Kanako Deguchi

Background and Aim: Underweight young adult women are vulnerable to health risks such as menstrual disorders and vitamin deficiencies. Because few seek medical care for low body weight, the underlying causes remain unclear. This study aimed to examine the associations of body type with dietary patterns and gut microbiota diversity in young women. Methods: We enrolled 40 women aged 20-39 years who visited a nutrition evaluation clinic with a BMI < 17.5 at their first consultation (underweight group) and 40 age-matched women with 18.5 ≤ BMI < 25 (control group). Some women in the underweight group were no longer underweight at the time of analysis but were classified based on their initial BMI. Dietary patterns were assessed based on ten major food categories (meat, fish, eggs, dairy products, soybeans, green and yellow vegetables, seaweed, fruit, tubers, and fats and oil) based on the Food Frequency Questionnaire based on Food Groups. Gut microbiota α-diversity was evaluated using the Shannon, Simpson, and Pielou indices, while β-diversity was analyzed by nonmetric multidimensional scaling (NMDS) and redundancy analysis (RDA). Genera contributing to group differences were identified by RDA and ANOVA-Like Differential Expression tool (ALDEx2). Results: Underweight women had significantly lower gut microbiota α-diversity, while no difference was observed in dietary patterns. NMDS revealed significant β-diversity differences in gut microbiota (PERMANOVA: R2 = 0.064, F = 5.31, p = 0.0001) but not in dietary patterns (p = 0.99). RDA showed that body type explained 4.5% of variance (adjusted R2 = 0.032, F = 3.65, p = 0.0005). Bacteroides, Bifidobacterium, Enterocloster, and Erysipelatoclostridium were enriched in underweight women, whereas Fusicatenibacter, Agathobacter, Dorea, and Prevotella were enriched in controls. AldEx2 confirmed increases in Bacteroides, Enterocloster, and Erysipelatoclostridium and a decrease in Dorea. Conclusions: Underweight women demonstrated reduced gut microbiota diversity and enrichment of taxa associated with inflammatory tendencies. Dietary therapies involving not only prebiotics but also probiotics may beneficially modulate gut microbiota and contribute to the management of low body weight.

Background/Aim: To date, there have been no data regarding the reproducibility or agreement of meal duration when a test meal is eaten. To confirm the reproducibility and agreement of the meal duration, number of chews, chewing tempo, and number of bites of a test meal, we performed a prospective observation study. Methods: We measured the duration, number of chews, chewing tempo, and number of bites of a test meal (salmon bento) among 33 participants (male: 15; female: 18) aged 20–60 years who ate twice at 2-week intervals to verify the agreement (by Bland-Altman (BA) analysis) and reproducibility (intraclass correlation coefficient (ICC)) by sex. Results: The meal duration (s) and number of bites (times) were significantly greater in the female group (560.4 (128.7) and 731.9 (266.3), p = 0.023; 17.1 (9.9) vs. 26.4 (13.7), p = 0.036), and the number of chews tended to be greater in the female group (752.5 (203.3) vs. 938.1 (375.9), p = 0.083). Meal duration was positively associated with the number of chews (0.64 [0.53, 0.74], p &lt; 0.001) and bites (10.4 [5.1, 15.8], p &lt; 0.001). For both sexes, the % error calculated via BA analysis was high for meal duration, the number of chews, and the chewing tempo (21.4 and 13.4%; 16.5 and 18.5%; and 6.8 and 5.3%, respectively) and low for the number of bites (37.9 and 68.9%). The ICCs were high for meal duration (0.73 and 0.90), the number of chews (0.76 and 0.89), and the chewing tempo (0.76 and 0.90), and low for the number of bites (0.84 and 0.69). Moreover, systematic and proportional errors were found only for the number of bites in the female group (median_difference with 95% CI: −9.00 (−13.00, −2.00); −0.320 (−0.45, −0.093)). Conclusions: Although the sample size was small due to the exploratory nature of the study, meal duration, number of chews, and chewing tempo had high reproducibility and agreement, at least when this test meal was consumed. These measures may indicate individual-specific eating behavior.

Background/Objectives: Dietary patterns vary with age and sex. The aim of this study was to clarify the differences in dietary patterns among young and middle-aged Japanese individuals by age group and sex via statistical methods such as alpha diversity and beta diversity analyses. Methods: Using data from a dietary survey of 10 food items during health checkups of 2743 Fujita Health University employees, we examined the effects of age and sex on alpha diversity (Shannon index) and beta diversity (nonmetric multidimensional scaling (NMDS) and RDA). Unlike principal component analysis which assumes linear relationships, redundancy analysis (RDA) incorporates explanatory variables to directly assess how external factors shape multivariate patterns. Results: The Shannon index increased with age and was greater in males across age groups. Type III ANOVA revealed significant main effects of age (p < 0.001) and sex (p < 0.001), and the effect of the interaction between age and sex approached significance (p = 0.08). Visualization of the NMDS data revealed that women aged 20-29 years and women aged 30 years and older and men aged 20-39 years and men aged 50-59 years have different dietary patterns. The RDA model accounted for 2.01% of the variance (adjusted R2 = 1.94%), with age and sex contributing 56.7% and 43.3%, respectively. RDA1 and RDA2 were correlated with age (r = 0.26, -0.14) and sex (r = 0.15, 0.21). The RDA1 values increased with age and were greater in females, whereas the RDA2 values decreased with age and were greater in females. RDA1 (1.41% of the total variance in food group intake, 70.1% of the constrained variance) was positively associated with fruits, milk, and seaweed and negatively associated with meat and eggs. In RDA2 (0.60% of total variance, 29.9% contribution), fruits, potatoes, and vegetables had positive effects, whereas fish had negative effects. Conclusions: Dietary patterns vary by age and sex, with meat, fish, eggs, and fruit as key determinants. Nutritional guidance must account for variations in dietary patterns influenced by age and sex.

Background/Aim: Skeletal muscle mass index (SMI) and body fat percentage (BF%) are components of body mass index (BMI) but are considered to play independent roles. We aimed to clarify whether SMI and BF% are associated with nutritional markers independent of BMI in underweight women. Methods: This retrospective observational study included a total of 102 women aged 20-65 years who were referred to the outpatient nutrition evaluation clinic from 2022 to 2024 with a body mass index (BMI) < 17.5. We performed a multivariate analysis with SMI and BF% as independent variables and BMI, BMI ratio (present-to-age 20 ratio), grip strength, and biochemical nutritional indicators (vitamin B1 level (ng/mL), cholesterol level (mg/dL), lymphocyte count (/μL), and HbA1c (%) level) as dependent variables, adjusting for age. Results: Women aged 30.9 ± 10.2 years (yo) with a BMI of 17.0 ± 0.7 participated in this study. BMI (kg/m2) was positively associated with SMI (kg/m2) (β (95% CI): 1.6 [1.4, 1.9], p < 0.001) and BF% (0.2 [0.1, 0.2], p < 0.001), and the BMI ratio (present-to-age 20 ratio) was positively associated only with BF% (0.5 [0.05, 0.9], p = 0.03). Grip strength was positively associated with SMI (4.0 [1.4, 6.6], p = 0.003), and lymphocyte count was positively associated with BF% (β (36.2 [6.0, 66.5], p = 0.02). BMI was not associated with grip strength or lymphocyte count. Vitamin B1, cholesterol, and HbA1c were not associated with SMI, BF%, or BMI. Conclusions: These results indicate that SMI reflects BMI and grip strength, whereas BF% reflects BMI, the BMI ratio (present to age 20), and lymphocyte count. In addition to BMI and SMI, changes in BF% should also be noted in underweight women.

BACKGROUND/AIM: Obese individuals are often said to eat fast. Given that obese individuals are often reported to consume fast food more frequently, we hypothesized that fast food can be eaten more quickly. This study aimed to examine the effects of meal type on meal duration, considering meal sequence. METHODS: Meal duration, number of chews and bites, and chewing tempo were measured among 41 participants (18 males, 23 females; average age, 41.1 years) using two meals: pizza (301 kcal) and hamburger steak bento (hamburger, rice and broccoli, 304 kcal; two eating sequences: vegetables first or last). RESULTS: Compared with pizza, bento meals (vegetables first or last) were associated with longer meal durations (sec) (mean differences in pizza-bento (vegetable first): -182 [-245.6, -118.9], p < 0.0001; pizza-bento (vegetables last): -216.0 [-273.3, -158.7], p < 0.0001). In contrast, no differences in meal duration (sec) were observed regardless of the order of vegetable consumption (p = 0.14). These findings were consistent with the number of chews and chewing tempos across both sexes. The number of bites was similar among pizza, bento (vegetable fast), and bento (vegetable last). Meal duration was positively associated with the number of chews and bites and meal type and negatively associated with age and sex. BMI was not associated with meal duration. CONCLUSIONS: Meal type affected meal duration, the number of chews, and the chewing tempo, independent of meal sequence. To eat more slowly, it is important to pay attention to the meal type.