Search

Abstract Purpose The FitMáx© was developed as a questionnaire-based instrument to estimate Cardiorespiratory Fitness (CRF) expressed as oxygen uptake at peak exercise (VO2peak). Test–retest reliability is a clinometric measurement property, which defines stability over time if multiple measurements are performed (i.e. reliability). The present study aimed to assess the test–retest reliability of the FitMáx©-questionnaire in different patient groups. Patients and methods A total of 127 cardiac, pulmonary and oncology patients and healthy subjects aged 19–84 years who completed the questionnaire twice within an average of 18 days were included for analysis. Participants were in a stable clinical situation (no acute disease or participating in a training program). To determine the test–retest reliability, the Intraclass Correlation Coefficient (ICC) and Standard Error of the Measurement (SEM) was calculated between the first (T0) and second (T1) administration of the questionnaires. Results An excellent agreement was found between the FitMáx©-questionnaire scores at T0 and T1, with an ICC of 0.97 (SEM 1.91) in the total study population and an ICC ranging from 0.93 to 0.98 (SEM 1.52–2.27) in the individual patient groups. Conclusion The FitMáx©-questionnaire proves to be reliable and stable over time to estimate CRF of patients and healthy subjects. Trial registration NTR (Netherlands Trial Register), NL8846. Registered 25 August 2020, https://trialsearch.who.int/Trial2.aspx?TrialID=NL8846

Background: Type 2 diabetes mellitus (T2DM) is associated with decreased muscle force generation. The disturbed force generation process in T2DM could be attributed to either or both agonist and antagonist muscles activation. The present study aims to assess the effects of T2DM on the interaction of antagonist and agonist muscles in the knee joint. Methods: The peak torque, root mean square (RMS) of the SEMG signals, the ratio of torque/RMS, and the interaction of antagonists and agonist muscles were compared between healthy and T2DM patients. Surface ElectroMyoGraphy (SEMG) of knee flexor and extensor muscles were recorded during concentric contraction with an isokinetic dynamometer at 60°/s in 13 T2DM and 12 healthy subjects. The independent sample t-tests were used to compare diabetic and healthy subjects. The significance level was set at 0.05. Results: The antagonist/agonist interaction during maximal extension (P = 0.010) and flexion (P = 0.022) torques of the knee joint showed significantly lower activation of antagonist muscles in T2DM patients than in healthy subjects. Lower knee flexion (41.3%) and extension torques (49.1%) and RMS of agonist and antagonist muscles were observed in T2DM. The torque/RMS ratio (P > 0.05) showed no significant differences in T2DM and healthy subjects. Conclusion: The reduced maximal knee flexor and extensor torques in T2DM are accompanied with the decreased myoelectric activity of corresponding muscles. The related mechanism could be attributed to lower values of antagonist/agonist interaction, which may point out some neural compensatory processes to preserve the functional capacity of the neuromuscular system in T2DM.

Abstract Mortality in type 2 diabetes, is determined not only by classical complications, but also by comorbidities, and is linked to hyperglycaemia and apparent even in prediabetes. We aimed to comprehensively investigate, in a population-based cohort, health burden defined as the presence of comorbidities in addition to classical complications and cardiometabolic risk factors, in not only type 2 diabetes but also prediabetes. Such population-based study has not been performed previously. Extensive phenotyping was performed in 3,410 participants of the population-based Maastricht Study (15.0% prediabetes and 28.6% type 2 diabetes) to assess presence of 17 comorbidities, six classical complications, and ten cardiometabolic risk factors. These were added up into individual and combined sum scores and categorized. Group differences were studied with multinomial regression analyses adjusted for age and sex. Individuals with type 2 diabetes and prediabetes, as compared to normal glucose metabolism (NGM), had greater comorbidities, classical complications, cardiometabolic risk factors and combined sum scores (comorbidities sum score ≥ 3: frequencies (95% CI) 61.5% (57.6;65.4) and 41.2% (36.5;45.9) vs. 25.4% (23.5;27.4), p-trend

Research suggests that sedentary behavior (SB) is negatively associated with cognitive outcomes. Interrupting prolonged sitting has been shown to improve cognitive functions, including executive functioning (EF), which is important for academic performance. No research has been conducted on the effect of standing on EF in VET students, who make up a large proportion of the adolescent population and who are known to sit more than other students of this age. In this study, we investigated the acute effects of reducing SB by short time standing on EF in vocational education and training (VET) students. In a randomized crossover study, 165 VET students were first taught for 15 min in seated position. After this, they performed while seated the Letter Memory Test for updating, and the Color Shape Test for shifting and inhibition. Students were randomly assigned to a sitting or standing condition. All students were taught again for 15 min and then took the same tests in the condition they were allocated to, respectively, standing or seated. After 1 week, the test procedure was repeated, in which students switched conditions. Mixed model analyses showed no significant effect of sitting or standing on updating, shifting, or inhibition. Also, no significant differences were found for the order of condition on updating, shifting, or inhibition. Our results suggest that 40 min of standing does not significantly influence EF among VET students.

A positive association has been found between physical activity (PA) and student mental wellbeing (SMW). This association has been mainly explored in secondary school and university students. Studies in vocational education and training (VET) are lacking, while VET students could especially benefit from exploring this association since research shows that VET students, who often come from low socioeconomic status (SES) households, are prone to low SMW. Low SMW can result in higher school dropout rates and long-term negative effects, such as unemployment, social exclusion, and impoverishment. The aim of the current study was to explore the association between total PA and different physical activity behaviors {PABs, i.e., moderate to vigorous physical activity (MVPA), light physical activity (LPA), and sedentary behavior (SB)}, and SMW in the VET setting. In this cross-sectional observational study, students wore an ActivPAL3™ accelerometer for 7 consecutive days to measure PAB. SMW was assessed using the Center for Epidemiologic Studies Depression Scale (CES-D) and the Rosenberg self-esteem questionnaire (RSE). Complete data for the analyses were obtained from 85 students. Multiple regression analyses showed a significant positive association between total PA and self-esteem and a significant negative association between total PA and depressive symptoms. Taking different PA intensities into account, there was a significant positive association between LPA and self-esteem and a significant negative association between LPA and depressive symptoms. No significant associations were found between MVPA and the outcome measures, although the associations were aligned with the findings for LPA. High levels of SB were significantly associated with low self-esteem; however, the association between SB and depressive symptoms was not significant. The significant positive associations between LPA and SMW and the negative association between SB and self-esteem indicate that decreasing SB and increasing LPA could contribute to improve SMW. Future research should determine if these are causal relationships.

In order to ensure long-term retention of information students must move from relying on surface-level approaches that are seemingly effective in the short-term to “building in” so called “desirable difficulties,” with the aim of achieving understanding and long-term retention of the subject matter. But how can this level of self-regulation be achieved by students when learning? Traditionally, research on learning strategy use is performed using self-report questionnaires. As this method is accompanied by several drawbacks, we chose a qualitative, in-depth approach to inquire about students' strategies and to investigate how students successfully self-regulate their learning. In order to paint a picture of effective learning strategy use, focus groups were organized in which previously identified, effectively self-regulating students (N = 26) were asked to explain how they approach their learning. Using a constructivist grounded theory methodology, a model was constructed describing how effective strategy users manage their learning. In this model, students are driven by a personal learning goal, adopting a predominantly qualitative, or quantitative approach to learning. While learning, students are continually engaged in active processing and self-monitoring. This process is guided by a constant balancing between adhering to established study habits, while maintaining a sufficient degree of flexibility to adapt to changes in the learning environment, assessment demands, and time limitations. Indeed, students reported using several strategies, some of which are traditionally regarded as “ineffective” (highlighting, rereading etc.). However, they used them in a way that fit their learning situation. Implications are discussed for the incorporation of desirable difficulties in higher education.

Abstract Background The majority of studies investigating associations between physical activity and mental health in adolescents have been cross-sectional in design. Potential associations between physical activity and mental health may be better examined longitudinally as physical activity levels tend to decrease in adolescence. Few studies have investigated these associations longitudinally in adolescents and none by measuring physical activity objectively. Methods A total of 158 Dutch adolescents (mean age 13.6 years, 38.6 % boys, grades 7 and 9 at baseline) participated in this longitudinal study. Physical activity, depressive symptoms and self-esteem were measured at baseline and at the 1-year follow-up. Physical activity was objectively measured with an ActivPAL3™ accelerometer during one full week. Depressive symptoms were measured with the Center for Epidemiologic Studies Depression Scale (CES-D) and self-esteem was assessed with the Rosenberg Self-Esteem Scale (RSE). Results were analysed using structural equation modelling. Results Physical activity levels decreased 15.3 % over a 1-year period (p

Background: We investigated whether substituting sitting with standing and self-perceived light walking in free-living conditions would improve cardiometabolic risk factors, mood, and cognition in overweight/obese adults.Methods: In a randomized, cross-over study, 24 (m/f: 13/11) sedentary overweight/obese participants (64 ± 7 years, BMI 29 ± 2 kg/m2) followed two activity regimens of each 4 days in free-living conditions: “Sit”: sitting 13.5 h/day, standing 1.4 h/day, self-perceived light-intensity walking 0.7 h/day; for “SitLess” these activities lasted 7.6, 4.0, and 4.3 h/day, respectively. Meals were standardized and physical activity was assessed by accelerometry (activPAL). Insulin sensitivity (expressed as Matsuda-index based on an oral glucose tolerance test), circulating lipids, blood pressure, mood (pleasantness and arousal), and cognition were assessed on the morning after the activity regimens. Quality of life and sleep were assessed on the last day of the activity regimens.Results: We observed that AUC (0–190 min) for insulin decreased by 20% after SitLess vs. Sit [10,125 (656) vs. 12,633 (818); p = 0.006]. Insulin sensitivity improved by 16% after SitLess vs. Sit [Matsuda-index, mean (SEM): 6.45 (0.25) vs. 5.58 (0.25) respectively; p = 0.007]. Fasting triglycerides, non-HDL-cholesterol, and apolipoprotein B decreased by 32, 7, and 4% respectively, whereas HDL-cholesterol increased by 7% after SitLess vs. Sit (all p < 0.01). Diastolic blood pressure was lower after SitLess vs. Sit (p < 0.05). Pleasantness (as one marker of mood status) after the oral glucose tolerance test was higher after SitLess vs. Sit (p < 0.05). There was no significant difference between regimens for cognition, quality of life and sleep.Conclusions: Reducing sitting time in free-living conditions markedly improved insulin sensitivity, circulating lipids, and diastolic blood pressure. Substituting sitting with standing and self-perceived light walking is an effective strategy to improve cardiometabolic risk factors in overweight/obese subjects.

Background: In an aging population, regular physical activity (PA) and exercise have been recognized as important factors in maintaining physical function and thereby preventing loss of independence and disability. However, (older) adults spent the majority of their day sedentary and therefore insight into the consequences of sedentary behavior on physical function, independent of PA, is warranted.Objective: To examine the associations of objectively measured sedentary time (ST), patterns of sedentary behavior, overall PA, and higher intensity PA (HPA) with objective measures of physical function.Methods: This is a cross-sectional study in 1,932 men and women (aged 40–75 years) participating in The Maastricht Study. The activPAL3 was used to assess daily sedentary behavior: ST (h), sedentary breaks (n), prolonged (≥30 min) sedentary bouts (n), and to assess time spent in (H)PA (h). Measures of physical function included: covered distance during a 6 min walk test [6MWD (meters)], timed chair rise stand test performance [TCSTtime (seconds)], grip strength (kg kg−1), and elbow flexion and knee extension strength (Nm kg−1). Linear regression analyses were used to examine associations between daily sedentary behavior and PA with physical function.Results: Every additional hour ST was associated with shorter 6MWD [B = −2.69 m (95% CI = −4.69; −0.69)] and lower relative elbow extension strength (B = −0.01 Nm kg−1 (−0.02; 0.00). More sedentary breaks were associated with faster TCSTtime: B = −0.55 s (−0.85; −0.26). Longer average sedentary bout duration was associated with slower TCSTtime [B = 0.17 s (0.09; 0.25)] and lower knee extension strength [B = −0.01 Nm kg−1 (−0.02; 0.00)]. Every hour of PA and HPA were associated with greater 6MWD [BPA = 15.88 m (9.87; 21.89), BHPA = 40.72 m (30.18; 51.25)], faster TCSTtime [BPA = −0.55 s (−1.03; −0.07), BHPA = −2.25 s (−3.09; −1.41)], greater elbow flexion strength [BPA = 0.03 Nm kg−1 (0.01; 0.07)], [BHPA = 0.05 Nm kg−1 (0.01; 0.08)], and greater knee extension strength [BPA = 0.04 Nm kg−1 (0.01; 0.07)], [BHPA = 0.13 Nm kg−1 (0.06; 0.20)].Conclusion: In adults aged 40–75 years, sedentary behavior appeared to be marginally associated with lower physical function, independent of HPA. This suggests that merely reducing sedentary behavior is insufficient to improve/maintain physical function. In contrast, engaging regularly in PA, in particular HPA, is important for physical function.

Schools can help to improve children’s health. The ‘Healthy Primary School of the Future’ (HPSF) aims to sustainably integrate health and well-being into the school system. This study examined the effects of HPSF on children’s dietary and physical activity (PA) behaviours after 1 and 2 years’ follow-up. The study (n = 1676 children) has a quasi-experimental design with four intervention schools, i.e., two full HPSF (focus: nutrition and PA) and two partial HPSF (focus: PA), and four control schools. Accelerometers and child- and parent-reported questionnaires were used at baseline, after 1 (T1) and 2 (T2) years. Mixed-model analyses showed significant favourable effects for the full HPSF versus control schools for, among others, school water consumption (effect size (ES) = 1.03 (T1), 1.14 (T2)), lunch intake of vegetables (odds ratio (OR) = 3.17 (T1), 4.39 (T2)) and dairy products (OR = 4.43 (T1), 4.52 (T2)), sedentary time (ES = −0.23 (T2)) and light PA (ES = 0.22 (T2)). Almost no significant favourable effects were found for partial HPSF compared to control schools. We conclude that the full HPSF is effective in promoting children’s health behaviours at T1 and T2 compared with control schools. Focusing on both nutrition and PA components seems to be more effective in promoting healthy behaviours than focusing exclusively on PA.

A valid non-wear algorithm for activity monitors is crucial to avoid the misclassification of sedentary time as non-wear time, and vice versa. Characteristics of the algorithm, such as time windows, should be well defined and tested. Furthermore, using tri-axial data might influence the algorithm’s performance. This study assessed the optimal time window length in a non-wear algorithm for overweight adults, applied to tri-axial data from sixteen participants. Ten time windows, from 10 up to 120 min, were tested with a diary as a criterion measure. We assessed the bias in non-wear time, sensitivity and specificity. The optimal time window length was based on ten participants; the validation of this time window was carried out with six other participants. The time window of 20 min showed the highest and 120 min showed the lowest mean amount of correctly classified non-wear time, at 94% and 70% respectively. Sensitivity and specificity were considered optimal in the 20 min time window. Validation of this time window demonstrated a sensitivity and specificity of 86% and 83% respectively. A 20 min time window showed the best non-wear estimations. The current study utilized tri-axial raw data and 1 s epoch data which might have facilitated the application of a short time window and thereby decreased the risk of misclassifying non-wear. [ABSTRACT FROM AUTHOR]

BackgroundClosed-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.MethodsWe 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).ResultsModels 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%).ConclusionsMachine 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.

Chronic kidney disease, which is defined as having a reduced kidney function (estimated glomerular filtration rate (eGFR)) and/or signs of kidney damage (albuminuria), is highly prevalent in Western society and is associated with adverse health outcomes, such as cardiovascular disease. This warrants a search for risk factors of lower eGFR and higher albuminuria. Physical activity and sedentary behavior may be such risk factors.To examine associations of physical activity (total, high, low), sedentary time and sedentary behavior patterns (breaks, prolonged bouts, average bout duration) with eGFR and albuminuria.We examined these associations in 2,258 participants of the Maastricht Study (average age 60.1±8.1 years; 51.3% men), who wore an accelerometer 24h/day on 7 consecutive days. Associations with continuous eGFR and categories of urinary albumin excretion (UAE;

BACKGROUND: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. OBJECTIVE: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). METHODS: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. RESULTS: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

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.

BackgroundTo date, detailed analyses of walking patterns using accelerometers during the 6-min walk test (6MWT) have not been performed in patients with chronic obstructive pulmonary disease (COPD). Therefore, it remains unclear whether and to what extent COPD patients have an altered walking pattern during the 6MWT compared to healthy elderly subjects.Methodology/principal findings79 COPD patients and 24 healthy elderly subjects performed the 6MWT wearing an accelerometer attached to the trunk. The accelerometer features (walking intensity, cadence, and walking variability) and subject characteristics were assessed and compared between groups. Moreover, associations were sought with 6-min walk distance (6MWD) using multiple ordinary least squares (OLS) regression models. COPD patients walked with a significantly lower walking intensity, lower cadence and increased walking variability compared to healthy subjects. Walking intensity and height were the only two significant determinants of 6MWD in healthy subjects, explaining 85% of the variance in 6MWD. In COPD patients also age, cadence, walking variability measures and their interactions were included were significant determinants of 6MWD (total variance in 6MWD explained: 88%).Conclusions/significanceCOPD patients have an altered walking pattern during 6MWT compared to healthy subjects. These differences in walking pattern partially explain the lower 6MWD in patients with COPD.