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Volume 15 No. 03
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Accepted Papers





Scientific Investigations

Oral Health and Oral Health-Related Quality of Life in Children With Obstructive Sleep Apnea

Basma Tamasas, BDS, MS, PhD1,2; Travis Nelson, DDS, MSD, MPH3; Maida Chen, MD4,5
1Department of Oral Health Sciences, University of Washington, Seattle, Washington; 2Center for Child Health, Behavior and Development, Seattle Children's Research Institute, Seattle, Washington; 3Department of Pediatric Dentistry, School of Dentistry, University of Washington, Seattle, Washington; 4Department of Pediatrics, Division of Pulmonary and Sleep Medicine, University of Washington School of Medicine, Seattle, Washington; 5Pediatric Sleep Disorders Center, Seattle Children's Hospital, Seattle, Washington

ABSTRACT

Study Objectives:

This aim of this study was to evaluate oral health and oral health-related quality of life (OHRQoL) in children with obstructive sleep apnea (OSA).

Methods:

This cross-sectional study involved 31 children who had baseline polysomnography studies and in whom a diagnosis of OSA was made by a sleep physician. They were evaluated against 36 control patients who, based on parent responses to the Pediatric Sleep Questionnaire, were at very low risk for having sleep problems. The mean age of the cohort was 12.3 ± 2.7 years. The oral health status was examined clinically and recorded using caries and periodontal indices. OHRQoL was measured using the Child Oral Health Impact Profile (COHIP) questionnaires.

Results:

Children with OSA had significantly worsened oral health compared to control patients as evidenced by more caries (15.2 and 3.2, respectively; P < .001) and more periodontitis. Periodontitis severity was measured by the presence of bleeding on probing, (87% versus 30%, P < .001) and higher number of sites with abnormally deep periodontal probing depths (2.7 versus 0.3, P < .001). The COHIP scores were significantly higher among children with OSA compared to control patients, (29.7 versus 11.8, P < .001) consistent with poorer OHRQoL.

Conclusions:

This study suggests that in children OSA may have a significant association with poorer oral health when compared to control patients without sleep problems, and that their oral health status may have a negative effect on their quality of life. Increased awareness regarding the oral health effects of sleep-disordered breathing in the medical and dental community is needed.

Citation:

Tamasas B, Nelson T, Chen M. Health and oral health-related quality of life in children with obstructive sleep apnea. J Clin Sleep Med. 2019;15(3):445–452.


BRIEF SUMMARY

Current Knowledge/Study Rationale: Obstructive sleep apnea (OSA) is a known risk factor for poor oral health. Nevertheless, the oral health status of children with OSA is largely unknown.

Study Impact: Children with OSA have more caries, periodontal disease, and poorer oral health-related quality of life than children without reported sleep difficulties. To improve patient outcomes, medical providers should collaborate with dentists to evaluate, treat, and prevent oral diseases in children with OSA.

INTRODUCTION

Obstructive sleep apnea (OSA) is a disorder characterized by repeated episodes of partial or complete upper airway collapse during sleep, resulting in apnea (airflow cessation) or hypopnea (airflow reduction), leading to disruption of normal sleep architecture and gas exchange abnormalities.1 OSA has a prevalence of 1% to 5% in the pediatric population of the United States. It has a substantial effect on individuals, families, the health care system, and society.2 OSA is associated with increased risks of multiple comorbidities including cardiovascular and metabolic disorders, neurocognitive impairment, and behavior problems.3,4 Thus, early recognition and treatment of OSA are crucial for a child's development and overall health.

Oral health is an integral component of systemic health. The links between the two make this topic an imperative public health issue.5 Children with OSA typically present with adenotonsillar hypertrophy, malocclusion, and craniofacial abnormalities.6,7 This skeletal and soft-tissue presentation contributes to increased risk of mouth breathing and dry mouth. In turn, this predisposes the patient to caries and periodontal disease.8 Dry mouth is amplified by the use of continuous positive airway pressure (CPAP) machines for sleep apnea.9,10 Moreover, research indicates that intermittent hypoxia in OSA may lead to increased levels of cytokines and chemokines, thus mediating both local and systemic inflammatory responses.4 These responses are linked to various oral health complications including gingivitis and periodontitis.11

Poor oral health may affect quality of life (QoL) by interfering with a person's ability to eat, sleep, and function.12 It can also contribute to systemic illness, and may further exacerbate challenging and costly medical care. Moreover, although sedation can be used to minimize the stress and physical discomfort of children undergoing dental procedures, patients with OSA are at greater risk of experiencing adverse sedation events. This may complicate treatment planning, and may result in the need to provide dental care in the hospital setting.13 Therefore, the dental practitioner plays a vital role in the treatment and health maintenance of children with OSA.

Despite the evidence that conditions associated with OSA may predispose patients to oral disease, studies investigating the relationship between OSA and oral health in children are quite scarce and discordant. Baseline data on children with and without OSA are needed to promote interprofessional collaboration between physicians and dentists and improve the overall health of this population. The aim of the current study was to assess dental caries, periodontal disease, occlusion, and dental and soft-tissue features in children with OSA. Oral health-related quality of life (OHRQoL) of the study population was also evaluated. Our hypothesis was that children with OSA will have more identifiable dental problems as well as worsened OHRQoL.

METHODS

Study Population

This was a cross-sectional study approved by Seattle Children's Hospital and the University of Washington Institutional Review Board. A total of 31 consecutive children with OSA were recruited at the Sleep Disorders Center of Seattle Children's Hospital. The control patients were 36 consecutive children who have been seen at the Center for Pediatric Dentistry at the University of Washington for a routine checkup. Inclusion criteria for all participants were as follows: (1) age 8–17 years; (2) no acute illnesses; and (3) parent or legal guardian present and age 18 years or older. Inclusion criteria for children with OSA were as follows: (1) diagnosis by a sleep specialist of OSA confirmed by polysomnography (PSG); (2) score ≥ 8 on parent's report of Pediatric Sleep Questionnaire (PSQ); and (3) no previous CPAP use. Inclusion criteria for control children were as follows: (1) no previous diagnosis of OSA; and (2) minimal risk of OSA based on a score of zero on PSQ. We excluded (1) children with systemic conditions, neurologic disease or cognitive impairment compromising their ability to maintain good oral health including asthma and diabetes; (2) children who were on medications with side effects shown to affect the oral health, such as nifedipine and diltiazem; (3) children who received active orthodontic treatment within the past year; and (4) non-English speakers.

Sleep Study

All children in the OSA group underwent diagnostic PSG as part of clinical care. PSG was performed at an accredited pediatric-specific facility at the Seattle Children's Sleep Disorders Center. PSG was performed in a private darkened room free of distraction and lasted at least 6 hours. The following physiologic parameters were monitored: electroencephalogram, electro-oculogram, submental and anterior tibialis electromyograms, electrocardiogram, oronasal airflow measured by thermistor and pressure transducer, expired end-tidal and transcutaneous carbon dioxide and/or transcutaneous carbon dioxide monitoring, oxygen saturation via pulse oximeter, and thoracic and abdominal movement. All data were recorded into a computer-based acquisition and analysis program (XLTEK, Natus Oakville, Ontario, Canada or Rembrandt, Buffalo, New York, United States), scored by certified technicians, and interpreted by a board certified sleep medicine physician in accordance with American Academy of Sleep Medicine guidelines.14

Questionnaires

After caregiver consent and child assent was obtained, caregivers were asked to complete the validated PSQ on behalf of their child to determine the child's risk for OSA.15 This validated questionnaire consists of 22 items representing three distinct domains: snoring, daytime sleepiness, and related behavioral disturbances. An overall score ≥ 8 has 0.85 sensitivity and 0.87 specificity, positive predictive value of < 50% and negative predictive value of ∼100% for predicting OSA seen on sleep study, and has been used as a suggested cutoff score for identifying those at risk. The validated Child Oral Health Impact Profile (COHIP) was used to assess children's OHRQoL based on the answers given by parents or guardians and by children themselves.16 The COHIP measures how oral health affects daily activities such as speaking, eating, smiling, learning, and emotional/social well-being. It consists of 35 items forming five conceptually distinct domains: oral health, functional well-being, social/emotional well-being, school environment, and self-image. A subscore for each of the five COHIP domains and an overall total COHIP score were calculated. Higher scores reflect worsened OHRQoL. Patient demographics and lifestyle factors such as age, sex, parental education, and smoking were also gathered as part of the COHIP questionnaire.

Clinical Examination

Dental examination was conducted by one trained dentist, under natural light using sterile instruments including mouth mirror, explorer, and cotton pellets. Craniofacial features and dental occlusion were recorded. Soft palate morphology was classified according to the Mallampati classification.17 Tonsil size was classified according to the Brodsky score.18 The occlusion was assessed according to the modified method of Bjoerk et al. in the intercuspal position.19 The recorded variables for dental occlusion included: (1) molar occlusion (normal [class I], distal [class II] or mesial [class III]); (2) overjet (the amount that the top teeth sit forward of the lower teeth, normally ∼3 mm); (3) overbite (the overlap between the top teeth and bottom teeth, normally ∼30%); and (4) crowding (dental misalignment caused by inadequate space for the teeth). The diagnosis of dental caries was based on the detection of carious lesions at the cavitation stage, as recommended by the World Health Organization (WHO).20 The most commonly used index of caries experience was used, the DMFS (Decayed, Missing, and Filled Surfaces) for permanent teeth and dmfs (decayed, missing, and filled surfaces) for primary teeth. The individuals' periodontal health was assessed according to the WHO recommendation. A periodontal examination was performed using four sites on Ramfjord index teeth (teeth numbers: 3, 9/F, 12/I, 19, 25/P, 28/S).21 Two periodontal indices were measured to assess periodontal status: (1) bleeding on probing (BOP) recorded after placing a periodontal probe to the depth of selected periodontal pockets; and (2) probing depth (PD), measured as the distance between the gingival margin and the bottom end of the periodontal pocket. The absence of BOP serves as a predictor of periodontal stability. PD served as the main indicator of periodontal inflammation. For PD the following classification for periodontitis was used: PD 0–3 mm, no/mild periodontitis; ≥ 4 mm to < 6 mm, moderate periodontitis; and ≥ 6 mm, severe periodontitis. For quality control, 10% of the examinations were repeated randomly, and examiner agreement was consistent during the study.

Statistical Analysis

Six different outcomes were used to compare the oral health status between children with OSA and the control group: DMFT, dmft, PD, BOP, and COHIP parent, and COHIP child. The unadjusted difference between the means for the continuous outcomes was calculated with a t test allowing for unequal variances. The unadjusted odds ratio for the categorical outcome was calculated with a Fisher exact test. For all six outcomes, a regression analysis was used to adjust for confounders: age, smoking, sex, ethnicity, education, income, insurance, obesity, Mallampati classification, Brodsky score, overjet, and overbite. Statistical analyses were conducted using SPSS, version 18.0 (IBM, Armonk, New York, United States). A value of P < .05 was considered to be statistically significant.

RESULTS

A total of 67 participants were enrolled. Mean age was 12.3 ± 2.7 years, and males constituted 54% of the sample. There were no significant differences between the OSA group and the control group for any of the demographic or lifestyle characteristics. There were, however, significantly higher body mass index (BMI) percentiles in children with OSA when compared with the control patients. Just under half of the children with OSA were overweight or had obesity compared to only 6% in the control group (Table 1, P < .001).

Characteristics of the study population.

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Table 1

Characteristics of the study population.

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The PSQ has three prominent symptom-complexes: snoring, excessive daytime sleepiness, and behavior manifestations. Based on the PSQ data, more than 90% of the children with OSA were reported by their parents to be snorers, have daytime symptoms including morning dry mouth, and experience behavior problems. Differences between participants with OSA and control participants for each sleep parameter were statistically significant (Table 2).

Sleep parameters extracted from the sleep questionnaires.

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Table 2

Sleep parameters extracted from the sleep questionnaires.

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Table 3 presents the dentofacial and pharyngeal morphology detected during the clinical examination. Mallampati and Brodsky scores were significantly higher in children with OSA compared to the control group (P < .001). Dental crowding was clinically observed in 71% of children with OSA compared to 22% in the control group (P < .01). Children with OSA were noted to have a tendency toward class II occlusion (48% versus 28% in the control group, P < .001).

Dentofacial and pharyngeal morphology characteristics of the study population.

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Table 3

Dentofacial and pharyngeal morphology characteristics of the study population.

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The mean caries score of the primary dentition (dmfs) was somewhat higher in the OSA group but did not reach statistical significance (5.1 ± 8.5; 2.9 ± 5.0, P = .19). However, mean caries score of the permanent dentition (DMFS) was significantly higher among children with OSA compared to the control group (15.2 ± 11.8; 3.2 ± 5.2, P < .001). Looking at each component of the DMFS index (Decayed versus Missing versus Filled Surfaces), only the Decayed score was significantly higher among children with OSA compared to the control group (11.7 ± 10.0; 1.8 ± 3.1, P < .001). In other words, the incidence of untreated decay was higher in the patients with OSA than in the control group (Table 4).

Caries and periodontal indices in the primary and permanent teeth by OSA status.

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Table 4

Caries and periodontal indices in the primary and permanent teeth by OSA status.

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We used clinical markers: periodontal pocket depth (PD) in combination with BOP as severity markers for periodontitis (Table 4). Overall, about 87% of the patients with OSA showed BOP compared to 30% in the control group (P < .01). The mean PD in the OSA group was significantly higher compared to the control group (2.7 ± 1.3; 0.3 ± 0.7, P < .001). However, no participants in either the OSA or control groups had moderate or severe periodontitis, with all participants fitting into an absent or mild periodontitis category.

Overall QoL and its domains were significantly different between case participants and control participants, except for the effect of oral health on school performance. Paired parent-child reports of OHRQoL were congruent, with no differences in scores by reporters (Table 5).

Comparison of overall and subscale COHIP scores for OSA versus control group.

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Table 5

Comparison of overall and subscale COHIP scores for OSA versus control group.

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Regression models were performed with COHIP, DMFS, dmfs, BOP, and PD as dependent variables and demographic and lifestyle measures as well as orofacial characteristics as predictor variables (Table 6). There was a significant association between OSA and all the oral health outcomes measured in the study (COHIP, DMFS, dmfs, BOP, and PD). Interestingly, of all the physical characteristic measured in this population including obesity and dentofacial and pharyngeal morphology, only Brodsky scores of II or higher was significantly and positively associated with all the oral health outcomes.

Association between each oral health-related measurement and OSA after adjusting for confounders.

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Table 6

Association between each oral health-related measurement and OSA after adjusting for confounders.

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DISCUSSION

In this study we examined oral health, and the effect of oral health on QoL among children with OSA in comparison with children who are at low risk of OSA. We found that children with OSA had significantly more caries and greater BOP and PD measures than healthy control participants. Patients with OSA were in a significantly greater BMI percentile and had more oral soft-tissue obstruction, dental crowding, and orthodontic class II occlusions. Overall OHRQoL was reported to be significantly lower for children with OSA.

Oral diseases (dental caries and periodontal disease) are a major public health concern because of their prevalence, the cost of their treatment, and their effect on individuals, families, and societies.22 Given the prevalence of childhood OSA and the associated comorbidities, poor oral health can be a great burden in this population.

Permanent teeth caries index (DMFS) was higher in children with OSA compared with the control group, whereas no difference was found in the primary teeth caries index (dmfs). One explanation for not detecting any difference in the primary teeth caries index could be that most of the children in our study were aged 12–14 years (an age where children generally have only permanent teeth). Also, the mean age of the study group represents the start of the adolescent period when frequent eating, intake of sugar-sweetened beverages, and less parental supervision are more common. Therefore, patients in this age range have a higher risk of developing dental caries.

We also found that periodontal health indices (PD, BOP) were significantly higher among children with OSA compared to the control group. A significant association between OSA and periodontal disease has previously been reported in the adult population.2325 Recognizing the risk factors for periodontal disease in patients with OSA, we recently investigated the oral health status of children who are at higher risk of sleep-disordered breathing (SDB), as defined by those above cutoff scores on the PSQ. Children at risk for OSA had more dental caries, periodontal disease, and poorer OHRQoL than unaffected peers.26 Interestingly, the oral health parameters of children with PSG-proven OSA were very similar to what we reported in children at high risk of OSA (based on PSQ). This highlights the benefit of using the PSQ as a noninvasive and practical tool for early detection of OSA. Although these findings suggest that children with OSA are at increased risk for poor periodontal health, this is not conclusive.

On the contrary, one study investigated oral health status in Saudi children (3–8 years old) and reported fewer dental caries and less gingival inflammation in children with OSA.27 However, the authors failed to report the criteria for the OSA diagnosis in their study. They only stated that a pediatric otorhinolaryngologist diagnosed the patients with OSA and snoring in their study. Also, they did not take into account demographic or orofacial characteristics that may influence the oral health of their study population.

Although the exact mechanisms that mediate the poor oral health in children with OSA are not yet known, one can speculate that the findings observed in our study may be related to mouth breathing and dry mouth reported by approximately 95% of the children with OSA. Dry mouth can lead to several oral and dental complications including disturbances in salivary function, reduced salivary clearance, increased plaque formation, and bacterial colonization. These factors predispose the patient to a higher prevalence of dental caries, gingival inflammation, and periodontitis.2830 In addition, emotional distress as a result of the sleepiness and subsequent reduction in daily comfort could lead to unbalanced salivary function and lower resistance to dental caries.31

Previous studies have proposed that both the upper airway and systemic inflammation are involved in the pathophysiology of OSA.32,33 It has been demonstrated that OSA leads to altered expression of varieties of inflammatory markers, making patients with OSA more prone to inflammation. Both gingivitis and periodontitis are inflammatory diseases caused by pathogenic bacteria that trigger an inflammatory response. Disease progression for both conditions is a result of inadequate or excessive host response.11 Therefore, it comes as no surprise that research has discovered a significant increase in the prevalence of periodontitis among adult patients with OSA. Thus, another mechanism that may explain the poor oral health in children with OSA could be the increase in local and systemic inflammatory response reported in OSA.

QoL is a key health metric in clinical medicine and has become a focus of clinical care goals. Likewise, the effect of oral diseases and disorders on everyday life, OHRQoL, must be considered to provide optimal dental care. Previous studies have shown that childhood OSA is associated with poor QoL and that adenotonsillectomy significantly improves QoL in children with OSA.34 Recently, our group reported that children at high risk of SDB have significantly poorer OHRQoL than children at lower risk of SDB.26 As far as we are aware, no studies have been conducted to evaluate OHRQoL in pediatric patients with OSA. We believe the current study is the first to report the association between OSA and poor child- and caregiver-rated OHRQoL. OHRQoL can be influenced by several factors, including dental caries and gingivitis. These conditions are known to be associated with esthetic and functional impairments that may negatively affect OHRQoL.3537 Our finding of a significant association between OSA and increased dental caries and periodontal disease indices supports this observation.

In our study children with OSA were more likely to present with higher Brodsky and Mallampati scores, be overweight or have obesity, and show a tendency toward class II malocclusion. Adenotonsillar hypertrophy is the most common etiology of childhood OSA.38 Obesity and alteration of the craniofacial structures (micrognathia, malocclusion) are also associated with higher risk of OSA.7 Despite several studies supporting an association between weight gain or obesity and caries, the literature is inconclusive.39,40 This could be mainly because both conditions are multifactorial, and an association may be caused by sugar intake and lifestyle issues rather than a causal relation. Nevertheless, our study regression analysis indicated that BMI percentile was not a predictor of any of the oral health outcomes investigated in the study (Table 6). Although we found that children with OSA had physical features that differed from healthy peers, only higher Brodsky score was predictive of the oral health outcomes. The exact mechanism linking tonsillar hypertrophy to poor oral health is yet to be investigated, Nevertheless, Brodsky score is highly correlated with OSA and is simple to assess during oral examination, so this finding may be a particularly important one for clinicians to take into account.

There are limitations to this study. It is a cross-sectional study and thus provides information only on associations among the study variables, and causality cannot be determined. In our study, we lack information on dental care utilization, the use of preventive dental care (such as toothpaste and fluoride), and dietary habits. This information could significantly contribute to the interpretation of future studies. Our cohort was small, recruited from local sleep center and university based dental clinic, and we only recruited healthy children, which may affect the generalization of our results. Furthermore, some of the information in our study was collected by self-reported questionnaires, the answers to which may be subject to recall bias. Although the PSQ is well validated as a predictor of OSA on PSG, our control group did not undergo PSG, which would have been quite costly. We mitigated this by enrolling participants with the lowest possible score on the PSQ to capture those at lowest reported risk. Given that the PSQ has a positive predictive value of approximately 100%, the chances of the children in the control group having OSA are almost nonexistent with a PSQ score of 0. Overall, despite the exploratory nature of our study, we believe that its results add useful information to the sparse knowledge on oral health and pediatric OSA, and they may motivate and indicate further studies in this field.

In conclusion, this study suggests that children with OSA may have a significant association with poorer oral health than control participants, and that their oral health status may have a negative effect on their quality of life. Pediatric medical and dental providers should take this into account during clinical encounters, focusing on oral findings, which may contribute to OSA. To improve overall health and QoL, patients at high risk for SDB should receive multidisciplinary care to address factors that contribute to OSA. Future research is needed to investigate the mechanisms underlying this relationship, and to examine whether appropriate treatment of OSA improves the oral health measures in children.

DISCLOSURE STATEMENT

All authors have seen and approved the manuscript. This study was funded by the Safeway Research Fund. All work related to this study was performed at the Pediatric Sleep Disorders Center, Seattle Children's Hospital, and the Department of Pediatric Dentistry, School of Dentistry, University of Washington, Seattle, WA. The authors report no conflicts of interest.

ABBREVIATIONS

BMI

body mass index

BOP

bleeding on probing

COHIP

Child Oral Health Impact Profile

DMFS

Decayed, Missed, Filled Surfaces of permanent teeth

dmfs

decayed, missed, filled surfaces of primary teeth

OHRQoL

oral health-related quality of life

OSA

obstructive sleep apnea

PD

probing depth

PSG

polysomnography

PSQ

Pediatric Sleep Questionnaire

QoL

quality of life

SDB

sleep-disordered breathing

WHO

World Health Organization

ACKNOWLEDGMENTS

The authors are grateful to Drs. Garret Godferry, Michael L. Cunningham, Sue Herring, Kelly Evans and Hitesh Kapadia for valuable support and advice throughout this study. Many thanks to all the study participants who made this study possible.

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