Occupational injury has been a serious social problem steadily. Sleep disturbance is a risk factor for occupational injury. However, there were few researches studied on the linking between sleep disturbance and occupational injury in general working population of Korea. Therefore, we explored the association between sleep disturbance and occupational injury among Korean workers.

This study used data from the 5th Korean Working Conditions Survey. Occupational injury was assessed by asking work related injury for 12 months prior to the point of the survey. Sleep disturbance was assessed using the Minimal Insomnia Symptoms Scale (MISS). To analyze the association between sleep disturbance and occupational injury, multiple logistic regression analysis was conducted.

The odds ratio (OR) of sleep disturbance group for occupational injury was 2.57 (95% confidence interval [CI]: 1.68–3.93) in the fully adjusted model. For the association between MISS score and occupational injury, it showed increasing trend that ORs increase from the 1st to the 4th quartiles. The OR of 2nd quartile was 1.10 (95% CI: 0.60–2.01), the OR of 3rd quartile was 2.27 (95% CI: 1.53–3.38) and the OR of 4th quartile was 2.80 (95% CI: 1.84–4.26).

Sleep disturbance was associated with occupational injury. In addition, increasing trend was observed between MISS score and occupational injury. These findings imply that developing of intervention programs to manage sleep disturbance and fatigue may be necessary to prevent occupational injury.

Sickness presenteeism (SP) indicates “going to work while being ill.” The importance of SP has only recently been investigated, and the association between SP and employment status has been inconsistent across studies. Therefore, we conducted this study to explore the association between SP and employment status by using presenteeism propensity (PP), which can reflect the individual decision-making process.

The study population included employees participating in the 5th Korean Working Condition Survey. We analyzed data of only employees with at least one health event, which was calculated as the sum of SP and sickness absenteeism days. Employment status was grouped into 3 categories: stable employment, unstable employment (contract period ≥ 1 year), and unstable employment (contract period < 1 year). Survey-weighted logistic regression analysis was conducted to assess the association between employment status and PP (dichotomized as “≤ 0.5” and “> 0.5”).

Unstable employees (contract period ≥ 1 year) had higher odds of PP than stable employees (odds ratio [OR]: 1.23, 95% confidence interval [CI]: 1.03–1.47), whereas unstable employees (contract period < 1 year) had lower odds of PP than stable employees (OR: 0.82, 95% CI: 0.71–0.96).

Employment status was associated with SP. Given the negative health impact of SP, social efforts, such as paid sick leave, are required to reduce SP and enhance the health status of unstable workers.