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. 2022 Sep;20(3):147–152. doi: 10.3121/cmr.2022.1679

Anthropometric Measures for the Prognosis of Obstructive Sleep Apnea in Obese

Laura Souza Lagares *, Ramon Souza Lino *, Eric Simas Bomfim †, Felipe Almeida Santos *, Ciro Oliveira Queiroz ‡, Lélia Lessa Pinto ⸹, Luiz Alberto Bastos Almeida ⁋, Clarcson Plácido Santos ‡,✉
PMCID: PMC9544195  PMID: 36028283

Abstract

Objective: The objective of this study was to identify, among the different anthropometric indicators, the one that shows higher discriminatory power for the prognosis of Obstructive Sleep Apnea Syndrome (OSAS).

Design: Observational cross-sectional study.

Participants: Obese individuals elective to bariatric surgery.

Methods: A study based on data of 758 patients aged ≥ 21 years old, of both sexes, in the pre-operatory stage of the surgical procedure of gastric bypass. Obstructive sleep apnea and obstructive sleep hypopnea were evaluated and classified through the apnea-hypopnea index, which was obtained through the examination of polysomnography. Variables were divided into two groups: individuals with and without OSAS. As predictors, measures of body mass index (BMI), neck circumference (NC), and waist circumference (WC) were used.

Results: The area under the ROC curve was used to check the sensitivity and specificity. All evaluated anthropometric indicators showed statistical significance. WC: area of 0.62 (CI 95%: 0.58 – 0.67), NC: area of 0,68 (CI 95%: 0.64 – 0.72) and BMI: area of 0.58 (CI 95%: 0.54 – 0.63).

Conclusion: The investigated anthropometric indicators performed as good predictors of OSAS. However, NC seems to be the best anthropometric indicator for the prognosis of OSAS in obese individuals when compared to BMI and WC.

Keywords: Anthropometry; Body Mass Index; Obesity; Prognosis; Sleep Apnea, Obstructive; Waist Circumference

Obstructive Sleep Apnea Syndrome (OSAS) is a breathing disorder characterized by repeated events of partial or total obstruction of the upper airways (UA) during sleep.1 It can be diagnosed through polysomnography or the value of the Apnea-Hypopnea Index (AHI) ≥ 15 events per hour, and its prevalence may vary from 1% to 4% in adults.2,3 OSAS is considered an independent risk factor for systemic arterial hypertension,4 development of atrial fibrillation, and increase of the prevalence of metabolic syndrome.5–7

Among the risk factors for OSAS, obesity shows a strong association,8 especially due to the concentration of adipose tissue in the neck and upper chest.9,10 Obesity and OSAS cause metabolic and endocrine alterations, which can cause health problems.11 Furthermore, it was noticed that the visceral fat accumulation and the distribution of adipose tissue also have a significant role before the risk factors that are related to OSAS.12,13

In this respect, it is noticed that obesity is related to body composition through anthropometric measures such as body mass index (BMI), waist-to-hip ratio, waist circumference, and skinfold measurements.14,15 Beyond obesity, previous studies showed the relation of OSAS with anthropometric measurements, such as neck circumference, abdominal circumference, and BMI.16,17 However, beyond the studies that investigated the relation of neck circumference with OSAS,18–20 there are gaps in the literature comparing the different anthropometric indicators and their predictive values for the prognosis of OSAS.

Once the predictive values of anthropometric indicators regarding OSAS are identified, the use of these tools can potentially be used in health assistance, especially in large populations where access to more expensive equipment is limited.21–25 Given the above, the objective of the present study was to investigate the discriminatory power of different anthropometric indicators for the prognosis of OSAS in adults with the diagnosis of obesity.

Materials and Methods

Study Design and Sample

This study was based on cross-sectional data of 758 patients aged ≥ 21 years old, of both sexes, in the pre-operatory phase of gastric bypass, who had been attending the Obesity Treatment and Surgery Center, between January 2017 and November 2018, in the city of Salvador (BA), Brazil. Information was collected through the exams of everyone.

Ethical Statement

The study was approved by the Research and Ethics Committee at the Bahian School of Medicine and Public Health, number 54119216.30000.5544. During the conduction of this research, there were observed directives of the research on human beings, norms of the Resolution 466/12, and all participants signed the free prior informed consent form.

Evaluation of Obstructive Sleep Apnea and Hypopnea

The patients underwent a polysomnographic examination using Respironics (Healthdyne Technologies Alice 4 System). The report was reviewed by a single expert, to minimize the cost of the examination, since it was performed according to the routine of the clinic in which the quantitative data collected are reviewed and the final report is prepared, both by a specialist doctor. The examination was held throughout the night, in spontaneous sleep, without any sedation or privation. In this examination, the following were recorded: electroencephalogram, electrooculogram, electromyogram, electrocardiogram, airway, respiratory effort, snoring, and body position. The final report was reviewed by a pneumologist. AHI was obtained through a polysomnographic examination, dividing the total of respiratory events by hours of sleep.20,21 Individuals were classified according to AHI:26,27 without apnea, fewer than 5 events/hour of sleep; with light apnea, between 5.0 and 14.9 events/hour of sleep; with moderate apnea, between 15 and 30 events /hour of sleep; and with serious apnea, more than 30 events/hour of sleep. The variables that had been analyzed in this study were divided into two groups: individuals with or without OSAS.

Anthropometric Measures

As predictors, the measures used were: BMI, neck circumference (NC), and waist circumference (WC). Anthropometric measures were held by two trained evaluators. In the cases where the two first measures differed in 0.5 cm, a third measure was recorded, and the average of all recorded measures were calculated. Height was measured by using a portable stadiometer (Seca Corporation, Hanover, MD) to calculate the BMI. Circumferences were measured with Gulick tape. Waist circumference was measured in the scar umbilicus and recorded with a precision of 0.1 cm. Neck circumference was measured under the laryngeal prominence, perpendicular along the neck axis, and the minimum circumference was recorded with an approximation of 0.1 cm.28 The average Pearson correlation coefficient between the repetitions for the measures was higher than 0.99, and it showed excellent reproducibility.

Volunteers were advised to fast 8 hours before the collection of anthropometric measures, not to drink alcohol 48 hours before the test, not to exercise – moderately or intensively – up to 12 hours before the evaluation, and wear a bathing suit or underwear.

Statistical Analysis

To build a database, analytical and descriptive analysis, the software Statistical Package for Social Sciences (SPSS), version 14.0 for Windows, was used. The normality of variables was analyzed through descriptive statistics and the Kolmogorov-Smirnov test. The continuous variables with normal distribution were represented by mean and standard deviation. For the comparison of the groups that are stratified in patients with and without OSAS, the Student’s t-test was used for independent samples, and the level of significance of 5% was adopted. For the analysis of the predictive value among the studied variables (OSAS and anthropometric measures), Receiver Operating Characteristic (ROC) curves were used. The confidence interval (CI) was 95% to determine if the discriminatory capacity of the anthropometric indicators was not due to chance, namely, its lower limit shall not be lower than 0.50.

Results

Data from 758 obese patients were evaluated; 512 (67.5%) were women with a mean age of 37±11 years, and around 11% of them had asthma or were smokers, and 246 (32.5%) were men. The averages and standard deviation in relation to the groups with and without OSAS were, respectively: age, 38.5 ± 11.3 years and 32.3 ± 8.4 years (P<0.001); BMI 41.5 ± 5.8 kg/m2 and 39.8 ± 4.2 kg/m2 (P<0,001); NC 41.8 ± 4.7 cm and 39.0 ± 3.3 cm (P<0.001); WC 125 ± 15.4 cm and 118.9 ± 11.1 cm (P< 0.001), sedentarism 67.9% and 32.1% (P=0.099).

Regarding the anthropometric indicators, it was verified that the BMI of the sample was higher than 40 kg/m², waist circumference was larger than 120 cm, and neck circumference was larger than 40 cm (Table 1).

Table 1.

General and anthropometric characteristics of obese patients according to the diagnosis of OSAS.

Characteristics Sleep Apnea Total P value
Yes
n = 524		 No
n = 234
Age (years) 39 (11) 32 (8) 37 (11) < 0.001
Men (%) 84.6 15.4 67.5 < 0.001
Physically inactive (%) 67.9 32.1 83.9 0.099
Patients with asthma (%) 11.6 11.2 11.5 0.848
Non-smoker patients (%) 11.9 94.4 92.7 0.216
Anthropometric indicators
    BMI kg/m2 41.5 (6) 39.8 (4) 40.9 (5) < 0.001
    NC cm 42 (5) 39 (3) 41 (4) < 0.001
    WC cm 125 (15) 119 (11) 123 (14) < 0.001
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Data is presented as mean (standard deviation); P < 0.005.

NC, Neck circumference; BMI, Body Mass Index; WC, Waist circumference.

In Figures 1, 2, and 3 this can be visualized using the ROC curve for sensitivity and specificity. Figure 1 shows the measure of WC with area of 0.62 (CI 95%: 0.58 – 0.67), in Figure 2, NC presented an area of 0,68 (CI 95%: 0.64 – 0.72) and Figure 3, BMI, area of 0.58 (CI 95%: 0.54 – 0.63).

Figure 1.

Figure 1.

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Area under the ROC curve for sensitivity and specificity of waist circumference measurement as an anthropometric indicator for OSAS prognosis. Diagonal segments are produced by ties.

Figure 2.

Figure 2.

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Area under the ROC curve for sensitivity and specificity of neck circumference measurement as an anthropometric indicator for OSAS prognosis. Diagnonal segments are produced by ties.

Figure 3.

Figure 3.

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Area under the ROC curve for sensitivity and specificity of BMI measurement as an anthropometric indicator for OSAS prognosis. Diagonal segments are produced by ties.

Areas under the curve, which are higher than 0.50 and statistically significant to discriminate OSAS, were found in all evaluated anthropometric indicators. WC had an area of 0.62 (CI 95%: 0.58 – 0.67), NC showed an area of 0,68 (CI 95%: 0.64 – 0.72) and BMI showed an area of 0.58 (CI 95%: 0.54 – 0.63).

Discussion

The ratio between OSAS, obesity, and anthropometric measures has already been reported in some previous studies,8–10,12,13,18–20 especially obesity and NC,8,18–20 once both have strong associations with OSAS. Faced with these previous findings, our study aimed to evaluate the discriminatory power of different anthropometric indicators, so that we could obtain a better and more reliable variable for the prognosis of OSAS, directly implying the use of anthropometric measures in clinical evaluation of individuals with the diagnosis of obesity.

In our study, we observed age was one of the variables that showed a statistically significant difference between the groups with and without OSAS. Due to advancing age, complaints related to sleep become more frequent.29 It is noticed that 70% of men and 56% of women between 65- and 95- years-of-age can present with obstructive sleep apnea.30 In another study held with men and women between ages 45- and 99-years-old, it was verified that older individuals showed a bigger prevalence of high risk for OSAS.31 It is observed that the elderlies present less muscle strength in general, which causes the aggravation in the reduction of the oropharyngeal muscle tone. It is also possible to associate the bigger prevalence of high risk for OSAS in this population, with diseases that are risk factors, such as diabetes, cardiac disease, and renal failure, which are more frequent in elderlies.32

Another relevant data, which has been pointed out in our findings, is related to the incidence of OSAS in male people. Studies show that the risk of men developing OSAS is 2 to 3 times higher when compared to women.33,34 Meanwhile, it is worth highlighting that women less frequently report symptoms of obstructive sleep apnea and/or show nonspecific and not too classic symptoms of OSAS, and, for this reason, women obtain subdued results, so that it decreases the prevalence if compared to males.35 A factor that may contribute to a higher prevalence of OSAS in males was observed through a study that demonstrated obesity in male individuals tends to show a higher concentration of fat in the upper body among them in the neck region, favoring a higher risk of OSAS, if compared to women.36

Concerning anthropometric measures, neck circumference stood out because it showed a higher discriminatory power for the prognosis of OSAS, because of a bigger area under the ROC curve. Previous studies showed that NC has a strong association with OSAS, and these results move in the same direction as the findings in our study.18,19 This ratio of higher predictive power can be justified by the biological plausibility related to the higher accumulation of adipose tissue in the neck, and which, as a consequence, may result in decreased airways, causing the development of OSAS.17

Regarding BMI, previous studies showed a strong association with OSAS.16,37,38 Data from our study corroborate these findings, and BMI was also considered a good discriminator for OSAS, according to the area under the ROC curve. This relation can be explained due to the strong association of BMI with obesity;14,15 notably in obese individuals, the weight ratio, which reflects the bigger accumulation of total fat, demonstrates this population’s higher risk for the development of OSAS.8

Still about the anthropometric measures, WC in our study was considered the second best discriminatory one for OSAS. In a recent study, it was noticed that WC showed a positive correlation with the severity of OSAS in patients; however, there was no statistically significant difference between the evaluated groups. Yet, from this study, it is suggested that abdominal adiposity can predict the severity of OSAS, which can explain the fact that WC was a good predictor.39 Previous findings also showed WC as a good predictor for OSAS, which corroborates with our study.16,37

The clinical approach can be very favored by the results found in our study; we can observe that anthropometric measures are important and can help in the prognosis of OSAS in a simpler and more applicable way. These results directly imply in the health of patients who have possibly been affected by OSAS, the disease is considered an independent risk factor for the development of atrial fibrillation, and systemic arterial hypertension,4,5 besides being associated with metabolic syndrome, cardiovascular morbidity, anxiety, and depression, among others.6,7,40

There are some limitations in this study, for example, data collection was held through medical records. Nevertheless, many studies also use this type of data, and they are relevant for the applicability in public health, because they use anthropometric indicators of low cost. In addition, the results of this study point to the need to collect and record these anthropometric data in the routine of medical care or health professionals who serve the public characteristic of this research.

Conclusion

In conclusion, among the investigated anthropometric indicators, all of them were good predictors of OSAS. On the other hand, NC seems to be the best anthropometric indicator for the prognosis of OSAS in obese individuals, if compared to BMI and WC. In the face of these findings, it is observed the need for a clinical approach that favors a higher applicability of this instrument once this tool can help health professionals in clinical practice.

Acknowledgments

To the nucleus for the treatment and surgery of obesity for all support, availability, and care so that this production of knowledge could be done. This study adhered to all indicative standards of the research ethics committee involving human beings.

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