Helen M. Seagle

Effects of aerobic fitness on fat oxidation and body fatness.

OBJECTIVE This study investigated the contributions of physical fitness and body composition to 24-h fat oxidation in adults under sedentary conditions in a whole-room calorimeter. METHODS The following measurements were studied in 109 adults (49 male/45 female) at least 36 h after a bout of exercise: 1) aerobic fitness level assessed by VO2max, 2) body composition determined by underwater weighing, 3) resting metabolic rate (RMR) after an overnight fast, and 4) 24-h energy expenditure (EE) and substrate oxidation determined in a whole-room calorimeter. While in the calorimeter, subjects were provided with a diet (15% protein, 30% fat, and 55% carbohydrate) estimated to produce energy balance on a sedentary day and of similar nutritional composition to their daily dietary intake. RESULTS We found strong negative correlations between VO2max and % body fat in both male and female subjects, but no relationship between VO2max and 24-h EE under the sedentary conditions of this study. In male subjects, VO2max (mL O2 x kg(-1) fat-free mass x min(-1)) was negatively related to fat oxidation (r = -0.397, P < 0.005), and fat oxidation was more closely related to fat mass (r = 0.434, P < 0.0002) than to fat-free mass (r = 0.165, NS). In contrast, none of these relationships were significant in females. CONCLUSION The results show that in male subjects under sedentary conditions, 24-h fat oxidation is positively related to body fat mass and negatively related to VO2max (the marker used here for level of physical fitness). This supports our hypothesis that regularly active males maintain lower body fat stores as the low contribution to daily fat oxidation from a lower body fat mass is counterbalanced by the high contribution to fat oxidation from daily physical activity. The lack of a relationship between VO2max and 24-h EE under the sedentary conditions of this study suggests that the major effects of physical activity on total daily EE and fat oxidation may occur during and relatively quickly after an exercise bout. Further, these data also suggest that cessation of regular exercise will likely be associated with a high risk of positive fat balance and weight gain.

Twenty-Four-Hour Metabolic Responses to Resistance Exercise in Women

Seven nonobese adult females (40 ± 8 years) were studied in a room calorimeter on a day that resistance exercise (REX) was performed (4 sets of 10 exercises) and on a nonexercise control day (CON). Twenty-four-hour energy expenditure (EE) on the REX day (mean ± SD, 2,328 ± 327 kcal·d-1) was greater than CON (2,001 ± 369 kcal·d-1, p < 0.001). The net increase in EE during and immediately after (30 minutes) exercise represented 76 ± 12% of the total increase in 24-hour EE. Twenty four–hour RQ on the REX day (0.86 ± 0.06) did not differ from CON (0.87 ± 0.02). Twenty four–hour carbohydrate oxidation was elevated on the REX day, but 24-hour fat and protein oxidation were not different. Thus, in women, the increase in EE due to resistance exercise is largely seen during and immediately after the exercise. The increased energy demand is met by increased carbohydrate oxidation, with no increase in 24-hour fat oxidation.

Obesity: overview of treatments and interventions.

This chapter provides a broad overview of weight-management interventions. We start with clinical assessment and the relevance of excess fat accumulation and then review specific interventions. These range from relatively low risk (e.g., lifestyle modifications) to higher risk but potentially a higher benefit for those individuals more compromised by their higher body weights. Ultimately, we encourage the reader to think about the treatment of obesity not just from an acute weight-loss perspective but also from the perspective of both prevention of weight gain and prevention of weight regain following the acute weight-loss phase.

CHAPTER 31 – Obesity: Overview of Treatments and Interventions

Obesity is a pervasive disease in the world. As excess weight is associated with a higher incidence of diseases such as diabetes, cardiovascular diseases, osteoarthritis, and some cancers, the burden of obesity is high. Obesity is a complex disease of multifactorial origins. However, there is simplicity in the underlying model of body weight change. The energy balance equation dictates that in order for body weight to change, there must be an energy imbalance. Either a change in energy intake or a change in energy output must occur so that body stores of energy are altered, causing a change in total body weight. Obesity is characterized by the accumulation of excess body fat. Prevention of obesity is the true future of weight management. Preventing excess weight gain from ever occurring should be an easier task than treating obesity once it is present. While obesity prevention can be targeted as a high priority, there is much to learn about how to do it effectively. There is a need for a concerted, integrated effort from all sectors of society to create an environment that is less obesity conducive. Despite the daunting nature of this task, the rapidity of the increase in obesity underscores the urgency in addressing the issue.

A Comparison of Three Prediction Equations for Estimating Energy Requirements

Abstract LEARNING OUTCOME: To determine the accuracy of three methods of predicting energy requirements across a range of energy needs. The accurate prediction of energy requirements is a challenge facing many dietitians. We have previously developed a regression equation using fat-free mass(FFM) to predict 24-hour(hr) energy expenditure(EE) based on whole-room indirect calorimetry. This equation was developed from calorimetry data where subjects were not performing any prescribed physical activity. Thirty female and 34 male subjects, aged 30.7 (+/−7.1) years, had measurements of body composition by hydrodensitometry, resting metabolic rate(RMR) using a ventilated hood system and 24-hr EE determined during a stay in a whole-room indirect calorimeter. During the stay in the calorimeter, subjects performed a low-intensity stepping and walking exercise to simulate usual sedentary daily activity. Subjects were primarily Caucasian (95% of sample) and all were weight-stable with a mean body mass index(BMI) of 23.4 +/−3.0kg/m 2 . Measured 24-hr EE was compared to three methods of prediction: 1) the regression equation based on FFM, 2) RMR and 3) the Harris-Benedict equation. An activity factor of 1.3 was applied to each method. The group mean difference (