Chronic arsenic exposure is a critical public health issue in many countries. The metabolism of arsenic in vivo is complicated because it can be influenced by many factors. In the present meta-analysis, two researchers independently searched electronic databases, including the Cochrane Library, PubMed, Springer, Embase, and China National Knowledge Infrastructure, to analyze factors influencing arsenic methylation. The concentrations of the following arsenic metabolites increase (p< 0.000001) following arsenic exposure: inorganic arsenic (iAs), monomethyl arsenic (MMA), dimethyl arsenic (DMA), and total arsenic. Additionally, the percentages of iAs (standard mean difference (SMD): 1.00; 95% confidence interval (CI): 0.60–1.40; p< 0.00001) and MMA (SMD: 0.49; 95% CI: 0.21–0.77; p = 0.0006) also increase, while the percentage of DMA (SMD: −0.57; 95% CI: −0.80–−0.31; p< 0.0001), primary methylation index (SMD: −0.57; 95% CI: −0.94–−0.20; p = 0.002), and secondary methylation index (SMD: −0.27; 95% CI: −0.46–−0.90; p = 0.004) decrease. Smoking, drinking, and older age can reduce arsenic methylation, and arsenic methylation is more efficient in women than in men. The results of this analysis may provide information regarding the role of arsenic oxidative methylation in the arsenic poisoning process.

Purpose: Sarcopenia is a pathological change characterized by muscle loss in older people. According to the reports, there is controversy on the relationship between dyslipidemia and sarcopenia. Therefore, this meta-analysis aimed to explore the association between sarcopenia and dyslipidemia. Methods: We searched the Cochrane Library, Web of Science, PubMed, China National Knowledge Infrastructure (CNKI), Wan Fang, China Science and Technology Journal Database (VIP Database) for case‒control studies to extract data on the odds ratio (OR) between sarcopenia and dyslipidemia and the MD(mean difference) of TC, LDL-C, HDL-C, TG, and TG/HDL-C between sarcopenia and nonsarcopenia. The JBI(Joanna Briggs) guidelines were used to evaluate the quality. Excel 2021, Review Manager 5.3 and Stata 16.0 were used for the statistical analysis. Results: Twenty studies were included in the meta-analysis, 19 of which were evaluated as good quality. The overall OR of the relationship between sarcopenia and dyslipidemia was 1.47, and the MD values of TC, LDL-C, HDL-C, TG, and TG/HDL-C were 1.10, 1.95, 1.27, 30.13, and 0.16 respectively. In female, compared with the non-sarcopnia, the MD of TC, LDL-C, HDL-C, TG of sarcopenia were − 1.67,2.21,1.02,-3.18 respectively. In male, the MD of TC, LDL-C, HDL-C, TG between sarcopenia and non-sarcopenia were − 0.51, 1.41, 5.77, -0.67. The OR between sarcopenia and dyslipidemia of the non-China region was 4.38, and it was 0.9 in China. In the group(> 60), MD of TC between sarcopenia and non-sarcopenia was 2.63, while it was 1.54 in the group(20–60). Conclusion: Dyslipidemia was associated with sarcopenia in the elderly, which was affected by sex, region and age.

Objective: This study aimed to estimate the prevalence of diabetes mellitus (DM) and impaired fasting glucose (IFG) in a Kazakh population aged ≥18 years living in the YiLi District of Xinjiang, China and to evaluate the associated risk factors of diabetes. Methods: Randomly selected adults, living for at least 6 months in the YiLi District in Xinjiang had their clinical characteristics and standard blood chemistries measured. DM and IFG were defined according to WHO 1999 criteria. The adjusted odds ratio (ORs) and 95% confidence intervals were calculated for the association of diabetes risk factors in multivariate logistic regression models. Results: A total of 3919 subjects were randomly selected. The age-and gender-standardized prevalence of DM and IFG were 5.9% and 10.0%, respectively. The prevalence of DM and IFG increased with age and BMI. Prevalence of 7.4%, 12.2% in males and 4.9%, 8.6% in females for DM and IFG. Compared by sex, prevalence of DM and IFG was higher in males. Prevalence of 3.4%, 8.1% in normal, 6.7%, 11.9% in overweight and 12.0%, 13.0% in obesity for diabetes and IFG. In the multivariable logistic models, male sex, older age, unmarried, overweight, obesity, hypertension, triglycerides and smoking were all significantly associated with an increased risk of diabetes. Conclusions: The prevalence of DM and IFG among minorities was lower than the overall national level both in men and women (9.7% in total, 10.6% in males, 8.8% in females), and also lower than among the Han ethnicity (9.26%) which predominates in China today.

Arsenic exposure can cause fibrosis of organs including the liver, heart and lung. It was reported that TGF-β/Smad pathway played a crucial role in the process of fibrosis. However, the mechanism of arsenic-induced fibrosis through TGF-β/Smad signaling pathway has remained controversial. A systematic review and meta-analysis was performed to clarify the relationship between arsenic and TGF-β/Smad pathway, providing a theoretical basis of fibrosis process caused by arsenic. A meta-analysis was used to reveal a correlation between arsenic and fibrosis markers of TGF-β/Smad pathway, including 47 articles of both in vivo and in vitro studies. (Standardized Mean Difference) SMD was employed to compare and analyze the combined effects. When I2 > was 50%, random effect model was selected and subgroup analysis was used to explore the source of heterogeneity. Arsenic exposure up-regulated the expression of TGF-β1, p-Smad2/3, α-SMA, Collagen1/3 and FN. The dose-response relationship showed that low dose (≤5 μmol/L) arsenic exposure up-regulated the expression of TGF-β1, whereas high doses had a tendency to down-regulate that of TGF-β1. Subgroup analysis showed that low or short-term arsenic exposure induced the expression of TGF-β1 and fibrosis markers. The results indicated that arsenic activates the TGF-β/Smad pathway and induced fibrosis. The mechanism is related to the up-regulation of NADPH oxidase and ROS accumulation. However, high-dose arsenic exposure may inhibit this pathway.