Identification of a Preliminary Plasma Metabolome-based Biomarker for Circadian Phase in Humans.

Measuring individual circadian phase is important to diagnose and treat circadian rhythm sleep-wake disorders and circadian misalignment, inform chronotherapy, and advance circadian science. Initial findings using blood transcriptomics to predict the circadian phase marker dim-light melatonin onset (DLMO) show promise. Alternatively, there are limited attempts using metabolomics to predict DLMO and no known omics-based biomarkers predict dim-light melatonin offset (DLMOff). We analyzed the human plasma metabolome during adequate and insufficient sleep to predict DLMO and DLMOff using one blood sample. Sixteen (8 male/8 female) healthy participants aged 22.4 ± 4.8 years (mean ± SD) completed an in-laboratory study with 3 baseline days (9 h sleep opportunity/night), followed by a randomized cross-over protocol with 9-h adequate sleep and 5-h insufficient sleep conditions, each lasting 5 days. Blood was collected hourly during the final 24 h of each condition to independently determine DLMO and DLMOff. Blood samples collected every 4 h were analyzed by untargeted metabolomics and were randomly split into training (68%) and test (32%) sets for biomarker analyses. DLMO and DLMOff biomarker models were developed using partial least squares regression in the training set followed by performance assessments using the test set. At baseline, the DLMOff model showed the highest performance (0.91 R2 and 1.1 ± 1.1 h median absolute error ± interquartile range [MdAE ± IQR]), with significantly (p < 0.01) lower prediction error versus the DLMO model. When all conditions (baseline, 9 h, and 5 h) were included in performance analyses, the DLMO (0.60 R2; 2.2 ± 2.8 h MdAE; 44% of the samples with an error under 2 h) and DLMOff (0.62 R2; 1.8 ± 2.6 h MdAE; 51% of the samples with an error under 2 h) models were not statistically different. These findings show promise for metabolomics-based biomarkers of circadian phase and highlight the need to test biomarkers that predict multiple circadian phase markers under different physiological conditions.

The effect of exercise on non-exercise physical activity and sedentary behavior in adults.

It is widely assumed that structured exercise causes an additive increase in physical activity energy expenditure (PAEE) and total daily energy expenditure (TDEE). However, the common observation that exercise often leads to a less than expected decrease in body weight, without changes in energy intake, suggests that some compensatory behavioral adaptations occur. A small number of human studies have shown that adoption of structured exercise can lead to decreases in PAEE, which is often interpreted as a decrease in physical activity (PA) behavior. An even smaller number of studies have objectively measured PA, and with inconsistent results. In animals, high levels of imposed PA induce compensatory changes in some components of TDEE. Recent human cohort studies also provide evidence that in those at the highest levels of PA, TDEE is similar when compared to less physically active groups. The objective of this review is to summarize the effects of structured exercise training on PA, sedentary behavior, PAEE and TDEE. Using models from ecological studies in animals and observational data in humans, an alternative model of TDEE in humans is proposed. This model may serve as a framework to investigate the complex and dynamic regulation of human energy budgets.

Inter- and intraindividual correlations of background abundances of (2)H, (18)O and (17)O in human urine and implications for DLW measurements.

BACKGROUND/OBJECTIVES: The method of choice for measuring total energy expenditure in free-living individuals is the doubly labeled water (DLW) method. This experiment examined the behavior of natural background isotope abundance fluctuations within and between individuals over time to assess possible methods of accounting for variations in the background isotope abundances to potentially improve the precision of the DLW measurement. SUBJECTS/METHODS: In this work, we measured natural background variations in (2)H, (18)O and (17)O in water from urine samples collected from 40 human subjects who resided in the same geographical area. Each subject provided a urine sample for 30 consecutive days. Isotopic abundances in the samples were measured using Off-Axis Integrated Cavity Output Spectroscopy. RESULTS: Autocorrelation analyses demonstrated that the background isotopes in a given individual were not temporally correlated over the time scales of typical DLW studies. Using samples obtained from different individuals on the same calendar day, cross-correlation analyses demonstrated that the background variations of different individuals were not correlated in time. However, the measured ratios of the three isotopes (2)H, (18)O and (17)O were highly correlated (R(2)=0.89-0.96). CONCLUSIONS: Although neither specific timing of DLW water studies nor intraindividual comparisons were found to be avenues for reducing the impact of background isotope abundance fluctuations on DLW studies, strong inter-isotope correlations within an individual confirm that use of a dosing ratio of 8‰:1‰ (0.6 p.p.m.: p.p.m.) optimizes DLW precision. Theoretical implications for the possible use of (17)O measurements within a DLW study require further study.

Effect of calcium from dairy and dietary supplements on faecal fat excretion: a meta-analysis of randomized controlled trials.

Observational studies have found that dietary calcium intake is inversely related to body weight and body fat mass. One explanatory mechanism is that dietary calcium increases faecal fat excretion. To examine the effect of calcium from dietary supplements or dairy products on quantitative faecal fat excretion, we performed a systematic review with meta-analysis. We included randomized, controlled trials of calcium (supplements or dairy) in healthy subjects, where faecal fat excretion was measured. Meta-analyses used random-effects models with changes in faecal fat excreted expressed as standardized mean differences, as the studies assessed the same outcome but measured in different ways. An increased calcium intake resulted in increased excretion of faecal fat by a standardized mean difference of 0.99 (95% confidence intervals: 0.63-1.34; P < 0.0001; expected to correspond to approximately 2g day(-1)) with moderate heterogeneity (I(2) = 49.5%) indicating some inconsistency in trial outcomes. However, the dairy trials showed homogeneous outcomes (I(2)=0%) indicating consistency among these trials. We estimated that increasing the dairy calcium intake by 1241 mg day(-1) resulted in an increase in faecal fat of 5.2 (1.6-8.8) g day(-1). In conclusion, dietary calcium has the potential to increase faecal fat excretion to an extent that could be relevant for prevention of weight (re-)gain. Long-term studies are required to establish its potential contribution.

Validation of the BodyGem hand-held calorimeter.

OBJECTIVE: To assess the validity and reliability of a hand-held indirect calorimeter. DESIGN: Resting metabolic rate (RMR) was measured on two separate mornings. SUBJECTS: A heterogeneous sample of 41 healthy adults. MEASUREMENTS: RMR using both a metabolic cart (Sensormedics 2900, SM-2900) and a hand-held indirect calorimeter (BodyGem, BG). RESULTS: There were no trial-to-trial differences in RMR measured by the BG (6756+/-163 vs 6697+/-163 kJ/day) or the SM-2900 (6400+/-163 vs 6396+/-167 kJ/day). RMR measured by the BG was significantly higher than that measured by the SM-2900 during both trials. In a sample of 10 subjects, the energy cost of holding the BG in position was determined to be (0.17+/-0.04 kJ/min, or 255+/-84 kJ/day). After applying this adjustment, the differences between systems were no longer significant during trial 1 (mean difference=101+/-67 kJ/day) or trial 2 (46+/-75 kJ/day). In overweight and obese individuals, RMR measured by the BodyGem was more accurate than that estimated by the Harris-Benedict equations. CONCLUSION: The BodyGem provides valid and reliable measurements of RMR. The BodyGem produces significantly higher values than the Sensor Medics 2900 indirect calorimeter, with the increase largely due to an increased energy demand required to hold the BG in position.

Tracmor system for measuring walking energy expenditure.

OBJECTIVE: Walking is an important mode of exercise and is likely to represent a major component of nonexercise activity thermogenesis. The question arises, how best to quantify walking-energy expenditure (EE) in free-living individuals. The triaxial accelerometer for movement registration (Tracmor) is a valid measure of body displacement and so we wanted to evaluate this tool for quantifying walking-EE. HYPOTHESIS: In this study, we test the hypothesis that walking-EE, measured in a Room Calorimeter, can be predicted from Tracmor output using a regression equation derived from a brief Tracmor/treadmill/Metabolic Cart protocol. DESIGN: First, 11 healthy subjects completed a 40-min procedure whereby they wore a Tracmor unit and walked on a treadmill at 0, 1, 2 and 3 mph while EE was measured using a Metabolic Cart. This allowed a regression equation to be defined for each subject to convert Tracmor output to EE. Each subject then entered a Room Calorimeter wearing the Tracmor Unit and walked at two self-selected velocities ('slow', 'fast') while EE was measured. 'Tracmor/regression equation' predictions of walking-EE were compared with Room Calorimeter measurements of walking-EE for the two velocities. RESULTS: The 'Tracmor/regression equation' prediction of EE for walking slowly was 6.36+/-1.67 kJ/min, and for walking fast it was 11.0+/-2.60 kJ/min. Room Calorimeter measurements were 6.43+/-1.85 and 10.9+/-3.03 kJ/min, respectively. The intraclass correlation coefficient for slow-paced walking was 0.93 (P<0.001), and for fast-paced walking it was 0.82 (P<0.005). CONCLUSIONS: When combined with laboratory measures of EE, the Tracmor accelerometer provides useful data on walking-EE and is applicable to free-living individuals.

Relation between calcium intake and fat oxidation in adult humans.

OBJECTIVE: To determine if total calcium (Ca(2+)) intake and intake of Ca(2+) from dairy sources are related to whole-body fat oxidation. DESIGN: : Cross-sectional study. SUBJECTS: A total of 35 (21 m, 14 f) non-obese, healthy adults (mean+/-s.d., age: 31+/-6 y; weight: 71.2+/-12.3 kg; BMI: 23.7+/-2.9 kg m(-2); body fat: 21.4+/-5.4%). MEASUREMENTS: Daily (24 h) energy expenditure (EE) and macronutrient oxidation using whole-room indirect calorimetry; habitual Ca(2+) intake estimated from analysis of 4-day food records; acute Ca(2+) intake estimated from measured food intake during a 24-h stay in a room calorimeter. RESULTS: Acute Ca(2+) intake (mg. kcal(-1)) was positively correlated with fat oxidation over 24 h (r=0.38, P=0.03), during sleep (r=0.36, P=0.04), and during light physical activity (r=0.32, P=0.07). Acute Ca(2+) intake was inversely correlated with 24-h respiratory quotient (RQ) (r=-0.36, P=0.04) and RQ during sleep (r=-0.31, P=0.07). After adjustment for fat mass, fat-free mass, energy balance, acute fat intake, and habitual fat intake, acute Ca(2+) intake explained approximately 10% of the variance in 24-h fat oxidation. Habitual Ca(2+) intake was not significantly correlated to fat oxidation or RQ. Total Ca(2+) intake and Ca(2+) intake from dairy sources were similarly correlated with fat oxidation. In backwards stepwise models, total Ca(2+) intake was a stronger predictor of 24 h fat oxidation than dairy Ca(2+) intake. CONCLUSION: Higher acute Ca(2+) intake is associated with higher rates of whole-body fat oxidation. These effects were apparent over 24 h, during sleep and, to a lesser extent, during light physical activity. Calcium intake from dairy sources was not a more important predictor of fat oxidation than total Ca(2+) intake.

American College of Sports Medicine position stand. Appropriate intervention strategies for weight loss and prevention of weight regain for adults.

In excess of 55% of adults in the United States are classified as either overweight (body mass index = 25-29.9 kg.m(-2)) or obese (body mass index > or = 30 kg.m(-2)). To address this significant public health problem, the American College of Sports Medicine recommends that the combination of reductions in energy intake and increases in energy expenditure, through structured exercise and other forms of physical activity, be a component of weight loss intervention programs. An energy deficit of 500-1000 kcal.d-1 achieved through reductions in total energy intake is recommended. Moreover, it appears that reducing dietary fat intake to <30% of total energy intake may facilitate weight loss by reducing total energy intake. Although there may be advantages to modifying protein and carbohydrate intake, the optimal doses of these macronutritents for weight loss have not been determined. Significant health benefits can be recognized with participation in a minimum of 150 min (2.5 h) of moderate intensity exercise per week, and overweight and obese adults should progressively increase to this initial exercise goal. However, there may be advantages to progressively increasing exercise to 200-300 min (3.3-5 h) of exercise per week, as recent scientific evidence indicates that this level of exercise facilitates the long-term maintenance of weight loss. The addition of resistance exercise to a weight loss intervention will increase strength and function but may not attenuate the loss of fat-free mass typically observed with reductions in total energy intake and loss of body weight. When medically indicated, pharmacotherapy may be used for weight loss, but pharmacotherapy appears to be most effective when used in combination with modifications of both eating and exercise behaviors. The American College of Sports Medicine recommends that the strategies outlined in this position paper be incorporated into interventions targeting weight loss and the prevention of weight regain for adults.

The effect of endurance training on resting heart rate variability in sedentary adult males.

Eleven previously sedentary adult males, serving as the experimental (EXP) group [mean (SE) age 36.6 (1.7) years, body mass 87.2 (4.3) kg, body mass index, BMI, 28.4 (1.5) kgm(-2)] participated in a 16-week supervised exercise program (3 days x week(-1), 30 min day(-1), at approximately equal to 80% of heart rate reserve) to determine the temporal effects of a moderate-to-vigorous-intensity exercise program on heart rate variability (HRV). Five sedentary males [mean (SD) age 36.6 (4.2 )years, body mass 83.8 (6.6) kg, BMI 22.8 (1.7) kg x m(-2)] served as non-exercising controls (CON). HRV was measured every 4 weeks from a resting electrocardiogram obtained while subjects paced their breathing at 10 breaths x min(-1) (0.167 Hz). The time-domain measures of HRV recorded were the proportion of adjacent intervals differing by more than 50 ms (pNN50), the root mean square of successive differences (rMSSD), and the standard deviation of the resting interbeat interval. The frequency-domain measures recorded were high (HF) and low (LF) frequency oscillations, as determined using the fast Fourier transform technique. Aerobic capacity (i.e., peak oxygen uptake) increased by 13.8% in EXP (P < 0.001), but did not change in CON. Resting heart rate did not change in either EXP or CON. In EXP, pNN50 at week 12 (P<0.01), rMSSD at weeks 12 (P < 0.01) and 16 (P = 0.05), and HF power at weeks 12 (P < 0.01) and 16 (P = 0.05) were elevated above baseline. Time- and frequency-domain measures of HRV remained unchanged in CON. It is concluded that a moderate-to-vigorous-intensity exercise program produces increases in time- and frequency-domain measures of HRV within 12 weeks.

Measurement of the components of nonexercise activity thermogenesis.

Nonexercise activity thermogenesis (NEAT) accounts for the vast majority of nonresting metabolic rate and changes in NEAT-predicted susceptibility to fat gain with overfeeding. Measuring physical activity and its components in free-living humans has been a long-standing challenge. In this study, we combine information about lightweight sensors that capture data on body position and motion with laboratory measures of energy expenditure to calculate nonfidgeting NEAT. This measurement of nonfidgeting NEAT was compared with total NEAT measured in a room calorimeter in 11 healthy subjects. The measurement of nonfidgeting NEAT accounted for 85 +/- 9% of total NEAT measured in the room calorimeter. The intraclass correlation coefficient for the two methods was 0.86 (95% confidence interval 0.56, 0.96; P < 0.05). This suggests that 86% of the variance is attributable to between-subject variance and 14% to between-method disagreement. These instruments are applicable to free-living subjects; they are stand-alone, are lightweight, and allow normal daily activities. This novel technology has potential application for not only assessing NEAT but also tracking physical activity in free-living humans.

The role of low-fat diets in body weight control: a meta-analysis of ad libitum dietary intervention studies.

OBJECTIVES: Low-fat high-carbohydrate diets are recommended to prevent weight gain in normal weight subjects and reduce body weight in overweight and obese. However, their efficacy is controversial. We evaluated the efficacy of ad libitum low-fat diets in reducing body weight in non-diabetic individuals from the results of intervention trials. DESIGN: Studies were identified from a computerized search of the Medline database from January 1966 to July 1999 and other sources. Inclusion criteria were: controlled trials lasting more than 2 months comparing ad libitum low-fat diets as the sole intervention with a control group consuming habitual diet or a medium-fat diet ad libitum. MAIN OUTCOME MEASURES: Differences in changes in dietary fat intake, energy intake and body weight. Weighted mean differences for continuous data and 95% confidence intervals (CIs) were calculated. RESULTS: Two authors independently selected the studies meeting the inclusion criteria and extracted data from 16 trials (duration of 2-12 months) with 19 intervention groups, enrolling 1910 individuals. Fourteen were randomized. Weight loss was not the primary aim in 11 studies. Before the interventions the mean proportions of dietary energy from fat in the studies were 37.7% (95% CI, 36.9-38.5) in the low-fat groups, and 37.4% (36.4-38.4) in the control groups. The low-fat intervention produced a mean fat reduction of 10.2% (8.1-12.3). Low-fat intervention groups showed a greater weight loss than control groups (3.2 kg, 95% confidence interval 1.9-4.5 kg; P < 0.0001), and a greater reduction in energy intake (1 138 kJ/day, 95% confidence interval 564-1712 kJ/day, P = 0.002). Having a body weight 10 kg higher than the average pre-treatment body weight was associated with a 2.6 +/- 0.8 kg (P = 0.011) greater difference in weight loss. CONCLUSION: A reduction in dietary fat without intentional restriction of energy intake causes weight loss, which is more substantial in heavier subjects.

Resting heart rate variability in men varying in habitual physical activity.

PURPOSE: The aims of this study were 1) to assess day-to-day stability of resting heart rate variability (HRV) in healthy adults; 2) to determine whether the reliability of these measures is influenced by self-reported habitual physical activity level; and 3) determine whether the magnitude of HRV is related to self-reported habitual physical activity level. METHODS: A resting electrocardiogram was obtained on five consecutive mornings in 37 men (age = 33+/-6 yr) grouped according to their self-reported level of weekly physical activity (LOW, N = 15; MOD, N = 10; HIGH, N = 12). All measurements were obtained while subjects breathed at 10 breaths x min(-1) (0.167 Hz). RESULTS: HRV was assessed using time and frequency domain measures. Most measures were highly reproducible (R > 0.90) regardless of activity level. After adjusting for differences in age and body mass index, weekly physical activity level was not a significant predictor of any measure of HRV. However, all time and frequency domain measures of HRV tended to be higher in active (MOD and HIGH) compared with inactive (LOW) subjects. No measure of HRV differed between the two most active groups. CONCLUSIONS: Heart rate and HRV are highly reproducible, regardless of physical activity level. Additionally, although time and frequency domain measures of HRV may be greater in active than sedentary individuals, HRV does not appear to be increased in a dose-dependent manner with increasing levels of physical activity.

The role of dietary fat in body fatness: evidence from a preliminary meta-analysis of ad libitum low-fat dietary intervention studies.

The role of high-fat diets in weight gain and obesity has been questioned because of inconsistent reports in the literature concerning the efficacy of ad libitum low-fat diets to reduce body weight. We conducted a meta-analysis of weight loss occurring on ad libitum low-fat diets in intervention trials, and analysed the relationship between initial body weight and weight loss. We selected controlled trials lasting more than 2 months comparing ad libitum low-fat diets with a control group consuming their habitual diet or a medium-fat diet ad libitum published from 1966 to 1998. Data were included from 16 trials with a duration of 2-12 months, involving 1728 individuals. No trials on obese subjects fulfilled the inclusion criteria. The weighted difference in weight loss between intervention and control groups was 2.55 kg (95% CI, 1.5-3.5; P < 0.0001). Weight loss was positively and independently related to pre-treatment body weight (r = 0.52, P < 0.05) and to reduction in the percentage of energy as fat (0.37 kg/%, P < 0.005) in unweighted analysis. Extrapolated to a BMI of about 30 kg/m2 and assuming a 10% reduction in dietary fat, the predicted weight loss would be 4.4 kg (95% CI, 2.0 to -6.8 kg). Because weight loss was not the primary aim in 12 of the 16 studies, it is unlikely that voluntary energy restriction contributed to the weight loss. Although there is no evidence that a high intake of simple sugars contributes to passive overconsumption, carbohydrate foods with a low glycaemic index may be more satiating and exert more beneficial effects on insulin resistance and cardiovascular risk factors. Moreover, an increase in protein content up to 25% of total energy may also contribute to reducing total energy intake. In conclusion, a low-fat diet, high in protein and fibre-rich carbohydrates, mainly from different vegetables, fruits and whole grains, is highly satiating for fewer calories than fatty foods. This diet composition provides good sources of vitamins, minerals, trace elements and fibre, and may have the most beneficial effect on blood lipids and blood-pressure levels. A reduction in dietary fat without restriction of total energy intake prevents weight gain in subjects of normal weight and produces a weight loss in overweight subjects, which is highly relevant for public health.

Genetic and environmental contributions to obesity.

Groups that are already concerned about obesity can be linked together. This can generate plans of action and may lead to small-scale interventions. At the same time, awareness needs to be raised among other potential partners, especially federal, state, and local government agencies. As a partnership is built, funding opportunities, from public and private entities, should increase. The ultimate need is a public health campaign to combat an important public health problem.

Field evaluation of the Computer Science and Applications, Inc. physical activity monitor.

PURPOSE: The purpose of this study was to evaluate the Computer Science and Applications, Inc. (CSA) activity monitor to quantify physical activity in free living subjects using an activity diary as the criterion measure. METHODS: Subjects also completed a 7-d physical activity recall at the end of the monitoring period. Nine male and 10 female subjects (mean, SD) (25.0, 3.6 yr) wore the CSA monitor for 7 consecutive days. On 3 of those days, subjects completed an activity diary (2 weekdays and 1 weekend day). Total kcal per day (Dkcal(tot)) was calculated from the self-reported diary classifications of the subject's activities. For the 3 days that coincided with the diary, total number of counts accumulated per day (cnt(tot)) was obtained from the monitor. RESULTS: The amount of activity per day recorded by the CSA monitor followed the same pattern of change as the activity diary. The cnt(tot) and Dkcal(tot) were significantly (P < or = 0.05) correlated on day 1 (r = 0.65), day 2 (r = 0.49), day 3 (r = 0.55), and for the 3 days pooled (r = 0.51). Subjects were classified as low, moderate, or highly active based on tertiles of kcal from the diary and counts from the CSA monitor. The percentage agreement between the CSA and the activity diary was 68.4% (Kappa = 0.53, P < 0.01). The number of minutes spent in the various activity categories were compared between instruments using an ANOVA model. The results of these analyses suggest that the CSA overestimated light activity and underestimated vigorous activity compared with the diary. CONCLUSION: In conclusion, the CSA monitor may be useful in a field situation where total physical activity and patterns of physical activity are the desired outcomes.

Dietary fat intake and regulation of energy balance: implications for obesity.

Obesity represents a major threat to health and quality of life. Although obesity has strong genetic determinants, the increasing prevalence of obesity in populations around the world suggests that environmental factors are promoting or exacerbating the problem. Experts are calling for public health efforts to deal with the global epidemic of obesity. Such a campaign would require that we identify and modify environmental factors that promote obesity. Our current food supply is high in fat, and high fat diets have been suggested to promote obesity by increasing energy intake, thus increasing the probability of positive energy balance and weight gain. However, others argue that high fat diets are not promoting obesity. In this paper, we review evidence from animal studies, carefully controlled laboratory studies, cross-sectional studies, clinical trials and studies in individuals at high risk to develop obesity. Although there are many environmental factors promoting excess energy intake and discouraging energy expenditure, it is clear that consumption of a high fat diet increases the likelihood of obesity and that the risk of obesity is low in individuals consuming low fat diets. On the basis of the available data, the current public health recommendations to lower dietary fat intake appear to be appropriate.

Overview of the determinants of overweight and obesity: current evidence and research issues.

PURPOSE: The prevalence of obesity has reached epidemic proportions in many countries around the world. However, the genetic and environmental factors contributing to obesity are incompletely understood. METHODS: We reviewed studies relating to the regulation of energy balance and how these factors may contribute to the development of obesity. RESULTS: Although it is widely believed that genetics contribute significantly to the variability in body fatness, the available data do not support a role for defects in resting metabolic rate, substrate metabolism, dietary induced thermogenesis, or the energy cost of physical activity as significant causes of obesity. Furthermore, it is safe to say that the human genotype has not changed substantially over the past two to three decades. Data from several national surveys indicate that over the past few decades, there has been either a slight increase or a very modest decline in total energy and fat intake. This suggests that decreases in physical activity are a major contributing factor. Participation in leisure time physical activity is low but has remained relatively constant. However, an increased reliance on technology has substantially reduced work-related physical activity and the energy expenditure required for daily living. CONCLUSION: The most likely environmental factor contributing to the current obesity epidemic is a continued decline in daily energy expenditure that has not been matched by an equivalent reduction in energy intake. Because daily energy expenditure is decreasing, it is difficult for most people to restrict intake to meet energy requirements, and more and more people are becoming obese. Thus, increasing physical activity may be the strategy of choice for public health efforts to prevent obesity.

Test-retest reproducibility of maximum cardiac output by Doppler echocardiography.

Test-retest reproducibility of stroke volume and cardiac output using Doppler echocardiography was examined during maximum cycle exercise in 13 young men. A coefficient of variation of 8.5% and 8.1% and intraclass correlation coefficient of 0.90 and 0.91 for maximum stroke volume and cardiac output, respectively, indicate a high degree of reproducibility using this technique.

Calibration of the Computer Science and Applications, Inc. accelerometer.

PURPOSE: We established accelerometer count ranges for the Computer Science and Applications, Inc. (CSA) activity monitor corresponding to commonly employed MET categories. METHODS: Data were obtained from 50 adults (25 males, 25 females) during treadmill exercise at three different speeds (4.8, 6.4, and 9.7 km x h(-1)). RESULTS: Activity counts and steady-state oxygen consumption were highly correlated (r = 0.88), and count ranges corresponding to light, moderate, hard, and very hard intensity levels were < or = 1951, 1952-5724, 5725-9498, > or = 9499 cnts x min(-1), respectively. A model to predict energy expenditure from activity counts and body mass was developed using data from a random sample of 35 subjects (r2 = 0.82, SEE = 1.40 kcal x min(-1)). Cross validation with data from the remaining 15 subjects revealed no significant differences between actual and predicted energy expenditure at any treadmill speed (SEE = 0.50-1.40 kcal x min(-1)). CONCLUSIONS: These data provide a template on which patterns of activity can be classified into intensity levels using the CSA accelerometer.

Changes in VO2max and maximal treadmill time after 9 wk of running or in-line skate training.

This study tested the hypothesis that running and in-line skating training elicit similar improvements in cardiorespiratory fitness. Changes in maximal oxygen consumption (VO2max) and maximal treadmill endurance time were compared in runners (N = 16), in-line skaters (N = 19), and controls who did no systematic training (N = 7). Training volumes were similar for runners and skaters (3 d.wk-1, 10-40 min/session, 80-90% of exercise specific maximal heart rate) and included both continuous and interval workouts. Pre- and post-training VO2max and maximal treadmill time were measured in all subjects using a running protocol and in skaters using an in-line skating protocol. The groups did not differ in pre-training running VO2max or maximal treadmill time. After 9 wk, significant increases in running VO2max and maximal treadmill time were observed in runners (mean +/- SE, 9.3 +/- 1.3%, 14.9 +/- 2.5%) and skaters (6.6 +/- 1.0%, 9.1 +/- 3.4%), but not controls. Skaters also significantly increased their skating VO2max and maximal treadmill time (8.6 +/- 1.8%, 7.9 +/- 2.9%). The magnitude of these increases was not different between the two training groups. In conclusion, in moderately active college-aged students, similar improvements in VO2max are achieved with running and in-line skating programs that are equivalent in training volume and intensity.