This study aimed to evaluate the association between exposure to occupational hazards and the metabolic syndrome. A secondary objective was to analyze the additive and multiplicative effects of exposure to risk factors. This retrospective cohort was based on 31,615 health examinees at the Pusan National University Yangsan Hospital in Republic of Korea from 2012–2021. Demographic and behavior-related risk factors were treated as confounding factors, whereas three physical factors, 19 organic solvents and aerosols, and 13 metals and dust were considered occupational risk factors. Time-dependent Cox regression analysis was used to calculate hazard ratios. The risk of metabolic syndrome was significantly higher in night shift workers (hazard ratio = 1.45: 95% confidence interval = 1.36–1.54) and workers who were exposed to noise (1.15:1.07–1.24). Exposure to some other risk factors was also significantly associated with a higher risk of metabolic syndrome. They were dimethylformamide, acetonitrile, trichloroethylene, xylene, styrene, toluene, dichloromethane, copper, antimony, lead, copper, iron, welding fume, and manganese. Among the 28 significant pairs, 19 exhibited both positive additive and multiplicative effects. Exposure to single or combined occupational risk factors may increase the risk of developing metabolic syndrome. Working conditions should be monitored and improved to reduce exposure to occupational hazards and prevent the development of the metabolic syndrome.

This study explored the effects of long working hours (LW) and night work (NW) on subjective well-being and the modifying effects of work creativity and task variety (WCTV) and occupation. In addition, we examined the influence of working time-related variables including working-time mismatch, variability, shift work, and autonomy on the effects of LW and NW. This study used data from the 5th Korean Working Conditions Survey on 50,205 workers. LW and NW were defined as 52–60 h (L1) or >60 h (L2) per week, and 1–10 days (N1) or >10 days (N2) of night work per month. Multiple logistic regression was used to examine the effects of LW and NW and the modifying influences of WCTV and occupation. Differences in ORs of LW and NW caused by working time-related variables were investigated, to determine effect sizes and directions. A high level of WCTV alleviated the risks of LW and NW. White-collar workers were more vulnerable to the risk associated with NW. Regarding working-time related variables, working-time mismatch and variability increased the risks of LW and NW, respectively, while shift work alleviated the risks of NW. In countries where flexible work systems are not well utilized, working-time autonomy might not be associated with the risk of LW or NW. This study showed that it is necessary to comprehensively consider the occupation and task characteristics of individual workers performing LW or NW. Further studies of the modifying effects of working time-related variables on LW and NW are needed.

Although exposure to asbestos via various routes has been acknowledged, comprehensive exposure and risk assessment methods have not been developed at the national level. We conducted a study to reconstruct comprehensive past asbestos exposure estimations and to suggest a method to calculate the Excess Lifetime Cancer Risk (ELCR) of Koreans. The past occupational exposure reconstruction was conducted by rebuilding the previous general population job-exposure matrix (JEM). The para-occupational and household exposure estimation was based on the pooled analysis of data from other countries as well as Korea. The neighborhood exposure from occupational sources by distance was estimated by the exponential decay model. As a result, 141 JEM exposure groups across four periods including ~79, the 80s, 90s, 2000s with a ratio of 2.0:1.0:0.5:0.05 were reconstructed. The para-occupational and household exposures were 11% and 1% of the JEM respectively. The environmental exposure source concentration from outside occupational exposure was 2.5% of the inside concentration. The ratio of the concentration of environmental exposure source (C₀) to distance d (C_d) was $ex{p}^{-kd}$ with a decay constant k of 6.834. The mean concentrations (f/cc) were 2.28 × 10⁻³ for outdoor, 4.65 × 10⁻⁵ for indoor, 1.95 × 10⁻² for transportation activity, 4.44 × 10⁻² for agricultural activity, and 4.68 × 10⁻² for daily life activity in naturally occurring asbestos areas. Indoor and outdoor asbestos concentrations from living in a slate roof house were 1.73 × 10⁻⁶ and 2.70 × 10⁻⁸, respectively. For improved generalizability, validity, and applicability of the proposed method, further studies on each route with real assessments and experiments are required.