Application of Pattern Mining Methods to Assess Exposures to Multiple Airborne Chemical Agents in Two Large Occupational Exposure Databases from France

Surveys of the French working population estimate that approximately 15% of all workers may be exposed to at least three different chemical agents, but the most prevalent coexposure situations and their associated health risks remain relatively understudied. To characterize occupational coexposure situations in France, we extracted personal measurement data from COLCHIC and SCOLA, two large administrative occupation exposure databases. We selected 118 chemical agents that had ≥100 measurements with detected concentrations over the period 2010-2019, including 31 carcinogens (IARC groups 1, 2A, and 2B). We grouped measurements by work situations (WS, combination of sector, occupation, task, and year). We characterized the mixtures across WS using frequent itemset mining and association rules mining. The 275,213 measurements extracted came from 32,670 WS and encompassing 4692 unique mixtures. Workers in 32% of all WS were exposed to ≥2 agents (median 3 agents/WS) and 13% of all WS contained ≥2 carcinogens (median 2 carcinogens/WS). The most frequent coexposures were ethylbenzene-xylene (1550 WS), quartz-cristobalite (1417 WS), and toluene-xylene (1305 WS). Prevalent combinations of carcinogens also included hexavalent chromium-lead (368 WS) and benzene-ethylbenzene (314 WS). Wood dust (6% of WS exposed to at least one other agent) and asbestos (8%) had the least amount of WS coexposed with other agents. Tasks with the highest proportions of coexposure to carcinogens include electric arc welding (37% of WS with coexposure), polymerization and distillation (34%), and construction drilling and excavating (34%). Overall, the coexposure to multiple chemical agents, including carcinogens, was highly prevalent in the databases, and should be taken into account when assessing exposure risks in the workplace.

Exposure Determinants in the French Database COLCHIC (1987-2019): Statistical Modeling across 77 Chemicals

OBJECTIVES

The COLCHIC database contains workplace exposure results of chemical samples collected by the French prevention network since 1987. We aimed to investigate potential associations between exposure levels and ancillary variables in COLCHIC across a broad range of chemical agents in order to provide insight into how to best interpret and exploit the information in this national database.

METHODS

We selected personal and area measurements in COLCHIC and collected outside respiratory personal protective equipment (PPE), restricted to chemical agents that had at least 1000 samples available. We used Tobit models to estimate associations between exposure concentrations and sample year, sampling duration, PPE, workforce size, collective protective equipment, origin of request, and reason for request for each chemical agent for the period 1987-2019. Models for period 2002-2019 also included type of process (open/closed) and exposure frequency. We used separate models for each combination of agent, period, and personal or area samples. We then applied Bayesian meta-analytical methods to assess average effects and effect heterogeneity of exposure factors across agents.

RESULTS

COLCHIC contained 720 282 exposure results (62% personal and 38% area samples) to 77 agents, including 346 766 results for the more recent period 2002-2019 (67% personal and 33% area samples). Sample year and duration, PPE, and process type had the strongest and most consistent associations with exposure levels across agents. Personal and area exposure levels decreased yearly (6% for the entire period and 9% since 2002), and 30-min samples were approximately twice as high as 240-min samples. Workers wearing PPE were exposed to levels 1.7 times higher on average than those without PPE for both area and personal samples. Personal exposure levels associated with enclosed or semi-enclosed processes were approximately 20-30% lower compared with open processes. The associations for the other exposure variables were weaker and more inconsistent between agents. Between-agent heterogeneity of estimated effects, based on 80% prediction intervals, was lowest for sampling duration, time trends, and the presence of PPE.

CONCLUSIONS

Sampling duration, time trends, and the presence of PPE are important factors to take into account when analyzing COLCHIC and had similar associations with exposure levels across agents. Other variables generally showed weaker associations or variable effects. These results will be used to adjust exposure estimates for the French working population from measurements stored in COLCHIC.