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' 4' ‘K i . . ‘v . . g I"_ _. ' v . ‘ u. ' ' -‘ g‘ ‘3 3' 21.; r \_ ‘ ‘ . i - ‘ A' '3 p I ' --. ', _ ’ 5 - . - ‘ ~-.. ..-. L.- u" im"""~vrw- -~' '~ 4*”? ”w. ‘mr. '9‘- -' - r . . m. ‘ ‘w This is to certify that the dissertation entitled Oxygen Consumption, Heart Rate and Blood Lactate Levels as Affected by Exercise Intensity, Meals and Diets in Humans During Rest, Exercise and Recovery presented by Kristian Lindsted has been accepted towards fulfillment of the requirements for Human Nutrition Ph ' D' degree in Major professor Date April 28, 1982 0~12771 MS U is an Affirmative Action/Equal Opportunity Institution MSU RETURNING MATERIALS: Place in book drop to remove this checkout from LIBRARIES . w your record. FINES Wlll be charged if book is ..... flu ~r ‘ returned after the date ' stamped below. ”Wfigngsw 92;: 21-13; .2 ' l.) I‘D‘ Oxygen Consumption, Heart Rate and Blood Lactate Levels as Affected by Exercise Intensity, Meals and Diets in Humans During Rest, Exercise and Recovery By Kristian Lindsted A DISSERTATION Submitted to Michigan State University in partial fulfillment of the requirements for the degree of Doctor of Philosophy Department of Food Science and Human Nutrition 1982 ABSTRACT Oxygen Consumption, Heart Rate and Blood Lactate Levels as Affected by Exercise Intensity, Meals and Diets in Humans During Rest, Exercise and Recovery By Kristian Lindsted One hundred linear regression equations (HROXCR) between HR (HR) and oxygen consumption (OXC) were developed based on 10 incremental exercise tests in each of 10 subjects. Both slopes and y-intercepts were found to be significantly inhomogenous within as well as among subjects. The inhomogeneity of the HROXCR was increased rather than decreased by using incremental HR. The HROXCR was singificantly affected by previous exercise but not by diet. The repeatability (R = 0.7) for the slopes and y-intercepts of the HROXCR indicates that the variation among subjects was larger than the variation within the subjects. The HROXCR observed during exercise was not followed during recovery. OXC returned to resting values faster than HR during early recovery (3-4 min). Duration rather than intensity was related to the HR recovery lag at greater than 65% max OXC. After 40 min of recovery the OXC had returned to the preexercise level, but the HR was still elevated 20 beats/min. The effects of 700 kcal meals from either fat, protein or carbo- hydrate on OXC during rest was investigated in five male subjects. The postabsorptive state served as control for each subject. The Kristian Lindsted mean OXC for control, fat, protein and carbohydrate meal respectively was 3.6, 3.8, 4.3 and 4.1 ml/minute/kg. The thermogenic responses were as follows: fat - borderline significance; protein - significant > 6 hrs; carbohydrate - significant > 3 hrs. Only following the carbohydrate meal was there a significant HROXC correlation (r = 0.5). It may be that the regulatory thermogenic response is related to car— bohydrate. Only the carbohydrate meal affected the RQ during rest (77 = 0.84 compared to 0.75). There were no significant treatment effects upon exercise RQs. There was no effect of meals or diets on the substrate utilization during exercise at 80% maxOXC. During rest, the carbo- hydrate meal caused a 3 to 4 fold increase in the blood lactate con- centration. During 40 min of recovery from exercise at 80% maxOXC after the control, protein and fat meals, the x for lactate decreased from 3 to 1 mM. However, following the carbohydrate meal, the x for lactate remained about 2 mM. ACKNOWLEDGMENTS The author wishes to express his appreciation to his major professor, Dr. R. Schemmel and to Dr. N. VanHuss, for their guidance, suggestions, and support throughout the research program and for their assistance in the preparation of the dissertation. Appreciation is expressed to Dr. N. Chenoweth, Dr. A. Sparrow, and Dr. N.G. Bergen for serving on the guidance committee. Special thanks are expressed to M.B. Savinski and L. Coleman for assistance with the research and to B. Andrea, D. Ankrap, B. Foran, C. Hoover, 8. Hughes, 6. Hunter, R. Kimbell, D.G. Kirsch, M. Todd, T. Riebow, T. Talsma, P. Thiry, C. Vossekuil, J. Snow, E.L. Andavan and K. Luxton for serving as subjects. The author is especially grateful to his wife, Cheri, for her understanding and assistance with typing. ii TABLE OF CONTENTS INTRODUCTION ......................... CHAPTER I - LITERATURE REVIEW ................ Introduction ....................... The Energy Equation ................... Heart Rate as a Measure of Energy Expenditure ...... Relation Between HR, SV, and Circulation ......... Thermogenesis ...................... Non-shivering thermogenesis ............. Cold-induced thermogenesis .............. Dietary-induced thermogenesis ............ Control mechanisms .................. Thermogenesis and exercise .............. Substrate Utilization .................. Glycogen ....................... Intramuscular Lipids ................. Control of Substrate Utilization ........... Effect of meals and exercise on substrate utiliza- tion ........................ Postexercise Lactate ................... Effect of exercise .................. Effect of diet .................... CHAPTER 2 - THE VARIABILITY OF THE HEART RATE-OXYGEN CONSUMP— TION RELATIONSHIP WITH TIME AND COMPARISON OF INDIVIDUAL REGRESSION LINES VS A COMMON REGRES- SION LINE FOR ALL SUBJECTS ............ Syn0psis ......................... Introduction ....................... Methods ........ ' ................. Subjects ....................... Measurements of oxygen consumption (OXC) and heart rate (HR) ..................... Test protocol .................... Measurements of resting HR and OXC .......... Treatment of data and statistical procedures ..... Results ......................... Correlation between HR and OXC at constant workload . Discussion ........................ 33 34 35 37 37 37 4O 4O 41 49 51 Page CHAPTER 3 - EFFECT OF DIET, PREVIOUS EXERCISE, AND RECOVERY UPON THE LINEAR REGRESSION BETWEEN HEART AND OXYGEN CONSUMPTION ................ 58 Synopsis ......................... 59 Introduction ....................... 60 Methods ......... - ................ 62 Subjects ....................... 62 Informed consent ................... 62 Diets ........................ 62 Measurements ..................... 66 Exercise tests .................... 66 Experimental protocol ................ 68 Statistical analysis ........ . ......... 69 Results ......................... 71 Effect of diet on the HROXCR during exercise ..... 7l Effect of previous exercise on HROXCR ........ 7l Effect of recovery on HROXCR ............. 74 Discussion ........................ lO4 Effect of diet and previous exercise ......... lO4 Recovery from exercise and HROXCR .......... l05 CHAPTER 4 — DIETARY INDUCED THERMOGENESIS DURING REST AND EXERCISE: EFFECT OF MEALS AND DIET ON OXYGEN CONSUMPTION AND ENERGY SUBSTRATE UTILIZATION DURING REST AND EXERCISE ............. llO Synopsis ......................... lll Introduction ....................... ll2 Methods ......................... llS Subjects ....................... ll5 Informed consent ................... llS Diets ........................ llS Measurements ..................... ll9 Exercise tests .................... lZO Experimental protocol . ._ .............. lZl Statistical analysis ................. l24 Results ......................... l25 Experiments during rest ............... l25 Exercise experiments ................. l32 Discussion ........................ l36 OXC during rest ................... l36 OXC during exercise ................. l39 Energy substrate utilization during exercise ..... I40 iv Page CHAPTER 5 — EFFECT OF MEALS AND DIET ON POSTEXERCISE BLOOD LACTATE LEVELS .................. l43 Synopsis ......................... l44 Introduction ....................... l45 Methods ......................... 147 Subjects ....................... l47 Informed consent ................... l47 Diet ......................... l47 Measurements ..................... l51 Exercise tests .................... l52 Experimental protocol ................ l53 Statistical analysis ................. l56 Results ......................... 157 Discussion ........................ l66 CHAPTER 6 - CONCLUSIONS ................... l7l BIBLIOGRAPHY ....................... l75 APPENDICES ........................ 197 LIST OF TABLES CHAPTER 2 - THE VARIABILITY OF THE HEART RATE-OXYGEN CONSUMP- CHAPTER 3 - TION RELATIONSHIP WITH TIME AND COMPARISON OF INDIVIDUAL REGRESSION LINES VS A COMMON REGRES- SION LINE FOR ALL SUBJECTS ............ Age, heightfi_weight, V02 max for_the ten subjects. The slopes 1 and y-intercepts Bo and the corre- sponding variances based on all ten trials in each subject is given .............. Calculated F-ratio for test of homogenity within the ten trials in each subject with observed HR (F-l) and with corrected HR (F-Z) ........ Repeatability R, calculated and critical F-ratio (a=0.05) for the slope B], the y-intercept Bo, the y-intercept corrected for resting heart rate Bo Cor, and 81-1 and Bo"1 Cor when the subject with a large deviation in the max V02 is disregarded ................... EFFECT OF DIET, PREVIOUS EXERCISE, AND RECOVERY UPON THE LINEAR REGRESSION BETWEEN HEART RATE AND OXYGEN CONSUMPTION .............. Physical characteristics of the two groups of five adult male subjects ............. Relative intensity of exercise for various tread- mill settings used in incremental exercise tests. Composition of meals and diets. The energy con- tent of the diets varied between 2,lOO and 2,400 kcal for the different subjects ...... Test of significant difference between the regression equations between HR and OXC for the five treatments and the regression equation for control ..................... vi Page 33 38 46 47 58 63 63 64 72 IO ll 12 Page Test of significance between the regression equations for two subjects exercised twice, one hour apart. Results are included with the regression lines corrected for the resting heart rate (cor) ............. 73 Comparison of mean recovery values and their respective standard deviation (SD) for eight trials in each of five subjects ......... 79 Mean recovery increamental heart rates after exercise on a treadmill at 4 different speeds, each speed maintained for 10 and 30 minutes, respectively. Mean of four subjects ....... 89 Mean recovery oxygen consumption in four sub- jects after exercise on a treadmill at four different speeds, two runs at each speed for 10 and 30 minutes, respectively ......... 90 Mean predicted oxygen consumption during recovery following exercise on a treadmill at four differ- ent speeds in four subjects. Each speed is repeated twice for 10 and 30 minutes, respec- tively. Time is given in minutes. Standard deviation (SD) is also given ........... 91 Mean difference (4 subjects) between the pre- dicted oxygen consumption and the actual oxygen consumption during recovery after running on a treadmill at four different speeds. The subjects ran at each speed twice for 10 and 30 minutes, respectively ....... 92 Mean values of 95% lower confidence limit (LCL) for predicted oxygen consumption (POXC), recovery oxygen consumption (ROXC), and the difference (DLCL) between LCL and ROXC in ml/kg/min follow- ing exercise on a treadmill at four different speeds (S) for 10 and 30 minutes (0), respec- tively. Mean of four subjects .......... 101 Test of significance for IRHR, ROXC and DOXC. . . 103 vii CHAPTER 4 - DIETARY INDUCED THERMOGENESIS DURING REST AND CHAPTER 5 - EXERCISE: EFFECT OF MEALS AND DIET ON OXYGEN CONSUMPTION AND ENERGY SUBSTRATE UTILIZATION DURING REST AND EXERCISE ............. Physical characteristics of the two groups of five adult male subjects ............. Composition of meals and diets. The energy con- tent of the diets varied between 2,100 and 2,400 kcal for the different subjects ...... Mean oxygen consumption following the ingestion of various meals for 5 male subjects in the resting state. Control was the postabsorptive state ...................... Mean respiratory quotient following the ingestion following ingestion of various meals for 5 male subjects in the resting state. Control was the postabsorptive state ............... Mean correlation coefficient (4) between HR and OXC during control, following a fat meal, pro- tein meal, and a carbohydrate meal. Number of subjects equal to 6 for control, 7 for fat meal, and 8 for carbohydrate meal. n=30 in each treat- ment for each subject. r=mean value for the subjects completing the treatment ........ EFFECT OF MEALS AND DIET ON POSTEXERCISE BLOOD LACTATE LEVELS .................. Physical characteristics of the two groups of five adult male subjects ............. Composition of meals and diets. The energy con- tent of the diets varied between 2,100 and 2,400 kcal for the different subjects ......... Blood lactate in arterialized blood for 6 hours following a carbohydrate meal, and in the post- absorptive state following an overnight fast as control. Mean of five subjects ......... viii Page 110 116 117 126 127 135 143 148 149 158 Page Mean blood lactate concentration during 40 minutes recovery from 20 minutes of exer- cise at 80% of maximal OXC in 5 subjects ..... 163 Bonferroni t for test of significance of post- exercise blood lactate concentration. CH-M is tested for interaction (between 5 and 40 minutes) against C and F-M. Total (40 minute) response to CH-M is tested against total res- ponse to F-M; and the postabsorptive (P) trials (C, F-D, CH-D) are tested against the absorp- tive (A) trials (F-M and P-M) at 5 minutes postexercise. There are four contrasts (n=4) ...................... 164 ix LIST OF FIGURES CHAPTER 2 - THE VARIABILITY OF THE HEART RATE-OXYGEN CON- 4 CHAPTER 3 - SUMPTION RELATIONSHIP WITH TIME AND COMPARI- SON OF INVIDIDUAL REGRESSION LINES VS A COMMON REGRESSION LINE FOR ALL SUBJECTS ..... Regression line between the OXC and the HR for a typical subject (#8) based on a single incre- mental exercise test ............... Regression line between OXC and HR in a typical subject (#8) based on ten incremental exercise tests ...................... Regression lines between HR and OXC for a hypothetical cases ................ Incremental and corrected HR ........... EFFECT OF DIET, PREVIOUS EXERCISE, AND RECOVERY UPON THE LINEAR REGRESSION BETWEEN HEART RATE AND OXYGEN CONSUMPTION .............. Two regression lines based on exercise trials one hour apart in one subject ............ Predicted OXC (POXC), lower confidence limits (LCL) and recovery OXC (ROXC) as a function of recovery HR ................... HR during 40-minute recovery. Mean of five subjects with eight exercise tests in each. . . . Predicted OXC (POXC), upper curve. Lower 95% confidence level for OXC (LCL), middle curve. Recovery OXC (ROXC), lower curve, as a function of time ..................... Difference between predicted OXC and recovery OXC (DOXC) as a function of time during 40 min- ute recovery ................... Page 33 42 44 53 58 75 77 80 82 84 CHAPTER 4 - CHAPTER 5 - DOXC as % of POXC vs recovery time (40- minute recovery) ................. Mean incremental HR (IHR) for four subjects during 40-minute recovery after exercise for 10 minutes at speed 4 (8.8 km/hr), lower curve; and speed 6 (12.5 km/hr), upper curve. . . Incremental HR during 40-minute recovery (RIHR) after exercise at speed 5 (10.5 km/hr) ...... Recovery OXC (ROXC) as a function of time . . . . Mean DOXC (difference between predicted and recovery OXC for four subjects .......... DIETARY INDUCED THERMOGENESIS DURING REST AND EXERCISE: EFFECT OF MEALS AND DIET ON OXYGEN CONSUMPTION AND ENERGY SUBSTRATE UTILIZATION DURING REST AND EXERCISE ............. OXC as a function of time ............ Respiratory Quotient (R.Q.) as a function of time for CH-M and Control (C) .......... Blood lactate as a function of time after a CH-M and C ...................... EFFECT OF MEALS AND DIET ON POSTEXERCISE BLOOD LACTATE LEVELS .................. Blood lactate concentration (mean of five sub- jects) in the postabsorptive state (following an overnight fast) as control (lower line) and following a 2.94 MJ carbohydrate meal (bananas) . Blood lactate concentration during recovery from exercise at 80% of maximal oxygen consumption for 20 minutes (mean of five subjects) ........ xi Page 87 93 95 97. 99 110 128 130 133 143 159 161 INTRODUCTION In order to evaluate the energy balance, it is necessary to have an accurate method for meaSuring both the energy intake and energy expendi- ture in free living individuals; but at present there is no generally accepted method for measuring the energy expenditure (Acheson et a1, 1980). The oxygen consumption (OXC) is an indirect method for measuring the energy expenditure. The heart rate (HR) has been used as a predictor of OXC in many studies (Bradfield, 1971) because it is simple to use. As pointed out by Durnin (1977), the correlation between the HR and OXC has not been thoroughly evaluated. The possible variation between tests of the linear regression between the HR and OXC has generally not been considered since the regression coefficient between the HR and OXC in a given experiment is very high. This was also true in our experiments where a continuous test with stepwise increased work rate was evaluated - r = 0.99. However, this does not mean that one will obtain the same correlation line if the test is repeated. Furthermore, it does not guarantee that HR and OXC will be correlated if only small changes in workload are considered, such as that observed in the resting state. Since many people spend most of their time at relatively low levels of activity it is important to know whether the HR can predict the OXC at rest and during low work loads. . Another question that has not been answered is whether the regres- sion equation for HR and OXC obtained during exercise is also valid during the recovery period following exercise. This is important, FJ since most subjects probably spend more time recovering from physical activity than actually engaged in it. If the regression equation obtained during exercise is still valid during recovery, this implies that HR and OXC return to the resting state at the same speed. While the OXC in low intensity exercise has been shown to return to resting values within 1-3 minutes, the HR recovery was slower (Linnarsson, 1974). Thus, it is important to evaluate the time relationship between HR and OXC during recovery and the effects of intensity and duration of the exercise. Diet is often mentioned as a factor that may alter the HROXCR (Durnin, 1978). Physical activity, however, rather than diet, was found by Lundgren (1946) to be the factor responsible. The effect of exercise and dietary modifications was therefore included in the study. The term "specific dynamic effect" goes back to Rubner (1902). Recently, however, Barrow and Hawes (1972) have forwarded the view that all the energy sources (fat, carbohydrates and proteins) have an equal thermogenic effect. Based primarily on overfeeding experiments in pigs, Gurr et a1. (1980) have concluded that it is carbohydrate rather than protein that exerts the primary thermogenic effect. There is presently much research activity (James and Trayhurn, 1981; Rothwell and Stock, 1979) in dietary induced thermogenesis (DIT). This is because variations in DIT are thought to be an explanation for obesity in many pe0p1e. However, a criticism of many of these studies is that physical activity is not well controlled. When a thermogenic response is measured as an increase in OXC or heat production, it takes very little activity to exceed the thermogenic effect of a meal. The 3 thermogenic response to a fat, protein and carbohydrate meal was therefore determined in human subjects by measuring the increase in OXC in the resting state. Many investigators believe that exercise will augment the thermo- genic response to meals and/or overeating (Bray et a1, 1974); however, others (Norgan and Durwin, 1980; Glick et a1, 1977) have found no such effect. It is possible, as pointed out by Bray, et a1 (1974) that there is a critical meal size below which no effect is seen. An increased thermogenic response to a normal sized meal could have important implications for weight control and was therefore investigated in the present study. It has been shown that a carbohydrate-free diet increases fat utilization during exercise compared to a carbohydrate-rich diet (Bergstrom et a1, 1967). It is therefore generally assumed that diet can modify substrate utilization; but the experimental evidence is conflicting. Hurni et a1 (1982) found an effect at rest but not during exercise. Ahlborg and Felig (1977) found an effect during low intensity exercise. Costill et al (1977) by elevating plasma FFA with fat meal and heparin found an effect during high intensity exer- cise; whereas Bergstrom et a1 (1969) found an effect during low but not high intensity exercise. Finally, Brooke (1981) found no effect regardless of the exercise intensity. However, it has been shown that when glycogen is depleted there is an effect of carbohydrate upon the carbohydrate utilization during exercise (Maughan et a1, 1978; BOnen et a1, 1981). It was therefore decided to study the effects of fat, carbohydrates and protein meals upon the substrate utilization without affecting the glycogen stores during exercise at 80% of the maximal OXC. The concept of a percentage of maximal oxygen consumption as an equalizer of the exercise load is almost universally used. It is, however, often criticized because people with the same maximal oxygen consumption may be in different degrees of endurance training. For this reason, many investigators have considered the use of blood lactate as an equalizer of the work load (Katz et a1, 1978). If the eXercise intensity is increased gradually, the blood lactate will increase slowly at first until it reaches about 2 mM/l (40-60% of maximal oxygen consumption). It then increases somewhat faster until it reaches about 4 mM/l (65-90% of maximal oxygen consumption), at which time it begins to increase very rapidly. Two and 4 mM/l lactate is arbitrarily defined as the aerobic and anaerobic thresholds, respectively (Skinner and McLellan, 1980). These levels of blood lactate, however, are of the same order as one could expect following a carbohydrate load (Owen et a1, 1980); and diet, therefore, presumably could affect these thresholds without having any effect upon the aerobic/anaerobic metabolism. For this reason, blood lactate was investigated during recovery from exercise at 80% of maximal oxygen consumption following different dietary treatments. CHAPTER 1 LITERATURE REVIEW LITERATURE REVIEW INTRODUCTION The measurement of the work output component by the heart rate (HR) method and some aspects of dietary induced thermogenesis will be the subject of this review. It will also include the effect of diet upon substrate utilization during rest and exercise, and dietary effects upon whole blood lactate production during rest and exercise. THE ENERGY EQUATION A simplified energy balance can be written as follows (Brobeck, 1981): Food Intake = Work Output + Heat Loss + Change in Energy Stores As Brody (1945) pointed out, provided an animal stays alive, body weight will eventually stabilize at some level. At this level, food intake has equilibrated with the other three components of the equation. The conventional concept that the body energy stores are controlled by a single set point, such as the size of the fat stores, has recently been challenged (Brobeck, 1981). It is argued that any set point depends upon a number of factors: (1) dietary composition, (2) work output, and (3) environmental temperature. Regardless of the set point, the above equation remains true at all times, provided all the terms are determined at the same point in time. It should be mentioned that the change in energy stores are not necessarily equivalent to a change in body mass, because different energy stores have different energy density (Garrow, 1974). The term "heat loss" is conveniently divided into several distinct components: Heat Loss = RMR + CIT + DIT + TISE + LUXC where: RMR = Resting metabolic rate CIT = Cold induced thermogenesis DIT = Dietary induced thermogenesis TISE = Energy required to build new tissue and store energy LUXC = Luxus consumption 4 Most of these tenns are well known, but a few require further comment. The basal metabolic rate (BMR) is well known, but because of diffi- culties in measuring it, RMR is often used instead (Dauncey, 1979). One cannot expect deposition of energy and synthesis of new tissue to be 100 percent effective, and consequently, Norgan and Durnin (1980) have proposed the TISE to account for the cost of change in tissue and energy stores. The tenn LUXC was proposed to account for the fact that overfeeding did not result in the expected weight gain (Apfelbaum, et a1, 1971). The term, however, is very controversial (Norgan and Durnin, 1980). HEART RATE AS A MEASURE OF ENERGY EXPENDITURE It is well known that the HR is linearly related to the oxygen consumption (OXC) (Astrand and Rodahl, 1977). This should not be interpreted as a causative relationship, since other factors affect the delivery of oxygen to the peripheral tissue. These factors include arterial-venous oxygen difference (AVOD), stroke volume (SV), and hemoglobin concentration (HEMC). OXC = HR x SV x AVOD Astrand, et a1 (1964) found that the AVOD increased gradually from about 7 m1 02/100 ml blood at rest to 17 ml 02/100 ml blood during maximal exercise, and that the SV increased from 63% of maximal volume at rest to 100% at 40% of maximal OXC, and then remained constant as the exercise load was increased further. It has been shown that the body position affects the relation between HR and OXC (HROXCR) (Andrews, 1969; Sato and Tanaka, 1973; Vokac, et a1, 1975). The primary factor here appears to be whether or not the legs are involved in the exercise, because of the effect venous pooling in the legs has on the venous return, and thereby, presumably, on the SV. Another factor that affects the HROXCR is environmental tempera- ture (Williams, et al, 1962; Rowell, et a1, 1966; Myhre, et a1, 1979; and Studier, et a1, 1975). The HR increases at both lower and higher temperatures with a minimum HR at about 20°C. While the cardiac out- put (CO) is unchanged at elevated temperatures, the SV is decreased with a corresponding increase in the HR. Training also appears to affect the HROXCR (Saltin, et a1, 1968; Pannier, et a1, 1980; Taylor, et a1, 1963). Training generally de- creases the resting HR and increases the blood volume, and thereby presumably the SV. Its effect upon the HROXCR is to increase the slope and decrease the OXC at a given HR. Sex and age are two factors that affect the HROXCR (Dill and Consolazio, 1962; Montoye, et a1, 1968; and Sheffield, et al, 1978). HR generally decreases with age in both sexes and it is higher in females than in males, which may partly be a training effect. As a result, women generally have less slope on the HROXCR than men. The effect of age is unknown because both HR and OXC decrease with age. Stress and added weight are also known to have an effect on the HROXCR (Taylor, et a1, 1963; Saltin, et al, 1968; and Borghols, et al, 1978). As expected, the effect of added weight would cause a linear increase in both the HR and OXC, and presumably there will be no change in the regression line if the extra weight is taken into account. The effect of stress, in general, is not well studied, but presumably it will have an effect upon both HR and OXC. However, it may still change the regression line, and in certain situations,'ithas been shown to have an effect upon the HROXCR. It is still controversial whether it is better to use an individual calibration line for the HROXCR for each subject or to use a common calibration line for all subjects (Bradfield, et al, 1970; Andrews, 1971; Bradfield, 1971; Payne, et al, 1971; and Astrand and Rodahl, 1977). Andrews (1971) reported that using incremental HR (Actual HR - Resting HR) removed the differences among the subjects. The effectsof meals and exercise on HROXCR are little studied, but it has been reported that previous exercise affects the HROXCR, presum- ably by decreasing the SV; however, the duration of this effect is not 10 known. Conflicting results have been reported for the effect of meals on HROXCR; thus, Lundgren (1946) found it to be due to physical activity, but Schutz, et al (1981) have recently reported an effect of meals. RELATION BETWEEN HEART RATE, STROKE VOLUME,_AND CIRCULATION There are many factors controlling the HR, but the central nervous system (CNS) plays a dominant role (Nyberg, 1981). Thus, during supine rest, the sympathetic nervous system contributes about 25% to the control of the HR, while the parasympathetic system dominates; but at maximal exercise, the sympathetic nervous system's contribution is virtually 100%. The parasympathetic contribution decreases simultaneously to almost zero at maximal exercise. During acute circulatory stress, such as exercise, the arterial pressure is controlled almost entirely by nervous reflex mechanisms (Guyton, 1981). However, it has been shown (Billman, et a1, 1981) that the baroreflex control of the heart rate is reduced by cen- tral blood volume shifts (i.e., a smaller decrement of HR is obtained by a given systolic blood pressure increase, when central blood volume is increased). It is well known that HR decreases with training (Lewis, et a1, 1980). These authors found that the bradycardia of training was not due to an autonomic component, but that the decrease in HR paralleled a decrease in OXC during constant workload; and they concluded that it might be due to the cardiac enlargement. However, it has also been shown by some (Ekblom, et al, 1972; Gulbring, et a1, 1960; and Pace, et a1, 1947) that an increase in blood volume (as also occurs during exercise training) increases the oxygen delivering capacity, which 11 could operate through an effect on the SV. Apparently, however, this is not the case (Ekblom, et a1, 1976); and the necessary adjustments are made in the oxygen extraction. It has been observed that dehydration, whether caused by heat exposure or exercise, causes a decrease in plasma volume (Saltin, 1964a; Saltin, 1964b; and Costill and Fink, 1974). In submaximal exercise following the dehydration, SV was decreased and the HR increased, but at maximal exercise, there was no difference. Damoto, et a1 (1966) found that a change in body position from supine to standing caused a decrease in SV and an increase in HR, with only a slight decrease in cardiac output. Roberts and Wenger (1979, 1980) have recently obtained similar results for the SV and HR. Additionally, they found that at high environmental temperatures, the skin blood flow increases, compared to cooler temperatures. This leads to an increased cutaneous blood flow in order to divert the metabolic heat. However, at high levels of skin blood flow, peripheral vascular pooling and fluid losses by filtration leads to reduced central venous pressure. This, in turn, lowers SV and increases HR. Reflexes which arise from receptors in working muscles produce vasoconstriction in a number of central and peripheral vascu- lar beds. In the long term, physical conditioning and heat acclimation lead to increases in sweat output during thermal stress, which de- creases the loss of vascular volume due to exercise and heat stress (because of more effective cooling and less cutaneous pooling of blood). Senay (1970) and Gaebelein and Senay (1980) have likewise found that endurance training results in modification of the vascular dynamics during exercise; that is, vascular volume becomes stabilized. In the untrained individual, heat exposure exaggerates body fluid shifts during exercise. With training, stability of the vascular volume is attained during heat exposure, but maximum protective responses towards exercise in heat are only gained upon heat acclimation. It has been shown (Nadel, 1980; and Nadel, et a1, 1980) that plasma volume is lost continuously throughout exercise, particularly at higher intensities, but the loss is most drastic during the first six minutes (at 70% of maximal OXC). This may be the reason why the HR continues to increase throughout exercise (80% maximal OXC): but most drastically at the beginning (Tanaka, et a1, 1979) and does not return to preexercise levels until after 45 minutes of recovery. There are mechanisms to compensate for loss of vascular volume during exercise. Thus, vasoconstriction in the splanchnic (Rowell, et a1, 1968) and renal (Grimby, 1965) vascular beds has been observed during exercise. Further reduction of blood flow to the non-exercising muscle also occurs (Johnson and Rowell, 1975). Finally, it has been demonstrated that during heavy exercise, as it becomes increasingly difficult to compensate for loss of vascular volume by increased HR, a cutaneous vasoconstriction superimposes itself upon the vasodilator drive at a certain point as skin blood flow increases (Brengelmann, et a1, 1977; Johnson, et a1, 1974; and Nadel, et a1, 1979). At a given intensity of exercise, it has been demonstrated (Nielsen, et al , 1971; Greenleaf and Castle, 1971; and Nadel, et a1, 1980) that the internal body temperature is higher in dehydrated subjects compared to normally hydrated subjects at a given work 13 intensity. It has also been demonstrated that dehydration causes a decrease in SV during exercise (Saltin, 1964b; and Nielsen, et a1, 1971). Thus, the circulatory instability during exercise depends upon the initial state of hydration (Nadel, et a1, 1980). Therefore, the variation in total body water with muscle glycogen changes may become important (Olsson and Saltin, 1970). THERMOGENESIS Thermogenesis has recently received c0nsiderable interest because of its possible role in the regulation of body weight or body energy stores. It is believed that the overweight of genetically obese mice (ob/ob) is primarily due to decreased energy expenditure (Trayhurn, et a1, 1979); and the ability of young lean rats to prevent obesity is probably due to increased dietary induced thennogenesis (DIT) (Rothwell and Stock, 1979). Non-shivering Thermogenesis Shivering involves the contraction of the muscles in order to produce heat. Non-shivering thermogenesis (NST), on the other hand, takes place without muscular contraction. Jansky (1973) has divided NST into basal NST and regulatory NST. The basal NST constitutes the heat production involved in BMR, while the regulatory NST is produced in response to specific thermoregulatory requirements. It has not been determined if DIT is regulatory or basal (Dauncey, 1979). Cold-induced Thermogenesis It is sometimes assumed that cold induced thermogenesis (CIT) need not be considered in man, since he does not normally expose himself to 1h cold severe enough to induce a metabolic response (Garrow, 1978). However, Dauncy (1979) found a significant thermogenic response in man due to slight (6°C) changes in ambient temperature, which indicates that man at least has the capacity for CIT (NST). Obese people have more thermal insulation than lean counterparts, which results in a reduced heat loss. And obese individuals appear to have a lower. metabolic rate in.the cold, compared to normal individuals (Buskirk,- et a1, 1963; Jequier, et a1, 1974; and Keatinge, 1960). By analogy to obese mice (ob/ob), this, however, may be due to a decreased CIT (Trayhurn, et a1, 1979). The increased metabolic rate of Eskimos in the cold may be a result of their high protein diet (Heinbecker, 1931). Dietary-induced Thermogenesis (DIT) A number of terms have been used for DIT: post-prandial thermo- genesis, specific dynamic action, and luxus-consumption. However, each covers more or less well-defined aspects of DIT. Thus, postpran- dial thermogenesis refers to the increased metabolic rate which follows a meal; specific dynamic action is the response in metabolic rate to a protein meal; and luxus consumption relates to the presumed increase in heat production following overeating. DIT covers both the immediate and long-term increase in heat production directly related to feeding, and this term is commonly used today. The basal DIT consists of the inevitable energy cost of digesting, absorbing, and processing or storing substrates, such as conversion of glucose to glycogen or fat and its storage in tissue, which may need to be synthesized. LUXC, on the other hand, is purely regulatory, if it exists at all (Trayhurn and James, 1981; James and Trayhurn, 1981). 15 The most convincing evidence in support of LUXC comes from a study in pigs (Miller and Payne, 1962) fed a low protein diet. On the low protein diets, the piglets ate five times as much energy as the ones on a high protein diet, without gaining any more weight. These studies have recently been repeated by Gurr, et a1 (1980). Similar experiments have also been carried out in rats fed a "cafeteria diet" (Rothwell and Stock, 1979). These authors also found that insulin plays a role in the DIT (Rothwell and Stock, 1981). This phenomenon has also been found in adult human subjects (Miller and Mumford, 1967). In some of the animal studies, there is reason to seriously question if the acti- vity of the animals was controlled. Thus, Gurr, et a1 (1980) states that activity could not be involved, since the pigs were chained. However, it is easy to conceive that the chaining could cause the animals to have even more muscular activity; and there is evidence that diet may affect activity (Hart, 1978; Schemmel, 1967). The study in piglets (Gurr, et a1, 1980) was also carried out in older pigs, and there, the excess energy intake on a low carbohydrate diet was stored as fat. In the cafeteria-fed rats (Rothwell and Stock, 1979), an increased metabolic response to norepinephrine is also seen in cold acclimatized rats; and warm adapted rats cease shivering much sooner when exposed to cold after being fed a "cafeteria diet" compared to a chow diet. This has led to the view that CIT and DIT are based on a similar mechanism (Trayhurn and James, 1981). 16 Control Mechanisms Brown Adipose Tissue According to recent studies by Foster and Frydman (1978a, 1978b, and 1979), brown adipose tissue (BAT) is the major site of NST, while skeletal muscle plays little or no role. According to the works of Nicholls (1979), thermogenesis is initiated by the release of norepinephrine, which binds to a receptor on the plasma membrane of the brown adipocyte. Adenyl cyclase is then activated and C-AMP is produced. This in turn activates the triacylglycerol lipase which causes release of FFA and glycerol. When the FFA's are oxidized in the mitochondria, protons (H+) are produced which pass through the mitochondrial membrane. Normally the passage of H+ back through the membrane is linked to the synthesis of ATP, but in BAT, the H+ gra- dient can be dissipated by the movement of H+ through a proton con- ductance pathway, without ATP synthesis in association with a specific protein (uncoupling protein) unique to BAT. Joy (1963) has demon- strated a metabolic response of cold acclimatized subjects to NE. Hormones Kuroshima and Yahata (1979) have shown that glucagon has twice the thermogenic response of norepinephrine, and that unlike the response to NE, the glucagon response is not affected by cold accli- matation (although reduced by heat acclimatation). Danforth and Burger (1981) state that the two hormones involvedin regulation of thermogenesis are thyroid hormone (T3) and centrally released catecholamines (NE). They seem to work in combination to regulate cellular thermogenesis. 13 appears to be responsible for 17 slow adjustments, while NE with its fast disappearance, appears to regulate the fast adjustment in thermogenesis. Thyroid hormones appear to regulate the sensitivity of BAT to NE. Shetty, et a1 (1979) found that during energy restriction, when the calorigenic hormones (T3 and NE) decrease, there was a decrease in thermogenesis. But when levadopa (a precursor of NE) was given, there was no decrease in BMR, despite a fall in T3. This indicates that NE is the primary short-term regulator of thermogenesis. Thermogenesis and Exercise Miller, et a1 (1967) found an almost 60% increase in energy expen- diture during exercise following a 4.75 MJ meal. The subjects partici- pated in a mild stepping exercise (mounting an 11-inch step 12 times per minute for 30 minutes). Apfelbaum, et al (1971) likewise found an increase in energy expenditure (20-30%) during exercise following a 6.2 MJ supplement per day for 15 days. Bray, et a1 (1974) reported that breakfasts of 4.2 or 12.6 MJ increased the RMR by 10% and the metabolic rate following exercise by 20%. Neither response was affected by the size of the meal. Bray, et a1 (1974) found no thermic effect during exercise after overeating (16 MJ/day) for 30 days. In contrast, Swindells (1972), found no effect of exercise following meals of 2.6-3.8 MJ. Bray, et a1 (1974) has concluded that this may be due to the smaller size of their meals. Norgan and Durnin (1980), during a six-week over-feeding study, found no thermic effect during exercise, when the weight gain was taken into consideration. 18 SUBSTRATE UTILIZATION It is well established both from the respiratory quotient (RQ) 14C turnover studies (Ahlborg, (Christensen and Hansen, 1939) and from et a1, 1974) that in the resting postabsorptive state FFA is the major energy substrate. During rest as well as exercise, it is, however, necessary to consider the availability of substrate. During exercise it also becomes necessary to account for both the type of exercise, and its duration and intensity. Furthermore, the two major substrates (fat and carbohydrate) can be supplied intramuscularly or through the blood. Glycogen Above 90% of maximal oxygen consumption, glycogen is the most important substrate, but it is far from depleted at exhaustion due to the relatively short.intensity which exercise of this duration can be sustained (Hultman & Bergstrom, 1973). At 70-80% of maximal oxygen consumption, glycogen concentration decreases in a curvilinear fashion and the time of exhaustion often coincides with glycogen depletion (Hultman and Bergstrom, 1973). Below 60% of maximal oxygen consump- tion, muscle glycogen, however, is not depleted at exhaustion; but liver glycogen may become a limiting factor because blood glucose is a very important substrate (Hultman and Nilsson, 1973). Intramuscular Lipids Below 60% of maximal oxygen consumption, FFA is the most important substrate; however, blood born FFA only accounts for about 50% of the total lipid oxidation, and the rest is derived from local lipid stores (intra- and intermuscular lipid stores). It has also been 19 shown that utilization of blood born FFA is proportional to the arterial concentration (Hagenfeldt and Wahren, 1972; Essen, 1977). Intramuscular lipid stores appear to supply FFA whenever blood born substrates are not available in sufficient quantity. Different modes of exercise involve different muscles to different degrees. The higher the work intensity, the more the type II fibers are recruited, and it has been shown that type II fibers are more likely to use glycogen as substrate than type I fibers. Furthermore, type I fibers can continue to use intramuscular fat as substrate even if the glycogen stores are depleted (Essen, 1977). Control of Substrate Utilization Glucose Several reactions in glycolysis are nonequilibrium: glucose transport, hexokinase, phosphofructokinase, and pyruvate kinase; and none of these pathways appear to be substrate saturated. Thus, blood glucose appears to be the flux generating step; the blood glucose, in turn, provides a feedback link between the glucose utilization and the rate of glycogenolysis in the liver (Newsholme and Crabtree, 1979). The muscle hexokinase shows product inhibition (G-6-P), whereas inorganic phosphate (Pi) is an activator. Thus, when G-6-P builds up in the cell, hexokinase is inhibited and glucose concentration will increase until it reaches equilibrium with the plasma level. The phosphofructokinase (PFK) is activated by ADP, AMP, Pi and creatine-P and inhibited by the ATP/F-6-P ratio and creatine-P. Thus, glucose transport, hexokinase and PFK act in concert to control the flux of 20 glucose (Newsholme and Start, 1973; Newsholme, 1977; Newsholme and Crabtree, 1979). ‘ Glycogen Glycogen utilization is regulated by the enzyme phosphorylase, which exists in two forms (a and b). Phosphorylase b is under meta- bolite control: ATP and G-6-P inhibit, whereas AMP and Pi activate. Thus, its activity is increased in concert with PFK to insure adequate substrate supply if the demand is higher than can be supplied by blood glucose and FFA. Under the influence of epinephrine (E) and nervous impulse, phosphorylase b is converted to phosphorylase a, which i always has maximal activity; the result being that during exercise of high intensity (with release of NE from CNS and E from the adrenal nedulla); particularly at the onset of exercise, glycogenolysis is fully activated (Rnflkes and Cohen, 1979; Galbo, et a1, 1977; Essen, 1978; Newsholme, 1977). The glycogenolysis during heavy exercise is of sufficient magnitude to prevent utilization of blood glucose and can actually lead to a net release of glucose from the working muscle (Wahren, 1970; Ahlborg, et a1, 1974; Essen, 1978). EEA_ Citrate generated by the metabolism of FFA will inhibit PFK, and, therefore, glucose utilization as long as sufficient substrate (FFA) to cover the demand is present. As the intensity of exercise increases, sufficient oxidation of FFA is no longer possible and AMP, NH4+, Pi, and FDP increase and release PFK from the citrate inhibition, thereby facilitating the increase in glucose utilization (Newsholme, 1977). 21 Hormonal Control It has been shown that E increases C-AMP which activates pro- tein kinase that phosphorykfles a phosphorylase kinase, which in turn converts the phosphorylase a to phosphorylase b. Recently, it has also been demonstrated that E also causes phosphorylation of a protein (inhibitor-l) which inhibits the phosphorylase phosphatase that dephosphorylate phosphorylase a to phosphorylase b. The above reac- tions are also stimulated by CNS stimulus (Foulkes and Cohen, 1979). Insulin decreases during exercise, and the decrease appears to be caused by the increased a-adrenergic activity, which inhibits the insulin secretion. Glucagon, on the other hand, increases during prolonged exercise, and this increase correlates with a decrease in the blood glucose concentration. At the same time, there is an increase in adrenal E, and these hormones also control the output of glucose from the liver. NE and E increase with the intensity of exercise, while glucagon is primarily affected by the duration of exercise when blood glucose decreases. Exercise also causes changes in growth hormone and cortisol (Galbo, et a1, 1977). Other Factors Caffeine has been shown to affect substrate utilization (by increased lipid oxidation, both during rest (Acheson, et a1, 1980) and during exercise (Costill, et a1, 1978), presumably by FFA mobiliza- tion. Training increases fat utilization (Johnson, et al, 1969). It is interesting to note that during heavy exercise, there is an increase in glucose utilization despite a decrease in the insulin/ glucagon ratio (Wahren, 1979). The fall in insulin during exercise 22 decreases with training (Wirth, et a1, 1979). During exercise, kinin is liberated from kininogen and this has been shown to greatly increase the effect of insulin on glucose uptake by skeletal muscle in man (Dietze, et a1, 1980). Nicotinic acid decreases FFA mobili- zation from adipose tissue, and heparin increases FFA mobilization. Costill, et a1 (1977) found that elevating plasma FFA with heparin at 70% maximal oxygen consumption decreased the rate of muscle glycogen utilization by 40%. However, experiments where adipose tissue lypolysis was blocked with heparin, showed there was no effect on glycogen utilization at high intensity work (Bergstrom, et a1, 1969). It is possible that greatly elevated FFA (by heparin in combination with a fat meal) does increase, even though a decreased blood FFA does not affect fat oxidation at high intensity work. Effect of Meals and Exercise on Substrate Utilization Hurni, et a1 (1982) found that during rest the diet quickly affects the substrate utilization, but during exercise of relatively low intensity, it had no effect upon the substrate used. As will be described in the following, many investigators have found an effect of diet upon substrate utilization during exercise; however, it is necessary to consider whether or not the glycogen stores were affected, as well as the intensity of exercise. Hurni, et a1 (1982) used a whole body calorimeter for determination of R0, and since the subjects were fed regularly, there is no reason to expect a signifi- cant effect upon the glycogen stores. 23 Effect of Meals on Blood Substrate Levels Stock (1980) found that a 1.67 MJ meal after one day of fasting significantly decreased the blood FFA level and increased blood glucose. Owen, et a1 (1980) similarly found that after a typical American breakfast (3.2 NO), blood glucose, lactate, and tri- glycerides increased for 2-3 hours; whereas blood levels of FFA were depressed for about 4 hours. Alanine and total amino acids were also increased, while urea nitrogen was depressed for at least four hours. Crapo, et a1 (1981) likewise found an increase in blood glucose and insulin, while FFA were depressed following a standard meal. Low Intensity Exercise Without Any_Change in Muscle Glycogen Luyckx, et a1 (1978) studied the effect of 100 g of orally ingested glucose upon plasma glucagon, FFA, and insulin. During rest, they found the expected increase in blood glucose and insulin, and a decrease in FFA and glucagon. The glucose was ingested during exercise (50% maximal oxygen consumption) or before the start of exercise. When preexercise glucose was compared to no glucose intake, blood glucose was elevated the first two hours of the exercise period. From 2 to about 3% hours, the blood glucose was depressed compared to control (no glucose), with a rebound after about 4 hours. As expected, plasma insulin fell in the control trial, but after the preexercise glucose meal, insulin rose in the same manner as in the resting state. After glucose, the plasma FFA was depressed in the same manner as during rest, whereas in the control trial, the FFA continued to rise throughout exercise. Preexercise glucose ingestion also prevented the expected increase in glucagon. When the glucose 2A was ingested after 15 minutes of exercise, the raise in blood glucose was reduced by about 1/3 compared to the preexercise glucose trial. Plasma insulin neither rose nor fell, and plasma FFA and glucagon rose, although less than during the control experiment. Using the same experimental protocol with 100 g 13C-glucose as metabolic tracer, Pirnay, et a1 (1977) found that ingestion of glucose after 15 minutes of walking on the treadmill did not affect protein utilization (l-2%), but increased the percentage of energy derived from glucose. It significantly reduced the utilization of endogenous glucose. Ahlborg and Felig (1977) studied the effect of ingestion of 200 g of glucose on substrate utilization during exercise at 30% maximal oxygen consumption for 4 hours. They found that arterial glucose increased 35%, arterial glycerol decreased 65%, and FFA failed to increase for 2 hours of exercise in the glucose-fed group compared to control. Plasma insulin increased two- to three-fold, but glucagon levels decreased 70% compared to control. Glucose uptake in the leg (by catheterization) was increased 55% compared to 35% in controls, and splanchnic glucose output was about 110% increased, whereas splanchnic uptake of gluconeogenic precursors was decreased (80%) compared to control. So at low levels of exercise (<60% of maximal oxygen consumption), preexercise glucose increases glucose utilization and decreases fat oxidation, and decreased hepatic gluconeogenesis. The ingestion of glucose, while increasing total glucose utilization, spares the endogenous glucose. It appears to make a difference if the glucose is ingested before or during exercise, and these changes 25 are hormonally determined. Low Intensity Exercise with Glycogen Depletion It has been observed that a greater proportion of an oral glucose load escapes the hepatic retention in glycogen depleted subjects com- pared to control (Maughan, et a1, 1978). This glucose is taken up preferentially by the depleted muscle. Rennie and Holloszy (1977), however, found that a high plasma FFA level, which occurs after glycogen depletion, inhibits muscular glucose uptake as well as its oxidation. Ravussin, et al (1979) studied the effect of exercise one hour following 100 g orally ingested 13C-glucose at 40% of maximal oxygen consumption in normal controls and glycogen depleted subjects. The major difference between the two groups was that the glycogen depleted subjects used primarily fat as substrate (70%), whereas the control subjects used primarily carbohydrate (65%). The exogenous glucose represented 20% and 24%, respectively. In the depleted subjects, plasma FFA remained 2-3 times higher than in control. So despite glycogen depletion, these subjects did not use exogenous carbohydrate to a higher extent. During exercise following glycogen depletion (by prior exhaustive exercise) and either a normal-, low-, or high-carbohydrate diet, a lower RQ, blood lactate, blood glucose, and blood triglycerides were found compared to elevated plasma FFA and plasma glycerol following a low carbohydrate diet than a high CHO diet. The control (normal) was very ' similar to the high carbohydrate diet in all aspects studied (Maughan, et a1, 1978). 26 High Work Intensity and GlyCOgen Depletion Bonen, et a1 (1981) used a regimen consisting of exhaustive exercise followed by about 40 hours of fast to deplete muscle and liver glycogen. The authors then studied the response to ingestion of carbo- hydrate (1.5 g/kg) 15 minutes prior to exercise or 3-5 minutes after the start of exercise. An exercise group with no glucose intake, and a rest group with glucose were used as control. As one could expect, the exer- cising control had no increase in blood glucose, and the increase during exercise was less than during rest, both in regard to blood glucose and insulin. During these workloads (80% maximal oxygen consumption), the preexercise glucose group had an initially sharp increase in both glucose and insulin (prior to exercise) followed by a sharp decrease during exercise (25 minutes) and a moderate increase during recovery. The during exercise glucose group of course did not have the preexercise increase, but both blood glucose and insulin was very similar to the pre-exercise glucose group, during exercise, with a more sharp increase during recovery. Maughan and Poole (1981) compared subjects with depleted, normal, and supercompensated glycogen stores at 105% of maximal oxygen consumption. Because of the rapid production of lactate at this high workload, it was not possible to determine substrate utilization (invalid RQ), but depleted subjects had lower blood glucose than normal and super- compensated subjects. Martin, et a1 (1978) studied the effect of exhaustive exercise fol- lowing a normal-, high carbohydrate-, and high-fat-diet for 3 days in 27 humans. The high fat diet provided 90% of energy from fat and the high carbohydrate diet, 75% of energy from carbohydrate. The effect of these dietary regimens on muscle glycogen are uncertain, but they may very well have had a significant effect, particularly since the exercise was exhausting. However, the high fat-protein diet had significantly lower R0 than either the mixed or high carbohydrate diet, and the blood con- centration of FFA was elevated. fligh,Work Intensity Without Glycogen Depletion Jones, et a1 (1980) compared heavy exercise (70% maximal oxygen consumption) with light exercise (40% maximal oxygen consumption) during 40 minutes. As expected, relatively less fat was used during the heavy (14C) was unchanged from work. During light work, palmitate turnover rate Crest, but a 40% decrease was observed during heavy work, as well as a fall in plasma FFA. However, during heavy work, plasma glycerol was increased (5-fold) compared to light work. This was interpreted to mean that heavy work caused a shift from adipose tissue lipolysis to muscle lipolysis. Foster, et a1 (1979) compared the effect of 75 g of glucose taken before exercise with a standard liquid meal (composition similar to a normal American diet)(water was used as control) during exercise to exhaustion at 80 and 100% of maximal oxygen consumption. The authors concluded that FFA mobilization was impeded by glucose ingestion. They also found a significant decrease in serum glucose following the glucose meal after 30 minutes of exercise compared to control, despite a higher initial level. They further reported an increase in the RQ following the oral glucose load compared to control. This difference, however, was not 28 significant. Mainly on the strength of the decreased serum FFA, the authors concluded that a glucose meal increased utilization of glucose as substrate; it is, however, necessary to also consider intramuscular FFA mobilization, and the plasma level of substrates is no certain indication of substrate utilization during heavy exercise. Conclusions During rest, it is well established that the diet affects the substrate utilization, and this probably extends to exercise of low intensities (<60% of maximal oxygen consumption). However, dUring heavy exercise, there is little support for this hypothesis. During rest and low intensity exercise, blood borne substrates (FFAand glucose) are of major importance in the supply of energy, but during heavy exercise, intramuscular substrates assume an increasing role and this change is mediated through hormones (insulin, glucagon, and E) and CNS. As a consequence, one would not expect diet to have a major effect upon the substrate utilization unless intramuscular substrate is depleted; but the experimental evidence is inconclusive at present. POSTEXERCISE LACTATE Effect of Exercise At the start of low level exercise, there is a rapid release of lactate from the exercising muscle (100-150 mmol/min/lOO ml), which gradually decreases toward resting level during 1 hour exercise. At the same time, there is net release of glucose (the first 2-3 minutes), indicating rapid glyconeogenesis. Soon, however, net uptake of glucose from the working muscle is observed. 29 As the work intensity increases, so does the lactate production. However, when a given work intensity is maintained for a sufficiently long time, the lactate concentration is generally considered to remain fairly constant once equilibrium has been reached (Hermansen, 1971). Freund and Gendry (1978) have fitted mathematic functions to the lactate response during recovery at rest. The blood lactate during recovery continues to increase during the first 2-6 minutes (depending on work intensity) of recovery, while there is a rapid decrease in the intra- muscular lactate. After 10 minutes, there is very little difference between muscle and blood lactate (Freund and Gendry, 1978). , Skinner & McLellan (1980) have divided exercise into three phases (l-III). During phase I, the R0 is between 0.7 and 0.8 and little or no lactate is formed during this low intensity steady state exercise. Between 40 and 60% of maximal oxygen consumption, phase II is reached and blood lactate level is about doubled. ,When the work intensity is increased further (65-90% maximal oxygen consumption), the blood lactate will rise above 4 mM, and then begin to increase rapidly as the subject approaches his maximal oxygen consumption. Above a subjects maximal oxygen consumption, blood lactate continues to increase with time and no steady state is reached. (Therefore, R0 is no longer a valid measurement of the substrate utilization.) The sharp rise in blood lactate with the increase in work intensity after a blood level of about 4.mM is reached (MacDougall, 1978; Green, et a1, 1979), corresponds to the anaerobic threshold. The early research by Hill, et a1 (1924) concluded that lactate was produced when there was an insufficient oxygen supply. It is well known 30 that training decreases lactate production during exercise at the same absolute work load (Hermansen, 1971; Johnson, et a1, 1969). The argument is used that since the total oxygen consumption is not increased follow- ing training or breathing a high oxygen gas (60-lOO% oxygen) (Holloszy, 1976; Welch, et al, 1977; Skinner & McLellan, 1980; Graham, 1978), hypoxia cannot be the cause of lactate production. However, this is probably incorrect, since under conditions where lactate is produced, it is reconverted to glucose in the liver or oxidized in other muscle fiber that is not hypoxic and therefore probably uses the oxygen saved during anaerobic glycolysis (for example, to reconvert lactate to pyruvate). Bylund-Fellenius et a1. (1981) recently presented strong evidence that the oxygen partial pressure in the exercising muscle indeed determines the lactate production. It has been shown that the muscle respiratory capacity is of primary importance in determining the work rate at which blood lactate accumu- lation begins (Ivy, et a1, 1980), and it is well known that type I fibers have higher respiratory capacity and capillary density than type II B fibers (Essen, 1978). It is well known that type I fibers are prefer- entially recruited at low work intensity, and both the recruitment pattern, respiratory capacity, and fiber composition may be affected by training (Saltin, et a1, 1977; Baldwin and Winder, 1977; Booth, 1977). The mode of exercise (intermittent vs continuous) also affects the lactate production (Essen, 1978). Intermittent exercise of twice the exercise intensity produced the same blood lactate level as continuous exercise. This difference is best explained by a greater oxygen availa- bility during intermittent exercise due to reloading of the muscle 31 myoglobin stores and to the decreased utilization of muscle glycogen during the intermittent exercise. Furthermore, it is well demonstrated that during low intensity exercise, lactate is a substrate for the exer- cising muscle (McGrail, et a1, 1978; Stamford, et a1, 1981; Poortmans, et a1, 1978). Effect of Diet It has been shown that following a meal containing carbohydrates, blood glucose and lactate becomes elevated, while FFA are depressed (Owen, et a1, 1980; Capro, et a1, 1981). On this basis, one would expect an interaction between carbohydrate intake and exercise following a carbohydrate meal. However, it has also been shown that the prime precursor of lactate is muscle glycogen (Wahren, et a1, 1971); further- more, that the muscle glycogen concentration affects the lactate produc- tion (Jacobs, 1981). Lactate production was significantly reduced when glycogen levels fell below about 40 mmol glycosyl units/kg. When con- sidering dietary effects upon lactate production, it is therefore impor- tant to also consider the dietary effect upon the glycogen stores. During low intensity work after depletion of muscle glycogen stores, a high carbohydrate diet increased blood lactate compared to a low carbo- hydrate diet, both during exercise (50% maximal oxygen consumption) and recovery. As expected at these workloads, the lactate production is very low (about lxmd), and it may very well be a dietary effect unrelated to exercise. In high intensity work (10 % maximal oxygen consumption) following glycogen depletion and either a carbohydrate-free or carbohydrate-rich diet, Maughan and Poole (1981) found that carbohydrate loading resulted 32 in highly significant increased blood lactate following exercise compared to the carbOhydrate-free regimen. Bonen, et a1 (1981) exercised their subjects at 80% of maximal oxygen consumption following glycogen depletion and either during control (no glucose) or 1.5 g/kg glucose before (15 minutes) or during (3-5 minutes) exercise. They found that preexercise glucose gave the highest blood lactate during exercise and recovery, while the lowest values were observed during the control treatment. Apparently, the effect of diet when muscle glycogen is unaffected has not been studied. CHAPTER 2 THE VARIABILITY OF THE HEART RATE-OXYGEN CONSUMPTION RELATIONSHIP WITH TIME AND COMPARISON OF INDIVIDUAL REGRESSION LINES VS A COMMON REGRESSION LINE FOR ALL SUBJECTS 33 3h Synogsis The variation with time of the heart rate oxygen consumption rela- tionship (HROXCR) was studied in ten subjects with 10 trials in each sub- ject and 40-minute recovery. A significant inhomogeneity was found in all but one subject. The significance was not decreased by using cOrrected heart rate (correctedHR = Actual HR + 60 - Resting HR). The slope differed little in subjects with similar maximal oxygen consump- tion, although significant differences existed. The y-intercepts were also significantly different, and the significance did not disappear when using correctedheart rate, unless only subjects with similar maximal oxygen consumptions were considered. It is concluded that it is best to use individual regression lines, but because of the variability within subjects, it should be based on more than one trial. Even the relatively small variations in the oxygen consumption from day to day is positively correlated with the HR. 35 Introduction The heart rate (HR) is often used as a predictor of the oxygen consumption (OXC) and/or degree of physical activity (Andrews, 1971; Payne et a1, 1971; Bradfield, 1971; Bradfield et a1, 1971; Astrand, 1971; Dauncy & James, 1979). One reason for this is the good linear correlation between HR and OXC in any given experiment (Londeree & Ames, 1976). This implies that the HR is a major determinant of the oxygen supply. However, besides the HR, the stroke volume (SV) and the arterial-venous oxygen difference (AVD) are other factors used to determine oxygen supply, and all three are known to vary with the intensity of exercise (Astrand et a1, 1964; Damato et a1, 1966; Williams et a1, 1962). The relationship between the HR and the OXC (HROXCR) has in fact, been shown to depend upon physical training (Saltin, et al, 1968; Pannier, et a1, 1980), age (Sheffield et a1, 1978; Montoye, et a1, 1968; Dill & Consolazio, 1962), body position (Andrews, 1971; Vokzc, et a1, 1975; Sato & Tanaka, 1973), and environmental tempera- ture (Oill & Consolazio, 1962; Rowel et a1, 1966; Taylor et a1, 1963; Myhre et a1, 1979). While sex, age and training are easily controlled, the effects of body position and environmental temperature cannot always be easily controlled. Since the effects of temperature and position on the HROXCR in general are not very large, they are probably safely ignored for many applications (Andrews, 1971). 36 It has not been determined if the HROXCR remains constant for a reasonable time period, although this assumption forms the basis for the use of HR to predict the OXC. Furthermore, it is controversial whether a common regression equation can be used for all subjects, or groups of subjects of similar age, sex, and physical condition (Andrews, 1971), or an individual equation should be used for each subject (Bradfield et al., 1970). The purpose of this study was to determine if the linear relation- ship between the HR and OXC is constant with time when no training effect is introduced. Andrews (1971) has suggested that the use of incremental HR will remove any significant differences in the regres- sion equation between subjects, and this was also tested in this study. Furthermore, this study addressed the question of whether individual or common regression lines best predict OXC. Durnin (1978) has argued that since most activity occurs at low level, the normal variability could easily obscure true differences. It is therefore necessary to test whether the variability in OXC at resting level of activity is correlated with the HR. 37 Methods Subjects Ten male students, 20-30 years of age, who were moderately fit and accustomed to exercise on a treadmill participated in this study. The subjects did not participate in regular physical training or athletic competition. None of the subjects were obese, that is, they were within 1 10% of desirable weight (Metropolitan Life Insurance Company, 1959), or received any medication during, and at least a month prior to, the trials. Anthropometric data and maximal oxygen consumption for the subjects are given in Table 1. The subjects gave informed consent, and the protocol used was approved by the University Committee on Research Involving Human Subjects (UCRIHS) at Michigan State University. Measurement of Oxygen Consumption (OXC) and Heart Rate (HR) The OXC was determined through a modified Douglas method (Consolazio et a1, 1963). The expired air was collected through a low resistance (Daniels) valve and collected in light-weight (neoprene) bags. The composition of the collected air was immediately determined using the Beckman LB-2 carbon dioxide and Beckman OM-ll oxygen analyzers. The air volume was determined by metering through (using constant flow) a Singer dry gas meter. The HR was determined from a 3-1ead electrocardiogram, and recorded continuously on a Sargent 38 .muue «new; m:_amme ecu Lou =o_uomcgoo coauo gamucmucmla as» m? Lou omm .om Lou mocmvce> mg“ m. oco>v .Fm cow mucowce> on» m_ pea) .uummozm comm :— m_a_cu emu ozu so; :o_um=cm zopmmwcamg mzu mo uamugmuc_-x same age m_ emu n .uumnaam zoom c. m—ovcu sou mg» Lo» :o.ua=ew :c_mmmcmmc use we oaopm cows mg» mp fine .mmucopgm> muuonnam cmozuma on» men mmucmwgc> m=_v:oammgcoo may tea .muumanzm —_m :. m_~.cu __o co ummoa covumzam copmmmcamg as» mcpuo—aopmu an vac—ouno one am can .m.mo memos mspm .Axpw>wuumamoc cm» ecu mco goo: :_V mac—aucmscmumu ozu ea cemzw .ummu wmvusmxw some 0» Lo—ca mco .m:o_uu=mscmumc emu be coo: — 0.8 ¢._ o.m e.~ e.m m.~ m.~ ¢._ o.m e.~ 8.“ e oca> e.m_- ~.m_- a.-- m.-- m.m_- 8.8.- ~.c_- _.N_- 8.8.- _.~_- _.N_- a too am N.m~ e.~ 8.8. e... m.~ ~.o_ m.~ _.m m.m_ m.~ m._~ a eta) 8.8,- ¢.~_- e.-- m..~- 8.8. 8.8.- m.__- m.m_- _.o_- m.m_- m.m_- a pm :8. 88. :8. 88. 28. 88. M88. .88. 888.. 88. a .8. a E; men. men. see. man. 8mm. can. own. sen. mam. Nmm. cam. a rm . . . . . . . . . . . 8&3? e Nm 8 mm o co e an m mm _ um a _m o me a me o as . cm N o» xaz c.om 8.85 ~.~m ~.mo ..oo_ 8.8m o.~m m.mm m.o~ m.om 8.88 .Aacv 338.8: a~_ om. ~e_ mo_ ~m_ co. amp map om_ we. @8— Aso. ogm.m= m.e~ cw am cm am on on mm mm om om Amtamsv am< mama: a. a m a m m e m N _ .cz Humanam .:o>.a m? uumnnam some c. m—evcu cw» .pc co woman mmocupeu> a:_u:oammceou oz» cam om mammogoac.-> ecu rm monopm och .mauwnazm emu mgu so; er ~c> ace .ugmwoz .u;m_w; .mmm .— m_aa~ 39 recorder. The mean HR for the time corresponding to each bag of expired air was determined. In an attempt to reduce error due to variation in resting HR, a corrected HR was calculated by adding or subtracting the difference between 60 and the resting HR from each HR measurement. 60 being the mean HR is arbitrarily chosen as standard. Test Protocol The ten subjects completed an incremental exercise test once a week for ten consecutive weeks. Each subject was assigned a specific day and time, on which he would arrive in the laboratory at least 5 hours postabsorptive (usually after an overnight fast). If a subject could not meet his appointment for a particular week, he would be rescheduled for another day the same week. On the test day, the subjects were instructed not to consume coffee or tea and not to engage in heavy exercise. The imcremental exercise test was performed on a treadmill. The steps consisted of resting and the following speeds (S-Z to S-7): 4.8, 6.8, 8.7, 9.7, 12.5, and 14.3 (miles/hour). At rest (S = O) the subjects were sitting relaxed in an armchair on the treadmill, but HR and expired air was collected as during exercise. During rest, three 5-minute bags were collected; for S-2 and S-3, three 2-minute bags; and for the remaining speeds (S-4 to S-7), three l-minute bags were col- lected. Not all subjects completed all the steps, but the trial was terminated when the subject approached his maximal oxygen consumption as determined in two separate tests. 140 Measurements of RestinngR and OXC Five different subjects (mean age i SD = 26.6 years i 1.7, mean weight : so = 78.2 kg :11.3 and mean height i so = 182 cm i 6.1) (were used to determine OXC and HR once an hour for 9 hours. The subjects were seated in an armchair while 3 consecutive 5 minute bags of expired air were collected and the mean HR corresponding to each bag determined from the HR-recordings. The correlation coeffiCient between HR and OXC was calculated for a 9 hour period in each subject. The resting values for HR and OXC for 9 of the 10 subjects used for the determinations of the regression equations as described above, were used for calculation of the correlation coefficients. These correlation coefficients are therefore based on simultaneous measure- ments of OXC and HR on ten different days one week apart. Treatment of Data and Statistical Procedures A computer program was used to calculate OXC from the composition of the expired air on a standard temperature, pressure, dry basis. The OXC for each collection period and the corresponding mean HR were used to calculate a regression equation for each trial in each subject. A regression equation for each subject, based on all ten trials, was calculated, as was a common regression equation based on all 100 trials in the ten subjects. The slopes B1 and the y-intercepts (80) for the individual trials were used as independent variables in a one-way analysis of variance (random model). The repeatability 2 R = j—Egfl—j—E-is calculated to evaluate the relative contributions of 0 +0 8 u) 111 x 2 . 2 msS ' mSE within and between subjects variance: ow = mSE and as = -——-T6-- where mSE is the mean square error term, and mSS is the mean square treat- ment term from the analysis of variance (Gill, 1978). The sum of squares ($551) for the individual regression equation and the total sum of squares for the sumation regression equation in each subject (SSET) are used to test for homogeneity of regression within a subject and between subjects (Gill, 1978). The critical value is ta, 2(t-1) (r-2), where t= trials and r=number of observations in a trial. Correlation coefficients were determined in the usual manner and mean and confidence intervals are calculated by transformation to z=O.5 1n %§E~(Gill, 1978). Results The regression line for a single incremental exercise test is shown in Figure 1 for a representative subject. The correlation coefficient between HR and OXC is very high (>O.99), which is partly due to the use of mean (integrated) HR. The regression line based on all ten incremental exercise tests in a typical subject is plotted in Figure 2. The calculated F-statistics for test of homogeneity of regression between independent samples are given in Table 2. The critical F value is 1.94 (a=0.05) and in all but one subject, there is significant inhomogeneity. Also shown are the calculated F-statistics after correcting for resting HR by adding 60-resting HR to all HR measure- ments. The critical F-value is again 1.94 and it is seen that rather 142 Figure 1. Regression line between the OXC and the HR for a typical subject (#8) based on a single incremental exercise test. The slope B] - 0.377, the y-intercept BO = 22.5, and the standard error of estimate SE = 0.86 ml 02/min/kg. 52-7 is the different speeds in the incremental exercise tests. 2+3 :.E\mumon m..- .ED. .3” _ .EN— AN _ _ .Nm .NP v0 ZO_._.<:ON 20.mmm¢0mm warez—m .8. .EN . .8” .HT. 6)l/l-llul/lu-l OX0 FIGURE 1 hh Figure 2. Regression line between OXC and HR in a typical subject (#8) based on ten incremental exercist tests. The slope B1 = 0.372, the y-intercept BO = 21.1, and SE = 2.03 ml 02/min/kg. AS ASS—\mumcav 5.. .BW _ .Nm _ .NT: .8“. .88 — .Bm .Bm + Acumen O: 20.._.<=Om 20_mmmm0mm . .Nm . .Hm . .HI B)l/“ll-fl/W OX0 FIGURE 2 46 Table 2. Calculated F-ratio for test of homogenity with- in the ten trials in each subject with observed HR (F-1) and with corrected HR (F-2).a Subject No. F-l F-2 1 20.01 28.37 2 12.50 6.36 3 9.95 ' 22.30 4 2.49 14.60 5 1.58 3.51 6 13.70 12.74 7 11.65 ' 13.04 8 11.16 27.49 9 3.17 9.55 10 24.78 25.71 Totalb 245.53 107.00 aThe critical F-ratio is 1.96 (0 =0.05). bTotal is the F-ratio for inhomo- genity between subjects. h? Table 3. Repeatability R, calculated and critical F-ratio (a=0.05) for the Slope b], the y-intercept 80, the y-intercept cor- rected for resting heart rate 30 Cor, and B]-1 and BD‘ICor when the subject with a large deviation in the max V02 is disregarded. B1 81-1 80 80-1 80 Cor Bo'lCor Repeatibility R 0.696 0.158 0.741 0.632 0.755 0.092 Calculated F 22.66 2.91 25.5 18.21 31.85 2.02 Criticial F 1.99 2.06 1.99 2.06 1.99 2.06 a HR is corrected by adding 60-resting HR to each observed HR. h8 than decreasing the inhomogeneity, it generally increases, resul- ting ‘Hl significant inhomogeneity in all subjects. The critical F- value for test of inhomogeneity between subjects 1.88 (a==0.05) and the calculated F is highly significant; but in this case, the inhomogeneity is drastically reduced by correcting for resting HR, although it is still highly significant (the F-ratio decrease from 246 to 107). From Table 1 it is seen that one subject (#9) has significantly higher maximal oxygen consumption than the other subjects (66 vs a mean of 52 i 2.8). Since the regression equation can be expected to vary with maximal oxygen consumption, the analysis of variance is done with and without this subject. Using corrected HR does not affect the slope (8]), but the y-intercept (80). The repeatability, calculated F, and critical F are given in Table 3. R can vary between 0 and l: R = 0 means that all the variability lies within the subjects, and R = l means_that all the variability lies between the subjects. From Table 3, it is seen that correction for differences in resting HR has no effect on R for the y-intercept (0.741 vs 0.755), and removing the inhomogenous subject (#9) has no effect in itself’ (0.741 vs 0.632); but using corrected HR and removing subject #9 causes practically all the variation to be within subjects (0.755 vs 0.092). As seen from Table 2, using corrected HR drastically reduces the varia— tion within subjects (from a mean of 25.2 to 9.9); but since it has no effect on R and B0 Corr is highly significant (F = 3l.9) as seen in.Table 3, it means that it reduces the variability equally within and among the subjects. When removing subject #9 from the analysis and 99 using corrected HR, there is no longer evidence of inhomogeneity (F = 2.02). R for the slopes is likewise reduced by removing subject #9 (0.696 vs 0.158); but in this case, the slopes are still significantly different between subjects (F = 2.91). In conclusion, it can be said that each subject has a character- istic B] and 80 around which the individual incremental exercise test values vary. When subjects are homogenous with respect to maximal oxygen consumption, the individual variation is far more important than the variation among subjects for the slope, and also for 30 if corrected HR is used. Correlation Between HR and OXC at Constant Workload The resting HR within a subject generally varies by 1:10 beats/ minute from minute to minute. But, during exercise, the short-term variation is decreased to :2 to 3 beats/minute at high workloads. The mean HR corresponding to each bag of expired air has a short-term (15 min) variation of :1 beat/minute or less; however, over extended test periods of up to 10 hours, there is variation in the mean HR of :5 beats/minute. There is also a variation in the resting HR from day ‘to day of about 15-20 beats/minute. The mean correlation between HR and OXC taken at rest at 9 different times throughout a day for the 5 subjects was -0.032 and the confidence interval -0.l99 to 0.135. The mean standard deviations for HR and OXC were 2.91 and 0.19 respectively. This means at a given workload (rest), HR and OXC vary independently of each other in the postabsorptive state. In 9 different subjects the'correlation between 50 HR and OXC was determined from measurements taken in the restjng state on ten different days. In this case the mean SD for HR and OXC were 4.55 and 0.47 respectively, that is approximately doubled due to day-to-day variation. The mean correlation coefficient F was 0.478 with the confidence interval from 0.375 to 0.570. This means that the relatively small variation in OXC observed from day to day in the resting state is significantly correlated with the HR. 51 Discussion The HR is frequently used as a predictor of OXC (Bradfield, 1971). The excellent regression between HR and OXC found in this study (r>0.99) when several different workloads are considered, gives support for the use of HR as a predictor of OXC. The mean standard error of estimate (SE) for the 100 regression equations calculated in this study was 1.40 ml oxygen/min/kg which corresponds to 0.49 kcal/ min. This compares favorably with the value of 0.37 reported by Andrews (1971), since we generally used a wider range of workloads; and the SE tends to increase with increasing workload. As discussed by Dauncy and James (1979),in most applications the HR varies within a relative narrow range (60-100 beat/min or less). It is therefore important to see how well HR and OXC is correlated within a narrow workload. The correlation (r) was calculated between HR and OXC in five subjects from periodic measurements throughout a day with no physical activity. Under these conditions there was no correlation between HR and OXC; and the standard deviations for HR and OXC were 2.9 and 0.19 respectively. When the correlation was based on measurements of HR and OXC on 10 different days (subjects again in the resting state) the correlation (r=0.478) was statistically different from 0 (a=0.05) and could explain about 25% of the variation, the remaining variation being due to random variation in HR and OXC. In the measurements from day to day, the SD for HR and OXC were 4.6 and 0.47 respectively. Thus even relatively small changes in 52 HR are positively correlated with the OXC. Andrews (1971) reported that substituting HR for incremental HR (IHR) (actual HR - resting HR) removes the differences in y-intercept for the regression lines between HR and OXC. Using IHR is equivalent to having all the individual regression lines going through a common point (IHR : 0 and OXC = Resting OXC), since the resting OXC generally varies very little compared to the SE of the regression equation (SE «4353 and 1.4 respectively). When the IHR is used the y-intercept corresponds to the resting OXC; since this, in our experience, invariably lies on the regression line; and an analysis of variance of the y-intercept therefore becomes meaningless. The corrected HR (CHR=actual HR + 60 - Resting HR) was therefore used in the present study. The effects of using corrected and incremental HR is illustrated in Figure 3 and Figure 4 for a hypothetical case. Like the IHR, the CHR adjust all the regression lines to a common resting HR; but instead of this being 0 it is 60, and the variability of the y-intercept due to variation in slope is thus retained. Using CHR has no effect upon the slope; and only where very homogenous subjects (with respect to maximal OXC) were considered did it decrease the variability in the y-intercept between subjects. However, as seen from Table 2, using CHR does not decrease the variability in the y-intercept within a subject. It is therefore concluded that there is no advantage in using CHR (or IHR). Whether to use a common regression equation between HR and OXC for all the subjects as recommended by Andrews (1971) or an individual determined regression equation as recommended by Bradfield gt El- (1970) and Astrand and Rodahl (1977) is still controversial. Since 53 Figure 3. Regression lines between HR and OXC for a hypothetical case: Training decrease HR and increase slope. Line a and b il- lustrate variation in the HROXCR such as caused by exercise. Sh 3.5362: m: can” . .fim — on” . .Bm .BT- OXC d m... Zumgbmm wwz: zo.mmm¢0mm (fin/unw/lw) oxo FIGURE 3 55 Figure 4. Incremental and Corrected HR. IHR = Actual HR - Resting HR CHR = Actual HR + 60 - Resting HR. Both adjustments reduce the variability of the y-intercept; but not necessarily the difference between the regression equations. INCREMENTAL 8: CORRECTED HR 56 2 '2 .9 N N .. 6' 1- 6'0‘9‘( 0 :9- 968' °o 4r 9” ‘42 94 94 ‘34 I El 61 19 si 0' 111 I 11 N - (Ba/in/Iw) oxo FIGURE. 4 taz._ 2mm. HR (beats/min) EZI. 57 both the slope and the y-intercept are significantly different even within homogenous subjects, it is always better to use individually determined regression lines. This can also be seen from the repeatae bility R (R=0.70 for the slope and 0.74 for the y-intercept), which means that most of the variability is between subjects even when only homogenous subjects are considered (R=0.63). The finding of significant inhomogeneity among the regression lines makes it necessary to determine the regression based on data from at least 3 exercise test spaced at least 2 days apart, in order to ascertain that the regression line is typical for the subject. Payne gt 31, (1971) reported that HR and OXC obtained during sitting and standing rest did not fall on the regression equation obtained during exercise. They did find, however, that HR and OXC obtained during supine rest fell on the regression line. In the present study 15 minutes of sitting rest was used as the first step in the incremental exercise test, and the HR and OXC obtained during rest almost invariably lay on the regression line. The reason for this discrepancy may lie in how the resting measures are conducted. As described by Dauncey and James (1979) it is important that the subjects moves the legs periodically in order to avoid venous pooling. As reported by Hirsch and Bishop (1981) the breathing pattern affects the HR and causes a cyclic variation. In the present study this effect was clearly seen at rest (:10 beats/min), but it disappeared at higher workloads. Since the HR was recorded continuously, and the mean HR corresponding to each bag of expired air was calculated, this variation had no effects on the results. CHAPTER 3 EFFECT OF DIET, PREVIOUS EXERCISE, AND RECOVERY UPON THE LINEAR REGRESSION BETWEEN HEART RATE AND OXYGEN CONSUMPTION -58 59 Synopsis We have studied the effect of diet composition upon the regression between heart rate (HR) and oxygen consumption (OXC) during an incre- mental exercise test. Our results do not give any evidence for a dietary effect. Repeated exercise one hour apart did, however, have a significant effect upon both the slope and y-intercept of the regres- sion equation between HR and OXC. During recovery, the HR did not predict the OXC based on the regression equation obtained during exer- cise. Both the exercise intensity (S) and duration (0) had a significant effect upon the recovery HR (RHR), whereas only S had a significant effect upon recovery OXC (ROXC). Consequently, RHR lagged behind the ROXC the first three minutes of recovery, but then returned toward resting values at the same rate as the OXC. The difference between ROXC and predicted OXC (POXC) is primarily determined by D. 60 Introduction The heart rate (HR) is often used as a predictor of the oxygen consumption (OXC) and/or degree of physical activity (Andrews, 1971; Payne, et a1, 1971; Bradfield, 1971; Bradfield, 1971; Astrand, 1971; Dauncy & James, 1979). One reason for this is the high linear corre- lation between HR and OXC in any given experiment (Londeree and Ames, 1976). This implies that the HR is a major determinant of the oxygen supply. However, besides the HR, the stroke volume (SV) and the arterial-venous oxygen difference are other factors that determine the oxygen supply; and all three are known to vary with the intensity of exercise (Astrand et al, 1964; Damato et a1, 1966; Williams et a1, 1962). The relationship between the HR and OXC (HROXCR) has been shown to vary with physical training (Saltin et a1, 1968; Pannier et a1, 1980), age (Sheffield, et al, 1978; Montoye et a1, 1968; Dill & Consolzio, 1962), body position (Andrews, 1971; Vokzc et a1, 1975; Sato 8 Tanaka, 1973), and environmental temperature (Dill & Consolazio, 1962; Rowell et al, 1966; Taylor et a1, 1963; Myhre et a1, 1979). While it is relatively easy to control for sex, age, and physical training, in most applications, it is difficult to control for body position and environmental temperature. However, in most experiments, it may be safe to assume that body position and environmental tempera- ture have an equal effect upon control and experimental groups. 61 The effects of diet, previous exercise or stress on HROXCR are not well studied (21). However, stress has been shown to increase the HR at constant OXC (Taylor et a1, 1963; Sonne & Galbo, 1980) and previous physical activity does affect the regression equation (Lundgren, 1946), whereas conflicting results are reported for dietary effects (Lundgren, 1946; Schutz et a1, 1981). Since the average subject will probably spend more time recovering from physical activity than he/she will spend exer- cising, it is also important to know if the HROXCR obtained during exer- cise is followed during recovery. The objectives of the present study were (1) to determine the effects of dietary composition upon the regression equation between HR and OXC, (2) to determine if the HROXCR obtained during an incremental exercise test also was valid during recovery, and (3) to determine what effect previous exercise might have upon the HROXCR. 62 Methods The study was divided into two parts. The first part examined the relationship between HR and OXC during recovery following 20 min of exercise at 80% of maximal OXC. In the second part the effects of duration(D) and intensity (5) of the exercise period upon the relationship between the HR and OXC during recovery was studied. Subjects Two groups of five healthy male college students volunteered for the study. The physical characteristics of the subjects are given in Table 1. None of the subjects took any medication; and on the day of the experiment, they were requested not to drink any caffeine-containing beverages: They also did not participate in any strenuous physical activity on the day before the experiments were conducted. Informed Consent Each subject signed an informed consent form after the details of the experiments were described to him. The form stated the experimental procedures, identified possible risks, and noted that a subject could terminate his participation at any time: Diets The composition of the diets and meals is given in Table 3. Each meal contained 700 kcal. The fat meal consisted of 288 ml whipping cream, which the subjects drank in less than 10 minutes. The protein 63 Table 1. Physical characteristics of the two groups of five adult male subjects. (SD = Standard Deviation.) Physical Group I (n35) Group II (n=4) Characteristics Mean SD Mean SD Ages (years) 24.8 3.1 28.8 2.2 Body Weight (kg) 74.5 11.9 81.9 7.0 Height (cm) 173 7.4 184 16.5 V02-max (ml/min/kgga 54.1 6.6 49 9 2.6 Mean running 5 eed 10.9 0.8 %V02-max (mean)b 78 0.6 aMaximal OXC bfinal treadmill setting Table 2. Relative intensity of exercise for various treadmill settings used in incremental exercise tests. Setting Speed % V02-maxa Duration (0) of Exercise (km/hr) (min) 0 0 (rest) 10 15 2 4.8 38 6 3 6.8 52 6 4 8.8 64 3 5 10.5 74 3 6 12.5 84 3 7 14.3 93 3 aMaximal OXC: mean of four subjects. bThe time given is for an intermediate step. When 4-7 was the final speed 0 was either 10 or 30 minutes. 6h .Am~¢_v gotzgo a £62358 “Ammo—V _.Pctaz 6:8 88838 e.m w.- mo mp NN om_.~ m_m»_6:< F66w56gu 36*: aseccszontmu o.8 o.m© @— o_ co om_.N m_mspee< _66m56;u cm_o and mo m_ cm omP.~ m6_nec woo; 38_o 68826»;68888 om m_ mo omp.~ mm_nep 6668 36_o you m¢ m N co“ m6_aah coca .882 mumcosgoncmu N mm mm oak 66,88» 666; .66: ccmuota m m mm 905 ammpnop good _882 and zmq cmumz wwwmwmw :Pmuocg «mu Apmuxv magma“ vogue: mpmmz co mum_o ugmvmz an & zmcmcm peace mo & Peach 00¢.N v:m ooP.~ :mmzuma vmwcm> mummu ms» we acmucou xmcmcm mg» .muumnosm uzmcmwwwu mg» Low .mux .mum_c ace m—mma mo :owummoaeou .m m_nc~ 65 / meal consisted of 94 g creamed cottage cheese and 545 g (raw weight) skinned chicken breast, with all visible fat removed. The subjects ate the protein meal in 30 minutes. The carbohydrate meal consisted of 824 g ripe bananas (peeled), which were eaten in less than 10 minutes. The subjects drank 340 cc of ginger ale (1 kcal) with the meals (Vernors, Detroit, MI), and were allowed salt, pepper, and water ad lib. During the experimental periods the subjects ate 2,100 to 2,400 kcal per day either as a high fat or as a high carbohydrate diet. The composition is given in Table 3- The subjects were fed one of the two experimental diets in random order for three days prior to the exercise test, which was performed in the postabsorptive state the fourth day. The diet and test meals were prepared and eaten in a kitchen adjacent to the exercise laboratory. Two menus were used for each diet: one for breakfast and one for dinner and supper. The menus were repeated for all three days. The subjects were supervised during the meals and ate all the allotted food. Duplicate portions were used for chemical analysis. Fat was analyzed by ether extraction, protein by micro- kjeldahl, minerals as ash (600°C) and carbohydrate by difference. For both diets regular food items were used. Sources of fat were: margarine, mayonnaise, cheese, eggs, bacon and olives; while sources of carbohydrate were: bananas, bread, potatoes, sweet potatoes, beans, carrots and peas. These foods contain some protein. Additional Protein came from soy protein. For the fat diet imitation chicken, and for the carbohydrate diet imitation beef (Worthington Foods, Worthington, 0H) were used. 66 Measurements Heart rate (HR) was obtained from an electrocardiogram (lead 2 with the positive lead in V5 position). The EKG signal was converted to heart rate through a cardiotachometer (built in our lab) and con- tinuously recorded by a calibrated Sargent Recorder, Model DTM-115-4 (Sargent and Company, Chicago, IL). The mean HR in beats/minute corres- ponding to each collection of expired air was calculated from the recording. The oxygen consumption (OXC) was determined by a modified Douglas method (Consolazio, et a1, 1963). The expired air was collected through a low resistance valve (Otis-McKerrow, Warren Collins, Inc., Braintree, MA) in light-weight neoprene bags. The composition (02 and C02 contents) of the collected air was immediately determined using the Beckman LB-2 carbon dioxide and Beckman OM-ll oxygen analyzers, respec- tively (Beckman Instruments, Schiller Park, IL). The air volume was determined by metering through (using a constant flow of 50 1/min) a Singer dry gas meter (American Meter Company, Philadelphia, PA). The mean OXC for the control experiment was compared to the baseline (mean resting OXC prior to the ingestion of the meal). To correct for the day to day variation in the resting OXC in each subject the difference between the control and baseline values were added or sub- tracted from the OXC for that day's treatment. Exercise Tests The maximal OXC was determined in a continuous incremental test with the subjects exercising on the treadmill until exhaustion. The speed was increased stewpise at 8.8, 10.5, 12.5 and 14.3 km/hour. When 67 the subjects reached the highest speed they could comfortably run (12.5 or 14.3 km/hr) further increases in the workload were accomplished by increasing the treadmill inclination in steps of 2%. The subjects ran 3 minutes at each step, the HR was recorded continuously, three one-minute bags of expired air were collected at each step, and the oxygen consumption calculated for each minute. The OXC following the different treatments was determined through an incremental exercise test with the final workload corresponding to 80% of the subjects' maximal OXC. Three collections of expired air were made at each step and the mean HR corresponding to each air collection was recorded. The test started at rest with the subject seated in an armchair, while 3 consecutive 5-minute collections of expired air were made.. During the following steps the subjects would walk or run on the treadmill. At the 4.8 km/hr and 6.8 km/hr levels the subjects exercised for 6 minutes each, and at the other levels they exercised for 3 minutes each; except when they reached the final speed (the one corresponding closest to 80% of their maximal OXC), they con- tinued the exercise for 20 minutes. During the final stage, one-minute bags of expired air were collected, every second minute starting with the second minute. Following the exercise, the HR and OXC were determined during 40 minutes of recovery. Two one-minute bags, one three-minute and one five-minute bag of expired air were collected during the first 10 minutes of recovery. During the next 30 minutes, 3 five-minute bags of expired air were collected every second 5-minute period. During the alternate 5-minute periods, when no collections were made, the subject 68 remained seated in the armchair, but was relieved of the face mask with air—collection valve and the noseclip. Arterialized blood samples were collected from one of the fingens at 5, 15, 25 and 40 minutes of recovery for determination of the blood lactate concentration. In the second group (group II) of subjects the final setting (S) of the treadmill was varied between 4 and 7 in order to investigate the effect of exercise intensity and the duration (0) of each speed was either 10 or 30 min. The various treatment combinations were administered to each subject in random order. The speeds, duration and mean % of maximal OXC are given in Table 2. The collection of expired air during recovery was slightly modified in this group. Instead of collecting 2 one min bags and one 3 min during the first 5 min of recovery, one 1 min bag and 2 two min bags were collected. Experimental Protocol In the second part of the experiment four subjects (group II) participated. The final setting of the treadmill was varied between 4 and 7. xThe corresponding speeds and % maximal OXC (mean) are given in Table 2. The duration at this setting was either 10 or 30 min. From these data the effect 6f speed and intensity on HR and OXC during recovery was evaluated. Not all subjects completed the higher ‘ exercise intensities; but statistical analysis is based only on the settings completed by all subjects. Exercise The exercise experiments were carried out over a lO-week period with each test given one week apart. During the first and last tests the maximal OXC were determined. The second test was always a 69 control (postabsorptive state) prior to which the subjects ate their normal diet. Prior to the third test, the subjects consumed one of the experimental diets for three days (two started with the high fat diet and three with the high carbohydrate diet). Then followed another control test before the opposite experimental diet was introduced, three days prior to the fifth test. Following both dietary treatments, the test was carried out in the postabsorptive state. The three meals and a final control were introduced in random order so that all the subjects would not consume the meals in the same order. The exercise tests began 30 minutes after termination of the carbohydrate meals and 2-3 hours following the fat and protein meals, which we had found to corres- pond to the maximal thermogenic response. Statistical Analysis The incremental recovery HR(IRHR), recovery OXC (ROXC) and the difference between the predicted OXC (POXC) based on the regression equation obtained during the preceding exercise in each subject (DOXC) were analyzed by a split block (block = subjects) repeated measurements design (each subject serves as his own control). In the first part of the experiment the HROXCR during recovery was compared to the linear regression line during exercise by calcula- ting the 95% confidence limits. In the second part of the experiment the treatment means for ROXC, IRHR and DOXC were compared by designed contrasts (Bonferroni t statistics; Miller, 1966). The regression lines between HR and OXC during exercise were calculated for the 5 subjects in part I of the study. A common regression line was calculated for the 3 control experiments. Dietary 70 effects on the HROXCR were evaluated by testing for differences in slopes and Y-intercepts between the regression lines; but because the regression equation can vary with time random significant results can be expected in some cases. Incremental HR as used by Andrews (1971) is the actual HR-resting HR in the individual subjects. By using incremental HR the Y-intercept of the regression line corresponds to the resting OXC; and it therefore does not have much meaning to test for differences in the Y-intercept. A "corrected" HR is therefore used in this study instead. The corrected HR is obtained by adding 60-resting HR to the measured HR. 71 Results Effect of diet on the HROXCR during exercise. There was no evidence that any of the dietary treatments had an effect upon the linear regression between HR and OXC during exercise. The calculated slopes and y intercepts are given in Table 4 for the 5 dietary treatments and control. The control line was calculated from HR and OXC for 3 separate experiments in order to compensate for possible variation in the regression equation with time. All the treatments are compared to the control line for each subject separately. In 5 cases, the regression line for a treatment differed from that of control, but in no case did it occur twice in the same subject. It is therefore not a treatment effect, but a change occurrence due to the variation of the regression line. Effect of previous exercise on HROXCR Exercise changes both the slope and y-intercept of the regression equation between HR and OXC. Two of the subjects in part I were exercised as usual at 80% of their maximal OXC, and after one hour rest the same exercise protocol was repeated. One hour after the first exercise test, the OXC had returned to preexercise levels, but the HR was still elevated (20 beats/min). Table 5 gives the values for the slopes (B1), y-intercepts (BO) and standard error of estimate (SE) for the two regression lines. The calculated t-statistics for the test of significance is also given. Both the slope and y-intercept are 72 Table 4. Test of significant difference between the regression equations between HR and OXC for the five treatments and the regression equation for control. Critical T = 1.99. Dietsb _§, Mealsb Subject Treatment Controla Fat 0 CHO 0 Fat M Pro M CHO M Slopes 0.372 0.337 0.347 0.385 0.372 0.371 Y- -Intercept -20.6 -23.4 -17.2 -23.2 . -22.0 -21.3 S. E. 1.59 2.71 1.34 1.25 0.84 1.49 Tld 0.36 2. 21* 1.02 0.01 0.07 To 1.41 2. 38* 1. 59 0.90 0.43 S10pes .0. 364 0.365 0.374 0.367 0.369 0.405 Y-Intercept -17.1 -17.4 -18.7 -13.8 =15.6 -22.9 S.E. 2.03 0.74 1.13 1.10 1.07 0.91 T1 0.07 0.73 0.52 0.35 2. 72* TO 0.21 0.92 1.98 0. 86 3. 28* Slopes 0.474 0.461 0.473 0.436 0.495 0.498 Y-Ihtercept -26.1 -23.5 -23.5 -22.6 -31.6 -29.1 S. E. 4.03 2.86 3.11 2.72 3.10 2.65 T1 0.44 0.05 1.23 0. 59 0.68 To 1.37 1.32 1. 83 2. 34* 1.43 Slopes 0.366 0.331 0.372 0.386 0.345 0.387 Y-Intercept -16. 6 =12. 8 -18.1 -18.7 -15.3 -18.6 S. E. 1. 99 1.30 1.38 1.55 1.57 1.46 T1 2. 80* 0.42 1. 49 1. 67 1. 64 To L 53* 0.98 1.32 0.81 1. 27 Slopes 0.321 0.307 0.305 0.330 0.290 0.348 Y-Intercept -12.6 -IL 0 -12.5 -14.2 -11. 0 -1S.7 S. E. 1.74 0.95 0.96 1.44 4'1.13 2.13 T1 1.34 1.53 0.79 2. 92* 1.98 To 0. 49 0.05 1.10 1.20 1.90 -54 bn =18 cStandard error of means in ml oxygen/kg/min. and T0 are the calculated t- values for test of difference between the particular regression line and the control line. *Indicates significance ( a = 0.05). 73 Table 5. Test of significance between the regression equations for two subjects exercised twice, one hour apart. Results are included with the regression lines corrected for the resting heart rate (cor). Subject Trial Slope Y-Intercept SEa le Tob 1 0.293 ~13.4 1.27 4.34 6.21 2 0.347 =23.6 1.31 1 1 cor 0.293 -13.4 1.27 2.92 2 cor 0.348 -18.2 1.31 1 0.359 -16.1 1.39 1 L 3.17 4.88 2 0.404 =25.5 2.14 2 1 cor 0.358 -18.1 1.39 1.19 2 cor 0.405 -20.7 2.14 aSE = standard error of estimate. PTl and T0 are the calculated t-statistics for slope and Y-Intercept, respectively. The critical t-value for both T1 and T0 are 2.04 for subject 1 and 2.02 for subject 2. (n = 18 and 22 respectively.) 74 significantly different between the two regression equations in each subject. Using corrected HR decreases of the y-intercepts, but in the one subject the difference is still significant. The regression lines are shown in Figure 1. Effect of recovery on HROXCR The linear regression equation between HR and OXC obtained during exercise is not followed during the 40 min of recovery. The ROXC is lower than the lower confidence limit (LCL) during the entire 40 min recovery period; and the predicted OXC (POXC) can be as much as 300% above the recovery OXC (ROXC). These results are based on 8 trials in each of 5 subjects, and are shown in Figure 2 and Table 6. After 40 min of recovery the RHR was still elevated 20 beats/min, and is only decreasing 1 beat/10 minutes. At the end of recovery the OXC has returned to the resting level (Figure 4). Two subjects were followed to complete recovery of the HR, which took at least 3 hours; and appeared to depend on the training of the subject. The RHR is shown in Figure 3 and POXC, LCL and ROXC in Figure 4. Since POXC and LCL are both derived from the RHR and the linear regression equation between HR and OXC obtained during exercise, it is not surprising that RHR, POXC and LCL have a very similar time course, although the values for LCL of course are somewhat lower. As seen from Figure 4 and Table 6, the ROXC falls much faster toward the resting preexercise OXC (the x-axis in Figure 4). The difference between POXC and ROXC (DOXC) quickly reaches a maximum at about 3 min of recovery and then decreases very slowly (Figure 5). Expressed as percentage of POXC, DOXC, however, reaches a maximum of 62% at 3 min, and then remains constant for the Figure l. 75 Two regression lines based on exercise trials one hour apart in one subject. The second line begins at a higher HR. Both slopes and y-intercepts are signifi— cantly different. The regression lines for the first and second test is marked 1 and 2 respectively. 76 . :.E\mumom m... .numw._ .nUTJ _ .numw _ .nunu _ .numm .numw :53 E p .. £62 3 «20.553 203.353 . 6)I/“N-ll/N-l-l OX0 FIGURE 1 77 Figure 2. Predicted OXC (POXC), lower confidence limits (LCL) and recovery OXC (ROXC) as a function of recovery HR. Mean of five subjects with eight exercise tests in each. 78 2:52.38 a: Hm _ .BI . >mm>00m¢ 02350 c... a 0x0 .. .HI (Swami/1N) oxo FIGURE 2 Table 6. Comparison of mean recovery values and their respective standard deviation (SD) for eight trials in each of five subjects. Timea 0.5 1.5 .3.5 7.5 17.5 27.5 37.5 (min) RHRP 142 111 101 92 84 81 80 so 12.4 7.8 7.0 8.9 ’5.6 4.6 4.4 Roxcc 26.4 11.3 7.4 5.7 5.1 4.6 4.4 so 2.5 ,0.85 1.4 0.54 0.59 0.57 0.59 LCLd 31.0 19.7 15.7 12.1 9.4 - 8.2 7.7 so 3.3 2.1 2.0 2.4 2.2 2.1 2.2 Poxce 34.6 23.2 19.3 15.9 H 13.3 12.0 11.3 so 3.0 2.0 2.2 1.8 1.2 0.7 0.8 oLc1.f 4.6 8.4 8.3 6.4 4.3 3.6 3.3 ooxcg 8.2 12.1 11.9 10.2 8.2 7.4 6.9 zooxch 24 52 62 64 62 .62 61 aTime refers to midpoint for collection of expired air. bRec0very heart rate in beats/min. Resting HR = 60 t 6. cRecovery oxygen consumption (ml/min/kg). Resting OXC = 4.2 t 0.4. d95% lower confidence limit for predicted oxygen consumption. ePredicted oxygen consumption during recovery, based on the RHR and the prediction equation for previous exercise. fDifference between LCL and ROXC (DLCL). 90ifference between POXC and ROXC (DOXC). hooxc as 1 of POXC. 80 Figure 3. HR during 40-minute recovery. Mean of five subjects with eight exercise tests in each. The x-axis inter- sects the y-axis at the preexercise HR. 81 C 1 :1: >- n: m > o 1 o 4 1n 1: .1 51 El 61 '. . .T N N E El .. .. .. m m (ugw/swaq) 8H FIGURE 3 3121. HE. Time (min) 2U. Figure 4. 82 Predicted OXC (POXC), upper curve. Lower 95% confidence level for OXC (LCL), middle curve. Recovery OXC (ROXC), lower curve, as a function of time. The x-axis represents resting value. Mean of five subjects with eight exercise tests in each. 83 3:5 08:. B.HT. . 8.8m" 0x0 >¢m>00mm . .N.IN F...” (Bx/U1w/1w) oxo FIGURE 4 84 Figure 5. Difference between predicted OXC and recovery OXC (DOXC) as a function of time during 40 minute recovery. Mean of eight trials in each of five subjects. 85 3:5 0&3. E.DT. n.8mu H.9N N.B _ 332:. 1 OXOAV 0x00 fifim a)lll-llm/IW 0X00 FIGURE 5 86 remainder of the 40 min recovery (Figure 6). This means that during the first 3 minutes of recovery, the HR progressively lags behind the ROXC, but thereafter, returns toward the resting levels at the same speed until ROXC reaches the resting level or slightly below. The RHR does not return to resting level until three or more hours later. The effect of exercise intensity (S) and duration (0) on this lag in RHR was investigated in four subjects. Because not all subjects completed all the S-levels, only the first five treatments are included in the statistical analysis, while the data are reported for any treat- ment completed by at least one subject. In order to reduce intra- subject variability, the IHR(HR-RHR) is used. The means for IHR are shown in Table 7, the mean ROXC in Table 8'mean POXC in Table 9, and mean DOXC in Table 10. IHR is plotted in Figure 7 for 2 exercise intensities and in Figure 8 for 10 and 30 min of exercise, while Figure 9 shows ROXC at 2 exercise intensities and Figure 10, DOXC as a function of time. LCL, ROXC and DOXC are shown for all the treatments in Table 11. Except for speed 4 at 10 minutes, ROXC is always less than LCL and the relationship is similar to that already discussed for recovery after exercise at constant speed (Figure 2). The effect of duration of exercise appears stronger than the effect of intensity of exercise on DOXC. Thus, the mean (over the 40 min recovery) DOXC for 30 minutes is 10 ml/min/kg and for 10 minutes is 6.6 ml/min/kg. The results of the analysis of variance show that both treatment and time have a highly significant effect upon IRHR, ROXC, and DPOXC. 87 Figure 6. DOXC as % of POXC vs recovery time (40-minute VECOVEVY). Mean of eight trials in five subjects. 88 3:5 08.... .BT. an” .8” .u — .8 u 1F 0 1 L on .numw .. .8... 14 4 4 - .Bm : Anumw AOXOn— .0 fiv XOQO is . (96) OXOdCI FIGURE 6 89 Table 7. Mean recovery incrementala heart rates after exercise on a treadmill at 4 different speeds, each speed main- tained for 10 and 30 minutes, respectively. Mean of four subjects. Recovery timec Setting Timeb 0.5 3.0 7.5 17.5 27.5 37.4 (min) 4 10 57 25 17 14 11 10 4 30 73 38 28 24 20 14 5 1o 71 32 26 22 18 ’16 5 30 84 47 36 31 27 24 6 10 90 45 32 30 26 22 6d 30 100 56 40 32 29 21 7d 10 103 - 51 39 34 31 22 7e 30 112 63 54 44 41 37 aIncremental = measured HR - resting HR in each subject. bTime refers to duration of exercise at the final setting. cRecovery time refers to the midpoint for collection of expired air. dThree subjects only. eOne subject, only. Standard errors of individual treatment means at one time are irrelevant for comparisons or reliability. Standard error for difference between 2 treatments at one time is 4.74 (beats/min). . Standard error of difference between 2 times for one treatment is 5.58 (beats/min). 90 Table 8. Mean recovery oxygen consumption in four subjects after exercise on a treadmill at four different speeds, two runs at each speed for 10 and 30 minutes. respectively. Recovery time (min)b Setting Timea 0.5 3.0 7.5 17.5 27.5 37.5 (min) . 4 10 19.6 6.1 4.2 4.0 3.9 3.8 4 30 19.0 6.2 4.6 4.7 4.0 4.0 5 10 ‘22.9 6.9 4.8 4.5 4.2 4.3 5 30 24.3 7.4 5.0 4.3 4.3 3.8 6 10 26.9 8.3 5.4 4.7 4.1 3.8 6C 30 29.3 10.2 6.5 ‘ 5.5 5.2 4.9 7c 10 30.9 8.9 6.6 4.9 4.7 4.3 7d 30 31.2 8.9 5.8 5.2 4.4 3.5 aDuration D of final treadmill setting. bRefers to midpoint of collection of expired air. cThree subjects only. dOne subject only. Standard errors of individual treatment means at one time are‘ irrelevant for comparisons or reliability. Standard error for difference between 2 treatments at one time is 0.698 (ml/min/kg). Standard error for difference between 2 times for one treatment is 2.13 (ml/min/kg). Resting OXC = 3.6 m1/min/kg. 91 Table 9. Mean predicted oxygen consumption during recovery following exercise on a treadmill at four different speeds in four subjects. Each speed is repeated twice for 10 and 30 minutes, respectively. Time is given in minutes. Standard deviation (SD) is also given. Recovery time (min)b Setting Timea 0.5 3.0 7.5 17.5 27.5 37.5 (”1") POXC in ml/min/kg. 4 10 23.9 13.1 9.7 9.0 7.5 7.1 SD 5.5 4.4 3.5 3.7 2.6 2.0 4 30 “27.3 17.2 12.9 11.4 9.9 8.3 SD 5 1 3.8 3.2 3.5 2.1 2.4 5 10 29.8 15.6 12.2 10.9 9.3 8.6 SD 6.8 3.8 3.7 3.2 1.8 2.1 5 30 32.6 19.5 15.6 14.0 12.5 11.5 SD 4.3 4.7 3.5 4.1 4.4 4.1 6 10 33.4 19.1 14.0 13.2 12.0 10.7 SD 5.8 3.6 2.5 3.4 3.1 1.9 6C 30 38.8 23.4 18.0 15.2 14.2 11.5 SD 4.2 3.4 3.5 2.2 2.4 3.2 7C 10 38.1 20.4 17.7 15.0 13.6 10.7 SD 2.2 2.4 2.6 2.2 2.2 2.3 7d 30 40.0 23.8 20.9 17.6 16.6 15.3 6Duration (0) of final exercise step. bRefers to midpoint for collection of expired air. cThree subjects only. dOne subject only. Table 10. Mean difference (4 subjects) between the predicted oxygen consumption and the actual oxygen consumption during recovery after running on a treadmill at four different speeds. The subjects ran at each speed twice for 10 and 30 minutes, respectively. Recovery time (min)b Setting Time3 015 3.0 7.5 17.5 27.5 37.5 (min) 4 10 4.3 6.7 5.5 4.6 3.6 3.3 4 30 8.8 11.4 9.4 7.3 6.9 5.4 5 10 6.9 8.5 7.5 6.3 5.1 4.4 5 30 , 8.4 11.9 10.6 9.7 8.2 7.6 6 10 6.1 9.7 8.7 8.5 7.1 6.8 6c 30 9.5 13.3 11.6 9.8 9.0 6.5 7c 10 8.2 11.8 10.1 9.1 9.4 6.6 7d 30 8.8 15.0 15.1 12.4 12.2 11.8 Mean 7.6 11.1 9.8 8.4 7.8 6.6 010e 6.4 9.2 8.0 7.1 6.3 5.3 030f 8.9 12.9 11.7 9.8 9.1 7.8 aDuration (D) of final exercise step. bRefers to midpoint for collection of expired air. cThree subjects only. dOne subject only. eMean for 10 min. fMean for 30 min. DOXC in ml/min/kg. Standard errors of individual treatment means at one time are irrelevant for comparisons or reliability. Standard error for difference between 2 treatments at one time 15 1.8 (ml/min/kg). Standard error for difference between 2 times for one treatment is 0.97 (ml/min/kg). Figure 7. Mean incremental HR (IHR) for four subjects during 40-minute recovery after exercise for 10 minutes at speed 4 (8.8 km/hr), lower curve; and speed 6 (12.5 km/hr), upper curve. Significant difference at 0.5, 3.0, 7.5, 17.5, and 27.5 minutes. Mean values for four subjects. Standard error for difference of 2 treatments at one time is 4.74 (beats/ min). Standard error for difference of 2 times for one treatment is 5.58 (beats/min). 911 3:5 05.... .NI .9” .BN .u _ i l. p >._._mzm._.z_ v3.03 m> 3:. .UT. .nm ' L.— WBE _ (“I‘ll/9193(1) HHI FIGURE 7 95 Figure 8. Incremental HR during 40-minute recovery (RIHR) after exer- cise at speed 5 (10.5 km/hr). Upper curve for D = 30 minutes, and lower curve for D = 10 minutes. 96 ASE» m2: .BT. .Bmu .8“ .fl _ ZO_._.<¢=D v3.03 m> m:— Lin. _ ("flu/9193(1) HHI FIGURE 8 Figure 9. 97 Recovery OXC (ROXC) as a function of time. As there is no difference in ROXC due to the duration of exercise, 10— and 30-minute periods are combined. Upper curve is for speed 4 (8.8 km/hr) and lower curve for speed 6 (12.5 km/hr). Significant differences for the first minute of recovery only. Mean values for four subjects. Standard error for difference of two treatments at one time is 0.698 (ml/min/kg). Standard error for difference of two times at one treatment is 2.13 (ml/min/kg). 98 .81 ASE. 65:. .N” .9” .E — 1’ L ' ‘01 i: '7’. N 1‘ can a o5 .6 52.. .em 11 f o.o.om >h.mzm._.z_ v2.03 m> 0x0: (fix/uawxiw) oxou FIGURE 9 Figure 10. 99 Mean DOXC (difference between predicted and recovery OXC) for four subjects. Significant differences at 3.0 and 7.5 minutes. Since there was no significant speed effects, the mean for 30 minutes for Speed 4 - Speed 7 (upper curve) is compared to the mean for 10 minutes of exercise for Speed 4 - Speed 7 (middle curve). The lower curve is for the lowest speed (8.8 km/hr) which is significantly differ- ent from S6 when all time points are considered. Ac-Ev 08-h ANT. 100 .um .BN .N . ' opo.vm 0.. O .hlvm .505 1’ A on a .hlvm coo: 20:42.30 d >._._mzm._.2_ Xm—OB m> 0x00 111 (Bx/umnw) oxoo FIGURE 10 Table 11. Mean values of 95% lower confidence limit (LCL) for predicted oxygen consumption (POXC), recovery oxygen consumption (ROXC), and the difference (DLCL) between LCL and ROXC in ml/kg/min followin exercise on a treadmill at four different speeds (S for 10 and 30 minutes (0), respectively. Mean of four subjects. Recovery time (min)c 5a 0D 0.5 3.0 7.5 17.5 27.5 37.5 LCL 4 10 20.5 9.6 6.2 4.9 3.8 3.4 ROXC 19.6 6.1 4.2 4.0 3.9 3.8 DLCL ”0.9 3.5 2.0 0.9 -0.1 -0.4 LCL 4 30 25.2 15.2 10.8 8.8 7.8 6.2 ROXC 19.0 6.2 4.6 4.7 4.0 4.0 DLCL 6.2 9.0 6.2 4.1 3.8 2.2 LCL 5 10 27.4 13.2 9.8 - 8.5 6.9 6.2 ROXC 22.9 6.9 4.8 4.5 4.2 4.3 DLCL 4.5 6.3 5.0 4.0 2.7 1.9 LCL 5 30 29.8 16.6 12.8 11.2 9.6 8.6 ROXC 24.3 7.4 5.0 4.3 4.3 3.8 DLCL 5.5 9.2 7.8 6.9 5.3 4.8 LCL 6 10 30.6 16.5 11.7 10.4 9.0 8.3 ROXC 26.9 8.3 5.4 4.7 4.1 3.8 DLCL 3.7 8.2 6.3 5.7 4.9 4.5 LCL 6d 30 35.7 20.5 15.2 12.3 11.3 8.5 ROXC 29.3 10.2 6.5 5.5 5.2 4.9 0101 6.4 10.3 8.7 6.8 _ 6.1 3.6 LCL 7d 10 34.8 17.2 13.3 11.5 10.4 7.5 ROXC 30.9 8.9 6.6 4.9 4.7 4.3 DLCL 3.9 8.3 6.7 6.6 5.7 3.2 LCL 7e 30 36.3 20.4 17.4 14.1 13.1 11.8 ROXC 31.2 8.9 5.8 5.2 4.4 3.5 DLCL 5.1 *11.5 9.6 8.9 8.7 8.3 aTreadmill setting. bDuration of final setting. cRefers to midpoint for collection of expired air. dThree subjects only. 8One subject only 102 Whereas the time response for IRHR and ROXC depends on the treatment, this is not the case for DPOXC. The results of designed contrast using Bonferroni t (Miller, 1966) are shown in Table 12. There is no interaction between speed and duration of exercise for either IRHR, ROXC, or DOXC, although there is a strong trend for DOXC at all six recovery times. IRHR is significantly affected by both speed and duration of exercise, whereas ROXC is only affected by speeds and only at 0.5 minutes. There is a strong trend for ROXC during the first 10 minutes of recovery. DOXC is significantly affected by duration of exercise only although there is a strong trend for exercise intensity (S), which becomes significant when the total response during recovery (over all time points) is considered. In conclusion, it can be said that the HROXCR is different during exercise and recovery, and the reason is that the HR lags behind ROXC during the first 3 minutes of recovery. This lag in RHR is primarily effected by duration of exercise, and above 75% of maximal oxygen consumption there is little if any effect of exercise intensity. 103 .AH.ou ,.v wo.~H u u use Amo.o u a V oo.m H u um unmoamwcwwmo .Ho>mH Nmm may um ucmowmwcwfimn .AH.o u .Amo.o n 53v “mm.~H u u .Acoma.umaawz mu acouummcomv ummuuaoo wmawwmmam u .Am 1 Ev 'U .mmEHu hhm>oowh XHm HHw CO Ummmn ummHucOUm .Ha>6H Nam 6;“ a v mom.~H u u 660mm -- -- -- mama a -- -- mm>H mN.H ao.H oo.H n~.a mm.o om.o- «.mm>N.H eaaam no.m- om.- mm.- o-.N- nma.m- 3m.- a.~m>m.H «any eoxom ma.o mo.o- -.o Hm.o- Hm.o- NH.H- m.~m>a.H .uaucH oo.o o~.o H~.o NN.H m~.~ poa.~ mm>H eaaam om.o Ho.o oH.o Ho.H mo.~ nH~.w «.mm>~.fl eaaam om.o- o~.o Hm.o He.o- He.o- Hm.o 3.Nm>m.H asap oxom Hm.o- .oo.o Hm.o- o~.o- He.o mo.~ m.~m>a.H .paucH o~.~ onw.~ nmo.m nmm.~ n~5.m nmw.o mm>H eaaam 3H.N mm.H oo.~ N~.~ 3H.~ nam.m 3.mm>N.H eaaam oo.H oa.~ .am.~ nom.m na~.m nem.m 3.~m>m.a mafia mmmH mm.o oo.o mH.o- mH.o- N~.o oa.o- m.~m>a.H .pauaH m.nm, m.n~ m.NH m.~ o.m -mmo . mmwfiv mafia wum>oomm ammuunoo ummH Hm> .oxon 8am oxom .mmmH pom aaoaauamaawfim mo 6669 .NH wanes 1014 Discussion Effect of Diet and Previous Exercise There is no evicence of any effect of the different dietary treatments upon either the slope or y-intercept of the regression equation between the HR and OXC. The HROXCR varies with time around one for the subject's characteristic value. One can therefore expect to find occasional significant values. As can be seen from Table 4, the significance does not occur at a particular treatment in more than one subject, but occurs at random. As shown in Table 5, where the regression equation between HR and OXC is determined twice one hour apart in the same subject, the regression lines are significantly different, both in regard to slope and y-intercept. After one hour of rest, the OXC has returned to baseline values, but the HR is still elevated by about 20 beats/minute. Using IHR will correct for the differences in resting HR, and as shown in Table 5, it does decrease the significance of the differences in the y-intercepts. However, since the slopes are different, this does not necessarily mean that the regression lines are more homogenous. Schutz, et al (1981) have presented evidence that meals change the HROXCR. In their protocol, they first determined the regression equation, then fed the meals before re-establishing the regression line. Thus, the effect they found may equally well be due to an effect of the previous exercise. The older subjects presumably 105 were not very fit; so even though they used low intensity exercise, an effect of previous exercise cannot be excluded. The effect of previous exercise, in our experience, is dependent upon the training of the subjects. Lundgren (1946) in his study on lumberjacks, also found an effect of breakfast on the HROXCR, but upon further study concluded that it' was due to increased activity unrelated to the meal. He found a similar effect after a day of lumbering. Others have found that pro- longed, heavy exercise causes an increase in HR (Saltin, 1964; Rowell, 1974). Recovery from Exercise and the HROXCR The HROXCR during exercise and recovery are statistically signif- icantly different throughout exercise at all work intensities, since the recovery OXC (ROXC) is less than the lower 95% confidence limit (LCL) for the predicted OXC (POXC) based on the RHR and the prediction equation obtained during exercise. It is remarkable that DOXC increases rapidly during the first 3-4 min of exercise, and thereafter decreasing in parallel with the RHR.. This means that the RHR falls behind the ROXC during the first few minutes of recovery, and then returns toward the resting value at the expected rate based on ROXC. During exercise there is a redistribution of the blood volume, with less blood going to the viscera and unused muscles (Saltin, 1964b; Saltin et al, 1968). During recovery the perfusion to these organs must increase which can further decrease an already compromised vascular volume and cause a decrease in SV and a compensatory increase . in HR (Tanaka et al, 1979; Nadel et a1, 1980). 106 In Figure 3, the RHR is plotted as a function of time. The HR stabilizes at a level of about 20 beats/minute above the resting level (x-axis). Figure 7 demonstrates the effect on the IHR of increasing the workload, and the differences are significant except at the last time interval (Table 12). Nahdi and Spodick (1977) have obtained similar results, although they only followed the recovery for 5 minutes. How- ever, as shown in Figure 8 for IRHR, there is also a significant effect of duration of exercise. The difference due to D slowly decreases with time, and it is significant for the first 10 minutes only. When we look at the ROXC as shown in Figure 4 (lower curve), we see that the OXC decreases rapidly at first, and then slowly approaches the baseline level (the x-axis = preexercise OXC). As shown in two subjects followed for 5 hours post-exercise, the ROXC ends approaching the POXC (Fig. 2), and both RHR and ROXC are lower than the preexercise resting level. For the ROXC there are significant differences for the first minute only. There is no effect of 0 upon the ROXC. This condition is clearly different from what was seen for the HR, where both speed and duration of exercise have significant effect. These results are in agreement with the data of Hagberg, et a1 (1980), who found that the OXC response was two-phasic during recovery. A rapid phase of approxi- mately 2 minutes duration was significantly affected by the work inten- sity, but not by duration. Neither speed nor duration had any effect on the slow component, except for work intensities of higher than 65% of maximal oxygen consumption. In the present study, we found highly significant effects of speed for the first minute only (fast component), 107 but no effect of duration. Although not significant, we found a strong positive effect of speed upon the slow component, even at 60% of the maximal oxygen consumption. In Figure 4, the two upper lines show that POXC and 95% lower confidence limit (LCL), and since both are based on the actual RHR, it is not surprising that they lag behind ROXC (lower curve). In Figure 2, POXC, LCL and ROXC are plotted as a function of RHR to illustrate the statistical significance. Only duration of exercise has a statistically significant effect upon DOXC, which is illustrated in Figure 10 by the two upper curves. However, as seen from Table 12, the effect of speed is significant when the lowest and highest speeds are contrasted for all times simultaneously. ‘ It is concluded that the RHR does not predict the ROXC based on the regression equation during the preceding exercise period, because the RHR lags behind the ROXC during the first three minutes of recovery. .This lag is affected by duration of exercise only above 65% of maximal oxygen consumption. At lower work intensities, there is an effect of intensity (5) also; and this lag in RHR is not observed below 50% of maximal oxygen consumption in moderately fit subjects. Analysis of the regression equations for HR and OXC during exercise following different dietary treatments provided no evidence for a dietary effect upon the HROXCR; but exercise clearly changes both the slope and y-intercept. It is the duration of activity which is primarily responsible for the lag in RHR, although at low work inten- sities (around 50% of maximal oxygen consumption, depending on the physical training of the subjects), it is not observed. 108 Despite the intra-subject variability, and the deviation of ROXC from POXC, the HROCSR still forms the best basis for prediction of activity and HR and OXC are still correlated when only the day-to-day variation in resting OXC is considered. The deviation during recovery will make the observed differences appear greater than they really are, which may be acceptable for many applications. Mode of work (Andrews, 1971) and environmental temperature (Dill 8 Consolazio, 1962) also affect the HROXCR. It is recommended that at least three determinations of the individual regression line be made; but if that is not possible, it may be better to use a common slope. During steady state exercise, the HR slowly increases. That is why duration of exercise has a significaht.effect upon RHR, as has also been found by others (Tanaka et al, 1979). This increase in HR appears to be correlated with an increase in body temperature (Tanaka et al., 1979). As the HR increases, there is a simultaneous decrease in stroke volume (Roberts 8 Wenger, 1980; Nadel et a1, 1980). SV, in addition to exercise, is also affected by the state of hydration (Nadel et al, 1980); and in fact, the effect of exercise is probably related to the decrease in vascular volume (Saltin, 1964b). Both thermal and metabolic dehydration cause a decrease in stroke volume and an increase in HR to compensate for the decrease in stroke volume at submaximal workload, while there is no difference in HR and OXC at maximal workload (Saltin, 1964a). Costill and Fink (1974) reported that dehydration due to heat was similar to that caused by exercise in the effect upon HR and stroke volume, provided the same weight loss was obtained. Senay (1979) reported that training decreases the plasma 109 volume loss due to exercise, and in this study the best-trained subjects (as evidenced by lactate accumulation) had a less pronounced increase in HR during exercise and a faster recovery than less well- trained subjects. I CHAPTER 4 DIETARY INDUCED THERMOGENESIS DURING REST AND EXERCISE: EFFECT OF MEALS AND DIET ON OXYGEN CONSUMPTION AND ENERGY SUBSTRATE UTILIZATION DURING REST AND EXERCISE 110 lll Synopsis In this study the oxygen consumption was followed for 8 hours after consumption of a fat, carbohydrate, or protein meal respectively with measurements in the post-absorptive state (no food) as control. We found that each meal had a (statistically significant) different effect on the oxygen consumption during rest, whereas neither the meals nor a high fat or high carbohydrate diet (for 3 days prior to exercise) had any effect during exercise. Substrate utilization during rest (as evaluated by the R0) was affected only by the carbohydrate meal, whereas none of the treatments had any effect during exercise. Exercise following the meals compared to control (postabsorptive state) did not show any thermogenic effect. A _a 112 Introduction Overfeeding is generally thought to cause an increase in thermo- genesis. It has been shown that subjects generally gain less weight than the excess energy intakes suggest (Dauncy, 1979). Conflicting evidence comes from Glick, et al (1977) who reported that there was no effect of overfeeding on thermogenesis. One explanation for the controversy may be that energy cost of physical activity is increased due to overfeeding, but Norgan and Durnin (1980) found no such effect. Norgan and Durnin also argue against what is termed "luxus-consumption" (Apfelbaum, et a1, 1971). It has also been shown that underfeeding results in a decreased resting metabolic rate (RMR) (Apfelbaum, et a1, 1971; Dauncy, 1979). ' Rubner (1902) and Lusk (1928) found that protein had a specific thermogenic response; but more recently, Garrow and Hawes (1972) found a similar thermogenic effect of a test meal regardless of its nutrient content. Shetty, et a1 (1980) found similar results, and Owen, et al (1980) found a thermogenic Response to breakfast as evaluated by the oral temperature. However, in an animal (pigs) study, Gurr, et al (1980) found a major response to a low protein diet, but none to a high protein diet. Dauncy (1979) reported a significant increase in 24-hour energy expenditure in man, when the energy intake was changed from glucose to protein. ‘ /__;a 113 Cold induced thermogenesis (CIT) due to epinepherine acting on brown adipose tissue and muscle is readily demonstrated in laboratory animals (Heldmeir, 1971) and also in man (Joy, 1963). This response can be reduced by B-adrenergic-blockade with propranolol (Dauncy and Ingram, 1979). In rats, DIT as well as CIT involves changes in the activity of the sympathetic nervous system (Rothwell and Stock, 1979; Glick, et al, 1981). Capro, et al (1981) demonstrated that the ingestion of a standard meal caused an increase in blood insulin and glucose, but a decrease in plasma free fatty acids in man. In the present study, both protein and carbohydrate meals had a thermogenic effect (maximal response was 38 and 27% respectively). The effect of a carbohydrate meal lasted less than 6 hrs compared to more than 8 hrs for a protein meal. The effect of diet on muscle glycogen content and therefore exercise endurance is well demonstrated (Karlson and Saltin, 1971). Under conditions where the glycogen stores are not expected to change, it has been shown that substrate concentration in the blood and the R0 are affected, whereas the OXC is not (Foster, et al, 1979) at exercise intensities of 80-100% of maximal oxygen consumption. Others have found an effect of diet upon energy substrate utilization at rest, but not during exercise (Hurni, et al, 1980). It is surprising that pre-exercise glucose feeding should have an effect on the substrate utilization during exercise, unless it affects the glycogen stores, since it has been shown that even at much lower work intensities, the major substrate is intramuscular (Essen, 1978). In the present study, there was no effect of diet or meals upon energy substrate utilization A _- 114 during exercise (80% of maximal oxygen consumption), but carbohydrate meals increased utilization of carbohydrates during rest. Apfelbaum, et al (1971) and Miller, et al (1967) found an increase in OXC during exercise following overeating. Bray, et a1 (1974) found no effect of overfeeding on OXC, but reported that a 4.2 and 12.6 MJ .meal increased the OXC during exercise. However, in the present study, we found no thermogenic effect on exercise following a meal. - 115 Methods The study was divided into two parts. The first part examined the effect of meals on OXC and the relative contribution of fat and carbo- hydrate to the energy utilization during rest. In the second part the effect of meals and diet composition upon the same parameters was investigated during exercise. Subjects Two groups of five healthy male college students volunteered for the study. The physical characteristics of the subjects are given in Table 1. None of the subjects took any medication; and on the day of the experiment, they were requested not to drink any caffeine-containing beverages. They also did not participate in any strenuous physical activity on the day before the experiments were conducted. Informed Consent Each subject signed an informed consent form after the details of the experiments were described to him. The form stated the experimental procedures, identified possible risks, and noted that a subject could terminate his participation at any time. Diets The composition of the diets and meals is given in Table 2. Each meal contained 700 kcal. The fat meal consisted of 288 m1 whipping cream, which the subjects drank in less than 10 minutes. The protein Table 1. Physical characteristics of the two groups of five adult (SD = Standard Deviation). male subjects. Physical __ Characteristics Exercise 1193.1 5.9. 829.2 23. Age (years) 26.6 1.7 24.8 3.1 Body Weight (kg) 78.2 11.3 74.5 11.9 Height (cm) 182 6.1 173 7.4 V02-maxa (ml Oz/min/kg) -- -- 54.1 6.6 aMaximal oxc. 117 .AmNmpv zugasu a zugzsu "Amompv Fppggmz vac uumzm q.m N.NN mm m_ NN om_.N m_m»_6=< .au_sa;u Sa_o aoacexcoagau o.e o.me o_ c. we om_.N m_mN.a=< .86_sagu 36_a com mm m. ON om_.N mapnap cool ua_o auaeusgoncau ON m. mo cm_.N m6_aac nook am_o 36L mm m N ooN m6_aac 666; _862 auacexgoacau N 6N NN ooN m6_aap noon .862 c.65628 m N No coN amapaac 666“ .66: 38L gm< Loam: mwmmwwu :_muoga an; apaoxv xmemcm conga: m_cmz Lo mum_o ugmwmz xn N xmgmcm Page» mo & peach occ.m use oo_.m :mmzuma um_gm> mummu use yo “cm“:ou xmemcm mzb .muumnnzm acmgmmm_u 6:» Lo» Pmux .muomu use mpmme Lo :o_u_moaeou .N m_nm~ 118 meal consisted of 94 g creamed cottage cheese and 545 g (raw weight) skinned chicken breast, with all visible fat removed. The subjects ate the protein meal in 30 minutes. The carbohydrate meal consisted of 824 g ripe bananas (peeled), which were eaten in less than 10 minutes. The subjects drank 340 cc of ginger ale with the meals containing 1 kcal (Vernors, Detroit, MI), and were allowed salt, pepper, and water ad lib. During the experimental periods the subjects ate 2,100 to 2,400 kcal per day either as a high fat or as a high carbohydrate diet. The composition is given in Table 2. The subjects were fed one of the two experimental diets in random order for three days prior to the exercise test, which was performed in the postabsorptive state the fourth day. The diet and meals were prepared and eaten in a kitchen adjacent to the exercise laboratory. Two menus were used for each diet: one for breakfast and one for dinner and supper. The menus were repeated for all three days. The subjects were supervised during the meals and ate all the allotted food. Duplicate portions were used for chemical analysis. Fat was analyzed by ether extraction, protein by micro- kjeldahl, minerals as ash (600°C) and carbohydrate by difference. For both diets regular food items were used. Sources of fat were: margarine, mayonnaise, chee5e, eggs, bacon and olives; while sources of carbohydrate were: bananas, bread, potatoes, sweet potatoes, beans, carrots and peas. These foods contain some protein. Additional protein came from soy protein. For the fat diet it was imitation chicken, and for the carbohydrate diet it was imitation beef (Worthington Foods, Worthington, OH). 119 Measurements Heart rate (HR) was obtained from an electrocardiogram (lead 2 with the positive lead in V5 position). The EKG signal was converted to heart rate through a cardiotachometer (built in our lab) and con- tinuously recorded by a calibrated Sargent Recorder, Model DTM-115—4 (Sargent and Company, Chicago, IL). The mean HR in beats/minute corres- ponding to each collection of expired air was calculated from the recording. The oxygen consumption (OXC) was determined by a modified Douglas method (Consolazio, et al, 1963). The expired air was collected through a low resistance valve (Otis-McKerrow, Warren Collins, Inc., Braintree, MA) in light-weight ne0prene bags. The composition (02 and C02 contents) of the collected air was immediately determined using the Beckman LB-2 carbon dioxide and Beckman OM-ll oxygen analyzers, respec- tively (Beckman Instruments, Schiller Park, IL). The air volume was determined by metering through (using a constant flow of 50 l/min) a Singer dry gas meter (American Meter Company, Philadelphia, PA). The mean OXC for the control experiment was compared the baseline (mean resting OXC prior to the ingestion of the meal). To correct for the day to day variation in the resting OXC in each subject the difference between the control and baseline values were added or subtracted from the OXC for that day's treatment. Lactic acid was determined in duplicate arterialized blood samples (Gambino, 1961; Jung et al, 1966) collected from the fingers after the hand was immersed in warm water (45°C) for two minutes. The finger was dried, cleaned with alcohol and punctured with a lancet. 120 The first drop of blood was wiped off with sterile gauze. One hundred ul of blood was collected in a capillary tube centrifuged-atZOOO rpm in 8% perchloric acid. The sample was then incubated at room temperature with lactate dehydrogenase for one hour. The nicotine adenine dinu- cleotide (NADH) generated was measured on a monocromatic spectro- photometer (Gilford Stasar II, Gilford Instruments, Inc., Oberlin, OH) at 340 nm. Exercise Tests The maximal OXC was determined in a continuous incremental test with the subjects exercising on the treadmill until exhaustion. The speed was increased stepwise at 8.8, 10.5, 12.5 and 14.3 km/h0ur. When the subjects reached the highest speed they could comfortably run (12.5 or 14.3 km/hr) further increases in the workload were accomplished by increasing the treadmill inclination in steps of 2%. The subjects ran 3 minutes at each step, the HR.Was recorded continuously, three one-minute bags of expired air were collected at each step, and the oxygen consumption calculated for each minute. The OXC following the different treatments was determined through an incremental exercise test with the final workload corresponding to 80% of the subjects' maximal OXC. Three collections of expired air were made at each step and the mean HR corresponding to each air collection was recorded. The test started at rest with the subject seated in an armchair, while 3 consecutive 5-minute collections of expired air were made. During the following steps the subjects would walk or run on the treadmill. At the 4:8 km/hr and 6.8 km/hr levels 121 the subjects exercised for 6 minutes each, and at the other levels they exercised for 3 minutes each; except when they reached the final speed (the one corresponding closest to 80% of their maximal OXC), they continued the exercise for 20 minutes. During the final stage, one-minute bags of expired air were collected, every second minute starting with the second minute. Following theexercise the HR and OXC were determined during 40 minutes of recovery. Two one-minute bags, one three-minute and one five-minute bag of expired air were collected during the first 10 minute of recovery. During the next 30 minutes, 3 five-minute bags of expired air were collected every second S-minute period. During the alternate 5-minute periods, when no collections were made, the subject remained seated in the armchair, but was relieved of the face mask with air-collection valve and the noseclip. Arterialized blood samples were collected from one of the fingers at 5, 15, 25 and 40 minutes of recovery for determination of the blood lactate concentra- tion. Experimental Protocol Best_ For measurements taken during rest, the subjects were seated in an armchair. The subjects were asked to restrict their movement, but at the same time, to change the leg position approximately once every minute to avoid venous pooling. The temperature of the laboratory was kept constant (11°C) throughout the experiment, but it did vary somewhat between experimental days depending on the environmental 122 temperature. The humidity and barometric pressure could not be controlled. The day of the experiment, the subjects arrived in the laboratory about 8:00 am in the postabsorptive state (after overnight fast), and spent the day in the laboratory resting, reading, or talking. No food or beverages except the experimental meal were consumed, but the subjects drank as much water as they wanted. The three treatments were (1) the fat meal, (2) the protein meal, and (3) the carbohydrate meal described previously, and for the control treatment, no food was given. The four treatments were done in a random order one week apart. Before the experimental meal was given, six five-minute baseline measurements of OXC and HR were taken. The subject was seated in an armchair for three consecutive five-minute periods while expired air was collected and HR recorded. The subject was then given a five- minute break in which he walked around in the laboratory before another series of three consecutive five-minute collections of expired air and recordings of HR were carried out. For each five minutes, one bag of expired air was collected for analysis of OXC and R0. The mean HR was calculated for each bag of expired air. The mean of the six determina- tions was used as the baseline (time 0) for that particular treatment (meal). Duplicate arterialized blood samples for lactate determinations were collected before the meals were eaten. After baseline determination, the subjects ate the experimental meal and three consecutive five-minute collections of expired air and recordings of HR were taken at 30 minutes and at one hour following the completion of the meal and thereafter at one-hour intervals for eight 123 hours following the meal. The mean of the three measurements was used. During the control treatment, when no meal was given, the protocol was the same, except that no "baseline" measurements were taken. Blood was collected for lactate determination at the same times as the other measurements were taken except for the first hour, when blood samples were taken every 15 minutes. Blood collections were discontinued after 6 hours. During rest lactate was measured only during the control treatment and following the carbohydrate meal. Exercise The exercise experiments were carried out over a lO-week period with each test given one week apart. During the first and last tests the maximal OXC were determined. The second test was always a control (postabsorptive state) prior to which the subjects ate their normal diet. Prior to the third test, the subjects consumed one of the experimental diets for three days (two started with the high fat diet and three with the high carbohydrate diet). Then followed another control test before the opposite experimental diet was introduced, three days prior to the fifth test. Following both dietary treatments, the ‘ test was carried out in the postabsorptive state. The three meals and a final control were introduced in random order so that all the subjects would not consume the meals in the same order. The exercise tests began 30 minutes after termination of the carbohydrate meals and 2-3 hours following the fat and protein meals, which we had found to correspond to the maximal thermogenic response. 12h Statistical Analysis OXC, R0 and lactate were analyzed by a split block (block = subjects) repeated measurements design. The differences among treat- ment means were evaluated by Tukey's test (Tukey, 1953). The correla- tion coefficient between HR and OXC was calculated for each test at rest in each subject, and the mean and confidence limits for each dietary treatment and control were calculated by conversion to the Z-score (Steel and Torrie, 1960). 125 Results Experiments During Rest Table 3 shows resting OXC for eight hrs following the experimental meals and during control when no food was given. All treatments were compared with control and each other and the Tukey test was used to determine the significance of the treatment differences shown in .Table 3. Although the fat meal caused an increased OXC compared to control from 1 to 6 hrs after the meal it was not significant. The protein meal caused a significant increase in OXC compared to control from 1 to 6 hrs after the meal; and the carbohydrate meal caused OXC to be significantly different from control to 3 hrs following the meal. The protein meal caused a significant increase in OXC from 3 to 6 hrs compared to the carbohydrate meal. The mean increases in OXC compared to control following the fat, protein and carbohydrate meals was 7.3%, 21.2% and 12.8% respectively, while the peak increases were 8.9%,33.0% and 27.4% respectively. The different thermogenic responses for the treatments are shoWh in Figure 1. Table 4 shows the effects of the treatments on the respiratory quotient (RQ). Only following the carbohydrate meal is there a sig- nificant effect upon the RO compared to control. Although the RO is increased for the eight hrs observed, the increase is only significant (p<0.05) for 3 hrs. The maximal increase in R0 compared to control is 0.14 and the mean increase is 0.09. The R0 for the carbohydrate meal and control is plotted in Figure 2. 126 Table 3. Mean oxygen consumption following the ingestion of various meals for 5 male subjects in the resting state. Control was the postabsorptive state. Time Meals (hrs) Control Fat Protein Carbohydrate 0 3.60 3.56 3.62 3.56 0.5 3.58 3.62 4.04Cf 4.06b 1.0 3.60 3.82 4.32af 4.32a 2.0 3.62 3.90 4.66ad 4.56a 3.0 3.58 3.90 4.76ag 4.14bg 4.0 3.56 3.90c 4.68adg 3.849 5.0 3.48 3.82c 4.54adg 3.709 6.0 3.60 3.70 4.22aCh 3.66h 7.0 3.56 3.62 3.96Cf 3.64 8.0 3.58 3.58 3.92Cf 3.58 alb/CValues for any of the meals are significantly different from control at the same time (a, p<0.01, b p<0.05; c, p<0.lO). d(e/fValues for the carbohydrate - or protein meal are significantly different from the fat meal at the same time (d, p<0.01; e, p<0.05; f, p<0.lO). g/h/1.Values for the protein meal are significantly different from the carbohydrate meal at the same time (9, p<0.0l; h, p<0.05; i, p<0.lO . Standard errors of individual treatment means at one time are irrele- vant for comparisons or reliability. Standard error of difference of 2 treatments at one time is 0.157. Standard error of difference of 2 times for one treatment is 0.088. OXC in ml/min/kg. 127 Table 4. Mean respiratory quotient following the ingestion following ingestion of various meals for 5 male subjects in the resting state. Control was the postabsorbtive state. Time Meals (hrs) Control Fat Protein Carbohydrate 0 0.750 0.762 0.756 0.760 0.5 0.750 0.756 0.756 0.856Cfi 1.0 0.746 0.760 0.760 0.880Eh 2.0 0.750 0.746 0.762 0.892adh 3.0 0.744 0.736 0.736 0.876 bdg 4.0 0.746 0.740 0.754 0.842 Cf 5.0 0.764 0.732 0.712 0.8081 6.0 0.750 0.736 0.752 0.780 7.0 0.754 0.738 0.740 0.796 8.0 0.742 0.748 0.744 0.790 a/b/CValues for any control at the d/9/fValues for the different from p<0.05; f, p<0. g/h/‘.Values for the different from one of the meals are significantly different from same time (a, p<0.01; b, p<0.05; c, p<0.lO). carbohydrate - or protein meal are significantly the fat meal at the same time (d, p<0.01; e, protein and carbohydrate meals are significantly each other (9, p<0.0l; h, p<0.05; i, p<0.lO). Standard errors of individual treatment means at one time are irrele- vant for comparisons or reliability. Standard error of difference of 2 treatments at one time is 0.035. Standard error of difference of 2 times for one treatment is 0.023. Figure l. 128 OXC as a function of time. Treatments are: C = control (lower curve), CH-M = carbohydrate meal (middle curve), and P-M = protein meal (upper curve). All treatments are the mean of 5 subjects. The 5% least significant difference (LSD) is 0.47. SE for difference between the treatment means at the same time is 0.111 ml/min/kg, and the SE for the difference between two time means in the same treatment is 0.062 ml/min/kg. 129 DIT 5.Z 1P 3.5 (fix/muI/Iw) oxo FIGURE 1 23.5 LLB B.Z E.Z Time (hrs) 2.Z Figure 2. 130 Respiratory Quotient (R.Q.) as a function of time for CH-M and Control (C). No other treatment had a significant effect. LSD is (5%) = 0.104. Mean of 5 subjects. (SE for the difference between the treatment means at the same time is 0.025 and the SE for difference between two time means in the same treatment is 0.016.) 131 A35 05.... N.m H.m L ‘ 1P .005 0:0 .ozcoo hmwm $2.230 Om O :8. OH FIGURE 2 132 As will be reported elsewhere the blood lactate concentration was measured following the carbohydrate meal and during the control. The results are shown in Figure 3. The peak lactate response of about 2.4 mM occurred 1 hr following the meal and the response was significant for 3 hrs. The mean correlation coefficient (F) between the HR and OXC was calculated for each treatment. As seen from Table 5 only for the carbohydrate meal was F significantly different from 0 (F = 0.516). Exercise Experiments The mean OXC for the 20 min during exercise following the fat, protein, carbohydrate meal, the high fat, high carbohydrate diet and control were: 41.7, 41.8, 42.0, 41.5, 41.6 and 42.4 ml/min/kg body weight. The standard error for difference of 2 treatments at one time is 2.58 ml/min/kg. The RQ during exercise following the fat, protein, carbohydrate meals, the high fat, high carbohydrate diets and control were: 0.84, 0.84, 0.87, 0.86, 0.83, 0.85; and the standard error was 0.069. There were no statistical significant treatment differences for either OXC or R0. Figure 3. 133 Blood lactate as a function of time after a CH-M and C (at least 5 hours postabsorptive). Mean of 5 subjects. Five percent LSD = 1.471. (The SE for difference between the two treatment means at the same time is 0.239‘mM, and the SE for difference between the two time means in the same treatment is 0.072 mM.) 134 .25 as: 8.7. EN 4 ill lll’ll 'h'l .ozcoo Chm»: mh75% of maximal oxygen consumption) provided the glycogen stores are not affected. Similar results were obtained by Bergstrom, et al (1969). CHAPTER 5 EFFECT OF MEALS AND DIET 0N POSTEXERCISE BLOOD LACTATE LEVELS 143 lhh Synopsis The effects of a high fat diet and a high carbohydrate diet; and fat, protein and carbohydrate meals on postexercise lactate were inves- tigated. Five subjects were exercised for 20 minutes at approximately 80% of maximal oxygen consumption. After each of the diets and control they were exercised in the postabsorptive state, and after the meals in the absorptive state. The lactate production was also measured in the resting state for six hours following a carbohydrate meal, and during control (postabsorptive state). Following a carbohydrate meal, there was a four-fold increase in the whole blood lactate concentration compared to control. After exercise, blood lactate was measured at 5, 15, 25, and 40 minutes. There was a significant time by treatment interaction for carbohydrate meal compared to control and fat meal. The total response was also significantly different for carbohydrate meal compared to fat meal. These results do not support the hypothesis that diet affects the lactate production during exercise, although a carbohydrate meal has a sighificant effect upon the decrease in blood lactate concentration during recovery. 145 Introduction The widely used concept that the percentage of maximal oxygen consumption can be used to equalize the physiological work load has recently been questioned (Katch, et al, 1978). The authors showed that at the same relative percent oxygen uptake, the subjects had different anaerobic thresholds. Kinderman, et a1 (1979) have showed that the aerobic-anaerobic threshold is a better predictor of the physiological work load. It is controversial whether decreased muscle oxygen tension, high rate of glycogenolysis, or both are responsible for lactate production (Bylund-Fellenius, 1981; Jacobs, 1981). However, it is clear that a number of factors affect the blood lactate. These include muscle respiratory capacity and fiber composition, mode (rest or exercise) of recovery (McGrail, et al, 1978; Poortmans, et al, 1978; Stanford, et al, 1981), as well as muscle glycogen content (Graham, 1978; Ivy, et a1, 1980; Jacobs, 1981). ‘ A number of studies haJe demonstrated how previous exercise and diet can affect muscle glycogen and lactate production (Jacobs, 1981; Essen, 1978; awen et a1, 1981; Maughan, et al, 1978; and Maughan and Poole, 1981). Thus, Maughan (1978, 1981) has shown that at both high and low intensity work, an exercise-diet regimen that increases muscle glycogen also increases lactate production during exercise and vice versa. The effect of lactate agrees with the explanation of Newsholme 146 and Crabtree (1979) that lack of substrate (glycogen) will reduce the flow through a metabolic pathway. Robin and Hance (1980) emphasize the importance of enzymes and substrates in regulation of the glyco- genolytic rate, and it has been demonstrated that blood FFA's affect the glycolytic rate and lactate production (Bergstrom, et al, 1969; Foster, et al, 1979); although Bergstrom found no effect at high work loads. In the present study we evaluated the effect of diet on the post-exercise blood lactate under conditions in which one would not expect any effect on muscle glycogen. We found that diet did effect blood lactate recovery rate but not the blood lactate concentration 5 min following exercise. 11.7 04211995. The study was divided into two parts. The first part examined the effect of meals on OXC and the relative contribution of fat and carbo- hydrate to the energy utilization during rest. In the second part the effect of meals and diet composition upon the same parameters was investigated during exercise. Subjects Two groups of five healthy male college students volunteered for the study. The physical characteristics of the subjects are given in Table 1. None of the subjects took any medication; and on the day of the experiment, they were requested not to drink any caffeine-containing beverages. They also did not participate in any strenuous physical activity on the day before the experiments were conducted. Informed Consent Each subject signed an informed consent form after the details of the experiments were described to him. The form stated the experimental procedures, identified possible risks, and noted that a subject could terminate his participation at any time. Diets The composition of the diets and meals is given in Table 2. Each meal contained 700 kcal. The fat meal consisted of 288 m1 whipping cream, which the subjects drank in less than 10 minutes. The protein 148 Table 1. Physical characteristics of the two groups of five adult male subjects. Physical _p_ Parts Characteristics Restri Exercise Mean §Q§ NEED. §Q_ Age (years) 26.6 1.7 24.8 3.1 Body Weight (kg) 78.2 11.3 74.5 11.9 Height (cm) 182 6.1 173 7.4 Maxoxcb (ml/min/kg) -- - -- 54.1 6.6 aso = Standard Deviation. bMaximal 0x0. 1’49 .Ammm.v 58.329 8 :u.=;u .Amom.v .....6z 6:8 88838 8.8 8.N. 88 8. NN 88..N 6.68.888 .88.e688 86.8 688.8.888.88 8.8 8.88 8. 8. 88 88..N 6.68.888 .88.e688 86.8 88. 68 8. 8N 88..N 66.88. 888. 86.8 688.8.888.88 8N 6. 88 88..N 66.88. 888. 86.8 88. 88 8 N 88. 66.88. 888. .86: 688.8.888.88 N 8. NN 88. 66.88. 888. .86: 8.688.. 8 8 N8 88. 866.88. 888. .86: 88. 86< .6883 6mmmmww 8.686.. 88. ..86¥. 88.68. 86:86: 6.862 .6 686.8 886.63 >8 8 86.686 .8868 .6 a .886. o08.~ 8:8 oo..~ 8663868 86..8> 686.8 6:8 .6 8:68:66 86.686 68. .6866n886 886.6...8 6:8 .6. .86. .686.8 6:8 6.86s .6 86.8.668568 .N 6.88. 150 meal consisted of 94 g creamed cottage cheese and 545 g (raw weight) skinned chicken breast, with all visible fat removed. The subjects ate the protein meal in 30 minutes. The carbohydrate meal consisted of 824 g ripe bananas (peeled), which were eaten in less than 10 minutes. The subjects drank 340 cc of ginger ale with the meals containing 1 kcal (Vernors, Detroit, MI), and were allowed salt, pepper, and water ad lib. During the experimental periods the subjects ate 2,100 to 2,400 kcal per day either as'a high fat or as a high carbohydrate diet. The composition is given in Table 2. The subjects were fed one of the two experimental diets in random order for three days prior to the exercise test, which was performed in the postabsorptive state the fourth day. The diet and meals were prepared and eaten in a kitchen adjacent to the exercise laboratory. Two menus were used for each diet: one for breakfast and one for dinner and supper. The menus were repeated for all three days. The subjects were supervised during the meals and ate all the allotted food. Duplicate portions were used for chemical analysis. Fat was analyzed by ether extraction, protein by micro- kjeldahl, minerals as ash (600°C) and carbohydrate by difference. For both diets regular food items were used. Sources of fat were: margarine, mayonnaise, chee5e, eggs, bacon and olives; while sources of carbohydrate were: bananas, bread, potatoes, sweet potatoes, beans, carrots and peas. These foods contain some protein. Additional protein came from soy protein. For the fat diet it was imitation chicken, and for the carbohydrate diet it was imitation beef (Worthington Foods, Worthington, 0H). 151 Measurements Heart rate (HR) was obtained from an electrocardiogram (lead 2 with the positive lead in V5 position). The EKG signal was converted to heart rate through a cardiotachometer (built in our lab) and con- .tinuously recorded by a calibrated Sargent Recorder, Model DTM-115-4 (Sargent and Company, Chicago, IL). The mean HR in beats/minute corres- ponding to each collection of expired air was calculated from the recording. The oxygen consumption (OXC) was determined by a modified Douglas method (Consolazio, et al, 1963). The expired air was collected through a low resistance valve (Otis-McKerrow, Warren Collins, Inc:, Braintree, MA) in light-weight neoprene bags. AThe composition (02 and C02 contents) of the collected air was immediately determined using the Beckman LB-2 carbon dioxide and Beckman OM-ll oxygen analyzers, respec- tively (Beckman Instruments, Schiller Park, IL). The air volume was determined by metering through (using a constant flow of 50 l/min) a Singer dry gas meter (American Meter Company, Philadelphia, PA). The mean OXC for the control eXperiment was compared the baseline (mean resting OXC prior to theiingestion of the meal). To correct for the day to day variation in the resting OXC in each subject the difference between the control and baseline values were added or subtracted from the OXC for that day's treatment. Lactic acid was determined in duplicate arterialized blood samples (Gambino, 1961; Jung et al, 1966) collected from the fingers after the hand was immersed in warm water (45°C) for two minutes. The finger was dried, cleaned with alcohol and punctured with a lancet. 152 The first drop of blood was wiped off with sterile gauze. One hundred ul of blood was collected in a capillary tube centrifuged-atZOOO rpm in 8% perchloric acid. The sample was then incubated at room temperature with lactate dehydrogenase for one hour. The nicotine adenine dinu- cleotide (NADH) generated was measured on a monocromatic spectro- photometer (Gilford Stasar II, Gilford Instruments, Inc., Oberlin, 0H) at 340 nm. Exercise Tests The maximal OXC was determined in a continuous incremental test with the subjects exercising on the treadmill until exhaustion. The speed was increased stepwise at 8.8, 10.5, 12.5 and 14.3 km/hour. When the subjects reached thehighest speed they could comfortably run (12.5 or 14.3 km/hr) further increases in the workload were accomplished by increasing the treadmill inclination in steps of 2%. The subjects ran 3 minutes at each step, the HR’was recorded continuously, three one-minute bags of expired air were collected at each step, and the oxygen consumption calculated for each minute. The OXC following the different treatments was determined through an incremental exercise test with the final workload corresponding to 80% of the subjects' maximal OXC. Three collections of expired air were made at each step and the mean HR corresponding to each air collection was recorded. The test started at rest with the subject seated in an armchair, while 3 consecutive 5-minute collections of expired air were made. During the following steps the subjects would walk or run on the treadmill. At the 4.8 km/hr and 6.8 km/hr levels 153 the subjects exercised for 6 minutes each, and at the other levels they exercised for 3 minutes each; except when they reached the final speed (the one correSponding closest to 80% of their maximal OXC), they continued the exercise for 20 minutes. During the final stage, one-minute bags of expired air were collected, every second minute starting with the second minute. Following the exercise the HR and OXC were determined during 40 minutes of recovery. Two one-minute bags, one three-minute and one five-minute bag of expired air were collected during the first 10 minute of recovery. During the next 30 minutes, 3 five-minute bags of expired air were collected every second 5-minute period. During the alternate 5-minute periods, when no collections were made, the subject remained seated in the armchair, but was relieved of the face mask with air-collection valve and the noseclip. Arterialized blood samples were collected from one of the fingers at 5, 15, 25 and 40 minutes of recovery for determination of the blood lactate concentra- tion. Experimental Protocol Rg§t_ For measurements taken during rest, the subjects were seated in an armchair. The subjects were asked to restrict their movement, but at the same time, to change the leg position approximately once every minute to avoid venous pooling. The temperature of the laboratory was kept constant (ilOC) throughout the experiment, but it did vary somewhat between experimental days depending on the environmental 1514 temperature. The humidity and barometric pressure could not be controlled. The day of the experiment, the subjects arrived in the laboratory about 8:00 am in the postabsorptive state (after overnight fast), and spent the day in the laboratory resting, reading, or talking. No food or beverages except the experimental meal were consumed, but the subjects drank as much water as they wanted. The three treatments were (1) the fat meal, (2) the protein meal, and (3) the carbohydrate meal described previously, and for the control treatnent, no food was given. The four treatments were done in a random order one week apart. Before the experimental meal was given, six five-minute baseline measurements of OXC and HR were taken. The subject was seated in an 'armchair for three consecutive five-minute periods while expired air was collected and HR recorded. The subject was then given a five- minute break in which he walked around in the laboratory before another series of three consecutive five-minute collections of expired air and recordings of HR were carried out. For each five minutes, one bag of expired air was collected for analysis of OXC and R0. The mean HR was calculated for each bag of expired air. The mean of the six determina- tions was used as the baseline (time 0) for that particular treatment (meal). Duplicate arterialized blood samples for lactate determinations were collected before the meals were eaten. After baseline determination, the subjects ate the experimental meal and three consecutive five—minute collections of expired air and recordings of HR were taken at 30 minutes and at one hour following the completion of the meal and thereafter at one-hour intervals for eight 155 hours following the meal. The mean of the three measurements was used. During the control treatment, when no meal was given, the protocol was the same, except that no "baseline“ measurements were taken. Blood was collected for lactate determination at the same times as the other measurements were taken except for the first hour, when blood samples were-taken every 15 minutes. Blood collections were discontinued after 6 hours. During rest lactate was measured only during the control treatment and following the carbohydrate meal. Exercise The exercise experiments were carried out over a lO-week period with each test giVen one week apart. During the first and last tests the maximal OXC were determined. The second test was always a control (postabsorptive state) prior to which the subjects ate their normal diet. Prior to the third test, the subjects consumed one of the experimental diets for three days (two started with the high fat diet and three with the high carbohydrate diet). Then followed another control test before the opposite experimental diet was introduced, three days prior to the fifth test. Following both dietary treatments, the test was carried out in the postabsorptive state. The three meals and a final control were introduced in random order so that all the subjects would not consume the meals in the same order. The exercise tests began 30 minutes after termination of the carbohydrate meals and 2-3 hours following the fat and protein meals, which we had found to correspond to the maximal thermogenic response. 156 Statistical Analysis Blood lactate during rest and recovery from exercise following the various treatments was analyzed by a split block (block = subject) repeat measurements design (each subject served as his own control). The differences between treatment means were evaluated by designed contrast (Bonferroni t statistics; Miller, 1966). 157 Results The resting blood lactate in the postabsorptive (after an over- night fast) resting state was about 0.5 mM and decreased slightly with time. Following the carbohydrate meal there was a rapid increase in the blood lactate concentration to a mean value of 2.3 mM, which was significantly different from control for the first 3 hrs. The results are given in Table 3 and plotted in Figure l. Regardless of time the postexercise blood lactate level are similar in the postabsorptive state for controls and when the subjects were fed a high fat or a high carbohydrate diet for 3 days. The mean for the 3 conditions was calculated and presented as "D" in Table 4 and plotted in Figure 2. The fat and protein meals give similar values and the mean is presented as "M" in Table 4 and plotted in Figure 2. For 0 the blood lactate decreases from 3.0 at 5 min of recovery to 0.7 at 40 min of recovery. The values for M - although lower - are not statistically different as shown in Table 5. Following the carbohy- drate meal the postexercise‘blood lactate decreases from 2.6 mM at 5 min to 1.8 mM at 40 min of recovery and is plotted separately in Figure 2. The total blood lactate response following the carbohydrate meal is significantly different from that following the fat meal as shown in Table 5. There is also a significant interaction between the post-exercise blood lactate following the carbohydrate meal and both the control and fat meal at 5 and 40 min of recovery. Thus . 158 Table 3. Blood lactate in arterialized blood for 6 hours following a carbohydrate meal, and in the post- absorptive state following an overnight fast as control. Mean of five subjects. Time Control Carbohydrate Dunnett's Test* (hrs) Meal to 0.00 0.51 0.59 0.37 0.25 0.49 1.44 4.43a 0.50 0.48 1.89 6.58a 0.75 0.49 2.21 8.03a 1.00 0.53 2.28 8.17a 2.00 0.41 1.66 ' 5.84a 3.00 0.40 0.93 2.47b 4.00 0.36 0.64 1.31 5.00 0.35 0.59 1.12 6.00 0.34 0.52 0.84 *Significant difference between treatment means of the same time was determined by Dunnett's test (Dunnett, 1955. 1964). \- aSignificant at 1% level (t 3.36). bSignificant at 5% level (t 2.31). Standard errors of individual treatment means at one time are irrelevant for comparisons or reliability. Standard error of difference of two treatments at one time is 0.214 (mM). Standard error of difference of two times for one treatment '15 0.102 (mM). Figure l. 159 Blood lactate concentration (mean of five subjects) in the postabsorptive state (following an overnight ffist) as con- trol (lower line) and following a 2.94 MJ carbohydrate meal (bananas). The S.E. for difference between the treatment means at the same line is 0.339 (mM); and the S.E. for difference between the means at two times is 0.102 (mM). 160 .85 68.: .N.m .N.I H.N 8.8 u '6 - Hon .1! 4 i .P ilfll-i P L- [lll-lllI' l- A .2230 .60.: 36.5....0830 . a. .8 nu.mu Ahmmm: m...<._.O<-_ GOO-E . .r a n ('VWW) 9191991 90019 Figure 1 Figure 2. 161 Blood lactate concentration during recovery from exercise at 80% of maximal oxygen consumption for 20 minutes (mean of five subjects). Upper curve following CH-M; middle curve is the postabsorptive state; and lower curve is mean of F-M and P-M. The S.E. for differences between the treatment means at the same time is 0.483 (mM); the S.E. for differences between two times is 1.13 (mM), and the S.E. for comparing interaction between two treatments at two different times is 0.282 (mM). 162 .58. OE... 36:600.. .NT. .MN .8” .MN .NN .M. .H. .60.: 086.52.68.60 m._.<._.0<... GOO-.0 >mm>00mm 1 (1/ww) uonenueouoo 6191081 pooga FIGURE 2 163 Table 4. Mean blood lactate concentration during 40 minutes recovery from 20 minutes of exercise at 80% maximal O x C in 5 subjects. Blood Lactate (HIM) Treatments 8;:Fcise 5 min 15 min 25 min 40 min Control 0.782 2.94 1.76 1.10 0.68 Fat Diet 0.517 2.99 1.48 1.22 0.75 Carbohydrate Diet 0.782 2.99 1.33 1.03 0.69 Fat Meal 0.543 2.21 1.03 0.65 0.45 Protein Meal 0.772 2.53 1.43 1.02 0.93 Carbohydrate Meal 0.698 2.62 1.99 1.83 1.82 -\ Mean 03 2.97 1.52 1.12 0.71 Mea n Mb 2.37 1.23 0.84 0.69 \ aMean of Control, Fat and Carbohydrate diets. bMean of Fat and Protein meals. \. Etandard errors of individual treatment means at one time are ‘““relevant for comparisons or reliability. Etandard error of difference of two treatments at one time is = 520 (mM). §tandard error of difference of two times for one treatment " :5 0.200 (mM). 16h Table 5. Bonferroni t for test of significance of postexercise blood lactate concentration. CH-M is tested for inter- action (between 5 and 40 minutes) against C and F-M. Total (40 minute) response to CH-M is tested a ainst total response to F-M; and the postabsorptive 7P) trials (C, F-D, CH-D) are tested against the absorp- tive (A) trials (F—M and P-M) at 5 minutes postexer- cise. There are four contrasts (m = 4). Test Contrasts TB Interaction CH-M vs C at 5 a 40 min a5.171 Interaction CH-M vs F-M at 5 8 40 min a3.401 Total CH vs Total F CH-M vs F-M at all times a3.702 M vs 0 F-M, P-M vs C, F-D, CH-D 1.772 at 5 min aSignificant at 5% level 1Tabular T B = 2.66 at 5% level 2Tabular T = 2.74 at 5% level 8 165 the rate of return for the post-exercise blood lactate differ from the other treatments. 166 Discussion Shortly after ingestion of the carbohydrate meal there is a significant increase in the blood lactate during rest compared to control. Although blood glucose was not measured in the present study, Capro, et al (1981) found that plasma glucose and insulin were elevated for approximately four hours following standard meal, and that plasma FFA were depressed for approximately 5 hours. Similar responses to ingestion of 100 9 glucose were found for blood glucose, insulin, and FFA by Ravussin, et al (1979) and Luyckx, et a1 (1978). I Owen, et a1 (1980) found that a typical American breakfast elevated blood glucose, lactate, and pyruvate for about 2 hours, while tri- glycerides were still elevated at 3 hours. They also found that FFA, glycerol and ketone bodies were depressed for about 3 hours following the breakfast. The blood lactate following the ingestion of the fat and protein meal was not studied except in a preliminary study in one subject, where no effect was found c6mpared to control. However, one would expect a decrease in blood glucose and lactate and an increase in FFA (Seyffert, et al, 1967) if any change occurs, since fat is already the major energy substrate used in the postabsorptive state during rest. It is controversial whether the oxygen tension in muscle tissue is the primary determinant of lactate production during exercise (Graham, 1978); but Bylund-Fellenius, et a1 (1981) have recently 167 presented evidence in support of this concept. However, the individual variation in lactate production is also determined by muscle respira- tory capacity and fiber composition (Ivy, et al, 1980), which in turn is modified by training (Johnson, 1969).. Jacobs (1981) has shown that the level of muscle glycogen affects lactate production during exercise. Thus, at low levels of muscle glycogen, glycogenolysis decreased drastically, but above about 40 mM/kg there is no effect. It has been shown in rats (Stankiewicz- Choroszucha and Gorski, 1978) that when muscle glycogen is not available, muscle triglycerides become the major source of energy. They also reported that the level of blood FFA did not affect intramuscular utilization of triglycerides, but blood FFA level did affect the rate of glycogen utilization. In agreement with these findings, Maughan, et a1 (1978, 1981) found that a high carbohydrate diet (after glycogen depleting exercise) elevated plasma lactate during and following exercise compared to control, whereas low carbohydrate diet increased plasma FFA under these conditions. These dietary effects were seen both after low and high intensity work. Bonen, et a1 (1981) also found that a high carbohydrate diet increased blood lactate during high intensity work. Both these authors used a protocol designed to deplete muscle glycogen, and under such conditions, it is Clear that diet has an effect upon blood lactate and substrate utilization. Costill, et al (1977) found that artificially elevating FFA (with heparin) following a fat meal increased utilization of fat as a substrate during high intensity work (70% of maximally oxygen consump- tion) compared to preexercise ingestion of 75 9 glucose. Consequently, 169 the utilization of muscle glycogen was decreased 40% compared to control. They also found that ingestion of glucose increased glycogen utilization 17% (partly at the expense of blood carbohydrate). Bergstrom, et al (1969), however, found that decreasing arterial FFA by nicotinic acid did affect substrate utilization, only at low intensity exercise (below about 65% of maximal oxygen consumption). In the present study, our diets and exercise were designed not to have a significant effect upon muscle glycogen stores, because there was sufficient carbohydrate present in the high fat diet and the exercise was of relatively short duration. In the case of the carbo- hydrate meal, there clearly was a significant interaction (Table 5), which means that the carbohydrate meal interferes with the normal post-exercise recovery of blood lactate. This is not surprising, in view of the highly significant response in blood lactate to the carbohydrate meal at rest. There are great intra-individual differences in blood lactate: one subject (more fit, as indicated by his maximal oxygen consumption of 66 ml/min/kg compared to about 50 for the other subjects) had very little lactate response to exercise. Following the carbohydrate meal lactate response was decreased at five minutes following exercise, but then the blood lactate actually increased to that expected following a carbohydrate meal at rest (1.5 mM). Apparently, either the liver does not produce lactate during exercise, or it is metabolized by the exercising muscle (Poortmans, 1978). These results do not support the hypothesis that diet affects the blood lactate concentration during high,intensity exercise, although a carbohydrate meal clearly affects the rate of decrease in blood 170 lactate during the recovery period. CHAPTER 6 CONCLUSIONS 171 172 CONCLUSIONS We developed one hundred regression equations between HR and OXC from 10 exercise test in each of 10 subjects. Several aspects of the regression equation between HR and OXC were investigated based on these equations. Inhomogeneity of the regression lines was found both within and between the subjects. Most (about 70%) of the variability is between subject variability as evaluated by the repeatability R1 and R is only slightly decreased by using more homogenous subjects. It is not valid to use the regression equation between HR and OXC measured during exercise to predict recovery OXC. This can lead to as much as 300% overestimation of OXC. The reason for this was found to be a lag in the HR recovery relative to the OXC recovery, which occurred during the first 3 min of the recovery period after exercise at 80% of the maximal OXC. This lag in the HR recovery is presumably caused by a loss of vascular volume, which causes a decrease in stroke volume and a compensatory increase in HR. Duration of exercise rather than the intensity of exercise was found to be primarily responsible for this lag in recovery HR. Repeated exercise was found to be one factor that could cause the regression line to Change with respect to slope and y-intercept. Meal feeding compared to the postabsorptive state and a high fat compared to a high carbohydrate diet did not alter the linear regres- sion equation between the HR and OXC. 173 There is a need to confirm and expand the present finding in groups of different physical training, which will also allow for comparing the effect of physical training on the linear regression equation between HR and OXC. Furthermore the effects of coffee, smoking and mental stress (such as anxiety) on the regression equation between HR and OXC need to be studied. The effects of a high fat, a high protein and a high carbohydrate meal (700 kcal) on dietary induced thermogenesis were studied at rest. Each meal differed in its thermogenic response as measured by OXC, both with respect to the maximal response and its duration. The maximal increases in OXC was 8.9%, 33.0% and 27.4% for the fat, (protein and carbohydrate meals respectively. There was also an increase in blood lactate (about 3 mM) and respiratory quotient following the carbohydrate meal, which indicates a shift in the metabolism. Only during the carbohydrate meal was the increase in OXC positively correlated with the HR, giving indirect evidence that the regulatory mechanism of DIT for the 3 meals may be different. There was no thermogenic responSe during exercise under our experimental procedures. There is a need for a §tudy of the regulatory mechanisms behind the thermogenic response to the different meals, as the results indi- cate that they are different. If the thermogenic response to a carbo- hydrate is regulated differently, it can resolve the controversy about the thermogenic response to the energy substrates and may help explain why some people develop obesity. There is also a need to study the effects of meal size, eating time and composition on habitual food intake on the thermogenic response to fat, protein and carbohydrate 171- meals. Furthermore, it may be of interest to study the effect of smoking on DIT since smoking cessation can lead to increased body weight. A carbohydrate meal was shown to significantly increase blood lactate concentration compared to control; and when the meal preceeded exercise it resulted in elevated blood lactate levels during recovery (2mM). However, there was no effect of either meals or diets high in fat or carbohydrate on the substrate utilization or blood lac- tate concentration during exercise at 80% of maximal OXC. 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APPENDICES 197 Appendix A Time duration of expired air collection (sec) R.Q. 902 = Oxygen consumption (ml/min/kg) Respiratory Quotient HR = Heart rate Resting = Collection of expired air samples in the resting state prior to exercise Exercise = Collection of expired air during the incremental exercise test ' Recovery = Collection of expired air during recovery following the exercise test 198 - : $=Slevt22253§§§§§§§§§§2 agaaas j j as: sagasssessassa 7 363 eqeefletefieeeezeeeet 532993 2 eee wetweeeeeeefifiz 5 fl ""“ 2222883§88888388== 8“""' a g “"” 2222228 32838: m fi 2:! 3§2k222888888888828 828222 fl 2:: 3322£2 $888882 6 a 666 6666666666666666666 666666 - ' 666 66666666666666 5 5 g B 2&3 3558888888888888888 3:53: . é §§§I§§§§§§33333333 2=d ==8§E§§§§§§£ 323882 Mt ”II. as =ttszs§§§§§§§§ 3“ szzzsnzaaaaaaanxsa 2'643‘ ONO KHNONO—NI‘DHNNO I I " 22222228fi28333 iflLlil 322228333888£88388“ 888382 ......................... . 01 0000000000000000000 000000 8Q 283338 3838883 uuuuuuuuuuuuuu 666 00666660606000 :3. 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