Kinesiology 326, Fall 2013 abstract background

Carla Bejjani, Leann Berry, Cynthia Cano, Amy Clark, Rebecca Gray,

Nicholas Larkin, & Erin Terregrossa

KINESIOLOGY 326, Fall 2013

Numerous studies have documented that the abundance of visceral adipose tissue is highly correlated with increased risks of coronary heart disease, obesity, Type II diabetes, and ultimately mortality (Wang, Thornton, Bari, Williamson, Gallagher, Heymsfield, Horlick, Kotler, Lafarrere, Mayer, Pi-Sunyer, & Pierson, 2003; Isacco, Duche, Thivel, Meddahi-Pelle, Lemoine-Morel, Duclos, & Boisseau, 2013). Previous studies have also suggested that subjects with greater abdominal fat displayed impairments regarding substrate mobilization and utilization (Isacco et al., 2013). A small waist circumference accompanied by large hip circumference has been shown to be associated with a decreased risk of cardiovascular disease (Wang et al., 2003).

Waist circumference measurements have become a practical method with which to measure distribution of adipose tissue (Wang et al., 2003). The National Institutes of Health have published a guide about obesity treatment which suggests that waist circumference and BMI are the most available and reliable means to identify and monitor the onset of obesity (Wang et al., 2003). There is no set standard for measurement sites when determining waist circumference. A study conducted by Wang et al. (2003) discovered four most reproducible sites for measuring WHR which include: directly below the lowest rib, the narrowest part of the waist, midpoint between the lowest rib and the iliac crest, and immediately above the iliac crest. Wang et al. (2003) concluded that the measurements between sites were significantly different in some cases and therefore not interchangeable across studies. It is for this reason that waist circumference in this study was measured at the narrowest part of the waist and the largest part of the hips (typically around the greater trochanter). In this study a WHR greater than 0.75 is defined as an android body shape whereas a ratio less than 0.75 is defined as gynoid.

Differing factors contribute to substrate metabolism, including gender, exercise intensity, duration, fitness level, and nutritional status (Venables, Achten, & Jeukendrup, 2003; Astorino, 2000). Research has shown that at a given intensity, women show a greater dependence of FO than men (Isacco et al., 2013; Venables et al., 2003). In order to apply the principles of the WHR in which measurements are consistent, this study focused on the body shape of women (gynoid or android) and its primary sources of fuel for metabolism. Fuel use was observed by monitoring gas exchange data such as volume of oxygen consumption (VO₂), carbon dioxide production (VCO₂), and the respiratory exchange ratio (RER), which according to Venables et al., (2003) shows an inverse relationship between FO and an increase in RER. Isacco et al., (2003), studied the localization of fat mass and how it altered fuel oxidation in normal weight women during exercise; their findings showed that women with less abdominal fat had higher lipid mobilization and oxidation. This present study aims to investigate the effects of fat patterning in premenopausal women on lipid oxidation during steady state, graded exercise. It is hypothesized, relating with previous research, that women with a lower WHR will exhibit higher lipid-oxidation than those with a higher WHR.

Sixteen healthy woman of similar fitness level participated in this study. Women were categorized into two groups: gynoid (n=8) and android (n=8). Ethnicities included Caucasian (n=13), Filipino (n=1), and Hispanic (n=2). Each participant provided written informed consent after explanations of the experimental procedures and possible risk and benefits, and all procedures were approved by the University Institutional Review Board. A preliminary screening process was employed to establish that subjects: (a) were free from serious illnesses or previous injuries, (b) have not begun menopause, (c) VO_2max of 30-45 ml/kg/min, and (d) at least 2-5 hr/wk of physical activity, which would reduce their ability to complete the experiment. Subjects were asked to avoid strenuous high-intensity exercise the day before the test and were instructed to report to the laboratory after a 12 to 14-h overnight fast. The physical and physiological characteristics of the subjects are displayed in Table 1.

Prior to testing subjects’ age, gender, height, weight and body fat percentage were recorded into the personal computer attached to the metabolic cart. Each subject’s seat level and handle bar height were adjusted comfortably on the Velotron Dynafit Pro cycle ergometer (Velotron Dynafit Pro, Racermate, Seattle, WA, USA). Before the start of the experiment, the subjects were familiarized with the equipment and the procedures.

Participants underwent 1 day of testing, during which height and body mass were measured to determine BMI. Body composition was determined using a sum of three skinfold model, measured twice in rotational order at triceps, suprailiac, and thigh, and these values were used to calculate body density used to calculate body fat (% BF). In addition, circumferences were measured twice in rotational order at the narrowest part of the waist and hips in order to determine WHR.

Prior to testing, a heart rate (HR) monitor (Polar, Woodbury, NY, USA) was placed below the breast line to assess HR during exercise, and women were prepared for incremental exercise to fatigue on the ergometer during which pulmonary gas exchange data were obtained to determine VO_2max . Subjects initiated exercise at 30 W for 5 min, after which workload increased by 20 W increments every 3 min. When the subjects RER reached 1.0, the workload was increased by 20 W every min until volitional fatigue. Subjects wore headgear and nose clips and were instructed to breath into a three-way Daniels valve in order to assess gas exchange data for each breath. Participants were encouraged to exercise “all-out” by maintaining a high cadence rate (rpm) prior to each increase in workload in order to facilitate each transition. The metabolic cart (Parvomedics True One, Sandy, UT) was calibrated to gases of known concentrations along with room air temperature, humidity and barometric pressure before exercise. Variables obtained from this test include maximal determinations of VO₂ (L∙min⁻1 and mL∙kg⁻1∙min⁻1), HR, RER, VCO₂ and ventilation.

Data Analyses

Data are expressed as mean ± SD and were analyzed using the Statistical Package for the Social Sciences (version 20.0; SPSS Inc., Chicago, IL). Statistical comparisons were performed using a mixed ANOVA (2-way ANOVA with repeated measures) to obtain the analysis of variance between and within all subjects. An independent t-test was used to examine the statistical significance between the two different groups of subjects. The level of significance was set at a p-value of p<0.05. Comparison of data between groups analyzed visually analyzed using Microsoft Excel (Microsoft Excel 2010; Windows Vista, 7, XP).

A) B)

Figures 1A and B depict the decline in FO with the increase in exercise intensity for all subjects.
Figure 2A-B: Carbohydrate oxidation for gynoid (A) and android (B) shaped subjects

A) B)

Figure 2A and B depict the increase in carbohydrate oxidation with the increase in exercise intensity for android and gynoid shaped subjects.

Carbohydrate oxidation (CHO) across groups had a p-value of 0.708 and FO across groups had a p-value of 0.425. CHO and FO across watts had p-values of 0.000. Mean differences and p-values for subject measurements acquired from an independent t-test had p-values > 0.05 for all measurements except for WHR with a p-value=0.000.

Figure 3 shows an increase in RER with an increase in exercise intensity for both gynoid and android

The purpose this study was to investigate the effects of fat patterning in premenopausal women on lipid oxidation during steady-state exercise. It was hypothesized, relating with previous research (Isacco et. al., 2013), that women with a lower WHR (<0.75; gynoid shape) would exhibit higher lipid-oxidation rates than those with a higher WHR (>0.75; android shape). Previous studies have shown that the ingestion of carbohydrates prior to exercise can reduce the rate of FO in the subsequent bout of exercise (Achten, Gleeson, & Jeukendrup 2001). To ensure that FO would not be impaired by carbohydrate ingestion, the tests were performed after a 12 to 14 hour fast. Results demonstrated that there was no significant difference between the gynoid and android groups in regards to FO (p >0.05).

Data analysis rejected this study’s initial hypothesis, which stated that women with a lower WHR are more apt to burn fat. These findings are contrary to those found in Isacco et al. (2013), which demonstrated that a lower abdominal to lower body fat mass ratio was correlated with a higher ability to oxidize and metabolize fat. Since there is no widely accepted WHR standard in assessing android and gynoid subjects, each study utilizes a different set of guidelines; Isacco et. al (2013) grouped androids with a WHR > 0.78, while the present study used the WHR of 0.75. WHR was the only significant difference between present subjects (p-value = 0.000). Although their testing was somewhat longer than the present study (45 minutes vs. 25-30 minutes), both tests observed primary FO at a moderate intensity. Difference in results could be attributed to the inability to recruit the appropriate type of “android” subjects, which is discussed furthermore in limitations of the study. There were no significant differences in all subject traits including age, height, weight, and VO_2max (p-value > 0.05) especially with fat and carbohydrate oxidation rates. Also, the results may not show any significant difference because all subjects were required to be physically active and have a VO_2max between 30-45 L/min. This requirement may limit results as trained women are prone to have higher FO rates during moderate to intense exercise intensities (Astorino, Schubert, Palumbo, Stirling, & McMillan, 2013).

The most detrimental limitation of this study had to do with subject recruitment. Android subjects didn’t necessarily have their fat deposited around their waist, they simply had smaller hips. Isacco et al (2013) observed the same type of subjects, but the WHR that they used to distinguish was 0.78 rather than 0.75.

In effort to maintain instrumentation validity, the same equipment (e.g., ergometer, skin calipers, scale, measuring tape) were used to assess all measurements obtained by a single researcher. Selective attrition was not a threat to internal validity because none of the subjects withdrew from the study. The research environment in which subjects were closely observed along with the unfamiliarity of equipment may have influenced the participants’ reaction to the study thus not performing to maximal exertion. Another possible improvement of the study could have been using a larger sample size to increase the probability of witnessing a significant difference between the two groups. Additional limitations of this study include inexperience with the machines from the facilitators, subject not reporting accurate food intake. In order to validate subjects’ nutritional status we could have measured insulin levels prior to testing, which would have confirmed that subjects were in a fasted state. Self-reported data, such as amount of physical activity per week and food intake prior to testing, is limited by the fact that it cannot be verified.

Future studies can observe sedentary females in the two body shape categories to see how the outcome would change. Additionally, blood samples could be taken to assess glucose, plasma concentration and insulin levels in order to monitor their effects on substrate oxidation. Implementing dietary intake for the 24hrs prior to the test would allow us to control for food intake and observe how substrate metabolism would change accordingly.  

 
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