A job exposure matrix for occupational exposure to airborne micro and nanoplastics (PlastiXJEM(R)) and associations with respiratory outcomes
Vasse, G. F.; Vrisekoop, N.; Klazen, J. A.; Vonk, J. M.; Melgert, B. N.
Show abstract
BackgroundMicroplastics and nanoplastics (MNP) are an increasingly recognized component of airborne particulate matter, yet their impact on respiratory health is unclear. This study aimed to develop a job exposure matrix (JEM) for occupational exposure to airborne MNP (PlastiXJEM(R)) and examine its association with respiratory outcomes in the Lifelines cohort. MethodsFour experts scored occupational airborne MNP exposure levels (none, low, high) for all ISCO-08 occupations based on documented sources and published evidence. After consensus, the PlastiXJEM(R) was applied to baseline current or last-held jobs of 136,928 adult Lifelines participants. Cross-sectional and longitudinal associations with lung function, respiratory symptoms, and asthma were assessed using linear and logistic regression models adjusted for age, sex, smoking, height, BMI, and co-exposure to organic dust, gasses and fumes, pesticides, metals, solvents and silica. ResultsHigh exposure was associated with lower FEV (-43 ml; 95% CI:-61;-25), lower FVC (-47 ml(-69;-26)), lower FEV1%FVC (-0.26 % (-0.51;-0.00) and higher odds of airway obstruction, respiratory symptoms and asthma (e.g. dyspnea OR=1.58; 1.34-1.87). Low exposure was associated with lower FEV1 and FVC in women only. Associations were attenuated after adjustment for socio-economic status but remained for FEV, airway obstruction and dyspnea. MNP exposure was not associated with accelerated lung function decline or with the development of airway obstruction, respiratory symptoms, or asthma. ConclusionOccupational exposure to airborne MNP is associated with lower lung function and a higher prevalence of respiratory symptoms in this cohort. These findings warrant further investigation with complete occupational histories.
Matching journals
The top 8 journals account for 50% of the predicted probability mass.