1.Long-Term Exposure to Ambient Air Pollution and Metabolic Syndrome and Its Components
Hyun-Jin KIM ; Juyeon HWANG ; Jin-Ho PARK
Journal of Obesity & Metabolic Syndrome 2025;34(2):91-104
Ambient air pollution is a serious public health issue worldwide. A growing number of studies has highlighted the negative effects of air pollution on metabolic syndrome (MetS) and its components, including abdominal obesity, disorders of lipid metabolism, elevated blood pressure, and impaired fasting blood glucose. This review provides a brief overview of epidemiological and genetic interaction studies of the links between chronic exposure to ambient air pollution and MetS and its components, as well as plausible mechanisms underlying these relationships. The cumulative evidence suggests that long-term exposure to air pollution, especially particulate matter, increases the risk of MetS and its components. These associations can be partly modified by baseline characteristics, lifestyle, and health conditions. Gene-by-air-pollution interaction studies, limited to candidate genes in the past, have recently been conducted at an expanded genome-wide level. However, more such studies are needed to comprehensively understand the genetics involved in the association between air pollution and MetS. Mechanistic evidence suggests potential biological pathways, including inflammation, oxidative stress, and endothelial dysfunction.
2.Long-Term Exposure to Ambient Air Pollution and Metabolic Syndrome and Its Components
Hyun-Jin KIM ; Juyeon HWANG ; Jin-Ho PARK
Journal of Obesity & Metabolic Syndrome 2025;34(2):91-104
Ambient air pollution is a serious public health issue worldwide. A growing number of studies has highlighted the negative effects of air pollution on metabolic syndrome (MetS) and its components, including abdominal obesity, disorders of lipid metabolism, elevated blood pressure, and impaired fasting blood glucose. This review provides a brief overview of epidemiological and genetic interaction studies of the links between chronic exposure to ambient air pollution and MetS and its components, as well as plausible mechanisms underlying these relationships. The cumulative evidence suggests that long-term exposure to air pollution, especially particulate matter, increases the risk of MetS and its components. These associations can be partly modified by baseline characteristics, lifestyle, and health conditions. Gene-by-air-pollution interaction studies, limited to candidate genes in the past, have recently been conducted at an expanded genome-wide level. However, more such studies are needed to comprehensively understand the genetics involved in the association between air pollution and MetS. Mechanistic evidence suggests potential biological pathways, including inflammation, oxidative stress, and endothelial dysfunction.
3.Long-Term Exposure to Ambient Air Pollution and Metabolic Syndrome and Its Components
Hyun-Jin KIM ; Juyeon HWANG ; Jin-Ho PARK
Journal of Obesity & Metabolic Syndrome 2025;34(2):91-104
Ambient air pollution is a serious public health issue worldwide. A growing number of studies has highlighted the negative effects of air pollution on metabolic syndrome (MetS) and its components, including abdominal obesity, disorders of lipid metabolism, elevated blood pressure, and impaired fasting blood glucose. This review provides a brief overview of epidemiological and genetic interaction studies of the links between chronic exposure to ambient air pollution and MetS and its components, as well as plausible mechanisms underlying these relationships. The cumulative evidence suggests that long-term exposure to air pollution, especially particulate matter, increases the risk of MetS and its components. These associations can be partly modified by baseline characteristics, lifestyle, and health conditions. Gene-by-air-pollution interaction studies, limited to candidate genes in the past, have recently been conducted at an expanded genome-wide level. However, more such studies are needed to comprehensively understand the genetics involved in the association between air pollution and MetS. Mechanistic evidence suggests potential biological pathways, including inflammation, oxidative stress, and endothelial dysfunction.
4.Occupation classification model based on DistilKoBERT: using the 5th and 6th Korean Working Condition Surveys
Tae-Yeon KIM ; Seong-Uk BAEK ; Myeong-Hun LIM ; Byungyoon YUN ; Domyung PAEK ; Kyung Ehi ZOH ; Kanwoo YOUN ; Yun Keun LEE ; Yangho KIM ; Jungwon KIM ; Eunsuk CHOI ; Mo-Yeol KANG ; YoonHo CHO ; Kyung-Eun LEE ; Juho SIM ; Juyeon OH ; Heejoo PARK ; Jian LEE ; Jong-Uk WON ; Yu-Min LEE ; Jin-Ha YOON
Annals of Occupational and Environmental Medicine 2024;36(1):e19-
Accurate occupation classification is essential in various fields, including policy development and epidemiological studies. This study aims to develop an occupation classification model based on DistilKoBERT. This study used data from the 5th and 6th Korean Working Conditions Surveys conducted in 2017 and 2020, respectively. A total of 99,665 survey participants, who were nationally representative of Korean workers, were included. We used natural language responses regarding their job responsibilities and occupational codes based on the Korean Standard Classification of Occupations (7th version, 3-digit codes). The dataset was randomly split into training and test datasets in a ratio of 7:3. The occupation classification model based on DistilKoBERT was fine-tuned using the training dataset, and the model was evaluated using the test dataset. The accuracy, precision, recall, and F1 score were calculated as evaluation metrics. The final model, which classified 28,996 survey participants in the test dataset into 142 occupational codes, exhibited an accuracy of 84.44%. For the evaluation metrics, the precision, recall, and F1 score of the model, calculated by weighting based on the sample size, were 0.83, 0.84, and 0.83, respectively. The model demonstrated high precision in the classification of service and sales workers yet exhibited low precision in the classification of managers. In addition, it displayed high precision in classifying occupations prominently represented in the training dataset. This study developed an occupation classification system based on DistilKoBERT, which demonstrated reasonable performance. Despite further efforts to enhance the classification accuracy, this automated occupation classification model holds promise for advancing epidemiological studies in the fields of occupational safety and health.
5.Characteristic magnetic resonance imaging Features of Disorders Causing Dorsal Column Myelopathy
Juyeon YI ; Hyung Jun PARK ; Bio JOO ; Mina PARK ; Sang Hyun SUH ; Sung Jun AHN
Journal of Neurosonology and Neuroimaging 2024;16(2):71-85
The spinal cord is a complex and densely packed structure of nerve tissue, and magnetic resonance imaging (MRI) is an excellent imaging modality for evaluating its pathologies. Among the distinct functional zones of the spinal cord, the dorsal (or posterior) column is a crucial white matter region responsible for transmitting sensory information and is located in the posterior aspect of the spinal cord. Myelopathies of the dorsal column typically appear as high signal intensity in this region on T2-weighted images. They may arise from several pathological processes, including degenerative, metabolic, inflammatory, infectious, and traumatic conditions. Identifying the specific etiology through characteristic MRI features, along with the patient’s clinical presentation, is crucial for developing an effective treatment plan and understanding the prognosis of sensory abnormalities. This study reviews myelopathies that specifically affect the dorsal column and outlines the MRI findings that aid in the differential diagnosis of these dorsal column lesions.
6.Occupation classification model based on DistilKoBERT: using the 5th and 6th Korean Working Condition Surveys
Tae-Yeon KIM ; Seong-Uk BAEK ; Myeong-Hun LIM ; Byungyoon YUN ; Domyung PAEK ; Kyung Ehi ZOH ; Kanwoo YOUN ; Yun Keun LEE ; Yangho KIM ; Jungwon KIM ; Eunsuk CHOI ; Mo-Yeol KANG ; YoonHo CHO ; Kyung-Eun LEE ; Juho SIM ; Juyeon OH ; Heejoo PARK ; Jian LEE ; Jong-Uk WON ; Yu-Min LEE ; Jin-Ha YOON
Annals of Occupational and Environmental Medicine 2024;36(1):e19-
Accurate occupation classification is essential in various fields, including policy development and epidemiological studies. This study aims to develop an occupation classification model based on DistilKoBERT. This study used data from the 5th and 6th Korean Working Conditions Surveys conducted in 2017 and 2020, respectively. A total of 99,665 survey participants, who were nationally representative of Korean workers, were included. We used natural language responses regarding their job responsibilities and occupational codes based on the Korean Standard Classification of Occupations (7th version, 3-digit codes). The dataset was randomly split into training and test datasets in a ratio of 7:3. The occupation classification model based on DistilKoBERT was fine-tuned using the training dataset, and the model was evaluated using the test dataset. The accuracy, precision, recall, and F1 score were calculated as evaluation metrics. The final model, which classified 28,996 survey participants in the test dataset into 142 occupational codes, exhibited an accuracy of 84.44%. For the evaluation metrics, the precision, recall, and F1 score of the model, calculated by weighting based on the sample size, were 0.83, 0.84, and 0.83, respectively. The model demonstrated high precision in the classification of service and sales workers yet exhibited low precision in the classification of managers. In addition, it displayed high precision in classifying occupations prominently represented in the training dataset. This study developed an occupation classification system based on DistilKoBERT, which demonstrated reasonable performance. Despite further efforts to enhance the classification accuracy, this automated occupation classification model holds promise for advancing epidemiological studies in the fields of occupational safety and health.
7.Occupation classification model based on DistilKoBERT: using the 5th and 6th Korean Working Condition Surveys
Tae-Yeon KIM ; Seong-Uk BAEK ; Myeong-Hun LIM ; Byungyoon YUN ; Domyung PAEK ; Kyung Ehi ZOH ; Kanwoo YOUN ; Yun Keun LEE ; Yangho KIM ; Jungwon KIM ; Eunsuk CHOI ; Mo-Yeol KANG ; YoonHo CHO ; Kyung-Eun LEE ; Juho SIM ; Juyeon OH ; Heejoo PARK ; Jian LEE ; Jong-Uk WON ; Yu-Min LEE ; Jin-Ha YOON
Annals of Occupational and Environmental Medicine 2024;36(1):e19-
Accurate occupation classification is essential in various fields, including policy development and epidemiological studies. This study aims to develop an occupation classification model based on DistilKoBERT. This study used data from the 5th and 6th Korean Working Conditions Surveys conducted in 2017 and 2020, respectively. A total of 99,665 survey participants, who were nationally representative of Korean workers, were included. We used natural language responses regarding their job responsibilities and occupational codes based on the Korean Standard Classification of Occupations (7th version, 3-digit codes). The dataset was randomly split into training and test datasets in a ratio of 7:3. The occupation classification model based on DistilKoBERT was fine-tuned using the training dataset, and the model was evaluated using the test dataset. The accuracy, precision, recall, and F1 score were calculated as evaluation metrics. The final model, which classified 28,996 survey participants in the test dataset into 142 occupational codes, exhibited an accuracy of 84.44%. For the evaluation metrics, the precision, recall, and F1 score of the model, calculated by weighting based on the sample size, were 0.83, 0.84, and 0.83, respectively. The model demonstrated high precision in the classification of service and sales workers yet exhibited low precision in the classification of managers. In addition, it displayed high precision in classifying occupations prominently represented in the training dataset. This study developed an occupation classification system based on DistilKoBERT, which demonstrated reasonable performance. Despite further efforts to enhance the classification accuracy, this automated occupation classification model holds promise for advancing epidemiological studies in the fields of occupational safety and health.
8.Risk Factors for Infertility in Korean Women
Juyeon LEE ; Chang-Woo CHOO ; Kyoung Yong MOON ; Sang Woo LYU ; Hoon KIM ; Joong Yeup LEE ; Jung Ryeol LEE ; Byung Chul JEE ; Kyungjoo HWANG ; Seok Hyun KIM ; Sue K. PARK
Journal of Korean Medical Science 2024;39(10):e85-
Background:
Female infertility is a crucial problem with significant implications for individuals and society. In this study, we explore risk factors for infertility in Korean women.
Methods:
A total of 986 female patients who visited six major infertility clinics in Korea were recruited from April to December 2014. Fertile age-matched controls were selected from two nationwide survey study participants. Conditional logistic regression after age-matching was used to estimate odds ratios (ORs) and 95% confidence intervals (CIs) of each risk factor for infertility.
Results:
Women with a body mass index (BMI) < 18.5 kg/m2 had 1.35 times higher odds of infertility (OR, 1.35; 95% CI, 1.03–1.77), while those with a BMI ≥ 25.0 kg/m2 had even higher odds (OR, 2.06; 95% CI, 1.61–2.64) compared to women with a normal BMI (18.5 kg/m2 ≤ BMI < 25 kg/m 2 ). Ever-smokers exhibited 4.94 times higher odds of infertility compared to never-smokers (95% CI, 3.45–8.85). Concerning alcohol consumption, women who consumed ≥ 7 glasses at a time showed 3.13 times significantly higher odds of infertility than those who consumed ≤ 4 glasses at a time (95% CI, 1.79–5.48). Lastly, women with thyroid disease demonstrated 1.44 times higher odds of infertility compared to women without thyroid disease (95% CI, 1.00–2.08).
Conclusion
Female infertility in Korea was associated with underweight, obesity, smoking, alcohol consumption, and thyroid disease.
9.Effect of local anesthetic volume (20 vs. 40 ml) on the analgesic efficacy of costoclavicular block in arthroscopic shoulder surgery: a randomized controlled trial
Yumin JO ; Chahyun OH ; Woo-Yong LEE ; Hyung-Jin CHUNG ; Hanmi PARK ; Juyeon PARK ; Jieun LEE ; Yoon-Hee KIM ; Youngkwon KO ; Woosuk CHUNG ; Boohwi HONG
Korean Journal of Anesthesiology 2024;77(1):85-94
Background:
Among the various diaphragm-sparing alternatives to interscalene block, costoclavicular block (CCB) demonstrated a low hemidiaphragmatic paresis (HDP) occurrence but an inconsistent analgesic effect in arthroscopic shoulder surgery. We hypothesized that a larger volume of local anesthetic for CCB could provide sufficient analgesia by achieving sufficient supraclavicular spreading.
Methods:
Sixty patients scheduled for arthroscopic rotator cuff repair were randomly assigned to receive CCB using one of two volumes of local anesthetic (CCB20, 0.75% ropivacaine 20 ml; CCB40, 0.375% ropivacaine 40 ml). The primary outcome was the rate of complete analgesia (0 on the numeric rating scale of pain) at 1 h postoperatively. The secondary outcomes included a sonographic assessment of local anesthetic spread, diaphragmatic function, pulmonary function, postoperative opioid use, and other pain-related experiences within 24 h postoperatively.
Results:
The rates of complete analgesia were not significantly different (23.3% [7/30] and 33.3% [10/30] in the CCB20 and CCB40 groups, respectively; risk difference 10%, 95% CI [–13, 32], P = 0.567). There were no significant differences in other pain-related outcomes. Among the clinical factors considered, the only factor significantly associated with postoperative pain was the sonographic observation of supraclavicular spreading. There were no significant differences in the incidence of HDP and the change in pulmonary function between the two groups.
Conclusions
Using 40 ml of local anesthetic does not guarantee supraclavicular spread during CCB. Moreover, it does not result in a higher rate of complete analgesia compared to using 20 ml of local anesthetic in arthroscopic shoulder surgery.
10.Identification of Organic Solvents in Agrochemicals Intoxication Cases
Meejung PARK ; Sohyun KIM ; Junghyun KIM ; Heejin PARK ; Juyeon LEE ; Sungmin MOON
Korean Journal of Legal Medicine 2024;48(2):35-40
In South Korea, deaths caused by poisoning are mostly suicides due to drug overdoses, or agrochemical poisonings. Even though the latter is becoming less frequent, they are still occurring in large numbers across the country. In some cases, deaths result from toxicity of organic solvents contained in the agrochemical products. In this study, we identified organic solvents in post-mortem blood of acute agrochemical poisoning cases using solid phase microextraction-gas chromatography/mass spectrometry with black fiber. Out of 42 cases, organic solvents were detected in 29, with toluene and butanol detected simultaneously in 13 cases. In these 13 cases, the original pesticides were of various types, including organophosphorus compounds, carbamate, nicotine, and oxadiazine. Xylene and ethyl benzene were simultaneously detected six times. In these six cases, the original pesticides were mainly pyrethroid-based pesticides, such as cypermethrin and deltamethrin. Methoxypropanol was detected in five cases in which the water-soluble pesticide glufosinate was detected. These organic solvents may cause acute poisoning and even death in some agrochemical poisoning cases.

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