Attenuating Effect of Vigorous Physical Activity on the Risk for Inherited Obesity: A Study of 47,691 Runners

Objective: Physical activity has been shown to attenuate the effect of the FTO polymorphism on body weight, and the heritability of body weight in twin and in family studies. The dose-response relationship between activity and the risk for inherited obesity is not well known, particularly for higher doses of vigorous exercise. Such information is needed to best prescribe an exercise dose for obesity prevention in those at risk due to their family history. Design: We therefore analyzed self-reported usual running distance, body mass index (BMI), waist circumference, and mother’s and father’s adiposity (1 = lean, 2 = normal, 3 = overweight, and 4 = very overweight) from survey data collected on 33,480 male and 14,211 female runners. Age-, education-, and alcohol-adjusted regression analyses were used to estimate the contribution of parental adiposities to the BMI and waist circumferences in runners who ran an average of,3, 3–6, 6–9, $9 km/day. Results: BMI and waist circumferences of runners who ran,3 km/day were significantly related to their parents adiposity (P,10 215 and P,10 211, respectively). These relationships (i.e., kg/m 2 or cm per increment in parental adiposity) diminished significantly with increasing running distance for both BMI (inheritance6exercise interaction, males: P,10 210; females: P,10 25) and waist circumference (inheritance6exercise interaction, males: P,10 29; females: P = 0.004). Compared to,3 km/day, the parental contribution to runners who averaged$9 km/day was diminished by 48 % for male BMI, 58 % for female BMI, 55 % for male waist circumference, and 58 % for female waist circumference. These results could not b

Combined effects of time spent in physical activity, sedentary behaviors and sleep on obesity and cardio-metabolic health markers: a novel compositional data analysis approach

<div><p>The associations between time spent in sleep, sedentary behaviors (SB) and physical activity with health are usually studied without taking into account that time is finite during the day, so time spent in each of these behaviors are codependent. Therefore, little is known about the combined effect of time spent in sleep, SB and physical activity, that together constitute a composite whole, on obesity and cardio-metabolic health markers. Cross-sectional analysis of NHANES 2005–6 cycle on N = 1937 adults, was undertaken using a compositional analysis paradigm, which accounts for this intrinsic codependence. Time spent in SB, light intensity (LIPA) and moderate to vigorous activity (MVPA) was determined from accelerometry and combined with self-reported sleep time to obtain the 24 hour time budget composition. The distribution of time spent in sleep, SB, LIPA and MVPA is significantly associated with BMI, waist circumference, triglycerides, plasma glucose, plasma insulin (all p<0.001), and systolic (p<0.001) and diastolic blood pressure (p<0.003), but not HDL or LDL. Within the composition, the strongest positive effect is found for the proportion of time spent in MVPA. Strikingly, the effects of MVPA replacing another behavior and of MVPA being displaced by another behavior are asymmetric. For example, re-allocating 10 minutes of SB to MVPA was associated with a lower waist circumference by 0.001% but if 10 minutes of MVPA is displaced by SB this was associated with a 0.84% higher waist circumference. The proportion of time spent in LIPA and SB were detrimentally associated with obesity and cardiovascular disease markers, but the association with SB was stronger. For diabetes risk markers, replacing SB with LIPA was associated with more favorable outcomes. Time spent in MVPA is an important target for intervention and preventing transfer of time from LIPA to SB might lessen the negative effects of physical inactivity.</p></div

Changes in Weight, Waist Circumference and Compensatory Responses with Different Doses of Exercise among Sedentary, Overweight Postmenopausal Women

It has been suggested that exercise training results in compensatory mechanisms that attenuate weight loss. However, this has only been examined with large doses of exercise. The goal of this analysis was to examine actual weight loss compared to predicted weight loss (compensation) across different doses of exercise in a controlled trial of sedentary, overweight or obese postmenopausal women (n = 411).Participants were randomized to a non-exercise control (n = 94) or 1 of 3 exercise groups; exercise energy expenditure of 4 (n = 139), 8 (n = 85), or 12 (n = 93) kcal/kg/week (KKW). Training intensity was set at the heart rate associated with 50% of each woman's peak VO(2) and the intervention period was 6 months. All exercise was supervised. The main outcomes were actual weight loss, predicted weight loss (exercise energy expenditure/ 7700 kcal per kg), compensation (actual minus predicted weight loss) and waist circumference. The study sample had a mean (SD) age 57.2 (6.3) years, BMI of 31.7 (3.8) kg/m(2), and was 63.5% Caucasian. The adherence to the intervention was >99% in all exercise groups. The mean (95% CI) weight loss in the 4, 8 and 12 KKW groups was -1.4 (-2.0, -0.8), -2.1 (-2.9, -1.4) and -1.5 (-2.2, -0.8) kg, respectively. In the 4 and 8 KKW groups the actual weight loss closely matched the predicted weight loss of -1.0 and -2.0 kg, respectively, resulting in no significant compensation. In the 12 KKW group the actual weight loss was less than the predicted weight loss (-2.7 kg) resulting in 1.2 (0.5, 1.9) kg of compensation (P<0.05 compared to 4 and 8 KKW groups). All exercise groups had a significant reduction in waist circumference which was independent of changes in weight.In this study of previously sedentary, overweight or obese, postmenopausal women we observed no difference in the actual and predicted weight loss with 4 and 8 KKW of exercise (72 and 136 minutes respectively), while the 12 KKW (194 minutes) produced only about half of the predicted weight loss. However, all exercise groups had a significant reduction in waist circumference which was independent of changes in weight.(ClinicalTrials.gov) NCT00011193

Objective vs. Self-Reported Physical Activity and Sedentary Time: Effects of Measurement Method on Relationships with Risk Biomarkers

&lt;p&gt;&lt;b&gt;Purpose:&lt;/b&gt; Imprecise measurement of physical activity variables might attenuate estimates of the beneficial effects of activity on health-related outcomes. We aimed to compare the cardiometabolic risk factor dose-response relationships for physical activity and sedentary behaviour between accelerometer- and questionnaire-based activity measures.&lt;/p&gt; &lt;p&gt;&lt;b&gt;Methods:&lt;/b&gt; Physical activity and sedentary behaviour were assessed in 317 adults by 7-day accelerometry and International Physical Activity Questionnaire (IPAQ). Fasting blood was taken to determine insulin, glucose, triglyceride and total, LDL and HDL cholesterol concentrations and homeostasis model-estimated insulin resistance (HOMAIR). Waist circumference, BMI, body fat percentage and blood pressure were also measured.&lt;/p&gt; &lt;p&gt;&lt;b&gt;Results:&lt;/b&gt; For both accelerometer-derived sedentary time (&#60;100 counts.min−1) and IPAQ-reported sitting time significant positive (negative for HDL cholesterol) relationships were observed with all measured risk factors – i.e. increased sedentary behaviour was associated with increased risk (all p&#8804;0.01). However, for HOMAIR and insulin the regression coefficients were &#62;50% lower for the IPAQ-reported compared to the accelerometer-derived measure (p&#60;0.0001 for both interactions). The relationships for moderate-to-vigorous physical activity (MVPA) and risk factors were less strong than those observed for sedentary behaviours, but significant negative relationships were observed for both accelerometer and IPAQ MVPA measures with glucose, and insulin and HOMAIR values (all p&#60;0.05). For accelerometer-derived MVPA only, additional negative relationships were seen with triglyceride, total cholesterol and LDL cholesterol concentrations, BMI, waist circumference and percentage body fat, and a positive relationship was evident with HDL cholesterol (p = 0.0002). Regression coefficients for HOMAIR, insulin and triglyceride were 43–50% lower for the IPAQ-reported compared to the accelerometer-derived MVPA measure (all p&#8804;0.01).&lt;/p&gt; &lt;p&gt;&lt;b&gt;Conclusion:&lt;/b&gt; Using the IPAQ to determine sitting time and MVPA reveals some, but not all, relationships between these activity measures and metabolic and vascular disease risk factors. Using this self-report method to quantify activity can therefore underestimate the strength of some relationships with risk factors.&lt;/p&gt

The effectiveness of physical activity monitoring and distance counselling in an occupational health setting - a research protocol for a randomised controlled trial (CoAct)

<p>Abstract</p> <p>Background</p> <p>The CoAct (Cocreating Activity) study is investigating a novel lifestyle intervention, aimed at the working population, with daily activity monitoring and distance counselling via telephone and secure web messages. The main purpose of this study is to evaluate the effectiveness of lifestyle counselling on the level of physical activity in an occupational health setting. The purposes include also analysing the potential effects of changes in physical activity on productivity at work and sickness absence, and healthcare costs. This article describes the design of the study and the participant flow until and including randomization.</p> <p>Methods/Design</p> <p>CoAct is a randomised controlled trial with two arms: a control group and intervention group with daily activity monitoring and distance counselling. The intervention focuses on lifestyle modification and takes 12 months. The study population consists of volunteers from 1100 eligible employees of a Finnish insurance company. The primary outcomes of this study are change in physical activity measured in MET minutes per week, work productivity and sickness absence, and healthcare utilisation. Secondary outcomes include various physiological measures. Cost-effectiveness analysis will also be performed. The outcomes will be measured by questionnaires at baseline, after 6, 12, and 24 months, and sickness absence will be obtained from the employer's registers.</p> <p>Discussion</p> <p>No trials are yet available that have evaluated the effectiveness of daily physical activity monitoring and distance counselling in an occupational health setting over a 12 month period and no data on cost-effectiveness of such intervention are available.</p> <p>Trial Registration</p> <p>ClinicalTrials.gov identifier: NCT00994565</p

Health enhancing strength training in nonagenarians (STRONG): rationale, design and methods

<p>Abstract</p> <p>Background</p> <p>The Health Enhancing Strength Training in Nonagenarians (STRONG) is a randomised control trial to assess the effectiveness of an aerobic and strength training program for improving muscle strength, functional capacity and quality of life in nonagenarians.</p> <p>Methods</p> <p>Sixty (51 women) nonagenarians (age range: 90–102 years) who live in a geriatric nursing home will be randomly assigned to either a usual care (control) group (n = 30) or an intervention (training) group (n = 30). Participants allocated in the usual care group will receive general physical activity guidelines and participants allocated in the intervention group will also enrol in three weekly non-consecutive individualized training sessions (~45–50 min each) during 8 weeks. The exercise program will consist of muscular strength [with a special focus on leg press at 30% (start of the program) to 70% 1 repetition maximum (end)] and aerobic exercises (cycle-ergometry during 3–5 to 15 minutes at 12–14 points in the rate of perceived exertion scale).</p> <p>Results</p> <p>Results from STRONG will help to better understand the potential of regular physical activity for improving the well-being of the oldest population groups.</p> <p>Conclusion</p> <p>The increase in life expectancy together with the dramatic decrease in birth rates in industrialized countries calls the attention to health care systems and public health policymakers to focus attention on promoting healthy lifestyle in the highest sector of the population pyramid. Our study attempts to improve functional capacity and QOL of nonagenarians by implementing an individualised aerobic and strength training program in a geriatric residential care. Results from STRONG will help to better understand the potential of regular physical activity for improving the well being even in persons aged 90 years or over.</p> <p>Trail Registration</p> <p>ClinicalTrials.gov ID: NCT00848978</p

HABITAT: A longitudinal multilevel study of physical activity change in mid-aged adults

Purpose. To explore the role of the neighborhood environment in supporting walking Design. Cross sectional study of 10,286 residents of 200 neighborhoods. Participants were selected using a stratified two-stage cluster design. Data were collected by mail survey (68.5% response rate). Setting. The Brisbane City Local Government Area, Australia, 2007. Subjects. Brisbane residents aged 40 to 65 years. Measures. Environmental: street connectivity, residential density, hilliness, tree coverage, bikeways, and street lights within a one kilometer circular buffer from each resident’s home; and network distance to nearest river or coast, public transport, shop, and park. Walking: minutes in the previous week categorized as < 30 minutes, ≥ 30 < 90 minutes, ≥ 90 < 150 minutes, ≥ 150 < 300 minutes, and ≥ 300 minutes. Analysis. The association between each neighborhood characteristic and walking was examined using multilevel multinomial logistic regression and the model parameters were estimated using Markov chain Monte Carlo simulation. Results. After adjustment for individual factors, the likelihood of walking for more than 300 minutes (relative to <30 minutes) was highest in areas with the most connectivity (OR=1.93, 99% CI 1.32-2.80), the greatest residential density (OR=1.47, 99% CI 1.02-2.12), the least tree coverage (OR=1.69, 99% CI 1.13-2.51), the most bikeways (OR=1.60, 99% CI 1.16-2.21), and the most street lights (OR=1.50, 99% CI 1.07-2.11). The likelihood of walking for more than 300 minutes was also higher among those who lived closest to a river or the coast (OR=2.06, 99% CI 1.41-3.02). Conclusion. The likelihood of meeting (and exceeding) physical activity recommendations on the basis of walking was higher in neighborhoods with greater street connectivity and residential density, more street lights and bikeways, closer proximity to waterways, and less tree coverage. Interventions targeting these neighborhood characteristics may lead to improved environmental quality as well as lower rates of overweight and obesity and associated chromic disease