Multivariate pattern analysis: a method and software to reveal, quantify, and visualize predictive association patterns in multicollinear data.

BACKGROUND: 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. RESULTS: MVPA has been implemented in an open-source R package of the same name, mvpa. To facilitate the usage and interpretation of complex association patterns, mvpa has also been integrated into an R shiny app, mvpaShiny, which can be accessed on www.mvpashiny.org . MVPA utilizes a general projection algorithm that embraces a diversity of possible models. The method handles multicollinear and even linear dependent covariates. MVPA separates the variance in the data into orthogonal parts within the frame of a single joint model: one part describing the relations between covariates, outcome, and explanatory variables and another part describing the "net" predictive association pattern between outcome and explanatory variables. These patterns are visualized and interpreted in variance plots and plots for pattern analysis and ranking according to variable importance. Adjustment for a linear dependent covariate is performed in three steps. First, partial least squares regression with repeated Monte Carlo resampling is used to determine the number of predictive PLS components for a model relating the covariate to the outcome. Second, postprocessing of this PLS model by target projection provided a single component expressing the predictive association pattern between the outcome and the covariate. Third, the outcome and the explanatory variables were adjusted for the covariate by using the target score in the projection algorithm to obtain "net" data. We illustrate the main features of MVPA by investigating the partial mediation of a linearly dependent metabolomics descriptor on the association pattern between a measure of insulin resistance and lifestyle-related factors. CONCLUSIONS: Our method and implementation in R extend the range of possible analyses and visualizations that can be performed for complex multivariate data structures. The R packages are available on github.com/liningtonlab/mvpa and github.com/liningtonlab/mvpaShiny.

Effects of a staff-led multicomponent physical activity intervention on preschooler's fundamental motor skills and physical fitness: The ACTNOW cluster-randomized controlled trial.

BACKGROUND: Fundamental motor skills (FMS) and physical fitness (FIT) play important roles in child development and provide a foundation for lifelong participation in physical activity (PA). Unfortunately, many children have suboptimal levels of PA, FMS, and FIT. The Active Learning Norwegian Preschool(er)s (ACTNOW) study investigated the effects of a staff-led PA intervention on FMS, FIT, and PA in 3-5-year-old children. METHODS: Preschools in Western Norway having ≥ six 3-4-year-old children were invited (n = 56). Of these, 46 agreed to participate and were cluster-randomized into an intervention (n = 23 preschools [381 children, 3.8 yrs., 55% boys]) or a control group (n = 23 [438, 3.7 yrs., 52% boys]). Intervention preschools participated in an 18-month PA intervention involving a 7-month staff professional development between 2019 and 2022, amounting to 50 h, including face-to-face seminars, webinars, and digital lectures. Primary outcomes in ACTNOW were cognition variables, whereas this study investigated effects on secondary outcomes. FMS was measured through 9 items covering locomotor, object control, and balance skills. FIT was assessed as motor fitness (4 × 10 shuttle-run test) and upper and lower muscular strength (handgrip and standing long jump). PA was measured with accelerometers (ActiGraph GT3X +). All measures took place at baseline, 7-, and 18-month follow-up. Effects were analysed using a repeated measures linear mixed model with child and preschool as random effects and with adjustment for baseline scores. RESULTS: Participants in the intervention preschools showed positive, significant effects for object control skills at 7 months (standardized effect size (ES) = 0.17) and locomotor skills at 18 months (ES = 0.21) relative to controls. A negative effect was found for handgrip strength (ES = -0.16) at 7 months. No effects were found for balance skills, standing long jump, or motor fitness. During preschool hours, sedentary time decreased (ES = -0.18), and light (ES = 0.14) and moderate-to-vigorous PA (ES = 0.16) increased at 7 months, whereas light PA decreased at 18 months (ES = -0.15), for intervention vs control. No effects were found for other intensities or full day PA. CONCLUSIONS: The ACTNOW intervention improved some FMS outcomes and increased PA short-term. Further research is needed to investigate how to improve effectiveness of staff-led PA interventions and achieve sustainable improvements in children's PA, FMS, and FIT. TRIAL REGISTRATION: Clinicaltrials.gov, identifier NCT04048967 , registered August 7, 2019. FUNDING: ACTNOW was supported by the Research Council of Norway (grant number 287903), the County Governor of Sogn og Fjordane, the Sparebanken Sogn og Fjordane Foundation, and the Western Norway University of Applied Sciences.

The influence of reliability and variability of objectively measured physical activity on associations with lower body muscle strength in young children.

It is not known how extended or multiple monitoring periods affect associations between accelerometer-measured physical activity and outcomes. The aim of this study was to examine how accelerometer monitoring length influenced cross-sectional and prospective associations for physical activity with lower body muscle strength in young children. 176 Norwegian 2-6-year-old children had 3 valid 14-day periods of accelerometer monitoring (ActiGraph GT3×+) between September 2015 and May 2016 (baseline) as well as baseline and 4-year follow-up measurements of standing long jump. We analysed physical activity using a descriptor with 4 intensities using 6 different monitoring lengths both within and across monitoring periods (1 day, 3 days, 1 week, 2 weeks, 3 weeks, 6 weeks) and determined associations with lower body muscle strength using multivariate pattern analysis. We found that the strength of cross-sectional associations with lower body muscle strength improved for longer monitoring periods (explained variances = 7.7%, 9.8%, 11.8%, 15.8%, 18.4% and 22.9% for 1 day, 3 days, 1 week, 2 weeks, 3 weeks and 6 weeks of measurement). Longitudinal associations were weaker and less clear. Our findings suggest that multiple extended physical activity monitoring periods improve the validity of the study findings regarding associations between physical activity and relevant outcomes.

Multivariate physical activity association patterns for fundamental motor skills and physical fitness in preschool children aged 3-5 years.

Physical activity (PA) is important for children's development of fundamental motor skills (FMS) and physical fitness (FIT) but evidence regarding which intensities are associated with these outcomes in early childhood is limited. The aim of this study was to determine the cross-sectional multivariate PA intensity signatures associated with FMS and FIT in children aged 3-5 years. We used a sample of 952 Norwegian preschoolers (4.3 years, 51% boys) who provided data on PA (ActiGraph GT3X+), at least one FMS (locomotor, object control and/or balance skills) or FIT (speed agility, standing long jump, and/or handgrip strength) outcome, body mass index, and socioeconomic status in 2019-2020. We created 17 PA intensity variables (0-99 to ≥15000 counts per minute) from the vertical axis and used multivariate pattern analysis for analyses. The PA intensity spectrum (including sedentary time) was significantly associated with all outcomes. Associations for PA intensities were positive (negative for sedentary time), strongest for moderate and vigorous intensities, and were significant across sex and age groups. Our findings show that the PA intensity spectrum is associated with FMS and FIT in young children and that promotion of PA, in particular moderate- and vigorous-intensity activity, from an early age benefits children's physical development.

An approach to assess and adjust for the influence of multicollinear covariates on metabolomics association patterns-applied to a study of the associations between a comprehensive lipoprotein profile and the homeostatic model assessment of insulin resistance.

INTRODUCTION: 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. OBJECTIVES: We aimed at (i) developing an approach for assessment and adjustment of the influence of multicollinear and even linear dependent covariates on regression models, and (ii) to use this approach to examine the influence of adiposity and physical activity on the association pattern between HOMA-IR and the lipoprotein profile. METHODS: For 841 children, lipoprotein profiles were obtained from serum proton NMR and physical activity (PA) intensity profiles from accelerometry. Adiposity was measured as body mass index, the ratio of waist circumference to height, and skinfold thickness. Target projections were used to assess and isolate the influence of adiposity and PA on the association pattern of HOMA-IR to the lipoproteins. RESULTS: Adiposity explained just over 50% of the association pattern of HOMA-IR to the lipoproteins with strongest influence on high-density lipoprotein features. The influence of PA was mainly attributed to a strong inverse association between adiposity and moderate and high-intensity physical activity. CONCLUSION: The presented covariate projection approach to obtain net association patterns, made it possible to quantify and interpret the influence of adiposity and physical (in)activity on the association pattern of HOMA-IR to the lipoprotein features.

Trajectories of physical activity and sedentary time in Norwegian children aged 3-9 years: a 5-year longitudinal study.

BACKGROUND: Limited evidence exists regarding the longitudinal development of physical activity during early to mid childhood. The aim of this study was to determine physical activity and sedentary time trajectories in children aged 3‒9 years from Western Norway. METHODS: A sample of 294 children (51% boys; aged 3‒5 years at baseline) from the Sogn og Fjordane Preschool Physical Activity Study was followed annually over 5 years (2015‒2019). Physical activity was measured every autumn during this period using hip-based accelerometry (ActiGraph GT3X+). Data was processed as counts. We used linear mixed models to analyse the data. Primary analyses included trajectories for total and intensity-specific physical activity (light, moderate, vigorous, and moderate to vigorous intensity) and sedentary time for boys and girls using 1-s epoch. Secondary analyses included trajectories for weekdays versus weekend days, preschool/school hours versus after school hours, and 1- versus 60-s epoch lengths. RESULTS: Over the total day, significant associations with age were found for boys and girls for all physical activity intensities and sedentary time (p < .001). Total physical activity peaked at age 5, whereas intensity-specific physical activity levels peaked at age 3 to 8 years (light intensity: 3-4 years; moderate intensity: 4-7 years; vigorous intensity: 7-8 years; moderate to vigorous intensity: 5-8 years). Boys had higher physical activity levels and more favourable trajectories than girls. Sedentary time increased from ages 3 to 9. Changes over time were larger for weekdays than for weekend days and larger for preschool/school hours than for after school hours. The use of a 60-s epoch resulted in larger changes over time than a 1-s epoch. CONCLUSIONS: Our findings suggest physical activity levels peaked between the ages of 3 and 8 years. Finding ways to prevent decline in physical activity during the transition from preschool to primary school is important, especially for girls. Standardising epoch length will help when comparing physical activity and sedentary behaviour across studies.

Associations of lipoprotein particle profile and objectively measured physical activity and sedentary time in schoolchildren: a prospective cohort study.

BACKGROUND: Our understanding of the mechanisms through which physical activity might benefit lipoprotein metabolism is inadequate. Here we characterise the continuous associations between physical activity of different intensities, sedentary time, and a comprehensive lipoprotein particle profile. METHODS: Our cohort included 762 fifth grade (mean [SD] age = 10.0 [0.3] y) Norwegian schoolchildren (49.6% girls) measured on two separate occasions across one school year. We used targeted proton nuclear magnetic resonance (1H NMR) spectroscopy to produce 57 lipoprotein measures from fasted blood serum samples. The children wore accelerometers for seven consecutive days to record time spent in light-, moderate-, and vigorous-intensity physical activity, and sedentary time. We used separate multivariable linear regression models to analyse associations between the device-measured activity variables-modelled both prospectively (baseline value) and as change scores (follow-up minus baseline value)-and each lipoprotein measure at follow-up. RESULTS: Higher baseline levels of moderate-intensity and vigorous-intensity physical activity were associated with a favourable lipoprotein particle profile at follow-up. The strongest associations were with the larger subclasses of triglyceride-rich lipoproteins. Sedentary time was associated with an unfavourable lipoprotein particle profile, the pattern of associations being the inverse of those in the moderate-intensity and vigorous-intensity physical activity analyses. The associations with light-intensity physical activity were more modest; those of the change models were weak. CONCLUSION: We provide evidence of a prospective association between time spent active or sedentary and lipoprotein metabolism in schoolchildren. Change in activity levels across the school year is of limited influence in our young, healthy cohort. TRIAL REGISTRATION: ClinicalTrials.gov , # NCT02132494 . Registered 7th April 2014.

Physical activity intensity profiles associated with cardiometabolic risk in middle-aged to older men and women.

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.

GRANADA consensus on analytical approaches to assess associations with accelerometer-determined physical behaviours (physical activity, sedentary behaviour and sleep) in epidemiological studies.

The inter-relationship between physical activity, sedentary behaviour and sleep (collectively defined as physical behaviours) is of interest to researchers from different fields. Each of these physical behaviours has been investigated in epidemiological studies, yet their codependency and interactions need to be further explored and accounted for in data analysis. Modern accelerometers capture continuous movement through the day, which presents the challenge of how to best use the richness of these data. In recent years, analytical approaches first applied in other scientific fields have been applied to physical behaviour epidemiology (eg, isotemporal substitution models, compositional data analysis, multivariate pattern analysis, functional data analysis and machine learning). A comprehensive description, discussion, and consensus on the strengths and limitations of these analytical approaches will help researchers decide which approach to use in different situations. In this context, a scientific workshop and meeting were held in Granada to discuss: (1) analytical approaches currently used in the scientific literature on physical behaviour, highlighting strengths and limitations, providing practical recommendations on their use and including a decision tree for assisting researchers' decision-making; and (2) current gaps and future research directions around the analysis and use of accelerometer data. Advances in analytical approaches to accelerometer-determined physical behaviours in epidemiological studies are expected to influence the interpretation of current and future evidence, and ultimately impact on future physical behaviour guidelines.

Accelerometer epoch length influence associations for physical activity intensities with body mass index and locomotor skills in young children.

The epoch length is decisive for the capture of physical activity intensities from accelerometry and possibly for associations between physical activity intensities and outcomes in children. The aim of the present study was to determine the multivariate physical activity intensity signatures related to body mass index and locomotor skills in preschool children using different epoch lengths. A sample of 1054 Norwegian children (mean age 4.8 years, 52% boys) from the Sogn og Fjordane Preschool Physical Activity Study provided data on physical activity (ActiGraph GT3X+), body mass index and locomotor skills in 2015-2016. Multivariate pattern analysis was used to determine associations between the physical activity intensity spectrum (0-99 to ≥15000 counts per minute) and the outcomes using files aggregated using 8 different epoch lengths from 1 to 60 seconds. We observed that associations across the intensity spectrum, from sedentary time to vigorous intensities, differed for data derived using different epoch lengths. For both outcomes, associations for moderate intensities became stronger and vigorous intensities became weaker for longer as compared to shorter epoch lengths. Aggregation of accelerometer data using different epoch lengths influences the capture of physical activity intensities and associations between physical activity intensities and related outcomes.

The role of weather conditions on time spent outdoors and in moderate-to-vigorous physical activity among Norwegian preschoolers.

The aim of this study was to determine associations between weather and playground surface conditions and time spent outdoors and in moderate-to-vigorous PA (MVPA) in preschool children aged 3-6 years. We included 1201 children (mean age 4.8 years, 51% boys) from 68 preschools in Norway who provided 12,030 days of observation during 2015-2016. Preschool MVPA was measured by accelerometry (ActiGraph GT3X+) for 10 consecutive weekdays. During this period, outdoor time and playground surface conditions were logged by staff and weather conditions were obtained from the Norwegian Meteorological Institute. Associations were determined using linear mixed models. Associations for MVPA depended on whether the analyses were adjusted for outdoor time or not. In unadjusted analyses, rainfall, wind, and wet, icy, and mixed playground conditions were negatively associated with MVPA, while temperature, snowfall, and dry playground conditions were positively associated with MVPA. In adjusted analyses, temperature and wet and mixed playground conditions were negatively associated with MVPA, while snowfall and dry and snowy playground conditions were positively associated with MVPA. Outdoor time and MVPA should be addressed simultaneously to inform interpretation of associations with weather characteristics and intervention development in early childhood education settings.

Structural validity of a test battery for assessment of fundamental movement skills in Norwegian 3-6-year-old children.

Fundamental movement skills (FMS) are building blocks of more advanced movements, including subdomains of locomotion, object control and balance skills, but limited evidence exists for this three-factor structure. The aim of this study was to examine the structural validity of a three-factor modified test battery of FMS across age and sex in two large samples of preschoolers aged 3-6 years (sample 1: n = 1213, mean age 4.8 (.09); sample 2: n = 1198, mean age 4.3 (.09)). We used a test battery of FMS consisting of movement tasks for locomotion (run, horizontal jump and hop) and object control (catch, overhand throw and kick) from the Test of Gross Motor Development and balance skills (single-leg standing, walking line backward and walking line forward) from the Preschoolers Gross Motor Quality Scale. Confirmatory factor analysis was used to analyse the data. We found support for both a three-factor and a two-factor structure. Measurement invariance testing showed invariance over age and partial scalar invariance over sex. We conclude that our modified test battery is an appropriate measure of young children's FMS across the domains of locomotion, object control and balance, but that locomotion and object control subdomains provide limited unique information.

The multivariate physical activity signature associated with body mass index in young children.

The evidence regarding associations between intensity-specific physical activity and adiposity in young children is conflicting. Moreover, the evidence is limited by analytical approaches that cannot handle the multicollinearity among multiple variables across the entire intensity spectrum. We aimed to determine the multivariate physical activity intensity signature associated with body mass index in a large sample of preschool children aged 3-6 years. 1182 Norwegian preschool children (mean age 4.7 years, 51% boys) provided data on physical activity (ActiGraph GT3X+) and body mass index during 2015-2016. Multivariate pattern analysis was used to determine associations between the entire triaxial intensity spectra (time spent in intensities from 0-99 to ≥ 15000 counts per minute) and body mass index in the total sample and in subgroups split by sex and age (median split). The association patterns were comparable across the three axes. For the vertical axis, associations were negative for time spent sedentary (0-99 counts per minute), positive for time spent in lower intensities (100-2999 counts per minute), and negative for time spent in vigorous intensities (4000-12,999 counts per minute). Associations were stronger in older than in younger children and no associations were observed for vigorous intensities among younger children. Association patterns were comparable for boys and girls. In conclusion, we found clear associations with body mass index across the physical activity intensity spectrum in preschool children. However, the age-specific association patterns suggest negative (unfavorable) associations with vigorous physical activity intensities develop around 5-6 years of age.

Bi-directional prospective associations between sedentary time, physical activity and adiposity in 10-year old Norwegian children.

There is an adverse cross-sectional association between sedentary time, physical activity (PA) and adiposity, but weak and inconsistent estimates raise question to the direction of associations. The present study aims to examine whether the prospective association between sedentary time, different PA intensities and indicators of adiposity is bi-directional. The Active Smarter Kids Study obtained data from 869 ten-year-old children with valid measurements for sedentary time, PA, and adiposity at baseline and follow-up. Time spent sedentary and PA was measured by accelerometry, adiposity was assessed by three different measures: body mass index (BMI), waist circumference (WC) and sum of four skinfolds (S4SF). Neither overall PA nor time spent sedentary predicted lower BMI or WC at follow-up, but the time spent in moderate-and-vigorous PA (MVPA) and vigorous PA (VPA) predicted lower S4SF at follow-up among boys (MVPA ß - 0.066 [95% CI -0.105, -0.027] p = 0.001). Baseline BMI and WC predicted less overall PA, MVPA and VPA in boys. All adiposity measures predicted more time spent sedentary at follow-up in boys. The results suggest that overall PA and sedentary time do not predict future adiposity. Baseline adiposity may rather predict more sedentary time and less higher intensity activity.

A comparison of analytical approaches to investigate associations for accelerometry-derived physical activity spectra with health and developmental outcomes in children.

The use of high-resolution physical activity intensity spectra obtained from accelerometry can improve knowledge of associations with health and development beyond the use of traditional summary measures of intensity. The aim of the present study was to compare three different approaches for determining associations for spectrum descriptors of physical activity (the intensity gradient, principal component analysis, and multivariate pattern analysis) with relevant outcomes in children. We used two datasets including physical activity spectrum data (ActiGraph GT3X+) and 1) a cardiometabolic health outcome in 841 schoolchildren and 2) a motor skill outcome in 1081 preschool children. We compared variance explained (R2) and associations with the outcomes for the intensity gradient (slope) across the physical activity spectra, a two-component principal component model describing the physical activity variables, and multivariate pattern analysis using the intensity spectra as the explanatory data matrices. Results were broadly similar for all analytical approaches. Multivariate pattern analysis explained the most variance in both datasets, likely resulting from use of more of the information available from the intensity spectra. Yet, volume and intensity dimensions of physical activity are not easily disentangled and their relative importance may be interpreted differently using different methodology.

Resemblance in accelerometer-assessed physical activity in families with children: the Lolland-Falster Health Study.

BACKGROUND: 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. METHOD: The study is a cross-sectional analysis of a subsample (902 parents and 935 children nested within 605 families) of the Danish population study Lolland-Falster Health Study. PA was measured using a dual-accelerometer system (Axivity AX3) with subsequent processing of time spent in light PA (LPA), moderate-to-vigorous PA (MVPA), and vigorous PA and classification of PA behaviour types. Families with at least one son/daughter aged 0-22 years and one parent providing minimum 4 days of valid accelerometer data were included in the analysis. A linear mixed model regression analysis was used to determine the intraclass correlation coefficient (ICC) of clustering among family members for PA intensities and PA behaviours, adjusted for sex, age, parental education, and the interaction between sex and age. RESULTS: In the analysis of within-family variation in PA, the ICCs across PA intensities and PA behaviours ranged from 0.06 to 0.34. We found stronger clustering in family members' PA for LPA and behaviours requiring low energy expenditure (LPA: ICC 0.22 (95% confidence interval (CI) 0.17; 0.28), sitting/lying: ICC 0.34 (95% CI 0.28; 0.40)), and walking: ICC 0.24 (95% CI 0.19; 0.30) than for higher intensities (e.g. MVPA: ICC 0.07 (95% CI 0.03; 0.14)). The ICC for biking was 0.23 (95% CI 0.18; 0.29). Analyses on parent-child dyads gave similar results. No interaction effects for gender and age (except for biking) were found. CONCLUSION: Parents and children's time spent in PA behaviours requiring low energy expenditure had moderate resemblance within families, whereas engagement in PA with higher intensities showed small or close-to-zero resemblance.

Bi-directional prospective associations between objectively measured physical activity and fundamental motor skills in children: a two-year follow-up.

BACKGROUND: 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. METHODS: A sample of 230 children (mean age at baseline 4.7 yr, 52% boys) from the 'Sogn og Fjordane Preschool Physical Activity Study' was measured 2 years apart. PA was assessed using ActiGraph accelerometers (GT3X+). FMS were evaluated by a test battery guided by the 'Test of Gross Motor Development 3' and the 'Preschooler Gross Motor Quality Scale'. PA outcomes were total PA (TPA [counts per minute]) and intensity specific PA and sedentary behaviour (SED) (min/day). FMS outcomes were locomotor, object control, and balance skills. Linear mixed model adjusting for potential co-variates was used to evaluate the bi-directional prospective associations between these variables, including the moderating effect of sex and age. RESULTS: Baseline total PA, moderate-to-vigorous PA (MVPA), and vigorous PA predicted higher locomotor, object control, and balance skills at follow-up (standardized regression coefficient (ß): 0.17 to 0.26, p = 0.002-0.017). Baseline SED predicted lower locomotor skills at follow-up (ß: - 0.27, p = 0.012). Baseline light PA did not predict FMS at follow-up. Baseline FMS were not associated with PA or SED at follow-up. CONCLUSIONS: MVPA was positively associated with development of FMS in young children. In contrast, FMS were not related to future PA levels. Our results suggest promotion of MVPA is important for FMS development in young children.

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.

The multivariate physical activity signature associated with metabolic health in children and youth: An International Children's Accelerometry Database (ICAD) analysis.

There is solid evidence for an association between physical activity and metabolic health outcomes in children and youth, but for methodological reasons most studies describe the intensity spectrum using only a few summary measures. We aimed to determine the multivariate physical activity intensity signature associated with metabolic health in a large and diverse sample of children and youth, by investigating the association pattern for the entire physical intensity spectrum. We used pooled data from 11 studies and 11,853 participants aged 5.8-18.4 years included in the International Children's Accelerometry Database. We derived 14 accelerometry-derived (ActiGraph) physical activity variables covering the intensity spectrum (from 0-99 to ≥8000 counts per minute). To handle the multicollinearity among these variables, we used multivariate pattern analysis to establish the associations with indices of metabolic health (abdominal fatness, insulin sensitivity, lipid metabolism, blood pressure). A composite metabolic health score was used as the main outcome variable. Associations with the composite metabolic health score were weak for sedentary time and light physical activity, but gradually strengthened with increasing time spent in moderate and vigorous intensities (up to 4000-5000 counts per minute). Association patterns were fairly consistent across sex and age groups, but varied across different metabolic health outcomes. This novel analytic approach suggests that vigorous intensity, rather than less intense activities or sedentary behavior, are related to metabolic health in children and youth.

Health-related quality of life and physical activity level after a behavior change program at Norwegian healthy life centers: a 15-month follow-up.

PURPOSE: 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. METHODS: We followed 524 adult participants (18-83 years), recruited from 32 HLCs in August 2016-January 2018, who provided data on HRQoL (SF-36) and PA (ActiGraph accelerometers) 12 months after a 3-month behavior change intervention. Changes in HRQoL and PA between baseline, 3-month and 15-month follow-ups, and associations between changes in PA and HRQoL were analyzed by linear mixed models. RESULTS: All HRQoL dimensions improved from baseline to 3-month follow-up, and the improvements maintained at 15-month follow-up (mean 3.1-13.1 points, p < 0.001). PA increased from baseline to 3 months (mean 418 steps/day, p < 0.001), but declined from 3 to 15 months (mean - 371 steps/day, p < 0.001). We observed positive associations between changes in PA and HRQoL (0.84-3.23 points per 1000 steps/day, p < 0.023). CONCLUSIONS: Twelve months after completing a 3-month HLC intervention we found improved HRQoL, but not PA level. Still, there were positive associations between PA and HRQoL over this period, indicating that participants increasing their PA were more likely to improve their HRQoL.