BackgroundDiabetes is a major global public health problem driven by a high prevalence of metabolic risk factors.ObjectiveTo describe the differences of metabolic risk factors of type 2 diabetes, as well as glycemic control and complicated diabetic complications between rural and urban Uygur residents in Xinjiang Uygur Autonomous Region of China.MethodsThis comparative cross-sectional study, conducted among 2879 urban and 918 rural participants in Xinjiang, China, assessed the metabolic risk factors of diabetes and related complications differences between urban and rural settlements.ResultsCompared to rural areas, urban participants had higher education level and more average income, little physical activity, less triglycerides and higher HDL-c (p < 0.05 respectively). Differences in metabolic risk factors by urban/rural residence included overweight or obesity, triglycerides (≥1.71mmol/l), HDL-c (< 1.04 mmol/l), alcohol intake, and physical inactivity (p < 0.01 respectively). There was significant difference regarding the prevalence of HbA1c >8% (48.1% versus 54.5%, p = 0.019) between rural and urban diabetic participants. No significant difference in the prevalence of type 2 diabetic complications between urban and rural participants (74.9% versus 72.2%; p = 0.263) was detected. Compared to rural participants, the most prevalent modifiable risk factors associated with diabetic complications in urban participants were obesity (BMI ≥ 28 Kg/m2), HDL-c (< 1.04 mmol/l), physical inactivity and irregular eating habits (p = 0.035, p = 0.001, p < 0.001, and p = 0.013, respectively).ConclusionsUrban settlers were significantly more likely to have metabolic risk factors highlighting the need for public health efforts to improve health outcomes for these vulnerable populations. Diabetes related complications risk factors were prevalent amongst rural and urban diabetes settlers.

Our study is major to establish and validate a simple type||diabetes mellitus (T2DM) screening model for identifying high-risk individuals among Chinese adults. A total of 643,439 subjects who participated in the national health examination had been enrolled in this cross-sectional study. After excluding subjects with missing data or previous medical history, 345,718 adults was included in the final analysis. We used the least absolute shrinkage and selection operator models to optimize feature selection, and used multivariable logistic regression analysis to build a predicting model. The results showed that the major risk factors of T2DM were age, gender, no drinking or drinking/time > 25 g, no exercise, smoking, waist-to-height ratio, heart rate, systolic blood pressure, fatty liver and gallbladder disease. The area under ROC was 0.811 for development group and 0.814 for validation group, and the p values of the two calibration curves were 0.053 and 0.438, the improvement of net reclassification and integrated discrimination are significant in our model. Our results give a clue that the screening models we conducted may be useful for identifying Chinses adults at high risk for diabetes. Further studies are needed to evaluate the utility and feasibility of this model in various settings. Diabetes, as a group of metabolic disorders characterized by hyperglycemia, can lead to many serious, long-term complications 1-3. The global epidemic of diabetes currently affects more than 440 million people. The Asia-pacific region has the highest number of people with diabetes, and the prevalence of diabetes in this region has risen sharply in recent decades 4-6. With a population of 1.38 billion and about 110 million people with diabetes, China now has the largest number of diabetes in the world 7 and the number continues to grow, placing a huge burden on the health care system. In the 2013 study, which included 170,287 participants, the prevalence of diabetes was 10.9 percent, with 60 percent not knowing they had been diagnosed with diabetes. In addition, an additional 35.7% of the population found abnormal glucose homeostasis, highlighting the large number of people at risk for Diabetes 8. The reasons for the missed diagnosis are on the one hand the lack of self-awareness of disease management, on the other hand, it is caused by the inaccuracy of diabetes results (only by checking the fasting blood glucose) 9,10. The ideal way is to check the fasting blood glucose and the two-hour blood glucose value after the oral glucose tolerance test (OGTT) at the same time. However, universal access to blood sugar testing seems unlikely in Northwest China, where the medical standards are poor. The prevalence of diabetes in Xinjiang is at a high level. According to the 2018 national health examination data of Xinjiang, the detection rate in Urumqi is the highest, reaching 13.9%. Research has proved that a healthy lifestyle and a reasonable diet structure can effectively delay or prevent the occurrence of type||diabetes mellitus (T2DM)...

Background: Genetic polymorphisms of the transcription factor 7-like 2 (TCF7L2) gene have been reported to be strongly associated with type 2 diabetes mellitus (T2DM) in Icelandic, Danish and American populations and further replicated in other European populations, African Americans, Mexican Americans, and Asian populations. The aim of the present study was to investigate the association of TCF7L2 gene polymorphisms with T2DM in a Uygur population of China. Methods: 877 T2DM patients and 871 controls were selected for the present study. Two single nucleotide polymorphisms (SNPs) (rs12255372 and rs7901695) were genotyped by using matrix-assisted laser desorption/ionization time-of-flight (MALDI-TOF) mass spectrometry. The associations of SNPs and haplotypes with T2DM and linkage disequilibrium (LD) structure of the TCF7L2 gene were analyzed. Results: For total participants and male, the distribution of rs12255372 alleles and the dominant model (Guanine Guanine (GG) genotype vs. Guanine Thymine (GT) genotype + Thymine Thymine (TT) genotype) showed significant difference between T2DM and control subjects (for allele: p = 0.013 and p = 0.002, respectively; for dominant model: p = 0.028 and p = 0.008, respectively). The distribution of rs7901695 alleles and the dominant model (TT genotype vs. Thymine Cytosine (TC) genotype + Cytosine Cytosine (CC) genotype) for total participants and male showed significant difference between T2DM and control subjects (for allele: both p = 0.001; for dominant model: p = 0.006 and p = 0.008, respectively). Conclusions: Our data suggested that the genetic polymorphisms of the TCF7L2 gene were associated with T2DM in the Uygur population of China.

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Objectives To investigate the expression levels of aromatase cytochrome P450 enzyme (P450AROM) and related molecules—estrogen receptor-beta (ER-β), Ki-67, and p53—in prolactinoma tumor tissue from pre- and post-menopausal women, and to determine the associations of tumor invasiveness with expression levels of these genes. Methods This study recruited 90 patients with prolactinoma who underwent adenoidectomy between 2012 and 2017. Information was collected regarding clinical characteristics, hormones, laboratory tests, and magnetic resonance imaging-assessed tumor invasiveness. Expression levels of P450AROM, ER-β, Ki-67, and p53 were examined by immunohistochemistry in prolactinoma tissues. Results Increased P450AROM expression was found in invasive prolactinoma tissues in post-menopausal women, compared with its expression in non-invasive prolactinoma tissues. ER-β level was significantly higher in patients resistant to treatment with bromocriptine, a dopamine agonist. However, there were no differences in rate of resistance to treatment (8.2% vs. 3.4%) or expression levels of P450AROM, Ki-67, p53, and ER-β between pre- and post-menopausal patients. Conclusions Our results demonstrated that increased P450AROM expression in prolactinoma of post-menopausal women was positively associated with invasiveness. Moreover, ER-β level was higher in both pre- and post-menopausal patients who were resistant to dopamine agonist treatment.