Background/Purpose: The steps to fully understand the nature of data (e.g. variability, shape, skewness, outlier, etc.)especially among socially disadvantaged groups, and assumptions check leading to specific statistical tests or measurement methods employed are essential, for making appropriate scientific inferences. Unfortunately, these imperative steps are often ignored in research practices and reported studies. The purpose of this study was to examine the data characteristics of several commonly used health, fitness and physical activity measures by using the entire population and selected subpopulations of a national health survey data set. Methods: A set of selected physical activity and fitness measures, including BMI, HDL, LDL, total cholesterol, Triglyceride, walking/biking, home/yard activities, and muscle strengthening activities from the 2005-2006 National Health and Nutrition Examination Survey (NHANES) data set (N = 3,352, 1,658 males & 1,694 females; mean age = 37.80 ± 21.8 years old) was employed for the study. The data characteristics (e.g., variability, shape, skewness, outliers, normality etc.) of these measures were examined using both descriptive statistics and histograms and Q-Q plots (gender, age [less than 18 years, 18-44 years, 45-64 years and more than 64 years old], and ethnics group [Mexican-American, Other Hispanic, Non-Hispanic White, Non-Hispanic Black and Other races]). Analysis/Results: Most of the measures were shown to be positively skewed, violating the assumption of normality (skew statistics BMI= 1.835 ± .043, HDL cholesterol= 1.233 ± .044, Triglyceride= 4.864 ± .044, Number of times engaged in walking/biking activity in last 30 days= 5.725 ± .073, Time engaged in walking/biking per session [minutes]= 3.637 ± .073, Number of times engaged in home/yard activities in last 30 days= 1.508 ± .046, Time home/yard activity per session [minutes]= 2.661 ± .060, Moderate activity last 30 days= 1.934 ± .042, Time engaged in muscle strengthening activity per day [minutes]= 3.165 ± .071). Furthermore, when data were analyzed by subgroups, a different data characteristic was found in some of these measures, (e.g., males illustrated a much larger skewness in BMI [skew statistics= 2.745 ± .061] than their female counterparts [1.065 ± .060]). Conclusions These findings further highlighted the importance of checking data characteristics of variables studied and assumptions related to statistical tests employed, especially for certain subpopulations. Keyword(s): exercise/fitness/physical activity, measurement/evaluation, research