Epidemiological studies suggest that excessive sitting time is associated with increased health risk, independent of the performance of exercise. We hypothesized that a daily bout of exercise cannot ...compensate the negative effects of inactivity during the rest of the day on insulin sensitivity and plasma lipids.
Eighteen healthy subjects, age 21±2 year, BMI 22.6±2.6 kgm(-2) followed randomly three physical activity regimes for four days. Participants were instructed to sit 14 hr/day (sitting regime); to sit 13 hr/day and to substitute 1 hr of sitting with vigorous exercise 1 hr (exercise regime); to substitute 6 hrs sitting with 4 hr walking and 2 hr standing (minimal intensity physical activity (PA) regime). The sitting and exercise regime had comparable numbers of sitting hours; compared to the exercise regime, the minimal intensity PA regime had a higher estimated daily energy expenditure (238kcal/day) corrected. PA was assessed continuously by an activity monitor (ActivPAL) and a diary. Measurements of insulin sensitivity (oral glucose tolerance test, OGTT) and plasma lipids were performed in the fasting state, the morning after the 4 days of each regime. In the sitting regime, daily energy expenditure was about 500 kcal lower than in both other regimes. Area under the curve for insulin during OGTT was significantly lower after the minimal intensity PA regime compared to both sitting and exercise regimes 6727.3±4329.4 vs 7752.0±3014.4 and 8320.4±5383.7 mU•min/ml, respectively. Triglycerides, non-HDL cholesterol and apolipoprotein B plasma levels improved significantly in the minimal intensity PA regime compared to sitting and showed non-significant trends for improvement compared to exercise.
One hour of daily physical exercise cannot compensate the negative effects of inactivity on insulin level and plasma lipids if the rest of the day is spent sitting. Reducing inactivity by increasing the time spent walking/standing is more effective than one hour of physical exercise, when energy expenditure is kept constant.
Celotno besedilo
Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
Aims/hypothesis
We aimed to examine the effects of breaking sitting with standing and light-intensity walking vs an energy-matched bout of structured exercise on 24 h glucose levels and insulin ...resistance in patients with type 2 diabetes.
Methods
In a randomised crossover study, 19 patients with type 2 diabetes (13 men/6 women, 63 ± 9 years old) who were not using insulin each followed three regimens under free-living conditions, each lasting 4 days: (1) Sitting: 4415 steps/day with 14 h sitting/day; (2) Exercise: 4823 steps/day with 1.1 h/day of sitting replaced by moderate- to vigorous-intensity cycling (at an intensity of 5.9 metabolic equivalents METs); and (3) Sit Less: 17,502 steps/day with 4.7 h/day of sitting replaced by standing and light-intensity walking (an additional 2.5 h and 2.2 h, respectively, compared with the hours spent doing these activities in the Sitting regimen). Blocked randomisation was performed using a block size of six regimen orders using sealed, non-translucent envelopes. Individuals who assessed the outcomes were blinded to group assignment. Meals were standardised during each intervention. Physical activity and glucose levels were assessed for 24 h/day by accelerometry (activPAL) and a glucose monitor (iPro2), respectively. The incremental AUC (iAUC) for 24 h glucose (primary outcome) and insulin resistance (HOMA2-IR) were assessed on days 4 and 5, respectively.
Results
The iAUC for 24 h glucose (mean ± SEM) was significantly lower during the Sit Less intervention than in Sitting (1263 ± 189 min × mmol/l vs 1974 ± 324 min × mmol/l;
p
= 0.002), and was similar between Sit Less and Exercise (Exercise: 1383 ± 194 min × mmol/l;
p
= 0.499). Exercise failed to improve HOMA2-IR compared with Sitting (2.06 ± 0.28 vs 2.16 ± 0.26;
p
= 0.177). In contrast, Sit Less (1.89 ± 0.26) significantly reduced HOMA2-IR compared with Exercise (
p
= 0.015) as well as Sitting (
p
= 0.001).
Conclusions/interpretation
Breaking sitting with standing and light-intensity walking effectively improved 24 h glucose levels and improved insulin sensitivity in individuals with type 2 diabetes to a greater extent than structured exercise. Thus, our results suggest that breaking sitting with standing and light-intensity walking may be an alternative to structured exercise to promote glycaemic control in patients type 2 diabetes.
Trial registration:
Clinicaltrials.gov NCT02371239
Funding:
The study was supported by a Kootstra grant from Maastricht University Medical Centre
+
, and the Dutch Heart Foundation. Financial support was also provided by Novo Nordisk BV, and Medtronic and Roche made the equipment available for continuous glucose monitoring
Both obesity and the metabolic syndrome are associated with increased risk of cardiovascular diseases and type 2 diabetes. Although both frequently occur together in the same individual, obesity and ...the metabolic syndrome can also develop independently from each other. The (patho)physiology of "metabolically healthy obese" (i.e. obese without metabolic syndrome) and "metabolically unhealthy non-obese" phenotypes (i.e. non-obese with metabolic syndrome) is not fully understood, but physical activity and sedentary behavior may play a role.
To examine objectively measured physical activity and sedentary behavior across four groups: I) "metabolically healthy obese" (MHO); II) "metabolically unhealthy obese" (MUO); III)"metabolically healthy non-obese" (MHNO); and IV) "metabolically unhealthy non-obese" (MUNO).
Data were available from 2,449 men and women aged 40-75 years who participated in The Maastricht Study from 2010 to 2013. Participants were classified into the four groups according to obesity (BMI≥30kg/m2) and metabolic syndrome (ATPIII definition). Daily activity was measured for 7 days with the activPAL physical activity monitor and classified as time spent sitting, standing, and stepping.
In our study population, 562 individuals were obese. 19.4% of the obese individuals and 72.7% of the non-obese individuals was metabolically healthy. After adjustments for age, sex, educational level, smoking, alcohol use, waking time, T2DM, history of CVD and mobility limitation, MHO (n = 107) spent, per day, more time stepping (118.2 versus 105.2 min; p<0.01) and less time sedentary (563.5 versus 593.0 min., p = 0.02) than MUO (n = 440). In parallel, MHNO (n = 1384) spent more time stepping (125.0 versus 115.4 min; p<0.01) and less time sedentary (553.3 versus 576.6 min., p<0.01) than MUNO (n = 518).
Overall, the metabolically healthy groups were less sedentary and more physically active than the metabolically unhealthy groups. Therefore, physical activity and sedentary time may partly explain the presence of the metabolic syndrome in obese as well as non-obese individuals.
Celotno besedilo
Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
We determined muscle fiber type–specific hypertrophy and changes in satellite cell (SC) content following a 12-week resistance training program in 13 healthy, elderly men (72 ± 2 years). Leg strength ...and body composition (dual-energy X-ray absorptiometry and computed tomography) were assessed, and muscle biopsy samples were collected. Leg strength increased 25%–30% after training (p < .001). Leg lean mass and quadriceps cross-sectional area increased 6%–9% (p < .001). At baseline, mean fiber area and SC content were smaller in the Type II versus Type I muscle fibers (p < .01). Following training, Type II muscle fiber area increased from 5,438 ± 319 to 6,982 ± 503 μm2 (p < .01). Type II muscle fiber SC content increased from 0.048 ± 0.003 to 0.084 ± 0.008 SCs per fiber (p < .001). No changes were observed in the Type I muscle fibers. In older adults, skeletal muscle tissue is still capable of inducing SC proliferation and differentiation, resulting in Type II muscle fiber hypertrophy.
Aims/hypothesis
The study investigated cross-sectional associations of total amount and patterns of sedentary behaviour with glucose metabolism status and the metabolic syndrome.
Methods
We included ...2,497 participants (mean age 60.0 ± 8.1 years, 52% men) from The Maastricht Study who were asked to wear an activPAL accelerometer 24 h/day for 8 consecutive days. We calculated the daily amount of sedentary time, daily number of sedentary breaks and prolonged sedentary bouts (≥30 min), and the average duration of the sedentary bouts. To determine glucose metabolism status, participants underwent an oral glucose tolerance test. Associations of sedentary behaviour variables with glucose metabolism status and the metabolic syndrome were examined using multinomial logistic regression analyses.
Results
Overall, 1,395 (55.9%) participants had normal glucose metabolism, 388 (15.5%) had impaired glucose metabolism and 714 (28.6%) had type 2 diabetes. The odds ratio per additional hour of sedentary time was 1.22 (95% CI 1.13, 1.32) for type 2 diabetes and 1.39 (1.27, 1.53) for the metabolic syndrome. No significant or only weak associations were seen for the number of sedentary breaks, number of prolonged sedentary bouts or average bout duration with either glucose metabolism status or the metabolic syndrome.
Conclusions/interpretation
An extra hour of sedentary time was associated with a 22% increased odds for type 2 diabetes and a 39% increased odds for the metabolic syndrome. The pattern in which sedentary time was accumulated was weakly associated with the presence of the metabolic syndrome. These results suggest that sedentary behaviour may play a significant role in the development and prevention of type 2 diabetes, although longitudinal studies are needed to confirm our findings.
Departments of 1 Movement Sciences and 2 Human Biology, Nutrition and Toxicology Research Institute Maastricht (NUTRIM), Maastricht University, Maastricht, The Netherlands
Submitted 13 June 2006
; ...accepted in final form 17 August 2006
Satellite cells (SC) are essential for skeletal muscle growth and repair. Because sarcopenia is associated with type II muscle fiber atrophy, we hypothesized that SC content is specifically reduced in the type II fibers in the elderly. A total of eight elderly (E; 76 ± 1 yr) and eight young (Y; 20 ± 1 yr) healthy males were selected. Muscle biopsies were collected from the vastus lateralis in both legs. ATPase staining and a pax7-antibody were used to determine fiber type-specific SC content (i.e., pax7-positive SC) on serial muscle cross sections. In contrast to the type I fibers, the proportion and mean cross-sectional area of the type II fibers were substantially reduced in E vs. Y. The number of SC per type I fiber was similar in E and Y. However, the number of SC per type II fiber was substantially lower in E vs. Y (0.044 ± 0.003 vs. 0.080 ± 0.007; P < 0.01). In addition, in the type II fibers, the number of SC relative to the total number of nuclei and the number of SC per fiber area were also significantly lower in E. This study is the first to show type II fiber atrophy in the elderly to be associated with a fiber type-specific decline in SC content. The latter is evident when SC content is expressed per fiber or per fiber area. The decline in SC content might be an important factor in the etiology of type II muscle fiber atrophy, which accompanies the loss of skeletal muscle with aging.
sarcopenia; muscle stem cells; atrophy; metabolism
Address for reprint requests and other correspondence: L. Verdijk, Dept. of Movement Sciences, Faculty of Health Sciences, Maastricht University, PO Box 616, 6200 MD Maastricht, The Netherlands (e-mail: Lex.Verdijk{at}bw.unimaas.nl )
Although self-regulated learning (SRL) is becoming increasingly important in modern educational contexts, disagreements exist regarding its measurement. One particularly important issue is whether ...self-reports represent valid ways to measure this process. Several researchers have advocated the use of behavioral indicators of SRL instead. An outstanding research debate concerns the extent to which it is possible to compare behavioral measures of SRL to traditional ways of measuring SRL using self-report questionnaire data, and which of these methods provides the most valid and reliable indicator of SRL. The current review investigates this question. It was found that granularity is an important concept in the comparison of SRL measurements, influencing the degree to which students can accurately report on their use of SRL strategies. The results show that self-report questionnaires may give a relatively accurate insight into students’ global level of self-regulation, giving them their own value in educational research and remediation. In contrast, when students are asked to report on specific SRL strategies, behavioral measures give a more accurate account. First and foremost, researchers and practitioners must have a clear idea about their research question or problem statement, before choosing or combining either form of measurement.
Closed-loop insulin delivery systems, which integrate continuous glucose monitoring (CGM) and algorithms that continuously guide insulin dosing, have been shown to improve glycaemic control. The ...ability to predict future glucose values can further optimize such devices. In this study, we used machine learning to train models in predicting future glucose levels based on prior CGM and accelerometry data.
We used data from The Maastricht Study, an observational population-based cohort that comprises individuals with normal glucose metabolism, prediabetes, or type 2 diabetes. We included individuals who underwent >48h of CGM (n = 851), most of whom (n = 540) simultaneously wore an accelerometer to assess physical activity. A random subset of individuals was used to train models in predicting glucose levels at 15- and 60-minute intervals based on either CGM data or both CGM and accelerometer data. In the remaining individuals, model performance was evaluated with root-mean-square error (RMSE), Spearman's correlation coefficient (rho) and surveillance error grid. For a proof-of-concept translation, CGM-based prediction models were optimized and validated with the use of data from individuals with type 1 diabetes (OhioT1DM Dataset, n = 6).
Models trained with CGM data were able to accurately predict glucose values at 15 (RMSE: 0.19mmol/L; rho: 0.96) and 60 minutes (RMSE: 0.59mmol/L, rho: 0.72). Model performance was comparable in individuals with type 2 diabetes. Incorporation of accelerometer data only slightly improved prediction. The error grid results indicated that model predictions were clinically safe (15 min: >99%, 60 min >98%). Our prediction models translated well to individuals with type 1 diabetes, which is reflected by high accuracy (RMSEs for 15 and 60 minutes of 0.43 and 1.73 mmol/L, respectively) and clinical safety (15 min: >99%, 60 min: >91%).
Machine learning-based models are able to accurately and safely predict glucose values at 15- and 60-minute intervals based on CGM data only. Future research should further optimize the models for implementation in closed-loop insulin delivery systems.
Celotno besedilo
Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
Aims/hypothesis
We aimed to examine associations of cardiometabolic risk factors, and (pre)diabetes, with (sensorimotor) peripheral nerve function.
Methods
In 2401 adults (aged 40–75 years) we ...previously determined fasting glucose, HbA
1c
, triacylglycerol, HDL- and LDL-cholesterol, inflammation, waist circumference, blood pressure, smoking, glucose metabolism status (by OGTT) and medication use. Using nerve conduction tests, we measured compound muscle action potential, sensory nerve action potential amplitudes and nerve conduction velocities (NCVs) of the peroneal, tibial and sural nerves. In addition, we measured vibration perception threshold (VPT) of the hallux and assessed neuropathic pain using the DN4 interview. We assessed cross-sectional associations of risk factors with nerve function (using linear regression) and neuropathic pain (using logistic regression). Associations were adjusted for potential confounders and for each other risk factor. Associations from linear regression were presented as standardised regression coefficients (
β
) and 95% CIs in order to compare the magnitudes of observed associations between all risk factors and outcomes.
Results
Hyperglycaemia (fasting glucose or HbA
1c
) was associated with worse sensorimotor nerve function for all six outcome measures, with associations of strongest magnitude for motor peroneal and tibial NCV,
β
fasting glucose
= −0.17 SD (−0.21, −0.13) and
β
fasting glucose
= −0.18 SD (−0.23, −0.14), respectively. Hyperglycaemia was also associated with higher VPT and neuropathic pain. Larger waist circumference was associated with worse sural nerve function and higher VPT. Triacylglycerol, HDL- and LDL-cholesterol, and blood pressure were not associated with worse nerve function; however, antihypertensive medication usage (suggestive of history of exposure to hypertension) was associated with worse peroneal compound muscle action potential amplitude and NCV. Smoking was associated with worse nerve function, higher VPT and higher risk for neuropathic pain. Inflammation was associated with worse nerve function and higher VPT, but only in those with type 2 diabetes. Type 2 diabetes and, to a lesser extent, prediabetes (impaired fasting glucose and/or impaired glucose tolerance) were associated with worse nerve function, higher VPT and neuropathic pain (
p
for trend <0.01 for all outcomes).
Conclusions/interpretation
Hyperglycaemia (including the non-diabetic range) was most consistently associated with early-stage nerve damage. Nonetheless, larger waist circumference, inflammation, history of hypertension and smoking may also independently contribute to worse nerve function.
Recent studies suggest that substituting sitting with light physical activity has beneficial metabolic effects, but it is unclear if this is associated with parallel changes in endothelial function. ...Data from three randomized cross-over studies were analyzed, in which 61 subjects (with normal weight, overweight and type 2 diabetes) followed different activity regimens (Sit, SitLess and/or Exercise) of four days each. Subjects were instructed to sit 14 h/day ('Sit'), to substitute 1 h/day of sitting with moderate-to-vigorous cycling ('Exercise') or to substitute 5-6 h/day sitting with light-intensity walking and standing ('SitLess'). Physical activity was assessed 24 h/day by accelerometry (ActivPAL) and diet was standardized. Fasted circulating biomarkers of endothelial dysfunction, lipids and insulin sensitivity were assessed the morning after each activity regimen. The endothelial dysfunction score (ED-score) was computed by averaging the Z-scores of the circulating biomarkers of endothelial dysfunction. Compared to Sit, Exercise resulted in lower ED-score, sICAM1 and sE-selectin (p < 0.05), while no significant changes were observed after SitLess. The ED-score, sVCAM1 and sE-selectin were lower after Exercise compared to SitLess (p < 0.05). In contrast, compared to Sit, insulin sensitivity (HOMA2-IR) and plasma lipids (HDL-cholesterol, non-HDL-cholesterol, total cholesterol and Apo B) did not change significantly after Exercise but were improved after SitLess (p < 0.05). In conclusion, light physical activity and moderate-to-vigorous physical activity had a differential effect on risk markers of cardio-metabolic health and suggest the need of both performing structured exercise as well as reducing sitting time on a daily basis.
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