Purpose: The aim of this study was to determine median audiograms and prevalence of hearing loss for U.S. 6- to 19-year-olds.
Method: U.S. national audiometric data for 2,709 six- to 19-year-olds from the National Health and Nutrition Examination Survey 2017-2020 were analyzed. Analyses were primarily descriptive and relied on distribution-free medians, cumulative distribution functions (CDFs), and population-weighted prevalence estimates. Differences between CDFs were examined using Cohen's effect size. Results are presented for the age range of 6-19 years. Main effects of sex, age, and race/ethnicity were examined.
Results: Differences in the audiograms between the sexes and among the various race/ethnicity groups were minor, but age group differences were notable. Pure-tone thresholds at 500 and 8000 Hz for the 6- to 9-year age group were 3-5 dB higher (worse) than those of the other age groups. The overall prevalence of hearing loss among 6- to 19-year-olds, defined as either of the pure-tone averages (PTAs) for 500, 1000, and 2000 Hz (PTA512) or 3000, 4000, 6000, and 8000 Hz (PTA3468k) exceeding 15 dB HL in either ear, was 11.24% (95% confidence interval [10.00%, 12.48%]). Binary logistic regression analyses found the odds of hearing loss to be significantly higher for individuals from families with a low income as well as for those with abnormal otoscopy or abnormal tympanometry.
Conclusions: For children and adolescents in the United States, hearing was unaffected by differences in sex and race/ethnicity, with only age impacting pure-tone thresholds and only at the lowest (500 Hz) and highest (8000 Hz) frequencies examined. The overall prevalence of hearing loss was about 11%.
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http://dx.doi.org/10.1044/2024_JSLHR-24-00050 | DOI Listing |
Acta Bioeng Biomech
September 2024
Faculty of Computer Science, Kazimierz Wielki University, Bydgoszcz, Poland.
Monitoring and assessing the level of lower limb motor skills using the Biodex System plays an important role in the training of football players and in post-traumatic rehabilitation. The aim of this study was to build and test an artificial intelligence-based model to assess the peak torque of the lower limb extensors and flexors. The model was based on real-world results in three groups: hearing ( = 19) and deaf football players ( = 28) and non-training deaf pupils ( = 46).
View Article and Find Full Text PDFJ Acoust Soc Am
January 2025
Department of Biology, University of Aarhus, Aarhus, 8000, Denmark.
Gransier and Kastelein [J. Acoust. Soc.
View Article and Find Full Text PDFCNS Neurosci Ther
January 2025
Department of Otolaryngology, Nanjing First Hospital, Nanjing Medical University, Nanjing, China.
Background: Sudden sensorineural hearing loss (SSNHL) is associated with abnormal changes in the brain's central nervous system. Previous studies on the brain networks of SSNHL have primarily focused on functional connectivity within the brain. However, in addition to functional connectivity, structural connectivity also plays a crucial role in brain networks.
View Article and Find Full Text PDFEar Hear
January 2025
McMaster Institute for Music and the Mind, McMaster University, Hamilton, Ontario, Canada.
Objectives: Live music creates a sense of connectedness in older adults, which can help alleviate the social isolation frequently associated with hearing loss and aging. However, most hearing-aid (HA) users are dissatisfied with the sound quality of live music and rate sound quality as important to them. Assistive listening systems are frequently independent of a user's HAs and fall short in tailoring to each individual's hearing loss.
View Article and Find Full Text PDFLaryngoscope
January 2025
Department of Otolaryngology-Head and Neck Surgery, NewYork-Presbyterian/Columbia University Irving Medical Center, Columbia University Vagelos College of Physicians and Surgeons, 180 Fort Washington Avenue, HP8, New York, New York, 10032, U.S.A.
Objectives: Hearing loss (HL) has significant implications on social functioning. Here, we study the relationship between HL, race, and these combined categories as risk factors for discrimination in the large national All of Us cohort.
Methods: The National Institutes of Health All of Us dataset was analyzed after including individuals who completed the Everyday Discrimination Survey between November 2021 and January 2022.
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