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A coding scheme is presented for classifying physical activity by rate of energy expenditure, i.e., by intensity. Energy cost was established by a review of published and unpublished data. This coding scheme employs five digits that classify activity by purpose (i.e., sports, occupation, self-care), the specific type of activity, and its intensity as the ratio of work metabolic rate to resting metabolic rate (METs). Energy expenditure in kilocalories or kilocalories per kilogram body weight can be estimated for all activities, specific activities, or activity types. General use of this coding system would enhance the comparability of results across studies using self reports of physical activity.

The purpose of this study was to determine how many days subjects should be monitored to provide an estimate of habitual physical activity in employed men engaged in a wide range of occupations. Caloric intake, movement recorders (accelerometers and pedometers), and heart rate were the measurements studied in 30 subjects who were monitored during their waking hours for 7 continuous days. A repeated measures ANOVA showed no significant difference between days (P > 0.05) for any of the measures when only weekdays were compared. However, when weekend days were included a majority of the measures showed a significant F-ratio (P < 0.05). An estimate was made of the number of days required to measure a 7-d period with less than 5% error. The average for all the different measures was 4.9 d. It appears that at least 5 or 6 d are needed to minimize the intra-individual variance a reasonable degree. Weekdays as well as weekend days need to be included.

The history of exercise science reveals that at least three scientists received the Nobel prize for investigations in exercise physiology. The work of these men and their contemporaries was concerned with physiological mechanisms and work performance, not directly with health. Hippocrates and other physicians and philosophers of the ancient world believed that regular physical activity contributed to health and longevity. However, it was only during the last 30-40 years that the focus of exercise research shifted to a study of the impact of physical activity on health and disease. The reason for this change in research emphasis is due to the fact that a) chronic disease is associated with life-styles, b) people are less active in the Western world, c) prevention is perhaps the ultimate answer to the maintenance of health, and d) chronic disease frequently begins in childhood. A summary of our knowledge concerning the effects of exercise is presented. Because former college athletes have engaged in strenous sports training in their youth, they are of particular interest in this regard. Results of many investigations indicate that former college athletes live about as long as their classmates, and die at about the same rate from heart disease. Former athletes come from larger families, gain less weight after college up to the age of 55 years, are more active in life, and are more likely to be smokers and/or drinkers than their former college classmates., (Copyright © 1992 Wiley-Liss, Inc., A Wiley Company.)

This is a report of our experience using the Uniq Heart Watch for recording the heart rate in epidemiologic settings. Relatively few heart rates are missed during occupational and leisure activities. However the mean daily heart rate among subjects is somewhat variable so that several week days and Saturday and Sunday should be monitored to obtain a representative daily average.

A longitudinal study was conducted on 398 athletes and 369 nonathletes who were born before 1920 and attended Michigan State University. The subjects were compared to determine if intercollegiate athletic competition accounts for significant variation in longevity when considered with somatotype. Because some of the subjects were still alive at the time of the study, the BMDP Statistical Software was used to do a survival analysis with covariates. Preliminary comparisons considered the differences in somatotype between athletes and nonathletes. Two sample t-tests indicated that athletes were more mesomorphic and less ectomorphic (p less than .05) than nonathletes. When comparing the relationship between somatotype and longevity, the pooled data of athletes and nonathletes indicated that endomorphs were shorter lived than the other three comparison groups. When only the athletes were considered, similar results were found. However, the nonathlete group exhibited differences only between the mesomorphic and endomorphic groups. The endomorphs were shorter lived. Longevity was examined by using the Cox proportional hazards regression method with somatotype and athlete/nonathlete status as covariates. Somatotype, by itself, was found to be significantly related to longevity, (p less than .001). Athletic status was not significantly related to longevity, either by itself or when entered into the model with somatotype.

One thousand and fifty-eight men walked on a motor-driven treadmill at 3 miles/hour with the grade increasing 3% at 3-min intervals. (The 30 oldest men walked at 2 miles/hour.) Ventilation, Vo2, and Vco2 were recorded at each treadmill grade. During exercise Vo2 (in ml/min/kg of body wt) is significantly higher in younger compared with older boys. Vo2 increases slightly from age 20 though 59 years at any given work load. The respiratory exchange ratio (Vco2/Vo2) increases throughout the age range, particularly at the higher work loads. Ventilation (in 1/min/kg of body wt) decreases from age 10 to 20 years and increases thereafter, as does the ventilatory equivalent. The increased ventilation in young boys is characterized by an increase in respiration rate, whereas in older men it is accomplished through an increase in tidal volume.

A modification of the Harvard Step Test was administered to approximately 4700 males and females, age 10-69 in Tecumseh, Michigan. Heart rate response to this standardized exercise test is an estimate of capacity for muscular work. A blood sample was drawn 1 h after a glucose challenge on the same day the exercise test was given. Four skinfolds were measured as an index of body fatnes. It was the purpose of this analysis to study the relationship of glucose tolerance to heart rate response to exercise. All analyses were done in age and sex-specific sub-groups. The correlation coefficients are low but positive in all but one sub-group and half of the coefficients are statistically significant. This suggests that poor fitness for work (high heart rate in response to exercise) was related, albeit weakly, to lowered glucose tolerance. However, there is a positive relationship between body fatness on the one hand and serum glucose and heart rate response to exercise on the other. When the effect of body fatness was eliminated the relationship of heart rate response to exercise ahd glucose tolerance remained about the same; low but statistically significant in some age groups.

More than 30 different methods have been used to assess physical activity. These methods can be grouped into seven major categories: calorimetry, job classification, survey procedures, physiological markers, behavioral observation, mechanical and electronic monitors, and dietary measures. No single instrument fulfills the criteria of being valid, reliable, and practical while not affecting behavior. The instruments that are very precise tend to be impractical on a population basis. Surveys are the most practical approach in large-scale studies, although little is known about their reliability and validity. Studies employing objective monitoring through heart rate, movement sensors, and doubly labeled water procedures appear promising, but are still experimental and costly. Despite the difficulty of measurement, relatively strong association has been found between physical activity and health, suggesting that, with improvements in assessment techniques, even stronger associations should be seen.

This well-designed study does not prove that athletic participation affects longevity and morbidity. Perhaps the same study of highly trained athletes would produce different results.

To improve health and fitness effectively through physical activity or exercise, we need to understand how this comes about. For many of these changes, the stimulus has been grossly defined in terms of type, intensity, duration, and frequency of exercise, but for others a dose-response relationship has not been determined. Physical activity that appears to provide the most diverse health benefits consists of dynamic, rhythmical contractions of large muscles that transport the body over distance or against gravity at a moderate intensity relative to capacity for extended periods of time during which 200 to 400 kilocalories (or 4 kilocalories per kilogram of body weight) are expended. For optimal health benefits, such activity should be performed daily or at least every other day and should be supplemented with some heavy resistance and flexibility exercises. The greatest benefits are achieved when the least active individuals become moderately active; much less benefit is apparent when the already active individual becomes extremely active. Overexertion or inappropriate exercise can produce significant health risks. Research is needed to characterize better the health-promoting features of physical activity and exercise.

A small portable accelerometer was developed to estimate the energy expenditure of daily activities. The accelerometer is reported to be an improvement over movement counters currently on the market. The oxygen requirement of 14 different activities was measured in 21 subjects while each wore the accelerometer on the waist. A movement counter (mercury switch), which is available commercially, was also worn on the waist and another was worn on the left wrist. The reproducibility of the accelerometer readings was high (4 subjects, 14 activities; r = 0.94) and was superior to either the waist movement counter (r = 0.63) or the wrist movement counter (r = 0.74). In estimating oxygen requirement (VO2) the standard error of estimate, based on 21 subjects and 14 activities, was 6.6 ml X min-1 X kg-1 for the accelerometer. This was also better (smaller) than for the waist movement counter (9.2 ml X min-1 X kg-1) or for the wrist movement counter (7.9 ml X min-1 X kg-1).

This study examined the accuracy of a new device (Caltrac) in estimating energy expenditure via acceleration measurements. Energy expenditure of 20 high school students during basketball class activity (average length = 37 min) was estimated using the Caltrac, heart rate recording, and video analysis. Heart rate recording and video analysis estimates of energy expenditure were determined from heart rate, caloric expenditure curves, and an activity rating scale, respectively. The following estimates of caloric expenditure (M +/- SD) were found: heart rate recording = 196 +/- 73 greater than Caltrac = 163 +/- 49 greater than film analysis = 123 +/- 30 kcal (p less than .05). Laboratory simulations of the basketball activity revealed that the Caltrac energy expenditure was not significantly different from the actual energy expenditure (p greater than .05). The heart rate recording and video analysis estimates of energy expenditure were significantly (p less than .05) higher and lower, respectively, than the actual energy expenditure. The Caltrac is a lightweight, low-cost device that provides a relatively accurate estimate of energy expenditure in free-ranging activities, such as basketball.

The purpose of the investigation was to determine the validity of a portable vertical accelerometer and a Large-Scale Integrated Motor Activity Monitor (LSI) for estimating energy expenditure in riding a bicycle at various velocities. Instrument placement was either at the knee or ankle. Energy consumption, i.e. oxygen consumption (VO2) was determined during bicycle rides after steady state metabolism was reached. Standard errors of estimate were used to express the accuracy of estimating VO2 from accelerometer or LSI recordings. The reliability of the vertical accelerometer was found to be satisfactory. The vertical accelerometer was also effective for estimating VO2 in bicycling (standard errors of estimate = 3.3 to 4.4 ml.kg-1.min-1). The accuracy of the LSI was not as good; the standard errors of estimate being = 5.9 to 8.5 ml.kg-1.min-1.

Maximal oxygen uptake (Vo2max) was measured or estimated in 597 males, aged 16-69. Smoking and drinking habits were also determined in this population. After the influences of age, weight, skinfold thickness, and drinking habits were removed, smokers clearly had decreased Vo2max. Similarly, when the relationships were corrected for age, weight, skinfolds and smoking habits, the heaviest drinkers and the non-drinkers had the lowest, Vo2max and the moderate drinkers had the highest Vo2max, at least in the younger age groups. The same results were found when only those subjects in whom Vo2max was measured (essentially subjects under age 40) were included. Levels of habitual physical activity could not account for these differences.

Age 10-69, 793 males and 80 females were tested on the treadmill as they walked at 4.83 km per hour (3.27 km per hour in subjects 60 years and older). Every three minutes, the grade was increased 3%. Maximal oxygen uptake (VO2max.) and related measurements were recorded during the third minute at each grade. Subjects age 10-39 exercised to exhaustion and VO2max. was measured. In subjects age 40-69, VO2max. was estimated from sub-maximal VO2 and heart rate. The sum of four skinfolds, serum uric acid (SUA) and one-hour glucose tolerance were also measured on these subjects. Body fatness was positively correlated with SUA and blood glucose and negatively correlated with VO2max. Age was negatively correlated with VO2max. and positively correlated with blood glucose. After removing the effects of age, weight and fatness, the correlation of VO2max. and SUA was low. Similarly, there was little or no correlation between VO2max. and blood glucose after the effects of age, weight and fatness were removed.

The data being reported are part of an epidemiologic study of health and disease in an entire community, Tecumseh, Michigan. Approximately 1,300 males age 16-65 were classified into three groups on the basis of their habitual leisure and occupational physical activity. A blood sample was drawn one hour after a glucose challenge and analyzed for glucose concentration. A measure of body fatness (sun of four skinfolds) was also available on the men. Glucose concentration of the three physical activity groups was compared by analyses of variance within narrow age group. There was no significant relationship between glucose tolerance and habitual physical activity. There was a slight, but in some age groups significant, relationship between glucose tolerance and body fatness. The population was then divided within each age group into subgroups (thirds) by sum of skinfolds. The analysis was repeated in each age-fatness group. Glucose tolerance was better in the active men but only among the leanest subgroup of subjects.

Serum uric acid was determined in 2298 males and 2237 females, age 10-64. Body fatness (sum of four skinfolds) and heart rate response to a modified Harvard Step Test were also measured in these subjects. Age and sex specific correlation coefficients between SUA and heart rate response to the standard exercise were low (about 0.15 on the average) but more than half were statistically significant. SUA was more closely related to body fatness than to heart rate response to exercise. Removing the effects of body fatness from the SUA - heart rate response correlations decreased these correlations so that only about one per cent of the variation in SUA among people is associated with one's physical fitness as reflected in heart rate response to exercise.

Oxygen uptake (VO2) was measured in males age 10-59 while they walked at 3 mph at various grades on a motor-driven treadmill. The number of subjects in each age group was as follows: age 10-11, N = 24; age 12-13, N = 46; age 14-15, N = 55; age 16-17, N = 53; age 18-19, N = 30; age 20-24, N = 56; age 25-29, N = 35; age 30-34, N = 32; age 35-39, N = 99; age 40-44, N = 106; age 45-49, N = 78; age 50-54, N = 42; and age 55-59, N = 11. Subjects walked at 3 mph at 0% grade for 3 min; thereafter, the treadmill was raised 3% every third minute with speed maintained. Oxygen uptake was measured continuously but only the values during the last minute at each grade were used in the present analysis. The subjects were in a "steady state," insofar as VO2 was concerned, by the second minute. These data were used to validate formulas for estimating VO2 in horizontal and grade walking published in Guidelines for Graded Exercise Testing and Exercise Prescription (1). The formulas are accurate for estimating the mean oxygen requirement in grade walking from 6-18% in adult males. In horizontal walking and walking at 3% grade, the formulas underestimate VO2 in all age groups. In boys under age 18, the formulas underestimate the energy requirement in walking at all grade levels.