When a novel infectious disease emerges, enhanced contact tracing and isolation are implemented to prevent a major epidemic, and indeed, they have been successful for the control of severe acute respiratory syndrome (SARS) and Middle East respiratory syndrome (MERS), which have been greatly reduced without causing a global pandemic. Considering that asymptomatic and pre-symptomatic infections are substantial for the novel coronavirus disease (COVID-19), the feasibility of preventing the major epidemic has been questioned. Using a two-type branching process model, the present study assesses the feasibility of containing COVID-19 by computing the probability of a major epidemic. We show that if there is a substantial number of asymptomatic transmissions, cutting chains of transmission by means of contact tracing and case isolation would be very challenging without additional interventions, and in particular, untraced cases contribute to lowering the feasibility of containment. Even if isolation of symptomatic cases is conducted swiftly after symptom onset, only secondary transmissions after the symptom onset can be prevented.

Depression is a leading cause of disease worldwide. The association between gut microbiota and depression has barely been investigated in the Japanese population. We analyzed Iwaki health check-up data collected from 2017 to 2019 and constructed generalized linear mixed models. The independent variable was the relative abundance of each of the 37 gut microbiota genera that were reported to be associated with depression. The dependent variable was the presence of depression assessed by the Center for Epidemiologic Studies Depression Scale. Potential confounders, including grip strength, gender, height, weight, smoking, and drinking habits, were adjusted in the regression models. Nine genera’s regression coefficients (Alistipes, Blautia, Coprococcus, Dorea, Faecalibacterium, Holdemania, Lactobacillus, Mitsuokella, and Oscillibacter) showed statistical significance after multiple comparisons adjustment. Among these nine gut bacteria genera, Alistipes, Blautia, Coprococcus, Dorea, Faecalibacterium, and Oscillibacter were reported to be associated with butyrate production in the intestine. Our results indicate that gut microbiotas may influence the depression condition of the host via the butyrate-producing process.

The association between the gut microbiota and muscle strength has garnered attention in the context of mitigating muscle decline. However, many study subjects have been individuals with existing illnesses or the elderly only. This study aims to elucidate the association between the gut microbiota and muscle strength indicators using grip strength/BMI in a large-scale study of community residents. The mean age of men (n = 442) and women (n = 588) was 50.5 (15.3) and 51.2 (15.9) years, respectively. The muscle strength indicator used was grip/BMI. The association between total read count and genus-level gut microbiota and muscle strength was analyzed. The mean grip/BMI was 1.8 (0.3) for men and 1.2 (0.2) for women. The genus of the gut microbiota that showed an association in both sexes was Eggerthella (men: β = 0.18, CI: 0.04–0.31, p = 0.009; women: β = 0.07, CI: 0.00–0.12, p = 0.028). Blautia, Eggerthella and Faecalibacterium were found to be significantly associated with grip/BMI in both the multiple regression analysis and Spearman’s correlation analysis after the multiple comparison adjustment. These results suggest that an increase in Blautia and Eggerthella, coupled with a decrease in Faecalibacterium, may contribute to muscle strengthening or the suppression of muscle weakness.

Telomeres, repeated TTAGGG sequences at chromosomal ends, shorten with age and indicate cellular lifespan. Zinc can protect against telomere damage through its anti-oxidative effect. Meanwhile, telomere shortening was correlated with metabolic diseases of hypertension and type 2 diabetes. The objective of this study was to investigate whether the association between zinc and telomere length differs by the presence or absence of hypertension/type 2 diabetes. This is a cross-sectional study with 1064 participants of the Iwaki area, Japan. Multiple linear regression models were performed to test the hypothesis. A higher serum zinc concentration was significantly associated with a longer G-tail length (β = 48.11, 95% confidence intervals [CI]: 25.69, 70.54, p < 0.001). By multivariate linear regression analysis, there was a significant positive association between zinc and G-tail length in both hypertensive (β = 46.84, 95%CI: 9.69, 84.0, p = 0.014) and non-hypertensive groups (β = 49.47, 95%CI: 20.75, 78.18, p = 0.001), while the association was significant only in the non-diabetes group (β = 50.82, 95%CI: 27.54, 74.11, p < 0.001). In conclusion, higher zinc concentration was significantly associated with longer G-tail length. The protective effect of zinc on G-tail did not differ by hypertension status; however, it disappeared in individuals with type 2 diabetes.

The predictive abilities of computer-based screening devices for early cognitive decline (CD) in older adults have rarely been longitudinally examined. Therefore, this study examined the ability of CogEvo, a short-duration, computer-based cognitive screening device requiring little professional involvement, to predict CD among community-dwelling older adults. We determined whether 119 individuals aged ≥ 65 years living in Japanese rural communities who scored ≥ 24 on the Mini-Mental State Examination (MMSE) at baseline developed CD by annually administering the MMSE to them. CD was defined as an MMSE score of ≤23. At baseline, the overall CogEvo judgment grade, with lower grades indicating better cognitive function, was calculated from the results of various cognitive tasks. Over 2 years, 10 participants developed CD. Participants with grades of 4 had a higher percentage of CD cases than those with grades of ≤3 (p < 0.01). This relationship remained significant after controlling for possible confounders, including the MMSE score at baseline. The sensitivity and specificity of the CogEvo grade cutoff of 4 were 50.0% and 93.6%, respectively. In conclusion, CogEvo may be an efficient tool for identifying individuals at a high risk for dementia. The possibility of missing CD cases should be considered when using CogEvo for screening.

Background/Objectives: Night shift workers (NSWs) are at a high risk of cardiovascular disease (CVD). However, the association between CVD risk factors and lifestyle behavior (sedentary behavior [SB], physical activity [PA], and sleep) is unclear among NSWs. NSWs lead different lifestyles on workdays and leisure days. This study aimed to investigate the association between lifestyle behavior times and CVD risk factors among NSWs during workdays and leisure days using an isotemporal substitution model. Methods: This cross-sectional study included 66 male NSWs. Time spent on lifestyle behaviors was obtained using a tri-axial accelerometer and classified into SB, light-intensity PA, moderate-to-vigorous PA (MVPA), and sleep. Lifestyle behavior times were divided into workdays and leisure days. CVD risk factors were determined based on periodic health checkups. An isotemporal substitution model was used to estimate the effect of replacing one lifestyle behavior with another on CVD risk factors. Results: The lifestyle behavior times differed between workdays and leisure days. On workdays, reallocating 30 min of SB to light-intensity PA was significantly associated with a lower waist circumference. In addition, reallocating sleep to SB or MVPA was significantly associated with higher triglyceride levels. On leisure days, reallocating SB or sleep time to MVPA was significantly associated with lower aspartate aminotransferase levels. Conclusions: Given the difference in the associations between lifestyle behavior times and CVD risk factors among NSWs between workdays and leisure days, NSWs should be mindful of the time spent on SB, PA, and sleep on workdays and leisure days to achieve healthier outcomes.