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Abstract Background Particulate matter with a diameter of

Abstract Background Supervised machine learning models have been widely used to predict and get insight into diseases by classifying patients based on personal health records. However, a class imbalance is an obstacle that disrupts the training of the models. In this study, we aimed to address class imbalance with a conditional normalizing flow model, one of the deep-learning-based semi-supervised models for anomaly detection. It is the first introduction of the normalizing flow algorithm for tabular biomedical data. Methods We collected personal health records from South Korean citizens (n = 706), featuring genetic data obtained from direct-to-customer service (microarray chip), medical health check-ups, and lifestyle log data. Based on the health check-up data, six chronic diseases were labeled (obesity, diabetes, hypertriglyceridemia, dyslipidemia, liver dysfunction, and hypertension). After preprocessing, supervised classification models and semi-supervised anomaly detection models, including conditional normalizing flow, were evaluated for the classification of diabetes, which had extreme target imbalance (about 2%), based on AUROC and AUPRC. In addition, we evaluated their performance under the assumption of insufficient collection for patients with other chronic diseases by undersampling disease-affected samples. Results While LightGBM (the best-performing model among supervised classification models) showed AUPRC 0.16 and AUROC 0.82, conditional normalizing flow achieved AUPRC 0.34 and AUROC 0.83 during fifty evaluations of the classification of diabetes, whose base rate was very low, at 0.02. Moreover, conditional normalizing flow performed better than the supervised model under a few disease-affected data numbers for the other five chronic diseases – obesity, hypertriglyceridemia, dyslipidemia, liver dysfunction, and hypertension. For example, while LightGBM performed AUPRC 0.20 and AUROC 0.75, conditional normalizing flow showed AUPRC 0.30 and AUROC 0.74 when predicting obesity, while undersampling disease-affected samples (positive undersampling) lowered the base rate to 0.02. Conclusions Our research suggests the utility of conditional normalizing flow, particularly when the available cases are limited, for predicting chronic diseases using personal health records. This approach offers an effective solution to deal with sparse data and extreme class imbalances commonly encountered in the biomedical context.

Abstract Background Exposure to noxious particles, including cigarette smoke and fine particulate matter (PM2.5), is a risk factor for chronic obstructive pulmonary disease (COPD) and promotes inflammation and cell death in the lungs. We investigated the combined effects of cigarette smoking and PM2.5 exposure in patients with COPD, mice, and human bronchial epithelial cells. Methods The relationship between PM2.5 exposure and clinical parameters was investigated in patients with COPD based on smoking status. Alveolar destruction, inflammatory cell infiltration, and pro-inflammatory cytokines were monitored in the smoking-exposed emphysema mouse model. To investigate the mechanisms, cell viability and death and pyroptosis-related changes in BEAS-2B cells were assessed following the exposure to cigarette smoke extract (CSE) and PM2.5. Results High levels of ambient PM2.5 were more strongly associated with high Saint George’s respiratory questionnaire specific for COPD (SGRQ-C) scores in currently smoking patients with COPD. Combined exposure to cigarette smoke and PM2.5 increased mean linear intercept and TUNEL-positive cells in lung tissue, which was associated with increased inflammatory cell infiltration and inflammatory cytokine release in mice. Exposure to a combination of CSE and PM2.5 reduced cell viability and upregulated NLRP3, caspase-1, IL-1β, and IL-18 transcription in BEAS-2B cells. NLRP3 silencing with siRNA reduced pyroptosis and restored cell viability. Conclusions PM2.5 aggravates smoking-induced airway inflammation and cell death via pyroptosis. Clinically, PM2.5 deteriorates quality of life and may worsen prognosis in currently smoking patients with COPD. Graphical Abstract

Background: This study aimed to investigate the relationship between work-related communication devices use during work outside of regular working hours and depressive symptoms in wage workers. Methods: Data from 50,538 workers aged 15 years or older who had participated in the 6th Korean Working Condition Survey (KWCS) were used. The final sample was 32,994 wage workers. The questionnaire asked the respondents how often they used communication devices for work during work outside of regular working hours. Depressive symptoms were assessed using WHO-5 Well-Being Index. Multiple logistic regression analysis was used to analyze the association between work-related communication devices use during work outside of regular working hours and depressive symptoms. Results: The rate of depressive symptoms was highest among workers who did not use work-related communication devices during work outside of regular working hours. After adjusting for socio-demographic and work-related factors, the odds ratio of depressive symptoms among workers who used communication devices when working outside of regular working hours was 1.20 (95% CI: 1.09–1.32); the odds ratio of depressive symptoms in the group not using communication devices for free-time work was 1.66 (95% CI: 1.37–2.00), which was higher than that of the reference group, that is, workers who did not work outside of regular working hours, and was statistically significant. Conclusion: Regardless of whether work-related communication devices are used, working outside of regular working hours increases depressive symptoms. The use of work-related communication devices during work outside of regular working hours can reduce the rate of depressive symptoms.

Background: Particulate air pollution and residential greenness are associated with sleep quality in the general population; however, their influence on maternal sleep quality during pregnancy has not been assessed. Objective: This cross-sectional study investigated the individual and interactive effects of exposure to particulate matter (PM) air pollution and residential greenness on sleep quality in pregnant women. Methods: Pregnant women (n = 4933) enrolled in the Korean Children's Environmental Health Study with sleep quality information and residential address were included. Sleep quality was assessed using the Pittsburgh Sleep Quality Index (PSQI). The average concentrations of PM (PM2.5 and PM10) during pregnancy were estimated through land use regression, and residential greenness in a 1000 m buffer area around participants' residences was estimated using the Normalized Difference Vegetation Index (NDVI1000-m). Modified Poisson regression models were used to estimate the associations between PM and NDVI and poor sleep quality (PSQI >5) after controlling for a range of covariates. A four-way mediation analysis was conducted to examine the mediating effects of PM. Results: After adjusting for confounders, each 10 μg/m3 increase in PM2.5 and PM10 exposure was associated with a higher risk of poor sleep quality (relative risk [RR]: 1.06; 95% confidence interval [CI]: 1.01, 1.11; and RR: 1.09; 95% CI: 1.06, 1.13, respectively), and each 0.1-unit increase in NDVI1000-m was associated with a lower risk of poor sleep quality (RR: 0.97; 95% CI: 0.95, 0.99). Mediation analysis showed that PM mediated approximately 37%–56% of the association between residential greenness and poor sleep quality. Conclusions: This study identified a positive association between residential greenness and sleep quality. Furthermore, these associations are mediated by a reduction in exposure to particulate air pollution and highlight the link between green areas, air pollution control, and human health.

Abstract Particulate matter (PM) is a major air pollutant that has led to global health concerns and can cause and exacerbate chronic obstructive pulmonary disease (COPD). We asked patients with COPD to complete a detailed questionnaire about their lifestyle practices to reduce PM2.5 exposure and analyzed the relationship between ambient PM2.5 concentrations and lifestyle practices. We prospectively enrolled 104 COPD patients from four hospitals in different areas of Korea. They completed detailed questionnaires twice (at enrollment and the end of the study) and Internet of Things-based sensors were installed in their homes to continuously measure PM2.5 for 1 year. The relationship between PM2.5 concentrations, lifestyle practices, and COPD exacerbations were analyzed in each season. The PM2.5 concentration was higher outdoors than indoors in all seasons except summer, and the difference was largest in winter. The six lifestyle practices that significantly lowered the annual indoor PM2.5 concentration compared with the outdoors. The higher the economic status and educational level of patients, the lower the indoor PM2.5 concentration. Some lifestyle practices were associated with reduced small airway resistance, presented as R5–R20 determined by impulse oscillometry, and scores of the St. George’s Respiratory Questionnaire. Some lifestyle practices are associated with reduced indoor PM2.5 concentrations and can even affect clinical outcomes, including small airway resistance and quality of life of COPD patients.

Background: Fine particulate matter (PM2.5) is a well-known risk factor for worse outcomes of chronic obstructive pulmonary disease (COPD). However, evidence-based guidance on effective personal behavioural strategies to minimise the effects of PM2.5 is limited. This study aimed to assess the effectiveness of a behavioural intervention in reducing PM2.5 exposure and improving clinical outcomes in patients with COPD. Materials and Methods: Participants were 1:1 randomised, and the intervention group received a behavioural intervention consisting of five activities, while the control group received usual care. The participants were followed up for 9 months. The primary outcomes were differences in the score of St. George’s Respiratory Questionnaire for patients with COPD (SGRQ-C) and COPD assessment test (CAT) from baseline. Results: A total of 106 participants were enrolled and 102 completed the study. At the end of the study, the intervention group showed significant improvements in the primary outcomes compared to the control group, with a group difference of −5.9 in the reduction of total SGRQ-C (−3.4 vs. 2.5; p = 0.049) and −3.8 in the CAT score (−1.2 vs. 2.7; p = 0.001). Participants with good adherence to the intervention demonstrated a greater extent of improvement in CAT score and lower PM2.5 levels compared to those who had poor adherence or were in the control group. Regular checking of air quality forecasts was significantly associated with a reduction in CAT scores among all the intervention activities. Conclusion: Individual-level behavioural interventions can be an effective strategy for mitigating the health hazards associated with PM2.5.ClinicalTrials.gov Identifier: NCT04878367.

Background: Occupational cancer is a global health issue. The Korean CARcinogen EXposure (K-CAREX), a database of CARcinogen EXposure, was developed for the Korean labor force to estimate the number of workers exposed to carcinogens by industry. The present study aimed to estimate the intensity of exposure to carcinogens by industry, in order to supply complementary information about CARcinogen EXposure intensity to the K-CAREX. Methods: We used nationwide workplace monitoring data from 2014 to 2016 and selected target carcinogens based on the K-CAREX list. We computed the 95th percentile levels of measurements for each industry by carcinogens. Based on the 95th percentile level relative to the occupational exposure limit, we classified the CARcinogen EXposure intensity into five exposure ratings (1–5) for each industry. Results: The exposure ratings were estimated for 21 carcinogenic agents in each of the 228 minor industry groups. For example, 3,058 samples were measured for benzene in the manufacturing industry of basic chemicals. This industry was assigned a benzene exposure rating of 3. Conclusions: We evaluated the CARcinogen EXposure ratings across industries in Korean workers. The results will provide information on the exposure intensity to carcinogens for integration into the K-CAREX. Furthermore, it will aid in prioritizing control efforts and identifying industries of concern.

Abstract Introduction By substituting the general ‘susceptibility factor’ concept for the conventional ‘gene’ concept in the case-only approach for gene-environment interaction, the case-only approach can also be used in environmental epidemiology. Under the independence between the susceptibility factor and environmental exposure, the case-only approach can provide a more precise estimate of an interaction effect. Methods Two analysis examples of the case-only approach in environmental epidemiology are provided using the 2015–2016 and 2017–2018 US National Health and Nutritional Examination Survey (NHANES): (i) the negative interaction effect between blood chromium level and glycohemoglobin level on albuminuria and (ii) the positive interaction effect between blood cobalt level and old age on albuminuria. The second part of the methods (theoretical backgrounds) summarized the logic and equations provided in previous studies about the case-only approach. Results (i) When a 1 μg/L difference of both blood chromium level (mcg/L) and a 1% difference in blood glycohemoglobin level coincide, the multiplicative interaction contrast ratio (ICRc/nc) was 0.72 (95% CI 0.35–1.60), with no statistical significance. However, when only the cases were analyzed, the case-only ICR (ICRCO) was 0.59 (95% CI 0.28–0.95), with a statistical significance (a negative interaction effect). (ii) When a 1 μg/L difference of both blood cobalt levels and a 1-year difference in age coincide, the multiplicative interaction contrast ratio (ICRc/nc) was 1.13 (95% CI 0.99–1.37), with no statistical significance. However, when only the cases were analyzed, the case-only ICR (ICRCO) was 1.21 (95% CI 1.06–1.51), with a statistical significance (a positive interaction effect). Discussion The discussion suggested the theoretical background and previous literature about the possible protective interaction effect between blood chromium levels and blood glycohemoglobin levels on the incidence of albuminuria and the possible aggravating interaction effect between blood cobalt levels and increasing ages on the incidence of albuminuria. If the independence assumption between a susceptibility factor and environmental exposure in a study with cases and non-cases is kept, the case-only approach can provide a more precise interaction effect estimate than conventional approaches with both cases and non-cases.

Background: In a previous study, we estimated exposure prevalence and the number of workers exposed to carcinogens by industry in Korea. The present study aimed to evaluate the optimal exposure intensity indicators of airborne lead exposure by comparing to blood lead measurements for the future development of the carcinogen exposure intensity database. Methods: Data concerning airborne lead measurements and blood lead levels were collected from nationwide occupational exposure databases, compiled between 2015 and 2016. Summary statistics, including the arithmetic mean (AM), geometric mean (GM), and 95th percentile level (X95) were calculated by industry both for airborne lead and blood lead measurements. Since many measurements were below the limits of detection (LODs), the simple replacement with half of the LOD and maximum likelihood estimation (MLE) methods were used for statistical analysis. For examining the optimal exposure indicator of airborne lead exposure, blood lead levels were used as reference data for subsequent rank correlation analyses. Results: A total of 19,637 airborne lead measurements and 32,848 blood lead measurements were used. In general, simple replacement showed a higher correlation than MLE. The results showed that AM and X95 using simple replacement could be used as optimal exposure intensity indicators, while X95 showed better correlations than AM in industries with 20 or more measurements. Conclusion: Our results showed that AM or X95 could be potential candidates for exposure intensity indicators in the Korean carcinogen exposure database. Especially, X95 is an optimal indicator where there are enough measurements to compute X95 values.

Abstract Air pollution may influence prenatal maternal stress, but research evidence is scarce. Using data from a prospective cohort study conducted on pregnant women (n = 2153), we explored the association between air pollution and perceived stress, which was assessed using the 14-item Perceived Stress Scale (PSS), among pregnant women. Average exposures to particulate matter with an aerodynamic diameter of

Abstract Background Pediatric allergic diseases are a major public health concern, and previous studies have suggested that exposure to traffic-related air pollution (TRAP) exposure is a risk factor. These studies have typically assessed TRAP exposure using traffic measures, such as distance to major roads, or by modeling air pollutant concentrations; however inconsistent associations with pediatric allergic diseases have often been found. Using road proximity and density, we previously found an association between TRAP and atopic eczema among approximately 15,000 children living in Seoul, Korea, heavily populated and highly polluted city in which traffic is a major emission source. We aimed to conduct a parallel analysis using modeled air pollution concentrations and thus examine the consistency of the association. Specifically, we examined the associations of individual-level annual-average concentrations of NO2, PM10, and PM2.5 with symptoms and diagnoses of three pediatric allergic diseases including asthma, allergic rhinitis, and atopic eczema. Methods The study population included 14,614 children from the Seoul Atopy Friendly School Project Survey in Seoul, Korea, in 2010. To assess individual exposures to TRAP among these children, we predicted annual-average concentrations of NO2, PM10, and PM2.5 at the children’s home addresses in 2010 using universal kriging and land use regression models along with regulatory air quality monitoring data and geographic characteristics. Then, we estimated odds ratios (ORs) of the three allergic diseases for interquartile increases in air pollution concentrations after adjusting for individual risk factors in mixed effects logistic regression. Results Symptoms and diagnoses of atopic eczema symptoms showed an association with NO2 (OR = 1.07, 95% confidence interval = 1.02–1.13; 1.08, 1.03–1.14) and PM10 (1.06, 1.01–1.12; 1.07, 1.01–1.13). ORs of PM2.5 were positive but not statistically significant (1.01, 0.95–1.07; 1.04, 0.98–1.10). No association was found between asthma and allergic rhinitis, although PM2.5 showed a marginal association with allergic rhinitis. Conclusions Our consistent findings regarding the association between TRAP and the prevalence of atopic eczema using traffic measures and surrogate air pollutants suggested the effect of TRAP on children’s health. Follow-up studies should elucidate the causal link, to support subsequent policy considerations and minimize adverse health effects in children.

Abstract Background The prevalence of atopic dermatitis (AD) is increasing worldwide. Prenatal particulate matter with an aerodynamic diameter

Introduction Patients with chronic obstructive pulmonary disease (COPD) are vulnerable to particulate matter (PM) exposure which can increase acute exacerbations and hospitalisation. Interventions to avoid PM exposure are important but evidence-based guidance is lacking. This study aims to assess the impact of PM on lung function, quality of life and exacerbations in patients with COPD using a panel design study; it will also provide evidence for interventional measures to reduce harm from PM exposure.Methods and analysis A prospective panel study of patients with COPD aged ≥40 years will be conducted. Patients will be required to have a forced expiratory volume in one second

Background: An association between maternal exposure to air pollution and the birth weight distribution has been reported, but the extent to which this relationship varies according to socioeconomic status (SES) is unknown. This study examined the relationship using the data from a Korean birth cohort. Methods: Data for singleton births in Seoul from 2007 to 2017 (n = 1739) were analyzed. Maternal exposures to particulate matter with an aerodynamic diameter

Background: The Mothers and Children's Environmental Health study (MOCEH) is a multi-centric prospective birth cohort study investigating effects of various environmental pollutants like heavy metals, endocrine disruptors, air pollutants, nutrition and lifestyle on birth outcomes, growth and development, health and disease of children. In this study, we report all the outcomes from the MOCEH study describing the different environmental pollutants affecting children’s health and disease. Methods: In MOCEH study, 1,751 pregnant women in their first trimester were recruited at 3 centers from 2006 to 2010 in South Korea. The children were followed from birth up to 6 years. Information on health outcomes of children including birth parameters, demographic characteristics, medical and child-rearing history, and nutritional status, were repeatedly obtained through the follow-ups by questionnaires administration, clinical evaluation, and biological specimen collection and measurements. Prenatal and postnatal measurement in biospecimen, i.e., lead, mercury, cadmium, manganese, 1-hydroxypyrene, 2-naphthol, malonadialdehyde, hippuric acid, bisphenol A and phthalate metabolites, and measurement in air samples, i.e., particulate matter, nitrogen dioxide, and total volatile organic compounds were performed. Results: The results show the adverse effect of prenatal exposure to heavy metals like mercury, lead and cadmium on children’s physical, cognitive and neurobehavioral development. Exposure to endocrine disruptors, air pollution, second hand smoke, and mother’s lifestyle during pregnancy affects children’s growth and development. We also identified specific window periods of exposure of pollutants significantly related to children’s health outcomes. Conclusion: The collective results from MOCEH study provide strong scientific evidence that exposures to prenatal and postnatal environmental pollutants have a negative effect on growth and development of children, which will be useful in implementing effective national policy to improve children’s environmental health. Keywords: Birth cohort, Children Environmental health, Environmental pollutants

Abstract Background Occupational injuries increase burden on society as well as personal health. Low satisfaction with life may not only increases the risk of occupational injuries directly, but also influences other factors that increase the risk of occupational injury. Along with previous studies on the risk of occupational injury, we sought to explore the relationship between satisfaction with life and occupational injury. Methods The study participants were 6234workers health screened at a university hospital in Incheon. Information on occupational injury and satisfaction with life scale (SWLS) was obtained in a self-report format. Participants were allocated to one of four SWLS groups; the dissatisfied group, the slightly dissatisfied group, the slightly satisfied group, and the satisfied group. The analysis was performed using the chi-square test primarily and by logistic regression adjusted for potential confounders. Results In men, the un-adjusted and adjusted odds ratios (ORs) of low satisfaction with life (SWLS

Inferring causality is necessary to achieve the goal of epidemiology, which is to elucidate the cause of disease. Causal inference is conducted in three steps: evaluation of validity of the study, inference of general causality, and inference of individual causality. To evaluate validity of the study, we propose a checklist that focuses on biases and generalizability. For general causal inference, we recommend utilizing Hill’s 9 viewpoints. Lastly, individual causality can be inferred based on the general causality and evidence of exposure. Additional considerations may be needed for social or legal purposes; however, these additional considerations should be based on the scientific truth elucidated by the causal inference described in the present article.

Objectives: The lung cancer mortality in Korea has increased remarkably during the last 20 years, and has been the first leading cause of cancer-related deaths since 2000. The aim of the current study was to examine the time trends of occupational lung cancer and carcinogens exposure during the period 2006-2009 in South Korea, by assessing the proportion of occupational burden. Methods: We defined occupational lung cancer for surveillance, and developed a reporting protocol and reporting website for the surveillance of occupational lung cancer. The study patients were chosen from 9 participating university hospitals in the following 7 areas: Seoul, Incheon, Wonju, Daejeon, Daegu, Busan, and Gwangju. Results: The combined proportion of definite and probable occupational lung cancer among all lung cancers investigated in this study was 10.0%, 8.6%, 10.7%, and 15.8% in the years 2006 to 2009, respectively, with an average of 11.7% over the four-year study period. The main carcinogens were asbestos, crystalline silica, radon, polyaromatic hydrocarbons (PAHs), diesel exhaust particles, chromium, and nickel. Conclusion: We estimated that about 11.7% of the incident lung cancer was preventable. This reveals the potential to considerably reduce lung cancer by intervention in occupational fields.

Objectives The objective of this study was to conduct a systematic review to provide summarized evidence on the association between maternal exposure to particulate air pollution and birth weight (BW) and preterm birth (PTB) after taking into consideration the potential confounding effect of maternal smoking. Methods We systematically searched all published cohort and case-control studies examining BW and PTB association with particulate matter (PM, less than or equal to 2.5μm and 10.0 μm in diameter, PM2.5 and PM10, respectively) from PubMed and Web of Science, from January 1980 to April 2015. We extracted coefficients for continuous BW and odds ratio (OR) for PTB from each individual study, and meta-analysis was used to combine the coefficient and OR of individual studies. The methodological quality of individual study was assessed using a standard protocol proposed by Downs and Black. Forty-four studies met the inclusion criteria. Results In random effects meta-analyses, BW as a continuous outcome was negativelyassociated with 10 μg/m3 increase in PM10 (-10.31 g; 95% confidence interval [CI], -13.57 to -3.13 g; I-squared=0%, p=0.947) and PM2.5 (-22.17 g; 95% CI, -37.93 to -6.41 g; I-squared=92.3%, p

Recent cohort studies have relied on exposure prediction models to estimate individuallevel air pollution concentrations because individual air pollution measurements are not available for cohort locations. For such prediction models, geographic variables related to pollution sources are important inputs. We demonstrated the computation process of geographic variables mostly recorded in 2010 at regulatory air pollution monitoring sites in South Korea. On the basis of previous studies, we finalized a list of 313 geographic variables related to air pollution sources in eight categories including traffic, demographic characteristics, land use, transportation facilities, physical geography, emissions, vegetation, and altitude. We then obtained data from different sources such as the Statistics Geographic Information Service and Korean Transport Database. After integrating all available data to a single database by matching coordinate systems and converting non-spatial data to spatial data, we computed geographic variables at 294 regulatory monitoring sites in South Korea. The data integration and variable computation were performed by using ArcGIS version 10.2 (ESRI Inc., Redlands, CA, USA). For traffic, we computed the distances to the nearest roads and the sums of road lengths within different sizes of circular buffers. In addition, we calculated the numbers of residents, households, housing buildings, companies, and employees within the buffers. The percentages of areas for different types of land use compared to total areas were calculated within the buffers. For transportation facilities and physical geography, we computed the distances to the closest public transportation depots and the boundary lines. The vegetation index and altitude were estimated at a given location by using satellite data. The summary statistics of geographic variables in Seoul across monitoring sites showed different patterns between urban background and urban roadside sites. This study provided practical knowledge on the computation process of geographic variables in South Korea, which will improve air pollution prediction models and contribute to subsequent health analyses.

Objectives: The effect of the combination of working hours and working time mismatch on depression is unknown. This study was undertaken to confirm the relationship between working time mismatch and depression with respect to hours worked. Material and Methods: The data of 45 514 adult workers that participated in the 6th Korean Working Conditions Survey (KWCS‐VI 2020) were reviewed. Depression was defined using the World Health Organization 5 Well-Being Index (WHO-5) cut-off score of 50. Working time mismatch was defined as a difference between actual and desired working hours. To identify associations between working hour mismatch and depression according to weekly hours worked, stratification analysis was conducted by dividing the study subjects into 3 groups based on actual hours worked weekly (<40 h, 40-<52 h, or ≥52 h). Multiple logistic regression analysis adjusted for potential confounders was performed to calculate odds ratios of depression. Results: In the <40 h, 40-<52 h, and ≥52 h groups, the odds ratios (OR) of working more hours than desired were 1.51, 95% CI: 1.20-1.92 (<40 h), 1.70, 95% CI: 1.58-1.84 (40-<52 h), and 1.55, 95% CI: 1.41-1.69 (≥52 h), respectively, compared to a matched actual versus desired working hours group (the matched group). On the other hand, the odds ratios of working fewer hours than desired were 1.17, 95% CI: 1.07-1.27 (<40 h), 1.38, 95% CI: 1.20-1.60 (40-<52 h), and 1.98, 95% CI: 1.24-3.17 (≥52 h), respectively. The risk of depression was found to increase significantly with working time mismatch within all 3 working hour groups. Conclusions: Working time mismatch increases the risk of worker depression regardless of hours worked. [ABSTRACT FROM AUTHOR]