento Correia Lima ◽  
Bianca Marques Santiago ◽  
Ademir Franco ◽  
Patrick Thevissen ◽  
Flávio De Barros Vidal ◽  
...  
Keyword(s):  
Linear Models ◽  
Data Extraction ◽  
Age Groups ◽  
Quadratic Model ◽  
Facial Growth ◽  
Linear Quadratic ◽  
Facial Aging ◽  
Morphological Alterations ◽  
Analysis System ◽  
Log Linear

This study aimed to investigate the dynamics of facial aging from photographs of individuals in different age groups and establish a pattern of facial growth. The sample consisted of digital photographs standardly taken from 1273 Brazilians aged between 2 and 24 years and equally distributed by sex into 12 specific age groups (2, 4, 6, 8, 10, 12, 14, 16, 18, 20, 22 and 24 years). SAFF-2D® (Forensic Facial Analysis System, Brazilian Federal Police, Brazil) software package was used for positioning 28 landmarks on each photograph. Two-hundred and eight measurements were established between the landmarks. Photoanthropometric Indicators (PAI) of facial morphological alterations were obtained from the relations of facial measurements with a fixed reference (diameter of the iris). Non-transformed linear, quadratic and log-linear models were tested to screen the best approach to describe the facial growth with aging in females and males. The quadratic model reached the best outcomes in females (R2 <73.2%, mean: 52.14% ± 0.15) and males (R2 <80.8%, mean: 60.87% ± 0.15). Most of the PAI (>99.04%) were statistically associated with age in females and males (p<0.05). Vertical facial alterations were the most evident over the time, especially the height of the human face (p<0.05). Data extraction and treatment performed with the photoanthropometric analysis and the quadratic statistical model described the dynamics of facial growth by tackling facial allometry.

scholarly journals Crowd-Sourced Reliability of an Assessment of Lower Facial Aging Using a Validated Visual Scale

2021 ◽  
Vol 9 (1) ◽  
pp. e3315
Author(s):  
Jason D. Kelly ◽  
Bryan Comstock ◽  
Timothy M. Kowalewski ◽  
James M. Smartt
Keyword(s):  
Facial Aging ◽  
Visual Scale

scholarly journals MR-pheWAS with stratification and interaction: Searching for the causal effects of smoking heaviness identified an effect on facial aging

2018 ◽  
Author(s):  
Louise A C Millard ◽  
Marcus R Munafò ◽  
Kate Tilling ◽  
Robyn E Wootton ◽  
George Davey Smith
Keyword(s):  
Lung Function ◽  
Detrimental Effect ◽  
Genetic Variant ◽  
Mendelian Randomization ◽  
Association Studies ◽  
Causal Effects ◽  
Uk Biobank ◽  
Facial Aging ◽  
Heavy Smoking ◽  
Never Smokers

AbstractMendelian randomization (MR) is an established approach for estimating the causal effect of an environmental exposure on a downstream outcome. The gene x environment (GxE) study design can be used within an MR framework to determine whether MR estimates may be biased if the genetic instrument affects the outcome through pathways other than via the exposure of interest (known as horizontal pleiotropy). MR phenome-wide association studies (MR-pheWAS) search for the effects of an exposure, and a recently published tool (PHESANT) means that it is now possible to do this comprehensively, across thousands of traits in UK Biobank. In this study, we introduce the GxE MR-pheWAS approach, and search for the causal effects of smoking heaviness – stratifying on smoking status (ever versus never) – as an exemplar. If a genetic variant is associated with smoking heaviness (but not smoking initiation), and this variant affects an outcome (at least partially) via tobacco intake, we would expect the effect of the variant on the outcome to differ in ever versus never smokers. If this effect is entirely mediated by tobacco intake, we would expect to see an effect in ever smokers but not never smokers. We used PHESANT to search for the causal effects of smoking heaviness, instrumented by genetic variant rs16969968, among never and ever smokers respectively, in UK Biobank. We ranked results by: 1) strength of effect of rs16969968 among ever smokers, and 2) strength of interaction between ever and never smokers. We replicated previously established causal effects of smoking heaviness, including a detrimental effect on lung function and pulse rate. Novel results included a detrimental effect of heavier smoking on facial aging. We have demonstrated how GxE MR-pheWAS can be used to identify causal effects of an exposure, while simultaneously assessing the extent that results may be biased by horizontal pleiotropy.Author summaryMendelian randomization uses genetic variants associated with an exposure to investigate causality. For instance, a genetic variant that relates to how heavily a person smokes has been used to test whether smoking causally affects health outcomes. Mendelian randomization is biased if the genetic variant also affects the outcome via other pathways. We exploit additional information – that the effect of heavy smoking only occurs in people who actually smoke – to overcome this problem. By testing associations in ever and never smokers separately we can assess whether the genetic variant affects an outcome via smoking or another pathway. If the effect is entirely via smoking heaviness, we would expect to see an effect in ever but not never smokers, and this would suggest that smoking causally influences the outcome. Previous Mendelian randomization studies of smoking heaviness focused on specific outcomes – here we searched for the causal effects of smoking heaviness across over 18,000 traits. We identified previously established effects (e.g. a detrimental effect on lung function) and novel results including a detrimental effect of heavier smoking on facial aging. Our approach can be used to search for the causal effects of other exposures, where the exposure only occurs in known subsets of the population.

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