Physical Activity Is Associated with Weight Loss and Increased Cardiorespiratory Fitness in Severely Obese Men and Women Undergoing Lifestyle Treatment

We aimed to examine the relationship between physical activity (PA) and change in body weight and cardiorespiratory fitness (CRF) in severely obese men and women. Thirty-five subjects (10 men, body mass index 43.2 ± 5.1 kg/m2) who participated in a 10-month lifestyle treatment programme were included. The PA duration correlated only with weight change for men (r = −0.69, P = .027 versus r = −0.19, P = .372 for women). Conversely, the PA intensity correlated only with CRF for women (r = 0.61, P = .003 versus r = 0.39, P = .340 for men). PA explained 55.8 and 5.6% of weight change for men and women, respectively, whereas the corresponding explained variances for CRF were 15.6 and 36.7%. We conclude that PA was associated with change in body weight and CRF; however, there was a trend towards a gender specific effect between severely obese men and women

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.publishedVersio

Clinical Study Physical Activity Is Associated with Weight Loss and Increased Cardiorespiratory Fitness in Severely Obese Men and Women Undergoing Lifestyle Treatment

We aimed to examine the relationship between physical activity (PA) and change in body weight and cardiorespiratory fitness (CRF) in severely obese men and women. Thirty-five subjects (10 men, body mass index 43.2 ± 5.1 kg/m 2 ) who participated in a 10-month lifestyle treatment programme were included. The PA duration correlated only with weight change for men (r = −0.69, P = .027 versus r = −0.19, P = .372 for women). Conversely, the PA intensity correlated only with CRF for women (r = 0.61, P = .003 versus r = 0.39, P = .340 for men). PA explained 55.8 and 5.6% of weight change for men and women, respectively, whereas the corresponding explained variances for CRF were 15.6 and 36.7%. We conclude that PA was associated with change in body weight and CRF; however, there was a trend towards a gender specific effect between severely obese men and women

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

IntroductionThis 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.MethodsPreschool 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).ResultsThe 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.ConclusionWe 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

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

Under embargo until: 2021-09-20The 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.acceptedVersio

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.publishedVersio

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.publishedVersio

Associations of physical activity and sedentary time with lipoprotein subclasses in Norwegian schoolchildren: The Active Smarter Kids (ASK) study

Background and aims: 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. Methods: Our cohort included 880 children (49.0% girls, mean age 10.2 years). Physical activity intensity and time spent sedentary were measured objectively using accelerometers. 30 measures of lipoprotein metabolism were quantified using nuclear magnetic resonance spectroscopy. Multiple linear regression models adjusted for age, sex, sexual maturity and socioeconomic status were used to determine associations of physical activity and sedentary time with lipoprotein measures. Additional models were adjusted for adiposity. Isotemporal substitution models quantified theoretical associations of replacing 30 min of sedentary time with 30 min of moderate- to vigorous-intensity physical activity (MVPA). Results: Time spent in MVPA was associated with a favourable lipoprotein profile independent of sedentary time. There were inverse associations with a number of lipoprotein measures, including most apolipoprotein B-containing lipoprotein subclasses and triglyceride measures, the ratio of total to high-density lipoprotein (HDL) cholesterol, and non-HDL cholesterol concentration. There were positive associations with larger HDL subclasses, HDL cholesterol concentration and particle size. Reallocating 30 min of sedentary time to MVPA had broadly similar associations. Sedentary time was only partly and weakly associated with an unfavourable lipoprotein profile. Conclusions: Physical activity of at least moderate-intensity is associated with a favourable lipoprotein profile in schoolchildren, independent of time spent sedentary, adiposity and other confounders.acceptedVersio

Associations of objectively-assessed physical activity and sedentary time with hippocampal gray matter volume in children with overweight/obesity

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.MINECO/FEDER DEP2013-47540 DEP2016-79512-R RYC-2011-09011Spanish Ministry of Education, Culture and Sport FPU15/02645 FPU17/04802Government of Andalusian, Integrated Territorial Initiative 2014-2020 for the province of Cadiz PI-0002-2017Spanish Government FJC2018-037925-IAlicia Koplowitz FoundationSpanish Ministry of Economy and Competitiveness RTI2018-095284-J-100University of Granada, Plan Propio de Investigacion 2016, Excellence actions: Units of ExcellenceScientific Excellence Unit on Exercise and Health (UCEES)Junta de AndaluciaConsejeria de Conocimiento, Investigacion y UniversidadesEuropean Union (EU)SAMID III network, RETICS - PN I + D+I 2017-2021 (Spain)ISCIII-Sub-Directorate General for Research Assessment and PromotionEuropean Union (EU) RD16/0022EXERNET Research Network on Exercise and Health in Special Populations DEP2005-00046/ACT

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