title: Notched audiograms and noise exposure history in older adults.
abstract: OBJECTIVE
  Using data from a population-based cohort study, we compared four published algorithms for identifying notched audiograms and compared their resulting classifications with noise exposure history.
  
  
  METHODS
  Four algorithms: (1) , (2) , (3) , and (4) were used to identify notched audiograms. Audiometric evaluations were collected as a part of the 10-yr follow-up examinations of the Epidemiology of Hearing Loss Study, in Beaver Dam, WI (2003-2005, N = 2395). Detailed noise exposure histories were collected by interview at the baseline examination (1993-1995) and updated at subsequent visits. An extensive history of occupational noise exposure, participation in noisy hobbies, and firearm usage was used to evaluate consistency of the notch classifications with the history of noise exposure.
  
  
  RESULTS
  The prevalence of notched audiograms varied greatly by definition (31.7, 25.9, 47.2, and 11.7% for methods 1, 2, 3, and 4, respectively). In this cohort, a history of noise exposure was common (56.2% for occupational noise, 71.7% for noisy hobbies, 13.4% for firearms, and 81.2% for any of these three sources). Among participants with a notched audiogram, almost one-third did not have a history of occupational noise exposure (31.4, 33.0, 32.5, and 28.1% for methods 1, 2, 3, and 4, respectively), and approximately 11% did not have a history of exposure to any of the three sources of noise (11.5, 13.6, 10.3, and 7.6%). Discordance was greater in women than in men.
  
  
  CONCLUSIONS
  These results suggest that there is a poor agreement across existing algorithms for audiometric notches. In addition, notches can occur in the absence of a positive noise history. In the absence of an objective consensus definition of a notched audiogram and in light of the degree of discordance in women between noise history and notches by each of these algorithms, researchers should be cautious about classifying noise-induced hearing loss by notched audiograms.
authors.affiliation: Department of Ophthalmology and Visual Sciences, University of Wisconsin, Madison, Wisconsin 53726-2397, USA.
authors.forename: David M
authors.initials: DM
authors.lastname: Nondahl
authors.forename: Xiaoyu
authors.initials: X
authors.lastname: Shi
authors.forename: Karen J
authors.initials: KJ
authors.lastname: Cruickshanks
authors.forename: Dayna S
authors.initials: DS
authors.lastname: Dalton
authors.forename: Ted S
authors.initials: TS
authors.lastname: Tweed
authors.forename: Terry L
authors.initials: TL
authors.lastname: Wiley
authors.forename: Lakeesha L
authors.initials: LL
authors.lastname: Carmichael
mesh_terms: D000368:Aged; D000369:Aged, 80 and over; D000465:Algorithms; D001301:Audiometry, Pure-Tone / Q000379:methods*; D001309:Auditory Threshold; D003430:Cross-Sectional Studies; D005260:Female; D005389:Firearms; D005500:Follow-Up Studies; D006317:Hearing Loss, Noise-Induced / Q000145:classification / Q000175:diagnosis* / Q000453:epidemiology; D006686:Hobbies; D006801:Humans; D008297:Male; D008875:Middle Aged; D009622:Noise / Q000009:adverse effects*; D009784:Occupational Diseases / Q000145:classification / Q000175:diagnosis / Q000453:epidemiology; D016017:Odds Ratio; D010897:Pitch Discrimination; D012044:Regression Analysis; D012737:Sex Factors; D013018:Sound Spectrography