title: Predictors of early leaving from the cotton spinning mill environment in newly hired workers.
abstract: OBJECTIVE
  This longitudinal study aimed to identify the predictors of leaving during the first year of employment from the cotton spinning mill environment in newly hired workers.
  
  
  METHODS
  One hundred and ninety eight consecutively appointed new employees were investigated by questionnaire, lung function test, and skin test. They were examined before employment and at the end of the 1st week, and the 1st, 3rd, 6th, and 12th month after starting work and when possible before leaving their job. 572 personal dust sampling and 191 endotoxin measurements were performed to assess the environmental exposure. For the univariate analysis chi2, Student t tests, ANOVA, and Kruskall Wallis tests were used. Cox proportional hazards analysis was used to identify factors associated with leaving the job.
  
  
  RESULTS
  Fifty three per cent of workers left the mill environment during their first working year. Work related lower respiratory tract symptoms reported at the third month were associated with an increase rate of leaving the industry compared to those remaining in the industry (25% v 4.8%; p<0.005). Having respiratory symptoms at the first month of work predicted those leaving the industry at some point in the next 11 months. According to the Cox model, increasing age and having work related lower respiratory tract symptoms were found to be predictors for leaving job at the first working year. Atopic status, dust and endotoxin levels, and lung function changes were not consistently predictive of workers who left the industry in the follow up period.
  
  
  CONCLUSIONS
  This study demonstrated that work related respiratory symptoms can predict workers likely to leave the cotton mill environment during the first year of employment, but atopy or acute lung function changes do not.
authors.affiliation: Marmara University, School of Medicine, Department of Public Health, Haydarpasa Istanbul, Turkey. nbakirci@marmara.edu.tr
authors.forename: N
authors.initials: N
authors.lastname: Bakirci
authors.forename: S
authors.initials: S
authors.lastname: Kalaca
authors.forename: A M
authors.initials: AM
authors.lastname: Fletcher
authors.forename: C A C
authors.initials: CA
authors.lastname: Pickering
authors.forename: N
authors.initials: N
authors.lastname: Tumerdem
authors.forename: S
authors.initials: S
authors.lastname: Cali
authors.forename: L
authors.initials: L
authors.lastname: Oldham
authors.forename: H
authors.initials: H
authors.lastname: Francis
authors.forename: R
authors.initials: R
authors.lastname: McL Niven
mesh_terms: D000293:Adolescent; D000328:Adult; D032561:Cotton Fiber; D004391:Dust / Q000032:analysis; D004784:Environmental Monitoring / Q000379:methods; D004812:Epidemiologic Methods; D062665:Epidemiological Monitoring; D005260:Female; D015989:Healthy Worker Effect; D006801:Humans; D008297:Male; D009784:Occupational Diseases / Q000209:etiology*; D016273:Occupational Exposure / Q000032:analysis; D016272:Occupational Health; D010563:Personnel Turnover / Q000706:statistics & numerical data*; D012120:Respiration Disorders / Q000209:etiology*; D012129:Respiratory Function Tests; D012882:Skin Tests; D013783:Textile Industry / Q000706:statistics & numerical data*; D014421:Turkey
chemical_list: D004391:Dust