Association between Loss of Sleep-specific Waves and Age, Sleep Efficiency, Body Mass Index, and Apnea-Hypopnea Index in Human N3 Sleep
Weiguang Li1, Ying Duan2, Jiaqing Yan3, He Gao2,*, Xiaoli Li1,*
1State Key Laboratory of Cognitive Neuroscience and Learning & IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing 100875, China 2Clinical Sleep Medical Center, Air Force Medical Center, PLA, Beijing 100036, China 3College of Electrical and Control Engineering, North China University of Technology, Beijing 100144, China.
Sleep spindles (SS) and K-complexes (KC) play important roles in human sleep. It has been reported that age, body mass index (BMI), and apnea-hypopnea index (AHI) may influence the number of SS or KC in non-rapid-eye-movement (NREM) 2 (N2) sleep. In this study, we investigated whether the loss of SS or KC is associated with the above factors in NREM 3 (N3) sleep. A total of 152 cases were enrolled from 2013 to 2017. The correlations between the number of SS or KC in N3 sleep and participants’ characteristics were analyzed using Spearman rank correlation. Chi-squared test was used to assess the effects of age, sleep efficiency, and BMI on the loss of N3 sleep, N3 spindle and N3 KC. Our results showed that there were negative correlations between the number of SS in N3 sleep with age, BMI, and AHI (P < 0.001), and similar trends were found for KC as well. The loss of SS and KC in N3 sleep was related with age, BMI, and AHI (P < 0.01), as was the loss of N3 sleep (P < 0.01). However, sleep efficiency was not related with the loss of N3 sleep, SS and KC in N3 sleep (P > 0.05). The present study supports that age, BMI, and AHI are all influencing factors of SS and KC loss in human N3 sleep, but sleep efficiency was not an influencing factor in the loss of N3 sleep and the loss of SS and KC in N3 sleep.
Weiguang Li,Ying Duan,Jiaqing Yan, et al. Association between Loss of Sleep-specific Waves and Age, Sleep Efficiency, Body Mass Index, and Apnea-Hypopnea Index in Human N3 Sleep[J]. Aging and disease,
2020, 11(1): 73-81.
Table 1 The characteristics and polysomnographic variables of 152 participants.
Figure 1. Schematic diagram of human sleep. (A) No N3 sleep. (B) Little N3 sleep. (C) Normal N3 sleep.
Figure 2. Correlation between N3 sleep and participants’ characteristics. There was a negative correlation between N3 sleep and participants’ age (A; P < 0.001), BMI (C; P < 0.001), and AHI (D; P < 0.001). Sleep efficiency had no correlation with N3 sleep (B; P > 0.05).
Figure 3. Correlation between the number of SS in N3 sleep and participants’ characteristics. There was a negative correlation between the number of SS and participants’ age (A; P < 0.001), BMI (C; P < 0.001), and AHI (D; P < 0.001). Sleep efficiency had little positive correlation with the number of SS in N3 sleep (B; P = 0.013).
Sleep Efficiency (%)
Sleep Efficiency (%)
Table 2 The correlations among the characteristics of participants (n = 152).
Figure 4. Correlation between the number of KC in N3 sleep and participants’ characteristics. There was a negative correlation between the number of KC and participants’ age (A; P < 0.001), BMI (C; P < 0.001), and AHI (D; P < 0.001). Sleep efficiency had no correlation with the number of KC in N3 sleep (B; P > 0.05).
Table 3 Influencing factor of N3 sleep loss, SS and KC loss in N3 sleep.
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