Biol Trace Elem Res DOI 10.1007/s12011-015-0393-5
Association of Serum Ferritin Level with Risk of Incident Abnormal Glucose Metabolism in Southwestern China: a Prospective Cohort Study Fangli Zhou 1 & Zhuoxian Zhao 1 & Li Tian 2 & Tianpeng Zheng 1 & Yun Gao 1 & Tao Chen 1 & Fangfang Yan 1 & Haoming Tian 1
Received: 29 March 2015 / Accepted: 1 June 2015 # Springer Science+Business Media New York 2015
Abstract This prospective cohort study aimed to analyze the association between serum ferritin levels and the risk of abnormal glucose metabolism (AGM) in Southwestern Chinese population. The 383 subjects who are aged ≥20 years and free of AGM at baseline between in 2007 and in 2008 were included in Southwestern China, and their baseline serum ferritin levels were measured. Among these subjects, 140 subjects were developed into AGM during the follow-up (2008–2012). In logistic regression models, the relative risk in the top versus that in the lowest quartile of serum ferritin levels was 2.86 (p = 0.013) in females and 3.50 (p = 0.029) in males after adjusting the age, gender, family history of diabetes, current smoking, and alcohol; however, serum ferritin levels were not significantly associated with incident of AGM after controlling for metabolic factors (waist circumference, systolic pressure (SBP), triglyceride (TG), and homeostasis model assessment formula insulin resistance (HOMA-IR)). Elevated serum ferritin levels are associated with AGM but not an independent risk factor.
Fangli Zhou and Zhuoxian Zhao contributed equally to this work * Haoming Tian [email protected] 1
Department of Endocrinology and Metabolism, West China Hospital, Sichuan University, 37 GuoXue Street, Chengdu 610041, Sichuan, People’s Republic of China
2
Laboratory of Endocrinology and Metabolism, West China Hospital, Sichuan University, Chengdu 610041, Sichuan, People’s Republic of China
Keywords Ferritin . Abnormal glucose metabolism . Prospective cohort study . Metabolic factors . Southwestern China
Introduction In recent years, the Western lifestyle has gradually pervaded the Chinese people’s daily life which characterizes with an increased consumption of red meat in the total amount of calories. The excess intake of red meat contributed to the rapid increase of the prevalence of type 2 diabetes mellitus (T2DM) in China [1]. It has been confirmed that the high content of iron in the red meat serves as a catalyst in the formation of reactive oxygen species (ROS) such as hydroxyl radical, which induced the oxidative stress of the liver and muscle, as well as the apoptosis of pancreatic β cells [2]. Serum ferritin is widely used as a clinical biomarker of body iron stores which is determined by the effect of genetic and dietary factors [3]. The pathologically increased ferritin level in genetic diseases, such as hereditary hemochromatosis, contributes to the occurrence of T2DM [4]. However, the association between moderately increased ferritin level caused by the over-intake of red meat and the risk of abnormal glucose metabolism (AGM) is still unclear. The study investigates the association between serum ferritin levels with abnormal glucose metabolism risk, especially in the prospective cohort or nested case-control studies which have provided strong evidence about the interrelation of them, and most of these studies are done in western countries [5–8]; however, the relevant studies among the Asian countries are quite rare [9, 10] and no one reports them in Southwestern China to date. In this study, we designed a prospective cohort to explore the association between serum ferritin levels and AGM risk in Southwestern Chinese population.
Zhou et al.
Materials and Methods
Demographic Characteristics
Study Design and Subjects
The clinical characteristics and lifestyle of participants were recorded by trained staff using a standard questionnaire [12]. Cigarette smoking was defined as having smoked at least 100 cigarettes in one’s lifetime. Alcohol consumption was defined as consumption of ≥30 g of alcohol per week for 1 year or more. Leisure-time physical activity was defined as participation in ≥30 min of moderate or vigorous activity per day at least 3 days per week. A physical examination was performed on all the participants and included an assessment of body height, weight, blood pressure, pulses, and waist circumference. Body mass index (BMI) was calculated as weight in kilograms divided by the square of height in meters. After an overnight fast ≥8 h, the Oral Glucose Tolerance Test (OGTT) using a 75 g glucose load was performed to measure fasting plasma glucose (FPG), 2 h-plasma glucose (2 h-PG), fasting serum insulin (FINS) and 2 h-serum insulin (2 h- INS).
The Chinese Diabetes Society conducted a cross-sectional study about diabetes and relevant metabolic risk factors by using multistage, stratified sampling method between 2007 and 2008 in China [11]. A total of 689 adults (age of 20 years old) who came from two urban communities and two rural villages in Southwestern China were involved in this study. Based on the previous cross-sectional study, these participants have been followed up for 4 years. The present study was reviewed and approved by The Ethics Committee of ChinaJapan Friendship Hospital (location: 2 Cherry Pank Street, Chaoyang District, Beijing 100029, China). Written informed consent was obtained from every subject before the study. Our study was registered in the Chinese clinical trial registry (#TRCCH-ChiCTR-OCS-09000361). Exclusion criteria included the following: the participants with AGM or who were taking medications for diabetes in the cross-sectional study at baseline, the subjects with chronic diseases such as hepatic or renal diseases, the subjects with thyroid or parathyroid diseases, the subjects taking osteoporosis medications or other drugs that might influence glucose metabolism such as glucocorticoid, pregnant women, and the subjects with incomplete data. According to the exclusion criteria, the final sample size for the present analysis was 383 participants (including 133 men and 250 women).
Subjects Classification Our study got the blood samples of participants who did not have AGM at baseline between 2007 and 2008, and the serum ferritin levels were measured. The study was designed as a prospective cohort study, which used the baseline serum ferritin levels as the exposure. The subjects whether developed into AGM including type 2 diabetes (T2DM), impaired fasting glucose (IFG), and impaired glucose tolerance (IGT), according to the diagnosis criteria of World Health Organization (WHO) in 1999, during the follow-up, or maintained normal glucose tolerance (NGT) were considered as the result. We make use of the quartile methods in classifying the subjects into four groups according to the baseline serum ferritin levels in females and males, respectively, and compared the differences in developing AGM under different baseline serum ferritin levels and analyzed the association between baseline serum ferritin levels and AGM. During the follow-up, we got the blood samples of the 383 participants and measured their serum ferritin levels.
Biochemical Parameter Measured Plasma glucose levels were measured by using a hexokinase enzymatic method. Insulin was measured by a radioimmunoassay with human insulin as a standard (Linco, St. Charles, MO). Triglyceride (TG), total cholesterol (TC), high-density lipoprotein-cholesterol (HDL-C), low-density lipoproteincholesterol (LDL-C), aspartate aminotransferase (AST), alanine transaminase (ALT), and blood creatinine (Cr) values were measured for all the patients by using the automated standardized equipment from the Clinical Laboratory of West China Hospital, Sichuan University. Serum ferritin level was measured with a radioimmunoassay kit (Beijing North Institute of Biological Technology). Both at baseline and during the follow-up, the questionnaire, physical examination, OGTT, biochemical indexes, and serum ferritin level were recorded and measured. At baseline, homeostasis model assessment formula insulin resistance (HOMA-IR) was used to measure the insulin resistance as the equation, HOMA IR ¼ ½FINS mIU FPG mmol L L =22:5, a n d h o meostasis model assessment formula beta-cell function (HOMA-β) was used to measure the function of pancreatic β-cells as the equation = ½FPG mmol 3:5. HOMA β ¼ 20 FINS mIU L L Statistical Analysis Normally distributed data are expressed as means ± standard deviation (SD) for continuous variables and percentage for categorical variables. Skewed variables were logarithmically transformed before analysis and were expressed as median (interquartile range). The quantitative variables were
Serum Ferritin and Abnormal Glucose Metabolism
compared using Student’s t test, while the qualitative variables were compared using the chi-square (χ2) test. The association of serum ferritin levels at baseline with AGM risk was analyzed using a logistic regression model to calculate the relative risk (RR) and 95 % confidence interval (CI). The variables included in the logistic regression model were those that were statistically significant in univariate analyses or were biologically relevant. Values with p ≤ 0.05 were considered statistically significant. All the statistical analysis was performed using SPSS 16.0 (SPSS, Inc., Chicago, IL).
Results Baseline and Follow-Up Characteristics During 4-years follow-up, 243 non-AGM participants did not develop into AGM, and 140 non-AGM participants (91 women and 49 men) developed into AGM. The 140 subjects
Table 1 Baseline characteristics of participants in 2007–2008
developed into AGM included 28 subjects with T2DM,15 subjects with IFG, and 107 subjects with IGT; there were 10 subjects developed into IFG and IGT at the same time. The characteristics of participants at baseline and after the follow-up were shown in Tables 1 and 2, separately. At baseline, compared with the participants who did not develop into AGM, participants who developed into AGM were older and the waist, BMI, systolic blood pressure (SBP), TG, FPG, 2 hPG, FINS, 2 h-INS, and HOMA-IR were higher significantly both in females and males. The baseline serum ferritin levels were higher in men than the ferritin concentration in women. Moreover, the concentration of serum baseline ferritins were markedly higher in subjects who developed into AGT compared to those who remained NGT, 110.9 (124.8) vs. 63.9 (108.6) in women and 199.5 (169.2) vs. 150.8 (159.8) in men, separately. During the follow-up, the age, waist, BMI, SBP, and DBP were significantly higher and the levels of TG, FPG, and 2 h-PG increased significantly both in women and men who developed AGM compared with those who did not.
Women
Men
NGT (n = 159)
AGT (n = 91)
NGT (n = 84)
AGT (n = 49)
Age (year) Current Smoking (%) Leisure-time physical activity (%) Family history of diabetes (%) Waist (cm) BMI (kg/m2) SBP (mmHg) DBP (mmHg) TC (mmol/L) LDL-C (mmol/L) HDL-C (mmol/L) FPG (mmol/L) 2 h-PG (mmol/L)
45.2 ± 12.1 3 (1.9) 135 (85.0) 23 (14.5) 74.3 ± 9.4 22.4 ± 2.7 113.3 ± 16.1 74.1 ± 8.8 4.9 ± 0.9 2.9 ± 0.8 1.5 ± 0.3 4.6 ± 0.5 5.4 ± 1.0
51.1 ± 12.1** 2 (2.2) 80 (87.9) 14 (15.4) 81.0 ± 10.8** 24.3 ± 3.8** 123.6 ± 20.5** 77.7 ± 11.4** 5.0 ± 1.0 3.1 ± 1.0 1.4 ± 0.4* 4.9 ± 0.6** 6.3 ± 1.1**
48.3 ± 14.0 42 (50.0) 63 (75.0) * 11 (13.1) 82.0 ± 9.4 23.2 ± 3.1 118.0 ± 13.4 77.5 ± 9.8 4.9 ± 0.8 3.0 ± 0.7 1.4 ± 0.4 4.5 ± 0.7 5.4 ± 1.1
55.8 ± 12.9** 20 (40.8) 45 (91.8) 5 (10.2) 88.3 ± 9.2** 25.4 ± 3.7** 123.3 ± 16.2* 80.0 ± 8.6 5.1 ± 0.9 3.1 ± 0.8 1.2 ± 0.3 5.0 ± 0.5** 6.6 ± 1.1**
ALT (IU/L) AST (IU/L) TG (mmol/L) Ferritin (ng/L) FINS (nU/L) 2 h-INS (nU/L) HOMA-IR HOMA-β
17.0 (11.0) 21.0 (7.0) 1.0 (0.6) 63.9 (108.6) 6.7 (2.9) 25.1 (23.1) 1.3 (0.7) 122.9 (91.5)
18.0 (15.8) 23.0 (9.8) 1.3 (0.75) ** 110.9 (124.8) ** 7.0 (4.3) * 39.4 (36.5) ** 1.6 (0.9) ** 107.0 (83.3)
23.0 (16.5) 24.0 (7.5) 1.2 (1.0) 150.8 (159.8) 6.8 (2.7) 22.8 (20.6) 1.3 (0.6) 120.6 (125.7)
30 (35.5)* 26.5 (12.3) 1.5 (0.9)* 199.5 (169.2)* 8.2 (4.2)* 39.3 (43.2)** 1.8 (1.0)** 102.5 (112.6)
NGT normal glucose tolerance, AGM Abnormal glucose metabolism, BMI body mass index, SBP systolic blood pressure, DBP diastolic blood pressure, TC total cholesterol, TG triglyceride, HDL-C high-density lipoproteincholesterol, LDL-C low-density lipoprotein-cholesterol, FPG fasting plasma glucose, 2 h-PG 2 h-plasma glucose in oral glucose tolerance test, ALT alanine aminotransferase, AST aspartate aminotransferase, Cr creatinine, FINS fasting serum insulin, 2 h-INS 2 h-serum insulin in oral glucose tolerance test, HOMA-IR homeostasis model assessment formula insulin resistance, HOMA-β homeostasis model assessment formula beta-cell function ***p value
Association of Serum Ferritin Level with Risk of Incident Abnormal Glucose Metabolism in Southwestern China: a Prospective Cohort Study Fangli Zhou 1 & Zhuoxian Zhao 1 & Li Tian 2 & Tianpeng Zheng 1 & Yun Gao 1 & Tao Chen 1 & Fangfang Yan 1 & Haoming Tian 1
Received: 29 March 2015 / Accepted: 1 June 2015 # Springer Science+Business Media New York 2015
Abstract This prospective cohort study aimed to analyze the association between serum ferritin levels and the risk of abnormal glucose metabolism (AGM) in Southwestern Chinese population. The 383 subjects who are aged ≥20 years and free of AGM at baseline between in 2007 and in 2008 were included in Southwestern China, and their baseline serum ferritin levels were measured. Among these subjects, 140 subjects were developed into AGM during the follow-up (2008–2012). In logistic regression models, the relative risk in the top versus that in the lowest quartile of serum ferritin levels was 2.86 (p = 0.013) in females and 3.50 (p = 0.029) in males after adjusting the age, gender, family history of diabetes, current smoking, and alcohol; however, serum ferritin levels were not significantly associated with incident of AGM after controlling for metabolic factors (waist circumference, systolic pressure (SBP), triglyceride (TG), and homeostasis model assessment formula insulin resistance (HOMA-IR)). Elevated serum ferritin levels are associated with AGM but not an independent risk factor.
Fangli Zhou and Zhuoxian Zhao contributed equally to this work * Haoming Tian [email protected] 1
Department of Endocrinology and Metabolism, West China Hospital, Sichuan University, 37 GuoXue Street, Chengdu 610041, Sichuan, People’s Republic of China
2
Laboratory of Endocrinology and Metabolism, West China Hospital, Sichuan University, Chengdu 610041, Sichuan, People’s Republic of China
Keywords Ferritin . Abnormal glucose metabolism . Prospective cohort study . Metabolic factors . Southwestern China
Introduction In recent years, the Western lifestyle has gradually pervaded the Chinese people’s daily life which characterizes with an increased consumption of red meat in the total amount of calories. The excess intake of red meat contributed to the rapid increase of the prevalence of type 2 diabetes mellitus (T2DM) in China [1]. It has been confirmed that the high content of iron in the red meat serves as a catalyst in the formation of reactive oxygen species (ROS) such as hydroxyl radical, which induced the oxidative stress of the liver and muscle, as well as the apoptosis of pancreatic β cells [2]. Serum ferritin is widely used as a clinical biomarker of body iron stores which is determined by the effect of genetic and dietary factors [3]. The pathologically increased ferritin level in genetic diseases, such as hereditary hemochromatosis, contributes to the occurrence of T2DM [4]. However, the association between moderately increased ferritin level caused by the over-intake of red meat and the risk of abnormal glucose metabolism (AGM) is still unclear. The study investigates the association between serum ferritin levels with abnormal glucose metabolism risk, especially in the prospective cohort or nested case-control studies which have provided strong evidence about the interrelation of them, and most of these studies are done in western countries [5–8]; however, the relevant studies among the Asian countries are quite rare [9, 10] and no one reports them in Southwestern China to date. In this study, we designed a prospective cohort to explore the association between serum ferritin levels and AGM risk in Southwestern Chinese population.
Zhou et al.
Materials and Methods
Demographic Characteristics
Study Design and Subjects
The clinical characteristics and lifestyle of participants were recorded by trained staff using a standard questionnaire [12]. Cigarette smoking was defined as having smoked at least 100 cigarettes in one’s lifetime. Alcohol consumption was defined as consumption of ≥30 g of alcohol per week for 1 year or more. Leisure-time physical activity was defined as participation in ≥30 min of moderate or vigorous activity per day at least 3 days per week. A physical examination was performed on all the participants and included an assessment of body height, weight, blood pressure, pulses, and waist circumference. Body mass index (BMI) was calculated as weight in kilograms divided by the square of height in meters. After an overnight fast ≥8 h, the Oral Glucose Tolerance Test (OGTT) using a 75 g glucose load was performed to measure fasting plasma glucose (FPG), 2 h-plasma glucose (2 h-PG), fasting serum insulin (FINS) and 2 h-serum insulin (2 h- INS).
The Chinese Diabetes Society conducted a cross-sectional study about diabetes and relevant metabolic risk factors by using multistage, stratified sampling method between 2007 and 2008 in China [11]. A total of 689 adults (age of 20 years old) who came from two urban communities and two rural villages in Southwestern China were involved in this study. Based on the previous cross-sectional study, these participants have been followed up for 4 years. The present study was reviewed and approved by The Ethics Committee of ChinaJapan Friendship Hospital (location: 2 Cherry Pank Street, Chaoyang District, Beijing 100029, China). Written informed consent was obtained from every subject before the study. Our study was registered in the Chinese clinical trial registry (#TRCCH-ChiCTR-OCS-09000361). Exclusion criteria included the following: the participants with AGM or who were taking medications for diabetes in the cross-sectional study at baseline, the subjects with chronic diseases such as hepatic or renal diseases, the subjects with thyroid or parathyroid diseases, the subjects taking osteoporosis medications or other drugs that might influence glucose metabolism such as glucocorticoid, pregnant women, and the subjects with incomplete data. According to the exclusion criteria, the final sample size for the present analysis was 383 participants (including 133 men and 250 women).
Subjects Classification Our study got the blood samples of participants who did not have AGM at baseline between 2007 and 2008, and the serum ferritin levels were measured. The study was designed as a prospective cohort study, which used the baseline serum ferritin levels as the exposure. The subjects whether developed into AGM including type 2 diabetes (T2DM), impaired fasting glucose (IFG), and impaired glucose tolerance (IGT), according to the diagnosis criteria of World Health Organization (WHO) in 1999, during the follow-up, or maintained normal glucose tolerance (NGT) were considered as the result. We make use of the quartile methods in classifying the subjects into four groups according to the baseline serum ferritin levels in females and males, respectively, and compared the differences in developing AGM under different baseline serum ferritin levels and analyzed the association between baseline serum ferritin levels and AGM. During the follow-up, we got the blood samples of the 383 participants and measured their serum ferritin levels.
Biochemical Parameter Measured Plasma glucose levels were measured by using a hexokinase enzymatic method. Insulin was measured by a radioimmunoassay with human insulin as a standard (Linco, St. Charles, MO). Triglyceride (TG), total cholesterol (TC), high-density lipoprotein-cholesterol (HDL-C), low-density lipoproteincholesterol (LDL-C), aspartate aminotransferase (AST), alanine transaminase (ALT), and blood creatinine (Cr) values were measured for all the patients by using the automated standardized equipment from the Clinical Laboratory of West China Hospital, Sichuan University. Serum ferritin level was measured with a radioimmunoassay kit (Beijing North Institute of Biological Technology). Both at baseline and during the follow-up, the questionnaire, physical examination, OGTT, biochemical indexes, and serum ferritin level were recorded and measured. At baseline, homeostasis model assessment formula insulin resistance (HOMA-IR) was used to measure the insulin resistance as the equation, HOMA IR ¼ ½FINS mIU FPG mmol L L =22:5, a n d h o meostasis model assessment formula beta-cell function (HOMA-β) was used to measure the function of pancreatic β-cells as the equation = ½FPG mmol 3:5. HOMA β ¼ 20 FINS mIU L L Statistical Analysis Normally distributed data are expressed as means ± standard deviation (SD) for continuous variables and percentage for categorical variables. Skewed variables were logarithmically transformed before analysis and were expressed as median (interquartile range). The quantitative variables were
Serum Ferritin and Abnormal Glucose Metabolism
compared using Student’s t test, while the qualitative variables were compared using the chi-square (χ2) test. The association of serum ferritin levels at baseline with AGM risk was analyzed using a logistic regression model to calculate the relative risk (RR) and 95 % confidence interval (CI). The variables included in the logistic regression model were those that were statistically significant in univariate analyses or were biologically relevant. Values with p ≤ 0.05 were considered statistically significant. All the statistical analysis was performed using SPSS 16.0 (SPSS, Inc., Chicago, IL).
Results Baseline and Follow-Up Characteristics During 4-years follow-up, 243 non-AGM participants did not develop into AGM, and 140 non-AGM participants (91 women and 49 men) developed into AGM. The 140 subjects
Table 1 Baseline characteristics of participants in 2007–2008
developed into AGM included 28 subjects with T2DM,15 subjects with IFG, and 107 subjects with IGT; there were 10 subjects developed into IFG and IGT at the same time. The characteristics of participants at baseline and after the follow-up were shown in Tables 1 and 2, separately. At baseline, compared with the participants who did not develop into AGM, participants who developed into AGM were older and the waist, BMI, systolic blood pressure (SBP), TG, FPG, 2 hPG, FINS, 2 h-INS, and HOMA-IR were higher significantly both in females and males. The baseline serum ferritin levels were higher in men than the ferritin concentration in women. Moreover, the concentration of serum baseline ferritins were markedly higher in subjects who developed into AGT compared to those who remained NGT, 110.9 (124.8) vs. 63.9 (108.6) in women and 199.5 (169.2) vs. 150.8 (159.8) in men, separately. During the follow-up, the age, waist, BMI, SBP, and DBP were significantly higher and the levels of TG, FPG, and 2 h-PG increased significantly both in women and men who developed AGM compared with those who did not.
Women
Men
NGT (n = 159)
AGT (n = 91)
NGT (n = 84)
AGT (n = 49)
Age (year) Current Smoking (%) Leisure-time physical activity (%) Family history of diabetes (%) Waist (cm) BMI (kg/m2) SBP (mmHg) DBP (mmHg) TC (mmol/L) LDL-C (mmol/L) HDL-C (mmol/L) FPG (mmol/L) 2 h-PG (mmol/L)
45.2 ± 12.1 3 (1.9) 135 (85.0) 23 (14.5) 74.3 ± 9.4 22.4 ± 2.7 113.3 ± 16.1 74.1 ± 8.8 4.9 ± 0.9 2.9 ± 0.8 1.5 ± 0.3 4.6 ± 0.5 5.4 ± 1.0
51.1 ± 12.1** 2 (2.2) 80 (87.9) 14 (15.4) 81.0 ± 10.8** 24.3 ± 3.8** 123.6 ± 20.5** 77.7 ± 11.4** 5.0 ± 1.0 3.1 ± 1.0 1.4 ± 0.4* 4.9 ± 0.6** 6.3 ± 1.1**
48.3 ± 14.0 42 (50.0) 63 (75.0) * 11 (13.1) 82.0 ± 9.4 23.2 ± 3.1 118.0 ± 13.4 77.5 ± 9.8 4.9 ± 0.8 3.0 ± 0.7 1.4 ± 0.4 4.5 ± 0.7 5.4 ± 1.1
55.8 ± 12.9** 20 (40.8) 45 (91.8) 5 (10.2) 88.3 ± 9.2** 25.4 ± 3.7** 123.3 ± 16.2* 80.0 ± 8.6 5.1 ± 0.9 3.1 ± 0.8 1.2 ± 0.3 5.0 ± 0.5** 6.6 ± 1.1**
ALT (IU/L) AST (IU/L) TG (mmol/L) Ferritin (ng/L) FINS (nU/L) 2 h-INS (nU/L) HOMA-IR HOMA-β
17.0 (11.0) 21.0 (7.0) 1.0 (0.6) 63.9 (108.6) 6.7 (2.9) 25.1 (23.1) 1.3 (0.7) 122.9 (91.5)
18.0 (15.8) 23.0 (9.8) 1.3 (0.75) ** 110.9 (124.8) ** 7.0 (4.3) * 39.4 (36.5) ** 1.6 (0.9) ** 107.0 (83.3)
23.0 (16.5) 24.0 (7.5) 1.2 (1.0) 150.8 (159.8) 6.8 (2.7) 22.8 (20.6) 1.3 (0.6) 120.6 (125.7)
30 (35.5)* 26.5 (12.3) 1.5 (0.9)* 199.5 (169.2)* 8.2 (4.2)* 39.3 (43.2)** 1.8 (1.0)** 102.5 (112.6)
NGT normal glucose tolerance, AGM Abnormal glucose metabolism, BMI body mass index, SBP systolic blood pressure, DBP diastolic blood pressure, TC total cholesterol, TG triglyceride, HDL-C high-density lipoproteincholesterol, LDL-C low-density lipoprotein-cholesterol, FPG fasting plasma glucose, 2 h-PG 2 h-plasma glucose in oral glucose tolerance test, ALT alanine aminotransferase, AST aspartate aminotransferase, Cr creatinine, FINS fasting serum insulin, 2 h-INS 2 h-serum insulin in oral glucose tolerance test, HOMA-IR homeostasis model assessment formula insulin resistance, HOMA-β homeostasis model assessment formula beta-cell function ***p value
