Validity of hearing impairment calculation methods for prediction of self-reported hearing handicap

Noise Health. Jan-Feb 2012;14(56):13-20. doi: 10.4103/1463-1741.93321.

Abstract

Worker's compensation for hearing loss caused by occupational noise exposure is calculated by varying methods, from state to state within the United States (US), with many employing arithmetic formulas based on the pure-tone audiogram, to quantify hearing loss. Several assumptions unsupported or weakly supported by empirical data underlie these formulas. The present study evaluated the ability of various arithmetic hearing impairment calculations to predict a self-reported hearing handicap in a sample of presenting with sensorineural hearing loss. 204 adults (127 male, 77 female) ranging in age from 18 to 94 served as participants. The sample was selected to exclude patients who had been referred for hearing testing for a medicolegal examination or a hearing conservation appointment. A hearing handicap was measured by the Hearing Handicap Inventory for Adults/for the Elderly (HHIA/E). The covariance analysis of linear structural equations was used to assess the relative strength of correlation with the HHIA/E score among the six formulas and various forms of pure-tone average. The results revealed that all the hearing impairment calculations examined were significantly, but weakly, correlated with the self-reported hearing impairment scores. No significant differences among the predictive abilities of the impairment calculations were evident; however, the average binaural impairment assigned differed significantly among the six calculations examined. Individuals who demonstrated 0% impairment had significantly lower (i.e., better) HHIA/E scores compared to those with non-zero impairment for each formula. These results supported the idea that audiometric data provided an insufficient explanation for real-world hearing difficulties.

Publication types

  • Multicenter Study
  • Validation Study

MeSH terms

  • Adolescent
  • Adult
  • Aged
  • Aged, 80 and over
  • Analysis of Variance
  • Audiometry, Pure-Tone
  • Female
  • Hearing Loss, Noise-Induced / diagnosis*
  • Hearing Loss, Noise-Induced / epidemiology
  • Humans
  • Male
  • Mathematics
  • Middle Aged
  • Noise, Occupational / adverse effects*
  • Occupational Exposure / adverse effects*
  • Predictive Value of Tests
  • United States / epidemiology
  • Workers' Compensation