Ronald L. Hager

Body Fat Percentage of Children Varies According to Their Diet Composition

OBJECTIVE To ascertain the association between diet composition and body fat percentage in 9- and 10-year-old children. Also, to examine the influence of gender, total energy intake, fitness, physical activity, and parental body mass on the relationship between diet composition and adiposity. DESIGN Diet composition was assessed using the National Cancer Institute food frequency questionnaire, and adiposity was measured using the average of results determined using two skinfold equations. Fitness levels and physical activity were ascertained using the 1-mile run/walk test and a self-report 15-item scale, respectively. SUBJECTS A sample of 262 children (162 boys and 100 girls, mean age = 9.8 +/- 0.5 years) participated. STATISTICAL ANALYSIS Regression analysis was used to determine the extent to which diet composition contributed to adiposity without statistical control for any potentially confounding variables. Partial correlations were calculated to assess the relationship between macronutrient intake and adiposity after potential confounders (gender, total energy intake, physical fitness, and parental body mass) were controlled statistically. RESULTS Energy intake was positively related to adiposity. Fat intake, calculated as a percentage of total energy, was also positively related to adiposity, before and after control for potential confounding variables. Percentage of energy derived from carbohydrate was inversely related to adiposity, before and after controlling for potential confounders. APPLICATIONS These findings indicate that the macronutrient intake of children, particularly dietary fat and carbohydrate intake, may play a role in adiposity, independent of the influence of total energy intake, gender, physical fitness, and parental body mass index.

An Accurate VO2max Nonexercise Regression Model for 18–65-Year-Old Adults

Abstract The purpose of this study was to develop a regression equation to predict maximal oxygen uptake (VO2max) based on nonexercise (N-EX) data. All participants (N= 100), ages 18–65 years, successfully completed a maximal graded exercise test (GXT) to assess VO2max (M= 39.96 mL·kg -1· min -1 , SD = 9.54). The N-EX data collected just before the maximal GXT included the participants age; gender; body mass index (BMI); perceived functional ability (PFA) to walk, jog, or run given distances; and current physical activity (PA-R) level. Multiple linear regression generated the following N-EX prediction equation (R = .93, SEE = 3.45 mL·kg -1· min -1 , %SEE= 8.62): VO2max (mL·kg -1· min -1 ) = 48.0730 + (6.1779 x gender; women = 0, men = 1) – (0.2463 x age) – (0.6186 x BMI) + (0.7115 x PFA) + (0.6709 x PA-R). Cross validation using PRESS (predicted residual sum of squares) statistics revealed minimal shrinkage (R p = .91 and SEE p = 3.63 mL·kg -1· min -1 ); thus, this model should yield acceptable accuracy when applied to an independent sample of adults (ages 18–-65 years) with a similar cardiorespiratory fitness level. Based on standardized β-weights, the PFA variable (0.41) was the most effective at predicting VO2max followed by age (-0.34), gender (0.33), BMI (-0.27), and PA-R (0.16). This study provides a N-EX regression model that yields relatively accurate results and is a convenient way to predict VO2max in adult men and women.

An internal promoter underlies the difference in disease severity between N- and C-terminal truncation mutations of Titin in zebrafish

Truncating mutations in the giant sarcomeric protein Titin result in dilated cardiomyopathy and skeletal myopathy. The most severely affected dilated cardiomyopathy patients harbor Titin truncations in the C-terminal two-thirds of the protein, suggesting that mutation position might influence disease mechanism. Using CRISPR/Cas9 technology, we generated six zebrafish lines with Titin truncations in the N-terminal and C-terminal regions. Although all exons were constitutive, C-terminal mutations caused severe myopathy whereas N-terminal mutations demonstrated mild phenotypes. Surprisingly, neither mutation type acted as a dominant negative. Instead, we found a conserved internal promoter at the precise position where divergence in disease severity occurs, with the resulting protein product partially rescuing N-terminal truncations. In addition to its clinical implications, our work may shed light on a long-standing mystery regarding the architecture of the sarcomere. DOI: http://dx.doi.org/10.7554/eLife.09406.001

Evaluation of an Internet, Stage-Based Physical Activity Intervention

Abstract This study evaluated the effectiveness of online, stage-based materials on exercise behavior and stage of readiness to change. Participants (n=525) were assigned to a stage-based group, an action-message group, or a control group. Seven-day physical activity, occupational and leisure activity, exercise self-efficacy, and stage of readiness to change were assessed at baseline and 6 weeks. The action-message group demonstrated significant increases in leisure time activity, occupational activity, and daily energy expenditure estimated from a 7-day recall. The stage-based message group demonstrated significant increases in leisure time activity only. All three groups demonstrated small improvements in stage of readiness to change. In a 6-week, online intervention, stage-based messages were less effective than action messages.

Tennis forehand kinematics change as post-impact ball speed is altered

Peak joint angles and joint angular velocities were evaluated for varying speed forehands in an attempt to better understand what kinematic variables are most closely related to increases in post-impact ball velocity above 50% of maximal effort. High-speed video was used to measure three-dimensional motion for 12 highly skilled tennis players who performed forehands at three different post-impact ball speeds: fast (42.7 ± 3.8 m/s), medium (32.1 ± 2.9 m/s), and slow (21.4 ± 2.0 m/s). Several dominant-side peak joint angles (prior to ball impact) increased as post-impact ball speed increased from slow to fast: wrist extension (16%), trunk rotation (28%), hip flexion (38%), knee flexion (27%), and dorsiflexion (5%). Between the aforementioned peak joint angles and ball impact, dominant-side peak angular velocities increased as ball speed increased from slow to fast: peak wrist flexion (118%), elbow flexion (176%), trunk rotation (99%), hip extension (143%), knee extension (56%), and plantarflexion (87%). Most kinematic variables changed as forehand ball speed changed; however, some variables changed more than others, indicating that range of motion and angular velocity for some joints may be more closely related to post-impact ball speed than for other joints.

A Maximal Graded Exercise Test to Accurately Predict VO2max in 18–65-Year-Old Adults

The purpose of this study was to develop an age-generalized regression model to predict maximal oxygen uptake (VO2max) based on a maximal treadmill graded exercise test (GXT; George, 1996). Participants (N = 100), ages 18–65 years, reached a maximal level of exertion (mean ± standard deviation [SD]; maximal heart rate [HRmax] = 185.2 ± 12.4 beats per minute (bpm); maximal respiratory exchange ratio [RERmax] = 1.18 ± 0.05; maximal rating of perceived exertion (RPEmax) = 19.1 ± 0.7) during the GXT to assess VO2max (mean ± SD; 40.24 ± 9.11 mL·kg−1·min−1). Multiple linear regression generated the following prediction equation (R = .94, standard error of estimate [SEE] = 3.18 mL·kg−1·min−1, %SEE = 7.9): VO2max (mL·kg−1·min−1) = 13.160 + (3.314 × gender; females = 0, males = 1) − (.131 × age) − (.334 × body mass index (BMI)) + (5.177 × treadmill speed; mph) + (1.315 × treadmill grade; %). Cross validation using predicted residual sum of squares (PRESS) statistics revealed minimal shrinkage (Rp  = .93 and SEE p  = 3.40 mL·kg−1·min−1); consequently, this model should provide acceptable accuracy when it is applied to independent samples of comparable adults. Standardized β-weights indicate that treadmill speed (.583) was the most effective at predicting VO2max followed by treadmill grade (.356), age (−.197), gender (.183), and BMI (−.148). This study provides a relatively accurate regression model to predict VO2max in relatively fit men and women, ages 18–65 years, based on maximal exercise (treadmill speed and grade), biometric (BMI), and demographic (age and gender) data.

Evaluation of a University General Education Health and Wellness Course Delivered by Lecture or Online

Purpose. To assess a single-semester university general education (GE) health and wellness course influence on physical activity (PA) and dietary habits among university students and to compare the course delivered through lecture or online for these outcomes. Design. A 15-week intervention with pre-post one-group design, allowing for comparative assessments in dietary and PA habits across time by delivery method (classroom lecture vs. online). Setting. A large Western university. Participants. Participants (n = 1638, female; n = 1333, male) were 82% university freshman or sophomores. Intervention. Participants were required to take a GE health and wellness course either by classroom lecture or online. The lecture and online curriculum content were similar. Participation in the study was entirely voluntary and was not connected to course grade. Measures. PA and dietary outcomes were determined from questions used in the Behavioral Risk Factor Surveillance System survey and were assessed pre- and post-intervention. Other validated questions were used to assess fitness. Analysis. The general linear model was utilized to determine group x period interactions when comparing the classroom lecture vs. online course. Results. Students improved overall level of PA by 12%, daily minutes of moderate-intensity PA by 8%, and fitness level by 2%. Students improved fruit/vegetable consumption by 4%, bran/whole grain cereal consumption by 8%, and brown rice/whole wheat bread consumption by 11%. All improvements were statistically significant (p < .001) with percent values indicating the size of the effect. The classroom lecture course yielded stronger improvements in several PA and dietary outcomes than the online course. Conclusions. A single-semester university wellness course may positively influence multiple PA and dietary behaviors; however, classroom lecture may be superior to online delivery.

The Effects of Leisure-Based Screen Time

Abstract Background: Use of television, computers, and video games competes with physical activity and may be a health risk factor. Purpose: This study assessed the relationship between leisure-based screen time and physical activity in families to determine whether assignment to a limited screen time group results in more physical activity. Methods: Ninety-four families participated for six weeks. Families were randomly assigned to unlimited or limited screen time viewing groups. Participants wore a pedometer to measure steps. Results: Results indicate no statistically significant differences in steps for adults (F(1,165)=0.81, p≤.369) or 13-to-18-year-olds (F(1,63)=0.21, p≤.647). Among the 5-to-12-year-olds, statistically significant group differences (F(1,165)=5.63, p≤.019) for steps were found between the unlimited viewing group and the limited viewing groups. Discussion: Lower amounts of leisure-based screen time yielded increased amounts of physical activity in the 5-to-12-year-olds, but this trend was not found in the 13-to-18-year-olds or adults. Additional research is needed in order to more fully understand the screen time and physical activity relationship. Translation to Health Education Practice: In general, promotion of physical activity at home and school could increase physical activity and decrease leisure-based screen time; otherwise, other sedentary activities may only replace the time not spent in front of a screen.

Cross-Validation of a Quarter-Mile Walk Test Using Two VO2 max Regression Models

This study was conducted to evaluate the accuracy of 2 regression models (Dolgener, Hensley, Marsh, & Fjelstul, 1994; Kline et al., 1987) in the prediction of VO2 max College-age men and women (N = 37) performed, in a counter-balanced order, a 1/4-mile walk test, a 1-mile walk test, followed by a maximal graded exercise test. For both walking tests, participants were instructed to self-select a fast (but less than maximal) steady exercise pace. For the 1-mile walk, the applicable data (e.g., age, gender, body weight, elapsed 1-mile exercise time, and ending exercise heart rate) were inserted into the Dolgener et al. (1994) equation and Kline et al. equation, respectively, to predict VO2 max A similar approach was taken to predict VO2 max for the 1/4-mile walk, except that elapsed exercise times were first multiplied by 4 to get 1-mile walk equivalents (because both equations are designed to predict VO2 max based on 1-mile data). The Kline et al. equation provided relatively accurate estimates of observed VO2 max values with mean residuals ranging from -0.36 to + 1.59 ml kg-1; min-1 and correlations ranging from .81 to .84. The percentage of predicted and observed VO2 max values within 4.5 ml kg-1; min-1; ranged from 67.6% to 75.7%. The Dolgener et al. (1994) equation, on the other hand, underpredicted observed VO2 max values with mean residuals ranging from -5.67 to -6.83 ml kg-11; min-1; and correlations ranging from .84 to .85. The percentage of predicted and observed VO2 max values within 4.5 ml kg-1; min-1; ranged from 18.9% to 43.2%. The results of this study provide evidence that the 1/4-mile walk predicts VO2 max with about the same accuracy as the 1-mile walk.

Estimating VO2max Using a Personalized Step Test

The purpose of this study was to develop a step test with a personalized step rate and step height to predict cardiorespiratory fitness in 80 college-aged males and females using the self-reported perceived functional ability scale and data collected during the step test. Multiple linear regression analysis yielded a model (R = 0.90, SEE = 3.43 mL·kg−1·min−1) that included gender, body mass, perceived functional ability, step rate, and recovery heart rate. Based on the standardized β-weights, gender explained the largest proportion of variance in VO2max values followed by perceived functional ability. The cross validation predicted residual sum of squares statistics show minimal shrinkage (RPRESS = 0.88, SEEPRESS = 3.57 mL·kg−1·min−1) in the accuracy of the regression model. This study provides a model to predict VO2max from non-exercise data and data collected during an individualized multistage step test that is accurate, time-efficient, and easy to administer.