Levels of Clara cell secretory protein and surfactant protein A in municipal solid waste management workers in Ibadan, Southwest Nigeria.
Adesina O OdewabiRomoke S AjibolaKolawole S OritogunMartins EkorPublished in: Toxicology and industrial health (2023)
Toxic pneumonitis and related respiratory symptoms are common among waste management workers (WMWs). Products of different cellular responses following exposure to toxic components of wastes can lead to the production of a variety of biomolecules. There is a growing recognition of the importance of biomarkers in risk assessment and a strong advocacy for their determination and use as indicators of health and safety. This study assessed the prevalence of respiratory symptoms and the relevance of pulmonary surfactant protein A (SP-A) and Clara cell 16 protein (CC16) as indicators of occupational inhalation exposure to toxic substances and irritants in WMW. A total of 172 subjects consisting of 112 WMWs and 60 Non-WMWs were recruited by purposive sampling. Data on socio-economic and work-related symptoms were collected using structured questionnaire. CC16 and SP-A were determined by ELISA in serum samples. Clinical history reveals a slightly higher prevalence of respiratory symptoms in WMWs relative to control subjects. Increased permeability of the lung-blood barrier, characterized by significant elevation of serum SP-A and serum CC16, was associated with respiratory symptoms in WMWs. Steady increases in SP-A and CC16, respectively, in relation to occupational duration were observed in WMWs relative to control. Receiver operating characteristic curve and multivariate analyses revealed SP-A and CC16 as important lung biomarkers for assessing sub-clinical effects of occupational exposure. Our data suggest SP-A and CC16 may be relevant indicators for assessing occupational inhalation exposure to toxic substances and irritants among WMWs.
Keyphrases
- risk assessment
- single cell
- municipal solid waste
- protein protein
- sleep quality
- risk factors
- amino acid
- healthcare
- heavy metals
- binding protein
- public health
- small molecule
- drinking water
- mental health
- electronic health record
- deep learning
- drug induced
- bone marrow
- sewage sludge
- respiratory tract
- big data
- interstitial lung disease
- depressive symptoms
- climate change
- data analysis
- liquid chromatography