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Adolescent depression is a significant public health concern. Although skipping breakfast is associated with depressive symptoms in adolescents, the effects of dietary patterns on their depressive symptoms remain unknown. Therefore, this study aims to determine whether dietary patterns are associated with depressive symptoms among junior and senior high school students in Japan. A total of 441 junior high school students and 417 senior high school students participated in this study. The Center for Epidemiologic Studies Depression scale (CES-D) was used to measure the participants’ depressive symptoms. We surveyed the participants’ breakfast consumption pattern, as well as their general dietary patterns (meat, fish, green and yellow vegetables, milk and dairy products, and fruits), using a self-report questionnaire. The results indicated that the senior high school students had a significantly higher CES-D score than the junior high school students. We found negative and significant partial correlations between regular consumption of breakfast and depressive symptoms, and between regular consumption of green and yellow vegetables and depressive symptoms in both junior and senior high school students, after controlling for age, sex, and sleep duration. Furthermore, a one-way analysis of covariance (ANCOVA) revealed that adolescents who consumed green and yellow vegetables every day (one or more times per day) had significantly lower depressive symptoms than those from the “Never/1–2 times a week” group. The findings of this study reveal that the regular consumption of green and yellow vegetables is associated with lower depressive symptoms in adolescents, that is, the consumption of green and yellow vegetables may be vital in the context of adolescents’ mental health. [ABSTRACT FROM AUTHOR]

The ability to ascertain the extent of product sale fluctuations for each store and locality is indispensable to inventory management. This study analyzed POS data from 158 convenience stores in Kawasaki City, Kanagawa Prefecture, Japan and found a power scaling law between the mean and standard deviation of product sales quantities for several product categories. For the statistical domains of low sales quantities, the power index was 1/2; for large sales quantities, the power index was 1, so called Taylor’s law holds. The value of sales quantities with changing power indixes differed according to product category. We derived a Poissonian compound distribution model taking into account fluctuations in customer numbers to show that the scaling law could be explained theoretically for most of items. We also examined why the scaling law did not hold in some exceptional cases. [ABSTRACT FROM AUTHOR]