The Korean Journal of Internal Medicine Vol. 29, No. 5 (Suppl. 1)
WCIM 2014 SEOUL KOREA 333
Poster Session
PS 1320 Endocrinology
Analysis of Anthropometric Indices to Predict Athero- sclerosis between Pre and Post-Menopausal Women
Hyun Jung Lee1, Ja Young Ryu1, Ho Cheol Hong1, Kyung Mook Choi1, Sei Hyun Baik1, Hye Jin Yoo1
Korea University Medical Center, Korea1
Background: Fat distribution may become more central, or android, after menopause.
Although many studies have been performed to identify superiority among anthropo- metric indices to predict cardiovascular disease (CVD) risk in individuals with all age ranges or with different ethnic groups or with type-2 diabetes, studies to evaluate the association between menopausal status and indicators of atherosclerosis are limited.
Thus, the objective of the present study is to assess the effi cacy of body mass index (BMI), waist circumference (WC) and waist-to-hip ratio (WHR) for predicting athero- sclerosis in pre and post-menopausal women.
Methods: A total of 442 participants (209 pre-menopausal and 233 post-meno- pausal women), who underwent a health examination between April 2012 and May 2013 were prospectively enrolled. We investigated the efficacy of each anthropo- metric marker including BMI, WC and WHR for predicting atherosclerosis in pre and post-menopausal women by carotid intima-media thickness (CIMT) and brachial ankle pulse wave velocity (baPWV) in healthy Korean women.
Results: Compared with post-menopausal women, pre-menopausal women had a thinner WC (76cm and 71cm respectively), and had a lower BMI (23.2 kg/m2 and 21.8 kg/m2 respectively) and WHR (0.9 and 0.8 respectively). In pre-menopausal women all anthropometric parameters (BMI, WC, WHR) are positively correlated to baPWV (0.20, 0.19 and 0.21, P < 0.01, respectively), and CIMT values (0.36, 0.34 and 0.27, P < 0.01, respectively) whereas in post-menopausal women only WHR was positively correlated to baPWV values (0.27, P < 0.01) and WC, WHR were positively correlated to CIMT (0.15, P < 0.05 and 0.21, P < 0.01, respectively) The correlation coeffi cient in all parameters of CIMT was signifi cantly higher in WHR than WC in post-menopausal women.
Conclusions: This study shows that WHR has the best predict value for predicting atherosclerosis than BMI or WC in post-menopausal women.
PS 1321 Endocrinology
A Retrospective, Observational Dose-Titration Study of Pioglitazone in Subjects with Type 2 Diabetes Mellitus with Inadequate Glycemic Control on 15mg of Pioglita- zone
So Young Ha1, Jung Hyun No1, Dong Jun Kim1 Inje University Ilsan Paik Hospital, Korea1
Background: Pioglitazone is known to improve insulin sensitivity, glycemic control in patients with T2DM. In spite of these advantages of pioglitazone, there are also concerns about the risk of adverse events. In practice, the usual initial and maintain- ing dosages of pioglitazone are 15mg although the maximal recommended dosage is 30mg in Korea. we planned to analyze the effi cacy and safety of pioglitazone when dose was up-titrated to 30mg in subjects with type 2 diabetes mellitus with inade- quate glycemic control on 15mg of pioglitazone retrospectively.
Methods: This is a single-arm, retrospective, observational study. Subjects (45 diabe- tes patients) must had been on a stable dose of 15 mg of pioglitazone for at least 3 months before dose titration to be eligible to enter the study. The combined treat- ments with stable doses of metformin or/and sulfonylurea will be allowed.
Results: HbA1c were decreased in 3 months and 6 months after 10mg pioglitazone treatment (HbA1c, base line :8.4 ± 0.84 vs 3 months : 8.1 ± 0.8 vs 6 months : 7.8 ± 0.8, P < 0.01). Body Weight increased in 3 months and 6 months after 10mg pioglitazone treatment. ( n = 44, Body weight, base line : 71.3± 7.9 vs 3 months : 70.8 ± 7.7 vs 6 months : 71.3 ± 8.2, P < 0.01).
Conclusions: Korean diabetes patients with 10mg pioglitazone use showed favorable metabolic effect for glycemic control, but dose up titration of pioglitazone increased the disadvantage of increasing the weight.
PS 1322 Endocrinology
The Relationship between Socioeconomic Status (SES) and Insulin Resistance(IR) in Non-Diabetic Adult
Suk yeon Kim1, Jun Goo Kang1, Chul Sik Kim1, Seong Jin Lee1, Sung-Hee Ihm1 Hallym University Sacred Heart Hospital, Korea1
Background: To investigate the relationship between socioeconomic status (SES) and insulin resistance(IR) in non-diabetic adult. Korea National Health and Nutrition Exam- ination Survey 2008–2010.
Methods: We analyzed the Korean National Health and Nutrition Examination Survey (2008-2010). Adult participants aged =30 years without diabetes in adult. SES, as measured by house income or education level. IR was assessed by homeostasis model assessment-insulin resistance (HOMA-IR). The adjusted OR for IR was calculated using multivariate logistic regression analysis across house income and education level quar- tiles.
Results: The adjusted OR (95% CI) for IR for the lowest vs. highest quartile of house income and education level were 0.66(0.55, 0.81) and 0.71(0.56, 0.90) in MODEL1, de- termined by multiple logistic regression analysis after adjusting for age, year in Korean non diabetic adult women. The adjusted OR (95% CI) for IR for the lowest vs. highest quartile of house income were 0.71(0.56, 0.90) in MODEL2, adjusted for model 1 plus BMI, place, occupation, smoking, alcohol, drinking, exercise, spouse, total energy, fat intake, house income level and education level. However, such relationship was not found among education level in model2.
Conclusions: The adjusted OR (95% CI) for IR for the lowest vs. highest quartile of house income and education level were 0.66(0.55, 0.81) and 0.71(0.56, 0.90) in MOD- EL1, determined by multiple logistic regression analysis after adjusting for age, year in Korean non diabetic adult women. The adjusted OR (95% CI) for IR for the lowest vs.
highest quartile of house income were 0.71(0.56, 0.90) in MODEL2, adjusted for model 1 plus BMI, place, occupation, smoking, alcohol, drinking, exercise, spouse, total energy, fat intake, house income level and education level. However, such relationship was not found among education level in model2.
