Background: This study aimed to develop standard job categories for constructing a job-exposure matrix (JEM) for police officers in South Korea and to evaluate their applicability. Methods: We examined standard job codes related to police personnel management and compared them with job classifications from police publications. Using R Shiny, we developed a web-based search tool for standard codes. A pilot survey of 130 police officers assessed the codes' applicability and relevance to health-related hazardous factors. Results: Eighty-seven standard functional codes used in the police personnel management system POOL were organized into minor categories as the basic units of standard jobs. These were grouped into 20 sub-major categories and further consolidated into 10 major categories to develop the standard job codes. The responses to the standard job codes in the pilot survey were 75% accurate compared with the final expert evaluation results and 99.2% accurate compared with the algorithm-based automatic allocation results. The results of the job-hazardous factor network analysis revealed that the most frequently reported hazardous factor was emotional labor, followed by night shifts and electromagnetic waves. Emotional labor was identified as the top hazardous factor in six out of the nine standard job categories. Conclusions The standard job codes developed in this study were designed in connection with the personnel management system for police officers, making them well-suited for constructing a comprehensive JEM for the entire police force.

OBJECTIVES: This study aimed to investigate the association between depression with atypical features and metabolic syndromes in Korean adults using the 2016 Korean National Health and Nutrition Examination Survey (KNHANES) data. METHODS: We used the 2016 KNHANES data to enroll 277 participants with a score of 10 or higher on Patient Health Questionnaire-9. Depression with atypical features was diagnosed when at least two of the following criteria were met : 1) sleeping more than 10 hours a day ; 2) weight gain of more than 3 kg in a year ; and 3) fatigue/anergia. Depression was divided into two groups based on the presence/absence of atypical features. Physical and mental health, and risk of metabolic syndrome were compared between the groups. RESULTS: Among the 277 participants, 91 had depression with atypical features. We identified significant differences in age, sex, income, and education between the two groups. After adjusting for these variables, depression with atypical features had lower EuroQol-5D index scores (p<0.001) and higher prevalence of metabolic syndromes (p=0.035) compared to the depression without atypical features. Depression with atypical features had higher odds ratio (OR) in association with metabolic syndromes after adjusting for confounding variables (OR=1.923 ; 95% confidence interval : 1.069–3.460). CONCLUSIONS Depression with atypical features increases the risk of metabolic syndromes and lowers the quality of life.