Suchergebnisse

A.P.-F. and J.M.A.: conception and design, statistical analysis, interpretation of data, writing paper. F.J.A.G. and F.M.A.: conducted experiments, analyzed and interpretation of data, feedback on the paper. J.M.G.: feedback on the paper. J.H.M., J.S., and F.B.O.: interpretation of data, feedback on the paper. All authors read and approved the final manuscript. ; Heart rate variability (HRV) is a valid and non-invasive indicator of cardiac autonomic nervous system functioning. Short-term HRV recordings (e.g., 10 min long) produce data that usually is manually processed. Researcher subjective decision-making on data processing could produce inter- or intraresearcher differences whose magnitude has not been previously quantified in three independent human cohorts. This study examines the inter- and intra-researcher reproducibility of HRV parameters (i.e., the influence of R–R interval selection by different researchers and by the same researcher in different moments on the quantification of HRV parameters, respectively) derived from short-term recordings in a cohort of children with overweight/obesity, young adults and middle-age adults. Participants were recruited from 3 different studies: 107 children (10.03 ± 1.13 years, 58% male), 132 young adults (22.22 ± 2.20 years, 33% males) and 73 middle-aged adults (53.62 ± 5.18 years, 48% males). HRV was measured using a Polar RS800CX heart rate monitor. The intraclass correlation coefficient (ICC) ranged from 0.703 to 0.989 and from 0.950 to 0.998 for inter-and intra-researcher reproducibility, respectively. Limits of agreement for HRV parameters were higher for the interresearcher processing compared with the intra-researcher processing. On average, the intraresearcher differences were 31%, 62%, and 80% smaller than the inter-researchers differences based on Coefficient of Variation in children, young and middle-aged adults, respectively. Our study provides the quantification of the inter-researcher and intra-researcher differences in three independent human cohorts, which could elicit some clinical relevant differences for HRV parameters. Based on our findings, we recommend the HRV data signal processing to be performed always by the same trained researcher and we postulate a development of algorithms for an automatic ECG selection. ; Spanish Ministry of Economy and Competitiveness DEP2013-47540 DEP2016-79512-R PTA 12264-I ; Spanish Ministry of Education, Culture and Sport FPU 16/02760 FPU15/02645 FPU15/04059 FPU14/06837 FPU14/04172 ; Unit of Excellence on Exercise and Health (UCEES) ; EXERNET Research Network on Exercise and Health in Special Populations DEP2005-00046/ACTI ; Unit of Excellence in Sport and Health (UCEES) - University of Granada ; Junta de Andalucía ; European Union (EU) SOMM17/6107/UGR

We are grateful to Ana Yara Postigo-Fuentes for her assistance with English language. ; The aim of this study was to examine the associations of sedentary behaviour, physical activity, cardiorespiratory fitness (CRF), and body composition parameters with risk of sleep-related breathing disorders (SRBD) in children with overweight/obesity. One-hundred and nine children (10.0 ± 1.1 years old, 45 girls) with overweight (n = 27) and obesity (n = 82) were included. Television viewing time was self-reported by using the Spanish adaptation of the "Youth Activity Profile" (YAP) questionnaire. Sedentary time and physical activity were measured with accelerometry. CRF was assessed with the 20-m shuttle-run test and body composition parameters with Dual-energy X-ray absorptiometry. SRBD were evaluated by using the Spanish version of the Pediatric Sleep Questionnaire. Television viewing time was positively associated with risk of SRBD (r = 0.222, p = 0.021). CRF was negatively correlated with risk of SRBD (r = −0.210, p = 0.030). Body composition parameters were positively associated with risk of SRBD (all p < 0.05), except fat mass index. Stepwise regression analyses showed that body mass index (BMI) explained the largest proportion of the variance in SRBD (r 2 = 0.063, p = 0.01) and television viewing time was the only one added after BMI (r 2 change = 0.048, p = 0.022). This study supports the notion that higher body weight status negatively influences risk of SRBD and adds that unhealthy behaviours could contribute to worsen SRBD, related to an increased risk of cardiovascular diseases. All the significant association observed in this manuscript were of small magnitude, indicating than other factors in addition to the one hereby studied contribute to explain the variance in SRBD. ; Spanish Ministry of Economy and Competitiveness ; European Union (EU) DEP2013-47540 DEP2016-79512-R DEP2017-91544-EXP RYC-2011-09011 ; Spanish Ministry of Science, Innovation and Universities FPU17/04802 ; University of Granada, Plan Propio de Investigacion y Transferencia 2018 ; Spanish Ministry of Education, Culture and Sport FPU15/02645 FPU 16/02760 ; Spanish Ministry of Economy and Competitiveness BES-2014-068829 ; Government of Andalusian, Integrated Territorial Initiative 2014-2020 for the province of Cadiz PI-0002-2017 ; Spanish Government FJC2018-037925-I ; University Jaume I PREDOC/2015/13 E-2017-13 ; Comision Nacional de Investigacion Cientifica y Tecnologica (CONICYT) 72180543 ; University of Granada, Plan Propio de Investigacion 2016, Excellence actions: Units of Excellence, Scientific Excellence Unit on Exercise and Health (UCEES) ; Junta de Andalucia ; European Union (EU) ; European Union (EU) SOMM17/6107/UGR ; SAMID III network, RETICS ; PNI + D + I 2017-2021 (Spain), ISCIIISub-Directorate General for Research Assessment and Promotion ; EXERNET Research Network on Exercise and Health in Special Populations DEP2005-00046/ACTI ; European Union (EU) 667302

Recent studies investigated the association of cardiorespiratory ftness with white matter microstructure in children, yet little work has explored to what extent other components of physical ftness (i.e., muscular or motor ftness) are associated with white matter microstructure. Indeed, this association has not been previously explored in children with overweight/obesity who present a diferent white matter development. Therefore, we aimed to examine associations between physical ftness components and white matter microstructure in children with overweight/obesity. In total, 104 (10.04 ± 1.15 years old; 43 girls) children were included in this cross-sectional study. Physical ftness was assessed using the ALPHA-ftness test battery. Fractional anisotropy (FA) and mean difusivity were derived from difusion tensor imaging (DTI). No association was found between physical ftness and global DTI metrics (all P> 0.082). Within individual tracts, all associations became non-signifcant when analyses were adjusted for multiple comparisons. Using the voxel-wise approach, we identifed a small cluster in the left lateral frontal lobe where children with greater upper-body muscular ftness showed higher FA (PFWE-corrected = 0.042). Although our results cannot conclude physical ftness is related to white matter microstructure in children with overweight/obesity; those fndings indicate that the association of muscular ftness with white matter microstructure might be more focal on frontal areas of the brain, as opposed to global diferences. ; Spanish Ministry of Economy and Competitiveness DEP2013-47540 DEP2016-79512-R DEP2017-91544-EXP RTI2018-095284-J-100 ; European Union (EU) ; European Commission Joint Research Centre 667302 ; Alicia Koplowitz Foundation ; University of Granada, Research and Knowledge Transfer Fund (PPIT) 2016 ; Excellence Actions Programme: Units of Excellence ; Scientific Unit of Excellence on Exercise and Health (UCEES) ; Andalusian Regional Government ; Regional Ministry of Economy, Knowledge, Entreprises and University ; European Union (EU) SOMM17/6107/UGR ; SAMID III network, RETICS - PN I+D+I 2017-2021 (Spain) ; Spanish Ministry of Education, Culture and Sport FPU14/06837 FPU 16/02760 ; Government of Andalusian, Integrated Territorial Initiative 2014-2020 for the province of Cadiz PI-0002-2017 ; Spanish Ministry of Science, Innovation and Universities FJCI-2017-33396

The following are available online at https://www.mdpi.com/2077-0383/9/2/325/s1, Figure S1: Example of a visual inspection of a R-R signal to find possible artefacts or premature contractions across Kubios filters; Figures S2 and S3: Differences on the Heart Rate Variability (HRV) time- and frequency-domains parameters respectively without considering the Very Strong filter; Figure S4: Differences between cohorts on the SDNN using different Kubios filters; Figure S5: Differences between cohorts on the pNN50 using different Kubios filters; and Figure S6: Differences between cohorts on the HF using different Kubios filters. ; Juan M.A. Alcantara, Abel Plaza-Florido, Jairo H. Migueles, Guillermo Sanchez-Delgado and Francisco J. Amaro-Gahete are supported by the Spanish Ministry of Education, Culture and Sport (FPU15/04059, FPU16/02760, FPU15/02645, FPU13/04365 and FPU14/04172 respectively). Guillermo Sanchez-Delgado is supported by the University of Granada Plan Propio de Investigación 2018 (Programa Contratos-Puente and Programa Perfeccionamiento de Docotres). Francisco J. Amaro-Gahete is supported by the University of Granada Plan Propio de Investigación 2019 (Programa Contratos-Puente). Guillermo Sanchez-Delgado and Borja Martinez-Tellez are supported by individual postdoctoral grants from the Fundación Alfonso Martin Escudero. ; Heart rate variability (HRV) is a non-invasive indicator of autonomic nervous system function. HRV recordings show artefacts due to technical and/or biological issues. The Kubios software is one of the most used software to process HRV recordings, offering different levels of threshold-based artefact correction (i.e., Kubios filters). The aim of the study was to analyze the impact of different Kubios filters on the quantification of HRV derived parameters from short-term recordings in three independent human cohorts. A total of 312 participants were included: 107 children with overweight/obesity (10.0 ± 1.1 years, 58% men), 132 young adults (22.2 ± 2.2 years, 33% men) and 73 middle-aged adults (53.6 ± 5.2 years, 48% men). HRV was assessed using a heart rate monitor during 10–15 min, and the Kubios software was used for HRV data processing using all the Kubios filters available (i.e., 6). Repeated-measures analysis of variance indicated significant differences in HRV derived parameters in the time-domain (all p < 0.001) across the Kubios filters in all cohorts, moreover similar results were observed in the frequency-domain. When comparing two extreme Kubios filters, these statistical differences could be clinically relevant, e.g. more than 10 ms in the standard deviation of all normal R-R intervals (SDNN). In conclusion, the results of the present study suggest that the application of different Kubios filters had a significant impact on HRV derived parameters obtained from short-term recordings in both time and frequency-domains. ; The study was funded by the Spanish Ministry of Economy and Competitiveness (DEP2013-47540 and DEP2016-79512-R), the Fondo de Investigación Sanitaria del Instituto de Salud Carlos III (PI13/01393), European Union Development Funds, the Fundación Iberoamericana de Nutrición (FINUT), the Redes Temáticas de Investigación Cooperativa RETIC (Red SAMID RD16/0022), the University of Granada Plan Propio de Investigación 2016 (Excellence actions: Unit of Excellence on Exercise and Health [UCEES]), and the Junta de Andalucía, Consejería de Conocimiento, Investigación y Universidades (FEDER: ref. SOMM17/6107/UGR).

Large epidemiological studies that use accelerometers for physical behavior and sleep assessment differ in the location of the accelerometer attachment and the signal aggregation metric chosen. This study aimed to assess the comparability of acceleration metrics between commonly-used body-attachment locations for 24 hours, waking and sleeping hours, and to test comparability of PA cut points between dominant and non-dominant wrist. Forty-five young adults (23 women, 18–41 years) were included and GT3X + accelerometers (ActiGraph, Pensacola, FL, USA) were placed on their right hip, dominant, and non-dominant wrist for 7 days. We derived Euclidean Norm Minus One g (ENMO), Low-pass filtered ENMO (LFENMO), Mean Amplitude Deviation (MAD) and ActiGraph activity counts over 5-second epochs from the raw accelerations. Metric values were compared using a correlation analysis, and by plotting the differences by time of the day. Cut points for the dominant wrist were derived using Lin's concordance correlation coefficient optimization in a grid of possible thresholds, using the nondominant wrist estimates as reference. They were cross-validated in a separate sample (N = 36, 10 women, 22–30 years). Shared variances between pairs of acceleration metrics varied across sites and metric pairs (range in r2: 0.19–0.97, all p < 0.01), suggesting that some sites and metrics are associated, and others are not. We observed higher metric values in dominant vs. non-dominant wrist, thus, we developed cut points for dominant wrist based on ENMO to classify sedentary time (<50 mg), light PA (50–110 mg), moderate PA (110–440 mg) and vigorous PA (≥440 mg). Our findings suggest differences between dominant and non-dominant wrist, and we proposed new cut points to attenuate these differences. ENMO and LFENMO were the most similar metrics, and they showed good comparability with MAD. However, counts were not comparable with ENMO, LFENMO and MAD. ; This study was conducted under the umbrella of the ActiveBrains and the SmarterMove projects supported by the MINECO/FEDER (DEP2013-47540, DEP2016- 79512-R, RYC-2011-09011). JHM and AP-F are supported by grants from the Spanish Ministry of Education, Culture and Sport (FPU15/02645, FPU16/02760). CC-S is supported by a grant from the Spanish Ministry of Economy and Competitiveness (BES-2014-068829). IE-C is supported by a grant from the Alicia Koplowitz Foundation and by the Spanish Ministry of Economy and Competitiveness (IJCI-2017-33642). PH is supported by a grant from the the Strategic Research Area Health Care Science, Karolinska Institutet/Umea University. AR is supported by the NIHR Leicester Biomedical Research Centre and the Collaboration for leadership in Applied Health Research and Care (CLAHRC) East Midlands. UE is supported by the Research Council of Norway (249932/F20). This study has been partially funded by the University of Granada, UGR Research and Knowledge Transfer Fund (PPIT) 2016, Excellence Actions Programme: Units of Scientific Excellence; Scientific Unit of Excellence on Exercise and Health (UCEES), and by the Regional Government of Andalusia, Regional Ministry of Economy, Knowledge, Entreprises and University and European Regional Development Fund (ERDF), ref. SOMM17/6107/UGR. In addition, funding was provided by the SAMID III network, RETICS, funded by the PN I + D + I 2017–2021 (Spain), ISCIII- Sub-Directorate General for Research Assessment and Promotion, the European Regional Development Fund (ERDF) (Ref. RD16/0022), the EXERNET Research Network on Exercise and Health in Special Populations (DEP2005-00046/ACTI) and the European Union Horizon 2020 research and innovation programme under grant agreement No 667302.