Little is known of the potential long term gait alterations that occur after an anterior cruciate ligament (ACL) reconstruction. In particular, variables such as impact loading which have been previously associated with joint deterioration have not been studied in walking and running after an ACL reconstruction. The purpose of this study was to define the alterations in impact forces, loading rates, and the accompanying sagittal plane kinematic and kinetic mechanics at the time of impact between the ACL reconstructed group and a healthy control group.
40 females (20 ACL reconstruction, 20 controls) participated in the study. An instrumented gait analysis was performed on all subjects. Between group and limb comparisons were made for initial vertical impact force, loading rate, sagittal plane knee and hip angles as well as moments.
During walking and running the ACL cohort had significantly greater initial vertical impact force (p=0.002 and p= 0.001), and loading rates (p=0.03 and p= 0.01), as well as a smaller knee extensor moment and hip angle during walking (p=0.000 and p=0.01). There was a trend towards a smaller knee moment and hip angle during running (p=0.08 and p=0.06) as well as a larger hip extensor moment during walking (p=0.06) in the ACL group. No differences were found for hip extensor moment during running, knee angles between groups during walking or running. Lastly, no between limb differences were found for any variable.
Gait deviations such as elevated impact loading and loading rates do not resolve long term after the individual has resumed previous activity levels and may contribute to the greater risk of early joint degeneration in this population.
running; knee injury; impact force; loading rates; walking
Childhood cancer survivors (CCS) experience late effects that interfere with physical function. Limitations in physical function can impact CCS abilities to actively participate in daily activities. The purpose of this investigation was to evaluate the concordance between self-reported physical performance and clinically evaluated physical performance among adult CCS.
CCS 18+ years of age and 10+ years from diagnosis who are participants in the St. Jude Lifetime Cohort study responded to the physical function section of the Medical Outcome Survey Short Form (SF36). Measured physical performance was evaluated with the physical performance test (PPT), and the six minute walk test (6MW).
1778 individuals (50.8% female) with a median time since diagnosis of 24.9 years (range 10.9-48.2) and a median age of 32.4 years (range 19.1-48.2) completed testing. Limitations in physical performance were self-reported by 14.1% of participants. The accuracy of self-report physical performance was 0.87 when the SF-36 was compared to the 6MW or PPT. Reporting inaccuracies most often involved reporting a physical performance limitation. Poor accuracy was associated with previous diagnosis of a bone or central nervous system tumor, lymphoma, older age, and large body size.
These results suggest that self-report, using the physical performance sub-scale of the SF-36 correctly identifies CCS who do not have physical performance limitations. In contrast, this same measure is less able to identify individuals who have performance limitations.
Self-report; physical function; childhood cancer; physical performance limitation; cancer survivorship
To examine whether knowledge of the 1995 Centers for Disease Control and Prevention (CDC) and the American College of Sports Medicine (ACSM) national physical activity recommendations varies by sociodemographic, behavioral, and communication-related factors.
Cross-sectional analyses of 2381 participants in the 2005 Health Information National Trends Survey, a national probability sample of the US population contacted via random-digit dial.
Only a third of respondents were accurately knowledgeable of the CDC/ACSM physical activity recommendations. Recommendation knowledge was higher among women (OR = 1.70; 95% confidence interval (CI) = 1.35–2.14) than men, the employed compared with those not currently working (OR = 0.73; 95% CI = 0.55–0.95), foreign-born individuals (OR = 1.62; 95% CI = 1.15–2.30) compared with the US-born, and those meeting CDC/ACSM recommendations vs those who do not (OR = 0.74; 95% CI = 0.58–0.96).
There is not widespread knowledge of the consensus national physical activity recommendations. These findings highlight the need for more effective campaigns to promote physical activity among the American public.
HINTS; EXERCISE; DIET; PHYSICAL INACTIVITY
To effectively evaluate activity-based interventions for weight management and disease risk reduction, objective and accurate measures of exercise dose are needed. This study examined cumulative exercise exposure defined by heart rate-based intensity, duration, and frequency as a measure of compliance with a prescribed exercise program and a predictor of health outcomes.
1,150 adults (21.3 ± 2.7 yrs) completed a 15-week exercise protocol consisting of 30 min/day, three days/wk at 65–85% maximum heart rate reserve (HRR). Computerized HR monitor data were recorded at every exercise session (33,473 valid sessions). To quantify total exercise dose, duration for each session was adjusted for average exercise intensity (%HRR) to create a measure of intensity-minutes for each workout, which were summed over all exercise sessions to formulate a heart rate physical activity score (HRPAS). Regression analysis was used to examine the relationship between HRPAS and physiological responses to exercise training. Compliance with the exercise protocol based on achievement of the minimum prescribed HRPAS was compared to adherence defined by attendance.
Using HRPAS, 868 participants were empirically defined as compliant, and 282 were non-compliant. HRPAS-based and attendance-based classifications of compliance and adherence differed for approximately 9% of participants. Higher HRPAS was associated with significant positive changes in body mass (p<0.001), BMI (p<0.001), waist and hip circumferences (p<0.001), percent body fat (%Fat, p<0.001), systolic blood pressure (p<0.011), resting heart rate (RHR, p<0.003), fasting glucose (p<0.001), and total cholesterol (p<.02). Attendance-based adherence was associated with body mass, hip circumference, %Fat, RHR, and cholesterol (p<0.05).
The HRPAS is a quantifiable measure of exercise dose associated with improvement in health indicators beyond that observed when adherence is defined as session attendance.
heart rate; physical activity; monitoring; dropout; attrition; compliance
Moderate intensity physical activity is recommended for individuals with diabetes to control glucose and prevent diabetes-related complications. The extent to which a diabetes diagnosis motivates patients to increase physical activity is unclear. This study used data from the Women’s Health Initiative Observational Study (baseline data collected from 1993-1998) to examine change in physical activity and sedentary behavior in women who reported a diabetes diagnosis compared to women who did not report diabetes over 7 years of follow-up (up to 2005).
Participants (n=84,300) were post-menopausal women who did not report diabetes at baseline [mean age=63.49; standard deviation (SD)=7.34; mean BMI=26.98 kg/m2; SD=5.67]. Linear mixed model analyses were conducted adjusting for study year, age, race/ethnicity, BMI, education, family history of diabetes, physical functioning, pain, energy/fatigue, social functioning, depression, number of chronic diseases and vigorous exercise at age 18. Analyses were completed in August 2012.
Participants who reported a diabetes diagnosis during follow-up were more likely to report increasing their total physical activity (p=0.002), walking (p<0.001) and number of physical activity episodes (p<0.001) compared to participants who did not report a diabetes diagnosis. On average, participants reporting a diabetes diagnosis reported increasing their total physical activity by 0.49 MET-hours/week, their walking by 0.033 MET-hours/week and their number of physical activity episodes by 0.19 MET-hours/week. No differences in reported sedentary behavior change were observed (p=0.48).
A diabetes diagnosis may prompt patients to increase physical activity. Healthcare professionals should consider how best to capitalize on this opportunity to encourage increased physical activity and maintenance.
type 2 diabetes; exercise; sedentary behavior; sedentary activity; Women’s Health Initiative
Weight loss has been associated with higher physical activity (PA) levels and frequent dietary self-monitoring. Less is known about how PA self-monitoring affects adherence to PA goals, PA levels and weight change.
The SMART Trial is a clinical weight loss trial in which 210 overweight adults were randomized equally to one of three arms: 1) paper record (PR); 2) personal digital assistant with self-monitoring software (PDA); and 3) PDA with daily tailored feedback message (PDA+FB). PA self-monitoring and adherence to PA goals were based on entries in weekly submitted diaries. PA levels were measured via self-report by the past 6 month Modifiable Activity Questionnaire at baseline and 6 months.
Data are presented on 189 participants with complete 6-month PA data [84% female, 77% White, mean age: 47.3 ± 8.8 years, mean BMI: 34.1 ± 4.5 kg/m2]. Median PA level was 7.96 MET-hr-wk−1 at baseline and 13.4 MET-hr-wk−1 at 6 months, with significant PA increases in all three arms. PDA+FB arm had a higher mean number of weekly self-monitoring entries than the PR arm (3.4 vs. 2.4; p=0.003) and were more likely to maintain high (i.e., 100%) adherence to PA goals over time than the PDA (p=0.02) or PR arms (p=0.0003). Both PA self-monitoring and adherence to PA goals were related to higher PA levels at 6 months. A higher mean rate of PA self-monitoring was associated with a greater percentage of weight decrease (rho=−0.49; p<0.0001) at 6 months.
PA self-monitoring and adherence to PA goals were more likely in participants in the PDA+FB arm and in turn predicted higher PA levels and weight loss.
adherence; feedback; lifestyle change; technology
Previous studies have used near-infrared spectroscopy (NIRS) to measure skeletal muscle mitochondrial capacity. This study tested the hypothesis that NIRS measured mitochondrial capacity would improve with endurance exercise training and decline with detraining.
Nine, young, participants performed four weeks of progressively increasing endurance exercise training of the wrist flexor muscles followed by approximately five weeks of inactivity. The rate of recovery of muscle oxygen consumption (mVO2) was measured with NIRS every 3-7 days, indicating mitochondrial oxidative capacity.
A linear increase in mitochondrial capacity (NIRS rate constant) was found with a group average of 64 ± 37% improvement after four weeks of exercise training (p < 0.05). Mitochondrial capacity declined exponentially upon cessation of exercise training, with a mean half-time of ~7.7 days.
Both the magnitude and time course of mitochondrial adaptations to exercise training and detraining measured with NIRS was consistent with previous studies using both in vitro and in vivo techniques. These findings show that NIRS based measurements can detect meaningful changes in mitochondrial capacity.
NIRS; mitochondrial capacity; oxidative metabolism; endurance training; detraining
Poor muscle quality and sedentary behavior are risk factors for metabolic dysfunction in children and adolescents. However, because longitudinal data are scarce, relatively little is known about how changes in muscle quality and physical activity influence bone development.
In a 2-year longitudinal study, we examined the effects of physical activity and changes in muscle quality on bone parameters in young girls.
The sample included 248 healthy girls aged 9–12 years at baseline. Peripheral quantitative computed tomography was used to measure calf and thigh muscle density, an indicator of skeletal muscle fat content or muscle quality, as well as bone parameters at diaphyseal and metaphyseal sites of the femur and tibia. Physical activity was assessed using a validated questionnaire specific for youth.
After controlling for covariates in multiple regression models, increased calf muscle density was independently associated with greater gains in cortical (β = 0.13, P < 0.01) and trabecular (β = 0.25, P < 0.001) volumetric bone mineral density (vBMD) and the bone strength index (BSI; β = 0.25, P < 0.001) of the tibia. Importantly, these relationships were generalized, as similar changes were present at the femur. Associations between physical activity and changes in bone parameters were weaker than those observed for muscle density. Nevertheless, physical activity was significantly (all P < 0.05) associated with greater gains in trabecular vBMD and the BSI of the distal femur.
These findings suggest that poor muscle quality may put girls at risk for suboptimal bone development. Physical activity is associated with more optimal gains in weight-bearing bone density and strength in girls, but to a lesser extent than changes in muscle quality.
MUSCLE DENSITY; EXERCISE; FEMALE; CHILDREN; BONE; PQCT
Parents play a critical role in shaping children’s attitudes, beliefs and behaviors, including those around physical activity and inactivity. Our ability to identify which practices effectively promote children’s physical activity and limit inactivity is limited by existing measurement instruments. This project will present a newly developed physical activity parenting practices survey, the psychometric properties of this survey’s scales, and their association with child physical activity and screen time behaviors.
A sample of 324 parents with 2–5 year old children from central North Carolina completed a series of questionnaires, including this newly developed survey of physical activity parenting practices. Child physical activity was assessed by ActiGraph (GT3X) accelerometers and parent report. Exploratory factor analysis was used to identify physical activity parenting practice constructs, and Pearson correlations were used to explore relationships between constructs and child physical activity.
Fourteen parent practices used to either control or support children’s physical activity or screen time were identified. Limits on screen time (r=−0.44), use of screen time to control behavior (r=0.23), exposure to TV (r=0.33), and parent modeling of physical activity (r=0.37) were all significantly associated with children’s TV viewing. Use of physical activity to control child behavior was significantly associated with time spent outside (r=0.15) and minutes of moderate or vigorous physical activity (r=0.16). Several supportive practices were associated with time outside (+) and TV time (−).
Results provide support for this new measure of physical activity parenting practices and identify several practices that are clearly associated with child physical activity.
home environment; physical activity; sedentary time; screen time; scale development; psychometric properties
To examine the temporal and bidirectional relationship between accelerometer-derived physical activity estimates and actigraphy-assessed sleep characteristics among older women.
A sub-group of participants [N=143, mean age= 73y] enrolled in the Healthy Women Study wore an ActiGraph accelerometer on their waist and an Actiwatch sleep monitor on their wrist concurrently for 7-consecutive days. Multi-level models examined whether ActiGraph-assessed daily activity counts (ct·min·d-1) and moderate- to vigorous- intensity physical activity (MVPA; min·d-1) predicted Actiwatch-assessed sleep onset latency, total sleep time, sleep efficiency, and sleep fragmentation. Similar models were used to determine if nighttime sleep characteristics predicted physical activity the following day.
In unadjusted models, greater daily activity counts (B=-.05, p=.005) and more minutes of MVPA (B=-.03, p=.01) were temporally associated with less total sleep time across the week. Greater sleep efficiency was associated with greater daily activity counts (B=.37, p=.01) and more minutes of MVPA (B=.64, p=.009) the following day. Less sleep fragmentation was also associated with greater daily activity counts and more MVPA the following day. Findings were similar after adjustment for age, education, BMI, depressive symptoms, arthritis, and accelerometer wear time.
Few studies have used objective measures to examine the temporal relationship between physical activity and sleep. Notably, these findings suggest that nightly variations in sleep efficiency influence physical activity the following day. Thus, improving overall sleep quality in addition to reducing nightly fluctuations in sleep may be important for encouraging a physically active lifestyle in older women.
accelerometer; Actiwatch; objective measurement; sleep efficiency; moderate to vigorous physical activity
Large physical activity surveillance projects such as the UK Biobank and NHANES are using wrist-worn accelerometer-based activity monitors that collect raw data. The goal is to increase wear time by asking subjects to wear the monitors on the wrist instead of the hip, and then to use information in the raw signal to improve activity type and intensity estimation. The purpose of this work is obtaining an algorithm to process wrist and ankle raw data and classify behavior into four broad activity classes: ambulation, cycling, sedentary and other.
Participants (N = 33) wearing accelerometers on the wrist and ankle performed 26 daily activities. The accelerometer data were collected, cleaned, and preprocessed to extract features that characterize 2 s, 4 s, and 12.8 s data windows. Feature vectors encoding information about frequency and intensity of motion extracted from analysis of the raw signal were used with a support vector machine classifier to identify a subject’s activity. Results were compared with categories classified by a human observer. Algorithms were validated using a leave-one-subject-out strategy. The computational complexity of each processing step was also evaluated.
With 12.8 s windows, the proposed strategy showed high classification accuracies for ankle data (95.0%) that decreased to 84.7% for wrist data. Shorter (4 s) windows only minimally decreased performances of the algorithm on the wrist to 84.2%.
A classification algorithm using 13 features shows good classification into the four classes given the complexity of the activities in the original dataset. The algorithm is computationally-efficient and could be implemented in real-time on mobile devices with only 4 s latency.
Activity classification; inertial sensing; mobile health; leave-one-subject-out validation; activity measurement; energy expenditure
Accurately and precisely estimating free-living energy expenditure (EE) is important for monitoring energy balance and quantifying physical activity. Recently, single and multi-sensor devices have been developed that can classify physical activities, potentially resulting in improved estimates of EE.
To determine the validity of EE estimation of a footwear-based physical activity monitor and to compare this validity against a variety of research and consumer physical activity monitors.
Nineteen healthy young adults (10 male, 9 female), completed a four-hour stay in a room calorimeter. Participants wore a footwear-based physical activity monitor, as well as Actical, Actigraph, IDEEA, DirectLife and Fitbit devices. Each individual performed a series of postures/activities. We developed models to estimate EE from the footwear-based device, and we used the manufacturer's software to estimate EE for all other devices.
Estimated EE using the shoe-based device was not significantly different than measured EE (476(20) vs. 478(18) kcal) (Mean (SE)), respectively, and had a root mean square error (RMSE) of (29.6 kcal (6.2%)). The IDEEA and DirectLlife estimates of EE were not significantly different than the measured EE but the Actigraph and Fitbit devices significantly underestimated EE. Root mean square errors were 93.5 (19%), 62.1 kcal (14%), 88.2 kcal (18%), 136.6 kcal (27%), 130.1 kcal (26%), and 143.2 kcal (28%) for Actical, DirectLife, IDEEA, Actigraph and Fitbit respectively.
The shoe based physical activity monitor provides a valid estimate of EE while the other physical activity monitors tested have a wide range of validity when estimating EE. Our results also demonstrate that estimating EE based on classification of physical activities can be more accurate and precise than estimating EE based on total physical activity.
Room calorimeter; oxygen consumption; free-living physical activity; shoe-based physical activity monitor
Insulin resistance in obesity is decreased after successful diet and exercise. Aerobic exercise training alone was evaluated as an intervention in subjects with the metabolic syndrome.
Eighteen non-diabetic, sedentary subjects, eleven with the metabolic syndrome, participated in eight weeks of increasing intensity stationary cycle training.
Cycle training without weight loss did not change insulin resistance in metabolic syndrome subjects or sedentary control subjects. Maximal oxygen consumption (VO2max), activated muscle AMP-dependent kinase, and muscle mitochondrial marker ATP synthase all increased. Strength, lean body mass, and fat mass did not change. Activated mammalian target of rapamycin was not different after training. Training induced a shift in muscle fiber composition in both groups but in opposite directions. The proportion of 2x fibers decreased with a concomitant increase in 2a mixed fibers in the control subjects, but in metabolic syndrome, 2x fiber proportion increased and type 1 fibers decreased. Muscle fiber diameters increased in all three fiber types in metabolic syndrome subjects. Muscle insulin receptor expression increased in both groups and GLUT4 expression increased in the metabolic syndrome subjects. Excess phosphorylation of insulin receptor substrate-1 (IRS-1) at Ser337 in metabolic syndrome muscle tended to increase further after training in spite of a decrease in total IRS-1.
In the absence of weight loss, cycle training of metabolic syndrome subjects resulted in enhanced mitochondrial biogenesis, and increased expression of insulin receptors and GLUT4 in muscle, but did not decrease the insulin resistance. The failure for the insulin signal to proceed past IRS-1 tyrosine phosphorylation may be related to excess serine phosphorylation at IRS-1 Ser337 and this is not ameliorated by eight weeks of endurance exercise training.
insulin resistance; metabolic syndrome; euglycemic clamp; exercise training
Physical activity (PA) is known to provide physical and mental health benefits to uterine cancer survivors. However, it is unknown if PA associates with lower limb lymphedema (LLL), an accumulation of protein-rich fluid in the lower limbs. Therefore, we sought to examine the association between PA and LLL in uterine cancer survivors, with a focus on walking.
We conducted a cross-sectional study using mailed surveys among uterine cancer survivors who received care at a university-based cancer center. We asked about PA, walking, and LLL symptoms using validated self-report questionnaires. PA was calculated using metabolic equivalent hours per week (MET-hrs∙wk−1), and walking was calculated using blocks per day (blocks∙d−1).
The response rate to our survey was 43%. Among the 213 uterine cancer survivors in our survey, 36% were classified as having LLL. Compared with participants who reported <3 MET-hrs∙wk−1 of PA, participants who reported ≥18.0 MET-hrs∙wk−1 of PA had an odds ratio of LLL of 0.32 (95% CI: 0.15–0.69; Ptrend = .003). Stratified analyses suggested the association of PA and LLL existed only among women with a body mass index (BMI) <30 kg/m2 (Ptrend = .007), compared to women with a BMI ≥30 kg/m2 (Ptrend = .47). Compared with participants who reported <4.0 blocks∙d−1 of walking, participants who reported ≥12 blocks∙d−1 of walking had an odds ratio of LLL of 0.19 (95% CI: 0.09–0.43; Ptrend < .0001). Stratified analyses suggested the association of walking and LLL was similar among women with a BMI <30 kg/m2 (Ptrend = .007) and women with a BMI ≥30 kg/m2 (Ptrend = .03).
Participation in higher levels of PA or walking is associated with reduced proportions of LLL in dose-response fashion. These findings should be interpreted as preliminary, and investigated in future studies.
gynecologic cancer; exercise; mobility disability; edema; quality of life
Previous studies suggest that African Americans (AA) have lower levels of cardiorespiratory fitness (CRF) than their Caucasian (C) counterparts. However, the association between CRF and race/ethnicity in the context of higher socioeconomic status (SES) has not been explored.
We evaluated 589 AA (309 men and 203 women) and 33,015 C (19,399 men and 8753 women) enrolled in the Cooper Center Longitudinal Study. Education years and access to a preventive health care examination were used as a proxy for higher SES. Data were collected from a questionnaire, maximal treadmill exercise stress test, and other clinical measures. The outcome variable was CRF, which was stratified into low fit (quintile 1 of CRF) and fit (quintiles 2–5). Multivariable regression was used to compare adjusted mean CRF between groups. P values were adjusted for unbalanced sample size and unequal variance between groups.
The mean education years were similar for AA and C men at 16 yr; however, AA women had more years of education than C (15.8 vs 15.2 yr, P = 0.0062). AA men and women had a significantly higher prevalence of being unfit compared with their C counterparts (men 26.7% vs 12.6%, P < 0.0001; women 21.3% vs 8.4%, P < 0.0001). The adjusted mean estimated maximal METs were 10.9 vs 11.7 and 8.8 vs 9.8 for AA and C men and women, respectively. Fully adjusted odds ratios revealed that AA men had more than twice the risk of being unfit compared with C men. A trend persisted for AA women to have a lower MET value than their counterparts.
Despite comparable higher SES, lower CRF existed among AA men versus C men. These results suggest that CRF may not be mediated strictly by environmental factors related to SES.
Racial/Ethnic Minorities; Disparities; Physical Activity
The purpose of this study was to determine whether the published left-wrist cut-points for the triaxial GENEA accelerometer, are accurate for predicting intensity categories during structured activity bouts.
A convenience sample of 130 adults wore a GENEA accelerometer on their left wrist while performing 14 different lifestyle activities. During each activity, oxygen consumption was continuously measured using the Oxycon mobile. Statistical analysis used Spearman's rank correlations to determine the relationship between measured and estimated intensity classifications. Cross tabulation tables were constructed to show under- or over-estimation of misclassified intensities. One-way chi-square tests were used to determine whether the intensity classification accuracy for each activity differed from 80%.
For all activities the GENEA accelerometer-based physical activity monitor explained 41.1% of the variance in energy expenditure. The intensity classification accuracy was 69.8% for sedentary activities, 44.9% for light activities, 46.2% for moderate activities, and 77.7% for vigorous activities. The GENEA correctly classified intensity for 52.9% of observations when all activities were examined; this increased to 61.5% with stationary cycling removed.
A wrist-worn triaxial accelerometer has modest intensity classification accuracy across a broad range of activities, when using the cut-points of Esliger et al. Although the sensitivity and specificity are less than those reported by Esliger et al., they are generally in the same range as those reported for waist-worn, uniaxial accelerometer cut-points.
activity monitor; accelerometry; physical activity; energy expenditure
The incretin hormones glucagon-like peptide-1 (GLP-1) and glucose-dependent insulinotropic polypeptide (GIP) help regulate postprandial triacylglycerol (TAG) and insulin concentrations, but the effects of acute aerobic exercise on GLP-1 or GIP responses are unclear. The purpose of this study was to determine if reductions in postprandial TAG and insulin with exercise are associated with GLP-1 and GIP responses.
Thirteen normal-weight (NW) and 13 Obese (Ob) individuals participated in two, 4-d trials in random order including an exercise (EX) and a no exercise (NoEX) trial. Diet was controlled during both trials. The EX trial consisted of 1 h of treadmill walking (55–60% of VO2peak) during the evening of day 3 of the trial, 12 h prior to a 4 h mixed meal test on day 4, during which frequent blood samples were taken to assess postprandial lipemia, glycemia, insulin, c-peptide, GIP, and GLP-1 responses. Insulin secretion was estimated using the Insulinogenic Index and insulin clearance was estimated using the ratio of insulin to c-peptide.
Postprandial TAG’s were 29% lower after EX in Ob individuals (P<0.05) but were not significantly altered in NW individuals (P>0.05). The drop in postprandial high-density lipoprotein cholesterol was attenuated with EX in Ob individuals (P<0.05). Insulin responses were 14% lower after EX in Ob individuals (P<0.05), and this was associated with reduced insulin secretion (P<0.05), with no change in insulin clearance (P>0.05). Glucose, c-peptide, GIP, and GLP-1 were not different between trials.
A 1 h bout of moderate intensity aerobic exercise the night prior to a mixed meal attenuates TAG and insulin responses in Ob, but not NW, individuals, an effect not associated with altered GLP-1 or GIP responses.
Glucagon like peptide 1; glucose-dependent insulinotropic polypeptide; insulin; physical activity; obesity; lipemia
Parks offer a free option for physical activity in many communities. How much time people spend using parks and the contribution that parks makes to their physical activity is not known. This study describes patterns of park use and physical activity among a diverse adult sample.
From five US states, 238 adults enrolled in or near 31 study parks. Participants wore a global positioning system (GPS) monitor (Qstarz BT-Q1000X) and an ActiGraph accelerometer (GT1M) concurrently for three weeks. Parks were mapped from local and national park shape files. Park visits and travel to and from the parks were derived from the objective data.
Participants visited parks a median of 2.3 times/week and park visits lasted a median of 42.0 minutes. Overall, participants engaged in a median of 21.7 minutes/day of moderate activity and 0.1 minutes/day of vigorous activity, with an average of 8.2% of all moderate and 9.4% of all vigorous activity occurring within the parks. Among those with at least one park visit (n=218), counts per minute, moderate, moderate to vigorous physical activity (MVPA), number and time in MVPA bouts/day, and sedentary behavior were all higher on days when a park was visited compared to days when a park was not visited. Considering several definitions of active travel, walking or bicycling to and from the park added an additional 3.7 to 6.6 mean minutes of MVPA per park visit.
Parks contributed as a place and destination for physical activity, but were underutilized. One of the next steps in this line of inquiry is to understand characteristics of parks used more often as a place and destination for physical activity.
accelerometer; active travel; geographic information systems (GIS); global positioning systems (GPS)
Whereas greater physical activity (PA) is known to prevent cardiovascular disease (CVD), the relative importance of performing PA in sustained bouts of activity versus shorter bouts of activity on CVD risk is not known. The objective of this study was to investigate the relationship between moderate-to-vigorous physical activity (MVPA), measured in bouts ≥10 minutes and <10 minutes, and CVD risk factors in a well-characterized, community-based sample of white adults.
We conducted a cross-sectional analysis of 2109 Framingham Heart Study Third Generation participants (mean age 47 years, 55% women) who underwent objective assessment of PA by accelerometry over 5–7 days. Total MVPA, MVPA done in bouts ≥10 minutes (MVPA10+), and MVPA done in bouts <10 minutes (MVPA<10) were calculated. MVPA exposures were related to individual CVD risk factors, including measures of adiposity and blood lipid and glucose levels, using linear and logistic regression.
Total MVPA was significantly associated with higher high-density lipoprotein (HDL) levels, and with lower triglycerides, BMI, waist circumference and Framingham risk score (P <0.0001). MVPA<10 showed similar statistically significant associations with these CVD risk factors (P <0.001). Compliance with national guidelines (≥150 minutes of total MVPA) was significantly related to lower BMI, triglycerides, Framingham risk score, waist circumference, higher HDL, and a lower prevalence of obesity and impaired fasting glucose (P < 0.001 for all).
Our cross-sectional observations on a large middle-aged community-based sample confirm a positive association of MVPA with a healthier CVD risk factor profile, and indicate that accruing physical activity in bouts <10 minutes may favorably influence cardiometabolic risk. Additional investigations are warranted to confirm our findings.
accelerometer; heart disease; exercise; guidelines