Music Tempo: A Tool for Regulating Walking Cadence and Physical Activity Intensity in Overweight Adults?

This study investigated if music tempo can prompt a desired walking cadence, and if music can provide a stimulus to regulate physical activity intensity in a longitudinal physical activity intervention with free-living adults. Overweight adults (n = 37; 94.26 ± 17.11 kg; 49.63 ± 12.37 years) were randomly assigned to an intervention (IG, n = 17) or usual care group (UC, n = 20) as part of a novel nine-month walking intervention. IG participants walked to self-selected music with a predetermined tempo and received a behavioural change support programme. At baseline, four-, six- and nine-months participants were asked to walk around an elliptical track at their habitual pace (0-2 min) and then in time to a predetermined tempo (2-8 min) designed to elicit moderate intensity. Cadence response (steps/min) was assessed and intensity (heart rate (bpm) recorded using wireless telemetry. A repeated measures general linear model (GLM) examined differences between groups over time (p < 0.05). All data is presented as means ± SD. At each assessment point both groups displayed an immediate cadence adjustment in response to music tempo (p < 0.01) i.e., habitual cadence vs. 3 METs target cadence (p < 0.05) and 3 METs target cadence vs. 5 METs target cadence (p < 0.05). Additionally, IG participants displayed an increased habitual cadence (0-2 min) at each assessment point (p < 0.05; 110 ± 9, 121.80 ± 7.5, 121.46 ± 10, 121.93 ± 7 steps/min respectively). UC participant's habitual cadence was unchanged from 0-9 months (p > 0.05; 120 ± 10, 116 ± 13, 119 ± 12 and 119 ± 9 steps/min respectively). Music tempo may be a useful regulatory tool to prompt the free-living individual to reach an appropriate stride rate to achieve a walking pace that is at least moderate intensity. It also appears that results may be trainable as throughout the study an increased habitual walking cadence was observed, in the absence of music.

Differences in educational attainment between obese and non-obese Kuwaiti female university students.

Individuals with obesity tend to perform less well than their non-obese peers in tertiary education, but there is little evidence from non-Western countries and recent studies. The present study aimed to test whether academic attainment differed between female undergraduates with obesity (defined by body mass index (BMI)), and those who were non-obese in Kuwait, a country with very high obesity prevalence. In 400 female Kuwaiti first- and second-year Social Science students (mean age 18⋅0, sd 0⋅6 years), educational attainment was defined as the Grade Point Average (GPA) across all subjects (from 1⋅00 to 4⋅00). The mean GPA (2⋅51, sd 0⋅53) among students defined as obese by the BMI (n 163) was significantly lower than among the students defined as non-obese by the BMI (n 237; 2⋅80, sd 0⋅63; P < 0⋅001), and those defined as obese were more likely to be in the lowest quartile for the GPA (OR 3⋅03; 95% CI 1⋅90, 4⋅85), independent of socio-economic status. Similar differences were observed between students defined as having high versus normal body fatness. Female undergraduates in Kuwait with obesity have lower academic attainment than their non-obese peers, and universities should consider measures to mitigate reduced attainment among their female undergraduates.

Diurnal patterns of objectively measured sedentary time and interruptions to sedentary time are associated with glycaemic indices in type 2 diabetes.

OBJECTIVES: To investigate diurnal patterns of sedentary time and interruptions to sedentary time and their associations with achievement of pre-meal glucose, post-meal glucose, bedtime glucose and the dawn phenomenon targets and with duration of hypoglycaemia, euglycaemia, hyperglycaemia and above target range. DESIGN: Intensive longitudinal study. METHODS: In 37 adults with type 2 diabetes, the FreeStyle Libre and activPAL3 were used to monitor glucose and sedentary time and interruptions to sedentary time in the morning (07:00-12:00), afternoon (12:00-17:00) and evening (17:00-23:00) for 14 days. Diurnal patterns of sedentary behaviour and associations with glycaemic indices were assessed using repeated measures ANOVA and linear regressions. RESULTS: Sedentary time was significantly higher in the evening (43.47±7.37min/h) than the morning (33.34±8.44min/h) and afternoon (37.26±8.28min/h). Interruptions to sedentary time were significantly lower in the evening (2.64±0.74n/h) than the morning (3.69±1.08n/h) and afternoon (3.06±0.87n/h). Sedentary time in the morning and afternoon was associated with lower achievement of the dawn phenomenon target. Sedentary time in the evening was associated with lower achievement of post-lunch glucose target. Interruptions to sedentary time in the morning and afternoon were associated with higher achievement of pre-dinner glucose target. Interruptions to sedentary time in the evening showed beneficial associations with achievement of post-dinner glucose and bedtime glucose targets and euglycaemia. CONCLUSIONS: Prolonged sedentary behaviour is high in the evening. Interruptions to sedentary time, particularly in the evening, have beneficial associations with glycaemic indices. Interventions targeting interruptions to sedentary time in the evening may be more clinically relevant.

Impact of free-living pattern of sedentary behaviour on intra-day glucose regulation in type 2 diabetes.

PURPOSE: To investigate how the pattern of sedentary behaviour affects intra-day glucose regulation in type 2 diabetes. METHODS: This intensive longitudinal study was conducted in 37 participants with type 2 diabetes (age, 62.8 ± 10.5 years). Glucose and sedentary behaviour/physical activity were assessed with a continuous glucose monitoring (Abbott FreeStyle Libre) and an activity monitor (activPAL3) for 14 days. Multiple regression models with generalised estimating equations (GEEs) approach were used to assess the associations of sedentary time and breaks in sedentary time with pre-breakfast glucose, pre-lunch glucose, pre-dinner glucose, post-breakfast glucose, post-lunch glucose, post-dinner glucose, bedtime glucose, the dawn phenomenon, time in target glucose range (TIR, glucose 3.9-10 mmol/L) and time above target glucose range (TAR, glucose > 10 mmol/L). RESULTS: Sedentary time was associated with higher pre-breakfast glucose (p = 0.001), pre-dinner glucose (p < 0.001), post-lunch glucose (p = 0.005), post-dinner glucose (p = 0.013) and the dawn phenomenon (p < 0.001). Breaks in sedentary time were associated with lower pre-breakfast glucose (p = 0.023), pre-dinner glucose (p = 0.023), post-breakfast glucose (p < 0.001) and the dawn phenomenon (p = 0.004). The association between sedentary time and less TIR (p = 0.022) and the association between breaks in sedentary time and more TIR (p = 0.001) were also observed. CONCLUSIONS: Reducing sedentary time and promoting breaks in sedentary time could be clinically relevant to improve intra-day glucose regulation in type 2 diabetes.

Dose-response between frequency of breaks in sedentary time and glucose control in type 2 diabetes: A proof of concept study.

OBJECTIVES: This study aimed to investigate dose-response between frequency of breaks in sedentary time and glucose control. DESIGN: Randomised three-treatment, two-period balanced incomplete block trial. METHODS: Twelve adults with type 2 diabetes (age, 60±11years; body mass index, 30.2±4.7kg/m2) participated in two of the following treatment conditions: sitting for 7h interrupted by 3min light-intensity walking breaks every (1) 60min (Condition 1), (2) 30min (Condition 2), and (3) 15min (Condition 3). Postprandial glucose incremental area under the curves (iAUCs) and 21-h glucose total area under the curve (AUC) were measured using continuous glucose monitoring. Standardised meals were provided. RESULTS: Compared with Condition 1 (6.7±0.8mmolL-1×3.5h-1), post-breakfast glucose iAUC was reduced for Condition 3 (3.5±0.9 mmolL-1×3.5h-1, p˂0.04). Post-lunch glucose iAUC was lower in Condition 3 (1.3±0.9mmolL-1×3.5h-1, p˂0.03) and Condition 2 (2.1±0.7mmolL-1×3.5h-1, p˂0.05) relative to Condition 1 (4.6±0.8mmolL-1×3.5h-1). Condition 3 (1.0±0.7mmolL-1×3.5h-1, p=0.02) and Condition 2 (1.6±0.6mmolL-1×3.5h-1, p˂0.04) attenuated post-dinner glucose iAUC compared with Condition 1 (4.0±0.7mmolL-1×3.5h-1). Cumulative 10.5-h postprandial glucose iAUC was lower in Condition 3 than Condition 1 (p=0.02). Condition 3 reduced 21-h glucose AUC compared with Condition 1 (p<0.001) and Condition 2 (p=0.002). However, post-breakfast glucose iAUC, cumulative 10.5-h postprandial glucose iAUC and 21-h glucose AUC were not different between Condition 2 and Condition 1 (p˃0.05). CONCLUSIONS: There could be dose-response between frequency of breaks in sedentary time and glucose. Interrupting sedentary time every 15min could produce better glucose control.

The associations of sedentary time and breaks in sedentary time with 24-hour glycaemic control in type 2 diabetes.

The aim of this study was to investigate the associations of accelerometer-assessed sedentary time and breaks in sedentary time with 24-h events and duration of hypoglycaemia (<3.9 mmol/l), euglycaemia (3.9-7.8 mmol/l), hyperglycaemia (>7.8 mmol/l) and above target glucose (>9 mmol/l). Thirty-seven participants with type 2 diabetes (age, 62.8 ±â€¯10.5 years; body mass index, 29.6 ±â€¯6.8 kg/m2) in Glasgow, United Kingdom were enrolled between February 2016 and February 2017. Participants wore an activity monitor (activPAL3) recording the time and pattern of sedentary behaviour and a continuous glucose monitoring (CGM, Abbott FreeStyle Libre) for up to 14 days. Linear regression analyses were used to investigate the associations. Participants spent 3.7%, 64.7%, 32.1% and 19.2% of recording h/day in hypoglycaemia, euglycaemia, hyperglycaemia and above target, respectively. There was a negative association between sedentary time and time in euglycaemia (ß = -0.44, 95% CI -0.86; -0.03, p = 0.04). There was a trend towards a positive association between sedentary time and time in hyperglycaemia (ß = 0.36, 95% CI -0.05; 0.78, p = 0.08). Breaks in sedentary time was associated with higher time in euglycaemia (ß = 0.38, 95% CI 0.00; 0.75, p = 0.04). To conclude, in individuals with type 2 diabetes, more time spent in unbroken and continuous sedentary behaviour was associated with poorer glucose control. Conversely, interrupting sedentary time with frequent breaks appears to improve glycaemic control. Therefore, this should be considered as a simple adjunct therapy to improve clinical outcomes in type 2 diabetes.

Methods for combining continuously measured glucose and activity data in people with Type 2 diabetes: Challenges and solutions.

AIMS: To present the novel application of combining continuously measured glucose with continuous accelerometer measured physical activity and sedentary behaviour data and discusses the principles used and challenges faced in combining and analysing these two sets of data in the context of diabetes management. METHODS: The background and rationale for exploring glucose, physical activity and sedentary behaviour in people with Type 2 diabetes is presented, the paper outlines the technologies used, the individual data extraction and finally the combined data analysis. A case study approach is used to illustrate the application of the combined data processing and analysis. RESULTS: The data analytic principles used could be transferred to different conditions where continuous data sets are being combined to help individuals or health professionals better manage and care for people with long term conditions. CONCLUSIONS: Future work should focus on generating validated techniques to visualise combined data sets and explore ways to present data back to the individual in an effective way to support health care management and rehabilitation.

A Systematic and Integrated Review of Mobile-Based Technology to Promote Active Lifestyles in People With Type 2 Diabetes.

AIM: The aim was to review studies examining the effectiveness, acceptability, and feasibility of mobile-based technology for promoting active lifestyles in people with type 2 diabetes (T2D). BACKGROUND: Benefits of leading an active lifestyle following a diagnosis of T2D, including improved glycemic control, have been reported. Studies examining the specific use of mobile-based technologies to promote an active lifestyle in T2D have not previously been reviewed. METHODS: Research studies examining effectiveness, feasibility or acceptability of mobile-based technology for active lifestyle promotion for T2D management were included (n = 9). The databases searched included PubMed, Medline, ScienceDirect, and ACM Digital Library (January 2005 to October 2015). Studies were categorized as (1) informing, (2) monitoring, (3) provoking, or (4) sustaining behavior change. RESULTS: Technologies used included smartphone or tablet apps, diabetes personal digital assistant, continuous glucose monitor and accelerometer, pedometer, and a website delivered by a smartphone. No articles examined the effectiveness of mobile-based technology in monitoring health behaviors and behavior change. Four of the studies found mobile-based technology to be motivational and supportive for behavior change. The visual reinforcement was identified as motivational. The feasibility and acceptability of using mobile-based technology to provide sustained lifestyle change and the effectiveness of mobile-based technology in monitoring health behaviors and behavior change have not been investigated. No studies examined all 3 of the outcomes or focused decreasing the participants' sedentary behavior. CONCLUSIONS: Limited research has examined the feasibility, acceptability, and effectiveness of mobile-based technology to promote active lifestyles and subsequently good diabetes management in people with T2D.

Cadence, energy expenditure, and gait symmetry during music-prompted and self-regulated walking in adults with unilateral transtibial amputation.

BACKGROUND: Walking cadence has shown promise for estimating walking intensity in healthy adults. Auditory cues have been shown to improve gait symmetry in populations with movement disorders. We investigated the walking cadence-energy expenditure relationship in unilateral transtibial amputees (TTAs), and the potential of music cues for regulating walking cadence and improving gait symmetry. METHODS: Seventeen unilateral TTAs performed 2 5-min treadmill walking trials, followed by 2 5-min overground walking trials (self-regulated "brisk" intensity, and while attempting to match a moderate-tempo digital music cue). RESULTS: Walking cadence significantly (P < .001) and accurately (R(2) = .55, SEE = 0.50 METs) predicted energy expenditure, and a cadence of 86 steps·min(-1) was equivalent to a 3-MET intensity. Although most participants were able to match cadence to prescribed music tempo, gait symmetry was not improved during the music-guided condition, compared with the self-regulated condition. CONCLUSIONS: This is the first study to investigate the utility of walking cadence for monitoring and regulating walking intensity in adults with lower limb prosthesis. Cadence has similar or superior accuracy as an indicator of walking intensity in this population, compared with the general population, and adults with a unilateral TTA are capable of walking at moderate intensity and above for meaningful bouts of time.

Stride rate and walking intensity in healthy older adults.

PURPOSE: The study investigated (a) walking intensity (stride rate and energy expenditure) under three speed instructions; (b) associations between stride rate, age, height, and walking intensity; and (c) synchronization between stride rate and music tempo during overground walking in a population of healthy older adults. METHODS: Twenty-nine participants completed 3 treadmill-walking trials and 3 overground-walking trials at 3 self-selected speeds. Treadmill VO2 was measured using indirect calorimetry. Stride rate and music tempo were recorded during overground-walking trials. RESULTS: Mean stride rate exceeded minimum thresholds for moderate to vigorous physical activity (MVPA) under slow (111.41 ± 11.93), medium (118.17 ± 11.43), and fast (123.79 ± 11.61) instructions. A multilevel model showed that stride rate, age, and height have a significant effect (p < .01) on walking intensity. CONCLUSIONS: Healthy older adults achieve MVPA with stride rates that fall below published minima for MVPA. Stride rate, age, and height are significant predictors of energy expenditure in this population. Music can be a useful way to guide walking cadence.