Jostein Steene-Johannessen

The aim of this study was to investigate how sleep, screen time, active school travel and sport and/or exercise participation associates with moderate-to-vigorous physical activity (MVPA) in nationally representative samples of Norwegian 9- and 15-y-olds, and whether these four behaviors at age nine predict change in MVPA from age nine to 15 years. We pooled cross-sectional accelerometer and questionnaire data from 9- (n = 2366) and 15-y-olds (n = 1554) that participated in the first (2005/06) and second (2011/12) wave of the Physical Activity among Norwegian Children Study to investigate cross-sectional associations. To investigate prospective associations, we used data from a sub-sample that participated in both waves (at age nine and 15 years, n = 517). Cross-sectional analyses indicated a modest, inverse association between screen time and MVPA among 9- (− 2.2 min/d (95% CI: -3.1, − 1.3)) and 15-y-olds (− 1.7 min/d (95% CI: -2.7, − 0.8)). Compared to their peers with 0–5 min/d of active travel to school, 9- and 15-y-olds with ≥16 min/d accumulated 7.2 (95% CI: 4.0, 10.4) and 9.0 (95% CI: 3.8, 14.1) more min/d of MVPA, respectively. Nine-y-old boys and 15-y-olds reporting ≥8 h/week of sports and/or exercise participation accumulated 14.7 (95% CI: 8.2, 21.3) and 17.9 (95% CI: 14.0, 21.8) more min/d of MVPA, respectively, than those reporting ≤2 h/week. We found no cross-sectional association between sleep duration and MVPA in either age group. None of the four behaviors predicted change in MVPA from age nine to 15 years (p ≥ 0.102). Active travel to school and sport/exercise participation may be important targets for future interventions aimed at increasing MVPA in children and adolescents. However, future studies are needed to determine causality.

Physical inactivity is a well-known public health risk that should be monitored at the population level. Physical activity levels are often surveyed across Europe. This systematic literature review aims to provide an overview of all existing cross-European studies that assess physical activity in European adults, describe the variation in population levels according to these studies, and discuss the impact of the assessment methods. Six literature databases (PubMed, EMBASE, CINAHL, PsycINFO, SportDiscus and OpenGrey) were searched, supplemented with backward- and forward tracking and searching authors’ and experts’ literature databases. Articles were included if they reported on observational studies measuring total physical activity and/or physical activity in leisure time in the general population in two or more European countries. Each record was reviewed, extracted and assessed by two independent researchers and disagreements were resolved by a third researcher. The review protocol of this review is registered in the PROSPERO database under registration number CRD42014010334. Of the 9,756 unique identified articles, twenty-five were included in this review, reporting on sixteen different studies, including 2 to 35 countries and 321 to 274,740 participants. All but two of the studies used questionnaires to assess physical activity, with the majority of studies using the IPAQ-short questionnaire. The remaining studies used accelerometers. The percentage of participants who either were or were not meeting the physical activity recommendations was the most commonly reported outcome variable, with the percentage of participants meeting the recommendations ranging from 7 % to 96 % across studies and countries. The included studies showed substantial variation in the assessment methods, reported outcome variables and, consequently, the presented physical activity levels. Because of this, absolute population levels of physical activity in European adults are currently unknown. However, when ranking countries, Ireland, Italy, Malta, Portugal, and Spain generally appear to be among the less active countries. Objective data of adults across Europe is currently limited. These findings highlight the need for standardisation of the measurement methods, as well as cross-European monitoring of physical activity levels.

Sedentary behaviour is increasingly recognized as a public health risk that needs to be monitored at the population level. Across Europe, there is increasing interest in assessing population levels of sedentary time. This systematic literature review aims to provide an overview of all existing cross-European studies that measure sedentary time in adults, to describe the variation in population levels across these studies and to discuss the impact of assessment methods. Six literature databases (PubMed, EMBASE, CINAHL, PsycINFO, SportDiscus and OpenGrey) were searched, supplemented with backward- and forward tracking and searching authors’ and experts’ literature databases. Articles were included if they reported on observational studies measuring any form of sedentary time in the general population in two or more European countries. Each record was reviewed, extracted and assessed by two independent researchers, and disagreements were resolved by a third researcher. The review protocol of this review is registered in the PROSPERO database under registration number CRD42014010335. Of the 9,756 unique articles that were identified in the search, twelve articles were eligible for inclusion in this review, reporting on six individual studies and three Eurobarometer surveys. These studies represented 2 to 29 countries, and 321 to 65,790 participants. Eleven studies focused on total sedentary time, while one studied screen time. The majority of studies used questionnaires to assess sedentary time, while two studies used accelerometers. Total sedentary time was reported most frequently and varied from 150 (median) to 620 (mean) minutes per day across studies and countries. One third of European countries were not included in any of the studies. Objective measures of European adults are currently limited, and most studies used single-item self-reported questions without assessing sedentary behaviour types or domains. Findings varied substantially between studies, meaning that population levels of sedentary time in European adults are currently unknown. In general, people living in northern Europe countries appear to report more sedentary time than southern Europeans. The findings of this review highlight the need for standardisation of the measurement methods and the added value of cross-European surveillance of sedentary behaviour.

Purpose Assess the agreement between commonly used self-report methods compared with objectively measured physical activity (PA) in defining the prevalence of individuals compliant with PA recommendations. Methods Time spent in moderate and vigorous PA (MVPA) was measured at two time points in 1713 healthy individuals from nine European countries using individually calibrated combined heart rate and movement sensing. Participants also completed the Recent Physical Activity Questionnaire (RPAQ), short form of the International Physical Activity Questionnaire (IPAQ), and short European Prospective Investigation into Cancer and Nutrition Physical Activity Questionnaire (EPIC-PAQ). Individuals were categorized as active (e.g., reporting ≥150 min of MVPA per week) or inactive, based on the information derived from the different measures. Sensitivity and specificity analyses and Kappa statistics were performed to evaluate the ability of the three PA questionnaires to correctly categorize individuals as active or inactive. Results Prevalence estimates of being sufficiently active varied significantly (P for all <0.001) between self-report measures (IPAQ 84.2% [95% confidence interval {CI}, 82.5–85.9], RPAQ 87.6% [95% CI, 85.9–89.1], EPIC-PAQ 39.9% [95% CI, 37.5–42.1] and objective measure 48.5% [95% CI, 41.6–50.9]. All self-report methods showed low or moderate sensitivity (IPAQ 20.0%, RPAQ 18.7%, and EPIC-PAQ 69.8%) to correctly classify inactive people and the agreement between objective and self-reported PA was low (ĸ = 0.07 [95% CI, 0.02–0.12], 0.12 [95% CI, 0.06–0.18], and 0.19 [95% CI, 0.13–0.24] for IPAQ, RPAQ, and EPIC-PAQ, respectively). Conclusions The modest agreement between self-reported and objectively measured PA suggests that population levels of PA derived from self-report should be interpreted cautiously. Implementation of objective measures in large-scale cohort studies and surveillance systems is recommended.

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 ASK study is a cluster randomized controlled trial that includes 1145 fifth graders (aged 10 years) from 57 schools (28 intervention schools; 29 control schools) in Sogn and Fjordane County, Norway. This represents 95.3 % of total possible recruitment. Children in all 57 participating schools took part in a curriculum-prescribed physical activity intervention (90 min/week of physical education (PE) and 45 min/week physical activity, in total; 135 min/week). In addition, children from intervention schools also participated in the ASK intervention model (165 min/week), i.e. a total of 300 min/week of physical activity/PE. The ASK study was implemented over 7 months, from November 2014 to June 2015. We assessed academic performance in reading, numeracy and English using Norwegian National tests delivered by The Norwegian Directorate for Education and Training. We assessed physical activity objectively at baseline, midpoint and at the end of the intervention. All other variables were measured at baseline and post-intervention. In addition, we used qualitative methodologies to obtain an in-depth understanding of children’s embodied experiences and pedagogical processes taking place during the intervention. If successful, ASK could provide strong evidence of a relation between physical activity and academic performance that could potentially inform the process of learning in elementary schools. Schools might also be identified as effective settings for large scale public health initiatives for the prevention of NCDs. Clinicaltrials.gov ID nr: NCT02132494 . Date of registration, 6^th of May, 2014.

I Brage finner du siste tekst-versjon av artikkelen, og den kan inneholde ubetydelige forskjeller fra forlagets pdf-versjon. Forlagets pdf-versjon finner du på www.informaworld.com: http://dx.doi.org/10.3109/17477160903497035 / In Brage you'll find the final text version of the article, and it may contain insignificant differences from the journal's pdf version. The original publication is available at www.informaworld.com: http://dx.doi.org/10.3109/17477160903497035Objectives. To examine markers of infl ammation in 9- and 15-year-olds with high waist circumference and compare these with controls, and to examine the relationships between infl ammatory markers and cardiovascular disease (CVD) risk factors. Methods. Cross-sectional analysis of data from 2 299 Norwegian 9- and 15-year-olds participating in the “Physical activity among Norwegian Children Study”. In each sex and age group, the 10 participants with the highest waist circumference (HW) were selected (n 40) for analyses, and a random sample of 40 participants within the same groups were included as controls. Infl ammatory markers included C-reactive protein (CRP), leptin, adiponectin, plasminogen activator inhibitor-1 (PAI-1), tumor necrosis factor-α (TNF-α), hepatocyte growth factor (HGF), resistin and interleukin-6 (IL-6). The CVD risk factors included blood pressure, glucose, insulin, triglycerides and high density lipoprotein cholesterol. Results. HW participants had elevated levels of CRP (mean difference 1.50 mg/l; 95% confi dence interval [CI] 0.33 to 2.66), PAI-1 (mean difference 13.3 ng/ml; 95% CI 4.1 to 22.5) and HGF (mean difference 0.29 ng/ml; 95% CI 0.07 to 0.51) compared with controls. All CVD risk factors differed between the HW group and controls. The CVD risk factors were not associated with TNFα or IL-6, but CRP, HGF and PAI-1 were related to the metabolic risk score. Conclusions. Low grade systemic infl ammation is already present in youth with high waist circumference. CRP, HGF and PAI-1 may be related to the adverse overall metabolic risk profi le observed in these children and adolescents

Among the9-and 15-yr-olds, respectively. We assessed muscular strength by measuring explosive, isometric, and endurance strength. Cardiorespiratory fitness was measured directly as peak oxygen uptake during a cycle ergometry test. Risk factors included in the composite risk factor score (sum of z-scores) were systolic blood pressure, triglyceride, high-density lipoprotein cholesterol, insulin resistance, and waist circumference. Results: Muscle fitness was negatively associated with clustered metabolic risk, independent of cardiorespiratory fitness, and after adjustment for age, sex, and pubertal stage (β = −0.112, P < 0.001). Independent of muscle fitness, an inverse association was found between cardiorespiratory fitness and clustered metabolic risk (β = −0.337, P < 0.001). Moreover, the odds ratios for having clustered risk in the least fit quartile compared with the most fit quartile were 7.2 (95% confidence interval (CI)=4.3-12.0) and 17.3 (95% CI = 9.2-32.7) for muscle fitness and cardiorespiratory fitness, respectively. Conclusions: Our results show that muscle fitness and cardiorespiratory fitness are independently associated with metabolic risk in youth....