TY - JOUR
T1 - A network analysis of self-reported sleep bruxism in the Netherlands sleep registry
T2 - its associations with insomnia and several demographic, psychological, and life-style factors
AU - Chattrattrai, Thiprawee
AU - Blanken, Tessa F.
AU - Lobbezoo, Frank
AU - Su, Naichuan
AU - Aarab, Ghizlane
AU - van Someren, Eus J. W.
N1 - Funding Information: TC has been supported by a Mahidol University's Academic Development Scholarship . Funding Information: This work was in part facilitated by funding from ZonMw Open Competition, project 09120011910032. TB has been supported by a Vrije Universiteit Amsterdam University Research Fellowship and a 284/20 BIAL Foundation Grant. Publisher Copyright: © 2022 The Author(s)
PY - 2022/5/1
Y1 - 2022/5/1
N2 - Objectives: To investigate the association between self-reported sleep bruxism and insomnia and their potential risk factors (eg, depression and anxiety), and to construct a network model with all these factors. Methods: We recruited 2251 participants from the Netherlands Sleep Registry. All participants completed questionnaires on self-reported sleep bruxism, insomnia, depression, anxiety, smoking frequency, and alcohol and caffeine consumption. The associations between self-reported sleep bruxism and other variables were analyzed by univariate analysis, multivariate logistic regression, and network analysis. Results: Although univariate analysis showed that there was a positive association between sleep bruxism and insomnia (P < 0.001), this association disappeared in the multivariate logistic regression model (P = 0.258). However, multivariate logistic regression did show an association between self-reported sleep bruxism and anxiety (OR = 1.087, 95% CI 1.041–1.134). The network model showed that there was no direct link between self-reported sleep bruxism and insomnia. However, there was an indirect link between self-reported sleep bruxism and insomnia via anxiety. Conclusions: Although self-reported sleep bruxism has no direct association with insomnia, anxiety is a bridging factor between these variables.
AB - Objectives: To investigate the association between self-reported sleep bruxism and insomnia and their potential risk factors (eg, depression and anxiety), and to construct a network model with all these factors. Methods: We recruited 2251 participants from the Netherlands Sleep Registry. All participants completed questionnaires on self-reported sleep bruxism, insomnia, depression, anxiety, smoking frequency, and alcohol and caffeine consumption. The associations between self-reported sleep bruxism and other variables were analyzed by univariate analysis, multivariate logistic regression, and network analysis. Results: Although univariate analysis showed that there was a positive association between sleep bruxism and insomnia (P < 0.001), this association disappeared in the multivariate logistic regression model (P = 0.258). However, multivariate logistic regression did show an association between self-reported sleep bruxism and anxiety (OR = 1.087, 95% CI 1.041–1.134). The network model showed that there was no direct link between self-reported sleep bruxism and insomnia. However, there was an indirect link between self-reported sleep bruxism and insomnia via anxiety. Conclusions: Although self-reported sleep bruxism has no direct association with insomnia, anxiety is a bridging factor between these variables.
KW - Anxiety
KW - Insomnia
KW - Network analysis
KW - Sleep bruxism
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UR - https://pure.uva.nl/ws/files/100424513/1_s2.0_S1389945722000946_mmc2.docx
U2 - https://doi.org/10.1016/j.sleep.2022.03.018
DO - https://doi.org/10.1016/j.sleep.2022.03.018
M3 - Article
C2 - 35429746
SN - 1389-9457
VL - 93
SP - 63
EP - 70
JO - Sleep Medicine
JF - Sleep Medicine
ER -