Validation of actigraphy sleep metrics in children aged 8 to 16 years: considerations for device type, placement and algorithms

BACKGROUND

Actigraphy is often used to measure sleep in pediatric populations, despite little confirmatory evidence of the accuracy of existing sleep/wake algorithms. The aim of this study was to determine the performance of 11 sleep algorithms in relation to overnight polysomnography in children and adolescents.

METHODS

One hundred thirty-seven participants aged 8-16 years wore two Actigraph wGT3X-BT (wrist, waist) and three Axivity AX3 (wrist, back, thigh) accelerometers over 24-h. Gold standard measures of sleep were obtained using polysomnography (PSG; Embletta MPRPG, ST + Proxy and TX Proxy) in the home environment, overnight. Epoch by epoch comparisons of the Sadeh (two algorithms), Cole-Kripke (three algorithms), Tudor-Locke (four algorithms), Count-Scaled (CS), and HDCZA algorithms were undertaken. Mean differences from PSG values were calculated for various sleep outcomes.

RESULTS

Overall, sensitivities were high (mean ± SD: 91.8%, ± 5.6%) and specificities moderate (63.8% ± 13.8%), with the HDCZA algorithm performing the best overall in terms of specificity (87.5% ± 1.3%) and accuracy (86.4% ± 0.9%). Sleep outcome measures were more accurately measured by devices worn at the wrist than the hip, thigh or lower back, with the exception of sleep efficiency where the reverse was true. The CS algorithm provided consistently accurate measures of sleep onset: the mean (95%CI) difference at the wrist with Axivity was 2 min (-6; -14,) and the offset was 10 min (5, -19). Several algorithms provided accurate measures of sleep quantity at the wrist, showing differences with PSG of just 1-18 min a night for sleep period time and 5-22 min for total sleep time. Accuracy was generally higher for sleep efficiency than for frequency of night wakings or wake after sleep onset. The CS algorithm was more accurate at assessing sleep period time, with narrower 95% limits of agreement compared to the HDCZA (CS:-165 to 172 min; HDCZA: -212 to 250 min).

CONCLUSION

Although the performance of existing count-based sleep algorithms varies markedly, wrist-worn devices provide more accurate measures of most sleep measures compared to other sites. Overall, the HDZCA algorithm showed the greatest accuracy, although the most appropriate algorithm depends on the sleep measure of focus.

Bioelectrical impedance as a measure of change in body composition in young children

BACKGROUND AND OBJECTIVES

The ability of bioelectrical impedance (BIA) to measure change in body composition in children has rarely been examined.

METHODS

Body composition was estimated by BIA (Tanita BC-418) and dual-energy x-ray absorptiometry (DXA) in 187 children aged 4-8 years at baseline and at 12 months. Change in body composition was compared between the two methods using mixed models.

RESULTS

Estimates of change in fat mass did not differ between BIA and DXA for overweight girls (mean difference between methods, 95% confidence interval: 0.04 kg, -0.19 to 0.28) or boys (0.07 kg, -0.14 to 0.27). BIA was also able to accurately detect change in fat-free mass, with no significant differences between methods (-0.14 kg, -0.10 to 0.38 in girls and -0.07 kg, -0.35 to -0.20 in boys). Change in percentage fat produced similar estimates in both genders (0.18%, -0.82 to 0.46 in girls and 0.38%, -0.37 to 1.13 in boys). BIA/DXA comparisons in normal weight children were also not significantly different, with the exception of percentage fat in girls, where BIA slightly underestimated change compared with DXA (0.7%, 0.02-0.37).

CONCLUSION

BIA performed well as a measure of change in body composition, providing confidence for its use as an outcome measure in children.