Validation of the SQUASH physical activity questionnaire using accelerometry: The NEO study.

Objective: To investigate the construct validity of the SQUASH (Short QUestionnaire to ASsess Health-enhancing physical activity). Design: This is a cross-sectional analysis using baseline measurements from middle-aged participants in the Netherlands Epidemiology of Obesity (NEO) study. The SQUASH consists of questions on eleven physical activities investigating days per week, average duration per day and intensity, leading to a summed score in Metabolic Equivalent of Task hours (MET h) per week. To assess convergent validity, a Spearman's rank correlation between SQUASH and ActiHeart was calculated. To assess extreme group validity, three groups expected to differ in SQUASH total physical activity outcome were compared. For discriminative validity, a Spearman's rank correlation between SQUASH physical activity and participant height was investigated. Results: SQUASH data were available for 6550 participants (mean age 56 years, 44% men, mean BMI 26.3, 15% with knee OA, 13% with hand OA). Median physical activity (interquartile range) was 118 (76; 154) MET h/week according to SQUASH and 75 (58; 99) according to ActiHeart. Convergent validity was weak (rho â€‹= â€‹0.20). For all three extreme group comparisons, a statistically significant difference was present. Discriminative validity was present (rho â€‹= â€‹0.01). Compared with the reference quintile, those with a discrepancy SQUASH â€‹> â€‹ActiHeart and SQUASH â€‹< â€‹ActiHeart were relatively younger and more often male. Conclusions: The construct validity of the SQUASH seems sub-optimal. Physical activity reported by the SQUASH was generally higher than reported by ActiHeart. Whether the differences between SQUASH and ActiHeart are e.g. due to different underlying domains, limitations to our study, or reflect true differences needs further investigation.

Cross-sectional associations between 24-hour movement behaviors and cardiometabolic health among adults with type 2 diabetes mellitus: A comparison according to weight status.

OBJECTIVES: Type 2 diabetes mellitus (T2DM) is a chronic disease associated with overweight and obesity. Evidence suggests that 24-hour movement behaviors (24 h-MBs) play a crucial role in cardiometabolic health. However, it is not yet known if 24 h-MBs differ between weight status groups among people with T2DM (PwT2DM) and how 24 h-MBs are associated with their cardiometabolic health. DESIGN: Cross-sectional study. METHODS: Cardiometabolic variables (i.e. Body Mass Index (BMI), waist circumference (WC), HbA1c, fasting glucose, triglycerides, total-cholesterol, HDL-cholesterol, LDL-cholesterol, blood pressure) and 24 h-MBs (accelerometry and sleep-diary) of 1001 PwT2DM were collected. Regression models using compositional data analysis explored differences in 24 h-MBs between weight status groups and analyzed associations with cardiometabolic variables. RESULTS: The 24 h-MBs of PwT2DM being obese consisted of less sleep, light physical activity (LPA) and moderate to vigorous physical activity (MVPA) and more sedentary time (ST) per day as compared to PwT2DM being overweight or normal weight (p < 0.001). Regardless of weight status, the largest associations were found when reallocating 20 min a day from ST into MVPA for BMI (-0.32 kg/m2; [-0.55; -0.09], -1.09 %), WC (-1.44 cm, [-2.26; -0.62], -1.35 %) and HDL-cholesterol (0.02 mmol/l, [0.01, 0.02], +1.59 %), as well as from ST into LPA for triglycerides (-0.04 mmol/l, [-0.05; -0.03], -2.3 %). Moreover, these associations were different when stratifying people by short-to-average (7.7 h/night) versus long sleep (9.3 h/night) period. CONCLUSIONS: This study highlights the importance of 24 h-MBs in the cardiometabolic health of PwT2DM. Shifting time from ST and/or sleep toward LPA or MVPA might theoretically benefit cardiometabolic health among relatively inactive PwT2DM, irrespective of weight status.

Timing of physical activity in relation to liver fat content and insulin resistance.

AIMS/HYPOTHESIS: We hypothesised that the insulin-sensitising effect of physical activity depends on the timing of the activity. Here, we examined cross-sectional associations of breaks in sedentary time and timing of physical activity with liver fat content and insulin resistance in a Dutch cohort. METHODS: In 775 participants of the Netherlands Epidemiology of Obesity (NEO) study, we assessed sedentary time, breaks in sedentary time and different intensities of physical activity using activity sensors, and liver fat content by magnetic resonance spectroscopy (n=256). Participants were categorised as being most active in the morning (06:00-12:00 hours), afternoon (12:00-18:00 hours) or evening (18:00-00:00 hours) or as engaging in moderate-to-vigorous-physical activity (MVPA) evenly distributed throughout the day. Most active in a certain time block was defined as spending the majority (%) of total daily MVPA in that block. We examined associations between sedentary time, breaks and timing of MVPA with liver fat content and HOMA-IR using linear regression analyses, adjusted for demographic and lifestyle factors including total body fat. Associations of timing of MVPA were additionally adjusted for total MVPA. RESULTS: The participants (42% men) had a mean (SD) age of 56 (4) years and a mean (SD) BMI of 26.2 (4.1) kg/m2. Total sedentary time was not associated with liver fat content or insulin resistance, whereas the amount of breaks in sedentary time was associated with higher liver fat content. Total MVPA (-5%/h [95% CI -10%/h, 0%/h]) and timing of MVPA were associated with reduced insulin resistance but not with liver fat content. Compared with participants who had an even distribution of MVPA throughout the day, insulin resistance was similar (-3% [95% CI -25%, 16%]) in those most active in morning, whereas it was reduced in participants who were most active in the afternoon (-18% [95% CI -33%, -2%]) or evening (-25% [95% CI -49%, -4%]). CONCLUSIONS/INTERPRETATION: The number of daily breaks in sedentary time was not associated with lower liver fat content or reduced insulin resistance. Moderate-to-vigorous activity in the afternoon or evening was associated with a reduction of up to 25% in insulin resistance. Further studies should assess whether timing of physical activity is also important for the occurrence of type 2 diabetes.

Objectively Measured Physical Activity and Body Fatness: Associations with Total Body Fat, Visceral Fat, and Liver Fat.

PURPOSE: It remains unclear to what extent habitual physical activity and sedentary time (ST) are associated with visceral fat and liver fat. We studied the substitution of ST with time spent physically active and total body fat (TBF), visceral adipose tissue (VAT), and hepatic triglyceride content (HTGC) in middle-age men and women. DESIGN: In this cross-sectional analysis of the Netherlands Epidemiology of Obesity study, physical activity was assessed in 228 participants using a combined accelerometer and heart rate monitor. TBF was assessed by the Tanita bioelectrical impedance, VAT by magnetic resonance imaging, and HTGC by proton-MR spectroscopy. Behavioral intensity distribution was categorized as ST, time spent in light physical activity (LPA), and moderate to vigorous physical activity (MVPA). To estimate the effect of replacing 30 min·d-1 of ST with 30 min·d-1 LPA or MVPA, we performed isotemporal substitution analyses, adjusted for sex, age, ethnicity, education, the Dutch Healthy Diet index, and smoking. RESULTS: Included participants (41% men) had a mean ± SD age of 56 ± 6 yr and spent 88 ± 56 min in MVPA and 9.0 ± 2.1 h of ST. Replacing 30 min·d-1 of ST with 30 min of MVPA was associated with 1.3% less TBF (95% confidence interval = -2.0 to -0.7), 7.8 cm2 less VAT (-11.6 to -4.0), and 0.89 times HTGC (0.82-0.97). Replacement with LPA was not associated with TBF (-0.03%; -0.5 to 0.4), VAT (-1.7 cm2; -4.4 to 0.9), or HTGC (0.98 times; 0.92-1.04). CONCLUSIONS: Reallocation of time spent sedentary with time spent in MVPA, but not LPA, was associated with less TBF, visceral fat, and liver fat. These findings contribute to the development of more specified guidelines on ST and physical activity.

Associations of cells from both innate and adaptive immunity with lower nerve conduction velocity: the Maastricht Study.

INTRODUCTION: Distal sensorimotor polyneuropathy (DSPN) is common in people with diabetes but is also found in pre-diabetes. Peripheral nerve myelin damage, which can be assessed by reduced nerve conduction velocity (NCV), is an essential feature of DSPN. Emerging evidence indicates that the development of DSPN may involve the activation of the immune system. However, available studies have mainly investigated circulating immune mediators, whereas the role of immune cells remains unclear. Therefore, we aimed to test whether leukocyte subsets are associated with NCV. RESEARCH DESIGN AND METHODS: This cross-sectional study analyzed data from 850 individuals (of whom 252 and 118 had type 2 diabetes and pre-diabetes, respectively) of the Maastricht Study. NCV was measured in the peroneal and tibial motor nerves and the sural sensory nerve and summed to calculate a standardized NCV sum score. Associations between percentages of leukocyte subsets and NCV sum scores were estimated using linear regression models adjusted for demographic, lifestyle, metabolic and clinical covariates. RESULTS: After adjustment for covariates, higher percentages of basophils and CD4+ T cells were associated with lower NCV (p=0.014 and p=0.005, respectively). The percentage of CD8+ T cells was positively associated with NCV (p=0.022). These associations were not modified by glucose metabolism status (all pinteraction >0.05). No associations were found for monocytes, eosinophils, neutrophils, lymphocytes, total T cells, Treg cells and B cells. CONCLUSIONS: The associations of basophils, CD4+ and CD8+ T cells with NCV suggest that cell types from both innate and adaptive immunity may be implicated in the development of DSPN.

Cardiometabolic risk factors as determinants of peripheral nerve function: the Maastricht Study.

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, HbA1c, 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 (ß) and 95% CIs in order to compare the magnitudes of observed associations between all risk factors and outcomes. RESULTS: Hyperglycaemia (fasting glucose or HbA1c) was associated with worse sensorimotor nerve function for all six outcome measures, with associations of strongest magnitude for motor peroneal and tibial NCV, ßfasting glucose = -0.17 SD (-0.21, -0.13) and ßfasting 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.

The Association Between ß-Blocker Use and Cardiorespiratory Fitness: The Maastricht Study.

PURPOSE: ß-Blockers (BBs) have been associated with a reduced cardiorespiratory fitness (CRF). This is possibly caused by inhibition of ß2-receptors in the airways. However, there are limited data available on ß-receptor selectivity and CRF. We therefore aimed to assess the association between BB use and CRF and to assess the association between ß-receptor selectivity and CRF. METHODS: Participants in the Maastricht Study were aged between 40 and 75 years. Exposure to BB use was determined by use of pharmacy records. General linear models were used to obtain adjusted means of 2 proxies for CRF: covered distance during the 6-minute walk test (6MWT) and estimated maximum power output adjusted for body mass ( Wmax kg-1) during the submaximal cycle ergometer test. Adjusted means were compared between current, past, and never BB users. Current users were subsequently stratified by ß-receptor selectivity and dose. RESULTS: Compared to never use, current use was associated with a lower CRF, based on the 6MWT (current use: 569.7 m; never use: 580.4 m [ P = .010]), but not based on the cycling test (current use: 2.14 W kg-1; never use: 2.13 W kg-1 [ P = .690]). There was no difference between current selective and current nonselective BB use. CONCLUSION: ß-Blockers use was associated with CRF based on the 6MWT but not the cycling test. There was no difference between current selective and nonselective BB users, possibly due to the small number of nonselective BB users, differential underlying diseases, other pharmacological properties, and limitations related to the proxies of the outcome.

Which is more important for cardiometabolic health: sedentary time, higher intensity physical activity or cardiorespiratory fitness? The Maastricht Study.

AIMS/HYPOTHESES: Our aim was to examine the independent and combined (cross-sectional) associations of sedentary time (ST), higher intensity physical activity (HPA) and cardiorespiratory fitness (CRF) with metabolic syndrome and diabetes status. METHODS: In 1933 adults (aged 40-75 years) ST and HPA (surrogate measure for moderate to vigorous physical activity) were measured with the activPAL3. CRF was assessed by submaximal cycle-ergometer testing. Metabolic syndrome was defined according to the Adult Treatment Panel (ATP) III guidelines. Diabetes status (normal, prediabetes [i.e. impaired glucose tolerance and/or impaired fasting glucose] or type 2 diabetes) was determined from OGTT. (Multinomial) logistic regression analyses were used to calculate likelihood for the metabolic syndrome, prediabetes and type 2 diabetes according to ST, HPA and CRF separately and combinations of ST-CRF and HPA-CRF. RESULTS: Higher ST, lower HPA and lower CRF were associated with greater odds for the metabolic syndrome and type 2 diabetes independently of each other. Compared with individuals with high CRF and high HPA (CRFhigh-HPAhigh), odds for the metabolic syndrome and type 2 diabetes were higher in groups with a lower CRF regardless of HPA. Individuals with low CRF and low HPA (CRFlow-HPAlow) had a particularly high odds for the metabolic syndrome (OR 5.73 [95% CI 3.84, 8.56]) and type 2 diabetes (OR 6.42 [95% CI 3.95, 10.45]). Similarly, compared with those with high CRF and low ST (CRFhigh-STlow), those with medium or low CRF had higher odds for the metabolic syndrome, prediabetes and type 2 diabetes, irrespective of ST. In those with high CRF, high ST was associated with significantly high odds for the metabolic syndrome (OR 2.93 [95% CI 1.72, 4.99]) and type 2 diabetes (OR 2.21 [95% CI 1.17, 4.17]). The highest odds for the metabolic syndrome and type 2 diabetes were observed in individuals with low CRF and high ST (CRFlow-SThigh) (OR [95% CI]: the metabolic syndrome, 9.22 [5.74, 14.80]; type 2 diabetes, 8.38 [4.83, 14.55]). CONCLUSIONS/INTERPRETATION: These data suggest that ST, HPA and CRF should all be targeted in order to optimally reduce the risk for the metabolic syndrome and type 2 diabetes.

Sedentary Behavior Is Only Marginally Associated with Physical Function in Adults Aged 40-75 Years-the Maastricht Study.

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.

Replacement Effects of Sedentary Time on Metabolic Outcomes: The Maastricht Study.

INTRODUCTION: Sedentary time has been associated with detrimental health effects, so in some countries, guidelines to reduce sedentary time have been developed. As reducing sedentary time inevitably results in more nonsedentary time, effects of this reduction may depend on the activity with which it is replaced. PURPOSE: This study aimed to examine associations of theoretical reallocations of sedentary time to standing or stepping with cardiometabolic outcomes and type 2 diabetes. METHODS: We included 2213 participants (51% men, mean ± SD age = 60.0 ± 8.1 yr) of the Maastricht Study who were asked to wear an accelerometer 24 h·d for a week. We calculated daily sedentary, standing, and stepping time. An isotemporal substitution modeling approach was applied to examine effects on waist circumference; body mass index; cholesterol, triacylglycerol, glucose, and insulin levels; metabolic syndrome; and type 2 diabetes. RESULTS: Replacement of sedentary time (30 min·d) with stepping was associated with lower odds for metabolic syndrome (odds ratio [OR] = 0.72, 95% confidence interval [CI] = 0.66-0.78) and type 2 diabetes (OR = 0.79, 95% CI = 0.72-0.87), more favorable waist circumference (B = -1.42, 95% CI = -1.78 to -1.06), and body mass index (B = -0.48, 95% CI = -0.62 to -0.35) and improved cholesterol, triacylglycerol, glucose, and insulin levels. Replacing sedentary time with standing was associated with lower odds for metabolic syndrome and type 2 diabetes and favorable outcomes in waist circumference, cholesterol, triacylglycerol, and insulin levels. CONCLUSION: Theoretical replacements of sedentary time with nonsedentary time (both standing and stepping) were associated with lower odds for metabolic syndrome, type 2 diabetes, and beneficial metabolic outcomes. These results could be important for the general population, including those who cannot meet physical activity guidelines. Consideration should be given to developing recommendations for daily reallocating sedentary time.

Sedentary Behavior, Physical Activity, and Fitness-The Maastricht Study.

PURPOSE: This cross-sectional study examined the mutual independent associations of sedentary behavior, lower intensity physical activity (LPA) and higher intensity physical activity (HPA) (an approximation of moderate to vigorous physical activity with cardiorespiratory fitness (CRF). METHODS: Two thousand twenty-four participants were included from The Maastricht Study (mean ± SD age, 59.7 ± 8.1 yr; 49.6% men). With the activPAL3 activity monitor, we assessed sedentary time (ST), sedentary pattern variables (number of sedentary breaks, average sedentary bout duration, and number of prolonged sedentary bouts [≥30 min]), LPA, and HPA. CRF was calculated as maximum power output per kilogram body mass (Wmax·kg) estimated from a submaximal cycle ergometer test. Linear regression analyses and isotemporal substitution analyses were used to examine associations of ST, sedentary pattern variables, and HPA with CRF. Analyses were stratified by sex. RESULTS: One hour of ST per day was associated with a lower Wmax·kg: Bmen = -0.03 (95% confidence interval [CI], -0.05 to -0.01) and Bwomen = -0.02 (95% CI, -0.04 to 0.00), independent of HPA. No statistically significant associations between sedentary patterns variables and CRF were observed. LPA was associated with a higher Wmax·kg: Bmen = 0.12 (95% CI, 0.07-0.17) and Bwomen = 0.12 (95% CI, 0.07-0.18). HPA was associated with a higher Wmax·kg: Bmen = 0.48 (95% CI, 0.38-0.58) and Bwomen = 0.27 (95% CI, 0.18-0.36). Replacing ST with LPA (Bmen, 0.08; 95% CI, 0.03-0.14; Bwomen, 0.10; 95% CI, 0.05-0.16) or with HPA (Bmen, 0.49; 95% CI, 0.39-0.59; Bwomen = 0.28; 95% CI, 0.19-0.36), but not with standing was associated with higher CRF. CONCLUSIONS: Modest associations between sedentary behavior and CRF were observed. Replacing ST with LPA was associated with higher CRF, which could be of particular importance for individuals who cannot engage in HPA. Nonetheless, replacing ST with HPA was associated with greatest estimated change in CRF.

Associations of total amount and patterns of sedentary behaviour with type 2 diabetes and the metabolic syndrome: The Maastricht Study.

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.

Identifying waking time in 24-h accelerometry data in adults using an automated algorithm.

As accelerometers are commonly used for 24-h measurements of daily activity, methods for separating waking from sleeping time are necessary for correct estimations of total daily activity levels accumulated during the waking period. Therefore, an algorithm to determine wake and bed times in 24-h accelerometry data was developed and the agreement of this algorithm with self-report was examined. One hundred seventy-seven participants (aged 40-75 years) of The Maastricht Study who completed a diary and who wore the activPAL3™ 24 h/day, on average 6 consecutive days were included. Intraclass correlation coefficient (ICC) was calculated and the Bland-Altman method was used to examine associations between the self-reported and algorithm-calculated waking hours. Mean self-reported waking hours was 15.8 h/day, which was significantly correlated with the algorithm-calculated waking hours (15.8 h/day, ICC = 0.79, P = < 0.001). The Bland-Altman plot indicated good agreement in waking hours as the mean difference was 0.02 h (95% limits of agreement (LoA) = -1.1 to 1.2 h). The median of the absolute difference was 15.6 min (Q1-Q3 = 7.6-33.2 min), and 71% of absolute differences was less than 30 min. The newly developed automated algorithm to determine wake and bed times was highly associated with self-reported times, and can therefore be used to identify waking time in 24-h accelerometry data in large-scale epidemiological studies.

Moderate activity and fitness, not sedentary time, are independently associated with cardio-metabolic risk in U.S. adults aged 18-49.

This cross-sectional study is one of the first to examine and compare the independent associations of objectively measured sedentary time, moderate to vigorous physical activity (MVPA) and fitness with cardio-metabolic risk factors. We studied 543 men and women (aged 18-49 years) from the NHANES 2003-2004 survey. Sedentary time and MVPA were measured by accelerometry. Fitness was assessed with a submaximal treadmill test. Cardio-metabolic risk factors included: waist circumference (WC), BMI, blood pressure, fasting glucose, HDL- and non HDL cholesterol, triglycerides (TG), and C-reactive protein (CRP). Sedentary time, MVPA and fitness were used as predictors for the cardio-metabolic outcomes in a multiple regression analysis. Standardized regression coefficients were computed. Results show that sedentary time was associated with HDL-cholesterol (ß=-0.080, p=0.05) and TG (ß=0.080, p=0.03). These results became non-significant after adjustment for MVPA and fitness. MVPA was associated with WC (ß=-0.226), BMI (ß=-0.239), TG (ß=-0.108) and HDL-cholesterol (ß=0.144) (all p<0.05). These results remained significant after adjustment for sedentary time and fitness. Fitness was associated with WC (ß=-0.287), BMI (ß=-0.266), systolic blood pressure (ß=-0.159), TG (ß=-0.092), and CRP (ß=-0.130) (all p<0.05). After adjustment for sedentary time and MVPA these results remained significant. These differences in relative importance of sedentary time, MVPA and fitness on cardio-metabolic-risk are important in the design of prevention programs. In this population, the strength of the associations between MVPA and fitness with cardio-metabolic markers appeared to be similar; both MVPA and fitness showed independent associations with cardio-metabolic risk factors. In contrast, sedentary time showed no independent associations with cardio-metabolic risk after correction for fitness and MVPA.

Torso undergarments: their merit for clothed and armored individuals in hot-dry conditions.

INTRODUCTION: The aim of this study was to evaluate how the textile composition of torso undergarment fabrics may impact upon thermal strain, moisture transfer, and the thermal and clothing comfort of fully clothed, armored individuals working in a hot-dry environment (41.2 degrees C and 29.8% relative humidity). METHODS: Five undergarment configurations were assessed using eight men who walked for 120 min (4 km x h(-1)), then alternated running (2 min at 10 km x h(-1)) and walking (2 min at 4 km x h(-1)) for 20 min. Trials differed only in the torso undergarments worn: no t-shirt (Ensemble A); 100% cotton t-shirt (Ensemble B); 100% woolen t-shirt (Ensemble C); synthetic t-shirt (Ensemble D: nylon, polyethylene, elastane); hybrid shirt (Ensemble E). RESULTS: Thermal and cardiovascular strain progressively increased throughout each trial, with the average terminal core temperature being 38.5 degrees C and heart rate peaking at 170 bpm across all trials. However, no significant between-trial separations were evident for core or mean skin temperatures, or for heart rate, sweat production, evaporation, the within-ensemble water vapor pressures, or for thermal or clothing discomfort. CONCLUSION: Thus, under these conditions, neither the t-shirt textile compositions, nor the presence or absence of an undergarment, offered any significant thermal, central cardiac, or comfort advantages. Furthermore, there was no evidence that any of these fabrics created a significantly drier microclimate next to the skin.