Sleep bruxism and sleep respiratory disorders in children and adolescents: A systematic review

Effect of Screen Time and Sugar Consumption Reduction on Sleep Bruxism in Children: A Randomised Clinical Trial

OBJECTIVE

Sleep bruxism (SB) is associated with alterations in dopamine and serotonin, which are related to increased consumption of added sugar and overuse of screens. The aim of this study was to compare the effect of the interventions 'Food, Fun and Family' (FFF) and Counselling and Education (CE) on the frequency of SB in children.

METHODS

A randomised clinical trial was conducted. Forty-eight participants aged between 4 and 8 years, attending the paediatric clinics of Universidad CES (Colombia) and Hospital Elina de la Serna (Argentina) participated in the study. Subjects were randomised into the FFF (experimental) and CE (regular intervention) groups. The frequency of SB was reported with the Children's Sleep Habits Questionnaire (CSHQ), the consumption of added sugar from items with the HBSC-FFQ and the time of use of screens through a diary in baseline (before starting the intervention), at Week 6 and Week 12. Data were analysed with Kruskal-Wallis test followed by Dunn's post hoc, Mann-Whitney test, a linear mixed model and logistic ordinal regression analyses.

RESULTS

The FFF group had a more significant reduction in consumption of added sugar and screen time compared to the CE group (p < 0.05), especially from Week 6 to baseline. Regression analysis showed that reducing TV watching and consumption of added sugar were associated with a decrease in SB frequency, especially in the FFF group (OR < 1, p < 0.05), and the results were consistent across different study environments.

CONCLUSION

The FFF intervention was more effective in reducing the screen time and sugar consumption and thus decreased the frequency of SB, when compared with the CE intervention.

TRIAL REGISTRATION

ClinicalTrials.gov identifier: NCT05310162.

Prevalence and risks of sleep bruxism in children and adolescents presenting for orthodontic treatment

OBJECTIVES

This study determined the prevalence and risks of definite sleep bruxism (SB) among children and adolescents presenting for orthodontic treatment.

METHODS

This was a cross-sectional study of 7-16-year-old subjects pursuing orthodontic treatment for the first time. The presence or absence of SB was determined using an overnight mandibular movement monitoring inertial measurement sensor, worn by each participant for two consecutive nights. Data from the sensor were extrapolated, then processed and analyzed to automatically identify rhythmic masticatory muscle activity for SB assessment. SB risks were evaluated from previously validated questionnaires, clinical examinations, lateral cephalometric radiographs, and digital study models.

RESULTS

A total of 87 subjects with a mean age of 12.82 years ± 2.24 and body mass index of 21.45 ± 5.49 participated in the study. The prevalence of SB was 60.7%. Multiple linear regression analysis revealed that SB had statistically significant association with microarousals (events/h) (β=0.31, 95% Confidence Interval [CI] 0.25-0.36, P < .001) and maxillary 6-6 dimension (mm) (β = 0.08, 95% CI 0.02-0.13, P = .008). A second model excluding microarousals showed that SB had a statistically significant association with sleep efficiency (SE) percentage (β = -0.15, 95% CI -0.28 to -0.01, P = .026) and obstructive respiratory disturbance index (ORDI) (events/h) (β = 0.33, 95% CI 0.15-0.51, P < .001).

CONCLUSIONS AND IMPLICATIONS

In a growing orthodontic population, definite SB is very common. SB is related to microarousals, maxillary intermolar width, SE percentage, and ORDI.

Sleep bruxism (SB) may be not associated with obstructive sleep apnea (OSA): A comprehensive assessment employing a systematic review and meta-analysis

Associations between obstructive sleep apnea (OSA) and sleep bruxism (SB) are the subject of discussion but have not been confirmed definitively. Therefore, the objective of this meta-analysis was to examine the relationship between OSA and SB. This systematic review was conducted in accordance with PRISMA 2020 guidelines. PubMed, Embase and Web of Science were screened up to February 2024. The risk of bias was assessed with the Joanna Briggs Institute tool. 2260 records were identified, but only 14 studies were included. The odds of SB presence in OSA did not differ from the control group (OR: 1.23, 95 % CI: 0.47-3.20). The chance of SB compared to controls also did not differ in mild OSA (OR: 1.56, 95 % CI: 0.76-3.18), in moderate OSA (OR: 1.51, 95 % CI: 0.77-2.94) and in severe OSA (OR: 1.50, 95 % CI: 0.68-3.29). Additionally, the odds of SB were not increased in moderate OSA in comparison to mild OSA (OR: 1.14, 95 % CI: 0.63-2.94), in severe OSA compared to moderate OSA (OR: 1.31, 95 % CI: 0.61-2.79) or in severe OSA compared to mild OSA (OR = 1.42, 95 % CI: 0.69-2.93). The presence of SB in OSA did not differ between genders (OR: 2.14, 95 % CI: 0.65-7.05). The quality of the major studies included is low; therefore, the noted lack of correlation between OSA and SB may require further research. The relationship between OSA and SB seems to be multi-faceted. Presented results should not exempt clinicians from exact diagnosis of concomitant sleep conditions in OSA subjects.