The amount of food waste in Japan is extremely high. In 2016, food waste generated by the food industry was 27.59 million tons. The breakdown is as follows: 16.17 million tons from food manufacturers, 270,000 tons from food wholesalers, 1.27 million tons from food retailers, and 1.99 million tons from restaurants, while consumers wasted 7.89 million tons. This means that about 6.43 million tons of food is lost (i.e. food that can be eaten has been thrown out). The total restaurant food waste rate is approximately 10% of which only 23% is recycled. Recycled food from restaurants is turned into fertilizer and feed. The main reasons for food waste in restaurants are leftovers and overstocking. As there are many different types of food restaurants in Japan, there has been little research on food loss reduction. We interviewed 15 restaurants and conducted a survey of consumers' awareness about food waste and loss. The results indicated that the most common cause of food loss was leftover foods. Therefore, many restaurants in Japan try to reduce food loss by offering "doggy bags" as a means for consumers to take leftover foods home. However, it is difficult to accept doggy bags in Japan. Consumers are becoming more conscious of food loss thus many are willing to take leftover food if there is an established and acceptable system. However, a small number of consumers said they did not want to take the leftover foods home, because if they live alone, they may use it and they end up discarding it. To promote doggy bags to reduce food loss in restaurants, may be necessary to improve communications between providers (restaurants) and consumers. In addition, at university restaurants like big cafeterias, there were many unsold foods. Thus, using the food share application for unsold foods is one tool to help reduce food waste, and some consumers want to use this food share application.
Background Whether our rehabilitation program of physical and cognitive Rec‐Xercise (REPCREC) for the elderly with MCI can bring any difference in cognition and QOL. Method Subjects are sixty‐nine cases, out of 73 enrolled individuals for more than three years, have undergone our evaluation and intervention program (REPCREC). The subjects have been divided into four groups; group A has taken the cognitive REPCREC, group B physical REPCREC, group C both cognitive and physical REPCREC and group D control. The design of this study is a non‐randomized controlled trial. Three intervention groups have received the each session once per week up to 12 times. Before and after the intervention, and, three, six and twelve months after the intervention, we have evaluated the following items: physical function, Geriatric Depression Scale, POMS2, Visual analog scale (VAS‐1: healthy life, VAS‐2: satisfaction), neuropsychological tests [MMSE, RBMT, TMT, Ravenʼs Colored Progressive Matrices (RCPM), Rey‐Osterrieth Complex Figure Test (ROCF), story retention, coding and Miyake's paired verbal associate learning test (MPVALT)]. A one‐day booster program has been provided at the time of evaluation. For statistical analysis, Fisher's exact test and Kruscal‐Wallis test for the baseline data, and linear mixed model (LMM) analysis and Friedman’s test for the prolonged effect of REPCREC have been performed. Results The median age 79.0 years old, median MMSE score 28.0 points, the number of each group is A 22, B 22, C 25, and D 7cases. At the baseline, no difference between groups. LMM analysis revealed the significant difference in RCPM, ROCF (recall), MPVALT (non‐related), MPVALT (related), coding and VAS‐2 (respectively p=0.000, 0.000, 0.000, 0.001, 0.011 and 0.006). Friedman's test showed significant difference in RCPM of group A (p=0.046) and C (p=0.042), ROCF (recall) group C (p=0.022), VAS‐2 of group A (p=0.013) and C (p=0.011), MPVALT (non‐related) of group A (p=0.007), MPVALT (related) of group A (p=0.016) and C (p=0.048). Conclusions The program REPCREC showed the prolonged effects on non‐verbal intelligence, visuospatial abilities, memory, attention, planning, working memory etc. [(RCPM), ROCF (recall), MPVALT] in group A and C comparing with control in the elderly with MCI.
Background To prevent or slow down the age‐related cognitive decline is an important issue. Therefore we have conducted intervention study with our rehabilitation program of physical and cognitive Rec‐Xercise (REPCREC) for the elderly with MCI. Method Seventy‐six cases, out of seventy‐nine enrolled individuals, have undergone our evaluation and intervention program (REPCREC). The subjects have been divided into four groups; group A the cognitive REPCREC, group B physical REPCREC, group C both cognitive and physical REPCREC and group D control. The design of this study is a non‐randomized controlled trial. Intervention groups have received the each session once per week up to twelve times. Before and after the intervention, and 3‐, 6‐, 12‐ & 18‐months after the intervention, we have evaluated the following items: physical function, GDS, POMS2, neuropsychological tests [MMSE, RBMT, TMT, Ravenʼs Colored Progressive Matrices(RCPM), Rey‐Osterrieth Complex Figure Test(ROCF), story retention, coding and Miyake’s paired verbal associate learning test(MPVALT)]. A one‐day booster program has been provided at the time of evaluation. For statistical analysis, Fisher’s exact test and Kruscal‐Wallis test for the baseline data, and linear mixed model(LMM) analysis have been performed. Result The median age is 79, median MMSE scare is 27.5, and the numbers of each group are A18, B24, C27, and D7 cases. At the baseline, no difference between groups except POMS‐F (p = 0.026). LMM analysis revealed the significant differences: 1) before REPCREC; RCPM of group A (p = 0.013), story retention delayed (p = 0.001) of group A (p = 0.011)▪C (p = 0.037), story retention immediate (p = 0.022), MPVALT (non‐related) (p = 0.048) and ROCF (recall) (p = 0.006), 2) after REPCREC; coding (p = 0.011) of group A (p = 0.049)▪C (p = 0.032) and ROCF(recall) (p = 0.018), 3) 3 months after REPCREC; TMTB (p = 0.031) of group A (p = 0.032) and story retention delayed of group A (p = 0.011). Conclusion The program REPCREC showed the better effects after REPCREC on non‐verbal intelligence, visuospatial abilities, memory, attention, planning, working memory etc. [RCPM, ROCF (recall), MPVALT] in especially the cognitive REPCREC (group A). And group A showed the significant improvement in TMTB and story retention delayed, even three months after REPCREC. That may indicate the prolonged efficacy of the REPCREP in shift of attention and coherent memory for MCI
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