Correlation between Combined Urinary Metal Exposure and Grip Strength under Three Statistical Models: A Cross-sectional Study in Rural Guangxi.

Objective: This study aimed to investigate the potential relationship between urinary metals copper (Cu), arsenic (As), strontium (Sr), barium (Ba), iron (Fe), lead (Pb) and manganese (Mn) and grip strength. Methods: We used linear regression models, quantile g-computation and Bayesian kernel machine regression (BKMR) to assess the relationship between metals and grip strength. Results: In the multimetal linear regression, Cu (ß = -2.119), As (ß = -1.318), Sr (ß = -2.480), Ba (ß = 0.781), Fe (ß = 1.130) and Mn (ß = -0.404) were significantly correlated with grip strength ( P < 0.05). The results of the quantile g-computation showed that the risk of occurrence of grip strength reduction was -1.007 (95% confidence interval: -1.362, -0.652; P < 0.001) when each quartile of the mixture of the seven metals was increased. Bayesian kernel function regression model analysis showed that mixtures of the seven metals had a negative overall effect on grip strength, with Cu, As and Sr being negatively associated with grip strength levels. In the total population, potential interactions were observed between As and Mn and between Cu and Mn ( P interactions of 0.003 and 0.018, respectively). Conclusion: In summary, this study suggests that combined exposure to metal mixtures is negatively associated with grip strength. Cu, Sr and As were negatively correlated with grip strength levels, and there were potential interactions between As and Mn and between Cu and Mn.

Effectiveness of mobile health interventions for pregnant women with gestational diabetes mellitus: a systematic review and meta-analysis.

Gestational diabetes mellitus is a growing global health problem. Inadequate management during pregnancy can lead to maternal and foetal complications. Currently, mobile health (mHealth) delivers healthcare services, playing an increasingly important role in the management of blood glucose in GDM. This study aimed to systematically evaluate the effectiveness of mHealth intervention in pregnant women with GDM. Based on randomised controlled trials of mHealth application in GDM patients searched from the database, literature screening, data extraction, and quality evaluation were conducted independently by two researchers. Statistical analysis was performed using Review Manager 5.4 software. The review included 27 studies with a total of 3483 patients. The results showed a significant improvement in glycemic control. In addition, mHealth interventions could reduce the occurrence of adverse pregnancy outcomes and improve self-management ability. In a subgroup analysis, recording of delivery mode and WeChat combined phone call indicated significant differences with mHealth interventions. It was suggested that mHealth interventions imposed a positive effect on glycemic control and reduction of adverse pregnancy outcomes in GDM patients. Our results demonstrated that the application of mHealth interventions can act as an effective and feasible approach to self-management to promote the self-management level and awareness of GDM patients.