Changes in Spirometry Indices and Lung Cancer Mortality Risk Estimation in Concrete Workers Exposed io Crystalline Silica.
Somayeh RahimimoghadamNarges KhanjaniMahmoud MohamadyanMojtaba EmkaniSaeed YariMohamad Nasser Layegh TizabiAli GanjaliPublished in: Asian Pacific journal of cancer prevention : APJCP (2020)
The health of workers in the concrete and cement industries can be at risk due to occupational exposure to silica dust. The purpose of this study was to evaluate the changes of pulmonary parameters and risk of mortality from lung cancer in concrete workers exposed to crystalline silica. This cross-sectional study was performed on 72 male workers exposed to silica at a concrete manufacturing plant in Neyshabur, Iran. Respiratory zone air sampling was performed using the standard NIOSH7602 method using individual sampling pumps and membrane filters. Then, the amount of silica in the samples was determined using the Fourier Transform Infrared technique. The risk of death from lung cancer was determined using Rice et al.'s model. Respiratory indices were measured using a spirometer. Data were analyzed by the SPSS 20 software. Occupational exposure to silica was 0.025 mg/m3 and mortality was estimated to be 7-94 per thousand. All spirometry indices significantly decreased during these 4 years of exposure to silica dust. The respiratory pattern of 22% of the exposed workers was obstructive and this prevalence was significantly higher than the control group. The results showed that although the average occupational exposure to silica in these concrete workers was below the recommended threshold of national and international organizations, their risk of death was significantly higher; and workers' lung indices had significantly decreased over four years. Therefore, appropriate measures should be taken to reduce silica exposure among these workers.
Keyphrases
- healthcare
- public health
- risk factors
- cardiovascular events
- chronic obstructive pulmonary disease
- type diabetes
- cardiovascular disease
- lung function
- machine learning
- pulmonary hypertension
- deep learning
- health risk
- climate change
- cystic fibrosis
- heavy metals
- social media
- health information
- polycyclic aromatic hydrocarbons