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Exposure to heavy metals pollutions in water predisposes consumers to human and environmental health deterioration. In this study, the extent of heavy metals contamination, water quality index, ecological and human health risk assessments of groundwater resources in Ajao industrial area of Lagos, Nigeria were carried out. Results revealed that Cu is the most prevalent heavy metal, contaminating 85.71% of the analyzed water samples. Based on the groundwater quality index, 76.19% of the samples are of excellent water quality and suitable for drinking, domestic and industrial purposes. However, the quality of 23.81% variedly deteriorated. Ecological risk assessment revealed that 85.71% and 14.29% of the samples pose low and moderate ecological risks, respectively. This assessment also showed that Cu was the major heavy metal posing ecological risk in the industrial area. Based on hazard quotients, Cu impacted the potentiality of chronic diseases than other heavy metals. Health hazard index analysis revealed that children are more exposed to non-carcinogenic chronic health risks due to ingestion of contaminated groundwater than the adult population. Probability of cancer risk (PCR) revealed that 19.05% of the samples pose high Cr cancer risk for both adult and children, while 14.29% pose high Cd and Ni cancer risks. Correlation and factor analyses indicated that the origin of the heavy metals in water is majorly attributed to anthropogenic inputs rather than natural, geogenic processes. Awareness programs towards protecting the groundwater in this area should be launched and encouraged. Moreover, contaminated water should be treated before use.

Several numerical models have been utilized in water quality assessments for various purposes. Among all the commonly used models, entropy-weighted water quality index (EWQI) has been recognized as the most unbiased model for assessing drinking water quality. Therefore, this paper presents a case study of the application of EWQI in assessing the effect of effluent-derived heavy metals on the groundwater quality in Ajao industrial estate, Nigeria. Three environmental pollution risk assessment tools were integrated to better evaluate the level of heavy metals contamination in the groundwater. Geoaccumulation index ( I geo ) placed 66% of the samples in uncontaminated to moderately contaminated category. However, 19% showed moderate to heavy contamination, whereas 14.29% were heavily contaminated. Similarly, enrichment factor (EF) revealed that 52% of the samples have minimal enrichment, 33% are moderately enriched, while 14.29% were extremely enriched with heavy metals. Vector modulus of pollution index (PI vector ) showed that the majority of the samples (80.9%) have low pollution, 4.76% recorded moderate pollution, while 14.29% had considerable to very high pollution. The EWQI showed that the majority (85.71%) of the groundwater samples are excellent drinking water, while 14.29% are unsuitable for drinking. However, a dendrogram integrating the results of the I geo , EF, PI vector , and EWQI was produced by hierarchical cluster analysis to harmonize and demarcate the groundwater quality in this industrial area. Although this study confirms the suitability of most samples for drinking, more awareness programs towards the protection of the groundwater should be embraced.

We examined risk factors associated with the intestinal acquisition of antimicrobial-resistant extraintestinal pathogenic Escherichia coli (ExPEC) and development of community-acquired urinary tract infection (UTI) in a case-control study of young women across Canada. A total of 399 women were recruited; 164 women had a UTI caused by E. coli resistant to ⩾1 antimicrobial classes and 98 had a UTI caused by E. coli resistant to ⩾3 antimicrobial classes. After adjustment for age, student health service (region of Canada) and either prior antibiotic use or UTI history, consumption of processed or ground chicken, cooked or raw shellfish, street foods and any organic fruit; as well as, contact with chickens, dogs and pet treats; and travel to Asia, were associated with an increased risk of UTI caused by antimicrobial resistant E. coli. A decreased risk of antimicrobial resistant UTI was associated with consumption of apples, nectarines, peppers, fresh herbs, peanuts and cooked beef. Drug-resistant UTI linked to foodborne and environmental exposures may be a significant public health concern and understanding the risk factors for intestinal acquisition of existing or newly emerging lineages of drug-resistant ExPEC is important for epidemiology, antimicrobial stewardship and prevention efforts.

Background Intensive care unit (ICU) outcome prediction models, such as Acute Physiology And Chronic Health Evaluation (APACHE), were designed in general critical care populations and their use in obstetric populations is contentious. The aim of the CIPHER (Collaborative Integrated Pregnancy High-dependency Estimate of Risk) study was to develop and internally validate a multivariable prognostic model calibrated specifically for pregnant or recently delivered women admitted for critical care. Methods A retrospective observational cohort was created for this study from 13 tertiary facilities across five high-income and six low- or middle-income countries. Women admitted to an ICU for more than 24 h during pregnancy or less than 6 weeks post-partum from 2000 to 2012 were included in the cohort. A composite primary outcome was defined as maternal death or need for organ support for more than 7 days or acute life-saving intervention. Model development involved selection of candidate predictor variables based on prior evidence of effect, availability across study sites, and use of LASSO (Least Absolute Shrinkage and Selection Operator) model building after multiple imputation using chained equations to address missing data for variable selection. The final model was estimated using multivariable logistic regression. Internal validation was completed using bootstrapping to correct for optimism in model performance measures of discrimination and calibration. Results Overall, 127 out of 769 (16.5%) women experienced an adverse outcome. Predictors included in the final CIPHER model were maternal age, surgery in the preceding 24 h, systolic blood pressure, Glasgow Coma Scale score, serum sodium, serum potassium, activated partial thromboplastin time, arterial blood gas (ABG) pH, serum creatinine, and serum bilirubin. After internal validation, the model maintained excellent discrimination (area under the curve of the receiver operating characteristic (AUROC) 0.82, 95% confidence interval (CI) 0.81 to 0.84) and good calibration (slope of 0.92, 95% CI 0.91 to 0.92 and intercept of −0.11, 95% CI −0.13 to −0.08). Conclusions The CIPHER model has the potential to be a pragmatic risk prediction tool. CIPHER can identify critically ill pregnant women at highest risk for adverse outcomes, inform counseling of patients about risk, and facilitate bench-marking of outcomes between centers by adjusting for baseline risk.