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Background:Most studies that have investigated factors influencing eating habits among obese children have focused mainly on individual or interpersonal factors and applied quantitative research methods.Purpose:This study was undertaken to identify the barriers in home and school settings that hamper healthy eating in overweight and obese children in South Korea.Methods:Focus group interviews were conducted with 15 overweight/obese children and 15 parents. A standard manual with open-ended questions was developed. Content analysis was used to identify key findings.Results:Participants were aware of the importance of home and school environments in shaping children's eating habits. Five major barriers, respectively, at home and at school emerged from the data. At home, the food preferences of parents affected the eating habits of their children. Moreover, parents worried about providing differentiated diets for siblings and about the permissiveness of grandparents toward grandsons. Furthermore, working parents preferred easy-to-prepare instant foods and said that their children ate overly quickly. At school, children cited time pressures, poor cafeteria environments, and ineffective nutrition education as barriers, whereas parents worried about inconsistent management by teachers and the unsafe food environment around the school.Conclusions:These environment-related barriers may be resolved through changes in the behavior of children, parents, and teachers as well as through the continued efforts of schools, community stakeholders, and policymakers, all of whose cooperation is essential to fostering a healthy food environment for children.

It is generally believed that there is correlation between cancer prognosis and pretreatment PLR and NLR. However, there are limited data about their role in diffuse large B cell lymphoma (DLBCL). This study aims to determine the prognostic value of pretreatment PLR and NLR for patients who have DLBCL. The associations between clinical characteristics and NLR and PLR were evaluated among 182 DLBCL patients from January 2005 to June 2016. The optimal cutoff values for high PLR (⩾150) and NLR (⩾2.32) in prognosis prediction were determined. The effect of NLR and PLR on survival was evaluated through multivariate Cox regression analysis, univariate analysis, and log-rank test. According to the evaluation results, patients with high NLR and PLR had significantly shorter OS (P=0.026 and P=0.035) and PFS (P=0.024 and P=0.022) compared with those who have low PLR and NLR. On multivariate analyses, IPI>2, elevated LDH, and PLR⩾2.32 were prognostic factors for OS and PFS in DLBCL patients. Therefore, we demonstrated that high PLR and NLR predicted adverse prognostic factors in DLBCL patients.

Computer simulations have been increasingly used to study physical problems in various fields. To relieve computational budgets, the cheap-to-run metamodels, constructed from finite experiment points in the design space using the design of computer experiments (DOE), are employed to replace the costly simulation models. A key issue related to DOE is designing sequential computer experiments to achieve an accurate metamodel with as few points as possible. This article investigates the performance of current Bayesian sampling approaches and proposes an adaptive maximum entropy (AME) approach. In the proposed approach, the leave-one-out (LOO) cross-validation error estimates the error information in an easy way, the local space-filling exploration strategy avoids the clustering problem, and the search pattern from global to local improves the sampling efficiency. A comparison study of six examples with different types of initial points demonstrated that the AME approach is very promising for global metamodeling.