Browsing by Author "Brown, Elise"

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    The impact of different high-intensity interval training protocols on body composition and physical fitness in healthy young adult females
    (2018-12-28) Brown, Elise; Hew-Butler, Tamara; Marks, Charles R.C.; Butcher, Scotty J.; Choi, Myung D.
    Although traditional high-intensity interval training (HIIT) has been effective in improving body composition and physical fitness, it is unclear how multimodal HIIT affects these variables. This study compared the differences between these two training programs on body composition and physical fitness in apparently healthy, nonobese young adult females. A total of 16 participants (mean age = 23 ± 5.08 years) completed a 12-week HIIT intervention with two treatment groups: rowing and multimodal. Immediately before and after the intervention, the following measures were assessed: body mass index (BMI), total body mass, waist circumference, waist-to-height ratio, total body fat %, visceral adipose tissue, lean mass, bone mineral outcomes, cardiovascular fitness, and muscular fitness. A general linear model with repeated measures was used to assess changes over time for the group as a whole, as well as between-group differences. For the group as a whole, there were significant decrease in total body fat % (p = 0.04) and significant increases in BMI (p = 0.015), total body mass (p = 0.003), lean mass (p < 0.001), bone mineral content (BMC) (p < 0.001), VO2max (p = 0.01), broad jump (p = 0.001), squat endurance (p = 0.006), press (p < 0.001), back squat (p < 0.001), and deadlift (p < 0.001) one repetition maximum (1RM). The multimodal group (p < 0.001) increased deadlift 1RM significantly more than the rowing group (p = 0.002). HIIT can be an effective means for improving cardiovascular and muscular fitness, increasing lean mass and BMC, and thereby improving cardiometabolic as well as musculoskeletal health in nonobese females. Using a multimodal approach may give the added benefit of superior muscular strength increases.
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    Optimal Cut-Points for Diagnostic Variables in Complex Surveys
    (2023-01-01) Madi, Samar Adnan; Drignei, Dorin; Brown, Elise; Ogunyemi, Theophilus; Perla, Subbaiah; So, Hon Yiu
    The ability to diagnose an individual is crucial in promoting treatment and improved health. However, finding a simple tool to base the diagnosis on can be complicated. This research will focus on developing statistical methodology for accurate diagnostic tests in the context of complex survey data. The proposed method will be illustrated with data from National Health and Nutrition Examination Survey (NHANES) to construct a diagnostic test to predict cardiometabolic disease risk in the US younger population. This research will begin with the exploration of a single diagnostic variable to be used as a diagnostic tool. The first 1-dimensional method explored uses receiver operating characteristic (ROC) curves for survey data as a means of determining an optimal cut-point for the diagnostic variable. This method is shown to be accurate but not conducive to multi-variable diagnostic tools using survey data. Another 1-dimensional method uses logistic regression for survey data to determine an optimal cut-point, using minimizing information criteria such as AIC to select the cut-point. The method is applied to NHANES data but considering a single diagnostic variable is shown to be too simplistic to create a comprehensive diagnostic tool. This method will then be extended to a multi-dimensional case, creating a diagnostic tool based on multiple variables using logistic regression for survey data. This method, although accurate, is shown to be time-consuming and computationally inefficient. A modified method using kriging-based optimization is proposed. Under this method, a more efficient search algorithm of efficient global optimization is explored, using a criterion of expected improvement. This proposed method is more computationally efficient in creating a multi-dimensional diagnostic tool. Application of these methods in a healthcare setting could be beneficial in promoting quick and easy diagnosis.