英文摘要 |
The purpose of this study was to investigate the factors associated with self-evaluated sleep quality among workers and provide some suggestions for health promotion program at workplace. Using cross-sectional survey, 391 subjects who had undergone health check-ups at 10 city hospital campus was selected by convenience sampling method. Self-reported measures of income, education, sleep quality (PSQI) and job content (JDCS) was designed for questionnaire. The major findings of this study were: 1. The sociodemographic picture of this study revealed that male was more than female, college educational level above was 80%, aged 45 above and income NT$ 34,000 under were the dominants among whole sampling. In labor condition variable, the formal employees was 88%, working hours over 48 hours weekly workers were more than 50%, not shifting workers were 84%, extraworking 1-2 days weekly and light physical workers were the dominants among whole sampling. Non- substance exposure workers were more than 50% of whole sampling but only the noisy exposure workers were 54%. In health behavior variable, coffee drinking 2 cups more weekly and alcoholic drinking workers were more than 50% of whole sampling, non-smoking and non-betel nut chewing worker were dominants among whole sampling. In job content variable, the passive type was the dominant one and next by highly job stress type. The average PSQI global score of total subjects was 5.47±3.25 and it revealed that the sleeping quality were the worse of sleep quality variable. 2. The correlation between sleep quality and subjects, male, college educational level above, higher income, formal employee, working hours under 48 hours weekly, non extraworking workers, no shifting work and light physical work, non-substance exposure, one cup coffee drinking weekly under and passive type workers had a better sleep quality. 3. While exploring the predictive important variables of social demography, working condition, substance exposure, health behavior, and job content towards the sleep quality, it could explain 24.3% of total variation. Of them, “income status” and ”job content” were the most important predictive factors for influence of workers’ sleep quality. In order to improve the sleep quality for workers, some suggestions for health promotion programming were provided also |