PURPOSE: This study aimed to determine the relationships between particulate matter risk perception, knowledge, and perceived barriers and health-promoting behaviors among college students. METHODS: Data for this cross-sectional study were collected from September 1 to 30, 2017. The study sample consisted of 85 students from a university, Seoul. Students not living in the Seoul metropolitan area during the spring 2017 semester were excluded from participation. Pearson's correlation coefficient was used to identify relationships among study variables. RESULTS: A significant positive correlation existed between particulate matter risk perception and health-promoting behaviors related to particulate matter (r=.51, p < .001). Among the risk perception subdomains, attention (r=.47, p < .001) and health effect (r=.55, p < .001) showed strong positive relationships with health-promoting behaviors. No significant relationships were found between knowledge (r=.12, p=.288) or perceived barriers (r=−.12, p=.264) and health-promoting behaviors related to particulate matter. CONCLUSION: Based on the study results, strategies for enhancing particulate matter risk perception are needed to increase the level of health-promoting behaviors related to particulate matter among college students.
Cross-Sectional Studies ; Health Promotion ; Humans ; Particulate Matter ; Seoul

BACKGROUND: Detection of the viral load of Human Immunodeficiency Virus type 1 (HIV-1) RNA is important for clinical decision making and for determining the prognosis of HIV-infected patients. The aim of the study is to compare the performance of real-time RT-PCR (COBAS AmpliPrep/COBAS TaqMan HIV-1, CAP/CTM, Roche Diagnostics) and the Nucleic Acid Sequence Based Amplification (NucliSens EasyQ HIV-1, NucliSens, BioMerieux) methods for testing Korean HIV-infected patients. METHODS: Among the specimens that were requested to undergo HIV-1 RNA viral load detection from 2005 to 2006, 153 specimens were selected based on the status of the specimens. The CAP/CTM and NucliSens tests were performed according to the manufacturer's instruction. RESULTS: HIV-1 RNA was detected by both tests in 93 specimens. Among the remainder, CAP/CTM detected HIV-1 RNA in 10 specimens, while the same specimens showed results lower than the detection limit with using the NucliSens. Though the results were appropriately correlated (r=0.85, P<0.0001), the mean differences between the two test results were -0.1321 log(10) IU/mL on the Bland-Altman test. CONCLUSION: The methodologic difference or the presence of a HIV subtype may affect the agreement between the two tests. The standardization of methods and the establishment of a linear range for the individual laboratory results may be helpful to obtain accurate test results.
Decision Making ; HIV ; HIV-1 ; Humans ; Limit of Detection ; Prognosis ; RNA ; Self-Sustained Sequence Replication ; Viral Load

OBJECTIVE: We examined the difference between IQ(Intelligence Quotient) estimated from computerized Standard Progressive Matrices(SPM) score(SPM IQ) and Korean-Wechsler Adult Intelligence Scale(KWAIS) IQ(KWAIS IQ) in Korean patients with mental disorders in order to test the validity of SPM as a brief nonverbal intelligence test, and to find the groups that need standardization. And, we studied the method to predict KWAIS IQ more precisely from SPM test. METHODS: SPM test in Vienna test system was administered to 166 Korean patients with mental disorders. The degree of consistency and Pearson's correlation coefficient between SPM IQ and KWAIS IQ in total subjects and groups by sex, age, education, and clinical diagnosis were investigated. And, we obtained a regression equation to predict KWAIS IQ from SPM score. RESULTS: In total subjects, Pearson's correlation coefficient between SPM IQ and KWAIS IQ was as high as 0.704, and the percent of patients whose absolute value of difference between SPM IQ and KWAIS IQ is equal to or less than 10 was 54.8%. The degree of consistency between SPM IQ and KWAIS IQ was influenced by age and educational level. SPM IQ were higher than KWAIS IQ in younger age and lower education group. SPM IQ were lower than KWAIS IQ in older age and higher education group. The regression equation from SPM score, age, and education years predicted KWAIS IQ more correctly. CONCLUSION: The Computerized Standard Progressive Matrices test is validated and can be used usefully as a brief nonverbal intelligence test in patients with mental disorders. In order to provide more precise evaluation, standardized data should be prepared for age group 16 to 25 and age group 26 to 35 with lower educational level.
Adult ; Diagnosis ; Education ; Humans ; Intelligence ; Intelligence Tests ; Mental Disorders*

BACKGROUND: Patients with Alzheimer's disease (AD) at an early stage present with memory decline and impairments of language and visuospatial functions. However, some AD patients occasionally show frontal lobe dysfunctions in the early stage those are known to emerge only at the advanced stage. This subtype of AD is called a frontal variant of AD (frontal AD). We report neuropsychological and FDG-PET findings of three cases of frontal AD. METHODS: Three patients met the diagnostic criteria of probable AD proposed by the NINCDS-ADRDA. However, they unusually showed clinical symptoms associated with frontal lobe dysfunctions even if they were relatively in the early stage of dementia. All the patients underwent neuropsychological tests and brain FDG-PET scans. Distribution of glucose hypometabolism was analyzed using statistical parametric mappings (SPM). RESULTS: Results of neuropsychological tests were consistent with findings of AD except that frontal lobe dysfunctions were prominent. FDG-PET scans and SPM analysis of these images showed hypometabolism in the frontal as well as temporo-parietal regions. Unlike the hypometabolism pattern found in frontotemporal dementia, frontal hypometabolism in our patients was not as severe as parietal hypometablism and hypometabolic regions within the temporal lobe were in the middle or posterior part of the middle and inferior temporal gyri rather than in the anterior part. CONCLUSIONS: Detailed neuropsycholgical tests and FDG-PET may help differentiate AD with frontal involvement in its early stage (frontal AD) from frontotemporal dementia. Future studies with FDG-PET in a larger series of frontal AD cases, especially with histologically proven cases, may be needed.
Alzheimer Disease* ; Brain ; Dementia ; Frontal Lobe ; Frontotemporal Dementia ; Glucose ; Humans ; Memory ; Neuroimaging* ; Neuropsychological Tests ; Rabeprazole ; Temporal Lobe

Objectives: In this study, we aimed to compare the genetic architecture of schizophrenia (SCZ) and bipolar disorder (BD) in a Korean population by analyzing polygenic risk scores (PRS) derived from large-scale psychiatric disorder genome-wide association study data, based on genetic information collected from SCZ, BD, and healthy control groups. Methods: The study included 713 Korean patients with SCZ, 1,317 with BD, 526 healthy controls. Genotyping was performed using the Korean Biobank Array. PRS-continuous shrinkage method was used to calculate the PRS. Analysis of covariance (ANCOVA) was conducted to determine the association between SCZ or BD disorder and PRS after adjusting for sex. Results: ANCOVA revealed significant differences in PRS values by diagnosis for PRS for SCZ (F=215.281, p<0.001), PRS for BD (F=13.811, p<0.001), and PRS for major depressive disorder (F=6.042, p=0.002). Post-hoc analysis showed that PRS for SCZ was highest in SCZ, followed by BD, and healthy controls. PRS for BD was elevated in both BD and SCZ compared to healthy controls. Conclusion Our study revealed quantitative differences in genetic architecture between SCZ and BD compared to healthy controls, while also suggesting a shared genetic background between the two disorders.

Objectives: In this study, we aimed to compare the genetic architecture of schizophrenia (SCZ) and bipolar disorder (BD) in a Korean population by analyzing polygenic risk scores (PRS) derived from large-scale psychiatric disorder genome-wide association study data, based on genetic information collected from SCZ, BD, and healthy control groups. Methods: The study included 713 Korean patients with SCZ, 1,317 with BD, 526 healthy controls. Genotyping was performed using the Korean Biobank Array. PRS-continuous shrinkage method was used to calculate the PRS. Analysis of covariance (ANCOVA) was conducted to determine the association between SCZ or BD disorder and PRS after adjusting for sex. Results: ANCOVA revealed significant differences in PRS values by diagnosis for PRS for SCZ (F=215.281, p<0.001), PRS for BD (F=13.811, p<0.001), and PRS for major depressive disorder (F=6.042, p=0.002). Post-hoc analysis showed that PRS for SCZ was highest in SCZ, followed by BD, and healthy controls. PRS for BD was elevated in both BD and SCZ compared to healthy controls. Conclusion Our study revealed quantitative differences in genetic architecture between SCZ and BD compared to healthy controls, while also suggesting a shared genetic background between the two disorders.

Objectives: In this study, we aimed to compare the genetic architecture of schizophrenia (SCZ) and bipolar disorder (BD) in a Korean population by analyzing polygenic risk scores (PRS) derived from large-scale psychiatric disorder genome-wide association study data, based on genetic information collected from SCZ, BD, and healthy control groups. Methods: The study included 713 Korean patients with SCZ, 1,317 with BD, 526 healthy controls. Genotyping was performed using the Korean Biobank Array. PRS-continuous shrinkage method was used to calculate the PRS. Analysis of covariance (ANCOVA) was conducted to determine the association between SCZ or BD disorder and PRS after adjusting for sex. Results: ANCOVA revealed significant differences in PRS values by diagnosis for PRS for SCZ (F=215.281, p<0.001), PRS for BD (F=13.811, p<0.001), and PRS for major depressive disorder (F=6.042, p=0.002). Post-hoc analysis showed that PRS for SCZ was highest in SCZ, followed by BD, and healthy controls. PRS for BD was elevated in both BD and SCZ compared to healthy controls. Conclusion Our study revealed quantitative differences in genetic architecture between SCZ and BD compared to healthy controls, while also suggesting a shared genetic background between the two disorders.

Objectives: In this study, we aimed to compare the genetic architecture of schizophrenia (SCZ) and bipolar disorder (BD) in a Korean population by analyzing polygenic risk scores (PRS) derived from large-scale psychiatric disorder genome-wide association study data, based on genetic information collected from SCZ, BD, and healthy control groups. Methods: The study included 713 Korean patients with SCZ, 1,317 with BD, 526 healthy controls. Genotyping was performed using the Korean Biobank Array. PRS-continuous shrinkage method was used to calculate the PRS. Analysis of covariance (ANCOVA) was conducted to determine the association between SCZ or BD disorder and PRS after adjusting for sex. Results: ANCOVA revealed significant differences in PRS values by diagnosis for PRS for SCZ (F=215.281, p<0.001), PRS for BD (F=13.811, p<0.001), and PRS for major depressive disorder (F=6.042, p=0.002). Post-hoc analysis showed that PRS for SCZ was highest in SCZ, followed by BD, and healthy controls. PRS for BD was elevated in both BD and SCZ compared to healthy controls. Conclusion Our study revealed quantitative differences in genetic architecture between SCZ and BD compared to healthy controls, while also suggesting a shared genetic background between the two disorders.