Changes In Physical Activity Energy Expenditure Research Articles

The acute effects of diet-induced energy restriction on physical activity energy expenditure and basal metabolic rate in men and women with overweight and obesity

Reductions in physical activity energy expenditure (PAEE) and basal metabolic rate (BMR) have been proposed as factors that may hinder diet-induced body mass loss. Although diet-mediated changes in PAEE and BMR are subject to large inter-individual variability, research investigating the impact of sex on diet-induced modulation of PAEE and BMR is lacking. Therefore, this study examined the effect of a diet-induced energy restriction on PAEE and BMR in non-exercising overweight and obese men and women. Eleven women (Age: 25 ± 7 yr; BMI: 29.7 ± 4.2 kg/m2) and eight men (Age 29.6 ± 4.0 yr; BMI: 29.7 ± 4.0 kg/m2) completed a 29-day investigation. Assessment of physical activity (PA) (PAEE and step count), BMR, body composition, systolic (SBP) and diastolic (DBP) blood pressure and fasting blood glucose (FBG) occurred on days 1, 8, 15, 22 and 29. Between days 15–22, participants consumed a liquid diet formula equivalent to 50% of their total daily energy expenditure (TDEE). The effects of time, sex and their interaction on all variables were assessed through a two-way mixed model ANOVA. Both men and women achieved a modest 3% body mass loss at the end of the intervention week. An effect of time was detected for body mass (p < 0.001), BMI (p < 0.001), body fat % (p = 0.001), SBP (p = 0.007), DBP (p = 0.033) and BG (p < 0.001). There was a time and sex interaction for body mass (p = 0.002), BMI (p = 0.002) and body fat % (p = 0.043). Sex differences were only present for body fat % (p = 0.001) and BMR (p < 0.001). No main or interaction effects were present for PAEE and step count. In the present study, a 7-day diet-induced energy restriction of 50% did not elicit compensatory changes in PAEE and BMR in overweight and obese men and women. Findings suggest that it may be a viable short-term strategy to produce initial reductions in body mass and body fat %, with improvements in fasting blood glucose and resting blood pressure.

Activity Energy Expenditure, Sedentary Time, And Cardiometabolic Responses To An Exercise Intervention: The PAACE Study

Sedentary time (ST) and physical activity energy expenditure (PAEE) are associated with obesity and related comorbidities, especially among older men and women. Older African Americans (AA) may have lower PAEE, higher ST, and greater cardiometabolic health disparities than other racial/ethnic groups. Thus assessing effects of physical activity interventions that improve PAEE and ST on cardiometabolic risk factors (CMRF) within this group is important. PURPOSE: To evaluate the association between physical activity intervention associated PAEE and ST changes and CMRF responses to the intervention among older AA. METHODS: Fifty-six sedentary older (mean ± SD, 69.2 ± 3.4 years) AA were randomized to a physical activity group (PAG, n = 28) or successful aging group (SAG, n = 28) for 12 weeks. PAG participants attended twice-weekly physical activity group sessions at a local YMCA. In addition, the PAG participants exercised 2-3 days per week at home for a total of 150 minutes of MVPA per week. The SAG participants attended weekly educational sessions on general aging topics not related to physical activity. Accelerometers worn on the waist before and during the last week of intervention were used to calculate PAEE and ST using 60-second epoch. Body mass index, fasted glucose (GLU), high density lipoprotein (HDL), low density lipoprotein (LDL), triglycerides, and blood pressure were collected before and after the intervention to assess cardiometabolic risk. Linear regression was used to test the association between PAEE and ST changes and CMRF. RESULTS: PAEE and ST change were not different between PAG and SAG participants (PAEE: 45.5 ± 149.1 vs. 10.9 ± 79.5 kcal/d resp., p = 0.298; ST: 41.6 ± 149.6 vs. -10.6 ± 122.9 min/d resp., p = 0.169). Baseline CMRF were not different between PAG and SAG participants (all p > 0.05). Change in PAEE was not associated with change in any CMRF within PAG participants (all p > 0.161). A decrease in ST was associated with an increase in HDL (F[1, 26] = 7.380, p = 0.012, R2 = 0.221) and a marginally significant decrease in GLU (F[1, 26] = 3.162, p = 0.087, R2 = 0.108) within PAG participants. CMRF changes were not related to PAEE change (all p > 0.159) or ST change (all p > 0.123) for SAG. CONCLUSIONS: The PAG may not have received sufficient stimulus to improve PAEE and ST, thus preventing more robust changes in CMRF.

Breakfast Consumption Suppresses Appetite but Does Not Increase Daily Energy Intake or Physical Activity Energy Expenditure When Compared with Breakfast Omission in Adolescent Girls Who Habitually Skip Breakfast: A 7-Day Randomised Crossover Trial

With concerns that adolescent girls often skip breakfast, this study compared the effects of breakfast consumption versus breakfast omission on free-living physical activity (PA) energy expenditure (PAEE) and dietary intakes among adolescent girls classified as habitual breakfast skippers. The participants went through two 7-day conditions in a trial with a crossover design: daily standardised breakfast consumption (energy content: 25% of resting metabolic rate) before 09:00 (BC) and daily breakfast omission (no energy-providing nutrients consumed) until 10:30 (BO). Free-living PAEE, dietary intakes, and perceived appetite, tiredness, and energy levels were assessed. Analyses were linear mixed models. Breakfast manipulation did not affect PAEE or PA duration. Daily fibre intake was higher (p = 0.005; d = 1.31), daily protein intake tended to be higher (p = 0.092; d = 0.54), post-10:30 carbohydrate intake tended to be lower (p = 0.096; d = 0.41), and pre-10:30 hunger and fullness were lower and higher, respectively (p ≤ 0.065; d = 0.33–1.01), in BC versus BO. No other between-condition differences were found. Breakfast-skipping adolescent girls do not compensate for an imbalance in energy intake caused by breakfast consumption versus omission through subsequent changes in PAEE but may increase their carbohydrate intakes later in the day to partially compensate for breakfast omission. Furthermore, breakfast can make substantial contributions to daily fibre intake among adolescent girls.

Change of energy expenditure from physical activity is the most powerful determinant of improved insulin sensitivity in overweight patients with coronary artery disease participating in an intensive lifestyle modification program

The objective was to evaluate the determinants of change (Δ) in insulin sensitivity in overweight coronary artery disease male patients without diabetes after an intensive lifestyle intervention. All patients received nutritional counseling and performed 4 months of exercise training (ET) according to 1 of 2 protocols: aerobic ET (65%-70% of peak aerobic capacity [VO2]) 25 to 40 minutes 3 times a week (n = 30) or walking (50%-60% of peak VO2) 45 to 60 minutes at least 5 times a week (n = 30). Data from participants of both ET groups were pooled, and post–intensive lifestyle intervention results were compared with baseline data. The primary outcome was Δ insulin sensitivity (m-value) assessed by the criterion standard technique, the euglycemic-hyperinsulinemic clamp. Changes in weight, body mass index, total and percentage fat mass (by dual-energy x-ray absorptiometry scan), waist circumference, total abdominal and visceral fat (by computed tomographic scan), high-sensitivity C-reactive protein, peak VO2, daily energy intake, and physical activity energy expenditure (PAEE) (by doubly labeled water technique) were also assessed. Daily energy intake decreased by 335 kcal, and PAEE increased by 482 kcal/d (all P < .0001). The mean weight loss was 6.4 kg, and the mean improvement in m-value was 1.6 mg/kg fat-free mass per minute. Univariate determinants of Δ m-value were low baseline PAEE, walking protocol, Δ weight, Δ body mass index, Δ total and percentage fat mass, Δ waist circumference, Δ total abdominal and visceral fat, and Δ PAEE (all P < .05). In multivariate analysis, the only significant determinant of Δ m-value was Δ PAEE (P < .02). In this analysis, the most powerful determinant of improved insulin sensitivity in overweight coronary artery disease patients is the change in PAEE.

Effects of an 8-Month Exercise Training Program on Off-Exercise Physical Activity

An active lifestyle is widely recognized as having a beneficial effect on cardiovascular health. However, no clear consensus exists as to whether exercise training increases overall physical activity energy expenditure (PAEE) or whether individuals participating in regular exercise compensate by reducing their off-exercise physical activity. The purpose of this study was to evaluate changes in PAEE in response to aerobic training (AT), resistance training (RT), or combined aerobic and resistance training (AT/RT). Data are from 82 participants in the Studies of Targeted Risk Reduction Interventions through Defined Exercise-Aerobic Training versus Resistance Training study, a randomized trial of overweight (body mass index = 25-35 kg·m(-2)) adults, in which participants were randomized to receive 8 months of AT, RT, or AT/RT. All subjects completed a 4-month control period before randomization. PAEE was measured using triaxial RT3 accelerometers, which subjects wore for a 5- to 7-d period before and after the exercise intervention. Data reduction was performed with a previously published computer-based algorithm. There was no significant change in off-exercise PAEE in any of the exercise training groups. We observed a significant increase in total PAEE that included the exercise training, in both AT and AT/RT but not in RT. Eight months of exercise training was not associated with a compensatory reduction in off-exercise physical activity, regardless of exercise modality. The absence of compensation is particularly notable for AT/RT subjects, who performed a larger volume of exercise than did AT or RT subjects. We believe that the extended duration of our exercise training program was the key factor in allowing subjects to reach a new steady-state level of physical activity within their daily lives.

Urbanization, Physical Activity, and Metabolic Health in Sub-Saharan Africa

OBJECTIVEWe examined the independent associations between objectively measured free-living physical activity energy expenditure (PAEE) and the metabolic syndrome in adults in rural and urban Cameroon.RESEARCH DESIGN AND METHODSPAEE was measured in 552 rural and urban dwellers using combined heart rate and movement sensing over 7 continuous days. The metabolic syndrome was defined using the National Cholesterol Education Program-Adult Treatment Panel III criteria.RESULTSUrban dwellers had a significantly lower PAEE than rural dwellers (44.2 ± 21.0 vs. 59.6 ± 23.7 kJ/kg/day, P < 0.001) and a higher prevalence of the metabolic syndrome (17.7 vs. 3.5%, P < 0.001). In multivariate regression models adjusted for possible confounders, each kJ/kg/day of PAEE was associated with a 2.1% lower risk of prevalent metabolic syndrome (odds ratio 0.98, P = 0.03). This implies a 6.5 kJ/kg/day difference in PAEE, equivalent to 30 min/day of brisk walking, corresponds to a 13.7% lower risk of prevalent metabolic syndrome. The population attributable fraction of prevalent metabolic syndrome due to being in the lowest quartile of PAEE was 26.3% (25.3% in women and 35.7% in men).CONCLUSIONSUrban compared with rural residence is associated with lower PAEE and higher prevalence of metabolic syndrome. PAEE is strongly independently associated with prevalent metabolic syndrome in adult Cameroonians. Modest population-wide changes in PAEE may have significant benefits in terms of reducing the emerging burden of metabolic diseases in sub-Saharan Africa.

Who will increase their physical activity? Predictors of change in objectively measured physical activity over 12 months in the ProActive cohort

BackgroundThe aim was to identify predictors of change in objectively measured physical activity over 12 months in the ProActive cohort to improve understanding of factors influencing change in physical activity.MethodsProActive is a physical activity promotion trial that took place in Eastern England (1999-2004). 365 offspring of people with type 2 diabetes underwent measurement of physical activity energy expenditure (PAEE) using heart rate monitoring, fitness, and anthropometric and biochemical status at baseline and 1 year (n = 321). Linear regression was used to quantify the associations between baseline demographic, clinical, psychosocial and behavioural variables and change in PAEE over 12 months. This study is registered as ISRCTN61323766.ResultsProActive participants significantly increased their PAEE by 0.6 kj/min (SD 4.2, p = 0.006) over one year, the equivalent of around 20 minutes brisk walking/day. Male sex and higher fitness at baseline predicted increase in PAEE. No significant associations were found for any other variables. Very few baseline demographic, clinical, psychosocial and behavioural predictors were associated with change in objectively measured physical activity.ConclusionsTraditional baseline determinants of self-reported physical activity targeted by behavioural interventions may be relatively weak predictors of change in objectively measured physical activity. Further research is needed to improve our understanding of factors influencing change in physical activity to inform the development and targeting of interventions.

Increasing overall physical activity and aerobic fitness is associated with improvements in metabolic risk: cohort analysis of the ProActive trial

Aims/hypothesisOur aim was to examine the association between change in physical activity energy expenditure (PAEE), total body movement (counts per day) and aerobic fitness (maximum oxygen consumption [{mathop {text{V}}limits^{text{.}} }{text{O}}_{{2max }} ]) over 1 year and metabolic risk among individuals with a family history of diabetes.MethodsThree hundred and sixty-five offspring of people with type 2 diabetes underwent measurement of energy expenditure (PAEE measured using the flex heart rate method), total body movement (daily activity counts from accelerometry data), {mathop {text{V}}limits^{text{.}} }{text{O}}_{{2max }} predicted from a submaximal graded treadmill exercise test and anthropometric and metabolic status at baseline and 1 year (n = 321) in the ProActive trial. Clustered metabolic risk was calculated by summing standardised values for waist circumference, fasting triacylglycerol, insulin and glucose, blood pressure and the inverse of HDL-cholesterol. Linear regression was used to quantify the association between changes in PAEE, total body movement and fitness and clustered metabolic risk at follow-up.ResultsParticipants increased their activity by 0.01 units PAEE kJ kg−1 day−1 over 1 year. Total body movement increased by an average of 9,848 counts per day. Change in total body movement (β = −0.066, p = 0.004) and fitness (β = −0.056, p = 0.003) was associated with clustered metabolic risk at follow-up, independently of age, sex, smoking status, socioeconomic status and baseline metabolic score.Conclusions/interpretationSmall increases in activity and fitness were associated with a reduction in clustered metabolic risk in this cohort of carefully characterised at-risk individuals. Further research to quantify the reduction in risk of type 2 diabetes associated with feasible changes in these variables should inform preventive interventions.Clinical trial registration number: ISRCTN61323766.

Physical Activity Energy Expenditure Decreases During a 5-Month Calorie Deficit Diet in Obese, Postmenopausal Women

Spontaneous physical activity energy expenditure (PAEE) is the most variable component of daily EE and is likely affected by alterations in energy intake. PURPOSE: To determine: 1) whether PAEE decreases in response to 5-month caloric restriction in middle-aged women, and 2) whether individual changes in PAEE are related to the magnitude of weight lost. METHODS: PAEE (RT3 monitor for 5–7 days) was measured monthly during a 5-month underfeeding intervention (400 kcal/day calorie deficit) in 19 postmenopausal obese/overweight (body mass index 33.6 ± 3.8 kg/m2) women (58 ± 6 years). Latent growth curve was used to test the slope of the line of PAEE values against time. Pearson's correlations between changes in PAEE and body weight were calculated. RESULTS: The average total weight loss during the 5-month intervention was 9.6 ± 2.6 kg (10.4 ± 2.6 %). Mean levels of PAEE decreased during the intervention (see table) and the rate of decrease over time (∼ 0.74 ± 0.26 kcals/day) was significant (p = 0.002). PAEE per kilogram of body weight (6.0 ± 1.5 to 5.5 ± 2.0 kcal/kg) remained unchanged (p=0.75, paired t-test comparing month 0 to 5). Individual changes in PAEE for each sequential month did not correlate with individual monthly weight loss with the exception of month 4 vs. month 3 (p=0.78, 0.34, 0.69, 0.03, and 0.17, for each month respectively). Likewise, there was no relationship between overall changes (month 0 to 5) in PAEE and body weight (p=0.26).TableCONCLUSION: In postmenopausal women, PAEE declines in response to an energy deficit induced by underfeeding; however, the magnitude of this decline was not related to the amount of weight lost. Thus, behavioral strategies designed to promote spontaneous daily physical activity may need to be implemented during dietary treatments for weight loss to override this compensatory decrease in PAEE. Supported by NIH grants R01-AG/DK20583 and the WFU GCRC (M01-RR07122)

Associations Between Change in Physical Activity Energy Expenditure, Aerobic Fitness and Body Fatness with Cardiovascular Disease Risk Factors

Low levels of physical activity and aerobic fitness are consistently associated with an increased risk of cardiovascular disease (CVD). Numerous studies have also shown that obesity indicators (BMI, waist circumference, waist-to-hip ratio, and waist-to-height ratio) are associated with CVD risk factors. However, it is uncertain whether change in physical activity is associated with CVD risk factors and whether this association is independent of change in aerobic fitness and body fatness. PURPOSE: To examine the associations between change in physical activity energy expenditure (PAEE), aerobic fitness and body fatness with CVD risk factors. METHODS: In a population-based sample of 393 men (n = 176) and women followed prospectively for 5.6 years, we measured PAEE by individually calibrated heart rate monitoring, maximal aerobic fitness (VO2max estimated from a graded exercise test), waist circumference, total body fat (by bio impedance) and eight established CVD risk factors (total cholesterol, HDL cholesterol, LDL cholesterol, triglycerides, insulin, 2-h glucose, systolic and diastolic blood pressure) at baseline and follow-up. RESULTS: Change in PAEE was significantly and inversely associated with fasting triglycerides (B = −0.69; P = 0.028), insulin (B = − 1.14; P = 0.015) and 2-h glucose (B = −0.57; P = 0.027) at follow-up, after adjusting for sex, age, smoking status, baseline phenotype, aerobic fitness and body fatness (waist circumference or total body fat). These associations were materially unchanged after adjustment for change in aerobic fitness and body fatness (P <0.05). However, change in body fatness was consistently associated with change in all CVD risk factors, except for HDL-cholesterol, independently of change in PAEE and aerobic fitness (P <0.02). CONCLUSIONS: Change in physical activity level is inversely associated with insulin resistance, glucose intolerance and hyperlipidemia, independent of change in aerobic fitness and body fatness. This may have implications for cardiovascular risk reduction as increasing levels of physical activity may have protective effects without improvements in aerobic fitness, and reduced body fat mass. However body fatness was more strongly related to CVD risk factors than physical activity. Therefore, the combination of increasing levels of physical activity and avoidance of unhealthy weight gain is likely to be the most successful approach for the prevention of cardiovascular disease.