Identifying Allostasis and Some of its Predictors in Spinning and Weaving Cotton Industry Workers: OAJBS Publishers

Identifying Allostasis and Some of its Predictors in Spinning and Weaving Cotton Industry Workers by Mai Sabry Saleh* in Open Access Journal of Biomedical Science (OAJBS)

Textile workers are subjected to many health hazards. Identifying risk predictors at early stage help as a predictive and preventive measure that saves workers from critical health condition in the future. Allostatic load index (ALI) is a potential indicator of complex health conditions that may result in chronic diseases if not properly managed. A sample of 75 male workers in cotton textile weaving and spinning participated in the study. They were examined clinically for their blood pressure and pulmonary functions. They completed their socio-demographic and work-related questionnaire. Blood samples were also withdrawn from the study sample to analyze some biochemical markers. ALI was then calculated for the whole sample using six parameters: cortisol, thyroid stimulating hormone, body mass index, systolic and diastolic blood pressure and heart rate. Statistical analysis showed descriptive data and a multiple linear regression model was performed to detect the factors that mostly contributed to the sample deteriorated health as per ALI. Results showed good mean value for ALI (2.2), yet the long exposure duration showed significant positive correlation with allostasis. Pulmonary function test, expressed in terms of forced expiratory volume, and age also showed significant direct correlation with ALI. In conclusion workplace stressors and the late effects of particulate matter are potent hazards threatening the health of cotton textile workers.
https://biomedscis.com/fulltext/identifying-allostasis-and-some-of-its-predictors-in-spinning-and-weaving-cotton-industry-workers.ID.000304.php

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