The purpose of this study was to validate an equation that has been used to predict peak oxygen uptake (VO2peak) and, if invalid, to develop a new equation predicting VO2peak from performance on a cycle ergometer test. Forty-five 9- and 15-year-old children underwent a VO2peak test and were randomized into developmental (DEV) and cross-validation (C-V) groups. The equation under validation, which requires knowledge of resting energy expenditure (REE), underestimated VO2peak (p < .05), but once adjusted with a new parameter calculated in DEV, it cross-validated well (r YY′ = .98, SE = .18 L · min−1). The accuracy of a new prediction equation built in DEV, not using REE, was confirmed in C-V (r YY′ = .98, SE = .17 L · min−1) and the slope and intercept were not different from the line of identity (p < .05). VO2peak in schoolchildren can be predicted with good accuracy from an equation based on the whole sample [VO2peak′ = −1.5986 + 0.0115 · (maximal power output) + 0.0109 · (mass) + 0.1313 · (gender) + 0.0085 · (maximal heart rate)].
Sigurbjörn Árni Arngrímsson, Torarinn Sveinsson and Erlingur Jóhannsson
Robert J. Brychta, Vaka Rögnvaldsdóttir, Sigríður L. Guðmundsdóttir, Rúna Stefánsdóttir, Soffia M. Hrafnkelsdóttir, Sunna Gestsdóttir, Sigurbjörn A. Arngrímsson, Kong Y. Chen and Erlingur Jóhannsson
Introduction: Sleep is often quantified using self-report or actigraphy. Self-report is practical and less technically challenging, but prone to bias. We sought to determine whether these methods have comparable sensitivity to measure longitudinal changes in adolescent bedtimes. Methods: We measured one week of free-living sleep with wrist actigraphy and usual bedtime on school nights and non-school nights with self-report questionnaire in 144 students at 15 y and 17 y. Results: Self-reported and actigraphy-measured bedtimes were correlated with one another at 15 y and 17 y (p < .001), but reported bedtime was consistently earlier (>30 minutes, p < .001) and with wide inter-method confidence intervals (> ±106 minutes). Mean inter-method discrepancy did not differ on school nights at 15 y and 17 y but was greater at 17 y on non-school nights (p = .002). Inter-method discrepancy at 15 y was not correlated to that at 17 y. Mean change in self-reported school night bedtime from 15 y to 17 y did not differ from that by actigraphy, but self-reported bedtime changed less on non-school nights (p = .002). Two-year changes in self-reported bedtime did not correlate with changes measured by actigraphy. Conclusions: Although methods were correlated, consistently earlier self-reported bedtime suggests report-bias. More varied non-school night bedtimes challenge the accuracy of self-report and actigraphy, reducing sensitivity to change. On school nights, the methods did not differ in group-level sensitivity to changes in bedtime. However, lack of correlation between bedtime changes by each method suggests sensitivity to individual-level change was different. Methodological differences in sensitivity to individual- and group-level change should be considered in longitudinal studies of adolescent sleep patterns.
Dane R. Van Domelen, Paolo Caserotti, Robert J. Brychta, Tamara B. Harris, Kushang V. Patel, Kong Y. Chen, Nanna Ýr Arnardóttir, Gudny Eirikdottir, Lenore J. Launer, Vilmundur Gudnason, Thórarinn Sveinsson, Erlingur Jóhannsson and Annemarie Koster
Accelerometers have emerged as a useful tool for measuring free-living physical activity in epidemiological studies. Validity of activity estimates depends on the assumption that measurements are equivalent for males and females while performing activities of the same intensity. The primary purpose of this study was to compare accelerometer count values in males and females undergoing a standardized 6-minute walk test.
The study population was older adults (78.6 ± 4.1 years) from the AGES-Reykjavik Study (N = 319). Participants performed a 6-minute walk test at a self-selected fast pace while wearing an ActiGraph GT3X at the hip. Vertical axis counts·s−1 was the primary outcome. Covariates included walking speed, height, weight, BMI, waist circumference, femur length, and step length.
On average, males walked 7.2% faster than females (1.31 vs. 1.22 m·s−1, P < .001) and had 32.3% greater vertical axis counts·s−1 (54.6 vs. 39.4 counts·s−1, P < .001). Accounting for walking speed reduced the sex difference to 19.2% and accounting for step length further reduced the difference to 13.4% (P < .001).
Vertical axis counts·s−1 were disproportionally greater in males even after adjustment for walking speed. This difference could confound free-living activity estimates.