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.

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.

Corrigendum: Structural validity of the Norwegian version of the Strengths and Difficulties Questionnaire in children aged 3-6 years.

[This corrects the article DOI: 10.3389/fpsyg.2022.1024918.].

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.

Prospective Association Patterns for the Physical Activity Intensity Spectrum With Body Mass Index and Lower Body Muscle Strength in Norwegian Children Aged 3-9 Years.

BACKGROUND: Limited evidence exists regarding prospective associations for physical activity (PA) and sedentary time (SED) with body mass index (BMI) and muscle strength in young children. We aimed to determine prospective associations for PA and SED with change in BMI and standing long jump over 2 and 4 years in children aged 3-5 years at baseline. METHODS: A sample of 262 Norwegian children (50% girls) was followed from 2015 to 2017 and/or 2019. PA and SED (hip-worn ActiGraph GT3X+) were measured at baseline and BMI and standing long jump at baseline and at follow-ups. Multivariate pattern analysis was used to determine prospective associations between the triaxial PA intensity spectrum (0-99 to ≥15,000 counts per minute) and the change in outcomes. RESULTS: We found significant prospective associations between the PA intensity spectrum and standing long jump at 2- (explained variance = 5.8%-7.7%) and 4-year (explained variance = 4.8%-5.6%) follow-ups. Associations were negative for SED and positive for all PA intensities. We found no associations between PA/SED and BMI. CONCLUSIONS: Our findings suggest that PA and SED can predict future lower body muscle strength but not BMI in early childhood.

Individual- and Environmental- Level Predictors of Recess Activity and Sedentary Behavior: Findings from the I-CAN! study.

Introduction/Purpose: Recess represents a prime opportunity for physical activity during the school day. However, evidence is mixed with regard to factors associated with activity during recess. Methods: Data were collected as a part of the Texas Initiative for Children's Activity and Nutrition (I-CAN!) program from 14 elementary schools and 1,049 4th-grade students. Percent of time in moderate-to-vigorous physical activity (MVPA) and sedentary behavior during recess was measured using GT3X+ accelerometers. Students' demographics, aerobic fitness, and body mass index (BMI) were collected from school records and FITNESSGRAM® data. Aspects of the playground environment supporting activity (e.g. soccer goals) or sedentary behavior (e.g. benches) were calculated following the procedures of the System for Observing Play and Leisure Activity in Youth (SOPLAY), with recess spatial area calculated via the polygon measurement tool in Google™ Earth Pro software. Recess time was collected from school data. Weather during recess was determined using time-stamped archived weather data from Weather Underground. Two-level, linear mixed model regression examined associations between individual- and school-level characteristics and percent time in MVPA. Results: At the student-level, boys were more active than girls (effect size (ES)=0.50) and percent time in MVPA was directly associated with aerobic fitness (ES=0.35). At the school-level, recess infrastructure was associated with percent time in MVPA (ES=1.45), except for factors related to sedentary behavior, which were indirectly associated with percent time in MVPA (ES=-1.98). Patterns for sedentary behavior mirrored these effects. Conclusions: This is one of the few studies to test the associations of fitness and sedentary upgrades to play areas with MVPA and sedentary behavior. The results suggest that recess is most likely to support MVPA in boys and those who are already most fit (i.e., those who would not be the target of intervention). This is not surprising because the focus of recess is on free choice of play, and thus recess might be supported more for social and emotional benefits than the impact on physical activity.

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.

The multivariate physical activity signatures associated with body mass index and waist-to-height ratio in 3-5-year-old Norwegian children.

The evidence regarding associations between intensity-specific physical activity and adiposity in young children is inconclusive. The aim of this study was to determine the multivariate physical activity intensity signatures associated with body mass index and waist-to-height ratio in children aged 3-5 years. A sample of 1003 Norwegian preschool children (mean age 4.3 years, 51 % boys) from the Active Learning Norwegian Preschool(er)s study provided data on physical activity (ActiGraph GT3X+), body mass index, and waist-to-height ratio during 2019-2020. Multivariate pattern analysis was used to determine associations between the triaxial intensity spectrum (0-99 to ≥15,000 counts per minute) and the outcomes. We found significant associations for physical activity with body mass index and waist-to-height ratio (explained variances = 10.8 and 11.5 %, respectively). For the vertical axis, associations were negative for time spent sedentary (0-99 counts per minute) and positive for time spent in lower intensities (100-2999 counts per minute) for both outcomes, whereas associations for vigorous intensities (≥4000 counts per minute) differed for body mass index (no associations) and waist-to-height ratio (negative associations). Association patterns for body mass index and waist-to-height ratio were rather similar, but the stronger associations with vigorous physical activity intensities for waist-to-height ratio suggest that waist-to-height ratio might better capture adiposity resulting from inactivity than body mass index.

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.

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.

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 Multivariate Physical Activity Signatures Associated With Self-Regulation, Executive Function, and Early Academic Learning in 3-5-Year-Old Children.

The evidence regarding associations between intensity-specific physical activity and cognitive and learning outcomes in preschoolers is inconsistent and limited by low sample sizes and analytical approaches that cannot handle the multicollinearity among multiple physical activity intensity variables. We aimed to determine the multivariate physical activity intensity signatures associated with self-regulation, executive function, and early academic learning in preschool children aged 3-5 years. A 711 Norwegian preschool children (mean age 4.6 years, 52% boys) provided valid data on physical activity (ActiGraph GT3X+), self-regulation, executive function, and early academic learning during 2019-2020. Multivariate pattern analysis was used to determine associations between uniaxial and triaxial intensity spectra (time spent in intensities from 0-99 to ≥15,000 counts per minute) and the outcomes in the total sample and in subgroups split by sex and age (median split). Uniaxial data led to the highest explained variances (R 2) and were reported as the primary findings. We found significant association patterns between physical activity and numeracy (R 2 = 4.28%) and inhibition (R 2 = 1.48%) in the total sample. The associations with numeracy were negative for time spent sedentary (0-99 counts per minute) and positive for time spent in moderate to vigorous intensities (≥ 1,000 counts per minute). The associations with inhibition were positive for time spent sedentary (0-99 counts per minute) and in vigorous intensities (≥ 8,500 counts per minute) and negative for time spent in low to moderate intensities (100-3,499 counts per minute). Associations with numeracy were stronger in boys (R 2 = 5.58%) and older children (R 2 = 7.27%), and associations with inhibition were stronger in girls (R 2 = 3.12%) and older children (R 2 = 3.33%). In conclusion, we found weak associations with numeracy and inhibition across the physical activity intensity spectrum in preschool children.

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.

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.

Structural validity of the Norwegian version of the Strengths and Difficulties Questionnaire in children aged 3-6 years.

Introduction: This study examined the structural validity of the teacher-report Strength and Difficulties Questionnaire (SDQ) in Norwegian preschoolers aged 3-6 years. We tested the original five-factor structure, the five-factor structure with two broader second-order factors, and a three-factor structure, all suggested in the literature. Since the positively worded items in SDQ have been shown to introduce noise, we also examined all three structures with a positive construal method factor for these items. Methods: Preschool teachers from 43 preschools completed the SDQ questionnaire for 1,142 children [48% girls, mean age 4.3 (SD 0.9) years]. Confirmatory factor analyses were used to estimate and compare the six models. Measurement invariance was tested across sex (multi-group approach) and age (multiple-indicator multiple-cause approach). Results: The original five-factor structure of SDQ was supported, where the model fit improved when including a method factor for positively worded items. Both models showed scalar invariance across sex and age. The second-order and the three-factor structures were not supported. Conclusion: We recommend using the original five-factor structure when using SDQ for both clinical and research purposes in young children and adding a method factor when using structural equation modeling.

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.

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.

Influence of adiposity and physical activity on the cardiometabolic association pattern of lipoprotein subclasses to aerobic fitness in prepubertal children.

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.

Cardiometabolic Associations between Physical Activity, Adiposity, and Lipoprotein Subclasses in Prepubertal Norwegian Children.

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.

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.