Due to a lack of a food composition database on starch and sugars, we developed a comprehensive database on starch and seven types of sugars in commonly consumed foods (n = 2222) in Japan. Dietary record data of 368 toddlers (aged 18–35 months), 376 preschool children (aged 3–6 years), 915 schoolchildren (aged 8–14 years) and 392 adults (aged 20–69 years) were used. The mean starch intake ranged from 55.6 g/day (female toddlers) to 206.0 g/day (male schoolchildren). Irrespective of age and sex, >50% of starch was provided by rice and grains. The mean total sugar intake ranged from 46.1 g/day (female toddlers) to 68.7 g/day (male schoolchildren). In all age and sex groups, the major contributors of total sugar included sucrose (mean: 18.2–34.0 g/day), glucose (7.8–13.1 g/day), lactose (5.3–13.1 g/day) and fructose (7.6–11.1 g/day). The top food sources were dairy products (toddlers) and confectionaries (other age groups) for total sugar, confectionaries for sucrose, fruits (toddlers) and vegetables (other age groups) for glucose, dairy products for lactose and fruits (toddlers and preschool children) and vegetables (schoolchildren and adults) for fructose. In conclusion, this study clarified the starch and sugar intake in Japan and provides a foundation for future research.

Frailty is gaining attention worldwide with the aging of society. Despite the potential lethality and multiple signs and symptoms in affected individuals, preclinical detection of early manifestations leading to frailty syndrome have not been established. We speculated that the composition of the oral microbiota is associated with general frailty, as well as a relationship between gut microbiota and general health condition. In the present study, we investigated the salivary microbiota composition in samples from healthy and frail elderly individuals using 16S rRNA sequencing analysis for characterization. We found a significant difference in diversity between elderly individuals living in a nursing home (EN) and healthy control (HC) subjects, as well as in the microbiota composition at the phyla level. A supervised orthogonal partial least squared discriminant analysis (OPLS-DA) revealed a significant difference in clear classification trend between the EN and HC groups, with all observations falling within the Hotellings T2 (0.95) ellipse, with model fitness parameters of R 2(cum) = 0.937 and Q 2(cum) = 0.888, respectively. In addition, the score plots by unsupervised principal component analysis (PCA) showed a clear classification trend in both groups. Our findings suggest that general frailty is associated with oral microbiota composition and formation.

Objective: To develop a greenhouse gas emissions (GHGE) database for Japanese foods using three different approaches, compare the results of estimated diet-related GHGE and determine major food contributors among Japanese adults. Design: Cross-sectional. Three GHGE databases were developed: (1) a literature-based method including a literature review of life cycle assessment studies of Japanese foods and (2) production- and (3) consumption-based input–output tables (IOT)-applied methods using the Japanese IOT. All databases were linked to the Japanese food composition table and food consumption data. Diet-related GHGE was estimated based on each database and the 4-d dietary record data. Diet-related GHGE were compared in both total and food group level between the databases. Setting: Japan. Participants: 392 healthy adults aged 20–69 years. Results: The mean diet-related GHGE significantly differed according to the calculation methods: 4145 g CO2-equivalent (CO2-eq)/d by the literature-based method, 4031 g CO2-eq/d by the production-based method and 7392 g CO2-eq/d by the consumption-based IOT-applied methods. It significantly differed in food group level as well. Spearman’s correlation coefficients between three methods ranged from 0·82 to 0·86. Irrespective of the methods, the top contributor to GHGE was meat (19·7–28·8 %) followed by fish and seafood (13·8–18·3 %). Conclusions: Although the identified major food contributors to GHGE were comparable between the three methods, the estimated GHGE values significantly differed by calculation methods. This finding suggested that caution must be taken when interpreting the estimated diet-related GHGE values obtained using the different calculation methods of GHGE.

We examined food combinations in relation to the quality of the overall diet and individual meals using a newly developed food combination questionnaire (FCQ) in a nationwide sample of Japanese adults aged 19–80 years (n = 2233). The quality of the overall diet and of each meal was assessed by the Healthy Eating Index-2015 (HEI-2015) and Nutrient-Rich Food Index 9.3 (NRF9.3). For all main meals (breakfast, lunch, and dinner), the most commonly consumed food combinations consisted of ‘rice, total vegetables, and tea and coffee’. Consistently positive associations between these food combinations and diet quality were found for breakfast (Spearman r: ≥0.46). Positive rather weak associations between these food combinations and diet quality were also observed for lunch (Spearman r: ≤0.48). Conversely, the associations were inconsistent for dinner: inverse associations with HEI-2015 (Spearman r: ≤−0.35) and generally weak positive associations with NRF9.3 (Spearman r: ≥0.09). For snacks, the most commonly consumed food combinations consisted of ‘confectioneries and tea and coffee’, but these showed rather weak associations with diet quality. Similar results were obtained when associations with the quality of overall diet were investigated. The FCQ may be useful in capturing the complex nature of food combinations in Japanese adults.

Many previous studies have shown that meditation practice has a positive impact on cognitive and non-cognitive functioning, which are related to job performance. Thus, the aims of this study were to (1) estimate the prevalence of meditation practice, (2) identify the characteristics of individuals who practice meditation, and (3) examine the association between meditation practice and job performance. Two population-based, cross-sectional surveys were conducted. In study 1, we examined the prevalence of meditation practice and the characteristics of the persons practicing meditation; in Study 2, we examined the association between meditation practice and job performance. The outcome variables included work engagement, subjective job performance, and job satisfaction. The Utrecht Work Engagement Scale was used to assess work engagement, the World Health Organization Health and Work Performance Questionnaire (HPQ) was used to measure subjective job performance, and a scale developed by the Japanese government was used to assess job satisfaction. Hierarchical multiple regression analyses were used in Study 2. Demographic characteristics and behavioral risk factors were included as covariates in the analyses. The results of Study 1 indicated that 3.9% of persons surveyed (n = 30,665) practiced meditation; these individuals were younger and had a higher education, higher household income, higher stress level, and lower body mass index than those who did not practice meditation. The results of Study 2 (n = 1,470) indicated that meditation practice was significantly predictive of work engagement (β = 0.112, p < .001), subjective job performance (β = 0.116, p < .001), and job satisfaction (β = 0.079, p = .002), even after adjusting for covariates (β = 0.083, p < .001; β = 0.104, p < .001; β = 0.060, p = .015, respectively). The results indicate that meditation practice may positively influence job performance, including job satisfaction, subjective job performance, and work engagement.