Assessment of the validity and utility of a sleep-symptom questionnaire

Am J Respir Crit Care Med. 1994 Sep;150(3):735-41. doi: 10.1164/ajrccm.150.3.8087345.

Abstract

Although questionnaires have been developed to assess symptoms of obstructive sleep apnea (OSA), their overall reliability and utility have not been established. We have evaluated the ability of a questionnaire to identify increased apnea activity (IAA) in 465 participants in an epidemiologic study of OSA. Subjects and their roommates each completed a questionnaire and underwent in-home sleep studies. Responses to 56 questions about sleep habits, sleepiness, and daytime performance were analyzed with factor analysis, logistic regression, and receiver-operator curves (ROCs). Factor analysis demonstrated that 16 questions, grouped into five factors (functional impact of sleepiness, self-reported breathing disturbances, roommate-observed breathing disturbances, driving impairment, and insomnia) explained 67% of the variance in the questionnaire data. Symptom questions demonstrated internal consistency (Cronbach correlations: 0.91 to 0.98). Moderate levels of agreement were observed between self- and roommate-reported responses for nine of ten questions asked of both the subject and his/her partner (kappa statistics: 0.34 to 0.57). Logistic regression analysis demonstrated that IAA could be best predicted by three questions about intensity of snoring, roommate-observed choking, and having fallen asleep while driving (ROC area: 0.78). Use of symptoms with data on gender and body mass index (BMI) improved predictive ability by 10% (ROC area: 0.87). Thus, questionnaire data provide a valid means of characterizing symptom distributions in population surveys of OSA. Predictive ability is not significantly improved with multiple questions or a separate roommate questionnaire, but is improved with consideration of data on BMI and gender.

Publication types

  • Comparative Study
  • Research Support, U.S. Gov't, P.H.S.

MeSH terms

  • Adult
  • Chi-Square Distribution
  • Factor Analysis, Statistical
  • Female
  • Humans
  • Logistic Models
  • Male
  • Middle Aged
  • Ohio / epidemiology
  • Polysomnography
  • Prognosis
  • ROC Curve
  • Reproducibility of Results
  • Sleep Apnea Syndromes / diagnosis*
  • Sleep Apnea Syndromes / epidemiology
  • Surveys and Questionnaires