Free-living Physical Activity Levels Research Articles

The effect of metformin treatment on volumes of free-living physical activity and sedentary behaviour: A post-hoc analysis of the PRE-D trial

ABSTRACT Perceived physical exertion is increased when exercise is performed on metformin treatment, but the clinical relevance of this is unknown. In this post hoc analysis of a randomized, controlled trial, we investigated whether metformin treatment was associated with lower levels of free-living physical activity. Ninety individuals with overweight/obesity (BMI>25 m2/kg) and HbA1c-defined prediabetes (39-47 mmol/mol) were randomized to treatment with dapagliflozin (SGLT2-inhibitor; 10 mg once daily, n=30), metformin (850 mg twice daily, n=30) or no treatment (control, n=30) for 13 weeks in a parallel-group, open-label trial. Before (baseline), during (6 weeks) and immediately after (13 weeks) cessation of treatment, a 6-day assessment of physical activity and sedentary behaviour was performed using accelerometer-based physical activity monitors. Intention-to-treat analyses revealed no within-group changes or differences in change between the groups for any measures of physical activity or sedentary behaviour at neither 6 nor 13 weeks. Short-term metformin treatment does not reduce free-living physical activity level in individuals with overweight/obesity and HbA1c-defined prediabetes.

Brief report: Free-living physical activity levels and cognitive control in multi-problem young adults

Previous studies indicate a positive association between physical activity and cognitive control in sedentary but healthy adults, yet not much is known about physical activity levels in multi-problem young adults. We examined the level of self-reported free-living physical activity (i.e., MET minutes per week) in an ecologically valid sample of young adults facing multiple problems, including unemployment, lack of education, frequent substance use, and history of delinquency. We compared cognitive control with an age- and sex-matched control sample. Additionally, the association between physical activity and cognitive control (i.e., response inhibition, error processing, interference effect) in the multi-problem group was examined. Physical activity and cognitive control were measured with the International Physical Activity Questionnaire-Long Form and three cognitive control experiments (i.e., Flanker, Go/NoGo, Stroop), respectively. With M = 4428 Metabolic Equivalents (METs), our multi-problem sample (n = 63) showed physical activity levels similar to the age- and sex-matched control sample from the general population (n = 62). The multi-problem young adults also showed impaired cognitive control indexed as decreased response inhibition and decreased Flanker correctness effect compared to their peers. We could not find an association between self-reported physical activity and cognitive control in the multi-problem sample. Due to the small sample size, results should be interpreted with caution. However, future dose-response studies could still use these results to further examine if within-individual increased physical activity may possibly lead to improved cognitive control in (already relatively active) multi-problem young adults.

Comparison of Child and Adolescent Physical Activity Levels From Open-Source Versus ActiGraph Counts

ActiGraph counts are commonly used for characterizing physical activity intensity and energy expenditure and are among the most well-studied accelerometer metrics. Researchers have recently replicated the counts processing method using a mechanical setup, now allowing users to generate counts from raw acceleration data. Purpose: The purpose of this study was to compare ActiGraph-generated counts to open-source counts and assess the impact on free-living physical activity levels derived from cut points, machine learning, and two-regression models. Methods: Children (n = 488, 13.0 ± 1.1 years of age) wore an ActiGraph wGT3X-BT on their right hip for 7 days during waking hours. ActiGraph counts and counts generated from raw acceleration data were compared at the epoch-level and as overall means. Seven methods were used to classify overall and epoch-level activity intensity. Outcomes were compared using weighted kappa, correlations, mean absolute deviation, and two one-sided equivalence testing. Results: All outcomes were statistically equivalent between ActiGraph and open-source counts; weighted kappa was ≥.971 and epoch-level correlations were ≥.992, indicating very high agreement. Bland–Altman plots indicated differences increased with activity intensity, but overall differences between ActiGraph and open-source counts were minimal (e.g., epoch-level mean absolute difference of 23.9 vector magnitude counts per minute). Regardless of classification model, average differences translated to 1.4–2.6 min/day for moderate- to vigorous-intensity physical activity. Conclusion: Open-source counts may be used to enhance comparability of future studies, streamline data analysis, and enable researchers to use existing developed models with alternative accelerometer brands. Future studies should verify the performance of open-source counts for other outcomes, like sleep.

Physical Activity and Cardiac Self-Efficacy Levels During Early Recovery After Acute Myocardial Infarction: A Jordanian Study.

ABSTRACTBackgroundRegular physical activity is important for patients with established coronary heart disease as it favorably influences their coronary risk profile. General self-efficacy is a powerful predictor of health behavior change that involves increases in physical activity levels. Few studies have simultaneously measured physical activity and self-efficacy during early recovery after a first acute myocardial infarction (AMI).PurposeThe aims of this study were to assess changes in objectively measured physical activity levels at 2 weeks (T2) and 6 weeks (T3) and self-reported cardiac self-efficacy at hospital discharge (T1) and at T2 and T3 in patients recovering from AMI.MethodsA repeated-measures design was used to recruit a purposive sample of patients from a single center in Jordan who were diagnosed with first AMI and who did not have access to cardiac rehabilitation. A body-worn activity monitor (activPAL) was used to objectively measure free-living physical activity levels for 7 consecutive days at two time points (T2 and T3). An Arabic version of the cardiac self-efficacy scale was administered at T1, T2, and T3. Paired t tests and analysis of variance were used to examine differences in physical activity levels and cardiac self-efficacy scores, respectively.ResultsA sample of 100 participants was recruited, of which 62% were male. The mean age of the sample was 54.5 ± 9.9 years. No statistically significant difference in physical activity levels was measured at 2 weeks (T2) and 6 weeks (T3). Cardiac self-efficacy scores improved significantly between T1, T2, and T3 across subscales and global cardiac self-efficacy.Conclusions/Implications for PracticeParticipants recovering from AMI in Jordan did not increase their physical activity levels during the early recovery phase, although cardiac self-efficacy scores improved. This may be because the increase in cardiac self-efficacy was not matched by the practical skills and knowledge required to translate this positive psychological construct into behavioral change. This study provides a first step toward understanding the complex relationship between cardiac self-efficacy and physical activity in this population. The authors hope that these findings support the design of culturally appropriate interventions to increase physical activity levels in this population.

Comparing Daily Class Schedule and its Influence on Undergraduate Students’ Physical Activity Patterns

Full-time undergraduate students’ daily physical activity patterns may be affected due to Penn State University’s different class schedules -Monday/Wednesday/Friday (M/W/F) and Tuesday/Thursday (T/Th). A no class period (common hour: 1:00pm-2:30pm) on M/W/F is offered as scheduled breaks in the academic course schedule for student activities at different Penn State University Commonwealth campuses. PURPOSE: To objectively determine the differences in daily step count and energy expenditure of Kinesiology students on different days of the week. METHODS: Sixty eight (35M/33F, 21.6±2.9 years, average BMI 25.9±5.2 kg/m2) apparently healthy juniors and seniors were recruited from the Penn State Berks. A wrist-worn activity-tracker was deployed for one week to assess students’ free-living physical activity levels. RESULTS: M/W/F vs. T/Th (Mean±SD) step count (10387 ± 3560 vs. 9268 ± 2899 steps/day; p=0.015) and activity calories (1056.4±535.2 vs. 963.5±608.3 kcal/day; p=0.097) were measured. Students were most active on Mondays (10691±4531 steps/day) compared to the rest of the week. CONCLUSION: Students achieved the recommended 10,000 steps daily goal on M/W/F and did not meet the step goal on T/Th. This difference in steps could be attributed to the mandatory no class ‘common hour’ which may allow students to be more physically active than the T/Th schedule. In addition, the shorter class structure on M/W/F (50 min/class) might also provide opportunities for students to be more active than T/Th (75 min/class). These preliminary results may be useful for planning early physical activity interventions on specific days of the week among college students.

Heart rate variability, adiposity, and physical activity in prepubescent children.

This study aimed at examining the associations between weight status, body fat mass, and heart rate variability in prepubescent children, adjusting for physical activity levels. A cross-sectional investigation in which a total of 50 Caucasian pre-pubertal children (21 normal weight; 8 overweight; 21 obese), aged 6-10years (8.33±1.14), including both boys (n=24) and girls (n=26), were recruited from local schools. Total body fat and trunk fat were evaluated through dual-energy X-ray absorptiometry. Free-living physical activity levels were evaluated by accelerometer. Short-term heart rate variability acquisition was performed; time- and frequency-domain parameters were analysed. Logarithmic transformations of the low-frequency (LnLFnu), high-frequency (LnHFnu) normalized units and low-frequency/high-frequency (LnLFnu/HFnu) ratio were computed. Adjusting for age, Tanner stage, and moderate to vigorous physical activity levels, obese children compared to normal weight children showed a significant decreased LnHfnu (3.8±0.2 vs 4.1±0.2%) and both higher LnLFnu (4.0±0.4 vs 3.7±0.3%) and LnLFnu/LnHFnu ratio (1.1±0.1 vs 0.9±0.1). LnHFnu showed significant negative correlation with waist circumference (r=-0.598; P=0.000), total body fat (r=-0.409; P=0.011) and trunk fat (r=-0.472; P=0.003). Both LnLFnu and LnLFnu/LnHFnu ratio showed positive correlations with waist circumference (r=0.455; r=0.513) and trunk fat (r=0.370; r=0.415). A higher amount of body fat mass, particularly central fat, was shown to be related to decreased parasympathetic modulation in time-domain heart rate variability. This finding highlights the potential cardiovascular risk that excessive fat mass may represent even at very young age.

Quantifying Physical Activity Levels of Survivors of Intensive Care: A Prospective Observational Study

Promotion of increased physical activity is advocated for survivors of an intensive care unit (ICU) admission to improve physical function and health-related quality of life. The primary aims of this study were: (1) to measure free-living physical activity levels and (2) to correlate the measurements with scores on a self-reported activity questionnaire. A secondary aim was to explore factors associated with physical activity levels. This was a prospective cohort study. Nested within a larger randomized controlled trial, participants were block randomized to measure free-living physical activity levels. Included participants wore an accelerometer for 7 days during waking hours at 2 months after ICU discharge. At completion of the 7 days of monitoring, participants were interviewed using the Physical Activity Scale for the Elderly (PASE) questionnaire. Factors associated with physical activity were explored using regression analysis. The ICU survivors (median age=59 years, interquartile range=49-66; mean Acute Physiologic Chronic Health Evaluation [APACHE II] score=18, interquartile range=16-21) were inactive when quantitatively measured at 2 months after hospital discharge. Participants spent an average of 90% of the time inactive and only 3% of the time walking. Only 37% of the sample spent 30 minutes or more per day in the locomotion category (more than 20 steps in a row). Activity reported using the PASE questionnaire was lower than that reported in adults who were healthy. The PASE scores correlated only fairly with activity measured by steps per day. The presence of comorbidities explained one third of the variance in physical activity levels. Accelerometer overreading, patient heterogeneity, selection bias, and sample size not reached were limitations of the study. Survivors of an ICU admission greater than 5 days demonstrated high levels of inactivity for prolonged periods at 2 months after ICU discharge, and the majority did not meet international recommendations regarding physical activity. Comorbidity appears to be a promising factor associated with activity levels.

How much locomotive activity is needed for an active physical activity level: analysis of total step counts.

BackgroundAlthough physical activity recommendations for public health have focused on locomotive activity such as walking and running, it is uncertain how much these activities contribute to overall physical activity level (PAL). The purpose of the present study was to determine the contribution of locomotive activity to PAL using total step counts measured in a calorimeter study.MethodsPAL, calculated as total energy expenditure divided by basal metabolic rate, was evaluated in 11 adult men using three different conditions for 24-hour human calorimeter measurements: a low-activity day (L-day) targeted at a low active level of PAL (1.45), and a high-frequency moderate activity day (M-day) or a high-frequency vigorous activity day (V-day) targeted at an active level of PAL (1.75). These subjects were permitted only light activities except prescribed activities. In a separate group of 41 adults, free-living PAL was evaluated using doubly-labeled water (DLW). In both experiments, step counts per day were also measured using an accelerometer.ResultsIn the human calorimeter study, PAL and step counts were 1.42 ± 0.10 and 8,973 ± 543 steps/d (L-day), 1.82 ± 0.14 and 29,588 ± 1,126 steps/d (M-day), and 1.74 ± 0.15 and 23,755 ± 1,038 steps/d (V-day), respectively. In the DLW study, PAL and step counts were 1.73 ± 0.15 and 10,022 ± 2,605 steps/d, and there was no significant relationship between PAL and daily step counts.ConclusionsThese results indicate that an enormous number of steps are needed for an active level of PAL if individuals extend physical activity-induced energy expenditure by only locomotive activity. Therefore, non-locomotive activity such as household activity should also play a significant role in increasing PAL under free-living conditions.

Effect of calorie restriction on the free-living physical activity levels of nonobese humans: results of three randomized trials

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 protocols. Participants were nonobese (body mass index = 23.5-29.9 kg/m² adults randomly 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.

Effect of Calorie Restriction on Resting Metabolic Rate and Spontaneous Physical Activity

It is unclear if resting metabolic rate (RMR) and spontaneous physical activity (SPA) decrease in weight-reduced non-obese participants. Additionally, it is unknown if changes in SPA, measured in a respiratory chamber, reflect changes in free-living physical activity level (PAL). Participants (N = 48) were randomized into 4 groups for 6 months: calorie restriction (CR, 25% restriction), CR plus structured exercise (CR+EX, 12.5% restriction plus 12.5% increased energy expenditure via exercise), low-calorie diet (LCD, 890 kcal/d supplement diet until 15% weight loss, then weight maintenance), and control (weight maintenance). Measurements were collected at baseline, Month 3, and Month 6. Body composition and RMR were measured by DXA and indirect calorimetry, respectively. Two measures of SPA were collected in a respiratory chamber (percent of time active and kcal/d). Free-living PAL (PAL = total daily energy expenditure by doubly labeled water/RMR) was also measured. Regression equations at baseline were used to adjust RMR for fat-free mass and SPA (kcal/d) for body weight. Adjusted RMR decreased at Month 3 in the CR group and at Month 6 in the CR+EX and LCD groups. Neither measure of SPA decreased significantly in any group. PAL decreased at Month 3 in the CR and LCD groups, but not in the CR+EX group, who engaged in structured exercise. Changes in SPA in the chamber and free-living PAL were not related. Body weight is defended in non-obese participants during modest caloric restriction, evidenced by metabolic adaptation of RMR and reduced energy expenditure through physical activity.

Dopamine D2 Receptor Genotypes And Physical Activity Levels

PURPOSE Dopamine influences physical activity via effects on motor control and motivation. Reduced D2 density has been associated with reduced physical activity. The DRD2 A1 allele is associated with reduced D2 receptors; therefore, this genotype may be associated with a more sedentary lifestyle. We examined the relationship between DRD2 genotypes and objectively measured physical activity and physical fitness. METHODS 31 adult subjects (18 males- mean age 45y; 13 females-mean age 48y) who had DRD2genotyping performed a submaximal cycle ergometer test to estimate aerobic fitness. Subjects walked on a treadmill wearing an accelerometer at an exercise intensity of 3 Mets to determine the accelerometer g value associated with each subject's moderate to vigorous physical activity level (MVPA, ≥3 Mets). They then wore the accelerometers for 2 weekdays and one weekend day to determine free-living physical activity levels. Group differences in physical activity and aerobic fitness were analyzed using a 2 sex × 2 genotype ANOVA. RESULTS Females with an A1 allele engaged in 33% less physical activity than females without an A1 allele (866.2±120.0 vs. 1291.0±96.0 min, p=0.01) due to less low intensity (< 3 Mets) physical activity (766.8±100.9 vs. 1150.1±80.1 min, p=0.005). There was no effect of genotype on MVPA or fitness in females. There was no effect of DRD2 genotype on male total activity time, low intensity physical activity, MVPA or fitness. CONCLUSIONS Females with a dopamine D2 receptor genotype that is associated with fewer D2 receptors have lower objectively measured physical activity levels than females with a genotype associated with a greater number of D2 receptors.

Dopamine D2 Receptor Genotypes And Physical Activity Levels

PURPOSE Dopamine influences physical activity via effects on motor control and motivation. Reduced D2 density has been associated with reduced physical activity. The DRD2 A1 allele is associated with reduced D2 receptors; therefore, this genotype may be associated with a more sedentary lifestyle. We examined the relationship between DRD2 genotypes and objectively measured physical activity and physical fitness. METHODS 31 adult subjects (18 males- mean age 45y; 13 females-mean age 48y) who had DRD2genotyping performed a submaximal cycle ergometer test to estimate aerobic fitness. Subjects walked on a treadmill wearing an accelerometer at an exercise intensity of 3 Mets to determine the accelerometer g value associated with each subject's moderate to vigorous physical activity level (MVPA, ≥3 Mets). They then wore the accelerometers for 2 weekdays and one weekend day to determine free-living physical activity levels. Group differences in physical activity and aerobic fitness were analyzed using a 2 sex × 2 genotype ANOVA. RESULTS Females with an A1 allele engaged in 33% less physical activity than females without an A1 allele (866.2±120.0 vs. 1291.0±96.0 min, p=0.01) due to less low intensity (< 3 Mets) physical activity (766.8±100.9 vs. 1150.1±80.1 min, p=0.005). There was no effect of genotype on MVPA or fitness in females. There was no effect of DRD2 genotype on male total activity time, low intensity physical activity, MVPA or fitness. CONCLUSIONS Females with a dopamine D2 receptor genotype that is associated with fewer D2 receptors have lower objectively measured physical activity levels than females with a genotype associated with a greater number of D2 receptors.