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Facial Cosmetic Surgery Can Makes You Look 6.4 to 7.9 Years Younger  

Summary:    This  study  aims  to  quantify  the  effectiveness  of  facial  cosmetic  surgery.    We  compared  the  perceived  age  of  patients  before  and  after  they  had  the  surgery.    Data  suggest  that  female  patients  between  the  age  of  45  and  72  looked  7.2  years  younger  on  average.    However,  there  was  no  evidence  to  support  either  patient’s  age  or  gender  determines  the  surgery’s  effectiveness.  

 

11/19/2012  

 

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Introduction  Plastic surgery is a growing business in both developed and developing countries. Facial cosmetic surgery is one of the best-known forms of plastic surgery that intents to enhance one’s appearance. Potential patients who are considering to undergo facial cosmetic surgery will be interested to know how much better or younger they will look after the surgery. This paper seeks to quantify the effectiveness of facial cosmetic surgery on patient’s appearance. First, we investigate whether there were any differences between patient’s appearance before and after the surgery. Then, we explored if patient’s age and gender had any effect on the differences.

Data  summary  A total of 60 patients underwent facial cosmetic surgery. Among them were 56 females and 4 males. The age of the patients was recorded at the time of surgery. For each patient, photos were taken prior to the surgery as well as one year after the surgery. Raters were chosen to estimate the age of the patients by viewing the photographs. Each photo was examined by 10 raters. To ensure raters assessed the photos independently, no rater observed both the pre- and post-surgery photo of the same patient. The average age given by raters for each photo was used as the perceived age.

Methods  To compare the perceived age before and after surgery for all 60 patients, we calculated the difference in perceived age by subtracting the before mean age by after mean age for each patient. A paired t-test was carried out by the TTEST procedure in SAS. Linear regressions were performed to investigate the association between the differences in perceived age and patient’s age and gender. We regressed the patient’s age, gender with and without the interaction term on the differences in perceived age. The General Linear Model procedure was used in SAS to carry out the regression. It is important to note that the differences in perceived age data need to be approximately normally distributed in order for the T-test and GLM results to be valid.

Results  The paired t-test comparing difference in perceived age before and after surgery was highly significant (p < 0.0001). The mean and standard deviation of the differences in perceived age were -6.2 years and 2.9 years. Therefore, on average, patients underwent facial cosmetic surgery looked 7.2 years younger (We need to account for the one year in between when the photos were taken). The 95% confidence interval of the mean was -6.9 to -5.4 years. In other words, we can be 95% sure that, on average, patients looked between 6.4 and 7.9 years younger. It is worth noting that we had identified one outlier in the differences data. However, removal of the outlier from the data did not yield materially different result. The results from the regressions were less interesting. With or without the interaction term, all the slope coefficients were not statistically significant (p > 0.05). Hence there was no evidence to support that patient’s age and gender

 

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played a role on outcome of the surgery. Furthermore, removal of the outlier did not produce materially different result.

Discussion  We had strong evidence to suggest that, on average, patients underwent facial cosmetic surgery looked 7.2 years younger. However, it is important to realize that the finding is limited to female patients between the age of 45 and 72 as we only had data for this age group. Future research can focus on other age groups. We need to be caution when drawing conclusion for males as the sample size was too small. Larger sample from male patients are needed to produce more convincing results. The assumption of normality in the differences data may be of concern and further statistical test such as the normal quantile (Q-Q) plot would be beneficial.