Is cardiac autonomic function associated with cardiorespiratory fitness and physical activity in children and adolescents? A systematic review of cross-sectional studies.

BACKGROUND: Heart rate variability (HRV) is considered to explain improvements in cardiovascular health accrued by physical activity (PA) and cardiorespiratory fitness (CRF) over and above traditional cardiovascular risk factors. OBJECTIVE: To systematically address associations between HRV, PA and CRF in children and adolescents. DATA SOURCES: Medline, EMBASE, SportDISCUS and CINAHL Plus were searched on 5th September 2015 and updated on 4th August 2016. ELIGIBILITY CRITERIA: Observational studies comparing HRV in different groups of PA and CRF, and/or studies investigating associations between PA, CRF and HRV. Sports practices and PA intensities were also included. The square root of the mean of the sum of the squares of differences between adjacent RR intervals (RMSSD), the spectral density in the high (HF) and low (LF) frequency, and the LF/HF ratio were included. Risk of bias was assessed using the adapted Newcastle-Ottawa Scale (NOS). RESULTS: Heterogeneity exists in the assessment of the exposures and outcomes, and sample characteristics. Risk of bias (NOS) was observed in most of the studies. Studies with low risk of bias showed positive associations between moderate-to-vigorous PA and RMSSD. The evidence for the associations between PA and frequency indices is weak. Similarly, the evidence for the association between CRF and HRV is weak. CONCLUSIONS: Despite the heterogeneity in the studies, moderate-to-vigorous PA is positively associated with RMSSD, but less clear are the associations between CRF and HRV, as well as other PA intensities. Further research is needed to clarify the role of PA and CRF on HRV in children and adolescents.

Capturing the pattern of physical activity and sedentary behavior: exposure variation analysis of accelerometer data.

BACKGROUND: Capturing the complex time pattern of physical activity (PA) and sedentary behavior (SB) using accelerometry remains a challenge. Research from occupational health suggests exposure variation analysis (EVA) could provide a meaningful tool. This paper (1) explains the application of EVA to accelerometer data, (2) demonstrates how EVA thresholds and derivatives could be chosen and used to examine adherence to PA and SB guidelines, and (3) explores the validity of EVA outputs. METHODS: EVA outputs are compared with accelerometer data from 4 individuals (Study 1a and 1b) and 3 occupational groups (Study 2): seated workstation office workers (n = 8), standing workstation office workers (n = 8), and teachers (n = 8). RESULTS: Line graphs and related EVA graphs highlight the use of EVA derivatives for examining compliance with guidelines. EVA derivatives of occupational groups confirm no difference in bouts of activity but clear differences as expected in extended bouts of SB and brief bursts of activity, thus providing evidence of construct validity. CONCLUSIONS: EVA offers a unique and comprehensive generic method that is able, for the first time, to capture the time pattern (both frequency and intensity) of PA and SB, which can be tailored for both occupational and public health research.