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A Statistical Analysis of the Individual Economic Impact of the DJIA, Gross Domestic Product, and Unemployment Rate on Cosmetic Surgery and Breast Reconstruction Volumes
Esther Kim, M.D., Peter Kreymerman, M.D..
Mayo Clinic Arizona, Phoenix, AZ, USA.

Goals/Purpose:
Over the past decade the U.S. economy has experienced two recessions. As per the National Bureau of Economic Research (NBER), a recession began on March 2001 and ended November 2001 and then again on December 2007 and ended June 2009. NBER considers stock market performance, Gross Domestic Product (GDP), and unemployment rate in categorizing the current U.S. economic status. The ASPS has recently begun tracking the volume of common cosmetic and reconstructive procedures through member reporting. The statistical analysis of the impact of specific economic indicators on plastic surgery volumes allows for a better understanding of future practice expectations.
Methods/Technique:
The published ASPS member only volume data, DJIA (market strength), GDP (standard of living), and unemployment rates from 1998 to 2010 were all added into a database. Linear regression was used to model the individual relationships between economic indicators and plastic surgery volumes. A correlation coefficient (“r”) was generated for each economic indicator to plastic surgery volume relationship. It is a value between -1 and 1 that expresses the strength of the linear relationship between two variables. It was generated with the formula in Figure 1.
Results/Complications:
Table 2 demonstrates the specific correlation coefficients for each economic indicator as it relates to each type of plastic surgery procedure. Body cosmetic procedures (breast augmentation, mastopexy, and abdominoplasty) have positive correlations with all economic indicators, with GDP being the strongest. Facial cosmetic procedures (blepharoplasty, facelift, and rhinoplasty) have almost no correlation to the DJIA and negative correlations with GDP and unemployment rate. Breast reconstruction has a weak negative correlation with DJIA, no correlation with GDP, and a strong positive correlation with unemployment.
Conclusion:
Body cosmetic procedures are most influenced by the GDP. As consumer spending increases more individuals are willing to pay for breast augmentation, mastopexy, and abdominoplasty. Mounting unemployment rates did not detour patients from undergoing body cosmetic procedures. Blepharoplasty, facelift, and rhinoplasty volumes drop when the GDP declines and unemployment rises, while market trends have absolutely no influence. Breast reconstruction is unique in that a decrease in the market, decrease in consumer spending, or an increase in unemployment did not lower volumes. With escalating unemployment rates the number of breast reconstruction procedures also increased. Presumably those plastic surgeons with declining cosmetic surgery volumes turn to supplementary reconstruction. These analyses are limited by only thirteen years of data, but do suggest how specific parts of the U.S. economy have distinctive influences on the volumes of different types of plastic surgery procedures.
Table 1: Correlation Coefficient Relating Economic Indicators to Plastic Surgery Volumes
DJIAGDPUnemployment
Breast Augmentation0.4590.9320.359
Mastopexy0.4760.9470.370
Abdominoplasty0.4750.8880.302
Blepharoplasty0.194-0.639-0.781
Facelift0.015-0.377-0.336
Rhinoplasty0.087-0.326-0.606
Breast Reconstruction-0.305-0.0340.558

Figure 1: Formula for Correlation Coefficient

n is the total number of samples, xi (x1, x2, ... ,xn) are the x values and yi are the y values


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