Literature DB >> 26246695

Association of Inflammation with Metabolic Syndrome among Low-Income Rural Kazakh and Uyghur Adults in Far Western China.

Yi-Zhong Yan1, Ru-Lin Ma1, Yu-Song Ding2, Heng Guo1, Jing-Yu Zhang1, La-Ti Mu1, Mei Zhang1, Jia-Ming Liu1, Dong-Sheng Rui1, Jia He1, Feng Sun3, Kui Wang1, Shu-Xia Guo2.   

Abstract

This study focused on low-income rural and nomadic minority people residing in China's far west and investigated their relationship between inflammatory markers (IL-6, hsCRP, FFA, and adiponectin) and MS and ethnic differences. And it found that improving behavioral lifestyle by education or using drugs to control inflammation may prevent MS. These observations may benefit low-income populations.

Entities:  

Mesh:

Substances:

Year:  2015        PMID: 26246695      PMCID: PMC4502304          DOI: 10.1155/2015/706768

Source DB:  PubMed          Journal:  Mediators Inflamm        ISSN: 0962-9351            Impact factor:   4.711


1. Introduction

Metabolic syndrome (MS) comprises a cluster of clinical metabolic diseases that include hypertension, insulin resistance (IR), obesity, and dyslipidemia [1-3]. MS is a global public s1/4–1/3 of the global population is affected by MS and that its prevalence will continue to increase [4]. China is a multiethnic country, with more than 10 ethnic groups in Xinjiang. In this region, Kazakh and Uyghur populations constitute large minority groups, with most individuals residing in low-income rural communities [5]. For example, more than 92% of Uyghurs in Jiashi County live on US $1.00 per day or less, and this percentage is much higher than the national average reported in 2005 (15.9%) [6, 7]. Due to a primitive economic system, limited public health resources, and a poor transportation system, few serious investigations have focused on the analyses of local public health issues, including the prevalence of hypertension, obesity, dyslipidemia, and related diseases such as diabetes and cardiovascular diseases (CVDs). Our previous studies demonstrated an MS prevalence of 21.2% in Uyghurs [8] and 26.6% in Kazakhs [9]; these values are significantly higher than the national average of 16.5% [10]. Differences in religion, culture, lifestyle, diet, and genetic background in these ethnic groups may be related to this high MS prevalence, and knowledge about these differences may be useful for establishing appropriate preventive public health policies for Xinjiang residents. MS is a chronic, low-grade, systemic inflammatory state [11], and the relationship between MS and inflammation has long been acknowledged. Indeed, studies have demonstrated that inflammatory markers such as IL-6, hsCRP, FFA, and adiponectin play an important role in MS development and are closely related to the occurrence of MS and its components [12, 13]. IL-6 and CRP may contribute to MS risk [14], and a sharp increase in FFA can cause both insulin resistance (IR) in the liver, increase the expression of proinflammatory cytokines such as IL-6, and stimulate the liver to secrete CRP [15]. Decreased adiponectin levels are also associated with IR and are observed in proinflammatory states [16, 17]. However, these findings were primarily obtained in high-income and urban settings, whereas little information has been gathered in low-income rural settings. Specifically, data concerning inflammatory marker levels and their relationship with MS in Uyghur and Kazakh people and data concerning differences between these two local minority groups are lacking. In this study, we analyzed the relationships between inflammation and MS and the possible differences between these ethnic groups residing in far western China to examine the reasons underlying the incidence of MS in Xinjiang.

2. Materials and Methods

2.1. Ethics Statement

The Institutional Ethics Review Board (IERB) at the First Affiliated Hospital of the Shihezi University School of Medicine approved the study (IERB no. SHZ2010LL01). Standard university hospital guidelines, including informed consent, voluntary participation, confidentiality, and anonymity, were followed. All of the participants provided written informed consent before the study began.

2.2. Settings and Participants

This study was conducted from 2009 to 2012 among Uyghurs residing along the Bazi Xiang River region of Jiashi and Kazakhs residing in Nalati township of Yili in Xinjiang. For the basic survey, we divided subjects from the two ethic groups into MS and non-MS groups according to the 2005 IDF criteria. Using a random number table in SPSS 19.0, we then randomly selected 218 and 156 cases from the MS groups and 201 and 180 cases from the non-MS groups of the Uyghur and Kazakh populations, respectively, for laboratory testing.

2.3. Definition of MS and HOMA-IR

(1) MS was defined by central obesity according to the IDF (modified guidelines of the WHO for the Asia Pacific region) [18], a waist circumference ≥ 90 cm in men or ≥80 cm in women, plus any two of the following four factors: (a) an elevated triglyceride level of >150 mg/dL (1.69 mM); (b) a reduced HDL cholesterol level of <40 mg/dL (1.04 mM) in males or <50 mg/dL (1.29 mM) in females; (c) elevated BP (SBP ≥ 130 or DBP ≥ 85 mmHg); and (d) an elevated fasting plasma glucose level of ≥100 mg/dL. (2) The homeostasis model assessment of insulin resistance (HOMA-IR) index was defined as follows: fasting insulin (in microinternational units [μIU] per mL) × fasting glucose (in mM)/22.5 [19]. The Chinese Diabetes Society (CDS) states that IR can be estimated using this formula in epidemiological or clinical studies, and the upper quartile of the subjects was the split point for this study: 1.17 in Uyghurs and 1.23 in Kazakhs.

2.4. Exclusion Criteria

The exclusion criteria were as follows: (1) patients with serious heart and liver dysfunction; (2) patients using insulin and oral hypoglycemic, antihypertensive, lipid-lowering drugs; (3) pregnant women; (4) patients with cancer or tuberculosis or other infectious diseases.

2.5. Laboratory Tests

(1) Total cholesterol (TC), triglyceride (TG), low-density lipoprotein cholesterol (LDL-C), high-density lipoprotein cholesterol (HDL-C), and fasting glucose levels were assessed using a biochemical autoanalyzer (Olympus AU 2700, Olympus Diagnostics, Hamburg, Germany) in a clinical laboratory. (2) IL-6 and adiponectin levels were determined by ELISA with kits purchased from Shanghai Westang Bio-Tech Co., Ltd. (Shanghai, China). hsCRP was determined by immunonephelometry, and FFA was determined by a colorimetric assay; the kits were purchased from Randox Laboratories Ltd. (UK). Insulin levels were determined by radioimmunoassay using a kit purchased from Beijing Atomic-Tech Co., Ltd. (Beijing, China).

2.6. Statistical Analysis

All of the analyses were performed using the SPSS statistical package for Windows (version 19.0). Continuously and normally distributed variables were analyzed using t-tests, and the results are presented as the means ± standard deviations (M ± SD); variables with a skewed distribution were analyzed using the Mann-Whitney U-test, and the results are expressed as the median (upper quartile, lower quartile) [M(Qu, QL)]. All of the rates were compared using the Chi-square test. Differences of P < 0.05 were considered to be statistically significant.

3. Results

3.1. Description of the General Situation in the Uyghur and Kazakh Populations

Average age and gender were not significantly different between the MS and non-MS groups in the Uyghur and Kazakh populations or between the two ethnicities (P > 0.05 for each comparison). Among Uyghurs and Kazakhs, BMI, WC, SBP, DBP, TG, HDL-C, FPG, LDL-C, and TC levels were higher in the MS group than in the non-MS group (P < 0.05 for each comparison). However, there were no differences between the two ethnicities, regardless of whether they were classified in the MS or non-MS group (P > 0.05 for each comparison) (Table 1).
Table 1

Age and gender data for the Uyghur and Kazakh subjects.

IndexUyghurKazakh
MS (n = 218)Non-MS (n = 201)MS (n = 156)Non-MS (n = 180)
Sex (male/female)104/11495/10674/8288/92
Age (years)41.49 ± 12.4241.86 ± 11.9042.03 ± 13.6940.71 ± 10.24
BMI (kg/m2)24.03 ± 1.73# 22.54 ± 2.5327.06 ± 4.25# 21.76 ± 2.01
WC (cm)92.76 ± 7.28# 82.73 ± 9.0995.26 ± 10.10# 82.89 ± 9.32
SBP (mmHg)140.41 ± 20.10# 112.95 ± 11.59142.98 ± 22.98# 116.60 ± 18.24
DBP (mmHg)93.07 ± 12.56# 85.24 ± 10.2392.91 ± 13.96# 86.51 ± 14.79
TG (mmol/L)1.64 ± 0.99# 0.86 ± 0.321.68 ± 1.13# 0.95 ± 0.37
HDL-C (mmol/L)1.06 ± 0.25# 1.58 ± 0.291.01 ± 0.28# 1.54 ± 0.40
FPG (mmol/L)4.89 ± 1.33# 4.49 ± 0.565.01 ± 1.64# 4.51 ± 0.95
LDL-C (mmol/L)2.68 ± 0.72# 2.27 ± 0.702.65 ± 0.81# 2.25 ± 0.66
TC (mmol/L)4.72 ± 1.08# 4.16 ± 0.994.98 ± 1.13# 4.20 ± 0.95

Notes: MS = metabolicsyndrome, WC = waist circumference, BMI = body mass index, SBP = systolic blood pressure, DBP = diastolic blood pressure, TG = triglyceride, TC = total cholesterol, HDL-C = high-density lipoprotein cholesterol, LDL-C = low-density lipoprotein cholesterol, and FPG = fasting plasma glucose. #Comparing the index in the same ethnicity, P < 0.05.

3.2. Serum IL-6, hsCRP, FFA, and Adiponectin Levels for Uyghurs and Kazakhs in the MS and Non-MS Groups

In both the Uyghur and Kazakh populations, serum IL-6, hsCRP, and FFA levels in the MS group were higher than those in the non-MS group; overall, the levels recorded in Kazakhs were higher than those measured in Uyghurs, both with and without MS (P < 0.01 for each comparison). Conversely, adiponectin levels displayed the opposite trends (P < 0.01 for each comparison) (Table 2).
Table 2

IL-6, hsCRP, FFA and adiponectin levels of MS and non-MS groups in the Uyghur and Kazakh populations.

UyghurKazakh
IL-6 (ng/L)hsCRP (mg/L)FFA (mg/L)Adiponectin (pg/L)IL-6 (ng/L)hsCRP (mg/L)FFA (mg/L)Adiponectin (pg/L)
MS30.86(21.22, 43.89) 1.26(0.79, 1.52) 0.57(0.38, 0.80) 4405.54(2524.4, 15964.34) 88.12(44.20, 197.02)3.20(1.70, 5.50)0.61(0.48, 0.77)446.17(103.03, 1796.71)
Non-MS23.32(11.09, 31.81) 1.16(0.79, 1.35) 0.45(0.33, 0.65) 5724.58(1824.22, 16388.89) 62.58(14.20, 159.90)1.50(0.60, 4.50)0.49(0.34, 0.59)841.71(298.80, 2716.31)
Z −5.852−2.550−4.398−3.730−3.456−4.911−5.518−3.783
P <0.0010.011<0.001<0.001<0.001<0.001<0.001<0.001

Notes: MS = metabolic syndrome, IL-6 = interleukin-6, CRP = C-reactive protein, and FFA = free fatty acids.

Comparing the same index between the two ethnicities, P < 0.05.

3.3. Detection Rates of MS and Its Components between Each Group by Quartile Assessment of Serum IL-6, hsCRP, FFA, and Adiponectin Levels in Uyghurs and Kazakhs (Q1 Group, Less Than the 25th Percentile; Q2 Group, 25th to 50th Percentile; Q3 Group, 50th to 75th Percentile; Q4 Group, Greater Than the 75th Percentile)

From the Q1 group to the Q4 group, the rates of detection for MS and its components in Uyghurs and Kazakhs tended to increase as the levels of IL-6, hsCRP, and FFA increased. Comparing the Q4 and Q1 groups, all OR values were >1, indicating that the Q4 group's risk was higher than that of the Q1 group. However, the adiponectin levels exhibited opposite results (Tables 3 –6).
Table 3

Detection rates of MS and components in each IL-6 level quartile.

MS and componentsUyghurKazakh
Q1 Q2 Q3 Q4 P OR (Q4/Q1) (OR 95% CI)Q1 Q2 Q3 Q4 P OR (Q4/Q1) (OR 95% CI)
MS7.613.412.918.40.0006.27 (3.444, 11.429)12.116.217.516.20.0152.14 (1.128, 4.049)
Hypertension4.59.88.614.60.0006.28 (3.341, 11.784)10.814.615.914.90.0182.10 (1.113, 3.946)
Low HDL-C19.319.118.122.90.00010.58 (3.579, 31.261)7.611.112.411.70.0202.14 (1.117, 4.113)
High TG3.67.26.410.30.0004.16 (2.128, 8.139)2.93.57.613.00.0008.87 (3.892, 20.193)
High FPG1.41.71.02.90.1962.13 (1.768, 5.904)4.47.08.99.80.0013.16 (1.517, 6.570)

Notes: MS = metabolicsyndrome, TG = triglyceride, HDL-C = high-density lipoprotein cholesterol, FPG = fasting plasma glucose, OR = odds ratio, and CI = confidence interval.

Table 4

Detection rates of MS and components in each hsCRP level quartile.

MS and componentsUyghurKazakh
Q1 Q2 Q3 Q4 P OR (Q4/Q1) (OR 95% CI)Q1 Q2 Q3 Q4 P OR (Q4/Q1) (OR 95% CI)
MS13.110.710.517.70.0152.17 (1.230, 3.829)7.018.719.017.10.0004.81 (2.428, 9.548)
Hypertension7.49.57.912.60.0082.43 (1.379, 4.292)5.717.117.515.90.0005.09 (2.532, 10.242)
Low HDL-C17.718.419.324.10.0303.16 (1.390, 7.184)5.112.712.113.00.0013.75 (1.847, 7.594)
High TG6.06.26.09.30.0471.89 (1.039, 3.441)1.03.58.614.00.00028.52 (8.280, 98.222)
High FPG3.11.01.41.40.1011.43 (1.057, 1.675)2.28.38.99.80.001 6.97 (2.844, 17.079)

Notes: MS = metabolic syndrome, TG = triglyceride, HDL-C = high-density lipoprotein cholesterol, FPG = fasting plasma glucose, OR = odds ratio, and CI = confidence interval.

Table 5

Detection rates of MS and components in each FFA level quartile.

MS and componentsUyghurKazakh
Q1 Q2 Q3 Q4 P OR (Q4/Q1) (OR 95% CI)Q1 Q2 Q3 Q4 P OR (Q4/Q1) (OR 95% CI)
MS10.710.714.116.50.0012.26 (1.294, 3.946)7.414.08.916.10.0033.44 (1.800, 6.582)
Hypertension6.97.411.211.90.0012.18 (1.226, 3.868)11.314.611.013.70.9261.15 (1.620, 2.433)
Low HDL-C18.418.119.823.20.0053.02 (1.364, 6.702)6.39.66.911.00.0951.98 (1.023, 3.825)
High TG6.05.76.29.50.0401.82 (1.698, 3.300)3.06.33.36.00.3052.00 (1.370, 4.597)
High FPG0.71.71.92.60.0411.34 (1.130, 2.306)4.36.25.86.20.939 1.04 (1.437, 2.456)

Notes: MS = metabolic syndrome, TG = triglyceride, HDL-C = high-density lipoprotein cholesterol, FPG = fasting plasma glucose, OR = odds ratio, and CI = confidence interval.

Table 6

Detection rates of MS and components in each adiponectin level quartile.

MS and componentsUyghurKazakh
Q1 Q2 Q3 Q4 P OR (Q4/Q1) (OR 95% CI)Q1 Q2 Q3 Q4 P OR (Q4/Q1) (OR 95% CI)
MS17.912.410.711.00.0000.31 (0.176, 0.553)13.414.611.07.40.0000.37 (0.195, 0.693)
Hypertension9.510.09.18.80.3230.88 (0.504, 1.550)13.114.013.110.40.1440.65 (0.353, 1.194)
Low HDL-C24.618.616.719.60.0000.07 (0.016, 0.302)8.79.67.87.80.1090.86 (0.453, 1.651)
High TG11.24.86.25.30.0010.33 (0.178, 0.600)5.76.63.62.70.0130.42 (0.176, 0.983)
High FPG3.81.70.70.70.0000.16 (0.046, 0.580)5.48.65.82.70.156 0.50 (0.187, 1.334)

Notes: MS = metabolic syndrome, TG = triglyceride, HDL-C = high-density lipoprotein cholesterol, FPG = fasting plasma glucose, OR = odds ratio, and CI = confidence interval.

3.4. Relationship of Serum IL-6, hsCRP, FFA, and Adiponectin Levels with the Number of Clustered MS Components

As the MS component clustering increased, the serum IL-6, hsCRP, and FFA levels gradually increased in both populations (P < 0.01 for each comparison); however, this trend was more obvious for Kazakh individuals, as shown in the top curve. In contrast, adiponectin levels showed the opposite trend (Figures 1 –4).
Figure 1

Comparing IL-6 with MS components.

Figure 2

Comparing hsCRP with MS components.

Figure 3

Comparing FFA with MS components.

Figure 4

Comparing adiponectin with MS components.

4. Discussion

MS is a major public health problem because of its rapidly increasing prevalence and its association with type 2 diabetes and cardiovascular disease (CVD) [20]. In fact, CVD risk in patients with MS is twice that of the normal population [3]. In the United States, Europe, and India, at least 25% of adults suffer from MS. However, the reasons underling the high incidence of MS have not been confirmed. Related studies have demonstrated that MS is associated with a proinflammatory state, which is hypothesized to be related to CVD [20-23], and some inflammatory markers, such as IL-6, hsCRP, FFA, and adiponectin, are closely related to MS [21, 24, 25]. The current study analyzed the relationship between MS and inflammation in adults of rural Kazakh and Uyghur populations in northwest China. We determined that, for both populations, IL-6, hsCRP, and FFA levels were higher in the MS group than in the non-MS group and that adiponectin is an adipose tissue factor that could improve IR. This trend is similar to those reported in domestic and foreign research, though the levels in our study are higher [26-28]. Nishida et al. determined that “high” IL-6 or hsCRP levels or “low” adiponectin levels are associated with an increased risk for MS. Additionally, IL-6 and adiponectin have been shown to be important risk factors for early arterial alterations in men [29]. MS incidence was found to increase with increased CRP and IL-6 levels [30], and hsCRP levels were markedly increased in older male patients with MS [31]. Moreover, hsCRP can facilitate the prediction of new-onset CVD [32]. IL-6, hsCRP, and FFA appear to promote MS development, whereas adiponectin negatively regulates MS by suppressing IR, ultimately preventing MS. Nishida et al. reported that individuals with an increased number of MS components have higher CRP levels [29]. In another study, when the number of components ≥ 3, FFA levels were notably increased, with a decrease in adiponectin levels [28]. The results of the present study demonstrated that IL-6, hsCRP, and FFA levels also increased among Uyghurs and Kazakhs as the clustering of MS components increased, though adiponectin levels decreased. We also analyzed the subjects according to quartiles of IL-6, hsCRP, FFA, and adiponectin levels and compared the detection rates of MS and its components from the Q1 group to the Q4 group. The results demonstrated increasing trends for the levels of IL-6, hsCRP, and FFA. Moreover, the OR values were >1 for the Q4 and Q1 groups, predicting that the incidence risk of MS and its components is higher in the Q4 group. However, the opposite trends were observed with increased adiponectin levels. Uyghurs and Kazakhs are the two main ethnic groups in Xinjiang, and their unique geographical environment and living habits are very different from those of the rest of the country. For instance, their economy is primitive, their environment is harsh, their education and medical knowledge are deficient, and their self-awareness of prevention and treatment is poor. Additionally, the staple of their diet is Nang, which contains a large amount of salt, and they do not eat many fruits or vegetables. Indeed, Kazakhs consume Nang three times a day and are accustomed to drinking tea with plenty of salt and milk. They also frequently consume cured meat, which may lead to higher prevalence of MS and its components in Kazakhs compared to Uyghurs. The reported prevalence of MS in Kazakhs is 26.6% [8], whereas that in Uyghurs is 21.2% [9]. In our study, IL-6, hsCRP, and FFA levels were higher in Kazakhs than in Uyghurs, and the positive association with MS components was more obvious in the former; the results for adiponectin displayed the opposite trend. These observations provide further evidence that IL-6, hsCRP, and FFA levels are positively correlated with the occurrence of MS and that adiponectin is negatively correlated with MS. We could not establish causal relationships in our study due to its cross-sectional design, and we did not collect data on the socioeconomic or environmental variables that could have an impact on MS. We also recruited subjects during a local investigation in northwest China and not from hospitals or other medical institutions. Subjects from hospitals or other medical institutions could be more representative, and the use of such a sample could have allowed us to explore the relationship between MS and inflammation over a range of demographic groups. Nonetheless, these findings provide important demographic insight into the growing problem of MS in rural Kazakh and Uyghur populations.

5. Conclusion

In conclusion, this study explored the relationship between MS and inflammation among Uyghur and Kazakh people. Despite the higher prevalence of MS in these groups compared with the rest of China, to date, few studies have investigated the underlying reasons for this higher prevalence. We observed that the abnormal expression of inflammatory cytokines might contribute to the high prevalence of MS, which could be associated with the characteristics of the different ethnicities and areas (e.g., differences in living environments, habits, and customs). To prevent MS, these groups could improve their lifestyle behaviors through education or medication to control IL-6, hsCRP, FFA, and adiponectin levels. Therefore, our observations and recommendations should be used to establish appropriate public health policies to benefit low-income populations.
  30 in total

1.  [Study on the prevalence of metabolic syndrome among the Kazakh population in Xinjiang].

Authors:  Heng Guo; Shu-xia Guo; Jing-yu Zhang; Ru-lin Ma; Dong-sheng Rui; Shang-zhi Xu; Feng Sun; Ao-rong Hu; Zhi-ming Yang
Journal:  Zhonghua Liu Xing Bing Xue Za Zhi       Date:  2010-07

Review 2.  The link between abdominal obesity, metabolic syndrome and cardiovascular disease.

Authors:  S A Ritchie; J M C Connell
Journal:  Nutr Metab Cardiovasc Dis       Date:  2006-11-15       Impact factor: 4.222

Review 3.  Relationship of C-reactive protein, metabolic syndrome and diabetes mellitus: potential role of statins.

Authors:  David T Nash
Journal:  J Natl Med Assoc       Date:  2005-12       Impact factor: 1.798

4.  [The epidemic situation of metabolic syndrome among the Uygur in Kashgar of Xinjiang in 2010].

Authors:  Chun-hui Li; Shu-xia Guo; Ru-lin Ma; Yu-song Ding; Heng Guo; Jia-ming Liu; Shang-zhi Xu; Jing-yu Zhang; Shu-gang Li; Mei Zhang
Journal:  Zhonghua Yu Fang Yi Xue Za Zhi       Date:  2012-05

Review 5.  The metabolic syndrome.

Authors:  Robert H Eckel; Scott M Grundy; Paul Z Zimmet
Journal:  Lancet       Date:  2005 Apr 16-22       Impact factor: 79.321

Review 6.  Adiponectin, obesity, and cardiovascular disease.

Authors:  Mathias Fasshauer; Ralf Paschke; Michael Stumvoll
Journal:  Biochimie       Date:  2004-11       Impact factor: 4.079

7.  Adiponectin and the development of type 2 diabetes: the atherosclerosis risk in communities study.

Authors:  Bruce B Duncan; Maria Inês Schmidt; James S Pankow; Heejung Bang; David Couper; Christie M Ballantyne; Ron C Hoogeveen; Gerardo Heiss
Journal:  Diabetes       Date:  2004-09       Impact factor: 9.461

Review 8.  Adiponectin in insulin resistance: lessons from translational research.

Authors:  Florencia Ziemke; Christos S Mantzoros
Journal:  Am J Clin Nutr       Date:  2009-11-11       Impact factor: 7.045

9.  Palmitate induced IL-6 and MCP-1 expression in human bladder smooth muscle cells provides a link between diabetes and urinary tract infections.

Authors:  Andreas Oberbach; Nadine Schlichting; Matthias Blüher; Peter Kovacs; Holger Till; Jens-Uwe Stolzenburg; Jochen Neuhaus
Journal:  PLoS One       Date:  2010-05-28       Impact factor: 3.240

10.  Cardiovascular risk factors and estimated 10-year risk of fatal cardiovascular events using various equations in Greeks with metabolic syndrome.

Authors:  Theodoros Chimonas; Vassilios G Athyros; Emmanouel Ganotakis; Vassilios Nicolaou; Demosthenes B Panagiotakos; Dimitri P Mikhailidis; Moses Elisaf
Journal:  Angiology       Date:  2010 Feb-Mar       Impact factor: 3.619

View more
  9 in total

1.  Parabolic relationship between sex-specific serum high sensitive C reactive protein and non-alcoholic fatty liver disease in Chinese adults: a large population-based study.

Authors:  Li-Ren Wang; Wen-Yue Liu; Sheng-Jie Wu; Gui-Qi Zhu; Yi-Qian Lin; Martin Braddock; Dong-Chu Zhang; Ming-Hua Zheng
Journal:  Oncotarget       Date:  2016-03-22

2.  Association between dietary patterns and metabolic syndrome in Chinese adults: a propensity score-matched case-control study.

Authors:  Yang Xia; Yeqing Gu; Fei Yu; Qing Zhang; Li Liu; Ge Meng; Hongmei Wu; Huanmin Du; Hongbin Shi; Xiaoyan Guo; Xing Liu; Chunlei Li; Peipei Han; Renwei Dong; Xiuyang Wang; Xue Bao; Qian Su; Liyun Fang; Fangfang Liu; Huijun Yang; Li Kang; Yixuan Ma; Bin Yu; Shaomei Sun; Xing Wang; Ming Zhou; Qiyu Jia; Qi Guo; Yuntang Wu; Kun Song; Guowei Huang; Guolin Wang; Kaijun Niu
Journal:  Sci Rep       Date:  2016-10-06       Impact factor: 4.379

3.  Expression pattern of genome-scale long noncoding RNA following acute myocardial infarction in Chinese Uyghur patients.

Authors:  Hui Zhai; Xiao-Mei Li; Fen Liu; Bang-Dang Chen; Hong Zheng; Xue-Mei Wang; Wu Liao; Qing-Jie Chen; Yi-Tong Ma; Yi-Ning Yang
Journal:  Oncotarget       Date:  2017-05-09

4.  Association between Dietary Inflammatory Index, C-Reactive Protein and Metabolic Syndrome: A Cross-Sectional Study.

Authors:  Zhongxia Ren; Ai Zhao; Yan Wang; Liping Meng; Ignatius Man-Yau Szeto; Ting Li; Huiting Gong; Zixing Tian; Yumei Zhang; Peiyu Wang
Journal:  Nutrients       Date:  2018-06-27       Impact factor: 5.717

5.  Expression profiles and potential functions of long non-coding RNA in stable angina pectoris patients from Uyghur population of China.

Authors:  Xin-Rong Zhou; Ning Song; Jun-Yi Luo; Hui Zhai; Xiang-Mei Li; Qian Zhao; Fen Liu; Xiao-Mei Li; Yi-Ning Yang
Journal:  Biosci Rep       Date:  2019-09-03       Impact factor: 3.840

6.  Association between Bone Mineral Density and Metabolic Syndrome among Reproductive, Menopausal Transition, and Postmenopausal Women.

Authors:  Rogelio Salas; Alexandra Tijerina; Mariana Cardona; Cristina Bouzas; Erik Ramirez; Gustavo Martínez; Aurora Garza; Rosario Pastor; Josep A Tur
Journal:  J Clin Med       Date:  2021-10-20       Impact factor: 4.964

7.  Association of high-sensitivity C-reactive protein and uric acid with the metabolic syndrome components.

Authors:  Santosh Kumar Sah; Saroj Khatiwada; Sunil Pandey; Rajendra Kc; Binod Kumar Lal Das; Nirmal Baral; Madhab Lamsal
Journal:  Springerplus       Date:  2016-03-03

8.  Dietary patterns and the risk of metabolic syndrome in Chinese adults: a population-based cross-sectional study.

Authors:  Zhi-Yong Wei; Jun-Jie Liu; Xue-Mei Zhan; Hao-Miao Feng; Yuan-Yuan Zhang
Journal:  Public Health Nutr       Date:  2018-05-02       Impact factor: 4.022

9.  The influence of the TNFα rs1800629 polymorphism on some inflammatory biomarkers in 45-60-year-old women with metabolic syndrome.

Authors:  Małgorzata Szkup; Elżbieta Chełmecka; Anna Lubkowska; Aleksander Jerzy Owczarek; Elżbieta Grochans
Journal:  Aging (Albany NY)       Date:  2018-10-31       Impact factor: 5.682

  9 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.