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Background/AimsThere is a paucity of population-based studies on the association between inflammatory bowel disease (IBD) and depression in the U.S. population. We sought to study this association using the National Health and Nutrition Examination Survey (NHANES) database.MethodsWe used NHANES data from 2009 to 2010. Our study included 190,269,933 U.S. adults without IBD and 2,325,226 with IBD. We sought to determine whether IBD is an independent risk factor for depressive symptoms (DS) in the U.S. population and studied the independent predictors of DS in IBD population.ResultsDS was present in 49% of the IBD population versus 23% of the non-IBD population (p<0.001). During the multivariate analysis, we found that IBD was independently associated with DS in the U.S. population (p=0.002). The independent predictors of DS in the IBD population were older age (p=0.048) and divorced/separated/widowed status (p=0.005). There was nonsignificant increase in suicidal risk in IBD population with DS versus that in non-IBD population with DS (27% vs 12%, respectively, p=0.080). Only 36% of IBD individuals with DS visited mental health professional or psychiatrist within the past year.ConclusionsIBD is independently associated with DS in the U.S. population. Further research is warranted on risk stratification, screening and management of those with IBD who are at risk of depression.

Objective: To investigate the possibility of utilizing the ratio of the methadone metabolite, 2-ethylidene-1,5-dimethyl-3,3-diphenylpyrrolidine (EDDP), to urine creatinine to develop a regression model that would predict drug adherence in patients prescribed methadone for either pain management or drug addiction.Design: Retrospective study. Setting:Marshfield Clinic-Lakeland Center, one of 41 regional centers that make up Marshfield Clinic, a large, private, multi-specialty healthcare institution in central Wisconsin. Participants:Patients receiving methadone treatment for substance abuse or chronic pain. Group 1 was an initial pilot group consisting of 7 patients who were followed for a 4-month period. Group 2 consisted of 33 patients who were followed over a 28-month period.Methods: Age, gender, weight, height, methadone dosage, quantitative urine creatinine and EDDP levels, reported compliance/non-compliance, and relevant clinical cofactors were retrospectively abstracted from the patients' medical records. Log-log regression analyses were used to model EDDP and the EDDP/creatinine ratio from urine screening results as functions of methadone dose, and in the larger cohort (group 2), body size, gender and age. The coefficient of determination adjusted for the number of predictor terms (R adj 2 ) was reported as a measure of model fit.Results: For group 1 data, there was a significant positive relation (P<0.001) but also substantial variability (R adj 2 = 0.49). Adjustment for creatinine through the EDDP/creatinine ratio provided a tighter relation (R adj 2 = 0.95). Similarly, for group 2 data, there was a significant positive relation (P=0.001) and substantial variability (R adj 2 = 0.53). Adjustment for creatinine through EDDP/creatinine ratios provided a substantially stronger relation (R adj 2 = 0.73). Gender and age showed no evidence of association with the EDDP/creatinine ratio (P=0.60 and P=0.51, respectively). Body size was significant in the model, both when measured by body surface area and by lean body weight, and improved the prediction when added to our model (R adj 2 = 0.80). Conclusion:For the first time, urine analyses may be used to monitor methadone over-or under-use in a clinical setting, regardless of the state of patient hydration or the manipulation of a sample by addition of another substance, such as bleach, soap, or even methadone, which could render an appropriate sample inappropriate or an inappropriate sample appropriate. A similar approach may prove useful for other drug treatments, allowing for more accurate monitoring of commonly abused prescription medications.

Abstract. In this paper we introduce a new approach to rare event simulation. Because of the extensive simulation required for precise estimation of performance criterion dependent on rare event occurrences, obstacles such as computing budget/time constraints and pseudo-random number generator limitations can become prohibitive, particularly if comparative study of different system designs is involved. Existing methods for rare events simulation have focused on simulation budget reduction while attempting to generate accurate performance estimates. In this paper we propose a new approach for rare events system analysis in which we relax the simulation goal to the isolation of a set of "good enough" designs with high probability. Given this relaxation, referred to as ordinal optimization and advanced by Ho et al. (1992), this paper's approach calls instead for the consideration of an appropriate surrogate design problem. This surrogate problem is characterized by its approximate ordinal equivalence to the original problem and its performance criterion's dependence not on rare event occurrences, but on more frequent events, Evaluation of such a surrogate problem under the relaxed goals of ordinal optimization has experimentally resulted in orders of magnitude reduction in simulation burden.Keywords: discrete event dynamic system, ordinal optimization, rare event probability problem, surrogate problem.

The impact of informational feedback on the depositing of aluminum cans in recycling receptacles at a medium-sized university was investigated. Informational signs were placed over 20-recycling receptacles in three academic buildings. Each informational sign was placed at eye level, with the number of aluminum cans deposited for recycling during the previous week displayed in red digits. A 65% increase in the number of aluminum cans deposited in recycling receptacles with the informational signs was observed. Furthermore, removal of the informational signs was observed to reliably decrease the number of aluminum cans deposited. These results are discussed in the context of employing feedback to increase environmental protection behaviors.