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 (β = -2.
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.
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