Abstract
Occupational noise is a severe stressor, yet its impact on unregulated informal economies remains poorly characterized. While the previous literature relies on crude unadjusted metrics, this study introduces demographic-adjusted multivariable models (
N
= 250) to isolate true workspace risk associations. A cross-sectional assessment was conducted across five informal sectors in Benin City, Nigeria: markets, motor parks, sawmills, abattoirs, and the vibrating block industry (VBI). Cumulative exposure was modelled via 8-hour time-weighted averages (Lex,8 h) and daily noise doses (%) using a 3-dB exchange rate. Multivariable logistic regression was used to calculate adjusted odds ratios (AORs) to isolate independent workspace risks while controlling for demographic confounders. All sectors breached the 85 dBA safety limit. The Sawmill and VBI cohorts exhibited extreme exposure, with daily doses reaching 23,375.3% and 28,711.7%, respectively—over 240-fold and 280-fold violation of permissible limits, respectively. Self-reported complications were widespread and included chronic stress (48.8%) and hearing difficulties (48.4%). Adjusted multivariable models revealed that mechanical processing workspaces independently predicted severe outcomes. Compared with workers in retail markets, workers in the Abattoir (AOR = 16.08), Sawmill (AOR = 14.51), and VBI (AOR = 11.69) markets faced massive odds of hearing difficulties (p < 0.001). The Abattoir sector was a critical hazard pocket, uniquely driving subjective tinnitus (AOR = 6.90), workplace irritation (AOR = 12.05), and chronic stress (AOR = 71.43). Lower-educated operators significantly underreported auditory symptoms (p < 0.05), indicating a health literacy bias. To mitigate these catastrophic exposure profiles, regulatory interventions must employ accurate risk models to implement sector-specific inspections, provide workplace PPE, and enforce targeted urban zoning.