Assessment of physical activity by means of a calorie counter combined with an accelerometer

To establish an easy and convenient method for assessing the daily physical activity of workers, validity of a calorie counter combined with an accelerometer (KENZ Calorie Counter) was tested and compared with the method of daily survey and Stanford's interview method for energy consumption of daily physical activity. The subjects of this study were 92 volunteers. Energy expenditure of daily physical activity during 3-4 d was measured in 20 volunteers by means of a calorie counter, and the daily energy consumption was calculated from relative metabolic rates of physical activity. In the remaining 72 volunteers the energy consumption over 4-7 d was measured by means of a calorie counter and calculated from the Stanford's interview method. Correlation of the energy expenditure of daily physical activity measured by calorie counter (y) and that calculated from daily survey (x) was y = 0.74 x + 473 (r = 0.91, n = 56). Correlation of the calorie expenditure over 4-7 d measured by the calorie counter (y) and that predicted by Stanford's interview method (x) was high (y = 0.65 x + 3513, r = 0.86, n = 72). Relationship between the energy expenditure measured by the calorie counter (y) and that calculated by both daily survey and Stanford's interview method (x) showed a high correlation (y = 0.84 x + 518, r = 0.98, n = 128). These results suggest that a calorie counter combined with an accelerometer is valid for assessing the daily physical activity of workers.     

Lipids and lipoproteins in a young adult population. The Beaver County Lipid Study

Though atherosclerosis may have its origins in childhood, intervention studies on coronary heart disease risk factors have usually begun in older adults. Whether young adults exhibit similar relationships of lifestyle to coronary heart disease risk factors, and therefore might be suitable candidates for appropriate intervention, is poorly understood. The Beaver County Lipid Study is a 9-year follow-up study of a free-living young adult population (mean age 22 years) who were initially screened for hypercholesterolemia as seventh grade school children. This report focuses upon cross-sectional correlates of lipid and lipoprotein concentrations in 561 individuals (males n = 262; females n = 299) in 1981-1982. Body mass index was positively related to low density lipoprotein (LDL) cholesterol and triglycerides in men (r = 0.21; p less than 0.001 and r = 0.41; p less than 0.001) and women (r = 0.16; p less than 0.001 and r = 0.20; p less than 0.001). Cigarette smoking was inversely associated with high density lipoprotein (HDL) cholesterol in men (r = -0.11; p less than 0.001) and women (r = -0.20; p less than 0.001) but positively related to triglycerides in both sexes (r = 0.10; p = 0.05 for men and r = 0.19; p less than 0.01 for women). Alcohol consumption was positively related to HDL cholesterol and triglycerides only among men (r = 0.19; p less than 0.001 and r = 0.12; p less than 0.05, respectively). Educational achievement was also positively related to HDL cholesterol in men (p less than 0.01) and women (p less than 0.001). Multivariate analyses indicate that the sex difference in LDL cholesterol was largely eliminated by controlling for body mass index while significant sex differences in both HDL cholesterol and triglycerides remained after controlling for covariates. Results suggest that the known associations in older adults of body mass index and health-related behavior with lipoproteins are well established by young adulthood. Early intervention particularly for obesity may help ameliorate some of the male excess in cardiovascular disease risk.     

Sex differences in the coronary heart disease risk profile: a possible role for insulin. The Beaver County Study

The mortality rate from coronary heart disease is much higher among men than women except in diabetes mellitus, which appears to reduce this sex difference. It is hypothesized that the female advantage is due, at least partly, to the more efficient insulin mediated glucose homeostasis in females, an advantage lost in the diabetic state. The authors studied 170 young adult men and women aged 20-24 years from a population-based survey in Beaver County, Pennsylvania, in 1981-1982, in an attempt to further elucidate the sex-specific relationships between fasting serum insulin concentrations and several risk factors. Women who used oral contraceptives and subjects whose fasting serum glucose exceeded 110 mg/dl were excluded. Insulin was related to body mass index in both sexes (r = 0.31; p less than 0.01 for men; r = 0.26, p less than 0.01 for women) and to systolic blood pressure (r = 0.27, p less than 0.01 for men; r = 0.36, p less than 0.001 for women). Insulin was related to diastolic blood pressure in men only (r = 0.31, p less than 0.05). Multivariate analysis revealed fasting serum insulin to be an independent predictor of systolic blood pressure in both sexes and of diastolic blood pressure in men only. Insulin was inversely related to high density lipoprotein cholesterol only among men and this relationship appeared to be largely independent of body mass index and triglycerides. Results indicate that insulin concentration is associated with an adverse coronary heart disease risk factor profile especially among men, consistent with their excess risk of cardiovascular disease.     

Blood lead concentration, renal function, and blood pressure in London civil servants.

Blood lead concentration was measured in 398 male and 133 female London civil servants not subject to industrial exposure to heavy metals. The relation between blood lead and serum creatinine concentrations and blood pressure were examined. Blood lead concentration ranged from 0.20 to 1.70 mumol/l with a geometric mean concentrations of 0.58 mumol/l in men and 0.46 mumol/l in women (p less than 0.001). In women blood lead concentration increased with age (r = +0.27; p = 0.002). In the two sexes blood lead concentration was positively correlated with the number of cigarettes smoked a day (men r = +0.17 and women r = +0.22; p less than or equal to 0.01), with the reported number of alcoholic beverages consumed a day (men r = +0.34 and women r = 0.23; p less than 0.01), and with serum gamma-glutamyltranspeptidase (men r = +0.23 and women r = +0.14; for men p less than 0.01). Blood lead concentration was not correlated with body weight, body mass index, and employment grade. In men 14% of the variance of blood lead concentration was explained by the significant and independent contributions of smoking and alcohol intake and in women 16% by age, smoking, and alcohol consumption. In men serum creatinine concentration tended to rise by 0.6 mumol/l (95% confidence interval from -0.2 to +1.36 mumol/l) for each 25% increment in blood lead concentration. In men and women the correlations between blood lead concentration and systolic and diastolic blood did not approach statistical significance. In conclusion, in subjects not exposed to heavy metals at work gender, age, smoking, and alcohol intake are determinants of blood lead concentration. At a low level of exposure, lead accumulation may slightly impair renal function, whereas blood pressure does not seem to be importantly influenced. Alternatively, a slight impairment of renal function may give rise to an increase in blood lead concentration.     

Blood lead concentration, renal function, and blood pressure in London civil servants

Blood lead concentration was measured in 398 male and 133 female London civil servants not subject to industrial exposure to heavy metals. The relation between blood lead and serum creatinine concentrations and blood pressure were examined. Blood lead concentration ranged from 0.20 to 1.70 mumol/l with a geometric mean concentrations of 0.58 mumol/l in men and 0.46 mumol/l in women (p less than 0.001). In women blood lead concentration increased with age (r = +0.27; p = 0.002). In the two sexes blood lead concentration was positively correlated with the number of cigarettes smoked a day (men r = +0.17 and women r = +0.22; p less than or equal to 0.01), with the reported number of alcoholic beverages consumed a day (men r = +0.34 and women r = 0.23; p less than 0.01), and with serum gamma-glutamyltranspeptidase (men r = +0.23 and women r = +0.14; for men p less than 0.01). Blood lead concentration was not correlated with body weight, body mass index, and employment grade. In men 14% of the variance of blood lead concentration was explained by the significant and independent contributions of smoking and alcohol intake and in women 16% by age, smoking, and alcohol consumption. In men serum creatinine concentration tended to rise by 0.6 mumol/l (95% confidence interval from -0.2 to +1.36 mumol/l) for each 25% increment in blood lead concentration. In men and women the correlations between blood lead concentration and systolic and diastolic blood did not approach statistical significance. In conclusion, in subjects not exposed to heavy metals at work gender, age, smoking, and alcohol intake are determinants of blood lead concentration. At a low level of exposure, lead accumulation may slightly impair renal function, whereas blood pressure does not seem to be importantly influenced. Alternatively, a slight impairment of renal function may give rise to an increase in blood lead concentration.     

Relationships between body fatness, adipose tissue distribution and blood pressure in men and women

The relationships between body fatness, fat distribution and blood pressure (BP) were studied in 234 women and 238 men, aged 18-50 years. In both sexes, subcutaneous (s.c.) fat (assessed by the measurement of s.c. skinfolds) and percent body fat (measured by underwater weighing) were correlated significantly with diastolic (0.27 less than or equal to r less than or equal to 0.37, p less than 0.0005) and systolic (0.17 less than or equal to r less than or equal to 0.29, p less than 0.01) BP. In either sex, the proportion of s.c. trunk fat as reflected by the ratio of trunk/extremity skinfolds showed significant associations with diastolic (men: r = 0.35, women: r = 0.20, p less than 0.01) and systolic BP (men: r = 0.15, women: r = 0.17, p less than 0.05). Control for the effects of covariables potentially affecting BP (energy intake, energy expenditure, maximal oxygen consumption, cigarette smoking, alcohol intake and age) revealed significant effects of age and alcohol intake on BP in men. In women, only age appeared to be associated with BP variation. Partial correlations after control for age and alcohol intake indicated a significant association between the trunk/extremity skinfolds ratio and diastolic BP in men. Such a correlation was not found in women after control for the effect of age. Analysis of variance (2 x 2 factorial with fixed effects) confirmed that, in men, the distribution of s.c. body fat was, per se, associated with diastolic BP (F = 8.43, p less than 0.01), whereas the proportional of s.c. trunk fat was not related to systolic BP in both sexes.(ABSTRACT TRUNCATED AT 250 WORDS)     

Physical activity in confined conditions as an indicator of free-living physical activity

OBJECTIVE: The main determinants of daily energy expenditure are body size and physical activity. Activity energy expenditure is the most variable component of total energy expenditure. It was assessed whether the physical activity level in confined conditions is an indicator of free-living physical activity. RESEARCH METHODS AND PROCEDURES: Activity energy expenditure was measured over 1 day in a confined environment of a respiration chamber (floor space, 7.0 m(2)), where activities were restricted to low-intensity activities of daily living, and over 2 weeks in a free-living environment using doubly labeled water. Subjects were 16 women and 29 men (age, 31 +/- 10 years; BMI, 24.2 +/- 2.7 kg/m(2)). RESULTS: The free-living activity level of the subjects, as a multiple of resting energy expenditure, was 1.76 +/- 0.13. Activity energy expenditure in the chamber was 47 +/- 13% of the value in daily life, and the two values were correlated (r = 0.50, p < 0.001; partial correlation corrected for age, gender, and BMI: 0.40, p < 0.01). The chamber value explained 25% of the total variance in free-living activity energy expenditure. DISCUSSION: The activity level of a subject under sedentary conditions is an indicator of activity energy expenditure in daily life, showing the importance of nonexercise activity for daily energy expenditure.     

A new predictive equation for resting energy expenditure in healthy individuals

A predictive equation for resting energy expenditure (REE) was derived from data from 498 healthy subjects, including females (n = 247) and males (n = 251), aged 19-78 y (45 +/- 14 y, mean +/- SD). Normal-weight (n = 264) and obese (n = 234) individuals were studied and REE was measured by indirect calorimetry. Multiple-regression analyses were employed to drive relationships between REE and weight, height, and age for both men and women (R2 = 0.71): REE = 9.99 x weight + 6.25 x height - 4.92 x age + 166 x sex (males, 1; females, 0) - 161. Simplification of this formula and separation by sex did not affect its predictive value: REE (males) = 10 x weight (kg) + 6.25 x height (cm) - 5 x age (y) + 5; REE (females) = 10 x weight (kg) + 6.25 x height (cm) - 5 x age (y) - 161. The inclusion of relative body weight and body-weight distribution did not significantly improve the predictive value of these equations. The Harris-Benedict Equations derived in 1919 overestimated measured REE by 5% (p less than 0.01). Fat-free mass (FFM) was the best single predictor of REE (R2 = 0.64): REE = 19.7 x FFM + 413. Weight also was closely correlated with REE (R2 = 0.56): REE = 15.1 x weight + 371.     

Total daily energy expenditure among middle-aged men and women: the OPEN Study

BACKGROUND: Few large doubly labeled water (DLW) studies have provided an objective measure of total energy expenditure (TEE) in free-living men and women. The committee that developed the 2002 Dietary Reference Intake (DRI) estimated energy requirements (EER) noted that DLW studies in adults aged 40 to 60 y were limited. OBJECTIVE: We aimed to describe TEE and physical activity energy expenditure in middle-aged men and women by sex, age, menopausal status, and level of obesity, and to compare TEE to the DRI EER. DESIGN: TEE was measured by the DLW method in 450 men and women aged 40-69 y from the Observing Protein and Energy Nutrition Study. Resting metabolic rate was estimated by use of the Mifflin equation. RESULTS: Unadjusted TEE was lower in women than in men (591 kcal/d); however, when the analysis was adjusted for fat-free mass, women had significantly higher TEE than did men (182 kcal/d). This difference appeared to be due to higher physical activity levels in women (physical activity energy expenditure adjusted for FFM was 188 kcal/d greater in women than in men). Mean TEE was lowest in the seventh decade. TEE from DLW was highly correlated (r = 0.93) with EER from the DRI equations. CONCLUSION: In this population, TEE was higher in women than in men when adjusted for FFM, apparently because of higher physical activity levels in women. There were no significant differences in TEE, FFM, or physical activity levels in women by menopausal status. TEE was inversely associated with age and increased linearly with body mass index. This study corroborates the use of the DRI equations for EER.     

Effects of the interaction of sex and food intake on the relation between energy expenditure and body composition

BACKGROUND: The relation between physical activity energy expenditure (PAEE) and percentage body fat (%BF) is not very strong in the general population. It is possible that variables such as sex, food intake, or both may in part explain this poor coupling. OBJECTIVE: This study was designed to show the relation between PAEE and %BF and to determine whether sex, food intake, or both influence the strength of the relation. DESIGN: We used doubly labeled water or energy intake balance, indirect calorimetry, dietary interview, and dual-energy X-ray absorptiometry to measure total energy expenditure (TEE), resting energy expenditure (REE), food intake, and %BF, respectively, in 91 healthy persons (women: aged 48 y, 38.6%BF, n = 47; men: aged 47 y, 24.1%BF, n = 44). RESULTS: TEE, PAEE, and REE were significantly lower in women than in men. TEE was related to %BF in women (r = 0.53, P < 0.0001) but not in men (r = -0.22, P > 0.05). The relation between PAEE and %BF was significant in men (r = -0.34, P < 0.03) but not in women. PAL was also significantly related to %BF in men (r = -0.36, P < 0.02) but not in women. Macronutrient intake (% of total energy) did not differ significantly between the sexes, but carbohydrate (r = -0.44, P < 0.003) and fat (r = 0.31, P < 0.04) intakes were significantly related to %BF in women. CONCLUSIONS: These results suggest that the relation between PAEE and %BF is stronger in men than in women. Macronutrient composition seems have a stronger influence on %BF in women than in men.     

Energy expenditure from minute-by-minute heart-rate recording: comparison with indirect calorimetry

Total daily energy expenditure (TDEE) and energy expended in activity (EAC) were estimated by the minute-by-minute heart-rate method in 22 (16 men, 6 women) individually calibrated subjects and compared with values obtained by whole-body indirect calorimetry. Subjects followed four activity protocols during the 22 h in the calorimeter; no exercise (n = 6) and 2 (n = 5), 4 (n = 4), and 6 (n = 6) 30-min bouts of exercise on a bicycle ergometer at varying intensities. There were no statistically significant differences between the two methods in TDEE or EAC in any of the sex or protocol groupings. The regression of TDEE by heart rate on TDEE in the calorimeter was y = 0.92x + 1.0 MJ; (r = 0.87, SEE = 0.91 MJ). The heart-rate method also follows the varying activity patterns of individuals and can be used to closely estimate the TDEE and EAC of even small (n = 4-6) groups of subjects. In the present measurements, it gave a maximum error of TDEE for individuals of +20% and -15%.     

Glucose intolerance and physical inactivity: the relative importance of low habitual energy expenditure and cardiorespiratory fitness

Glucose intolerance and diabetes mellitus are associated with physical inactivity, but it is unclear whether preventive interventions should aim at increasing overall energy expenditure or increasing participation in vigorous, fitness-enhancing activities. Studies aimed at separating and quantifying the effects of these two dimensions of physical activity should use well-validated measurement instruments and employ a study design in which the bivariate error structure of these instruments is determined. In the Isle of Ely Study (Cambridgeshire, United Kingdom), 775 individuals aged 45-70 years in 1994-1997 completed a glucose tolerance test and assessment of 4-day physical activity level (total energy expenditure/basal metabolic rate) by heart rate monitoring, a technique that has been validated against doubly labeled water and whole-body calorimetry. Cardiorespiratory fitness (maximum oxygen uptake (VO2max) per kg)) was measured in a submaximal test. To correct for measurement error, the authors had 190 individuals repeat both tests on three occasions at 4-month intervals. Two-hour glucose level was negatively correlated with physical activity level (men: r = -0.22, p < 0.001; women: r = -0.11, p < 0.05) and VO2max per kg (men: r = -0.18, p < 0.01; women: r = -0.19, p < 0.001) and was positively correlated with age and obesity. The model incorporating bivariate adjustment for measurement error showed that energy expenditure had a major effect on glucose tolerance, but there was less of an effect for cardiorespiratory fitness. These data provide support for public health strategies aimed at increasing overall energy expenditure.     

Energy requirements in the eighth decade of life

BACKGROUND: Knowledge of energy requirements among relatively healthy elderly is limited. OBJECTIVES: The objectives of the study were to measure total energy expenditure (TEE)-derived energy requirements in a biracial population of older adults without limitations to daily life and to test these empirical measures against national and international recommendations. DESIGN: TEE (measured by the doubly labeled water method), resting metabolic rate (RMR), activity-related energy expenditure (AEE), and body composition were measured in 288 persons aged 70-79 y selected from the Health, Aging, and Body Composition Study. RESULTS: TEE was lower in women (approximately 530 kcal/d; P < 0.0001) than in men because of the women's lower RMR and AEE. Fat-free mass explained the sex difference in RMR, but body weight failed to account for the women's lower AEE (approximately 1 kcal x kg(-1) x d(-1); P = 0.007). Blacks had lower TEE than did whites (approximately 100 kcal/d, P = 0.03), and that was explained by blacks' lower RMR. Physical activity level (TEE/RMR) did not differ significantly between sexes and races (1.70 +/- 0.23). The World Health Organization (WHO) recommendations overestimated TEE by 10 +/- 15% (P < 0.0001) in women but not in men, and the dietary reference intakes (DRIs) were accurate to 0 +/- 14% (P = 0.1). Both WHO and DRI recommendations are based on an underestimated physical activity level, and WHO recommendations are based on overestimated RMR. CONCLUSIONS: This study of well-functioning older adults confirms the racial difference in energy metabolism and supports the use of the 2002 DRIs. Because the DRIs and WHO recommendations underestimated PAL, new predictive equations of energy requirements are proposed.     

Energy expenditure measured by doubly labeled water,activity recall,and diet records in the rural elderly

OBJECTIVE: The purpose of this study was to determine whether energy expenditure estimated from physical activity and energy intake were equivalent to total daily energy expenditure in an elderly rural population. METHODS: Twenty-seven elderly male (n = 14) and female (n = 13) subjects (mean age, 74 y) were recruited from a rural Pennsylvania population. Over a 2-wk period, total daily energy expenditure was measured by doubly labeled water (TEE) and estimated from 7-d physical activity recall factors multiplied by weight (PA(WT)), estimated basal metabolic rate (PA(BMR)) and resting energy expenditure from indirect calorimetry (PA(REE)), and energy intake from 3-d self-reported diet records (EI). Analysis of variance was used to determine significant within-subject differences in physical activity, energy intake, and energy expenditure. RESULTS: PA(REE) (men: 13.69 +/- 3.23 MJ, women: 9.51 +/- 2.40 MJ) and PA(BMR) (men: 13.69 +/- 2.99 MJ, women: 10.15 +/- 2.21 MJ) were not significantly different from TEE (men: 12.43 +/- 1.63 MJ, women: 9.44 +/- 0.90 MJ). EI (men: 8.66 +/- 2.34 MJ, women: 7.12 +/- 0.93 MJ) was significantly less than TEE, and PA(WT) (men: 17.03 +/- 4.07 MJ, women: 12.86 +/- 3.41 MJ) was significantly greater than TEE. CONCLUSIONS: Whereas 7-d physical activity recall determined with an age- and gender-specific estimate of resting metabolic rate or measured using indirect calorimetry accurately estimated TEE for this group of rural elderly, self-reported diet records consistently underestimated and physical activity recall determined with weight alone consistently overestimated energy expenditure measured by doubly labeled water.     

Validity of daily energy expenditure estimated by calorie counter combined with accelerometer

To estimate a reasonable and convenient method for the assessment of daily energy expenditure in workers, the validity of a calorie counter combined with an accelerometer (Kenz Calorie Counter) was tested during treadmill exercise. Ten male and female students each volunteered for exercise on a treadmill at different running speeds: 9 speeds at 2 to 10 km/h each for male subjects: 8 speeds at 2 to 9 km/h each for female subjects. Energy expenditure measured with respiratory gas analysis was compared with that estimated by the calorie counter outfitted on the waist of the subjects. For running speed slower than 9 km/h, the work intensity reading on the calorie counter increased in direct proportion to the speed of the treadmill. The correlation between running speed and the work intensity reading of the calorie counter was linear up to 8 km/h (y = 0.95 x -0.2, r = 0.96, P less than 0.001). A linear relationship during treadmill exercise (at a speed of less than 9 km/h) was also established between energy consumption measured by respiratory gas analysis and that estimated from the calorie counter (y = 1.00 x + 11.7, r = 0.94, P less than 0.001). Thus, we validated the usefulness of the calorie counter for the assessment of energy expenditure during daily physical activities.     

Energy Balance and Rectal Cancer: An Evaluation of Energy Intake,Energy Expenditure,and Body Mass Index

Lack of energy balance, or greater energy intake than expenditure as indicated by a large body mass index (BMI), has been associated with colon cancer, although less is known about its association with rectal cancer. In this study, we examined the association between BMI, energy intake, and energy expenditure and their combined effect on rectal cancer risk. A population-based case-control study was conducted in Utah and Northern California. Incident cases (n = 952) of rectal cancer and population-based controls (n = 1205) were interviewed between 1997 and 2002 to obtain detailed information on body size, dietary intake, and physical activity patterns. BMI (kg/m2) was not associated with rectal cancer in either men or women. Participation in vigorous leisure-time physical activity over the past 20 yr was associated with a significant 40% reduction in rectal cancer risk. Energy intake was associated significantly with increased risk of rectal cancer, especially among people whose diagnosis was prior to age 60 yr (odds ratio [OR] = 3.9; 95% confidence interval [CI] = 1.7-9.1 for men; OR = 2.8; 95% CI = 1.1-7.2 for women). There was a significant interaction between energy intake and energy expenditure, although not between BMI and either energy intake or energy expenditure. These data suggest that large BMI, an indicator of lack of energy balance, is not an important component of the etiology of rectal cancer. However, both physical activity and energy intake were significantly associated with rectal cancer risk. These data suggest that energy expenditure and energy intake alter rectal cancer risk through mechanisms other than energy balance.     

Estimation of daily energy needs with the FAO/WHO/UNU 1985 procedures in adults: comparison to whole-body indirect calorimetry measurements

OBJECTIVES: To measure daily energy expenditure (DEE) with indirect calorimetric facilities in sedentary and active subjects. To estimate daily energy needs with the FAO/WHO/UNU (1985) procedures (EDEE) and estimated energy requirement (EER) with the dietary reference intakes 2002 (DRI) in healthy adults with sedentary or high-activity conditions. To compare estimated daily energy needs with their measured values. DESIGN: Two groups of healthy subjects were tested under sedentary or high-activity conditions. In both groups, resting energy expenditure was measured after a 12-h overnight fast. DEE and basal metabolic rate (BMR) values were also measured with indirect calorimetry and compared to the relevant predicted values. Physical activity level and BMR were also estimated. SUBJECTS: A total of 45 sedentary (26 men and 19 women) and 69 active subjects (43 men and 26 women) aged 18-30 and 30-60 y. RESULTS: Measured daily energy expenditure (MDEE) was significantly lower than EDEE in sedentary men and women and in active men for the two age groups considered (P<0.05). EER was significantly lower than EDEE in both sedentary and active subjects of each subgroup (P<0.05). CONCLUSIONS: The FAO/WHO/UNU (1985) procedures may overestimate daily energy needs, particularly in sedentary individuals. However, DRI (2002) are probably more adapted to estimate real daily energy needs in sedentary and active subjects in comparison to the FAO/WHO/UNU (1985) procedures.     

Leisure time physical activity and its relationship to coronary risk factors in a population-based sample. The Minnesota Heart Survey

Energy expenditure in leisure time physical activity was measured using the Minnesota Leisure Time Physical Activity Questionnaire in a probability sample of 25- to 74-year-old residents of the seven-county metropolitan area of Minneapolis-St. Paul, Minnesota. Geometric mean estimates of leisure time physical energy expenditure were 193 kcal per day for men and 111 kcal per day for women. Only 34% of men and 17% of women expended 2,000 kcal or more per week in leisure time physical activity. Energy expenditure, especially in heavy intensity activities, declined with age, more so for women than men. Significant associations were observed between leisure time physical activity, particularly heavy intensity activity, and other coronary heart disease risk factors. Greater heavy intensity activity was associated with higher education (r = 0.14 to 0.26), greater Type A behavior (r = 0.14 to 0.15), higher serum high density lipoprotein (HDL) cholesterol levels (r = 0.09 to 0.10), lower serum thiocyanate (r = 0.10 to -0.14), lower body mass index (r = -0.10 to -0.11), lower heart rate (r = -0.07 to -0.10), and lower systolic blood pressure (r = -0.06 to -0.09). Thus, although energy expenditure was generally low in this population, greater leisure time physical activity for the most part was associated with lower coronary risk factors.     

Single prediction equation for bioelectrical impedance analysis in adults aged 20--94 years

Existing equations for bioelectrical impedance analysis (BIA) are of limited use when subjects age or become overweight because these equations were developed in young, normal-weight subjects and are not valid in elderly or overweight people. The purpose of this study was to validate a single BIA equation in healthy white subjects aged 22--94 y with a body mass index between 17.0 and 33.8 kg/m(2). Healthy subjects (202 men and 141 women) aged 20--94 y were measured by two methods: fat-free mass (FFM) was measured by dual-energy x-ray absorptiometry (Hologic QDR-4500) and by a bioelectrical impedance analyzer (Xitron 4000B). Validity of BIA was assessed by double cross validation. Because correlations were high (r = 0.986--0.987) and prediction errors low, a single equation was developed using all subjects, as follows: FFM = -4.104 + (0.518 x height(2)/resistance) + (0.231 x weight) + (0.130 x reactance) + (4.229 x sex: men = 1, women = 0). FFM predicted with dual-energy x-ray absorptiometry was 54.0 +/- 10.7 kg. BIA-predicted FFM was 54.0 +/- 10.5 kg (r = 0.986, standard error of the estimate = 1.72 kg, technical error = 1.74 kg). In conclusion, the new Geneva BIA equation was valid for prediction of FFM in healthy adults aged 22--94 y with body mass indexes between 17.0 and 33.8 kg/m(2). Inclusion of reactance in the single prediction equation appeared to be essential for use of BIA equations in populations with large variations in age or body mass.     

Seasonal variation in total energy expenditure and physical activity in Dutch young adults

OBJECTIVE: The impact of season on energy expenditure and physical activity is not well quantified. This study focused on summer-winter differences in total energy expenditure (TEE) and physical activity. RESEARCH METHODS AND PROCEDURES: Twenty-five healthy Dutch young adults, living in an urban environment, were measured in the summer season and the winter season. TEE was measured using doubly labeled water, and sleeping metabolic rate (SMR) was measured during an overnight stay in a respiration chamber. Subsequently, the physical activity level (PAL = TEE/SMR) and activity-related energy expenditure [(0.9 x TEE) - SMR] were calculated. Maximal mechanical power (Wmax) was determined with an incremental test on a cycle ergometer. Body composition was measured with hydrostatic weighing and deuterium dilution using Siri's three-compartment model. RESULTS: There was no difference in TEE between seasons. PAL was higher in summer than in winter (1.87 +/- 0.22 vs. 1.76 +/- 0.18; p < 0.001), and the difference was higher for men than for women (0.20 +/- 0.14 vs. 0.05 +/- 0.16; p = 0.04). The difference in PAL between seasons was dependent on the initial activity level. There was a strong linear relation (R2 = 0.48) between PAL and physical fitness (Wmax/fat-free mass), but Wmax/fat-free mass did not change between seasons in response to the lower PAL in winter. DISCUSSION: The extent of the changes in PAL is of physiological significance, and seasonality in physical activity should be taken into account when studying physical activity patterns or relationships between physical activity and health.