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Individuals with low socioeconomic status and multimorbidity tend to have lower physical activity (PA) levels than the general population. Primary care is an important setting for reaching high-risk individuals to support behaviour change. This study aimed to investigate the impact of behaviour change interventions delivered by Norwegian Healthy Life Centres (HLCs) on participants' PA levels, aerobic fitness and obesity, and furthermore to investigate possible predictors of change.
Evidence is emerging from school-based studies that physical activity might favorably affect children's academic performance. However, there is a need for high-quality studies to support this. Therefore, the main objective of the Active Smarter Kids (ASK) study is to investigate the effect of daily physical activity on children's academic performance. Because of the complexity of the relation between physical activity and academic performance it is important to identify mediating and moderating variables such as cognitive function, fitness, adiposity, motor skills and quality of life (QoL). Further, there are global concerns regarding the high prevalence of lifestyle-related non-communicable diseases (NCDs). The best means to address this challenge could be through primary prevention. Physical activity is known to play a key role in preventing a host of NCDs. Therefore, we investigated as a secondary objective the effect of the intervention on risk factors related to NCDs. The purpose of this paper is to describe the design of the ASK study, the ASK intervention as well as the scope and details of the methods we adopted to evaluate the effect of the ASK intervention on 5 (th) grade children.
The direction of the longitudinal relationship between physical activity (PA) and fundamental motor skills (FMS) remains unclear. We evaluated the bi-directional, prospective relationships between intensity-specific physical activity (PA) and domain-specific fundamental motor skills (FMS) over 2 years in children attending preschool at baseline.
Health-related quality of life (HRQoL) is an important outcome for health interventions, such as physical activity (PA) promotion among high-risk populations. The aim of this study was to investigate levels of PA and HRQoL, and associations between PA and HRQoL, in participants attending a behavior change service within primary care in Norway.
Knowledge of reproducibility of accelerometer-determined physical activity (PA) and sedentary time (SED) estimates are a prerequisite to conduct high-quality epidemiological studies. Yet, estimates of reproducibility might differ depending on the approach used to analyze the data. The aim of the present study was to determine the reproducibility of objectively measured PA and SED in children by directly comparing a day-by-day and a week-by-week approach to data collected over two weeks during two different seasons 3-4 months apart.
Changes in cognitive function induced by physical activity have been proposed as a mechanism for the link between physical activity and academic performance. The aim of this study was to investigate if executive function mediated the prospective relations between indices of physical activity and academic performance in a sample of 10-year-old Norwegian children. The study included 1,129 children participating in the Active Smarter Kids (ASK) trial, followed over 7 months. Structural equation modeling (SEM) with a latent variable of executive function (measuring inhibition, working memory, and cognitive flexibility) was used in the analyses. Predictors were objectively measured physical activity, time spent sedentary, aerobic fitness, and motor skills. Outcomes were performance on national tests of numeracy, reading, and English (as a second language). Generally, indices of physical activity did not predict executive function and academic performance. A modest mediation effect of executive function was observed for the relation between motor skills and academic performance. Trial registration: Clinicaltrials.gov registry, trial registration number: NCT02132494.
Aerobic fitness (AF) and lipoprotein subclasses associate to each other and to cardiovascular health. Adiposity and physical activity (PA) influence the association pattern of AF to lipoproteins almost inversely making it difficult to assess their independent and joint influence on the association pattern. This study, including 841 children (50% boys) 10.2 ± 0.3 years old with BMI 18.0 ± 3.0 kg/m2 from rural Western Norway, aimed at examining the association pattern of AF to the lipoprotein subclasses and to estimate the independent and joint influence of PA and adiposity on this pattern. We used multivariate analysis to determine the association pattern of a profile of 26 lipoprotein features to AF with and without adjustment for three measures of adiposity and a high-resolution PA descriptor of 23 intensity intervals derived from accelerometry. For data not adjusted for adiposity or PA, we observed a cardioprotective lipoprotein pattern associating to AF. This pattern withstood adjustment for PA, but the strength of association to AF was reduced by 58%, while adjustment for adiposity weakened the association of AF to the lipoproteins by 85% and with strongest changes in the associations to a cardioprotective high-density lipoprotein subclass pattern. When adjusted for both adiposity and PA, the cardioprotective lipoprotein pattern still associated to AF, but the strength of association was reduced by 90%. Our results imply that the (negative) influence of adiposity on the cardioprotective association pattern of lipoproteins to AF is considerably stronger than the (positive) contribution of PA to this pattern. However, our analysis shows that PA contributes also indirectly through a strong inverse association to adiposity. The trial was registered 7 May, 2014 in clinicaltrials.gov with trial reg. no.: NCT02132494 and the URL is https://clinicaltrials.gov/ct2/results?term=NCT02132494&cntry=NO.
Evidence of intra-family resemblance in physical activity (PA) is lacking. The association between parent and child PA appears weak, the influence of age and gender on this association is uncertain, and no studies have investigated the degree of resemblance in family members' PA behaviours such as walking, sitting/lying, and biking. Thus, the aims of the study were to examine the degree of resemblance in PA within families, specifically between parents and children, and to explore the size of resemblance across age of children, gender of parents and children, and intensity and type of PA.
Comprehensive lipoprotein profiling using proton nuclear magnetic resonance (NMR) spectroscopy of serum represents an alternative to the homeostatic model assessment of insulin resistance (HOMA-IR). Both adiposity and physical (in)activity associate to insulin resistance, but quantification of the influence of these two lifestyle related factors on the association pattern of HOMA-IR to lipoproteins suffers from lack of appropriate methods to handle multicollinear covariates.
Physical activity is favourably associated with certain markers of lipid metabolism. The relationship of physical activity with lipoprotein particle profiles in children is not known. Here we examine cross-sectional associations between objectively measured physical activity and sedentary time with serum markers of lipoprotein metabolism.
The preschool environment exerts an important influence on children's behaviour, including physical activity (PA). However, information is lacking regarding where and when most of children's PA is undertaken. This study aimed to describe PA and sedentary time (SED) during preschool hours and time out-of-care, and on weekdays and weekend days, and to investigate differences in PA patterns according to sex, age, and MVPA levels. From September 2015 to June 2016, we measured PA levels of 1109 children (age range, 2.7-6.5 years; mean age 4.7 years; boys, 52%) using ActiGraph GT3X+ accelerometers for up to 14 consecutive days. We applied a linear mixed model to analyse associations and interactions between total PA (counts per minute [cpm]), light PA (LPA), moderate-to-vigorous PA (MVPA), SED, sex, age, and overall MVPA regardless of setting, during preschool hours versus time out-of-care, and on weekdays versus weekend days. Children undertook more PA and less SED on weekdays compared to weekend days (p < 0.01). For boys, MVPA levels were higher during preschool hours than during time out-of-care (p < 0.05). Differences in total PA and MVPA between preschool hours versus time out-of-care, and between weekdays and weekend days, were greater in boys, older children, and highly active children than in girls, younger children, and children with lower overall MVPA levels (p < 0.01). The preschool arena is important for children's PA. Concerning MVPA, this study showed that boys, older children, and highly active children benefit more from this environment compared to girls, younger preschoolers, and children with lower MVPA levels.
The long-term impact of primary care behavior change programs on health-related quality of life (HRQoL) and physical activity (PA) level is unknown. The aim of this study was to investigate changes in HRQoL and PA among participants after a 3-month behavior change intervention at Norwegian healthy life center (HLCs) and at a 15-month follow-up. Furthermore, we aimed to study associations between changes in PA and HRQoL.
Lipoprotein subclasses possess crucial cardiometabolic information. Due to strong multicollinearity among variables, little is known about the strength of influence of physical activity (PA) and adiposity upon this cardiometabolic pattern. Using a novel approach to adjust for covariates, we aimed at determining the "net" patterns and strength for PA and adiposity to the lipoprotein profile. Principal component and multivariate pattern analysis were used for the analysis of 841 prepubertal children characterized by 26 lipoprotein features determined by proton nuclear magnetic resonance spectroscopy, a high-resolution PA descriptor derived from accelerometry, and three adiposity measures: body mass index, waist circumference to height, and skinfold thickness. Our approach focuses on revealing and validating the underlying predictive association patterns in the metabolic, anthropologic, and PA data to acknowledge the inherent multicollinear nature of such data. PA associates to a favorable cardiometabolic pattern of increased high-density lipoproteins (HDL), very large and large HDL particles, and large size of HDL particles, and decreasedtriglyceride, chylomicrons, very low-density lipoproteins (VLDL), and their subclasses, and to low size of VLDL particles. Although weakened in strength, this pattern resists adjustment for adiposity. Adiposity is inversely associated to this pattern and exhibits unfavorable associations to low-density lipoprotein (LDL) features, including atherogenic small and very small LDL particles. The observed associations are still strong after adjustment for PA. Thus, lipoproteins explain 26.0% in adiposity after adjustment for PA compared to 2.3% in PA after adjustment for adiposity.
Strongly multicollinear covariates, such as those typically represented in metabolomics applications, represent a challenge for multivariate regression analysis. These challenges are commonly circumvented by reducing the number of covariates to a subset of linearly independent variables, but this strategy may lead to loss of resolution and thus produce models with poorer interpretative potential. The aim of this work was to implement and illustrate a method, multivariate pattern analysis (MVPA), which can handle multivariate covariates without compromising resolution or model quality.
It is unknown how changes in physical activity may affect changes in quality of life (QoL) outcomes during lifestyle interventions for severely obese adults. The purpose of this study was to examine associations in the patterns of change between objectively assessed physical activity as the independent variable and physical, mental, and obesity-specific QoL and life satisfaction as the dependent variables during a two-year lifestyle intervention. Forty-nine severely obese adults (37 women; 43.6 ± 9.4 years; body mass index 42.1 ± 6.0 kg/m(2)) participated in the study. Assessments were conducted four times using Medical Outcomes Study Short-Form 36 Health Survey (SF-36), Obesity-Related Problems (OP) scale, a single item on life satisfaction, and accelerometers. The physical component summary (PCS) score and the mental component summary (MCS) score were used as SF-36 outcomes. Associations were determined using linear regression analyses and reported as standardized coefficients (stand. coeff.). Change in physical activity was independently associated with change in PCS (stand. coeff. = 0.35, P = .033), MCS (stand. coeff. = 0.51, P = .001), OP (stand. coeff. = -0.31, P = .018), and life satisfaction (stand. coeff. = 0.39, P = .004) after adjustment for gender, age, and change in body mass index.
Associations between multicollinear accelerometry-derived physical activity (PA) data and cardiometabolic health in children needs to be analyzed using an approach that can handle collinearity among the explanatory variables. The aim of this paper is to provide readers a tutorial overview of interpretation of multivariate pattern analysis models using PA accelerometry data that reveals the associations to cardiometabolic health. A total of 841 children (age 10.2 ± 0.3 years) provided valid data on accelerometry (ActiGraph GT3X+) and six indices of cardiometabolic health that were used to create a composite score. We used a high-resolution PA description including 23 intensity variables covering the intensity spectrum (from 0-99 to ≥10000 counts per minute), and multivariate pattern analysis to analyze data. We report different statistical measures of the multivariate associations between PA and cardiometabolic health and use decentile groups of PA as a basis for discussing the meaning and impact of multicollinearity. We show that for high-resolution accelerometry data; considering all explanatory variables is crucial to obtain a correct interpretation of associations to cardiometabolic health; which is otherwise strongly confounded by multicollinearity in the dataset. Thus; multivariate pattern analysis challenges the traditional interpretation of findings from linear regression models assuming independent explanatory variables.
Accelerometers provide detailed data about physical activity (PA) across the full intensity spectrum. However, when examining associations with health, results are often aggregated to only a few summary measures [e.g. time spent "sedentary" or "moderate-to-vigorous" intensity PA]. Using multivariate pattern analysis, which can handle collinear exposure variables, we examined associations between the full PA intensity spectrum and cardiometabolic risk (CMR) in a population-based sample of middle-aged to older adults. Participants (n = 3660; mean ± SD age = 69 ± 8y and BMI = 26.7 ± 4.2 kg/m2; 55% female) from the EPIC-Norfolk study (UK) with valid accelerometry (ActiGraph-GT1M) data were included. We used multivariate pattern analysis with partial least squares regression to examine cross-sectional multivariate associations (r) across the full PA intensity spectrum [minutes/day at 0-5000 counts-per-minute (cpm); 5 s epoch] with a continuous CMR score (reflecting waist, blood pressure, lipid, and glucose metabolism). Models were sex-stratified and adjusted for potential confounders. There was a positive (detrimental) association between PA and CMR at 0-12 cpm (maximally-adjusted r = 0.08 (95%CI 0.06-0.10). PA was negatively (favourably) associated with CMR at all intensities above 13 cpm ranging between r = -0.09 (0.07-0.12) at 800-999 cpm and r = -0.14 (0.11-0.16) at 75-99 and 4000-4999 cpm. The strongest favourable associations were from 50 to 800 cpm (r = 0.10-0.12) in men, but from ≥2500 cpm (r = 0.18-0.20) in women; with higher proportions of model explained variance for women (R2 = 7.4% vs. 2.3%). Most of the PA intensity spectrum was beneficially associated with CMR in middle-aged to older adults, even at intensities lower than what has traditionally been considered "sedentary" or "light-intensity" activity. This supports encouragement of PA at almost any intensity in this age-group.
This study investigated physical activity (PA) and sedentary time (SED) in relation to hippocampal gray matter volume (GMV) in pediatric overweight/obesity. Ninety-three children (10 ± 1 year) were classified as overweight, obesity type I, or type II-III. PA was assessed with non-dominant wrist accelerometers. GMV was acquired by magnetic resonance imaging (MRI). Neither PA nor SED associated with GMV in the hippocampus in the whole sample (p > 0.05). However, we found some evidence of moderation by weight status (p < 0.150). Moderate-to-vigorous PA (MVPA) positively associated with GMV in the right hippocampus in obesity type I (B = 5.62, p = 0.017), which remained when considering SED, light PA, and sleep using compositional data (γ = 375.3, p = 0.04). Compositional models also depicted a negative association of SED relative to the remaining behaviors with GMV in the right hippocampus in overweight (γ = -1838.4, p = 0.038). Reallocating 20 min/day of SED to MVPA was associated with 100 mm3 GMV in the right hippocampus in obesity type I. Multivariate pattern analysis showed a negative-to-positive association pattern between PA of increasing intensity and GMV in the right hippocampus in obesity type II-III. Our findings support that reducing SED and increasing MVPA are associated with greater GMV in the right hippocampus in pediatric overweight/obesity. Further studies should corroborate our findings.
Knowledge of the reproducibility of domain-specific accelerometer-determined physical activity (PA) estimates are a prerequisite to conduct high-quality epidemiological studies. The aim of this study was to determine the reproducibility of objectively measured PA level in children during school hours, afternoon hours, weekdays, weekend days, and total leisure time over two different seasons.
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