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. 2021 May 17;74(Suppl 2):1483–1491. doi: 10.1007/s12070-021-02623-8

Correlating Nasal Patency with Obstructive Sleep Apnea in Obese Versus Non-Obese Patients: An Acoustic Rhinometry Study

Shiv Shankar Agarwal 1,✉, Sanjeev Datana 1, N K Sahoo 2, S K Bhandari 2
PMCID: PMC9701976  PMID: 36452587

Abstract

The aim of this study was to correlate nasal patency with Obstructive Sleep Apnea (OSA) in obese versus non-obese patients using Acoustic Rhinometry (AR). Eccovision® Acoustic Rhinometer equipment was used to compare nasal cross-sectional areas (CSA1,2 & 3 corresponding to nasal valve region, anterior portion of middle & inferior turbinate and posterior portion of middle & inferior turbinate respectively) and volume in age and gender matched sample divided into three groups: Group 1: Non-obese patients without OSA (25 patients, 13 males and 12 females); Group 2: Non-obese patients with OSA (25 patients, 14 males and 11 females); Group 3: Obese patients with OSA (25 patients, 13 males and 12 females). The mean nasal cross-sectional areas and volume were lower in Group 2 compared to Group 1 but statistically non-significant (P value > 0.05 for all). The mean nasal cross-sectional areas and volume were significantly lower in Group 3 as compared to Groups 1 and 2 (P value < 0.05 for all). BMI showed a statistically significant positive (direct) correlation with AHI in Groups 2 and 3 (P value < 0.05 for both). The nasal cross-sectional areas and volume showed a statistically significant negative (inverse) correlation with AHI in Groups 2 and 3 (P value < 0.05 for both). OSA diagnosed cases with high BMI may not present with an obvious nasal obstruction; the nasal patency may still be compromised due to reduced nasal lumen secondary to obesity. AR, being cost-effective and non-invasive modality; is advocated to evaluate pre-treatment nasal patency, as well as follow up evaluation to ascertain improvement after the intervention.

Keywords: Acoustic rhinometry, Nasal patency, Obstructive Sleep Apnea

Introduction

Obstructive sleep apnoea (OSA) is a breathing disorder which is characterised by narrowing/collapse of airway during sleep and is usually associated with repetitive apneic and hypopneic episodes along with oxygen desaturation, sleep fragmentation and excessive daytime sleepiness. It is an emerging public health problem worldwide affecting 2 to 4% of the adults [1]. OSA is associated with an increased risk of cardiovascular ailments like hypertension and stroke. Studies have associated untreated OSA with a higher mortality rate on a long term [2].

Various factors such as obesity, craniofacial and upper airway anatomical abnormalities etc. have been associated with an increased risk of OSA in adults [3]. Literature has also associated reduced nasal patency with an increased incidence of OSA [4]. An increased nasal resistance has been associated with factors affecting nasal patency such as obesity, deviated nasal septum, nasal polyps, presence of nasopharyngeal mass, rhinitis etc. A few studies have linked a higher nasal resistance with an increased risk of snoring and OSA [4–6]. However, there is a contradicting evidence in literature regarding this with some studies finding no or weak correlation between reduced nasal patency and OSA [7–9].

Studies have also associated obesity with reduced nasal patency and increased airflow resistance [10]. However, there is limited literature which correlates obesity, nasal patency and OSA in a single study. It is pertinent to study the impact of reduced nasal patency secondary to obesity on OSA by comparing nasal geometry of obese and non-obese patients suffering from OSA with healthy controls in a sample with no other apparent cause of nasal obstruction to know the influence of obesity on OSA.

Therefore, the present study was conducted with aim to correlate the nasal patency with OSA in obese versus non-obese patients using Acoustic Rhinometry (AR). AR, a non-ionising and non-invasive modality which can be routinely used for assessment of nasal patency, was used as a diagnostic tool in the present study.

Material and Methods

Study Design

Cross-sectional study.

Study Sample

The present study was conducted at the Department of Orthodontics & Dentofacial Orthopaedics of a government teaching institute. The permission of the Institutional Ethical Committee was obtained prior to the start of study. The AR records (Rhinogram) (Fig. 1) obtained for the Polysomnography (PSG) diagnosed patients suffering from OSA who were referred to the department for evaluation of craniofacial risk factors for OSA between 01 Jan 2018 and 31 Jan 2020 were utilized in the present study. The control group was of 25 randomly selected Rhinogram from the departmental archives after considering the inclusion and exclusion criteria of the study. All Rhinogram used in the present study were obtained with Eccovision® Acoustic Rhinometer equipment (Sleep Group Solutions) with a standardized technique. [11] All patients selected for the study had undergone an overnight Type 1 PSG for diagnosis of OSA at the sleep centre. The height and weight measurements of all patients were noted and Body Mass Index (BMI) was calculated by using the formula: BMI = Weight (kg)/Height (m2).

Fig. 1.

Fig. 1

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Rhinogram: sample area-distance graph recorded by Acoustic Rhinometry, showing the nasal cavity cross-sectional areas measured at the sites corresponding to the nasal valve (CSA1), the anterior (CSA2) and the posterior (CSA3) portions of the middle and lower nasal turbinates

Inclusion Criteria

  • PSG diagnosed OSA cases with no known cause of nasal obstruction.

  • Age range: 30–50 years (both genders included).

  • AHI greater than 5 and less than 40/sleep hour

  • BMI greater than 25 and less than 40 kg/m2

Exclusion criteria

  • Patients with central or mixed sleep apnea.

  • Morbid obesity i.e. BMI > 40 kg/m2

  • Syndromes which affect nasal growth including cleft lip & palate.

  • Any local or systemic disease/ condition affecting nasal airway and breathing.

  • History of surgeries like adenoidectomy, tonsillectomy, septoplasty, rhinoplasty and excision of polyps/any other mass in the nasal cavity.

  • Patients under medication for nasal allergies, acute nasal swelling or history of recent maxillofacial/nasal trauma and who underwent orthodontic treatment affecting nose.

  • Moderate to severe dentofacial deformity.

Categorization of Study Sample

The treatment records of 75 patients were selected for the study. The patients were classified as non-obese (BMI < 30 kg/m2) and obese (BMI > 30 kg/m2) based on BMI. The patients with AHI ≥ 5 ≤ 40/per sleep hour were considered under OSA group. Healthy individuals with no history of any sleep disorder having BMI < 30 kg/m2matching the inclusion and exclusion criteria were selected as a control group. Entire study sample was age and gender matched and divided into 03 groups (Table 1):

Table 1.

Demographic characteristics

Parameter Group 1 n = 25 (Non obese without OSA, BMI < 30) Group 2 n = 25 (Non obese with OSA, BMI < 30) Group 3 N = 25 (Obese with OSA, BMI > 30) P value (Group 1 Vs. Group 2) P value (Group 1 Vs. Group 3) P value (Group 2 Vs. Group 3)
Age (years) Mean ± SD 39.8 ± 10.4 Mean ± SD 40.2 ± 9.8 Mean ± SD 41.5 ± 11.2 0.552NS 0.469NS 0.566NS
Gender 0.999NS 0.999NS 0.999NS
Male M 13 (52.0%) M 14 (56.0%) M 13 (52.0%)
Female F 12 (48.0%) F 11 (44.0%) F 12 (48.0%)
Mean BMI (Kg/cm2) Mean ± SD 25.8 ± 2.7 Mean ± SD 26.5 ± 2.4 Mean ± SD 32.4 ± 2.2 0.327NS 0.008** 0.028*
Mean AHI – Mean ± SD 24.7 ± 10.5 Mean ± SD 27.6 ± 11.1 – – 0.293NS
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*P-value<0.05, **P-value<0.01, ***P-value<0.001, NS-Statistically non-significant

Group 1: Non-obese patients without OSA (25 patients, 13 males and 12 females).

Group 2: Non-obese patients with OSA (25 patients, 14 males and 11 females).

Group 3: Obese patients with OSA (25 patients, 13 males and 12 females).

The AR procedure was performed separately for both nostrils as per protocol given by Corey et al. [11]. The nasal cross sectional areas (CSA) and volume were recorded for both nostrils separately from the Rhinogram (Fig. 1). The mean of above parameters for right and left nostrils was considered for the study. The values of nasal CSA were obtained at three dips of the area distance curve i.e. CSA1 denoting the nasal valve region, CSA2 denoting the anterior and CSA3 denoting the posterior region of inferior and middle turbinates. The nasal volume from nasal valve to posterior part of the middle nasal turbinate was measured for both nostrils separately and the mean nasal volume was considered for the study. The entire data for the three groups was recorded and entered in Microsoft (MS) excel sheets and subjected to statistical analyses.

Statistical Analysis

The inter-group statistical comparison of distribution of categorical variables was tested using Chi-Square test. The inter-group statistical comparison of means of continuous variables was done using analysis of variance (ANOVA) with Bonferroni’s post-Hoc test for multiple group comparisons. The underlying normality assumption was tested using Kolmogorov–Smirnov test before subjecting the study variables to ANOVA. The p values less than 0.05 were considered to be statistically significant. All the hypotheses were formulated using two tailed alternatives against each null hypothesis (hypothesis of no difference). The entire data was statistically analyzed using Statistical Package for Social Sciences (SPSS version 22.0, IBM Corporation, USA) for MS Windows.

Results

Demographic Characteristics

The mean age and gender did not differ significantly across the three study groups (P value > 0.05 for all). The mean BMI scores did not differ significantly between Group 1 and 2 (P value > 0.05) but were significantly higher in Group 3 compared to Group 1 and 2 (P value < 0.05 for both). The mean AHI did not differ significantly between Groups 2 and 3 (P value > 0.05) (Table 1, Figs. 2–5).

Fig. 3.

Fig. 3

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Inter-group comparison of gender

Fig. 4.

Fig. 4

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Inter-group comparison of mean BMI

Fig. 2.

Fig. 2

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Inter-group comparison of mean age

Fig. 5.

Fig. 5

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Inter-group comparison of mean AHI

Comparison of Mean Nasal CSA (CSA1, 2 & 3) and Mean Volume in Three Groups

Inter-group Comparison of Mean CSA

The mean CSA1, 2 and 3 values were lower in Group 2 as compared to Group 1 but statistically insignificant (P value > 0.05 for all). The mean CSA1, 2 and 3 values were significantly lower in Group 3 as compared to Groups 1 and 2 (P value < 0.05 for all) (Table 2, Fig. 6).

Table 2.

Comparison of mean nasal CSA (CSA1, 2 & 3) and mean volume in three groups

Parameter Group 1 n = 25 (Non obese without OSA, BMI < 30) Group 2 n = 25 (Non obese with OSA, BMI < 30) Group 3 N = 25 (Obese with OSA, BMI > 30) P value (Group 1 Vs. Group 2) P value (Group 1 Vs. Group 3) P value (Group 2 Vs. Group 3)
Mean Nasal CSA in Cm2 (mean of right and left nostrils)
CSA1 0.63 0.60 0.56 0.548NS 0.028* 0.009**
CSA2 1.12 1.09 0.98 0.412NS 0.031* 0.007**
CSA3 1.74 1.65 1.46 0.642NS 0.041* 0.008**
Volume in Cm3 (mean of right and left nostrils) 25.18 24.22 21.02 0.609NS 0.029* 0.033*
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*P-value<0.05, **P-value<0.01, ***P-value<0.001, NS-Statistically non-significant

Fig. 6.

Fig. 6

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Inter-group comparison of mean CSA

Inter-group Comparison of Mean Volume

The mean nasal volume showed lower values in Group 2 as compared to Group 1 but statistically insignificant (P value > 0.05 for all). The mean volume was significantly lower in Group 3 as compared to Groups 1 and 2 (P value < 0.05 for all) (Table 2, Fig. 7).

Fig. 7.

Fig. 7

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Inter-group comparison of mean volume

Correlation of AHI with BMI, Mean Nasal CSA (CSA1, 2 & 3) and Mean Volume in Group 2 and 3

BMI showed a statistically significant positive (direct) correlation with AHI in Groups 2 and 3 (P value < 0.05 for both). The nasal cross-sectional areas (CSA 1, 2 and 3) and volume showed a statistically significant negative (inverse) correlation with AHI in Groups 2 and 3 (P value < 0.05 for both) (Table 3, Fig. 8).

Table 3.

Correlation of AHI with BMI, mean nasal CSA (CSA1, 2 & 3) and mean volume in Group 2 and 3

Group 2 n = 25 (Non obese with OSA, BMI < 30) Group 3 N = 25 (Obese with OSA, BMI > 30)
AHI With r-value P value r-value P value
BMI 0.395 0.001*** 0.406 0.001***
CSA 1 – 0.401 0.001*** – 0.413 0.001***
CSA 2 – 0.305 0.001*** – 0.395 0.001***
CSA 3 – 0.395 0.001*** – 0.402 0.001***
Volume – 0.374 0.001*** – 0.485 0.001***
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*P-value<0.05, **P-value<0.01, ***P-value<0.001, NS-Statistically non-significant

Fig. 8.

Fig. 8

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Correlation of AHI with BMI, mean nasal CSA (CSA1, 2 & 3) and mean volume in Group 2 and 3

Discussion

The association between nasal obstruction and sleep have been well documented in literature along with improvement in quality of sleep following relief from nasal congestion/ obstruction [12, 13]. Majority of studies have observed a moderate [14] to strong correlation [15, 16] between reduced nasal patency and increased resistance to nasal airflow. A few studies have even found no correlation between nasal patency and airflow resistance [17].

Obesity has been observed as an important risk factor for OSA with two-thirds of OSA patients being obese [18–20]. The fat deposition on the nasal and pharyngeal lumen leads to its narrowing and makes the airway more prone to collapse, thereby making obese patients more prone to OSA [20, 21]. Studies have shown that about 50% of upper airway resistance is contributed by the nostrils [22].

The upper airway acts as a hollow collapsible tube. The nostrils are the anterior, constricted opening of this tube. The oropharynx behaves as the posterior and collapsible part of this tube. Any upstream obstruction i.e. reduced nasal patency/ CSA of nose will generate a suction force or negative intraluminal pressure downstream in the oropharynx. This may result in pharyngeal collapse especially in individuals with pre-existing airway compromise and may contribute to OSA [23, 24]. The reduced nasal patency may also lead to open mouth posture, mouth breathing, retro-positioning of the tongue and subsequent narrowing of the oro-pharynx [25].

Though there are studies which have associated obesity with OSA and reduced nasal patency with OSA [6, 20, 26, 27], there is inadequate literature which compares the nasal patency between obese and non-obese patients suffering from OSA in a sample with no other apparent cause of nasal obstruction. Therefore, the present study was undertaken to provide baseline evidence in this aspect which can be supported by further prospective studies.

AR is a non-invasive, non-ionising, accurate &reproducible three dimensional (3D) modality for instant chair-side assessment of nasal patency. It measures nasal CSA and volume by using Acoustic Reflection Technique (ART). Studies have compared its accuracy with Computed Tomography (CT) and Magnetic Resonance Imaging (MRI) in assessment of airway [28, 29]. Rhinomanometry, the traditional technique of nasal airflow assessment is associated with various shortcomings; one of them is being flow dependent. This shortcoming has been overcome by AR which provides a 3D anatomy of airway by acoustic reflection of sound wave [30, 31]. AR was therefore used in the present study as a diagnostic modality.

The results of the present study show that the nasal CSA and volume were reduced in non-obese patients with OSA compared to the control group (non-obese, non-OSA) (statistically insignificant). The nasal CSA and volumes were further reduced in obese patients with OSA. All patients had no other apparent cause of nasal obstruction. This signifies the role of reduced nasal patency which may aggravate OSA in these patients. The BMI showed a statistically significant positive correlation whereas the nasal CSA and volume showed a statistically significant negative correlation with AHI in both obese and non-obese patients with OSA. The findings of the present study are similar to other studies [4–6, 32, 33] which associated reduced nasal patency and increased airflow resistance with higher risk of snoring and OSA. The present study contradicts with some studies which found no/weak correlation between reduced nasal patency and OSA [7–9]. Since, there is limited literature which correlates and compares the nasal patency in obese versus non-obese OSA patients; the authors recommend further prospective studies to add further evidence in this regard.

Conclusions

The present study highlights the importance of pre-treatment evaluation of nasal patency. OSA diagnosed cases with high BMI may not present with an obvious nasal obstruction; the nasal patency may still be compromised due to reduced nasal lumen secondary to obesity. In the present study, the mean values of cross-sectional areas (CSA 1, 2 & 3) were reduced in Group 3 (OSA with high BMI) as compared to Group 2 (OSA with normal BMI) and control. Similarly, the mean value of nasal volume was reduced among Group 3 as compared to Group 2 and control. AHI scores have shown a positive correlation with BMI and negative correlation with nasal cross-sectional areas and volume.

Acoustic rhinometry, being cost-effective, non-invasive, chair side modality to evaluate the cross-sectional areas and volume of nasal cavity, is advocated to evaluate pre-treatment nasal patency, as well as follow up evaluation to ascertain improvement after the intervention.

Funding

None.

Declarations

Conflict of interest

The authors declare that they have no competing interest.

Footnotes

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

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