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Efficacy of a pedometer-based physical activity program on parameters of diabetes control in type 2 diabetes mellitus

School of Medicine, Department of Internal Medicine, University of New Mexico Health Sciences Center, Albuquerque, NM 87131, USA.
Metabolism (Impact Factor: 3.61). 11/2006; 55(10):1382-7. DOI: 10.1016/j.metabol.2006.06.009
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ABSTRACT The aim of the study was to determine whether a recommendation to walk 10000 steps per day would result in significant improvements in glycemic control, insulin sensitivity, and cardiovascular risk in patients with type 2 diabetes mellitus. The study was a 6-week randomized controlled trial that included 30 patients with type 2 diabetes mellitus. After 10 days of baseline activity, patients were randomized into 2 groups: control and active. The control group (n = 15) was instructed to continue with their baseline activity for 6 weeks. The active group (n = 15) was instructed to walk at least 10000 steps per day 5 or more days per week, for 6 weeks. Data relevant to glycemic control and other parameters of health were collected at study weeks 0 and 6. There were no differences in the baseline activity between groups (P = .36). Subjects in the active group significantly increased physical activity by 69% during the intervention phase of the study (P = .002), whereas there was no change in the physical activity of the control group (P > .05). High-density lipoprotein cholesterol and resting energy expenditure significantly increased in the active group (P < .05). Finally, plasminogen activator inhibitor 1 (PAI-1) activity was reduced by exercise relative to the control group (P = .03). There were no differences in any other study parameters during the 6-week study. In conclusion, short-term intervention with a pedometer increased physical activity and positively affected plasminogen activator inhibitor 1 activity in previously inactive patients with type 2 diabetes mellitus. The use of a pedometer may prove to be an effective tool for promoting healthy lifestyle changes that include daily physical activity and self-monitoring of therapeutic goals.

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    • "Prior studies using pedometers and goal setting have asked participants to set weekly goals [22], [26]–[31], prescribed goals for participants by adding standard amounts to baseline levels (e.g. 250 steps/day increase each week) [3], [32], or provided a static goal, such as 10,000 steps/day for the duration of the study [33], [34]. The current pilot study tested a novel approach that prescribed daily adaptive goals and feedback based on an algorithm using participants' own behavior in a randomized controlled trial. "
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    ABSTRACT: Physical activity (PA) interventions typically include components or doses that are static across participants. Adaptive interventions are dynamic; components or doses change in response to short-term variations in participant's performance. Emerging theory and technologies make adaptive goal setting and feedback interventions feasible. To test an adaptive intervention for PA based on Operant and Behavior Economic principles and a percentile-based algorithm. The adaptive intervention was hypothesized to result in greater increases in steps per day than the static intervention. Participants (N = 20) were randomized to one of two 6-month treatments: 1) static intervention (SI) or 2) adaptive intervention (AI). Inactive overweight adults (85% women, M = 36.9±9.2 years, 35% non-white) in both groups received a pedometer, email and text message communication, brief health information, and biweekly motivational prompts. The AI group received daily step goals that adjusted up and down based on the percentile-rank algorithm and micro-incentives for goal attainment. This algorithm adjusted goals based on a moving window; an approach that responded to each individual's performance and ensured goals were always challenging but within participants' abilities. The SI group received a static 10,000 steps/day goal with incentives linked to uploading the pedometer's data. A random-effects repeated-measures model accounted for 180 repeated measures and autocorrelation. After adjusting for covariates, the treatment phase showed greater steps/day relative to the baseline phase (p<.001) and a group by study phase interaction was observed (p = .017). The SI group increased by 1,598 steps/day on average between baseline and treatment while the AI group increased by 2,728 steps/day on average between baseline and treatment; a significant between-group difference of 1,130 steps/day (Cohen's d = .74). The adaptive intervention outperformed the static intervention for increasing PA. The adaptive goal and feedback algorithm is a "behavior change technology" that could be incorporated into mHealth technologies and scaled to reach large populations. ClinicalTrials.gov NCT01793064.
    PLoS ONE 12/2013; 8(12):e82901. DOI:10.1371/journal.pone.0082901 · 3.23 Impact Factor
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    • "Furthermore, subjects in the CWT group did not show any significant improvements in body composition or glycemic control. Type 2 diabetic patients’ self-paced walking speed is low, and potentially too low to improve health-related outcome (16,26), and previous studies using CWT interventions report only modest improvements in health-related parameters (9–11,13,15). Thus, it is likely that walking speed in our CWT group was close to the subjects’ normal walking speed, possibly explaining the apparent lack of effect. "
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    ABSTRACT: OBJECTIVEdTo evaluate the feasibility of free-living walking training in type 2 diabetes patients, and to investigate the effects of interval-walking training versus continuous-walking training upon physical fitness, body composition, and glycemic control. RESEARCH DESIGN AND METHOD SdSubjects with type 2 diabetes were randomized to a control (n = 8), continuous-walking (n = 12), or interval-walking group (n = 12). Training groups were prescribed five sessions per week (60 min/session) and were controlled with an accelerometer and a heart-rate monitor. Continuous walkers performed all training at moderate intensity, whereas interval walkers alternated 3-min repetitions at low and high intensity. Before and after the 4-month intervention, the following variables were measured: VO 2 max, body composition, and glycemic control (fasting glucose, HbA 1c , oral glucose tolerance test, and continuous glucose monitoring [CGM]). RESULTSdTraining adherence was high (89 6 4%), and training energy expenditure and mean intensity were comparable. VO 2 max increased 16.1 6 3.7% in the interval-walking group (P , 0.05), whereas no changes were observed in the continuous-walking or control group. Body mass and adiposity (fat mass and visceral fat) decreased in the interval-walking group only (P , 0.05). Glycemic control (elevated mean CGM glucose levels and increased fasting insulin) wors-ened in the control group (P , 0.05), whereas mean (P = 0.05) and maximum (P , 0.05) CGM glucose levels decreased in the interval-walking group. The continuous walkers showed no changes in glycemic control. CONCLUSION SdFree-living walking training is feasible in type 2 diabetes patients. Con-tinuous walking offsets the deterioration in glycemia seen in the control group, and interval walking is superior to energy expenditure–matched continuous walking for improving physical fitness, body composition, and glycemic control.
    Diabetes Care 01/2012; 36(2). DOI:10.2337/dc12-0658 · 8.57 Impact Factor
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    • "However, when focusing on investigations using patients with T2DM, the results are mixed. Two investigations have reported that patients with T2DM experienced a decrease in total cholesterol and low-density lipoprotein-cholesterol (LDL-C), as well as elevations in high-density lipoprotein-cholesterol (HDL-C) with aerobic training (consisting of mainly walking or running on a treadmill, cycling and calisthenics involving the upper and lower limbs) (Kadoglou et al., 2007; Ronnemaa et al., 1988) or walking (Araiza et al., 2006). However, other investigations with T2DM participants have noted no effect on the blood lipid profile following a period of exercise training (Loimaala et al., 2009; Sigal et al., 2007; Tudor-Locke et al., 2004). "
    Role of the Adipocyte in Development of Type 2 Diabetes, 09/2011; , ISBN: 978-953-307-598-3
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