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Exposure of an individual to occupational and environmental risk factors for a certain disease affects them and their family. Children are highly vulnerable in this setting because they are family-dependent. This review discusses diseases that occur in children according to the occupational and behavioral characteristics of their parents. Toxic agents in the home environment can affect children’s health. Maternal exposure to substances during pregnancy may directly affect fetal outcomes. The Industrial Accident Compensation Insurance Act in Korea was amended in 2023 to compensate for children’s adverse health effects due to their parents’ occupational risks. The long working hours and smoking behaviors of parents and toxic materials in the home environment are highlighted. To control for the diverse factors affecting children’s health in medical research, this review introduces directed acyclic graphs. Pediatric, occupational, and environmental medicine must collaborate to prevent childhood diseases related to environmental factors.

Objectives This systematic review and meta‐analysis aimed to assess sedentary work's contribution to breast cancer risk quantitatively using thorough research articles. Methods We performed a meta‐analysis using a registered protocol in PROSPERO (registration number: CRD42020204629). Literature from PubMed, Embase, and Cochrane involving sedentary work and breast cancer risk was reviewed. We calculated the overall pooled risk ratios (RRs) and 95% CI with a random‐effect model from the included studies. Furthermore, we performed stratified analyses by characteristics of studies. Results Thirty‐one studies (13 cohort studies and 18 case‐control studies) were included in the analysis. The overall effect of the pooled analysis was an RR of 1.16 (95% CI 1.08‐1.23). The results were 1.20 (95% CI 1.10‐1.30) and 1.12 (95% CI 1.02‐1.23) for cohort and case‐control studies. The effect of sedentary work did not seem to be consistently attenuated by controlling body mass index, menopausal status, or experience of hormone replacement therapy. Conclusion The results from this meta‐analysis suggest that sedentary behavior within the occupational domain was associated with a 15.5% increased risk of breast cancer. It is essential to reduce the sedentary time spent at work and to secure time for leisure‐time physical activity among sedentary workers as a primary preventive measure.

Background Microorganisms are important occupants of many different environments. Identifying the composition of microbes and estimating their abundance promote understanding of interactions of microbes in environmental samples. To understand their environments more deeply, the composition of microorganisms in environmental samples has been studied using metagenomes, which are the collections of genomes of the microorganisms. Although many tools have been developed for taxonomy analysis based on different algorithms, variability of analysis outputs of existing tools from the same input metagenome datasets is the main obstacle for many researchers in this field. Results Here, we present a novel meta-analysis tool for metagenome taxonomy analysis, called TAMA, by intelligently integrating outputs from three different taxonomy analysis tools. Using an integrated reference database, TAMA performs taxonomy assignment for input metagenome reads based on a meta-score by integrating scores of taxonomy assignment from different taxonomy classification tools. TAMA outperformed existing tools when evaluated using various benchmark datasets. It was also successfully applied to obtain relative species abundance profiles and difference in composition of microorganisms in two types of cheese metagenome and human gut metagenome. Conclusion TAMA can be easily installed and used for metagenome read classification and the prediction of relative species abundance from multiple numbers and types of metagenome read samples. TAMA can be used to more accurately uncover the composition of microorganisms in metagenome samples collected from various environments, especially when the use of a single taxonomy analysis tool is unreliable. TAMA is an open source tool, and can be downloaded at https://github.com/jkimlab/TAMA .

Background Thanks to the recent advancements in next-generation sequencing (NGS) technologies, large amount of genomic data, which are short DNA sequences known as reads, has been accumulating. Diverse assemblers have been developed to generate high quality de novo assemblies using the NGS reads, but their output is very different because of algorithmic differences. However, there are not properly structured measures to show the similarity or difference in assemblies. Results We developed a new measure, called the GMASS score, for comparing two genome assemblies in terms of their structure. The GMASS score was developed based on the distribution pattern of the number and coverage of similar regions between a pair of assemblies. The new measure was able to show structural similarity between assemblies when evaluated by simulated assembly datasets. The application of the GMASS score to compare assemblies in recently published benchmark datasets showed the divergent performance of current assemblers as well as its ability to compare assemblies. Conclusion The GMASS score is a novel measure for representing structural similarity between two assemblies. It will contribute to the understanding of assembly output and developing de novo assemblers.

Objectives: This study investigated the effects of hot and cold temperature on the renal function of people with chronic diseases, such as diabetes, hypertension, and chronic kidney disease, using large-scale clinical data.Methods: We used retrospective cohort data from the Clinical Data Warehouse of the Seoul St Mary’s Hospital, which contains clinical, diagnostic, laboratory, and other information about all patients who have visited the hospital since 1997. We obtained climate data from the Automated Synoptic Observing System of the Korea Meteorological Administration. The heat index was used as a measuring tool to evaluate heat exposure by indexing the actual heat that individuals feel according to temperature and humidity. The estimated glomerular filtration rate (eGFR) was calculated using the Chronic Kidney Disease Epidemiology Collaboration equation. To investigate changes in renal function trends with heat index, this study used generalized additive mixed models.Results: Renal function decreased linearly with increasing heat index after approximately 25°C, which was considered the flexion point of temperature. A linear decrease in the eGFR was observed with the effects of 0 to 5 lag days. Although there was a correlation observed between the decrease in eGFR and temperatures below −10°C, the results did not indicate statistical significance.Conclusions: The results of our study provide scientific evidence that high temperatures affect the renal function of people with chronic diseases. These results can help prevent heat-related morbidity by identifying those who are more likely to develop renal disease and experience worsening renal function.

ObjectivesWe studied the association between long working hours and decreased kidney function, which was determined using estimated glomerular filtration rate (eGFR), among the working population in South Korea.MethodsWe analysed nationally representative cross-sectional data for 20 851 Korean workers ≥20 years of age. A negative binomial regression model was used to test differences in the prevalence of chronic kidney disease (eGFR <60 mL/min/1.73 m2) among workers divided into groups according to weekly working hours (<30, 30–40, 41–51 and ≥52 hours/week). Multivariate linear regression analysis was performed to investigate the association between weekly working hours and eGFR, with adjustments made for age, sex/gender, income, education, shift work, occupation, smoking, alcohol use, hypertension, diabetes mellitus, body mass index, systolic blood pressure, fasting blood glucose and total serum cholesterol.ResultsA 1-hour increase in weekly working hours was associated with 0.057 mL/min/1.73 m2 (95% CI 0.005 to 0.109) decrease in eGFR among participants who worked ≥52 hours/week. Among participants without hypertension or diabetes, a 1-hour increase in weekly working hours was significantly associated with 0.248 and 0.209 mL/min/1.73 m2 decrease in eGFR among participants who worked 30–40 hours/week and 41–51 hours/week, respectively.ConclusionLong working hours are associated with decreased kidney function. We expect that our findings could call for more research regarding this association and provide policy-oriented perspectives.

Background Many studies have been performed to identify various genomic loci and genes associated with the meat quality in pigs. However, the full genetic architecture of the trait still remains unclear in part because of the lack of accurate identification of related structural variations (SVs) which resulted from the shortage of target breeds, the limitations of sequencing data, and the incompleteness of genome assemblies. The recent generation of a new pig breed with superior meat quality, called Nanchukmacdon, and its chromosome-level genome assembly (the NCMD assembly) has provided new opportunities. Results By applying assembly-based SV calling approaches to various genome assemblies of pigs including Nanchukmacdon, the impact of SVs on meat quality was investigated. Especially, by checking the commonality of SVs with other pig breeds, a total of 13,819 Nanchukmacdon-specific SVs (NSVs) were identified, which have a potential effect on the unique meat quality of Nanchukmacdon. The regulatory potentials of NSVs for the expression of nearby genes were further examined using transcriptome- and epigenome-based analyses in different tissues. Conclusions Whole-genome comparisons based on chromosome-level genome assemblies have led to the discovery of SVs affecting meat quality in pigs, and their regulatory potentials were analyzed. The identified NSVs will provide new insights regarding genetic architectures underlying the meat quality in pigs. Finally, this study confirms the utility of chromosome-level genome assemblies and multi-omics analysis to enhance the understanding of unique phenotypes.

Objectives We examined whether the effect of long working hours on the risk of developing cardiovascular disease (CVD) differs depending on individual risk factors. Methods Seven‐year follow‐up data were extracted from the 2009 to 2016 waves of the Korea Health Panel Survey. Physician's diagnosis or medication for hypertension, diabetes, dyslipidemia, and obesity were included as chronic disease status. Smoking, drinking alcohol, and exercise levels were considered as lifestyle behavior. Hazard ratios were calculated using the Cox regression models to evaluate the risk of CVD related to chronic diseases and unhealthy behavior, based on working hour groups, after adjusting for other covariates. The interactive effects of long working hours with or without chronic diseases and unhealthy behavior on CVD were assessed using the relative excess risk due to interaction and attributable proportion measures. Results There was a statistically significant interaction between long working hours and chronic diseases within the population, especially among male participants (P‐value for interaction <.01 and .03, respectively). There were no significant interactions between unhealthy behavior and long working hours. Conclusions Long working hours and chronic disease have a synergistic negative effect on the risk of CVD.

Objectives We aimed to explore the association between long working hours and health‐related productivity loss (HRPL), due to either sickness, absenteeism or presenteeism, stratified by household income level. Methods From January 2020 to February 2020, data were collected using a web‐based questionnaire. A total of 4197 participants were randomly selected using the convenience sampling method. The nonparametric association between weekly working hours and HRPL was determined. Subsequently, a stratified analysis was conducted according to household income (1st, 2nd, and 3rd tertiles). Finally, the differences in HRPL of the different working hour groups (<40, 40, 40‐51, and ≥52 hours) were investigated using a multivariate linear regression model. Results Long working hours were more significantly associated with HRPL, as compared to the ‘standard’ working hours (40 hours/week). A larger proportion of productivity loss was associated with the presenteeism of workers, rather than absenteeism. The relationship between HRPL and weekly working hours was more prominent in the lower household income group. Conclusions The results of our study indicate that HRPL is associated with long working hours, especially in the lower household income group. Reducing the workload for the individual employee to a manageable level and restructuring sick leave policies to effectively counteract absenteeism and presenteeism may be a feasible option for better labor productivity and employee health.