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Summary Background Despite wide use of severity scoring systems for case-mix determination and benchmarking in the intensive care unit (ICU), the possibility of scoring bias across ethnicities has not been examined. Guidelines on the use of illness severity scores to inform triage decisions for allocation of scarce resources, such as mechanical ventilation, during the current COVID-19 pandemic warrant examination for possible bias in these models. We investigated the performance of the severity scoring systems Acute Physiology and Chronic Health Evaluation IVa (APACHE IVa), Oxford Acute Severity of Illness Score (OASIS), and Sequential Organ Failure Assessment (SOFA) across four ethnicities in two large ICU databases to identify possible ethnicity-based bias. Methods Data from the electronic ICU Collaborative Research Database (eICU-CRD) and the Medical Information Mart for Intensive Care III (MIMIC-III) database, built from patient episodes in the USA from 2014–15 and 2001–12, respectively, were analysed for score performance in Asian, Black, Hispanic, and White people after appropriate exclusions. Hospital mortality was the outcome of interest. Discrimination and calibration were determined for all three scoring systems in all four groups, using area under receiver operating characteristic (AUROC) curve for different ethnicities to assess discrimination, and standardised mortality ratio (SMR) or proxy measures to assess calibration. Findings We analysed 166 751 participants (122 919 eICU-CRD and 43 832 MIMIC-III). Although measurements of discrimination were significantly different among the groups (AUROC ranging from 0·86 to 0·89 [p=0·016] with APACHE IVa and from 0·75 to 0·77 [p=0·85] with OASIS), they did not display any discernible systematic patterns of bias. However, measurements of calibration indicated persistent, and in some cases statistically significant, patterns of difference between Hispanic people (SMR 0·73 with APACHE IVa and 0·64 with OASIS) and Black people (0·67 and 0·68) versus Asian people (0·77 and 0·95) and White people (0·76 and 0·81). Although calibrations were imperfect for all groups, the scores consistently showed a pattern of overpredicting mortality for Black people and Hispanic people. Similar results were seen using SOFA scores across the two databases. Interpretation The systematic differences in calibration across ethnicities suggest that illness severity scores reflect statistical bias in their predictions of mortality.

Background Online dating has become increasingly popular over the years. Few research studies have examined the association between dating apps and disordered eating. In this study, we evaluated the association between dating app use and unhealthy weight control behaviors (UWCBs) among a sample of U.S. adults. Methods Our sample includes 1769 adults who completed an online survey assessing dating app use and UWCBs in the past year. Survey assessed participants’ self-reported frequency of using dating apps within the past 30 days and engagement in six UWCBs with the purpose of lowering weight or changing their body shape within the past 12 months. UWCBs included vomiting, laxative use, fasting, diet pill use, muscle building supplement use, and use of anabolic steroids. Results Results of multivariate logistic regression models suggest dating app users had substantially elevated odds of UWCBs compared with non-users (odds ratios [OR] range = 2.7—16.2). These findings were supported by results of additional gender-stratified multivariate logistic regression analyses among women and men. Conclusions This study’s findings contribute to the limited literature exploring the association between dating app use and adverse health outcomes, particularly UWCBs. While additional longitudinal and representative research is needed, public health professionals ought to explore dating app use as a potential risk factor for UWCBs. Electronic supplementary material The online version of this article (10.1186/s40337-019-0244-4) contains supplementary material, which is available to authorized users.