Effect of Exercise Training Intensity on Abdominal Visceral Fat and Body Composition

Brian A. Irving; Christopher K. Davis; David W. Brock; Judy Y. Weltman; Damon Swift; Eugene J. Barrett; Glenn A. Gaesser; Arthur Weltman

Disclosures

Med Sci Sports Exerc. 2008;40(11):1863-1872. 

In This Article

Methodology

Participants

Twenty-seven middle-aged women (mean ± SD; 51 ± 9 yr) who met the IDF criteria for the metabolic syndrome[2] completed the present study. To meet the IDF criteria for the metabolic syndrome, each participant had to have an elevated waist circumference (≥80 cm) and at least two of the following: elevated fastingblood glucose (≥100 mg·dL-1), low HDL-C (≤50 mg·dL-1), hypertriglyceridemia (≥150 mg·dL-1), and/or elevated blood pressure (≥130/85 mm Hg).[2] The participants were sedentary at baseline, reporting less than 2 d·wk-1 of structured exercise. All participants underwent an initial eligibility screening in the University of Virginia's General Clinical Research Center (GCRC; see below). The Institutional Review Board, Human Investigation Committee of the University of Virginia's Health System approved this study, and each participant provided written informed consent.

Metabolic Syndrome and Medical Screening Protocol

Participants reported to the GCRC for screening after a 10- to 12-h fast at ~0900 h. Participants provided a detailed medical history and underwent a physical examination, which included an assessment of the five risk factors associated with the metabolic syndrome as defined by the IDF.[2] In brief, waist circumference measurements were taken in triplicate to the nearest 0.1 cm using a nonelastic measuring tape midway between the iliac crest and the lowest rib.[28] Seated blood pressure was assessed in duplicate using an automated sphygmomanometer (Dynamap 100; General Electric, Tampa, FL) after participants sat quietly for 10 to 15 min. Fasting blood samples were then drawn, and serum was separated by centrifugation. Glucose, triglycerides, and HDL-C concentrations were assessed inserum. Glucose concentrations were determined by usingan automated glucose analyzer (2300 STAT Plus; Yellow Springs Instruments (YSI), Yellow Springs, OH). Triglycerides and HDL-C concentrations were determined using an automatic analyzer (Olympus AU640; Olympus, Melville, NY). All participants were asked to refrain from caffeine, alcohol, and vigorous physical activity for 24 h before testing. Exclusion criteria included a history of ischemic heart disease, diabetes, or pulmonary or musculoskeletal limitations to exercise; the use of vasoactive medications, oral hypoglycemics, insulin, glucocorticoids, antipsychotics, hormone replacement; or birth control and if pregnant, breast feeding, or unwilling to provide written informed consent.

Study Design

Eligible participants were randomized to one of three 16-wk exercise training conditions: (i) no-exercise training (Control), (ii) LIET, or (iii) HIET. Figure 1 presents the distribution of study participants. Participants were assessed before and after the 16-wk intervention. Participants were admitted to the GCRC for 2 d during which the following evaluations were performed (see below). The one exception was the cardiorespiratory fitness assessment that was conducted as an outpatient visit. To control for the effects of menstrual cycle on outcome variables, premenopausal women were admitted between days 2 and 8 of their menstrual cycle. Postmenopausal status was determined by the absence of menses for >1 yr. In the no-exercise training condition, there was one premenopausal woman, one woman who underwent a hysterectomy (menopausal status unknown), and five postmenopausal women; in the LIET condition, there were three premenopausal women, four women who underwent a hysterectomy (menopausal status unknown), and four postmenopausal women; and in the HIET condition, there were two premenopausal women, two women who underwent a hysterectomy (menopausal status unknown), and seven postmenopausal women. Participants were asked to refrain from alcohol, caffeine, and cigarette smoking for at least 72 h before their admission.

Figure 1.

Distribution of study participants.

Body Composition Assessment

Body composition was measured using air displacement plethysmography (Bod-Pod; Life Measurement Instruments, Concord, CA) corrected for thoracic gas volume as described previously.[7]

Single-slice computed tomography (CT) images were obtained at the level of L4-L5 intervertebral disc space and at the midpoint between the inguinal crease and the top of the patella as previously described.[22] All scans were performed using a CT scanner (Lightspeed; GE Medical Systems, Milwaukee, WI) and saved as DICOM images for analysis. Standard CT procedures of 120-kV, 5-mm thickness, and a 512 × 512 matrix were used for all subjects. A single trained investigator analyzed each of the blinded CT images using the Slice-O-Matic version 4.3 software package (TomoVision, Montreal, Canada) for the delineation and quantification of cross-sectional areas of fat, muscle, and bone as previously described.[22,29] The measurement boundary for AVF was defined as the innermost aspect of the abdominal and oblique muscle walls and the posterior aspect of the vertebral body as described previously.[6] In addition, we also quantified abdominal subcutaneous fat area at the L4-L5 intervertebral disc space. At the midthigh, we assessed the total midthigh fat area and the total midthigh skeletal muscle area. The inter- and intrainvestigator coefficient of variations for these analyses in our laboratory are less than 5%.[22]

Cardiorespiratory Fitness Assessment

Participants completed a continuous V˙O2peak treadmill protocol. The initial treadmill (Model Q65; Quinton Instrument Co, Seattle, WA) velocity was 60 m·min-1, and the velocity was increased by 10 m·min-1 every 3 min until volitional fatigue. Metabolic data were collected during the protocol using standard open-circuit spirometric techniques (Vmax 229; Viasys Healthcare, Yorba Linda, CA), and heart rate was assessed electrocardiographically (Marquette Max-1; Marquette Medical Systems, Inc, Marquette, WI). V˙O2peak was chosen as the highest V˙O2 attained during the exercise protocol. An indwelling venous cannula was inserted in a forearm vein, and blood samples were taken at rest and at the end of each exercise stage for the measurement of blood lactate concentration (2300 STAT Plus; YSI). The LT was determined from the blood lactate-velocity relationship and was defined as the highest velocity attained before the curvilinear increase in blood lactate concentrations above baseline.[43] A lactate elevation of at least 0.2 mmol·L-1 (the error associated with the lactate analyzer) was required for LT determination. Individual plots of V˙O2 versus velocity allowed for the determination of the V˙O2 associated with the LT. RER, heart rate, and blood lactate responses were monitored to ensure that participants attained peak values at the point of volitional exhaustion. V˙O2peak was chosen as the highest V˙O2 attained during the test.

Physical Activity and Dietary Assessment

The time spent in physical activity at different intensities was assessed using the Aerobic Center Longitudinal Study's Physical Activity Questionnaire.[26] The questionnaire was administered using an interview technique to increase accuracy.[34] Total physical activity was calculated as MET-hours per week (1 MET = 3.5 mL·kg-1·min-1) using the compendium of physical activities.[1] Participants were instructed by a registered dietician on how to complete a 3-d dietary record that was analyzed using a commercially available nutrition software program (The Food Processor SQL; ESHA Research, Salem, OR).

Basal Metabolic Rate

After an overnight fast, participants were awakened at 0600 h, asked to void, return to bed, and remain awake in the supine position for 30 min in a quiet and thermoneutral environment. Basal metabolic rate (BMR) was measured by indirect calorimetry (Delta Trac metabolic cart and ventilation hood; SensorMedics, Yorba Linda, CA) for 30 min.

Exercise Intervention

Participants were randomized to one of the following three interventions: (i) no-exercise training, (ii) LIET, or (iii) high-intensity.

(i) No-Exercise Training (Control). Participants maintained their current level of physical activity for the duration of the study.

(ii) LIET. Participants completed a 16-wk supervised low-intensity exercise intervention. Participants were progressed to complete five exercise sessions (days) per week by week 5 at an intensity at or below their LT (RPE ~10-12). The duration of each exercise session was adjusted on the basis of each participant's individual V˙O2-velocity relationship so that each participant expended a total of 300 kcal per training session for weeks 1-2 (3 d·wk-1), 350 kcal per session for weeks 3-4 (4 d·wk-1), and 400 kcal per session for weeks 5-16 (5 d·wk-1). As each participant's fitness level improved, the velocity required to maintain her assigned RPE was increased; therefore, the duration was readjusted to maintain the kilocalorie requirement. Exercise was prescribed on the basis of the rating of perceived exertion obtained during the LT/V˙O2peak protocol, and one of the investigators monitored RPE during each training session.

(iii) HIET. Participants completed a 16-wk supervised moderate- to high-intensity exercise intervention. Participants were progressed to five exercise sessions (days) per week by week 5. Three days per week (e.g., M, W, F), participants exercised at an intensity midway between the LT and the V˙O2peak (RPE ~15-17), and on the remaining 2 d (e.g., T, Th), they exercised at or below their LT (RPE ~10-12). The progression of caloric expenditures and the velocity and duration adjustments were made as described for LIET, with the exception that participants always had 3 d·wk-1 > LT and 1 d·wk-1 < LT training session was added at week 3 and again at week 5.

All exercise training sessions were supervised by a member of the investigative team and took place at the University of Virginia indoor or outdoor track. Each participant was instructed to walk/run the distance associated with her prescribed caloric expenditure on the basis of each participant's body weight and associated caloric output from the compendium of physical activity. If participants lost weight, the distance required to expend a given energy expenditure increased accordingly. For example, a 90-kg woman would complete 3.5 miles per session to expend 400kcal per session, whereas an 80-kg woman would complete 4.0 miles per session.

The rationale for using RPE as an index of training intensity comes from our previous data that suggest that RPE is an accurate marker of the blood lactate response toexercise that is not affected by gender, fitness, training state, mode of exercise, or intensity of training[20,35,38] and that RPE can be used to produce a desired blood lactate concentration during 30 min of treadmill running.[38] In addition, Jakicic et al.[24] reported that RPE provide amore accurate marker of relative exercise intensity compared with the percentage of heart rate reserve in obese women before and after weight loss. Each participant's RPE was monitored on a lap-by-lap basis to assess the prescribed exercise intensity, and the velocities required to maintain the assigned RPE were adjusted accordingly. Heart rate data were not collected during the exercise sessions; however, as stated above, RPE have been shown to be an accurate marker of relative exercise intensity among obese adults.

Statistical Analysis

All statistical analyses were conducted using SAS software (version 9.1; SAS Institute, Cary, NC). Because measurements of the responses at 16wk were required for the participant to be included in the analysis, our target study population with respect to statistical inference was the population of individuals who met the study inclusion criteria and who successfully completed the 16-wk intervention. The frequency of patient dropouts was analyzed across the three interventions to determine whether the dropout rate was at random or whether it was associated with the participants' treatment assignment. Data are presented as means ± SD.

The present study was powered to detect a ~30-cm2 reduction in AVF (ΔAVF = baseline - 16-wk AVF measurement) with 12 participants per group. Two-way, mixed-effects ANCOVA was used to examine mean differences in pre- to posttraining values.[14] The model specification included parameters to estimate the exercise intensity main effect (Control, LIET, and HIET), the time main effect (pre- and posttraining), and their interaction effect on the change in the dependent variables. Their baseline value served as the covariate. In addition, the model included random effects that represented the between- and within-subject error terms. The model parameters were estimated on the basis of the principles of restricted maximum likelihood, with the variance-covariance structure estimated using unstructured estimate. For all analyses, pairwise comparisons of the means were conducted when the main effect of group or time or the interaction between group and time was significant. Fisher's restricted least significant differences criterion was used to maintain the a priori type I error rate of 0.05. In addition, we conducted ANCOVA using menopausal status as a covariate (data not shown). Because we did not observe any significant effects of menopausal status on any of the outcome measures, group data are presented. Spearman rank correlations were calculated to test the association among changes in weight, fat mass, waist circumference, and metabolic syndrome parameters.

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