Accelerometer Measured Levels of Moderate-to-Vigorous Intensity Physical Activity and Sedentary Time in Children and Adolescents with Chronic Disease: a Systematic Review and Meta-Analysis

Context: Moderate-to-vigorous physical activity (MVPA) and sedentary time (ST) are important for child and adolescent health. Objective: To examine habitual levels of accelerometer measured MVPA and ST in children and adolescents with chronic disease, and how these levels compare with healthy peers. Methods: Data sources: An extensive search was carried out in Medline, Cochrane library, EMBASE, SPORTDiscus and CINAHL from 2000–2017. Study selection: Studies with accelerometer-measured MVPA and/or ST (at least 3 days and 6 hours/day to provide estimates of habitual levels) in children 0–19 years of age with chronic diseases but without co-morbidities that would present major impediments to physical activity. In all cases patients were studied while well and clinically stable. Results: Out of 1592 records, 25 studies were eligible, in four chronic disease categories: cardiovascular disease (7 studies), respiratory disease (7 studies), diabetes (8 studies), and malignancy (3 studies). Patient MVPA was generally below the recommended 60 min/day and ST generally high regardless of the disease condition. Comparison with healthy controls suggested no marked differences in MVPA between controls and patients with cardiovascular disease (1 study, n = 42) and type 1 diabetes (5 studies, n = 400; SMD -0.70, 95% CI -1.89 to 0.48, p = 0.25). In patients with respiratory disease, MVPA was lower in patients than controls (4 studies, n = 470; SMD -0.39, 95% CI -0.80, 0.02, p = 0.06). Meta-analysis indicated significantly lower MVPA in patients with malignancies than in the controls (2 studies, n = 90; SMD -2.2, 95% CI -4.08 to -0.26, p = 0.03). Time spent sedentary was significantly higher in patients in 4/10 studies compared with healthy control groups, significantly lower in 1 study, while 5 studies showed no significant group difference. Conclusions: MVPA in children/adolescents with chronic disease appear to be well below guideline recommendations, although comparable with activity levels of their healthy peers except for children with malignancies. Tailored and disease appropriate intervention strategies may be needed to increase MVPA and reduce ST in children and adolescents with chronic disease

Collapsibility of Graphical CG-Regression Models

CG-regressions are multivariate regression models for mixed continuous and discrete responses that result from conditioning in the class of conditional Gaussian (CG) models. Their conditional independence structure can be read off a marked graph. The property of collapsibility, in this context, means that the multivariate CG-regression can be decomposed into lower dimensional regressions that are still CG and are consistent with the corresponding subgraphs. We derive conditions for this property that can easily be checked on the graph, and indicate computational advantages of this kind of collapsibility. Further, a simple graphical condition is given for checking whether a decomposition into univariate regressions is possible. Copyright 2004 Board of the Foundation of the Scandinavian Journal of Statistics..

Using molecular classification to predict gains in maximal aerobic capacity following endurance exercise training in humans.

A low maximal oxygen consumption (VO2max) is a strong risk factor for premature mortality. Supervised endurance exercise training increases VO2max with a very wide range of effectiveness in humans. Discovering the DNA variants that contribute to this heterogeneity typically requires substantial sample-sizes. In the present study we first use RNA expression profiling to produce a molecular classifier that predicts VO2max training response. We then hypothesised that the classifier genes would harbour DNA variants that contributed to the heterogeneous VO2max response. Two independent pre-intervention RNA expression data sets were generated (n=41 gene-chips) from subjects that underwent supervised endurance training. One identified, the second blindly validated an RNA expression signature that predicted change in VO2max ('predictor genes'). The HERITAGE Family Study (n=473) was used for genotyping. We discovered a 29 RNA signature that predicted VO2max training response on a continuous scale, and these genes contained ~6 new SNPs associated with gains in VO2max in HERITAGE. Three from 4 novel HERITAGE candidate genes were confirmed as RNA predictor genes (i.e. 'reciprocal' RNA validation of a QTL genotype), enhancing the performance of the 29 RNA based predictor. Notably, RNA abundance for the predictor genes was unchanged by exercise training, supporting the idea that expression was pre-set by genetic variation. Regression analysis yielded a model where 11 SNPs explained 23% of the variance in gains in VO2max, corresponding to ~50% of the estimated genetic variance for VO2max. In conclusion, combining RNA profiling with single-gene DNA marker association analysis yields a strongly validated molecular predictor with meaningful explanatory power. VO2max responses to endurance training can be predicted by measuring a ~30 gene RNA expression signature in muscle prior to training. The general approach taken could accelerate the discovery of genetic biomarkers, sufficiently discrete for diagnostic purposes, for a range of physiological and pharmacological phenotypes in humans. Key words: aerobic capacity, personalised medicine, genotype, endurance training