Differences between observed and predicted energy costs at rest and during exercise in three subsistence-level populations.код для вставкиСкачать
AMERICAN JOURNAL OF PHYSICAL ANTHROPOLOGY 99:537-545 (1996) Differences Between Observed and Predicted Energy Costs at Rest and During Exercise in Three Subsistence-Level Populations PETER T. KATZMARZYK, WILLIAM R. LEONARD, MERRILL A. STEPHEN, PETER R. BERTI, AND ALLEN G.P. ROSS Department of Physical Education and Exercise Science, Michigan State University, East Lansing, Michigan 48824-1049 (PZK.); Department of Human Biology and Nutritional Sciences, University of Guelph, Guelph, Ontario Canada N l G 2Wl (W.R.L., M.A.S., P.R.B., A.G.PR.) KEY WORDS Energy expenditure, Metabolic adaptation, Factorial method, Temperature stress, Siberia, Ecuador ABSTRACT Estimates of daily energy expenditure are important for many areas of research in human ecology and adaptability. The most common technique for estimating human energy expenditure under field conditions, the factorial method, generally relies on activity-specific energy costs derived from published sources, based largely on North American and European subjects. There is concern that such data may not be appropriate for nonWestern populations because of differences in metabolic costs. The present study addresses this concern by comparing measured vs. predicted energy costs at rest and during sub-maximal exercise in 83 subjects (52 males, 31 females) from three subsistence-level populations (Siberian herders and highland and coastal Ecuadorian farmers). Energy costs at rest (i.e., lying, sitting and standing) and while performing a standard stepping exercise did not significantly differ among the three groups. However, resting energy costs were significantly elevated over predicted levels (+16% in men, +ll% in women), whereas exercising costs were comparable to predicted values (-6% in men, +3% in women). Elevations in resting energy needs appear to reflect responses to thermal stress. These results indicate that temperature adjustments of resting energy costs are critical for accurately predicting daily energy needs among traditionally living populations. o 1996 Wiley-Liss, Inc. Accurate estimates of energy expenditure are critical to research in human ecology and adaptability (Ulijaszek, 1992). Quantifications of daily energy requirements and energy balance help to provide insights into physiological and behavioral responses to fluctuations in food availability that are so common among traditional, subsistencelevel populations (de Garine and Harrison, 1988; Ferro-Luzzi, 1990; Huss-Ashmore, 1988;Leonard, 1992).Additionally energetic data are useful in understanding the adaptive significance of human subsistence strategies in different ecosystems (Dufour, 1983; Little et al., 1988;Montgomery and Johnson, 1976; Smith, 1981; Thomas, 1973). 0 1996 WILEY-LISS, INC. There are several methods currently available for assessing total daily energy expenditure (TDEE) in free-living human populations. The most widely used technique remains the factorial method of recall and observation. This approach involves having either the subject or an observer record the amount oftime that the subject spends in various activities throughout the day. The energetic costs for these activities are then ob- Received May 2, 1995;accepted July 14, 1995 Address reprint requests to William R. Leonard, Department of Human Biology and Nutritional Sciences, 116JT Powell Building, University of Guelph, Guelph, Ontario Canada N1G 2W1 538 P.T.KATZMARZYK ET AL. tained by indirect calorimetry, or, more often, from published sources (e.g., Passmore and Durnin, 1955; Durnin and Passmore, 1967; James and Schofield, 1990).The most recent WHO recommendations on energy and protein requirements (FAO/WHO/UNU, 1985) advocate the use of the factorial method for estimating adult energy demands in populations throughout the world; however, there remain concerns regarding the accuracy of this approach, in part because it is unclear whether activity-specific energy costs derived on one population can be effectively applied to a different population (Durnin, 1990). Several recent studies have indicated that the factorial method may underestimate daily energy needs. Both Roberts and colleagues (1991) and Haggarty et al. (1994) found that the factorial method underestimated energy expenditures relative to values obtained using the doubly labelled water technique. Leonard et al. (1995a) demonstrated a similar pattern among farmers of highland and coastal Ecuador; for this sample, factorial estimates based on the WHO methodology were 16%lower than those obtained from daily heart-rate (HR) monitoring. Yet, while these and other studies have questioned the accuracy of the factorial method, none have specificallyidentified the factors that contribute to the inaccuracy. The purpose of this study is to examine the potential sources of error associated with the factorial method, by comparing measured vs. predicted energy costs at rest and during sub-maximal exercise for adults from three subsistence-level groups (Siberian herders and highland and coastal Ecuadorian farmers). We expect that if the errors in the factorial method are due to differences in energetic demands among populations, that the measured energy costs for the resting andlor active conditions will be significantly different from those derived from the reference values, based largely on subjects from Europe and North America. METHODS Subjects Anthropometric and energy expenditure data were collected from herding and fishing populations of central Siberia and from agricultural populations of highland and coastal Ecuador. In Siberia, data were collected in the context of a larger, ongoing research project examining the ecology, health and genetic structure of indigenous Siberian groups (see Leonard et al., 1992).The Siberian sample includes 44 individuals (30 males, 14 females) of the Evenki and Keto populations randomly selected from three villages of the Stony Tunguska region (Surinda,Poligus and Sulamai). Subjects rangedin age from 14to 4lyears (see Katzmarzyket al., 1994,for additional details of the sample). Physiological and anthropometric data were collected in the village health posts (for individuals living in the central communities) or in the bush (forthose living in the herding parties). The Ecuadorian data were collected as part of a research program examining the biosocial determinants of undernutrition and growth stunting among rural farmers (see Leonard et al., 1995b). The highland Ecuadorian sample was derived from two communities of the Salcedo county (Cotopaxi Province), and includes 29 subjects (17 males, 12 females) between 16 and 63 years of age. Data from coastal Ecuador were collected from a single village in the Jipijapa county (Manabi Province) on a sample of 10 subjects (5 males, 5 females) who ranged in age from 23 to 71 years (see Leonard et al., 1995a, for additional details on the Ecuadorian samples). In each region, measurements were taken in a field laboratory that was set up in one the community’s households. Anthropometrics Anthropometrics for each subject were obtained following the methods outlined in Lohman et al. (1988). Stature was measured to the nearest millimeter using a portable field anthropometer (Creative Health Products, Plymouth, MI), and body mass was assessed t o the nearest 0.5 kg using a standing spring scale (Seca Corp., Columbia, MD). Mid-arm circumference was measured to the nearest millimeter using insertion tape measures (Ross Labs, Columbus, OH). Skinfold measurements (mm) at the triceps and subscapular sites were measured to the nearest 0.5 mm with Lange calipers (Cambridge Scientific, Cambridge, MD). Upper-arm muscle area (UMA, cm2)was derived from the triceps skinfold and mid-arm circumference measurements. VARIATION IN HUMAN ENERGY DEMANDS Energy expenditure For each subject, energy expenditure (EE; kJ/min) and heart rate (HR) were measured for three resting positions (lying, sitting and standing) and two t o four exercise levels. The exercise data were collected while the subject performed a standard step test (the Canadian Aerobic Fitness Test [CAFT]; Jett6 et al., 1976;Fitness Canada, 1986). For both the resting and exercising conditions, HR was measured continuously via a portable HR monitor (Polar Vantage XL HR monitor; Polar Electro, Stamford, CT). Energy expenditure was measured using the Douglas bag method of indirect calorimetry (Douglas, 1911). Expired air samples were collected for 3 minutes under resting conditions, and during the final minute of each 3 minute exercise bout. These samples were analyzed for oxygen ( 0 2 ) content using a portable 0, monitor (Model 74222; Biotek Instruments Inc., Winoosk, VT) which had been calibrated with external air, and a tank containing 15% 0,. The volume of expired air was then determined with a dry gas volume meter (Model 802; American Meter Go., Fullerton, CA), and corrected to standard temperature and pressure, dry (STPD). Energy expenditure for each of the resting and exercising conditions was then calculated as: EE = 20.6 . (VE/100)(20.93- FeOd where VE = volume of expired air (Umin) and FeOz = fraction of 0, in expired air (%). Basal metabolic rate (BMR;kJ/min) was estimated from body mass using the age and sex-specific predictive equations of the FAO/ WHOAJNU (1985). Energy costs of the step test were used to calculate the net mechanical efficiency (NME) of stepping for each subject. The mechanical efficiency reflects the amount of work performed as a percentage of the metabolic costs associated with the task. For the CAFT step test, NME was calculated as: NME(%) = 100 where Wt Work load (joules/min) Energy cost (jouleshin) Wt . Ht ' 9.8 ' N (EE - BMR) = 100. = body mass (kg), Ht = height of 539 stairs (m), N = number of ascentdmin, EE = energy expenditure of exercise level (joules/min) and BMR = basal metabolic rate (jouledmin). Analytical methods Predicted energy costs of the three resting conditions (lying, sitting and standing) were estimated from data compiled by James and Schofield (1990).These costs were calculated as 1.2 x BMR for lying and sitting, and 1.4 X BMR for standing (James and Schofield, 1990).For the exercise levels, predicted energy costs were derived from values presented by Fitness Canada (1986). Paired t-tests were used to assess differences between measured and predicted energy costs in the resting and exercising conditions. Differences among the three samples were evaluated using one-way analyses of variance (ANOVA) with SPSSpc (SPSS, 1990). RESULTS Mean age and anthropometric characteristics of the three samples are presented in Table 1. Siberian men and women are significantly younger than their Ecuadorian counterparts. Body size and composition, however, are similar among the three populations, with men and women from all of the groups being short relative to US norms (55th centile; Frisancho, 1990).The only dimension that differs among the groups is UMA, with the Siberian women being significantly less muscular than their coastal Ecuadorian counterparts. Table 2 presents basal and resting energy costs for men and women of the three samples. One-way ANOVAs indicate that there are no significant differences in EE among the three regional groups for any of the resting conditions. However, average expenditure levels for the three resting conditions are 16% higher than predicted from the James and Schofield (1990) standards for males (6.80 vs. 5.88 kJ/min; t = 5.58; P < 0.001) and 11%higher for females (5.24 vs. 4.74 kJ/min; t = 3.17; P = 0.004). As shown in Figure 1, expenditure levels for males are 15%greater in Siberians, and are elevated by 16% and 26% in highland and coastal Ecuadoreans, respectively. For women, the differences are more modest, but are still statistically significant. Siberian 540 P.T.KATZMARZYK ET AL. TABLE 1. Anthropometric characteristics of male and female samples from the three subsistence-leuel populations n Age (yr) Body mass (kg) Stature (cm) Triceps (mm) Subscapular (mm) UMA (cm2) Males Siberia Highland Ecuador Coastal Ecuador 30 17 5 26 ? 6a,b 37 t 13" 49 C l g b 61.4 t 7.7 60.6 t 6.6 55.6 5 7.4 161.3 t 5.3 160.0 t 6.6 157.6 i 5.5 6.7 5 3.1 6.8 t 2.3 10.1 ? 6.6 9.0 t 3.4 10.2 t 4.1 13.8 t 8.8 51.2 2 8.6 47.6 t 6.2 53.3 f 15.9 Females Siberia Highland Ecuador Coastal Ecuador 14 12 5 23 2 6c,d 39 2 13' 34 2 16d 50.6 4.7 55.6 t 11.0 47.8? 3.4 149.8 t 4.1 146.9 t 5.8 145.8 t 2.1 15.4 _f 4.5 16.2 t 4.7 18.0? 6.1 14.6 t 4.4 19.0 t 7.7 20.6 t 3.6 32.0 -t 6.0' 39.3 t 8.6 39.5 t 5.6' Values expressed as mean 2 SD. "Shared letters denote significant _f (P< 0.05) differences between groups using Tukey's HSD test TABLE 2. Resting physiologic characteristics of male and female subiects from the three subsistence-level populations BMR' (kJ/min) Lying EE (kJ/mini Sitting EE (kJ/mini Standing EE (kJ/mini Males Siberia Highland Ecuador Coastal Ecuador F-ratio 4.67 t .31 4.61 t .43 4.44 t .26 0.89 6.17 t 1.39 6.66 f 1.33 6.92 t 0.83 0.08 6.67 ? 1.86 6.74 2 1.54 7.42 t 0.65 0.39 7.09 i 1.85 6.84 t 1.00 7.00 t 1.46 0.16 Females Siberia Highland Ecuador Coastal Ecuador F-ratio 3.75 t .20 3.84 t .41 3.57 t .13 1.49 4.91 2 1.32 5.11 t 1.03 5.40 t 1.06 0.33 4.97 t 1.40 5.60 t 0.78 6.22 t 0.55 2.70 5.35 ? 1.45 4.94 t 0.85 5.64 f 0.66 0.80 Values expressed as mean i SD. ' Basal metabolic rate predicted from FAO/WHO/LTNU (1985)equations Percent Difference 40 T 30 20 DSiberia OHighland Ecuador 10 Coastal Ecuador 0 -1 0 -20 Rest Exercise Males Rest Exercise Females Fig. 1. Percent differences (%SE)between observed and expected energy costs a t rest and during exercise for males and females of three subsistence-level groups (Siberians and highland and coastal Ecuadoreans). Resting energy costs are significantly greater than predicted values for both men and women. Exercise costs are comparable to predicted levels for both sexes. 54 1 VARIATION IN HUMAN ENERGY DEMANDS TABLE 3. Exercising energy costs (kJ/min) for the first four levels ofthe Canadian Aerobic Fitness R s t (CAFT) Population n Males Siberia Highland Ecuador Coastal Ecuador F-ratio 1 3 5 Females Siberia Highland Ecuador Coastal Ecuador F rati o 13 11 5 ~ Level 1 kJImin n Level 2 kJImin 7 26.8 22.9 t 3.5 21.6 t 4.9 0.57 17 5 20.0 t 3.7 21.0 2 5.9 17.8 t 4.4 0.87 13 12 5 n 28.9 t 2.6 27.5 t 5.0 27.6 t 6.1 0.25 30 17 3 22.5 t 3.9 23.2 t 4.6 20.7 t 4.7 0.61 8 8 3 Level 3 kJImin 31.9 t 5.6 30.8 t 7.9 31.1 -t 7.6 0.15 26.3 t 5.5 31.8 ? 11.2 25.3 t 1.7 0.81 n 28 15 - Level 4 kJImin 36.5 t 6.1 35.7 % 6.1 - 0.20 1 1 - 31.9 29.1 - Stepping rates for levels 1 through 4 are 11, 14, 17 and 19 ascentdmin. women expend 6%more energy a t rest than predicted, as compared to +8% in highland Ecuadoreans and +31% in coastal Ecuadoreans. Table 3 presents energy costs for the first four levels of the CAFT. Variation in sample sizes across the four levels reflects the fact that not all subjects started and finished at the same points. EE does not significantly vary across the three samples for any exercise level. Moreover, expenditure levels are also comparable to those predicted based on data collected among Canadian samples. This point is demonstrated in Figure 2, which shows the mean measured energy costs at each stepping level for the three samples, along with the predicted costs, based on the reference data (Fitness Canada, 1986). Among men, measured energy costs for the exercise levels average 6%below predicted values (see Fig. l), whereas for women, the measured values differ by +3%. The NME of stepping is presented in Figure 3. Again, no significant differences are evident between the samples. For the male samples, NME averages 15.4%in the coastal Ecuadoreans, 15.9% in the Siberians, and 16.8% in the Ecuadorian highlanders. For women, average NMEs are 15.9% in the highland sample, 16.3%in the coastal group, and 16.0% in the Siberians. As shown in Table 4, the stepping efficiencies for all three groups are similar to those reported for most other populations, with the exception of Tamang men and women from Nepal, who have substantially higher efficiencies (22-27%). The greater efficiency of the Nepali subjects is thought to reflect adaptation to nutritional stress (Strickland and Ulijazsek, 1990) and/ or anemia (Panter-Brick et al., 1992). DISCUSSION The factorial method is currently the technique prescribed by the World Health Organization for assessing TDEE in free-living human populations (FAO/WHO/UNU, 1985; James and Schofield,1990). However, recent work has indicated that this method may consistently underestimate TDEE (Roberts et al., 1991; Haggarty et al., 1994; Leonard et al., 1995a). The findings of this study suggest that the inaccuracy in the factorial estimates arises from underestimation of energy costs a t rest. Our results demonstrate that measured energy costs for resting conditions (i.e., lying, sitting and standing) significantly differ from those predicted from current standards, whereas EE during low to moderate exercise does not. Resting EE values averaged 16%higher than predicted in males and 11%greater in females; exercising levels, on the other hand, deviated by only -6% in men and +3% in women. The energetic efficiency of the three groups for the step test was also comparable to that observed among Canadian and British populations, ranging from 15 to 17%. These results are surprising in that they suggest that differences in work efficiency (e.g., mechanical efficiency) are not a large source of error in estimating energy needs with the factorial approach. Rather, they imply that the sedentary component of daily expenditure is more important in contributing to the biases observed. Since a large pro- 542 P.T.KATZMARZYK ET AL. Energy Cost (kJ/min) 15 10 1 2 3 4 1 2 3 4 Level (CAFT) *Canada (Reference) -Siberia 0 Highland Ecuador +Coastal Ecuador Fig. 2. Sub-maximal energy expenditure for males and females of three subsistence-level groups (Siberians and highland and coastal Ecuadoreans) for four levels of a standard stepping exercise test. Reference values for Canadian subjects were derived from Fitness Canada (1986). Energy costs do not significantly differ among the three groups, and all are comparable to the Canadian reference values. Net Mechanical Efficiency (%) 22 20 Men 0 18 16 14 12 1 2 3 4 1 2 3 4 Level (CAFT) I -Siberia 0 Highland Ecuador -D Coastal Ecuador 1 Fig. 3. The net mechanical efficiency of stepping for the meals and females of the three subsistencelevel groups (Siberians and highland and coastal Ecuadoreans). 543 VARIATION IN HUMAN ENERGY DEMANDS TABLE 4. Comparison of net mechanical efficiency (NME) estimates for stepping in selected populations Population Body mass (kg) Stature (cm) NME (%) References Shephard et al. (1968) Strickland and Ulijaszek (1990) Strickland and Ulijaszek (1990) Young Canadian men British soldiers Gurkha soldiers - - 67.4 67.6 173.7 167.1 16.3 15.3 21.1 Nepal Tamang men (anemic) Tamang men (non-anemic) Tamang women (anemic) Tamang women (non-anemic) Rural women 51.3 52.0 47.1 48.4 43.6 160.0 158.0 150.0 151.0 148.1 26.6 22.0 23.4 22.6 16.9 Panter-Brick et al. (1992)' Panter-Brick et al. (1992) Panter-Brick et al. (1992) Panter-Brick et al. (1992) Malville (1991)' - 14.8 15.3 Shephard (1974) Shephard (1974) Eskimo men Eskimo women Highland Ecuador Men Women 60.6 55.6 160.0 146.9 16.8 15.9 This study This study Coastal Ecuador Men Women 55.6 47.8 157.6 145.8 15.4 16.3 This study This study Siberia Men Women 61.4 50.6 161.3 149.8 15.9 16.0 This study This studv 'Anemic group defined as having a hemoglobin concentration below 120.3 g L (men) and 109.4 g L (women) 2Rural sample includes Brahman, Chetri, Newar and Tamang women. portion of typical day is spent in sedentary activities (James and Schofield, 1990), only a small deviation from predicted energy requirements at rest (i.e., 0.5-1.0 kJ/min) is necessary to produce a large bias in daily energy requirements. The elevations in resting metabolic costs presented here are similar to those reported for other subsistence-level populations (see Katzmarzyk et al., 1994; Table 4),and likely reflect the influence of thermal stress. Unlike populations of the developed world, these traditionally living groups are exposed to temperatures that are outside of their thermoneutral range throughout the course of a normal day. For this reason, physiological measurements for the present samples were taken in typical dwellings so as to most closely approximate the actual energy demands in each environment. As shown in Table 5, the data indicate a significant interaction between resting energy costs and temperature at the time of measurement for both males and females. Deviations from predicted energy costs are smallest for temperatures ranging from 20-25°C (+7% in males, +3% in females), and are significantly greater for temperatures below 20°C TABLE 5. Variation in resting energy expenditure with temperature Temperature range' <2O0C 20-25°C >25T F-ratio n 27 15 10 Males %Difference2 16.0 i 18.5 7.3 1- 21.5a 30.1 ? 13.2a 4.20* n 19 6 6 Females %Difference 4.9 i- ll.gh 3.2 t 18.8' 37.1 i 11.2b,e 14.61** Variation among temperature groups is significant at: *P < 0.05; **P < 0.0001. Shared letters denote significant ( P < 0.05) differences between groups using Tukey's HSD test. 'The samples in each temperature category are composed as follows. Males, <20T = 10 Siberians, 17 Highland Ecuadoreans; 20-25°C = 15 Siberians; >25"C = 5 Siberians, 5 Coastal Ecuadoreans. Females, <20"C = 7 Siberians, 12 Highland Ecuadoreans; 20-25°C = 5 Siberians, 1 Coastal Ecuadorean, >25"C = 2 Siberians, 4 Coastal Ecuadoreans. 2Percent difference from predicted EE, based on James and Schofield (1990). (+16% in males, +5% in females) and above 25°C (+30%in males, +37% in females). It is possible, as well, that the higher resting energy costs among these three populations reflect longer term adaptations in basal energy requirements. Roberts' (1978) classic work, Climate and Human Variability, found a strong negative relationship between BMR and mean annual temperature, suggesting a genetic andor developmental component 544 P.T. KATZMARZYK ET AL. to BMR variation among humans. Additionally, metabolic studies on indigenous high latitude populations of Europe and the New World (e.g., Itoh, 1980; Rode and Shephard, 1995), and on high altitude populations of the Andes (e.g., Picon-Reategui, 1961; Mazess et al., 1969) have demonstrated significant elevations in BMR. Consequently, there is reason to expect th at BMRs in the Siberian and highland Ecuadorian samples of this study may be higher than those predicted by the WHO’S equations (FAO/WHO/LTNU, 1985, a s derived from Schofield, 1985). Unfortunately, this hypothesis cannot be directly tested here, since none of the metabolic data were collected under basal conditions. Our ongoing research in Siberia, however, is examining BMR levels among the Evenki herders to address this question. In light of the research cited above, it is surprising that the most recent WHO report on energy and protein requirements found insufficient evidence for recommending a temperature adjustment in determining daily energy needs (FAO/WHO/UNU, 1985). Earlier FAOMrHO recommendations (FAO, 1957)acknowledged the influence of climate on EE, and other recent models for predicting energy expenditure have also advocated use of a temperature adjustment for basal and resting metabolic needs (see Buskirk and Mendez, 1980; Leslie et al., 1984; Little et al., 1988). Results presented here strongly indicate that a temperature adjustment is necessary for accurately predicting energy expenditure with the factorial approach, especially among traditionally living populations, who are exposed to greater amounts of thermal stress. Without such correction, the current WHO protocol will tend to substantially underestimate energy demands and potentially minimize evidence of nutritional stress. ACKNOWLEDGMENTS We are indebted to the subjects who participated in this study. We also thank Katherine McCaston, James Stansbury, Ramon Rodriguez, and Nadia Blagitko for assistance with data collection. The Siberian portion of this research was conducted in collaboration with Drs. M.H. Crawford (Universityof Kan- sas) and R.I. Sukernik (Russian Academy of Sciences); the Ecuadorian component was a collaboration with Drs. K.M. DeWalt (University of Pittsburgh), J.E. Uquillas (World Bank), and el Fundacion para el Desarrollo Agropecuario (Quito, Ecuador). 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