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The aim of this study is to determine changes in sedentary behaviour in response to extensive aerobic exercise training. Participants included adults who self-selected to run a marathon. Sedentary behaviour, total activity counts and physical activity (PA) intensity were assessed (Actigraph GT3X) for seven consecutive days during seven assessment periods (−3, −2, and −1 month prior to the marathon, within 2 weeks of the marathon, and +1, +2, and +3 months after the marathon). Models were fitted with multiple imputation data using the STATA mi module. Random intercept generalized least squares (GLS) regression models were used to determine change in sedentary behaviour with seven waves of repeated measures.Results: Twenty-three individuals (mean ± Sx: 34.4 ± 2.1y, 23.0 ± 1.9% fat, 15 women, 8 men) completed the study. Marathon finishing times ranged from 185 to 344 minutes (253.2 ± 9.6 minutes). Total counts in the vertical axis were 1,729,414 lower one month after the race, compared with two months prior to the race (peak training). Furthermore, counts per minute decreased by 252.7 counts·minute−1during that same time period. Daily sedentary behaviour did not change over the seven assessment periods, after accounting for age, gender, per cent body fat, wear time, marathon finishing time, and previous marathon experience. This prospective study supports the notion that PA and sedentary behaviours are distinct, showing that sedentary behaviour was not impacted by high levels of aerobic training. [ABSTRACT FROM PUBLISHER]

BACKGROUND: We previously reported increased moderate-intensity (3-6 metabolic equivalents (METs)) physical activity (PA) reverses aging-associated vascular endothelial dysfunction, a surrogate marker of cardiovascular risk. Whether reductions in sedentary time alone contribute to this improvement is unknown. METHODS: Data from 96 adults (aged ≥50 years) enrolled in a randomized control trial evaluating a 12-week intervention to increase PA in sedentary individuals were analyzed. Amount and intensity of activity were measured pre- and post-intervention by step count and accelerometry. Subjects were divided into 3 categories based on change in sedentary activity (<1. 5 METs): (i) ≥5% reduction in sedentary time, (ii) 0-4.99% reduction, and (iii) increase sedentary time. Vascular endothelial function was measured by brachial artery flow-mediated dilation (FMD%) pre- and post-intervention. RESULTS: Sedentary time decreased overall (P = 0.001), with a 101-minute decrease in category 1 (N = 27, P < 0.001), a 42-minute decrease in category 2 (N = 29, P = 0.003), and a 44-minute increase in category 3 (N = 40, P = 0.02). While FMD% increased in the entire study population (P = 0.008) over 12 weeks, no differences were observed between the categories (P = 0.73). In category 1, FMD% improvement was associated achievement of ≥20 minutes/day of moderate intensity PA in bouts ≥ 10 minutes in length. CONCLUSIONS: Reductions of up to 100 minutes of sedentary time per day over 12 weeks was not significantly associated with improved vascular endothelial function in older adults. FMD% was significantly higher among those with lower sedentary behavior and concomitant moderate- intensity PA of ≥20 minutes/day in bouts. [ABSTRACT FROM AUTHOR]

Nowhere is improving understanding and accurate assessment of physical activity more important for disease prevention and health promotion than among health disparities populations such as those residing in rural and Appalachian regions. To enhance accurate assessment of physical activity and potentially improve intervention capacity, we conducted a mixed-methods study examining the acceptability and feasibility of self-report physical activity questionnaires, pedometers, and accelerometers among rural Appalachian children, adolescents, and adults. Most participants reported positive experiences with all three physical activity assessment tools. Several acceptability ratings differed by age group and by sex within each age group. With very few exceptions, no significant differences in acceptability were found by race, education, employment status, health status, BMI categories, income levels, or insurance status within age groups or overall. Several factors may impact the choice of the physical activity assessment method, including target population age, equipment cost, researcher burden, and potential influence on physical activity levels. Children and adolescents appear to have more constraints on when they can wear pedometers and accelerometers. While pedometers are inexpensive and convenient, they may influence physical activity levels, rather than simply measure them. Accelerometers, while less influential on behavior, consume extensive resources, including high purchase costs and researcher burden. [ABSTRACT FROM AUTHOR]

Background The purpose of this study was to determine the responsiveness of two motion sensors to detect change in sedentary behaviour (SB) and physical activity (PA) during an occupational intervention to reduce sitting time. Methods SB and PA were assessed using a hip-worn Actigraph GTX3 (AG) and a thigh-worn activPAL (AP) during three consecutive workdays throughout baseline and intervention periods. Mean scores at baseline and intervention were estimated by hierarchical linear models (HLM) with robust SEs, adjusting for random variance of average scores between participants. Change scores (mean baseline minus mean intervention) were calculated for each device. Response to change was assessed for each device using the standardised response mean. Results 67 adults (45±11 years; 29.3±7.7 kg/m²) wore the acceleration-based motion sensors for 8.3 (SD=1.2) and 8.3 (SD=1.1) h during the baseline and intervention periods, respectively. HLM showed that AP sitting/lying time (-16.5 min, -5%), AP stepping (+7.5 min, 19%), AP steps/day (+838 steps/day, +22%), AP sit-to-stand transitions (+3, +10%), AG SB (-14.6 min, -4%), AG lifestyle moderate-intensity PA (LMPA, +4 min, +15%) and AG MPA (+3 min, 23%) changed significantly between the baseline and the intervention period. Standardised response means for AP sitting/lying time, stepping, steps/day, sit-to-stand transitions and AG SB, LMPA and MPA were above 0.3, indicating a small but similar responsiveness to change. Conclusions Responsiveness to change in SB and PA was similar and comparable for the AP and AG, indicating agreement across both measurement devices. [ABSTRACT FROM AUTHOR]

Increasing physical activity among low-income African American women is an important target for addressing racial and economic disparities in chronic conditions and related risk factors. While barriers to physical activity for women have been examined empirically, successful strategies for navigating those barriers among physically active, low-income women have not been thoroughly explored. Informed by grounded theory, we conducted in-depth individual interviews between 2007–2010 with 14 low-income African American women who were physically active at nationally recommended levels for one year or more. We analyzed the data using thematic analysis techniques. Key themes emerged in three main categories: motivation for maintaining active lifestyle, strategies for maintaining physical activity, and challenges to maintaining physical activity. Important motivations included getting or staying healthy, social connections, and gratification. Two planning strategies emerged: flexibility and freedom. Critical challenges included financial constraints, physical strain and history of sedentary relapse. The motivations, strategies and challenges reported by low-income African American women who successfully maintained an active lifestyle provided important information for developing effective health promotion strategies for their inactive and underactive counterparts. A qualitative, asset-based approach to physical activity research contributes rich data to bridge the gap between epidemiological knowledge and community health improvement. [ABSTRACT FROM AUTHOR]

This article reviews the current use of objective methods which feature accelerometers to assess physical activity in observational, determinant, and intervention studies for children, older adults, and adults with functional limitations. A discussion of factors which researchers need to consider when adopting prediction algorithms which have been developed on one population and using them in another population that is markedly different in age, health, and functional status, is presented. The best practices for using accelerometers with individuals with functional limitations are discussed.