Urinary tract infection caused by ESBL are a serious problem and identifying risk factors facilitates early detection and improved prognosis. Male sex, hospitalisation, institutionalisation, diabetes, recurrent UTI and comorbidity were risk factors and were associated with more symptoms and longer hospital stay.

Background The association of low-level exposure to metals and metal mixtures with cardiovascular incidence in the general population has rarely been studied. We flexibly evaluated the association of urinary metals and metal mixtures concentrations with cardiovascular diseases in a representative sample of a general population from Spain. Methods Urine antimony (Sb), barium (Ba), cadmium (Cd), chromium (Cr), cobalt (Co), copper (Cu), molybdenum (Mo), vanadium (V) and zinc (Zn) were measured in 1171 adults without clinical cardiovascular diseases, who participated in the Hortega Study. Cox proportional hazard models were used for evaluating the association between single metals and cardiovascular incidence. We used a Probit extension of Bayesian Kernel Machine Regression (BKMR-P) to handle metal mixtures in a survival setting. Results In single-metal models, the hazard ratios [confidence intervals (CIs)] of cardiovascular incidence, comparing the 80th to the 20th percentiles of metal distributions, were 1.35 (1.06, 1.72) for Cu, 1.43 (1.07, 1.90) for Zn, 1.51 (1.13, 2.03) for Sb, 1.46 (1.13, 1.88) for Cd, 1.64 (1.05, 2.58) for Cr and 1.31 (1.01, 1.71) for V. BKMR-P analysis was confirmatory of these findings, supporting that Cu, Zn, Sb, Cd, Cr and V are related to cardiovascular incidence in the presence of the other metals. Cd and Sb showed the highest posterior inclusion probabilities. Conclusions Urine Cu, Zn, Sb, Cd, Cr and V were independently associated with increased cardiovascular risk at levels relevant for the general population of Spain. Urine metals in the mixture were also jointly associated with cardiovascular incidence, with Cd and Sb being the most important components of the mixture.

Background The contribution of metabolomic factors to the association of healthy lifestyle with type 2 diabetes risk is unknown. We assessed the association of a composite measure of lifestyle with plasma metabolite profiles and incident type 2 diabetes, and whether relevant metabolites can explain the prospective association between healthy lifestyle and incident type 2 diabetes. Methods A Healthy Lifestyle Score (HLS) (5-point scale including diet, physical activity, smoking status, alcohol consumption and BMI) was estimated in 1016 Hortega Study participants, who had targeted plasma metabolomic determinations at baseline examination in 2001–2003, and were followed-up to 2015 to ascertain incident type 2 diabetes. Results The HLS was cross-sectionally associated with 32 (out of 49) plasma metabolites (2.5% false discovery rate). In the subset of 830 participants without prevalent type 2 diabetes, the rate ratio (RR) and rate difference (RD) of incident type 2 diabetes (n cases = 51) per one-point increase in HLS was, respectively, 0.69 (95% CI, 0.51, 0.93), and − 8.23 (95% CI, − 16.34, − 0.13)/10,000 person-years. In single-metabolite models, most of the HLS-related metabolites were prospectively associated with incident type 2 diabetes. In probit Bayesian Kernel Machine Regression, these prospective associations were mostly driven by medium HDL particle concentration and phenylpropionate, followed by small LDL particle concentration, which jointly accounted for ~ 50% of the HLS-related decrease in incident type 2 diabetes. Conclusions The HLS showed a strong inverse association with incident type 2 diabetes, which was largely explained by plasma metabolites measured years before the clinical diagnosis.

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