Response

This is not the published version.See the article "Resistance to exercise-induced weight loss: compensatory behavioral adaptations" here at http://hdl.handle.net/1808/24571

Resistance to exercise-induced weight loss: compensatory behavioral adaptations

This is not the published version.In many interventions that are based on an exercise program intended to induce weight loss, the mean weight loss observed is modest and sometimes far less than the individual expected. The individual responses are also widely variable, with some individuals losing a substantial amount of weight, others maintaining weight, and a few actually gaining weight. The media have focused on the sub-population that loses little weight, contributing to a public perception that exercise has limited utility to cause weight loss. The purpose of the symposium was to present recent, novel data that help explain how compensatory behaviors contribute to a wide discrepancy in exercise-induced weight loss. The presentations provide evidence that some individuals adopt compensatory behaviors, i.e. increased energy intake and/or reduced activity, that offset the exercise energy expenditure and limit weight loss. The challenge for both scientists and clinicians is to develop effective tools to identify which individuals are susceptible to such behaviors, and to develop strategies to minimize their impact

The feasibility of measuring the activation of the trunk muscles in healthy older adults during trunk stability exercises

<p>Abstract</p> <p>Background</p> <p>As the older adult population increases, the potential functional and clinical burden of trunk muscle dysfunction may be significant. An evaluation of risk factors including the impact of the trunk muscles in terms of their temporal firing patterns, amplitudes of activation, and contribution to spinal stability is required. Therefore, the specific purpose of this study was to assess the feasibility of measuring the activation of trunk muscles in healthy older adults during specific leg exercises with trunk stabilization.</p> <p>Methods</p> <p>12 asymptomatic adults 65 to 75 years of age were included in the study. Participants performed a series of trunk stability exercises, while bilateral activation of abdominal and back extensor muscles was recorded by 24 pairs of Meditrace™ surface electrodes. Maximal voluntary isometric contractions (MVIC) were performed for electromyographic (EMG) normalization purposes. EMG waveforms were generated and amplitude measures as a percentage of MVIC were calculated along with ensemble average profiles. 3D kinematics data were also recorded, using an electromagnetic sensor placed at the left lateral iliac crest. Furthermore, a qualitative assessment was conducted to establish the participant's ability to complete all experimental tasks.</p> <p>Results</p> <p>Excellent quality abdominal muscle activation data were recorded during the tasks. Participants performed the trunk stability exercises with an unsteady, intermittent motion, but were able to keep pelvic motion to less than 10°. The EMG amplitudes showed that during these exercises, on average, the older adults recruited their abdominal muscles from 15–34% of MVIC and back extensors to less than 10% of MVIC. There were similarities among the abdominal muscle profiles. No participants reported pain during the testing session, although 3 (25%) of the participants reported delayed onset muscle soreness during follow up that was not functionally limiting.</p> <p>Conclusion</p> <p>Older adults were able to successfully complete the trunk stability protocol that was developed for younger adults with some minor modifications. The collected EMG amplitudes were higher than those reported in the literature for young healthy adults. The temporal waveforms for the abdominal muscles showed a degree of synchrony among muscles, except for the early activation from the internal oblique prior to lifting the leg off the table.</p

A Comprehensive Evaluation of Commonly Used Accelerometer Energy Expenditure and MET Prediction Equations

Numerous accelerometers and prediction methods are used to estimate energy expenditure (EE). Validation studies have been limited to small sample sizes in which participants complete a narrow range of activities and typically validate only one or two prediction models for one particular accelerometer. Purpose—To evaluate the validity of nine published and two proprietary EE prediction equations for three different accelerometers. Methods—277 participants completed an average of 6 treadmill (TRD) (1.34, 1.56, 2.23 m・sec−1 each at 0% and 3% grade) and 5 self-paced activities of daily living (ADLs). EE estimates were compared to indirect calorimetry. Accelerometers were worn while EE was measured using a portable metabolic unit. To estimate EE, 4 ActiGraph prediction models were used, 5 Actical models, and 2 RT3 proprietary models. Results—Across all activities, each equation underestimated EE (bias −0.1 to −1.4 METs and −0.5 to −1.3 kcals, respectively). For ADLs EE was underestimated by all prediction models (bias −0.2 to −2.0 and −0.2 to −2.8, respectively), while TRD activities were underestimated by seven equations, and overestimated by four equations (bias −0.8 to 0.2 METs and −0.4 to 0.5 kcals, respectively). Misclassification rates ranged from 21.7% (95% CI 20.4%, 24.2%) to 34.3% (95% CI 32.3%, 36.3%), with vigorous intensity activities being most often misclassified. Discussion—The prediction equations did not yield accurate point estimates of EE across a broad range of activities, nor were they accurate at classifying activities across a range of intensities (light \u3c 3 METs, moderate 3–5.99 METs, vigorous ≥ 6 METs). Current prediction techniques have many limitations when translating accelerometer counts to EE

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