Hearing loss configurations in low- and middle-income countries

Newall, John; Kim, Rebecca; Dawes, Piers; Alnafjan, Fadwa; Vaughan, Glyn; Carkeet, Donna; Ghannoum, Heba; Mcpherson, Bradley; Patel, Nitish; Sasidharan, Megha; Damam, Nitin; Goswami, S.; Chinnaraj, Geetha; Sartika, Dahlia; Alhanbali, Sara; Bartlett, Rebecca; Ismail, Afzarini; Smith, Mike; Ghimire, Anup; Shah, Shankar; Martinez, Norberto; Ramos, Hubert; Alparce, Ultima; Tavartkiladze, George; Bakhshinyan, Vigen; Boboshko, Maria; Kasper, Annette; Pifeleti, Sione; Swanepoel, De; Myburgh, Herman; Frisby, Caitlin; Pitathawatchai, Pittayapon; Atas, Ahmet; ŞERBETÇİOĞLU, Mustafa; SENNAROĞLU, GONCA; Konukseven, SEVİLAY; TOKGÖZ YILMAZ, SUNA; TÜRKYILMAZ, MERAL; BATUK, MERVE; KARA, EYYUP; Senkaya, Duygu; Babaoglu, Gizem; Oruc, Yesim; Ozkan, Melek; Cetinkaya, Merve; Ceyhan, Aysenur; Adali, Inci

doi:10.1080/14992027.2025.2466746

Hearing loss configurations in low- and middle-income countries

Newall J., Kim R., Dawes P., Alnafjan F., Vaughan G., Carkeet D., ...More

INTERNATIONAL JOURNAL OF AUDIOLOGY, 2025 (SCI-Expanded)

Publication Type: Article / Article
Publication Date: 2025
Doi Number: 10.1080/14992027.2025.2466746
Journal Name: INTERNATIONAL JOURNAL OF AUDIOLOGY
Journal Indexes: Science Citation Index Expanded (SCI-EXPANDED), Scopus, Academic Search Premier, ASSIA, BIOSIS, CINAHL, Communication & Mass Media Index, EBSCO Education Source, EMBASE, MEDLINE, Psycinfo
Hacettepe University Affiliated: Yes

Abstract

ObjectiveThe majority of individuals with hearing loss worldwide reside in low- and middle-income countries (LMICs), but there is limited information regarding the characteristics of hearing loss in these regions. This descriptive study aims to address this knowledge gap by analysing audiogram patterns in LMIC populations. Greater knowledge about the properties of hearing loss in LMICs allows for improved planning of interventions.Study sampleRetrospective data from 23 collaborating centres across 16 LMICs were collected. All participants were adults seeking help for hearing problems. A machine learning approach was utilised to classify the hearing threshold data and identify representative profiles. The study comprised 5773 participants.ResultsThe results revealed mildly sloping audiometric patterns with varying severity. The patterns differed from previous studies conducted in high-income regions which included more steeply sloping losses. The findings also indicated a higher proportion of more severe levels of hearing loss.ConclusionsThese variations could be attributed to population-level differences in the causative mechanisms of hearing loss in LMICs, such as a higher prevalence of infectious disease-related hearing loss. The results may also reflect differences in health seeking behaviours. This study highlights the need for tailored, scalable, hearing interventions for LMICs.