Clustered Cardiometabolic Risk Score Research Articles

Associations of 24 h time-use compositions of sitting, standing, physical activity and sleeping with optimal cardiometabolic risk and glycaemic control: The Maastricht Study

Aims/hypothesisThe associations of sitting, standing, physical activity and sleep with cardiometabolic health and glycaemic control markers are interrelated. We aimed to identify 24 h time-use compositions associated with optimal metabolic and glycaemic control and determine whether these varied by diabetes status.MethodsThigh-worn activPAL data from 2388 participants aged 40–75 years (48.7% female; mean age 60.1 [SD = 8.1] years; n=684 with type 2 diabetes) in The Maastricht Study were examined. Compositional isometric log ratios were generated from mean 24 h time use (sitting, standing, light-intensity physical activity [LPA], moderate-to-vigorous physical activity [MVPA] and sleeping) and regressed with outcomes of waist circumference, fasting plasma glucose (FPG), 2 h plasma glucose, HbA1c, the Matsuda index expressed as z scores, and with a clustered cardiometabolic risk score. Overall analyses were adjusted for demographics, smoking, dietary intake and diabetes status, and interaction by diabetes status was examined separately. The estimated difference when substituting 30 min of one behaviour with another was determined with isotemporal substitution. To identify optimal time use, all combinations of 24 h compositions possible within the study footprint (1st–99th percentile of each behaviour) were investigated to determine those cross-sectionally associated with the most-optimal outcome (top 5%) for each outcome measure.ResultsCompositions lower in sitting time and with greater standing time, physical activity and sleeping had the most beneficial associations with outcomes. Associations were stronger in participants with type 2 diabetes (p<0.05 for interactions), with larger estimated benefits for waist circumference, FPG and HbA1c when sitting was replaced by LPA or MVPA in those with type 2 diabetes vs the overall sample. The mean (range) optimal compositions of 24 h time use, considering all outcomes, were 6 h (range 5 h 40 min–7 h 10 min) for sitting, 5 h 10 min (4 h 10 min–6 h 10 min) for standing, 2 h 10 min (2 h–2 h 20 min) for LPA, 2 h 10 min (1 h 40 min–2 h 20 min) for MVPA and 8 h 20 min (7 h 30 min–9 h) for sleeping.Conclusions/interpretationShorter sitting time and more time spent standing, undergoing physical activity and sleeping are associated with preferable cardiometabolic health. The substitutions of behavioural time use were significantly stronger in their associations with glycaemic control in those with type 2 diabetes compared with those with normoglycaemic metabolism, especially when sitting time was balanced with greater physical activity.Graphical

Fitness and fatness in children and adolescents: investigating their role in the association between physical activity and cardiometabolic health.

To verify the role of the combination of fitness and fatness in the relationship between physical activity (PA) and cardiometabolic risk in children and adolescents. This is a cross-sectional study performed with 2786 children and adolescents (6 to 17 years). Fitness was determined by the cardiorespiratory fitness (CRF) six-minute walking and running test. Waist circumference (WC) was considered a fatness indicator. A selfreported questionnaire was used to determine PA practice, whereas the clustered cardiometabolic risk score (cMetS) was calculated by summing z-scores of triglycerides, total cholesterol/HDL-C ratio, systolic blood pressure, glucose, and WC. Considering the combination of CRF (fitness) and WC (fatness), the following phenotypes were created: Fit/Unfat, Fit/Fat, Unfit/Unfat and Unfit/Fat. Moderation analyses were tested using linear regression models. Significant interactions were found between PA and Unfit/Fat category (β = -0.001; p = 0.001) only for adolescents. The interaction observed in the Unfit/Fat phenotype indicated that adolescents who practise PA for 330 minutes per week presented lower cMetS compared to those who do not practise or practise for 60 minutes respectively. The combination of fitness and fatness moderates the relationship between PA and cardiometabolic risk, suggesting that adolescents, particularly those who are less fit and present high adiposity, should be encouraged to engage in regular PA to improve their metabolic health.

Physical Activity Assessed by Wrist and Thigh Worn Accelerometry and Associations with Cardiometabolic Health.

Physical activity is increasingly being captured by accelerometers worn on different body locations. The aim of this study was to examine the associations between physical activity volume (average acceleration), intensity (intensity gradient) and cardiometabolic health when assessed by a thigh-worn and wrist-worn accelerometer. A sample of 659 office workers wore an Axivity AX3 on the non-dominant wrist and an activPAL3 micro on the right thigh concurrently for 24 h a day for 8 days. An average acceleration (proxy for physical activity volume) and intensity gradient (intensity distribution) were calculated from both devices using the open-source raw accelerometer processing software GGIR. Clustered cardiometabolic risk (CMR) was calculated using markers of cardiometabolic health, including waist circumference, triglycerides, HDL-cholesterol, mean arterial pressure and fasting glucose. Linear regression analysis assessed the associations between physical activity volume and intensity gradient with cardiometabolic health. Physical activity volume derived from the thigh-worn activPAL and the wrist-worn Axivity were beneficially associated with CMR and the majority of individual health markers, but associations only remained significant after adjusting for physical activity intensity in the thigh-worn activPAL. Physical activity intensity was associated with CMR score and individual health markers when derived from the wrist-worn Axivity, and these associations were independent of volume. Associations between cardiometabolic health and physical activity volume were similarly captured by the thigh-worn activPAL and the wrist-worn Axivity. However, only the wrist-worn Axivity captured aspects of the intensity distribution associated with cardiometabolic health. This may relate to the reduced range of accelerations detected by the thigh-worn activPAL.

Neighborhood socioeconomic status and cardiometabolic risk: mediating roles of domain-specific physical activities and sedentary behaviors

PurposeWe examined the potential mediating roles of domain-specific physical activities and sedentary behaviors in the relationship between area-level socioeconomic status (SES) and cardiometabolic risk. MethodsData were from the 2011/2012 Australian Diabetes, Obesity and Lifestyle study (n = 3431). The outcome was a clustered cardiometabolic risk (CCR) score, and the exposure was suburb-level SES. Potential mediators were domain-specific physical activities and sedentary behaviors. Multilevel linear regression models examined associations between SES and potential mediators (α) and between mediators and CCR (β). Mediation was assessed using the joint-significance test. ResultsHigher SES was associated with a lower CCR score. Lower SES was associated with less frequent walking for transport, lower vigorous-intensity recreational physical activity, and higher TV time, which were associated with higher CCR scores. However, higher SES was associated with longer transport-related sitting time (all modes and in cars), which were associated with higher CCR scores. ConclusionsThe SES-cardiometabolic risk relationship may be partially explained by walking for transport, vigorous-intensity recreational physical activity, and TV viewing. These findings, which require corroboration from prospective evidence and clarification of the roles of transport-related sitting and occupational physical activity, can inform initiatives addressing socioeconomic inequalities in cardiometabolic health.

Moderate-to-vigorous physical activity, but not sedentary time, predicts changes in cardiometabolic risk factors in 10-y-old children: the Active Smarter Kids Study

Background: Cross-sectional data have suggested an inverse relation between physical activity and cardiometabolic risk factors that is independent of sedentary time. However, little is known about which subcomponent of physical activity may predict cardiometabolic risk factors in youths. Objective: We examined the independent prospective associations between objectively measured sedentary time and subcomponents of physical activity with individual and clustered cardiometabolic risk factors in healthy children aged 10 y. Design: We included 700 children (49.1% males; 50.9% females) in which sedentary time and physical activity were measured with the use of accelerometry. Systolic blood pressure, waist circumference (WC), and fasting blood sample (total cholesterol, high-density lipoprotein cholesterol, triglycerides, glucose, fasting insulin) were measured with the use of standard clinical methods and analyzed individually and as a clustered cardiometabolic risk score standardized by age and sex (z score). Exposure and outcome variables were measured at baseline and at follow-up 7 mo later. Results: Sedentary time was not associated with any of the individual cardiometabolic risk factors or clustered cardiometabolic risk in prospective analyses. Moderate physical activity at baseline predicted lower concentrations of triglycerides (P = 0.021) and homeostatic model assessment for insulin resistance (P = 0.027) at follow-up independent of sex, socioeconomic status, Tanner stage, monitor wear time, or WC. Moderate-to-vigorous physical activity (P = 0.043) and vigorous physical activity (P = 0.028) predicted clustered cardiometabolic risk at follow-up, but these associations were attenuated after adjusting for WC. Conclusions: Physical activity, but not sedentary time, is prospectively associated with cardiometabolic risk in healthy children. Public health strategies aimed at improving children’s cardiometabolic profile should strive for increasing physical activity of at least moderate intensity rather than reducing sedentary time. This trial was registered at clinicaltrials.gov as NCT02132494.

The Longitudinal Association of Cardiorespiratory Fitness and Adiposity With Clustered Cardiometabolic Risk: A Mediation Analysis.

Previous literature has demonstrated the mediating role of adiposity in the association between cardiorespiratory fitness (CRF) and cardiometabolic risk as well as the potential role of CRF in attenuating the adverse consequences associated with excess weight. This study aimed to evaluate the mediating role of CRF and adiposity in the possible association with cardiometabolic risk. Observational 3-year longitudinal study that included 420 children and adolescents (10.50 [2.05]y of age at baseline; 56.2% girls). Body mass index (BMI) was calculated, and CRF was evaluated using field assessments. A clustered cardiometabolic risk score (cMetS) was calculated from glucose, systolic blood pressure, total cholesterol/high-density lipoprotein cholesterol ratio, and triglycerides z scores. Analyses evaluated the mediating role of BMI in the association between CRF and cMetS as well as whether CRF mediated the association between BMI and cMetS. BMI at baseline was directly associated with the cMetS at follow-up (0.102; 95% confidence interval, 0.020 to 0.181), independently of CRF, whereas CRF was only indirectly associated with cMetS at follow-up through BMI (-0.036; 95% confidence interval, -0.070 to -0.009), meaning that the association between CRF and cMetS was explained via the mediation role of BMI. BMI presented direct association with cMetS, whereas CRF exhibited indirect association with cMetS mediated via BMI.

IS THE AMOUNT OF WEIGHT LOSS AFTER BARIATRIC SURGERY A FACTOR DETERMINING CARDIOMETABOLIC RISK REDUCTION?

Objective: This study aimed to investigate whether differential weight loss amount appropriately reflects improvements in cardiometabolic health in patients undergoing bariatric surgery. Materials and Methods: Patients who underwent bariatric surgery (BS) and were followed up for six months were divided into three groups according to their weight loss (Group-1: Low weight loss; Group-2: Moderate weight loss; Group-3: High weight loss). Before and after surgery, patients were evaluated for metabolic syndrome (MetS) using waist circumference, blood pressure, glucose, HDL-C, and triglyceride data, and a clustered cardiometabolic risk (CMR) score was obtained for each patient using a calculator available in the literature online. Changes in each MetS criterion and CMR score in the groups before and after the operation, and their relations with each other were compared. Results: Sixty-six patients were included in the study. It was observed that the prevalence of MetS, which was 74.2% before the operation, decreased to 25.8%. A significant difference was observed between the groups in the decrease in weight, waist circumference, fat mass, fasting blood sugar, and HOMA-IR values. However, no significant difference was found between the groups in the change in MetS parameters and CMR scores. While a significant negative correlation was found between the amount of weight loss and the difference in the CMR score, no relation was observed between each MetS parameter and the amount of weight loss. It was also found that each 1% increase in weight loss was associated with a 57% decrease in the CMR score. Conclusion: Although there is a significant decrease in cardiometabolic risk parameters after bariatric surgery, the amount of weight loss of the patients does not affect the individual parameters. However, using a scoring system to evaluate and monitor patients’ cardiometabolic cluster risks will make it possible to follow the gradual changes in patients after surgery, making interventions by physicians and nutritionists more targeted and efficient.

Associations of Vigorous Gardening With Cardiometabolic Risk Markers for Middle-Aged and Older Adults.

This study investigates the associations of vigorous-intensity gardening time with cardiometabolic health risk markers. This cross-sectional study (AusDiab) analyzed 2011-2012 data of 3,664 adults (55% women, mean [range], age = 59.3 [34-94] years) in Australia. Multiple linear regression models examined associations of time spent participating in vigorous gardening (0, <150min/week, ≥150min/week) with a clustered cardiometabolic risk (CMR) score and its components, for the whole sample and stratified by age and gender. Of participants, 61% did no vigorous gardening, 23% reported <150min/week, and 16% reported ≥150min/week. In the whole sample, spending ≥150min/week in vigorous gardening was associated with lower CMR (lower CMR score, waist circumference, diastolic blood pressure, and triglycerides) compared with no vigorous gardening. Stratified analyses suggested that these associations were almost exclusively observed for older adults and women. These findings suggest the public health potential of vigorous-intensity gardening in reducing CMR.

Associations of circulating xanthine oxidoreductase activity with cardiometabolic risk markers in overweight and obese Japanese men: a cross-sectional pilot study.

Circulating xanthine oxidoreductase (XOR) activity may contribute to the pathogenesis of obesity-related adverse cardiometabolic profiles. This pilot study aimed to examine the cross-sectional associations between plasma XOR activity and cardiometabolic risk (CMR) markers in overweight and obese men. In 64 overweight and obese Japanese men (aged 31–63 years), plasma XOR activity and several CMR markers, such as homeostasis model assessment of insulin resistance (HOMA-IR), and clustered CMR score were measured in each participant. Clustered CMR score was constructed based on waist circumference, triglyceride, blood pressure, fasting plasma glucose, and high-density lipoprotein cholesterol. Plasma XOR activity in overweight and obese men was positively associated with the body mass index, waist circumference, visceral fat area, body fat mass, hemoglobin A1c, serum 8-hydroxy-2'-deoxyguanosine, HOMA-IR, and clustered CMR score and was inversely associated with handgrip strength and high-density lipoprotein cholesterol. Multiple linear regression analysis further demonstrated that the associations of plasma XOR activity with HOMA-IR and the clustered CMR score remained significant after adjustment for covariates including uric acid. Our data demonstrate that circulating XOR activity was independently associated, albeit modestly, with HOMA-IR and the clustered CMR score. These preliminary findings suggest that circulating XOR activity can potentially be one of the preventive targets and biomarkers of cardiometabolic disorders in over­weight and obese men.

Low performance-related physical fitness levels are associated with clustered cardiometabolic risk score in schoolchildren: a cross-sectional study

PurposeThe study aim was to verify if there were associations between performance-related physical fitness levels and the clustered cardiometabolic risk score among children and adolescents.MethodsThe cross-sectional study involved 1200 (655 females) children and adolescents aged 7–17 years. Performancerelated physical fitness levels (upper limb strength [ULS], lower limb strength [LLS], agility, speed, and cardiorespiratory fitness [CRF]) were evaluated and categorized as healthy or unhealthy levels. Waist circumference, systolic blood pressure, glucose, and blood lipoprotein (triglycerides, total cholesterol, and high-density lipoprotein cholesterol) were measured. The clustered cardiometabolic risk score constituted the sum of internationally-derived standardized values (z-scores) for each risk factor divided by 5. Associations between performance-related physical fitness levels and the clustered cardiometabolic risk score were determined with linear regression models.ResultsParticipants with healthy ULS levels exhibited a less favourable clustered cardiometabolic risk score, whereas healthy levels of LLS, agility (only in girls), and CRF (only in boys) were related with a more favourable clustered cardiometabolic risk score. ULS (β: –0.091 [95% CI: –0.120; –0.062]), LLS (β: –0.272 [95% CI: –0.368; –0.177]), and CRF (β: –0.218 [95% CI: –0.324; –0.112]) were inversely associated with the clustered cardiometabolic risk score, while agility (β: 0.112 [95% CI: 0.082; 0.142]) and speed (β: 0.079 [95% CI: 0.039; 0.119]) demonstrated a positive association with the clustered cardiometabolic risk score.ConclusionsOur results emphasize the importance of following moderate-to-vigorous physical activity guidelines to better develop physical fitness levels for the maintenance of cardiometabolic health during childhood and adolescence.

Biological and socioeconomic factors as moderator in relationship between leisure-time physical activity and cardiometabolic risk in adolescents from southern Brazil

BackgroundGiven the important repercussions that sociodemographic factors can have on physical activity, especially in the field of leisure, and cardiometabolic risk, it seems relevant to analyze the implications of these variables on the relationship between physical activity in leisure time (LTPA) and cardiometabolic risk. In this sense, the present study aims to verify the moderating role of biologic and socioeconomic factors in the relationship between LTPA and cardiometabolic risk in adolescents in southern Brazil.MethodsCross-sectional study that included 1596 adolescents selected at random (58.2% girls), aged between 10 and 17 years. LTPA, biological and socioeconomic factors were assessed using a self-reported questionnaire and the cardiometabolic risk score (total cholesterol/HDL-c ratio, triglycerides, fasting glucose, systolic blood pressure, and waist circumference, considering the participant’s age and sex) was included as an outcome. Associations and moderations were tested by multiple linear regression models.ResultsIt was observed a positive interaction of LTPA and sex (p = 0.048) and LTPA and school system (p = 0.037), and negative interaction of LTPA and skin color (p = 0.040), indicating that these factors were moderators in the relationship between LTPA and clustered cardiometabolic risk score (cMetS) in adolescents. A reduction in cardiometabolic risk was observed according to the increase in weekly minutes of LTPA among boys, non-white adolescents, and students from municipal schools.ConclusionsThe association between LTPA and cardiometabolic risk was moderated by sex, skin color, and school system in adolescents from southern Brazil.

Efficacy of the \u2018Stand and Move at Work\u2019 multicomponent workplace intervention to reduce sedentary time and improve cardiometabolic risk: a group randomized clinical trial

BackgroundSedentary time is associated with chronic disease and premature mortality. We tested a multilevel workplace intervention with and without sit-stand workstations to reduce sedentary time and lower cardiometabolic risk.MethodsStand and Move at Work was a group (cluster) randomized trial conducted between January 2016 and December 2017 among full-time employees; ≥18 years; and in academic, industry/healthcare, and government worksites in Phoenix, Arizona and Minneapolis/St. Paul, Minnesota, USA. Eligible worksites were randomized to (a) MOVE+, a multilevel intervention targeting reduction in sedentary time and increases in light physical activity (LPA); or (b) STAND+, the MOVE+ intervention along with sit-stand workstations to allow employees to sit or stand while working. The primary endpoints were objectively-measured workplace sitting and LPA at 12 months. The secondary endpoint was a clustered cardiometabolic risk score (blood pressure, glucose, insulin, triglycerides, and HDL-cholesterol) at 12 months.ResultsWorksites (N = 24; academic [n = 8], industry/healthcare [n = 8], and government [n = 8] sectors) and employees (N = 630; 27 ± 8 per worksite; 45 ± 11 years of age, 74% female) were enrolled. All worksites were retained and 487 participants completed the intervention and provided data for the primary endpoint. The adjusted between arm difference in sitting at 12 months was − 59.2 (CI: − 74.6,-43.8) min per 8 h workday, favoring STAND+, and in LPA at 12 months was + 2.2 (− 0.9,5.4) min per 8 h workday. Change in the clustered metabolic risk score was small and not statistically significant, but favored STAND+. In an exploratory subgroup of 95 participants with prediabetes or diabetes, the effect sizes were larger and clinically meaningful, all favoring STAND+, including blood glucose, triglycerides, systolic blood pressure, glycated hemoglobin, LDL-cholesterol, body weight, and body fat.ConclusionsMultilevel workplace interventions that include the use of sit-stand workstations are effective for large reductions in sitting time over 12 months. Among those with prediabetes or diabetes, clinical improvements in cardiometabolic risk factors and body weight may be realized.Trial registrationClinicalTrials.gov Identifier: NCT02566317. Registered 2 October 2015, first participant enrolled 11 January 2016.

Healthy breakfast habits and changes in obesity-related cardiometabolic markers in children: a longitudinal analysis.

Data on the association of breakfast habits and changes in cardiometabolic markers in children are limited. In total, 6964 children aged 6-13 years from Beijing, Shanghai, Chongqing, Jinan, Harbin, and Guangzhou were included in the final analysis. Daily consumption, consumption of ≥3 food groups, and at-home consumption were defined as healthy breakfast habits. Blood pressure, % fat mass, total cholesterol (TC), high-density lipoprotein cholesterol (HDL-C), low-density lipoprotein cholesterol (LDL-C), triglycerides, glucose, and 50-m × 8 shuttle run were measured at baseline (May 2009) and follow-up (May 2010). Clustered cardiometabolic risk score (CCRS) was computed by summing Z scores of five components: % fat mass, systolic blood pressure, glucose, TC to HDL-C ratio, and triglyceride. Children who ate breakfast daily had a higher decrease in TC to HDL-C ratio and a higher increase in HDL-C compared with breakfast skippers (both P values < 0.05). There was an inverse association of the number of food groups consumed at breakfast with the change in CCRS (P trend = 0.005). At-home breakfast consumption was associated with a lower increase in BMI, LDL-C, TC to HDL-C ratio, fasting glucose, and 50-m × 8 shuttle run and a higher increase in HDL-C (all P values < 0.05). Children with two or three healthy breakfast habits had a lower increase in CCRS, LDL-C, TC to HDL-C ratio, glucose, and a higher increase in HDL-C compared with those with none or one (all P values < 0.05). Healthy breakfast habits might help minimize the cardiometabolic risk factors in children.

ActivPAL and ActiGraph Assessed Sedentary Behavior and Cardiometabolic Health Markers.

To establish whether associations between sedentary behavior and cardiometabolic health differ when assessed by thigh-worn and waist-worn accelerometry. Participants were recruited from several areas in the United Kingdom. Sedentary behavior was assessed using the activPAL worn on the thigh and ActiGraph worn on the waist. Average total (TST), prolonged (bouts ≥30 min; PST) and breaks (BST) in sedentary time were calculated. Cardiometabolic health markers included: adiposity (body fat) and surrogate markers of adiposity ((waist circumference, body mass index [BMI]), lipids (total, low density lipoprotein, and high-density lipoprotein [HDL] cholesterol, triglycerides), blood pressure, and glucose (fasting, 2 h and glycated hemoglobin A1c). A clustered cardiometabolic risk score was calculated. Linear regression analysis examined the associations with cardiometabolic health. There were 1457 participants (mean age [± standard deviation], 59.38 ± 11.85 yr; 51.7% male; mean BMI, 30.19 ± 5.59 kg·m) included in the analyses. ActivPAL and ActiGraph sedentary variables were moderately correlated (0.416-0.511, P < 0.01); however, all variables were significantly different from each other (P < 0.05). Consistency was observed across devices in the direction and magnitude of associations of TST and PST with adiposity, surrogate markers of adiposity, HDL, triglycerides, and cardiometabolic risk score and for BST with adiposity, surrogate markers of adiposity, and cardiometabolic risk. Differences across devices were observed in associations of TST and PST with diastolic blood pressure, for TST with 2-h glucose and for BST with HDL. No other associations were observed for any other health marker for either device. Results suggest that associations with cardiometabolic health are largely comparable across the two common assessments of sedentary behavior but some small differences may exist for certain health markers.

Prospectively Reallocating Sedentary Time: Associations with Cardiometabolic Health.

This study aimed to investigate whether prospectively reallocating time away from sedentary behavior (SB) into different physical activity intensities is associated with 12-month change to cardiometabolic health in a cohort at high risk of type 2 diabetes (T2DM). Participants with known risk factors for T2DM were recruited from primary care (Leicestershire, United Kingdom) as part of the Walking Away from Type 2 Diabetes trial (n = 808). Participants were followed up at 12, 24, and 36 months. SB, light-intensity physical activity (LPA) and moderate-to-vigorous intensity physical activity (MVPA) were measured objectively by accelerometer. Postchallenge glucose, triglycerides, HDL cholesterol, systolic blood pressure, and waist circumference were analyzed individually and combined into a clustered cardiometabolic risk score (CMRS). Associations of changing SB over each consecutive 12-month period were analyzed taking account of repeated measures. Reallocating 30 min from SB to LPA was associated with 0.21-cm (95% confidence interval, 0.03-0.38 cm) reduction in waist circumference, 0.09-mmol·L (0.04-0.13 mmol·L) reduction in 2-h glucose, 0.02-mmol·L (0.00-0.04 mmol·L) reduction in triglycerides, and 0.02 (0.01-0.03) reduction in CMRS. Every 30-min reallocation from SB to MVPA was associated with 1.23-cm (0.68-1.79 cm) reduction in waist circumference, 0.23-mmol·L (0.10-0.36 mmol·L) reduction in 2-h glucose, 0.04-mmol·L (0.00-0.09 mmol·L) reduction in triglycerides, and 0.07 (0.04-0.11) reduction in CMRS. Reallocating 30 min from LPA into MVPA was also associated with 1.02-cm (0.43-1.60 cm) reduction in waist circumference, 0.16-mmol·L (0.02-0.30 mmol·L) reduction in 2-h glucose, and 0.05 (0.01-0.09) reduction in CMRS. Over 12 months, reallocating time away from SB into LPA or MVPA was associated with improved cardiometabolic health in a population at risk of T2DM, with the greatest benefits observed for MVPA.

Effects of the Active Smarter Kids (ASK) physical activity intervention on cardiometabolic risk factors in children: A cluster-randomized controlled trial

The onset of cardiometabolic diseases are recognized to occur in childhood. We aimed to investigate the effect of a school-based cluster-randomized controlled trial of physical activity (PA) on single and clustered cardiometabolic risk factors.We included 1129 fifth-grade children from 57 schools (≥seven children in each class) in Sogn and Fjordane County, Norway, randomized to 28 intervention schools and 29 control schools. The PA intervention was conducted between November 2014 and June 2015. Cardiometabolic risk factors were waist circumference (WC), systolic blood pressure (SBP), total cholesterol (TC):high-density lipoprotein (HDL)-ratio, triglycerides (TG), homeostatic model assessment (HOMA)-score, and cardiorespiratory fitness (CRF). PA was measured by accelerometry.No significant intervention effects were found for single or clustered cardiometabolic risk factors. However, in children with the less favorable baseline values, beneficial effects were found for SBP (p = 0.07 for group ∗ tertile interaction), TC:HDL ratio (p = 0.03 for group ∗ tertile interaction) and the clustered cardiometabolic risk score (p = 0.01 for group ∗ tertile interaction). Compared to boys, girls had a greater effect of the intervention on WC (p = 0.03 for group ∗ sex interaction) and CRF (p < 0.001 for group ∗ sex interaction).The majority of the children had high PA levels, thus limited potential for change, and we found no effects of the PA intervention on cardiometabolic risk in the total sample. However, the intervention had a significantly enhanced effect on fatness and fitness of girls compared to boys. Furthermore, the data suggest that children with the least favorable cardiometabolic risk profile and therefore most in need of change can benefit from school-based PA interventions.Trial registration number: Clinicaltrials.gov ID no.: NCT02132494.

Associations of context-specific sitting time with markers of cardiometabolic risk in Australian adults

BackgroundHigh volumes of sitting time are associated with an elevated risk of type 2 diabetes and cardiovascular disease, and with adverse cardiometabolic risk profiles. However, previous studies have predominately evaluated only total sitting or television (TV) viewing time, limiting inferences about the specific cardiometabolic health impacts of sitting accumulated in different contexts. We examined associations of sitting time in four contexts with cardiometabolic risk biomarkers in Australian adults.MethodsParticipants (n = 3429; mean ± SD age 58 ± 10 years) were adults without clinically diagnosed diabetes or cardiovascular disease from the 2011–2012 Australian Diabetes, Obesity and Lifestyle (AusDiab) study. Multiple linear regressions examined associations of self-reported context-specific sitting time (occupational, transportation, TV-viewing and leisure-time computer use) with a clustered cardiometabolic risk score (CMR) and with individual cardiometabolic risk biomarkers (waist circumference, BMI, resting blood pressure, triglycerides, HDL- and LDL-cholesterol, and fasting and 2-h post-load plasma glucose).ResultsHigher CMR was significantly associated with greater TV-viewing and computer sitting time (b [95%CI] = 0.07 [0.04, 0.09] and 0.06 [0.03, 0.09]), and tended to be associated with higher occupational and transport sitting time (0.01 [− 0.01, 0.03] and 0.03 [− 0.00, 0.06]), after adjustment for potential confounders. Furthermore, keeping total sitting time constant, accruing sitting via TV-viewing and computer use was associated with significantly higher CMR (0.05 [0.02, 0.08] and 0.04 [0.01, 0.06]), accruing sitting in an occupational context was associated with significantly lower CMR (− 0.03 [− 0.05, − 0.01]), while no significant association was seen for transport sitting (0.00 [− 0.03, 0.04]). Results varied somewhat between the respective biomarkers; however, higher sitting time in each domain tended to be associated detrimentally with individual biomarkers except for fasting glucose (non-significant associations) and systolic blood pressure (a beneficial association was observed). Overall, associations were stronger for TV-viewing and computer use, and weaker for occupational sitting.ConclusionsHigher context-specific sitting times tended to be detrimentally associated, albeit modestly, with CMR and several cardiometabolic risk biomarkers. There was some evidence suggesting that the context in which people sit is relevant above and beyond total sitting time. Methodological issues notwithstanding, these findings may assist in identifying priorities for sitting-reduction initiatives, in order to achieve optimal cardiometabolic health benefits.

Cardiometabolic risk through an integrative classification combining physical activity and sedentary behavior in European adolescents: HELENA study

PurposeThis study aims to compare adolescents’ cardiometabolic risk score through an integrative classification of physical activity (PA), which involves the combination of moderate-to-vigorous physical activity (MVPA) and sedentary behavior (SB). MethodsA cross-sectional study derived from the Healthy Lifestyle in Europe by Nutrition in Adolescence Cross-Sectional Study database (2006–2008) was conducted in adolescents (n = 548; boys, 47.3%; 14.7 ± 1.2 years) from 10 European cities. MVPA and SB were objectively measured using accelerometry. Adolescents were divided into 4 categories according to MVPA (meeting or not meeting the international recommendations) and the median of SB time (above or below sex- and age-specific median) as follows: High-SB & Inactive, Low-SB & Inactive, High-SB & Active, and Low-SB & Active. A clustered cardiometabolic risk score was computed using the homeostatic model assessment, systolic blood pressure, triglycerides, total cholesterol/high-density lipoprotein cholesterol, sum 4 skinfolds, and cardiorespiratory fitness (CRF). Analyses of covariance were performed to discern differences on cardiometabolic risk scores among PA categories and each health component. ResultsThe cardiometabolic risk score was lower in adolescents meeting the MVPA recommendation and with less time spent in SB in comparison to the high-SB & Inactive group (p < 0.05). However, no difference in cardiometabolic risk score was established between High-SB or Low-SB groups in inactive adolescents. It is important to note that CRF was the only variable that showed a significant modification (higher) when children were compared from the category of physically inactive with “active” but not from high- to low-SB. ConclusionBeing physically active is the most significant and protective outcome in adolescents to reduce cardiometabolic risk. Lower SB does not exhibit a significant and extra beneficial difference.

A cross-sectional analysis of the associations between leisure-time sedentary behaviors and clustered cardiometabolic risk

BackgroundThe aim of this study was to conduct a comprehensive investigation of the association between different types of leisure-time sedentary behavior (watching television, using a computer, reading and socializing) and clustered cardiometabolic risk in apparently healthy adults aged 40 to 65 years.MethodsOne hundred seventy-three participants from the general population (64% women; mean age = 54.4 years) consented to attend a cardiovascular examination program and to complete a questionnaire on leisure-time sedentary behaviors. Waist circumference, blood pressure, glucose, triglycerides, and high-density lipoprotein cholesterol of non-fasting blood samples were assessed, and a clustered cardiometabolic risk score [CMRS] was calculated. Data were collected between February and July 2015. Associations between leisure-time sedentary behaviors and CMRS were analyzed using linear and quantile regression, adjusted for socio-demographic variables and other types of leisure-time sedentary behavior (model 1) and additionally, adjusted for leisure-time physical activity and traveling in motor vehicles (model 2).ResultsLinear regression revealed that there was a positive association between watching television and CMRS (model 1: b = 0.27 [CI: 0.03; 0.52]; model 2: b = 0.30 [CI: 0.05; 0.56]). In addition, quantile regression analysis revealed that using a computer was negatively associated with the 50th (model 1: b = − 0.43 [CI: -0.79; − 0.07]) and the 75th percentiles (model 1: b = − 0.71 [CI: -1.27; − 0.14]) of CMRS. Reading and socializing were not associated with CMRS.ConclusionsWatching television was positively associated with a clustered cardiometabolic risk score, while time spent using a computer revealed inconsistent findings. Our results give reason to consider different types of behaviors in which individuals are sedentary and the associations between these behaviors and cardiometabolic risk, supporting the need for behavior-specific assessments as well as public health recommendations to maintain or enhance adults’ health.Trial registrationClinical trial registration number: NCT02990039, Retrospectively registered (December 12, 2016).

Ability of Nontraditional Risk Factors and Inflammatory Biomarkers for Cardiovascular Disease to Identify High Cardiometabolic Risk in Adolescents: Results From the LabMed Physical Activity Study

PurposeThen objective of this study was to evaluate the ability of several nontraditional cardiometabolic and inflammatory biomarkers in identifying high cardiometabolic risk in adolescents. MethodsA cross-sectional study was conducted with 529 Portuguese adolescents (267 girls) aged 14.3 ± 1.7 years. A clustered cardiometabolic risk score (body fat percentage, systolic blood pressure, ratio of total cholesterol to high-density lipoprotein cholesterol, triglycerides, homeostatic model assessment of insulin resistance, and negative values of cardiorespiratory fitness) was computed. The nontraditional cardiometabolic biomarkers assessed were complement factors (C3 and C4), C-reactive protein (CRP), fibrinogen, leptin, white blood cells (WBCs), albumin, interleukin-6, and a clustered score of inflammatory biomarkers (InflaScore) (C3, C4, CRP, fibrinogen, and leptin). ResultsReceiver operating characteristic curves analyses showed that C3, C4, CRP, fibrinogen, leptin, and the InflaScore were able to present discriminatory ability in identifying an unfavorable cardiometabolic profile in both girls and boys (p < .01 for all). Logistic regression analyses showed that C3, C4, CRP, fibrinogen, leptin, the InflaScore (in both sexes), and WBC (boys) were associated with high cardiometabolic risk, independent of age, pubertal stage, socioeconomic status, or adherence to a Mediterranean diet (p < .05 for all). ConclusionsC3, C4, CRP, fibrinogen, and leptin were associated with high cardiometabolic risk in both sexes and WBC in boys. In addition, the clustered inflammatory biomarkers seem to have a better diagnostic accuracy in identifying an unfavorable cardiometabolic profile than single biomarkers. Such biomarkers may have utility in motivating health professionals, public health workers, and adolescents' families toward lifestyle changes, improving prevention efforts early in life.