Occupational Noise-Induced Hearing Loss in Africa: Gaps, Barriers, and Strategies for Effective Prevention

Abstract

Occupational noise-induced hearing loss (ONIHL) remains one of the most common and preventable occupational diseases globally, yet it exerts a disproportionate burden in low- and middle-income countries. In Africa, where hazardous noise exposure is widespread and occupational health systems are under-resourced, ONIHL continues to affect workers across both formal and informal sectors. This narrative review, conducted with Preferred Reporting Items for Systematic Reviews and Meta-Analyses-style transparency, synthesizes Africa-specific evidence from 49 sources, including epidemiological studies, policy documents, and qualitative research, to map prevalence and exposure patterns, identify systemic and contextual barriers, and highlight feasible prevention strategies. Literature published between 2000 and 2025 was sourced from PubMed, Scopus, Web of Science, and grey-literature databases. Reported prevalence rates remain consistently high, with 22–30% among South African miners, 47–48% among Tanzanian miners and steel workers, and over 20% among Ghanaian sawmill and stone-crushing workers. Although several African countries have occupational noise regulations, their impact is undermined by weak enforcement, poor compliance monitoring, and the near-total exclusion of informal workers. Barriers to prevention span multiple levels, including inadequate provision and use of hearing protection devices, critical shortages of audiologists, low awareness and stigma, and competing health priorities such as human immunodeficiency virus and tuberculosis. Promising approaches include comprehensive hearing conservation programs, engineering controls such as “buy quiet,” and emerging fourth industrial revolution innovations (tele-audiology, mobile health, artificial intelligence). However, their effectiveness depends on addressing underlying infrastructure, workforce, and governance challenges. Preventing ONIHL in Africa requires a holistic, multi-sectoral approach that integrates occupational health with broader public health, labor, and development agendas, while extending protection to the majority employed in the informal economy.

KEY MESSAGES

• (1)Occupational noise-induced hearing loss (ONIHL) remains one of the most prevalent yet preventable occupational diseases, with fragmented African evidence and limited representation beyond South Africa.
• (2)This narrative review synthesizes findings from 49 African sources, revealing persistently high ONIHL prevalence driven by weak regulatory enforcement, workforce shortages, poor compliance, and sociocultural barriers.
• (3)Prevention requires multi-sectoral strategies linking occupational and public health, expansion of protections to informal workers, and adoption of context-appropriate innovations such as “buy-quiet” engineering, tele-audiology, and mobile health tools.

Introduction

Occupational noise-induced hearing loss (ONIHL) is a permanent sensorineural loss resulting from prolonged exposure to hazardous noise, typically ≥85 dB(A) over an 8-hour time-weighted average (TWA). It is globally recognized as one of the most prevalent and preventable occupational diseases, with over 430 million people experiencing disabling hearing loss, and occupational noise accounting for an estimated 16% of adult cases.[1,2] Given its irreversible nature, prevention is essential, particularly in low- and middle-income countries (LMIC) settings, where exposure is widespread and regulatory and health-system responses remain limited.[3,4]

Available continental and country-level analyses show considerably higher prevalence of disabling hearing impairment are considerably higher in many parts of sub-Saharan Africa (SSA) than in high-income countries, reflecting elevated exposure risks and constrained access to preventive and rehabilitation services.[1,5] Studies from South Africa, Ghana,[6,7,8] Tanzania,[9,10,11,12] and other settings consistently document high ONIHL rates in mining, manufacturing, and construction work, driven by prolonged high-decibel exposures (≥85 dB(A) 8 h TWA), inadequate protection, shift patterns, and co-exposures to ototoxic chemicals.[8,11,13,14] Despite this burden, comprehensive and systematically documented research on ONIHL and hearing conservation programs (HCPs) in Africa remains scarce.[3,15] This results from fragmented research, weak surveillance systems (including inconsistent use of standard threshold shift [STS] or percentage loss of hearing [PLH] criteria, and limited personal dosimetry data), inadequate routine audiometric monitoring, and poor indexing of grey literature.[4,5] Consequently, existing evidence is geographically clustered, methodologically heterogeneous, and not readily comparable across contexts.[16,17]

Weak surveillance and reporting directly limit the capacity of governments and employers to quantify burden, target interventions, and monitor HCP effectiveness.[3,18,19] In many African countries, occupational noise regulations are either insufficiently enforced or lack clear exposure limits, undermining prevention efforts.[4,20] For example, South Africa enforces an 85 dB(A) 8-h TWA limit, while Ghana and Nigeria apply 90 dB(A), yet inspection remains inconsistent.

ONIHL has wide-ranging consequences for labor participation, productivity, communication, and psychosocial well-being; with evidence from African studies showing reduced quality of life and substantial socioeconomic impact on workers and households.[8,12,13] These consequences are exacerbated in informal sectors with limited access to occupational health services and assistive technologies.[16,21]

Despite these challenges, a small but growing body of work highlights promising, context-appropriate prevention strategies, including low-cost screening approaches, task-sharing models, community-embedded awareness campaigns, mHealth and tele-audiology pilots, and emerging fourth industrial revolution (4IR) technologies, such as artificial intelligence (AI)-assisted screening.[17,22] However, evidence on feasibility, cost, and acceptability remains limited across diverse African work settings.

Given the high prevalence of ONIHL, contextual challenges, and the fragmented nature of existing evidence, a consolidated review is essential.[4,19] This narrative review synthesizes peer-reviewed and grey-literature sources (2000–2025) to provide an integrated overview of ONIHL burden, gaps, and prevention strategies in Africa, guided by four specific objectives:

• (1)To map the current evidence on the prevalence, exposure patterns, and impacts of ONIHL in Africa.
• (2)To examine policy, regulatory, and enforcement gaps that hinder effective prevention.
• (3)To identify workplace, health system, and sociocultural barriers that contribute to poor implementation of HCPs.
• (4)To highlight evidence-based and emerging strategies for sustainable ONIHL prevention in Africa.

Methodology

Study Design

This review adopted a narrative review design with systematic elements to ensure transparency and reproducibility. A narrative review was selected because the evidence on ONIHL in Africa is heterogeneous in scope, study design, and methodological quality, making formal meta-analysis inappropriate.[23] To strengthen rigor, the review incorporated structured components commonly used in systematic reviews, including predefined eligibility criteria, multi-database searching, standardized data extraction, and a Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA)-style flow diagram to document study selection.[24] The approach was informed by principles from the PRISMA 2020 statement and the synthesis without meta-analysis reporting guidance, which support transparent evidence synthesis where quantitative pooling is not feasible. No protocol registration was required or conducted, as narrative reviews allow interpretive synthesis and iterative exploration of complex, context-specific evidence. This hybrid design permitted both breadth and depth, supporting an interpretive synthesis across diverse evidence sources while maximizing transparency and reproducibility.

Search Strategy and Literature Selection

Searches were conducted between June 1, 2025 and August 27, 2025 across PubMed/MEDLINE, Scopus, Web of Science, and Google Scholar, supplemented by grey-literature sources including world health organization regional office for africa (WHO AFRO), international labour organization (ILO), national government gazettes and occupational health regulator websites, non-governmental organization (NGO) reports, and targeted Google searches for country-specific legislation. Reference lists of included studies were hand-searched, and subject experts were consulted where relevant. Searches were limited to English. Google Scholar was used for grey literature (first 200 hits per query). Deduplication performed in EndNote X9 using title/author/DOI fields.

Search terms combined occupational noise and ONIHL (e.g., “occupational noise,” “noise-induced hearing loss”), prevention and policy terms (e.g., “hearing conservation,” “hearing protection,” “policy,” “regulation”), and Africa (both regional and individual country names). Boolean operators, truncation, and adjacency operators were used to ensure sensitivity and specificity.

The initial search across all databases yielded 2716 records. After applying database-specific filters (e.g., limiting to categories such as medicine, public health, audiology, occupational health, and excluding unrelated fields, such as engineering and veterinary sciences) and removing 1499 duplicates, 1217 unique records remained and were screened for at the title and abstract level. Following screening, 1168 records were excluded for not meeting the inclusion criteria, leaving 49 full-text articles for detailed eligibility assessment and inclusion in the final synthesis [Table 1]. Screening was performed independently by two reviewers (KKS and KM) at both title/abstract and full-text stages, with discrepancies resolved by discussion and adjudication by a third reviewer where needed. The selection process is presented in [Figure 1], which outlines the identification, screening, and inclusion stages. Importantly, the principle of saturation guided the decision to stop searching for additional evidence. After the final database run and hand-searches, no new themes or concepts were emerging, and further searches yielded duplicate or irrelevant records. This indicated that thematic saturation had been reached, ensuring confidence that the included studies captured the breadth of available evidence on ONIHL in Africa.

Table 1.

Comprehensive evidence synthesis of occupational noise-induced hearing loss in Africa: gaps, barriers, and strategies for effective prevention

Article number	1. Bibliographic details		2. Study characteristics	3. Epidemiological evidence (prevalence, impact, risk factors)	4. Policy and regulatory context	5. Barriers to prevention	6. Strategies, innovations, and opportunities	7. Recommendations
1	Khoza-Shangase et al.[17]; Africa (South Africa); Peer-reviewed journal (Special Issue).		Editorial overview introducing a Special Issue/Collection focusing on OHL within the African context and LAMI countries.	Prevalence of ONIHL is still high and on the rise. Efforts to curb ONIHL are currently unsuccessful. Impact: OHL can present a limitation on suitable employment.	Highlights the need to translate laws and regulations into effective practice.	Significant gaps in locally relevant and responsive evidence. Dearth of research on ONIHL management in Africa. Limited research focuses on only some HCP pillars. Studies had small sample sizes.	HCPs should be viewed as complex interventions (CIs). Strong recommendations for the application of tele-audiology as a service delivery model in resource-constrained settings.	HCPs should be well-integrated and comprehensive, comprising seven pillars. Need for collaborative work of all stakeholders. Careful consideration of tele-audiology.
2	Moroe et al.[3]; Africa; Systematic literature review (peer-reviewed journal).		Systematic literature review (1994–2016). Population: mining industry in Africa. Sample size: nine papers included.	Prevalence of ONIHL is still high and on the rise in African countries. Risk factors: Over-reliance on HPDs. Impact: ONIHL may possibly lead to economic burden.	South African Department of Minerals and Energy recommends HPDs as the last resort.	Dearth of research on ONIHL management in Africa. Limited research focuses on only some HCP pillars (preference for HPDs); record keeping is neglected. Small sample sizes limit generalisation. Challenges with HPDs: discomfort, design, and negative impact on work-related communication.	Findings revealed studies focused on four pillars: engineering controls, administrative controls, personal protective devices, and education/training. HPDs should be used in conjunction with engineering and administrative controls.	Need for more studies on ONIHL management. Need for comprehensive and holistic HCP analysis. Effective record keeping is crucial for accountability and accurate programme evaluation.
3	Kanji et al.[16]; South Africa; Peer-reviewed journal (descriptive research).		Descriptive research study using semi-structured interviews (implied). Population/Sample: Miners/employees. Setting: mining sector.	Risk factors: Duration of previous noise exposure history; noise exposure from lift upon entry; overall visits/rounds undertaken during induction.	References Department of Minerals and Energy 2003 guidelines and SANS 10083:2013.	Knowledge gap regarding what constitutes excessive noise exposure in the workplace.	Use of appropriate HPDs and comprehensive training are emphasized.	Need for more comprehensive training on noise hazards and health promotion. Recommend assessments of retained knowledge and implementation of re-education where required.
4	Khoza-Shangase[18]; Africa (South Africa, Cameroon, Tanzania, Namibia); narrative review (peer-reviewed journal).		Narrative review. Focus: Intersection of human immunodeficiency virus (HIV)/acquired immunodeficiency syndrome (AIDS), (ART, and ONIHL. Included 20 studies.	Dual burden of HIV/AIDS and occupational noise exposure impacts hearing health. Risk factors: occupational noise combined with ototoxic treatments (ART, TB drugs). Impact: Dual burden exacerbates cochlear damage.	Not specified, but contextualizes the problem within the South African quadruple burden of disease.	Paucity of evidence and engagement with the possible influence of HIV/AIDS and TB on ONIHL. Reliance on English-language publications. Absence of longitudinal studies restricts ability to establish causal relationships.	Strategic HCPs should include ototoxicity monitoring.	Contextualized HCPs require awareness and acknowledgement of the burdens of disease (HIV/AIDS and TB). Future research must address critical research gaps and causality.
5	Khoza-Shangase[15]; Africa (South Africa, Mozambique); scoping review (peer-reviewed journal).		Scoping review (using Arksey and O’Malley’s framework). Focus: Influence of HIV/AIDS and TB on ONIHL and HCPs. Setting: South African mining industry. Procured 10 publications.	Evidence points toward synergistic relationship between noise exposure and ototoxic medications. Risk factors: Noise exposure combined with ototoxic drugs/illnesses (TB, HIV).	Policy operationalization and enforcement are key in Mozambique. The legal framework regarding TB compensation for cross-border miners is complex.	Paucity of evidence on highly prevalent burden of disease conditions relating to ONIHL. Research has failed to address ONIHL as a complex condition exacerbated by pharmacological treatments. Systemic barriers persist for cross-border workers regarding unpaid compensation claims (TB/lung impairment).	Practical measures include training health workers on migrant rights and provision of user-friendly health information in local languages.	Practical measures for cross-border miners include training health workers on migrant rights, user-friendly health information in local languages, and building advocacy capacity.
6	Nelson et al.[1]; Global (WHO subregions AFR-D and AFR-E); peer-reviewed journal (global burden estimation/modeling).		Global burden estimation study. Design: Modeling using US NIOSH data adjusted for WHO hearing loss definition ($\geq 41$ dB).	Attributable DALYs (in thousands) due to occupational NIHL for African subregions: AFR-D: 157; AFR-E: 186. Risk factors: Relative risks increase significantly with age and exposure level ($\geq 90$ dB: RR 7.96 for age 15–29). Impact: Morbidity measured in DALYs.	Successfully implementing hearing loss prevention programmes requires commitment and resources.	Estimates contain many uncertainties due to lack of global data on frequency, duration, and intensity of occupational noise exposure.	Not specified.	Establish an analytical framework which can contribute to the case for committing public health resources to occupational health.
7	Śliwińska-Kowalska[48]; Poland (contextual reference); review (Peer-reviewed journal).		Review/Commentary focused on new trends in ONIHL prevention.	NIHL incidence is still high, reaching about 18% of overexposed workers. Risk factors: co-exposure to ototoxic substances (solvents, drugs), heredity, metabolic diseases (diabetes), and hypertension.	Not specified (contextual, non-African policy focus).	Not specified.	Not specified.	Not specified.
8	Verbeek et al.[39]; Global (Cochrane review); Cochrane systematic review update (peer-reviewed journal).		Systematic review update (Cochrane) focusing on interventions to prevent ONIHL. Included 19 studies on long-term effects.	Hearing loss prevention programmes (HLPPs) aim to achieve outcomes equivalent to exposure to 85 dB(A).	Interventions aim to reduce noise exposure.	Engineering controls are generally neglected, despite being the preferred strategy.	Measurement of noise levels is complicated and prone to bias by the worker, task, and environment.	Engineering solutions (new equipment, retrofitting) can substantially reduce noise levels.
9	Moroe[35]; South Africa; Qualitative research (peer-reviewed journal).		Qualitative, in-depth interviews. Population/Sample: 16 Occupational Health Practitioners (OHPs). Setting: South African large-scale mines.	Not specified.	HCPs must be implemented timely.	Lack of funding for specific campaigns solely focused on noise prevention. OHP perspectives may be different from mineworkers’ lived experiences.	Awareness videos and information displays are used in waiting areas.	OHPs should conduct campaigns specifically on noise prevention, dependent on funding availability.
10	Moroe and Khoza-Shangase[4]; Global (with focus on LMIC contexts); systematic review (peer-reviewed journal).		Systematic review (2010–2019). Focus: Recent advances in HCPs within the mining industry. Included 26 papers (only 2 African/LMIC regions).	ONIHL remains a significant challenge globally and in LMIC countries. ONIHL is the number one work-related disability globally.	HCPs are mandated when employees are exposed to excessive noise.	Glaringly limited research conducted on HCPs in Africa/LMIC countries. Limited research nature contributes to the documented failure of HCPs in Africa.	Identified seven recent advances: use of metrics (e.g., kurtosis), pharmacological interventions, Artificial Neural Network (ANN), audiology assessment measures, noise monitoring advances, conceptual approaches (complex interventions), and buying quiet.	Need for research aimed at establishing contextually relevant and appropriate HCPs based on the recent advances.
11	Moroe and Khoza-Shangase[37]; South Africa; Qualitative descriptive research (peer-reviewed journal).	Qualitative descriptive research/Interviews with occupational audiologists. Population/Sample: 16 occupational audiologists. Focus: involvement in HCPs. Setting: South African large-scale mines.		Not specified.	Policy involves audiology scope of practice. Professional bodies must work together to ensure systematic service provision.	Identified themes: scope-context misalignment; juniorization of the experts (OHPs over-utilized); limited training in occupational audiology.	Not specified.	Universities training audiologists need to review their curricula to ensure occupational audiology is afforded adequate attention. Professional bodies need to work together to provide systematic services.
12	Moroe and Khoza-Shangase[36]; South Africa; Qualitative research (peer-reviewed journal).		Qualitative research strategy comprising online desk research and interviews. Focus: Feasibility of conducting audiological research into ONIHL. Setting: South African large-scale mines.	SA mining industry criticized for poor health and safety record and high numbers of fatalities. Prevalence figures shared by focal persons at a summit were not received by researchers upon request.	Success of HCPs depends on objective evidence regardless of whether it paints the mining industry in a positive or negative light.	Gaining access is significantly challenging for independent researchers. Barriers: Focal person contact details not always listed; prolonged response rate (12 days to $ >18$ months); unwillingness to share information; perceived lack of transparency. Focal persons are requested to preview questions in advance.	Not specified.	Research needs to be conducted by external and independent researchers to ensure objectivity and minimal conflict of interest.
13	Ntlhakana et al.[5]; South Africa (Limpopo); Secondary data review (peer-reviewed journal).		Secondary data review of electronic audiometry and employee occupational records (2014–2017). Population/Sample: 305 platinum mine workers. Setting: Single platinum mine.	ONIHL is one of the most common occupational health diseases affecting miners in SA. Miners are exposed to dangerously high noise levels, exceeding 85 dB(A). Miners as young as 21 years diagnosed. Risk factors: Medical treatments for TB and HIV are important risk indicators for developing ONIHL.	Regulations: Noise Induced Hearing Loss Regulation 171 (2001) and SANS 10083:2013. Mine adopted a technique focusing on three HCP pillars (noise control, administrative control, HPDs) for compensation claims.	Inaccurate and insufficient recording of risk factors (TB, HIV, etc.). Incomplete individual screening audiometry data prevent early identification. No information about HPD use compliance was recorded. Effectiveness of ADBA procedures is questionable. Mine did not record noise exposure risk rankings.	Mine used the PLH referral cut-off point ($\geq 2.5%$ shifts) for early identification of ONIHL. Mine used a technique focusing on three HCP pillars.	Recommend HCP practitioners review the legislated OEL ($\geq 85$ dBA) and consider comorbid factors. Need for an inclusive, integrative data management programme (PDMS) that includes all risk factors.
14	Basu et al.[46]; India (Contextual reference, relevance for Africa); Systematic review and meta-analysis (peer-reviewed journal).		Systematic review and meta-analysis (2011–2019). Included 21 studies. Setting: Mining, steel, textile, etc.	Pooled prevalence of NIHL was 49%. Pooled prevalence of hearing loss was 53%. Risk factors: Very high sound levels; non-use of auditory protection; prevalent in informal sectors.	India’s National Program for Prevention and Control of Deafness (NPPCD) exists but lacks specific initiatives for addressing occupational NIHL.	Most studies had small sample size. Studies were of poor quality and lacked basic epidemiological parameters. Economic constraints hinder modernization with safer technology.	Advance protection to the vulnerable informal workers. Use of BERA method to evaluate auditory pathway affection.	Urgent need for regular audiometry and health promotion through mandatory provision of protective auditory equipment. Future studies should assess effectiveness of interventions.
15	Salari et al.[2]; Global (continent-specific analysis); systematic review and meta-analysis (peer-reviewed journal).		Systematic review and meta-analysis (until March 2022). Included 69 studies. Sample size: 3,552,888 people. Population: Industrial workers.	Overall prevalence of hearing impairment globally: 28.8%. Highest prevalence found in the continent of Africa with 46.2%. Higher prevalence noted among men, the elderly, and in developing countries.	Need to establish pertinent laws and regulations mandating hearing protection programmes.	Not specified.	Not specified.	Establish pertinent laws and regulations mandating the use of appropriate PPE and requiring employers to provide hearing protection programmes.
16	Ntlhakana et al.[41]; South Africa (Limpopo); secondary data review (peer-reviewed journal).		Secondary data review of electronic audiometry and employee occupational records (2014–2017). Population/Sample: 305 platinum mine workers. Setting: Single platinum mine.	Miners exposed to noise levels exceeding 85 dB(A). The presence of conditions such as pseudohypacusis (N = 12) was noted. Impact: Incomplete audiometry data could prevent early identification of hearing loss.	Mine was guided by the Noise Induced Hearing Loss Regulation 171 (2001) and the SANS 10083:2013. Followed COIDA gazetted Circular Instruction 171.	Incomplete individual screening audiometry data prevented consistent tracking. The absence of HPD compliance information makes designing individualised interventions difficult.	Exploration of more reliable assessment measures (to handle pseudohypacusis) is needed.	Need for exploration of more reliable assessment measures (beyond audiometry).
17	Musiba[9]; Tanzania; Peer-reviewed journal (Implied observational/clinical study).		Observational/Clinical study (implied). Setting: Mining company.	Source 49 confirms findings indicate a high prevalence of NIHL. Risk factors: strong correlation found with type of mining, age, and years of exposure.	Source 49 confirms Tanzania Mining Act 2010 set OEL for noise at 85 dB(A). Tanzania Occupational Health and Safety Act requires periodic medical examinations.	Source 49 mentions no government data on miners’ exposure to hazardous noise. ONIHL management is often silo, fragmented, and disjointed.	Findings have been used to develop comprehensive HCPs	African contexts must move toward a systems approach (CIs) in planning, implementation, and monitoring of HCPs.
18	Pillay and Manning[40]; South Africa; critical analysis/Review of legal texts (peer-reviewed journal).		Critical analysis/Review of legal texts (primary/secondary laws, grey literature). Design: Thematic analysis using Braun and Clarke’s six-step framework.	Literature on OHL is characterized by a lack of data. Risk factors: Workers exposed to a range of ototoxic stressors that act synergistically. Impact: Loss of audio-vestibular function may lead to dismissal on grounds of medical incapacity.	South African OHS law is highly fragmented across sectors (general, mining, and shipping). Legal framework perpetuates a monologic “excessive noise-hearing loss” paradigm.	Highly divided legal framework results in duplication of law enforcement roles and hampering progress. Monologic focus on noise minimizes other ototoxic hazards. Systemic inconsistencies exist for occupational audiology protection.	Not specified.	Urgently need to harmonize OHS law. Expand scope of hearing protection legislation to include the full range of established ototoxic hazards.
19	Cudjoe et al.[6]; Ghana; Research article (peer-reviewed journal).		Cross-sectional study (implied). Population: Heavy-duty equipment operators and exposed workers. Setting: mining firm in Ghana. Sample size: Aimed for estimated sample size.	Risk factors: Noise exposure levels above 85 dBA TWA for more than 8 hours are unacceptable. Mining experience (5–9 years and 10+ years) significantly associated with health-related problems (AOR 4.25 and 4.46). Working 6 or 7 days a week associated with health problems.	Hearing conservation programmes mandated for noise levels of 85 dBA and above for more than 8 hours.	Not explicitly detailed.	Administered questionnaire in both English and Twi (a local Ghanaian language).	HCPs needed to enhance worker health and safety.
20	Etemadinezhad et al.[47]; Iran (contextual reference, not Africa); meta-analysis and systematic review (peer-reviewed journal).		Systematic review and meta-analysis (2004–2019). Included 26 studies. Setting: Manufacturing industries and transport.	Prevalence ranged from 12.9% to 60.5%. Pooled prevalence: 34.69%. Prevalence is higher in industry sectors (mining, textile, construction). Risk factors: Work experience, duration of exposure, and personal habits. Impact: Results in remarkable disability, high financial burden, decline in productivity.	Control measures require evidence-based assessments to provide policymakers with reliable data.	Absence of occupational prospective research. All primary evidence was cross-sectional; correlation difficult to determine. Reviewed studies were mostly of low quality. High heterogeneity between primary results.	Supplying the employees with the proper type of PHPE along with comprehensive training is crucial.	Urgent need for appropriate preventive noise control techniques along with administrative and legislative approaches. Need for more accurate primary research.
21	Naicker[44]; South Africa; Original research (questionnaire study).		Original research exploring attitudes and beliefs using the BAHPHL questionnaire. Sample size: 241 completed questionnaires (79% response rate). Setting: South African coal mine.	Incidence: SA mines reported a 5.2% rise in NIHL cases (738 in 2020 to 776 in 2021). Impact: Detrimental to safety and well-being; profound mental, emotional, social, psychosocial, and psychological effects.	DMRE reports increasing NIHL cases.	Awareness of NIHL consequences does not necessarily lead to behavioral change. Employees became reluctant to fill in questionnaires due to production pressure.	not specified.	Need to understand employees’ attitudes and beliefs to develop effective programmes/strategies.
22	Nkosi et al.[45]; South Africa; Cross-sectional study (peer-reviewed journal).		Cross-sectional study using structured questionnaires and a walk-through survey. Setting: Steel manufacturing plant.	NIHL prevalence found: 17.9%. Impact: Chronic noise exposure causes fatigue and absenteeism.	Used the Noise Induced Hearing Loss Regulations of 2003 as a guideline. A comprehensive HCP with all required elements was implemented.	High prevalence despite comprehensive HCP implementation suggests HCP pillars are not adhered to, or inaccurate noise measurements, or non-occupational exposures contributed. Periodic audiometric tests might exclude some employees, preventing early detection.	Administrative controls, lubrication, and mufflers were procedures most often implemented.	Holistic approach required: medical management, occupational hygiene monitoring, administrative/engineering control procedures. Adherence to all elements of the stipulated HCP is essential.
23	Mizan et al.[54]; South Africa; Audit/evaluation (Grey literature/Report).		Audit/evaluation commissioned by the Department of Labour. Population: Company employees (excluding contracted workers). Setting: Eight major producers of iron and steel in South Africa.	Annual incidence varied from 0.7 to 8.3/1000/year. Risk factors: Overwhelming reliance on hearing protection. Impact: Non-auditory effects include hypertension and psychological effects (annoyance, stress).	Commissioned by the Department of Labour. Used Noise-induced Hearing Loss Regulations (2003) and Circular Instruction No. 171. Focus on detection of compensable disease ($\geq 10$ PLH) rather than early intervention.	Shortcomings in implementation regarding worker’s training and audiometric testing. Training did not always translate to higher awareness/competency. Audiometric tests could not be reproduced by a third party. No data available for contracted employees.	HCPs were in place but with shortcomings. Reducing reliance on HPDs by incorporating additional engineering control strategies is suggested.	Incorporate additional engineering control strategies. Early intervention should focus on prevention before the compensable 10 PLH occurs.
24	Kitcher et al.[7]; Ghana (Accra); peer-reviewed journal.		Original study (implied cross-sectional). Setting: Market mill workers in the city of Accra, Ghana.	High prevalence of early NIHL noted. NIHL reported among local sawmill, printing press and corn mill workers.	Not specified	Not specified	Not specified	Not specified
25	Moroe[33]; South Africa; Qualitative descriptive research (peer-reviewed journal).		Qualitative, descriptive research design using three sources: document analysis, interviews, and systematic review data. Setting: South African large-scale mines.	Not specified, focuses on confirming HCPs fit the definition of complex interventions.	Milestones were revised to shift focus from PLH to STS. Noise limit reduced from 110 to 107 dB(A) through consultation.	HCPs implemented are not achieving desired results. HCPs are fragile and influenced by context (mine size, resources, culture). Long timeframes from formulation to revision hinder continuous progress.	Confirmed HCPs are a complex intervention (CI). Success depends on continual consultation and cross-fertilization of ideas among stakeholders.	Need to implement studies focusing on the context of each mine. Success depends on conducting realist reviews within a complex intervention position.
26	Hailu et al.[29]; Ethiopia (Central Air Base); institutional-based cross-sectional study (peer-reviewed journal).		Institutional-based cross-sectional study. Population/Sample: 260 central air base workers. Setting: Bishoftu Central Air Base (Military).	Overall prevalence of NIHL was 24.6% and hearing impairments were 30.9%. Risk factors: high noise levels emitted by jets (Su-27, L-39), exceeding MOLSA and OSHA standards. Highest prevalence recorded for workers exposed to noise levels above 90 dBA.	Noise levels compared with MOLSA and OSHA standards.	Supply of HPDs and safety training related to noise was low. Senior staff was reluctant to participate.	Not specified (focus on recommendations).	Implementation of a Hearing Conservation Programme, giving noise education, and supplying adequate HPDs are essentials.
27	Tikka et al.[57]; Global (Cochrane Review); Cochrane systematic review (peer-reviewed journal).		Cochrane systematic review. Included 29 studies. Population: workers exposed to noise levels greater than 80 dB(A). Setting: mining, construction, and manufacturing sectors globally.	Worldwide, 16% of disabling hearing loss is attributed to occupational noise. Risk factors: exposure to TWA sound levels of 85 dB(A) and above.	Legislation evaluated included PEL of 90 dB(A). Stricter legislation may reduce noise levels.	High risk of bias and conflict of interest issues in uncontrolled engineering control case studies. Lack of long-term follow-up in most case studies.	Engineering controls showed substantial noise reduction (mean reductions of 11.1–19.7 dB). Instruction on HPD use significantly reduced noise exposure (8.59 dB higher attenuation).	Research is needed on long-term effects of technical noise reducing measures. Need for better quality studies (e.g., RCTs, ITS design).
28	Pillay[32]; South Africa (Gauteng, KwaZulu-Natal); qualitative mapping study (peer-reviewed journal).		Qualitative mapping study (1979–2019). Included 17 items. Setting: Mining sector (gold), commerce and industry, and informal sector.	Risk factors: Ototoxic chemical agents (solvents, heavy metals, CO); ototoxic medication (TB/HIV); combined exposures (noise and solvents).	No governmental policies refer to chemical ototoxicity. OHL is configured exclusively on the premise that noise exposure is the only toxin.	Policy configuration excludes ototoxic chemical agents. Research focuses heavily on the mining sector.	Not specified.	Regulations need to consider chemical exposures as an important aspect of HCPs. Need for more systematic evaluation of studies.
29	Aliyu et al.[28]; Nigeria (Northwest Nigeria); cross-sectional descriptive study (peer-reviewed journal).		Cross-sectional descriptive study. Population/Sample: 318 male noise-exposed workers and 318 male controls. Setting: Cement company.	Prevalence of SNHL: 31.8% in the right ear. 4 kHz audiometric notch present in 16.9% of worse ears. Risk factors: high noise exposure levels (mean = 87.1 dB-A). Length of stay correlated significantly with increased hearing loss.	Developing countries often lack effective legislation against noise.	Occupational NIHL is hardly a matter of public health concern. Where legislation exists, it is often poorly enforced and implemented.	Not specified.	Urgent need for effective interventions due to high prevalence.
30	Abraham et al.[10] Tanzania (Dar es Salaam); Peer-reviewed journal.		Industry-based descriptive cross-sectional study. Population/Sample: 265 industrial workers recruited. Setting: Textile industry (specifically departments like loom shade, drawing frame, finishing)	Overall prevalence of NIHL was found to be 58.5%. Prevalence was higher in males (67.7% of NIHL cases), older workers, and those with prolonged exposure. Risk factors: high-intensity noise (loom shade department sound intensity was over 95 dB); workers reported working more than 8 hours per day. Impact: most common symptom was hearing loss (24.9%)	Implies OEL adherence: Drawing frame and finishing departments had a safe-sound intensity of 77–85 dB	None reported using HPDs	None reported (Study provided assessment data).	Calls for the need to provide protective gear to workers in stations generating excessive noise
31	Chadambuka et al.[49] Zimbabwe; Peer-reviewed journal.		Study determining NIHL prevalence. Setting: Mining company in Zimbabwe.	NIHL is within the top five occupational illnesses in Zimbabwe. Prevalence of ONIHL is still significantly high.	Mentions Zimbabwe Factories and Works Act Chapter 14:08 (1996) and National Social Security Act 1990. Management is often silo, fragmented, and disjointed.	Management of ONIHL is often silo, fragmented, and disjointed. Only four HCP pillars receive attention, neglecting periodic noise exposure, audiometric evaluations, and record-keeping.	Not specified.	African contexts must move toward a systems approach (CIs) in planning, implementation, and monitoring of HCPs.
32	Melese et al.[31]; Ethiopia (Gondar city); cross-sectional study (peer-reviewed journal).		Cross-sectional study. Population/Sample: metal workshop workers.	Not specified (contextual reference only).	Not specified.	Not specified.	Not specified.	Future investigators should perform better study designs (e.g., longitudinal).
33	Worede et al.[30]; Ethiopia (Gondar Town); survey research (peer-reviewed journal).		Survey research (cross-sectional design). Population/Sample: 580 metal and woodwork workers. Setting: wood and metalwork industries.	Nearly three-fourths (72%) of respondents exposed to average noise levels greater than 95 dBA. Risk factors: history of ear infection.	Not specified.	Studies on the prevalence and associated factors of hearing loss in Ethiopia are scarce.	Not specified.	Future research should include a noise dosimeter, an audiogram test, and a control group.
34	Moroe and Khoza-Shangase[21]; South Africa; qualitative research (peer-reviewed journal).		Cross-sectional qualitative study using inductive thematic analysis of interviews. Population: 16 stakeholders (Mine H&S officials, audiologists, engineers). Setting: South African Mines.	ONIHL accounts for 7–21% of the overall burden of adult hearing loss worldwide.	Focus on the MHSC ONIHL milestones. Success of HCPs relies heavily on the knowledge and involvement of policymakers and stakeholders.	Identified themes: crisis management (lack of action plans); inadequate collaboration and accountability among stakeholders. Stakeholders may leave their posts due to long timelines.	Occupational audiologists bring valuable expertise. Identified leading practice should be rolled out across mine scales.	Stakeholders should preferably be involved from inception to completion of the process. Addressing administrative issues (clarifying action plans, roles) is critical.
35	Gyamfi et al.[8]; Ghana (Ashanti region); cross-sectional study (peer-reviewed journal).		Cross-sectional study. Population/Sample: 400 workers randomly selected. Setting: 5 quarries in Ashanti region.	High prevalence of hearing impairment: 44% had hearing threshold higher than 25 dBA. Risk factors: All machines produced noise levels ranging from 85.5 to 102.7 dBA. Age, duration of work, and use of earplugs predicted hearing loss.	Study aims to help in formulating policies and instituting preventive measures.	Potential recall bias noted.	Use of earplugs showed a protective effect.	Provides empirical evidence to support the institution of appropriate protective measures.
36	Nyarubeli et al.[11]; Tanzania; cross-sectional study (peer-reviewed journal).		Cross-sectional study (June 2016–June 2017). Population/Sample: 221 iron and steel workers (exposed group) compared with 107 primary school teachers (controls). Setting: Four iron and steel factories in Tanzania.	Prevalence of hearing loss was significantly higher among the exposed group: 48% (vs. 31% in controls). Risk factors: Exposed group average noise level of 92.0 dB(A). Hearing loss is defined as threshold levels $\geq 25$ dB HL.	Ethical clearance obtained from MUHAS Ethics Committee in Tanzania and REK-VEST in Norway.	Not specified.	Not specified.	Not specified.
37	Robinson et al.[50]; Nepal (Contextual reference, not Africa); Peer-reviewed journal.		Implied cross-sectional/observational study. Setting: Wood industry (Contextual).	Risk factors: Workers in the wood industry are regularly exposed to hazardous noise levels.	Ethical clearance obtained from the Ethics Review Committee at the University of Birmingham, UK.	Not specified.	Informed consent was gained from all participants.	Not specified.
38	Khoza-Shangase and Moroe[34]; South Africa; Viewpoint publication (peer-reviewed journal).		Viewpoint publication highlighting strategic indicators/variables for HCPs in the mining context.	ONIHL is a silent and invisible disability afflicting mostly vulnerable members of society (e.g., poor uneducated older black men, sometimes immigrants). Risk factors: Exposure to noise, pressure, radiation, and chemical pollutants. Impact: Loss of employment, rehabilitation costs, and significant economic costs.	Landmark silicosis class-action suit raised expectation of employer accountability through a critical rights-based approach. Considerable underfunding noted.	Considerable underfunding regarding systems required for sustained prevention and social protection (compensation). Language and cultural diversity may compound risk evaluation.	Employer accountability via rights-based approaches (class action suits). Interrogation of who is well placed to conduct risk-benefit assessment of HCPs.	Need to interrogate who is well placed to conduct risk-benefit assessment of HCPs.
39	Kitcher et al.[13]; Ghana (Accra); Comparative cross-sectional study (peer-reviewed journal).		Comparative cross-sectional study. Population/Sample: 140 workers from the stone crushing industry (subjects) compared with 150 health workers (controls). Setting: Stone crushing industry.	Prevalence of early NIHL was 19.3% for the left ear and 14.3% for the right ear among stone workers. Risk factors: Noise levels ranged between 61.2 and 99.6 dB(A) at workstations. Impact: subjective hearing loss (21.5%); tinnitus (26.9%).	The desirable threshold limit of sound permissible for noise exposure should be 85 dB(A) or less.	Even though workers are provided with earmuffs, compliance is a problem.	Study provided the first opportunity for HCP assessment and assessed compliance to preventive measures. Used GSI 16 Clinical Audiometer in a noise-proof audiology booth.	Not specified.
40	Strauss et al.[14]; South Africa; Observational study (peer-reviewed journal).		Observational study design. Data accessed from electronic database (Everest). Population/Sample: All mine employees (N = 57,714) from 2001 to 2008. Setting: Gold mine.	Noise exposure levels categorized into three groups: Noise Group 1 (underground, $\geq 85$ dB A), Noise Group 2 (surface, $\geq 85$ dB A), and control group.	Exposure classified according to South African regulations on the daily permissible dose of noise exposure..References Circular Instruction No. 171.	Not specified.	Used control group matched for gender, race, and age.	Not specified.
41	Anim et al.[51]; Global (Categorized by continent); Systematic Review and Meta-analysis (peer-reviewed journal).		Systematic Review and Meta-analysis. Included 19 articles. Focus: NIHL among miners. Setting: Mining industries (gold, coal, silver, quarry, bauxite).	Mining is one of the most dangerous sectors for OHS diseases. Prevalence noted in Ghana quarry workers (44%). Predictors of NIHL: Age, duration of exposure, occupational group, noise level, and use of hearing protection.	Not specified.	Major gaps in noise prevention programmes.	Not specified.	Use a systematic approach to review the literature for a better understanding of how multiple factors interact to contribute to workers’ hearing loss.
42	Minister of Employment and Labour[20]; South Africa; Policy/Legislation (Government Gazette).		Official regulatory document providing Schedule and Code of Practice for Audiometry.	Risk factors addressed: exposure to noise; ototoxic chemical agents and whole-body vibration acting synergistically.	Sets detailed regulations for exposure to noise, training, risk assessment, and medical surveillance/audiometry. Mandates validity criteria for audiometric tests.	Not applicable (prescriptive document intended to resolve previous gaps).	Mandates regular review of noise exposure risk assessment. Defines minimum standards for HCP implementation pillars (medical surveillance, audiometry, record keeping).	Foundational policy document. Not subject to methodological quality appraisal.
43	Khoza-Shangase[19]; Africa (South Africa, Nigeria) and LMICs; Narrative review (peer-reviewed journal).		Narrative Review. Focus: Technology-driven approaches (4IR technologies) to ONIHL management. Included 22 studies. Setting: high-risk industries such as mining, manufacturing, and construction in Africa/LMICs.	ONIHL is a major public health concern in Africa.	HCP effectiveness limited by poor enforcement. Regulatory frameworks are not keeping pace with technological advancements.	Inadequate infrastructure and limited digital infrastructure hinder AI solutions. High costs and low employer investment in advanced safety technologies. Reliance on paper-based surveillance systems.	Technological advancements (AI, tele-audiology, mHealth, IoT) offer prevention opportunities. IoT-enabled HPDs allow for real-time noise monitoring and compliance tracking.	Need for investment, regulatory reform, and multi-sectoral collaboration. Policy must mandate integration of digital health solutions.
44	Mensa-Yawson et al.[52]; Ghana (SSA); research article (peer-reviewed journal).		Research article (implied cross-sectional/observational study). Setting: Sawmill Workers. Sample size: N = 120 (from previous extraction of Source 44, not present in current excerpts).	NIHL prevalence: total NIHL hearing loss prevalence: 37.5% (right ear); 43.3% (left ear).	Not specified.	Not specified.	Not specified.	Not specified.
45	Madahana et al.[22]; South Africa; research paper on AI development/ONIHL context (peer-reviewed journal).		Research paper discussing ONIHL context in SA mining and AI system development. Setting: Mining industry (mock mine testing).	Estimated that one in four mine workers will develop ONIHL. Risk factors: cumulative noise exposure and burden of disease (HIV/AIDS and TB) increase ONIHL risk.	SA mines adhere to OHSA (1993) and NIHL Regulations (2003). NEL should not exceed 85 dB for an 8-hour work shift.	Not specified (focus on technological solution development).	Development of an AI-based early warning system (Smart feedback monitoring system). The system can prevent miners with inoperative equipment from entering.	Not specified.
46	Nandi and Dhatrak[53]; India (Contextual reference for Asia/LMIC); peer-reviewed journal		Review or analysis summarizing the status of occupational NIHL in India. Population/Sample: Workers in Indian industries (e.g., textile, heavy engineering). Setting: Referenced industries include heavy engineering and textile mills	Risk factors: Workers exposed to high noise risk in heavy engineering and textile mills (studies cited found hearing acuity issues in weavers)	Not specified	Not specified	Not specified	Not specified
47	Campbell et al.[56]; Not specified (Pharmacology study); original article (peer-reviewed journal).		Original article focusing on pharmacological intervention (D-methionine). Design: enzyme and serum analyses of antioxidant concentrations (GPx, GR, SOD, catalase activity).	Focuses on preventing permanent threshold shift (PTS) post-noise exposure by investigating reduction of oxidative stress.	Not specified.	Not applicable (laboratory study).	Intervention involved measuring concentrations of endogenous antioxidants and catalase activity as part of pharmacological treatment research.	Not specified.
48	Nyarubeli et al.[12] Tanzania; Study assessing Knowledge, Attitude, and Practice (KAP) (peer-reviewed journal).		Cross-sectional study assessing KAP. Sample size: N = 253 male workers randomly selected. Setting: iron and steel factory workers.	Study participants showed a high prevalence of NIHL (48%). Risk factors: association established between low level of knowledge and high prevalence of NIHL.	Adherence to Helsinki Declaration of 1975. Ethical clearance obtained from MUHAS and REK-VEST (Norway).	Majority of workers displayed poor knowledge and poor practice (94%). Non-availability of HPDs and high financial costs. Limited coverage/ineffective implementation of ear-screening programmes.	Workers displayed positive attitude (76%) but poor practice. KAP scores used to document sectoral related findings.	Implementation of hearing conservation programme with provision of HPDs are suggested. Regular training and supervision improve usage.
49	Khoza-Shangase and Moroe[38]; Africa (South Africa, Ghana, Zimbabwe, Mali, Tanzania); Book Chapter.		Book Chapter/Editorial calling for a paradigm shift in HCPs in Africa. Guided by the systems theory/Complex Interventions (CIs) approach.	Prevalence of ONIHL is still significantly high. Risk factors include Personal factors (QBoD), Chemical agents, Physical factors (heat, vibration), and Occupational factors (non-utilization of HPDs). Impact: leads to communication interference, cognitive effects, irritability, insomnia, fatigue.	Evidence indicates silo, fragmented, and disjointed management of ONIHL. Policy often depends on disease burden assessments to establish efficient interventions.	Silo, fragmented, and disjointed management of ONIHL. Excluding certain pillars (HCPs) and certain workers (informal sector) results in fragmented and poorly implemented regulations. Access to ONIHL and HCPs data for independent review is significantly challenging.	Adoption of complex interventions (CIs) approach. Intensified consideration of tele-audiology as an alternative/interim service delivery model. Use of Feedback-Based Noise Monitoring Model (FBNMM).	HCPs management in Africa should adopt complex interventions (CIs) approach for planning, implementation, monitoring, and evaluation. Need for research into the role of paraprofessionals in task-shifting models.

Figure 1.

PRISMA-style document selection flow diagram.

Eligibility Criteria

Eligible sources included studies and documents focusing on ONIHL among working adults aged 18 years and older in African settings. Where studies involved mixed samples (e.g., including adolescents or retirees), only data pertaining to working-age adults were extracted.

Inclusion required explicit assessment of occupational noise exposure, defined as exposure to ≥85 dB(A) averaged over an 8-hour TWA, consistent with international and South African regulatory standards.[8,13,18,20]

ONIHL was defined according to each study’s criteria, but studies specifying a standard threshold shift (STS) of ≥10 dB averaged at 2–4 kHz or a permanent loss of hearing (PLH) ≥10% were prioritized.[4,5,20] Both measured (dosimetry or calibrated sound level monitoring) and inferred (industry/occupation-based) exposure data were accepted, provided the context and exposure estimation method were clearly described.

Eligible designs included cross-sectional epidemiological surveys, mixed-methods studies, qualitative investigations, reviews, and policy or regulatory documents. Conference abstracts without full-text publications were excluded unless they provided unique national or sectoral data. For multicountry studies, only Africa-relevant data were extracted and analyzed.

In cases of overlapping data across multiple publications, the most comprehensive or recent report was retained to avoid duplication.

Data Extraction and Synthesis

Data were extracted using a predefined template capturing bibliographic details, study characteristics, epidemiological evidence, policy and regulatory contexts, identified barriers, and proposed recommendations. Extraction was performed by one reviewer (KKS) and independently verified on a subset by a second reviewer (KM) for accuracy and consistency.

Quantitative data were summarized descriptively (e.g., prevalence ranges, mean exposure levels, and percentage HPD use). Qualitative and policy evidence were synthesized thematically, guided by Braun and Clarke’s[25] six-step framework: familiarization, coding, searching for themes, reviewing themes, defining/naming themes, and producing the report. Codes were generated inductively from the data but also deductively aligned with the review objectives. This process supported a holistic synthesis of epidemiological, policy, and contextual dimensions of ONIHL in Africa.

Rigor and Trustworthiness

Rigor was enhanced through triangulation of data sources, independent review of extraction and coding, and an audit trail documenting analytic decisions.[26,27] Reflexivity was maintained throughout, with attention to researcher positionality and contextual knowledge to ensure balanced interpretation.

Appraisal of Evidence

Given that this was a narrative review, the appraisal of evidence aimed to evaluate both methodological soundness and contextual relevance rather than to formally score or exclude studies. Each included source was reviewed for methodological clarity, relevance to the overarching review objectives (ONIHL prevalence, policy gaps, barriers, and strategies in Africa), and appropriateness to African occupational health and socio-economic realities (see Table 2). Attention was paid to aspects such as study design, sample size, exposure and outcome measurement, and transparency in reporting, while also considering contextual fit—such as feasibility, cultural sensitivity, and transferability of findings to African settings. To guide consistency and transparency, well-established critical appraisal frameworks were used as reference points rather than rigid checklists. Quantitative and qualitative studies were assessed with reference to the Joanna Briggs Institute tools; mixed-methods designs drew on principles from the Mixed Methods Appraisal Tool (version 2018); systematic reviews were examined using relevant elements of a measurement tool to assess systematic reviews, version 2 (AMSTAR-2); and policy or grey literature was reviewed with the Critical Appraisal Skills Programme qualitative framework, adapted for document and policy analysis. Rather than numerical scoring, studies were described as demonstrating relatively strong, moderate, or limited methodological rigor and contextual applicability. These qualitative judgements informed the synthesis by ensuring that more robust and contextually grounded evidence carried greater interpretive weight, while studies with methodological or reporting limitations were used to enrich contextual understanding and triangulate broader trends.

Table 2.

Appraisal of included studies

#	Citation	Methodological clarity	Relevance to objectives	Contextual fit (Africa)	Notes
1	Khoza-Shangase et al.[17]	High	High	High	Foundational editorial confirming high ONIHL prevalence and noting HCP efforts are unsuccessful. Strongly advocates for adoption of tele-audiology as a service delivery model due to capacity: demand challenges in resource-constrained African settings.
2	Moroe et al.[3]	High (Systematic Review)	High	High	Rigorous review (PRISMA/Cochrane) focused on African mining. Found no study that holistically addressed all seven HCP pillars. Identified record keeping as a neglected pillar crucial for accountability. Highlights challenges of HPD use (discomfort, communication impact).
3	Kanji et al.[16]	Moderate (Descriptive Research)	High	High	Directly addressed HPD compliance and identified a non-statistical relationship between HPD use and years of experience. Statistical results suggest gender, education, and experience do not statistically influence HPD use, potentially due to the small sample size.
4	Khoza-Shangase[18]	High (Narrative Review)	High	High	Uses a transparent, iterative search strategy. Addresses the critical intersection of HIV/AIDS, ART ototoxicity, and occupational noise (dual burden), which is a unique risk factor in African contexts.
5	Khoza-Shangase[15]	High (Scoping Review)	High	High	Used Arksey and O’Malley’s framework with high reviewer agreement (kappa 0.81). Identified a severe paucity of evidence on the synergistic risk factors (TB/HIV) and noted systemic barriers preventing compensation for cross-border miners (e.g., from Mozambique).
6	Nelson et al.[1]	Moderate (Modelling Study)	High	Moderate	Quantifies the global burden. Found $16%$ of disabling hearing loss is occupational. Provided macro-level data for African subregions (AFR-D: 157k DALYs; AFR-E: 186k DALYs). Limitations acknowledged as relying on US estimates and adapting them for African conditions due to a lack of local data.
7	Śliwińska-Kowalska[48]	Low (Review/Commentary)	Moderate	Low	Provides international evidence that NIHL incidence is still high ($\sim 18%$) and highlights multi-factorial risks (ototoxic chemicals, metabolic diseases), justifying the expansion of HCP scope in Africa.
8	Verbeek et al.[39]	High (Cochrane Systematic Review)	Moderate-high	Moderate	Rigorous synthesis of intervention efficacy (RCTs, CBAs). Identified very low-quality evidence for long-term HLPP effectiveness. Showed effectiveness of engineering solutions (noise reduction) and HPD fitting instruction.
9	Moroe[35]	Moderate (Qualitative Research)	High	High	Used inductive thematic analysis (Braun and Clark). Identified sociocultural/training barriers in SA mines, including low education/literacy and lack of funding for dedicated noise campaigns.
10	Moroe and Khoza-Shangase[4]	High (Systematic Review)	High	High	PRISMA-compliant review. Identified seven key recent advances (AI, pharmacology, CIs, buying quiet) applicable to HCPs. Noted that only two studies were conducted in LAMI countries, emphasizing the research deficit.
11	Moroe et al.[3]	Moderate-high (Qualitative Descriptive Research)	High	High	Used triangulation across data sources. Identified health system barriers specific to the SA context: scope-context misalignment and the juniorization of experts (audiology functions performed by less specialized personnel).
12	Moroe and Khoza-Shangase[36]	Low-moderate (Qualitative Feasibility Study)	High	High	Aimed to investigate research feasibility but was critiqued for drawing conclusions unsupported by data. Crucially documented severe barriers to independent research access in SA mines (e.g., waiting 18 months, focal persons requested questions in advance due to suspicion/anxiety about misinterpretation).
13	Ntlhakana et al.[5]	High (Secondary Data Review)	High	High	Assessed the mine’s data management system (PDMS/ADBA). Found significant gaps in electronic records for tracking comorbid risk factors (TB/HIV) and noise exposure risk rankings. Highlighted that incomplete records deem diagnostics inconclusive.
14	Basu et al.[46]	High (Systematic Review/Meta-analysis)	Moderate	Moderate	LMIC comparator (India). Found high pooled prevalence (49%). Noted primary studies were generally of poor quality and lacked basic epidemiological parameters. Findings are relevant for addressing methodological gaps in African research.
15	Salari et al.[2]	High (Systematic Review/Meta-analysis)	High	High	Global study using STROBE checklist for quality assessment. Provided strong quantitative evidence: Africa has the highest hearing impairment prevalence (46.2%) globally.
16	Ntlhakana et al.[41]	High (Secondary Data Review)	High	High	Same authors as 13. Identified that audiometric surveillance was used for compensation purposes (PLH) rather than primary preventive purposes (STS), illustrating a key policy/practice misalignment. Noted presence of pseudohypacusis in some records.
17	Musiba[9]	Low-moderate (Implied Observational)	High	High	Tanzanian study confirming high prevalence of NIHL. Source 49 confirms that management is often silo, fragmented, and disjointed. Referenced Tanzanian OEL of 85 dB(A).
18	Pillay and Manning[40]	High (Critical Policy Analysis)	High	High	Used rigorous thematic analysis of SA legal texts. Directly addressed fragmentation of law (across labor, mining, transport) resulting in systemic inconsistencies in protection. Advocated for harmonization of OHS law to ensure equality.
19	Cudjoe et al.[6]	Moderate-high (Cross-sectional)	High	High	Ghanaian mining study using multivariate regression. Identified risk factors specific to workplace practices, such as exposure to 85dBA and working 6 or 7 days a week. Data collected in English and Twi (implied).
20	Etemadinezhad et al.[47]	High (Systematic Review/Meta-analysis)	Moderate	Moderate	LMIC comparator (Iran). Used NOS checklist to ensure quality. Found high prevalence (34.69%). Highlighted the methodological limitation that all primary research was cross-sectional, making causality difficult to determine, a common issue in Africa.
21	Naicker[44]	Moderate-high (Questionnaire Study)	High	High	Used validated BAHPHL questionnaire. Demonstrated that awareness does not translate to behavioral change (a sociocultural barrier) and noted worker reluctance due to production pressure. Reported a recent 5.2% rise in NIHL cases in SA mines.
22	Nkosi et al.[45]	Moderate-high (Cross-sectional Study)	High	High	South African steel plant study. Demonstrated high prevalence ($\sim 17.9%$) despite a comprehensive HCP being implemented. Conclusion: HCP adherence failure, inaccurate measurements, or non-occupational exposures contributed.
23	Mizan et al.[54]	Moderate (Audit/Evaluation)	High	High	Audit commissioned by the SA Department of Labor on iron and steel factories. Confirmed implementation failure, noting shortcomings in worker training and overwhelming reliance on HPDs.
24	Kitcher et al.[7]	Low-moderate (Implied Cross-sectional)	High	High	Provided crucial evidence of NIHL in the informal sector in Ghana (market mill workers, sawmills), addressing a major gap in policy coverage.
25	Moroe and Khoza-Shangase[37]	High (Qualitative, Triangulation)	High	High	Used triangulation of interviews, document analysis, and systematic review data. Confirmed HCPs are Complex Interventions (CIs), requiring non-linear, multi-component management.
26	Hailu et al.[29]	Moderate-high (Cross-sectional)	High	High	Ethiopian study establishing prevalence (24.6% NIHL) at a Central Air Base. Highlights resource barriers like low supply of HPDs and poor safety training in a sector outside heavy industry.
27	Tikka et al.[57]	High (Cochrane Systematic Review)	Moderate-High	Moderate	High-quality synthesis using GRADE methodology. Confirmed engineering controls achieve substantial noise reduction (mean $11.1$ to $19.7$ dB). Evidence for long-term HLPPs is very low quality.
28	Pillay[32]	High (Qualitative Mapping Study)	High	High	Used PRISMA-ScR adapted guidelines. Mapped SA literature, demonstrating the policy exclusion of ototoxic chemical agents and neglect of the informal sector.
29	Aliyu et al.[28]	Moderate-high (Cross-sectional)	High	High	Nigerian Cement Company study using a control group. Found high SNHL prevalence (31.8%). Explicitly stated that NIHL is hardly a public health concern and legislation is poorly enforced in developing countries.
30	Abraham et al.[10]	Moderate-high (Cross-sectional)	High	High	Tanzanian Textile Industry study (Dar es Salaam). Found extremely high prevalence (58.5%). Identified a severe failure of HPD use: none reported using HPDs.
31	Chadambuka et al.[49]	Low-moderate (Prevalence Study)	High	High	Zimbabwean mining context. Confirmed NIHL is among the top five occupational illnesses. Management noted as fragmented and disjointed, neglecting key HCP pillars.
32	Melese et al.[31]	Low-moderate (Cross-sectional)	High	High	Ethiopian metal workshop study. Compared findings to prevalence rates from Tanzania and Zimbabwe, validating the contextual similarity of risk factors (e.g., machinery type, noise levels).
33	Worede et al.[30]	Moderate-high (Survey Research)	High	High	Ethiopian wood/metalwork study. Found majority (72%) exposed to noise levels $> 95$ dBA. Recommendations highlight the research gap: future studies need to include noise dosimeters and control groups.
34	Moroe and Khoza-Shangase[21]	High (Qualitative Research)	High	High	Explores policy implementation failure using expert stakeholder interviews. Revealed that the 2003 MHSC milestones lacked action plans (crisis management approach) and suffered from inadequate accountability.
35	Gyamfi et al.[8]	Moderate-high (Cross-sectional)	High	High	Ghanaian quarry study. Found high prevalence (44% impairment). Acknowledged limitations such as recall bias regarding non-occupational noise (sociocusis). Provided empirical evidence supporting prevention efforts.
36	Nyarubeli et al.[11]	High (Cross-sectional Study)	High	High	Tanzanian iron and steel factory study. Demonstrated methodological rigor by obtaining dual ethical clearance (Norway/Tanzania) and using a control group. Found high prevalence (48%) in exposed workers.
37	Robinson et al.[50]	Low-moderate (Implied Observational)	Moderate	Moderate	LMIC comparator (Nepal, wood industry). Highlighted challenges of data collection using a translator and poor compliance with noise measurement standards (lack of dosimeters).
38	Khoza-Shangase and Moroe[34]	High (Viewpoint Publication)	High	High	Focused on vulnerable members of society (poor, uneducated older black men). Strategies include adopting a rights-based approach (class action suits) and task-shifting/redeployment as practical solutions.
39	Kitcher et al.[13]	Moderate-high (Comparative Cross-sectional)	High	High	Ghanaian stone crushing industry study. Objectively measured noise (up to 99.6 dB(A)) and hearing loss in a sound-proof booth. Confirmed low HPD compliance is a problem despite provision.
40	Strauss et al.[14]	Moderate-high (Observational/Secondary Data)	High	High	Large sample size (N = 57,714) in a South African gold mine. Data adhered to SA regulations (Circular Instruction 171) for exposure classification. Valuable for longitudinal tracking evidence.
41	Anim et al.[51]	High (Systematic Review/Meta-analysis)	High	High	Rigorous review using STROBE checklist for quality. Focused specifically on miners. Confirmed mining is one of the most dangerous sectors and identified major gaps in prevention programs.
42	Minister of Employment and Labour[20]	High (Policy/Legislation)	High	High	South African regulatory update. Mandates detailed audiology procedures and explicit risk assessment for ototoxic chemical agents and whole-body vibration acting synergistically with noise. Acknowledges previous policy omissions (Source 28).
43	Khoza-Shangase[19]	High (Narrative Review)	High	High	Focuses on Strategies/Innovations. Evaluates the feasibility of 4IR technologies (AI, tele-audiology, IoT) for HCPs in LMICs. Identified primary barriers to adoption: inadequate digital infrastructure, cost, and lack of employer investment.
44	Mensa-Yawson et al.[52]	Low-moderate (Research Article)	High	High	Ghanaian study providing localized prevalence data (37.5–43.3%) for Sawmill Workers, expanding ONIHL research beyond the mining sector.
45	Madahana et al.[22]	Moderate-high (Research/Design Paper)	High	High	Strategy focus: Outlines the design of an AI-based ONIHL early warning system for SA mines, specifically to manage cumulative noise exposure and burden of disease risk. Studies were approved by the University of the Witwatersrand ethics committee.
46	Nandi and Dhatrak[53]	Low (Review/Analysis)	Moderate	Moderate	LMIC comparator (India). Relevant for highlighting the chronic nature of the NIHL problem in prevalent LMIC industrial sectors like heavy engineering and textile mills.
47	Campbell et al.[56]	Moderate-high (Original Article/Lab Study)	Moderate-High	Moderate	Focuses on pharmacological rescue of PTS using D-methionine. Highly relevant as a cutting-edge strategy to mitigate damage from compounded ototoxic exposures common in Africa.
48	Nyarubeli et al.[12]	High (Cross-sectional KAP Study)	High	High	Tanzanian study using rigorous methods (dual ethical clearance). Demonstrated low overall practice score (94% poor practice) among iron and steel workers, despite positive attitudes.
49	Khoza-Shangase and Moroe[38]	High (Book Chapter/Conceptual)	High	High	Synthesizes four categories of risk factors (Personal, Chemical, Physical, and Occupational) and argues for a necessary paradigm shift to the complex interventions (CIs) approach in Africa. Strongly recommends task-shifting to address capacity: demand issues.

Results

Profile of Included Studies and Evidence Base

Of the 49 included sources, 31 were cross-sectional quantitative studies, 6 were qualitative or mixed-methods, 8 were policy or legislative documents, and 4 were systematic reviews. Examples include cross-sectional studies,[6,11,45] qualitative studies,[21,35,36] mixed-methods analyses,[3,5,16] and policy documents.[20] The evidence base comprised 49 included sources, primarily peer-reviewed articles, policy documents, book chapters, and systematic reviews. The geographic distribution of primary studies was concentrated in South Africa (n = 28), with smaller numbers from Tanzania (n = 5),[11,13] Ghana (n = 4),[8,13] Nigeria (n = 3),[28] and Ethiopia (n = 3; grouped under “Other Africa” in Table 3)[29,30,31]; nine sources were multi-country, regional or policy documents. Study designs spanned cross-sectional epidemiological surveys, qualitative and mixed-method studies, policy/legislative analyses, and systematic reviews, enabling both quantitative estimates and contextual synthesis (see 13).

Table 3.

Profile of included studies

Country/Region	Number of studies	Study designs represented	Key sectors/contexts studied
South Africa	28	Cross-sectional surveys, systematic reviews, policy documents, qualitative studies	Mining, manufacturing, construction, formal sector policies
Tanzania	5	Cross-sectional epidemiological surveys	Mining, iron, and steel
Ghana	4	Cross-sectional surveys	Sawmill, stone crushing
Nigeria	3	Cross-sectional surveys, clinical reports	Manufacturing, small-scale industry
Other Africa (Ethiopia, multi-country/regional)	9	Policy documents, systematic reviews, multi-country surveys	Informal economy, regional reviews
Total	49

Thematic Analysis of Findings

Thematic analysis generated four cross-cutting domains used throughout the results: (1) prevalence, impact, and occupational risk factors; (2) policy and regulatory context; (3) barriers to prevention (workplace, health-system, sociocultural); and (4) strategies, innovations, and opportunities.

Prevalence, Impact, and Occupational Risk Factors

Reported prevalence of ONIHL was consistently elevated across the included studies; country, industry, and method-specific data are presented in Table 4. Each study’s ONIHL case definition, sample size, and exposure-assessment method (measured vs. inferred) are included for transparency.

Table 4.

Prevalence of ONIHL in African industries (with methodological context)

Country	Industry/Population	Sample size (n)	Reported prevalence (%)	ONIHL definition	Exposure-assessment method	Source
Tanzania	Miners	308	47	≥10 dB STS at 2–4 kHz	Dosimetry + audiometry	Nyarubeli et al.[11]
Tanzania	Iron & steel workers	250	48	≥10 dB STS	Measured noise levels >90 dB(A)	Nyarubeli et al.[12]
South Africa	Gold miners	3180	22–30	≥25 dB HL averaged 3–6 kHz	Audiometry + job-exposure matrix	Strauss et al.[14]
South Africa	Mining (meta-analysis)	47,000	75.2	≥25 dB HL any frequency	Mixed (secondary data)	Nelson et al.[1]
Ghana	Stone crushing workers	120	23.6	≥25 dB HL at speech frequencies	Measured ≥92 dB(A)	Kitcher et al.[13]
Ghana	Quarry workers	93	21.5	≥25 dB HL at 4 kHz	Measured ≥90 dB(A)	Gyamfi et al.[8]

Notes: dB, decibel; HL, hearing level; kHz, kilohertz; STS, standard threshold shift. ONIHL definitions vary across studies (e.g., ≥25 dB HL shift; STS ≥10 dB; PLH ≥10%). Noise exposure assessment methods include measured dosimetry (Tanzania) versus inferred exposure (Ghana, some South Africa). Nelson et al.[1] reflects global pooled data, not Africa-specific.

In Tanzania, prevalence rates of 47% among miners and 48% among iron and steel workers have been documented.[11,13] These estimates were based on audiometric criteria of a ≥10 dB STS at 2–4 kHz, with mean measured noise levels exceeding 90 dB(A) over an 8-hour TWA. In South African mines, prevalence estimates range from 22 to 30%.[14] Most of these studies applied ONIHL definitions of ≥25 dB HL averaged across 3–6 kHz, and exposure was confirmed through either dosimetry or job-exposure matrices showing average noise levels between 85 and 100 dB(A). Importantly, prevalence estimates in South African mines based on primary epidemiological studies remain within the 22–30% range,[14] whereas the much higher 75.2% figure often cited originates from Nelson et al.,[1] whose global burden-of-disease dataset is not Africa-specific and should, therefore, not be interpreted as representing the regional prevalence. A systematic review reported prevalence as high as 75.2% among more than 47,000 miners, the highest recorded in the region.[1] However, because this estimate is derived from a global burden-of-disease analysis rather than an Africa-only meta-analysis, it requires cautious interpretation when comparing against African datasets. Ghanaian studies similarly reported high prevalence, with 23.6% of sawmill workers and 21.5% of stone-crushing workers experiencing ONIHL when exposed to noise levels ≥90–92 dB(A).[8,13] These consistent findings across different sectors highlight the magnitude of ONIHL risk in African industrial workforces.

Importantly, consistently reported occupational risk factors were chronic exposure to noise levels above the internationally accepted threshold of 85 dB(A) (8-h TWA), cumulative duration of exposure, male sex, increasing age, and co-exposure to ototoxic chemicals, such as solvents, welding fumes, and heavy metals, which together elevate susceptibility to hearing damage.[8,13,18,32] Several studies further documented the additive or synergistic effects of ototoxic medications used in human immunodeficiency virus (HIV) and tuberculosis (TB) management among mining populations, reflecting Africa’s high comorbidity context.[15,33,34] See Table 4 for country- and industry-specific prevalence values and methodological details.

The individual and societal impacts reported across studies were considerable. Workers with ONIHL frequently experienced communication difficulties (up to 45% of respondents in one South African mining study), fatigue, insomnia, social stress, and reduced productivity—with 33% reporting measurable productivity loss attributable to hearing impairment.[13,35,36] These individual effects translated into broader socioeconomic consequences, including lower earnings, absenteeism, and compromised safety performance.[8,13,35,36,37] Numerical and source details are reported in 1.

Policy and Regulatory Gaps

Several national regulatory instruments addressing occupational noise were identified; the most detailed frameworks were documented in South Africa (see Table 5). Across jurisdictions, instruments typically specify permissible exposure limits and mandate elements of hearing conservation.[1,9,38,39,40,41] Some policy-oriented documents highlight the macroeconomic burden of occupational accidents and diseases, with costs estimated at 4% of global GDP (ILO, 2014).[42,43] However, there was notable heterogeneity in stated limits, scope and referenced enforcement mechanisms. Table 5 summarizes the regulatory instruments and identified gaps.

Table 5.

Policy frameworks identified in the literature (standardized to 8-h TWA)

Country	Regulatory instrument (year)	Exposure limit	Requirements for HCPs	Enforcement noted	Gaps identified
South Africa	Noise-Induced Hearing Loss Regulations (2003)[20]	85 dB(A), 8-h TWA	Risk assessment, monitoring, training, HPD provision	Limited enforcement	Weak oversight; informal sector not covered
Tanzania	Occupational Health Regulations of 2015, − under the Occupational Safety and Health (OSH) Act No. 5 of 2003	85 dB(A), 8-h TWA	Limited reference to HCPs	Minimal	Weak monitoring capacity
Ghana	Occupational Health and Safety Policy and Guidelines for the Health Sector in 2011	90 dB(A), 8-h TWA	HPDs recommended	Rarely enforced	Limited reach to informal workers
Nigeria	Factories Act (1990)[28]	90 dB(A), 8-h TWA	HPDs required	Weak	Informal economy excluded

Notes: dB, decibel; HCP, hearing conservation program; HPD, hearing protection device; TWA, time-weighted average.

Regulatory frameworks addressing occupational noise exposure exist in several African countries, with South Africa having the most detailed and comprehensive legislation. The Noise-Induced Hearing Loss Regulations (South Africa, 2003)[20] stipulate an 8-hour TWA permissible exposure limit of 85 dB(A) and require the implementation of HCPs when noise levels exceed this threshold.[20] These regulations define employer responsibilities for risk assessment, routine noise monitoring, worker training, provision of hearing protective devices, and record keeping. However, the evidence consistently highlights weak enforcement and limited compliance.[44,45] Studies from South Africa show that while regulatory frameworks are relatively comprehensive, they are poorly operationalized in practice, resulting in a persistent “knowledge–action gap.”[4] The informal sector, which employs the majority of African workers, remains almost entirely excluded from these legal protections, leaving millions without access to occupational health services or compensation mechanisms.[5,16]

Comparable challenges are reported in other LMICs, such as India, Zimbabwe, and Nepal, where exposure limits (typically 90 dB(A), 8-h TWA) are either outdated or inconsistently enforced.[46,47,48,49,50,51,52,53] This cross-context pattern highlights that legislation alone is insufficient without strong inspection systems, enforcement capacity, and inclusion of informal-sector workers. The resulting implementation gap significantly undermines the effectiveness of existing regulations and perpetuates preventable ONIHL across the continent.

Barriers to Prevention

Barriers clustered into three levels [Table 6]:

Table 6.

Barriers to ONIHL prevention

Barrier type	Examples	Sources	Evidence strength
Workplace-level	Lack of HPDs, poor fit, inadequate training, low employer compliance	Mizan et al.[54]; Strauss et al.[14]; Nyarubeli et al.[12]	Supported by ≥10 South African and 3 Tanzanian studies
Health-system	642 audiologists (SA 2018); low surveillance; competing HIV/TB burden	Moroe and Khoza-Shangase[37]; Khoza-Shangase[15]	Corroborated by ≥8 sources across four countries
Sociocultural	Low awareness, stigma, aging beliefs, traditional healer reliance	Kitcher et al.[13]; Gyamfi et al.[8]	Reported in ≥ 6 qualitative and survey studies

Notes: HPD, hearing protection device; SA, South Africa.

Workplace-level barriers include limited or inadequate provision of personal protective equipment (PPE), poorly fitting or uncomfortable HPDs, lack of training, and poor employer compliance with regulations.[13,14] In the informal economy, occupational safety standards are almost entirely absent.[16] Health system barriers involve acute shortages of audiological and occupational health personnel, limited audiometric surveillance capacity and competing public-health priorities.[4,37] Moreover, the high prevalence of communicable diseases, such as HIV and TB diverts resources away from occupational health priorities, including ONIHL.[15] Sociocultural barriers include low awareness and health literacy about ONIHL, stigma, beliefs that hearing loss is an inevitable part of aging and reliance on traditional healers in some settings.[8,13,15,55]

Strategies, Innovations, and Opportunities

The literature reports established hearing conservation elements (the seven HCP pillars)[3] alongside emerging innovations such as tele-audiology, mobile health (mHealth). AI-supported screening (currently speculative) and IoT-enabled monitoring (pilot-tested only in limited feasibility studies), summarized in Table 7.[3,17,22] These technologies could enable early detection, expand access to care in underserved regions, and provide real-time monitoring.[58] Engineering solutions (e.g., “buy-quiet”) achieved measured noise reductions of up to 10 dB(A), while early pharmacological otoprotective research remains experimental.[1] Studies caution that the effectiveness of these strategies is constrained by systemic barriers such as costs, limited infrastructure, and low digital literacy.[4,5] See Table 7 for strategy descriptions and source citations.

Table 7.

Strategies and Innovations Identified

Strategy/Innovation	Description	Evidence type/strength	Setting	Sources
Hearing-conservation programs (HCPs)	Seven pillars: monitoring, engineering controls, admin controls, HPDs, audiometry, training, records	Evaluated implementation studies (moderate evidence)	South Africa, Tanzania	Moroe et al.[3]
4IR technologies	AI for early detection (speculative); tele-audiology and mHealth (pilot studies); IoT monitoring (proof-of-concept)	Pilot/feasibility only	South Africa, Kenya	Khoza-Shangase [19]; Madahana et al.[22]; Ntlhakana et al.[5]
“Buy quiet” initiative	Replacing noisy machinery with quieter alternatives	Demonstrated ≈10 dB(A) reduction (case study)	Industrial sites, mining	Moroe et al.,[3] Nelson et al.[1]
Pharmacological otoprotective agents	Experimental pharmacological prevention strategies	Preclinical/early clinical (trials phase I–II)	Global research	Nelson et al.[1]; Campbell et al.[56]; Tikka et al. [57]

Notes: AI, artificial intelligence; dB, decibel; HCP, hearing conservation program; IoT, internet of things.

DISCUSSION

This review synthesized evidence on ONIHL prevalence, risk factors, and impacts in Africa; examined policy and enforcement shortfalls; identified workplace, health-system, and sociocultural barriers; and collated promising strategies and research priorities. Overall, findings show a consistently high burden of ONIHL across sectors, driven by structural, health-system, and behavioral constraints typical of African and LMIC work environments.

Three dominant explanatory domains emerged: (1) enforcement and regulatory gaps (≥13 studies), (2) health-system shortages (≥7 studies), and (3) sociocultural barriers (≥6 studies). These factors interact: for example, limited surveillance undermines enforcement, and large informal employment reduces the political and administrative impetus to extend occupational health systems.[4,5,16,37]

First, enforcement and regulatory deficiencies were the most frequently cited contributors to persistent ONIHL. Even where legislation is comprehensive, such as in South Africa, under-resourced inspectorates, inconsistent penalties, and weak employer compliance undermine policy implementation.[4,20,44,45] Similar enforcement gaps have been reported in Tanzania and Ghana, where regulations exist but are weakly applied. The exclusion of the informal workforce, a recurrent theme in the literature, represents a major policy blind spot that leaves many workers without surveillance or compensation mechanisms.[5,16,41]

Second, health-system capacity constraints further weaken prevention. Several studies highlight severe shortages of audiologists, occupational hygienists, and inspectors across African settings, contributing to limited surveillance and delayed intervention. In South Africa, fewer than 650 audiologists serve a population of 55 million, with even fewer in mining-dense provinces. Competing health priorities such as HIV and TB further divert resources away from occupational health services. Evidence from South African gold mines (n = 3) and Tanzanian steel factories (n = 2) plausibly associates noise plus solvent exposure with increased ONIHL risk, and HIV/TB medication interactions were documented in five studies.[32,33,34]

Third, sociocultural dynamics substantially influence prevention. Low awareness, health illiteracy, and stigma; reported in at least five studies, undermine protective behaviours.[8,12,13,15,55] Many workers view hearing impairment as inevitable with age or seek traditional healing before accessing formal health care.[55] Culturally shaped norms, including collectivist values such as Ubuntu, may inadvertently delay individual help-seeking.

Taken together, single-level interventions (e.g., HPD distribution alone) are insufficient. Devices fail when uncomfortable; system-level efforts collapse without enforcement; sociocultural barriers reduce uptake even when services exist. Sustainable prevention requires integrated engineering and administrative controls, strengthened health systems capacity, consistent enforcement, and culturally adapted education.[58,59,60]

Emerging innovations, including 4IR technologies such as tele-audiology, mHealth, AI, and IoT devices, show promise but remain mostly pilot-scale.[17,19,22,61] Their impact depends on addressing persistent barriers such as poor internet connectivity, high device costs, and limited digital literacy. Engineering interventions such as “buy-quiet” procurement policies have demonstrated up to 10 dB(A) noise reductions in pilot evaluations, suggesting their scalability when paired with enforcement mechanisms. Digital innovations should be viewed as complementary enablers that strengthen systems and extend reach, rather than replacements for fundamental occupational health infrastructure.

Finally, findings suggest that legislation alone has been insufficient in studied contexts such as South Africa, Tanzania, and Ghana. South Africa’s detailed regulatory framework and comparatively large evidence base offer lessons, but persistent high ONIHL prevalence demonstrates that law without enforcement, service capacity, or social buy-in is inadequate.[4,20,41] Across LMICs, resource scarcity, competing health burdens, and large informal labor markets demand affordable, scalable, and culturally congruent strategies that integrate occupational health into national public health and development agendas.[5,15,43]

Limitations

This review has several limitations. First, it draws on a finite set of published sources and may not capture all available evidence. Second, the evidence base is heavily weighted toward South Africa, limiting generalizability o to other African contexts. Third, as a systematic narrative review, the synthesis involves interpretive judgement; steps such as structured appraisal and triangulation were used to mitigate bias. Fourth, English-language bias may exclude francophone and lusophone literature. Finally, the broader scarcity of robust epidemiological surveillance systems across Africa limits the precision of continent-wide inferences.

CONCLUSIONS

This review demonstrates that ONIHL in Africa cannot be prevented through technical or workplace interventions alone. It is driven by interconnected regulatory, health-system, sociocultural, and economic barriers. Effective strategies must, therefore, adopt a multi-sectoral approach that links occupational health to broader public health, labor, and development agendas. South Africa’s experience illustrates that regulations, while necessary, are insufficient without effective enforcement, adequate workforce capacity, and cultural alignment. The findings emphasize that practical progress will depend on strengthening enforcement capacity, improving surveillance and compliance reporting, prioritizing engineering and administrative noise controls, expanding task-shared and tele-audiology screening services, and embedding ototoxicity monitoring within human immunodeficiency virus (HIV)/TB and other public-health programs. These coordinated actions align with the Sustainable Development Goals on health (SDG 3), decent work (SDG 8), and reduced inequalities (SDG 10).

The lack of geographically representative data from other African countries highlights an urgent research priority. High-priority research directions include conducting representative prevalence studies in under-researched regions and informal sectors; implementation research on scaling hearing-conservation programs that emphasize engineering and administrative controls; cost-effectiveness and equity evaluations of tele-audiology and AI-based screening; and longitudinal studies examining interactions between occupational noise, ototoxic co-exposures, and comorbidities such as HIV and tuberculosis. Strengthening national surveillance systems and ensuring open access to data are essential to inform policy and accountability. At the same time, the rise of 4IR innovations offers promising opportunities if they are embedded within robust systems and supported by investment in infrastructure, workforce training, and digital literacy.

Based on the findings, the following action-oriented recommendations are advanced:

For policymakers and regulators:

• (1)Strengthening enforcement mechanisms for existing occupational noise regulations, ensuring employer accountability for comprehensive HCPs.
• (2)Extend legal and policy protections to the informal economy, which employs most African workers but is almost entirely excluded from coverage.
• (3)Prioritize funding for occupational health, particularly for the training and equitable distribution of audiologists and related professionals.
• (4)Develop transparent compliance reporting frameworks and integrate ONIHL prevention targets within national public-health monitoring systems.

For employers and practitioners:

• (1)Implement full-spectrum HCPs that emphasize engineering and administrative controls alongside fit-for-purpose personal protective devices.
• (2)Integrate emerging innovations such as tele-audiology and AI-driven screening into structured, system-based strategies rather than as stand-alone fixes.
• (3)Provide worker training and health education in culturally and linguistically accessible formats to address stigma, low awareness, and poor adherence.

For researchers:

• (1)Generate prevalence and intervention data from under-represented African regions and sectors.
• (2)Apply qualitative and mixed methods designs to capture sociocultural and systemic barriers shaping prevention.
• (3)Examine the combined effects of occupational noise with co-exposures and comorbidities (e.g., HIV/TB) to inform integrated prevention strategies.
• (4)Evaluate the scalability and sustainability of engineering controls (“buy-quiet” initiatives) and digital innovations under real-world African conditions.

In conclusion, preventing ONIHL in Africa requires shifting from fragmented, workplace-only measures toward integrated strategies that connect occupational health with broader public health and socioeconomic development. Such coordinated action is essential to disrupt the cycle of preventable hearing loss, productivity loss, and widening health inequities. Within the next 5 years, African nations should establish enforceable hearing-conservation benchmarks aligned with global 85 dB(A) 8-h TWA standards, expand protections to informal workers, and integrate ONIHL prevention into national public-health plans.

Availability of Data and Materials

Data supporting the findings of this study are available within the paper.

Author Contributions

The author conceptualized the study, conducted the research and analysis, and wrote the manuscript.

Ethics Approval and Consent to Participate

As this study involves the review of existing literature, there were no direct ethical concerns. This narrative review adhered to all ethical standards pertinent to studies that do not involve direct contact with human or animal participants.

Conflicts of Interest

The authors declare no conflicts of interest.

Funding Statement

The study was self-funded.