Methods for evaluating temporal trends in noise exposure

A Quantitative General Population Job Exposure Matrix for Occupational Noise Exposure

Occupational noise exposure is a known risk factor for hearing loss and also adverse cardiovascular effects have been suggested. A job exposure matrix (JEM) would enable studies of noise and health on a large scale. The objective of this study was to create a quantitative JEM for occupational noise exposure assessment of the general working population. Between 2001–2003 and 2009–2010, we recruited workers from companies within the 10 industries with the highest reporting of noise-induced hearing loss according to the Danish Working Environment Authority and in addition workers of financial services and children day care to optimize the range in exposure levels. We obtained 1343 personal occupational noise dosimeter measurements among 1140 workers representing 100 different jobs according to the Danish version of the International Standard Classification of Occupations 1988 (DISCO 88). Four experts used 35 of these jobs as benchmarks and rated noise levels for the remaining 337 jobs within DISCO 88. To estimate noise levels for all 372 jobs, we included expert ratings together with sex, age, occupational class, and calendar year as fixed effects, while job and worker were included as random effects in a linear mixed regression model. The fixed effects explained 40% of the total variance: 72% of the between-jobs variance, −6% of the between-workers variance and 4% of the within-worker variance. Modelled noise levels showed a monotonic increase with increasing expert score and a 20 dB difference between the highest and lowest exposed jobs. Based on the JEM estimates, metal wheel-grinders were among the highest and finance and sales professionals among the lowest exposed. This JEM of occupational noise exposure can be used to prioritize preventive efforts of occupational noise exposure and to provide quantitative estimates of contemporary exposure levels in epidemiological studies of health effects potentially associated with noise exposure.

Patterns and trends in OSHA occupational noise exposure measurements from 1979 to 2013

OBJECTIVES

Noise is one of the most common exposures, and occupational noise-induced hearing loss (NIHL) is highly prevalent. In addition to NIHL, noise is linked to numerous non-auditory health effects. The Occupational Safety and Health Administration (OSHA) maintains the Integrated Management Information System (IMIS) database of compliance-related measurements performed in various industries across the USA. The goal of the current study was to describe and analyse personal noise measurements available through the OSHA IMIS, identifying industries with elevated personal noise levels or increasing trends in worker exposure over time.

METHODS

Through a Freedom of Information Act request, we obtained OSHA's noise measurements collected and stored in IMIS between 1979 and 2013 and analysed permissible exposure limit (PEL) and action level (AL) criteria measurements by two-digit industry code.

RESULTS

The manufacturing industry represented 87.8% of the 93 920 PEL measurements and 84.6% of the 58 073 AL measurements. The highest mean noise levels were found among the agriculture, forestry, fishing and hunting industry for PEL (93.1 dBA) and the mining, quarrying and oil and gas extraction group for AL (93.3 dBA). Overall, measurements generally showed a decreasing trend in noise levels and exceedances of AL and PEL by year, although this was not true for all industries.

CONCLUSIONS

Our results suggest that, despite reductions in noise over time, further noise control interventions are warranted both inside and outside of the manufacturing industry. Further reductions in occupational noise exposures across many industries are necessary to continue to reduce the risk of occupational NIHL.

Imputation of missing values in a large job exposure matrix using hierarchical information

Job exposure matrices (JEMs) represent a useful and efficient approach for estimating occupational exposures. This study uses a large dataset of full-shift measurements and employs imputation strategies to develop noise exposure estimates for almost all broad level standard occupational classification (SOC) groups in the US. The JEM was constructed using 753,702 measurements from the government, private industry, and the published literature. Parametric Bayes imputation was used to take advantage of the hierarchical structure of the SOCs and the mean occupational noise exposures were estimated for all broad level SOCs, except those in major group 23-0000, for which no data were available. The estimated posterior mean for all broad SOCs was found to be 82.1 dBA with within- and between-major SOC variabilities of 22.1 and 13.8, respectively. Of the 443 broad SOCs, 85 were found to have an estimated mean exposure >85 dBA while 10 were >90 dBA. By taking advantage of the size and structure of the dataset, we were able to employ imputation techniques to estimate mean levels of noise exposure for nearly all SOCs in the US. Possible sources of errors in the estimates include misclassification of job titles due to limited data, temporal variations that were not accounted for, and variation in exposures within the same SOC. Our efforts have resulted in an almost completely populated noise JEM that provides a valuable tool for the assessment of occupational exposures to noise. Imputation techniques can lead to maximal use of available information that may be incomplete.

Assessing Hearing Conservation Program Effectiveness: Results of a Multisite Assessment

OBJECTIVES

Noise-induced hearing loss (NIHL) remains one of the most prevalent occupational diseases. Occupational hearing conservation programs (HCPs) can reduce the risk of NIHL, but there remains no consensus on assessing HCP effectiveness. We conducted a multisite, mixed-method assessment of HCP programs.

METHODS

At 13 manufacturing plants, we performed assessments, including interviews with program staff and worker focus groups and surveys. We analyzed the association between these assessments and age-corrected NIHL rates.

RESULTS

Only a few items from the HCP staff interviews correlated with NIHL rates. For the employee survey, management commitment to NIHL prevention and being counseled about NIHL were strongly associated with NIHL rates.

CONCLUSION

Management commitment and counseling of workers about NIHL may be key factors in program effectiveness. A combination of qualitative and quantitative methods appears to be useful for assessing HCPs.