Metrics of Diabetes Risk Are Only Minimally Improved by Exercise Training in Postmenopausal Breast Cancer Survivors.

CONTEXT: Insulin resistance is a risk factor for breast cancer recurrence. How exercise training changes fasting and postglucose insulin resistance in breast cancer survivors is unknown. OBJECTIVE: To evaluate exercise-induced changes in postglucose ingestion insulin concentrations, insulin resistance, and their associations with cancer-relevant biomarkers in breast cancer survivors. SETTING: The University of Massachusetts Kinesiology Department. PARTICIPANTS: 15 postmenopausal breast cancer survivors not meeting the physical activity guidelines (150 min/week of exercise). INTERVENTION: A supervised 12-week aerobic exercise program (60 min/day, 3-4 days/week). MAIN OUTCOME MEASURES: Postglucose ingestion insulin was determined by peak insulin and area under the insulin curve (iAUC) during a 5-sample oral glucose tolerance test. Insulin sensitivity was estimated from the Matsuda composite insulin sensitivity index (C-ISI). Changes in fitness and body composition were determined from submaximal VO2peak and dual energy X-ray absorptiometry. RESULTS: Participants averaged 156.8 ± 16.6 min/week of supervised exercise. Estimated VO2peak significantly increased (+2.8 ± 1.4 mL/kg/min, P < .05) and body weight significantly decreased (-1.1 ± 0.8 kg, P < .05) following the intervention. There were no differences in fasting insulin, iAUC, C-ISI, or peak insulin following the intervention. Insulin was only significantly lower 120 min following glucose consumption (68.8 ± 34.5 vs 56.2 ± 31.9 uU/mL, P < .05), and there was a significant interaction with past/present aromatase inhibitor (AI) use for peak insulin (-11.99 non-AI vs +13.91 AI uU/mL) and iAUC (-24.03 non-AI vs +32.73 AI uU/mL). CONCLUSIONS: Exercise training had limited overall benefits on insulin concentrations following glucose ingestion in breast cancer survivors but was strongly influenced by AI use.

Advantages and Limitations of Wearable Activity Trackers: Considerations for Patients and Clinicians.

BACKGROUND: Exercise, light physical activity, and decreased sedentary time all have been associated with health benefits following cancer diagnoses. Commercially available wearable activity trackers may help patients monitor and self-manage their behaviors to achieve these benefits. OBJECTIVES: This article highlights some advantages and limitations clinicians should be aware of when discussing the use of activity trackers with cancer survivors. METHODS: Limited research has assessed the accuracy of commercially available activity trackers compared to research-grade devices. Because most devices use confidential, proprietary algorithms to convert accelerometry data to meaningful output like total steps, assessing whether these algorithms account for differences in gait abnormalities, functional limitations, and different body morphologies can be difficult. Quantification of sedentary behaviors and light physical activities present additional challenges. FINDINGS: The global market for activity trackers is growing, which presents clinicians with a tremendous opportunity to incorporate these devices into clinical practice as tools to promote activity. This article highlights important considerations about tracker accuracy and usage by cancer survivors.

The independent and combined effects of exercise training and reducing sedentary behavior on cardiometabolic risk factors.

This pilot study examined if the combination of exercise training and reducing sedentary time (ST) results in greater changes to health markers than either intervention alone. Fifty-seven overweight/obese participants (19 males/39 females) (mean ± SD; age, 43.6 ± 9.9 years; body mass index (BMI), 35.1 ± 4.6 kg·m(-2)) completed the 12-week study and were randomly assigned to (i) EX: exercise 5 days·week(-1) for 40 min·session(-1) at moderate intensity; (ii) rST: reduce ST and increase nonexercise physical activity; (iii) EX-rST: combination of EX and rST; and (iv) CON: maintain behavior. Fasting lipids, blood pressure (BP), peak oxygen uptake, BMI, and 2-h oral glucose tolerance tests were completed pre- and post-intervention. EX and EX-rST increased peak oxygen uptake by ∼10% and decreased systolic BP (both p < 0.001). BMI decreased by -3.3% (95% confidence interval: -4.6% to -1.9%) for EX-rST and -2.2% (-3.5% to 0.0%) for EX. EX-rST significantly increased composite insulin-sensitivity index by 17.8% (2.8% to 32.8%) and decreased insulin area under the curve by 19.4% (-31.4% to -7.3%). No other groups improved in insulin action variables. rST group decreased ST by 7% (∼50 min·day(-1)); however, BP was the only health-related outcome that improved. EX and EX-rST improved peak oxygen uptake and BMI, providing further evidence that moderate-intensity exercise is beneficial. The within-group analysis provides preliminary evidence that exercising and reducing ST may result in improvements in metabolic biomarkers that are not seen with exercise alone, though between-group differences did not reach statistical significance. Future studies, with larger samples, should examine health-related outcomes resulting from greater reductions in ST over longer intervention periods.

Validation of a previous day recall for measuring the location and purpose of active and sedentary behaviors compared to direct observation.

PURPOSE: Gathering contextual information (i.e., location and purpose) about active and sedentary behaviors is an advantage of self-report tools such as previous day recalls (PDR). However, the validity of PDR's for measuring context has not been empirically tested. The purpose of this paper was to compare PDR estimates of location and purpose to direct observation (DO). METHODS: Fifteen adult (18-75 y) and 15 adolescent (12-17 y) participants were directly observed during at least one segment of the day (i.e., morning, afternoon or evening). Participants completed their normal daily routine while trained observers recorded the location (i.e., home, community, work/school), purpose (e.g., leisure, transportation) and whether the behavior was sedentary or active. The day following the observation, participants completed an unannounced PDR. Estimates of time in each context were compared between PDR and DO. Intra-class correlations (ICC), percent agreement and Kappa statistics were calculated. RESULTS: For adults, percent agreement was 85% or greater for each location and ICC values ranged from 0.71 to 0.96. The PDR-reported purpose of adults' behaviors were highly correlated with DO for household activities and work (ICCs of 0.84 and 0.88, respectively). Transportation was not significantly correlated with DO (ICC = -0.08). For adolescents, reported classification of activity location was 80.8% or greater. The ICCs for purpose of adolescents' behaviors ranged from 0.46 to 0.78. Participants were most accurate in classifying the location and purpose of the behaviors in which they spent the most time. CONCLUSIONS: This study suggests that adults and adolescents can accurately report where and why they spend time in behaviors using a PDR. This information on behavioral context is essential for translating the evidence for specific behavior-disease associations to health interventions and public policy.

Guide to the assessment of physical activity: Clinical and research applications: a scientific statement from the American Heart Association.

The deleterious health consequences of physical inactivity are vast, and they are of paramount clinical and research importance. Risk identification, benchmarks, efficacy, and evaluation of physical activity behavior change initiatives for clinicians and researchers all require a clear understanding of how to assess physical activity. In the present report, we have provided a clear rationale for the importance of assessing physical activity levels, and we have documented key concepts in understanding the different dimensions, domains, and terminology associated with physical activity measurement. The assessment methods presented allow for a greater understanding of the vast number of options available to clinicians and researchers when trying to assess physical activity levels in their patients or participants. The primary outcome desired is the main determining factor in the choice of physical activity assessment method. In combination with issues of feasibility/practicality, the availability of resources, and administration considerations, the desired outcome guides the choice of an appropriate assessment tool. The decision matrix, along with the accompanying tables, provides a mechanism for this selection that takes all of these factors into account. Clearly, the assessment method adopted and implemented will vary depending on circumstances, because there is no single best instrument appropriate for every situation. In summary, physical activity assessment should be considered a vital health measure that is tracked regularly over time. All other major modifiable cardiovascular risk factors (diabetes mellitus, hypertension, hypercholesterolemia, obesity, and smoking) are assessed routinely. Physical activity status should also be assessed regularly. Multiple physical activity assessment methods provide reasonably accurate outcome measures, with choices dependent on setting-specific resources and constraints. The present scientific statement provides a guide to allow professionals to make a goal-specific selection of a meaningful physical activity assessment method.

Amount of time spent in sedentary behaviors in the United States, 2003-2004.

Sedentary behaviors are linked to adverse health outcomes, but the total amount of time spent in these behaviors in the United States has not been objectively quantified. The authors evaluated participants from the 2003-2004 National Health and Nutrition Examination Survey aged >/=6 years who wore an activity monitor for up to 7 days. Among 6,329 participants with at least one 10-hour day of monitor wear, the average monitor-wearing time was 13.9 hours/day (standard deviation, 1.9). Overall, participants spent 54.9% of their monitored time, or 7.7 hours/day, in sedentary behaviors. The most sedentary groups in the United States were older adolescents and adults aged >/=60 years, and they spent about 60% of their waking time in sedentary pursuits. Females were more sedentary than males before age 30 years, but this pattern was reversed after age 60 years. Mexican-American adults were significantly less sedentary than other US adults, and White and Black females were similarly sedentary after age 12 years. These data provide the first objective measure of the amount of time spent in sedentary behavior in the US population and indicate that Americans spend the majority of their time in behaviors that expend very little energy.

The association between an objective measure of physical activity and weight status in preschoolers.

OBJECTIVE: Our objective was to determine the association between physical activity and BMI among racially diverse low-income preschoolers. RESEARCH METHODS AND PROCEDURES: This was a cross-sectional study of 2- to 5-year-olds (n = 56) enrolled in Massachusetts Special Supplemental Nutrition Program for Women, Infants & Children (WIC). Physical activity was measured for 7 consecutive days with an accelerometer. Height and weight were obtained from WIC records, and BMI-for-age percentiles were calculated based on the Centers for Disease Control and Prevention's (CDC) 2000 Growth Charts. At-risk-for-overweight (BMI-for-age of > or = 85th to < 95th percentile) and overweight (BMI-for-age > or = 95th percentile) groups were combined and referred to as overweight. Final analysis inclusion criteria were: completion of 4.5 days of activity assessment and anthropometric data obtained within 90 and 120 days of the activity assessment for children ages 24 to 35.99 and 36 to 59.99 months, respectively. RESULTS: Overweight children had significantly lower mean daily very vigorous minutes (VVM) (2.6 mins vs. 4.6 mins, p < 0.05) and lower very active minutes (VAM) [i.e., sum of vigorous minutes (VM) and VVM] per day (22.9 mins vs. 32.1 mins, p < 0.05) than children who were not overweight. Daily VVM [odds ratio (OR) = 0.68; 95% confidence interval (CI), 0.49 to 0.96], VM (OR = 0.94; CI, 0.88 to 1.00), and VAM (OR = 0.94; 95% CI, 0.89 to 1.00) were all associated with significantly lower odds of being overweight. DISCUSSION: This study suggests that, in a diverse group of preschoolers, vigorous and very vigorous activity are associated with lower odds of overweight. However, these findings require corroboration in a diverse sample of preschoolers using a longitudinal design.

Body mass index, but not physical activity, is associated with C-reactive protein.

UNLABELLED: Elevated high-sensitivity c-reactive protein (hs-CRP) is associated with increased risk of future first and recurrent coronary events and has been associated with both high body mass index (BMI) and low physical activity in cross sectional studies. PURPOSE: To longitudinally examine the effects of BMI and both current and previous-year physical activity on hs-CRP in healthy men and women (N = 109). METHODS: BMI and hs-CRP were measured five times (baseline and quarterly) over 1 yr. Current physical activity was assessed 12-15 times during the study via 24-h recall. Previous-year physical activity was assessed using the Baecke questionnaire at baseline. RESULTS: Mean BMI and hs-CRP were unchanged over the course of the study, but current physical activity increased on visit 3. Average hs-CRP was not related to average current physical activity or to natural changes in current physical activity across the five visits. Additionally, current physical activity on any given visit was not associated with hs-CRP on the following visit. When current physical activity, BMI, age, gender, and smoking were included in the statistical model, only BMI was significantly related to hs-CRP (P < 0.001). Average hs-CRP was significantly correlated with average BMI (r = 0.50; P < 0.001) but was not related to previous-year (Baecke) physical activity levels (r = 0.02; P = 0.89). When subjects were grouped by BMI (<25 kg.m-2, 25-29.9 kg x m-2, >30 kg x m-2) hs-CRP was significantly greater in obese (3.2 +/- 1.9 mg.L-1) and overweight (2.1 +/- 1.7 mg x L-1) than normal weight (1.1 +/- 1.0 mg.L-1) subjects (ANOVA P < 0.05). Current physical activity was similar between the three BMI groups at all times, and was unrelated to hs-CRP in all groups, throughout the study period. CONCLUSION: These data indicate that BMI, but not previous-year or current physical activity, predicts hs-CRP.