Effect of calorie restriction on the free-living physical activity levels of nonobese humans: results of three randomized trials. The influence of physical activity-induced energy expenditure on the variance in body weight change among individuals during a diet intervention. Weight-Loss Induced Changes in Physical Activity and Activity Energy Expenditure in Overweight and Obese Subjects before and after Energy Restriction Accelerometer prediction of energy expenditure: vector magnitude versus vertical axis. Role of physical activity and sleep duration in growth and body composition of preschool-aged children. Relationships between physical activity, physical fitness, muscle strength and nutritional state in 5- to 11-year-old children
The objective of this study was to evaluate the influence of calorie restriction ( CR ) on free-living physical activity levels among humans . Data were from three CALERIE phase I site-specific protocol s. Participants were nonobese ( body mass index = 23.5 - 29.9 kg/m² adults r and omly assigned to 25 % CR , low-calorie diet ( LCD , 890 kcal/day supplement diet until 15 % weight loss , then weight maintenance ) , or control at Pennington Biomedical Research Center ( PBRC ) ; 30 % or 10 % CR  at Tufts University ; and 20 % CR or control  at Washington University School of Medicine ( WUSM )  . Activity was measured at months 0 , 3 , and 6 ( PBRC ) and at months 0 , 3 , 6 , 9 , and 12 ( WUSM and Tufts ) . Total daily energy expenditure ( TEE ) by doubly labeled water and resting metabolic rate ( RMR ) were used to compute activity energy expenditure : AEE = TEE - RMR - 0.1 * TEE . Accelerometry and 7-day recall categorized activities by intensity . At Tufts , the 10 % and 30 % CR groups experienced significant decreases in AEE at months 6 , 9 , and 12 . At month 6 , a larger decrease in AEE was observed in the CR than the control group at WUSM . At months 3 and 6 , larger decreases in AEE were observed in the CR and LCD groups than the control group at PBRC . Accelerometry and 7-day PAR did not consistently detect changes in activity categories . CR-associated changes in AEE were variable but , generally , reduced the energy deficit , which would reduce the expected rate of weight loss . Accelerometry and recall did not consistently explain reduced AEE , suggesting that increased muscle efficiency and /or decreased fidgeting accounted for decreased AEE . Inaccuracy of accelerometry and recall also likely negatively affected sensitivity SUMMARY OBJECTIVE We investigated the relationship between the variability in body weight change among individuals and diet restriction or physical activity during a 14-week intervention . DESIGN A prospect i ve clinical trial with a 14-week weight reduction intervention design . In total , 90 middle aged , Japanese , obese women enrolled as subjects . MEASUREMENTS The outcome variable was the change in body weight during the intervention period . Other primary variables were total energy intake , carbohydrate intake , fat intake , protein intake , total energy expenditure ( TEE ) , and activity energy expenditure ( AEE ) . Diet intake  was assessed by 3 days , weighed dietary records and dietary recall interviews . Physical activity  was assessed by a uniaxial accelerometry sensor and a diary of exercise . RESULTS Significant reductions were observed in body weight ( -8.5 kg ) as a result of intervention . When the subjects were assigned to three categories depending on AEE during intervention , the loss of body weight was significantly greater for subjects within the upper ( -9.6 kg ) AEE category than for those in the middle ( -8.5 kg ) or lower AEE ( -7.5 kg ) categories . In addition , a significant correlation ( r = 0.57 , p < 0.0001 ) was observed between a subject 's AEE before and during the intervention . On the other h and , no significant correlation was observed between body weight reduction and energy intake , indicating that strict diet restriction does not always result in a large weight loss . CONCLUSION Activity energy expenditure , not only through voluntary exercise but also through spontaneous , daily , physical activities can have a positive effect on reducing body weight 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 aim ed 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 vali date d 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 dem and 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 UNLABELLED It is suggested that triaxial accelerometers ( RT3 ) are superior to single-plane accelerometers for predicting energy expenditure ( EE ) . PURPOSE To compare the RT3 uniaxial and triaxial prediction of activity EE ( AEE ) during treadmill activities ( TM ) and activities of daily living ( ADL ) . METHODS Two hundred and twelve subjects ( aged 20 - 60 yr ) completed TM speeds of 1.34 , 1.56 , and 2.23 m x s(-1 ) at 0 % and 3 % grade s , stair ascent/descent , moving a box , and two r and omly assigned ADL . Subjects wore a portable indirect calorimeter to measure EE  to calculate AEE by subtracting resting metabolic rate . Acceleration counts in the vertical ( V ) , medial-lateral , and anterior-posterior planes were collected in a single RT3 secured to the hip . Predicted AEE ( RT3AEE ) was estimated from vector magnitude ( VM ) counts using a proprietary algorithm . A paired t-test compared RT3AEE versus AEE . The relationship among V and VM counts and AEE was examined using linear regression analyses . RESULTS RT3 overestimated AEE for all activities combined , overestimated for TM ( 9.0 % ) , and underestimated for ADL ( 34.3 % ; P < 0.001 ) . The R2 values between RT3AEE and AEE for TM and ADL were R2 = 0.78 and R2 = 0.15 , respectively . The RT3 underestimated activity with greater upper body movements by 24.4%-64.5 % ( P < 0.001 ) . V and VM counts were similarly related to AEE ( R2 = 0.35 ) and RT3AEE ( R2 = 0.83 - 0.89 ) . CONCLUSIONS Although the RT3 did not accurately predict AEE from accelerometer counts , stronger relationships existed between predicted and measured AEE for TM compared with ADL . Compared with V counts , using VM counts to predict AEE did not significantly improve the relationship between counts and AEE . Analytic techniques beyond linear regression with VM as a covariate or with counts from each axis entering the model separately may improve estimates of AEE from triaxial accelerometers OBJECTIVE The impact of physical activity patterns and sleep duration on growth and body composition of preschool-aged children remains unresolved . Aims were ( 1 ) to delineate cross-sectional associations among physical activity components , sleep , total energy expenditure ( TEE ) , and body size and composition ; and ( 2 ) to determine whether physical activity components , sleep , and TEE predict 1-year changes in body size and composition in healthy preschool-aged children . METHODS Anthropometry , body composition , accelerometry , and TEE by doubly labeled water were measured at baseline ; anthropometry and body composition were repeated 1 year later ( n = 111 ) . RESULTS Cross-sectionally , positive associations between sedentary activity and weight and fat-free mass ( FFM ) ( P = 0.009 - 0.047 ) , and a negative association between moderate-vigorous physical activity ( MVPA ) and percent fat mass ( FM ) ( P = 0.015 ) were observed . TEE and activity energy expenditure ( AEE ) were positively associated with weight , body mass index ( BMI ) , FFM , and FM ( P = 0.0001 - 0.046 ) . Prospect ively , TEE , AEE , physical activity level , and MVPA , but not sedentary activity , were positively associated with changes in BMI ( P = 0.0001 - 0.051 ) and FFM ( P = 0.0001 - 0.037 ) , but not percent FM . Sleep duration inversely predicted changes in FM ( P = 0.005 ) and percent FM ( P = 0.006 ) . CONCLUSIONS Prospect ively , MVPA , TEE , AEE , and physical activity level promote normal growth and accretion of FFM , whereas sleep duration inversely predicts changes in adiposity in preschool-aged children Abstract The purpose of the present study was to assess different aspects of physical activity and fitness in order to develop a basis for sport programmes for overweight and obese children . Eighty-eight prepubertal children ( 49 boys , 39 girls , 4.8–11.4 years old , 61 % obese , 14 % overweight and 25 % normal weight ) were examined . Body composition was assessed by combined use of anthropometrics and bioelectrical impedance analysis . Resting energy expenditure ( REE ) and total energy expenditure ( TEE ) were measured by indirect calorimetry ( IC ) and individually calibrated 24-h heart rate ( HR ) monitoring , respectively . Activity-related energy expenditure ( AEE ) and physical activity level ( PAL )  were calculated from TEE and REE .  Fitness [ assessed by O2-pulse , respiratory exchange ratio ( RER ) at submaximal work intensities ] was determined by ergometry . The maximal isometric muscle strength of the legs ( m. quadriceps , Fa max , m. ischiocruralis , Fb max ) was measured by computer tensiometry .  Children were grouped according to their nutritional state , AEE , O2-pulse and muscle strength . When compared with normal weight children , obese and overweight children had increased fat mass ( FM ) , fat-free mass ( FFM ) , waist-to-hip ratio and REE , but no group differences were observed for TEE , AEE , and PAL . Obese and overweight children spent more hours per day watching TV  . After correction for body weight and FFM , no group differences in REE were observed , but normal weight children had a higher O2-pulse than overweight and obese children . By contrast , RER was increased in the latter group . The fittest group had the lowest body weight , BMI , FM and FFM . Children with a low O2-pulse spent more hours per day watching TV . Grouping children according to their degree of muscle strength , younger children ( 4–7.5 years ) did not show group differences in nutritional state , energy expenditure , physical activity and fitness . However , in the group of 7.6- to 11-year-old children , those with the greatest muscle strength and FFM had reduced BMI , skin folds , FM and FFM . FM correlated inversely with O2-pulse , but was not associated with TEE , AEE , PAL or muscle strength . By contrast TV consumption was positively associated with FM . To summarize , overweight and obese children were less fit and watched more TV than their normal weight counterparts . FM did not correspond to TEE , AEE or PAL . Muscle strength was not associated with FM in young children , but was inversely associated with FM in older children . Our cross-sectional data are consistent with the idea that increased fitness and reduced physical inactivity may prevent children from being overweight
Conclusions : We conclude that there is large heterogeneity across studies in the explained variance of AEE when estimated based on accelerometry .
Background / Objectives : Activity-related energy expenditure ( AEE ) might be an important factor in the etiology of chronic diseases .
However , measurement of free-living AEE is usually not feasible in large-scale epidemiological studies but instead has traditionally been estimated based on self-reported physical activity .