Relation between sick leave and selected exposure variables among women semiconductor workers in Malaysia.
OBJECTIVE
To determine the relation between sick leave and selected exposure variables among women semiconductor workers.


METHODS
This was a cross sectional survey of production workers from 18 semiconductor factories. Those selected had to be women, direct production operators up to the level of line leader, and Malaysian citizens. Sick leave and exposure to physical and chemical hazards were determined by self reporting. Three sick leave variables were used; number of sick leave days taken in the past year was the variable of interest in logistic regression models where the effects of age, marital status, work task, work schedule, work section, and duration of work in factory and work section were also explored.


RESULTS
Marital status was strongly linked to the taking of sick leave. Age, work schedule, and duration of work in the factory were significant confounders only in certain cases. After adjusting for these confounders, chemical and physical exposures, with the exception of poor ventilation and smelling chemicals, showed no significant relation to the taking of sick leave within the past year. Work section was a good predictor for taking sick leave, as wafer polishing workers faced higher odds of taking sick leave for each of the three cut off points of seven days, three days, and not at all, while parts assembly workers also faced significantly higher odds of taking sick leave.


CONCLUSIONS
In Malaysia, the wafer fabrication factories only carry out a limited portion of the work processes, in particular, wafer polishing and the processes immediately prior to and following it. This study, in showing higher illness rates for workers in wafer polishing compared to semiconductor assembly, has implications for the governmental policy of encouraging the setting up of wafer fabrication plants with the full range of work processes.
Chee
H L
HL
Dept of Community Health, Faculty of Medicine and Health Sciences, Universiti Putra Malaysia, 43400 UPM Serdang, Selangor, Malaysia. hengleng@medic.upm.edu.my
Rampal
K G
KG
D000328:Adult; D017677:Age Distribution; D003430:Cross-Sectional Studies; D005260:Female; D006801:Humans; D007509:Irritants / Q000009:adverse effects; D016015:Logistic Models; D008296:Malaysia / Q000453:epidemiology; D017533:Marital Status; D008875:Middle Aged; D009784:Occupational Diseases / Q000453:epidemiology* / Q000209:etiology; D016273:Occupational Exposure / Q000706:statistics & numerical data; D016017:Odds Ratio; D012307:Risk Factors; D012666:Semiconductors; D018582:Sick Leave / Q000706:statistics & numerical data*
D007509:Irritants