Greater male variability in daily energy expenditure develops through puberty.

There is considerably greater variation in metabolic rates between men than between women, in terms of basal, activity and total (daily) energy expenditure (EE). One possible explanation is that EE is associated with male sexual characteristics (which are known to vary more than other traits) such as musculature and athletic capacity. Such traits might be predicted to be most prominent during periods of adolescence and young adulthood, when sexual behaviour develops and peaks. We tested this hypothesis on a large dataset by comparing the amount of male variation and female variation in total EE, activity EE and basal EE, at different life stages, along with several morphological traits: height, fat free mass and fat mass. Total EE, and to some degree also activity EE, exhibit considerable greater male variation (GMV) in young adults, and then a decreasing GMV in progressively older individuals. Arguably, basal EE, and also morphometrics, do not exhibit this pattern. These findings suggest that single male sexual characteristics may not exhibit peak GMV in young adulthood, however total and perhaps also activity EE, associated with many morphological and physiological traits combined, do exhibit GMV most prominently during the reproductive life stages.

Variability in energy expenditure is much greater in males than females.

In mammals, trait variation is often reported to be greater among males than females. However, to date, mainly only morphological traits have been studied. Energy expenditure represents the metabolic costs of multiple physical, physiological, and behavioral traits. Energy expenditure could exhibit particularly high greater male variation through a cumulative effect if those traits mostly exhibit greater male variation, or a lack of greater male variation if many of them do not. Sex differences in energy expenditure variation have been little explored. We analyzed a large database on energy expenditure in adult humans (1494 males and 3108 females) to investigate whether humans have evolved sex differences in the degree of interindividual variation in energy expenditure. We found that, even when statistically comparing males and females of the same age, height, and body composition, there is much more variation in total, activity, and basal energy expenditure among males. However, with aging, variation in total energy expenditure decreases, and because this happens more rapidly in males, the magnitude of greater male variation, though still large, is attenuated in older age groups. Considerably greater male variation in both total and activity energy expenditure could be explained by greater male variation in levels of daily activity. The considerably greater male variation in basal energy expenditure is remarkable and may be explained, at least in part, by greater male variation in the size of energy-demanding organs. If energy expenditure is a trait that is of indirect interest to females when choosing a sexual partner, this would suggest that energy expenditure is under sexual selection. However, we present a novel energetics model demonstrating that it is also possible that females have been under stabilizing selection pressure for an intermediate basal energy expenditure to maximize energy available for reproduction.

Total daily energy expenditure has declined over the past three decades due to declining basal expenditure, not reduced activity expenditure.

Obesity is caused by a prolonged positive energy balance1,2. Whether reduced energy expenditure stemming from reduced activity levels contributes is debated3,4. Here we show that in both sexes, total energy expenditure (TEE) adjusted for body composition and age declined since the late 1980s, while adjusted activity energy expenditure increased over time. We use the International Atomic Energy Agency Doubly Labelled Water database on energy expenditure of adults in the United States and Europe (n = 4,799) to explore patterns in total (TEE: n = 4,799), basal (BEE: n = 1,432) and physical activity energy expenditure (n = 1,432) over time. In males, adjusted BEE decreased significantly, but in females this did not reach significance. A larger dataset of basal metabolic rate (equivalent to BEE) measurements of 9,912 adults across 163 studies spanning 100 years replicates the decline in BEE in both sexes. We conclude that increasing obesity in the United States/Europe has probably not been fuelled by reduced physical activity leading to lowered TEE. We identify here a decline in adjusted BEE as a previously unrecognized factor.

Total energy expenditure is repeatable in adults but not associated with short-term changes in body composition.

Low total energy expenditure (TEE, MJ/d) has been a hypothesized risk factor for weight gain, but repeatability of TEE, a critical variable in longitudinal studies of energy balance, is understudied. We examine repeated doubly labeled water (DLW) measurements of TEE in 348 adults and 47 children from the IAEA DLW Database (mean ± SD time interval: 1.9 ± 2.9 y) to assess repeatability of TEE, and to examine if TEE adjusted for age, sex, fat-free mass, and fat mass is associated with changes in weight or body composition. Here, we report that repeatability of TEE is high for adults, but not children. Bivariate Bayesian mixed models show no among or within-individual correlation between body composition (fat mass or percentage) and unadjusted TEE in adults. For adults aged 20-60 y (N = 267; time interval: 7.4 ± 12.2 weeks), increases in adjusted TEE are associated with weight gain but not with changes in body composition; results are similar for subjects with intervals >4 weeks (N = 53; 29.1 ± 12.8 weeks). This suggests low TEE is not a risk factor for, and high TEE is not protective against, weight or body fat gain over the time intervals tested.

Variation in human water turnover associated with environmental and lifestyle factors.

Water is essential for survival, but one in three individuals worldwide (2.2 billion people) lacks access to safe drinking water. Water intake requirements largely reflect water turnover (WT), the water used by the body each day. We investigated the determinants of human WT in 5604 people from the ages of 8 days to 96 years from 23 countries using isotope-tracking (2H) methods. Age, body size, and composition were significantly associated with WT, as were physical activity, athletic status, pregnancy, socioeconomic status, and environmental characteristics (latitude, altitude, air temperature, and humidity). People who lived in countries with a low human development index (HDI) had higher WT than people in high-HDI countries. On the basis of this extensive dataset, we provide equations to predict human WT in relation to anthropometric, economic, and environmental factors.

Energy compensation and adiposity in humans.

Understanding the impacts of activity on energy balance is crucial. Increasing levels of activity may bring diminishing returns in energy expenditure because of compensatory responses in non-activity energy expenditures.1-3 This suggestion has profound implications for both the evolution of metabolism and human health. It implies that a long-term increase in activity does not directly translate into an increase in total energy expenditure (TEE) because other components of TEE may decrease in response-energy compensation. We used the largest dataset compiled on adult TEE and basal energy expenditure (BEE) (n = 1,754) of people living normal lives to find that energy compensation by a typical human averages 28% due to reduced BEE; this suggests that only 72% of the extra calories we burn from additional activity translates into extra calories burned that day. Moreover, the degree of energy compensation varied considerably between people of different body compositions. This association between compensation and adiposity could be due to among-individual differences in compensation: people who compensate more may be more likely to accumulate body fat. Alternatively, the process might occur within individuals: as we get fatter, our body might compensate more strongly for the calories burned during activity, making losing fat progressively more difficult. Determining the causality of the relationship between energy compensation and adiposity will be key to improving public health strategies regarding obesity.

Daily energy expenditure through the human life course.

Total daily energy expenditure ("total expenditure") reflects daily energy needs and is a critical variable in human health and physiology, but its trajectory over the life course is poorly studied. We analyzed a large, diverse database of total expenditure measured by the doubly labeled water method for males and females aged 8 days to 95 years. Total expenditure increased with fat-free mass in a power-law manner, with four distinct life stages. Fat-free mass-adjusted expenditure accelerates rapidly in neonates to ~50% above adult values at ~1 year; declines slowly to adult levels by ~20 years; remains stable in adulthood (20 to 60 years), even during pregnancy; then declines in older adults. These changes shed light on human development and aging and should help shape nutrition and health strategies across the life span.

Physical activity and fat-free mass during growth and in later life.

BACKGROUND: Physical activity may be a way to increase and maintain fat-free mass (FFM) in later life, similar to the prevention of fractures by increasing peak bone mass. OBJECTIVES: A study is presented of the association between FFM and physical activity in relation to age. METHODS: In a cross-sectional study, FFM was analyzed in relation to physical activity in a large participant group as compiled in the International Atomic Energy Agency Doubly Labeled Water database. The database included 2000 participants, age 3-96 y, with measurements of total energy expenditure (TEE) and resting energy expenditure (REE) to allow calculation of physical activity level (PAL = TEE/REE), and calculation of FFM from isotope dilution. RESULTS: PAL was a main determinant of body composition at all ages. Models with age, fat mass (FM), and PAL explained 76% and 85% of the variation in FFM in females and males < 18 y old, and 32% and 47% of the variation in FFM in females and males ≥ 18 y old, respectively. In participants < 18 y old, mean FM-adjusted FFM was 1.7 kg (95% CI: 0.1, 3.2 kg) and 3.4 kg (95% CI: 1.0, 5.6 kg) higher in a very active participant with PAL = 2.0 than in a sedentary participant with PAL = 1.5, for females and males, respectively. At age 18 y, height and FM-adjusted FFM was 3.6 kg (95% CI: 2.8, 4.4 kg) and 4.4 kg (95% CI: 3.2, 5.7 kg) higher, and at age 80 y 0.7 kg (95% CI: -0.2, 1.7 kg) and 1.0 kg (95% CI: -0.1, 2.1 kg) higher, in a participant with PAL = 2.0 than in a participant with PAL = 1.5, for females and males, respectively. CONCLUSIONS: If these associations are causal, they suggest physical activity is a major determinant of body composition as reflected in peak FFM, and that a physically active lifestyle can only partly protect against loss of FFM in aging adults.

A standard calculation methodology for human doubly labeled water studies.

The doubly labeled water (DLW) method measures total energy expenditure (TEE) in free-living subjects. Several equations are used to convert isotopic data into TEE. Using the International Atomic Energy Agency (IAEA) DLW database (5,756 measurements of adults and children), we show considerable variability is introduced by different equations. The estimated rCO2 is sensitive to the dilution space ratio (DSR) of the two isotopes. Based on performance in validation studies, we propose a new equation based on a new estimate of the mean DSR. The DSR is lower at low body masses (<10 kg). Using data for 1,021 babies and infants, we show that the DSR varies non-linearly with body mass between 0 and 10 kg. Using this relationship to predict DSR from weight provides an equation for rCO2 over this size range that agrees well with indirect calorimetry (average difference 0.64%; SD = 12.2%). We propose adoption of these equations in future studies.

Physical activity, fat intake and body fat.

The body fatness of a subject is a long-term reflection of the energy balance, the more intake exceeds expenditure the more energy is stored as fat. There is not yet a clear answer on the question whether the current obesity epidemic is a consequence of gluttony or sloth. Review studies do not show a reduction of physical activity over the years, and food intake is difficult to measure in daily life conditions. Food intake can only be derived from self-report, where under-reporting of food intake and selective underreporting of fat intake are major issues. Fat intake might be an important factor in the increase of body weight. Many studies suggest the capacity of the body to oxidize dietary fat is a major risk factor for a positive energy balance. Additionally, there is evidence that most of the fat consumed is stored before oxidation. Obesity prone subjects might be characterized by a higher storage of dietary fat. The only way to increase the oxidation of dietary fat, other than consuming more dietary fat, is to increase energy expenditure by an increase of physical activity. Indeed, there are indications that physical activity is an important determinant of fat oxidation. Based on the evidence presented, it is concluded that the obesity epidemic is mainly due to a high dietary intake, especially as fat, and that physical activity can be a tool to modulate the effect of fat intake on body fat.

Exercise-induced oxidative stress in older adults as a function of habitual activity level.

OBJECTIVES: It has been suggested that regular physical activity might maintain and promote the antioxidant defense capacity against oxidative stress. Therefore, we assessed exercise-induced oxidative stress in relation to habitual physical activity level (PAL) in older adults. DESIGN: The study included a 2-week observation period for the measurement of average daily metabolic rate (ADMR) and PAL. Exercise-induced oxidative stress was measured during a 45-minute cycling test at submaximal intensity. SETTING: A university medical research center. PARTICIPANTS: Twenty-six subjects volunteered for the study (n = 26; mean age +/- standard deviation 60 +/- 1; body mass index 27 +/- 1 kg/m2). MEASUREMENTS: PAL was determined as ADMR combined with a measurement of basal metabolic rate (BMR): PAL = ADMR/BMR. ADMR was measured over 2 weeks with the doubly labeled water method, preceded by a BMR measurement with a ventilated hood. Antipyrine oxidation was used as marker for oxidative stress in vivo. Reaction of antipyrine with hydroxyl radicals results in the formation of para-hydroxyantipyrine (p-APOH) and ortho-hydroxyantipyrine (o-APOH), where o-APOH is not formed through alternative oxygenetic pathways. RESULTS: PAL was inversely related to the exercise-induced increase in the ratio of o-APOH to native antipyrine (r = 0.49, P = .010). The relationship between PAL and exercise-induced increase in the ratio of p-APOH (r = 0.30, P = .140) or thiobarbituric acid reactive species (r = 0.31, P = .130) did not reach the level of significance. CONCLUSION: Physically active older adults have a reduced exercise-induced oxidative stress than older adults with a lower level of physical activity. It seems that regular physical activity improves the antioxidant defense capacity.

Weight-loss induced changes in physical activity and activity energy expenditure in overweight and obese subjects before and after energy restriction.

Activity energy expenditure (AEE) is the component of daily energy expenditure that is mainly influenced by the amount of physical activity (PA) and by the weight of the body displaced. This study aimed at analyzing the effect of weight loss on PA and AEE. The body weight and PA of 66 overweight and obese subjects were measured at baseline and after 12 weeks of 67% energy restriction. PA was measured using a tri-axial accelerometer for movement registration (Tracmor) and quantified in activity counts. Tracmor recordings were also processed using a classification algorithm to recognize 6 common activity types engaged in during the day. A doubly-labeled water validated equation based on Tracmor output was used to estimate AEE. After weight loss, body weight decreased by 13±4%, daily activity counts augmented by 9% (95% CI: +2%, +15%), and this increase was weakly associated with the decrease in body weight (R(2) = 7%; P<0.05). After weight loss subjects were significantly (P<0.05) less sedentary (-26 min/d), and increased the time spent walking (+11 min/d) and bicycling (+4 min/d). However, AEE decreased by 0.6±0.4 MJ/d after weight loss. On average, a 2-hour/day reduction of sedentary time by increasing ambulatory and generic activities was required to restore baseline levels of AEE. In conclusion, after weight loss PA increased but the related metabolic demand did not offset the reduction in AEE due to the lower body weight. Promoting physical activity according to the extent of weight loss might increase successfulness of weight maintenance.

Validation of the TracmorD triaxial accelerometer to assess physical activity in preschool children.

OBJECTIVES: To assess validity evidence of TracmorD to determine energy used for physical activity in 3-4-year-old children. DESIGN AND METHODS: Participants were randomly selected from GECKO Drenthe cohort (n = 30, age 3.4 ± 0.3 years). Total energy expenditure (TEE) was measured using the doubly labeled water method. Sleeping metabolic rate (SMR) was measured by indirect calorimetry (Deltatrac). TEE and SMR were used to calculate physical activity level (PAL) and activity energy expenditure (AEE). Physical activity was monitored using a DirectLife triaxial accelerometer, TracmorD with activity counts per minute (ACM) and activity counts per day (ACD) as outcome measures. RESULTS: The best predictor for PAL was ACM with gender and weight, the best predictor for AEE was ACM alone (backward regression, R(2) = 0.50, P = 0.010 and R2 = 0.31, P = 0.011, respectively). With ACD, the prediction model for PAL included ACD, height, gender, and sleep duration (R2 = 0.48, P = 0.033), the prediction model for AEE included ACD, gender and sleep duration (R2 = 0.39, P = 0.042). The accelerometer was worn for 5 days, but 3 days did not give a different estimated PAL. CONCLUSION: TracmorD provides moderate-to-strong validity evidence that supports its use to evaluate energy used for physical activity in 3-4-year-old children.

Estimation of free-living energy expenditure using a novel activity monitor designed to minimize obtrusiveness.

The aim of this study was to investigate the ability of a novel activity monitor designed to be minimally obtrusive in predicting free-living energy expenditure. Subjects were 18 men and 12 women (age: 41 +/- 11 years, BMI: 24.4 +/- 3 kg/m(2)). The habitual physical activity was monitored for 14 days using a DirectLife triaxial accelerometer for movement registration (Tracmor(D)) (Philips New Wellness Solutions, Lifestyle Incubator, the Netherlands). Tracmor(D) output was expressed as activity counts per day (Cnts/d). Simultaneously, total energy expenditure (TEE) was measured in free living conditions using doubly labeled water (DLW). Activity energy expenditure (AEE) and the physical activity level (PAL) were determined from TEE and sleeping metabolic rate (SMR). A multiple-linear regression model predicted 76% of the variance in TEE, using as independent variables SMR (partial-r(2) = 0.55, P < 0.001), and Cnts/d (partial r(2) = 0.21, P < 0.001). The s.e. of TEE estimates was 0.9 MJ/day or 7.4% of the average TEE. A model based on body mass (partial-r(2) = 0.31, P < 0.001) and Cnts/d (partial-r(2) = 0.23, P < 0.001) predicted 54% of the variance in TEE. Cnts/d were significantly and positively associated with AEE (r = 0.54, P < 0.01), PAL (r = 0.68, P < 0.001), and AEE corrected by body mass (r = 0.71, P < 0.001). This study showed that the Tracmor(D) is a highly accurate instrument for predicting free-living energy expenditure. The miniaturized design did not harm the ability of the instrument in measuring physical activity and in determining outcome parameters of physical activity such as TEE, AEE, and PAL.

Detection of type, duration, and intensity of physical activity using an accelerometer.

OBJECTIVE: The aim of this study was to develop models for the detection of type, duration, and intensity of human physical activity using one triaxial accelerometer. METHODS: Twenty subjects (age = 29 +/- 6 yr, BMI = 23.6 +/- 3.2 kg.m) performed 20 selected activities, including walking, running, and cycling, wearing one triaxial accelerometer mounted on the lower back. Identification of activity type was based on a decision tree. The decision tree evaluated attributes (features) of the acceleration signal. The features were measured in intervals of defined duration (segments). Segment size determined the time resolution of the decision tree to assess activity duration. Decision trees with a time resolution of 0.4, 0.8, 1.6, 3.2, 6.4, and 12.8 s were developed, and the respective classification performances were evaluated. Multiple linear regression was used to estimate speed of walking, running, and cycling based on acceleration features. RESULTS: Maximal accuracy for the classification of activity type (93%) was reached when the segment size of analysis was 6.4 or 12.8 s. The smaller the segment size, the lower the classification accuracy achieved. Segments of 6.4 s gave the highest time resolution for measuring activity duration without decreasing the classification accuracy. The developed models estimated walking, running, and cycling speeds with a standard error of 0.20, 1.26, and 1.36 km.h, respectively. CONCLUSIONS: This study demonstrated the ability of a triaxial accelerometer in detecting type, duration, and intensity of physical activity using models based on acceleration features. Future studies are needed to validate the presented models in free-living conditions.

Water loss as a function of energy intake, physical activity and season.

Although water is an important nutrient, there are no recommended intake values. Here, water intake, energy intake, physical activity and water loss was measured over 1 week in summer and in winter. Subjects were healthy volunteers, forty-two women and ten men, mean age of 29 (SD 7) years and mean BMI 21.8 (SD 2.2) kg/m2. Water intake was measured with a 7 d food and water record. Physical activity level (PAL) was observed as the ratio of total energy expenditure, as measured with doubly labelled water, to resting energy expenditure as measured in a respiration chamber. Water loss was measured with the deuterium elimination method. Water loss was highly reproducible and ranged from 0.20 to 0.35 l/MJ, independent of season and activity level, with higher values in women. Water loss was related to water and energy intake in summer (r 0.96, P<0.0001 and r 0.68, P<0.001, respectively) as well as in winter (r 0.98, P<0.0001 and r 0.63, P<0.01, respectively). Water loss was, for men, higher in subjects with a higher physical activity in summer (r 0.94, P<0.0001) and in winter (r 0.70, P<0.05). Normalizing water loss for differences in energy expenditure by expressing water loss in litres per MJ resulted in the same value for men in summer and winter. For women, physical activity-adjusted values of water loss were higher, especially in summer. In men, water turnover was determined by energy intake and physical activity, while seasonal effects appeared through energy expenditure. Women showed a higher water turnover that was unrelated to physical activity.

Measuring free-living energy expenditure and physical activity with triaxial accelerometry.

OBJECTIVE: To investigate the ability of a newly developed triaxial accelerometer to predict total energy expenditure (EE) (TEE) and activity-related EE (AEE) in free-living conditions. RESEARCH METHODS AND PROCEDURES: Subjects were 29 healthy subjects between the ages of 18 and 40. The Triaxial Accelerometer for Movement Registration (Tracmor) was worn for 15 consecutive days. Tracmor output was defined as activity counts per day (ACD) for the sum of all three axes or each axis separately (ACD-X, ACD-Y, ACD-Z). TEE was measured with the doubly labeled water technique. Sleeping metabolic rate (SMR) was measured during an overnight stay in a respiration chamber. The physical activity level was calculated as TEE x SMR(-1), and AEE was calculated as [(0.9 x TEE) - SMR]. Body composition was calculated from body weight, body volume, and total body water using Siri's three-compartment model. RESULTS: Age, height, body mass, and ACD explained 83% of the variation in TEE [standard error of estimate (SEE) = 1.00 MJ/d] and 81% of the variation in AEE (SEE = 0.70 MJ/d). The partial correlations for ACD were 0.73 (p < 0.001) and 0.79 (p < 0.001) with TEE and AEE, respectively. When data on SMR or body composition were used with ACD, the explained variation in TEE was 90% (SEE = 0.74 and 0.77 MJ/d, respectively). The increase in the explained variation using three axes instead of one axis (vertical) was 5% (p < 0.05). DISCUSSION: The correlations between Tracmor output and EE measures are the highest reported so far. To measure daily life activities, the use of triaxial accelerometry seems beneficial to uniaxial.

Validity of the assessment of dietary intake: problems of misreporting.

PURPOSE OF REVIEW: This is a review of recent studies on the analysis of misreporting of food intake and on the consequences of misreporting for the interpretation of dietary surveys. Bias in the assessment of dietary intake was analysed from studies comparing reported intake with doubly labelled water assessed energy expenditure. RECENT FINDINGS: There is not yet a method for the accurate determination of dietary intake. Physical and psychological characteristics of study participants play an important role in the observed reporting bias. The degree of misreporting might increase with repeated dietary assessment in the same subjects, confounding the results of intervention studies. SUMMARY: Campaigns aimed at changing food intake might not be as successful as concluded from the results of national food consumption measurements. Subjects might be reporting according to expected instead of real intake. In a clinical setting, the increased awareness of the nursing staff has been observed to result in overreporting of intake.

Alcohol energy intake and habitual physical activity in older adults.

Alcohol forms a significant component of many diets and it supplements rather than displaces daily energy intake. Surprisingly, alcohol intake does not systematically increase body weight. The present study assessed whether a higher level of habitual physical activity in the daily environment is associated with a higher alcohol intake. Alcohol intake as part of total food intake was measured with a 7 d dietary record while at the same time physical activity was monitored with a tri-axial accelerometer for movement registration. Subjects were twenty women and twenty-four men, aged 61+/-5 years, of BMI 27.1+/-4.6 kg/m(2). Between subjects, there was a positive association between the level of habitual physical activity and alcohol intake (r 0.41; P<0.01). The subjects with higher alcohol intake had a higher activity level. On days with and days without alcohol consumption there was no difference in physical activity within subjects. In conclusion, it was shown that subjects with higher alcohol consumption are habitually more active. This may explain the lack of increasing body weight through additional energy intake from alcohol.

Habitual meal frequency in relation to resting and activity-induced energy expenditure in human subjects: the role of fat-free mass.

Habitual meal frequency was assessed as a possible function of components of energy expenditure (EE) in human subjects. Fifty-six subjects participated (four categories differing in body composition): ten older women (fat-free mass (FFM) 42.0 (sd 6.3) kg, aged 59 (sd 2) years, BMI 27.5 (sd 6.9) kg/m(2)), fifteen younger women (FFM 45.5 (sd 5.2) kg, aged 34 (sd 10) years, BMI 21.9 (sd 2.3) kg/m(2)), twelve older men (FFM 56.8 (sd 5.9) kg, aged 62 (sd 4) years, BMI 25.7 (sd 3.3) kg/m(2)) and nineteen younger men (FFM 63.9 (sd 7.5) kg, aged 23.1 (sd 3.9) years, BMI 22.9 (sd 1.8) kg/m(2)). Measurements consisted of habitual meal frequency by validated food-intake diaries, physical activity by tri-axial accelerometers and resting EE by a ventilated hood system. Habitual meal frequency was expressed as a function of resting EE (including resting EE as a function of FFM), and of activity-induced EE, using regression analysis. FFM differed according to gender and age categories (P<0.01). Physical activity level was higher in the younger men than in the other categories (P<0.05). No relationship of meal frequency with the variables assessed was observed in subjects with a low FFM (the women). In the subjects with a medium FFM (the older men), meal frequency was positively related to resting EE (r(2) 0.4, P<0.05), but not to the residuals of resting EE as a function of FFM, and inversely related to activity-induced EE (r(2) 0.3, P<0.05). Resting EE explained 40 % of the variation in meal frequency; adding activity-induced EE increased this to 60 %. In the subjects with a high FFM (the younger men), meal frequency was inversely related to resting EE (r(2) 0.8, P<0.0001) and to the residuals of resting EE as a function of FFM (P=0.03), and positively related to activity-induced EE (r(2) 0.6, P<0.0001). Resting EE explained 85 % of the variation in meal frequency; adding activity-induced EE increased this to 89 %. Habitual meal frequency was a function of components of EE, namely resting EE and activity-induced EE, only in subjects with a medium to high FFM (men). FFM-related differences in these relationships suggest a role of physical activity.