Biological Monitoring: Evidence for Reductions in Occupational Exposure and Risk

Aims: The aim of this publication is to explore occupational exposure trends from biological monitoring data collected over a period of more than 20 years. The data is stored within the HSE database, which holds more than 950,000 results from 120,000 workers in 8,000 companies. The data were collated for all biological monitoring results for lead, mercury, benzene, and hexamethylene diisocyanate exposures where there have been some regulatory drivers within the reported time period of the data searched. Methods: Relevant results from sample analysed were extracted from the database and categorised by year from 1996 to the end of 2019 for individual blood lead results and individual urine results for mercury, benzene, and hexamethylene diisocyanate. Results were classed by broad occupational sector where possible. Data were reported graphically by analytical biomarker result (as 90th percentile (P90)) and number of samples per year as well as with overall summary statistics. To look at longer-term trends, results were also evaluated as P90 over 6-year periods. Results: In the period 1996–2019, 37,474 blood lead, 11,723 urinary mercury, 9,188 urinary S-phenylmercapturic acid (SPMA, benzene metabolite) and 21,955 urinary hexamethylene diamine (HDA, metabolite of hexamethylene diisocyanate, HDI) samples were analysed and reported. Over the time period the blood lead concentrations saw the P90 reduce from 53 μg/dl 1996) to 24 μg/dl in 2019; the P90 urinary mercury levels reduced from 13.7 μmol/mol creatinine to 2.1 μmol/mol creatinine and the P90 urinary SPMA levels reduced from 133.7 μmol/mol creatinine to 1.7 μmol/mol creatinine. For HDI the P90 results reduced from 2 µmol HDA/mol creatinine in 1996–2000 to 0.7 in 2005–2010 but levels have since increased to 1.0 µmol HDA/mol creatinine (2016–2019). Conclusion: There is strong evidence of reductions in exposure of GB workers to lead, benzene and mercury from the data presented here. These reductions may reflect the impact of national, regional and global regulatory action to reduce exposures however, the loss of high exposure industries (from either GB as a whole or just this dataset i.e., samples are being sent elsewhere) and the increase in automation or substitution also need to be considered as potential factors. The results for HDI show that whilst interventions can reduce exposures significantly, such initiatives may need to be refreshed at intervals to maintain the reductions in exposure. We have observed that exposures move between sectors over time. Waste and recycling (lead, mercury) and tunnelling through contaminated land (benzene) were sectors or tasks associated with significant exposures and may be increasingly areas of concern.