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High-Sensitivity C-Reactive Protein Leads to Increased Incident Metabolic Syndrome in Women but Not in Men: A Five-Year Follow-Up Study in a Chinese Population
Polycystic ovary syndrome (PCOS) is a common reproductive disorder. Obesity, which is linked with lower adiponectin levels, increases a woman's risk of developing PCOS; however, the association between adiponectin and PCOS is controversial. Adiponectin levels could be affected by single nucleotide polymorphisms (SNPs) in the
One hundred and fifty-four women with PCOS and 149 age- and body mass index–matched normally menstruating controls were recruited. Serum adiponectin levels were measured using enzyme-linked immunosorbent assay. Genotyping was performed using polymerase chain reaction–restriction fragment length polymorphism analysis.
Serum adiponectin levels were significantly lower (P=0.0064) in PCOS women and rs1501299 (+276 G/T) genotype distributions were significantly different (P=0.01) between them and normally menstruating women. Multivariate analysis revealed that adiponectin levels remained significantly lower in PCOS women (P=0.001; odds ratio [OR], 0.9; 95% confidence interval [CI], 0.84–0.96). The GT genotype of rs1501299 increased the risk of PCOS (P<0.001; OR, 5.46; 95% CI, 2.42–12.33) and increased the risk of PCOS by three-fold (P<0.001; OR, 3.00; 95% CI, 1.36–6.60) relative to the TT genotype. The GG genotype increased the risk of PCOS as well (P<0.001; OR, 3:00; 95% CI, 1.36–6.60).
PCOS is associated with lower serum adiponectin levels independent of age and body mass index. The T allele of the rs1501299 (+276 G/T) SNP of the
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Metabolic syndrome is associated with cardiovascular diseases and is characterized by insulin resistance. Recent studies suggest that the triglyceride/high-density lipoprotein cholesterol (TG/HDLC) ratio predicts insulin resistance better than individual lipid levels, including TG, total cholesterol, low-density lipoprotein cholesterol (LDLC), or HDLC. We aimed to elucidate the relationship between the TG/HDLC ratio and metabolic syndrome in the general Korean population.
We evaluated the data of adults ≥20 years old who were enrolled in the Korean National Health and Nutrition Examination Survey in 2013 and 2014. Subjects with angina pectoris, myocardial infarction, stroke, or cancer were excluded. Metabolic syndrome was defined by the harmonized definition. We examined the odds ratios (ORs) of metabolic syndrome according to TG/HDLC ratio quartiles using logistic regression analysis (SAS ver. 9.4; SAS Institute Inc., Cary, NC, USA). Weighted complex sample analysis was also conducted.
We found a significant association between the TG/HDLC ratio and metabolic syndrome. The cutoff value of the TG/HDLC ratio for the fourth quartile was ≥3.52. After adjustment, the OR for metabolic syndrome in the fourth quartile compared with that of the first quartile was 29.65 in men and 20.60 in women (P<0.001).
The TG/HDLC ratio is significantly associated with metabolic syndrome.
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Metabolic syndrome (MS) is known to increase the risk of various cardiometabolic diseases and in-sulin resistance (IR) has known to have central role in the development of MS. Many surrogate indices of IR have been proposed and the detection of MS might be a suitable model for assessing the accuracy of surrogate indices. The aims of our study are to invest the most appropriate index by assessment of the diagnostic capacity of IR among each surrogate index and identifying cut-off values for discriminating uncomplicated MS in Korean adults.
A cross-sectional study was performed, assessing 294 Korean adults, 85 of whom were diagnosed with uncomplicated MS. The sensitivities and specificities of five surrogate IR indices were compared to discriminate MS from healthy subjects; these included fasting serum insulin, homeostasis model assessment–insulin resistance index, quantitative insulin sensitivity check index, McAuley index, and Disse index. Correlations between each index value were assessed using Pearson's and Spearman's correlation methods.
The McAuley index showed the highest area under the curve (0.85), specificity (86.12%), accuracy (82.31%), positive predictive value (68.13%), and negative predictive value (88.67%) to distinguish MS, with a cut-off point of 5.3 defined. Correlation coefficients of the five indices showed that the McAuley index had the strongest correlation with IR.
The McAuley index showed the best accuracy in the detection of MS as a surrogate marker of IR. To establish more effective and accurate standards of measuring IR, comprehensive and multi-scaled studies are required.
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Menstrual irregularity is a common major complaint in women of reproductive age. It is also a known marker for underlying insulin resistance. We investigated the association between menstrual irregularity and metabolic syndrome in the general population of middle-aged women in Korea.
This cross-sectional study used data from the Korea National Health and Nutrition Examination Survey 2010–2012. A total of 2,742 subjects were included in the analysis. Participants were divided into two categories based on their menstrual cycle regularity and the relationship between metabolic syndrome and its variables was investigated by multiple logistic regression analysis.
Adjusted analyses revealed significantly higher odds ratios for metabolic syndrome, high waist circumference, high triglyceride levels, and low high density lipoprotein cholesterol levels with the presence of menstrual irregularity.
Metabolic syndrome and its components (high waist circumference, high triglyceride levels, and low high density lipoprotein cholesterol levels) were significantly associated with menstrual irregularity in women of reproductive age.
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Carcinoembryonic antigen (CEA), a serological marker of malignant tumors, demonstrates a modest increase under nonmalignant conditions such as aging and smoking. Also, recent study results suggested that serum CEA levels may be related to insulin resistance or low-grade inflammation. The aim of this study was to investigate the factors associated with serum CEA levels in healthy non-smokers.
Data was gathered from 21,501 adults aged 20 and over. We excluded 19,081 subjects who had omissions in anthropometric measurements or laboratory tests, or who had previous or current smoking history.
The mean CEA level was 1.18 ± 0.85 ng/dL in males and 0.93 ± 0.73 ng/dL in females. After adjustment for age, CEA level was positively correlated with fasting glucose, glycosylated hemoglobin (HbA1C), high density lipoprotein (HDL) cholesterol, estimated glomerular filtration rate in males. In females, CEA level was positively correlated with fasting glucose, HbA1C, HDL cholesterol, aspartate aminotransferase, and high-sensitivity C-reactive protein. In both gender groups, HbA1C had a strong influence on CEA levels when all other variables were included in the regression model (P < 0.05).
Within normal range, serum CEA levels were significantly associated with HbA1C levels but not with homeostasis model assessment of insulin resistance in the non-smoking population. These findings suggest that serum CEA levels are influenced by the glucose level itself instead of insulin resistance.
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Insulin resistance, decreased response of peripheral tissue to normal insulin levels, is known to be related to cardiometabolic diseases. Cardiopulmonary fitness is also considered to be related to these comorbidities. Therefore, we investigated the relationship between insulin resistance and cardiopulmonary fitness by performing a 3-minute step test in a Korean non-diabetes mellitus (DM) population.
A total of 118 non-DM subjects were enrolled during their routine health check-up. Insulin resistance was measured by calculating homeostatic model assessment-insulin resistance (HOMA-IR), and a 3-minute step test was performed to measure cardiopulmonary fitness.
Post-60 seconds exercise heart rate after 3-minute test (R60 heart rate) was correlated with age (r = -0.21, P = 0.02), education (r = 0.17, P = 0.04), body mass index (r = 0.23, P = 0.01), waist circumference (r = 0.28, P < 0.01), fasting insulin (r = 0.28, P < 0.01), HOMA-IR (r = 0.25, P < 0.01), low density lipoprotein-cholesterol (r = 0.28, P < 0.01), high sensitivity C-reactive protein levels (r = 0.22, P = 0.02), and baseline heart rate (r = 0.56, P < 0.01). In a step-wise multiple regression analysis, baseline heart rate (β = 0.79, P < 0.001), HOMA-IR (β = 0.65, P = 0.02), and systolic blood pressure (β = 0.15, P = 0.03) were identified as explanatory variables for R60 heart rates.
Our results suggested that cardiopulmonary fitness was associated with insulin resistance in non-DM patients of a university hospital in Korea. Further studies are needed to elucidate the underlying mechanisms.
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Though adiponectin has been associated with insulin resistance and cardiovascular risk factors, the relationship between adiponectin and polycystic ovary syndrome (PCOS) remains controversial. The aim of this study was to compare adiponectin level in women with PCOS and without PCOS, and to investigate the relationship between adiponectin level and metabolic variables including insulin resistance.
60 women with PCOS were enrolled along with a control group of 80 healthy women, matched for age and body mass index (BMI). We measured hormonal and metabolic parameters, as well as the plasma adiponectin concentration of each participant. We estimated the insulin sensitivity according to the quantitative insulin sensitivity check index (QUICKI).
The PCOS group displayed significantly lower level of adiponectin (P < 0.001) after adjustment for age, BMI, mean blood pressure, fasting glucose, fasting insulin, and several metabolic parameters. Adiponectin levels were positively correlated with QUICKI in the PCOS group (P < 0.001) and the control group (P = 0.03). Following step-wise multiple regression analysis, however, adiponectin level was positively correlated with QUICKI in the control group only (P = 0.03). In addition, adiponectin level was found to be independently associated with HDL-cholesterol level (P < 0.001) and BMI (P = 0.02) in the PCOS group and independently associated with HDL-cholesterol (P = 0.02) in the control group.
We report decreased adiponectin level in PCOS patients in relation to controls independently of insulin resistance or other metabolic factors. And adiponectin is associated with both lipid metabolism and obesity, which, in turn, is related to insulin resistance in PCOS. Further studies are needed to clarify the mechanism of adiponectin in PCOS.
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