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Haile LM, Orji AU, Reavis KM, Briant PS, Lucas KM, Alahdab F, Bärnighausen TW, Bell AW, Cao C, Dai X, Hay SI, Heidari G, Karaye IM, Miller TR, Mokdad AH, Mostafavi E, Natto ZS, Pawar S, Rana J, Seylani A, Singh JA, Wei J, Yang L, Ong KL, Steinmetz JD. Hearing Loss Prevalence, Years Lived With Disability, and Hearing Aid Use in the United States From 1990 to 2019: Findings From the Global Burden of Disease Study. Ear Hear 2024; 45:257-267. [PMID: 37712826 PMCID: PMC10718207 DOI: 10.1097/aud.0000000000001420] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/29/2022] [Accepted: 06/17/2023] [Indexed: 09/16/2023]
Abstract
OBJECTIVES This article describes key data sources and methods used to estimate hearing loss in the United States, in the Global Burden of Disease study. Then, trends in hearing loss are described for 2019, including temporal trends from 1990 to 2019, changing prevalence over age, severity patterns, and utilization of hearing aids. DESIGN We utilized population-representative surveys from the United States to estimate hearing loss prevalence for the Global Burden of Disease study. A key input data source in modeled estimates are the National Health and Nutrition Examination Surveys (NHANES), years 1988 to 2010. We ran hierarchical severity-specific models to estimate hearing loss prevalence. We then scaled severity-specific models to sum to total hearing impairment prevalence, adjusted estimates for hearing aid coverage, and split estimates by etiology and tinnitus status. We computed years lived with disability (YLDs), which quantifies the amount of health loss associated with a condition depending on severity and creates a common metric to compare the burden of disparate diseases. This was done by multiplying the prevalence of severity-specific hearing loss by corresponding disability weights, with additional weighting for tinnitus comorbidity. RESULTS An estimated 72.88 million (95% uncertainty interval (UI) 68.53 to 77.30) people in the United States had hearing loss in 2019, accounting for 22.2% (20.9 to 23.6) of the total population. Hearing loss was responsible for 2.24 million (1.56 to 3.11) YLDs (3.6% (2.8 to 4.7) of total US YLDs). Age-standardized prevalence was higher in males (17.7% [16.7 to 18.8]) compared with females (11.9%, [11.2 to 12.5]). While most cases of hearing loss were mild (64.3%, 95% UI 61.0 to 67.6), disability was concentrated in cases that were moderate or more severe. The all-age prevalence of hearing loss in the United States was 28.1% (25.7 to 30.8) higher in 2019 than in 1990, despite stable age-standardized prevalence. An estimated 9.7% (8.6 to 11.0) of individuals with mild to profound hearing loss utilized a hearing aid, while 32.5% (31.9 to 33.2) of individuals with hearing loss experienced tinnitus. Occupational noise exposure was responsible for 11.2% (10.2 to 12.4) of hearing loss YLDs. CONCLUSIONS Results indicate large burden of hearing loss in the United States, with an estimated 1 in 5 people experiencing this condition. While many cases of hearing loss in the United States were mild, growing prevalence, low usage of hearing aids, and aging populations indicate the rising impact of this condition in future years and the increasing importance of domestic access to hearing healthcare services. Large-scale audiometric surveys such as NHANES are needed to regularly assess hearing loss burden and access to healthcare, improving our understanding of who is impacted by hearing loss and what groups are most amenable to intervention.
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Affiliation(s)
- Lydia M. Haile
- Institute for Health Metrics and Evaluation, University of Washington, Seattle, WA, USA
| | - Aislyn U. Orji
- Institute for Health Metrics and Evaluation, University of Washington, Seattle, WA, USA
| | - Kelly M. Reavis
- National Center for Rehabilitative Auditory Research, US Department of Veterans Affairs—Portland Healthcare System, Portland, OR, USA
| | - Paul Svitil Briant
- Institute for Health Metrics and Evaluation, University of Washington, Seattle, WA, USA
| | - Katia M. Lucas
- Institute for Health Metrics and Evaluation, University of Washington, Seattle, WA, USA
| | - Fares Alahdab
- Mayo Evidence-based Practice Center, Mayo Clinic Foundation for Medical Education and Research, Rochester, MN, USA
| | - Till Winfried Bärnighausen
- Heidelberg Institute of Global Health (HIGH), Heidelberg University, Heidelberg, Germany
- T.H. Chan School of Public Health, Harvard University, Boston, MA, USA
| | - Arielle Wilder Bell
- Department of Global Health and Social Medicine, Harvard University, Boston, MA, USA
- Department of Social Services, Tufts Medical Center, Boston, MA, USA
| | - Chao Cao
- Program in Physical Therapy, Washington University in St. Louis, St. Louis, MO, USA
| | - Xiaochen Dai
- Institute for Health Metrics and Evaluation, University of Washington, Seattle, WA, USA
- Department of Health Metrics Sciences, School of Medicine, University of Washington, Seattle, WA, USA
| | - Simon I. Hay
- Institute for Health Metrics and Evaluation, University of Washington, Seattle, WA, USA
- Department of Health Metrics Sciences, School of Medicine, University of Washington, Seattle, WA, USA
| | | | - Ibraheem M. Karaye
- School of Health Professions and Human Services, Hofstra University, Hempstead, NY, USA
| | - Ted R. Miller
- Pacific Institute for Research & Evaluation, Calverton, MD, USA
- School of Public Health, Curtin University, Perth, WA, Australia
| | - Ali H. Mokdad
- Institute for Health Metrics and Evaluation, University of Washington, Seattle, WA, USA
- Department of Health Metrics Sciences, School of Medicine, University of Washington, Seattle, WA, USA
| | - Ebrahim Mostafavi
- Department of Medicine, Stanford University, Palo Alto, CA, USA
- Stanford Cardiovascular Institute, Stanford University, Palo Alto, CA, USA
| | - Zuhair S. Natto
- Department of Dental Public Health, King Abdulaziz University, Jeddah, Saudi Arabia
- Department of Oral Health Policy and Epidemiology, Harvard University, Boston, USA
| | - Shrikant Pawar
- Department of Genetics, Yale University, New Haven, CT, USA
| | - Juwel Rana
- Department of Epidemiology, Biostatistics and Occupational Health, McGill University, Montreal, QC, Canada
- Research and Innovation Division, South Asian Institute for Social Transformation (SAIST), Dhaka, Bangladesh
| | - Allen Seylani
- National Heart, Lung, and Blood Institute, National Institute of Health, Rockville, MD, USA
| | - Jasvinder A. Singh
- School of Medicine, University of Alabama at Birmingham, Birmingham, AL, USA
- Medicine Service, US Department of Veterans Affairs (VA), Birmingham, AL, USA
| | - Jingkai Wei
- Department of Epidemiology and Biostatistics, University of South Carolina, Columbia, SC, USA
| | - Lin Yang
- Cancer Epidemiology and Prevention Research, Alberta Health Services, Calgary, BC, Canada
- Department of Oncology, University of Calgary, Calgary, AB, Canada
| | - Kanyin Liane Ong
- Institute for Health Metrics and Evaluation, University of Washington, Seattle, WA, USA
| | - Jaimie D. Steinmetz
- Institute for Health Metrics and Evaluation, University of Washington, Seattle, WA, USA
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Caminschi I, Lucas KM, O'Keeffe MA, Hochrein H, Laâbi Y, Brodnicki TC, Lew AM, Shortman K, Wright MD. Molecular cloning of a C-type lectin superfamily protein differentially expressed by CD8alpha(-) splenic dendritic cells. Mol Immunol 2001; 38:365-73. [PMID: 11684292 DOI: 10.1016/s0161-5890(01)00067-0] [Citation(s) in RCA: 39] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/06/2023]
Abstract
Dendritic cells (DC) are potent antigen presenting cells that activate naive T cells. It is becoming increasingly clear that DC are not a homogeneous cell population, but comprise different subpopulations that differ in ontogeny and function. To further the molecular characterisation of DC, we screened for genes that were differentially expressed amongst DC subsets and could therefore give insight into their varying biological functions. Using Representational Difference Analysis (RDA) we identified a gene (CIRE) that is expressed at higher levels in the myeloid-related CD8alpha(-) DC than in the lymphoid-related CD8alpha(+) DC. CIRE is a 238 amino acid type II membrane protein, of approximately 33 kDa in size, whose extracellular region contains a C-type lectin domain. Northern blot analysis revealed that CIRE is almost exclusively expressed in DC and was not detected in organs such as heart, brain, kidney, liver, and thymus. T cells failed to express message for CIRE, whilst B cells expressed very low levels. These data here further substantiated by Northern blot analysis of 18 cell lines of various origins (myeloid, macrophage, B and T cell) where only one cell line, which was of myeloid origin and could give rise to DC, expressed mRNA for CIRE. Semi-quantitative RT-PCR suggested that CIRE is down-regulated upon activation. CIRE shares 57% identity with human DC-SIGN, a molecule that has been shown to be the ligand of ICAM-3 and that is also a receptor that binds HIV and facilitates trans-infection of T cells.
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Affiliation(s)
- I Caminschi
- The Walter and Eliza Hall Institute of Medical Research, PO Royal Melbourne Hospital, Victoria 3050, Melbourne, Australia.
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