Predictors of moderate to severe obstructive sleep apnea: identification of sex differences



Home sleep apnea tests are recommended only for patients at high risk of moderate to severe obstructive sleep apnea (OSA, apnea-hypopnea index [AHI] ≥ 15/h). We evaluated 14 factors known to be associated with OSA and identified sex differences in predictors of moderate to severe OSA.


Retrospective analysis was done on 545 subjects who completed sleep questionnaires and underwent diagnostic polysomnogram at a tertiary sleep center. Univariate and multivariate analysis was conducted separately in males and females to determine which variables were independent predictors of moderate to severe OSA.


Overall, physical traits were stronger predictors in both males and females. For each sex, only 3 variables were found to be independently predictive of moderate to severe OSA. In order of predictive strength, this included body mass index (BMI) ≥ 38 kg/m2 (aOR 5.80, p < 0.001), neck circumference (NC) ≥ 17 in. (aOR 2.52, p = 0.002), and Epworth sleepiness scale (ESS) ≥ 13 (aOR 2.22, p = 0.015) for males and age ≥ 50 years (aOR 4.19, p < 0.001), NC ≥ 14.5 in. (aOR 3.13, p = 0.003), and report of morning headaches (aOR 2.00, p = 0.039) for females. Applying the Bonferroni correction, BMI and NC remained significant for males, and age and NC remained significant for females.


In a subject population referred for sleep evaluation at a tertiary care center only a few variables are independently predictive of moderate to severe OSA, and these variables differed between males and females. Only BMI, NC, and a high ESS were independently predictive of moderate to severe OSA in males, whereas age, NC, and morning headaches were independently predictive in females.

This is a preview of subscription content, log in to check access.

Fig. 1


  1. 1.

    Senaratna CV, Perret JL, Lodge CJ, Lowe AJ, Campbell BE, Matheson MC, Hamilton GS, Dharmage SC (2017) Prevalence of obstructive sleep apnea in the general population: a systematic review. Sleep Med Rev 34:70–81

    Article  Google Scholar 

  2. 2.

    Gonzaga C, Bertolami A, Bertolami M, Amodeo C, Calhoun D (2015) Obstructive sleep apnea, hypertension and cardiovascular diseases. J Hum Hypertens 29(12):705–712

    CAS  Article  Google Scholar 

  3. 3.

    Kerner NA, Roose SP (2016) Obstructive sleep apnea is linked to depression and cognitive impairment: evidence and potential mechanisms. Am J Geriatr Psychiatry 24(6):496–508

    Article  Google Scholar 

  4. 4.

    Knauert M, Naik S, Gillespie MB, Kryger M (2015) Clinical consequences and economic costs of untreated obstructive sleep apnea syndrome. World J Otorhinolaryngol Head Neck Surg 1(1):17–27

    Article  Google Scholar 

  5. 5.

    Steinke E, Palm Johansen P, Fridlund B, Brostrom A (2016) Determinants of sexual dysfunction and interventions for patients with obstructive sleep apnoea: a systematic review. Int J Clin Pract 70(1):5–19

    CAS  Article  Google Scholar 

  6. 6.

    Dong JY, Zhang YH, Qin LQ (2013) Obstructive sleep apnea and cardiovascular risk: meta-analysis of prospective cohort studies. Atherosclerosis 229(2):489–495

    CAS  Article  Google Scholar 

  7. 7.

    Goldstein CA, Karnib H, Williams K, Virk Z, Shamim-Uzzaman A (2017) The utility of home sleep apnea tests in patients with low versus high pre-test probability for moderate to severe OSA. Sleep Breath

  8. 8.

    Kapur VK, Auckley DH, Chowdhuri S, Kuhlmann DC, Mehra R, Ramar K, Harrod CG (2017) Clinical practice guideline for diagnostic testing for adult obstructive sleep apnea: an American Academy of Sleep Medicine clinical practice guideline. J Clin Sleep Med 13(3):479–504

    Article  Google Scholar 

  9. 9.

    Hoffstein V, Szalai JP (1993) Predictive value of clinical features in diagnosing obstructive sleep apnea. Sleep 16(2):118–122

    CAS  PubMed  Google Scholar 

  10. 10.

    Friedman M, Tanyeri H, La Rosa M, Landsberg R, Vaidyanathan K, Pieri S, Caldarelli D (1999) Clinical predictors of obstructive sleep apnea. Laryngoscope 109(12):1901–1907

    CAS  Article  Google Scholar 

  11. 11.

    Pillar G, Peled N, Katz N, Lavie P (1994) Predictive value of specific risk factors, symptoms and signs, in diagnosing obstructive sleep apnoea and its severity. J Sleep Res 3(4):241–244

    CAS  Article  Google Scholar 

  12. 12.

    Prasad KT, Sehgal IS, Agarwal R, Nath Aggarwal A, Behera D, Dhooria S (2017) Assessing the likelihood of obstructive sleep apnea: a comparison of nine screening questionnaires. Sleep Breath 21(4):909–917

    Article  Google Scholar 

  13. 13.

    Cowan DC, Allardice G, Macfarlane D, Ramsay D, Ambler H, Banham S, Livingston E, Carlin C (2014) Predicting sleep disordered breathing in outpatients with suspected OSA. BMJ Open 4(4):e004519

    Article  Google Scholar 

  14. 14.

    Sharma SK, Malik V, Vasudev C, Banga A, Mohan A, Handa KK, Mukhopadhyay S (2006) Prediction of obstructive sleep apnea in patients presenting to a tertiary care center. Sleep Breath 10(3):147–154

    CAS  Article  Google Scholar 

  15. 15.

    Marti-Soler H, Hirotsu C, Marques-Vidal P, Vollenweider P, Waeber G, Preisig M, Tafti M, Tufik SB, Bittencourt L, Tufik S, Haba-Rubio J, Heinzer R (2016) The NoSAS score for screening of sleep-disordered breathing: a derivation and validation study. Lancet Respir Med 4(9):742–748

    Article  Google Scholar 

  16. 16.

    Duarte RLM, Rabahi MF, Magalhaes-da-Silveira FJ, de Oliveira ESTS, Mello FCQ, Gozal D (2018) Simplifying the screening of obstructive sleep apnea with a 2-item model, no-apnea: a cross-sectional study. J Clin Sleep Med

  17. 17.

    Duarte RL, Magalhaes-da-Silveira FJ (2015) Factors predictive of obstructive sleep apnea in patients undergoing pre-operative evaluation for bariatric surgery and referred to a sleep laboratory for polysomnography. J Bras Pneumol 41(5):440–448

    Article  Google Scholar 

  18. 18.

    Dixon JB, Schachter LM, O'Brien PE (2003) Predicting sleep apnea and excessive day sleepiness in the severely obese: indicators for polysomnography. Chest 123(4):1134–1141

    Article  Google Scholar 

  19. 19.

    Hein M, JP Lanquart G, Loas PH, Linkowski P (2017) Prevalence and risk factors of moderate to severe obstructive sleep apnea syndrome in insomnia sufferers: a study on 1311 subjects. Respir Res 18(1):135

    Article  Google Scholar 

  20. 20.

    Kang HH, Kang JY, Ha JH, Lee J, Kim SK, Moon HS, Lee SH (2014) The associations between anthropometric indices and obstructive sleep apnea in a Korean population. PLoS One 9(12):e114463

    Article  Google Scholar 

  21. 21.

    Berry RB, Budhiraja R, Gottlieb DJ, Gozal D, Iber C, Kapur VK, Marcus CL, Mehra R, Parthasarathy S, Quan SF, Redline S, Strohl KP, Davidson Ward SL, Tangredi MM, M American Academy of Sleep (2012) Rules for scoring respiratory events in sleep: update of the 2007 AASM manual for the scoring of sleep and associated events. Deliberations of the sleep apnea definitions task force of the American Academy of Sleep Medicine. J Clin Sleep Med 8(5):597–619

    PubMed  PubMed Central  Google Scholar 

  22. 22.

    Gabbay IE, Lavie P (2012) Age- and gender-related characteristics of obstructive sleep apnea. Sleep Breath 16(2):453–460

    Article  Google Scholar 

  23. 23.

    Huang T, Lin BM, Redline S, Curhan GC, Hu FB, Tworoger SS (2018) Type of menopause, age at menopause, and risk of developing obstructive sleep apnea in postmenopausal women. Am J Epidemiol 187(7):1370–1379

    Article  Google Scholar 

  24. 24.

    Johns MW (1992) Reliability and factor analysis of the Epworth sleepiness scale. Sleep 15(4):376–381

    CAS  Article  Google Scholar 

Download references


The authors thank Michael Lutz, Ph.D. for statistical advice, Onyinye Iweala, M.D., Ph.D. for review of the manuscript, and Aatif Husain, M.D. and Rodney Radtke, M.D. for support of the research.

Author information



Corresponding author

Correspondence to Andrew R. Spector.

Ethics declarations

Conflict of interest

The authors declare that they have no conflict of interest.

Informed consent

This study was approved by the Duke University Health System Institutional Review Board. For retrospective chart reviews, formal consent is not required.

Ethical approval

All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Helsinki declaration and its later amendments or comparable ethical standards.

Ethical publication statement

We confirm that we have read the Journal’s position on issues involved in ethical publication and affirm that this report is consistent with those guidelines.

Additional information

Publisher’s note

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

Rights and permissions

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

Earl, D.E., Lakhani, S.S., Loriaux, D.B. et al. Predictors of moderate to severe obstructive sleep apnea: identification of sex differences. Sleep Breath 23, 1151–1158 (2019).

Download citation


  • Obstructive sleep apnea
  • Predictors
  • Sex
  • Body mass index
  • Neck circumference
  • Symptoms