We aimed to find the relationship between sleep duration and impaired fasting glucose according to working type in non-regular workers using the 2016 and 2017 Korean National Health And Nutrition Examination (KNHANE, 7th revision).

In the 1st and 2nd year (2016, 2017) of the 7th KNHANE, 16,277 people participated. Minors were excluded because this study was intended for individuals aged 19 years and older. As this study was based on wage workers, unemployment, self-employed workers, employers, unpaid family workers, and those who have insufficient answers such as unknown or no response were excluded. Regular workers were excluded because this study was intended for non-regular workers. Finally, a total of 2,168 people were included in the survey, except those who had been diagnosed with diabetes, had a fasting blood glucose level of 126 mg/dL or higher, or taking hypoglycemic agents or receiving insulin injections. To find the relationship between sleep duration and impaired fasting glucose according to work type in non-regular workers, multiple logistic regression analysis was performed by adjusting the general and occupational characteristics after stratification according to work type. All statistical analyses were performed using the SPSS software (version 26.0; SPSS Inc., Chicago, IL, USA).

In the case of insufficient sleep duration in irregular female workers, the odds ratio (OR) of impaired fasting glucose was statistically insignificant, but in the case of insufficient sleep duration in irregular male workers who have shift work, the odds ratio (OR) of impaired fasting glucose was significantly higher than that of sufficient sleep duration (Model 1, OR: 3.05, 95% confidence interval [CI]: 1.18–7.90; Model 2, OR: 2.81, 95% CI: 1.08–7.29).

Our findings demonstrate that insufficient sleep duration was associated with an increase in fasting blood glucose levels in non-regular male workers working shifts. This means that non-regular workers are in desperate need for adequate sleep and health care. We hope that our study will help improve the health of non-regular workers and more systematic and prospective follow-up studies will be conducted to further improve the health of non-regular workers.

This study was conducted to identify the sleep status of daytime workers who do not work in shifts. This study analyzed factors affecting sleep duration and sleep quality.

This study was conducted on 1171 daytime workers at a manufacturing workshop. We used a self-administered questionnaire to investigate demographic variables, work type, working period, musculoskeletal symptoms and the Pittsburgh Sleep Quality Index to assess sleep. Regular health checkup was conducted for the worker’s clinical examination.

The mean sleep duration was 6.36 h and the mean score on the Pittsburgh Sleep Quality Index was 4.46. Work type and obesity were related to sleep duration. Age, obesity and musculoskeletal pain were significantly related to sleep quality. The prevalence ratio of researcher group for short sleep duration was 1.27 (95% confidence interval: 1.02–1.58). The prevalence ratio of those aged 50 years and over was 0.47 (0.25–0.91) and of those in their 40s was 0.56 (0.35–0.91) for poor sleep quality compared to those in their 20s. The prevalence ratio of the obesity group for poor sleep quality was 1.53 (1.10–2.12). The prevalence ratio of musculoskeletal pain group for poor sleep quality was 1.92 (1.29–2.84).

Age, obesity and musculoskeletal pain were factors affecting the poor quality on sleep of daytime workers. In addition, work type related to short sleep duration.

This study was conducted to analyze the distribution of the psychosocial well-being index among adults living in two rural communities in Korea and to examine its correlation with lifestyle variables such as sleep duration, regular exercise, and sedentary time.

Using the cohort data of the Atherosclerosis Risk of a Rural Area Korean General Population, this study examined 3631 participants living in Wonju and Pyeongchang in Gangwon Province; their preliminary data were established from 2005 to 2007 while their follow-up data were collected 3 years later. This study investigated demographic characteristics, lifestyle habits, disease history, Psychosocial Well-being Index-Short Form (PWI-SF) scores, sleep duration, regular exercise, and sedentary time during work. Using repeated measures ANOVA, this study examined how the variables and PWI-SF scores changed over the course of 3 years and identified the correlation between them based on mixed model analysis. Afterwards, using the generalized estimation equation, this study identified each variable’s risk towards the PWI-SF high-risk group and performed a stratified analysis by occupation after dividing the participants into farmers and non-farmers.

The PWI-SF high-risk group was found to be 18.9% of the participants from preliminary data and 15.5% from follow-up data. The odds ratio towards the PWI-SF high-risk group was 1.503 (95% CI 1.241–1.821) in the short sleep duration group and 1.327 (95% CI 1.136–1.550) in the non-regular exercise group. A stratified analysis by occupation showed that middle and long sedentary time in the white-collar group increased the risk toward the PWI-SF high-risk group.

Short sleep duration, no regular exercise, and long sedentary time in the white-collar group were identified as risk factors toward the PWI-SF high-risk group in the rural communities, and policy interventions are needed to address this issue.