ObjectiveDespite extensive vaccination campaigns to combat the coronavirus disease (COVID-19) pandemic, variants of concern, particularly the Omicron variant (B.1.1.529 or BA.1), may escape the antibodies elicited by vaccination against SARS-CoV-2. Therefore, this study aimed to evaluate 50% neutralizing activity (NT50) against SARS-CoV-2 D614G, Delta, Omicron BA.1, and Omicron BA.2 and to develop prediction models to predict the risk of infection in a general population in Japan.MethodsWe used a random 10% of samples from 1,277 participants in a population-based cross-sectional survey conducted in January and February 2022 in Yokohama City, the most populous municipality in Japan. We measured NT50 against D614G as a reference and three variants (Delta, Omicron BA.1, and BA.2) and immunoglobulin G against SARS-CoV-2 spike protein (SP-IgG).ResultsAmong 123 participants aged 20–74, 93% had received two doses of SARS-CoV-2 vaccine. The geometric means (95% confidence intervals) of NT50 were 65.5 (51.8–82.8) for D614G, 34.3 (27.1–43.4) for Delta, 14.9 (12.2–18.0) for Omicron BA.1, and 12.9 (11.3–14.7) for Omicron BA.2. The prediction model with SP-IgG titers for Omicron BA.1 performed better than the model for Omicron BA.2 (bias-corrected R2 with bootstrapping: 0.721 vs. 0.588). The models also performed better for BA.1 than for BA.2 (R2 = 0.850 vs. 0.150) in a validation study with 20 independent samples.ConclusionIn a general Japanese population with 93% of the population vaccinated with two doses of SARS-CoV-2 vaccine, neutralizing activity against Omicron BA.1 and BA.2 were substantially lower than those against D614G or the Delta variant. The prediction models for Omicron BA.1 and BA.2 showed moderate predictive ability and the model for BA.1 performed well in validation data.
Background This study aimed to develop models to predict the 5-year incidence of type 2 diabetes mellitus (T2DM) in a Japanese population and validate them externally in an independent Japanese population. Methods Data from 10,986 participants (aged 46–75 years) in the development cohort of the Japan Public Health Center-based Prospective Diabetes Study and 11,345 participants (aged 46–75 years) in the validation cohort of the Japan Epidemiology Collaboration on Occupational Health Study were used to develop and validate the risk scores in logistic regression models. Results We considered non-invasive (sex, body mass index, family history of diabetes mellitus, and diastolic blood pressure) and invasive (glycated hemoglobin [HbA1c] and fasting plasma glucose [FPG]) predictors to predict the 5-year probability of incident diabetes. The area under the receiver operating characteristic curve was 0.643 for the non-invasive risk model, 0.786 for the invasive risk model with HbA1c but not FPG, and 0.845 for the invasive risk model with HbA1c and FPG. The optimism for the performance of all models was small by internal validation. In the internal-external cross-validation, these models tended to show similar discriminative ability across different areas. The discriminative ability of each model was confirmed using external validation datasets. The invasive risk model with only HbA1c was well-calibrated in the validation cohort. Conclusion Our invasive risk models are expected to discriminate between high- and low-risk individuals with T2DM in a Japanese population.
Background Loneliness is a global issue, and primary care physicians play an important role in assessing and intervening with loneliness. This study aimed to examine the association between having a usual source of care (USC) or a good quality of primary care, and loneliness. Methods This cross-sectional study was conducted in Japan in 2022. A total of 6,000 residents were randomly sampled from the general population, aged 20–74 years. The outcome was the total score of the University of California, Los Angeles (UCLA) 3-item loneliness scale. The exposure included USC and the Person-Centered Primary Care Measure (PCPCM), which assesses the quality of primary care. We conducted a linear regression analysis to adjust for age, sex, educational status, annual household income, self-rated health, living status (whether alone or not), and the existence of physical health problems. Results Of the 6,000 residents, 1,277 responded to the survey. The median score of the UCLA 3-item loneliness scale was 6.0 and the mean total score of the PCPCM was 2.62. Of the 1,277 individuals, 713 (55.8%) had USC. Having USC was significantly associated with lower scores on the UCLA 3-item loneliness scale; the coefficient was −0.34 (95% confidence interval (CI): −0.57 to −0.12). Also, the total PCPCM score was significantly associated with lower loneliness scores; the coefficient was −0.56 (P < 0.001, 95% CI: −0.78 to −0.35). Conclusions Having USC and a better quality primary care were associated with a lower loneliness score. The quality of primary care could be a factor to mitigate patient loneliness.
Background Little is known about the population prevalence of antibodies against emerging immune escape variants of SARS-CoV-2. Methods A population-based prevalence study was conducted in Yokohama City, the most populous municipality of Japan. Quantitative measurements of immunoglobulin G against SARS-CoV-2 spike protein (SP-IgG) and qualitative measurements of neutralization antibodies against the Omicron BA.1 and BA.2 variants were performed. Results Of 6,000 randomly selected residents aged 20-74, 1,277 participated in the study during a period from January 30 to February 28, 2022. Of them, 3% had prior diagnosis of COVID-19, 96% received at least two-doses of SARS-CoV-2 vaccines, and 94% were positive for SP-IgG. The positive rates of neutralizing antibodies were 28% to Omicron BA.1 and BA.2 variants in a random sample of 10% of participants (n=123) and 100% to BA.1 and BA.2 among participants who received the third vaccination at least 7 days before (n=66). Conclusions In this population-based prevalence study in Japan, most had SP-IgG antibodies but the overall neutralizing antibody positive rate was 28% against the Omicron BA.1 and BA.2 variants. The population-level insufficient humoral immunity against the Omicron variants may explain the outbreak of COVID-19 during this period in Japan.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.