| ORIGINAL ARTICLE |
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| Year : 2022 | Volume
: 26
| Issue : 2 | Page : 78-83 |
Occupational ventilatory defects among workers employed in tea gardens, A cross-sectional study in siliguri subdivision of Darjeeling District, West Bengal
Papiya Roychowdhury1, Abhijit Mukherjee2, Sharmistha Bhattacherjee2, Prem Dorjee Bhutia3, Saikat Datta4, Samir Dasgupta5
1 Department of Community Medicine, Dr B.N. Bose Subdivisional Hospital, Barrackpore, West Bengal, India
2 Department of Community Medicine, North Bengal Medical College, Sushrutanagar, West Bengal, India
3 Department of Internal Medicine, Neotia Getwel Hospital, Uttarayon Township, Matigara, West Bengal, India
4 Department of Medicine, MJN Medical College, Coochbehar, West Bengal, India
5 Department of Community Medicine, KPC Medical College, Jadavpur, Kolkata, India
Correspondence Address:
Dr. Abhijit Mukherjee
34, SN Banerjee Road, New Barrackpore, Kolkata - 131, West Bengal
India
 Source of Support: None, Conflict of Interest: None  | Check |
DOI: 10.4103/ijoem.ijoem_91_21
Introduction: During the refining and packing of tea, a very fine dust is formed which is called the tea fluff. Exposure to this fluff has been reported to cause ventilatory defects on chronic exposure. Objective: To determine the association between air quality of the different work sections of tea gardens and the ventilatory functions of the workers. Methodology: An observational analytical study with cross sectional design was conducted on 400 apparently healthy individuals working in different sections of 4 tea gardens. Data on sociodemographic characters of the population, particulate matter (PM) and air quality (AQI) was recorded. All participants underwent spirometric evaluation. Results: The mean (SD) age of the study population was 37.8 (8) years. Most (67%) of the study participants were females. The participants were engaged in the job for a mean (SD) of 4.7 (2.7) years. The median distribution of PM2.5, PM 10 and AQI are progressively higher from the garden section to the dry section. A significant correlation between FVC and PM2.5 and PM10 is seen. FEV1 and FEV1/FVC shows a significant correlation with all air quality parameters while FEF25-75 is correlated to none of them. Comparison of the three models to predict the spirometric variables show that even after adjustments, the FEV1 is significantly associated with air quality parameters, FEV1/FVC is significantly associated with the air quality parameters and age while the FEF25-75% is dependent on the age of the participant. Conclusion: There is a strong correlation between the ventilatory parameters and the cumulative exposure of PM2.5, PM10 and AQI, which persists even after adjustment for confounders.
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