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1.
Journal of Zhejiang University. Medical sciences ; (6): 255-259, 2006.
Article in Chinese | WPRIM | ID: wpr-332162

ABSTRACT

<p><b>OBJECTIVE</b>To investigate the difference between serum true insulin (TI) and immunoreactive insulin (IRI) in evaluating islet beta-cell function and insulin resistance.</p><p><b>METHODS</b>The arginine stimulation test was performed in 141 individuals, including 35 with normal glucose tolerance (NGT) and 106 with type 2 diabetes (T2DM). Plasma glucose (PG), TI, IRI and proinsulin (PI) levels were measured; the incremental value of TI/PG, (TI+PI)/PG and IRI/PG (delta TI/PG, delta(TI+PI)/PG and deltaIRI/PG) and the area under curve of TI/PG, (TI+PI)/PG and IRI/PG (AUC [TI/PG], AUC[(TI+PI)/PG] and AUC [IRI/PG]) after arginine stimulation were calculated to evaluate beta-cell function.</p><p><b>RESULT</b>There were positive correlations of delta TI/PG with delta (TI+PI)/PG and delta IRI/PG in both NGT and T2DM patients (r=0.68 - 0.99, P<0.01). The similar correlations of AUC [TI/PG] with AUC [(TI+PI)/PG] and AUC [IRI/PG] were also shown (r=0.62 - 0.99, P<0.01). delta TI/PG was correlated with AUC [TI/PG] in two groups (NGT r=0.96, T2DM r=0.82, P<0.01). HOMA-IRTI, HOMA-IR(TI+PI) and HOMA-IRIRI in T2DM were higher than those in NGT (P<0.01). After arginine stimulation T2DM subjects mainly presented insulin resistance and decreased insulin secretion.</p><p><b>CONCLUSION</b>The determination of TI may be more accurate than IRI in evaluating beta-cell function and insulin resistance.</p>


Subject(s)
Adult , Aged , Female , Humans , Male , Middle Aged , Arginine , Pharmacology , Blood Glucose , Metabolism , Diabetes Mellitus, Type 2 , Blood , Glucose Tolerance Test , Insulin , Blood , Allergy and Immunology , Insulin Resistance , Insulin-Secreting Cells , Physiology , Proinsulin , Blood
2.
Chinese Journal of Epidemiology ; (12): 65-68, 2004.
Article in Chinese | WPRIM | ID: wpr-246367

ABSTRACT

<p><b>OBJECTIVE</b>To study the relationship between the prevalence of microalbuminuria and components of metabolic syndrome in Shanghai.</p><p><b>METHODS</b>A total of 3532 Shanghai Chinese (men 1622, women 1910) aged over 20 years were included. Body mass index (BMI), blood pressure, fasting plasma glucose, lipid profile and plasma insulin concentrations were measured in all subjects. Oral glucose tolerance test was performed in those subjects without knowing the diabetic history. Urinary albumin-to-creatinine ratio (ACR) was measured in an early morning spot urine sample. Microalbuminuria was diagnosed when ACR was between 30 and 300 mg/g.</p><p><b>RESULTS</b>(1) The prevalence of microalbuminuria was increasing with aging (P < 0.001). When compared with subjects having normal ACR, the waist-hip ratio, systolic and diastolic pressure, serum triglyceride level, fasting plasma glucose and homeostasis model assessment-insulin resistance (HOMA-IR) were all significantly increased in those subjects with microalbuminuria. (2) Along with the increment of number of items on metabolic disorders, the prevalence of microalbuminuria was significantly increased (P for trend < 0.001). (3) Multiple logistic regression analyses revealed that hypertension and hyperglycemia were independent factors associated with microalbuminuria (OR = 2.15, P < 0.001 and OR = 1.64, P = 0.01 respectively). Those subjects with two or more items on metabolic disorders had higher odd ratio for the development of microalbuminuria (OR = 3.93 and 4.77, both P < 0.001) when compared with the subjects without metabolic disorder.</p><p><b>CONCLUSION</b>The prevalence of microalbuminuria was independently associated with hypertension and hyperglycemia. The subjects with multiple metabolic abnormalities had higher risk for the development of microalbuminuria, especially in metabolic syndrome.</p>


Subject(s)
Adult , Female , Humans , Male , Albuminuria , Epidemiology , Blood Glucose , Metabolism , Blood Pressure , China , Epidemiology , Insulin , Blood , Insulin Resistance , Physiology , Logistic Models , Metabolic Diseases , Prevalence , Random Allocation , Risk Factors , Triglycerides , Blood
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