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Original Research: SLEEP MEDICINE |

Prevalence and Risk Factors of Habitual Snoring in Primary School Children FREE TO VIEW

Albert M. Li, MD; Chun T. Au, MPhil; Hung K. So, PhD; Joseph Lau, PhD; Pak C. Ng, MD; Yun K. Wing, MBChB
Author and Funding Information

from the Department of Pediatrics (Drs Li, Au, So, and Ng), Centre for Epidemiology and Biostatistics (Dr Lau), and Department of Psychiatry (Dr Wing), Prince of Wales and Shatin Hospital, The Chinese University of Hong Kong, Shatin, Hong Kong.

Correspondence to: Albert M. Li, MD, Department of Pediatrics, Prince of Wales Hospital, The Chinese University of Hong Kong, Shatin, Hong Kong; e-mail: albertmli@cuhk.edu.hk


For editorial comment see page 469

Funding/Support: This study was supported by the Research Grants Council of the Hong Kong Special Administrative Region, China [Grant CUHK4161/02M].

Reproduction of this article is prohibited without written permission from the American College of Chest Physicians (http://www.chestpubs.org/site/misc/reprints.xhtml).


© 2010 American College of Chest Physicians


Chest. 2010;138(3):519-527. doi:10.1378/chest.09-1926
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Objective:  Our study aimed to determine the prevalence of habitual snoring (HS) in primary school children and to evaluate the diurnal symptoms and conditions that may be associated with it.

Methods:  A validated questionnaire completed by parents was used to assess the sleep and daytime behaviors of Chinese children aged 5 to 14 years. Thirteen primary schools in two representative districts were randomly selected.

Results:  A total of 6,349 out of 9,172 questionnaires (response rate 69.2%) with complete answers were returned. The prevalence rate of HS was 7.2%. Male sex (odds ratio [OR] [95% CI]: 2.5 [1.7-3.6]), BMI z score (OR [95% CI]: 1.4 [1.1-1.6]), maternal HS (OR [95% CI]: 3.4 [2.0-5.7]), paternal HS (OR [95% CI]: 3.8 [2.7-5.5]), allergic rhinitis (OR [95% CI]: 2.9 [2.0-4.2]), asthma (OR [95% CI]: 2.4 [1.2-5.2]), nasosinusitis (OR [95% CI]: 4.0 [1.5-10.6]), and tonsillitis (OR [95% CI]: 3.1 [1.9-5.1]) in the past 12 months were identified to be independent risk factors associated with HS. HS was also associated with daytime, nocturnal, parasomniac, and sleep-related breathing symptoms. HS was demonstrated to be an independent risk factor for parent-reported poor temper (OR [95% CI]: 1.9 [1.4-2.5]), hyperactivity (OR [95%CI]: 1.7 [1.2-2.5]), and poor school performance (OR [95% CI]: 1.7 [1.2-2.5]).

Conclusions:  HS was a significant and prevalent problem in primary school children. Male sex, obesity, parental HS, atopic symptoms, and history of upper respiratory infections were significant risk factors. HS was also associated with sleep-disordered breathing symptoms and adverse neurobehavioral outcomes.

Figures in this Article

Snoring is the most important and common manifestation related to obstructive sleep apnea (OSA) and may cause hypoxemia and hypercapnia because of partial obstruction of the upper airway during sleep.1 In adults, habitual snoring (HS) is associated with hypertension,2 cardiovascular/cerebrovascular disease,3,4 and daytime sleepiness.5 Our research group has previously demonstrated higher BP in children with HS compared with healthy controls.6 Recent studies have also documented impaired neuropsychologic functioning in children with a history of snoring7,8 Thus, the clinical importance of HS as a potential marker of morbidity and even mortality is increasingly being recognized.

The prevalence of HS has been reported to vary between 2.4% and 34.5% in children.9 Such a wide range may be attributed to the discrepancy in the definition of HS, different age groups, and methods of sampling. Most studies examining the prevalence of HS and associated risk factors have been carried out in populations from Western countries.9 A telephone survey that was carried out locally reported an HS prevalence of 10.9%. However, the study had a response rate of only 50%, such that sampling bias might exist.10 A variety of parameters have also been reported to be associated with HS. Some studies suggested a positive relationship between HS and male sex,10-15 overweight,14-18 exposure to tobacco smoke,11,12,18-22 and low socioeconomic status,16 whereas others have not been able to confirm these findings.23-25

Using a large population-based sample, we aimed to determine the prevalence of HS and its association with clinical features, environmental and socioeconomic factors, neurobehavioral outcomes, and other sleep-related symptoms in primary school Chinese children.

Study Population

As part of our childhood OSA epidemiology study, we have chosen two representative primary school districts for subject recruitment. Because the income distribution of the two districts is similar to the whole of Hong Kong, results obtained from this study should be a good representation of the territory. Thirteen primary schools from the two districts were randomly chosen to participate in this study. The study population consisted of children aged 5 to 14 years. Approval by the ethics committee of the Chinese University of Hong Kong was obtained.

Questionnaire

A questionnaire based on parental report was used (Hong Kong Children Sleep Questionnaire26). Parents were invited to attend an education forum in each participating school during which full explanation of the purpose of the study was given by the investigators. An envelope containing the questionnaire to be filled out by parents and a personally addressed letter asking for consent was then distributed to children at the chosen schools with the help of their teachers within a week after the forum. The parents were asked to return the completed questionnaire within a week. For those who failed to return the questionnaire within the defined period, another copy was given with a self-addressed envelope enclosed for ease of return.

The following information from the questionnaire was extracted for analysis: (1) demographics and body size: age, sex, weight, and height. The z score for BMI was calculated from local normal reference27; (2) clinical features: atopic symptoms, upper respiratory tract infection (URTI) in the past 12 months, and parental history of HS; (3) environmental factors: household smoking, household furry pets, breast-feeding (≥ 6 months), number of siblings, and sleep environment (sleep in own room, cosleeping); (4) socioeconomic factors: family income, overcrowding (living space per person < 5.5 m2), parental education, and single parenthood; (5) neurobehavioral outcomes: poor temper, hyperactivity, and poor school performance; (6) sleep duration during weekdays, weekends, and vacations; and (7) snoring frequency and 23 sleep-related symptoms rated on a five-point rating scale (0-4): 0 = never; 1 = rarely, for zero to one night per month; 2 = sometimes, for one to two nights per month; 3 = often, for one to two nights per week; 4 = frequently, for three nights or more per week. Factor analysis categorized the 23 items into six factors, namely daytime symptoms, nocturnal symptoms, parasomnia, insomnia, sleep-related movement, and sleep-related breathing (Table 1). The total variance explained by this six-factor model was 50.3%. Factor scores were calculated using regression method. The subjects were divided into three groups for comparisons: (1) nonsnorers, those reporting “never” in the questionnaire; (2) occasional snorers, those reporting “rarely” to “often,” and (3) habitual snorer, those reporting “frequently.”

Table Graphic Jump Location
Table 1 —Summary of Items and Factor Loadings of the Six Factors
Data Analysis

Data were presented as mean ± SD, median (interquartile range), and percentages, for parametric, nonparametric, and categorical data, respectively. Parametric and nonparametric variables were compared using one-way analysis of variance and Kruskal-Wallis tests. Post hoc tests (Tukey or Games-Howell method) were carried out for pairwise comparisons. Categorical variables were compared using χ2 tests. The significance level for pairwise comparisons were adjusted to P < .016. The 95% CIs of prevalence of HS were calculated using the modified Wald method suggested by Agresti and Coull.28

Multivariate logistic regression analyses were subsequently performed to further confirm the association between potential risk factors and HS. All the analyses compared habitual snorers with nonsnorers. The association was assessed in two logistic regression models: (1) adjusted for age, sex, and BMI z score only; (2) further adjusted for clinical features, and environmental and socioeconomic factors simultaneously. Independent variables with a P value of < .1 in model 1 were included in model 2. Multivariate logistic regression analyses were also used to assess the association between snoring and neurobehavioral outcomes while adjusting for possible confounders. All analyses were performed using SPSS version 15.0.

Subject Characteristics

Of 9,172 children enrolled, 6,471 questionnaires were returned giving a response rate of 70.6%. One hundred twenty-two questionnaires were excluded from analysis because of missing snoring information, making a final response rate of 69.2%. The characteristics of the remaining 6,349 children are shown in Table 2.

Table Graphic Jump Location
Table 2 —Subject Characteristics by Sex

AR = allergic rhinitis; household crowding = living space per person < 5.5 m2; HS - habitual snoring; poverty = family income per person < HK$2,500; poor parental education = full-time education up to primary level; URTI = upper respiratory tract infection.

Prevalence of HS

Overall, there were 454 habitual snorers (7.2%), 2,780 occasional snorers (43.8%), and 3,115 nonsnorers (49.1%). Figure 1 showed the prevalence of HS by age and sex. HS was significantly more prevalent in boys than in girls among subjects from age 7 to 11 years. The prevalence of HS was highest in 7-year-old boys and 6-year-old girls.

Figure Jump LinkFigure 1. Prevalence of habitual snoring (HS) by age and sex. *Significant difference between boys and girls (P < .05).Grahic Jump Location
Risk Factors of HS

The possible risk factors of HS were compared among different groups and the results were tabulated in Table 3. A number of variables were demonstrated to have a dose-response relationship with snoring frequency. Body size increased, whereas age decreased across groups. The proportions of male sex, parental snoring, atopic symptoms and upper respiratory tract infection in the past 12 months, and single child increased across groups, whereas the proportions of breast-feeding for ≥ 6 months, having two or more siblings, poverty (family income per person < HK$2500), poor parental education (full-time education up to primary level), and overcrowding (living space per person < 5.5 m2) decreased across groups.

Table Graphic Jump Location
Table 3 —Characteristics of Subjects According to Snoring Status

See Table 2 for explanation of terms and expansion of abbreviations.

Table 4 shows the results of logistic regression analyses identifying risk factors for HS. With reference to the nonsnoring group, male sex, BMI z score, parental HS, and history of allergic rhinitis (AR) symptoms, wheezing, nasosinusitis, and tonsillitis in the past 12 months were significantly associated with HS in the fully adjusted model. Children who slept in their own room were demonstrated to be less likely to have HS.

Table Graphic Jump Location
Table 4 —Risk Factors Associated With HS With Reference to Nonsnorers

OR = odds ratio. See Table 2 for explanation of terms and expansion of other abbreviations.

a 

Adjusted for age, sex, and BMI z score.

b 

Adjusted for all factors with a P < .1 in model 1 simultaneously.

Sleep-Related Symptoms Associated With HS

The HS group had significantly higher factor scores of daytime symptoms, nocturnal symptoms, parasomnia, and sleep-related breathing than the nonsnorer group. On the other hand, no significant differences could be found in the factor scores of insomnia and sleep-related movements between the two groups (Table 5).

Table Graphic Jump Location
Table 5 —Comparison of the Factor Scores of Sleep-Related Symptoms, Sleep Duration, and Neurobehavioral Outcomes Between Groups
a 

Significantly different from nonsnoring controls.

Neurobehavioral Outcomes of HS

The habitual snorer group had a greater proportion of subjects having poor temper, hyperactivity, and poor school performance compared with nonsnorers (Table 5). Multivariate logistic regression analysis demonstrated that HS was significantly associated with a higher risk for all these neurobehavioral outcomes with reference to nonsnoring after adjusting for all possible confounders, whereas occasional snoring was not (Table 6).

Table Graphic Jump Location
Table 6 —Associations Between Snoring and Neurobehavioral Outcomes

P value adjusted for age, sex, BMI z score, atopic symptoms, URTI, environmental factors, and socioeconomic factors. See Tables 2 and 4 for expansion of abbreviations.

There was a significant decreasing trend in sleep duration from nonsnorers, to occasional snorers, and then to habitual snorers (Table 5). However, after adjusting for age, sex, BMI z score, atopic symptoms, and socioeconomic factors, neither HS nor occasional snoring was significantly associated with sleep duration.

To our knowledge, this is one of the largest epidemiologic research studies carried out in this region to examine for the prevalence of HS among 5- to 14-year-old primary school children. We found the prevalence of HS in this age group to be 7.2%, which is less compared with figures from Australia,15,19 South America,22,25 and the United States21,29 involving a similar age group, reported to range from 10.5% to 27.6% (Table 7).

Table Graphic Jump Location
Table 7 —Prevalence and Risk Factors of HS in Different Countries

NA = not applicable. See Table 2 for expansion of other abbreviation.

On the other hand, our prevalence rate is greater than that reported from various Middle East and European countries, namely Italy,13,17 Turkey,23,30,31 and Greece.11 This discrepancy may be related to different diagnostic criteria used for the definition of HS, and/or there is a genuine racial difference in the prevalence of HS.

In our study, HS was more prevalent in boys, especially from 7 to 11 years of age. The issue of sex difference in the prevalence of HS is controversial, and has only been reported in a few of the published studies.9-15 In adults HS is more common in men,36 and sex hormones and their influence on respiratory control and/or body fat distribution have been suggested to play a crucial role. Clearly, these factors would be much less prominent in prepubertal children, which accounted for the majority of subjects in our study. Increased prevalence of AR among male Hong Kong children could explain the sex discrepancy in children with HS.10 AR causing inflammation and narrowing to the upper airways would increase flow resistance and hence one’s liability to snore. In addition, nasal corticosteroid spray used for the treatment of AR also improved OSA.37 In the current study, further analysis showed that the prevalence of AR in boys was significantly higher than in girls at age 7 to 11 years, sharing the same pattern as the prevalence of HS (Fig 2). Moreover, AR was significantly associated with HS in the multivariate model. The observed male predominance in AR may be explained by the relative male disadvantage in terms of possible reduced adaptive immunity during the early period of life.38

Figure Jump LinkFigure 2. Prevalence of allergic rhinitis by age and sex. *Significant difference between boys and girls (P < .05).Grahic Jump Location

Our result indicated that having one parent who is a habitual snorer significantly increased the risk of HS by nearly 3.4-fold. This finding corresponded to previous reports and provides further support to the role of genetics in the development of HS.11,39 Genetic factors that determine craniofacial structure, body composition, and neuromuscular control of the upper airway interact to produce a phenotype. A previous study involving children with a mean age of 1 year when there was less opportunity for environmental influence demonstrated similar risk inheritance in HS across generations.39

Sore throat and enlarged tonsils as independent risk factors for HS have been reported.16,17,30,31,33-35 Our study showed that nasosinusitis and tonsillitis in the past 12 months were associated with a higher risk for HS. These parameters could be markers of viral exposure, which causes adenotonsillar hypertrophy leading to pharyngeal airway narrowing and thus snoring. Household crowding may allow more accurate reporting of nighttime symptoms. It has been shown that snoring may go unreported in a single-child family where the child tends to sleep alone.20 In this study, neither household crowding nor single-child family was significantly associated with the risk of HS. On the other hand, children who slept in their own room were shown to be less likely to have HS. This was possibly related to the accuracy of parental report. It was reasonable to presume that nighttime symptoms of these children were not detected by their parents.

Smoking has been suggested to result in obstruction and collapse of the pharyngeal airway by inducing inflammation and mucosal edema, predisposing to snoring.20 Passive parental smoking was reported to be a risk factor for snoring in children.11,12,18-22 Corbo et al20 demonstrated a significant dose-effect correlation between prevalence of HS and number of cigarettes smoked by parents. We did not, however, find significant association between household smoking and HS or a dose-effect relationship between prevalence of household smoking and frequency of snoring. It was possible that parents underreported household smoking, given the fact that many parents think smoking in the bathroom or kitchen well away from their child is acceptable.

Factor analysis is a commonly used statistical method to reduce a large number of clinical parameters to a relatively small number of independent factors. As each factor groups associated parameters, the results help to provide an insight into the pathophysiology of complex diseases. Being free of a predetermined hypothesis on any interrelated parameters, this technique can be seen as a hypothesis-generating tool. It was not surprising to document strong correlation between HS and various sleep-related symptoms, especially those related to OSA, as HS is a cardinal symptom of the condition. There is accumulating evidence to suggest snoring, which signifies upper airway narrowing, is associated with neurocognitive deficits.21,40 Although the information obtained from this questionnaire was a crude way to assess neurocognitive outcome, we found a dose-dependent relationship between prevalence of such outcomes (namely poor temper, hyperactivity, and poor academic performance) and snoring frequency. Furthermore, HS was demonstrated to be a significant risk factor for these surrogate markers of neurocognitive deficit.

There are limitations to our study. First, the response rate was 70% of all students invited to participate. This could have introduced a degree of selection bias whereby parents whose child had sleep symptoms or problems were more likely to return the questionnaire. This might have resulted in an overestimation of the prevalence. On comparing the demographic and socioeconomic data of respondents and nonrespondents, we could not find any significant differences between the two groups. We believe that our studied cohort was a good overall representation of the sample population. Second, the survey questionnaires were completed by parents, and very often they do not rest in the same room as their child and therefore would not know their actual sleep behavior. This is a known intrinsic problem associated with the use of postal questionnaire survey. Nonetheless, a recent publication on preschool children showed a significant and independent association between parentally reported and objectively measured HS.41 Furthermore, the reliability of sleep-disordered breathing questionnaires, including ours, has been demonstrated previously.26,42

In summary, we found the prevalence of HS to be 7.2% in Hong Kong. Male sex, BMI z score, parental HS, AR and asthmatic symptoms, and URTI in the past 12 months were independent risk factors of HS. HS was also demonstrated to be associated with various OSA symptoms and neurobehavioral outcomes.

Author contributions: Drs Li and Wing accept full responsibility for the work and conduct of the study, had access to the data, and controlled the decision to publish.

Dr Li: contributed to the planning and design of the study, recruiting subjects, collecting data, revising the article, and approving the final manuscript.

Mr Au: contributed to the planning and design of the study, recruiting subjects, collecting data, analyzing data, revising the article, and approving the final manuscript.

Dr So: contributed to the planning and design of the study, recruiting subjects, collecting data, analyzing data, revising the article, and approving the final manuscript.

Dr Lau: contributed to the planning and design of the study, analyzing data, revising the article, and approving the final manuscript.

Dr Ng: contributed to the planning and design of the study, revising the article, and approving the final manuscript.

Dr Wing: contributed to the planning and design of the study, recruiting subjects, collecting data, revising the article, and approving the final manuscript.

Financial/nonfinancial disclosures: The authors have reported to CHEST the following conflicts of interest: Dr Wing has lectured in scientific meeting under the sponsorship of Eli Lilly. He also has received grant sponsorship from the government of HKSAR and sanofi-aventis. Drs Li, So, Lau, and Ng and Mr Au have reported no conflicts.

Other contributions: We thank all participating schools, parents, and children for their dedication. This work was performed at the Department of Pediatrics, The Chinese University of Hong Kong.

AR

allergic rhinitis

HS

habitual snoring

OSA

obstructive sleep apnea

URTI

upper respiratory tract infection

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Figures

Figure Jump LinkFigure 1. Prevalence of habitual snoring (HS) by age and sex. *Significant difference between boys and girls (P < .05).Grahic Jump Location
Figure Jump LinkFigure 2. Prevalence of allergic rhinitis by age and sex. *Significant difference between boys and girls (P < .05).Grahic Jump Location

Tables

Table Graphic Jump Location
Table 1 —Summary of Items and Factor Loadings of the Six Factors
Table Graphic Jump Location
Table 2 —Subject Characteristics by Sex

AR = allergic rhinitis; household crowding = living space per person < 5.5 m2; HS - habitual snoring; poverty = family income per person < HK$2,500; poor parental education = full-time education up to primary level; URTI = upper respiratory tract infection.

Table Graphic Jump Location
Table 3 —Characteristics of Subjects According to Snoring Status

See Table 2 for explanation of terms and expansion of abbreviations.

Table Graphic Jump Location
Table 4 —Risk Factors Associated With HS With Reference to Nonsnorers

OR = odds ratio. See Table 2 for explanation of terms and expansion of other abbreviations.

a 

Adjusted for age, sex, and BMI z score.

b 

Adjusted for all factors with a P < .1 in model 1 simultaneously.

Table Graphic Jump Location
Table 5 —Comparison of the Factor Scores of Sleep-Related Symptoms, Sleep Duration, and Neurobehavioral Outcomes Between Groups
a 

Significantly different from nonsnoring controls.

Table Graphic Jump Location
Table 6 —Associations Between Snoring and Neurobehavioral Outcomes

P value adjusted for age, sex, BMI z score, atopic symptoms, URTI, environmental factors, and socioeconomic factors. See Tables 2 and 4 for expansion of abbreviations.

Table Graphic Jump Location
Table 7 —Prevalence and Risk Factors of HS in Different Countries

NA = not applicable. See Table 2 for expansion of other abbreviation.

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