Age and gender were observed to be associated with MCI, in which age was considered as an impact factor for DR. The strong heterogeneity may result from variations in study design and baselines. Standardized MCI criteria were suggested to systematically evaluate MCI in the future.

Objectives. In this study, we aimed to conduct a 6-year follow-up and acquire a large sample dataset to analyze the most important demographic factors and cognitive function scale variables associated with mild cognitive impairment (MCI) progression for an elderly cohort (age ≥ 60 years old). Patients and Methods. We analyzed the subjects who had participated in a survey in 2011 and were successfully contacted in the later survey in 2017. For each subject, the basic demographic information was recorded, including sex, age, education level, marital status, working status, income level, and physical mental illness history. Cognitive assessments were performed using the following scales if possible: (1) the mini-mental state examination (MMSE) scale, (2) Montreal cognitive assessment (MoCA), (3) the clinical dementia rating (CDR) scale, and (4) Hamilton Depression Scale (HAMD-17). Results. The progression outcomes were different between sexes, among age brackets, education degrees, occupations types, and income levels; different progression groups had distinct children numbers (p<0.001), heights (p<0.05), and body weights (p<0.01); the positive ends six years later were positively related to better performance in the MoCA and MMSE scales (progressed vs stable p<0.01). Moreover, we constructed some indicators using age, MoCA, and MMSE scores, which showed an efficiency in predicting the progression outcomes. Conclusions. In conclusion, the MCI progression outcomes were associated with sex, age, education degrees, occupations types, income level, children number, height, and weight. MoCA and MMSE scales are supporting tools to predict the progression outcomes, especially combined with the demographic data.

BackgroundStudies conducted outside of China have found that stigma can predict low quality of life, and research in China has shown that stigma has an impact on the quality of life of convalescent patients with schizophrenia. Nevertheless, there is no indepth research on the impact of stigma on the quality of life of patients.AimsTo research the correlation of stigma and the subjective quality of life of persons with chronic schizophrenia in the community.MethodsWe adopted a stratified sampling method. General questionnaire, quality of life scale and stigma scale were given to 602 persons with chronic schizophrenia in the community.ResultsThe mean (SD) value of the Subjective Quality of Life Scale total scores was 32.99 (13.85). The mean (SD) value of the total stigma scores was 43.50 (5.02). After correlation analysis and multivariate stepwise regression analysis, it was shown that the total scores for self-stigma and each factor were positively correlated with subjective quality of life (r=0.462,p<0.001), psychosocial factors (r=0.517,p<0.001), and symptoms and adverse reaction factor scores (r=0.363,p<0.001), and the correlation coefficients were statistically significant.ConclusionsThe higher the stigma of persons with schizophrenia in the community, the lower the subjective quality of life is. This suggests that reduction of self-stigma should be considered in the improvement of the quality of life of persons with schizophrenia in the community.

The COVID-19 vaccine has been administered to over 200 countries and regions. With the unprecedented vaccination scale and speed, vaccination correlated mental health issues should be paid precise attention to. This study aims to assess the association between socio-demographic factors and mental health following vaccination and to analyze the mediation effect of vaccine hesitancy. This study recruited 2112 individuals who took two doses of the COVID-19 vaccine in Shanghai. Structural equation modeling was performed to assess factors associated with anxiety and depression of the vaccinated individuals and the underlying mechanism. The results yielded that vaccine hesitancy partially mediated/suppressed the effect from gender and employment status to anxiety/depression and fully mediated the effects from education to anxiety/depression. This study advanced the understanding of mental health disparity among different socio-demographic groups after vaccination and the impact of vaccine hesitancy on the vaccinated population’s mental health. The finding offered insights into the possible mental vulnerability of people holding a hesitant attitude before vaccination and suggested that vaccine hesitancy played a crucial role in people’s mental health after vaccination. Health promotion programs can target vaccine hesitancy to prevent unfavorable mental health consequences among specific populations.

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