INTRODUCTION: Adolescence is a time of rapid changes in sleep habits and rising prevalence of sleepiness. The importance of measuring sleep in this population is increasingly recognized. In adults, measurements of sleep by actigraphy correlate well with sleep data from EEG recordings. Since actigraphy is increasingly utilized in adolescent sleep studies, more information is needed about reliability in this age group. This analysis investigated which actigraphy data mode is optimal for data collection in adolescents and explored the level of agreement between actigraphy and polysomnography (PSG) in population subgroups. METHODS: 181 adolescents aged 12-16 years were concurrently monitored with PSG and wrist actigraphy (measured in 3 data modes: Time Above Threshold [TAT], Zero Crossing Mode [ZCM], and Proportional Integration Mode [PIM]) to measure total sleep time (TST). RESULTS: The sample was 50% male, 55% African American, 9% with sleep disordered breathing (SDB; apnea-hypopnea index > or = 5). Intraclass correlation coefficients (ICC) for TST between actigraphy and PSG were low to moderate and were highest for TAT (0.41) compared to ZCM (0.32) and PIM (0.34). Subgroup analyses revealed that ICCs were higher among those without SDB (0.55) than those with SDB (0.00), and for girls (0.66) compared with boys (0.31). CONCLUSIONS: Results suggest that actigraphy provides a reasonably good estimate of TST in adolescents without SDB. Recognition of the variation in sleep estimates among different data collection modes, among population subgroups, and across the age spectrum, may be of fundamental importance in the interpretation of actigraphy data for sleep duration estimation.
INTRODUCTION: Adolescence is a time of rapid changes in sleep habits and rising prevalence of sleepiness. The importance of measuring sleep in this population is increasingly recognized. In adults, measurements of sleep by actigraphy correlate well with sleep data from EEG recordings. Since actigraphy is increasingly utilized in adolescent sleep studies, more information is needed about reliability in this age group. This analysis investigated which actigraphy data mode is optimal for data collection in adolescents and explored the level of agreement between actigraphy and polysomnography (PSG) in population subgroups. METHODS: 181 adolescents aged 12-16 years were concurrently monitored with PSG and wrist actigraphy (measured in 3 data modes: Time Above Threshold [TAT], Zero Crossing Mode [ZCM], and Proportional Integration Mode [PIM]) to measure total sleep time (TST). RESULTS: The sample was 50% male, 55% African American, 9% with sleep disordered breathing (SDB; apnea-hypopnea index > or = 5). Intraclass correlation coefficients (ICC) for TST between actigraphy and PSG were low to moderate and were highest for TAT (0.41) compared to ZCM (0.32) and PIM (0.34). Subgroup analyses revealed that ICCs were higher among those without SDB (0.55) than those with SDB (0.00), and for girls (0.66) compared with boys (0.31). CONCLUSIONS: Results suggest that actigraphy provides a reasonably good estimate of TST in adolescents without SDB. Recognition of the variation in sleep estimates among different data collection modes, among population subgroups, and across the age spectrum, may be of fundamental importance in the interpretation of actigraphy data for sleep duration estimation.
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