• Korean Journal of Psychosomatic Medicine
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• v.25 no.1
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• pp.27-32
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• 2017

Objectives : The purpose of this study was to determine the association between serum lipid profiles and depression according to gender difference. Methods : This retrospective cohort study included 27,452 subjects(15044 men and 12408 women) who underwent health examination. The duration was from January 2013 to December 2013. We estimate the correlation between serum lipid profile and Beck Depression Inventory(BDI) scores. We compare the effect size using beta coefficient. Results : In men, serum Triglyceride level was correlated positively with BDI scores(r=0.020, p<0.01). Serum LDL-C and HDL-C were negatively correlated with BDI scores(r=-0.015, p<0.01 ; r=-0.016, p<0.05). In women, Triglyceride level was also correlated positively with BDI scores(r=0.020, p<0.01), Serum HDL-C were negatively correlated with BDI scores(r=-0.019, p<0.01). There was no statistical significance between Serum LDL-C and Beck Depression Inventory(BDI) score. Conclusions : Both men and women had more depressive symptoms when they had low serum HDL-C level or high serum Triglyceride level. The depression symptoms were more severe when serum LDL-C level was low only in men.

• Anxiety and mood
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• v.7 no.1
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• pp.16-21
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• 2011

Objective : Depressive symptoms often coexist with other anxiety disorder symptoms. Furthermore, an anxiety disorder that is comorbid with a depressive disorder results in more severe symptoms and a poorer outcome prognosis. To understand the construct of depressive symptoms in anxiety disorder, this study investigated the factor structure of the Beck Depression Inventory among outpatients with anxiety disorders. Methods : All data were from psychiatric department outpatients at a university-affiliated hospital. We conducted a principal component analysis using data from 194 outpatients with DSM-IV anxiety disorders and calculated goodness-of-fit-indices. Results : Exploratory factor analysis revealed a four factor structure--Cognitive-affective symptoms (Factor 1), Somatic symptoms (Factor 2), Self-reproach (Factor 3), and Hypochondriasis/indecisiveness (Factor 4)--and a 57% total variance. This four-factor model demonstrated an acceptable level of model fit, and it fit better than did a three-factor solution from the literature on depressive disorder. Conclusion : This study's results suggest a difference in the construct of self-reported depressive symptoms in anxiety disorders. These findings also support a dimensional approach to studying anxiety and depression. Further studies may benefit from including comorbid depressive disorder and its influence on anxiety disorders.

• Korean Journal of Psychosomatic Medicine
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• v.28 no.1
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• pp.53-62
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• 2020

Objectives : This study investigated lifetime experiences of trauma, treatment retention, and psychiatric symptoms among outpatients with panic disorder after initiation of pharmacotherapy. Our research hypothesis was that panic patients with childhood trauma would display more severe symptoms and less treatment retention compared to those without such history. Methods : A total of 135 first-visit outpatients with DSM-IV panic disorder were approached during the period from March 2012 to August 2016. Fifty-three patients (39%) either refused or returned incomplete questionnaires, leading to a final sample size of 82. Participants completed the Trauma History Screen, the Beck Depression Inventory, the Beck Anxiety Inventory, and the Abbreviated PTSD checklist. Results : The number of lifetime trauma was significantly correlated with treatment retention (rho=-0.269, p=0.015). Among subtypes of trauma, only childhood physical abuse was significantly correlated with treatment retention (rho=-0.298, p=0.007). Conclusions : Our results indicated that psychological trauma, particularly of an interpersonal nature from childhood, can affect pharmacotherapy treatment retention in panic disorder. This may be mediated by poor patient-doctor relationships originating from trust issues among childhood trauma survivors or lack of perceived improvement due to the more severe symptoms and unfavorable course experienced by those with childhood trauma. Further studies are needed to explore the reasons for poor treatment adherence in this population.

• Sleep Medicine and Psychophysiology
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• v.22 no.1
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• pp.11-19
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• 2015

Objectives: Whether daytime sleepiness is proportional to the severity of sleep apnea in obstructive sleep apnea syndrome (OSAS) is controversial. In this study we investigated how insomnia severity affects the association between daytime sleepiness and sleep apnea severity in OSAS. Methods: The present study included 235 male subjects who were diagnosed with OSAS based on clinical history and nocturnal polysomnography. Pearson's correlation analysis was conducted among sleep and mood-related self-reported data, polysomnographic data and demographic data of all subjects. Based on Pittsburgh Sleep Quality Index (PSQI), the subjects were divided into 2 groups; group A (n = 75; $PSQI{\leq}5$) and group B (n = 160; PSQI > 5). Partial correlation analysis was performed between the Epworth Sleepiness Scale (ESS) and other data in both groups. Multiple linear regression analysis was conducted to investigate the factors which affected the ESS in group A. Results: Pearson's correlation analysis showed weak or non-existent correlations between ESS and apnea severity data such as apnea-hypopnea index (AHI) (r = 0.148, p = 0.023), apnea index (AI) (r = 0.137, p = 0.036), hypopnea index (HI) (r = 0.058, p = 0.377), oxygen desaturation index (ODI) (r = 0.149, p = 0.022) and arousal total index (ATI) (r = 0.129, p = 0.048). Positive correlations between ESS and apnea severity data such as AHI ($r_p=0.313$, p = 0.008), AI ($r_p=0.339$, p = 0.004), ODI ($r_p=0.289$, p = 0.015) and ATI ($r_p=0.256$, p = 0.031) were observed only in group A. Multiple regression analysis showed that AI (t = 2.996, p = 0.004) and BAI (t = 2.721, p = 0.008) were associated with ESS in group A. Conclusion: The correlation between daytime sleepiness and sleep apnea severity was shown only in group A. This result suggests that associations between daytime sleepiness in OSAS and sleep apnea severity will become prominent when controlling for insomnia-related variables.

• Sleep Medicine and Psychophysiology
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• v.25 no.2
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• pp.51-57
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• 2018

Objectives: Previous studies have shown that periodic limb movements in sleep (PLMS) could be one of risk factors for cardiovascular morbidity. The purpose of this study was to investigate the association between PLMS and blood pressure changes during sleep. Methods: We analyzed data from 358 adults (176 men and 182 women) aged 18 years and older who were free from sleep apnea syndrome (Respiratory Disturbance Index < 5) and sleep disorders such as REM sleep behavior disorder or narcolepsy. Demographic characteristics, polysomnography records, and clinical variable data including blood pressure, body mass index, alcohol, smoking, and current medications were collected. In addition, self-report questionnaires including the Beck Depression Index, Epworth Sleepiness Scale and Pittsburgh Sleep Quality Index were completed. Blood pressure change from bedtime to awakening was compared between the two periodic limb movement index (PLMI) groups [low PLMI ($PLMI{\leq}15$) and high PLMI (PLMI > 15)]. Blood pressure change patterns were compared using repeated measures analysis of variance. Results: Systolic blood pressure in the high PLMI group was lower than that in the low PLMI group (p = 0.036). These results were also significant when adjusted for gender and age, but were not statistically significant when adjusted for BMI, alcohol, smoking, anti-hypertension medication use and sleep efficiency (p = 0.098). Systolic blood pressure dropped by 9.7 mm Hg in the low PLMI group, and systolic blood pressure in the high PLMI group dropped by 2.9 mm Hg. There was a significant difference in delta systolic blood pressure after sleep between the two groups in women when adjusted for age, BMI, alcohol, smoking, antihypertensive medication use and sleep efficiency (p = 0.023). Conclusion: PLMS was significantly associated with a decreasing pattern in nocturnal BP during sleep, and this association remained significant in women when adjusted for age, BMI, alcohol, smoking, antihypertension medication use and sleep efficiency related to blood pressure. We suggest that PLMS may be associated with cardiovascular morbidity.