Graduation Year


Document Type




Degree Name

Master of Science (M.S.)

Degree Granting Department

Public Health

Major Professor

Thomas E. Bernard, Ph.D., PE

Committee Member

Rene Salazar, Ph.D., CIH

Committee Member

Yehia Hammad, Sc.D Ph.D.


HSA, dermal, occupational, exposure assessment, skin, industrial hygiene


Recent occupational health studies have focused on dermal exposure at the hands, but have been unable to accurately express dose without knowing the HSA. There is no standard method to calculate HSA, though some researchers have derived HSA formulas based on dimensions from a Taiwanese population. This research paper describes a shortcut method to estimate the hand surface area (HSA) of a human hand from a two-dimensional hand tracing, and repeated a Taiwanese HSA study in order to explore the viability of its HSA formula in an American university population. A sample of nine adult men and nine adult women, each representing one third of the population percentile in hand length and hand breadth, were selected from a population within the University of South Florida in Tampa, FL. Hand length, breadth, a 2D hand tracing and a 3D light hand scan were collected from each participant. A linear regression was used to analyze the data sets and found a correlation (R=0.94) between 2D HSA and 3D HSA and slope of 2.6 (SD=0.2), with a regression equation of Y=2.6(X). A paired t-test was used to compare the Taiwanese HSA formula data against the 3D HSA. Results found that the Taiwanese data sets were significantly different from the 3D HSA (p<0.001), averaging 57 cm2 less than the 3D HSA. A jackknife analysis was implemented on the 2D HSA hand tracing data, and a paired t-test was performed between the jackknife estimate predictions and 3D HSA. Mean differences were not significantly different (p=0.97), with 0.87 cm2 difference between means. Results indicate that the USF Hand Tracing Method will provide a better estimate of HSA than the Taiwanese method, and can be used as a tool in HSA estimation.