Dietary intake can modify the impact of metals on human health, and is also closely related to glucose metabolism in human bodies. However, research on their interaction is limited. We used data based on 1738 adults aged ≥20 years from the National Health and Nutrition Examination Survey 2011-2016. We combined linear regression and restricted cubic splines with Bayesian kernel machine regression (BKMR) to identify metals associated with each glucose metabolism index (P < 0.05 and the posterior inclusion probabilities of BKMR >0.5) in eight non-essential heavy metals (barium, cadmium, antimony, tungsten, uranium, arsenic, lead, and thallium) and glucose metabolism indexes [fasting plasma glucose (FPG), blood hemoglobin A1c (HbA1c) and homeostatic model assessment of insulin resistance (HOMA-IR)]. We identified two pairs of metals associated with glucose metabolism indexes: cadmium and tungsten to HbA1c and barium and thallium to HOMA-IR. Then, the cross-validated kernel ensemble (CVEK) approach was applied to identify the specific nutrient group (nutrients) that interacted with the association. By using the CVEK model, we identified significant interactions between the energy-adjusted diet inflammatory index (E-DII) and cadmium, tungsten and barium (all P < 0.05); macro-nutrients and cadmium, tungsten and barium (all P < 0.05); minerals and cadmium, tungsten, barium and thallium (all P < 0.05); and A vitamins and thallium (P = 0.043). Furthermore, a lower E-DII, a lower intake of carbohydrates and phosphorus, and a higher consumption of magnesium seem to attenuate the positive association between metals and glucose metabolism indexes. Our finding identifying the nutrients that interact with non-essential heavy metals could provide a feasible nutritional guideline for the general population to protect against the adverse effects of non-essential heavy metals on glucose metabolism.