Iron and steel factory workers in Tanzania are likely to develop noise-induced hearing loss (NIHL) due to exposure to high sound levels. Studies on hearing status in this population are lacking. The aims of this study were to determine prevalence of NIHL among iron and steel workers and compare hearing thresholds at different frequencies with a control group. We conducted a cross-sectional study among 221 iron and steel workers exposed to average noise level of 92 dB(A), compared with 107 primary school teachers recruited as controls and exposed to average noise level of 79.7 dB(A). We used a questionnaire-based interview to collect information on socio demographic characteristics and other confounding variables. Hearing loss was defined as hearing threshold levels ≥25 dB hearing loss in either ear at 3000, 4000 or 6000 Hz. The prevalence of hearing loss was significantly higher among the exposed group than among the controls, i.e. 48% and 31%, respectively. There were significant differences in hearing thresholds between the exposed and control groups at 3000, 4000, 6000, and 8000 Hz. Hearing loss was more frequent among workers exposed to higher noise levels than among the controls suggesting that iron and steel workers run a higher risk of developing hearing loss.

BackgroundMachines, processes, and tasks in the iron and steel factories may produce noise levels that are harmful to hearing if not properly controlled. Studies documenting noise exposure levels and related determinants in sub-Saharan Africa, including Tanzania are lacking. The aim of this study was to document noise exposure and to identify determinants of noise exposure with a view to establishing an effective hearing conservation programme.MethodsA walk-through survey was conducted to describe the working environment in terms of noise sources in four metal factories (A–D) in Tanzania. Noise measurements were conducted by both personal, full-shift noise measurements (8 h) using dosimeters and area measurements (10-s measurements) using a sound level meter. A total of 163 participants had repeated personal noise measurements (Factory A: 46 participants, B: 43, C: 34, and D: 40). Workers were randomly selected and categorized into 13 exposure groups according to their job. Linear mixed effects models were used to identify significant determinants of noise exposure in the furnace section and the rolling mill section.ResultsThe average personal noise exposure in the four factories was 92.0 dB(A) (range of job group means; 85.4–96.2 dB(A)) (n = 326). Personal exposure was significantly higher in the rolling mill section (93.0 dB(A)) than in the furnace section (89.6 dB(A)). Among the job groups, the cutters located in the rolling mill section had the highest noise exposure (96.2 dB(A)). In the furnace section, furnace installation (below the ground floor), manual handling of raw materials/billets/crowbars, and billet weighing/transfer were significant determinants explaining 40% of the total variance in personal noise exposure. In the rolling mill section, the size of the cutting machine, steel billet weight and feeding re-heating furnace explained 46% of the total variance in personal noise exposure. The mean noise level of the area measurements was 90.5 dB(A) (n = 376).ConclusionWorkers in the four iron and steel factories in Tanzania were exposed to average noise of 92.0 dB(A), without using hearing protection, implying a high risk of developing hearing loss. Task and factory level determinants were identified in the furnace and the rolling mill sections of the plant, which can inform noise control in factories with similar characteristics.

We assessed Knowledge Attitude and Practice (KAP) regarding occupational noise exposure, Noise-induced hearing loss, audiometry and use of hearing protection devices among iron and steel factory workers exposed to high noise level. A modified, validated, structured questionnaire was used to collect information from 253 male workers randomly selected from the four factories. The sum scores for each domain of KAP were computed. Scores above 75% were defined as good knowledge and positive attitude. For practice, scores of >50% were defined as good. Independent samples t-test and Chi-squared test were used to analyze association between KAP and continuous/categorical variables respectively. Majority of workers displayed poor knowledge and poor practice (94%), but 76% displayed a positive attitude. Most of the workers (86%) had never been provided with hearing protection devices. The mean scores for attitude and practice differed significantly between the four factories (one-way ANOVA, p < 0.001). Implementation of hearing conservation program with provision of hearing protection devices are suggested.