36 research outputs found

    Observational and genetic associations between cardiorespiratory fitness and cancer: a UK Biobank and international consortia study

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    BACKGROUND: The association of fitness with cancer risk is not clear. METHODS: We used Cox proportional hazards models to estimate hazard ratios (HRs) and 95% confidence intervals (CIs) for risk of lung, colorectal, endometrial, breast, and prostate cancer in a subset of UK Biobank participants who completed a submaximal fitness test in 2009-12 (N = 72,572). We also investigated relationships using two-sample Mendelian randomisation (MR), odds ratios (ORs) were estimated using the inverse-variance weighted method. RESULTS: After a median of 11 years of follow-up, 4290 cancers of interest were diagnosed. A 3.5 ml O2⋅min-1⋅kg-1 total-body mass increase in fitness (equivalent to 1 metabolic equivalent of task (MET), approximately 0.5 standard deviation (SD)) was associated with lower risks of endometrial (HR = 0.81, 95% CI: 0.73-0.89), colorectal (0.94, 0.90-0.99), and breast cancer (0.96, 0.92-0.99). In MR analyses, a 0.5 SD increase in genetically predicted O2⋅min-1⋅kg-1 fat-free mass was associated with a lower risk of breast cancer (OR = 0.92, 95% CI: 0.86-0.98). After adjusting for adiposity, both the observational and genetic associations were attenuated. DISCUSSION: Higher fitness levels may reduce risks of endometrial, colorectal, and breast cancer, though relationships with adiposity are complex and may mediate these relationships. Increasing fitness, including via changes in body composition, may be an effective strategy for cancer prevention

    Calibration of GENEActiv accelerometer wrist cut-points for the assessment of physical activity intensity of pre-school aged children

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    This study sought to validate cut-points for use of wrist worn GENEActiv accelerometer data, to analyse preschool children’s (4 to 5 year olds) physical activity (PA) levels via calibration with oxygen consumption values (VO2). This was a laboratory based calibration study. Twenty-one preschool children, aged 4.7 ± 0.5 years old, completed six activities (ranging from lying supine to running) whilst wearing the GENEActiv accelerometers at two locations (left and right wrist), these being the participants’ non-dominant and dominant wrist, and a Cortex face mask for gas analysis. VO2 data was used for the assessment of criterion validity. Location specific activity intensity cut points were established via Receiver Operator Characteristic curve (ROC) analysis. The GENEActiv accelerometers, irrespective of their location, accurately discriminated between all PA intensities (sedentary, light, and moderate and above), with the dominant wrist monitor providing a slightly more precise discrimination at light PA and the non-dominant at the sedentary behaviour and moderate and above intensity levels (Area Under the Curve (AUC) for non-dominant = 0.749-0.993, compared to AUC dominant = 0.760-0.988). Conclusion: This study establishes wrist-worn physical activity cut points for the GENEActiv accelerometer in pre-schoolers.N/

    Different healthy habits between northern and southern Spanish school children

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    Aim: Healthy habits are influenced by several factors such as, geographical location. The aims of this study were to describe and compare healthy habits within two populations of sixth-grade primary school children (aged 11-12 years) from Northern and Southern Spain. Subject and Methods: A cross-sectional study using two representative samples of school children was conducted. Participants came from Logroño (n=329), in the North and Granada (n=284), in the South of Spain. Socio-demographic and anthropometric variables, adherence to the Mediterranean diet, aerobic fitness, and healthy lifestyles were recorded. Results: Boys reported higher level of physical activity and aerobic fitness than girls (p=0.000). Southern school children reported significantly higher adherence to the Mediterranean diet (♀: p=0.041; ♂: p=0.008), and lower aerobic fitness (♀: p=0.000; ♂: p=0.042) and hours of nightly sleep (♀: p=0.008, ♂: p=0.007) than Northern school children. Southern boys also reported lower levels of physical activity (p=0.013). There were slight or moderate correlations among all habits measured (physical activity, diet, screen and sleep time). Additionally, physical activity level was inversely related to body mass index in Northern boys (p=0.020) and Southern girls (p=0.024). Conclusions: Results showed differences in physical activity, eating and sleep habits, and aerobic fitness, according to geographical location. The relationships found among lifestyle habits indicate the need of health promotion interventions nationally and considering the differences discussed here

    Cross-Sectional Associations of Reallocating Time Between Sedentary and Active Behaviours on Cardiometabolic Risk Factors in Young People: An International Children's Accelerometry Database (ICAD) Analysis.

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    INTRODUCTION: Sedentary time and time spent in various intensity-specific physical activity are co-dependent, and increasing time spent in one behaviour requires decreased time in another. OBJECTIVE: The aim of the present study was to examine the theoretical associations with reallocating time between categories of intensities and cardiometabolic risk factors in a large and heterogeneous sample of children and adolescents. METHODS: We analysed pooled data from 13 studies comprising 18,200 children and adolescents aged 4-18 years from the International Children's Accelerometry Database (ICAD). Waist-mounted accelerometers measured sedentary time, light physical activity (LPA) and moderate-to-vigorous physical activity (MVPA). Cardiometabolic risk factors included waist circumference (WC), systolic blood pressure (SBP), fasting high- and low-density lipoprotein cholesterol (HDL-C and LDL-C), triglycerides, insulin, and glucose. Associations of reallocating time between the various intensity categories with cardiometabolic risk factors were explored using isotemporal substitution modelling. RESULTS: Replacing 10 min of sedentary time with 10 min of MVPA showed favourable associations with WC, SBP, LDL-C, insulin, triglycerides, and glucose; the greatest magnitude was observed for insulin (reduction of 2-4%), WC (reduction of 0.5-1%), and triglycerides (1-2%). In addition, replacing 10 min of sedentary time with an equal amount of LPA showed beneficial associations with WC, although only in adolescents. CONCLUSIONS: Replacing sedentary time and/or LPA with MVPA in children and adolescents is favourably associated with most markers of cardiometabolic risk. Efforts aimed at replacing sedentary time with active behaviours, particularly those of at least moderate intensity, appear to be an effective strategy to reduce cardiometabolic risk in young people

    Impact of Lifelong Exercise Training Dose on Ventricular-Arterial Coupling

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